Frequent transmission of the Mycobacterium tuberculosis Beijing lineage and positive selection for the EsxW Beijing variant in Vietnam

Bayesian reconstruction of Mycobacterium tuberculosis transmission networks in a high incidence area over two decades in Malawi reveals associated risk factors and genomic variants

Understanding host and pathogen factors that influence tuberculosis (TB) transmission can inform strategies to eliminate the spread of Mycobacterium tuberculosis (Mtb). Determining transmission links between cases of TB is complicated by a long and variable latency period and undiagnosed cases, although methods are improving through the application of probabilistic modelling and whole-genome sequence analysis. Using a large dataset of 1857 whole-genome sequences and comprehensive metadata from Karonga District, Malawi, over 19 years, we reconstructed Mtb transmission networks using a two-step Bayesian approach that identified likely infector and recipient cases, whilst robustly allowing for incomplete case sampling. We investigated demographic and pathogen genomic variation associated with transmission and clustering in our networks. We found that whilst there was a significant decrease in the proportion of infectors over time, we found higher transmissibility and large transmission clusters for lineage 2 (Beijing) strains. By performing evolutionary convergence testing (phyC) and genome-wide association analysis (GWAS) on transmitting versus non-transmitting cases, we identified six loci, PPE54, accD2, PE_PGRS62, rplI, Rv3751 and Rv2077c, that were associated with transmission. This study provides a framework for reconstructing large-scale Mtb transmission networks. We have highlighted potential host and pathogen characteristics that were linked to increased transmission in a high-burden setting and identified genomic variants that, with validation, could inform further studies into transmissibility and TB eradication.

Model-based integration of genomics and metabolomics reveals SNP functionality in Mycobacterium tuberculosis

Human tuberculosis is caused by members of the Mycobacterium tuberculosis complex (MTBC) that vary in virulence and transmissibility. While genome-wide association studies have uncovered several mutations conferring drug resistance, much less is known about the factors underlying other bacterial phenotypes. Variation in the outcome of tuberculosis infection and diseases has been attributed primarily to patient and environmental factors, but recent evidence indicates an additional role for the genetic diversity among MTBC clinical strains. Here, we used metabolomics to unravel the effect of genetic variation on the strain-specific metabolic adaptive capacity and vulnerability. To define the functionality of single-nucleotide polymorphisms (SNPs) systematically, we developed a constraint-based approach that integrates metabolomic and genomic data. Our model-based predictions correctly classify SNP effects in pyruvate kinase and suggest a genetic basis for strain-specific inherent baseline susceptibility to the antibiotic para-aminosalicylic acid. Our method is broadly applicable across microbial life, opening possibilities for the development of more selective treatment strategies.

Xpert MTB/RIF Ultra versus Xpert MTB/RIF for the diagnosis of tuberculous meningitis: a prospective, randomised, diagnostic accuracy study

BACKGROUND

Xpert MTB/RIF Ultra (Xpert Ultra) might have higher sensitivity than its predecessor, Xpert MTB/RIF (Xpert), but its role in tuberculous meningitis diagnosis is uncertain. We aimed to compare Xpert Ultra with Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults.

METHODS

In this prospective, randomised, diagnostic accuracy study, adults (≥16 years) with suspected tuberculous meningitis from a single centre in Vietnam were randomly assigned to cerebrospinal fluid testing by either Xpert Ultra or Xpert at baseline and, if treated for tuberculous meningitis, after 3-4 weeks of treatment. Test performance (sensitivity, specificity, and positive and negative predictive values) was calculated for Xpert Ultra and Xpert and compared against clinical and mycobacterial culture reference standards. Analyses were done for all patients and by HIV status.

FINDINGS

Between Oct 16, 2017, and Feb 10, 2019, 205 patients were randomly assigned to Xpert Ultra (n=103) or Xpert (n=102). The sensitivities of Xpert Ultra and Xpert for tuberculous meningitis diagnosis against a reference standard of definite, probable, and possible tuberculous meningitis were 47·2% (95% CI 34·4-60·3; 25 of 53 patients) for Xpert Ultra and 39·6% (27·6-53·1; 21 of 53) for Xpert (p=0·56); specificities were 100·0% (95% CI 92·0-100·0; 44 of 44) and 100·0% (92·6-100·0; 48 of 48), respectively. In HIV-negative patients, the sensitivity of Xpert Ultra was 38·9% (24·8-55·1; 14 of 36) versus 22·9% (12·1-39·0; eight of 35) by Xpert (p=0·23). In HIV co-infected patients, the sensitivities were 64·3% (38·8-83·7; nine of 14) for Xpert Ultra and 76·9% (49·7-91·8; ten of 13) for Xpert (p=0·77). Negative predictive values were 61·1% (49·6-71·5) for Xpert Ultra and 60·0% (49·0-70·0) for Xpert. Against a reference standard of mycobacterial culture, sensitivities were 90·9% (72·2-97·5; 20 of 22 patients) for Xpert Ultra and 81·8% (61·5-92·7; 18 of 22) for Xpert (p=0·66); specificities were 93·9% (85·4-97·6; 62 of 66) and 96·9% (89·5-91·2; 63 of 65), respectively. Six (22%) of 27 patients had a positive test by Xpert Ultra after 4 weeks of treatment versus two (9%) of 22 patients by Xpert.

INTERPRETATION

Xpert Ultra was not statistically superior to Xpert for the diagnosis of tuberculous meningitis in HIV-uninfected and HIV-infected adults. A negative Xpert Ultra or Xpert test does not rule out tuberculous meningitis. New diagnostic strategies are urgently required.

FUNDING

Wellcome Trust and the Foundation for Innovative New Diagnostics.

Structure guided prediction of Pyrazinamide resistance mutations in pncA

Pyrazinamide plays an important role in tuberculosis treatment; however, its use is complicated by side-effects and challenges with reliable drug susceptibility testing. Resistance to pyrazinamide is largely driven by mutations in pyrazinamidase (pncA), responsible for drug activation, but genetic heterogeneity has hindered development of a molecular diagnostic test. We proposed to use information on how variants were likely to affect the 3D structure of pncA to identify variants likely to lead to pyrazinamide resistance. We curated 610 pncA mutations with high confidence experimental and clinical information on pyrazinamide susceptibility. The molecular consequences of each mutation on protein stability, conformation, and interactions were computationally assessed using our comprehensive suite of graph-based signature methods, mCSM. The molecular consequences of the variants were used to train a classifier with an accuracy of 80%. Our model was tested against internationally curated clinical datasets, achieving up to 85% accuracy. Screening of 600 Victorian clinical isolates identified a set of previously unreported variants, which our model had a 71% agreement with drug susceptibility testing. Here, we have shown the 3D structure of pncA can be used to accurately identify pyrazinamide resistance mutations. SUSPECT-PZA is freely available at: http://biosig.unimelb.edu.au/suspect_pza/.

A Comprehensive Computational Platform to Guide Drug Development Using Graph-Based Signature Methods

High-throughput computational techniques have become invaluable tools to help increase the overall success, process efficiency, and associated costs of drug development. By designing ligands tailored to specific protein structures in a disease of interest, an understanding of molecular interactions and ways to optimize them can be achieved prior to chemical synthesis. This understanding can help direct crucial chemical and biological experiments by maximizing available resources on higher quality leads. Moreover, predicting molecular binding affinity within specific biological contexts, as well as ligand pharmacokinetics and toxicities, can aid in filtering out redundant leads early on within the process. We describe a set of computational tools which can aid in drug discovery at different stages, from hit identification (EasyVS) to lead optimization and candidate selection (CSM-lig, mCSM-lig, Arpeggio, pkCSM). Incorporating these tools along the drug development process can help ensure that candidate leads are chemically and biologically feasible to become successful and tractable drugs.

Prediction of impacts of mutations on protein structure and interactions: SDM, a statistical approach, and mCSM, using machine learning

Next-generation sequencing methods have not only allowed an understanding of genome sequence variation during the evolution of organisms but have also provided invaluable information about genetic variants in inherited disease and the emergence of resistance to drugs in cancers and infectious disease. A challenge is to distinguish mutations that are drivers of disease or drug resistance, from passengers that are neutral or even selectively advantageous to the organism. This requires an understanding of impacts of missense mutations in gene expression and regulation, and on the disruption of protein function by modulating protein stability or disturbing interactions with proteins, nucleic acids, small molecule ligands, and other biological molecules. Experimental approaches to understanding differences between wild-type and mutant proteins are most accurate but are also time-consuming and costly. Computational tools used to predict the impacts of mutations can provide useful information more quickly. Here, we focus on two widely used structure-based approaches, originally developed in the Blundell lab: site-directed mutator (SDM), a statistical approach to analyze amino acid substitutions, and mutation cutoff scanning matrix (mCSM), which uses graph-based signatures to represent the wild-type structural environment and machine learning to predict the effect of mutations on protein stability. Here, we describe DUET that uses machine learning to combine the two approaches. We discuss briefly the development of mCSM for understanding the impacts of mutations on interfaces with other proteins, nucleic acids, and ligands, and we exemplify the wide application of these approaches to understand human genetic disorders and drug resistance mutations relevant to cancer and mycobacterial infections. STATEMENT FOR A BROADER AUDIENCE: Genetic or somatic changes in genes can lead to mutations in human proteins, which give rise to genetic disorders or cancer, or to genes of pathogens leading to drug resistance. Computer software described here, using statistical approaches or machine learning, uses the information from genome sequencing of humans and pathogens, together with experimental or modeled 3D structures of gene products, the proteins, to predict impacts of mutations in genetic disease, cancer and drug resistance.

Tuberculosis in Liberia: high multidrug-resistance burden, transmission and diversity modelled by multiple importation events

Tuberculosis (TB) surveillance is scarce in most African countries, even though it is the continent with the greatest disease incidence according to the World Health Organization. Liberia is within the 30 countries with the highest TB burden, probably as a consequence of the long civil war and the recent Ebola outbreak, both crippling the health system and depreciating the TB prevention and control programmes. Due to difficulties working in the country, there is a lack of resistance surveys and bacillus characterization. Here, we use genome sequencing of Mycobacteriumtuberculosis clinical isolates to fill this gap. Our results highlight that the bacillus population structure is dominated by lineage 4 strains that harbour an outstanding genetic diversity, higher than in the rest of Africa as a whole. Coalescent analyses demonstrate that strains currently circulating in Liberia were introduced several times beginning in the early year 600 CE until very recently coinciding with migratory movements associated with the civil war and Ebola epidemics. A higher multidrug-resistant (MDR)-TB frequency (23.5 %) than current estimates was obtained together with non-catalogued drug-resistance mutations. Additionally, 39 % of strains were in genomic clusters revealing that ongoing transmission is a major contribution to the TB burden in the country. Our report emphasizes the importance of TB surveillance and control in African countries where bacillus diversity, MDR-TB prevalence and transmission are coalescing to jeopardize TB control programmes.

New insights into the mycobacterial PE and PPE proteins provide a framework for future research

The PE and PPE proteins of Mycobacterium tuberculosis have been studied with great interest since their discovery. Named after the conserved proline (P) and glutamic acid (E) residues in their N-terminal domains, these proteins are postulated to perform wide-ranging roles in virulence and immune modulation. However, technical challenges in studying these proteins and their encoding genes have hampered the elucidation of molecular mechanisms and leave many open questions regarding the biological functions mediated by these proteins. Here, I review the shared and unique characteristics of PE and PPE proteins from a molecular perspective linking this information to their functions in mycobacterial virulence. I discuss how the different subgroups (PE_PGRS, PPE-PPW, PPE-SVP and PPE-MPTR) are defined and why this classification of paramount importance to understand the PE and PPE proteins as individuals and or groups. The goal of this MicroReview is to summarize and structure the existing information on this gene family into a simplified framework of thinking about PE and PPE proteins and genes. Thereby, I hope to provide helpful starting points in studying these genes and proteins for researchers with different backgrounds. This has particular implications for the design and monitoring of novel vaccine candidates and in understanding the evolution of the M. tuberculosis complex.

Characterization of Polymorphisms Associated with Multidrug-Resistant Tuberculosis by Whole Genomic Sequencing: A Preliminary Report from Mexico

Whole genome sequencing (WGS) has been proposed as a tool for the diagnosis of drug resistance in tuberculosis (TB); however, there have been few studies on its effectiveness in countries with significantly high drug resistance rates. This study therefore aimed to evaluate the effectiveness of WGS to identify mutations related to drug resistance in TB isolates from an endemic region of Mexico. The results showed that, of 35 multidrug-resistant isolates analyzed, the values of congruence found between the phenotypic drug susceptibility testing and polymorphisms were 94% for isoniazid, 97% for rifampicin, 90% for ethambutol, and 82% for pyrazinamide. It was also possible to identify eight isolates as potential pre-extensive drug resistant (XDR) and one as XDR. Twenty nine isolates were classified within L4 and two transmission clusters were identified. The results show the potential utility of WGS for predicting resistance against first- and second-line drugs, as well as providing a phylogenetic characterization of TB drug-resistant isolates circulating in Mexico.

Dispersal of Mycobacterium tuberculosis Driven by Historical European Trade in the South Pacific

Mycobacterium tuberculosis (Mtb) is a globally distributed bacterial pathogen whose population structure has largely been shaped by the activities of its obligate human host. Oceania was the last major global region to be reached by Europeans and is the last region for which the dispersal and evolution of Mtb remains largely unexplored. Here, we investigated the evolutionary history of the Euro-American L4.4 sublineage and its dispersal to the South Pacific. Using a phylodynamics approach and a dataset of 236 global Mtb L4.4 genomes we have traced the origins and dispersal of L4.4 strains to New Zealand. These strains are predominantly found in indigenous Māori and Pacific people and we identify a clade of European, likely French, origin that is prevalent in indigenous populations in both New Zealand and Canada. Molecular dating suggests the expansion of European trade networks in the early 19th century drove the dispersal of this clade to the South Pacific. We also identify historical and social factors within the region that have contributed to the local spread and expansion of these strains, including recent Pacific migrations to New Zealand and the rapid urbanization of Māori in the 20th century. Our results offer new insight into the expansion and dispersal of Mtb in the South Pacific and provide a striking example of the role of historical European migrations in the global dispersal of Mtb.

Isolation and comparative genomics of Mycobacterium tuberculosis isolates from cattle and their attendants in South India

The major human pathogen Mycobacterium tuberculosis is rarely reported to cause disease in other animals. Cases in livestock are thought to occur through contact with infected handlers, but previous studies evaluating putative livestock-human transmission used typing techniques with limited resolution. Here, we undertook cross-sectional surveillance for tuberculosis in 271 livestock handlers and 167 cattle on three farms in Chennai, India and defined the relatedness of cultured isolates using whole genome sequencing. Humans and livestock were screened for active mycobacterial infection, and opportunistic post-mortem examination was performed on comparative intradermal test-positive cattle that died. Four cattle and 6 handlers on two farms were culture-positive for M. tuberculosis; M. bovis was not isolated. All 10 isolates (one from each case) belonged to Lineage 1. Pairwise genome comparisons of single nucleotide polymorphism (SNP) differences ranged from 1 to 600 SNPs, but 3 isolate pairs were less than 5 SNPs different. Two pairs were from handlers and the third pair were from two cattle on the same farm. The minimum pairwise SNP difference between a cattle and human isolate was >250 SNPs. Our study confirms the presence of M. tuberculosis infection in cattle in India, sequencing of which characterised relatedness between human and cattle-derived isolates.

Genotyping of Mycobacterium tuberculosis spreading in Hanoi, Vietnam using conventional and whole genome sequencing methods

Hanoi is the capital of Vietnam, one of the 30 countries with a high tuberculosis (TB) burden. Fundamental data on the molecular epidemiology of the disease is required for future TB management. To identify lineages and genotypes of Mycobacterium tuberculosis (Mtb), conventional genotyping data from clinical isolates of the Hanoi area was compared with whole genome sequencing (WGS) analysis from 332 of 470 samples. It was obtained from lineage-specific single nucleotide variants (SNVs), large sequence polymorphisms, spoligotyping, and variable number of tandem repeats (VNTR) analysis using mycobacterial interspersed repetitive unit (MIRU) and Japan anti-tuberculosis association (JATA) locus sets. This information was directly compared with results obtained from WGS. Mini-satellite repeat unit variants were identified using BLAST search against concatenated short read sequences, the RepUnitTyping tool. WGS analysis revealed that the Mtb strains tested are diverse and classified into lineage (L) 1, 2 and 4 (24.7, 57.2 and 18.1% respectively). The majority of the L2 strains were further divided into ancient and modern Beijing genotypes, and most of the L1 group were EAI4_VNM strains. Although conventional PCR-based genotyping results were mostly consistent with information obtained through WGS analysis, in-depth analysis identified aberrant deletions and spacers that may cause discordance. JATA-VNTR sets, including hypervariable loci, separated large Beijing genotypic clusters generated by MIRU15 into smaller groups. The distribution of repeat unit variants observed within 33 VNTR loci showed clear variation depending on the three lineages. WGS-based pairwise-SNV differences within VNTR-defined genotypic clusters were greater in L1 than in L2 and L4 (P = .001). Direct comparisons between results of PCR-based genotyping and in silico analysis of WGS data would bridge a gap between classical and modern technologies during this transition period, and provide further information on Mtb genotypes in specific geographical areas.

Pre-detection history of extensively drug-resistant tuberculosis in KwaZulu-Natal, South Africa

Antimicrobial-resistant (AMR) infections pose a major threat to global public health. Similar to other AMR pathogens, both historical and ongoing drug-resistant tuberculosis (TB) epidemics are characterized by transmission of a limited number of predominant Mycobacterium tuberculosis (Mtb) strains. Understanding how these predominant strains achieve sustained transmission, particularly during the critical period before they are detected via clinical or public health surveillance, can inform strategies for prevention and containment. In this study, we employ whole-genome sequence (WGS) data from TB clinical isolates collected in KwaZulu-Natal, South Africa to examine the pre-detection history of a successful strain of extensively drug-resistant (XDR) TB known as LAM4/KZN, first identified in a widely reported cluster of cases in 2005. We identify marked expansion of this strain concurrent with the onset of the generalized HIV epidemic 12 y prior to 2005, localize its geographic origin to a location in northeastern KwaZulu-Natal ∼400 km away from the site of the 2005 outbreak, and use protein structural modeling to propose a mechanism for how strain-specific rpoB mutations offset fitness costs associated with rifampin resistance in LAM4/KZN. Our findings highlight the importance of HIV coinfection, high preexisting rates of drug-resistant TB, human migration, and pathoadaptive evolution in the emergence and dispersal of this critical public health threat. We propose that integrating whole-genome sequencing into routine public health surveillance can enable the early detection and local containment of AMR pathogens before they achieve widespread dispersal.

Hyper transmission of Beijing lineage Mycobacterium tuberculosis: Systematic review and meta-analysis

OBJECTIVES

The globally distributed "Beijing" lineage of Mycobacterium tuberculosis has been associated with outbreaks worldwide. Laboratory based studies have suggested that Beijing lineage may have increased fitness; however, it has not been established whether these differences are of epidemiological significance with regards to transmission. Therefore, we undertook a systematic review of epidemiological studies of tuberculosis clustering to compare the transmission dynamics of Beijing lineages versus the non-Beijing lineages.

METHODS

We systematically searched Embase and MEDLINE before 31st December 2018, for studies which provided information on the transmission dynamics of the different M. tuberculosis lineages. We included articles that conducted population-based cross-sectional or longitudinal molecular epidemiological studies reporting information about extent of transmission of different lineages. The protocol for this systematic review was prospectively registered with PROSPERO (CDR42018088579).

RESULTS

Of 2855 records identified by the search, 46 were included in the review, containing 42,700 patients from 27 countries. Beijing lineage was the most prevalent and highly clustered strain in 72.4% of the studies and had a higher likelihood of transmission than non-Beijing lineages (OR 1·81 [95% 1·28-2·57], I² = 94·0%, τ² = 0·59, p < 0·01).

CONCLUSIONS

Despite considerable heterogeneity across epidemiological contexts, Beijing lineage appears to be more transmissible than other lineages.

The Interplay of Human and Mycobacterium Tuberculosis Genomic Variability

Tuberculosis (TB), caused by the human pathogens Mycobacterium tuberculosis (Mtb) and Mycobacterium africanum, has plagued humanity for millennia and remains the deadliest infectious disease in the modern world. Mycobacterium tuberculosis and M. africanum can be subdivided phylogenetically into seven lineages exhibiting a low but significant degree of genomic diversity and preferential geographic distributions. Human genetic variability impacts all stages of TB pathogenesis ranging from susceptibility to infection with Mtb, progression of infection to disease, and the development of distinct clinical subtypes. The genetic study of severe childhood TB identified strong inborn single-gene errors revealing crucial pathways of vulnerability to TB. However, the identification of major TB-susceptibility genes on the population level has remained elusive. In particular, the replication of findings from candidate and genome-wide association studies across distinct human populations has proven difficult, thus hampering the characterization of reliable host molecular markers of susceptibility. Among the possible confounding factors of genetic association studies is Mtb genomic variability, which generally was not taken into account by human genetic studies. In support of this possibility, Mtb lineage was found to be a contributing factor to clinical presentation of TB and epidemiological spread of Mtb in exposed populations. The confluence of pathogen and human host genetic variability to TB pathogenesis led to the consideration of a possible coadaptation of Mtb strains and their human hosts, which should reveal itself in significant interaction effects between Mtb strain and TB-susceptibility/resistance alleles. Here, we present some of the most consistent findings of genetic susceptibility factors in human TB and review studies that point to genome-to-genome interaction between humans and Mtb lineages. The limited results available so far suggest that analyses considering joint human–Mtb genomic variability may provide improved power for the discovery of pathogenic drivers of the ongoing TB epidemic.

Mycobacterium tuberculosis Drug Resistance and Transmission among Human Immunodeficiency Virus-Infected Patients in Ho Chi Minh City, Vietnam

Vietnam has a high burden of tuberculosis (TB) and multidrug-resistant (MDR) TB, but drug resistance patterns and TB transmission dynamics among TB/human immunodeficiency virus (HIV) coinfected patients are not well described. We characterized 200 Mycobacterium tuberculosis isolates from TB/HIV coinfected patients diagnosed at the main TB referral hospital in Ho Chi Minh City, Vietnam. Phenotypic drug susceptibility testing (DST) for first-line drugs, spoligotyping, and 24-locus mycobacterial interspersed repetitive unit (MIRU-24) analysis was performed on all isolates. The 24-locus mycobacterial interspersed repetitive unit clusters and MDR isolates were subjected to whole genome sequencing (WGS). Most of the TB/HIV coinfected patients were young (162/174; 93.1% aged < 45 years) males (173; 86.5% male). Beijing (98; 49.0%) and Indo-Oceanic (70; 35.0%) lineage strains were most common. Phenotypic drug resistance was detected in 84 (42.0%) isolates, of which 17 (8.5%) were MDR; three additional MDR strains were identified on WGS. Strain clustering was reduced from 84.0% with spoligotyping to 20.0% with MIRU-24 typing and to 13.5% with WGS. Whole genome sequencing identified five additional clusters, or members of clusters, not recognized by MIRU-24. In total, 13 small (two to three member) WGS clusters were identified, with less clustering among drug susceptible (2/27; 7.4%) than among drug-resistant strains (25/27; 92.6%). On phylogenetic analysis, strains from TB/HIV coinfected patients were interspersed among strains from the general community; no major clusters indicating transmission among people living with HIV were detected. Tuberculosis/HIV coinfection in Vietnam was associated with high rates of drug resistance and limited genomic evidence of ongoing M. tuberculosis transmission among HIV-infected patients.

The molecular clock of Mycobacterium tuberculosis

The molecular clock and its phylogenetic applications to genomic data have changed how we study and understand one of the major human pathogens, Mycobacterium tuberculosis (MTB), the etiologic agent of tuberculosis. Genome sequences of MTB strains sampled at different times are increasingly used to infer when a particular outbreak begun, when a drug-resistant clone appeared and expanded, or when a strain was introduced into a specific region. Despite the growing importance of the molecular clock in tuberculosis research, there is a lack of consensus as to whether MTB displays a clocklike behavior and about its rate of evolution. Here we performed a systematic study of the molecular clock of MTB on a large genomic data set (6,285 strains), covering different epidemiological settings and most of the known global diversity. We found that sampling times below 15-20 years were often insufficient to calibrate the clock of MTB. For data sets where such calibration was possible, we obtained a clock rate between 1x10-8 and 5x10-7 nucleotide changes per-site-per-year (0.04-2.2 SNPs per-genome-per-year), with substantial differences between clades. These estimates were not strongly dependent on the time of the calibration points as they changed only marginally when we used epidemiological isolates (sampled in the last 40 years) or three ancient DNA samples (about 1,000 years old) to calibrate the tree. Additionally, the uncertainty and the discrepancies in the results of different methods were sometimes large, highlighting the importance of using different methods, and of considering carefully their assumptions and limitations.

Identification and Characterization of Genetic Determinants of Isoniazid and Rifampicin Resistance in Mycobacterium tuberculosis in Southern India

Drug-resistant tuberculosis (TB), one of the leading causes of death worldwide, arises mainly from spontaneous mutations in the genome of Mycobacterium tuberculosis. There is an urgent need to understand the mechanisms by which the mutations confer resistance in order to identify new drug targets and to design new drugs. Previous studies have reported numerous mutations that confer resistance to anti-TB drugs, but there has been little systematic analysis to understand their genetic background and the potential impacts on the drug target stability and/or interactions. Here, we report the analysis of whole-genome sequence data for 98 clinical M. tuberculosis isolates from a city in southern India. The collection was screened for phenotypic resistance and sequenced to mine the genetic mutations conferring resistance to isoniazid and rifampicin. The most frequent mutation among isoniazid and rifampicin isolates was S315T in katG and S450L in rpoB respectively. The impacts of mutations on protein stability, protein-protein interactions and protein-ligand interactions were analysed using both statistical and machine-learning approaches. Drug-resistant mutations were predicted not only to target active sites in an orthosteric manner, but also to act through allosteric mechanisms arising from distant sites, sometimes at the protein-protein interface.

Lineage specific histories of Mycobacterium tuberculosis dispersal in Africa and Eurasia

Mycobacterium tuberculosis (M.tb) is a globally distributed, obligate pathogen of humans that can be divided into seven clearly defined lineages. An emerging consensus places the origin and global dispersal of M.tb within the past 6,000 years: identifying how the ancestral clone of M.tb spread and differentiated within this timeframe is important for identifying the ecological drivers of the current pandemic. We used Bayesian phylogeographic inference to reconstruct the migratory history of M.tb in Africa and Eurasia and to investigate lineage specific patterns of spread from a geographically diverse sample of 552 M.tb genomes. Applying evolutionary rates inferred with ancient M.tb genome calibration, we estimated the timing of major events in the migratory history of the pathogen. Inferred timings contextualize M.tb dispersal within historical phenomena that altered patterns of connectivity throughout Africa and Eurasia: trans-Indian Ocean trade in spices and other goods, the Silk Road and its predecessors, the expansion of the Roman Empire, and the European Age of Exploration. We found that Eastern Africa and Southeast Asia have been critical in the dispersal of M.tb. Our results further reveal that M.tb populations have grown through range expansion, as well as in situ, and delineate the independent evolutionary trajectories of bacterial subpopulations underlying the current pandemic.

Whole genomic sequencing as a tool for diagnosis of drug and multidrug-resistance tuberculosis in an endemic region in Mexico

Background

Whole genome sequencing (WGS) has been proposed as a tool for diagnosing drug resistance in tuberculosis. However, reports of its effectiveness in endemic countries with important numbers of drug resistance are scarce. The goal of this study was to evaluate the effectiveness of this procedure in isolates from a tuberculosis endemic region in Mexico.

Methods

WGS analysis was performed in 81 tuberculosis positive clinical isolates with a known phenotypic profile of resistance against first-line drugs (isoniazid, rifampin, ethambutol, pyrazinamide and streptomycin). Mutations related to drug resistance were identified for each isolate; drug resistant genotypes were predicted and compared with the phenotypic profile. Genotypes and transmission clusters based on genetic distances were also characterized.

Findings

Prediction by WGS analysis of resistance against isoniazid, rifampicin, ethambutol, pyrazinamide and streptomycin showed sensitivity values of 84%, 96%, 71%, 75% and 29%, while specificity values were 100%, 94%, 90%, 90% and 98%, respectively. Prediction of multidrug resistance showed a sensitivity of 89% and specificity of 97%. Moreover, WGS analysis revealed polymorphisms related to second-line drug resistance, enabling classification of eight and two clinical isolates as pre- and extreme drug-resistant cases, respectively. Lastly, four lineages were identified in the population (L1, L2, L3 and L4). The most frequent of these was L4, which included 90% (77) of the isolates. Six transmission clusters were identified; the most frequent was TC6, which included 13 isolates with a L4.1.1 and a predominantly multidrug-resistant condition.

Conclusions

The results illustrate the utility of WGS for establishing the potential for prediction of resistance against first and second line drugs in isolates of tuberculosis from the region. They also demonstrate the feasibility of this procedure for use as a tool to support the epidemiological surveillance of drug- and multidrug-resistant tuberculosis.

Genomic determinants of speciation and spread of the Mycobacterium tuberculosis complex

Models on how bacterial lineages differentiate increase our understanding of early bacterial speciation events and the genetic loci involved. Here, we analyze the population genomics events leading to the emergence of the tuberculosis pathogen. The emergence is characterized by a combination of recombination events involving core pathogenesis functions and purifying selection on early diverging loci. We identify the phoR gene, the sensor kinase of a two-component system involved in virulence, as a key functional player subject to pervasive positive selection after the divergence of the Mycobacterium tuberculosis complex from its ancestor. Previous evidence showed that phoR mutations played a central role in the adaptation of the pathogen to different host species. Now, we show that phoR mutations have been under selection during the early spread of human tuberculosis, during later expansions, and in ongoing transmission events. Our results show that linking pathogen evolution across evolutionary and epidemiological time scales points to past and present virulence determinants.

Empirical ways to identify novel Bedaquiline resistance mutations in AtpE

Clinical resistance against Bedaquiline, the first new anti-tuberculosis compound with a novel mechanism of action in over 40 years, has already been detected in Mycobacterium tuberculosis. As a new drug, however, there is currently insufficient clinical data to facilitate reliable and timely identification of genomic determinants of resistance. Here we investigate the structural basis for M. tuberculosis associated bedaquiline resistance in the drug target, AtpE. Together with the 9 previously identified resistance-associated variants in AtpE, 54 non-resistance-associated mutations were identified through comparisons of bedaquiline susceptibility across 23 different mycobacterial species. Computational analysis of the structural and functional consequences of these variants revealed that resistance associated variants were mainly localized at the drug binding site, disrupting key interactions with bedaquiline leading to reduced binding affinity. This was used to train a supervised predictive algorithm, which accurately identified likely resistance mutations (93.3% accuracy). Application of this model to circulating variants present in the Asia-Pacific region suggests that current circulating variants are likely to be susceptible to bedaquiline. We have made this model freely available through a user-friendly web interface called SUSPECT-BDQ, StrUctural Susceptibility PrEdiCTion for bedaquiline (http://biosig.unimelb.edu.au/suspect_bdq/). This tool could be useful for the rapid characterization of novel clinical variants, to help guide the effective use of bedaquiline, and to minimize the spread of clinical resistance.

Extensive global movement of multidrug-resistantM. tuberculosis strains revealed by whole-genome analysis

Background

While the international spread of multidrug-resistant (MDR) Mycobacterium tuberculosis strains is an acknowledged public health threat, a broad and more comprehensive examination of the global spread of MDR-tuberculosis (TB) using whole-genome sequencing has not yet been performed.

Methods

In a global dataset of 5310 M. tuberculosis whole-genome sequences isolated from five continents, we performed a phylogenetic analysis to identify and characterise clades of MDR-TB with respect to geographic dispersion.

Results

Extensive international dissemination of MDR-TB was observed, with identification of 32 migrant MDR-TB clades with descendants isolated in 17 unique countries. Relatively recent movement of strains from both Beijing and non-Beijing lineages indicated successful global spread of varied genetic backgrounds. Migrant MDR-TB clade members shared relatively recent common ancestry, with a median estimate of divergence of 13–27 years. Migrant extensively drug-resistant (XDR)-TB clades were not observed, although development of XDR-TB within migratory MDR-TB clades was common.

Conclusions

Application of genomic techniques to investigate global MDR migration patterns revealed extensive global spread of MDR clades between countries of varying TB burden. Further expansion of genomic studies to incorporate isolates from diverse global settings into a single analysis, as well as data sharing platforms that facilitate genomic data sharing across country lines, may allow for future epidemiological analyses to monitor for international transmission of MDR-TB. In addition, efforts to perform routine whole-genome sequencing on all newly identified M. tuberculosis, like in England, will serve to better our understanding of the transmission dynamics of MDR-TB globally.

Insights into the genetic diversity of Mycobacterium tuberculosis in Tanzania

BACKGROUND

Human tuberculosis (TB) is caused by seven phylogenetic lineages of the Mycobacterium tuberculosis complex (MTBC), Lineage 1-7. Recent advances in rapid genotyping of MTBC based on single nucleotide polymorphisms (SNP), allow for phylogenetically robust strain classification, paving the way for defining genotype-phenotype relationships in clinical settings. Such studies have revealed that, in addition to host and environmental factors, strain variation in the MTBC influences the outcome of TB infection and disease. In Tanzania, such molecular epidemiological studies of TB however are scarce in spite of a high TB burden.

METHODS AND FINDINGS

Here we used SNP-typing to characterize a nationwide collection of 2,039 MTBC clinical isolates representative of 1.6% of all new and retreatment TB cases notified in Tanzania during 2012 and 2013. Four lineages, namely Lineage 1-4 were identified within the study population. The distribution and frequency of these lineages varied across regions but overall, Lineage 4 was the most frequent (n = 866, 42.5%), followed by Lineage 3 (n = 681, 33.4%) and 1 (n = 336, 16.5%), with Lineage 2 being the least frequent (n = 92, 4.5%). We found Lineage 2 to be independently associated with female sex (adjusted odds ratio [aOR] 2.14; 95% confidence interval [95% CI] 1.31 - 3.50, p = 0.002) and retreatment cases (aOR 1.67; 95% CI 0.95 - 2.84, p = 0. 065) in the study population. We found no associations between MTBC lineage and patient age or HIV status. Our sublineage typing based on spacer oligotyping on a subset of Lineage 1, 3 and 4 strains revealed the presence of mainly EAI, CAS and LAM families. Finally, we detected low levels of multidrug resistant isolates among a subset of 144 retreatment cases.

CONCLUSIONS

This study provides novel insights into the MTBC lineages and the possible influence of pathogen-related factors on the TB epidemic in Tanzania.

Whole genome sequencing identifies bacterial factors affecting transmission of multidrug-resistant tuberculosis in a high-prevalence setting

Whole genome sequencing (WGS) can elucidate Mycobacterium tuberculosis (Mtb) transmission patterns but more data is needed to guide its use in high-burden settings. In a household-based TB transmissibility study in Peru, we identified a large MIRU-VNTR Mtb cluster (148 isolates) with a range of resistance phenotypes, and studied host and bacterial factors contributing to its spread. WGS was performed on 61 of the 148 isolates. We compared transmission link inference using epidemiological or genomic data and estimated the dates of emergence of the cluster and antimicrobial drug resistance (DR) acquisition events by generating a time-calibrated phylogeny. Using a set of 12,032 public Mtb genomes, we determined bacterial factors characterizing this cluster and under positive selection in other Mtb lineages. Four of the 61 isolates were distantly related and the remaining 57 isolates diverged ca. 1968 (95%HPD: 1945-1985). Isoniazid resistance arose once and rifampin resistance emerged subsequently at least three times. Emergence of other DR types occurred as recently as within the last year of sampling. We identified five cluster-defining SNPs potentially contributing to transmissibility. In conclusion, clusters (as defined by MIRU-VNTR typing) may be circulating for decades in a high-burden setting. WGS allows for an enhanced understanding of transmission, drug resistance, and bacterial fitness factors.

Mycobacterial Evolution Intersects With Host Tolerance

Over the past 200 years, tuberculosis (TB) has caused more deaths than any other infectious disease, likely infecting more people than it has at any other time in human history. Mycobacterium tuberculosis (Mtb), the etiologic agent of TB, is an obligate human pathogen that has evolved through the millennia to become an archetypal human-adapted pathogen. This review focuses on the evolutionary framework by which Mtb emerged as a specialized human pathogen and applies this perspective to the emergence of specific lineages that drive global TB burden. We consider how evolutionary pressures, including transmission dynamics, host tolerance, and human population patterns, may have shaped the evolution of diverse mycobacterial genomes.

Exploring Protein Supersecondary Structure Through Changes in Protein Folding, Stability, and Flexibility

The ability to predict how mutations affect protein structure, folding, and flexibility can elucidate the molecular mechanisms leading to disruption of supersecondary structures, the emergence of phenotypes, as well guiding rational protein engineering. The advent of fast and accurate computational tools has enabled us to comprehensively explore the landscape of mutation effects on protein structures, prioritizing mutations for rational experimental validation.Here we describe the use of two complementary web-based in silico methods, DUET and DynaMut, developed to infer the effects of mutations on folding, stability, and flexibility and how they can be used to explore and interpret these effects on protein supersecondary structures.

The Wonder Years: What Can Primary School Children Teach Us About Immunity to Mycobacterium tuberculosis?

In high burden settings, the risk of infection with Mycobacterium tuberculosis increases throughout childhood due to cumulative exposure. However, the risk of progressing from tuberculosis (TB) infection to disease varies by age. Young children (<5 years) have high risk of disease progression following infection. The risk falls in primary school children (5 to <10 years), but rises again during puberty. TB disease phenotype also varies by age: generally, young children have intrathoracic lymph node disease or disseminated disease, while adolescents (10 to <20 years) have adult-type pulmonary disease. TB risk also exhibits a gender difference: compared to adolescent boys, adolescent girls have an earlier rise in disease progression risk and higher TB incidence until early adulthood. Understanding why primary school children, during what we term the "Wonder Years," have low TB risk has implications for vaccine development, therapeutic interventions, and diagnostics. To understand why this group is at low risk, we need a better comprehension of why younger children and adolescents have higher risks, and why risk varies by gender. Immunological response to M. tuberculosis is central to these issues. Host response at key stages in the immunopathological interaction with M. tuberculosis influences risk and disease phenotype. Cell numbers and function change dramatically with age and sexual maturation. Young children have poorly functioning innate cells and a Th2 skew. During the "Wonder Years," there is a lymphocyte predominance and a Th1 skew. During puberty, neutrophils become more central to host response, and CD4+ T cells increase in number. Sex hormones (dehydroepiandrosterone, adiponectin, leptin, oestradiol, progesterone, and testosterone) profoundly affect immunity. Compared to girls, boys have a stronger Th1 profile and increased numbers of CD8+ T cells and NK cells. Girls are more Th2-skewed and elicit more enhanced inflammatory responses. Non-immunological factors (including exposure intensity, behavior, and co-infections) may impact disease. However, given the consistent patterns seen across time and geography, these factors likely are less central. Strategies to protect children and adolescents from TB may need to differ by age and sex. Further work is required to better understand the contribution of age and sex to M. tuberculosis immunity.

China's tuberculosis epidemic stems from historical expansion of four strains of Mycobacterium tuberculosis

A small number of high-burden countries account for the majority of tuberculosis cases worldwide. Detailed data are lacking from these regions. To explore the evolutionary history of Mycobacterium tuberculosis in China-the country with the third highest tuberculosis burden-we analysed a countrywide collection of 4,578 isolates. Little genetic diversity was detected, with 99.4% of the bacterial population belonging to lineage 2 and three sublineages of lineage 4. The deeply rooted phylogenetic positions and geographic restriction of these four genotypes indicate that their populations expanded in situ following a small number of introductions to China. Coalescent analyses suggest that these bacterial subpopulations emerged in China around 1,000 years ago, and expanded in parallel from the twelfth century onwards, and that the whole population peaked in the late eighteenth century. More recently, sublineage L2.3, which is indigenous to China and exhibited relatively high transmissibility and extensive global dissemination, came to dominate the population dynamics of M. tuberculosis in China. Our results indicate that historical expansion of four M. tuberculosis strains shaped the current tuberculosis epidemic in China, and highlight the long-term genetic continuity of the indigenous M. tuberculosis population.

Virulence of Mycobacterium tuberculosis Clinical Isolates Is Associated With Sputum Pre-treatment Bacterial Load, Lineage, Survival in Macrophages, and Cytokine Response

It is uncertain whether differences in Mycobacterium tuberculosis (Mtb) virulence defined in vitro influence clinical tuberculosis pathogenesis, transmission, and mortality. We primarily used a macrophage lysis model to characterize the virulence of Mtb isolates collected from 153 Vietnamese adults with pulmonary tuberculosis. The virulence phenotypes were then investigated for their relationship with sputum bacterial load, bacterial lineages, bacterial growth, and cytokine responses in macrophages. Over 6 days of infection, 34 isolates (22.2%) showed low virulence (< 5% macrophages lysed), 46 isolates (30.1%) showed high virulence (≥90% lysis of macrophages), and 73 isolates (47.7%) were of intermediate virulence (5–90% macrophages lysed). Highly virulent isolates were associated with an increased bacterial load in patients' sputum before anti-tuberculosis therapy (P = 0.02). Isolate-dependent virulence phenotype was consistent in both THP-1 and human monocyte-derived macrophages. High virulence isolates survived better and replicated in macrophages one hundred fold faster than those with low virulence. Macrophages infected with high virulence isolates produced lower concentrations of TNF-α and IL-6 (P = 0.002 and 0.0005, respectively), but higher concentration of IL-1β (P = 5.1 × 10⁻⁵) compared to those infected with low virulence isolates. High virulence was strongly associated with East Asian/Beijing lineage [P = 0.002, Odd ratio (OR) = 4.32, 95% confident intervals (CI) 1.68–11.13]. The association between virulence phenotypes, bacterial growth, and proinflammatory cytokines in macrophages suggest the suppression of certain proinflammatory cytokines (TNF-α and IL-6) but not IL-1β allows better intracellular survival of highly virulent Mtb. This could result in rapid macrophage lysis and higher bacterial load in sputum of patients infected with high virulence isolates, which may contribute to the pathogenesis and success of the Beijing lineage.

Highlights on the Application of Genomics and Bioinformatics in the Fight Against Infectious Diseases: Challenges and Opportunities in Africa

Genomics and bioinformatics are increasingly contributing to our understanding of infectious diseases caused by bacterial pathogens such as Mycobacterium tuberculosis and parasites such as Plasmodium falciparum. This ranges from investigations of disease outbreaks and pathogenesis, host and pathogen genomic variation, and host immune evasion mechanisms to identification of potential diagnostic markers and vaccine targets. High throughput genomics data generated from pathogens and animal models can be combined with host genomics and patients’ health records to give advice on treatment options as well as potential drug and vaccine interactions. However, despite accounting for the highest burden of infectious diseases, Africa has the lowest research output on infectious disease genomics. Here we review the contributions of genomics and bioinformatics to the management of infectious diseases of serious public health concern in Africa including tuberculosis (TB), dengue fever, malaria and filariasis. Furthermore, we discuss how genomics and bioinformatics can be applied to identify drug and vaccine targets. We conclude by identifying challenges to genomics research in Africa and highlighting how these can be overcome where possible.

Global variation in bacterial strains that cause tuberculosis disease: a systematic review and meta-analysis

BACKGROUND

The host, microbial, and environmental factors that contribute to variation in tuberculosis (TB) disease are incompletely understood. Accumulating evidence suggests that one driver of geographic variation in TB disease is the local ecology of mycobacterial genotypes or strains, and there is a need for a comprehensive and systematic synthesis of these data. The objectives of this study were to (1) map the global distribution of genotypes that cause TB disease and (2) examine whether any epidemiologically relevant clinical characteristics were associated with those genotypes.

METHODS

We performed a systematic review of PubMed and Scopus to create a comprehensive dataset of human TB molecular epidemiology studies that used representative sampling techniques. The methods were developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). We extracted and synthesized data from studies that reported prevalence of bacterial genotypes and from studies that reported clinical characteristics associated with those genotypes.

RESULTS

The results of this study are twofold. First, we identified 206 studies for inclusion in the study, representing over 200,000 bacterial isolates collected over 27 years in 85 countries. We mapped the genotypes and found that, consistent with previously published maps, Euro-American lineage 4 and East Asian lineage 2 strains are widespread, and West African lineages 5 and 6 strains are geographically restricted. Second, 30 studies also reported transmission chains and 4 reported treatment failure associated with genotypes. We performed a meta-analysis and found substantial heterogeneity across studies. However, based on the data available, we found that lineage 2 strains may be associated with increased risk of transmission chains, while lineages 5 and 6 strains may be associated with reduced risk, compared with lineage 4 strains.

CONCLUSIONS

This study provides the most comprehensive systematic analysis of the evidence for diversity in bacterial strains that cause TB disease. The results show both geographic and epidemiological differences between strains, which could inform our understanding of the global burden of TB. Our findings also highlight the challenges of collecting the clinical data required to inform TB diagnosis and treatment. We urge future national TB programs and research efforts to prioritize and reinforce clinical data collection in study designs and results dissemination.

Clinically prevalent mutations in Mycobacterium tuberculosis alter propionate metabolism and mediate multidrug tolerance

The global epidemic of drug-resistant tuberculosis is a catastrophic example of how antimicrobial resistance is undermining the public health gains made possible by combination drug therapy. Recent evidence points to unappreciated bacterial factors that accelerate the emergence of drug resistance. In a genome-wide association study of Mycobacterium tuberculosis isolates from China, we find mutations in the gene encoding the transcription factor prpR enriched in drug-resistant strains. prpR mutations confer conditional drug tolerance to three of the most effective classes of antibiotics by altering propionyl-CoA metabolism. prpR-mediated drug tolerance is carbon-source dependent, and while readily detectable during infection of human macrophages, is not captured by standard susceptibility testing. These data define a previously unrecognized and clinically prevalent class of M. tuberculosis variants that undermine antibiotic efficacy and drive drug resistance.

Kinact: a computational approach for predicting activating missense mutations in protein kinases

Protein phosphorylation is tightly regulated due to its vital role in many cellular processes. While gain of function mutations leading to constitutive activation of protein kinases are known to be driver events of many cancers, the identification of these mutations has proven challenging. Here we present Kinact, a novel machine learning approach for predicting kinase activating missense mutations using information from sequence and structure. By adapting our graph-based signatures, Kinact represents both structural and sequence information, which are used as evidence to train predictive models. We show the combination of structural and sequence features significantly improved the overall accuracy compared to considering either primary or tertiary structure alone, highlighting their complementarity. Kinact achieved a precision of 87% and 94% and Area Under ROC Curve of 0.89 and 0.92 on 10-fold cross-validation, and on blind tests, respectively, outperforming well established tools (P < 0.01). We further show that Kinact performs equally well on homology models built using templates with sequence identity as low as 33%. Kinact is freely available as a user-friendly web server at http://biosig.unimelb.edu.au/kinact/.