Genomic sequencing is required for identification of tuberculosis transmission in Hawaii

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.

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.

Performance evaluation of core genome multilocus sequence typing for genotyping of Mycobacterium tuberculosis strains in China: based on multicenter, population-based collection

PURPOSE

To evaluate the performance of core genome multilocus sequence typing (cgMLST) for genotyping Mycobacterium tuberculosis (M.tuberculosis) Strains in regions where the lineage 2 strains predominate.

METHODS

We compared clustering by whole-genome SNP typing with cgMLST clustering in the analysis of WGS data of 6240 strains from five regions of China. Using both the receiver operating characteristic (ROC) curve and epidemiological investigation to determine the optimal threshold for defining genomic clustering by cgMLST. The performance of cgMLST was evaluated by quantifying the sensitivity, specificity and concordance of clustering between two methods. Logistic regression was used to gauge the impact of strain genetic diversity and lineage on cgMLST clustering.

RESULTS

The optimal threshold for cgMLST to define genomic clustering was determined to be ≤ 10 allelic differences between strains. The overall sensitivity and specificity of cgMLST averaged 99.6% and 96.3%, respectively; the concordance of clustering between two methods averaged 97.1%. Concordance was significantly correlated with strain genetic diversity and was 3.99 times (95% CI, 2.94-5.42) higher in regions with high genetic diversity (π > 1.55 × 10-4) compared to regions with low genetic diversity. The difference missed statistical significance, while concordance for lineage 2 strains (96.8%) was less than that for lineage 4 strains (98.3%). CONCLUSION : cgMLST showed a discriminatory power comparable to whole-genome SNP typing and could be used to genotype clinical M.tuberculosis strains in different regions of China. The discriminative power of cgMLST was significantly correlated with strain genetic diversity and was slightly lower with strains from regions with low genetic diversity.

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.

Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas

BACKGROUND

Reductions in tuberculosis (TB) transmission have been instrumental in lowering TB incidence in the United States. Sustaining and augmenting these reductions are key public health priorities.

METHODS

We fit mechanistic transmission models to distributions of genotype clusters of TB cases reported to the Centers for Disease Control and Prevention during 2012-2016 in the United States and separately in California, Florida, New York, and Texas. We estimated the mean number of secondary cases generated per infectious case (R0) and individual-level heterogeneity in R0 at state and national levels and assessed how different definitions of clustering affected these estimates.

RESULTS

In clusters of genotypically linked TB cases that occurred within a state over a 5-year period (reference scenario), the estimated R0 was 0.29 (95% confidence interval [CI], .28-.31) in the United States. Transmission was highly heterogeneous; 0.24% of simulated cases with individual R0 >10 generated 19% of all recent secondary transmissions. R0 estimate was 0.16 (95% CI, .15-.17) when a cluster was defined as cases occurring within the same county over a 3-year period. Transmission varied across states: estimated R0s were 0.34 (95% CI, .3-.4) in California, 0.28 (95% CI, .24-.36) in Florida, 0.19 (95% CI, .15-.27) in New York, and 0.38 (95% CI, .33-.46) in Texas.

CONCLUSIONS

TB transmission in the United States is characterized by pronounced heterogeneity at the individual and state levels. Improving detection of transmission clusters through incorporation of whole-genome sequencing and identifying the drivers of this heterogeneity will be essential to reducing TB transmission.

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.

Genomic variant-identification methods may alter Mycobacterium tuberculosis transmission inferences

Pathogen genomic data are increasingly used to characterize global and local transmission patterns of important human pathogens and to inform public health interventions. Yet, there is no current consensus on how to measure genomic variation. To test the effect of the variant-identification approach on transmission inferences for Mycobacterium tuberculosis, we conducted an experiment in which five genomic epidemiology groups applied variant-identification pipelines to the same outbreak sequence data. We compared the variants identified by each group in addition to transmission and phylogenetic inferences made with each variant set. To measure the performance of commonly used variant-identification tools, we simulated an outbreak. We compared the performance of three mapping algorithms, five variant callers and two variant filters in recovering true outbreak variants. Finally, we investigated the effect of applying increasingly stringent filters on transmission inferences and phylogenies. We found that variant-calling approaches used by different groups do not recover consistent sets of variants, which can lead to conflicting transmission inferences. Further, performance in recovering true variation varied widely across approaches. While no single variant-identification approach outperforms others in both recovering true genome-wide and outbreak-level variation, variant-identification algorithms calibrated upon real sequence data or that incorporate local reassembly outperform others in recovering true pairwise differences between isolates. The choice of variant filters contributed to extensive differences across pipelines, and applying increasingly stringent filters rapidly eroded the accuracy of transmission inferences and quality of phylogenies reconstructed from outbreak variation. Commonly used approaches to identify M. tuberculosis genomic variation have variable performance, particularly when predicting potential transmission links from pairwise genetic distances. Phylogenetic reconstruction may be improved by less stringent variant filtering. Approaches that improve variant identification in repetitive, hypervariable regions, such as long-read assemblies, may improve transmission inference.

Contextualizing tuberculosis risk in time and space: comparing time-restricted genotypic case clusters and geospatial clusters to evaluate the relative contribution of recent transmission to incidence of TB using nine years of case data from Michigan, USA

PURPOSE

Novel approaches must address the underlying factors sustaining the tuberculosis (TB) epidemic in the United States, specifically what maintains new Mycobacterium tuberculosis (Mtb) transmission.

METHODS

Culture-confirmed TB cases reported to the Michigan Department of Health and Human Services (2004-2012) were analyzed for time-restricted genotypic and/or geospatial clustering. Cases with both types of clustering were used as a proxy for recent, local transmission. Modified, multivariate Poisson regression models were fit to estimate this prevalence in relation to various individual- and neighborhood-level demographic and socio-economic variables.

RESULTS

Those individuals that were spatially clustered were 1.7 times as likely to also be time-restricted genotypically clustered. The prevalence of recent, local transmission was higher among U.S.-born cases, males, and non-Hispanic blacks. Moreover, people living in neighborhoods in the highest poverty quartile had 13.8 times the prevalence of recent, local transmission compared with those in the lowest poverty neighborhoods.

CONCLUSIONS

Our results suggest geographic areas with high concentration of TB cases are likely driven by ongoing transmission, rather than enclaves of individuals who have reactivated a case of latent TB. Furthermore, efforts to continue reducing Mtb transmission in the United States, and other low-incidence settings, must better identify community-level sources of risk, manifested through the complex social interactions among people and their environments.