Cross-sectional Whole-genome Sequencing and Epidemiological Study of Multidrug-resistant Mycobacterium tuberculosis in China

Enhanced diagnosis of multi-drug-resistant microbes using group association modeling and machine learning

New solutions are needed to detect genotype-phenotype associations involved in microbial drug resistance. Herein, we describe a Group Association Model (GAM) that accurately identifies genetic variants linked to drug resistance and mitigates false-positive cross-resistance artifacts without prior knowledge. GAM analysis of 7,179 Mycobacterium tuberculosis (Mtb) isolates identifies gene targets for all analyzed drugs, revealing comparable performance but fewer cross-resistance artifacts than World Health Organization (WHO) mutation catalogue approach, which requires expert rules and precedents. GAM also reveals generalizability, demonstrating high predictive accuracy with 3,942 S. aureus isolates. GAM refinement by machine learning (ML) improves predictive accuracy with small or incomplete datasets. These findings were validated using 427 Mtb isolates from three sites, where GAM inputs are also found to be more suitable in ML prediction models than WHO inputs. GAM + ML could thus address the limitations of current drug resistance prediction methods to improve treatment decisions for drug-resistant microbial infections.

Drug Resistance and Epidemiological Success of Modern Mycobacterium tuberculosis Lineages in Western India

BACKGROUND

Drivers of tuberculosis (TB) transmission in India, the country estimated to carry a quarter of the world's burden, are not well studied. We conducted a genomic epidemiology study to compare epidemiological success, host factors, and drug resistance among the 4 major Mycobacterium tuberculosis (Mtb) lineages (L1-L4) circulating in Pune, India.

METHODS

We performed whole-genome sequencing (WGS) of Mtb sputum culture-positive isolates from participants in two prospective cohort studies and predicted genotypic susceptibility using a validated random forest model. We compared lineage-specific phylogenetic and time-scaled metrics to assess epidemiological success.

RESULTS

Of the 612 isolates that met sequence quality criteria, Most were L3 (44.6%). The majority (61.1%) of multidrug-resistant isolates were L2 (P < .001) and L2 demonstrated a higher rate and more recent resistance acquisition. L4 and/or L2 demonstrated higher clustering and time-scaled haplotypic density (THD) compared to L3 and/or L1, suggesting higher epidemiological success. L4 demonstrated higher THD and clustering (odds ratio, 5.1 [95% confidence interval, 2.3-12.3]) in multivariate models controlling for host factors and resistance.

CONCLUSIONS

L2 shows a higher frequency of resistance, and both L2 and L4 demonstrate evidence of higher epidemiological success than L3 or L1 in Pune. Contact tracing around TB cases and heightened surveillance of TB DR in India is a public health priority.

Genomic analysis of lineage-specific transmission of multidrug resistance tuberculosis in China

OBJECTIVES

We investigated the genetic diversities and lineage-specific transmission dynamics of multidrug-resistant tuberculosis (MDR-TB), with the goal of determining the potential factors driving the MDR epidemics in China.

METHODS

We curated a large nationwide Mycobacterium tuberculosis (M. tuberculosis) whole genome sequence data set, including 1313 MDR strains. We reconstructed the phylogeny and mapped the transmission networks of MDR-TB across China using Bayesian inference. To identify drug-resistance variants linked to enhanced transmissibility, we employed ordinary least-squares (OLS) regression analysis.

RESULT

The majority of MDR-TB strains in China belong to lineage 2.2.1. Transmission chain analysis has indicated that the repeated and frequent transmission of L2.2.1 plays a central role in the establishment of MDR epidemic in China, but no occurrence of a large predominant MDR outbreak was detected. Using OLS regression, the most common single nucleotide polymorphisms (SNPs) associated with resistance to isoniazid (katG_p.Ser315Thr and katG_p.Ser315Asn) and rifampicin (rpoB_p.Ser450Leu, rpoB_p.His445Tyr, rpoB_p.His445Arg, rpoB_p.His445Asp, and rpoB_p.His445Asn) were more likely to be found in L2 clustered strains. Several putative compensatory mutations in rpoA, rpoC, and katG were significantly associated with clustering. The eastern, central, and southern regions of China had a high level of connectivity for the migration of L2 MDR strains throughout the country. The skyline plot showed distinct population size expansion dynamics for MDR-TB lineages in China.

CONCLUSION

MDR-TB epidemic in China is predominantly driven by the spread of highly transmissible Beijing strains. A range of drug-resistance mutations of L2 MDR-TB strains displayed minimal fitness costs and may facilitate their transmission.

Association between toxin-antitoxin system mutations and global transmission of MDR-TB

BACKGROUND

The emergence of Multidrug-Resistant Tuberculosis (MDR-TB) poses a significant threat to global tuberculosis control efforts. This study aimed to examine the influence of mutations in Toxin-Antitoxin system genes on the global transmission of MDR-TB caused by Mycobacterium tuberculosis (M. tuberculosis).

METHODS

Whole-genome sequencing was conducted on 13,518 M. tuberculosis isolates. Genes of the Toxin-Antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Techniques such as Random Forest, Gradient Boosting Decision Tree, and Generalized Linear Mixed Models were employed to identify mutation sites in Toxin-Antitoxin system-related genes that facilitated the transmission of MDR-TB.

RESULTS

4,066 (30.08%) were identified as MDR-TB strains of all analyzed isolates. We found significant associations between specific gene mutations and MDR-TB transmission clusters including mutations in Rv0298 (G213A), Rv1959c (parE1, C88T), Rv1960c (parD1, C134T), Rv1991A (maze, G156A), Rv2547 (vapB, C54G), Rv2862A (vapB23, T2C), and Rv3385c (vapB46, G70A). Additionally, several gene mutations associated with MDR-TB transmission clades such as Rv1956 (higA, G445T), Rv1960c (parD1, C134T), and Rv1962A (vapB35, G99A) were noted. Certain gene mutations including vapB35 (G99A), higA (G445T), and parD1 (C134T) correlated with cross-regional transmission clades.

CONCLUSION

This study highlights the significant association between specific gene mutations in the Toxin-Antitoxin system and the global transmission of MDR-TB, providing valuable insights for developing targeted interventions to control MDR-TB.

A Profile of Drug-Resistant Mutations in Mycobacterium tuberculosis Isolates from Guangdong Province, China

Guangdong Province, China's largest economy, has a high incidence of tuberculosis (TB). At present, there are few reports on the distribution, transmission and drug resistance of Mycobacterium tuberculosis (Mtb) strains in this region. In this study, we performed minimum inhibitory concentration testing for 14 anti-TB drugs and whole-genome sequencing of 713 clinical Mtb isolates from 20,662 sputum culture-positive tuberculosis patients registered at 31 tuberculosis drug resistance surveillance sites covering 20 cities in Guangdong Province from 2016 to 2018. Moreover, we evaluated genome-wide associations between mutations and drug resistance, and further investigated the differences in the MICs of mutations. The epidemiology, drug-resistant phenotypes and whole genome sequencing data of 713 clinical Mtb isolates were analyzed, revealing the lineage distribution and drug-resistant gene profiles in Guangdong Province. WGS combined with quantitative MIC measurements identified several novel loci associated with resistance, of which 16 loci were found to be related to resistance to more than one drug. This study analyzed the lineage distribution, prevalence characteristics and resistance-corresponding gene profiles of Mtb isolates in Guangdong province, and provided a theoretical basis for the formulation of tuberculosis prevention and control policy in the province.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12088-024-01236-3.

Association of mutations in Mycobacterium tuberculosis complex (MTBC) respiration chain genes with hyper-transmission

BACKGROUND

The respiratory chain plays a key role in the growth of Mycobacterium tuberculosis complex (MTBC). However, the exact regulatory mechanisms of this system still need to be elucidated, and only a few studies have investigated the impact of genetic mutations within the respiratory chain on MTBC transmission. This study aims to explore the impact of respiratory chain gene mutations on the global spread of MTBC.

RESULTS

A total of 13,402 isolates of MTBC were included in this study. The majority of the isolates (n = 6,382, 47.62%) belonged to lineage 4, followed by lineage 2 (n = 5,123, 38.23%). Our findings revealed significant associations between Single Nucleotide Polymorphisms (SNPs) of specific genes and transmission clusters. These SNPs include Rv0087 (hycE, G178T), Rv1307 (atpH, C650T), Rv2195 (qcrA, G181C), Rv2196 (qcrB, G1250T), Rv3145 (nuoA, C35T), Rv3149 (nuoE, G121C), Rv3150 (nuoF, G700A), Rv3151 (nuoG, A1810G), Rv3152 (nuoH, G493A), and Rv3157 (nuoM, A1243G). Furthermore, our results showed that the SNPs of atpH C73G, atpA G271C, qcrA G181C, nuoJ G115A, nuoM G772A, and nuoN G1084T were positively correlated with cross-country transmission clades and cross-regional transmission clades.

CONCLUSIONS

Our study uncovered an association between mutations in respiratory chain genes and the transmission of MTBC. This important finding provides new insights for future research and will help to further explore new mechanisms of MTBC pathogenicity. By uncovering this association, we gain a more complete understanding of the processes by which MTBC increases virulence and spread, providing potential targets and strategies for preventing and treating tuberculosis.

Toxin-antitoxin system gene mutations driving Mycobacterium tuberculosis transmission revealed by whole genome sequencing

Background

The toxin-antitoxin (TA) system plays a vital role in the virulence and pathogenicity of Mycobacterium tuberculosis (M. tuberculosis). However, the regulatory mechanisms and the impact of gene mutations on M. tuberculosis transmission remain poorly understood.

Objective

To investigate the influence of gene mutations in the toxin-antitoxin system on M. tuberculosis transmission dynamics.

Method

We performed whole-genome sequencing on the analyzed strains of M. tuberculosis. The genes associated with the toxin-antitoxin system were obtained from the National Center for Biotechnology Information (NCBI) Gene database. Mutations correlating with enhanced transmission within the genes were identified by using random forest, gradient boosting decision tree, and generalized linear mixed models.

Results

A total of 13,518 M. tuberculosis isolates were analyzed, with 42.29% (n = 5,717) found to be part of genomic clusters. Lineage 4 accounted for the majority of isolates (n = 6488, 48%), followed by lineage 2 (n = 5133, 37.97%). 23 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, including vapB1 G34A, vapB24 A76C, vapB2 T171C, mazF2 C85T, mazE2 G104A, vapB31 T112C, relB T226A, vapB11 C54T, mazE5 T344C, vapB14 A29G, parE1 (C103T, C88T), and parD1 C134T. Six SNPs, including vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, Rv2653c A80C, and vapB22 C167T, were associated with transmission clades across different countries. Notably, our findings highlighted the positive association of vapB6 A29C, vapB31 T112C, parD1 C134T, vapB37 G205C, vapB19 C188T, and Rv2653c A80C with transmission clades across diverse regions. Furthermore, our analysis identified 32 SNPs that exhibited significant associations with clade size.

Conclusion

Our study presents potential associations between mutations in genes related to the toxin-antitoxin system and the transmission dynamics of M. tuberculosis. However, it is important to acknowledge the presence of confounding factors and limitations in our study. Further research is required to establish causation and assess the functional significance of these mutations. These findings provide a foundation for future investigations and the formulation of strategies aimed at controlling TB transmission.

Apramycin has high in vitro activity against Mycobacterium tuberculosis

Introduction. Aminoglycoside antibiotics such as amikacin and kanamycin are important components in the treatment of Mycobacterium tuberculosis (Mtb) infection. However, more and more clinical strains are found to be aminoglycoside antibiotic-resistant. Apramycin is another kind of aminoglycoside antibiotic that is commonly used to treat infections in animals.Hypothesis. Apramycin may have in vitro activity against Mtb.Aim. This study aims to evaluate the efficacy of apramycin against Mtb in vitro and determine its epidemiological cut-off (ECOFF) value.Methodology. One hundred Mtb isolates, including 17 pansusceptible and 83 drug-resistant tuberculosis (DR-TB) strains, were analysed for apramycin resistance using the MIC assay.Results. Apramycin exhibited significant inhibitory activity against Mtb clinical isolates, with an MIC50 of 0.5 μg ml-1 and an MIC90 of 1 μg ml-1. We determined the tentative ECOFF value as 1 µg ml-1 for apramycin. The resistant rates of multidrug-resistant tuberculosis (MDR-TB), pre-extensively drug-resistant (pre-XDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) strains were 12.12 % (4/33), 20.69 % (6/29) and 66.67 % (14/21), respectively. The rrs gene A1401G is associated with apramycin resistance, as well as the cross-resistance between apramycin and other aminoglycosides.Conclusion. Apramycin shows high in vitro activity against the Mtb clinical isolates, especially the MDR-TB clinical isolates. This encouraging discovery calls for more research on the functions of apramycin in vivo and as a possible antibiotic for the treatment of drug-resistant TB.

Spread of antibiotic resistance genes in drinking water reservoirs: Insights from a deep metagenomic study using a curated database

The exploration of antibiotic resistance genes (ARGs) in drinking water reservoirs is an emerging field. Using a curated database, we enhanced the ARG detection and conducted a comprehensive analysis using 2.2 Tb of deep metagenomic sequencing data to determine the distribution of ARGs across 16 drinking water reservoirs and associated environments. Our findings reveal a greater diversity of ARGs in sediments than in water, underscoring the importance of extensive background surveys. Crucial ARG carriers-specifically Acinetobacter, Pseudomonas, and Mycobacterium were identified in drinking water reservoirs. Extensive analysis of the data uncovered a considerable concern for drinking water safety, particularly in regions reliant on river sources. Mobile genetic elements have been found to contribute markedly to the propagation of ARGs. The results of this research suggest that the establishment of drinking water reservoirs for supplying raw water may be an effective strategy for alleviating the spread of water-mediated ARGs.

Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR'-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M. tuberculosis samples. We performed association analysis (Fisher's exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR'-ahpC (N = 7) that were considered either 'highly likely' or 'likely' to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Iron-related gene mutations driving global Mycobacterium tuberculosis transmission revealed by whole-genome sequencing

BACKGROUND

Iron plays a crucial role in the growth of Mycobacterium tuberculosis (M. tuberculosis). However, the precise regulatory mechanism governing this system requires further elucidation. Additionally, limited studies have examined the impact of gene mutations related to iron on the transmission of M. tuberculosis globally. This research aims to investigate the correlation between mutations in iron-related genes and the worldwide transmission of M. tuberculosis.

RESULTS

A total of 13,532 isolates of M. tuberculosis were included in this study. Among them, 6,104 (45.11%) were identified as genomic clustered isolates, while 8,395 (62.04%) were classified as genomic clade isolates. Our results showed that a total of 12 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, such as Rv1469 (ctpD, C758T), Rv3703c (etgB, G1122T), and Rv3743c (ctpJ, G676C). Additionally, seven SNPs, including Rv0104 (T167G, T478G), Rv0211 (pckA, A302C), Rv0283 (eccB3, C423T), Rv1436 (gap, G654T), ctpD C758T, and etgB C578A, demonstrated a positive correlation with transmission clades across different countries. Notably, our findings highlighted the positive association of Rv0104 T167G, pckA A302C, eccB3 C423T, ctpD C758T, and etgB C578A with transmission clades across diverse regions. Furthermore, our analysis identified 78 SNPs that exhibited significant associations with clade size.

CONCLUSIONS

Our study reveals the link between iron-related gene SNPs and M. tuberculosis transmission, offering insights into crucial factors influencing the pathogenicity of the disease. This research holds promise for targeted strategies in prevention and treatment, advancing research and interventions in this field.

Transmission dynamics and phylogeography of Mycobacterium tuberculosis in China based on whole-genome phylogenetic analysis

OBJECTIVES

This study aimed to describe the lineage-specific transmissibility and epidemiological migration of Mycobacterium tuberculosis in China.

METHODS

We curated a large set of whole-genome sequences from 3204 M. tuberculosis isolates, including thousands of newly sequenced genomes, and applied a series of metrics to compare the transmissibility of M. tuberculosis strains between lineages and sublineages. The countrywide transmission patterns of major lineages were explored.

RESULTS

We found that lineage 2 (L2) was the most prevalent lineage in China (85.7%), with the major sublineage 2.2.1 (80.9%), followed by lineage 4 (L4) (13.8%), which comprises major sublineages 4.2 (1.5%), 4.4 (6.2%) and 4.5 (5.8%). We showed evidence for frequent cross-regional spread and large cluster formation of L2.2.1 strains, whereas L4 strains were relatively geographically restricted in China. Next, we applied a series of genomic indices to evaluate M. tuberculosis strain transmissibility and uncovered higher transmissibility of L2.2.1 compared with the L2.2.2 and L4 sublineages. Phylogeographic analysis showed that southern, eastern, and northern China were highly connected regions for countrywide L2.2.1 strain spread.

CONCLUSIONS

The present study provides insights into the different transmission and migration patterns of the major M. tuberculosis lineages in China and highlights that transmissible L2.2.1 is a threat to tuberculosis control.

Polyketide synthases mutation in tuberculosis transmission revealed by whole genomic sequence, China, 2011-2019

Introduction: Tuberculosis (TB) is an infectious disease caused by a bacterium called Mycobacterium tuberculosis (Mtb). Previous studies have primarily focused on the transmissibility of multidrug-resistant (MDR) or extensively drug-resistant (XDR) Mtb. However, variations in virulence across Mtb lineages may also account for differences in transmissibility. In Mtb, polyketide synthase (PKS) genes encode large multifunctional proteins which have been shown to be major mycobacterial virulence factors. Therefore, this study aimed to identify the role of PKS mutations in TB transmission and assess its risk and characteristics. Methods: Whole genome sequences (WGSs) data from 3,204 Mtb isolates was collected from 2011 to 2019 in China. Whole genome single nucleotide polymorphism (SNP) profiles were used for phylogenetic tree analysis. Putative transmission clusters (≤10 SNPs) were identified. To identify the role of PKS mutations in TB transmission, we compared SNPs in the PKS gene region between "clustered isolates" and "non-clustered isolates" in different lineages. Results: Cluster-associated mutations in ppsA, pks12, and pks13 were identified among different lineage isolates. They were statistically significant among clustered strains, indicating that they may enhance the transmissibility of Mtb. Conclusion: Overall, this study provides new insights into the function of PKS and its localization in M. tuberculosis. The study found that ppsA, pks12, and pks13 may contribute to disease progression and higher transmission of certain strains. We also discussed the prospective use of mutant ppsA, pks12, and pks13 genes as drug targets.

Association between fatty acid metabolism gene mutations and Mycobacterium tuberculosis transmission revealed by whole genome sequencing

BACKGROUND

Fatty acid metabolism greatly promotes the virulence and pathogenicity of Mycobacterium tuberculosis (M.tb). However, the regulatory mechanism of fatty acid metabolism in M.tb remains to be elucidated, and limited evidence about the effects of gene mutations in fatty acid metabolism on the transmission of M.tb was reported.

RESULTS

Overall, a total of 3193 M.tb isolates were included in the study, of which 1596 (50%) were genomic clustered isolates. Most of the tuberculosis isolates belonged to lineage2(n = 2744,85.93%), followed by lineage4(n = 439,13.75%) and lineage3(n = 10,0.31%).Regression results showed that the mutations of gca (136,605, 317G > C, Arg106Pro; OR, 22.144; 95% CI, 2.591-189.272), ogt(1,477,346, 286G > C ,Gly96Arg; OR, 3.893; 95%CI, 1.432-10.583), and rpsA (1,834,776, 1235 C > T, Ala412Val; OR, 3.674; 95% CI, 1.217-11.091) were significantly associated with clustering; mutations in gca and rpsA were also significantly associated with clustering of lineage2. Mutation in arsA(3,001,498, 885 C > G, Thr295Thr; OR, 6.278; 95% CI, 2.508-15.711) was significantly associated with cross-regional clusters. We also found that 20 mutation sites were positively correlated with cluster size, while 11 fatty acid mutation sites were negatively correlated with cluster size.

CONCLUSION

Our research results suggested that mutations in genes related to fatty acid metabolism were related to the transmission of M.tb. This research could help in the future control of the transmission of M.tb.

Association between two-component systems gene mutation and Mycobacterium tuberculosis transmission revealed by whole genome sequencing

BACKGROUND

Two-component systems (TCSs) assume a pivotal function in Mycobacterium tuberculosis (M.tuberculosis) growth. However, the exact regulatory mechanism of this system needs to be elucidated, and only a few studies have investigated the effect of gene mutations within TCSs on M.tuberculosis transmission. This research explored the relationship between TCSs gene mutation and the global transmission of (M.tuberculosis).

RESULTS

A total of 13531 M.tuberculosis strains were enrolled in the study. Most of the M.tuberculosis strains belonged to lineage4 (n=6497,48.0%), followed by lineage2 (n=5136,38.0%). Our results showed that a total of 36 single nucleotide polymorphisms (SNPs) were positively correlated with clustering of lineage2, such as Rv0758 (phoR, C820G), Rv1747(T1102C), and Rv1057(C1168T). A total of 30 SNPs showed positive correlation with clustering of lineage4, such as phoR(C182A, C1184G, C662T, T758G), Rv3764c (tcrY, G1151T), and Rv1747 C20T. A total of 19 SNPs were positively correlated with cross-country transmission of lineage2, such as phoR A575C, Rv1028c (kdpD, G383T, G1246C), and Rv1057 G817T. A total of 41 SNPs were positively correlated with cross-country transmission of lineage4, such as phoR(T758G, T327G, C284G), kdpD(G1755A, G625C), Rv1057 C980T, and Rv1747 T373G.

CONCLUSIONS

Our study identified that SNPs in genes of two-component systems were related to the transmission of M. tuberculosis. This finding adds another layer of complexity to M. tuberculosis virulence and provides insight into future research that will help to elucidate a novel mechanism of M. tuberculosis pathogenicity.

Whole genome sequencing of drug resistance Mycobacterium tuberculosis from extra-pulmonary sites

This study aimed to determinate characteristics of drug resistance Mycobacterium tuberculosis from patients with extra-pulmonary tuberculosis (EPTB). Patients were retrospectively studied from January 2020 to December 2021. All the isolates were cultured, tested drug susceptibility, and detected the gene mutation using whole genome sequencing. The correlations of whole genome sequencing, pattern of DR, patients' distribution, and transmission were analyzed. 111 DR-EPTB isolates included pre-XDR-TB (53.2%), MDR-TB (29.7%), and poly-DR-TB (12.6%). The resistant drugs were INH followed by RFP and SM. The genotypes of 111 strains were lineage 2 and lineage 4. KatG_p.Ser315Thr was main gene mutation for resistance to INH; rpsL_p.Lys43Arg for SM, rpoB_p.Ser450Leu for rifampicin, embB_p.Met306Val for ethambutol, gyrA_p.Asp94Gly for FQs, and pncA_p.Thr76Pro for PZA. The residence was a significant risk factor for cluster transmission by patients and phenotypic DR types of strains for lineage 2 transmission. In the local area of southwest China INH, rifampicin and SM were main drugs in patients with DR-EPTB. KatG_p.Ser315, rpoB_p.Ser450Leu, and rpsL_p.Lys43Arg were main gene mutations. Phenotypic DR types and residence were main risk of transmission.

Proteomic analyses of smear-positive/negative tuberculosis patients uncover differential antigen-presenting cell activation and lipid metabolism

Background

Tuberculosis (TB) remains a major global health concern, ranking as the second most lethal infectious disease following COVID-19. Smear-Negative Pulmonary Tuberculosis (SNPT) and Smear-Positive Pulmonary Tuberculosis (SPPT) are two common types of pulmonary tuberculosis characterized by distinct bacterial loads. To date, the precise molecular mechanisms underlying the differences between SNPT and SPPT patients remain unclear. In this study, we aimed to utilize proteomics analysis for identifying specific protein signatures in the plasma of SPPT and SNPT patients and further elucidate the molecular mechanisms contributing to different disease pathogenesis.

Methods

Plasma samples from 27 SPPT, 37 SNPT patients and 36 controls were collected and subjected to TMT-labeled quantitative proteomic analyses and targeted GC-MS-based lipidomic analysis. Ingenuity Pathway Analysis (IPA) was then performed to uncover enriched pathways and functionals of differentially expressed proteins.

Results

Proteomic analysis uncovered differential protein expression profiles among the SPPT, SNPT, and Ctrl groups, demonstrating dysfunctional immune response and metabolism in both SPPT and SNPT patients. Both groups exhibited activated innate immune responses and inhibited fatty acid metabolism, but SPPT patients displayed stronger innate immune activation and lipid metabolic inhibition compared to SNPT patients. Notably, our analysis uncovered activated antigen-presenting cells (APCs) in SNPT patients but inhibited APCs in SPPT patients, suggesting their critical role in determining different bacterial loads/phenotypes in SNPT and SPPT. Furthermore, some specific proteins were detected to be involved in the APC activation/acquired immune response, providing some promising therapeutic targets for TB.

Conclusion

Our study provides valuable insights into the differential molecular mechanisms underlying SNPT and SPPT, reveals the critical role of antigen-presenting cell activation in SNPT for effectively clearing the majority of Mtb in bodies, and shows the possibility of APC activation as a novel TB treatment strategy.

Insight into the drug-resistant characteristics and genetic diversity of multidrug-resistant Mycobacterium tuberculosis in China

Multidrug-resistant tuberculosis (MDR-TB) has a severe impact on public health. To investigate the drug-resistant profile, compensatory mutations and genetic variations among MDR-TB isolates, a total of 546 MDR-TB isolates from China underwent drug-susceptibility testing and whole genome sequencing for further analysis. The results showed that our isolates have a high rate of fluoroquinolone resistance (45.60%, 249/546) and a low proportion of conferring resistance to bedaquiline, clofazimine, linezolid, and delamanid. The majority of MDR-TB isolates (77.66%, 424/546) belong to Lineage 2.2.1, followed by Lineage 4.5 (6.41%, 35/546), and the Lineage 2 isolates have a strong association with pre-XDR/XDR-TB (P < 0.05) in our study. Epidemic success analysis using time-scaled haplotypic density (THD) showed that clustered isolates outperformed non-clustered isolates. Compensatory mutations happened in rpoA, rpoC, and non-RRDR of rpoB genes, which were found more frequently in clusters and were associated with the increase of THD index, suggesting that increased bacterial fitness was associated with MDR-TB transmission. In addition, the variants in resistance associated genes in MDR isolates are mainly focused on single nucleotide polymorphism mutations, and only a few genes have indel variants, such as katG, ethA. We also found some genes underwent indel variation correlated with the lineage and sub-lineage of isolates, suggesting the selective evolution of different lineage isolates. Thus, this analysis of the characterization and genetic diversity of MDR isolates would be helpful in developing effective strategies for treatment regimens and tailoring public interventions. IMPORTANCE Multidrug-resistant tuberculosis (MDR-TB) is a serious obstacle to tuberculosis prevention and control in China. This study provides insight into the drug-resistant characteristics of MDR combined with phenotypic drug-susceptibility testing and whole genome sequencing. The compensatory mutations and epidemic success analysis were analyzed by time-scaled haplotypic density (THD) method, suggesting clustered isolates and compensatory mutations are associated with MDR-TB transmission. In addition, the insertion and deletion variants happened in some genes, which are associated with the lineage and sub-lineage of isolates, such as the mpt64 gene. This study offered a valuable reference and increased understanding of MDR-TB in China, which could be crucial for achieving the objective of precision medicine in the prevention and treatment of MDR-TB.

Drug resistance prediction for Mycobacterium tuberculosis with reference graphs

Tuberculosis is a global pandemic disease with a rising burden of antimicrobial resistance. As a result, the World Health Organization (WHO) has a goal of enabling universal access to drug susceptibility testing (DST). Given the slowness of and infrastructure requirements for phenotypic DST, whole-genome sequencing, followed by genotype-based prediction of DST, now provides a route to achieving this. Since a central component of genotypic DST is to detect the presence of any known resistance-causing mutations, a natural approach is to use a reference graph that allows encoding of known variation. We have developed DrPRG (Drug resistance Prediction with Reference Graphs) using the bacterial reference graph method Pandora. First, we outline the construction of a Mycobacterium tuberculosis drug resistance reference graph. The graph is built from a global dataset of isolates with varying drug susceptibility profiles, thus capturing common and rare resistance- and susceptible-associated haplotypes. We benchmark DrPRG against the existing graph-based tool Mykrobe and the haplotype-based approach of TBProfiler using 44 709 and 138 publicly available Illumina and Nanopore samples with associated phenotypes. We find that DrPRG has significantly improved sensitivity and specificity for some drugs compared to these tools, with no significant decreases. It uses significantly less computational memory than both tools, and provides significantly faster runtimes, except when runtime is compared to Mykrobe with Nanopore data. We discover and discuss novel insights into resistance-conferring variation for M. tuberculosis - including deletion of genes katG and pncA - and suggest mutations that may warrant reclassification as associated with resistance.

pncA Large Deletion is the Characteristic of Pyrazinamide-Resistant Mycobacterium tuberculosis belonging to the East Asian Lineage

BACKGROUND

Pyrazinamide (PZA) is often used as an add-on agent in the treatment of multidrug-resistant tuberculosis, regardless of phenotypic drug susceptibility testing (pDST) results. However, evaluating the effectiveness of PZA is challenging because of its low pH activity, which can result in unreliable pDST results. This study aimed to investigate the genomic characteristics associated with PZA resistance that can be used to develop genotypic DST.

MATERIALS AND METHODS

A publicly available whole genome sequencing (WGS) dataset of 10,725 Mycobacterium tuberculosis complex genomes (3,326 phenotypically PZA-resistant and 7,399 phenotypically PZA-susceptible isolates) were analyzed.

RESULTS

In total, 2,934 pncA non-silent mutations were identified in 2,880 isolates (26.9%). Detected mutations were found throughout the entire coding region of pncA in a scattered pattern, of which the most frequent mutation was p.Q10P (n = 278), followed by p.H57D (n = 167) and c.-11A>G (n = 122). The sensitivity and specificity of the group 1 or 2 mutations reported by the World Health Organization (WHO) mutational catalogue were 73.0% and 98.9%, respectively. We further identified 18 novel pncA mutations that were significantly associated with phenotypically PZA-resistant. In addition to these mutations, we identified 102 large deletions in the pncA gene, and all but two isolates were phenotypically resistant to PZA isolates. Notably, pncA deletions were mutually exclusive to pncA mutations, and more than half of the isolates with pncA large deletions belonged to the East Asian lineage (67.6%). The sensitivity, specificity, positive predictive value, and negative predictive value of the pooled variants (group 1 or 2 mutations, novel resistance-associated mutations, and large deletions of the pncA gene) were 79.0%, 98.9%, 97.0%, and 91.3%, respectively. The area under the curve (AUC) value for the pooled variants was significantly higher than the AUC value for the group 1 or 2 mutations (P <0.001), indicating that the pooled variants have a better discriminative ability for predicting PZA resistance.

CONCLUSION

Using WGS, we found that the pncA mutations are scattered without specific mutational hotspots, and large deletions associated with PZA resistance are more common in the East Asian lineage of M. tuberculosis isolates. Our data also demonstrated the reliability of group 1 or 2 mutations presented in the WHO mutation catalogue and the need for further investigation on group 3 mutations, contributing to the evaluation of the current knowledge base on mutations associated with the PZA-resistant M. tuberculosis complex.

Structural insights into RNase J that plays an essential role in Mycobacterium tuberculosis RNA metabolism

Ribonucleases (RNases) are responsible for RNA metabolism. RNase J, the core enzyme of the RNA degradosome, plays an essential role in global mRNA decay. Emerging evidence showed that the RNase J of Mycobacterium tuberculosis (Mtb-RNase J) could be an excellent target for treating Mtb infection. Here, crystal structures of Mtb-RNase J in apo-state and complex with the single-strand RNA reveal the conformational change upon RNA binding and hydrolysis. Mtb-RNase J forms an active homodimer through the interactions between the β-CASP and the β-lactamase domain. Knockout of RNase J slows the growth rate and changes the colony morphologies and cell length in Mycobacterium smegmatis, which is restored by RNase J complementation. Finally, RNA-seq analysis shows that the knockout strain significantly changes the expression levels of 49 genes in metabolic pathways. Thus, our current study explores the structural basis of Mtb-RNase J and might provide a promising candidate in pharmacological treatment for tuberculosis.

Investigation of bedaquiline resistance and genetic mutations in multi-drug resistant Mycobacterium tuberculosis clinical isolates in Chongqing, China

BACKGROUND

To investigate the prevalence and molecular characterization of bedaquiline resistance among MDR-TB isolates collected from Chongqing, China.

METHODS

A total of 205 MDR-TB isolates were collected from Chongqing Tuberculosis Control Institute between March 2019 and June 2020. The MICs of BDQ were determined by microplate alamarblue assay. All strains were genotyped by melting curve spoligotyping, and were subjected to WGS.

RESULTS

Among the 205 MDR isolates, the resistance rate of BDQ was 4.4% (9/205). The 55 (26.8%) were from male patients and 50 (24.4%) were new cases. Furthermore, 81 (39.5%) of these patients exhibited lung cavitation, 13 (6.3%) patients afflicted with diabetes mellitus, and 170 (82.9%) isolates belonged to Beijing family. However, the distribution of BDQ resistant isolates showed no significant difference among these characteristics. Of the 86 OFX resistant isolates, 8 isolates were XDR (9.3%, 8/86). Six BDQ resistant isolates (66.7%, 6/9) and two BDQ susceptible isolates (1.0%, 2/196) carried mutations in Rv0678. A total of 4 mutations types were identified in BDQ resistant isolates, including mutation in A152G (50%, 3/6), T56C (16.7%, 1/6), GA492 insertion (16.7%, 1/6), and A274 insertion (16.7%, 1/6). BDQ showed excellent activity against MDR-TB in Chongqing.

CONCLUSIONS

BDQ showed excellent activity against MDR-TB in Chongqing. The resistance rate of BDQ was not related to demographic and clinical characteristics. Mutations in Rv0678 gene were the major mechanism to BDQ resistance, with A152G as the most common mutation type. WGS has a good popularize value and application prospect in the rapid detection of BDQ resistance.

The mutation rate of rpoB gene showed an upward trend with the increase of MIRU10, MIRU39 and QUB4156 repetitive number

BACKGROUND

Mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) is a frequently used typing method for identifying the Beijing genotype of Mycobacterium tuberculosis (Mtb), which is easily transformed into rifampicin (RIF) resistance. The RIF resistance of Mtb is considered to be highly related with the mutation of rpoB gene. Therefore, this study aimed to analyze the relationship between the repetitive number of MIRU loci and the mutation of rpoB gene.

METHODS

An open-source whole-genome sequencing data of Mtb was used to detect the mutation of rpoB gene and the repetitive number of MIRU loci by bioinformatics methods. Cochran-Armitage analysis was performed to analyze the trend of the rpoB gene mutation rate and the repetitive number of MIRU loci.

RESULTS

Among 357 rifampicin-resistant tuberculosis (RR-TB), 304 strains with mutated rpoB genes were detected, and 6 of 67 rifampicin susceptible strains were detected mutations. The rpoB gene mutational rate showed an upward trend with the increase of MIRU10, MIRU39, QUB4156 and MIRU16 repetitive number, but only the repetitive number of MIRU10, MRIU39 and QUB4156 were risk factors for rpoB gene mutation. The Hunter-Gaston discriminatory index (HGDI) of MIRU10 (0.65) and QUB4156 (0.62) was high in the overall sample, while MIRU39 (0.39) and MIRU16 (0.43) showed a moderate discriminatory Power.

CONCLUSION

The mutation rate of rpoB gene increases with the addition of repetitive numbers of MIRU10, QUB4156 and MIRU39 loci.

Combining metabolome and clinical indicators with machine learning provides some promising diagnostic markers to precisely detect smear-positive/negative pulmonary tuberculosis

Background

Tuberculosis (TB) had been the leading lethal infectious disease worldwide for a long time (2014–2019) until the COVID-19 global pandemic, and it is still one of the top 10 death causes worldwide. One important reason why there are so many TB patients and death cases in the world is because of the difficulties in precise diagnosis of TB using common detection methods, especially for some smear-negative pulmonary tuberculosis (SNPT) cases. The rapid development of metabolome and machine learning offers a great opportunity for precision diagnosis of TB. However, the metabolite biomarkers for the precision diagnosis of smear-positive and smear-negative pulmonary tuberculosis (SPPT/SNPT) remain to be uncovered. In this study, we combined metabolomics and clinical indicators with machine learning to screen out newly diagnostic biomarkers for the precise identification of SPPT and SNPT patients.

Methods

Untargeted plasma metabolomic profiling was performed for 27 SPPT patients, 37 SNPT patients and controls. The orthogonal partial least squares-discriminant analysis (OPLS-DA) was then conducted to screen differential metabolites among the three groups. Metabolite enriched pathways, random forest (RF), support vector machines (SVM) and multilayer perceptron neural network (MLP) were performed using Metaboanalyst 5.0, “caret” R package, “e1071” R package and “Tensorflow” Python package, respectively.

Results

Metabolomic analysis revealed significant enrichment of fatty acid and amino acid metabolites in the plasma of SPPT and SNPT patients, where SPPT samples showed a more serious dysfunction in fatty acid and amino acid metabolisms. Further RF analysis revealed four optimized diagnostic biomarker combinations including ten features (two lipid/lipid-like molecules and seven organic acids/derivatives, and one clinical indicator) for the identification of SPPT, SNPT patients and controls with high accuracy (83–93%), which were further verified by SVM and MLP. Among them, MLP displayed the best classification performance on simultaneously precise identification of the three groups (94.74%), suggesting the advantage of MLP over RF/SVM to some extent.

Conclusions

Our findings reveal plasma metabolomic characteristics of SPPT and SNPT patients, provide some novel promising diagnostic markers for precision diagnosis of various types of TB, and show the potential of machine learning in screening out biomarkers from big data.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07694-8.

Drug exposure and susceptibility of second-line drugs correlate with treatment response in patients with multidrug-resistant tuberculosis: a multi-centre prospective cohort study in China

Background

Understanding the impact of drug exposure and susceptibility on treatment response of multidrug-resistant tuberculosis (MDR-TB) will help to optimise treatment. This study aimed to investigate the association between drug exposure, susceptibility and response to MDR-TB treatment.

Methods

Drug exposure and susceptibility for second-line drugs were measured for patients with MDR-TB. Multivariate analysis was applied to investigate the impact of drug exposure and susceptibility on sputum culture conversion and treatment outcome. Probability of target attainment was evaluated. Random Forest and CART (Classification and Regression Tree) analysis was used to identify key predictors and their clinical targets among patients on World Health Organization-recommended regimens.

Results

Drug exposure and corresponding susceptibility were available for 197 patients with MDR-TB. The probability of target attainment was highly variable, ranging from 0% for ethambutol to 97% for linezolid, while patients with fluoroquinolones above targets had a higher probability of 2-month culture conversion (56.3% versus 28.6%; adjusted OR 2.91, 95% CI 1.42–5.94) and favourable outcome (88.8% versus 68.8%; adjusted OR 2.89, 95% CI 1.16–7.17). Higher exposure values of fluoroquinolones, linezolid and pyrazinamide were associated with earlier sputum culture conversion. CART analysis selected moxifloxacin area under the drug concentration–time curve/minimum inhibitory concentration (AUC_0–24h/MIC) of 231 and linezolid AUC_0–24h/MIC of 287 as best predictors for 6-month culture conversion in patients receiving identical Group A-based regimens. These associations were confirmed in multivariate analysis.

Conclusions

Our findings indicate that target attainment of TB drugs is associated with response to treatment. The CART-derived thresholds may serve as targets for early dose adjustment in a future randomised controlled study to improve MDR-TB treatment outcome.

Drug exposure and susceptibility were proved to be associated with treatment responses during multidrug-resistant tuberculosis treatment, and identified thresholds may serve as targets for dose adjustment in future clinical studies to improve treatment efficacyhttps://bit.ly/3pZQbFU

Analysis of Factors Influencing Multidrug-Resistant Tuberculosis and Validation of Whole-Genome Sequencing in Children with Drug-Resistant Tuberculosis

Objective

Pediatric tuberculosis (TB) is one of the top ten causes of death in children. Our study was to analyze influencing factors of multidrug-resistant tuberculosis (MDR-TB) and validation of whole-genome sequencing (WGS) used in children with drug-resistant TB (DR-TB).

Methods

All Mycobacterium tuberculosis (Mtb) strains were isolated from patients aged below 18 years old of Children’s Hospital of Chongqing Medical University, China. A total of 208 Mtb isolates were tested for eight anti-TB drugs with phenotypic drug susceptibility test (DST) and for genetic prediction of the susceptible profile with WGS. The patients corresponding to each strain were grouped according to drug resistance and genotype. Influencing factors of MDR-TB and DR-TB were analyzed.

Results

According to the phenotypic DST and WGS, 82.2% of Mtb strains were susceptible to all eight drugs, and 6.3% were MDR-TB. Using the phenotypic DSTs as the gold standard, the kappa value of WGS to predict isoniazid, rifampin, ethambutol, rifapentine, prothionamide, levofloxacin, moxifloxacin and amikacin was 0.84, 0.89, 0.59, 0.86, 0.89, 0.82, 0.88 and 1.00, respectively. There was significant difference in the distribution of severe TB, diagnosis, treatment and outcome between MDR and drug-susceptible group (P<0.05). The distribution of severe TB and treatment between DR and drug-susceptible group was statistically different (P<0.05). The results of binary logistic regression showed that Calmette–Guérin bacillus (BCG) vaccine is the protective factor for MDR-TB (OR=0.19), and MDR-TB is the risk factor for PTB and EPTB (OR=17.98).

Conclusion

The BCG vaccine is a protective factor for MDR-TB, and MDR-TB might not be confined to pulmonary infection, spreading to extrapulmonary organs in children. MDR-TB had more severe cases and a lower recovery rate than drug-susceptible TB. WGS could provide an accurate prediction of drug susceptibility test results for anti-TB drugs, which are needed for the diagnosis and precise treatment of TB in children.

Tuberculosis Pathways to Care and Transmission of Multidrug-Resistance in India

Rationale

India is experiencing a regional increase in cases of multidrug-resistant tuberculosis (MDR-TB).

Objectives

Given the complexity of MDR-TB diagnosis and care, we sought to address key knowledge gaps in MDR risk factors, care delays, and drivers of delay to help guide disease control.

Methods

From January 2018 to September 2019, we conducted interviews with adults registered with the National TB Elimination Program for MDR (n = 128) and non–MDR-TB (n = 269) treatment to quantitatively and qualitatively study care pathways. We collected treatment records and GeneXpert-TB/RIF diagnostic reports.

Measurements and Main Results

MDR-TB was associated with young age and crowded residence. GeneXpert rifampicin resistance diversity was measured at 72.5% Probe E. Median time from symptom onset to diagnosis of MDR was 90 days versus 60 days for non-MDR, Wilcoxon P < 0.01. Delay decreased by a median of 30 days among non-MDR patients with wider access to GeneXpert, Wilcoxon P = 0.02. Pathways to care were complex, with a median (interquartile range) of 4 (3–5) and 3 (2–4) encounters for MDR and non-MDR, respectively. Of patients with MDR-TB, 68% had their first encounter in the private sector, and this was associated with a larger number of subsequent healthcare encounters and catastrophic expenditure.

Conclusions

The association of MDR with young age, crowding, and low genotypic diversity raises concerns of ongoing MDR transmission fueled by long delays in care. Delays are decreasing with GeneXpert use, suggesting the need for routine use in presumptive TB. Qualitatively, we identify the need to improve patient retention in the National TB Elimination Program and highlight patients’ trust relationship with private providers.

Prevalence of Mycobacterium tuberculosis resistant to bedaquiline and delamanid in China

OBJECTIVES

The new antituberculous drugs delamanid and bedaquiline form the last line of defence against drug-resistant tuberculosis (TB). Understanding the background prevalence of resistance to new drugs can help predict the lifetime of these drugs' effectiveness and inform regimen design.

METHODS

Mycobacterium tuberculosis without prior exposure to novel anti-TB drugs were analysed retrospectively. Drug susceptibility testing for bedaquiline, delamanid, linezolid, clofazimine and widely used first- and second-line anti-TB drugs was performed. All TB isolates with resistance to new or repurposed drugs were subjected to whole-genome sequencing to explore the molecular characteristics of resistance and to perform phylogenetic analysis.

RESULTS

Overall, resistance to delamanid, bedaquiline, linezolid and clofazimine was observed in 0.7% (11/1603), 0.4% (6/1603), 0.4% (7/1603) and 0.4% (6/1603) of TB isolates, respectively. Moreover, 1.0% (1/102), 2.9% (3/102), 3.9% (4/102) and 1.0% (1/102) of multidrug-resistant TB (MDR-TB) were resistant to bedaquiline, delamanid, linezolid and clofazimine, respectively. Whereas 22.2% (2/9) of extensively-drug resistant tuberculosis (XDR-TB) isolates were resistant to both delamanid and linezolid, and none was resistant to bedaquiline or clofazimine. Phylogenetic analysis showed that recent transmission occurred in two XDR-TB with additional resistance to delamanid and linezolid. None known gene mutation associated with delamanid resistance was detected. All four isolates with cross-resistance to bedaquiline and clofazimine had a detected gene mutation in Rv0678. Three of five strains with linezolid resistance had a detected gene mutation in rplC.

CONCLUSION

Detection of resistance to new anti-TB drugs emphasises the pressing need for intensive surveillance for such resistance before their wide usage.

Multiple Merger Genealogies in Outbreaks of Mycobacterium tuberculosis

The Kingman coalescent and its developments are often considered among the most important advances in population genetics of the last decades. Demographic inference based on coalescent theory has been used to reconstruct the population dynamics and evolutionary history of several species, including Mycobacterium tuberculosis (MTB), an important human pathogen causing tuberculosis. One key assumption of the Kingman coalescent is that the number of descendants of different individuals does not vary strongly, and violating this assumption could lead to severe biases caused by model misspecification. Individual lineages of MTB are expected to vary strongly in reproductive success because 1) MTB is potentially under constant selection due to the pressure of the host immune system and of antibiotic treatment, 2) MTB undergoes repeated population bottlenecks when it transmits from one host to the next, and 3) some hosts show much higher transmission rates compared with the average (superspreaders).

Here, we used an approximate Bayesian computation approach to test whether multiple-merger coalescents (MMC), a class of models that allow for large variation in reproductive success among lineages, are more appropriate models to study MTB populations. We considered 11 publicly available whole-genome sequence data sets sampled from local MTB populations and outbreaks and found that MMC had a better fit compared with the Kingman coalescent for 10 of the 11 data sets. These results indicate that the null model for analyzing MTB outbreaks should be reassessed and that past findings based on the Kingman coalescent need to be revisited.

Changes in Incidence and Epidemiological Characteristics of Pulmonary Tuberculosis in Mainland China, 2005-2016

IMPORTANCE

The World Health Organization End TB (Tuberculosis) Strategy aims to decrease the global incidence and mortality of TB by 90% and 95%, respectively, as of 2035.

OBJECTIVE

To characterize the recent epidemiological trend of pulmonary TB (PTB) in mainland China based on the national surveillance data.

DESIGN, SETTING, AND PARTICIPANTS

This cross-sectional study collected demographic and clinical data of all patients reported in the national Tuberculosis Information Management System of China from January 1, 2005, to November 21, 2016. Data were analyzed from December 1, 2019, to July 31, 2020.

EXPOSURES

Pulmonary TB was defined as bacteriologically confirmed or clinically diagnosed TB in the lung parenchyma or the tracheobronchial tree.

MAIN OUTCOMES AND MEASURES

Temporal and spatial variation of annual incidence and demographic features of PTB in mainland China.

RESULTS

In total, 10 582 903 patients with PTB were reported in mainland China from 2005 to 2016. The median age of patients with PTB was 46 (interquartile range [IQR], 30-61) years, and 28.53% were 60 years or older. Most patients with PTB were male (69.8%) and farmers or herders (70.0%). The mean (SD) incidence of PTB was 66.61 (8.09) per 100 000 population. The annual incidence decreased from 72.95 per 100 000 population in 2005 to 52.18 per 100 000 population in 2016, and the reduction was greater in the eastern and central regions (31.6%; from 69.43 to 47.48 per 100 000 population) than in the western region (21.0%; from 82.06 to 64.82 per 100 000 population). Xinjiang Uygur Autonomous Region (135.03 per 100 000 population), Guizhou Province (115.98 per 100 000 population), and the Tibet Autonomous Region (101.98 per 100 000 population) had the highest mean annual incidences. The median time from onset of illness to diagnosis decreased from 36 (IQR, 16-92) days from 2005 to 2007 to 31 (IQR, 15-63) days in 2008 and later (P < .001) and was longer in the western region than in the eastern and central regions (41 [IQR, 20-91] vs 30 [IQR, 13-61] days; P < .001).

CONCLUSIONS AND RELEVANCE

Although this study found that the incidence of PTB in mainland China showed a downward trend from 2005 to 2016, to achieve the World Health Organization 2035 goal, innovative and more efficient prevention and control strategies are needed, particularly among the most susceptible population, that is, farmers and herders in western China.

Reporting practices for genomic epidemiology of tuberculosis: a systematic review of the literature using STROME-ID guidelines as a benchmark

BACKGROUND

Pathogen genomics have become increasingly important in infectious disease epidemiology and public health. The Strengthening the Reporting of Molecular Epidemiology for Infectious Diseases (STROME-ID) guidelines were developed to outline a minimum set of criteria that should be reported in genomic epidemiology studies to facilitate assessment of study quality. We evaluate such reporting practices, using tuberculosis as an example.

METHODS

For this systematic review, we initially searched MEDLINE, Embase Classic, and Embase on May 3, 2017, using the search terms "tuberculosis" and "genom* sequencing". We updated this initial search on April 23, 2019, and also included a search of bioRxiv at this time. We included studies in English, French, or Spanish that recruited patients with microbiologically confirmed tuberculosis and used whole genome sequencing for typing of strains. Non-human studies, conference abstracts, and literature reviews were excluded. For each included study, the number and proportion of fulfilled STROME-ID criteria were recorded by two reviewers. A comparison of the mean proportion of fulfilled STROME-ID criteria before and after publication of the STROME-ID guidelines (in 2014) was done using a two-tailed t test. Quasi-Poisson regression and tobit regression were used to examine associations between study characteristics and the number and proportion of fulfilled STROME-ID criteria. This study was registered with PROSPERO, CRD42017064395.

FINDINGS

976 titles and abstracts were identified by our primary search, with an additional 16 studies identified in bioRxiv. 114 full texts (published between 2009 and 2019) were eligible for inclusion. The mean proportion of STROME-ID criteria fulfilled was 50% (SD 12; range 16-75). The proportion of criteria fulfilled was similar before and after STROME-ID publication (51% [SD 11] vs 46% [14], p=0·26). The number of criteria reported (among those applicable to all studies) was not associated with impact factor, h-index, country of affiliation of senior author, or sample size of isolates. Similarly, the proportion of criteria fulfilled was not associated with these characteristics, with the exception of a sample size of isolates of 277 or more (the highest quartile). In terms of reproducibility, 100 (88%) studies reported which bioinformatic tools were used, but only 33 (33%) reported corresponding version numbers. Sequencing data were available for 86 (75%) studies.

INTERPRETATION

The reporting of STROME-ID criteria in genomic epidemiology studies of tuberculosis between 2009 and 2019 was low, with implications for assessment of study quality. The considerable proportion of studies without bioinformatics version numbers or sequencing data available highlights a key concern for reproducibility.

Fidaxomicin has high in vitro activity against Mycobacterium tuberculosis

This study aimed to evaluate whether the antibiotic fidaxomicin has in vitro activity against Mycobacterium tuberculosis (Mtb). 38 fully drug-sensitive Mtb strains and 34 multidrug-resistant tuberculosis (MDR-TB) strains were tested using the microplate alamar blue assay (MABA) method to determine the minimum inhibitory concentrations (MICs) for fidaxomicin and rifampicin. Fidaxomicin has high in vitro activity against Mtb and is a potential drug to treat Mtb, and MDR-TB infections in particular.

Epidemiology characteristics of the clonal complexes of Mycobacterium tuberculosis Lineage 4 in China

Mycobacterium tuberculosis (M. tuberculosis) Lineage 4 (L4) is frequently prevailing in Western regions of China, where the tuberculosis incidence rate is high. However, the epidemiology characteristics of M. tuberculosis L4 in China remain poorly understood. Here, the 15-loci Variable number of tandem repeats (VNTR) patterns of 975 L4 isolates from a National Survey of Tuberculosis in China were used to construct a Minimum Spanning Tree (MST), which divided the 975 isolates into 5 major clonal complexes (CC; named CC1 to CC5). We found that the CCs of M. tuberculosis L4 were nationally distributed, geographically restricted, and different in epidemiology characteristics. For example, CC1 was mainly concentrated in East and Central China and significantly related to the farmer occupation and income of an individual (>4200 yuan) (p < .05); CC5 was mainly distributed in Southwest China and was associated with ethnic minorities. Notably, using whole genome sequencing (WGS) data of 141 strains that matched our samples, we found that both CC1 and CC5 were mapped to the sublineage L4.5. Nevertheless, due to the difference of geographical distribution, the epidemiology characteristics of these CCs were largely different. We found that income and occupation significantly contributed to the odds of infection by CC1 to CC5. Consequently, our findings revealed the epidemiology characteristics of the CCs of M. tuberculosis L4, and will help in the formulation of more effective intervention measures in line with regional specifications and patient characteristics in China.

A routine blood test-associated predictive model and application for tuberculosis diagnosis: a retrospective cohort study from northwest China

Objectives

This study aimed to use the results of routine blood tests and relevant parameters to construct models for the prediction of active tuberculosis (ATB) and drug-resistant tuberculosis (DRTB) and to assess the diagnostic values of these models.

Methods

We performed logistic regression analysis to generate models of plateletcrit-albumin scoring (PAS) and platelet distribution width-treatment-sputum scoring (PTS). Area under the curve (AUC) analysis was used to analyze the diagnostic values of these curves. Finally, we performed model validation and application assessment.

Results

In the training cohort, for the PAS model, the AUC for diagnosing ATB was 0.902, sensitivity was 82.75%, specificity was 82.20%, accuracy rate was 81.00%, and optimal threshold value was 0.199. For the PTS model, the AUC for diagnosing DRTB was 0.700, sensitivity was 63.64%, specificity was 73.53%, accuracy rate was 89.00%, and optimal threshold value was −2.202. These two models showed significant differences in the AUC analysis, compared with single-factor models. Results in the validation cohort were similar.

Conclusions

The PAS model had high sensitivity and specificity for the diagnosis of ATB, and the PTS model had strong predictive potential for the diagnosis of DRTB.

Small RNA Profiles of Serum Exosomes Derived From Individuals With Latent and Active Tuberculosis

Tuberculosis (TB) has been the leading lethal infectious disease worldwide since 2014, and about one third of the world’s population has a latent TB infection (LTBI). This is largely attributed to the difficulties in diagnosis and treatment of TB and LTBI patients. Exosomes offer a new perspective on investigation of the process of TB infection. In this study, we performed small RNA sequencing to explore small RNA profiles of serum exosomes derived from LTBI and TB patients and healthy controls (HC). Our results revealed distinct miRNA profile of the exosomes in the three groups. We screened 250 differentially expressed miRNAs including 130 specifically expressed miRNAs. Some miRNAs were further validated to be specifically expressed in LTBI (hsa-let-7e-5p, hsa-let-7d-5p, hsa-miR-450a-5p, and hsa-miR-140-5p) and TB samples (hsa-miR-1246, hsa-miR-2110, hsa-miR-370-3P, hsa-miR-28-3p, and hsa-miR-193b-5p). Additionally, we demonstrated four expression panels in LTBI and TB groups, and six expression patterns among the three groups. These specifically expressed miRNAs and differentially expressed miRNAs in different panels and patterns provide potential biomarkers for detection/diagnosis of latent and active TB using exosomal miRNAs. Additionally, we also discovered plenty of small RNAs derived from genomic repetitive sequences, which might play roles in host immune responses along with Mtb infection progresses. Overall, our findings provide important reference and an improved understanding about miRNAs and repetitive region-derived small RNAs in exosomes during the Mtb infectious process, and facilitate the development of potential molecular targets for detection/diagnosis of latent and active tuberculosis.