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

PE/PPE mutations in the transmission of Mycobacterium tuberculosis in China revealed by whole genome sequencing

OBJECTIVE

This study aims to examine the impact of PE/PPE gene mutations on the transmission of Mycobacterium tuberculosis (M. tuberculosis) in China.

METHODS

We collected the whole genome sequencing (WGS) data of 3202 M. tuberculosis isolates in China from 2007 to 2018 and investigated the clustering of strains from different lineages. To evaluate the potential role of PE/PPE gene mutations in the dissemination of the pathogen, we employed homoplastic analysis to detect homoplastic single nucleotide polymorphisms (SNPs) within these gene regions. Subsequently, logistic regression analysis was conducted to analyze the statistical association.

RESULTS

Based on nationwide M. tuberculosis WGS data, it has been observed that the majority of the M. tuberculosis burden in China is caused by lineage 2 strains, followed by lineage 4. Lineage 2 exhibited a higher number of transmission clusters, totaling 446 clusters, of which 77 were cross-regional clusters. Conversely, there were only 52 transmission clusters in lineage 4, of which 9 were cross-regional clusters. In the analysis of lineage 2 isolates, regression results showed that 4 specific gene mutations, PE4 (position 190,394; c.46G > A), PE_PGRS10 (839,194; c.744 A > G), PE16 (1,607,005; c.620T > G) and PE_PGRS44 (2,921,883; c.333 C > A), were significantly associated with the transmission of M. tuberculosis. Mutations of PE_PGRS10 (839,334; c.884 A > G), PE_PGRS11 (847,613; c.1455G > C), PE_PGRS47 (3,054,724; c.811 A > G) and PPE66 (4,189,930; c.303G > C) exhibited significant associations with the cross-regional clusters. A total of 13 mutation positions showed a positive correlation with clustering size, indicating a positive association. For lineage 4 strains, no mutations were found to enhance transmission, but 2 mutation sites were identified as risk factors for cross-regional clusters. These included PE_PGRS4 (338,100; c.974 A > G) and PPE13 (976,897; c.1307 A > C).

CONCLUSION

Our results indicate that some PE/PPE gene mutations can increase the risk of M. tuberculosis transmission, which might provide a basis for controlling the spread of tuberculosis.

Transcriptional convergence after repeated duplication of an amino acid transporter gene leads to the independent emergence of the black husk/pericarp trait in barley and rice

The repeated emergence of the same trait (convergent evolution) in distinct species is an interesting phenomenon and manifests visibly the power of natural selection. The underlying genetic mechanisms have important implications to understand how the genome evolves under environmental challenges. In cereal crops, both rice and barley can develop black-coloured husk/pericarp due to melanin accumulation. However, it is unclear if this trait shares a common origin. Here, we fine-mapped the barley HvBlp gene controlling the black husk/pericarp trait and confirmed its function by gene silencing. The result was further supported by a yellow husk/pericarp mutant with deletion of the HvBlp gene, derived from gamma ray radiation of the wild-type W1. HvBlp encodes a putative tyrosine transporter homologous to the black husk gene OsBh4 in rice. Surprisingly, synteny and phylogenetic analyses showed that HvBlp and OsBh4 belonged to different lineages resulted from dispersed and tandem duplications, respectively, suggesting that the black husk/pericarp trait has emerged independently. The dispersed duplication (dated at 21.23 MYA) yielding HvBlp occurred exclusively in the common ancestor of Triticeae. HvBlp and OsBh4 displayed converged transcription in husk/pericarp tissues, contributing to the black husk/pericarp trait. Further transcriptome and metabolome data identified critical candidate genes and metabolites related to melanin production in barley. Taken together, our study described a compelling case of convergent evolution resulted from transcriptional convergence after repeated gene duplication, providing valuable genetic insights into phenotypic evolution. The identification of the black husk/pericarp genes in barley also has great potential in breeding for stress-resilient varieties with higher nutritional values.

Actionable mechanisms of drug tolerance and resistance in Mycobacterium tuberculosis

The emergence of antimicrobial resistance (AMR) across bacterial pathogens presents a serious threat to global health. This threat is further exacerbated in tuberculosis (TB), mainly due to a protracted treatment regimen involving a combination of drugs. A diversity of factors contributes to the emergence of drug resistance in TB, which is caused by the pathogen Mycobacterium tuberculosis (Mtb). While the traditional genetic mutation-driven drug resistance mechanisms operate in Mtb, there are also several additional unique features of drug resistance in this pathogen. Research in the past decade has enriched our understanding of such unconventional factors as efflux pumps, bacterial heterogeneity, metabolic states, and host microenvironment. Given that the discovery of new antibiotics is outpaced by the emergence of drug resistance patterns displayed by the pathogen, newer strategies for combating drug resistance are desperately needed. In the context of TB, such approaches include targeting the efflux capability of the pathogen, modulating the host environment to prevent bacterial drug tolerance, and activating the host anti-mycobacterial pathways. In this review, we discuss the traditional mechanisms of drug resistance in Mtb, newer understandings and the shaping of a set of unconventional approaches to target both the emergence and treatment of drug resistance in TB.

Identification of positively selected genes in Mycobacterium tuberculosis from southern Xinjiang Uygur autonomous region of China

Background

Tuberculosis (TB), mainly caused by Mycobacterium tuberculosis (Mtb), remains a serious public health problem. Increasing evidence supports that selective evolution is an important force affecting genomic determinants of Mtb phenotypes. It is necessary to further understand the Mtb selective evolution and identify the positively selected genes that probably drive the phenotype of Mtb.

Methods

This study mainly focused on the positive selection of 807 Mtb strains from Southern Xinjiang of China using whole genome sequencing (WGS). PAML software was used for identifying the genes and sites under positive selection in 807 Mtb strains.

Results

Lineage 2 (62.70%) strains were the dominant strains in this area, followed by lineage 3 (19.45%) and lineage 4 (17.84%) strains. There were 239 codons in 47 genes under positive selection, and the genes were majorly associated with the functions of transcription, defense mechanisms, and cell wall/membrane/envelope biogenesis. There were 28 codons (43 mutations) in eight genes (gyrA, rpoB, rpoC, katG, pncA, embB, gid, and cut1) under positive selection in multi-drug resistance (MDR) strains but not in drug-susceptible (DS) strains, in which 27 mutations were drug-resistant loci, 9 mutations were non-drug-resistant loci but were in drug-resistant genes, 2 mutations were compensatory mutations, and 5 mutations were in unknown drug-resistant gene of cut1. There was a codon in Rv0336 under positive selection in L3 strains but not in L2 and L4 strains. The epitopes of T and B cells were both hyper-conserved, particularly in the T-cell epitopes.

Conclusion

This study revealed the ongoing selective evolution of Mtb. We found some special genes and sites under positive selection which may contribute to the advantage of MDR and L3 strains. It is necessary to further study these mutations to understand their impact on phenotypes for providing more useful information to develop new TB interventions.

Large-scale Pan Genomic Analysis of Mycobacterium tuberculosis Reveals Key Insights Into Molecular Evolutionary Rate of Specific Processes and Functions

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis (TB), an infectious disease that is a major killer worldwide. Due to selection pressure caused by the use of antibacterial drugs, Mtb is characterised by mutational events that have given rise to multi drug resistant (MDR) and extensively drug resistant (XDR) phenotypes. The rate at which mutations occur is an important factor in the study of molecular evolution, and it helps understand gene evolution. Within the same species, different protein-coding genes evolve at different rates. To estimate the rates of molecular evolution of protein-coding genes, a commonly used parameter is the ratio dN/dS, where dN is the rate of non-synonymous substitutions and dS is the rate of synonymous substitutions. Here, we determined the estimated rates of molecular evolution of select biological processes and molecular functions across 264 strains of Mtb. We also investigated the molecular evolutionary rates of core genes of Mtb by computing the dN/dS values, and estimated the pan genome of the 264 strains of Mtb. Our results show that the cellular amino acid metabolic process and the kinase activity function evolve at a significantly higher rate, while the carbohydrate metabolic process evolves at a significantly lower rate for M. tuberculosis. These high rates of evolution correlate well with Mtb physiology and pathogenicity. We further propose that the core genome of M. tuberculosis likely experiences varying rates of molecular evolution which may drive an interplay between core genome and accessory genome during M. tuberculosis evolution.

Optimising machine learning prediction of minimum inhibitory concentrations in Klebsiella pneumoniae

Minimum Inhibitory Concentrations (MICs) are the gold standard for quantitatively measuring antibiotic resistance. However, lab-based MIC determination can be time-consuming and suffers from low reproducibility, and interpretation as sensitive or resistant relies on guidelines which change over time. Genome sequencing and machine learning promise to allow in silico MIC prediction as an alternative approach which overcomes some of these difficulties, albeit the interpretation of MIC is still needed. Nevertheless, precisely how we should handle MIC data when dealing with predictive models remains unclear, since they are measured semi-quantitatively, with varying resolution, and are typically also left- and right-censored within varying ranges. We therefore investigated genome-based prediction of MICs in the pathogen Klebsiella pneumoniae using 4367 genomes with both simulated semi-quantitative traits and real MICs. As we were focused on clinical interpretation, we used interpretable rather than black-box machine learning models, namely, Elastic Net, Random Forests, and linear mixed models. Simulated traits were generated accounting for oligogenic, polygenic, and homoplastic genetic effects with different levels of heritability. Then we assessed how model prediction accuracy was affected when MICs were framed as regression and classification. Our results showed that treating the MICs differently depending on the number of concentration levels of antibiotic available was the most promising learning strategy. Specifically, to optimise both prediction accuracy and inference of the correct causal variants, we recommend considering the MICs as continuous and framing the learning problem as a regression when the number of observed antibiotic concentration levels is large, whereas with a smaller number of concentration levels they should be treated as a categorical variable and the learning problem should be framed as a classification. Our findings also underline how predictive models can be improved when prior biological knowledge is taken into account, due to the varying genetic architecture of each antibiotic resistance trait. Finally, we emphasise that incrementing the population database is pivotal for the future clinical implementation of these models to support routine machine-learning based diagnostics.

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

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

Phylogenetic Survival Analysis

Going back in time through a phylogenetic tree makes it possible to evaluate ancestral genomes and assess their potential to acquire key polymorphisms of interest over evolutionary time. Knowledge of this kind may allow for the emergence of key traits to be predicted and pre-empted from currently circulating strains in the future. Here, we present a novel genome-wide survival analysis and use the emergence of drug resistance in Mycobacterium tuberculosis as an example to demonstrate the potential and utility of the technique.

Recent gene selection and drug resistance underscore clinical adaptation across Candida species

Understanding how microbial pathogens adapt to treatments, humans and clinical environments is key to infer mechanisms of virulence, transmission and drug resistance. This may help improve therapies and diagnostics for infections with a poor prognosis, such as those caused by fungal pathogens, including Candida. Here we analysed genomic variants across approximately 2,000 isolates from six Candida species (C. glabrata, C. auris, C. albicans, C. tropicalis, C. parapsilosis and C. orthopsilosis) and identified genes under recent selection, suggesting a highly complex clinical adaptation. These involve species-specific and convergently affected adaptive mechanisms, such as adhesion. Using convergence-based genome-wide association studies we identified known drivers of drug resistance alongside potentially novel players. Finally, our analyses reveal an important role of structural variants and suggest an unexpected involvement of (para)sexual recombination in the spread of resistance. Our results provide insights on how opportunistic pathogens adapt to human-related environments and unearth candidate genes that deserve future attention.

Machine learning and phylogenetic analysis allow for predicting antibiotic resistance in M. tuberculosis

BACKGROUND

Antimicrobial resistance (AMR) poses a significant global health threat, and an accurate prediction of bacterial resistance patterns is critical for effective treatment and control strategies. In recent years, machine learning (ML) approaches have emerged as powerful tools for analyzing large-scale bacterial AMR data. However, ML methods often ignore evolutionary relationships among bacterial strains, which can greatly impact performance of the ML methods, especially if resistance-associated features are attempted to be detected. Genome-wide association studies (GWAS) methods like linear mixed models accounts for the evolutionary relationships in bacteria, but they uncover only highly significant variants which have already been reported in literature.

RESULTS

In this work, we introduce a novel phylogeny-related parallelism score (PRPS), which measures whether a certain feature is correlated with the population structure of a set of samples. We demonstrate that PRPS can be used, in combination with SVM- and random forest-based models, to reduce the number of features in the analysis, while simultaneously increasing models' performance. We applied our pipeline to publicly available AMR data from PATRIC database for Mycobacterium tuberculosis against six common antibiotics.

CONCLUSIONS

Using our pipeline, we re-discovered known resistance-associated mutations as well as new candidate mutations which can be related to resistance and not previously reported in the literature. We demonstrated that taking into account phylogenetic relationships not only improves the model performance, but also yields more biologically relevant predicted most contributing resistance markers.

Evolution and transmission of antibiotic resistance is driven by Beijing lineage Mycobacterium tuberculosis in Vietnam

IMPORTANCE

Drug-resistant tuberculosis (TB) infection is a growing and potent concern, and combating it will be necessary to achieve the WHO's goal of a 95% reduction in TB deaths by 2035. While prior studies have explored the evolution and spread of drug resistance, we still lack a clear understanding of the fitness costs (if any) imposed by resistance-conferring mutations and the role that Mtb genetic lineage plays in determining the likelihood of resistance evolution. This study offers insight into these questions by assessing the dynamics of resistance evolution in a high-burden Southeast Asian setting with a diverse lineage composition. It demonstrates that there are clear lineage-specific differences in the dynamics of resistance acquisition and transmission and shows that different lineages evolve resistance via characteristic mutational pathways.

Genome-Wide Association Studies (GWAS) Approaches for the Detection of Genetic Variants Associated with Antibiotic Resistance: A Systematic Review

Antibiotic resistance is a significant threat to public health worldwide. Genome-wide association studies (GWAS) have emerged as a powerful tool to identify genetic variants associated with this antibiotic resistance. By analyzing large datasets of bacterial genomes, GWAS can provide valuable insights into the resistance mechanisms and facilitate the discovery of new drug targets. The present study aimed to undertake a systematic review of different GWAS approaches used for detecting genetic variants associated with antibiotic resistance. We comprehensively searched the PubMed and Scopus databases to identify relevant studies published from 2013 to February 2023. A total of 40 studies met our inclusion criteria. These studies explored a wide range of bacterial species, antibiotics, and study designs. Notably, most of the studies were centered around human pathogens such as Mycobacterium tuberculosis, Escherichia coli, Neisseria gonorrhoeae, and Staphylococcus aureus. The review seeks to explore the several GWAS approaches utilized to investigate the genetic mechanisms associated with antibiotic resistance. Furthermore, it examines the contributions of GWAS approaches in identifying resistance-associated genetic variants through binary and continuous phenotypes. Overall, GWAS holds great potential to enhance our understanding of bacterial resistance and improve strategies to combat infectious diseases.

Learning from the unknown: exploring the range of bacterial functionality

Determining the repertoire of a microbe's molecular functions is a central question in microbial biology. Modern techniques achieve this goal by comparing microbial genetic material against reference databases of functionally annotated genes/proteins or known taxonomic markers such as 16S rRNA. Here, we describe a novel approach to exploring bacterial functional repertoires without reference databases. Our Fusion scheme establishes functional relationships between bacteria and assigns organisms to Fusion-taxa that differ from otherwise defined taxonomic clades. Three key findings of our work stand out. First, bacterial functional comparisons outperform marker genes in assigning taxonomic clades. Fusion profiles are also better for this task than other functional annotation schemes. Second, Fusion-taxa are robust to addition of novel organisms and are, arguably, able to capture the environment-driven bacterial diversity. Finally, our alignment-free nucleic acid-based Siamese Neural Network model, created using Fusion functions, enables finding shared functionality of very distant, possibly structurally different, microbial homologs. Our work can thus help annotate functional repertoires of bacterial organisms and further guide our understanding of microbial communities.

The Mycobacterium tuberculosis genome at 25 years: lessons and lingering questions

First achieved in 1998 by Cole et al., the complete genome sequence of Mycobacterium tuberculosis continues to provide an invaluable resource to understand tuberculosis (TB), the leading cause of global infectious disease mortality. At the 25-year anniversary of this accomplishment, we describe how insights gleaned from the M. tuberculosis genome have led to vital tools for TB research, epidemiology, and clinical practice. The increasing accessibility of whole-genome sequencing across research and clinical settings has improved our ability to predict antibacterial susceptibility, to track epidemics at the level of individual outbreaks and wider historical trends, to query the efficacy of the bacille Calmette-Guérin (BCG) vaccine, and to uncover targets for novel antitubercular therapeutics. Likewise, we discuss several recent efforts to extract further discoveries from this powerful resource.

A statistical genomics framework to trace bacterial genomic predictors of clinical outcomes in Staphylococcus aureus bacteremia

Outcomes of severe bacterial infections are determined by the interplay between host, pathogen, and treatments. While human genomics has provided insights into host factors impacting Staphylococcus aureus infections, comparatively little is known about S. aureus genotypes and disease severity. Building on the hypothesis that bacterial pathoadaptation is a key outcome driver, we developed a genome-wide association study (GWAS) framework to identify adaptive mutations associated with treatment failure and mortality in S. aureus bacteremia (1,358 episodes). Our research highlights the potential of vancomycin-selected mutations and vancomycin minimum inhibitory concentration (MIC) as key explanatory variables to predict infection severity. The contribution of bacterial variation was much lower for clinical outcomes (heritability <5%); however, GWASs allowed us to identify additional, MIC-independent candidate pathogenesis loci. Using supervised machine learning, we were able to quantify the predictive potential of these adaptive signatures. Our statistical genomics framework provides a powerful means to capture adaptive mutations impacting severe bacterial infections.

Selective Pressure by Rifampicin Modulates Mutation Rates and Evolutionary Trajectories of Mycobacterial Genomes

Resistance to the frontline antibiotic rifampicin constitutes a challenge to the treatment and control of tuberculosis. Here, we analyzed the mutational landscape of Mycobacterium smegmatis during long-term evolution with increasing concentrations of rifampicin, using a mutation accumulation assay combined with whole-genome sequencing. Antibiotic treatment enhanced the acquisition of mutations, doubling the genome-wide mutation rate of the wild-type cells. While antibiotic exposure led to extinction of almost all wild-type lines, the hypermutable phenotype of the ΔnucS mutant strain (noncanonical mismatch repair deficient) provided an efficient response to the antibiotic, leading to high rates of survival. This adaptative advantage resulted in the emergence of higher levels of rifampicin resistance, an accelerated acquisition of drug resistance mutations in rpoB (β RNA polymerase), and a wider diversity of evolutionary pathways that led to drug resistance. Finally, this approach revealed a subset of adaptive genes under positive selection with rifampicin that could be associated with the development of antibiotic resistance. IMPORTANCE Rifampicin is the most important first-line antibiotic against mycobacterial infections, including tuberculosis, one of the top causes of death worldwide. Acquisition of rifampicin resistance constitutes a major global public health problem that makes the control of the disease challenging. Here, we performed an experimental evolution assay under antibiotic selection to analyze the response and adaptation of mycobacteria, leading to the acquisition of rifampicin resistance. This approach explored the total number of mutations that arose in the mycobacterial genomes under long-term rifampicin exposure, using whole-genome sequencing. Our results revealed the effect of rifampicin at a genomic level, identifying different mechanisms and multiple pathways leading to rifampicin resistance in mycobacteria. Moreover, this study detected that an increase in the rate of mutations led to enhanced levels of drug resistance and survival. In summary, all of these results could be useful to understand and prevent the emergence of drug-resistant isolates in mycobacterial infections.

Analysis of whiB7 in Mycobacterium tuberculosis reveals novel AT-hook deletion mutations

Mutations in whiB7 have been associated with both hypersusceptibility and resistance to various antibiotics in Mycobacterium tuberculosis (Mtb). Unlocking the secrets of antibiotic resistance in the bacterium, we examined mutations in the coding sequences of whiB7 of over 40,000 diverse Mtb isolates. Our results unveil the dominant c.191delG (Gly64delG) mutation, present in all members of the lineage L1.2.2 and its impact on WhiB7's conserved GVWGG-motif, causing conformational changes and deletion of the C-terminal AT-hook. Excitingly, we discovered six unique mutations associated with partial or total deletion of the AT-hook, specific to certain sublineages. Our findings suggest the selective pressures driving these mutations, underlining the potential of genomics to advance our understanding of Mtb's antibiotic resistance. As tuberculosis remains a global health threat, our study offers valuable insights into the diverse nature and functional consequences of whiB7 mutations, paving the way for the development of novel therapeutic interventions.

Mycobacterium tuberculosis Gene Expression Associated With Fluoroquinolone Resistance and Efflux Pump Inhibition

BACKGROUND

We evaluated the relationship between response to efflux pump inhibition in fluoroquinolone-resistant Mycobacterium tuberculosis (Mtb) isolates and differences in gene expression and expression quantitative trait loci (eQTL).

METHODS

We determined ofloxacin minimum inhibitory concentration (MIC) for ofloxacin-resistant and -susceptible Mtb isolates without and with the efflux pump inhibitor verapamil. We performed RNA sequencing (RNA-seq), whole genome sequencing (WGS), and eQTL analysis, focusing on efflux pump, transport, and secretion-associated genes.

RESULTS

Of 42 ofloxacin-resistant Mtb isolates, 27 had adequate WGS coverage and acceptable RNA-seq quality. Of these 27, 7 had >2-fold reduction in ofloxacin MIC with verapamil; 6 had 2-fold reduction, and 14 had <2-fold reduction. Five genes (including Rv0191) had significantly increased expression in the MIC fold change >2 compared to <2 groups. Among regulated genes, 31 eQTLs (without ofloxacin) and 35 eQTLs (with ofloxacin) had significant allele frequency differences between MIC fold change >2 and <2 groups. Of these, Rv1410c, Rv2459, and Rv3756c (without ofloxacin) and Rv0191 and Rv3756c (with ofloxacin) have previously been associated with antituberculosis drug resistance.

CONCLUSIONS

In this first reported eQTL analysis in Mtb, Rv0191 had increased gene expression and significance in eQTL analysis, making it a candidate for functional evaluation of efflux-mediated fluoroquinolone resistance in Mtb.

Combining Radiological and Genomic TB Portals Data for Drug Resistance Analysis

Tuberculosis (TB) drug resistance is a worldwide public health problem. It decreases the likelihood of a positive outcome for the individual patient and increases the likelihood of disease spread. Therefore, early detection of TB drug resistance is crucial for improving outcomes and controlling disease transmission. While drug-sensitive tuberculosis cases are declining worldwide because of effective treatment, the threat of drug-resistant tuberculosis is growing, and the success rate of drug-resistant tuberculosis treatment is only around 60%. The TB Portals program provides a publicly accessible repository of TB case data with an emphasis on collecting drug-resistant cases. The dataset includes multi-modal information such as socioeconomic/geographic data, clinical characteristics, pathogen genomics, and radiological features. The program is an international collaboration whose participants are typically under a substantial burden of drug-resistant tuberculosis, with data collected from standard clinical care provided to the patients. Consequentially, the TB Portals dataset is heterogenous in nature, with data representing multiple treatment centers in different countries and containing cross-domain information. This study presents the challenges and methods used to address them when working with this real-world dataset. Our goal was to evaluate whether combining radiological features derived from a chest X-ray of the host and genomic features from the pathogen can potentially improve the identification of the drug susceptibility type, drug-sensitive (DS-TB) or drug-resistant (DR-TB), and the length of the first successful drug regimen. To perform these studies, significantly imbalanced data needed to be processed, which included a much larger number of DR-TB cases than DS-TB, many more cases with radiological findings than genomic ones, and the sparse high dimensional nature of the genomic information. Three evaluation studies were carried out. First, the DR-TB/DS-TB classification model achieved an average accuracy of 92.4% when using genomic features alone or when combining radiological and genomic features. Second, the regression model for the length of the first successful treatment had a relative error of 53.5% using radiological features, 25.6% using genomic features, and 22.0% using both radiological and genomic features. Finally, the relative error of the third regression model predicting the length of the first treatment using the most common drug combination varied depending on the feature type used. When using radiological features alone, the relative error was 17.8%. For genomic features alone, the relative error increased to 19.9%. The model had a relative error of 19.0% when both radiological and genomic features were combined. Although combining radiological and genomic features did not improve upon the use of genomic features when classifying DR-TB/DS-TB, the combination of the two feature types improved the relative error of the predictive model for the length of the first successful treatment. Furthermore, the regression model trained on radiological features achieved the best performance when predicting the treatment length of the most common drug combination.

Phase variation as a major mechanism of adaptation in Mycobacterium tuberculosis complex

Phase variation induced by insertions and deletions (INDELs) in genomic homopolymeric tracts (HT) can silence and regulate genes in pathogenic bacteria, but this process is not characterized in MTBC (Mycobacterium tuberculosis complex) adaptation. We leverage 31,428 diverse clinical isolates to identify genomic regions including phase-variants under positive selection. Of 87,651 INDEL events that emerge repeatedly across the phylogeny, 12.4% are phase-variants within HTs (0.02% of the genome by length). We estimated the in-vitro frameshift rate in a neutral HT at 100× the neutral substitution rate at [Formula: see text] frameshifts/HT/year. Using neutral evolution simulations, we identified 4,098 substitutions and 45 phase-variants to be putatively adaptive to MTBC (P < 0.002). We experimentally confirm that a putatively adaptive phase-variant alters the expression of espA, a critical mediator of ESX-1-dependent virulence. Our evidence supports the hypothesis that phase variation in the ESX-1 system of MTBC can act as a toggle between antigenicity and survival in the host.

Development of a Single-nucleotide Polymorphism Genotyping Assay for the Rapid Detection of Vancomycin-intermediate Resistance in Staphylococcus aureus Epidemic Lineage ST5

Background

Vancomycin is a treatment option for patients with severe methicillin-resistant Staphylococcus aureus (MRSA) infection. Unfortunately, reduced susceptibility to vancomycin in S. aureus is becoming increasingly common. We developed a method for the rapid and accurate diagnosis of vancomycin-intermediate resistant S. aureus (VISA).

Methods

We performed a microbial genome-wide association study to discriminate between VISA and vancomycin-susceptible S. aureus (VSSA) using 42 whole-genome sequences. A TaqMan single-nucleotide polymorphism (SNP) genotyping assay was developed to detect target SNPs in VISA strains.

Results

Four SNPs in the VISA strains resulting in nonsynonymous amino-acid substitutions were associated with reduced susceptibility to vancomycin: SA_RS01235 (G203S), SA_RS09725 (V171A), SA_RS12250 (I48F), and SA_RS12550 (G478A). These four SNPs were mainly detected in the typical hospital-associated sequence type (ST)5 clonal lineage. The TaqMan assay successfully detected all four SNPs using as little as 0.2 ng DNA per reaction. Using 10 VSSA and VISA clinical strains each, we validated that the assay accurately discriminates between VISA and VSSA.

Conclusions

The TaqMan SNP genotyping assay targeting four SNPs may be an alternative to current standard methods for the rapid detection of vancomycin-intermediate resistance in S. aureus epidemic lineage ST5.

Detecting patterns of accessory genome coevolution in Staphylococcus aureus using data from thousands of genomes

Bacterial genomes exhibit widespread horizontal gene transfer, resulting in highly variable genome content that complicates the inference of genetic interactions. In this study, we develop a method for detecting coevolving genes from large datasets of bacterial genomes based on pairwise comparisons of closely related individuals, analogous to a pedigree study in eukaryotic populations. We apply our method to pairs of genes from the Staphylococcus aureus accessory genome of over 75,000 annotated gene families using a database of over 40,000 whole genomes. We find many pairs of genes that appear to be gained or lost in a coordinated manner, as well as pairs where the gain of one gene is associated with the loss of the other. These pairs form networks of rapidly coevolving genes, primarily consisting of genes involved in virulence, mechanisms of horizontal gene transfer, and antibiotic resistance, particularly the SCCmec complex. While we focus on gene gain and loss, our method can also detect genes that tend to acquire substitutions in tandem, or genotype-phenotype or phenotype-phenotype coevolution. Finally, we present the R package DeCoTUR that allows for the computation of our method.

Genome-wide association and dissociation studies in Pantoea ananatis reveal potential virulence factors affecting Allium porrum and Allium fistulosum × Allium cepa hybrid

Pantoea ananatis is a member of a Pantoea species complex that causes center rot of bulb onions (A. cepa) and also infects other Allium crops like leeks (Allium porrum), chives (Allium schoenoprasum), bunching onion or Welsh onion (Allium fistulosum), and garlic (Allium sativum). This pathogen relies on a chromosomal phosphonate biosynthetic gene cluster (HiVir) and a plasmid-borne thiosulfinate tolerance cluster (alt) for onion pathogenicity and virulence, respectively. However, pathogenicity and virulence factors associated with other Allium species remain unknown. We used phenotype-dependent genome-wide association (GWAS) and phenotype-independent gene-pair coincidence (GPC) analyses on a panel of diverse 92 P. ananatis strains, which were inoculated on A. porrum and A. fistulosum × A. cepa under greenhouse conditions. Phenotypic assays showed that, in general, these strains were more aggressive on A. fistulosum × A. cepa as opposed to A. porrum. Of the 92 strains, only six showed highly aggressive foliar lesions on A. porrum compared to A. fistulosum × A. cepa. Conversely, nine strains showed highly aggressive foliar lesions on A. fistulosum × A. cepa compared to A. porrum. These results indicate that there are underlying genetic components in P. ananatis that may drive pathogenicity in these two Allium spp. Based on GWAS for foliar pathogenicity, 835 genes were associated with P. ananatis' pathogenicity on A. fistulosum × A. cepa whereas 243 genes were associated with bacterial pathogenicity on A. porrum. The Hivir as well as the alt gene clusters were identified among these genes. Besides the 'HiVir' and the alt gene clusters that are known to contribute to pathogenicity and virulence from previous studies, genes annotated with functions related to stress responses, a potential toxin-antitoxin system, flagellar-motility, quorum sensing, and a previously described phosphonoglycan biosynthesis (pgb) cluster were identified. The GPC analysis resulted in the identification of 165 individual genes sorted into 39 significant gene-pair association components and 255 genes sorted into 50 significant gene-pair dissociation components. Within the coincident gene clusters, several genes that occurred on the GWAS outputs were associated with each other but dissociated with genes that did not appear in their respective GWAS output. To focus on candidate genes that could explain the difference in virulence between hosts, a comparative genomics analysis was performed on five P. ananatis strains that were differentially pathogenic on A. porrum or A. fistulosum × A. cepa. Here, we found a putative type III secretion system, and several other genes that occurred on both GWAS outputs of both Allium hosts. Further, we also demonstrated utilizing mutational analysis that the pepM gene in the HiVir cluster is important than the pepM gene in the pgb cluster for P. ananatis pathogenicity in A. fistulosum × A. cepa and A. porrum. Overall, our results support that P. ananatis may utilize a common set of genes or gene clusters to induce symptoms on A. fistulosum × A. cepa foliar tissue as well as A. cepa but implicates additional genes for infection on A. porrum.

GWAS and functional studies suggest a role for altered DNA repair in the evolution of drug resistance in Mycobacterium tuberculosis

The emergence of drug resistance in Mycobacterium tuberculosis (Mtb) is alarming and demands in-depth knowledge for timely diagnosis. We performed genome-wide association analysis using 2237 clinical strains of Mtb to identify novel genetic factors that evoke drug resistance. In addition to the known direct targets, we identified for the first time, a strong association between mutations in DNA repair genes and the multidrug-resistant phenotype. To evaluate the impact of variants identified in the clinical samples in the evolution of drug resistance, we utilized knockouts and complemented strains in Mycobacterium smegmatis and Mtb. Results show that variant mutations compromised the functions of MutY and UvrB. MutY variant showed enhanced survival compared with wild-type (Rv) when the Mtb strains were subjected to multiple rounds of ex vivo antibiotic stress. In an in vivo guinea pig infection model, the MutY variant outcompeted the wild-type strain. We show that novel variant mutations in the DNA repair genes collectively compromise their functions and contribute to better survival under antibiotic/host stress conditions.

A pro-oxidant property of vitamin C to overcome the burden of latent Mycobacterium tuberculosis infection: A cross-talk review with Fenton reaction

Tuberculosis (TB), caused by the bacillus M. tuberculosis, is one of the deadliest infectious illnesses of our day, along with HIV and malaria.Chemotherapy, the cornerstone of TB control efforts, is jeopardized by the advent of M. tuberculosis strains resistant to many, if not all, of the existing medications.Isoniazid (INH), rifampicin (RIF), pyrazinamide, and ethambutol are used to treat drug-susceptible TB for two months, followed by four months of INH and RIF, but chemotherapy with potentially harmful side effects is sometimes needed to treat multidrug-resistant (MDR) TB for up to two years. Chemotherapy might be greatly shortened by drugs that kill M. tuberculosis more quickly while simultaneously limiting the emergence of drug resistance.Regardless of their intended target, bactericidal medicines commonly kill pathogenic bacteria (gram-negative and gram-positive) by producing hydroxyl radicals via the Fenton reaction.Researchers have concentrated on vitamins with bactericidal properties to address the rising cases globally and have discovered that these vitamins are effective when given along with first-line drugs. The presence of elevated iron content, reactive oxygen species (ROS) generation, and DNA damage all contributed to VC's sterilizing action on M. tb in vitro. Moreover, it has a pleiotropic effect on a variety of biological processes such as detoxification, protein folding - chaperons, cell wall processes, information pathways, regulatory, virulence, metabolism etc.In this review report, the authors extensively discussed the effects of VC on M. tb., such as the generation of free radicals and bactericidal mechanisms with existing treatments, and their further drug development based on ROS production.

Detecting bacterial adaptation within individual microbiomes

The human microbiome harbours a large capacity for within-person adaptive mutations. Commensal bacterial strains can stably colonize a person for decades, and billions of mutations are generated daily within each person's microbiome. Adaptive mutations emerging during health might be driven by selective forces that vary across individuals, vary within an individual, or are completely novel to the human population. Mutations emerging within individual microbiomes might impact the immune system, the metabolism of nutrients or drugs, and the stability of the community to perturbations. Despite this potential, relatively little attention has been paid to the possibility of adaptive evolution within complex human-associated microbiomes. This review discusses the promise of studying within-microbiome adaptation, the conceptual and technical limitations that may have contributed to an underappreciation of adaptive de novo mutations occurring within microbiomes to date, and methods for detecting recent adaptive evolution. This article is part of a discussion meeting issue 'Genomic population structures of microbial pathogens'.

Transcriptional regulation and drug resistance in Mycobacterium tuberculosis

Bacterial drug resistance is one of the major challenges to present and future human health, as the continuous selection of multidrug resistant bacteria poses at serious risk the possibility to treat infectious diseases in the near future. One of the infection at higher risk to become incurable is tuberculosis, due to the few drugs available in the market against Mycobacterium tuberculosis. Drug resistance in this species is usually due to point mutations in the drug target or in proteins required to activate prodrugs. However, another interesting and underexplored aspect of bacterial physiology with important impact on drug susceptibility is represented by the changes in transcriptional regulation following drug exposure. The main regulators involved in this phenomenon in M. tuberculosis are the sigma factors, and regulators belonging to the WhiB, GntR, XRE, Mar and TetR families. Better understanding the impact of these regulators in survival to drug treatment might contribute to identify new drug targets and/or to design new strategies of intervention.

Poor eyesight reveals a new vision gene

Comparing the genomes of mammals which evolved to have poor vision identifies an important gene for eyesight.

Genome-wide association studies of global Mycobacterium tuberculosis resistance to 13 antimicrobials in 10,228 genomes identify new resistance mechanisms

The emergence of drug-resistant tuberculosis is a major global public health concern that threatens the ability to control the disease. Whole-genome sequencing as a tool to rapidly diagnose resistant infections can transform patient treatment and clinical practice. While resistance mechanisms are well understood for some drugs, there are likely many mechanisms yet to be uncovered, particularly for new and repurposed drugs. We sequenced 10,228 Mycobacterium tuberculosis (MTB) isolates worldwide and determined the minimum inhibitory concentration (MIC) on a grid of 2-fold concentration dilutions for 13 antimicrobials using quantitative microtiter plate assays. We performed oligopeptide- and oligonucleotide-based genome-wide association studies using linear mixed models to discover resistance-conferring mechanisms not currently catalogued. Use of MIC over binary resistance phenotypes increased sample heritability for the new and repurposed drugs by 26% to 37%, increasing our ability to detect novel associations. For all drugs, we discovered uncatalogued variants associated with MIC, including in the Rv1218c promoter binding site of the transcriptional repressor Rv1219c (isoniazid), upstream of the vapBC20 operon that cleaves 23S rRNA (linezolid) and in the region encoding an α-helix lining the active site of Cyp142 (clofazimine, all p < 10-7.7). We observed that artefactual signals of cross-resistance could be unravelled based on the relative effect size on MIC. Our study demonstrates the ability of very large-scale studies to substantially improve our knowledge of genetic variants associated with antimicrobial resistance in M. tuberculosis.

Diversity and novel mutations in membrane transporters of Mycobacterium tuberculosis

Mycobacterium tuberculosis (MTB), the causative agent of tuberculosis (TB), encodes a family of membrane proteins belonging to Resistance-Nodulation-Cell Division (RND) permeases also called multidrug resistance pumps. Mycobacterial membrane protein Large (MmpL) transporters represent a subclass of RND transporters known to participate in exporting of lipid components across the cell envelope. These proteins perform an essential role in MTB survival; however, there are no data regarding mutations in MmpL, polyketide synthase (PKS) and acyl-CoA dehydrogenase FadE proteins from Khyber Pakhtunkhwa, Pakistan. This study aimed to screen mutations in transmembrane transporter proteins including MmpL, PKS and Fad through whole-genome sequencing (WGS) in local isolates of Khyber Pakhtunkhwa province, Pakistan. Fourteen samples were collected from TB patients and drug susceptibility testing was performed. However, only three samples were completely sequenced. Moreover, 209 whole-genome sequences of the same geography were also retrieved from NCBI GenBank to analyze the diversity of mutations in MmpL, PKS and Fad proteins. Among the 212 WGS (Accession ID: PRJNA629298, PRJNA629388, and ERR2510337-ERR2510345, ERR2510546-ERR2510645), numerous mutations in Fad (n = 756), PKS (n = 479), and MmpL (n = 306) have been detected. Some novel mutations were also detected in MmpL, PKS and acyl-CoA dehydrogenase Fad. Novel mutations including Asn576Ser in MmpL8, Val943Gly in MmpL9 and Asn145Asp have been detected in MmpL3. The presence of a large number of mutations in the MTB membrane may have functional consequences on proteins. However, further experimental studies are needed to elucidate the variants' effect on MmpL, PKS and FadE functions.

Population genomics of Group B Streptococcus reveals the genetics of neonatal disease onset and meningeal invasion

Group B Streptococcus (GBS), or Streptococcus agalactiae, is a pathogen that causes preterm births, stillbirths, and acute invasive neonatal disease burden and mortality. Here, we investigate bacterial genetic signatures associated with disease onset time and meningeal tissue infection in acute invasive neonatal GBS disease. We carry out a genome-wide association study (GWAS) of 1,338 GBS isolates from newborns with acute invasive disease; the isolates had been collected annually, for 30 years, through a national bacterial surveillance program in the Netherlands. After controlling for the population structure, we identify genetic variation within noncoding and coding regions, particularly the capsule biosynthesis locus, statistically associated with neonatal GBS disease onset time and meningeal invasion. Our findings highlight the impact of integrating microbial population genomics and clinical pathogen surveillance, and demonstrate the effect of GBS genetics on disease pathogenesis in neonates and infants.

Genome-Wide Study of Drug Resistant Mycobacterium tuberculosis and Its Intra-Host Evolution during Treatment

The emergence of drug resistant Mycobacterium tuberculosis (MTB) strains has become a global public health problem, while, at the same time, there has been development of new antimicrobial agents. The main goals of this study were to determine new variants associated with drug resistance in MTB and to observe which polymorphisms emerge in MTB genomes after anti-tuberculosis treatment. We performed whole-genome sequencing of 152 MTB isolates including 70 isolates as 32 series of pre- and post-treatment MTB. Based on genotypes and phenotypic drug susceptibility, we conducted phylogenetic convergence-based genome-wide association study (GWAS) with streptomycin-, isoniazid-, rifampicin-, ethambutol-, fluoroquinolones-, and aminoglycosides-resistant MTB against susceptible ones. GWAS revealed statistically significant associations of SNPs within Rv2820c, cyp123 and indels in Rv1269c, Rv1907c, Rv1883c, Rv2407, Rv3785 genes with resistant MTB phenotypes. Comparisons of serial isolates showed that treatment induced different patterns of intra-host evolution. We found indels within Rv1435c and ppsA that were not lineage-specific. In addition, Beijing-specific polymorphisms within Rv0036c, Rv0678, Rv3433c, and dop genes were detected in post-treatment isolates. The appearance of Rv3785 frameshift insertion in 2 post-treatment strains compared to pre-treatment was also observed. We propose that the insertion within Rv3785, which was a GWAS hit, might affect cell wall biosynthesis and probably mediates a compensatory mechanism in response to treatment. These results may shed light on the mechanisms of MTB adaptation to chemotherapy and drug resistance formation.

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.

Genomic analysis of diversity, biogeography, and drug resistance in Mycobacterium bovis

Mycobacterium bovis is the cause of bovine tuberculosis, and it can also cause disease in humans, with symptoms similar to those caused by Mycobacterium tuberculosis. However, our understanding of its genomic diversity, biogeography, and drug resistance remains incomplete. We performed a comparative and phylogenetic analysis of 3,228 M. bovis genomes from 24 countries. Following drug susceptibility testing, we applied a bacterial genome-wide association study to capture associations between genomic variation and drug resistance in 74 newly isolated strains from China. The data show that the cattle-adapted M. bovis were divided into six lineages with a strong phylogeographical population structure. Lineage 1 and Lineage 6 are the most widespread globally, while others show a strong geographical restriction. 17.39% of M. bovis isolates were resistant to at least one drug in China. Furthermore, we identify genomic variations associated with an increased risk of resistance acquisition. This study furthers our knowledge of M. bovis diversity, biogeography, and drug resistance and will facilitate more deeply informed genomic tracking and surveillance to minimize its threat to human health, as a cause of zoonotic tuberculosis. This article is protected by copyright. All rights reserved.

A genome-wide scan of wastewater E. coli for genes under positive selection: focusing on mechanisms of antibiotic resistance

Antibiotic resistance is a global health threat and consequently, there is a need to understand the mechanisms driving its emergence. Here, we hypothesize that genes and mutations under positive selection may contribute to antibiotic resistance. We explored wastewater E. coli, whose genomes are highly diverse. We subjected 92 genomes to a statistical analysis for positively selected genes. We obtained 75 genes under positive selection and explored their potential for antibiotic resistance. We found that eight genes have functions relating to antibiotic resistance, such as biofilm formation, membrane permeability, and bacterial persistence. Finally, we correlated the presence/absence of non-synonymous mutations in positively selected sites of the genes with a function in resistance against 20 most prescribed antibiotics. We identified mutations associated with antibiotic resistance in two genes: the porin ompC and the bacterial persistence gene hipA. These mutations are located at the surface of the proteins and may hence have a direct effect on structure and function. For hipA, we hypothesize that the mutations influence its interaction with hipB and that they enhance the capacity for dormancy as a strategy to evade antibiotics. Overall, genomic data and positive selection analyses uncover novel insights into mechanisms driving antibiotic resistance.

Evolution and spread of a highly drug resistant strain of Mycobacterium tuberculosis in Papua New Guinea

BACKGROUND

Molecular mechanisms determining the transmission and prevalence of drug resistant tuberculosis (DR-TB) in Papua New Guinea (PNG) are poorly understood. We used genomic and drug susceptibility data to explore the evolutionary history, temporal acquisition of resistance and transmission dynamics of DR-TB across PNG.

METHODS

We performed whole genome sequencing on isolates from Central Public Health Laboratory, PNG, collected 2017-2019. Data analysis was done on a composite dataset that also included 100 genomes previously sequenced from Daru, PNG (2012-2015).

RESULTS

Sampled isolates represented 14 of the 22 PNG provinces, the majority (66/94; 70%) came from the National Capital District (NCD). In the composite dataset, 91% of strains were Beijing 2.2.1.1, identified in 13 provinces. Phylogenetic tree of Beijing strains revealed two clades, Daru dominant clade (A) and NCD dominant clade (B). Multi-drug resistance (MDR) was repeatedly and independently acquired, with the first MDR cases in both clades noted to have emerged in the early 1990s, while fluoroquinolone resistance emerged in 2009 (95% highest posterior density 2000-2016). We identified the presence of a frameshift mutation within Rv0678 (p.Asp47fs) which has been suggested to confer resistance to bedaquiline, despite no known exposure to the drug. Overall genomic clustering was significantly associated with rpoC compensatory and inhA promoter mutations (p < 0.001), with high percentage of most genomic clusters (12/14) identified in NCD, reflecting its role as a potential national amplifier.

CONCLUSIONS

The acquisition and evolution of drug resistance among the major clades of Beijing strain threaten the success of DR-TB treatment in PNG. With continued transmission of this strain in PNG, genotypic drug resistance surveillance using whole genome sequencing is essential for improved public health response to outbreaks. With occurrence of resistance to newer drugs such as bedaquiline, knowledge of full drug resistance profiles will be important for optimal treatment selection.

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.

Comprehensive Analysis of the Nocardia cyriacigeorgica Complex Reveals Five Species-Level Clades with Different Evolutionary and Pathogenicity Characteristics

Nocardia cyriacigeorgica is a common etiological agent of nocardiosis that has increasingly been implicated in serious pulmonary infections, especially in immunocompromised individuals. However, the evolution, diversity, and pathogenesis of N. cyriacigeorgica have remained unclear. Here, we performed a comparative genomic analysis using 91 N. cyriacigeorgica strains, 45 of which were newly sequenced in this study. Phylogenetic and average nucleotide identity (ANI) analyses revealed that N. cyriacigeorgica contained five species-level clades (8.6 to 14.6% interclade genetic divergence), namely, the N. cyriacigeorgica complex (NCC). Further pan-genome analysis revealed extensive differences among the five clades in nine functional categories, such as energy production, lipid metabolism, secondary metabolites, and signal transduction mechanisms. All 2,935 single-copy core genes undergoing purifying selection were highly conserved across NCC. However, clades D and E exhibited reduced selective constraints, compared to clades A to C. Horizontal gene transfer (HGT) and mobile genetic elements contributed to genomic plasticity, and clades A and B had experienced a higher level of HGT events than other clades. A total of 129 virulence factors were ubiquitous across NCC, such as the mce operon, hemolysin, and type VII secretion system (T7SS). However, different distributions of three toxin-coding genes and two new types of mce operons were detected, which might contribute to pathogenicity differences among the members of the NCC. Overall, our study provides comprehensive insights into the evolution, genetic diversity, and pathogenicity of NCC, facilitating the prevention of infections.

IMPORTANCENocardia species are opportunistic bacterial pathogens that can affect all organ systems, primarily the skin, lungs, and brain. N. cyriacigeorgica is the most prevalent species within the genus, exhibits clinical significance, and can cause severe infections when disseminated throughout the body. However, the evolution, diversity, and pathogenicity of N. cyriacigeorgica remain unclear. Here, we have conducted a comparative genomic analysis of 91 N. cyriacigeorgica strains and revealed that N. cyriacigeorgica is not a single species but is composed of five closely related species. In addition, we discovered that these five species differ in many ways, involving selection pressure, horizontal gene transfer, functional capacity, pathogenicity, and antibiotic resistance. Overall, our work provides important clues in dissecting the evolution, genetic diversity, and pathogenicity of NCC, thereby advancing prevention measures against these infections.

Whole Genome Sequencing Contributions and Challenges in Disease Reduction Focused on Malaria

Malaria elimination remains an important goal that requires the adoption of sophisticated science and management strategies in the era of the COVID-19 pandemic. The advent of next generation sequencing (NGS) is making whole genome sequencing (WGS) a standard today in the field of life sciences, as PCR genotyping and targeted sequencing provide insufficient information compared to the whole genome. Thus, adapting WGS approaches to malaria parasites is pertinent to studying the epidemiology of the disease, as different regions are at different phases in their malaria elimination agenda. Therefore, this review highlights the applications of WGS in disease management, challenges of WGS in controlling malaria parasites, and in furtherance, provides the roles of WGS in pursuit of malaria reduction and elimination. WGS has invaluable impacts in malaria research and has helped countries to reach elimination phase rapidly by providing required information needed to thwart transmission, pathology, and drug resistance. However, to eliminate malaria in sub-Saharan Africa (SSA), with high malaria transmission, we recommend that WGS machines should be readily available and affordable in the region.

PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies

Genome-wide association studies (GWAS) are increasingly being applied to investigate the genetic basis of bacterial traits. However, approaches to perform power calculations for bacterial GWAS are limited. Here we implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. First, a sub-sampling approach was undertaken to reduce the allele frequency and effect size of a known and detectable genotype-phenotype relationship by modifying phenotype labels. Second, a phenotype-simulation approach was conducted to simulate phenotypes from existing genetic variants. We implemented both approaches into a computational pipeline (PowerBacGWAS) that supports power calculations for burden testing, pan-genome and variant GWAS; and applied it to collections of Enterococcus faecium, Klebsiella pneumoniae and Mycobacterium tuberculosis. We used this pipeline to determine sample sizes required to detect causal variants of different minor allele frequencies (MAF), effect sizes and phenotype heritability, and studied the effect of homoplasy and population diversity on the power to detect causal variants. Our pipeline and user documentation are made available and can be applied to other bacterial populations. PowerBacGWAS can be used to determine sample sizes required to find statistically significant associations, or the associations detectable with a given sample size. We recommend to perform power calculations using existing genomes of the bacterial species and population of study.

Genome-Wide Association Study Reveals Host Factors Affecting Conjugation in Escherichia coli

The emergence and dissemination of antibiotic resistance threaten the treatment of common bacterial infections. Resistance genes are often encoded on conjugative elements, which can be horizontally transferred to diverse bacteria. In order to delay conjugative transfer of resistance genes, more information is needed on the genetic determinants promoting conjugation. Here, we focus on which bacterial host factors in the donor assist transfer of conjugative plasmids. We introduced the broad-host-range plasmid pKJK10 into a diverse collection of 113 Escherichia coli strains and measured by flow cytometry how effectively each strain transfers its plasmid to a fixed E. coli recipient. Differences in conjugation efficiency of up to 2.7 and 3.8 orders of magnitude were observed after mating for 24 h and 48 h, respectively. These differences were linked to the underlying donor strain genetic variants in genome-wide association studies, thereby identifying candidate genes involved in conjugation. We confirmed the role of fliF, fliK, kefB and ucpA in the donor ability of conjugative elements by validating defects in the conjugation efficiency of the corresponding lab strain single-gene deletion mutants. Based on the known cellular functions of these genes, we suggest that the motility and the energy supply, the intracellular pH or salinity of the donor affect the efficiency of plasmid transfer. Overall, this work advances the search for targets for the development of conjugation inhibitors, which can be administered alongside antibiotics to more effectively treat bacterial infections.

Integrative Reverse Genetic Analysis Identifies Polymorphisms Contributing to Decreased Antimicrobial Agent Susceptibility in Streptococcus pyogenes

Identification of genetic polymorphisms causing increased antibiotic resistance in bacterial pathogens traditionally has proceeded from observed phenotype to defined mutant genotype. The availability of large collections of microbial genome sequences that lack antibiotic susceptibility metadata provides an important resource and opportunity to obtain new information about increased antimicrobial resistance by a reverse genotype-to-phenotype bioinformatic and experimental workflow. We analyzed 26,465 genome sequences of Streptococcus pyogenes, a human pathogen causing 700 million infections annually. The population genomic data identified amino acid changes in penicillin-binding proteins 1A, 1B, 2A, and 2X with signatures of evolution under positive selection as potential candidates for causing decreased susceptibility to β-lactam antibiotics. Construction and analysis of isogenic mutant strains containing individual amino acid replacements in penicillin-binding protein 2X (PBP2X) confirmed that the identified residues produced decreased susceptibility to penicillin. We also discovered the first chimeric PBP2X in S. pyogenes and show that strains containing it have significantly decreased β-lactam susceptibility. The novel integrative reverse genotype-to-phenotype strategy presented is broadly applicable to other pathogens and likely will lead to new knowledge about antimicrobial agent resistance, a massive public health problem worldwide. IMPORTANCE The recent demonstration that naturally occurring amino acid substitutions in Streptococcus pyogenes PBP2X are sufficient to cause severalfold reduced susceptibility to multiple β-lactam antibiotics in vitro raises the concern that these therapeutic agents may become compromised. Substitutions in PBP2X are common first-step mutations that, with the incremental accumulation of additional adaptive mutations within the PBPs, can result in high-level resistance. Because β-lactam susceptibility testing is not routinely performed, the nature and extent of such substitutions within the PBPs of S. pyogenes are poorly characterized. To address this knowledge deficit, polymorphisms in the PBPs were identified among the most comprehensive cohort of S. pyogenes genome sequences investigated to date. The mutational processes and selective forces acting on the PBPs were assessed to identify specific substitutions likely to influence β-lactam susceptibility and to evaluate factors posited to be impediments to resistance emergence.

Evidence of episodic positive selection in Corynebacterium diphtheriae complex of species and its implementations in identification of drug and vaccine targets

BACKGROUND

Within the pathogenic bacterial species Corynebacterium genus, six species that can produce diphtheria toxin (C. belfantii, C. diphtheriae, C. pseudotuberculosis, C. rouxii, C. silvaticum and C. ulcerans) form a clade referred to as the C. diphtheria complex. These species have been found in humans and other animals, causing diphtheria or other diseases. Here we show the results of a genome scale analysis to identify positive selection in protein-coding genes that may have resulted in the adaptations of these species to their ecological niches and suggest drug and vaccine targets.

METHODS

Forty genomes were sampled to represent species, subspecies or biovars of Corynebacterium. Ten phylogenetic groups were tested for positive selection using the PosiGene pipeline, including species and biovars from the C. diphtheria complex. The detected genes were tested for recombination and had their sequences alignments and homology manually examined. The final genes were investigated for their function and a probable role as vaccine or drug targets.

RESULTS

Nineteen genes were detected in the species C. diphtheriae (two), C. pseudotuberculosis (10), C. rouxii (one), and C. ulcerans (six). Those were found to be involved in defense, translation, energy production, and transport and in the metabolism of carbohydrates, amino acids, nucleotides, and coenzymes. Fourteen were identified as essential genes, and six as virulence factors. Thirteen from the 19 genes were identified as potential drug targets and four as potential vaccine candidates. These genes could be important in the prevention and treatment of the diseases caused by these bacteria.

The Structural Basis of Mycobacterium tuberculosis RpoB Drug-Resistant Clinical Mutations on Rifampicin Drug Binding

Tuberculosis (TB), caused by the Mycobacterium tuberculosis infection, continues to be a leading cause of morbidity and mortality in developing countries. Resistance to the first-line anti-TB drugs, isoniazid (INH) and rifampicin (RIF), is a major drawback to effective TB treatment. Genetic mutations in the β-subunit of the DNA-directed RNA polymerase (rpoB) are reported to be a major reason of RIF resistance. However, the structural basis and mechanisms of these resistant mutations are insufficiently understood. In the present study, thirty drug-resistant mutants of rpoB were initially modeled and screened against RIF via a comparative molecular docking analysis with the wild-type (WT) model. These analyses prioritized six mutants (Asp441Val, Ser456Trp, Ser456Gln, Arg454Gln, His451Gly, and His451Pro) that showed adverse binding affinities, molecular interactions, and RIF binding hinderance properties, with respect to the WT. These mutant models were subsequently analyzed by molecular dynamics (MD) simulations. One-hundred nanosecond all-atom MD simulations, binding free energy calculations, and a dynamic residue network analysis (DRN) were employed to exhaustively assess the impact of mutations on RIF binding dynamics. Considering the global structural motions and protein-ligand binding affinities, the Asp441Val, Ser456Gln, and His454Pro mutations generally yielded detrimental effects on RIF binding. Locally, we found that the electrostatic contributions to binding, particularly by Arg454 and Glu487, might be adjusted to counteract resistance. The DRN analysis revealed that all mutations mostly distorted the communication values of the critical hubs and may, therefore, confer conformational changes in rpoB to perturb RIF binding. In principle, the approach combined fundamental molecular modeling tools for robust "global" and "local" level analyses of structural dynamics, making it well suited for investigating other similar drug resistance cases.

Whole genome sequencing reveals large deletions and other loss of function mutations in Mycobacterium tuberculosis drug resistance genes

Drug resistance in Mycobacterium tuberculosis, the causative agent of tuberculosis disease, arises from genetic mutations in genes coding for drug-targets or drug-converting enzymes. SNPs linked to drug resistance have been extensively studied and form the basis of molecular diagnostics and sequencing-based resistance profiling. However, alternative forms of functional variation such as large deletions and other loss of function (LOF) mutations have received much less attention, but if incorporated into diagnostics they are likely to improve their predictive performance. Our work aimed to characterize the contribution of LOF mutations found in 42 established drug resistance genes linked to 19 anti-tuberculous drugs across 32689 sequenced clinical isolates. The analysed LOF mutations included large deletions (n=586), frameshifts (n=4764) and premature stop codons (n=826). We found LOF mutations in genes strongly linked to pyrazinamide (pncA), isoniazid (katG), capreomycin (tlyA), streptomycin (e.g. gid) and ethionamide (ethA, mshA) (P<10^-5), but also in some loci linked to drugs where relatively less phenotypic data is available [e.g. cycloserine, delaminid, bedaquiline, para-aminosalicylic acid (PAS), and clofazimine]. This study reports that large deletions (median size 1115 bp) account for a significant portion of resistance variants found for PAS (+7.1% of phenotypic resistance percentage explained), pyrazinamide (+3.5%) and streptomycin (+2.6%) drugs, and can be used to improve the prediction of cryptic resistance. Overall, our work highlights the importance of including LOF mutations (e.g. large deletions) in predicting genotypic drug resistance, thereby informing tuberculosis infection control and clinical decision-making.

SNPPar: identifying convergent evolution and other homoplasies from microbial whole-genome alignments

Homoplasic SNPs are considered important signatures of strong (positive) selective pressure, and hence of adaptive evolution for clinically relevant traits such as antibiotic resistance and virulence. Here we present a new tool, SNPPar, for efficient detection and analysis of homoplasic SNPs from large whole genome sequencing datasets (>1000 isolates and/or >100 000 SNPs). SNPPar takes as input an SNP alignment, tree and annotated reference genome, and uses a combination of simple monophyly tests and ancestral state reconstruction (ASR, via TreeTime) to assign mutation events to branches and identify homoplasies. Mutations are annotated at the level of codon and gene, to facilitate analysis of convergent evolution. Testing on simulated data (120 Mycobacterium tuberculosis alignments representing local and global samples) showed SNPPar can detect homoplasic SNPs with very high specificity (zero false-positives in all tests) and high sensitivity (zero false-negatives in 89 % of tests). SNPPar analysis of three empirically sampled datasets (Elizabethkingia anophelis, Burkholderia dolosa and M. tuberculosis) produced results that were in concordance with previous studies, in terms of both individual homoplasies and evidence of convergence at the codon and gene levels. SNPPar analysis of a simulated alignment of ~64 000 genome-wide SNPs from 2000 M. tuberculosis genomes took ~23 min and ~2.6 GB of RAM to generate complete annotated results on a laptop. This analysis required ASR be conducted for only 1.25 % of SNPs, and the ASR step took ~23 s and 0.4 GB of RAM. SNPPar automates the detection and annotation of homoplasic SNPs efficiently and accurately from large SNP alignments. As demonstrated by the examples included here, this information can be readily used to explore the role of homoplasy in parallel and/or convergent evolution at the level of nucleotide, codon and/or gene.

An evolutionary functional genomics approach identifies novel candidate regions involved in isoniazid resistance in Mycobacterium tuberculosis

Efforts to eradicate tuberculosis are hampered by the rise and spread of antibiotic resistance. Several large-scale projects have aimed to specifically link clinical mutations to resistance phenotypes, but they were limited in both their explanatory and predictive powers. Here, we combine functional genomics and phylogenetic associations using clinical strain genomes to decipher the architecture of isoniazid resistance and search for new resistance determinants. This approach has allowed us to confirm the main target route of the antibiotic, determine the clinical relevance of redox metabolism as an isoniazid resistance mechanism and identify novel candidate genes harboring resistance mutations in strains with previously unexplained isoniazid resistance. This approach can be useful for characterizing how the tuberculosis bacilli acquire resistance to new antibiotics and how to forestall them.

Victoria Furió et al. apply functional genomics and evolutionary analyses to the study of antibiotic resistance in tuberculosis. Focusing on isoniazid resistance and using genomic data from clinical strains, they identify novel candidate genes with resistance mutations and further uncover the mechanisms underlying drug resistance.