thesis on pulmonary tuberculosis

• Open access
• Published: 23 September 2021

Duration and determinants of delayed tuberculosis diagnosis and treatment in high-burden countries: a mixed-methods systematic review and meta-analysis

• Alvin Kuo Jing Teo   ORCID: orcid.org/0000-0002-0569-3518 1 , 6   na1 ,
• Shweta R. Singh 1   na1 ,
• Kiesha Prem 1 , 2   na1 ,
• Li Yang Hsu 1 , 3 &
• Siyan Yi 1 , 4 , 5  

Respiratory Research volume  22 , Article number:  251 ( 2021 ) Cite this article

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Thirty countries with the highest tuberculosis (TB) burden bear 87% of the world’s TB cases. Delayed diagnosis and treatment are detrimental to TB prognosis and sustain TB transmission in the community, making TB elimination a great challenge, especially in these countries. Our objective was to elucidate the duration and determinants of delayed diagnosis and treatment of pulmonary TB in high TB-burden countries.

We conducted a systematic review and meta-analysis of quantitative and qualitative studies by searching four databases for literature published between 2008 and 2018 following PRISMA guidelines. We performed a narrative synthesis of the covariates significantly associated with patient, health system, treatment, and total delays. The pooled median duration of delay and effect sizes of covariates were estimated using random-effects meta-analyses. We identified key qualitative themes using thematic analysis.

This review included 124 articles from 14 low- and lower-middle-income countries (LIC and LMIC) and five upper-middle-income countries (UMIC). The pooled median duration of delays (in days) were—patient delay (LIC/LMIC: 28 (95% CI 20–30); UMIC: 10 (95% CI 10–20), health system delay (LIC/LMIC: 14 (95% CI 2–28); UMIC: 4 (95% CI 2–4), and treatment delay (LIC/LMIC: 14 (95% CI 3–84); UMIC: 0 (95% CI 0–1). There was consistent evidence that being female and rural residence was associated with longer patient delay. Patient delay was also associated with other individual, interpersonal, and community risk factors such as poor TB knowledge, long chains of care-seeking through private/multiple providers, perceived stigma, financial insecurities, and poor access to healthcare. Organizational and policy factors mediated health system and treatment delays. These factors included the lack of resources and complex administrative procedures and systems at the health facilities. We identified data gaps in 11 high-burden countries.

Conclusions

This review presented the duration of delays and detailed the determinants of delayed TB diagnosis and treatment in high-burden countries. The gaps identified could be addressed through tailored approaches, education, and at a higher level, through health system strengthening and provision of universal health coverage to reduce delays and improve access to TB diagnosis and care.

PROSPERO registration : CRD42018107237.

In 1993, the World Health Organization (WHO) declared global tuberculosis (TB) emergency to make TB a high priority [ 1 ]. Twenty-five years on, TB remains one of the leading infectious causes of illness and death worldwide [ 2 ]. Despite that TB is both preventable and curable, and efforts such as the implementation of directly observed treatment short course and coordinated national TB programs worldwide, approximately 10 million people fell ill with TB, of which 1.5 million died from the disease in 2018 [ 2 ]. The cumulative reduction in the TB incidence rate globally between 2015 and 2018 stood at 6% [ 2 ], imposing a significant delay in reaching the end TB milestone of 20% [ 3 ] reduction by 2020. TB control and elimination are critical challenges in many countries. However, the burden is disproportionately borne by 30 countries, mostly in Asia and Africa, accounting for 87% of the world’s TB (both pan-TB and drug-resistant TB) and TB/HIV cases [ 2 ].

In 2018, nearly one-third of the people with TB were estimated to be undiagnosed globally [ 2 ]. The delay in diagnosis and treatment is detrimental to the patients’ prognosis and perpetuates TB transmission in the community [ 4 ] and thus poses a great challenge to eliminating TB. Therefore, identifying the factors that lead to delayed TB diagnosis and treatment is imperative in developing interventions to reduce TB incidence substantially. Collectively, recent systematic reviews have provided empirical evidence associating sociodemographic, clinical, health system, and economic factors with delayed diagnosis and treatment of TB in different countries and regions [ 5 , 6 , 7 , 8 , 9 , 10 , 11 ]. However, delays in diagnosis and treatment vary across countries with a different burden of the disease. From what we know, no systematic reviews have addressed delayed diagnosis and treatment of TB among countries bearing most of the global TB burden. There is also a lack of reviews that triangulate qualitative and quantitative findings to provide a more complete and all-inclusive view of the matter. Therefore, a mixed-methods systematic review and meta-analysis were undertaken to derive the determinants and duration of diagnosis and treatment delays of pulmonary TB in the high TB-burden countries.

We structured this review following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA)-statement [ 12 ]. The protocol of this systematic review has been published [ 13 ] and registered with the International Prospective Register of Systematic Reviews (PROSPERO) (Registration Number CRD42018107237).

Inclusion and exclusion criteria

In this review, we considered all studies conducted in the WHO high TB-burden countries—Angola, Bangladesh, Brazil, Cambodia, Central African Republic, China, Congo, Democratic People’s Republic of Korea, Democratic Republic of Congo, Ethiopia, India, Indonesia, Kenya, Lesotho, Liberia, Mozambique, Myanmar, Namibia, Nigeria, Pakistan, Papua New Guinea, the Philippines, Russian Federation, Sierra Leone, South Africa, Tanzania, Thailand, Vietnam, Zambia, and Zimbabwe. We included studies that reported on individual and interpersonal risk factors, social and physical environment, health systems, and policies associated with delayed TB diagnosis and treatment initiation published between 2008 and 2018. The factors could be self-reported, ascertained by health providers, or abstracted from medical charts or programs/administrative records.

We included study populations comprising presumptive TB (persons presenting with signs and/or symptoms suggestive of TB) and people with TB (new diagnosis, previously treated, and those without a known history of previous TB treatment) regardless of HIV and bacteriological status. We included observational (cross-sectional, case–control, retrospective, and prospective cohort design) and qualitative studies published in English or Chinese. Systematic reviews, meta-analyses, scoping reviews, intervention studies, publications in the form of letters and reviews, and studies lacking and/or unclear reporting of key outcomes were excluded.

Our primary outcomes were—(1) patient delay: the time interval between the onset of symptoms and the first encounter with healthcare professionals; (2) health system delay: the time interval between the first encounter with healthcare professionals and the diagnosis of pulmonary TB; (3) treatment delay: the time interval between TB diagnosis and TB treatment initiation; and (4) total delay: the time interval between onset of symptoms and TB treatment initiation. As there were no universal cut-offs [ 8 ] to a duration that constituted delay, we treated delay in this review as how they were defined in individual studies. We did not exclude studies based on the delay thresholds defined in individual studies.

Literature search strategy and study selection

First, we conducted a preliminary search of articles on PubMed and EMBASE to develop a set of appropriate Medical Subject Heading terms, index terms, and keywords [ 13 ], centered around three domains (population/problems: tuberculosis, outcomes: health-seeking behaviours; delays; barriers, countries: high burden countries). Using these identified search terms structured with Boolean logic operators (AND and OR), we contextualized the search strategies in PubMed, EMBASE, CINAHL, and PsycInfo (Additional file 1 ). The search fields included title, abstract, keywords, and text words. We also reviewed the reference list of key articles for additional studies. We managed all identified citations into EndNote X8 (Clarivate Analytics, Philadelphia, USA). Duplicates were removed, and the remainder was exported to Microsoft Excel (Microsoft Corporation, Washington, USA) for further assessment. AKJT and SRS independently screened the titles, abstracts, and full-text articles based on the inclusion and exclusion criteria. Interrater agreements for the titles and abstract screening between the reviewers were high (agreement = 98%, Cohen’s kappa = 0.95, and Krippendorf alpha = 0.95), and discrepancies were discussed. The two primary reviewers were able to resolve all the discrepancies without having to involve a third reviewer. The search and selection processes were conducted and presented in accordance with the PRISMA guidelines.

Data extraction

Study characteristics and data on risk factors were extracted independently by two authors (AKJT and SRS). We recorded study and participants’ characteristics, exposure variables (various factors associated with delays reported by individual study), primary outcome measures, and study quality assessment scores using a standard form. Data on variables to be included in the meta-analysis were extracted by one author (AKJT) and subsequently reviewed by a second author (KP). This included duration of delay (median and interquartile range/range and mean and standard deviation) and the effect sizes (crude and adjusted odds ratios) for exposures of interest.

Quality assessment

The quality of the selected non-randomized (quantitative) and qualitative studies was critically evaluated using the Newcastle–Ottawa Scale for cross-sectional studies, case–control studies, and cohort studies, and the Critical Appraisal Skills Program (CASP) tool, respectively [ 14 , 15 , 16 ]. For non-randomized quantitative studies, the assessment was made based on four main domains—(1) selection of samples (representativeness, sample size, definition and selection of cases and controls (for case–control studies), and non-response rate), (2) comparability of groups included in the analyses, (3) the ascertainment of exposures and outcomes, and (4) the statistical tests applied in the studies. A score of 1 was given to individual questions if the criterion was satisfied and 0 if the criterion was not satisfied or not justified. The highest possible score for cross-sectional studies was 10 (5 for selection, 2 for comparability, and 3 for outcomes). The highest possible score for case–control studies was 9 (4 for selection, 2 for comparability, and 3 for exposure). The highest possible score for cohort studies was 9 (4 for selection, 2 for comparability, and 3 for exposures). Studies that scored 0–3 were regarded as low quality (LQ), 4–6 were regarded as moderate quality (MQ), and ≥ 7 were regarded as high quality (HQ).

For qualitative studies, the assessment was made based on ten questions regarding the results, validity, and the value of the research. We gave a score of 1 if the paper fulfilled a criterion, 0.5 if we could not tell if the paper fulfilled a criterion, and 0 if the paper did not fulfill a criterion. A score of 0–5 equated to LQ study, a score of 6–7 equated to MQ study, and a score of ≥ 8 equated to HQ study. The final synthesized qualitative findings were graded based on the dependability and credibility of the findings using the ConQual approach [ 17 ].

Data synthesis and analyses

We described the studies by the populations, countries, study designs, and sample sizes. Countries were grouped by WHO region and categorized as low-income economies (LIC)—gross national income (GNI) per capita $1,025 or less in 2018; lower-middle-income economies (LMIC)—GNI per capita between $1,026 and $3,995; upper-middle-income economies (UMIC)—GNI per capita between $3,996 and $12,375 according to World Bank classification in 2019 [ 18 ]. We reported the independent variables significantly associated with the patient, health system, treatment, and total delays. Results from the multivariable analyses preceded bivariate for studies that reported both bivariate and multivariable analyses.

Median and interquartile range/range for the duration of delays in days were extracted and used to estimate a pooled median, i.e., median of study-specific medians [ 19 ]. We pooled weighted medians by incorporating study-specific sample sizes [ 19 ]. For patient delay, we excluded two studies [ 20 , 21 ] from China with sample sizes > 10,000 because the pooled weighted medians were heavily skewed, including only estimates of the study with the largest sample size [ 21 ].

For independent variables (risk factors), effect sizes were extracted and used to calculate pooled odds ratios (OR) and their 95% confidence interval (CI). We pooled effect sizes of covariates from studies that utilized similar delay thresholds if data were available in more than two studies and duration of delays by meta-analysis using R (R Foundation for Statistical Computing, Vienna). We pooled effect sizes for studies that defined patient delay using threshold values of 14–15 days (n = 5), 20–21 days (n = 7), 28–30 days (n = 17); and health system delay using threshold values of 14–15 days (n = 5). We found five studies that reported treatment delay using a threshold value of 7 days. However, the studies did not report similar covariates with effect sizes that allowed pooling. Where adjustments for covariates had been performed, the data from the adjusted model were pooled.

We quantified between-study heterogeneity using Chi-square statistic Q, I 2 , and Tau [ 22 ]. We estimated the pooled OR and its 95% CI using a Bayesian random-effect model for each meta-analysis, which accounted for between-study heterogeneity [ 23 ]. The estimates for Tau and I 2 statistics were presented together with the pooled estimates and the 95% CI. We used the inverse of the effect size variance to determine the pooling weights. We assessed the association of the primary outcomes and (1) sociodemographic and economic variables: sex, urbanicity; (2) behavioral variables: smoking, alcohol use, TB knowledge; and (3) clinical and health services-related variables: hemoptysis, weight loss, fever, chest pain, night sweats in the meta-analyses.

We extracted qualitative findings and sample quotes reported in qualitative and mixed-method studies verbatim. The extracted data were annotated and analyzed using NVIVO 12 (QSR International). We retrieved references deductively and applied thematic analyses to categorize the textual references. Two authors (AKJT and SRS) coded the data independently. Discrepancies, code definitions, and the emergence of sub-themes were discussed. The results were presented by income categories that the high-burden countries represent.

Study selection

The systematic review process is presented in Fig.  1 . A total of 4878 records were identified from electronic database searches. Following the removal of duplicates (n = 1189) and non-relevant records (n = 3383), 306 records were assessed for eligibility. Of these, 182 articles were further excluded. Finally, 124 articles were reviewed. A qualitative synthesis was performed for 36 studies. We conducted quantitative and narrative synthesis on 86 studies. Two mixed-method studies underwent both qualitative and quantitative/narrative synthesis. We found large heterogeneity among studies included in the meta-analyses—1 (7%) had I 2  ≤ 50%, 14 (93%) had I 2  > 50%, and 13 (87%) had I 2  > 75%.

PRISMA flow diagram for identification of studies via databases

Study characteristics and quality assessments

These studies described data from 18,759 presumptive TB and 131,142 people with TB [ 20 , 21 , 24 , 25 , 26 , 27 , 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 , 84 , 85 , 86 , 87 , 88 , 89 , 90 , 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 , 99 , 100 , 101 , 102 , 103 , 104 , 105 , 106 , 107 , 108 , 109 ], 1659 in-depth and structured interviews, and 87 focus groups [ 48 , 96 , 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 129 , 130 , 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 143 , 144 , 145 ] from 19 countries in three continents (Table 1 ). A total of 14 countries were classified as lower-income (LIC) and lower-middle-income economies (LMIC), and five were classified as upper-middle-income economies (UMIC) [ 18 ]. Patient delay was reported in 103 studies, health system delay in 29 studies, treatment delay in 18 studies, and total delay in 21 studies. Of the 30 high TB-burden countries, 11 countries were not included in this review, either due to data unavailability or lack of key outcome data (Fig.  2 ). After assessments of study quality, a total of 81 HQ studies, 40 MQ studies, and one LQ study were identified. Two mixed-methods studies scored MQ/HQ and HQ/MQ for the quantitative and qualitative components, respectively. The final synthesized qualitative findings were rated HQ (55%) and MQ (45%) using the ConQual method. Details of the assessments were illustrated in the Additional file 1 . No studies were excluded based on the outcome of quality assessments; instead, the information was considered during data synthesis and interpretation.

Geographical coverage of studies published between 2008 and 2018 included in this systematic review of delayed diagnosis and treatment of pulmonary tuberculosis. The 30-high tuberculosis (TB) burden countries which have been designated by the World Health Organization are outlined in black. Of them, countries with studies presenting various types of delay are categorized by the various colors. For example, countries shaded in green had studies presenting both patient and health system delay, and those with diagonal strips presented total delay too. Some of the high TB burden countries shaded in grey had no studies identified here or lacked key outcome data. The table on the left represents the TB incidence per 100,000 population of high TB burden countries in 2019. Rows shaded in grey represent countries that were not included in this review either due to data unavailability or lack of key outcome data

• Patient delay

The pooled median patient delay (Fig.  3 ) in LIC and LMIC was 28 days (95% CI 17–30). The pooled median patient delay in UMIC was 10 days (95% CI 10–20). The overall median patient delay in high TB burden countries was 16 days (95% CI 11–20). In the meta-analysis and narrative synthesis of quantitative data (Table 2 ), females (pooled OR 1.48. 95% CI 1.09–1.98, P = 0.01) were more likely to delay care-seeking for TB (Fig.  4 ). Qualitative studies highlighted limitations for women to seek healthcare [ 115 , 117 , 125 , 126 , 130 ]. Women reported economic constraints and power imbalances in the decision-making process as barriers to care-seeking [ 115 , 117 , 125 , 126 ]. We further stratified the analysis by sex. We found that women were disproportionately affected by risk factors for patient delay (Fig.  5 ), such as unemployment, poor TB knowledge, and difficulties traveling a long distance to visit health facilities [ 43 , 51 ]. Long-distance to health facilities was also reported by qualitative studies as a barrier to care-seeking [ 48 , 111 , 112 , 114 , 117 , 126 , 131 , 136 , 137 , 140 , 142 , 145 ]. In addition to physical barriers, financial insecurities and economic challenges also compounded patient delay [ 20 , 25 , 28 , 33 , 38 , 39 , 40 , 43 , 50 , 51 , 66 , 67 , 69 , 72 , 76 , 77 , 83 , 87 , 88 ]. Among qualitative studies (Table 3 ), seven articles reflected on participant’s experiences where competing priorities of livelihoods and commitment to work and family led to individual care-seeking delay [ 48 , 125 , 126 , 127 , 134 , 138 , 145 ]. We also found that being rural residents in LIC and LMIC (Table 2 and Fig.  4 ) was associated with patient delay (pooled OR 1.75, 95% CI 1.01–2.94, P = 0.02). No studies from the UMIC were included in the meta-analysis for urbanicity. This review also reported other sociodemographic and economic risk factors for patient delay, such as lower education level and being older, unmarried, and unemployed. High indirect medical costs [ 48 , 126 ], absence of health insurance, productivity, time, and income loss [ 48 , 125 , 127 , 134 , 138 , 145 ] resulting from disease suffering further worsen household vulnerabilities and contribute to a delay in TB diagnosis and poor health outcomes (Table 2 ) [ 146 ].

Duration of patient delay by regions reported in high tuberculosis burden countries. Countries were grouped by WHO regions ( AFR African region, AMR Region of the Americas, SEAR South-East Asia region, WPR Western Pacific region). Countries were also categorized as (i) LIC (low-income countries), (ii) LMIC (low-middle income countries), or (ii) UMIC (upper-middle income countries) as designated by the World Bank in 2019. Studies from LIC and LMIC were in bold. Patient delay (in blue) was pooled by the countries’ economic status using Weighted Medians of Medians methods by McGrath (2019). The estimates were weighted by sample sizes of the studies. Pooled results for LIC and LMIC were not presented separately due to insufficient studies from LIC. Duration of delay in days were presented in the log scale

Association between sex of individuals, urbanicity and patient delay. Countries were grouped by WHO region ( AFR African region, AMR Region of the Americas, SEAR South-East Asia region, WPR Western Pacific region) and categorized as (i) LIC/LMIC (low- or lower-middle-income countries), or (ii) UMIC (upper-middle-income countries) as designated by the World Bank in 2019. The reference group for sex (left panel) was male and urbanicity (right panel) was urban. The odds ratio (OR) were pooled (in blue) by countries’ economic status using Bayesian random-effects meta-analysis. Odds ratios are presented in the log scale

Subgroup analysis of patient delay and selected covariates by sex of the individual. Tamhane et al. (2012), represented as square points, and Mfinanga et al. (2008), represented as round points, provided sex-specific association of patient delay and three covariates; i.e., being unemployed, having to travel long distances or long travelling time, and having poor TB knowledge. The sex-specific odds ratio, in the log scale, for males are presented in hues of blues and for females in hues of reds

Furthermore, poor TB knowledge (Table 2 ), unawareness of free TB treatment policies [ 30 ], low perceived susceptibility, and severity of TB was associated with patient delay [ 40 , 48 , 110 , 113 , 114 , 115 , 117 , 119 , 124 , 126 , 137 ]. However, the pooled estimates for TB knowledge (delay thresholds 21 days—(pooled OR 0.91, 95% CI 0.24–2.71, P = 0.62) and 28 days—(pooled OR 1.36, 95% CI 0.39–4.83, P = 0.25) were not significantly associated with patient delay in the meta-analysis (Fig.  6 ).

Association between TB knowledge, smoking, alcohol use and patient delay. Countries were grouped by WHO region ( AFR African region, AMR Region of the Americas, SEAR South-East Asian region, WPR Western Pacific region) and categorized as (i) LIC/LMIC (low- or lower-middle-income countries), or (ii) UMIC (upper-middle-income countries) as designated by the World Bank in 2019. For TB knowledge, the top left panel pooled estimates from studies that defined patient delay threshold as 28 days. The bottom left panel pooled estimates from studies that defined patient delay threshold as 21 days. The reference group was TB knowledge (no or low). The top right panel represented pooled estimates for the association between alcohol use and patient delay. The bottom right panel represented pooled estimates for the association between smoking and patient delay. Both plots pooled estimates that defined patient delay threshold as 28 days. The reference groups were no smoking and no alcohol use, respectively. The odds ratio (OR) were pooled (in blue) by countries’ economic status using Bayesian random-effects meta-analysis. Odds ratios are presented in the log scale

Perceived stigma and discrimination (Table 3 ) at the workplace, within the family, and community and associating TB with HIV deterred presumptive TB patients from care-seeking [ 110 , 114 , 115 , 116 , 117 , 121 , 125 , 126 , 127 , 128 , 129 , 130 , 135 , 136 , 137 , 139 , 140 , 141 , 142 , 143 , 144 ]. From the qualitative data, we found studies that explained the use of alcohol and smoking to conceal health issues, especially among men, which resulted in delayed care-seeking [ 116 , 128 , 137 , 138 , 144 , 145 ]. However, these lifestyle behaviors were not statistically significant in the meta-analysis, where the estimates from both sexes were pooled (Fig.  6 ). Several studies in Africa [ 110 , 113 , 114 ] highlighted superstitious beliefs that TB is caused by divine retributions of past misdeeds, sinful behaviors, and curses; thus, help is first sought from traditional or spiritual healers instead of a health provider. Besides, studies in Asia reported the misconception that TB is hereditary [ 117 , 126 ].

Long chains of care-seeking through multiple non-formal or private health providers were also reported as a determinant of patient delay [ 110 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 , 121 , 122 , 123 , 124 , 125 , 126 , 127 , 128 , 134 , 135 , 137 , 138 , 140 , 142 , 143 , 144 ]. Qualitative data also suggested that the lack of trust in the public health care system perpetuated delays in care-seeking [ 122 , 131 , 136 , 137 , 138 , 139 , 143 , 144 ]. The inability of people with TB to recognize symptoms such as fever and cough that were not ascribed to TB intrinsically led to self-medication and treatment or waiting for symptoms to self-resolve due to low perceived disease severity [ 110 , 119 , 126 , 128 , 129 , 134 , 137 , 140 , 142 ]. Studies reported that the presence of cough [ 69 , 70 , 74 , 80 , 86 , 88 ] was associated with patient delay compared to hemoptysis and weight loss that were perceived to be more severe (Table 2 ). However, the relationships between TB symptoms and patient delay were not statistically significant in the meta-analysis (Fig.  7 ).

Association between TB symptoms and patient delay. Countries were grouped by WHO region ( AFR African region, AMR Region of the Americas, SEAR South-East Asian region, WPR Western Pacific region) and categorized as (i) LIC/LMIC (low- or lower-middle-income countries), or (ii) UMIC (upper-middle-income countries) as designated by the World Bank in 2019. The reference group was no symptom. The patient delay threshold was 28 days. The odds ratio (OR) were pooled (in blue) by countries’ economic status using Bayesian random-effects meta-analysis. Odds ratios are presented in the log scale

• Health system delay

The pooled median health system delay (Fig.  8 ) in LIC and LMIC was 14 days (95% CI 2–28). The pooled median health system delay in UMIC was 4 days (95% CI 2–4). The overall median health system delay in high TB-burden countries was 4 days (95% CI 2–4). We explored the association between sex and health system delay, and we did not find a significant relationship (Additional file 1 ). Twelve qualitative studies reported that poor practices and ignorance of TB among health providers at health facilities led to a delay in TB diagnosis [ 110 , 111 , 114 , 116 , 118 , 122 , 123 , 124 , 129 , 132 , 133 , 135 ]. Seven qualitative studies explained that complicated administrative procedures at the health facilities [ 96 , 119 , 126 , 130 , 132 , 133 , 144 ], which could have resulted in longer waiting time [ 46 ], and complex referral system[ 144 ] that eventually prolonged health system delay. This review identified studies reporting that health system delays were associated with visiting lower-level facilities that did not provide TB services [ 34 , 46 , 72 , 75 , 90 ]. Six qualitative studies mentioned that inadequate resources and supplies in health facilities could have delayed TB diagnosis [ 96 , 129 , 130 , 132 , 138 , 144 ]. Three quantitative studies reported that people with smear-negative TB were more likely to experience health system delay [ 81 , 82 , 91 ].

Duration of health system and treatment delay by regions reported in high tuberculosis burden countries. Countries were grouped by WHO regions ( AFR African region, AMR Region of the Americas, SEAR South-East Asian region, WPR Western Pacific region). Countries were also categorized as (i) LIC (low-income countries), (ii) LMIC (low-middle income countries), or (ii) UMIC (upper-middle income countries) as designated by the World Bank in 2019. Studies from LIC and LMIC were in bold. Health system delay (in yellow) and treatment delay (in red) were pooled by the countries’ economic status using Weighted Medians of Medians methods by McGrath (2019). The estimates were weighted by sample sizes of the studies. Pooled results for LIC and LMIC were not presented separately due to insufficient studies from LIC. Duration of delay in days were presented in the log scale

• Treatment delay

The pooled median treatment delay (Fig.  8 ) in LIC and LMIC was 14 days (95% CI 3–84). The pooled median treatment delay in UMIC was 0 days (95% CI 0–1). The overall median treatment delay in high TB burden countries was 1 day (95% CI 0–14). One qualitative study noted that the geographical distance to health facilities, especially when treatment was initiated in separate institutions, delayed TB treatment initiation [ 141 ]. This could be exacerbated by residing in areas without health centers nearby [ 97 ]. Health system factors such as logistical issues in drug transportation [ 96 , 141 ] and the absence of TB diagnostic services in local health facilities [ 96 , 119 ] compounded delay in treatment initiation. Like patient delay, a qualitative study provided insights into TB stigma experienced by women resulting in the concealment of diagnosis, expulsion from their community, or isolation; thus, delaying access to TB care and treatment[ 127 ]. Four qualitative studies mentioned self-perception of health, unconvinced diagnosis and need for TB treatment, and the perceived low effectiveness of TB treatment led to a delay in TB treatment initiation [ 48 , 96 , 119 , 141 ]. We also found that retreatment cases were more likely to delay TB treatment initiation [ 94 , 95 , 96 , 97 , 98 ].

Our review is the first to focus on determinants of delayed TB diagnosis and treatment among high TB burden countries using evidence-based quantitative and qualitative information. Studies from high TB-burden LIC/LMIC reported longer median patient delay (28 days) than UMIC (10 days). Our findings were consistent with previous systematic reviews conducted in countries of different income levels [ 5 , 8 ]. However, the median patient delay among UMIC in this review was shorter than the findings from observational studies conducted in other high-income countries [ 147 , 148 ]. TB burden in high-income countries has been progressively reduced through improvements in socio-economic conditions, strong health systems components such as the delivery of TB services and universal health coverage, and social protection schemes [ 149 ]. Nevertheless, the high standards of living and wellbeing have shaped the notion that TB is not a significant concern, rendering a lower index of suspicion of TB and thus delaying TB care-seeking [ 150 ]. Notwithstanding, TB remains an issue, especially among hard-to-reach populations living in high-income settings like migrants [ 151 , 152 ], who face challenges in accessing healthcare due to stigma, language barriers, and cost of testing and treatment [ 6 ].

The median health system delay in this review (LIC/LMIC: 14 days and UMIC: 4 days) was found to be shorter than previous systematic reviews conducted among countries of similar economies [ 5 , 8 ]. As this review included studies conducted in the last decade, the improvement in health system delay may be attributed to the enhancements of healthcare systems [ 153 ] and the quality of TB laboratories [ 154 ]. The clinicians’ ability to consider TB as a differential diagnosis in high burden settings is also essential for early diagnosis and treatment [ 155 ]. However, there remains a paucity of data in several high TB burden countries, including seven in Africa (Central African Republic, Democratic Republic of Condo, Lesotho, Liberia, Namibia, Republic of the Congo, and Sierra Leone) and four in Asia (Democratic People’s Republic of Korea, Myanmar, Papua New Guinea, and Vietnam), potentially due to logistical challenges in conducting such studies.

While TB is a disease mainly affecting men[ 156 ], in our review, we found that women faced challenges in accessing TB care promptly in some settings due to resource constraints, power imbalances, and poor TB knowledge. However, there was a paucity of sex-specific data on the determinants of delay in TB diagnosis and treatment. It is imperative to recognize sex disparities in TB care-seeking. Women with TB in high burden countries experienced delays in diagnosis and treatment because of barriers to TB services. Therefore, future studies should report disaggregated data by sex to inform programs and interventions addressing sex-specific vulnerabilities in improving access to TB services among men and women.

Despite wide coverage of free TB diagnostic and treatment services in high burden countries [ 157 ], people with TB and their families, especially the poor, bear the impact of high economic costs [ 158 ]. Studies included in our review also reported that livelihood, work, and family were prioritized and led to a delay in care-seeking. These factors, coupled with the physical environments and impoverished living conditions [ 127 , 138 ], plunged low-income households into a vicious cycle of impoverishments [ 159 , 160 ], making TB elimination overtly challenging. Aside from the broad expansion of TB services that have been shown to reduce the financial burden on TB-affected households [ 161 ], it is also essential to ensure that financial and social protection policies are in place to protect those at risk of catastrophic TB costs and poverty.

Our pooled estimates showed that rural dwellers were significantly associated with patient delay. In the rural setting, access to healthcare facilities, particularly an institution that offers TB diagnostic services, might be lacking [ 5 ]. Rural populations were also more likely to have a lower health literacy [ 162 ], resulting in poorer health status and outcomes [ 163 ]. Nevertheless, the concept of urban–rural is dynamic and context-dependent, driven by migration, population, and economic growth over time [ 164 ]. The consistent findings of rural residence and patient delay in TB [ 5 , 8 , 165 ] suggest increased efforts tailored to the country’s specific circumstances in reaching the affected communities are required.

In countries where TB diagnostic and treatment services are provided for free, access to TB care is further challenged by poor knowledge and awareness regarding such policies, making presumptive TB seek treatment early [ 123 , 135 ]. In addition to poor awareness about the free TB treatment policy, we also identified studies that reported poor knowledge regarding TB symptoms associated with a delay in TB care-seeking. Therefore, people with TB would delay care-seeking until only when their illness compromised their ability to work and earn livelihoods [ 115 ]. Conventionally, symptomatic individuals are linked to TB transmission, and they are regarded as the target group for TB case-finding activities using the TB symptoms screening approach [ 166 ]. However, TB transmission could also occur during the subclinical (asymptomatic) phase, particularly heightened during episodes of symptoms exhibition unrelated to TB pathologies, such as bouts of either acute or chronic cough [ 167 ]. As people with subclinical TB might not report any symptoms, they have lower awareness and motivation to seek care; thus, leading to a delay in TB diagnosis and treatment and potentially sustaining TB transmission [ 168 ] in the household and community. Therefore, a better understanding of subclinical TB, its transmission dynamics, and the implications for TB control efforts are needed. Nevertheless, individuals who exhibit TB symptoms, such as cough, are more likely to have a higher bacillary load and transmit infection [ 169 , 170 ]. Therefore, it is crucial to ensure that ill and symptomatic persons with TB are reached, tested, and treated promptly.

Furthermore, misperception regarding the causes of TB was also found to delay TB care-seeking. When no one in the family is ever diagnosed with TB, presumptive TB did not self-initiate care-seeking or is discouraged explicitly by family members to seek TB diagnosis and treatment [ 117 ]. Therefore, it is imperative first to measure the level of knowledge, awareness, and practices regarding TB in settings where studies as such have yet to be conducted. The gaps identified could then be used to develop health education programs and interventions about TB. Studies have shown that health education programs and dissemination of TB information effectively improve TB knowledge and awareness [ 171 ], enabling care-seeking and increasing the identification of TB cases [ 172 ]. Furthermore, understanding the knowledge and practices of health professionals could be done in parallel to improve care and facilitate the early identification of TB [ 173 ].

TB stigma continues to be a major barrier for people to access TB diagnosis and complete treatment [ 10 , 143 ]. Moreover, stigma could also reduce the use of face masks [ 6 , 174 ], further contributing to infection transmission. Despite being an increasingly important agenda of TB programs worldwide, there is a paucity of data on stigma [ 175 ], particularly information from the perpetrators of stigma [ 176 ]. There is also limited evidence on effective interventions that can reduce TB-related stigma [ 177 ]. Considering the importance of stigma reduction in TB control and elimination efforts, stigma should be systematically measured. De-stigmatisation must include approaches in healthcare institutions and beyond for a more inclusive care plan.

In high TB-burden countries, we found that people who presented with cough, fever, and night sweats were more likely to delay TB care-seeking. This is consistent with another systematic review conducted among low and middle-income countries [ 5 ]. The attribution of these symptoms to other respiratory infections or smoking and the inability to link them to TB was claimed as one of the primary reasons causing a delay in seeking care [ 138 ]. Contrarily, more severe symptoms such as hemoptysis were more likely to reduce delays in care-seeking. Therefore, education and awareness-raising activities could be recalibrated to specifically highlight the possibility of TB besides other respiratory illnesses in the event of more general symptoms such as cough and fever. Simultaneously, health workers' awareness on this matter in high-burden settings should be raised to improve TB case findings.

Health system and treatment delay

Health system delay was more pronounced in LIC and LMIC than UMIC, likely due to the standard of health care, the strength of the national health systems, and the availability of resources. Among LIC and LMIC, a systematic review reported that the quality of health care in the public and private sectors was poor. The private sector relatively outperformed the public sector regarding the delivery of care and medicines availability [ 178 ]. The discrepancies in effectiveness and efficiency were highlighted as a facilitator to seek private healthcare, which eventually leads to a delay in TB diagnosis in a high TB burden setting like Cambodia[ 179 ]. Narrowing down to high TB-burden countries, the quality of public and private healthcare was also found to be below par, and systematic evaluations are needed to identify gaps in the TB care pathway [ 157 ].

Likewise, treatment delay was longer in LIC and LMIC than UMIC. The delay might be due to logistic factors such as long distance to treatment centers, availability of anti-TB drugs, and the absence of TB diagnostic services in local health facilities [ 96 , 97 ]. Beyond systemic factors, individuals’ low perceived susceptibility and TB stigma could delay a person’s decision to initiate TB treatment [ 48 , 127 ]. Interventions to decrease isolation post-diagnosis and social support should be provided to encourage prompt initiation of TB treatment [ 180 ]. Health providers also play a vital role in assisting people with TB to internalize the diagnosis and support them in decision-making [ 181 ].

Strengths and limitations

To our knowledge, this systematic review will be the first to focus on countries with a high TB burden, where most of the TB cases in the world [ 2 ] are found. As the list consisted of countries from LIC, LMIC, and UMIC, we attempted to discern the differences in the determinants of delayed TB diagnosis and treatment between these countries.

However, we found high levels of heterogeneity amongst the studies potentially due to clinical and methodological diversities. We included studies from different high TB-burden countries and economic statuses. While we have restricted the study populations to people with presumptive TB and people with TB, their sociodemographic profiles were diverse. We acknowledged the limitation in analyzing data comprising of all possible subgroups in this review. Furthermore, we included the different observational non-randomized studies in this review. The design differed by temporality and the potential biases, contributing to methodological diversity.

In our attempt for comprehensiveness, we retained the threshold of delays as to how they were defined in individual studies. While it might not pose severe concerns for the narrative synthesis and pooling of median delays, the utilization of the delay threshold defined by individual studies in the meta-analysis of risk factors could lead to misinterpretation. Therefore, we pooled effect sizes from eligible studies that utilized similar delay thresholds in the meta-analyses. We incorporated heterogeneity into random-effects models using the Bayesian approach [ 23 ], which could yield more accurate interval estimates than conventional methods, especially for studies with a small sample size and are heterogenous [ 23 , 182 , 183 ]. However, the incorporation of heterogeneity in the random-effects models would not fully account for the clinical and methodological diversity in the studies. Analyses of study-level covariates in a meta-regression may be relevant to further investigate heterogeneities by the differences in studies characteristics and populations. We did not perform a meta-regression in this review, and this method could be considered in future reviews of similar nature.

Nevertheless, caution in interpreting and extrapolating the findings from the meta-analyses is warranted. For the pooled median delays, the overall estimates were influenced by studies in UMIC with larger sample sizes. Therefore, we opined that the pooled estimates by economies would be more informative. In the meta-analyses of risk factors, the pooling of estimates from studies with similar delay thresholds limited the number of studies that could be included. Most of the independent variables were also grouped differently, and we could not standardize them all. Hence, the meta-analyses were only performed for selected variables. However, we strived to maintain this review's comprehensiveness by triangulating findings from narrative synthesis and thematic analyses of qualitative studies.

This review did not include data from all 30 high TB-burden countries due to the absence of key outcome data and research activities. Notwithstanding the potential lack of representativeness due to the scarcity of data from several countries, this review highlights the gaps in knowledge and provides insights into the determinants of TB diagnosis and treatment delay in high-burden countries. However, the heterogeneity of the data limited the generalizability of our findings to settings underrepresented in this review.

Our analyses revealed a substantial delay between the onset of TB symptoms and TB care-seeking among high burden countries, highlighting the need to continue to shape knowledge, change attitude, and raise awareness of the community, people at risk of TB, and the health providers. Specific vulnerabilities such as sex disparities in care-seeking, being older, and geographic isolation should be recognized and addressed through tailored approaches to improve access to TB services and early diagnosis [ 184 ]. It is also crucial to improve the consciousness of the society regarding TB to battle stigma, and networks [ 185 ] of support from within the families, the grassroots, and institutions could create an enabling environment for early care-seeking and treatment adherence and success. In contrast to patient delay, the shorter health system and treatment delay were encouraging. Nonetheless, TB programs should strive to test and treat TB by adopting WHO recommendations for same-day TB diagnosis [ 186 ] to further reduce TB transmission and mortality [ 187 ]. Higher-level policies and interventions such as health system strengthening, universal health coverage, and the provision of sustainable social welfare schemes are important to reduce delays, improve access to TB care, and ultimately achieve the global TB targets [ 188 ].

Availability of data and materials

Not applicable. All data generated or analyzed during this study are included in this published article and its Additional file 1 .

Abbreviations

Critical Appraisal Skills Program

Confidence interval

Human immunodeficiency virus

High quality

Low-income countries

Lower-middle-income countries

Low quality

Medium quality

Preferred Reporting Items for Systematic Reviews and Meta-analysis

International Prospective Register of Systematic Reviews

• Tuberculosis

Upper-middle-income countries

Unites States of America

World Health Organization

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Acknowledgements

We would like to thank Dr. Asano Miho for her guidance in the early part of the study and Miss Annelissa Chin and Miss Ratnala Sukanya Naidu for their assistance with developing the search terms, scanning, and retrieving articles.

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Alvin Kuo Jing Teo, Shweta R. Singh and Kiesha Prem have contributed equally to this work

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Saw Swee Hock School of Public Health, National University of Singapore, National University Health System, Singapore, Singapore

Alvin Kuo Jing Teo, Shweta R. Singh, Kiesha Prem, Li Yang Hsu & Siyan Yi

Department of Infectious Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK

Kiesha Prem

Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore, Singapore

Li Yang Hsu

KHANA Center for Population Health Research, Phnom Penh, Cambodia

Center for Global Health Research, Touro University California, Vallejo, USA

Saw Swee Hock School of Public Health, National University of Singapore, #10-01, 12 Science Drive 2, Singapore, 117549, Singapore

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AKJT, SY, LYH, and SRS conceptualized and designed the study. AKJT and SRS developed the search terms. AKJT conducted the searches. AKJT and STS screened, extracted, and verified the data. AKJT, SRS, and KP analyzed the data. KP and AKJT performed the meta-analysis. AKJT and SRS performed the systematic review and analyzed the qualitative data. AKJT, KP, and SRS prepared the tables and figures. AKJT, KP, and SRS wrote the initial draft of the manuscript. All authors read and approved the final manuscript.

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Additional file 1: table s1..

Newcastle–Ottawa scale scores. Table S2. Critical Appraisal Skills Program (CASP) scores. Table S3. Computation of ConQual rating for patient delay. Table S4. Computation of ConQual score for health system delay. Table S5. Computation of ConQual score for treatment delay. Search strategy: EMBASE. Search strategy: PUBMED. Search strategy: CINAHL. Search strategy: PSYCINFO. Figure S1. Association between sex of individuals and health system delay.

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Teo, A.K.J., Singh, S.R., Prem, K. et al. Duration and determinants of delayed tuberculosis diagnosis and treatment in high-burden countries: a mixed-methods systematic review and meta-analysis. Respir Res 22 , 251 (2021). https://doi.org/10.1186/s12931-021-01841-6

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DOI : https://doi.org/10.1186/s12931-021-01841-6

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Electrical Engineering and Systems Science > Image and Video Processing

Title: phd thesis. computer-aided assessment of tuberculosis with radiological imaging: from rule-based methods to deep learning.

Abstract: Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (Mtb.) that produces pulmonary damage due to its airborne nature. This fact facilitates the disease fast-spreading, which, according to the World Health Organization (WHO), in 2021 caused 1.2 million deaths and 9.9 million new cases. Fortunately, X-Ray Computed Tomography (CT) images enable capturing specific manifestations of TB that are undetectable using regular diagnostic tests. However, this procedure is unfeasible to process the thousands of volume images belonging to the different TB animal models and humans required for a suitable (pre-)clinical trial. To achieve suitable results, automatization of different image analysis processes is a must to quantify TB. Thus, in this thesis, we introduce a set of novel methods based on the state of the art Artificial Intelligence (AI) and Computer Vision (CV). Initially, we present an algorithm to assess Pathological Lung Segmentation (PLS). Next, a Gaussian Mixture Model ruled by an Expectation-Maximization (EM) algorithm is employed to automatically. Chapter 3 introduces a model to automate the identification of TB lesions and the characterization of disease progression. Chapter 4 extends the classification of TB lesions. Namely, we introduce a computational model to infer TB manifestations present in each lung lobe of CT scans by employing the associated radiologist reports as ground truth. In Chapter 5, we present a DL model capable of extracting disentangled information from images of different animal models, as well as information of the mechanisms that generate the CT volumes. To sum up, the thesis presents a collection of valuable tools to automate the quantification of pathological lungs. Chapter 6 elaborates on these conclusions.

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Article Contents

Second time’s the charm assessing the sensitivity and yield of inpatient diagnostic algorithms for pulmonary tuberculosis in a low-prevalence setting.

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Caitlin M Dugdale, Kimon C Zachary, Dustin S McEvoy, John A Branda, Amy Courtney, Rebecca Craig, Alexandra Doms, Lindsay Germaine, Chloe V Green, Eren Gulbas, David C Hooper, Rocio M Hurtado, Emily P Hyle, Michelle S Jerry, Jacob E Lazarus, Molly Paras, Sarah E Turbett, Erica S Shenoy, Second time’s the charm? Assessing the sensitivity and yield of inpatient diagnostic algorithms for pulmonary tuberculosis in a low-prevalence setting, Open Forum Infectious Diseases , 2024;, ofae253, https://doi.org/10.1093/ofid/ofae253

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Among persons with suspected pulmonary tuberculosis, CDC guidelines recommend collecting three respiratory specimens 8-24 hours apart for acid-fast bacilli (AFB) smear and culture, in addition to one nucleic acid amplification test (NAAT). However, data supporting this approach are limited. Our objective was to estimate the performance of one, two, or three AFB smears +/- NAAT to detect pulmonary tuberculosis in a low-prevalence setting.

We conducted a retrospective study of hospitalized persons at eight Massachusetts acute care facilities who underwent mycobacterial culture on one or more respiratory specimens between July 2016–December 2022. We evaluated percent positivity and yield on serial AFB smears and on NAAT among people with growth of Mycobacterium tuberculosis on mycobacterial cultures.

Among 104 participants with culture-confirmed pulmonary tuberculosis, the first AFB smear was positive in 41/104 cases (39%). A second AFB smear was positive in 11/49 cases (22%) in which it was performed. No third AFB smears were positive following two initial negative smears. 36/52 smear-negative cases had NAAT performed, leading to 23 additional diagnoses. Overall sensitivity to detect tuberculosis prior to culture positivity was higher in any strategy involving one or two NAATs (74-79%), even without AFB smears, compared with three smears alone (60%).

Tuberculosis diagnostic testing with two AFB smears offered the same yield as three AFB smears while potentially reducing laboratory burden and duration of airborne infection isolation. Use of one or two NAATs increased sensitivity to detect culture-positive pulmonary tuberculosis when added to AFB smear-based diagnostic testing alone.

• pulmonary tuberculosis
• centers for disease control and prevention (u.s.)
• diagnostic techniques and procedures
• mycobacterium tuberculosis
• tuberculosis
• acid fast stain
• nucleic acid amplification tests
• acid fast bacilli culture

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• Research article
• Open access
• Published: 07 April 2021

Knowledge about tuberculosis, treatment adherence and outcome among ambulatory patients with drug-sensitive tuberculosis in two directly-observed treatment centres in Southwest Nigeria

• Rasaq Adisa 1 ,
• Teju T. Ayandokun 1 &
• Olusoji M. Ige 2  

BMC Public Health volume  21 , Article number:  677 ( 2021 ) Cite this article

9206 Accesses

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Metrics details

Tuberculosis (TB) remains one of the most common infectious diseases worldwide. Although TB is curable provided the treatment commenced quickly, appropriately and uninterrupted throughout TB treatment duration. However, high default rate, treatment interruption and therapy non-adherence coupled with inadequate disease knowledge significantly contribute to poor TB treatment outcome, especially in developing countries. This study therefore assessed knowledge about TB and possible reasons for treatment non-adherence among drug-sensitive TB (DS-TB) patients, as well as evaluated treatment outcomes for the DS-TB managed within a 5-year period.

A mixed-method design comprising a cross-sectional questionnaire-guided survey among 140-ambulatory DS-TB patients from January–March 2019, and a retrospective review of medical-records of DS-TB managed from 2013 to 2017 in two WHO-certified TB directly-observed-treatment centres. Data were summarized using descriptive statistics, while categorical variables were evaluated with Chi-square at p  < 0.05.

Among the prospective DS-TB patients, males were 77(55.0%) and females were 63(45.0%). Most (63;45.0%) belonged to ages 18-34 years. A substantial proportion knew that TB is curable (137;97.9%) and transmittable (128;91.4%), while 107(46.1%) accurately cited coughing without covering the mouth as a principal mode of transmission. Only 10(4.0%) mentioned adherence to TB medications as a measure to prevent transmission. Inaccessibility to healthcare facility (33;55.0%) and pill-burden (10,16.7%) were topmost reasons for TB treatment non-adherence. Of the 2262-DS-TB patients whose treatment outcomes were evaluated, 1211(53.5%) were cured, 580(25.6%) had treatment completed, 240(10.6%) defaulted, 54(2.3%) failed treatment and 177(7.8%) died. Overall, the treatment success rate within the 5-year period ranged from 77.4 to 81.9%.

Conclusions

Knowledge about TB among the prospective DS-TB patients is relatively high, especially with respect to modes of TB transmission and preventive measures, but a sizeable number lacks the understanding of ensuring optimal TB medication-adherence to prevent TB transmission. Inaccessibility to healthcare facility largely accounts for treatment non-adherence. Outcomes of treatment within the 5-year period show that nearly half were cured, while almost one-tenth died. Overall treatment success rate is about 12% below the WHO-defined target. There is generally a need for concerned stakeholders to step-up efforts in ensuring consistent TB enlightenment, while improving access to TB care is essential for better treatment outcome.

Peer Review reports

Tuberculosis (TB) remains one of the most common infectious diseases worldwide [ 1 , 2 , 3 ]. It is estimated that about 10 million people were infected with TB in 2017 with 1.3 million deaths among HIV negative people and an additional 350,000 deaths among HIV positive [ 4 , 5 ]. Tuberculosis incidence rates in Africa have been decreasing at a rate of 4% per year between 2013 and 2017, however, TB incidence rates in Nigeria have remained steady from 2000 through 2017 [ 4 , 6 ]. About 429,000 people in Nigeria have TB each year, while the total TB incidence rate was reported as 219 per 100,000 population [ 1 , 4 , 6 ]. Nigeria ranked number one in Africa and sixth globally among the 30 high TB burden countries and is also among the 14 countries in the world with the triple high burden of TB, TB/HIV and MDR-TB [ 1 , 3 , 6 ]. The global TB treatment success rate was reported as 85% among all new tuberculosis cases, and in Nigeria, TB treatment success rate progressed from 79 to 86% between year 2000 and 2017 [ 5 , 7 ].

Although TB is curable if treatment commenced quickly, appropriately and uninterrupted throughout the 6–9 months course of treatment [ 1 , 4 , 5 ]. However, high default rate, treatment interruption and therapy non-adherence coupled with inadequate disease knowledge significantly contribute to poor TB treatment outcomes among TB patients [ 5 , 7 , 8 ]. Therefore, accurate diagnosis, use of effective anti-TB medications and optimal adherence are priority tools for minimizing morbidity and mortality, as well as mitigating the spread of TB among the population [ 8 , 9 , 10 , 11 ]. In Nigeria, the standard short-course therapy for all categories of drug-sensitive tuberculosis (DS-TB) comprised a 6-month regimen, with 2-month intensive phase of four medications (HRZE) viz. Isoniazid (H), Rifampicin (R), Pyrazinamide (Z) and Ethambutol (E), and a 4-month continuation phase of two medications viz. Isoniazid and Rifampicin (i.e. 2HRZE/4HR) [ 10 , 12 , 13 , 14 , 15 ]. The treatment remained free of charge through the donor support funds, particularly the Damien foundation, and the regimen is administered daily to TB patients in the clinic under the direct supervision of healthcare workers who observe and record patient taking each TB dose (i.e. health facility-based directly observed therapy (DOT) [ 10 , 13 , 14 , 15 ]. Also, the treatment guideline or recommendation for TB patients co-infected with HIV indicated that antiretroviral therapy (ART) should be initiated in all TB-HIV co-infected patients regardless of the CD4 cell counts, within the first 8 weeks of TB treatment (intensive phase), while HIV positive patients with profound immunosuppression (CD4 cell counts < 50 cells /mm3) should receive ART within the first 2 weeks of initiating TB treatment [ 5 , 10 , 16 , 17 , 18 ].

The directly observed therapy concept is one of the five components of DOTs strategy endorsed by the World Health Organisation to create the basis for standard TB care and management [ 10 , 19 , 20 ]. The DOTs strategy had been widely promoted and implemented in many developed and developing countries [ 10 , 21 ]. Nigeria adopted the DOT concept in 1993, as a proactive core management approach to address non-adherence problem among TB patents [ 12 , 14 , 19 ]. However, despite the significant progress made in the control of TB through DOTs strategy, as well as potential advantages of DOT approach in enhancing adherence, TB has remained prevalent, while treatment outcomes and success rate still falls below the WHO defined target especially in low and middle-income countries (LMICs) including Nigeria [ 3 , 4 , 14 , 22 ].

The WHO Global Tuberculosis Report 2020 identified the latest challenges to TB management to include equitable access to quality and timely diagnosis, prevention, treatment and care [ 5 ]. However, non-adherence to TB treatment had also been consistently recognised as a principal factor linked to poor treatment outcomes and suboptimal TB control globally [ 21 , 23 , 24 , 25 ]. Treatment adherence among TB patients is challenging given the complexity, modest tolerability and long duration of treatment regimen currently available for both drug-susceptible and drug-resistant TB [ 23 , 26 ]. Adherence to TB medications is estimated to be as low as 40% in developing countries including Nigeria [ 25 ]. Low adherence may result in failure of initial treatment, emergence of multidrug resistant tuberculosis (MDR-TB), prolonged infectiousness and poor TB treatment outcomes [ 23 , 26 , 27 , 28 ]. In addition, TB patients who are not cured due to treatment non-adherence may pose a serious risk for individuals and community [ 24 , 26 , 29 ]. The WHO recommends at least 85 to 90% treatment success rate for all diagnosed TB cases [ 1 , 7 ]. However, to achieve the target among TB patients, there may be a need for better understanding of the particular barriers to TB treatment adherence, as well as patients’ knowledge and experience about TB and its management [ 30 ]. This may become necessary since adherence to treatment is critical for cure of TB, as well as controlling the spread of TB infection, while minimising the development of drug resistance [ 27 ]. Also, possession of adequate knowledge of the disease may aid the uptake of TB services [ 28 ].

Though, there are studies from many developed and some developing countries that had evaluated knowledge, attitude and practice about TB, as well as barriers to TB treatment adherence [ 30 , 31 , 32 , 33 , 34 , 35 ]. However, most of these studies still left gaps that underscore the necessity for continuous monitoring and evaluation of patient-specific reasons for TB treatment non-adherence, while making consistent efforts to evaluate the knowledge deficits of patients about TB may be essential in finding appropriate solution to the low TB treatment success rate. This study therefore assessed knowledge about TB and the possible reasons for suboptimal treatment adherence among ambulatory drug-sensitive TB (DS-TB) patients in two WHO-certified TB-DOT hospitals in Ibadan, southwest, Nigeria. Also, the treatment outcomes documented in the medical records of DS-TB patients managed in the hospitals between 2013 and 2017 were evaluated.

Study design

The study employed a mixed-method design comprising a prospective questionnaire-guided cross-sectional survey among DS-TB patients for eight consecutive weeks, between January and March, 2019, and a retrospective review of medical records of DS-TB patients managed within the 5-year period in the two hospitals.

Study setting

The tuberculosis DOT clinic of the University College Hospital (UCH) and Government Chest Hospital Jericho (GCHJ) Ibadan. Both hospitals are WHO-certified TB-DOT centres of excellence, supported by Damien Foundation, Belgium, and they both have fully equipped and functional DOT clinic for management of TB patients.

Study population

Adult outpatients (> 18 years) with DS-TB and who were registered with the TB-DOT clinic of the hospitals.

Inclusion and exclusion criteria

All consenting DS-TB outpatients, aged over 18 years, who were on TB treatment for at least one month prior to the commencement of the study were included. Patients with MDR-TB, as well as pregnant women whose condition may necessitate adjustment of standard TB dosage regimen were excluded. Also, case notes of DS-TB patients with incomplete data, especially with respect to treatment outcomes were excluded.

Sample size determination

Representative sample size for the study was calculated using Raosoft® sample size calculator ( www.raosoft.com/samplesize.html ). Eligible population of adult outpatients with DS-TB attending the TB-DOT clinic in UCH and GCHJ were estimated as 55 and 125, respectively for the 8-weeks study period. Thus, with the estimated population of 180 from both hospitals, and assumptions of 95% confidence level, 5% margin of error, as well as 50% conservative estimate to represent the proportion in the target population estimated to have a particular characteristics, a sample size of 125 was obtained. However, adjusting for 10% attrition rate, gave a target sample size of approximately 138 (rounded off to 140) patients. Subsequently, the proportion of participants recruited from each hospital was determined as follows: UCH: (55 ÷ 180) × 140 = 42.7; GCHJ: (125 ÷ 180) × 140 = 97.2. Approximately 40 patients from UCH and 100 from GCHJ were used as target sample size to guide participants’ enrolment. Also, the medical records of all DS-TB patients managed between 2013 and 2017 were selected and reviewed accordingly.

Data collection instrument

The questionnaire and data collection form were designed by the investigators following extensive review of relevant studies [ 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ], as well as previous practice experience. The prospective cross-sectional survey consisted of 25-item questions, including open-ended, closed-ended and open-ended questions with relevant prompts. The questionnaire has three sections, with the primary outcomes measured in Section A included socio-demographic characteristics such as age, sex, educational qualification, occupation and marital status, as well as clinical characteristics including duration on TB treatment, family history of TB, as well as symptoms experienced at the onset of TB infection. Section B contained questions that evaluated patients’ knowledge about TB, modes of TB transmission and suggested preventive measures, as well as TB medications and other adjuncts being taking by the patients. Section C focused largely to explore the patients about possible reason(s) for TB treatment non-adherence, side effects experienced with TB medications and reporting of such side effects to healthcare provider (See additional file  1 ).

The retrospective review of medical records of DS-TB patients was guided by data collection form to retrieve information on demographic characteristics especially age, sex and year of treatment. Also retrieved were disease-specific clinical parameters including sputum smear acid-fast bacilli (AFB) results and any other diagnostic options, as well as patients’ HIV status and outcomes of treatment. In this study, treatment outcomes explored for the DS-TB retrospective cohort included: cured defined as pulmonary TB patients with smear or culture negative in the last month of treatment and in at least one previous occasion; completed treatment defined as pulmonary TB patients with smear or culture negative in the last month of treatment and in at least one previous occasion; failed treatment defined as a positive sputum smear or culture at the month 5 or later during treatment; defaulted defined as an interruption of TB treatment for 2 or more consecutive months; and died defined as TB patients who dies for any reason before starting or during the course of treatment. The definitions were in accordance with the WHO TB treatment guidelines and National Tuberculosis and Leprosy Control Programme (NTBLCP) classifications of TB treatment outcomes [ 7 , 10 , 12 ]. In our study, transferred out was defined as TB patients for whom no treatment was assigned, and which include those transferred out to another facility or treatment unit. The transferred out patients were only captured in the review and documentation, but were not considered as part of treatment outcomes.

Also, successful treatment was defined as the sum of TB patients who were cured and those who completed treatment, while unsuccessful treatment was defined as the sum total of TB patients who defaulted, failed treatment and died [ 7 , 10 , 12 ].

Pre-test and validation of data collection instrument

The questionnaire was assessed for content validity by a panel of consultant pulmonologist working in each of the DOT clinics and a clinical pharmacist in the academia. Subsequently, a pre-test of the instrument was done among 14 randomly selected TB patients from the GCHJ, representing 10% of the total number of patients enrolled for the study. These patients were excluded from the main study. Feedback from pre-test and validity assessment led to minor modifications in the questionnaire including some closed-ended questions which were rephrased in open-ended format with relevant prompts to guide patients’ opinion.

Sampling and recruitment procedure

Eligible DS-TB patients were consecutively enrolled on daily TB-DOT clinic of the hospitals while waiting for their turn of directly observed TB medication-taking or consultation with the attending healthcare provider. Individual patient was courteously approached by the investigators on the daily DOT clinic while strictly observing the TB precautionary measures. Procedure and objectives of the study were comprehensively explained to participants, after which verbal/oral informed consent was obtained from individual patient. The informed consent form and questionnaire were translated into Yoruba, the local language for majority of participants. Patients who do not understand English language were interacted with using the Yoruba version of the questionnaire. Back-translation was subsequently done to ensure response consistency. Patients were assured of confidentiality and anonymity of their responses, while they were informed that participation is entirely voluntary. The questionnaire was interviewed-administered to consented patients on every clinic day by the investigators. All the targeted eligible patients consented for participation and they were all enrolled and administered the questionnaire. Also, the medical records of DS-TB patients from January 2013 to December 2017 in each hospital were chronologically arranged according to the respective year, with relevant parameters retrieved and reviewed.

Data analysis

Data obtained were sorted, coded and entered into the Statistical Package for Social Sciences (SPSS) version 23 for analysis. Descriptive statistics including frequency and percentage were used to summarise the data for prospective and retrospective cohorts. Treatment outcome rates for the retrospective cohort, including cure rate, treatment failure and default rate, as well as mortality or death rate were determined as total number each of TB patients who were cured, failed treatment, defaulted and died divided by the total number of patients who were commenced on TB treatment, multiply by 100 (e.g. cure rate = number of DS-TB patients cured ÷ total number of DS-TB patients placed on TB treatment × 100). Subsequently, treatment success rate was calculated as the sum total of all the patients who were cured and completed treatment (i.e. successful treatment) divided by the total number of patients who were commenced on TB treatment (i.e. successful and unsuccessful treatment) multiply by 100. Transferred out TB patients were excluded as component of unsuccessful treatment since they were not placed on any form of TB treatment. Person Chi-square (χ2) was used to investigate association between relevant patients’ characteristics and those with or without successful TB treatment outcome. Priori level of significance was set at p  < 0.05.

Prospective participants

All the participants enrolled from both hospitals within the study period consented to partake in the study, giving a response rate of 100%.

Socio-demographic characteristics

Out of the 140 DS-TB patients who were administered the questionnaire, 40 (28.6%) were from UCH and 100 (71.4%) from GCHJ. Seventy seven (55.0%) were males and 63 (45.0%) were females. Most (63; 45.0%) patients were within the ages of 18–34 years, while secondary education was highest (66; 47.1%). Fifty-one (36.4%) of the DS-TB patients were in the intensive phase of treatment, while 89 (63.6%) were in the continuous phase (Table l). Of the presenting symptoms reported by patients at the onset of TB infection, cough was the highest manifestation in different combinations (140; 33.7%) Table  1 .

Knowledge of tuberculosis, modes of transmission and suggested preventive measure

A total of 137 (97.9%) patients knew that TB is a curable disease, with most (76; 55.5%) patients obtained the information from healthcare professionals, mostly nurses (42; 32.7%) and physicians (34; 24.8%), while pharmacists were not cited. Also, 128 (91.4%) knew that TB can be transmitted to another person, while 107 (46.1%) accurately cited coughing without covering the mouth as a principal mode of TB transmission. Covering of mouth when coughing (123; 49.6%) topped the list of suggested measures to prevent TB transmission, while 10 (4.0%) mentioned adherence to TB medications (Table  2 ).

Anti-tuberculosis and adjunct medications taken by patients

All the DS-TB patients (51; 100%) in the intensive phase were prescribed quadruple combination of isoniazid (H), rifampicin (R), pyrazinamide (Z) and ethambutol (E), while the 89 (100.0%) patients in continuation phase were on the dual combination of rifampicin and isoniazid. The class of adjunct medications taken by the patients were haematinics (50; 52.1%), antibacterial (13; 13.5%), antiretroviral therapy (12; 12.5%), antihypertensive (6; 6.3%), antidiabetic (4; 4.2%), cough syrup (4; 4.2%), anticonvulsant (3; 3.1%), antipsychotic (2; 2.1%), antiasthmatic (1; 1.0%), and one (1.0%) mentioned herbal preparation.

Reasons for TB treatment non-adherence and side effects experienced with tuberculosis medications

Forty-nine (35.0%) indicated reasons for TB treatment non-adherence, while 91 (65.0%) gave no specific reason. Inaccessibility to healthcare facility (33; 55.0%) topped the list of reasons for TB treatment non-adherence. Other reasons mentioned included too much medications to take at once (10; 16.7%) and size of the tablet being taken (8; 13.9%) Table  3 . Sixty-seven (47.9%) reported to have experienced side effect(s) with TB medications, while 73 (52.1%) did not. Of this, 37 (55.2%) reported the experienced reaction(s) to their physician, while 30 (44.8%) did not report (Table 3 ).

Retrospective participants

Treatment outcomes among the ds-tb patients managed between 2013 and 2017.

Of the 2400 medical records of DS-TB patients reviewed between 2013 and 2017, a total of 2389 (99.5%) had the required information documented, comprising 934 (39.1%) from UCH and 1455 (60.9%) from GCHJ. Also, the case notes reviewed for each year were 431 (18.0%) in 2013; 523 (21.9%) in 2014; 393 (16.5%) in 2015; 516 (21.6%) in 2016 and 526 (22.0%) in 2017. Out of the 2389 eligible case notes, 2262 (94.7%) patients had sputum smear AFB results documented in their case notes before the commencement of TB treatment. This comprised 1596 (70.6%) who had positive AFB sputum smear, and 666 (29.4%) with negative AFB sputum smear but chest X-ray and clinical presentation suggestive of active TB infection. The reminder 127 (5.3%) had neither AFB sputum smear nor chest X-ray results recorded, and were considered as transferred out patients. There was no documentation on TB culture test in the case notes of the DS-TB patients reviewed. Also, of the 2389 patients, 2117 (88.6%) had their HIV status documented, with 427 (20.2%) who had HIV positive status, while 1690 (79.8%) were HIV negative.

Table  4 shows details of treatment outcomes between 2013 and 2017. Of the 2262 (94.7%) whose treatment outcomes were retrieved from the case notes, 1211 (53.5%) DS-TB patients were cured, 580 (25.6%) had their treatment completed, 240 (10.6%) defaulted, 54 (2.3%) failed treatment, while 177 (7.8%) deaths were recorded. The treatment success rate between 2013 and 2017 ranged from 77.4 to 81.9%, and overall 1791 (79.2%) had successful treatment outcome (cured + completed treatment) within the 5-year period. Associations between relevant socio-demographic characteristics and TB treatment outcomes are shown in Table  5 . There were significant associations between sex (χ2 = 8.780, p  = 0.003), HIV status (χ2 = 29.110, p  < 0.001), DOT clinic attended (χ2 = 18.215, p  < 0.001) and patients’ with or without successful treatment outcome. Treatment were significantly successful among males TB patients (57.4%) compared to their female counterparts (42.6%), p  = 0.003, also TB patients with HIV negative status (82.2%) versus HIV positive status (17.8%), p  < 0.001.

In this study, we evaluated knowledge about TB and possible reasons for TB treatment non-adherence among prospective ambulatory DS-TB patients, as well as reviewed the trend in treatment outcomes for DS-TB outpatients managed within a 5-year period in two WHO certified TB-DOT centres. Our study revealed that nearly 98 and 91%, respectively, succinctly understood TB to be curable, as well as being a disease transmittable from one person to another. Previous studies had reported between 76 and 95% of TB patients who knew about the curable nature of TB [ 36 , 37 , 38 , 39 , 40 , 41 ]. Higher values of 96.3 and 97.6% about patients’ awareness of the curability of TB had also been reported in other studies [ 42 , 43 ]. In addition, coughing without covering the mouth, sharing of cutleries and indiscriminate spitting by TB-infected individuals were copiously cited by patients in our study as common modes of TB transmission. This is consistent with previous studies where varying proportions, 25, 53.6 and 63.4% of their patients were reported to be aware of cough hygiene, as an important TB preventive measure [ 42 , 43 , 44 ].

Noteworthy to mention that, only 1.2% of the TB patients in our study expressed some level of misconceptions about TB preventive measures, such as short-term abstinence from sexual intercourse during TB treatment, as well as avoiding clothes sharing. This proportion is far less than 10.8, 15.5, and 22.7% in previous studies [ 39 , 44 , 45 ], where avoiding food and utensils were cited as modes of TB prevention. Surprisingly, 4.3% of the patients could correctly mentioned the current medications for treating TB infection, while only 4% cited adherence to TB medications as a measure to prevent TB transmission. The low proportion of patients with correct response in these regards is a concern that may underscore the need for concerned stakeholders, especially the National Tuberculosis and Leprosy Control Programme (NTBLCP) and TB primary care providers to step-up counselling and enlightenment efforts for TB patients, especially in the areas of core TB preventive measures and modes of transmission, of which adherence to TB medications is most essential. Though, our study did not directly assign score in quantifying patients’ knowledge about TB, rather we focused largely to explore the depth of patients’ understanding of some basic aspects in TB management. However, the perceived good knowledge of patients in some TB preventive measures and modes of transmission seems encouraging and may further emphasise the necessity for continuous public education and enlightenment on TB prevention, treatment and care among the patients. Incidentally, in our study, nurses and physicians were the healthcare providers who were largely cited as source of knowledge information about TB, with no mention of pharmacists. Amazingly, pharmacists are expected to be the core healthcare provider to dispense and counsel patients on their TB medication usage. This perhaps reveals that pharmacists might not have been in direct contact with TB patients at the DOT service point in the hospitals. Thus, a call for concern among relevant stakeholders in the pharmacy profession in Nigeria, of the need to ensure and encourage pharmacists to be more proactively engaged in TB care, whether in the hospital or community pharmacy setting.

Topmost of the reasons cited by patients for TB treatment non-adherence were inaccessibility to healthcare facility, perhaps in terms of travel costs for daily DOT at the clinic, and the idea of taking many anti-TB medicines at once. Lack of access to formal health services, and the consequent non-clinic attendance, as well as poor socio-economic status among many patients with TB have been reported in previous studies [ 46 , 47 ], as key factors hindering continuous progress of DOT concept in enhancing TB treatment adherence. Generally, the two studied TB-DOT facilities largely rely on healthcare-facility or clinic-based DOT, in which TB patients report to the clinic on a daily basis (opening hours 8a.m to 2p.m, in most cases) for their daily dose of TB medications under the direct observation of the attending primary care provider, who monitor and record the TB dose taken. As a result, many TB patients asides from tackling other competing routine demands such as job schedule overlapping with clinic appointment time [ 46 ], may also face the burden of daily transportation/travel costs to the clinic. Nevertheless, the challenge of healthcare inaccessibility may be partly overcome through consideration of non-healthcare facility or clinic-based DOT, perhaps the community-based DOT, where the healthcare provider visit the TB patients in their community to deliver the DOT service [ 10 ]. Although, community-based DOT may involve extra costs to the institution and other supporting partners, however, evidence has shown that community or home-based DOT had higher rates of treatment success in terms of cure, treatment completion and 2-month sputum conversion, as well as having lower rates of mortality and unfavourable outcomes compared with health facility-based DOT [ 10 , 26 ]. In addition, decentralization of TB-DOT service to peripheral facilities closer to the people may also be a vital option to improve access to TB treatment. Many developed and developing countries have embraced decentralization of TB-DOT services, with a positive report of increased access to TB care [ 10 , 11 , 48 , 49 ]. The WHO and NTBLCP have also advocated that further strengthening and decentralization of TB services may be a way forward to achieve the WHO End TB strategy [ 48 , 49 ]. In Nigeria, the major drawback to the TB-DOT decentralization advocacy, may be the lack of competent healthcare personnel at the peripheral facilities to deliver the DOT services [ 19 , 33 , 48 ]. Thus, government and other concerned stakeholders may need to step-up their political and financial commitments toward TB treatment and care, in order to achieve the third united nation sustainable development goals and the WHO End TB strategy of eradicating TB globally by the year 2030 target [ 1 , 50 ]. More importantly, institution of appropriate support systems, specifically, material support including financial incentives such as transport subsidies or financial bonus to TB patients may be essential, to at least take care of the indirect costs that are incurred by patients when attending the daily DOT clinic. In addition, consideration of fixed dose combination (FDC) tablets for TB medications may be useful to overcome the issue of pill burden raised by the patients. The FDC for TB medications is now a conditional recommendation in the 2017 update of WHO TB treatment guidelines, for DS-TB patients [ 10 , 11 ].

A sizeable proportion of the patients claimed to have experienced side effect(s) with their TB medications, but only 5% cited fear of medication side effects as a reason for TB treatment non-adherence. More than one-third of the patients reported that the side effects experienced were expected reactions which they have been pre-informed by their primary care physician. Thus, they probably do not consider such side effect(s) as a barrier to TB treatment adherence. The overwhelming positive response of patients on pre-knowledge information about expected medication side effects is noteworthy and commendable. Therefore, such counselling role and value-added services should be continuous and consistently done at every TB patient-provider encounters. However, our study finding in this regard is in contrast with report from previous studies stating that patients were not informed about side effects and what to do to counter it [ 51 , 52 ]. Providing counsel on possible adverse drug events in language the patient best understand may be helpful in preparing patients towards better appreciation and commitment to their treatment. Typically, the healthcare providers and supporting staff working in the TB-DOT centres used to undergo periodic TB care-related training, as well as seminars organised either by the respective hospital or the funding partners, largely to enhance job performance and competence. This might have helped the TB primary care providers in the efficient discharge of their clinical roles and duties in TB care and management. In general, TB primary care providers should continuously explore the possible reasons for poor TB treatment adherence at every patient-provider encounters, thereby making effort to offer necessary assistance, especially psychological support through robust counselling session or peer group support, with a view to collectively enhance treatment adherence and outcome [ 52 , 53 , 54 ].

Precisely, 54% of TB patients evaluated between 2013 and 2017 were cured, and nearly one-quarter had treatment completed, with close to one-tenth deaths recorded. An overall treatment success rate of approximately 79% was achieved within the 5-year period reviewed, which is about 12% below the WHO-defined target of 90% for new TB cases [ 1 , 7 , 10 ]. The treatment success rate noted in our study is higher than the values recorded in some developing countries [ 55 , 56 , 57 , 58 ], while studies conducted in high-income countries reported a higher treatment success rates [ 7 , 26 ] . Varying TB treatment success rates ranging from 34 to 85% in the low- and middle-income countries have earlier been reported [ 1 , 50 ]. In addition, the default rate of about 10% obtained in our study is three times the WHO target of 3% default rate among TB patients [ 7 , 10 ], but the value is still lower than that reported in previous studies in Nigeria [ 57 , 58 ]. Also, the TB default rates in other studies conducted in South Africa [ 59 ] and Brazil [ 60 ] reported higher rates of default than found in our study. Thus, as previously suggested, there may be a need for institution of appropriate support systems, which may include material, structural and psychological supports [ 61 ] for all categories of DS-TB patients, as this may go a long way to relief the patients’ disease burdens, with greater likelihood of facilitating optimal commitment to TB treatment, and subsequently, there may be improved treatment outcomes and success rate.

In our study, we observed that 8.6% among the prospective DS-TB participants reported antiretroviral therapy (ART) as adjunct medications taking alongside the core anti-TB medications. Although, we may not be able to directly assume this percent prevalence as proportion who may genuinely have HIV positive status. The use of ART drugs with anti-TB medications may perhaps indicate a greater possibility that the concerned patients may be managing or treating a TB co-infected HIV infection. In addition, a value of 20.2% HIV positive status documented in the medical records of DS-TB patients in the retrospective cohort may seem more reliable than the indirect prediction of patient’s HIV status from the self-report mentioning of antiretroviral medications taking by the patients. Nevertheless, a carefully considered future study to further explore the precise prevalence of TB/HIV co-infection may be necessary, in order to make a far-reaching conclusion. The HIV prevalence observed among the DS-TB patients in the retrospective cohort is lower that the HIV prevalence of between 27.2 and 61% reported among TB patients in Eastern and Southern Africa countries [ 53 , 59 , 62 ]. It is noted that TB treatment outcomes was significantly successful among TB patients with HIV negative status, compared to the HIV positive counterparts. Poor treatment outcome among HIV co-infected TB patients has been corroborated by other studies, where HIV co-infection was found to increase the chance of unsuccessful treatment outcome among TB patients [ 57 , 63 , 64 , 65 ]. In general, the low treatment success rates perhaps further reiterates the necessity for concerned stakeholders in tuberculosis control in LMICs including Nigeria, to step-up efforts at ensuring institutionalization of functional and robust TB patients’ support systems, increased advocacy and enlightenment on TB control, as well as consistent availability of anti-TB and relevant adjunct medications at the TB-DOT service centres.

Despite the useful information from our study, the following limitations are worthy of mentioning. This includes the possibility of documentation bias that may arise from patients’ medical records. In the studied facilities, all the DS-TB patients were placed on the same standard 6-month short-course regimen of 2HRZE/4HR, with no discrimination into category 1 (new TB cases) or category II (retreatment TB cases). This was consistent all through the period of review, and this treatment approach conforms to the 2017 update of the WHO TB treatment guidelines [ 10 ]. Also, the cross-sectional nature of our study may not concisely permit the establishment of a causal relationship, while the inherent limitation(s) such as recall bias from the self-report measure [ 37 ] may not be totally excluded. Nevertheless, the use of non-judgemental and non-threatening question-items may probably allow for a sincere opinion among the patients. In addition, the representativeness of sampled population, as well as conduct of the study in two WHO-certified TB-DOT centres may perhaps ensure collection of a more reliable data on TB management, thus a useful strength for our study. Another limitation may be linked to the non-availability of the reasons for treatment non-adherence among the DS-TB patients whose case notes were retrospectively reviewed. Also, patients in the prospective cohort were not explored on other useful patients’ characteristics such as living condition, monthly income, residence area/distance from the DOT facility, lifestyles especially smoking and alcohol intake, which were largely considered to be outside the scope of our study objectives. We focused generally on gaps that may not have been concisely captured in the previous related studies. In addition, the prospective patients were not follow-up to explore their treatment outcomes. These limitations may therefore need to be carefully considered when making generalisation about our study findings.

It can be concluded that knowledge about TB among the prospective DS-TB patients is relatively high, especially with respect to common modes of TB transmission and preventive measures, but a sizeable number lacks the understanding of ensuring optimal TB medication-adherence to prevent TB transmission. Inaccessibility to healthcare facility largely accounts for TB treatment non-adherence. Treatment outcomes within the 5-year period show that nearly half were cured, while almost one-tenth died. Overall treatment success rate of 79% achieved is about 12% below the WHO-defined target. There is generally a need for concerned stakeholders to step-up efforts in ensuring consistent TB enlightenment, while improving access to TB care is essential, perhaps by instituting necessary support systems including financial incentives/subsidies for TB patients generally. Also, the TB primary care provider should consistently re-evaluate the possible reason(s) for TB treatment non-adherence during provider-patient encounters and endeavour to offer essential psychological support through value-added counselling, with a view to increase treatment outcomes and success rate.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

Tuberculosis

Drug sensitive tuberculosis

Directly Observed Treatment Short-course

Institution Review Board

Ethics Review Committee

National Health Research and Ethics Committee

Isoniazid-H, Rifampicin-R, Pyrazinamide-Z and Ethambutol-E

Acid Fast Bacilli

Multidrug Resistance Tuberculosis

Low and middle income countries

World Health Organisation

Tuberculosis and Leprosy Control Programme

Human Immunodeficiency Virus

Antiretroviral Therapy

Statistical Package for Social Sciences

University of Ibadan

University College Hospital

Government Chest Hospital, Jericho

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Acknowledgements

We sincerely acknowledge the medical record staff in the chest clinics of the University College Hospital and Government Chest Hospital Jericho, Ibadan for their assistance during the retrospective data collection, while we appreciate the patients who consented to partake in this study for their cooperation and perseverance.

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Rasaq Adisa & Teju T. Ayandokun

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RA and TTA designed the study, conduct the statistical analysis, developed the manuscript and completed the final write up of the manuscript. OMI proofread and edit the study instruments and the completed manuscript. The authors read and approved the final submission.

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Rasaq Adisa is a Ph. D holder, Senior Lecturer and the Head of Department, Clinical Pharmacy and Pharmacy Administration, Faculty of Pharmacy, University of Ibadan, Ibadan, Nigeria. Teju T. Ayandokun is a postgraduate student in the department of Clinical Pharmacy and Pharmacy Administration, Faculty of Pharmacy, University of Ibadan, and superintendent pharmacist in a community pharmacy in Ibadan, Nigeria . Olusoji M. Ige is a consultant pulmonologist and Head of chest unit in the department of Medicine, College of Medicine, University of Ibadan and University College Hospital, Ibadan, Nigeria.

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The University of Ibadan/University College Hospital (UI/UCH) and the Oyo State Ministry of Health (OYMOH) Ethics Review Committees (ERCs) approved the study protocol, consent form and other participants’ information vide the approval numbers, NHREC/05/01/2008a and AD13/479/957, respectively. We confirm that the oral/verbal inform consent was approved by the UI/UCH and OYMOH ethics committees for consent taken from the participants in our study, especially after the protocol has been duly translated to the local language (Yoruba), to ensure adequate comprehension by participants who did not understand English Language. Also, the consent information as contained in the informed consent form was read and explained to individual participant prior to their enrolment. In addition, the preliminary information on the study questionnaire contained a section with a caption ‘Do you consent to partake in this study’ with a Yes/NO response option, so as to clearly capture participant’s intention to partake in the study before the commencement of interview-administered questionnaire. An affirmative response of Yes, was taken as consent for participation and noted on individual coded questionnaire as a documented evidence for reference purpose.

The UI/UCH and OYMOH Institution Review Boards/ERCs approved and deemed appropriate the use of oral/verbal consent instead of written/signatory informed consent for participation in our study, largely on account of non-invasive nature of our study procedures, as well as consideration of a questionnaire-based survey as the major tool for data collection, with questions carefully designed without infringement on patients’ privacy. However, we ensured and confirmed that all the procedures used in carrying out our study were strictly in accordance with the approved study protocol by the ethics committees, as well as following the ethical principles as stipulated by the Declaration of Helsinki for the conduct of research in human subjects including beneficence, non-maleficence, voluntariness and confidentiality of information among others.

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Questionnaire for the prospective cohort

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Adisa, R., Ayandokun, T.T. & Ige, O.M. Knowledge about tuberculosis, treatment adherence and outcome among ambulatory patients with drug-sensitive tuberculosis in two directly-observed treatment centres in Southwest Nigeria. BMC Public Health 21 , 677 (2021). https://doi.org/10.1186/s12889-021-10698-9

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• Published: 17 May 2024

Mycobacterium tuberculosis suppresses host antimicrobial peptides by dehydrogenating L-alanine

• Cheng Peng   ORCID: orcid.org/0009-0008-5624-4393 1 , 2   na1 ,
• Yuanna Cheng 1 , 2   na1 ,
• Mingtong Ma 1 , 2   na1 ,
• Qiu Chen 1 , 2 ,
• Yongjia Duan 1 , 2 ,
• Shanshan Liu 1 , 2 ,
• Hongyu Cheng 1 , 2 ,
• Hua Yang 1 , 3 ,
• Jingping Huang 1 , 2 ,
• Wenyi Bu 1 , 2 ,
• Chenyue Shi 1 , 2 ,
• Xiangyang Wu 1 , 4 ,
• Jianxia Chen 1 , 3 , 4 ,
• Ruijuan Zheng 1 , 3 ,
• Zhonghua Liu 1 , 3 ,
• Jie Wang 1 , 3 ,
• Xiaochen Huang 1 , 3 ,
• Peng Wang 3 ,
• Wei Sha 3 ,
• Baoxue Ge   ORCID: orcid.org/0000-0002-4086-8299 1 , 2 , 3 , 4 &
• Lin Wang   ORCID: orcid.org/0000-0002-3566-8663 1 , 2 , 3  

Nature Communications volume  15 , Article number:  4216 ( 2024 ) Cite this article

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• Tuberculosis

Antimicrobial peptides (AMPs), ancient scavengers of bacteria, are very poorly induced in macrophages infected by Mycobacterium tuberculosis ( M. tuberculosis ), but the underlying mechanism remains unknown. Here, we report that L-alanine interacts with PRSS1 and unfreezes the inhibitory effect of PRSS1 on the activation of NF-κB pathway to induce the expression of AMPs, but mycobacterial alanine dehydrogenase (Ald) Rv2780 hydrolyzes L-alanine and reduces the level of L-alanine in macrophages, thereby suppressing the expression of AMPs to facilitate survival of mycobacteria. Mechanistically, PRSS1 associates with TAK1 and disruptes the formation of TAK1/TAB1 complex to inhibit TAK1-mediated activation of NF-κB pathway, but interaction of L-alanine with PRSS1, disables PRSS1-mediated impairment on TAK1/TAB1 complex formation, thereby triggering the activation of NF-κB pathway to induce expression of AMPs. Moreover, deletion of antimicrobial peptide gene β-defensin 4 ( Defb4 ) impairs the virulence by Rv2780 during infection in mice. Both L-alanine and the Rv2780 inhibitor, GWP-042, exhibits excellent inhibitory activity against M. tuberculosis infection in vivo. Our findings identify a previously unrecognized mechanism that M. tuberculosis uses its own alanine dehydrogenase to suppress host immunity, and provide insights relevant to the development of effective immunomodulators that target M. tuberculosis .

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Introduction.

Until the coronavirus (COVID-19) pandemic, tuberculosis (TB) was the leading cause of death from a single infectious agent, ranking above HIV/AIDS. In 2022, M. tuberculosis infection was responsible for estimated 10.6 million new TB cases and 1.3 million deaths 1 . M. tuberculosis infection usually triggers host innate and adaptive immune cells to restrict bacterial growth 2 , 3 , 4 , 5 . However, M. tuberculosis has responded to these host defense strategies by evolving virulence factors to counteract host antibacterial mechanisms and facilitate successful intracellular infection 6 , 7 , 8 .

Antimicrobial peptides (AMPs), small cationic and amphipathic peptides, are ancient members of the host defense system that act against a diverse set of pathogens 9 , 10 . It has been shown that the expression of AMPs is induced by M. tuberculosis 11 , 12 and contributes to controlling its infection 13 , 14 , 15 , 16 . However, unlike the strong induction (20- to 40-fold) of AMPs expression by the extracellular pathogens, Pseudomonas aeruginosa and Streptococcus , in macrophages 17 , infection by the intracellular pathogens, M. tuberculosis or Mycobacterium avium , induces very low levels of antimicrobial peptide Hepcidin mRNA in bone marrow-derived monocytes (BMDMs) or the human monocytic cell line THP1 18 . Similarly, in vitro experiments of M. tuberculosis infection have shown that β-defensin is only induced at a high multiple of infection (MOI) in alveolar macrophages and is not detected in blood monocytes at any experimental MOI 19 , 20 . Consistent with this, it has been shown that AMPs are not detected in tuberculous granulomas 19 , 20 , 21 . This suggests that there may be an additional mechanism underlying the suppression of AMPs by pathogenic mycobacteria in monocytes or macrophages, which serve as both habitats for, and the first line of defense against M. tuberculosis .

One striking characteristic of M. tuberculosis is its utilization of type VII secretion systems to secrete numerous proteins across its hydrophobic and highly impermeable cell walls 22 . However, it has remained unclear whether and how such M. tuberculosis -secreted proteins inhibit the production of AMPs. It has been shown that M. tuberculosis infection can induce AMPs efficiently in a human lung epithelial A549 cell line and respiratory murine epithelial cells 19 , 20 . Considering that epithelial cells have very limited phagocytic capacity compared with macrophages, we hypothesized that M. tuberculosis inhibited the production of AMPs in macrophages through their secretory proteins.

In this work, by screening of M. tuberculosis secretory proteins that inhibit the expression of antimicrobial peptide DEFB4 in HEK293T cells and knockout strain validation in macrophages, we observe that M. tuberculosis alanine hydrogenase Rv2780 inhibits the expression of AMPs. Mechanistically, we find that Rv2780 dehydrogenates L-alanine and reduces the level of L-alanine in macrophages. By streptavidin-biotin-L-alanine pull down assay, we show that L-alanine interacts with PRSS1. Moreover, L-alanine relieves the inhibitory effects of PRSS1 on NF-κB activation to induce the expression of AMPs. Functionally, both supplementation of L-alanine and Rv2780 inhibitor GWP-042 show inhibitory activity against M. tuberculosis infection in macrophages and in vivo.

Rv2780 inhibits the expression of AMPs

HEK293T cells are widely used to study the function of pathogenic bacteria secretory proteins on the activation of host NF-κB and MAPKs signal, indicating the existence of integral immune molecules of these two pathways in HEK293T cells 23 , 24 . We also detected endogenous β-Defensin 4 ( DEFB4 ) mRNA levels in HEK293T cells to verify AMP DEFB4 expression at baseline (Supplementary Fig.  1A ). To identify M. tuberculosis proteins that inhibit the expression of AMPs, we transfected HEK293T cells with plasmids encoding 201  M. tuberculosis secreted proteins or lipoproteins 25 and examined their effects on the expression of DEFB4 using reverse transcription (RT)-PCR (Supplementary Fig.  1B ; Supplementary Data  1 ). Rv2780, a secreted alanine dehydrogenase 26 , 27 of M. tuberculosis , was found to reduce the mRNA levels of several AMPs including not only DEFB4 but also β-Defensin 3 ( DEFB3 ) and Cathelicidin Antimicrobial Peptide ( CAMP ), as measured by RT-PCR assay (Supplementary Fig.  1C–E ). Rv2780 was detected in both the supernatants and lysates of M. tuberculosis cultures (Supplementary Fig.  1F, G ), illustrating that Rv2780 is a secreted protein. In addition, Rv2780 was detected in the cytoplasm of mice peritoneal macrophages (MPMs) and A549 cells during M. tuberculosis infection (Supplementary Fig.  1H, I ), suggesting Rv2780 could be secreted to host cells. However, compared to A549 cells, much more abundant Rv2780 protein was detected in H37Rv-infected macrophages (Supplementary Fig.  1H ), suggesting a more powerful function of Rv2780 in macrophages. To analyze the subcellular localization of Rv2780 during M. tuberculosis infection, we detected Rv2780 by immunofluorescence microscopy. Rv2780 was mainly detected in the cytoplasm, partially in mitochondria, very minimally in the endoplasmic reticulum (ER) or lysosome (Supplementary Fig.  1I ).

To further evaluate whether Rv2780 inhibits the expression of AMPs during M. tuberculosis infection, we deleted Rv2780 from an M. tuberculosis H37Rv strain, thus generating an H37RvΔRv2780 strain (Supplementary Fig.  1F, G ). Consistent with previous report 28 , 29 , Rv2780 did not significantly change in vitro H37Rv growth in aerobic condition or fitness to hypoxic condition (Supplementary Fig.  1J, K ). Electronic scanning microscopy analysis showed the similar morphology of H37RvΔRv2780 and H37Rv strain (Supplementary Fig.  1L ). Rv2779c is an Lrp/AsnC family transcriptional factor that binds amino acid ligands to regulate Rv2780 expression 30 , 31 . Deletion of Rv2780 in H37Rv strain dramatically decreased Rv2780 expression but did not significantly change Rv2779c expression (Supplementary Fig.  1M, N ). Besides, alanine level was significantly increased in H37RvΔRv2780 strain (Supplementary Fig.  1O ), suggesting that Rv2780 may function as an alanine dehydrogenase in M. tuberculosis .

Macrophages, which serve as both habitats for and the first line of defense against M. tuberculosis , were infected with the H37Rv or H37RvΔRv2780 strain. Primary peritoneal macrophages infected with H37Rv showed limited increase in the expression of Defb4 (9.63-fold), Defb3 (5.67-fold) and Camp (3.79-fold) at 24 h post-infection (Fig.  1A and Supplementary Fig.  2A, B ). However, H37RvΔRv2780 was associated with much higher induction of the mRNA of Defb4 (21.08-fold), Defb3 (16.94-fold) and Camp (10.41-fold) than in cells infected with wild-type H37Rv for 24 h (Fig.  1A and Supplementary Fig.  2A, B ). Complementation of H37RvΔRv2780 with Rv2780 restored the ability of M. tuberculosis to suppress the expression of Defb4 , Defb3 and Camp (Fig.  1B and Supplementary Fig.  2C, D ). Taken together, these results suggest that M. tuberculosis Rv2780 may inhibit the expression of AMPs.

A RT-PCR analysis of Defb4 in mice peritoneal macrophages infected with wild-type H37Rv or H37RvΔRv2780 for 0, 3, 6, 9,12 and 24 h (multiplicity of infection (MOI) = 2). B RT-PCR analysis of Defb4 in mice peritoneal macrophages infected with wild-type H37Rv, H37RvΔRv2780 or H37RvΔRv2780 + Rv2780 for 0 and 24 h (MOI = 2). Intracellular colony-forming units (CFUs) assay. CFU counts ( C ) and relative intracellular CFU ratio ( D ) in mice peritoneal macrophages (MPMs) infected with wild-type H37Rv, H37RvΔRv2780 and H37RvΔRv2780 + Rv2780 for 3, 6, 12, and 24 h (MOI = 2). 6–8 weeks old female C57BL/6J mice were aerosol-infected with roughly 200 CFUs per mouse of H37Rv, H37RvΔRv2780 or H37RvΔRv2780 + Rv2780. We assayed: CFU of bacterial load ( E ); lung sections with acid-fast staining ( F ), haematoxylin and eosin staining ( F ) and histological score ( G ). Data in ( A–E and G ) are representative of one experiment with at least three independent biological replicates; ( A–D ) n  = 3, each circle represents one technical repeat (mean ± s.e.m); ( E ) n   =  3 mice infected for 1 day and n  = 12 mice infected for 30 days with red, blue and white circles denoting separate experiments (mean ± s.e.m); ( G ) n   =  3 mice (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( A–D ) and two-sided Mann-Whitney U -test ( E , G ) were used for statistical analysis. P values are shown in ( A–D and E , G ). 1#, 2# and 3# in ( F ) represent lung tissues from 3 mice infected for 30 days. Scale bars, 100 μm (top; original magnification, ×400) and 20 μm (bottom; original magnification, ×1000). Source data are provided as a Source Data file.

Antimicrobial peptides kill bacteria directly in vitro and are crucial for macrophages to limit the intracellular survival of M. tuberculosis 11 , 12 , 13 , 14 , 15 . We also examined direct killing effects of AMPs on M. tuberculosis as described previously by ref. 11 , and found that the MIC of Defb4, Defb3 and Camp were at 0.01 μg/ml, 10 μg/ml and 0.1 μg/ml, respectively, suggesting that these AMPs may have the anti- M. tuberculosis activity in vitro (Supplementary Fig.  2E ). To examine whether Rv2780 regulates the intracellular survival of M. tuberculosis , we infected primary peritoneal macrophages with H37Rv or H37RvΔRv2780 strains and measured the survival rate of intracellular M. tuberculosis using a colony forming unit (CFU) assay. H37RvΔRv2780 showed much lower CFU counts in macrophages at 24-h post-infection than H37Rv and H37Rv(ΔRv2780 + Rv2780) (Fig.  1C, D ), suggesting that Rv2780 may be essential for the intracellular survival of M. tuberculosis . ROS production and xenophagy were also shown to restrict the intracellular M. tuberculosis 32 , however deletion of Rv2780 did not significantly change ROS production and xenophagy during M. tuberculosis infection in macrophages (Supplementary Fig.  2F–H ). H37RvΔRv2780 infected macrophages had much lower levels of mRNAs encoding proinflammatory cytokines Interleukin (IL)−1β, IL-6, IL-12p40 and Tumor Necrosis Factor α (TNFα) (Supplementary Fig.  2I–L ).

To further investigate the functional relevance of Rv2780 in the in vivo pathogenesis of M. tuberculosis infection, we challenged C57BL/6J mice with wild-type H37Rv, H37RvΔRv2780 or H37Rv(ΔRv2780 + Rv2780) for 30 days. The bacterial burden in the lung tissues of mice infected with H37RvΔRv2780 was much lower (decreased 1.26-fold in log 10 ) than mice infected with H37Rv and H37Rv(ΔRv2780 + Rv2780) (Fig.  1E ). Consistent with this, lung tissues from mice infected with H37RvΔRv2780 showed less immune-cell infiltration and fewer inflammatory lesions than those from mice infected with H37Rv (Fig.  1F, G ). The lung tissue of mice infected with H37RvΔRv2780 exhibited much lower expression of Il1b , Il6 , Il12 and Tnf than the lung tissue of mice infected with H37Rv (Supplementary Fig.  2M–P ). Together, these results suggest that Rv2780 is an essential virulence factor of M. tuberculosis .

Rv2780 dehydrogenates L-alanine

Rv2780 encodes L-alanine dehydrogenase, an enzyme that catalyzes the NAD + -dependent interconversion of alanine and pyruvate 26 , 27 (Fig.  2A ). The enzymatic kinetics of Rv2780 was assesses by analyzing the enzymatic product pyruvate. The K m and V max were found to be 0.964 mM and 111.8 M/s, respectively (Fig.  2B ). Another in vitro alanine dehydrogenation assay showed that the addition of purified recombinant wild-type Rv2780 led to the greater production of NADH from alanine (Fig.  2C ), suggesting that Rv2780 has the alanine dehydrogenase activity.

A Catalytic model diagram: Rv2780 is an alanine dehydrogenase. Nicotinamide adenine dinucleotide (NAD), reduced NAD (NADH). B Dose-response curves of Rv2780 detected by pyruvate. Km, Vmax were shown in the figure. C In vitro catalytic assay of Rv2780 with increasing concentration of L-alanine (0, 10, 100 mM). Rv2780 enzyme inactive mutant Rv2780 (H96A, D70A) (Rv2780 DM ) was used as negative control. D Heat map of downregulated (blue) and upregulated (red) metabolites in sera from C57BL/6J mice aerosol-infected with roughly 200 CFUs per mouse of H37Rv for 30 days; Uninfected n  = 4, H37Rv infection n  = 4. E Heat map of all the detected amino acids in sera from each uninfected or H37Rv infected mice. 1#, 2#, 3# and 4# represent serum samples from 4 mice. F Quantitative analysis of alanine in plasma from healthy controls (HC) or tuberculosis patients (TB) (mean ± s.e.m. of n  = 35). Alanine detection assay. Normalized alanine level in cell lysates ( G ) and supernatants ( H ) of MPMs infected with wild-type H37Rv, H37RvΔRv2780, H37RvΔRv2780 + Rv2780 or H37RvΔRv2780 + Rv2780 DM for 0, 3, 6, 9,12, 24 and 48 h (MOI = 2). Normalized alanine level in sera ( I ) or lung homogenates ( J ) of mice infected with indicated strains for 7 and 28 days (mean ± s.e.m. of n  = 3 or n  = 5). Alanine level was normalized to GAPDH level in ( G and H ). Alanine level was normalized to protein level in ( I ) and ( J ). Data in ( B , C ) and ( F , G – J ) are representative of one experiment with at least three independent biological replicates; C n  = 3, each circle represents one technical repeat (mean ± s.e.m); F n   =  35 samples for each group (mean ± s.e.m); ( I , J ) n   =  4 mice in uninfected group or n   =  5 mice in other groups (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( C ) and two-sided Mann-Whitney U -test ( F , I , J ) were used for statistical analysis. P values are shown in ( C , F , I and J ). Source data are provided as a Source Data file.

By performing gas chromatography-mass spectroscopy analysis of metabolites in sera of C57BL/6 J mice infected with M. tuberculosis H37Rv, we found that the level of alanine was markedly reduced in sera of infected mice (Fig.  2D ; Supplementary Data  2 ). By contrast, other amino acids such as methionine, phenylalanine and aspartic acid were not significantly changed in response to H37Rv infection (Fig.  2E and Supplementary Fig.  3A–C ), suggesting that the decreased alanine level may be specifically caused by M. tuberculosis infection rather than food intake or metabolism. Moreover, smear-positive patients with TB had much lower level of alanine in their plasma than healthy people (Fig.  2F ). This is consistent with a previous report showing that alanine was one of the metabolites showing the greatest decrease in a 1 H nuclear magnetic resonance spectroscopy-based metabolomic analysis of sera from TB patients 33 . Host glutamic pyruvic transaminase (GPT) also known as alanine aminotransferase (ALT) can catalyze the reversible interconversion of L-alanine and 2-oxoglutarate to pyruvate and L-glutamate 34 . Therefore, we next analyzed the relationship between alanine level and GPT in sera of TB patients. However, as shown in Supplementary Fig.  3D–F , no significant correlation between alanine and GPT was noted in patients with TB. Together, the decrease of alanine level in M. tuberculosis -infected mice and TB patients might be mediated by M. tuberculosis infection.

We further compared the chest X-ray score and the smear score between the top seven patients with the highest plasma alanine level and the bottom seven patients. We found TB patients with lower alanine level exhibited a trend of more severe pulmonary pathological damage, indicated by higher X-ray score (Supplementary Fig.  3F, G ). However, it seems that alanine level is not correlated with the smear score (Supplementary Fig.  3H ). This may be because the smear score cannot fully reflect the bacterial load in TB patients.

Structural analysis of Rv2780 revealed two typical alanine dehydrogenase activity sites at histidine 96 (H 96 ) of the catalytic domain and aspartic acid 270 (D 270 ) of the NAD + binding domain, which are highly conserved across different bacterial species (Supplementary Fig.  3I ). Mutation of two active sites on Rv2780 (Rv2780 DM , with H96A and D270A) impaired its alanine dehydrogenase activity (Fig.  2C ). Overexpression of wild-type Rv2780, but not its inactive mutant Rv2780 DM markedly decreased the level of L-alanine in both HEK293T and A549 cells (Supplementary Fig.  3J, K ). Moreover, the level of alanine was reduced in H37Rv or H37Rv(ΔRv2780 + Rv2780) infected macrophages, but infection of H37RvΔRv2780 or H37Rv(ΔRv2780 + Rv2780 DM ) led to much more abundant alanine in the infected cells (Fig.  2G, H ; Supplementary Fig.  3L ). We analyzed total metabolic profiling of macrophages infected with H37Rv, H37Rv(ΔRv2780), H37Rv(ΔRv2780 + Rv2780) and H37Rv(ΔRv2780 + Rv2780 DM ) for 24 h. Consistently, the level of pyruvate was higher in H37Rv or H37Rv (ΔRv2780 + Rv2780) infected macrophages than that of H37RvΔRv2780 or H37Rv (ΔRv2780 + Rv2780 DM ) infection group (Supplementary Fig.  3L ; Supplementary Data  3 ). However, deletion Rv2780 had no effects on the content of other metabolites in central carbon metabolism, including citrate, α-ketoglutarate, fumarate, and lactate (Supplementary Fig.  3M, N ; Supplementary Data  3 ).

To measure the effect of Rv2780 on central carbon metabolic flux, 13 C-labeled tracing analysis was conducted in macrophages. As shown in Supplementary Fig.  4A–D , 13 C6-glucose is converted to produce labeled pyruvate, which can be decarboxylated to form labeled two-carbon metabolite acetyl-CoA and entered into Trichloroacetic acid (TCA) cycle, while unlabeled alanine is dehydrogenized by Rv2780 to form unlabeled pyruvate. Pyruvate provides two carbons to acetyl-CoA, citrate, α-ketoglutarate, succinate and fumarate. Both labeled and unlabeled pyruvate-derived acetyl-CoA are entered into the TCA cycle respectively. Compared with ΔRv2780 infection, the percentage of unlabeled alanine was decreased in H37Rv-infected macrophage suggesting the metabolic flux from alanine to pyruvate in the presence of Rv2780 (Supplementary Fig.  4B ; Supplementary Data  4 ). However, the percentage of unlabeled other metabolites were not significantly different between H37Rv- and H37RvΔRv2780-infected macrophages. These results suggest that Rv2780 has no significant effect on macrophages glycolysis or TCA cycle.

Besides, complementation of H37RvΔRv2780 with wild-type Rv2780, rather than Rv2780 DM mutant significantly decreased alanine in lung tissues and sera from H37Rv infected mice at 7- and 28-days post-infection (Fig.  2I, J ). These results suggest that M. tuberculosis may have evolved a metabolic ability to dehydrogenate L-alanine via Rv2780 in host cells and can therefore reduce the alanine level in eukaryotes.

Rv2780 suppresses AMPs by dehydrogenating alanine

Given that Rv2780 decreased both the level of L-alanine and expression of AMPs, we hypothesized Rv2780 might suppress AMPs expression through L-alanine dehydrogenation. To verify the effect of L-alanine on AMPs expression, we supplemented macrophages with L-alanine before M. tuberculosis infection. Addition of L-alanine significantly increased mRNA levels of Defb4 (27.95-fold), Defb3 (9.97-fold) and Camp (8.57-fold) in macrophages infected with M. tuberculosis H37Rv for 24 h (Fig.  3A and Supplementary Fig.  5A, B ). Rv2780 also shows glycine dehydrogenase activity in vitro 35 , 36 . We supplemented Rv2780-overexpressed HEK293T cell with L-alanine or glycine, and ELISA analysis was performed to determine the protein level of Defb4 and Camp 37 , 38 . Administration of alanine rather than glycine rescued the Rv2780-mediated inhibition of AMPs expression (Supplementary Fig.  5C–E ). Moreover, only supplementation with L-alanine, but not D-alanine or glycine increased Defb4 and Camp protein level in response to H37Rv infection (Fig.  3B and Supplementary Fig.  5F ). These results suggest that Rv2780 may inhibit AMPs expression through its alanine dehydrogenase activity.

A RT-PCR analysis of Defb4 in MPMs treated with 1mM L-alanine (L-ala) for 12 h followed by H37Rv infection for another 0, 3, 6, 9, 12, and 24 h (MOI = 2). B ELISA analysis of Defb4 in MPMs treated with 1mM L-alanine, 1 mM D-alanine (D-ala) or 1 mM Glycine (Gly) for 12 h followed by H37Rv infection for another 0, 24 and 48 h (MOI = 2). ELISA analysis of Defb4 in cell lysates of MPMs ( C ) infected with indicated strains for 0, 24 and 48 h (MOI = 2) or lung homogenates ( D ) and sera ( E ) of mice infected with indicated strains for 7 and 28 days. CFU counts ( F ) and relative intracellular CFU ratio ( G ) in MPMs infected with indicated strains for 3 and 24 h (MOI = 2). CFU counts ( H ) and relative intracellular CFU ratio ( I ) in wild type and Defb4 -/- MPMs infected with indicated strains for 3 and 24 h (MOI = 2). CFU assay ( J ), histopathological assay by acid-fast staining and haematoxylin and eosin staining ( K ) and histological score ( L ) in lung tissues of wild type (WT) and Defb4 −/− mice aerosol-infected with H37Rv and H37RvΔRv2780 for 7 days and 30 days. Data in ( A – J ) and ( L ) are representative of one experiment with at least three independent biological replicates; ( A – C and F – I ) n   =  3, each circle represents one technical repeat (mean ± s.e.m); ( D , E ) n   =  3 mice (mean ± s.e.m); ( J ) n   =  3 mice infected for 7 days and n  = 12 mice infected for 30 days with red, blue and white circles denoting separate experiments (mean ± s.e.m); ( L ) n  = 3 mice (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( A – C , F – I ) and two-sided Mann-Whitney U -test ( D , E , J , L ) were used for statistical analysis. P values are shown in A – J and L . 1#, 2# and 3# in ( K ) represent lung tissues from 3 mice infected for 30 days. Scale bars, 100 μm (top; original magnification, ×400) and 20 μm (bottom; original magnification, ×1000). Source data are provided as a Source Data file.

To further examine whether Rv2780 suppresses the AMPs by its dehydrogenase activity, we infected mice peritoneal macrophages or BMDMs with H37Rv(ΔRv2780 + Rv2780) or H37Rv(ΔRv2780 + Rv2780 DM ) and examined the protein level or mRNA level of Camp and Defb4 . Only the H37RvΔRv2780 strain complemented with wild-type Rv2780, but not with Rv2780 DM , restored the ability of M. tuberculosis to suppress Defb4 and Camp (Fig.  3C and Supplementary Fig.  5G-J ). Consistently, infection with H37Rv(ΔRv2780 + Rv2780), but not with H37Rv(ΔRv2780 + Rv2780 DM ), induced much lower production of Camp and Defb4 in the serum or lung of mice (Fig.  3D, E and Supplementary Fig.  5K, L ).

H37Rv(ΔRv2780 + Rv2780), but not H37Rv(ΔRv2780 + Rv2780 DM ), rescued an Rv2780-mediated increase in the intracellular survival of M. tuberculosis in mice peritoneal macrophages (Fig.  3F, G ). However, no difference in cell viability was observed in macrophages infected with different strains (Supplementary Fig.  6A ). In addition, deletion of Rv2780 also reduced M. tuberculosis survival in BMDMs (Supplementary Fig.  6B, C ), alveolar macrophages (Supplementary Fig.  6D, E ), or neutrophils (Supplementary Fig.  6F, G ), and the reduced survival of H37RvΔRv2780 was rescued by the complementation of Rv2780, but not Rv2780 DM . These results suggest that M. tuberculosis Rv2780 may suppress the expression of AMPs, thus promoting M. tuberculosis intracellular survival by its alanine dehydrogenase activity.

To examine whether Rv2780 increased M. tuberculosis intracellular survival via inhibiting AMPs, we infected Defb4 −/− mice peritoneal macrophage with H37Rv, H37RvΔRv2780, H37Rv(ΔRv2780 + Rv2780) and H37Rv(ΔRv2780 + Rv2780 DM ). We found that deletion of Defb4 markedly increased intracellular survival of H37Rv, and eliminated the enhanced effects of Rv2780 on intracellular survival of H37Rv and H37Rv(ΔRv2780 + Rv2780) (Fig.  3H, I ). Moreover, we infected Defb4 knockout mice with H37Rv or H37RvΔRv2780 to further validate in vivo relevance of Rv2780 and Defb4. Knockout of Defb4 markedly increased bacterial burden and pathological damages in lung tissues of the M. tuberculosis H37Rv-infected mice, and abolished the increased bacterial burden and pathological damages by Rv2780 in lung tissues of the M. tuberculosis -infected mice (Fig.  3J–L ). However, no difference in the alanine level in sera and lung tissues was detected between WT and Defb4 -/- mice when infected with H37Rv (Supplementary Fig.  6H, I ). Above all, these data suggest that Rv2780 may increase the survival of M. tuberculosis through suppressing the expression of AMPs.

L-Alanine interacts with PRSS1

We next investigated the mechanism underlying the induction of AMPs by L-alanine. By performing biotin-streptavidin pull-down assay combined with mass spectrometry analyses 39 , 40 (Fig.  4A and Supplementary Fig.  7A ; Supplementary Data  5 ), we found that cationic trypsinogen (protease serine 1, PRSS1), encoded by a susceptibility gene associated with chronic pancreatitis 41 , interacted with L-alanine, but not with D-alanine (Fig.  4B, C ), and non-biotinylated L-alanine could competitively elute biotinylated L-alanine from PRSS1 (Supplementary Fig.  7B ). PRSS1 is a serine protease composed of the N-terminal alpha-trypsin chain 1 and C-terminal chain 2 that are linked by a disulfide bond 42 , 43 (Supplementary Fig.  7C ). Only the N-terminal alpha-trypsin chain 1, not C-terminal chain 2, of PRSS1 interacted with L-alanine (Supplementary Fig.  7D ). MicroScale Thermophoresis (MST) analysis 44 revealed that L-alanine strongly interacted with PRSS1 (KD = 8.88 × 10 −5  M) (Fig.  4D ). These results suggest that L-alanine may interact with PRSS1.

A Work flow of biotin-streptavidin pulldown assay combined with mass spectrometry. Streptavidin pulldown assays of the binding of biotin-conjugated L-alanine to Flag-PRSS1 in HEK293T cells ( B ) or recombinant PRSS1 ( C ). Biotin-conjugated D-alanine was used as control ( C ). D MicroScale Thermophoresis (MST) assay of the direct interaction of L-alanine with Prss1. E – G Immunoblot and immunoprecipitation of HEK293T cells transfected with indicated plasmids. H Endogenous immunoprecipitation analysis of wild type (WT) or heterozygous Prss1 knockout ( Prss1 +/− ) MPMs infected with H37Rv for 0, 1 and 3 h (MOI = 2). I Immunoblot analysis of WT or Prss1 +/− MPMs infected with H37Rv or H37RvΔRv2780 for 0, 1, and 3 h (MOI = 2). J RT-PCR analysis of Defb4 in WT or Prss1 +/− MPMs treated with 1mM L-alanine followed by H37Rv infection for 24 h (MOI = 2). CFU ( K ), histological score ( L ) and histopathological images ( M ) by acid-fast staining and haematoxylin and eosin staining in lung tissues of macrophage conditional Prss1 knockout mice ( Lyz2 cre Prss1 fl/fl ) and control mice ( Prss1 fl/fl ) after 28 days of H37Rv infection. Scale bars, 1000 μm (top; original magnification, ×40) and 200 μm (bottom; original magnification, ×100). CFU counts ( N ) and relative intracellular CFU ratio ( O ) in WT or Prss1 +/− MPMs treated with 1 mM L-alanine followed by H37Rv infection for 3 and 24 h (MOI = 2). Data are representative of one experiment with at least three independent biological replicates; ( D , J , N , O ) n  = 3 samples (mean ± s.e.m), each circle represents one technical repeat in ( J and N ,  O ); ( K ) n  = 16 mice infected for 28 days with red, blue and white circles denoting separate experiments (mean ± s.e.m); ( L ) n   =  4 mice (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( J , N , O ) and two-sided Mann-Whitney U -test ( K , L ) were used for statistical analysis. P values are shown in ( J , L and N , O ). 1#, 2# and 3# in ( M ) represent lung tissues from 3 mice. Scale bars, 100 μm (top; original magnification, ×400) and 20 μm (bottom; original magnification, ×1000). Source data are provided as a Source Data file.

It has been shown that M. tuberculosis infection induces the expression of AMPs through the TLR2/NF-κB signaling pathway 11 . Upon stimulation, the ubiquitin ligase, TRAF6, which is downstream of the TLR2 receptor, induces TAK1 oligomerization-dependent auto-phosphorylation and TAK1 subsequently activates the IKK-mediated NF-κB signaling pathway 45 , 46 . We next examined whether PRSS1 had any effect on activation of NF-κB using a luciferase reporter gene assay. As shown in Supplementary Fig.  7E , the overexpression of PRSS1 markedly suppressed the activation of NF-κB by TRAF6 or TAK1, but not that mediated by IKKα/β, suggesting that PRSS1 may block the activation of NF-κB signaling by acting at downstream of the TAK1 complex and upstream of IKKα/β.

To elucidate the mechanism underlying the inhibition of NF-κB signaling by PRSS1, we examined the interactions between PRSS1 and TLR pathway signaling molecules. PRSS1 was found to interact with TAK1, which is co-expressed with TAB1 in HEK293T cells (Fig.  4E ). The interaction between TAK1 and TAB1 is important for the activation of TAK1 47 . In HEK293T cells, PRSS1 markedly impeded the interaction between TAK1 and TAB1 and consequently inhibited the enhanced phosphorylation of TAK1 by TAB1 (Fig.  4F, G ). Moreover, enhanced formation of TAK1-TAB1 complex was found in Prss1 +/- peritoneal macrophages (Fig.  4H ), suggesting that PRSS1 may disrupt formation of the TAK1-TAB1 complex. Lastly, deletion of Rv2780 markedly increased the phosphorylation of p65, but treatment of TAK1 inhibitor ((5Z)-7-oxozeaenol, 5Z-7Ox) eliminated the reduced phosphorylation of p65 by Rv2780. (Supplementary Fig.  7F ). Consistently, inhibition of p65 phosphorylation by Rv2780 was not observed in Prss1 +/- macrophages (Fig.  4I ). Much higher level of NF-κB activation and AMPs expression are also observed in Prss1 +/− macrophages in response to gram-negative bacteria Escherichia coli ( E. coli ) (Supplementary Fig.  7G ) or another gram-positive bacteria Staphylococcus aureus ( S. aureus ) infection (Supplementary Fig.  7H ), suggesting the inhibition of NF-κB by PRSS1 may be a general mechanism. These results suggest that Rv2780 may inhibit NF-κB signaling via PRSS1 and TAK1 during M. tuberculosis infection.

L-alanine induces AMPs via PRSS1

We next investigated the role of PRSS1 in the regulation of AMPs. Prss1 +/− macrophages had much higher mRNA levels of AMPs than wild-type cells infected with E. coli (Supplementary Fig.  7I–K ), S. aureus (Supplementary Fig.  7l–N ), or M. tuberculosis H37Rv (Fig.  4J and Supplementary Fig.  7O–Q ), suggesting PRSS1 is a potent negative regulator of AMPs expression.

The in vivo role of Prss1 in macrophages was validated by generating macrophage conditional Prss1 knockout mice ( Lyz2 cre Prss1 floxp/floxp mice). Accordingly, Lyz2 cre Prss1 floxp/floxp mice exhibited decreased lung bacterial burden and tissue damage compared with Prss1 floxp/floxp mice (Fig.  4K–M ). These results suggest that PRSS1 may inhibit the induction of AMPs, and negatively regulates anti-TB immunity.

To further examine the functional relevance of PRSS1 and L-alanine, peritoneal macrophages from WT or Prss1 +/− mice were treated with L-alanine followed by infection with M. tuberculosis H37Rv. As shown in Fig.  4J and Supplementary Fig.  7O-Q , L-alanine promoted AMPs expression in WT but not Prss1 +/− MPMs, suggesting L-alanine induces AMPs via PRSS1. The binding affinity between PRSS1 and L-alanine was 8.88 × 10 -5  M, suggesting a strong interaction. To determine the threshold on L-alanine level to enhance antimicrobial peptide through PRSS1, we supplemented WT and Prss1 +/- macrophages with different concentrations of L-alanine, and found 0.01 mM L-alanine was sufficient to induce Defb4 expression in WT, but not Prss1 +/- MPMs (Supplementary Fig.  7Q ).

In addition, Prss1 +/− MPMs infected with M. tuberculosis H37Rv had much lower intracellular CFU than those WT counterparts (Fig.  4N, O ). L-alanine significantly inhibited the intracellular survival of M. tuberculosis H37Rv in WT macrophages, but not in Prss1 +/− peritoneal macrophages (Fig.  4N, O ), suggesting that L-alanine may restrict the intracellular growth of M. tuberculosis through PRSS1.

Supplementation of L-alanine enhances anti-TB immunity

Above all, we aim to test the effect of L-alanine on the clearance of M. tuberculosis inside macrophages. The growth of the M. tuberculosis H37Rv strain in vitro was not significantly affected by L-alanine treatment (Supplementary Fig.  8A, B ). However, treatment with L-alanine dramatically inhibited the intracellular survival of M. tuberculosis H37Rv at an efficient level equivalent to that of the best-in-class antibiotic rifampicin (RIF) 48 and a combination of L-alanine and RIF resulted in an even lower bacterial burden compared with either agent alone (Fig.  5A, B ), suggesting that L-alanine could be used to complement first-line anti-TB drugs. Moreover, L-alanine efficiently killed a clinical multiple-drug-resistant (MDR) M. tuberculosis strain in macrophages (Fig.  5C, D ). No significant effect on cell viability was observed of L-alanine, no matter with or without H37Rv infection (Supplementary Fig.  8C, D ). These results suggest that L-alanine may act as an efficient host-directed inhibitor of M. tuberculosis , particularly for drug-resistant M. tuberculosis for which current antibiotics are largely ineffective.

CFU counts ( A ) and relative intracellular CFU ratio ( B ) in MPMs treated with 1 mM L-alanine, 50 nM rifampicin (RIF) or combination of 1 mM L-alanine and 50 nM RIF followed by H37Rv infection for 3 and 24 h (MOI = 2). CFU counts ( C ) and relative intracellular CFU ratio ( D ) in MPMs treated with 1 mM L-alanine or 50 nM rifampicin (RIF) followed by multidrug-resistant M. tuberculosis (MDR) infection for 3 and 24 h (MOI = 2). E Survival curve of 6-week-old female SCID mice treated with ddH 2 O or 30 mg/ml L-alanine and aerosol infected with roughly 100 CFUs per mouse of H37Rv. CFU assay ( F ), histological score ( G ) and histopathological assay ( H ) with acid-fast staining and haematoxylin and eosin staining in lung tissues of C57BL/6J mice treated with ddH 2 O or 30 mg/ml L-alanine after 28 days of H37Rv infection. Data in ( A – D ) are representative of one experiment with at least three independent biological replicates; ( A – D ) n   =  3, each circle represents one technical repeat (mean ± s.e.m); ( F ) n  = 6 mice (mean ± s.e.m); ( G ) n   =  3 mice (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( A – D ), Log-rank test ( E ) and two-sided Mann-Whitney U -test ( F , G ) were used for statistical analysis. P values are shown in ( A – G ). 1#, 2# and 3# in ( H ) represent lung tissues from 3 mice. Scale bars, 100 μm (top; original magnification, ×400) and 20 μm (bottom; original magnification, ×1,000). Source data are provided as a Source Data file.

Since L-alanine was a strong inducer of AMPs that restrict the intracellular survival of M. tuberculosis , while M. tuberculosis infection substantially reduced the level of alanine in host immune cells, we next addressed the therapeutic effectiveness of L-alanine in vivo. In severe combined immunodeficient (SCID) mice model 49 , mice given L-alanine lived much longer, suggesting L-alanine functions in an innate immunity-dependent way (Fig.  5E ). C57BL/6J mice challenged with H37Rv were given double-distilled water or that containing 30 mg/mL L-alanine or D-alanine, and their lungs examined by histopathology and for bacterial burden. Upon M. tuberculosis H37Rv infection, mice supplemented with L-alanine, but not D-alanine, had less histological damage in their lungs than mice given double-distilled water alone (mock) (Fig.  5F–H ). Similarly, the bacterial burden in the lungs of H37Rv-infected mice treated with L-alanine was also much lower (decreased 1.332-fold in log 10 ) than control mice. These results suggest that L-alanine may inhibit the pathogenesis of M. tuberculosis infection in vivo.

Targeting Rv2780 inhibits the growth of mycobacteria in vivo

The crystal structure of the M. tuberculosis Rv2780 (PDB code: 2VHX) with NAD + binding domain was used for structure-based virtual screening of commercial databases (Locator Library and MCE Compound Library), which contain 309,800 inhibitors. As shown in Fig.  6A-C , a small-molecule compound, (S)-N-(5-(3-fluorobenzyl)-1H-1,2,4-triazol-3-yl) tetrahydrofuran-2-carboxamide (GWP-042), bound to Rv2780, forming four hydrogen bonds, one cation - π interaction and multiple hydrophobic interactions (Supplementary Data  6 ). Localized surface plasmon resonance (SPR) assay revealed that GWP-042 interacted strongly with Rv2780. The equilibrium dissociation constant (KD) of GWP-042 to Rv2780 was 1.896×10 -5  M, nearly 3-10 folds lower than other reported anti-tuberculosis drug to their target protein 50 , 51 (Fig.  6D ). To further clarify whether GWP-042 inhibits the activity of Rv2780, we measured the hydrogenase activity of Rv2780 in the presence of increasing concentrations of GWP-042. By measuring the enzymatic production of pyruvate that reflects the enzyme activity of Rv2780, the IC 50 of GWP-042 on Rv2780 was 0.21 ± 0.05 μM as indicated by pyruvate (Fig.  6E ), which is almost 100 folds lower than the reported Rv2780 inhibitors 52 . These data suggest that GWP-042 may act as a powerful inhibitor of Rv2780.

A Structure of GWP-042. Superimposition image ( B ) of docked pose of the GWP-042 to Rv2780 protein. Ligand-target interaction diagram ( C ) showing interactions of GWP-042 with the active site residues of Rv2780 protein. D Surface plasmon resonance (SPR) assay of the direct interaction of GWP-042 with Rv2780 protein. ( E ) The dehydrogenase activity of Rv2780 was measured by pyruvate concentration in the presence of increasing concentrations of GWP-042. Dose–response curves for IC 50 values were determined by nonlinear regression. F ELISA analysis of Defb4 in MPMs treated with 50 μM GWP-042 followed by H37Rv or H37RvΔRv2780 infection for 0, 24 and 48 h (MOI = 2). CFU counts ( G ) and relative intracellular CFU ratio ( H ) in mice peritoneal macrophages treated with 50 μM GWP-042 followed by H37Rv or H37RvΔRv2780 infection for 3, 6, 12, and 24 h (MOI = 2). CFU assay ( I ), histological score ( J ) and histopathological assay with acid-fast staining and haematoxylin and eosin staining ( K ) in lung tissues of C57BL/6 J mice aerosol-infected with roughly 200 CFUs per mouse of H37Rv for 21 days, and treated with Rifampicin (RIF) (10 mg/kg/day) or GWP-042 (10 mg/kg/day) via oral gavage for another 28 days. Data in ( E–J ) are representative of one experiment with at least three independent biological replicates; ( E – H ) n   =  3 samples (mean ± s.e.m), each circle represents one technical repeat in ( F – H ); ( I ) n  = 13 mice infected for 28 days with red, blue and white circles denoting separate experiments (mean ± s.e.m); ( J ) n  = 3 mice (mean ± s.e.m). Two-tailed unpaired Student’s t -test ( F – H ) and two-sided Mann-Whitney U -test ( I , J ) were used for statistical analysis. P values are shown in ( F–J) . 1#, 2# and 3# in ( K ) represent lung tissues from three mice. Scale bars, 100 μm (top; original magnification, ×400) and 20 μm (bottom; original magnification, ×1000). Source data are provided as a Source Data file.

Mycobacterium marinum ( M. marinum ), a pathogen of zebrafish that is the closest genetic relative of the M. tuberculosis organism complex 53 , possesses a conserved homolog of alanine dehydrogenase (Rv2780) (Supplementary Fig.  3I ). Zebrafishes have an antimicrobial peptide system 54 and have been used as a powerful host–pathogen system for characterizing anti-mycobacterial compounds 55 , 56 . From the top 15 compounds of the docking study with the best docking scores, GWP-042 was found to be the most effective inhibitor to restrict the growth of M. marinum in zebrafish larvae (Supplementary Fig.  9A, B ), but showed no significant effect on the growth rate of M. marinum in vitro (Supplementary Fig.  9C, D ).

One hallmark of TB is the formation of caseous necrotic granulomas 57 , which are organized aggregates of macrophages and other immune cells that serve as niches for the bacteria to obtain nutrients or evade anti-TB immunity, and to provide a source for mycobacteria for later reactivation and dissemination 58 , 59 . Respiration-inhibiting conditions, such as hypoxia, nitric oxide, low pH and nutrient starvation, are assumed to be characteristics of TB granulomatous lesions. Expression of the ald gene is upregulated under oxygen-limiting, nutrient starvation and nitrogen monoxide (NO) conditions 28 , 60 , 61 , 62 . The growth rate of M. marinum under hypoxia was not significantly affected by the treatment of GWP-042 (Supplementary Fig.  9D ). Moreover, adult zebrafish treated with GWP-042 had a much lower bacterial burden of wild-type and rifampicin resistant M. marinum at 14 days post-infection (Supplementary Fig.  9E, F ). These results suggest that targeting mycobacterial alanine dehydrogenase may inhibit the growth of pathogenic mycobacteria in granulomas.

In mice peritoneal macrophages infected with wild-type H37Rv, the addition of GWP-042 increased the production of Defb4 and Camp; but the increases were not observed upon infection with H37RvΔRv2780 strains (Fig.  6F and Supplementary Fig.  9G ). These results suggest that GWP-042 may increase the AMPs by targeting Rv2780. However, GWP-042 had no significant effect on cytokines expression or NO production in M. tuberculosis -infected macrophages (Supplementary Fig.  10A, B ). GWP-042 dramatically inhibited the intracellular survival of both M. tuberculosis H37Rv and a clinical MDR strain in infected macrophages (Supplementary Fig.  10C–F ). However, treatment with GWP-042 showed no significant effect on the in vitro growth curve of M. tuberculosis H37Rv or MDR M. tuberculosis (Supplementary Fig.  10G–J ), suggesting that GWP-042 may exert its anti-mycobacterial effect through targeting host anti-TB pathways. Moreover, the deletion of Rv2780 almost eliminated the inhibitory effect of GWP-042 on the growth of intracellular M. tuberculosis (Fig.  6G, H ), indicating that GWP-042 may exert its anti-mycobacterial activity through inhibiting Rv2780. Furthermore, GWP-042 showed no significant effect on the viability of cells even at very high concentrations, no matter with or without H37Rv infection (Supplementary Fig.  10K, L ). GWP-042 has no effect on the expression of cytochrome P450 (CYP450) homologs, Cyp1a2 , Cyp2b10 , Cyp2c38 , Cyp2d9 and Cyp3a11 , in murine hepatocytes (Supplementary Fig.  10M ), which suggests GWP-042 may not activate the CYP450 system. Together, these results suggest that targeting Rv2780 has potential as a host-directed candidate for the therapeutic treatment of TB, especially drug-resistant TB.

We further evaluated the pharmacokinetic properties of GWP-042. As shown in Supplementary Data  7 , the half-life of GWP-042 was 2.07 and 2.25 h when C57BL/6J mice were treated by intravenous injection (10 mg/kg) and intragastric administration (100 mg/kg), respectively. We also observed a high maximal concentration ( C max  = 7237 ng/mL for intravenous injection and C max  = 45425 ng/mL for intragastric administration) and a good bioavailability of 80.79% when GWP-042 was given orally. A clearance of 8.68 mL/min/kg suggests the metabolic stability of GWP-042 was good. An in vivo toxicity study of GWP-042 was performed in C57BL/6J mice (Supplementary Data  8 ). No mice died after receiving 50 or 200 mg/kg by intragastric administration. When the dosage was raised up to 1000 mg/kg, two of three mice died. No significant change in bodyweight was observed for C57BL/6J mice administrated with GWP-042 at 50 mg/kg once by oral gavage for 14 days (Supplementary Fig.  10N ), indicating that GWP-042 was nontoxic. Furthermore, when treated with GWP-042, the lung tissues of C57BL/6J mice infected with H37Rv had much lower bacteria burden and less inflammatory infiltration than those mice treated with rifampicin (Fig.  6I–K ), indicating that the killing effect of GWP-042 against M. tuberculosis alone is better than rifampicin. These results suggest that targeting mycobacterial alanine dehydrogenase may inhibit the growth of pathogenic mycobacteria in vivo. This is consistent with our conjecture that the mechanism of GWP-042 activity differs from that of traditional anti-TB drugs, which directly target M. tuberculosis itself; GWP-042 may resuscitate host immunity to eliminate M. tuberculosis .

Antimicrobial peptides are major components of host immunity, but previous studies have shown that they are very poorly induced in macrophages infected by M. tuberculosis 18 , 19 , 20 , 21 . Our findings identify the mycobacterial alanine dehydrogenase, Rv2780, as a previously unrecognized component of M. tuberculosis that suppresses the expression of AMPs. We found that PRSS1, a pancreatitis-associated factor 41 , 63 , inhibits NF-κB–mediated expression of AMPs by disrupting the formation of the TAK1-TAB1 complex. L-alanine directly interacted with PRSS1, which disabled the latter’s inhibitory effect on the TAK1/TAB1 complex formation, thereby triggering the NF-κB-mediated expression of AMPs. Nevertheless, M. tuberculosis secretes an alanine dehydrogenase Rv2780 that hydrolyzes L-alanine in host macrophages, thus suppressing the production of AMPs to facilitate the intracellular survival of mycobacteria. Thus, Rv2780 appears to be a virulence factor that allows M. tuberculosis to consume host metabolite L-alanine to evade host innate immunity. This mechanism depends on an ancient bactericidal mechanism, AMPs production, highlighting the versatility of host- M. tuberculosis interactions.

M. tuberculosis infection activates TLR2/NF-κB signaling pathway to induce the expression of AMPs 11 , but how the induction of AMPs is negatively regulated remains unexplored. We found that heterozygous deletion of PRSS1, a pancreatitis-associated factor 41 , 63 , markedly increases the expression of AMPs, indicating PRSS1 is a strong suppressor of AMPs expression. Moreover, our in vitro study showed that Prss1 +/− mice peritoneal macrophages infected with M. tuberculosis H37Rv had much lower intracellular CFU than those WT counterparts. Given that antimicrobial peptides (AMPs) directly target intracellular bacteria, Prss1 deficiency may mediate bacterial clearance in vitro mainly through regulating the expression of AMPs. In vivo study showed that significantly decreased lung bacterial burden and tissues damages were observed in Lyz2 cre Prss1 floxp/floxp mice infected with M. tuberculosis , suggesting that Prss1 may negatively regulate anti-TB immunity through downregulating the activation of NF-κB signal and not only AMP-related. Because higher NF-κB activation may not only induce AMPs expression, but also promote cytokines and chemokines expression in Prss1 deficient macrophages, which may subsequently activate other immune cells (including neutrophils or T cells) to maintain the in vivo anti-TB immunity. Therefore, we could not exclude the involvement of other NF-κB regulated genes, which needs further exploration.

Mechanistically, PRSS1 interacted with TAK1 and disrupted the formation of TAK1-TAB1 complex to inhibit TAK1-mediated activation of NF-κB pathway, thus suppressing the expression of AMPs. Besides, NF-κB plays a central role in host response to different infection of pathogens 64 , 65 , including gram-negative bacteria E. coli , gram-positive bacteria S. aureus and M. tuberculosis . Thus, the inhibitory effects of Prss1 on NF-κB activation were also observed during other bacterial infections. Considering multiple functions of AMPs 9 , 66 , 67 , 68 , inhibition of AMPs by PRSS1 may keep the expression of AMPs in a quiescent state to avoid unnecessary side-effects. To the best of our knowledge, our study is the first time to show PRSS1 is an immune molecule that negatively regulates the expression of AMPs and anti-TB immunity. However, whether and how the protease activity of PRSS1 is involved in its suppression of AMPs await further investigation.

Pro-inflammatory cytokines were upregulated by Rv2780 in macrophages or lung tissue of M. tuberculosis -infected mice in spite of Rv2780 mediated inhibition of NF-kB activation. Although the expression of pro-inflammatory cytokines is mainly regulated by NF-κB activation, there are many NF-κB-independent mechanisms regulating cytokines expression such as epigenetic regulation of microRNA 69 , 70 or histone modification 71 . Besides, transcription factor Nrf2 suppresses inflammation through redox control without affecting NF-κB activation 72 . Thus Rv2780 may elevate inflammation cytokines expression through other NF-κB-independent pathways, which needs further investigation.

Amino acid metabolism has been shown to regulate immune responses to M. tuberculosis infection 73 . L-arginine is essential for macrophages to generate NO through inducible nitric oxide synthase 74 . M. tuberculosis requires the tryptophan biosynthetic pathway for their survival 75 , but interferon-γ induces an isoform of the host enzyme, indoleamine 2,3-dioxygenase, that converts tryptophan to N-formylkynurenine, thus depleting tryptophan to exert an antimicrobial effect 76 . Alanine, an aliphatic neutral non-essential amino acid, is a critical structural component of mycobacterial cell wall peptidoglycan, and is utilized as a nitrogen source for the growth of M. tuberculosis 77 , 78 , but its role in the regulation of immune responses to M. tuberculosis infection remains unclear. Our results indicate L-alanine is a strong inducer of AMPs that relieve the inhibitory effect of PRSS1, a pancreatitis-associated factor 41 , 63 , by triggering NF-κB-mediated expression of AMPs. Furthermore, supplementation of alanine reduces the histopathologic damage and bacterial burden in the lung tissues of mice infected with M. tuberculosis H37Rv, indicating the therapeutic effectiveness of L-alanine in vivo. However, further study is needed to investigate whether alanine inhibits the protease activity of PRSS1 and confirm the anti-TB efficacy of L-alanine in nonhuman primates or humans.

M. tuberculosis infection reprograms host metabolism to exploit host metabolites for nutrients or to regulate host immunometabolism 73 , 79 , 80 , 81 , 82 , 83 . Ald was originally identified as one of the major antigens present in culture filtrates of M. tuberculosis 36 . It has a homohexameric quaternary structure with N-terminal catalytic and C-terminal NAD(H)-binding domains 26 , 27 , 35 and catalyzes the reversible conversion of L-alanine to pyruvate with concomitant reduction of NAD + to NADH. The expression of the mycobacterial ald gene was strongly upregulated by alanine, nutrient starvation, hypoxia or in granuloma 60 , 61 , 62 , 84 , 85 . Mycobacterium smegmatis ( M. smegmatis ) Ald is required for utilization of alanine as a nitrogen source 29 , and M. bovis BCG is unable to catabolize L-alanine due to a frameshift mutation in the ald gene 86 . In addition, Ald maintains the optimal NADH/NAD + ratio for mycobacterial survival under respiration-inhibitory conditions and for reactivation when oxygen is enough for the regrowth of mycobacteria 29 , 61 . Other studies also reported that treatment of M. smegmatis with bedaquiline, which inhibits the F 1 F o -ATP synthase by binding to c subunits, leading to the induction of ald expression 87 . We found that Rv2780, an M. tuberculosis Ald, dehydrogenates alanine inside infected macrophages to reduce alanine level and promotes the intracellular survival of M. tuberculosis , indicating that pathogenic mycobacteria may secret alanine dehydrogenase such as Rv2780 to suppress the expression of AMPs.

Several inhibitors of Ald have been developed 52 , 88 , 89 , 90 , 91 , and their potent anti-TB activity has been validated in vitro. We found that the Ald-targeting inhibitor, GWP-042, restored the production of AMPs and inhibited the growth of mycobacteria in vivo. Notably, GWP-042 also inhibited the growth of pathogenic mycobacteria in a zebrafish granuloma model. As natural antimicrobial agents, AMPs have clear advantages over conventional antibiotics, including rapid and broad-spectrum bactericidal activity and limited emergence of resistance 92 , 93 . Considering the rapid growth and global spread of drug-resistant mycobacteria, targeting a mycobacterial immune evasion factor to boost primitive antimicrobial immunity may provide a window for the development of effective immunomodulators against TB, especially drug-resistant TB (Supplementary Fig.  11 ). Desjardins et al. hypothesized that strains lacking functional Rv2780 are unable to convert L-alanine to pyruvate, thereby increasing the pool of available L-alanine in M. tuberculosis . As L-alanine is the precursor to the pathway competitively inhibited by D-cycloserine, abundant L-alanine may allow for continued peptidoglycan production despite competitive inhibition by D-cycloserine 94 . Thus, Rv2780 inhibitor GWP-042 could be applied for other drug-resistant M. tuberculosis infection, except for D-cycloserine-resistant strains. Furthermore, given that the expression of the ald gene is induced under respiration-inhibitory conditions in M. smegmatis and inactivation of the ald gene exacerbates the growth defect of M. smegmatis by respiration inhibition 29 , the combination of GWP-042 with respiration-inhibitory anti-TB drugs, such as Q203 95 and bedaquiline 87 , are likely to be a more efficient treatment against TB, especially latent TB, which currently lacks an efficient drug target. However, the anti-TB efficacy of the Ald-targeting inhibitor, GWP-042, in nonhuman primates or humans needs further investigation.

In summary, our findings propose an intriguing model for the regulation of AMPs expression by host and pathogen interaction: first, PRSS1 acts as a negative regulator to keep the expression of AMPs in a quiescent state to avoid unnecessary side effects; in response to mycobacteria infection, L-alanine is induced to disable PRSS1-mediated inhibition, thus triggering AMPs expression for the clearance of bacteria; however, pathogenic mycobacteria have evolved an alanine dehydrogenase that suppresses the host AMPs through dehydrogenating L-alanine. Considering AMP’s efficient and broad-spectrum bactericidal activity but limited emergence of resistance, targeting the mycobacterial virulence factor to boost the host AMPs may provide a window for the development of effective immunomodulators against TB, especially for drug-resistant TB.

Relevant ethical regulations

All protocols were approved by the local ethics committee of Shanghai Pulmonary Hospital (permit number: K23-333Z) or the local ethics committee of Tongji University (permit number: TJAA06522101). This study was conducted according to the Declaration of Helsinki principles and signed informed consent was obtained from all subjects. Specifically, the collection and use of samples from TB patients were approved by the local ethics committee of Shanghai Pulmonary Hospital (permit number: K23-333Z). The use of animal in our work was approved by the local ethics committee of Tongji University (permit number: TJAA06522101).

Bacterial culture and infections

Mycobacteria tuberculosis ( M. tuberculosis ) H37Rv strains (Supplementary Data  9 ) were grown in Middlebrook 7H9 broth (7H9, BD Biosciences) supplemented with 10% oleic acid-albumin-dextrose-catalase (OADC), 0.5% glycerol (Sigma-Aldrich) and 0.05% Tween-80 (Sigma-Aldrich), or on Middlebrook 7H10 agar (BD Biosciences) supplemented with 10% OADC.

H37RvΔRv2780 was constructed by Shanghai Gene-optimal Science & Technology Co., Ltd. according to previous publications 96 , 97 . In brief, screening gene cassette sacB-hygromycin B was inserted H37Rv genome replacing Rv2780 gene through recombinant phage with homologous gene by homologous recombination. H37RvΔRv2780 was confirmed by PCR and western blot. The shuttle vector pMV261 (provided by K. Mi, Institute of Microbiology, Beijing, China) was used to complement the strain H37RvΔRv2780 with wild-type Rv2780 (H37RvΔRv2780 + Rv2780) or to create the strain H37RvΔRv2780 + Rv2780 DM . Expression of Rv2780 or its mutants (with a C-terminal Flag-tag) in mycobacteria was examined by immunoblot analysis. For H37RvΔRv2780, 50 μg/ml hygromycin B was added to culture. For H37Rv (ΔRv2780 + Rv2780) or H37Rv (ΔRv2780 + Rv2780 DM ), 50 μg/ml hygromycin B and kanamycin were added to culture. E. coli DH5a/BL21 or S. aureus were grown in LB medium.

For macrophages infection, mice peritoneal macrophages or BMDMs were seeded in six-well plates (1 × 10 6 cells/well) and cultured for 24 h at 37 °C in a 5% CO 2 incubator. M. tuberculosis , E. coli DH5a/BL21 or S. aureus were added to cells at MOI = 2.

Cell culture

HEK293T cells (ATCC CRL-3216), A549 (ATCC CRM-CCL-185) and AML-12 cells (ATCC CRL-2254) were obtained from the American type culture collection (ATCC). The cells were cultured in Dulbecco’s modified Eagle’s medium (DMEM, HyClone) supplemented with 10% (v/v) heat-inactivated fetal bovine serum (FBS, Gibco) and 100 U/ml penicillin and streptomycin. The transient transfection of HEK293T was carried out using polyethylenimine (Polysciences) or Lipofectamine 2000 (Invitrogen). All the cells were routinely tested for mycoplasma contamination, and only those tested negative cells were used for experiments.

Mice peritoneal macrophages were harvested from mice that were injected 10% thioglycollate (BD Biosciences) for 3 days. The peritoneal macrophages were cultures in RPMI-1640 medium (HyClone) supplemented with or without 10% (v/v) FBS. BMDMs were obtained from isolated mouse bone marrow cells followed by incubation in 10% (v/v) FBS, 40 ng/ml M-CSF (Peprotech) and 20 ng/ml IL-4 (Peprotech) for 7 days. Mice alveolar macrophages were generated from single-cell suspensions of bronchial alveolar lavage fluid via macrophage adherence 98 , 99 . Mice bone marrow-derived neutrophils were isolated from mouse bone marrow cells via EasySep™ Mouse Neutrophil Enrichment Kit (Stemcell).

Plasmids, antibodies, and reagents

Plasmids are described in Supplementary Data  1 and Supplementary Data  7 . The polyclonal rabbit anti-Rv2780 antibody was produced and purified by ABclonal Biotech. The following antibodies were used in this study: rabbit anti-HA antibody (H6908/polyclonal, Sigma-Aldrich, 1:2000 for immunoblot analysis); rabbit anti-GAPDH antibody (SAB2701826/polyclonal, Sigma-Aldrich, 1:2000 for immunoblot analysis), rabbit anti-FLAG antibody (F7425, Sigma-Aldrich, 1:2000 for immunoblot analysis), Goat anti-Rabbit IgG (H + L) Secondary Antibody, Alexa Fluor 488 (A-11008, Invitrogen, 1:500 for immunofluorescence), anti-FLAG M2 Magnetic Beads (M8823, Sigma-Aldrich, for immunoprecipitation), rabbit Anti-PRSS1 antibody (ab200996/monoclonal, Abcam, 1:1000 for immunoblot analysis), rabbit anti-NF-κB p65 (C22B4) antibody (4764/monoclonal, Cell Signaling Technology, 1:1000 for immunoblot analysis), rabbit anti-TAK1 (D94D7)antibody(5206/monoclonal, Cell Signaling Technology, 1:1000 for immunoblot analysis, 1:50 for immunoprecipitation), rabbit anti-TAB1 antibody (A5749/polyclonal, Abclonal, 1:1000 for immunoblot analysis), rabbit anti-phospho-TAK1 (Thr187) antibody (4536/polyclonal, Cell Signaling Technology, 1:1000 for immunoblot analysis), rabbit anti-phospho-NF-κB p65 (Ser536) antibody(3033/monoclonal, Cell Signaling Technology, 1:1000 for immunoblot analysis), purified anti- E. coli RNA Sigma 70 antibody(663208, BioLegend, 1:1000 for immunoblot analysis of RpoD). GWP-042 was purchased from MedChemExpress (Cat.No.: HY-45854), the purity of the compound was 95.63% as detected by the company.

Immunofluorescence and confocal microscopy

Mice peritoneal macrophages were plated in Glass Bottom Culture Dishes (NEST, 801002) and infected with Mycobacterium tuberculosis H37Rv (MOI = 2) for 24 h. After infection, cells were stained with MitoTracker Deep Red FM (Invitrogen, M22426), LysoTracker Red DND-99 (Invitrogen, L7528) or ER-Tracker Red (Beyotime, C1041S) at 37 °C for 30 min in the dark. Cells were washed with precooled PBS for three times, 5 min each time, and were then fixed, permeabilized, and blocked at room temperature. Primary anti-Rv2780 antibodies (Abclonal, customized) were then applied at 4 °C overnight. After washing three times with PBS, culture dishes were incubated with Alexa Fluor 488-conjugated secondary antibodies for 1 h followed by staining with DAPI. For autophagic flux analysis, primary peritoneal macrophages were pre-treated with adenovirus expressing mCherry-GFP-LC3B fusion protein for 48 h before H37Rv or ΔRv2780 infection. Confocal images were taken with the Leica SP8 confocal microscope (Leica Microsystems) and analyzed by the Leica Application Suite Las X (v2.0.1.14392) software.

Mice and Infection

Prss1 +/- mice on C57BL/6J genetic background were purchased from the Cyagen Biosciences. Macrophage conditional knockout mice female 6-8 weeks old SPF C57BL/6J and SCID mice were purchased from Slaccas for peritoneal macrophages and BMDMs separation. Prss1 floxp/floxp mice and Lyz2 cre mice on C57BL/6J genetic background were purchased from Shanghai Model Organisms Center. Macrophage conditional Prss1 knockout mice were generated by breeding Prss1 floxp/floxp mice and Lyz2 cre mice.

All the mice infection experiments were performed with age- and sex-matched groups of 8–12-weeks old mice. Each mouse was aerosol infected with H37Rv, H37RvΔRv2780, H37Rv(ΔRv2780 + Rv2780) or H37Rv(ΔRv2780 + Rv2780 DM ) (100–200 CFUs) for 0, 14 and 28 days. The pathological sections were examined with hematoxylin and eosin (H&E) stain and bacteria load in lung section was analyze by acid-fast staining. The digital images were captured by 3Dhistech Pannoramic Scan system (3DHISTECH Ltd.) and processed by CaseViewer™ application. The histopathological scores were calculated by dividing inflammatory infiltrated area by total lung area. For CFU analysis, lung tissues were homogenized and plated on 7H10 agar plates for CFU counting. For L-alanine supplement mice infection experiments, C57BL/6 J mice drink double distilled water or 30 mg/ml L-alanine (Sangon Biotech) two days before infection and lasted until the end of the experiment. To rule out the effect of L-alanine on regulating adaptive immune cell responses, SICD mice, which are adaptive immune deficient, were used examine the functional role of L-alanine in regulating innate immunity in vivo by survival analysis of M. tuberculosis -infected mice. To validate the effectiveness of tuberculosis drug regimens, C57BL/6 J mice were treated with RIF (Rifampicin) (10 mg/kg/day), or combination of RIF (10 mg/kg/day) and Rv2780 inhibitor GWP-042 (MedChemExpress, 91%) (10 mg/kg/day) via oral gavage after three weeks of H37Rv aerosol infection. After 4 weeks of treatment, all mice were sacrificed for analysis of lung bacterial burden and histopathology. All animal experiments were reviewed and approved by the Animal Experiment Administration Committee of Shanghai Pulmonary Hospital.

Zebrafish and infection

According to the reported assay, 300 CFU of Td-Tomato labeled Mycobacterium marinum (Supplementary Data  7 ) were injected into caudal vein of zebrafish larva at 48 hpf (hours post fertilization). Zebrafish larva were transferred to drug-containing egg water since 2 days post infection. Overall bacterial burden of whole larvae can be quantified at 5 days post infection by fluorescence microscopy followed by fluorescence quantification of images via imageJ. Adult zebrafish (EzeRinka Biotech) were infected with 200 CFU of Td-Tomato labeled Mycobacterium marinum by intraperitoneal injection as previously reported 71 . Drug treatment(4 mg/kg) was conducted once a day via oral gavage after 7 days post infection. To access the bacterial burden, zebrafishes infected for 14 days were euthanized in Tricaine (Sigma), followed by plating whole body homogenate on 7H10 agar plates.

Intracellular CFU assay

MPMs were infected with H37Rv (MOI = 2) or other H37Rv strains. Cells were incubated for 3 h at 37 °C with 5% CO 2 . Subsequently, cells were washed three times with sterile PBS, and were then incubated in fresh RPMI medium. CFUs were enumerated at indicated time. For CFU enumeration in infected cells, supernatants were removed and cell pellets were lysed with sterile 1% Triton followed by gradient dilutions in PBS. Serial dilutions in PBS were plated on 7H10 agar plates with 10% OADC enrichment. Plates were then incubated at 37 °C and counted after 21 days. The relative intracellular CFU ratio was calculated through dividing CFU counts at the corresponding time by CFU counts at 3 h.

Quantitative metabolomic analysis

Sera from H37Rv-infected mice and age-matched control were processed at Biotree, Inc. (Shanghai, China) by a gas chromatograph coupled with a time-of-flight mass spectrometer (GC-TOF-MS, Agilent 7890) using a DB-5MS capillary column. Helium was used as the carrier gas, the front inlet purge flow was 3 mL/min, and the gas flow rate through the column was 1 mL/min. The initial temperature was kept at 50 °C for 1 min, then raised to 310 °C at a rate of 20 °C/min, then kept for 6 min at 310 °C. The injection, transfer line, and ion source temperatures were 280, 280 and 250 °C, respectively. The energy was −70 eV in electron impact mode. The mass spectrometry data were acquired in full-scan mode with the m/z range of 50–500 at a rate of 12.5 spectra per second after a solvent delay of 4.8 min. Raw data analysis, including peak extraction, baseline adjustment, deconvolution, alignment and integration, was finished with Chroma TOF (V 4.3×, LECO) software and LECO-Fiehn Rtx5 database was used for metabolite identification by matching the mass spectrum and retention index.

Carbon flux analysis with U 13 C glucose

MPMs were seeded on 90 mm Petri dishes (1 × 10 7 cells per dish) in RPMI 1640 medium. One hour before the infection, the culture medium was replaced by RPMI 1640 containing 5 mM U 13 C glucose without FBS followed by infection with indicated strains for 24 h. Cells were scraped in 80% methanol and phase separation was achieved by centrifugation at 4 °C and the methanol-water phase containing polar metabolites was separated and dried using a vacuum concentrator. The dried metabolite samples were derivatized for GC/MS analysis as follows: First, 70 μl of O-Isobutylhydroxylamine hydrochloride was added to the dried pellet and incubated for 20 min at 85 °C. After cooling, 30 µl of N-tert -butyldimethylsilyl- N -methyltrifluoroacetamide (MTBSTFA) was added and samples were re-incubated for 60 min at 85 °C before centrifugation for 15 min at 13,400 ×  g (4 °C). The supernatant was transferred to an autosampler vial for GC/MS analysis. Isotopologue distributions and metabolite levels were measured with a Shimadzu QP-2020 GC-MS system.

GC/MS data were analyzed to determine isotope labeling and quantities of metabolites. To determine 13 C labeling, the mass distribution for known fragments of metabolites was extracted from the appropriate chromatographic peak. These fragments contained either the whole carbon skeleton of the metabolite, or lacked the alpha carboxyl carbon, or (for some amino acids) contained only the backbone minus the side-chain 100 . For each fragment, the retrieved data comprised mass intensities for the lightest isotopomer (without any heavy isotopes, M0), and isotopomers with increasing unit mass (up to M6) relative to M0. M + 0 to M + n indicate the different mass isotopologues for a given metabolite with n carbons, where mass increases due to 13 C-labeling.

ELISA of antimicrobial peptides

ELISA analysis for protein level of Camp and Defb4 was conducted as previous reported 37 , 38 . Cell pellets of MPMs infected with H37Rv strains for indicated time were harvested and lysed in the lysis buffer lysed with RIPA Lysis Buffer (Beyotime). Cell lysates and supernatants were collected for ELISA analysis. According to the manufacturer’s instructions, Camp levels were measured by ELISA kit (Cusabio Biotech Co., Ltd.), while Defb4 levels were measured by ELISA kit (Fine Biotech Co., Ltd.).

Alanine detection assay

Alanine level of cellular and tissue samples was tested by Alanine Assay Kit (Sigma-Aldrich Co. LLC., MAK001). Cell pellets of MPMs infected with H37Rv strains were lysed in Alanine Assay Buffer and centrifuged at 4 °C for 10 min at 12,000  g , and the supernatants were used for alanine detection. Supernatants of lung homogenate and sera were diluted with Alanine Assay Buffer. According to the manufacturer’s instructions, all samples were collected and deproteinized before use in assay with a 10 kDa Molecular Weight Cut-Off spin filter (Sigma-Aldrich Co. LLC.). The filtrates were detected for analysis of alanine amount, while the unfiltered concentrates were detected by BCA protein assay for quantification protein level or immunoblotting analysis of GAPDH, an indicator that can reflect the number of cells. Then the normalization alanine level of macrophages was calculated as follows: Normalized alanine level = Alanine concentration/Gray value of GAPDH. The normalization alanine level of sera or lung homogenate was calculated as followings: Normalized alanine level = Alanine concentration / BCA protein concentration.

Virtual screening of Rv2780 inhibitors

For virtual screening of Rv2780 inhibitors, 2D structures of 309800 compounds from Hit Locator Library 300 and MCE Bioactive Compound Library and 3D structure of MtAlaDH (PDB ID: 2VHX) were submitted to Schrödinger’ Glid docking module level (HTVS, SP, XP) for molecular docking. The compounds were ranked according to their binding affinity to target protein Rv2780. Top 50 compounds were selected for subsequent functional screening. Figures of molecular docking structures were generated using PyMOL (The PyMOL Molecular Graphics System, Schrödinger, LLC).

Pharmacokinetics of GWP-042

Male SPF ICR mice were treated with a solution of GWP-042(DMSO/Solutol/Saline, 5/10/85, v/v/v/v) at a single dose of 10 mg/kg or a solution of GWP-042 dissolved in 0.5% CMC-Na at a single dose of 100 mg/kg via intravenous injection (iv) or oral administration(op), respectively. Blood samples were collected at 0.5, 1, 2, 4, 6, 8, 12, 24 h after administration. Plasma was separated and the concentration of compounds in plasma was calculated by LC-MS/MS analysis.

Intracellular ROS production assays

Mice peritoneal macrophages were infected with H37Rv or as indicated and incubated with fresh medium added containing 10 μM DCFH-DA (Sigma-Aldrich) at 37 °C for 30 min. The cells were then washed with PBS 3 times and lysed with lysis buffer (50% methanol containing 0.1 M NaOH). After gently stripping the cells from the plate and spinning at 2671 × g for 5 min, the supernatants were transferred and fluorescence at 488/525 nm was detected using a Synergy H1 multi-mode reader (Biotek). All the data were normalized with protein concentration.

Mice peritoneal macrophages were seeded in 96-well plates. L-alanine and GWP-042 were added into the medium and plates were incubated for 24 h followed by MTT assays. For analysis during M. tuberculosis infection, MPMs treated with L-alanine or GWP-042 followed by infection with indicated strains for 0, 3, 6, 9, 12, 24 h. Cells were washed once with PBS and incubated in MTT Solvent containing 5 mg/mL MTT (3-(4,5-dimethylthiazol-2-yl) - 2,5-diphenyltetrazolium bromide) (Beyotime). Following 4 h incubation at 37 °C, cells were added with Formazan Solvent and mixed gently and continue incubation until Formazan is completely dissolved. Absorbance was measured at 570 nm using a TECAN microplate reader.

In vivo toxicity of GWP-042

Female 8 weeks C57BL/6 J mice were administrated with GWP-042 dissolved in 0.5% CMC-Na at a single dose of 50 mg/kg, 200 mg/kg and 1000 mg/kg respectively by oral gavage for acute toxicity study. The mice were observed for mortality and toxic signs for 14 days.

Western blot analysis and immunoprecipitation

For immunoblot analysis, cells were lysed in the 1 × loading buffer (50 mM Tris-HCl(pH6.8), 2% SDS, 10%glycerol, 1% β- mercaptoethanol, 0.1% Bromophenol BLUE). After boiled for 10 min denaturation, Proteins were separated by SDS-PAGE and transferred to nitrocellulose filter membrane (Whatman), The membranes were blocked with 5% BSA in TBST buffer (0.1% Tris, 0.1% Tween-20) for 1 h at room temperature and subsequently incubated with primary antibodies overnight at 4 °C. The membranes were washed three times with TBST before incubation with secondary antibody for 1 h at room temperature. After another three washes, analysis was performed using chemiluminescence reagent (Thermo Scientific).

For immunoprecipitation (IP), cells were lysed in Western blot and IP cell lysate buffer (20 mM Tris(pH7.5), 150 mM NaCl, 1% Triton X-100) supplemented with protease inhibitor cocktail (MedChemExpress). After centrifugation, supernatants were incubated with anti-FLAG M2 Magnetic Beads (Sigma-Aldrich) overnight at 4 °C. The samples were washed three times with PBST (KH 2 PO 4 2 mM, Na 2 HPO 4 8 mM, NaCl 136 mM, KCL 2.6 mM, 1% Triton X-100) and subjected to Western blot analysis. For biotin pull down assay, PRSS1 recombinant protein or cell lysates of HEK293T cells overexpressed with Flag-PRSS1 were incubated with biotinylated alanine or biotinylated serine for 2 h followed by incubation with Streptavidin Magnetic Beads (MedChemExpress) overnight at 4 °C. For competition assay, PRSS1 recombinant proteins were incubated with increasing concentrations of non-biotinylated alanine before incubation with biotinylated amino acids.

Identification of H37Rv knockout and complementary strains

Various H37Rv strains were cultured to log phase culture and centrifugated at 12,000  g for 10 min. For immunoblotting, bacterial pellets were washed three times with PBS buffer, and denatured at 95 °C with 1×SDS loading buffer (Tris-HCl pH 8.0 10 mM, DTT 50 mM, SDS 1%, Glycerol 10%, Bromophenol Blue 0.008%) for 10 min. Culture supernatants were mixed with adequately with an organic solvent (supernatant: methyl alcohol: chloroform = 4:4:1, v/v/v) followed by centrifugation at 4 °C for 10 min at 12,000  g to isolate crude protein extract. Insoluble substances were denatured at 95 °C with 1×SDS loading buffer and subjected to Western blot analysis. Anti-RpoD antibody (BioLegend, 663208) was used as control.

RT-PCR analysis

Transfected HEK293T cells or M. tuberculosis infected macrophages in 12-well plates were lysed by 1 ml TRIzol reagent (Invitrogen). Total RNA is precipitated from with chloroform and isopropanol according to the manufacturer’s instructions. The first-strand complementary DNA (cDNA) was synthesized using the ReverTra Ace-α-First-Strand cDNA Synthesis Kit (Toyobo Biologics) according to the manufacturer’s instructions. Lastly, qPCR analyses were performed with SYBR Grreen realtime PCR Master Mix (TOYOBO) on ABI 7300 system (Applied Biosystems) using gene-specific primers (Supplementary Data  7 ).

Luciferase assay

HEK293T cells were transiently transfected with pNF-κB–luc, pRL–TK plasmids and the indicated plasmids for 24 h. The Dual-Luciferase reporter assay system (Promega, Madison, USA) was used for the detection of luciferase activity.

In vitro Rv2780 enzyme assay

The reaction buffer was 125 mM glycine/KOH (pH 10.2), increasing concentration of L-alanine (0, 10, 100 mM), 1.25 mM NAD + and 6.026 pM of Rv2780 protein in a final volume of 200 μL. The reactions were carried out in 96-well plate at 37 °C. Inhibitors at indicated concentrated were incubated with Rv2780 protein before the reaction. The reaction was measured by the production of NADH via NAD + /NADH Assay Kit with WST-8 (Beyotime). For direct detection of enzymatic product pyruvate, the reaction mixture was deproteinized with a 10 kDa MWCO spin filter (Sigma-Aldrich Co. LLC.) before quantification of pyruvate level with Pyruvate Assay Kit (Abcam, ab65342).

Clinical samples

All the TB patients providing blood samples were from Shanghai Pulmonary Hospital between 2020 and 2021. They were diagnosed based on chest X-rays, acid-fast bacillus staining of biofluids samples, culture on Lowenstein–Jensen media and were corroborated with clinical symptoms. Patients were given informed consent. The ethics committee of Shanghai Pulmonary Hospital approved this consent procedure (permit number: K23-333Z). X-ray scores were calculated according to previously reported 101 . Lungs were divided into six zones (low, middle, and high zones for each left and right lung). The score was based on the percentage of lung parenchyma that showed evidence of each recorded abnormality: (l) involvement of less than 25% of the image; (2) 25% to 50%; (3) 50% to 75%; (4) more than75%. A profusion score (l to 4) was given and the scores of each zone were then summed to obtain a global profusion score for chest CT. Total weighted X-ray score is equal to score × 100/24 (total score) + 40 (if cavitation is present).

Microscale thermophoresis

Purified human recombinant protein PRSS1 were labeled by Monolith NT Protein labeling kit RED—NHS (Nano Temper Technologies, Germany) according to the manufacturer’s protocol. 10 μl of 40 nM labeled proteins were incubated with 10 μl of increasing concentrations of L-alanine (250–0.007 μM) in Assay Buffer (50 mM HEPES, pH7.5, 500 mM NaCl, 5% Glycerol, 1 mM TCEP). Then, samples were loaded into standard glass capillaries (Monolith NT Capillaries, Nano Temper Technologies) and the MST analysis was performed on a NanoTemper Monolith NT.115 apparatus (Nano Temper Technologies, Germany).

Surface plasmon resonance (SPR)

The interaction of GWP-042 with Rv2780 was detected by OpenSPRTM (Nicoya Lifesciences, Waterloo, Canada). Briefly, Rv2780 protein was fixed on the COOH sensor chip by capture‐coupling, then GWP-042 at indicated concentrations was injected sequentially into the chamber in PBS at 25 °C. The binding time was 240 s and the disassociation time was 360 s with the flow rate of 20 μl/min. The chip was regenerated with 10 mM Glycine-HCl with a flow rate of 150 μl/min. A one‐to‐one diffusion corrected model was fitted to the wavelength shifts corresponding to the varied glycan concentration. The kinetic constants, including the association constant ( k a ), dissociation constant ( k d ), and affinity (KD, KD = kd/ka), were analyzed with TraceDrawer software (Ridgeview Instruments AB, Sweden).

Statistical analysis

Statistical significance between groups was determined by two-tailed Student’s t -test, two-tailed analysis of variance followed by Bonferroni post hoc test, Log-rank test or two-sided Mann-Whitney U -test. Differences were significant at P  < 0.05. The experiments were not randomized, and the investigators were not blinded to allocation during experiments and outcome assessment.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

Source data are provided in this paper. M. tuberculosis secreted protein screening, metabolite profiling, carbon metabolic flux, mass spectrometry, preliminary pharmacokinetic evaluation and in vivo toxicity data in this study are available in Supplementary Data file. Further information and requests for resources or reagents should be directed to and will be fulfilled by Lin Wang ([email protected]) or Baoxue Ge ([email protected]).  Source data are provided with this paper.

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Acknowledgements

We thank Prof. K. Mi (CAS Key Laboratory of Pathogenic Microbiology and Immunology) for the pMV261 plasmid and members of B. Ge’s laboratory (Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China) for helpful discussions and technical assistance. This project was supported by the National Key R&D Program of China (2023YFC2307300 and 2022YFC2302900 to L.W.; 2021YFA1300902 to R.Z.; 2017YFA0505900 to B.G.); National Natural Science Foundation of China (32188101, 32030038, 91842303, and 3170025 to B.G.; 82122029 and 82071776 to L.W.; 82100007 to P.W.); The Most Important Clinical Discipline in Shanghai (2017ZZ02003); Shanghai Rising-Star Program (20QA1408400 to L.W.); and the Shanghai “Chen Guang” project (19CG22 to L.W.). The fellowship of China National Postdoctoral Program for Innovative Talents (BX2021215 to Y.D.).

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These authors contributed equally: Cheng Peng, Yuanna Cheng, Mingtong Ma.

Authors and Affiliations

Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

Cheng Peng, Yuanna Cheng, Mingtong Ma, Qiu Chen, Yongjia Duan, Shanshan Liu, Hongyu Cheng, Hua Yang, Jingping Huang, Wenyi Bu, Chenyue Shi, Xiangyang Wu, Jianxia Chen, Ruijuan Zheng, Zhonghua Liu, Jie Wang, Xiaochen Huang, Baoxue Ge & Lin Wang

Department of Microbiology and Immunology, Tongji University School of Medicine, Shanghai, China

Cheng Peng, Yuanna Cheng, Mingtong Ma, Qiu Chen, Yongjia Duan, Shanshan Liu, Hongyu Cheng, Jingping Huang, Wenyi Bu, Chenyue Shi, Zhe Ji, Baoxue Ge & Lin Wang

Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

Hua Yang, Jianxia Chen, Ruijuan Zheng, Zhonghua Liu, Jie Wang, Xiaochen Huang, Peng Wang, Wei Sha, Baoxue Ge & Lin Wang

Clinical Translation Research Center, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

Xiangyang Wu, Jianxia Chen & Baoxue Ge

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Conceptualization: B.X.G., L.W. Methodology: C.P., Y.N.C., M.T.M., Q.C., Y.J.D., H.Y., Z.H.L.,. R.J.Z., J.X.C., J.W., X.C.H. Investigation: C.P., L.W., Y.N.C., M.T.M., Q.C., H.Y. Animal infection experiments: C.P., L.W., Y.N.C., M.T.M., H.Y., Y.J.D., S.S.L., H.Y.C., X.Y.W., Z.J.; Macrophages isolation, infection and Q-PCR.: C.P., J.P.H., W.Y.B., C.Y.S.; Western blot and confocal imaging: C.P., L.W., Y.N.C., Q.C.; Strains construction and preservation: J.W. and X.C.H.; Clinical samples and analysis: P.W. and W.S.; Writing: B.X.G., L.W., C.P.

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• Published: 15 May 2019

Knowledge, attitude and preventive practice towards tuberculosis among clients visiting public health facilities

• Ayele Semachew Kasa   ORCID: orcid.org/0000-0003-3320-8329 1   na1 ,
• Alebachew Minibel 1   na1 &
• Getasew Mulat Bantie 2   na1  

BMC Research Notes volume  12 , Article number:  276 ( 2019 ) Cite this article

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Metrics details

The aim of the study was to assess knowledge, attitude and preventive practice towards tuberculosis.

More than half of the study participants stated that bacteria are responsible agents in causing tuberculosis and as the same time 12.2% study participants thought that tuberculosis is not preventable disease. Overall, 54% of study participants had good knowledge, 68% had good attitude but only 48% had good practice in preventing tuberculosis. Compared to many national and international studies, knowledge, attitude and preventive practice towards tuberculosis was not satisfactory. Strengthening of awareness creation and health education program towards tuberculosis is needed.

Introduction

Globally, 9.7 million people get sick with tuberculosis (TB) and 1.7 million people die from it, each year [ 1 ]. TB continues to be a major public health problem across the world, including Ethiopia. It causes ill-health among millions of people each year and ranks as the second leading cause of death from an infectious disease [ 2 ].

In 2006, 1.7 million deaths resulted from TB: the majority situated in sub-Sahara Africa [ 3 ]. Even though the incidence of TB has decreased worldwide, an estimated 10.4 million people developed TB in the year 2015 of which one-quarter was from Africa [ 4 ].

In every second; around the globe a person is infected with TB and every 10 s someone dies as a consequence of the disease [ 5 ].The 2018 Global TB report showed that Ethiopia is included in the 30 high TB burden countries [ 6 ] and in Ethiopia the case detection of the disease was 62 (51–74%) for all forms of TB [ 7 , 8 ].

Raising communities’ awareness contributes for early diagnosis of TB which is one of the pillars of the End TB Strategy [ 4 ]. Studies documented a positive association between TB knowledge, care seeking and treatment adherence [ 9 , 10 ]. To address such issues, the level of knowledge should be known to design an appropriate interventional programmes [ 11 ] in a specific regions.

The finding from various studies indicate that patient delay may be influenced by several factors, namely lack of knowledge, lack of awareness of the significance of symptoms, negative social attitudes or combinations of these [ 12 ].

Though few studies were conducted on knowledge, attitude and preventive practice (KAP) towards tuberculosis in Ethiopia, no study has been done about KAP towards tuberculosis among Mecha District communities. Therefore, this study was designed to investigate KAP of Mecha District communities towards tuberculosis.

Study design

A cross-sectional descriptive study was conducted on North Mecha district residents who visited the adult outpatient departments (OPD) of public health facilities for various medical, maternity and family planning services from April 901 to May 30/2018. The district has 290,546 total population which is located in West Gojjam Zone which is part of Amhara Region, Ethiopia. The district is situated at 530 km North West of Addis Ababa, capital city of Ethiopia. Merawi is the administrative city of the district [ 13 ]. In this district there are a total of 10 health centers and one primary Hospital with 96% TB cure rate, 97% TB success rate, and 85% Bacillus Calmette–Guérin (BCG) vaccination coverage. The Catchment area had a total population of 14,034 in the selected health institutions [ 14 ].

Sample size determination and sampling procedure

Sample size was calculated using; 95% confidence interval (CI), 5% margin of error (d), P as 45.9% taken from a study done in Gambella Region, Ethiopia [ 18 ]. Based on the above assumptions and by adding 10% non-response rate to the initial sample size, the sample size was 420.

From the total 11 health facilities (HFs) found in North Mecha district, 4 HFs (Wotet Abay Health center, Abyot Fana Health Center, Felege Birehan Health Center and Merawi Primary Hospital) were selected using simple random sampling method. Then based on the client flow, the total sample size was proportionally allocated to each selected HFs. Finally clients visiting each of the selected health facilities in the data collection period were selected using systematic random sampling technique.

The data collection questionnaire was developed after reviewing different relevant literatures. The questionnaire, first developed in English language and then translated to Amharic (local language). The questionnaire had four different parts. Part-I: comprising of socio-demographic questions, Part-II: comprising of twelve different knowledge assessing questions, Part-III: comprising of seven different attitude assessing questions and Part-IV: comprising of seven questions assessing the preventive practice towards TB.

Pretest was done on 5% of the total sample size at Meshenti Health Center. After the pretest, necessary modifications and correction took place to ensure validity. Four data collectors and one supervisor were recruited and trained for 1 day to collect and supervise the data respectively.

Data processing and analysis

Those respondents who scored greater than or equal to the mean value of knowledge questions were regarded as having good knowledge. Respondents who scored greater than or equal to the mean value of attitude assessing questions were regarded as having favorable attitude. The respondents’ score greater than or equal to the mean value of preventive practice assessing questions were regarded as a participant having good practice.

The data were checked and cleaned, coded using non-overlapping numerical codes. Computer data files were thoroughly checked for errors, implausible values and inconsistencies that might be due to coding, entry, typing and other errors. Then, it was exported to SPSS version 20 for analysis. Descriptive statistics, like percentage, mean and standard deviation was used for the presentation. Then the data were presented by using sentences, graphs, tables, frequencies, percentages.

Out of the total 420 sample size, 403 individuals participated in the study making the response rate 95.9%. Of which, 53.3% respondents were females. All the respondents’ fall in the age range between 12 and 82 years old, with 35 years being the mean age. Majority of respondents were Orthodox Christian religion followers and ethnically almost all (97.8%) were from Amhara ethnicity. The minimum monthly income of the study participants was no income to 25, 141 Ethiopian Birr (ETB) the maximum monthly income and 1, 124 ETB was the average monthly income (Table  1 ).

From the total 403 study participants, 354 (87.8%) heard about tuberculosis. From these, majority (56.8%) of them received the information from health workers and followed by 26.8% from different Medias.

Knowledge towards TB

From those study participants who had information about TB, 74% mentioned that droplet inhalation as the main mode of transmission of the disease whereas 2% replied that heredity as the mode of transmission of the disease. Regarding sign and symptoms of TB, 39.4% mentioned that cough for greater than or equal 2 weeks is the clinical manifestation of a client with TB. Forty-nine (12.2%) study participants thought that TB is not preventable disease. More than half (56%) of the study participants stated that bacteria is the responsible agent in causing TB.

Attitude towards TB

Regarding to communities attitude towards tuberculosis, 40.7% of study participants stated that TB is dangerous and serious for the community. Majority of study participants (46.2%) stated that TB is cannot transmitted from human to human. Almost one-fifth (19.3%) of study participants stated that discriminating TB patient is necessary.

Practice towards in the prevention of TB

Three hundred sixty-five (90.6%) of study participants’ house had window but only 60% of them open the window regularly. Almost one-fifth (19.4%) of study participants ever screened for TB. Two-third of the study participants ever received health education about TB. From all study participants, two-third stated that they will cover their mouth during coughing if they had TB as a measure to prevent further spread of the disease (Table  2 ).

Overall KAP level

Two hundred eighteen (54%) of study participants had good knowledge towards TB and 193 (48%) of participants had good preventive practice in preventing TB (Fig.  1 ).

Study participants overall KAP level towards tuberculosis, Mecha District, Northwest Ethiopia, 2018

This study offers information on the knowledge, self-reported attitudes and practices towards TB. This finding entails that there is a significant gaps in preventive practice towards TB infection control.

It is a well-known fact that knowledge can influence people’s practices regarding prevention [ 15 ]. The current study revealed that the overall knowledge about TB was 54% which was lower than a study done in Iran [ 16 ] in which 62% of participants had good knowledge about TB. Whereas the current finding was better than a study done in Thailand in which 74.2% respondents had low level of knowledge about TB [ 17 ].

In the current study, 87.8% heard about tuberculosis which was lower from other studies conducted in different settings. Study done in Shinile town revealed that 94.9% heard about TB [ 18 ]. Another study done in middle and lower Awash valley of Afar region, Ethiopia [ 19 ] showed that, 92.8% and 95.6% of the study participants were aware of the disease, respectively. A study done in Libya [ 20 ], Sabah [ 12 ] and Iraq [ 21 ] also showed that 95%, 96% and 91% of the respondents heard about TB respectively. The discrepancies might be explained; study participants in the current study were from the rural communities whereas other studies were included communities from town/urban sites in which information access towards TB will be gain from health workers and Medias. But in the current study, majority of them responded the sign and symptoms of TB in a good way which was consistent with studies done in southwest Ethiopia [ 22 ], northeast Ethiopia [ 19 ], Iran [ 23 ] and Philippines [ 24 ].

The current study showed that the overall attitude towards TB was 68% which is better than a study conducted in Thailand [ 17 ] showed that 47.9% of study participants were categorized as they had high level of attitude.

The current finding indicated that the overall preventive practice towards TB was 48%. The finding was better than a study done in Iran [ 16 ] in which the overall preventive practices towards TB was 42.6%. Whereas a study done in Thailand [ 17 ] showed that 55.5% of study participants had high level of preventive behavior. The discrepancy might be due to that, those study participants from different countries may have differences in health education program design, health literacy, and access to health workers and Medias.

Regarding the screening practice for TB in the current study, 19.4% of study participants ever screened for TB which is consistent with a study conducted in Thailand [ 25 ] in which 18.6% of participants stated that they had undergone a TB screening test.

In regard to preventive measures, 66.5% of participants had practice of covering their mouth during coughing which is better than a nationwide study done in Mongolia [ 1 ] 42.9% of participants pointed covering their mouth and nose when coughing and sneezing. This difference might be the study done in Mongolia is a nationwide study in which more rural residents had a chance to be included and this may raise the chance of getting study participants with limited access to health information and practice.

Concerning the consultation practice, 86.1% of study participants in the current study stated that they would find a health worker if they got TB. This is lower than a study done in Sabah [ 12 ] in which 98% of respondents said that they would consult a doctor immediately.

Compared to many national and international studies, the knowledge, attitude and preventive practice towards TB was not satisfactory. The finding from this research showed that majority of participants received information about the disease but their practical knowledge, attitude and practice was not as such comparative with the information they received. This urges the healthcare providers and other concerned bodies to design strategies to provide a better awareness creation towards the disease.

Recommendation

Based on the gaps identified, this research forwards some recommendation to the concerned body.

Mecha District Health office: to strengthen the awareness creation and health education program towards TB in each healthcare facilities.

Other responsible stakeholders and NGOs: to launch awareness creation session about the impact of poor TB Practice for their health and the community.

Limitations

The study was done on patients rather than community members using cross sectional study design in a single district. Study participants were not given the chance to respond for qualitative type questions so that we might not include their deep insight about their attitude and practices.

The study addresses only clients who came to health facilities.

Availability of data and materials

Not applicable.

Abbreviations

Bacillus Calmette–Guérin

drug resistant tuberculosis

Ethiopian Birr

health facilities

human immune virus

knowledge, attitude and practice

multidrug resistant tuberculosis

outpatient department

tuberculosis

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We are very grateful to all study participants for their commitment in responding to our questionnaires.

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ASK: conceived the proposal, participated in data collection analyzed the data and drafted the paper. AM and GMB: approved the proposal with some revisions, participated in data analysis. All authors read and approved the final manuscript.

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Kasa, A.S., Minibel, A. & Bantie, G.M. Knowledge, attitude and preventive practice towards tuberculosis among clients visiting public health facilities. BMC Res Notes 12 , 276 (2019). https://doi.org/10.1186/s13104-019-4292-2

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A questionnaire of knowledge, attitude and practices on tuberculosis among medical interns in Nepal

Anna berg-johnsen.

a Department of Public Health and Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, NO 7489 Trondheim, Norway

Synne Osaland Hådem

Dipesh tamrakar.

c Department of Community Program, Dhulikhel Hospital, Kathmandu University Hospital, Dhulikhel, Kavre, Nepal

Ingunn Harstad

b Department of Pulmonary Medicine, St Olavs University Hospital, PO Box 3250 Sluppen, N-7006 Trondheim, Norway

Tuberculosis (TB) remains a major health problem worldwide, including in Nepal where around 33,000 new cases of TB were diagnosed in 2018 and 5400 patients died. There are challenges in the diagnostic process, treatment, and follow-up. Deaths, increased transmission and development of multi- drug resistant TB could be the consequences. Young doctors play an important role in this struggle, and therefore, their knowledge of and attitudes towards TB are crucial.

We surveyed medical interns in Nepal regarding their knowledge, attitude and practices on TB and their adherence to the National Tuberculosis Programmes’ guidelines. The objective was to determine the associations between TB knowledge, and attitude and the factors that influence them.

A WHO cross-sectional questionnaire template was modified and piloted. It was distributed anonymously among medical interns at three private medical colleges. Statistical analyses were performed to establish possible associations between TB knowledge and attitude, and the investigated variables, and to investigate differences between the medical colleges.

Of 270 interns, 185 (69%) interns were included. The mean knowledge score was 13,3 (SD: 2,12) of a maximum of 19. The possible attitude scores ranged from zero to 14 points, whereas the mean attitudes score was 9,4 (SD: 1,89). Some unacceptable attitudes and knowledge gaps were identified, including disease detection and management. There was an association between the knowledge score and attitude score and between the number of TB patients seen and knowledge/attitude.

The surveyed interns had an adequate level of TB related knowledge, and acceptable attitudes. However, some unacceptable knowledge gaps and attitudes were detected. This survey underlines the considerable need of closing these knowledge gaps, and improving the attitudes, for which it is important for medical students to practice at a TB clinic and see a certain number of TB patients.

1. Introduction

Tuberculosis (TB) is still a major global health problem as the global incidence in 2018 was estimated to be 10.0 millions, and the mortality 1.2 millions [1] . The World Health Organization (WHO) and the United Nations’ Millennium Development Goals (MDG) [3] together with the Stop TB Strategy [4] have developed strategies for eliminating TB, which have led to a decline in absolute number of TB-deaths and TB incidence rate since year 2000.

Nepal is one of the member states that have committed to these strategies and have made progress regarding TB throughout the last decades. The National Tuberculosis Programme, (NTP) has been the responsible agency, and, in 1996, the directly-observed treatment short-course (DOTS) strategy, a 5-component strategy for TB management and control, was initiated in Nepal. Subsequently, the Stop TB Strategy, The WHO‘s strategy to curb TB by 2015, and the END TB Strategy were both adopted [5] .

In 2018, 33.474.000 new cases were notified in Nepal, and an estimated 5.400 died from TB the same year [1] , [6] . However, that figure likely underestimated the actual number of 8.000–10.000 cases, that were either not detected or not reported [6] . About 2.2% of new TB cases and 15.4% of retreatment cases have Multi Drug Resistant (MDR)-TB, with around 400 such cases reported each year. However, the real numbers could be higher as drug susceptibility testing is done only in a minority of TB cases. Health service delivery in Nepal is provided by both the private and public sectors. The NTP has faced challenges in providing free TB care and integrating the TB Control Programme into the private sector [7] .

As TB is a leading cause of disability adjusted life years (DALYs), acknowledging, managing and investing in the disease will result in substantial economic and health returns [8] . WHO emphasizes that “the medical school should provide every graduate with the knowledge, skills and attitudes essential to the management of tuberculosis in the patient and in the community as a whole” [9] . Studies from several countries have assessed the knowledge, attitude and/or practices on TB among medical students and young doctors. Several of those studies indicate a lack of knowledge about TB among interns and inadequate management of the disease by them [10] , [11] , [12] , [13] , [14] . However, a study comparing students from Canada, India, and Uganda found that TB-related knowledge and practices were adequate [15] . The results were related to the number of TB patients seen and curriculum hours on TB. Another study from Italy also found a relationship between knowledge and the number of TB patients seen as well as a strong link between knowledge and memory of a previously taken Mantoux test [16] .In this study, the knowledge was described as moderate. There have been no similar studies from Nepal.

The present study aimed to investigate interns knowledge, attitude and practices (KAP) on TB, as well as their adherence to the NTP guidelines. The purpose was to identify the associations between their knowledge and attitude and factors that influence them. This information can help make pre-and postgraduate medical teaching and training better suited to the needs of the population and the TB control programme. This is necessary to meet the future requirements for well-educated medical doctors with a good attitude towards TB patients.

This quantitative cross-sectional study was conducted via a self-administered, anonymous questionnaire. The questionnaire was a modified version of the WHO’s Knowledge Attitude Practice (KAP)-template assessing sociodemographic data and knowledge, attitude and practices on tuberculosis [17] . The questionnaire was piloted among 10 randomly selected young doctors in Nepal before the study could be conducted.

2.1. Study site and study population

Nepal has 19 medical colleges, and Kathmandu University (KU), a private university, has nine affiliated medical colleges. The Norwegian University of Science and Technology (NTNU) has a collaboration with the School of Medical Sciences (KUSMS) Dhulikhel at KU [18] . All KU-affiliated medical colleges were invited by a contact person at KUSMS to participate in the survey. Three colleges accepted the invitation: Nepal Medical College (NMC) in Kathmandu, Dhulikhel (KUSMS), and Bharatpur College of Medical Sciences (CMS) outside of the Kathmandu valley. The participants were medical interns who had completed their bachelor of medicine, bachelor of surgery (MBBS) degree . Participants were over 21 years old, and included both men and women.

Data collection took place in Nepal from 3 September 2017 to 17 October 2017. The interns who were available at their college at the time of the study; one day at CMS, and several days at KUSMS and NMC, answered a self-administered questionnaire on paper, which was handed out by a third party responsible for the interns at the respective colleges. The answers from the questionnaire were not scanned, but manually entered into SPSS Statistics Version 24 with every answer given a code during the entry. Data validity was ensured through double entry and crosschecking of data and random checks before analysis.

2.2. Analysis

SPSS Statistics Version 24 and Version 25 were used for the analyses.

Some of the questions allowed multiple responses (“check all that apply”), while other questions requiring only one answer. Some of the interns gave more than one answer to questions only requiring one answer. Those replies were excluded from the analysis.

The knowledge score was calculated based on 18 questions regarding TB knowledge. Correct answers were determined based on the annual report from the NTP in Nepal [6] . All questions with only one correct answer were each given 1point and questions allowing more than one answer were given 1–2 points. The maximum possible knowledge score was 19.

The attitude score to measure good or poor attitude towards TB was calculated based on attitude related questions. The maximum possible attitude score was 14 points. The answers indication a good attitude were given 2 points, while the answers showing poor attitude got zero points. Neutral and missing answers got 1 point. Question 32 regarding attitude allowed multiple responses. The choices were “fear”, “surprise”, “shame”, “sadness/hopelessness”, and “I don’t know”, with each choice getting 1 point. Thus, maximum score on this question was 4, while the other questions regarding attitude had a maximum score of 2 each.

To analyse the factors associated with the TB knowledge score and factors associated with the attitude score, regression analysis with one-way ANOVA was performed. To check correlation between knowledge and attitude two-tailed T-test using Pearson Correlation was used. Significance was considered at a p-value < 0.05.

2.3. Ethical considerations

The interns were given an information sheet and gave informed consent by participating in the study. The data was collected anonymously, and only unidentifiable sociodemographic data was collected.

A verbal request to the Regional Committees for Medical and Health Research Ethics Norway clarified that ethical approval in Norway was not needed as no patient information was gathered in the study.

In Nepal ethical approval was received from the KUSMS Institutional Review Committee (KUSMS/IRC) (84/17), and from the Research Director at NMC (IRC-NMC), while CMS accepted the KUSMS/IRC.

3.1. Study population and characteristics

Three medical schools with a total of 270 interns accepted the invitation, with 185 (69%) interns, including 81 females (44%), participating in the study ( Table1 ). The age of the participants ranged between 21 and 30 years, and 126 (68%) were below 25 years of age.

Demographic characteristics of study population by medical colleges, gender and age.

KUSMS: Kathmandu University School of Medical Sciences, CMS: College of Medical Sciences, NMC: Nepal Medical College.

One out of five interns had taken a tuberculin skin test (TST) less than five years ago ( Table 2 ), 131 (71%) had seen more than 10 TB patients, and 56 (30%) had friends or family members with TB ( Table 2 ).

Mean knowledge and attitude scores.

SD: standard deviation, KUSMS: Kathmandu University School of Medical Sciences, CMS: College of Medical Sciences, NMC: Nepal Medical College.

3.2. TB knowledge

The survey found that 131 (71%) and 167 (89%) of the responders were unaware of the incidence of TB cases in Nepal and of TB related mortality ( Fig. 1 ). Less than half of the interns mentioned guidelines or the NTP as the main source of information but almost all of them knew about the strategy for and costs of treatment. However, only one fourth of the interns knew all main symptoms of TB, and half of them knew the four most important symptoms. Also, half of them knew which test to do first and nearly half of them knew how to monitor TB. However, 178 (96%) knew about the referral process and knowledge about treatment was good. Only half of the interns knew that TB patients are non-infectious after two weeks of treatment ( Fig. 1 ).

Percentage of correct answers on 18 knowledge-related questions regarding TB.

The mean knowledge score for all participants was 13.3 (SD: 2.12) of a maximum of 19. The mean knowledge score for the three medical colleges was as follows: KUSMS 12.9 (SD: 2.1) CMS 13.4 (SD: 2.0), and NMC 13.6 (SD: 2.2). There were no significant differences between the colleges. ( Table 2 , Table 3 ). However, there was a positive association between being female, having “seen more than 10 patients”, and having taken a TST within the last five years, and the knowledge score ( Table 3 ). The interns who considered themselves not at risk for TB, or who would tell no one or just one person if they contracted TB, had a lower knowledge score.

Correlates of TB knowledge, using one-way ANOVA.

TST: Tuberculin skin test, CI: Confidence interval, KUSMS: Kathmandu University School of Medical Sciences, CMS: College of Medical Sciences, NMC: Nepal Medical College.

3.3. TB attitude

Among the interns, 144 (77%) said they could imagine themselves working with TB patients in the future and 179 (97%) wanted to learn more about TB ( Fig. 2 ). Altogether 144 (78%) interns considered themselves to be at risk of contracting the disease. If a friend of them developed TB, 171 (92%) of them would visit him/her. When asked about how they would react if they developed TB themselves, 99 (54%) of the interns said they would react with fear, 41 (22%) with surprise, 25 (14%) would feel sadness/hopelessness and 7 (4%) embarrassment ( Fig. 2 ). More than 1/3 would only tell the diagnosis to a doctor/medical worker, and to nobody else.

Distribution of answers on attitude questions.

The mean attitude score was 9.4 (SD:1.89) and CMS and NMC had a higher score than KUSMS ( Table 2 , Table 4 ). Being 25 years or older were found to have a positive association with the attitude score ( Table 4 ). There was a positive correlation between greater knowledge and better attitude (0.3) p < 0,001 when tested using two tailed Pearson correlation test.

Correlates of TB attitude, using one-way ANOVA.

Test for normality and visual inspection of normal Q-q plots showed that the knowledge score was normally distributed. When adjusted for the knowledge score, the attitude score was also normally distributed in the same tests.

4. Discussion

4.1. important findings.

The WHO recommendations that medical school should “provide every graduate with the knowledge, skills and attitudes essential to the management of tuberculosis in the patient and in the community as a whole” [9] was only partly investigated in this study as the skills were not tested and not all details in the recommendations were checked. A large proportion of the interns were considered to have adequate knowledge overall regarding TB and the NTP, and there was no significant difference in the knowledge scores between the medical colleges included in the study. However, one should not ignore the identified knowledge gaps regarding at risk groups, symptoms and examination, and the current TB epidemiology in Nepal or the fact that 37% of the interns felt unable to speak freely of TB. There was a correlation between knowledge and attitude score. The median attitude score was considered adequate in general and 77% of the interns said they could imagine themselves working with TB in the future, while almost all of them acknowledged that TB was a major health problem in Nepal.

4.2. Knowledge

In contrast to some studies in other countries, which found insufficient TB related knowledge among medical students and/or interns [10] , [11] , [12] , [13] , [14] , the present study found a proportion of approximately 70% correct answers witch was considered adequate TB knowledge among Nepalese interns in general. However, there are other studies that have found adequate knowledge [15] , [16] . Like this study, those studies also found an association between better knowledge and the number of TB patients seen [15] , [16] . All of the theoretical concepts had been taught according to the syllabus set by Kathmandu University, and there were no differences between the colleges in terms of the knowledge score. Students‘ knowledge could be improved by requiring them to spend some time at DOTS clinics and/or see a specified number of TB patients during medical school.

Even though the general knowledge was adequate, there were some serious knowledge gaps with resepct to at-risk groups, main symptoms of TB and sputum tests for both diagnosis and follow-up. Similar important knowledge gaps have been detected in other studies among both students/interns and medical doctors [11] , [13] , [19] , [20] . These knowledge gaps could lead to serious mismanagement of TB patients, under- and over-diagnosis, and late diagnosis of MDR-TB. Twenty-seven percent of the interns did not know the standard treatment for TB, which is another risk for developing drug-resistant TB. Other studies of students and doctors have shown even higher numbers [10] , [14] , [16] .

There was a positive association between having done a TST in the last five years and the knowledge score. In a study from Rome, where all students had done a TST, there was an association between the reported taking of the test and knowledge of TB. Other studies have also reported an association between knowledge and better-integrated preventive measures [21] .

4.3. Attitude

Health care personnel’s attitude towards TB patients is perceived to be important for patients‘ treatment completion and health seeking behavior [13] , [22] . In our study 77% of the interns could imagine themselves working with TB and 97% wanted to learn more about the disease. The mean attitude score was 9.4 of a maximum of 14 and was considered good. However, one-third of the interns felt unable to speak freely about TB. In a study of family physicians in Turkey, almost half of the doctors could not imagine themselves working with TB patients [20] , while in a study of residents in India 51% reported fear, lack of compassion and a tendency to avoid TB patients [23] . Thus, the Nepalese interns in general, have better attitudes, which can serve as a good base for further improvements in knowledge and attitudes towards TB.

4.4. Strengths and limitations

As our questionnaire is based on the WHO‘s KAP template, which has been developed by skilled and knowledgeable developers [17] , the questionnaire has an acceptable professional standing. In addition, the anonymity provided by the survey, which could prevent any negative individual consequences and could reduce the threshold for responding, resulted in a higher sample size. Most of the interns filled out the questionnaires completely, and just three responses had to be removed, while one was excluded from some of the analyses due to insufficient answers. These advantages provided a solid base for our analyses and survey.

The completion rate of the present study was good (69%) and no one declined to answer the questionnaire. However, we do not know exactly how many interns were asked to participate but were told that everybody who was asked, answered the questionnaire. The percentage of interns who participated varied from 49 to 90%.This could have been caused by handing out the questionnaires to only a fraction of the interns at the respective colleges. Due to the time limitation, the questionnaires were handed out to the interns present at the colleges at the time of the study which could have caused a selection bias. However, this bias would have been random and only diluted the results, not led the results in any particular direction. Furthermore, as it was a written questionnaire, some of the participants checked outside of the box, between two boxes, or in too many or too few boxes, all leading to an imprecise estimate of their KAP. As three medical colleges in different parts of Nepal were included, and their results are mostly in conformity, our results might extrapolate to the rest of the country.

Confounders, such as interest, clinical practice and personal experience, could have led to better participation in the survey yielding higher knowledge and attitude scores. The questionnaire was not filled out in a controlled environment, making it impossible to state if the interns used the internet, books or other sources for information. The consequence could be a falsely higher knowledge score. Generalisability could be suboptimal due to the low percentage of included interns, because all the medical colleges were affiliated to KU and none were government-run, and because only three out of 19 medical colleges were included in the study.

5. Conclusion

The surveyed interns had adequate knowledge level about TB, and acceptable attitudes towards the disease in general. However, some knowledge gaps and unacceptable attitudes were also found, including with respect to disease detection and management. As most of the interns could imagine themselves working with TB in the future, and are receptive to more education in this area, TB should be a priority area in medical education including in their post-graduate education. This survey underlines the importance of clinical experience and seeing TB patients during medical college. We suggest that all students gain experience at a TB clinic or see a minimum prescribed number of TB patients during medical schools.

Ethical statement

A verbal request to Regional Committees for Medical and Health Research Ethics Norway clarified that ethical approval in Norway was not needed as no patient information was gathered in the study.

In Nepal ethical approval was received from KUSMS Institutional Review Committee (KUSMS/IRC) (84/17), at NMC the Research Director gave an approval from IRC-NMC, and CMS accepted the KUSMS/IRC.

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

We are grateful to Turid Follestad who gave statistical advice. Dr Suresh Kayastha from Dhulikhel, dr Dipendra Khatiwada from CMS, dr Bharati Shakya from NMC and intern Niraj Neupane from NMC all gave important help in the data collection. We also thank all the interns who filled in the questionnaire.

The two medical students received funding from Norwegian University of Science and Technolgoy (NTNU) for their thesis work. No other funding was given.

Authors contribution

Anna Berg-Johnsen; she is first author together with Synne Oasaland Hådem. They both participated in the planning of the project, did the data collection, and wrote their student thesis on this study. Afterwards, she did more statistical analysis and participated in the writing of the manuscript.

Synne Osaland Hådem : she is first author together with Anna Berg-Johansen. They both participated in the planning of the project, did the data collection, and wrote their student thesis on this study. Afterwards, she participated in the writing of the manuscript.

Dr Dipesh Tamrakar was the local supervisor in Nepal. He helped out planning the study and during the data collection. He read the manuscript and gave input and comments.

Ingunn Harstad : supervised the planning of the project, the data collection and analyses of data. She revised the manuscript critically, finalized the manuscript for submission and is the corresponding author.

Scoring system for calculating attitude score

Scoring system for calculating knowledge score

Questionnaire with information sheet and marked correct answers

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Peer-reviewed

Research Article

Systematic review and meta-analysis of Tuberculosis and COVID-19 Co-infection: Prevalence, fatality, and treatment considerations

Roles Conceptualization, Formal analysis, Investigation, Methodology, Visualization, Writing – original draft, Writing – review & editing

¶ ‡ QW, YC, and XL are joint first authors of this paper and they contributed equally.

Affiliations School of Public Health, Peking University, Beijing, China, Brown School, Washington University in St Louis, St Louis, Missouri, United States of America

Roles Data curation, Formal analysis, Investigation, Validation

Affiliation Jinan Municipal Center for Disease Control and Prevention, Jinan, Shandong Province, China

Roles Data curation, Formal analysis, Investigation, Validation, Writing – review & editing

Roles Writing – review & editing

Affiliation School of Public Health, Peking University, Beijing, China

Affiliation Centre for Global Health Economics, University College London, London, United Kingdom

Affiliation Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

Roles Funding acquisition, Project administration, Resources, Software, Supervision, Validation, Writing – review & editing

* E-mail: [email protected]

• Quan Wang, 
• Yanmin Cao, 
• Xinyu Liu, 
• Yaqun Fu, 
• Jiawei Zhang, 
• Yeqing Zhang, 
• Lanyue Zhang, 
• Xiaolin Wei, 

• Published: May 13, 2024
• https://doi.org/10.1371/journal.pntd.0012136
• Reader Comments

Tuberculosis (TB) and COVID-19 co-infection poses a significant global health challenge with increased fatality rates and adverse outcomes. However, the existing evidence on the epidemiology and treatment of TB-COVID co-infection remains limited.

This updated systematic review aimed to investigate the prevalence, fatality rates, and treatment outcomes of TB-COVID co-infection. A comprehensive search across six electronic databases spanning November 1, 2019, to January 24, 2023, was conducted. The Joanna Briggs Institute Critical Appraisal Checklist assessed risk of bias of included studies, and meta-analysis estimated co-infection fatality rates and relative risk.

From 5,095 studies screened, 17 were included. TB-COVID co-infection prevalence was reported in 38 countries or regions, spanning both high and low TB prevalence areas. Prevalence estimates were approximately 0.06% in West Cape Province, South Africa, and 0.02% in California, USA. Treatment approaches for TB-COVID co-infection displayed minimal evolution since 2021. Converging findings from diverse studies underscored increased hospitalization risks, extended recovery periods, and accelerated mortality compared to single COVID-19 cases. The pooled fatality rate among co-infected patients was 7.1% (95%CI: 4.0% ~ 10.8%), slightly lower than previous estimates. In-hospital co-infected patients faced a mean fatality rate of 11.4% (95%CI: 5.6% ~ 18.8%). The pooled relative risk of in-hospital fatality was 0.8 (95% CI, 0.18–3.68) for TB-COVID patients versus single COVID patients.

TB-COVID co-infection is increasingly prevalent worldwide, with fatality rates gradually declining but remaining higher than COVID-19 alone. This underscores the urgency of continued research to understand and address the challenges posed by TB-COVID co-infection.

Author summary

Tuberculosis (TB) and COVID-19, both highly infectious diseases, have posed significant global health challenges, particularly in low/middle-income countries (LMICs) with limited medical resources. Our research highlights that TB-COVID co-infection remains a substantial concern, impacting regions with varying TB burdens. The predominant treatment approach for TB-COVID co-infection has not notably evolved since our earlier study in 2021. It typically involves a combination of the recommended TB regimen and standard COVID-19 treatment. Our analysis consistently shows that individuals with TB-COVID co-infection are at heightened risk of hospitalization, protracted recovery periods, and accelerated mortality compared to those with sole COVID-19 infections. Remarkably, we found limited information on the post-COVID-19 condition of co-infected patients. One study indicated a higher prevalence of anxiety symptoms, highlighting the potential psychological toll of TB-COVID co-infection. Although the fatality rate has gradually decreased, it remains notably higher than that of COVID-19 alone. Our findings underscore the urgent need for global collaboration to address the complex challenges posed by TB-COVID co-infection, particularly in countries with limited medical resources.

Citation: Wang Q, Cao Y, Liu X, Fu Y, Zhang J, Zhang Y, et al. (2024) Systematic review and meta-analysis of Tuberculosis and COVID-19 Co-infection: Prevalence, fatality, and treatment considerations. PLoS Negl Trop Dis 18(5): e0012136. https://doi.org/10.1371/journal.pntd.0012136

Editor: Dileepa Ediriweera, University of Kelaniya Faculty of Medicine, SRI LANKA

Received: September 5, 2023; Accepted: April 5, 2024; Published: May 13, 2024

Copyright: © 2024 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All relevant data are within the paper and its Supporting information files.

Funding: LY was supported by grant from National Natural Science Foundation of China [72174010] and Natural Science Foundation of Beijing Municipality [M22033]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

The ongoing COVID-19 pandemic has created an unprecedented healthcare crisis, especially in low/middle-income countries (LMICs) where medical resources are severely limited [ 1 , 2 ]. Unfortunately, these countries are also heavily burdened by tuberculosis (TB), with their populations being the main victims of this disease [ 3 ]. World Health Organization (WHO) has emphasized that the COVID-19 pandemic has not only disrupted TB services and response but also reversed years of progress made in the fight against tuberculosis [ 4 , 5 ]. Consequently, more people have fallen ill with TB and experienced higher mortality rates, timely diagnosis rates have decreased, and global spending on essential TB services has significantly declined [ 6 ].

A systematic review, encompassing evidence from 2019 to mid-2021, revealed a consistent upward trend in the absolute number of co-infected patients. Furthermore, an increasing number of countries reported co-infected patients, including both high-income countries and LMICs [ 7 ]. TB, as one of the world’s deadliest infectious diseases, comes second only to COVID-19 in terms of its impact[ 8 ]. Some experts believe that TB-COVID co-infection is associated with a poorer prognosis and a higher risk of mortality[ 9 , 10 ]. It is crucial to note that despite an exhaustive review, we did not encounter a universally accepted definition for TB–COVID co-infection. In this context, our systematic analysis provides a preliminary characterization, defining TB–COVID co-infection as a state arising from both ongoing and past infections involving M . tuberculosis and SARS-CoV-2. It’s essential to emphasize that while latent TB infection and TB disease (or active TB) present significant clinical distinctions, our usage of ’TB’ in this study encompasses all forms of M . tuberculosis infection, spanning latent, active, cured, and current states.

While there have been studies that have synthesized evidence on co-infection, they have primarily relied on case reports and case series, providing relatively weak support for epidemiology and treatment [ 11 , 12 ]. Consequently, there remains a dearth of information regarding the treatment and outcomes of TB-COVID co-infection, and a lack of consensus regarding its epidemiological status. This study serves as an update to our previous systematic review, which collected and pooled evidence as of the middle of 2021[ 7 ]. In this updated systematic review, we aim to summarize the latest epidemiological data on TB-COVID co-infection, discuss fatality rates, and explore possible clinical outcomes.

This systematic review follows the PRISMA guidelines ( S1 Table ) [ 13 ]. The study was registered in PROSPERO’s database with the registration number CRD42021253660.

Search strategy

We conducted a comprehensive search using six electronic databases: MEDLINE, Web of Science, ProQuest, Scopus, Cochrane database, and Embase. To maximize the scope of our search, we also employed the Grey Matters Checklist to identify relevant grey literature [ 14 ]. The literature search was conducted until January 24, 2023. Medical Subject Heading (MeSH) terms, title/abstract, topic, or subject words were used in the selected databases. The search formula included the terms "TB" AND "COVID-19". For "TB," key terms such as "tuberculosis," "TB," "tuberculos*," "mycobacterium tuberculosis," and "m.tuberculosis" were used. For "COVID-19," the key terms used were "COVID-19" and "SARS-COV-2".

Eligibility criteria of included studies

This systematic review included epidemiological and fatality data on TB-COVID co-infection from cohort studies, cross-sectional studies, and experimental research, excluding case reports, series, reviews, editorials, and clinical guidelines. Studies with sample sizes less than 20 were also excluded to reduce potential bias. Two reviewers (QW and XL) independently screened and selected studies using Covidence. Non-English and non-Chinese articles were translated to English using TranslateGo (Hangzhou Qingxun Science and Technology Co., China). Manual reference screening ensured study inclusivity. Conflicts were resolved by a third author (LY), and duplicates were managed across similar studies. We would like to stress that, unlike our previous work in 2021, we did not include case reports or case series in this study. Building on the insights from our earlier research, we found that these study types contributed little to our understanding of the topic, and they did not provide sufficient data for estimating fatality rates, prevalence status, or determining best practices in treatment.

Data extraction, quality assessment, and analysis

Relevant data, including authors, publication dates, study design, location, sample size, settings, epidemiological and treatment information, and clinical outcomes, were extracted. Prevalence rates of co-infection were prioritized for epidemiological data, along with total and hospitalized fatality rates. The total fatality rate represents the proportion of patients documented as deceased among all TB-COVID co-infected individuals, irrespective of whether they received treatment. On the other hand, the hospitalized fatality rate pertains to the proportion of patients documented as deceased among all TB-COVID co-infected individuals who underwent hospitalization. Treatment details, including drugs and ICU utilization, were also collected. The quality of included studies was evaluated using the Joanna Briggs Institute (JBI) Critical Appraisal Checklist for Study Reporting Prevalence Data [ 15 ].

Location data from all studies identified the reporting countries and regions of TB-COVID co-infection cases. Prevalence and fatality rates were chronologically listed for temporal trends analysis.

Random-effects meta-analysis calculated pooled fatality rates and relative risks (RR) of fatality between TB-COVID co-infection and single COVID-19 patients. Forest plots displayed point estimates and 95% confidence intervals (CIs), while I 2 assessed heterogeneity. P values < 0.05 indicated statistical significance.

Egger’s tests assessed publication bias, and sensitivity analyses assessed robustness by omitting studies one at a time. Subgroup analyses explored LMICs vs. high-income countries and active TB vs. previous TB status. Stata 17 (StataCorp LLC, USA) performed calculations.

A comprehensive search strategy utilizing the building blocks approach was executed to identify pertinent studies. After an extensive search, we retrieved 1,792 records from MEDLINE, 2,863 from Web of Science, 2,404 from ProQuest, 2,928 from Scopus, 1,314 from the Cochrane database, 1,962 from Embase, and 61 from Grey Matters Checklist (refer to S2 Table for details). Upon importing these records into Covidence, 8,229 duplicate records were identified and subsequently removed, resulting in 5,095 records available for title and abstract screening. In this phase, 4,391 records were excluded. The remaining 704 records entered the full-text review process, during which 38 potentially relevant records were identified. Ultimately, 689 out of 704 records and 36 out of 38 records were excluded, and 17 retrospective studies were included for analysis; no experimental studies were identified in the search. The entire process is visually presented in Fig 1 .

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As of the search date, our analysis identified TB-COVID co-infection cases reported in 38 countries or regions, including Argentina, Belarus, Belgium, Brazil, Chile, China, France, Republic of Guinea, India, Italy, Mexico, Niger, Pakistan, Panama, Peru, Philippines, Portugal, Romania, Russia, Singapore, Spain, Switzerland, UK, Australia, Canada, Colombia, Greece, Honduras, Lithuania, the Netherlands, Oman, Paraguay, Serbia, Slovakia, South Africa, Turkey, Thailand, and USA. Among the studies included, there was one notable study conducted by the TB/COVID-19 Global Study Group in 2022, which involved TB-COVID patients from 172 centers in 34 countries. The remaining 16 studies reported patients within a single region or country [ 16 ].

Regarding the prevalence rate of TB-COVID co-infection, two studies provided information. The first study, conducted by the Western Cape Department of Health in collaboration with the National Institute for Communicable Diseases, analyzed data from the Western Cape Provincial Health Data Centre. They found a prevalence rate of approximately 0.04% among individuals aged 20 years or above in the Western Cape Province until 1 June 2020. After testing criteria changed, the prevalence rate increased to approximately 0.06% until 9 June 2020 [ 17 ]. The second study, led by Nabity in 2021, identified 6371 co-infected patients among all California residents between September 3, 2019, and December 31, 2020, resulting in a prevalence rate of approximately 0.02% [ 18 ]. The S3 Table provides detailed information on these two studies.

Among the studies included in our analysis, only a limited number of studies provided information on the treatment of TB-COVID co-infection. Upon comparing our findings with our previous study conducted in 2021, we did not identify any new treatments that have emerged. The most commonly utilized treatment approach involved the use of first-line anti-TB treatment (ATT) drugs, including rifampicin, isoniazid, ethambutol, and pyrazinamide, which were administered in the majority of cases. In terms of antiviral drugs, lopinavir, ritonavir, and arbidol were the three most frequently prescribed medications. Notably, the use of hydroxychloroquine (HCQ) has become limited, as it has been demonstrated to have no benefit in the treatment of TB-COVID co-infection [ 19 ]. Three studies included in our review highlighted the utilization of Intensive Care Units (ICUs) in the management of TB-COVID co-infection. The reported ICU admission rates varied from 1.3% to 31.8% [ 20 – 22 ]. Additionally, Wang discussed the usage of Paxlovid, an antiviral therapeutic for COVID-19 treatment, and emphasized its contraindication in patients receiving rifampicin, one of the first-line agents for TB treatment, due to drug interactions as Paxlovid is a strong cytochrome P450 3A4 inhibitor. Consequently, Paxlovid was not deemed suitable for treating patients with active TB-COVID co-infection undergoing ATT [ 21 ].

Several studies have indicated that TB-COVID co-infected patients face increased risks of hospitalization, longer time-to-recovery in elderly patients, and shorter time-to-death compared to individuals with single COVID-19 infection [ 21 , 23 – 25 ]. Parolina’s study highlighted various factors associated with an increased risk of developing severe COVID-19 in TB patients, including female gender, smoking, fever, dyspnea, disseminated TB, having three or more co-morbidities, and patient age[ 26 ]. Wang emphasized that despite the milder nature of infections with the Omicron variant compared to earlier variants, patients with TB-COVID co-infection do not exhibit the mild disease course observed in the general population [ 21 ]. Notably, the majority of patients in Wang’s study, 142 out of 153 co-infected individuals, were classified as nonsevere, with 10 being asymptomatic [ 21 ]. This may be attributed to lung parenchyma damage resulting from pulmonary remodeling due to persistent cavitation, fibrosis, or bronchiectasis, which is present in approximately 50% of cured TB patients and may increase susceptibility to COVID-19 and mortality rates [ 25 ]. The presence of dual lung damage following both TB and COVID-19 necessitates careful follow-up of patients with post-tuberculosis lung disease who have experienced COVID-19 pneumonia [ 25 ]. These findings underscore the complex interactions and challenges associated with TB-COVID co-infection. The coexistence of two lung diseases can lead to heightened severity and poorer outcomes, warranting specialized management approaches and continued monitoring of affected individuals. For more detailed information, please refer to S4 Table .

Fatality rate

A total of 17studies were included in our analysis, reporting data on the fatality rate of TB-COVID co-infection. The reported fatality rates among the total patient population varied widely, ranging from 0% to 23.6%. Similarly, the in-hospital fatality rates also showed considerable variation, ranging from 0% to 27.3% ( Table 1 ).

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To further explore the impact of active TB and previous TB on fatality rates, we collected and analyzed information specific to these subgroups ( Table 2 ). Among co-infected patients with concurrent TB disease (active TB), the reported fatality rates ranged from 7.6% to 23.6% for the total patient population, and for hospitalized active TB-COVID patients, the fatality rates ranged from 0% to 27.3%. Regarding previous TB-COVID patients, the fatality rates ranged from 4.9% to 14.5% for the total patient population, and for hospitalized patients, the fatality rates ranged from 0% to 24.0%. Please refer to S4 Table and S5 Table , and S6 Table for comprehensive and detailed information about the included studies.

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Quality assessment of included studies

We employed the JBI Critical Appraisal Checklist for Study Reporting Prevalence Data as a tool to assess the quality of the 17 included studies. The checklist consisted of 9 questions covering various aspects such as sampling method, sample size, study subjects and setting, analysis method, and participant response. Each question was evaluated using one of the four options: yes, no, unclear, or not applicable. In total, 10 studies reached more than 70% of ‘yes’ scores, 6 studies reached from 50% to 69% of ‘yes’ scores, and 1 study was below 50%. Upon further analysis, it was identified that the sample frame, sampling method, and sample size were the areas most frequently identified as having a higher risk of bias within the included studies. Check S7 Table and S1 Fig for assessment result of each study.

Meta-analysis of fatality rates

Among all included studies, the pooled fatality rate of TB-COVID co-infection among total patients was estimated to be 7.1% (95% CI, 4.0%-10.8%). However, when examining the results by country income status, significant variations were observed. In high-income countries (HICs), the pooled fatality rate was higher, with a result of 10.2% (95% CI, 9.4%-10.9%) based on two studies that included a total of 6,569 individuals. On the other hand, in low- and middle-income countries, the pooled fatality rate was lower at 5.8% (95% CI, 2.0%-11.3%), based on five studies involving 2,888 individuals ( Fig 2 ). The GTN’s study provided three cohorts: total co-infected patients, co-infected patients in Europe, and co-infected patients outside of Europe. Considering that most included countries in Europe are HICs and most countries outside of Europe are LMICs, we placed these two cohorts in the HICs and LMICs subgroups, respectively. The results of Egger’s test indicated no evidence of publication bias across all the included study groups, as well as within the low- and middle-income countries subgroup ( S8 Table and S2 Fig ). To assess the robustness of our pooled results, we performed sensitivity analyses by systematically omitting one study at a time. These analyses consistently demonstrated the stability and reliability of our pooled estimates ( S9 Table and S3 Fig ).

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The estimated fatality rate among hospitalized patients with TB-COVID co-infection was 11.4% (95% CI, 5.6%-18.8%). It is important to note that significant heterogeneity was detected among the studies and groups analyzed. Unlike the total fatality rate, the results for low- and middle-income countries (LMICs) were similar to those of high-income countries (HICs) in terms of fatality rate among hospitalized patients. The pooled result for LMICs was 11.1% (95% CI, 4.0%-20.9%) based on eight studies involving 985 individuals. In comparison, the pooled result for HICs was 10.9% (95% CI, 5.9%-17.1%) based on four studies involving 148 individuals. These findings suggest a comparable fatality rate among hospitalized TB-COVID co-infection patients in both LMICs and HICs. For detailed results, please refer to Fig 3 . Based on the results of Egger’s tests, publication bias was observed in all included study groups. However, no evidence of publication bias was found within the 2 subgroups ( S10 Table and S4 Fig ). Furthermore, the sensitivity analysis, which involved systematically omitting one study at a time, demonstrated that the exclusion of any particular study did not significantly alter the pooled results. This finding supports the robustness and reliability of our study findings ( S11 Table and S5 Fig ).

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In our subgroup analysis based on TB status (active/previous), the pooled results revealed significant differences in the fatality rates between active TB-COVID infection and previous TB- COVID infection ( Fig 4 ). For total fatality rate, the pooled estimate for active TB-COVID infection was 10.6% (95% CI, 7.9%-13.6%), which was higher compared to previous TB-COVID infection with a pooled estimate of 5.7% (95% CI, 4.7%-6.7%). Regarding in-hospital fatality rate, the estimated pooled result for active TB-COVID infection was 9.8% (95% CI, 2.8%-19.8%) based on eight studies involving 739 individuals. In contrast, the in- hospital fatality rate for previous TB-COVID infection was higher, with a pooled estimate of 21.0% (95% CI, 16.7%-25.6%). Furthermore, Egger’s tests were conducted to assess publication bias, and the results can be found in S12 Table and S6 Fig . Additionally, sensitivity analyses were performed, and the results demonstrated the stability and robustness of the study findings (refer to S13 Table and S7 Fig ).

A: Total active TB-COVID co-infection patients; B: Total previous TB-COVID co-infection patients; C: Hospitalized active TB-COVID co-infection patients; D: Hospitalized previous TB-COVID co-infection patients.

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Meta-analysis of relative risk

Three studies included in our analysis provided results on the relative risk (RR) of in-hospital fatality between TB-COVID patients and single COVID patients. The pooled analysis, which involved a total of 1285 patients, suggested that TB infection might potentially reduce the fatality risk with a relative risk estimate of 0.8 (95% CI, 0.18–3.68) ( S8 Fig ). Regarding publication bias, the results of Egger’s test indicated no evidence of publication bias in the included studies ( S9 Fig ). However, the sensitivity analysis revealed some instability in the pooled results, suggesting the need for caution in interpreting these findings ( S14 Table and S10 Fig ).

This updated systematic review collected relevant studies up until January 24, 2023, and included a total of 17 studies. In comparison to a previous study that identified co-infection cases in 12 countries or regions based on population studies, our review expanded the scope and identified an additional 18 countries or regions reporting TB-COVID co-infection. This finding suggests that despite COVID-19 no longer being classified as a Public Health Emergency of International Concern by the WHO, the prevalence of TB-COVID co-infection remains significant in both high and low TB-burden countries or regions.

A notable contribution to the field is a large-scale study led by Nabity in 2021, which provided an updated prevalence rate estimate of approximately 0.02% in California, USA [ 18 ]. In contrast, an earlier study conducted in West Cape Province, South Africa in early 2020 reported a prevalence rate of 0.06%. The discrepancy in prevalence rates between these two regions suggests that the burden of TB-COVID co-infection may vary across different geographic locations. Factors such as differences in TB prevalence, COVID-19 incidence, and the effectiveness of TB and COVID-19 control measures implemented in each region may contribute to these variations.

In terms of treatment, our analysis revealed that the treatment approach for TB-COVID co-infection has not undergone significant changes since our previous study in 2021. The predominant strategy employed in the included studies involved the administration of first-line anti-TB drugs, which is in accordance with the established standard treatment protocol for TB. Despite our comprehensive review of the available literature, we did not identify any experimental studies that could provide specific guidance on the best practices for managing TB-COVID co-infection. Only a limited number of studies made any mention of adjustments to treatment regimens based on the unique characteristics of co-infected patients. As a result, the current approach to treatment for TB-COVID co-infection appears to be a combination of the recommended TB regimen and the standard treatment for COVID-19.

The studies that reported ICU utilization in the context of TB-COVID co-infection provided insights into the severity of the disease and the clinical management required. The wide range of reported ICU admission rates, ranging from 1.3% to 31.8%, highlights the heterogeneity in disease presentation and underscores the need for specialized care for individuals with severe forms of co-infection. These findings emphasize the importance of tailored management approaches that address the complex interactions between TB and COVID-19. Consistent findings across multiple studies indicate that individuals with TB-COVID co-infection face a higher risk of hospital admission, longer time-to-recovery, and shorter time-to-death compared to individuals with single COVID-19 infection [ 21 , 23 – 25 ]. These observations underscore the unique challenges posed by the coexistence of TB and COVID-19 and emphasize the necessity for tailored management strategies that effectively address both diseases.

Another important aspect to consider in the context of TB-COVID co-infection is the potential development of Post-COVID-19 condition (PCC), commonly known as long COVID [ 34 ]. PCC refers to a range of persistent symptoms and health issues that can affect individuals even after recovering from acute COVID-19 infection [ 35 ]. It has been observed that PCC can significantly impact a person’s daily functioning, employability, and overall well-being. Moreover, it has been associated with an increased risk of developing new health conditions and the utilization of healthcare services, which can further strain the individual’s financial stability [ 34 ]. However, it is worth noting that the current evidence regarding PCC specifically in the context of TB-COVID co-infection is scarce. We only identified one study that mentioned the proportion of individuals experiencing long-lasting symptoms after COVID-19 infection in conjunction with previous tuberculosis (PTB) treatment [ 36 ]. This study reported that over time, the proportion of individuals with persistent symptoms decreased, although a significant proportion, approximately one in six, still experienced ongoing symptoms. Furthermore, this group exhibited a higher prevalence of anxiety symptoms, underscoring the potential psychological impact of TB-COVID co-infection. The recurrence of pulmonary tuberculosis and the need for psychological support for individuals with a history of both COVID-19 and pulmonary TB after discharge warrant additional attention and investigation [ 36 ].

The meta-analyses conducted on the overall fatality rate of TB-COVID co-infection revealed an estimated rate of 7.1%, which is lower than our previous study’s estimate of 13.9%. This difference could potentially be attributed to the emergence of new SARS-CoV-2 variants that may exhibit milder clinical manifestations. However, it is important to note that the fatality rate of TB-COVID co-infection remains higher than that of COVID-19 alone, which was estimated at 0.68% by mid of 2020[ 37 ]. Subgroup analyses based on high-income countries and low- and middle-income countries showed a higher fatality rate in high-income countries (10.2%) compared to LMICs (5.8%). It is crucial to recognize that multiple confounding factors may contribute to this observed discrepancy. For instance, lower vigilance and delayed time-to-diagnosis in outpatient clinics, particularly in higher-income countries with traditionally lower TB burdens, could play a role. Another potential factor is the higher frequency of COVID-19 testing in high-income countries, which might dilute the numbers of identified active TB-COVID infection. Additionally, the average age of co-infected patients tends to be higher in HICs, and given that age is a proven risk factor for COVID-19 mortality, this demographic difference could contribute to the observed higher fatality rate. These findings underline the importance of considering various contextual factors when interpreting fatality rates and emphasize the need for further research to elucidate the complex dynamics at play. In terms of in-hospital fatality rates, the results were similar between high-income countries (11.1%) and LMICs (10.9%), further supporting the assumption mentioned above.

Our subgroup analysis based on TB status (active/previous) revealed significant differences in the fatality rates between active TB-COVID infection and previous TB-COVID infection. These findings highlight the differential risks and outcomes associated with active and previous TB in the context of COVID-19 co-infection. The reasons for these differences may be multifactorial. Active TB-COVID infection may impose a greater burden on the immune system and respiratory function, leading to increased susceptibility to severe COVID-19 illness and poorer outcomes. In contrast, individuals with previous TB may have partially developed immunity or residual lung damage, which could potentially confer some level of protection or adaptation against severe COVID-19. We acknowledge the variability in the status of TB infection extracted from the included origin studies, as there was no uniform standard criterion across different studies. Active TB is a complex disease with a lengthy treatment regimen, which is commonly defined as disease that occurs in someone infected with Mycobacterium tuberculosis . It is characterized by signs or symptoms of active disease, or both, and is distinct from latent tuberculosis infection, which occurs without signs or symptoms of active disease [ 38 ]. The absence of consistent definitions or criteria may have contributed to the heterogeneity observed in the meta-analysis.

An intriguing trend in current TB-COVID research centers around a significant focus on the pandemic’s impact on TB care services. Global studies have demonstrated a substantial adverse effect on the delivery, accessibility, and utilization of TB care services [ 39 ]. Comparing 2020 to 2019, there was an 18% reduction in global tuberculosis case detection, dropping from 7.1 million to 5.8 million cases, with up to a 24% decrease in the ten worst-affected countries with a high tuberculosis burden [ 5 ]. This service disruption in TB care has led to a consequential increase in additional tuberculosis-related deaths. From a critical thinking perspective, we posit that this impact might contribute to an augmentation in our estimated TB-COVID fatality rate in two crucial ways. Firstly, the reduction in tuberculosis case detection may result in fewer identified TB-COVID co-infected patients. This is particularly significant as COVID-related deaths are usually more rigorously recorded in many countries, and during this process, the TB infection can also be documented. Secondly, the disruption in TB care services might result in insufficient treatment for numerous co-infected individuals, potentially contributing to preventable deaths. This concern is particularly pronounced in LMICs, where healthcare services are often limited and of lower quality [ 40 , 41 ]. Additionally, the decrease in discovered cases of TB could contribute to a lower total number of identified co-infected patients.

In our analysis, we observed a relative risk (RR) value suggesting that TB-COVID co-infection might reduce the fatality risk compared to single COVID-19 infection. This finding may initially seem counterintuitive given that TB is a known risk factor for severe respiratory illness and mortality. It’s essential to emphasize that the groups with TB-COVID co-infection and those with single COVID-19 infection did not exhibit precisely homogeneous patient characteristics, including differences in age, gender, comorbidities, and treatment modalities. For instance, studies by Parolina and Sereda reported a higher proportion of male patients in the TB-COVID co-infection group compared to the single COVID-19 infection group [ 26 , 31 ]. Also of note is that Sy’s 2020 study, employing propensity score matched sampling, suggested that co-infected patients experienced higher fatality rates [ 24 ]. However, due to the limited information available regarding the specific details of the included patient groups, we cannot deduce the underlying reasons for this counterintuitive RR. Therefore, readers are advised to approach this finding with caution and interpret it within the acknowledged limitations we have outlined.

As a systematic review focused on TB-COVID co-infection, understanding how TB impacts COVID-19 is as crucial as comprehending how COVID-19 impacts TB. However, given the prominence of COVID-19 as a research topic, many studies at the individual level tend to emphasize the perspective of COVID-19 infection. While we did encounter studies exploring how COVID-19 impacts TB, these primarily delved into microbiological mechanisms or the pandemic’s disruption of TB service delivery. Immunologically, a shared dysregulation of immune responses in COVID-19 and TB has been identified, indicating a dual risk posed by co-infection in worsening COVID-19 severity and favoring TB disease progression [ 42 , 43 ]. Notably, for some severe COVID-19 patients, corticosteroid use can induce immunosuppression [ 44 ], significantly increasing the risk of new secondary infections and/or reactivation of existing quiescent TB infections [ 45 , 46 ]. From the TB service perspective, the COVID-19 pandemic has substantially impacted the normal delivery of TB services, exerting a negative influence on TB patients [ 39 ]. However, some studies suggest a potential reduction in Mycobacterium tuberculosis transmission during the pandemic, potentially lowering TB fatality rates [ 47 , 48 ]. Unfortunately, the current evidence is limited, and the impact of the pandemic on TB remains conflicting and inconclusive. We cautiously posit that COVID-19 exerts a negative influence on individuals already carrying Mycobacterium tuberculosis .

In our assessment of study quality, two critical bias factors emerged: insufficient sample size and unappreciated sample frame. Insufficient sample size refers to studies with limited participants, hampering findings’ generalizability. With relatively lower prevalence for TB-COVID co-infection compared to individual TB or COVID-19, obtaining a sizeable co-infected cohort, especially where TB and COVID-19 are rarer, becomes challenging. Limited sample size may curtail statistical power and precision, potentially biasing prevalence estimates. Unappreciated sample frame denotes studies unintentionally selecting populations misrepresenting the target group. Poorly described sampling or inclusion criteria misaligned with intended population characteristics can lead to biases. In TB-COVID co-infection, ensuring representation of individuals with both conditions, not biased subgroups, is vital. Incorrect sample framing may introduce biases and limit findings’ applicability.

While we recognize that a randomized controlled trial (RCT) stands as the gold standard for investigating treatments or risk factors, we contend that diverse study designs can offer valuable contributions to this field. In light of our current findings, we advocate for the consideration of a comparable sampling frame, such as the utilization of propensity score matched sampling in future studies. This approach allows for the creation of balanced groups, resembling the random assignment achieved in an RCT, thus minimizing selection bias and improving the internal validity of observational studies. Furthermore, we propose a more comprehensive description of patients’ baseline conditions and treatment regimens in subsequent research endeavors. This detailed information holds the potential to mitigate bias significantly. A thorough account of patients’ characteristics and treatment variables enhances the ability to control for confounding factors, providing a clearer understanding of the associations under investigation. Employing such strategies not only bolsters the robustness of observational studies but also facilitates the comparability of findings across different research designs.

Several limitations should be acknowledged in the interpretation of our findings. First, we did not include “comorbidity” as a keyword and MeSH term in the searching process, which might have resulted in the omission of relevant studies taking TB as a kind of comorbidity of COVID-19 patients. Second, the observational design precludes establishing causation, and although we employed rigorous statistical methods to control for confounding factors, residual confounders may persist. Third, the generalizability of our results may be influenced by the predominantly retrospective and multicentric nature of the included studies. Variability in healthcare settings, patient populations, diagnostic criteria, and treatment approaches across different regions and countries could impact the external validity of our findings. Additionally, the lack of uniformity in reporting across studies may have introduced inconsistencies in our data synthesis. Furthermore, the limited availability of detailed information on certain variables, such as socioeconomic status, comorbidities, and M . tuberculosis infection status, restricted our ability to conduct more granular subgroup analyses. As mentioned earlier, distinctions exist among latent, active, cured, and current M . tuberculosis infections. However, due to insufficient details, we faced considerable challenges in differentiating between these states. Finally, the evolving landscape of the COVID-19 pandemic and variations in healthcare infrastructure over time may have influenced treatment strategies and outcomes. Despite these limitations, our study provides valuable insights into the landscape of TB-COVID co-infection, emphasizing the need for further research to address these complexities comprehensively.

In conclusion, the fatality rate of co-infection declined gradually and still stayed higher than COVID-19 alone, underscoring the heightened vulnerability in co-infected individuals. Addressing this challenge requires targeted measures such as heightened awareness campaigns, improved screening strategies for TB infection, and the provision of comprehensive long COVID care for co-infected patients. Collaboration on a global scale may be beneficial in addressing the challenges posed by TB-COVID co-infection, particularly in regions with limited medical resources.

Supporting information

S1 table. the preferred reporting items for systematic reviews and meta-analyses (prisma) 2020 checklist..

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S2 Table. Search strategies to identify studies reporting the prevalence status, treatment and outcomes of tuberculosis and COVID-19.

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S3 Table. Studies reported prevalence rate (n = 2).

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S4 Table. Detailed basic information of included studies (n = 17).

Detailed basic information of included case reports (n = 17).

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S5 Table. The fatality rates of active and previous TB-COVID co-infection (n = 11).

The fatality rates of active TB-COVID co-infection (n = 11).

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S6 Table. The fatality rates of previous TB-COVID co-infection (n = 3).

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S7 Table. Quality assessment of each included study.

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S8 Table. Egger’s test on total fatality rate.

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S9 Table. Sensitives analysis on MA of total fatality rate.

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S10 Table. Egger’s test on MA of In-hospital fatality rate.

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S11 Table. Sensitives analysis on MA of In-hospital fatality rate.

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S12 Table. Egger’s test on MA of active/previous TB-COVID co-infection fatality rate.

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S13 Table. Sensitives analysis on MA of In-hospital fatality rate.

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S14 Table. Sensitives analysis on RR of in-hospital fatality between TB-COVID patients and single COVID patients.

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S1 Fig. Quality assessment of included studies (N = 17).

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S2 Fig. Egger’s test on MA of total fatality rate.

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S3 Fig. Sensitives analysis on MA of total fatality rate.

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S4 Fig. Egger’s test on MA of In-hospital fatality rate.

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S5 Fig. Sensitives analysis on MA of In-hospital fatality rate.

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S6 Fig. Egger’s test on MA of hospitalized Active TB-COVID co-infection patients fatality rate.

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S7 Fig. Sensitives analysis on MA of hospitalized Active TB-COVID co-infection patients fatality rate.

https://doi.org/10.1371/journal.pntd.0012136.s021

S8 Fig. Relative risk of in-hospital Fatality between TB-COVID co-infection and Single COVID-19 co-infection.

https://doi.org/10.1371/journal.pntd.0012136.s022

S9 Fig. Egger’s test on RR of in-hospital fatality between TB-COVID patients and single COVID patients.

https://doi.org/10.1371/journal.pntd.0012136.s023

S10 Fig. Sensitives analysis on RR of in-hospital fatality between TB-COVID patients and single COVID patients.

https://doi.org/10.1371/journal.pntd.0012136.s024

Acknowledgments

We would like to express our sincere thanks to Dr. Lusine Abrahamyan at University of Toronto for her kind help. We also want to present our best wishes to the front-line medical worker all over the world, and we believe their work of integrity and selflessness is key to ending the COVID-19 pandemic.

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Mycobacterium tuberculosis suppresses host antimicrobial peptides by dehydrogenating L-alanine

Affiliations.

• 1 Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
• 2 Department of Microbiology and Immunology, Tongji University School of Medicine, Shanghai, China.
• 3 Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
• 4 Clinical Translation Research Center, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China.
• 5 Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. [email protected].
• 6 Department of Microbiology and Immunology, Tongji University School of Medicine, Shanghai, China. [email protected].
• 7 Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. [email protected].
• 8 Clinical Translation Research Center, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. [email protected].
• 9 Shanghai Key Laboratory of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. [email protected].
• 10 Department of Microbiology and Immunology, Tongji University School of Medicine, Shanghai, China. [email protected].
• 11 Shanghai Clinic and Research Center of Tuberculosis, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China. [email protected].
• PMID: 38760394
• PMCID: PMC11101664
• DOI: 10.1038/s41467-024-48588-4

Antimicrobial peptides (AMPs), ancient scavengers of bacteria, are very poorly induced in macrophages infected by Mycobacterium tuberculosis (M. tuberculosis), but the underlying mechanism remains unknown. Here, we report that L-alanine interacts with PRSS1 and unfreezes the inhibitory effect of PRSS1 on the activation of NF-κB pathway to induce the expression of AMPs, but mycobacterial alanine dehydrogenase (Ald) Rv2780 hydrolyzes L-alanine and reduces the level of L-alanine in macrophages, thereby suppressing the expression of AMPs to facilitate survival of mycobacteria. Mechanistically, PRSS1 associates with TAK1 and disruptes the formation of TAK1/TAB1 complex to inhibit TAK1-mediated activation of NF-κB pathway, but interaction of L-alanine with PRSS1, disables PRSS1-mediated impairment on TAK1/TAB1 complex formation, thereby triggering the activation of NF-κB pathway to induce expression of AMPs. Moreover, deletion of antimicrobial peptide gene β-defensin 4 (Defb4) impairs the virulence by Rv2780 during infection in mice. Both L-alanine and the Rv2780 inhibitor, GWP-042, exhibits excellent inhibitory activity against M. tuberculosis infection in vivo. Our findings identify a previously unrecognized mechanism that M. tuberculosis uses its own alanine dehydrogenase to suppress host immunity, and provide insights relevant to the development of effective immunomodulators that target M. tuberculosis.

© 2024. The Author(s).

• Alanine Dehydrogenase / genetics
• Alanine Dehydrogenase / metabolism
• Alanine* / metabolism
• Antimicrobial Peptides* / genetics
• Antimicrobial Peptides* / metabolism
• Bacterial Proteins / genetics
• Bacterial Proteins / metabolism
• MAP Kinase Kinase Kinases / genetics
• MAP Kinase Kinase Kinases / metabolism
• Macrophages* / immunology
• Macrophages* / metabolism
• Macrophages* / microbiology
• Mice, Inbred C57BL
• Mycobacterium tuberculosis* / metabolism
• Mycobacterium tuberculosis* / pathogenicity
• NF-kappa B* / metabolism
• RAW 264.7 Cells
• Signal Transduction
• Tuberculosis* / immunology
• Tuberculosis* / microbiology
• MAP kinase kinase kinase 7

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Clinical Symptoms of Tuberculosis

• Most individuals with tuberculosis (TB) disease have one or more symptoms.

Symptoms of TB disease may vary depending on the part of the body affected.

Why TB Patients Seek Medical Care

Usually, TB disease is diagnosed when someone with symptoms seeks medical care.

In a few instances, TB disease can be diagnosed when someone is receiving care for an unrelated problem, such as when trauma is evaluated with a chest radiograph that unexpectedly indicates TB in the lungs. In other instances, TB disease can be diagnosed after recent infection, as part of a TB contact investigation.

The onset of TB disease is usually gradual. A rapid onset is rare and may be related to an immune deficiency.

Usually, the symptoms are mild at first, developing slowly. A patient might blame the symptoms on something common, like allergies for cough or daily stresses for low energy. The symptoms might be present for weeks or months before reaching a tipping point that convinces the patient to seek medical care.

TB disease is not as common in the United States as it was many years ago. Health care providers might not consider the possibility of TB disease when evaluating patients who have symptoms. As a result, the diagnosis of TB disease may be delayed or even overlooked, and the patient may remain ill and possibly infectious for a prolonged period.

Some symptoms of TB disease, like cough or weight loss, can be the same as the symptoms of other diseases. These symptoms should prompt heath care providers to consider TB disease, especially after more common problems are ruled out.

Common symptoms

Symptoms of tb disease (in any part of the body).

Some general, systemic symptoms are common to TB in any part of the body:

• Night sweats
• Weight loss
• Loss of appetite
• Sense of illness or loss of energy

Symptoms of pulmonary TB disease

TB disease most commonly affect the lungs (pulmonary TB disease). Most cases of TB disease are pulmonary.

Symptoms of pulmonary disease include:

• Cough (especially lasting for 3 weeks or longer)
• Coughing up sputum or blood (hemoptysis)
• Shortness of breath

Symptoms of extrapulmonary TB disease

Extrapulmonary TB disease affects organs in addition to or instead of the lungs. It may cause symptoms related to the part of the body that is affected.

Symptoms of extrapulmonary TB disease include:

• Blood in the urine (may indicate TB disease of the kidney)
• Headache or confusion (may indicate TB meningitis)
• Back pain (may indicate TB disease of the spine)
• Hoarseness (may indicate TB disease of the larynx)
• Swollen glands (may indicate TB disease of the lymph nodes)
• Swollen, painful joint (may indicate TB disease of the bone or cartilage)

Extrapulmonary TB disease should be considered in the differential diagnosis of ill persons who have systemic symptoms and who are at high risk for TB disease.

Core Curriculum on Tuberculosis: What the Clinician Should Know

Self-Study Modules on Tuberculosis

Tuberculosis (TB)

Tuberculosis is caused by bacteria called Mycobacterium tuberculosis . The bacteria usually attack the lungs but can attack any part of the body.

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