Genomic analysis identifies targets of convergent positive selection in drug-resistant Mycobacterium tuberculosis

Current Affairs of Microbial Genome-Wide Association Studies: Approaches, Bottlenecks and Analytical Pitfalls

Microbial genome-wide association studies (mGWAS) are a new and exciting research field that is adapting human GWAS methods to understand how variations in microbial genomes affect host or pathogen phenotypes, such as drug resistance, virulence, host specificity and prognosis. Several computational tools and methods have been developed or adapted from human GWAS to facilitate the discovery of novel mutations and structural variations that are associated with the phenotypes of interest. However, no comprehensive, end-to-end, user-friendly tool is currently available. The development of a broadly applicable pipeline presents a real opportunity among computational biologists. Here, (i) we review the prominent and promising tools, (ii) discuss analytical pitfalls and bottlenecks in mGWAS, (iii) provide insights into the selection of appropriate tools, (iv) highlight the gaps that still need to be filled and how users and developers can work together to overcome these bottlenecks. Use of mGWAS research can inform drug repositioning decisions as well as accelerate the discovery and development of more effective vaccines and antimicrobials for pressing infectious diseases of global health significance, such as HIV, TB, influenza, and malaria.

Analysis of tomato spotted wilt virus RNA-dependent RNA polymerase adaptative evolution and constrained domains using homology protein structure modelling

Tomato spotted wilt virus (TSWV; genus Orthotospovirus, family Tospoviridae) has a huge impact on a large range of plants worldwide. In this study, we determined the sequence of the large (L) RNA segment that encodes the RNA-dependent RNA polymerase (RdRp) from a TSWV isolate (LYE51) collected in the south of France. Analysis of the phylogenetic relationships of TSWV-LYE51 with other TSWV isolates shows that it is closely related to other European isolates. A 3D model of TSWV-LYE51 RdRp was built by homology with the RdRp structure of the La Crosse virus (genus Orthobunyavirus, family Peribunyaviridae). Finally, an analysis of positive and negative selection was carried out on 30 TSWV full-length RNA L sequences and compared with the phylogeny and the protein structure data. We showed that the seven codons that are under positive selection are distributed all along the RdRp gene. By contrast, the codons associated with negative selection are especially concentrated in three highly constrained domains: the endonuclease in charge of the cap-snatching mechanism, the thumb domain and the mid domain. Those three domains could constitute good candidates to look for host targets on which genetic resistance by loss of susceptibility could be developed.

Characteristics of compensatory mutations in the rpoC gene and their association with compensated transmission of Mycobacterium tuberculosis

The aim of this study was to characterize rpoC gene mutations in Mycobacterium tuberculosis (MTB) and investigate the factors associated with rpoC mutations and the relation between rpoC mutations and tuberculosis (TB) transmission. A total of 245 MTB clinical isolates from patients with TB in six provinces and two municipalities in China were characterized based on gene mutations through DNA sequencing of rpoC and rpoB genes, phenotyping via standard drug susceptibility testing, and genotypic profiling by mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR) typing. Approximately 36.4% of the rifampin-resistant isolates harbored nonsynonymous mutations in the rpoC gene. Twenty-nine nonsynonymous single mutations and three double mutations were identified. The rpoC mutations at locus 483 (11.3%) were predominant, and the mutations at V483G, W484G, I491V, L516P, L566R, N698K, and A788E accounted for 54.5% of the total detected mutations. Fifteen new mutations in the rpoC gene were identified. Rifampin resistance and rpoB mutations at locus 531 were significantly associated with rpoC mutations. MIRU-VNTR genotype results indicated that 18.4% of the studied isolates were clustered, and the rpoC mutations were not significantly associated with MIRU-VNTR clusters. A large proportion of rpoC mutation was observed in the rifampicin-resistant MTB isolates. However, the findings of this study do not support the association of rpoC mutation with compensated transmissibility.

Parallel selection on ecologically relevant gene functions in the transcriptomes of highly diversifying salmonids

Background

Salmonid fishes are characterised by a very high level of variation in trophic, ecological, physiological, and life history adaptations. Some salmonid taxa show exceptional potential for fast, within-lake diversification into morphologically and ecologically distinct variants, often in parallel; these are the lake-resident charr and whitefish (several species in the genera Salvelinus and Coregonus). To identify selection on genes and gene categories associated with such predictable diversifications, we analysed 2702 orthogroups (4.82 Mbp total; average 4.77 genes/orthogroup; average 1783 bp/orthogroup). We did so in two charr and two whitefish species and compared to five other salmonid lineages, which do not evolve in such ecologically predictable ways, and one non-salmonid outgroup.

Results

All selection analyses are based on Coregonus and Salvelinus compared to non-diversifying taxa. We found more orthogroups were affected by relaxed selection than intensified selection. Of those, 122 were under significant relaxed selection, with trends of an overrepresentation of serine family amino acid metabolism and transcriptional regulation, and significant enrichment of behaviour-associated gene functions. Seventy-eight orthogroups were under significant intensified selection and were enriched for signalling process and transcriptional regulation gene ontology terms and actin filament and lipid metabolism gene sets. Ninety-two orthogroups were under diversifying/positive selection. These were enriched for signal transduction, transmembrane transport, and pyruvate metabolism gene ontology terms and often contained genes involved in transcriptional regulation and development. Several orthogroups showed signs of multiple types of selection. For example, orthogroups under relaxed and diversifying selection contained genes such as ap1m2, involved in immunity and development, and slc6a8, playing an important role in muscle and brain creatine uptake. Orthogroups under intensified and diversifying selection were also found, such as genes syn3, with a role in neural processes, and ctsk, involved in bone remodelling.

Conclusions

Our approach pinpointed relevant genomic targets by distinguishing among different kinds of selection. We found that relaxed, intensified, and diversifying selection affect orthogroups and gene functions of ecological relevance in salmonids. Because they were found consistently and robustly across charr and whitefish and not other salmonid lineages, we propose these genes have a potential role in the replicated ecological diversifications.

Genetic and metabolic signatures of Salmonella enterica subsp. enterica associated with animal sources at the pangenomic scale

BACKGROUND

Salmonella enterica subsp. enterica is a public health issue related to food safety, and its adaptation to animal sources remains poorly described at the pangenome scale. Firstly, serovars presenting potential mono- and multi-animal sources were selected from a curated and synthetized subset of Enterobase. The corresponding sequencing reads were downloaded from the European Nucleotide Archive (ENA) providing a balanced dataset of 440 Salmonella genomes in terms of serovars and sources (i). Secondly, the coregenome variants and accessory genes were detected (ii). Thirdly, single nucleotide polymorphisms and small insertions/deletions from the coregenome, as well as the accessory genes were associated to animal sources based on a microbial Genome Wide Association Study (GWAS) integrating an advanced correction of the population structure (iii). Lastly, a Gene Ontology Enrichment Analysis (GOEA) was applied to emphasize metabolic pathways mainly impacted by the pangenomic mutations associated to animal sources (iv).

RESULTS

Based on a genome dataset including Salmonella serovars from mono- and multi-animal sources (i), 19,130 accessory genes and 178,351 coregenome variants were identified (ii). Among these pangenomic mutations, 52 genomic signatures (iii) and 9 over-enriched metabolic signatures (iv) were associated to avian, bovine, swine and fish sources by GWAS and GOEA, respectively.

CONCLUSIONS

Our results suggest that the genetic and metabolic determinants of Salmonella adaptation to animal sources may have been driven by the natural feeding environment of the animal, distinct livestock diets modified by human, environmental stimuli, physiological properties of the animal itself, and work habits for health protection of livestock.

Purifying Selective Pressure Suggests the Functionality of a Vitamin B12 Biosynthesis Pathway in a Global Population of Mycobacterium tuberculosis

Mycobacterium tuberculosis is one of the deadliest and most challenging pathogens to study in current microbiological research. One of the issues that remains to be resolved is the importance of cobalamin in the metabolism of M. tuberculosis. The functionality of a vitamin B12 biosynthesis pathway in M. tuberculosis is under dispute, and the ability of this pathogen to scavenge vitamin B12 from the host is unknown. Here, we quantified the ratios of nonsynonymous and synonymous nucleotide substitution rates (dN/dS) in the genes involved in vitamin B12 biosynthesis and transport and in genes encoding cobalamin-dependent enzymes in nearly four thousand strains of M. tuberculosis. We showed that purifying selection is the dominant force acting on cobalamin-related genes at the levels of individual codons, genes and groups of genes. We conclude that cobalamin-related genes may not be essential but are adaptive for M. tuberculosis in clinical settings. Furthermore, the cobalamin biosynthesis pathway is likely to be functional in this species.

Whole genome sequencing, analyses of drug resistance-conferring mutations, and correlation with transmission of Mycobacterium tuberculosis carrying katG-S315T in Hanoi, Vietnam

Drug-resistant tuberculosis (TB) is a serious global problem, and pathogen factors involved in the transmission of isoniazid (INH)-resistant TB have not been fully investigated. We performed whole genome sequencing of 332 clinical Mycobacterium tuberculosis (Mtb) isolates collected from patients newly diagnosed with smear-positive pulmonary TB in Hanoi, Vietnam. Using a bacterial genome-wide approach based on linear mixed models, we investigated the associations between 31-bp k-mers and clustered strains harboring katG-S315T, a major INH-resistance mutation in the present cohort and in the second panel previously published in South Africa. Five statistically significant genes, namely, PPE18/19, gid, emrB, Rv1588c, and pncA, were shared by the two panels. We further identified variants of the genes responsible for these k-mers, which are relevant to the spread of INH-resistant strains. Phylogenetic convergence test showed that variants relevant to PPE46/47-like chimeric genes were significantly associated with the same phenotype in Hanoi. The associations were further confirmed after adjustment for the confounders. These findings suggest that genomic variations of the pathogen facilitate the expansion of INH-resistance TB, at least in part, and our study provides a new insight into the mechanisms by which drug-resistant Mtb maintains fitness and spreads in Asia and Africa.

Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics.

Genetically diverse Pseudomonas aeruginosa populations display similar transcriptomic profiles in a cystic fibrosis explanted lung

Previous studies have demonstrated substantial genetic diversification of Pseudomonas aeruginosa across sub-compartments in cystic fibrosis (CF) lungs. Here, we isolate P. aeruginosa from five different sampling areas in the upper and lower airways of an explanted CF lung, analyze ex vivo transcriptional profiles by RNA-seq, and use colony re-sequencing and deep population sequencing to determine the genetic diversity within and across the various sub-compartments. We find that, despite genetic variation, the ex vivo transcriptional profiles of P. aeruginosa populations inhabiting different regions of the CF lung are similar. Although we cannot estimate the extent to which the transcriptional response recorded here actually reflects the in vivo transcriptomes, our results indicate that there may be a common in vivo transcriptional profile in the CF lung environment.

Deciphering drug resistance in Mycobacterium tuberculosis using whole-genome sequencing: progress, promise, and challenges

Tuberculosis (TB) is a global infectious threat that is intensified by an increasing incidence of highly drug-resistant disease. Whole-genome sequencing (WGS) studies of Mycobacterium tuberculosis, the causative agent of TB, have greatly increased our understanding of this pathogen. Since the first M. tuberculosis genome was published in 1998, WGS has provided a more complete account of the genomic features that cause resistance in populations of M. tuberculosis, has helped to fill gaps in our knowledge of how both classical and new antitubercular drugs work, and has identified specific mutations that allow M. tuberculosis to escape the effects of these drugs. WGS studies have also revealed how resistance evolves both within an individual patient and within patient populations, including the important roles of de novo acquisition of resistance and clonal spread. These findings have informed decisions about which drug-resistance mutations should be included on extended diagnostic panels. From its origins as a basic science technique, WGS of M. tuberculosis is becoming part of the modern clinical microbiology laboratory, promising rapid and improved detection of drug resistance, and detailed and real-time epidemiology of TB outbreaks. We review the successes and highlight the challenges that remain in applying WGS to improve the control of drug-resistant TB through monitoring its evolution and spread, and to inform more rapid and effective diagnostic and therapeutic strategies.

Genome-Wide Analysis of MDR and XDR Tuberculosis from Belarus: Machine-Learning Approach

Emergence of drug-resistant microorganisms has been recognized as a serious threat to public health worldwide. This problem is extensively discussed in the context of tuberculosis treatment. Alterations in pathogen genomes are among the main mechanisms by which microorganisms exhibit drug resistance. Analysis of 144 M. tuberculosis strains of different phenotypes including drug susceptible, MDR, and XDR isolated in Belarus was fulfilled in this paper. A wide range of machine learning methods that can discover SNPs related to drug-resistance in the whole bacteria genomes was investigated. Besides single-SNP testing approaches, methods that allow detecting joint effects from interacting SNPs were considered. We proposed a framework for automated selection of the best performing statistical model in terms of recall, precision, and accuracy to identify drug resistance-associated mutations. Analysis of whole-genome sequences often leads to situations where the number of treated features exceeds the number of available observations. For this reason, special attention is paid to fair evaluation of the model prediction quality and minimizing the risk of overfitting while estimating the underlying parameters. Results of our experiments aimed at identifying top-scoring resistance mutations to the major first-line and second-line anti-TB drugs are presented.

Machine learning for classifying tuberculosis drug-resistance from DNA sequencing data

Motivation

Correct and rapid determination of Mycobacterium tuberculosis (MTB) resistance against available tuberculosis (TB) drugs is essential for the control and management of TB. Conventional molecular diagnostic test assumes that the presence of any well-studied single nucleotide polymorphisms is sufficient to cause resistance, which yields low sensitivity for resistance classification.

Summary

Given the availability of DNA sequencing data from MTB, we developed machine learning models for a cohort of 1839 UK bacterial isolates to classify MTB resistance against eight anti-TB drugs (isoniazid, rifampicin, ethambutol, pyrazinamide, ciprofloxacin, moxifloxacin, ofloxacin, streptomycin) and to classify multi-drug resistance.

Results

Compared to previous rules-based approach, the sensitivities from the best-performing models increased by 2-4% for isoniazid, rifampicin and ethambutol to 97% (P < 0.01), respectively; for ciprofloxacin and multi-drug resistant TB, they increased to 96%. For moxifloxacin and ofloxacin, sensitivities increased by 12 and 15% from 83 and 81% based on existing known resistance alleles to 95% and 96% (P < 0.01), respectively. Particularly, our models improved sensitivities compared to the previous rules-based approach by 15 and 24% to 84 and 87% for pyrazinamide and streptomycin (P < 0.01), respectively. The best-performing models increase the area-under-the-ROC curve by 10% for pyrazinamide and streptomycin (P < 0.01), and 4–8% for other drugs (P < 0.01).

Availability and implementation

The details of source code are provided at http://www.robots.ox.ac.uk/~davidc/code.php.

Supplementary information

Supplementary data are available at Bioinformatics online.

Serotype-specific evolutionary patterns of antimicrobial-resistant Salmonella enterica

Background

The emergence of antimicrobial-resistant (AMR) strains of the important human and animal pathogen Salmonella enterica poses a growing threat to public health. Here, we studied the genome-wide evolution of 90 S. enterica AMR isolates, representing one host adapted serotype (S. Dublin) and two broad host range serotypes (S. Newport and S. Typhimurium).

Results

AMR S. Typhimurium had a large effective population size, a large and diverse genome, AMR profiles with high diversity, and frequent positive selection and homologous recombination. AMR S. Newport showed a relatively low level of diversity and a relatively clonal population structure. AMR S. Dublin showed evidence for a recent population bottleneck, and the genomes were characterized by a larger number of genes and gene ontology terms specifically absent from this serotype and a significantly higher number of pseudogenes as compared to other two serotypes. Approximately 50% of accessory genes, including specific AMR and putative prophage genes, were significantly over- or under-represented in a given serotype. Approximately 65% of the core genes showed phylogenetic clustering by serotype, including the AMR gene aac (6′)-Iaa. While cell surface proteins were shown to be the main target of positive selection, some proteins with possible functions in AMR and virulence also showed evidence for positive selection. Homologous recombination mainly acted on prophage-associated proteins.

Conclusions

Our data indicates a strong association between genome content of S. enterica and serotype. Evolutionary patterns observed in S. Typhimurium are consistent with multiple emergence events of AMR strains and/or ecological success of this serotype in different hosts or habitats. Evolutionary patterns of S. Newport suggested that antimicrobial resistance emerged in one single lineage, Lineage IIC. A recent population bottleneck and genome decay observed in AMR S. Dublin are congruent with its narrow host range. Finally, our results suggest the potentially important role of positive selection in the evolution of antimicrobial resistance, host adaptation and serotype diversification in S. enterica.

Electronic supplementary material

The online version of this article (10.1186/s12862-019-1457-5) contains supplementary material, which is available to authorized users.

Nonoptimal Gene Expression Creates Latent Potential for Antibiotic Resistance

Bacteria regulate genes to survive antibiotic stress, but regulation can be far from perfect. When regulation is not optimal, mutations that change gene expression can contribute to antibiotic resistance. It is not systematically understood to what extent natural gene regulation is or is not optimal for distinct antibiotics, and how changes in expression of specific genes quantitatively affect antibiotic resistance. Here we discover a simple quantitative relation between fitness, gene expression, and antibiotic potency, which rationalizes our observation that a multitude of genes and even innate antibiotic defense mechanisms have expression that is critically nonoptimal under antibiotic treatment. First, we developed a pooled-strain drug-diffusion assay and screened Escherichia coli overexpression and knockout libraries, finding that resistance to a range of 31 antibiotics could result from changing expression of a large and functionally diverse set of genes, in a primarily but not exclusively drug-specific manner. Second, by synthetically controlling the expression of single-drug and multidrug resistance genes, we observed that their fitness–expression functions changed dramatically under antibiotic treatment in accordance with a log-sensitivity relation. Thus, because many genes are nonoptimally expressed under antibiotic treatment, many regulatory mutations can contribute to resistance by altering expression and by activating latent defenses.

Effects of Host, Sample, and in vitro Culture on Genomic Diversity of Pathogenic Mycobacteria

Mycobacterium tuberculosis (M. tb), an obligate human pathogen and the etiological agent of tuberculosis (TB), remains a major threat to global public health. Comparative genomics has been invaluable for monitoring the emergence and spread of TB and for gaining insight into adaptation of M. tb. Most genomic studies of M. tb are based on single bacterial isolates that have been cultured for several weeks in vitro. However, in its natural human host, M. tb comprises complex, in some cases massive bacterial populations that diversify over the course of infection and cannot be wholly represented by a single genome. Recently, enrichment via hybridization capture has been used as a rapid diagnostic tool for TB, circumventing culturing protocols and enabling the recovery of M. tb genomes directly from sputum. This method has further applicability to the study of M. tb adaptation, as it enables a higher resolution and more direct analysis of M. tb genetic diversity within hosts with TB. Here we analyzed genomic material from M. tb and Mycobacterium bovis populations captured directly from sputum and from cultured samples using metagenomic and Pool-Seq approaches. We identified effects of sampling, patient, and sample type on bacterial genetic diversity. Bacterial genetic diversity was more variable and on average higher in sputum than in culture samples, suggesting that manipulation in the laboratory reshapes the bacterial population. Using outlier analyses, we identified candidate bacterial genetic loci mediating adaptation to these distinct environments. The study of M. tb in its natural human host is a powerful tool for illuminating host pathogen interactions and understanding the bacterial genetic underpinnings of virulence.

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.

GWAS for quantitative resistance phenotypes in Mycobacterium tuberculosis reveals resistance genes and regulatory regions

Drug resistance diagnostics that rely on the detection of resistance-related mutations could expedite patient care and TB eradication. We perform minimum inhibitory concentration testing for 12 anti-TB drugs together with Illumina whole-genome sequencing on 1452 clinical Mycobacterium tuberculosis (MTB) isolates. We evaluate genome-wide associations between mutations in MTB genes or non-coding regions and resistance, followed by validation in an independent data set of 792 patient isolates. We confirm associations at 13 non-canonical loci, with two involving non-coding regions. Promoter mutations are measured to have smaller average effects on resistance than gene body mutations. We estimate the heritability of the resistance phenotype to 11 anti-TB drugs and identify a lower than expected contribution from known resistance genes. This study highlights the complexity of the genomic mechanisms associated with the MTB resistance phenotype, including the relatively large number of potentially causal loci, and emphasizes the contribution of the non-coding portion of the genome.

Whole-Genome Sequencing in Relation to Resistance of Mycobacterium Tuberculosis

Tuberculosis, a disease caused by Mycobacterium tuberculosis, represents one of the deadliest infections worldwide. The incidence of resistant forms is increasing year by year; therefore, it is necessary to involve new methods for rapid diagnostics and treatment. One of the possible solutions is the use of whole-genome sequencing (WGS).

The WGS provides an identification of complete genome of the microorganism, including all genes responsible for resistance, in comparison with other genotypic methods (eg. Xpert MTB / RIF or Hain line-probes) that are capable to detect only basic genes. WGS data are available in 1-9 days and several online software tools (TBProfiler, CASTB, Mykrobe PredictorTB) are used for their interpretation and analysis, compared to 3-8 weeks in the case of classic phenotypic evaluation.

Furthermore, WGS predicts resistance to the first-line antituberculotics with a sensitivity of 85-100% and a specificity of 85-100%.

This review elucidates the importance and summarizes the current knowledge about the possible use of WGS in diagnosis and treatment of resistant forms of tuberculosis elucidates.

WGS of M. tuberculosis brings new possibilities for rapid and accurate diagnostics of resistant forms of tuberculosis. Introducing WGS into routine practice can help to reduce the spread of resistant forms of tuberculosis as well as to increase the success rate of the treatment, especially through an appropriate combination of antituberculotics ATs. Introduction of WGS into routine diagnostics can, in spite of the financial difficulty, significantly improve patient care.

Microbial evolutionary medicine: from theory to clinical practice

Medicine and clinical microbiology have traditionally attempted to identify and eliminate the agents that cause disease. However, this traditional approach is becoming inadequate for dealing with a changing disease landscape. Major challenges to human health are non-communicable chronic diseases, often driven by altered immunity and inflammation, and communicable infections from agents which harbour antibiotic resistance. This Review focuses on the so-called evolutionary medicine framework, to study how microbial communities influence human health. The evolutionary medicine framework aims to predict and manipulate microbial effects on human health by integrating ecology, evolutionary biology, microbiology, bioinformatics, and clinical expertise. We focus on the potential of evolutionary medicine to address three key challenges: detecting microbial transmission, predicting antimicrobial resistance, and understanding microbe-microbe and human-microbe interactions in health and disease, in the context of the microbiome.

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.

Genome-wide analysis of Mycobacterium tuberculosis polymorphisms reveals lineage-specific associations with drug resistance

Background

Continuing evolution of the Mycobacterium tuberculosis (Mtb) complex genomes associated with resistance to anti-tuberculosis drugs is threatening tuberculosis disease control efforts. Both multi- and extensively drug resistant Mtb (MDR and XDR, respectively) are increasing in prevalence, but the full set of Mtb genes involved are not known. There is a need for increased sensitivity of genome-wide approaches in order to elucidate the genetic basis of anti-microbial drug resistance and gain a more detailed understanding of Mtb genome evolution in a context of widespread antimicrobial therapy. Population structure within the Mtb complex, due to clonal expansion, lack of lateral gene transfer and low levels of recombination between lineages, may be reducing statistical power to detect drug resistance associated variants.

Results

To investigate the effect of lineage-specific effects on the identification of drug resistance associations, we applied genome-wide association study (GWAS) and convergence-based (PhyC) methods to multiple drug resistance phenotypes of a global dataset of Mtb lineages 2 and 4, using both lineage-wise and combined approaches. We identify both well-established drug resistance variants and novel associations; uniquely identifying associations for both lineage-specific and -combined GWAS analyses. We report 17 potential novel associations between antimicrobial resistance phenotypes and Mtb genomic variants.

Conclusions

For GWAS, both lineage-specific and -combined analyses are useful, whereas PhyC may perform better in contexts of greater diversity. Unique associations with XDR in lineage-specific analyses provide evidence of diverging evolutionary trajectories between lineages 2 and 4 in response to antimicrobial drug therapy.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5615-3) contains supplementary material, which is available to authorized users.

Deciphering Within-Host Microevolution of Mycobacterium tuberculosis through Whole-Genome Sequencing: the Phenotypic Impact and Way Forward

The Mycobacterium tuberculosis genome is more heterogenous and less genetically stable within the host than previously thought. Currently, only limited data exist on the within-host microevolution, diversity, and genetic stability of M. tuberculosis As a direct consequence, our ability to infer M. tuberculosis transmission chains and to understand the full complexity of drug resistance profiles in individual patients is limited. Furthermore, apart from the acquisition of certain drug resistance-conferring mutations, our knowledge on the function of genetic variants that emerge within a host and their phenotypic impact remains scarce. We performed a systematic literature review of whole-genome sequencing studies of serial and parallel isolates to summarize the knowledge on genetic diversity and within-host microevolution of M. tuberculosis We identified genomic loci of within-host emerged variants found across multiple studies and determined their functional relevance. We discuss important remaining knowledge gaps and finally make suggestions on the way forward.

Transmission dynamics study of tuberculosis isolates with whole genome sequencing in southern Sweden

Epidemiological contact tracing complemented with genotyping of clinical Mycobacterium tuberculosis isolates is important for understanding disease transmission. In Sweden, tuberculosis (TB) is mostly reported in migrant and homeless where epidemiologic contact tracing could pose a problem. This study compared epidemiologic linking with genotyping in a low burden country. Mycobacterium tuberculosis isolates (n = 93) collected at Scania University Hospital in Southern Sweden were analysed with the standard genotyping method mycobacterial interspersed repetitive units-variable number tandem repeats (MIRU-VNTR) and the results were compared with whole genome sequencing (WGS). Using a maximum of twelve single nucleotide polymorphisms (SNPs) as the upper threshold of genomic relatedness noted among hosts, we identified 18 clusters with WGS comprising 52 patients with overall pairwise genetic maximum distances ranging from zero to nine SNPs. MIRU-VNTR and WGS clustered the same isolates, although the distribution differed depending on MIRU-VNTR limitations. Both genotyping techniques identified clusters where epidemiologic linking was insufficient, although WGS had higher correlation with epidemiologic data. To summarize, WGS provided better resolution of transmission than MIRU-VNTR in a setting with low TB incidence. WGS predicted epidemiologic links better which could consolidate and correct the epidemiologically linked cases, avoiding thus false clustering.

Mutational convergence acts as a major player in adaptive parallel evolution of Shigella spp

Shigella spp., emerging from multiple origins of Escherichia coli, poses a significant health threat as a causative agent of bacillary dysentery. While multiple serotypes of four different species have evolved via independent lineages, Shigella spp. are designated as a single pathotype, primarily because of their common mode of pathogenesis. Convergent horizontal transfer events have so far been attributed to the commonalities in the evolution of virulence across diverse lineages. However, the role of mutational convergence in such parallel evolution is not yet well understood. Here we have carried out a genome-wide analysis of Shigella strains from all four species to detect the core genes (i.e. the ones present in all analyzed strains) acquiring convergent mutations of evolutionarily recent origin. Simulation studies show non-neutral accumulation of these convergent mutations across species, suggesting their adaptive role in the evolution of Shigella virulence. S. dysenteriae strain 197, representing highly virulent type 1 (Sd1) clone, carries excessively high number of core genes with recent convergent mutations compared to other analyzed strains. We propose that this high frequency of adaptive convergence in S. dysenteriae strain 197 could be linked to recent re-emergence of the Sd1 clone and its increased resistance to antimicrobials.

Whole genome sequencing for drug resistance determination in Mycobacterium tuberculosis

South Africa remains challenged with a high tuberculosis burden accompanied by an increase in drug resistant cases. We assessed the use of the Illumina MiSeq, a next-generation sequencing platform for whole genome sequencing, followed by bioinformatic analysis using a commercial software package to determine resistance to selected drugs used for Mycobacterium tuberculosis treatment in our setting. Whole genome sequencing shows potential as a diagnostic platform for the detection of drug resistance in Mycobacterium tuberculosis with the provision of information for several drugs simultaneously.

HomoplasyFinder: a simple tool to identify homoplasies on a phylogeny

A homoplasy is a nucleotide identity resulting from a process other than inheritance from a common ancestor. Importantly, by distorting the ancestral relationships between nucleotide sequences, homoplasies can change the structure of the phylogeny. Homoplasies can emerge naturally, especially under high selection pressures and/or high mutation rates, or be created during the generation and processing of sequencing data. Identification of homoplasies is critical, both to understand their influence on the analyses of phylogenetic data and to allow an investigation into how they arose. Here we present HomoplasyFinder, a java application that can be used as a stand-a-lone tool or within the statistical programming environment R. Within R and Java, HomoplasyFinder is shown to be able to automatically, and quickly, identify any homoplasies present in simulated and real phylogenetic data. HomoplasyFinder can easily be incorporated into existing analysis pipelines, either within or outside of R, allowing the user to quickly identify homoplasies to inform downstream analyses and interpretation.

Mycobacterial genomics and structural bioinformatics: opportunities and challenges in drug discovery

Of the more than 190 distinct species of Mycobacterium genus, many are economically and clinically important pathogens of humans or animals. Among those mycobacteria that infect humans, three species namely Mycobacterium tuberculosis (causative agent of tuberculosis), Mycobacterium leprae (causative agent of leprosy) and Mycobacterium abscessus (causative agent of chronic pulmonary infections) pose concern to global public health. Although antibiotics have been successfully developed to combat each of these, the emergence of drug-resistant strains is an increasing challenge for treatment and drug discovery. Here we describe the impact of the rapid expansion of genome sequencing and genome/pathway annotations that have greatly improved the progress of structure-guided drug discovery. We focus on the applications of comparative genomics, metabolomics, evolutionary bioinformatics and structural proteomics to identify potential drug targets. The opportunities and challenges for the design of drugs for M. tuberculosis, M. leprae and M. abscessus to combat resistance are discussed.

Evolution of Rifampin Resistance in Escherichia coli and Mycobacterium smegmatis Due to Substandard Drugs

Poor-quality medicines undermine the treatment of infectious diseases, such as tuberculosis, which require months of treatment with rifampin and other drugs. Rifampin resistance is a critical concern for tuberculosis treatment. While subtherapeutic doses of medicine are known to select for antibiotic resistance, the effect of drug degradation products on the evolution of resistance is unknown. Here, we demonstrate that substandard drugs that contain degraded active pharmaceutical ingredients select for gene alterations that confer resistance to standard drugs. We generated drug-resistant Escherichia coli and Mycobacterium smegmatis strains by serially culturing bacteria in the presence of the rifampin degradation product rifampin quinone. We conducted Sanger sequencing to identify mutations in rifampin-resistant populations. Strains resistant to rifampin quinone developed cross-resistance to the standard drug rifampin, with some populations showing no growth inhibition at maximum concentrations of rifampin. Sequencing of the rifampin quinone-treated strains indicated that they acquired mutations in the DNA-dependent RNA polymerase B subunit. These mutations were localized in the rifampin resistance-determining region (RRDR), consistent with other reports of rifampin-resistant E. coli and mycobacteria. Rifampin quinone-treated mycobacteria also had cross-resistance to other rifamycin class drugs, including rifabutin and rifapentine. Our results strongly suggest that substandard drugs not only hinder individual patient outcomes but also restrict future treatment options by actively contributing to the development of resistance to standard medicines.

A genome-wide association analysis reveals a potential role for recombination in the evolution of antimicrobial resistance in Burkholderia multivorans

Cystic fibrosis (CF) lung infections caused by members of the Burkholderia cepacia complex, such as Burkholderia multivorans, are associated with high rates of mortality and morbidity. We performed a population genomics study of 111 B. multivorans sputum isolates from one CF patient through three stages of infection including an early incident isolate, deep sampling of a one-year period of chronic infection occurring weeks before a lung transplant, and deep sampling of a post-transplant infection. We reconstructed the evolutionary history of the population and used a lineage-controlled genome-wide association study (GWAS) approach to identify genetic variants associated with antibiotic resistance. We found the incident isolate was basally related to the rest of the strains and more susceptible to antibiotics from three classes (β-lactams, aminoglycosides, quinolones). The chronic infection isolates diversified into multiple, distinct genetic lineages and showed reduced antimicrobial susceptibility to the same antibiotics. The post-transplant reinfection isolates derived from the same source as the incident isolate and were genetically distinct from the chronic isolates. They also had a level of susceptibility in between that of the incident and chronic isolates. We identified numerous examples of potential parallel pathoadaptation, in which multiple mutations were found in the same locus or even codon. The set of parallel pathoadaptive loci was enriched for functions associated with virulence and resistance. Our GWAS analysis identified statistical associations between a polymorphism in the ampD locus with resistance to β-lactams, and polymorphisms in an araC transcriptional regulator and an outer membrane porin with resistance to both aminoglycosides and quinolones. Additionally, these three loci were independently mutated four, three and two times, respectively, providing further support for parallel pathoadaptation. Finally, we identified a minimum of 14 recombination events, and observed that loci carrying putative parallel pathoadaptations and polymorphisms statistically associated with β-lactam resistance were over-represented in these recombinogenic regions.

Cystic fibrosis (CF) is the most common lethal genetic disorder affecting individuals of European descent. Most CF patients die at a young age due to chronic lung infections. Among the organisms involved in these infections are bacteria from the Burkholderia cepacia complex (BCC), which are strongly associated with poor clinical prognosis. This study examines how the most prevalent BCC species among CF patients, B. multivorans, evolves within a single CF patient by studying the first B. multivorans isolate recovered from the patient, one hundred isolates recovered over a one year period during the chronic infection phase, and an additional ten isolates recovered after the reinfection of the transplanted lungs. We found that B. multivorans diversify phenotypically and genetically within the CF lung over the course of the infection, and evolves into a complex population during the chronic infection phase. We found that isolates collected from the post-transplant reinfection were more closely related to descendants of the original isolate rather than those recovered in the chronic infection. We identify genetic variants statistically associated with resistance to the antibiotics, and showed that some of these variants were found in regions that show patterns of recombination (genetic exchange) between strains. We also found that genes which were mutated multiple times during overall infection were more likely to be found in regions showing signals consistent with recombination. The presence of multiple independent mutations in a gene is a very strong signal that the gene helps bacteria adapt to their environment. Overall, this study provides insight into how pathogens adapt to the host during long-term infections, specific genes associated with antibiotic resistance, and the origin of new and recurrent infections.

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.

A fast and agnostic method for bacterial genome-wide association studies: Bridging the gap between k-mers and genetic events

Genome-wide association study (GWAS) methods applied to bacterial genomes have shown promising results for genetic marker discovery or detailed assessment of marker effect. Recently, alignment-free methods based on k-mer composition have proven their ability to explore the accessory genome. However, they lead to redundant descriptions and results which are sometimes hard to interpret. Here we introduce DBGWAS, an extended k-mer-based GWAS method producing interpretable genetic variants associated with distinct phenotypes. Relying on compacted De Bruijn graphs (cDBG), our method gathers cDBG nodes, identified by the association model, into subgraphs defined from their neighbourhood in the initial cDBG. DBGWAS is alignment-free and only requires a set of contigs and phenotypes. In particular, it does not require prior annotation or reference genomes. It produces subgraphs representing phenotype-associated genetic variants such as local polymorphisms and mobile genetic elements (MGE). It offers a graphical framework which helps interpret GWAS results. Importantly it is also computationally efficient-experiments took one hour and a half on average. We validated our method using antibiotic resistance phenotypes for three bacterial species. DBGWAS recovered known resistance determinants such as mutations in core genes in Mycobacterium tuberculosis, and genes acquired by horizontal transfer in Staphylococcus aureus and Pseudomonas aeruginosa-along with their MGE context. It also enabled us to formulate new hypotheses involving genetic variants not yet described in the antibiotic resistance literature. An open-source tool implementing DBGWAS is available at https://gitlab.com/leoisl/dbgwas.

A Putative Zn2Cys6 Transcription Factor Is Associated With Isoprothiolane Resistance in Magnaporthe oryzae

Isoprothiolane (IPT), a systemic fungicide, has been applied to control rice blast since the 1970s. Although resistance to IPT has been observed, the mechanism of resistance still has not been fully elucidated. In this study, nucleotide polymorphisms were detected between two IPT-resistant mutants generated in the lab, and their parental wild type isolates using a whole-genome sequencing approach. In the genomes of the two resistant mutants, single point mutations were identified in a gene encoding a Zn2Cys6 transcription factor-like protein. Notably, either knocking out the gene or replacing the wild type allele with the mutant allele (R343W) in a wild type isolate resulted in resistance to IPT, indicating that the gene is associated with IPT resistance, and thus was designated as MoIRR (Magnaporthe oryzae isoprothiolane resistance related). Along with point mutations R343W in mutant 1a_mut, and R345C in 1c_mut, a 16 bp insertion in 6c_mut was also located in the Fungal_TF_MHR domain of MoIRR, revealing that this domain may be the core element for IPT resistance. In addition, IPT-resistant mutants and transformants showed cross-resistance with iprobenfos (IBP), which was consistent with previous observations. These results indicated that MoIRR is strongly connected to resistance to choline biosynthesis inhibitor (CBI), and further work should focus on investigating downstream effects of MoIRR.

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many publicly available datasets describing its AMR characteristics demand disparate data-type analyses. Here, we develop a reference strain-agnostic computational platform that uses machine learning approaches, complemented by both genetic interaction analysis and 3D structural mutation-mapping, to identify signatures of AMR evolution to 13 antibiotics. This platform is applied to 1595 sequenced strains to yield four key results. First, a pan-genome analysis shows that M. tuberculosis is highly conserved with sequenced variation concentrated in PE/PPE/PGRS genes. Second, the platform corroborates 33 genes known to confer resistance and identifies 24 new genetic signatures of AMR. Third, 97 epistatic interactions across 10 resistance classes are revealed. Fourth, detailed structural analysis of these genes yields mechanistic bases for their selection. The platform can be used to study other human pathogens.

Global expansion of Mycobacterium tuberculosis lineage 4 shaped by colonial migration and local adaptation

On the basis of population genomic and phylogeographic analyses of 1669 Mycobacterium tuberculosis lineage 4 (L4) genomes, we find that dispersal of L4 has been completely dominated by historical migrations out of Europe. We demonstrate an intimate temporal relationship between European colonial expansion into Africa and the Americas and the spread of L4 tuberculosis (TB). Markedly, in the age of antibiotics, mutations conferring antimicrobial resistance overwhelmingly emerged locally (at the level of nations), with minimal cross-border transmission of resistance. The latter finding was found to reflect the relatively recent emergence of these mutations, as a similar degree of local restriction was observed for susceptible variants emerging on comparable time scales. The restricted international transmission of drug-resistant TB suggests that containment efforts at the level of individual countries could be successful.

Insights into the processes that drive the evolution of drug resistance in Mycobacterium tuberculosis

At present, the successful transmission of drug-resistant Mycobacterium tuberculosis, including multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains, in human populations, threatens tuberculosis control worldwide. Differently from many other bacteria, M. tuberculosis drug resistance is acquired mainly through mutations in specific drug resistance-associated genes. The panel of mutations is highly diverse, but depends on the affected gene and M. tuberculosis genetic background. The variety of genetic profiles observed in drug-resistant clinical isolates underlines different evolutionary trajectories towards multiple drug resistance, although some mutation patterns are prominent. This review discusses the intrinsic processes that may influence drug resistance evolution in M. tuberculosis, such as mutation rate, drug resistance-associated mutations, fitness cost, compensatory mutations and epistasis. This knowledge should help to better predict the risk of emergence of highly resistant M. tuberculosis strains and to develop new tools and strategies to limit the development and spread of MDR and XDR strains.

Genetics and roadblocks of drug resistant tuberculosis

Considering the extensive evolutionary history of Mycobacterium tuberculosis, anti-Tuberculosis (TB) drug therapy exerts a recent selective pressure. However, in a microorganism devoid of horizontal gene transfer and with a strictly clonal populational structure such as M. tuberculosis the usual, but not sole, path to overcome drug susceptibility is through de novo mutations on a relatively strict set of genes. The possible allelic diversity that can be associated with drug resistance through several mechanisms such as target alteration or target overexpression, will dictate how these genes can become associated with drug resistance. The success demonstrated by this pathogenic microbe in this latter process and its ability to spread is currently one of the major obstacles to an effective TB elimination. This article reviews the action mechanism of the more important anti-TB drugs, including bedaquiline and delamanid, along with new findings on specific resistance mechanisms. With the development, validation and endorsement of new in vitro molecular tests for drug resistance, knowledge on these resistance mechanisms and microevolutionary dynamics leading to the emergence and fixation of drug resistance mutations within the host is highly important. Additionally, the fitness toll imposed by resistance development is also herein discussed together with known compensatory mechanisms. By elucidating the possible mechanisms that enable one strain to reacquire the original fitness levels, it will be theoretically possible to make more informed decisions and develop novel strategies that can force M. tuberculosis microevolutionary trajectory down through a path of decreasing fitness levels.

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.

Functional Analysis of Genetic Variations in Surfactant Protein D in Mycobacterial Infection and Their Association With Tuberculosis

Surfactant proteins (SPs)-A and -D are C-type lectins of the collectin family and function in the clearance of infectious particles in the lungs. Some polymorphisms of SPs that give rise to amino acid changes have been found to affect their function. Several SP-A gene polymorphisms have been reported to be associated with respiratory infection diseases, such as tuberculosis (TB). However, the relationship between surfactant proteins D (SP-D) polymorphisms and TB is still unclear. To study the associations between SP-D polymorphisms and TB, the correlations of SP-D polymorphisms with TB were examined in a case-control study, which included 364 patients with TB and 177 control subjects. In addition, we cloned two major SP-D exonic polymorphism C92T (rs721917) and A538G (rs2243639) constructs and used these for in vitro assays. The effects of SP-D polymorphisms on agglutination and other interactions with Mycobacterium bovis bacillus Calmette-Guérin (M. bovis BCG) were evaluated. In comparison with SP-D 92C (amino acid residue 16, Threonine), our results showed that SP-D 92T (amino acid residue 16, Methionine) had a lower binding ability to M. bovis BCG, a lower capacity to inhibit phagocytosis, lesser aggregation, poorer survival of bacillus Calmette-Guérin (BCG)-infected MH-S cells, and less inhibition of intracellular growth of M. bovis BCG. The case-control association study showed that the 92T homozygous genotype was a risk factor for TB. However, a lesser effect was seen for polymorphism A538G. In conclusion, the results of functional and genetic analyses of SP-D variants consistently showed that the SP-D 92T variant increased susceptibility to TB, which further confirmed the role of SP-D in pulmonary innate immunity against mycobacterial infection.

Applications of genomics to slow the spread of multidrug-resistant Neisseria gonorrhoeae

Infections with Neisseria gonorrhoeae, a sexually transmitted pathogen that causes urethritis, cervicitis, and more severe complications, are increasing. Gonorrhea is typically treated with antibiotics; however, N. gonorrhoeae has rapidly acquired resistance to many antibiotic classes, and lineages with reduced susceptibility to the currently recommended therapies are emerging worldwide. In this review, we discuss the contributions of whole genome sequencing (WGS) to our understanding of resistant N. gonorrhoeae. Genomics has illuminated the evolutionary origins and population structure of N. gonorrhoeae and the magnitude of horizontal gene transfer within and between Neisseria species. WGS can be used to predict the susceptibility of N. gonorrhoeae based on known resistance determinants, track the spread of these determinants throughout the N. gonorrhoeae population, and identify novel loci contributing to resistance. WGS has also allowed more detailed epidemiological analysis of transmission of N. gonorrhoeae between individuals and populations than previously used typing methods. Ongoing N. gonorrhoeae genomics will complement other laboratory techniques to understand the biology and evolution of the pathogen, improve diagnostics and treatment in the clinic, and inform public health policies to limit the impact of antibiotic resistance.

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

To examine the transmission dynamics of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients in Ho Chi Minh City, Vietnam, we sequenced the whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data identify an underlying burden of disease caused by the endemic Mtb lineage 1 associated with the activation of long-term latent infection, and a threefold higher burden associated with the more recently introduced Beijing lineage and lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than the endemic lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify an alteration in the ESX-5 type VII-secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.

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

To examine the transmission dynamics of Mycobacterium tuberculosis (Mtb) isolated from tuberculosis patients in Ho Chi Minh City, Vietnam, we sequenced the whole genomes of 1,635 isolates and compared these with 3,144 isolates from elsewhere. The data identify an underlying burden of disease caused by the endemic Mtb lineage 1 associated with the activation of long-term latent infection, and a threefold higher burden associated with the more recently introduced Beijing lineage and lineage 4 Mtb strains. We find that Beijing lineage Mtb is frequently transferred between Vietnam and other countries, and detect higher levels of transmission of Beijing lineage strains within this host population than the endemic lineage 1 Mtb. Screening for parallel evolution of Beijing lineage-associated SNPs in other Mtb lineages as a signal of positive selection, we identify an alteration in the ESX-5 type VII-secreted protein EsxW, which could potentially contribute to the enhanced transmission of Beijing lineage Mtb in Vietnamese and other host populations.

Whole genome sequencing data of 1110 Mycobacterium tuberculosis isolates identifies insertions and deletions associated with drug resistance

Background

Drug resistance in Mycobacterium tuberculosis (MTB) is one of the major challenges in tuberculosis (TB) treatment. However, known mutations cannot explain all of the cases of resistance and little research has focused on the relationship between insertions / deletions (indels) and drug resistance.

Results

Here, we retrieved whole genome sequencing data of 743 drug-resistant MTB strains and 367 pan-susceptible strains from TB patients from the public domain to identify novel genomic markers of drug resistance. A total of 20 region markers containing genes and intergenic regions (IGRs) with significant statistical correlation with antibiotic resistance were revealed, four of which have been previously reported to be associated with drug resistance. In addition, 83 point markers containing frameshift (FS) mutations and IGR indels were also identified independently based on differences in their incidence rates between drug-sensitive and -resistant strains. Among the 83 point markers, eight indels were detected in known drug-associated genes or IGRs. Furthermore, the overlap between 20 region markers and 83 point markers further indicated their associations with drug resistance. The markers identified were involved in essential bacterial metabolic functions, including cell wall and transmembrane transporter functions. A strong correlation between FS mutations and mutations in DNA repair genes including I21V in alkA, R48G in mutT4 and P2R in nth was also found.

Conclusions

This study identified a set of novel genetic markers with FS mutations and IGR indels associated with MTB drug resistance, which greatly broadens the pool of mutations related to MTB drug resistance. This insight may be important in identifying novel mechanisms of drug resistance in MTB.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4734-6) contains supplementary material, which is available to authorized users.

DNA Replication Fidelity in the Mycobacterium tuberculosis Complex

Mycobacterium tuberculosis is genetically isolated, with no evidence for horizontal gene transfer or the acquisition of episomal genetic information in the modern evolution of strains of the Mycobacterium tuberculosis complex. When considered in the context of the specific features of the disease M. tuberculosis causes (e.g., transmission via cough aerosol, replication within professional phagocytes, subclinical persistence, and stimulation of a destructive immune pathology), this implies that to understand the mechanisms ensuring preservation of genomic integrity in infecting mycobacterial populations is to understand the source of genetic variation, including the emergence of microdiverse sub-populations that may be linked to the acquisition of drug resistance. In this chapter, we focus on mechanisms involved in maintaining DNA replication fidelity in M. tuberculosis, and consider the potential to target components of the DNA replication machinery as part of novel therapeutic regimens designed to curb the emerging threat of drug-resistance.

TnSeq of Mycobacterium tuberculosis clinical isolates reveals strain-specific antibiotic liabilities

Once considered a phenotypically monomorphic bacterium, there is a growing body of work demonstrating heterogeneity among Mycobacterium tuberculosis (Mtb) strains in clinically relevant characteristics, including virulence and response to antibiotics. However, the genetic and molecular basis for most phenotypic differences among Mtb strains remains unknown. To investigate the basis of strain variation in Mtb, we performed genome-wide transposon mutagenesis coupled with next-generation sequencing (TnSeq) for a panel of Mtb clinical isolates and the reference strain H37Rv to compare genetic requirements for in vitro growth across these strains. We developed an analytic approach to identify quantitative differences in genetic requirements between these genetically diverse strains, which vary in genomic structure and gene content. Using this methodology, we found differences between strains in their requirements for genes involved in fundamental cellular processes, including redox homeostasis and central carbon metabolism. Among the genes with differential requirements were katG, which encodes the activator of the first-line antitubercular agent isoniazid, and glcB, which encodes malate synthase, the target of a novel small-molecule inhibitor. Differences among strains in their requirement for katG and glcB predicted differences in their response to these antimicrobial agents. Importantly, these strain-specific differences in antibiotic response could not be predicted by genetic variants identified through whole genome sequencing or by gene expression analysis. Our results provide novel insight into the basis of variation among Mtb strains and demonstrate that TnSeq is a scalable method to predict clinically important phenotypic differences among Mtb strains.

Potential Application of Digitally Linked Tuberculosis Diagnostics for Real-Time Surveillance of Drug-Resistant Tuberculosis Transmission: Validation and Analysis of Test Results

BACKGROUND

Tuberculosis (TB) is the highest-mortality infectious disease in the world and the main cause of death related to antimicrobial resistance, yet its surveillance is still paper-based. Rifampicin-resistant TB (RR-TB) is an urgent public health crisis. The World Health Organization has, since 2010, endorsed a series of rapid diagnostic tests (RDTs) that enable rapid detection of drug-resistant strains and produce large volumes of data. In parallel, most high-burden countries have adopted connectivity solutions that allow linking of diagnostics, real-time capture, and shared repository of these test results. However, these connected diagnostics and readily available test results are not used to their full capacity, as we have yet to capitalize on fully understanding the relationship between test results and specific rpoB mutations to elucidate its potential application to real-time surveillance.

OBJECTIVE

We aimed to validate and analyze RDT data in detail, and propose the potential use of connected diagnostics and associated test results for real-time evaluation of RR-TB transmission.

METHODS

We selected 107 RR-TB strains harboring 34 unique rpoB mutations, including 30 within the rifampicin resistance-determining region (RRDR), from the Belgian Coordinated Collections of Microorganisms, Antwerp, Belgium. We subjected these strains to Xpert MTB/RIF, GenoType MTBDRplus v2.0, and Genoscholar NTM + MDRTB II, the results of which were validated against the strains' available rpoB gene sequences. We determined the reproducibility of the results, analyzed and visualized the probe reactions, and proposed these for potential use in evaluating transmission.

RESULTS

The RDT probe reactions detected most RRDR mutations tested, although we found a few critical discrepancies between observed results and manufacturers' claims. Based on published frequencies of probe reactions and RRDR mutations, we found specific probe reactions with high potential use in transmission studies: Xpert MTB/RIF probes A, Bdelayed, C, and Edelayed; Genotype MTBDRplus v2.0 WT2, WT5, and WT6; and Genoscholar NTM + MDRTB II S1 and S3. Inspection of probe reactions of disputed mutations may potentially resolve discordance between genotypic and phenotypic test results.

CONCLUSIONS

We propose a novel approach for potential real-time detection of RR-TB transmission through fully using digitally linked TB diagnostics and shared repository of test results. To our knowledge, this is the first pragmatic and scalable work in response to the consensus of world-renowned TB experts in 2016 on the potential of diagnostic connectivity to accelerate efforts to eliminate TB. This is evidenced by the ability of our proposed approach to facilitate comparison of probe reactions between different RDTs used in the same setting. Integrating this proposed approach as a plug-in module to a connectivity platform will increase usefulness of connected TB diagnostics for RR-TB outbreak detection through real-time investigation of suspected RR-TB transmission cases based on epidemiologic linking.

Mycobacterium tuberculosis Whole Genome Sequences From Southern India Suggest Novel Resistance Mechanisms and the Need for Region-Specific Diagnostics

Background.

India is home to 25% of all tuberculosis cases and the second highest number of multidrug resistant cases worldwide. However, little is known about the genetic diversity and resistance determinants of Indian Mycobacterium tuberculosis, particularly for the primary lineages found in India, lineages 1 and 3.

Methods.

We whole genome sequenced 223 randomly selected M. tuberculosis strains from 196 patients within the Tiruvallur and Madurai districts of Tamil Nadu in Southern India. Using comparative genomics, we examined genetic diversity, transmission patterns, and evolution of resistance.

Results.

Genomic analyses revealed (11) prevalence of strains from lineages 1 and 3, (11) recent transmission of strains among patients from the same treatment centers, (11) emergence of drug resistance within patients over time, (11) resistance gained in an order typical of strains from different lineages and geographies, (11) underperformance of known resistance-conferring mutations to explain phenotypic resistance in Indian strains relative to studies focused on other geographies, and (11) the possibility that resistance arose through mutations not previously implicated in resistance, or through infections with multiple strains that confound genotype-based prediction of resistance.

Conclusions.

In addition to substantially expanding the genomic perspectives of lineages 1 and 3, sequencing and analysis of M. tuberculosis whole genomes from Southern India highlight challenges of infection control and rapid diagnosis of resistant tuberculosis using current technologies. Further studies are needed to fully explore the complement of diversity and resistance determinants within endemic M. tuberculosis populations.

Classification of pathogenic microbes using a minimal set of single nucleotide polymorphisms derived from whole genome sequences

In a context specific manner, Intra-species genomic variation plays an important role in phenotypic diversity observed among pathogenic microbes. Efficient classification of these pathogens is important for diagnosis and treatment of several infectious diseases. NGS technologies have provided access to wealth of data that can be utilized to discover important markers for pathogen classification. In this paper, we described three different approaches (Jensen-Shannon divergence, random forest and Shewhart control chart) for identification of a minimal set of SNPs that can be used for classification of organisms. These methods are generic and can be implemented for analysis of any organism. We have shown usefulness of these approaches for analysis of Mycobacterium tuberculosis and Escherichia coli isolates. We were able to identify a minimal set of 18 SNPs that can be used as molecular markers for phylogroup based classification and 8 SNPs for pathogroup based classification of E. coli.