Signatures of Selection at Drug Resistance Loci in Mycobacterium tuberculosis

Ongoing evolution of the Mycobacterium tuberculosis lactate dehydrogenase reveals the pleiotropic effects of bacterial adaption to host pressure

The bacterial determinants that facilitate Mycobacterium tuberculosis (Mtb) adaptation to the human host environment are poorly characterized. We have sought to decipher the pressures facing the bacterium in vivo by assessing Mtb genes that are under positive selection in clinical isolates. One of the strongest targets of selection in the Mtb genome is lldD2, which encodes a quinone-dependent L-lactate dehydrogenase (LldD2) that catalyzes the oxidation of lactate to pyruvate. Lactate accumulation is a salient feature of the intracellular environment during infection and lldD2 is essential for Mtb growth in macrophages. We determined the extent of lldD2 variation across a set of global clinical isolates and defined how prevalent mutations modulate Mtb fitness. We show the stepwise nature of lldD2 evolution that occurs as a result of ongoing lldD2 selection in the background of ancestral lineage-defining mutations and demonstrate that the genetic evolution of lldD2 additively augments Mtb growth in lactate. Using quinone-dependent antibiotic susceptibility as a functional reporter, we also find that the evolved lldD2 mutations functionally increase the quinone-dependent activity of LldD2. Using 13C-lactate metabolic flux tracing, we find that lldD2 is necessary for robust incorporation of lactate into central carbon metabolism. In the absence of lldD2, label preferentially accumulates in dihydroxyacetone phosphate (DHAP) and glyceraldehyde-3-phosphate (G3P) and is associated with a discernible growth defect, providing experimental evidence for accrued lactate toxicity via the deleterious buildup of sugar phosphates. The evolved lldD2 variants increase lactate incorporation to pyruvate while altering triose phosphate flux, suggesting both an anaplerotic and detoxification benefit to lldD2 evolution. We further show that the mycobacterial cell is transcriptionally sensitive to the changes associated with altered lldD2 activity which affect the expression of genes involved in cell wall lipid metabolism and the ESX- 1 virulence system. Together, these data illustrate a multifunctional role of LldD2 that provides context for the selective advantage of lldD2 mutations in adapting to host stress.

Clustering minimal inhibitory concentration data through Bayesian mixture models: An application to detect Mycobacterium tuberculosis resistance mutations

Antimicrobial resistance is becoming a major threat to public health throughout the world. Researchers are attempting to contrast it by developing both new antibiotics and patient-specific treatments. In the second case, whole-genome sequencing has had a huge impact in two ways: first, it is becoming cheaper and faster to perform whole-genome sequencing, and this makes it competitive with respect to standard phenotypic tests; second, it is possible to statistically associate the phenotypic patterns of resistance to specific mutations in the genome. Therefore, it is now possible to develop catalogues of genomic variants associated with resistance to specific antibiotics, in order to improve prediction of resistance and suggest treatments. It is essential to have robust methods for identifying mutations associated to resistance and continuously updating the available catalogues. This work proposes a general method to study minimal inhibitory concentration distributions and to identify clusters of strains showing different levels of resistance to antimicrobials. Once the clusters are identified and strains allocated to each of them, it is possible to perform regression method to identify with high statistical power the mutations associated with resistance. The method is applied to a new 96-well microtiter plate used for testing Mycobacterium tuberculosis.

Decoding a cryptic mechanism of metronidazole resistance among globally disseminated fluoroquinolone-resistant Clostridioides difficile

Severe outbreaks and deaths have been linked to the emergence and global spread of fluoroquinolone-resistant Clostridioides difficile over the past two decades. At the same time, metronidazole, a nitro-containing antibiotic, has shown decreasing clinical efficacy in treating C. difficile infection (CDI). Most metronidazole-resistant C. difficile exhibit an unusual resistance phenotype that can only be detected in susceptibility tests using molecularly intact heme. Here, we describe the mechanism underlying this trait. We find that most metronidazole-resistant C. difficile strains carry a T-to-G mutation (which we term PnimB^G) in the promoter of gene nimB, resulting in constitutive transcription. Silencing or deleting nimB eliminates metronidazole resistance. NimB is related to Nim proteins that are known to confer resistance to nitroimidazoles. We show that NimB is a heme-dependent flavin enzyme that degrades nitroimidazoles to amines lacking antimicrobial activity. Furthermore, occurrence of the PnimB^G mutation is associated with a Thr82Ile substitution in DNA gyrase that confers fluoroquinolone resistance in epidemic strains. Our findings suggest that the pandemic of fluoroquinolone-resistant C. difficile occurring over the past few decades has also been characterized by widespread resistance to metronidazole.

Comparative Genomics of Streptococcus oralis Identifies Large Scale Homologous Recombination and a Genetic Variant Associated with Infection

The viridans group streptococci (VGS) are a large consortium of commensal streptococci that colonize the human body. Many species within this group are opportunistic pathogens causing bacteremia and infective endocarditis (IE), yet little is known about why some strains cause invasive disease. Identification of virulence determinants is complicated by the difficulty of distinguishing between the closely related species of this group. Here, we analyzed genomic data from VGS that were isolated from blood cultures in patients with invasive infections and oral swabs of healthy volunteers and then determined the best-performing methods for species identification. Using whole-genome sequence data, we characterized the population structure of a diverse sample of Streptococcus oralis isolates and found evidence of frequent recombination. We used multiple genome-wide association study tools to identify candidate determinants of invasiveness. These tools gave consistent results, leading to the discovery of a single synonymous single nucleotide polymorphism (SNP) that was significantly associated with invasiveness. This SNP was within a previously undescribed gene that was conserved across the majority of VGS species. Using the growth in the presence of human serum and a simulated infective endocarditis vegetation model, we were unable to identify a phenotype for the enriched allele in laboratory assays, suggesting a phenotype may be specific to natural infection. These data highlighted the power of analyzing natural populations for gaining insight into pathogenicity, particularly for organisms with complex population structures like the VGS. IMPORTANCE The viridians group streptococci (VGS) are a large collection of closely related commensal streptococci, with many being opportunistic pathogens causing invasive diseases, such as bacteremia and infective endocarditis. Little is known about virulence determinants in these species, and there is a distinct lack of genomic information available for the VGS. In this study, we collected VGS isolates from invasive infections and healthy volunteers and performed whole-genome sequencing for a suite of downstream analyses. We focused on a diverse sample of Streptococcus oralis genomes and identified high rates of recombination in the population as well as a single genome variant highly enriched in invasive isolates. The variant lies within a previously uncharacterized gene, nrdM, which shared homology with the anaerobic ribonucleoside triphosphate reductase, nrdD, and was highly conserved among VGS. This work increased our knowledge of VGS genomics and indicated that differences in virulence potential among S. oralis isolates were, at least in part, genetically determined.

Hit Compounds and Associated Targets in Intracellular Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb), the etiological agent of tuberculosis, is one of the most devastating infectious agents in the world. Chemical-genetic characterization through in vitro evolution combined with whole genome sequencing analysis was used identify novel drug targets and drug resistance genes in Mtb associated with its intracellular growth in human macrophages. We performed a genome analysis of 53 Mtb mutants resistant to 15 different hit compounds. We found nonsynonymous mutations/indels in 30 genes that may be associated with drug resistance acquisitions. Beyond confirming previously identified drug resistance mechanisms such as rpoB and lead targets reported in novel anti-tuberculosis drug screenings such as mmpL3, ethA, and mbtA, we have discovered several unrecognized candidate drug targets including prrB. The exploration of the Mtb chemical mutant genomes could help novel drug discovery and the structural biology of compounds and associated mechanisms of action relevant to tuberculosis treatment.

Rapid adaptation of a complex trait during experimental evolution of Mycobacterium tuberculosis

Tuberculosis (TB), caused by Mycobacterium tuberculosis (M. tb), is a leading cause of death due to infectious disease. TB is not traditionally associated with biofilms, but M. tb biofilms are linked with drug and immune tolerance and there is increasing recognition of their contribution to the recalcitrance of TB infections. Here, we used M. tb experimental evolution to investigate this complex phenotype and identify candidate loci controlling biofilm formation. We identified novel candidate loci, adding to our understanding of the genetic architecture underlying M. tb biofilm development. Under selective pressure to grow as a biofilm, regulatory mutations rapidly swept to fixation and were associated with changes in multiple traits, including extracellular matrix production, cell size, and growth rate. Genetic and phenotypic paths to enhanced biofilm growth varied according to the genetic background of the parent strain, suggesting that epistatic interactions are important in M. tb adaptation to changing environments.

Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection

SignificancePrevious attempts to identify the action of natural selection in the Mycobacterium tuberculosis complex (MTBC) were limited by sample size and averaging across time and lineages. We investigate changes in selective pressures across time for every single gene of the MTBC. We developed a methodology to analyze temporal signals of selection in a large dataset (∼5,000 complete genomes) and showed that 1) almost half of the genes seem to have been under positive selection at some point in time; 2) experimentally confirmed epitopes tend to accumulate more mutations in deeper branches than in external branches; and 3) temporal signals identify genes that were conserved in the past but under positive selection in the present, suggesting ongoing adaptation to the host.

Structural and functional characterization of a hypothetical protein in the RD7 region in clinical isolates of Mycobacterium tuberculosis - an in silico approach to candidate vaccines

Background

Mycobacterium tuberculosis has been ravaging humans by inflicting respiratory tuberculosis since centuries. Bacillus Calmette Guerine (BCG) is the only vaccine available for tuberculosis, and it is known to be poorly effective against adult tuberculosis. Proteins belonging to the ESAT-6 family and PE/PPE family show immune responses and are included in different vaccine trials. Herein, we study the functional and structural characterization of a 248 amino acid long putative protein novel hypothetical protein 1 (NHP1) present in the RD7 region of Mycobacterium tuberculosis (identified first by subtractive hybridization in the clinical isolate RGTB123) using bioinformatics tools.

Results

Physicochemical properties were studied using Expasy ProtParam and SMS software. We predicted different B-cell and T-cell epitopes by using the immune epitope database (IEDB) and also tested antigenicity, immunogenicity, and allergenicity. Secondary structure of the protein predicted 30% alpha helices, 20% beta strands, and 48% random coils. Tertiary structure of the protein was predicted using the Robetta server using the Mycobacterium smegmatis protein as the putative protein with homology. Structural evaluations were done with Ramachandran plot analysis, ProSA-web, and VERIFY3D, and with GalaxyWEB server, a more stable structure was validated with good stereo chemical properties.

Conclusion

The present study of a subtracted genomic locus using various bioinformatics tools indicated good immunological properties of the putative mycobacterial protein, NHP1. Evidence obtained from the analyses of NHP1 using structure prediction tools strongly point to the fact that NHP1 is an ancient protein having flavodoxin folding structure with ATP binding sites. Positive scores were obtained for antigenicity, immunogenicity, and virulence too, implying the possibility of NHP1 to be a potential vaccine candidate. Such computational studies might give clues for developing newer vaccines for tuberculosis, which is the need of the hour.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43141-022-00340-5.

Drug-Resistant Characteristics, Genetic Diversity, and Transmission Dynamics of Rifampicin-Resistant Mycobacterium tuberculosis in Hunan, China, Revealed by Whole-Genome Sequencing

To gain a deep insight into the additional drug-resistant profiles, genetic diversity, and transmission dynamics of rifampicin-resistant tuberculosis (RR-TB) circulating in Hunan province, drug susceptibility testing and whole-genome-sequencing were performed among RR-TB strains collected from Jan. 2013 to Jun. 2018 in Hunan province. A total of 124 RR-TB strains were recovered successfully and included into the final analysis. Lineage 2.2.1 was the dominant sublineage, accounting for 72.6% (90/124), followed by lineage 4.5 (11.3%, 14/124), lineage 4.4 (8.1%, 10/124), lineage 4.2 (6.5%, 8/124) and lineage 2.2.2 (1.6%, 2/124). Overall, 83.1% (103/124) and 3.2% (4/124) of RR-TB were MDR-TB and XDR-TB, respectively. Nearly 30% of RR-TB isolates were resistant to fluoroquinolones, and 26.6% (33/124) were pre-XDR-TB. Moreover, 30.6% (38/124) of RR-TB strains were identified as phenotypically resistance to pyrazinamide. Totally, 17 clusters containing 48 (38.7%, 48/124) RR-TB strains were identified, ranging in size from 2 to 10 isolates. No significant difference was detected in clustering rate between lineage 2 and lineage 4 (χ² = 0.027, P = 0.870). Our study revealed the complexity of RR-TB strains circulating in Hunan province with complex additional drug-resistant profile and relatively higher clustering rates. Comprehensive information based on WGS should be used to guide the design of treatment regimens and tailor public interventions. IMPORTANCE Comprehensive information such as genetic background and drug-resistant profile of MTB strains could help to tailor public interventions. However, these data are limited in Hunan province, one of the provinces with high-TB burden in China. So, this study aimed to provide us with deep insight into the molecular epidemiology of RR-TB isolates circulating in Hunan province by combining phenotypic drug susceptibility testing and whole-genome sequencing. To our knowledge, this is the first study to use whole-genome sequencing data of RR-TB strains spanning more than 5 years for molecular epidemiology analysis in Hunan province, which allows us to identify genetic background information and clustered strains more accurately. Our study revealed the complexity of RR-TB strains circulating in Hunan province with complex additional drug-resistant profile and relatively higher clustering rates. Comprehensive information based on WGS should be used to guide the design of treatment regimens and tailor public interventions.

GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes

The dN/dS ratio provides evidence of adaptation or functional constraint in protein-coding genes by quantifying the relative excess or deficit of amino acid-replacing versus silent nucleotide variation. Inexpensive sequencing promises a better understanding of parameters, such as dN/dS, but analyzing very large data sets poses a major statistical challenge. Here, I introduce genomegaMap for estimating within-species genome-wide variation in dN/dS, and I apply it to 3,979 genes across 10,209 tuberculosis genomes to characterize the selection pressures shaping this global pathogen. GenomegaMap is a phylogeny-free method that addresses two major problems with existing approaches: 1) It is fast no matter how large the sample size and 2) it is robust to recombination, which causes phylogenetic methods to report artefactual signals of adaptation. GenomegaMap uses population genetics theory to approximate the distribution of allele frequencies under general, parent-dependent mutation models. Coalescent simulations show that substitution parameters are well estimated even when genomegaMap’s simplifying assumption of independence among sites is violated. I demonstrate the ability of genomegaMap to detect genuine signatures of selection at antimicrobial resistance-conferring substitutions in Mycobacterium tuberculosis and describe a novel signature of selection in the cold-shock DEAD-box protein A gene deaD/csdA. The genomegaMap approach helps accelerate the exploitation of big data for gaining new insights into evolution within species.

Genome-wide analysis in Escherichia coli unravels a high level of genetic homoplasy associated with cefotaxime resistance

Cefotaxime (CTX) is a third-generation cephalosporin (3GC) commonly used to treat infections caused by Escherichia coli. Two genetic mechanisms have been associated with 3GC resistance in E. coli. The first is the conjugative transfer of a plasmid harbouring antibiotic-resistance genes. The second is the introduction of mutations in the promoter region of the ampC β-lactamase gene that cause chromosome-encoded β-lactamase hyperproduction. A wide variety of promoter mutations related to AmpC hyperproduction have been described. However, their link to CTX resistance has not been reported. We recultured 172 cefoxitin-resistant E. coli isolates with known CTX minimum inhibitory concentrations and performed genome-wide analysis of homoplastic mutations associated with CTX resistance by comparing Illumina whole-genome sequencing data of all isolates to a PacBio sequenced reference chromosome. We mapped the mutations on the reference chromosome and determined their occurrence in the phylogeny, revealing extreme homoplasy at the -42 position of the ampC promoter. The 24 occurrences of a T at the -42 position rather than the wild-type C, resulted from 18 independent C>T mutations in five phylogroups. The -42 C>T mutation was only observed in E. coli lacking a plasmid-encoded ampC gene. The association of the -42 C>T mutation with CTX resistance was confirmed to be significant (false discovery rate <0.05). To conclude, genome-wide analysis of homoplasy in combination with CTX resistance identifies the -42 C>T mutation of the ampC promotor as significantly associated with CTX resistance and underlines the role of recurrent mutations in the spread of antibiotic resistance.

Mapping Gene-by-Gene Single-Nucleotide Variation in 8,535 Mycobacterium tuberculosis Genomes: a Resource To Support Potential Vaccine and Drug Development

Tuberculosis (TB) is responsible for millions of deaths annually. More effective vaccines and new antituberculous drugs are essential to control the disease. Numerous genomic studies have advanced our knowledge about M. tuberculosis drug resistance, population structure, and transmission patterns. At the same time, reverse vaccinology and drug discovery pipelines have identified potential immunogenic vaccine candidates or drug targets. However, a better understanding of the sequence variation of all the M. tuberculosis genes on a large scale could aid in the identification of new vaccine and drug targets. Achieving this was the focus of the current study. Genome sequence data were obtained from online public sources covering seven M. tuberculosis lineages. A total of 8,535 genome sequences were mapped against M. tuberculosis H37Rv reference genome, in order to identify single nucleotide polymorphisms (SNPs). The results of the initial mapping were further processed, and a frequency distribution of nucleotide variants within genes was identified and further analyzed. The majority of genomic positions in the M. tuberculosis H37Rv genome were conserved. Genes with the highest level of conservation were often associated with stress responses and maintenance of redox balance. Conversely, genes with high levels of nucleotide variation were often associated with drug resistance. We have provided a high-resolution analysis of the single-nucleotide variation of all M. tuberculosis genes across seven lineages as a resource to support future drug and vaccine development. We have identified a number of highly conserved genes, important in M. tuberculosis biology, that could potentially be used as targets for novel vaccine candidates and antituberculous medications.

IMPORTANCE Tuberculosis is an infectious disease caused by the bacterium Mycobacterium tuberculosis. In the first half of the 20th century, the discovery of the Mycobacterium bovis BCG vaccine and antituberculous drugs heralded a new era in the control of TB. However, combating TB has proven challenging, especially with the emergence of HIV and drug resistance. A major hindrance in TB control is the lack of an effective vaccine, as the efficacy of BCG is geographically variable and provides little protection against pulmonary disease in high-risk groups. Our research is significant because it provides a resource to support future drug and vaccine development. We have achieved this by developing a better understanding of the nucleotide variation of all of the M. tuberculosis genes on a large scale and by identifying highly conserved genes that could potentially be used as targets for novel vaccine candidates and antituberculous medications.

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

BACKGROUND

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

METHODS

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

FINDINGS

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

INTERPRETATION

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

Genome analyses of 174 strains of Mycobacterium tuberculosis provide insight into the evolution of drug resistance and reveal potential drug targets

Mycobacterium tuberculosis is a known human pathogen that causes the airborne infectious disease tuberculosis (TB). Every year TB infects millions of people worldwide. The emergence of multi-drug resistant (MDR), extensively drug resistant (XDR) and totally drug resistant (TDR) M. tuberculosis strains against the first- and second-line anti-TB drugs has created an urgent need for the development and implementation of new drug strategies. In this study, the complete genomes of 174 strains of M. tuberculosis are analysed to understand the evolution of molecular drug target (MDT) genes. Phylogenomic placements of M. tuberculosis strains depicted close association and temporal clustering. Selection pressure analysis by deducing the ratio of non-synonymous to synonymous substitution rates (dN/dS) in 51 MDT genes of the 174 M. tuberculosis strains led to categorizing these genes into diversifying (D, dN/dS>0.70), moderately diversifying (MD, dN/dS=0.35-0.70) and stabilized (S, dN/dS<0.35) genes. The genes rpsL, gidB, pncA and ahpC were identified as diversifying, and Rv0488, kasA, ndh, ethR, ethA, embR and ddn were identified as stabilized genes. Furthermore, sequence similarity networks were drawn that supported these divisions. In the multiple sequence alignments of diversifying and stabilized proteins, previously reported resistance mutations were checked to predict sensitive and resistant strains of M. tuberculosis. Finally, to delineate the potential of stabilized or least diversified genes/proteins as anti-TB drug targets, protein-protein interactions of MDT proteins with human proteins were analysed. We predict that kasA (dN/dS=0.29), a stabilized gene that encodes the most host-interacting protein, KasA, should serve as a potential drug target for the treatment of TB.

Nonsynonymous Polymorphism Counts in Bacterial Genomes: a Comparative Examination

Genomic data reveal single-nucleotide polymorphisms (SNPs) that may carry information about the evolutionary history of bacteria. However, it remains unclear what inferences about selection can be made from genomic SNP data. Bacterial species are often sampled during epidemic outbreaks or within hosts during the course of chronic infections. SNPs obtained from genomic analysis of these data are not necessarily fixed. Treating them as fixed during analysis by using measures such as the ratio of nonsynonymous to synonymous evolutionary changes (dN/dS) may lead to incorrect inferences about the strength and direction of selection. In this study, we consider data from a range of whole-genome sequencing studies of bacterial pathogens and explore patterns of nonsynonymous variation to assess whether evidence of selection can be identified by investigating SNP counts alone across multiple WGS studies. We visualize these SNP data in ways that highlight their relationship to neutral baseline expectations. These neutral expectations are based on a simple model of mutation, from which we simulate SNP accumulation to investigate how SNP counts are distributed under alternative assumptions about positive and negative selection. We compare these patterns with empirical SNP data and illustrate the general difficulty of detecting positive selection from SNP data. Finally, we consider whether SNP counts observed at the between-host population level differ from those observed at the within-host level and find some evidence that suggests that dynamics across these two scales are driven by different underlying processes.IMPORTANCE Identifying selection from SNP data obtained from whole-genome sequencing studies is challenging. Some current measures used to identify and quantify selection acting on genomes rely on fixed differences; thus, these are inappropriate for SNP data where variants are not fixed. With the increase in whole-genome sequencing studies, it is important to consider SNP data in the context of evolutionary processes. How SNPs are counted and analyzed can help in understanding mutation accumulation and trajectories of strains. We developed a tool for identifying possible evidence of selection and for comparative analysis with other SNP data. We propose a model that provides a rule-of-thumb guideline and two new visualization techniques that can be used to interpret and compare SNP data. We quantify the expected proportion of nonsynonymous SNPs in coding regions under neutrality and demonstrate its use in identifying evidence of positive and negative selection from simulations and empirical data.

Insertion and deletion evolution reflects antibiotics selection pressure in a Mycobacterium tuberculosis outbreak

In genome evolution, genetic variants are the source of diversity, which natural selection acts upon. Treatment of human tuberculosis (TB) induces a strong selection pressure for the emergence of antibiotic resistance-conferring variants in the infecting Mycobacterium tuberculosis (MTB) strains. MTB evolution in response to treatment has been intensively studied and mainly attributed to point substitutions. However, the frequency and contribution of insertions and deletions (indels) to MTB genome evolution remains poorly understood. Here, we analyzed a multi-drug resistant MTB outbreak for the presence of high-quality indels and substitutions. We find that indels are significantly enriched in genes conferring antibiotic resistance. Furthermore, we show that indels are inherited during the outbreak and follow a molecular clock with an evolutionary rate of 5.37e-9 indels/site/year, which is 23 times lower than the substitution rate. Inherited indels may co-occur with substitutions in genes along related biological pathways; examples are iron storage and resistance to second-line antibiotics. This suggests that epistatic interactions between indels and substitutions affect antibiotic resistance and compensatory evolution in MTB.

Exploiting Homoplasy in Genome-Wide Association Studies to Enhance Identification of Antibiotic-Resistance Mutations in Bacterial Genomes

Many antibacterial drugs have multiple mechanisms of resistance, which are often represented simultaneously by a mixture of resistance mutations (some more frequent than others) in a clinical population. This presents a challenge for Genome-Wide Association Studies (GWAS) methods, making it difficult to detect less prevalent resistance mechanisms purely through (weak) statistical associations. Homoplasy, or the occurrence of multiple independent mutations at the same site, is often observed with drug resistance mutations and can be a strong indicator of positive selection. However, traditional GWAS methods, such as those based on allele counting or linear regression, are not designed to take homoplasy into account. In this article, we present a new method, called ECAT (for Evolutionary Cluster-based Association Test), that extends traditional regression-based GWAS methods with the ability to take advantage of homoplasy. This is achieved through a preprocessing step which identifies hypervariable regions in the genome exhibiting statistically significant clusters of distinct evolutionary changes, to which association testing by a linear mixed model (LMM) is applied using GEMMA (a well-established LMM-based GWAS tool). Thus, the approach can be viewed as extending GEMMA from the usual site- or gene-level analysis to focusing on clustered regions of mutations. This approach was evaluated on a large collection of more than 600 clinical isolates of multidrug-resistant (MDR) Mycobacterium tuberculosis from Lima, Peru. We show that ECAT does a better job of detecting known resistance mutations for several antitubercular drugs (including less prevalent mutations with weaker associations), compared with (site- or gene-based) GEMMA, as representative of existing GWAS methods. The power of the multiphase approach in ECAT comes from focusing association testing on the hypervariable regions of the genome, which reduces complexity in the model and increases statistical power.

Homoplastic single nucleotide polymorphisms contributed to phenotypic diversity in Mycobacterium tuberculosis

Homoplastic mutations are mutations independently occurring in different clades of an organism. The homoplastic changes may be a result of convergence evolution due to selective pressures. Reports on the analysis of homoplastic mutations in Mycobacterium tuberculosis have been limited. Here we characterized the distribution of homoplastic single nucleotide polymorphisms (SNPs) among genomes of 1,170 clinical M. tuberculosis isolates. They were present in all functional categories of genes, with pe/ppe gene family having the highest ratio of homoplastic SNPs compared to the total SNPs identified in the same functional category. Among the pe/ppe genes, the homoplastic SNPs were common in a relatively small number of homologous genes, including ppe18, the protein of which is a component of a promising candidate vaccine, M72/AS01E. The homoplastic SNPs in ppe18 were particularly common among M. tuberculosis Lineage 1 isolates, suggesting the need for caution in extrapolating the results of the vaccine trial to the population where L1 is endemic in Asia. As expected, homoplastic SNPs strongly associated with drug resistance. Most of these mutations are already well known. However, a number of novel mutations associated with streptomycin resistance were identified, which warrants further investigation. A SNP in the intergenic region upstream of Rv0079 (DATIN) was experimentally shown to increase transcriptional activity of the downstream gene, suggesting that intergenic homoplastic SNPs should have effects on the physiology of the bacterial cells. Our study highlights the potential of homoplastic mutations to produce phenotypic changes. Under selective pressure and during interaction with the host, homoplastic mutations may confer advantages to M. tuberculosis and deserve further characterization.

Mycobacterium tuberculosis associated with severe tuberculosis evades cytosolic surveillance systems and modulates IL-1β production

Genetic diversity of Mycobacterium tuberculosis affects immune responses and clinical outcomes of tuberculosis (TB). However, how bacterial diversity orchestrates immune responses to direct distinct TB severities is unknown. Here we study 681 patients with pulmonary TB and show that M. tuberculosis isolates from cases with mild disease consistently induce robust cytokine responses in macrophages across multiple donors. By contrast, bacteria from patients with severe TB do not do so. Secretion of IL-1β is a good surrogate of the differences observed, and thus to classify strains as probable drivers of different TB severities. Furthermore, we demonstrate that M. tuberculosis isolates that induce low levels of IL-1β production can evade macrophage cytosolic surveillance systems, including cGAS and the inflammasome. Isolates exhibiting this evasion strategy carry candidate mutations, generating sigA recognition boxes or affecting components of the ESX-1 secretion system. Therefore, we provide evidence that M. tuberculosis strains manipulate host-pathogen interactions to drive variable TB severities.

Evaluating the contributions of purifying selection and progeny-skew in dictating within-host Mycobacterium tuberculosis evolution

The within-host evolutionary dynamics of tuberculosis (TB) remain unclear, and underlying biological characteristics render standard population genetic approaches based upon the Wright-Fisher model largely inappropriate. In addition, the compact genome combined with an absence of recombination is expected to result in strong purifying selection effects. Thus, it is imperative to establish a biologically relevant evolutionary framework incorporating these factors in order to enable an accurate study of this important human pathogen. Further, such a model is critical for inferring fundamental evolutionary parameters related to patient treatment, including mutation rates and the severity of infection bottlenecks. We here implement such a model and infer the underlying evolutionary parameters governing within-patient evolutionary dynamics. Results demonstrate that the progeny skew associated with the clonal nature of TB severely reduces genetic diversity and that the neglect of this parameter in previous studies has led to significant mis-inference of mutation rates. As such, our results suggest an underlying de novo mutation rate that is considerably faster than previously inferred, and a progeny distribution differing significantly from Wright-Fisher assumptions. This inference represents a more appropriate evolutionary null model, against which the periodic effects of positive selection, associated with drug-resistance for example, may be better assessed.

Value of pyrazinamide for composition of new treatment regimens for multidrug-resistant Mycobacterium tuberculosis in China

Background

Pyrazinamide still may be a useful drug for treatment of rifampin-resistant (RR-TB) or multidrug-resistant tuberculosis (MDR-TB) in China while awaiting scale up of new drugs and regimens including bedaquiline and linezolid. The level of pyrazinamide resistance among MDR-TB patients in China is not well established. Therefore, we assessed pyrazinamide resistance in a representative sample and explored determinants and patterns of pncA mutations.

Methods

MDR-TB isolates from the 2007 national drug resistance survey of China were sub-cultured and examined for pyrazinamide susceptibility by BACTEC MGIT 960 method. pncA mutations were identified by sequencing. Characteristics associated with pyrazinamide resistance were analyzed using univariable and multivariable log-binominal regression.

Results

Of 401 MDR-TB isolates, 324 were successfully sub-cultured and underwent drug susceptibility testing. Pyrazinamide resistance was prevalent in 40.7% of samples, similarly among new and previously treated MDR-TB patients. Pyrazinamide resistance in MDR-TB patients was associated with lower age (adjusted OR 0.54; 95% CI, 0.34–0.87 for those aged ≧60 years compared to < 40 years). Pyrazinamide resistance was not associated with gender, residential area, previous treatment history and Beijing genotype. Of 132 patients with pyrazinamide resistant MDR-TB, 97 (73.5%) had a mutation in the pncA gene; with 61 different point mutations causing amino acid change, and 11 frameshifts in the pncA gene. The mutations were scattered throughout the whole pncA gene and no hot spot region was identified.

Conclusions

Pyrazinamide resistance among MDR-TB patients in China is common, although less so in elderly patients. Therefore, pyrazinamide should only be used for treatment of RR/MDR-TB in China if susceptibility is confirmed. Molecular testing for detection of pyrazinamide resistance only based on pncA mutations has certain value for the rapid detection of pyrazinamide resistance in MDR-TB strains but other gene mutations conferring to pyrazinamide resistance still need to be explored to increase its predictive ability .

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.

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.

Genome Sequencing and Comparative Analysis of Stenotrophomonas acidaminiphila Reveal Evolutionary Insights Into Sulfamethoxazole Resistance

Stenotrophomonas acidaminiphila is an aerobic, glucose non-fermentative, Gram-negative bacterium that been isolated from various environmental sources, particularly aquatic ecosystems. Although resistance to multiple antimicrobial agents has been reported in S. acidaminiphila, the mechanisms are largely unknown. Here, for the first time, we report the complete genome and antimicrobial resistome analysis of a clinical isolate S. acidaminiphila SUNEO which is resistant to sulfamethoxazole. Comparative analysis among closely related strains identified common and strain-specific genes. In particular, comparison with a sulfamethoxazole-sensitive strain identified a mutation within the sulfonamide-binding site of folP in SUNEO, which may reduce the binding affinity of sulfamethoxazole. Selection pressure analysis indicated folP in SUNEO is under purifying selection, which may be owing to long-term administration of sulfonamide against Stenotrophomonas.