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

Holistic understanding of trimethoprim resistance in Streptococcus pneumoniae using an integrative approach of genome-wide association study, resistance reconstruction, and machine learning

Antimicrobial resistance (AMR) is a public health threat worldwide. Next-generation sequencing (NGS) has opened unprecedented opportunities to accelerate AMR mechanism discovery and diagnostics. Here, we present an integrative approach to investigate trimethoprim (TMP) resistance in the key pathogen Streptococcus pneumoniae. We explored a collection of 662 S. pneumoniae genomes by conducting a genome-wide association study (GWAS), followed by functional validation using resistance reconstruction experiments, combined with machine learning (ML) approaches to predict TMP minimum inhibitory concentration (MIC). Our study showed that multiple additive mutations in the folA and sulA loci are responsible for TMP non-susceptibility in S. pneumoniae and can be used as key features to build ML models for digital MIC prediction, reaching an average accuracy within ±1 twofold dilution factor of 86.3%. Our roadmap of in silico analysis-wet-lab validation-diagnostic tool building could be adapted to explore AMR in other combinations of bacteria-antibiotic.

IMPORTANCE

In the age of next-generation sequencing (NGS), while data-driven methods such as genome-wide association study (GWAS) and machine learning (ML) excel at finding patterns, functional validation can be challenging due to the high numbers of candidate variants. We designed an integrative approach combining a GWAS on S. pneumoniae clinical isolates, followed by whole-genome transformation coupled with NGS to functionally characterize a large set of GWAS candidates. Our study validated several phenotypic folA mutations beyond the standard Ile100Leu mutation, and showed that the overexpression of the sulA locus produces trimethoprim (TMP) resistance in Streptococcus pneumoniae. These validated loci, when used to build ML models, were found to be the best inputs for predicting TMP minimal inhibitory concentrations. Integrative approaches can bridge the genotype-phenotype gap by biological insights that can be incorporated in ML models for accurate prediction of drug susceptibility.

Population genomics of Streptococcus mitis in UK and Ireland bloodstream infection and infective endocarditis cases

Streptococcus mitis is a leading cause of infective endocarditis (IE). However, our understanding of the genomic epidemiology and pathogenicity of IE-associated S. mitis is hampered by low IE incidence. Here we use whole genome sequencing of 129 S. mitis bloodstream infection (BSI) isolates collected between 2001-2016 from clinically diagnosed IE cases in the UK to investigate genetic diversity, antimicrobial resistance, and pathogenicity. We show high genetic diversity of IE-associated S. mitis with virtually all isolates belonging to distinct lineages indicating no predominance of specific lineages. Additionally, we find a highly variable distribution of known pneumococcal virulence genes among the isolates, some of which are overrepresented in disease when compared to carriage strains. Our findings suggest that S. mitis in patients with clinically diagnosed IE is not primarily caused by specific hypervirulent or antimicrobial resistant lineages, highlighting the accidental pathogenic nature of S. mitis in patients with clinically diagnosed IE.

Pan-lineage Mycobacterium tuberculosis reference genome for enhanced molecular diagnosis

In Mycobacterium tuberculosis (MTB) control, whole genome sequencing-based molecular drug susceptibility testing (molDST-WGS) has emerged as a pivotal tool. However, the current reliance on a single-strain reference limits molDST-WGS's true potential. To address this, we introduce a new pan-lineage reference genome, 'MtbRf'. We assembled 'unmapped' reads from 3,614 MTB genomes (751 L1; 881 L2; 1,700 L3; and 282 L4) into 35 shared, annotated contigs (54 coding sequences [CDSs]). We constructed MtbRf through: (1) searching for contig homologues among genome database that precipitate results uniquely within Mycobacteria genus; (2) comparing genomes with H37Rv ('lift-over') to define 18 insertions; and (3) filling gaps in H37Rv with insertions. MtbRf adds 1.18% sequences to H37rv, salvaging >60% of previously unmapped reads. Transcriptomics confirmed gene expression of new CDSs. The new variants provided a moderate DST predictive value (AUROC 0.60-0.75). MtbRf thus unveils previously hidden genomic information and lays the foundation for lineage-specific molDST-WGS.

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.

The Emergence of Non-Linear Evolutionary Trade-offs and the Maintenance of Genetic Polymorphisms

Evolutionary models of quantitative traits often assume trade-offs between beneficial and detrimental traits, requiring modelers to specify a function linking costs to benefits. The choice of trade-off function is often consequential; functions that assume diminishing returns (accelerating costs) typically lead to single equilibrium genotypes, while decelerating costs often lead to evolutionary branching. Despite their importance, we still lack a strong theoretical foundation to base the choice of trade-off function. To address this gap, we explore how trade-off functions can emerge from the genetic architecture of a quantitative trait. We developed a multi-locus model of disease resistance, assuming each locus had random antagonistic pleiotropic effects on resistance and fecundity. We used this model to generate genotype landscapes and explored how additive versus epistatic genetic architectures influenced the shape of the trade-off function. Regardless of epistasis, our model consistently led to accelerating costs. We then used our genotype landscapes to build an evolutionary model of disease resistance. Unlike other models with accelerating costs, our approach often led to genetic polymorphisms at equilibrium. Our results suggest that accelerating costs are a strong null model for evolutionary trade-offs and that the eco-evolutionary conditions required for polymorphism may be more nuanced than previously believed.

Large-scale statistical analysis of Mycobacterium tuberculosis genome sequences identifies compensatory mutations associated with multi-drug resistance

Tuberculosis (TB), caused by Mycobacterium tuberculosis, has a significant impact on global health worldwide. The development of multi-drug resistant strains that are resistant to the first-line drugs isoniazid and rifampicin threatens public health security. Rifampicin and isoniazid resistance are largely underpinned by mutations in rpoB and katG respectively and are associated with fitness costs. Compensatory mutations are considered to alleviate these fitness costs and have been observed in rpoC/rpoA (rifampicin) and oxyR'-ahpC (isoniazid). We developed a framework (CompMut-TB) to detect compensatory mutations from whole genome sequences from a large dataset comprised of 18,396 M. tuberculosis samples. We performed association analysis (Fisher's exact tests) to identify pairs of mutations that are associated with drug-resistance, followed by mediation analysis to identify complementary or full mediators of drug-resistance. The analyses revealed several potential mutations in rpoC (N = 47), rpoA (N = 4), and oxyR'-ahpC (N = 7) that were considered either 'highly likely' or 'likely' to confer compensatory effects on drug-resistance, including mutations that have previously been reported and validated. Overall, we have developed the CompMut-TB framework which can assist with identifying compensatory mutations which is important for more precise genome-based profiling of drug-resistant TB strains and to further understanding of the evolutionary mechanisms that underpin drug-resistance.

Drug-resistant tuberculosis: a persistent global health concern

Drug-resistant tuberculosis (TB) is estimated to cause 13% of all antimicrobial resistance-attributable deaths worldwide and is driven by both ongoing resistance acquisition and person-to-person transmission. Poor outcomes are exacerbated by late diagnosis and inadequate access to effective treatment. Advances in rapid molecular testing have recently improved the diagnosis of TB and drug resistance. Next-generation sequencing of Mycobacterium tuberculosis has increased our understanding of genetic resistance mechanisms and can now detect mutations associated with resistance phenotypes. All-oral, shorter drug regimens that can achieve high cure rates of drug-resistant TB within 6-9 months are now available and recommended but have yet to be scaled to global clinical use. Promising regimens for the prevention of drug-resistant TB among high-risk contacts are supported by early clinical trial data but final results are pending. A person-centred approach is crucial in managing drug-resistant TB to reduce the risk of poor treatment outcomes, side effects, stigma and mental health burden associated with the diagnosis. In this Review, we describe current surveillance of drug-resistant TB and the causes, risk factors and determinants of drug resistance as well as the stigma and mental health considerations associated with it. We discuss recent advances in diagnostics and drug-susceptibility testing and outline the progress in developing better treatment and preventive therapies.

Iron-related gene mutations driving global Mycobacterium tuberculosis transmission revealed by whole-genome sequencing

BACKGROUND

Iron plays a crucial role in the growth of Mycobacterium tuberculosis (M. tuberculosis). However, the precise regulatory mechanism governing this system requires further elucidation. Additionally, limited studies have examined the impact of gene mutations related to iron on the transmission of M. tuberculosis globally. This research aims to investigate the correlation between mutations in iron-related genes and the worldwide transmission of M. tuberculosis.

RESULTS

A total of 13,532 isolates of M. tuberculosis were included in this study. Among them, 6,104 (45.11%) were identified as genomic clustered isolates, while 8,395 (62.04%) were classified as genomic clade isolates. Our results showed that a total of 12 single nucleotide polymorphisms (SNPs) showed a positive correlation with clustering, such as Rv1469 (ctpD, C758T), Rv3703c (etgB, G1122T), and Rv3743c (ctpJ, G676C). Additionally, seven SNPs, including Rv0104 (T167G, T478G), Rv0211 (pckA, A302C), Rv0283 (eccB3, C423T), Rv1436 (gap, G654T), ctpD C758T, and etgB C578A, demonstrated a positive correlation with transmission clades across different countries. Notably, our findings highlighted the positive association of Rv0104 T167G, pckA A302C, eccB3 C423T, ctpD C758T, and etgB C578A with transmission clades across diverse regions. Furthermore, our analysis identified 78 SNPs that exhibited significant associations with clade size.

CONCLUSIONS

Our study reveals the link between iron-related gene SNPs and M. tuberculosis transmission, offering insights into crucial factors influencing the pathogenicity of the disease. This research holds promise for targeted strategies in prevention and treatment, advancing research and interventions in this field.

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.

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis. However, molecular diagnostics to date have focused largely on first-line drugs and predicting susceptibilities in a binary manner (classifying strains as either susceptible or resistant). Here, we used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration (MIC) in 15,211 Mycobacterium tuberculosis clinical isolates from 23 countries across five continents. We identified 492 unique MIC-elevating variants across 13 drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.

The population-level impact of Enterococcus faecalis genetics on intestinal colonization and extraintestinal infection

IMPORTANCE

Enterococcus faecalis causes life-threatening invasive hospital- and community-associated infections that are usually associated with multidrug resistance globally. Although E. faecalis infections cause opportunistic infections typically associated with antibiotic use, immunocompromised immune status, and other factors, they also possess an arsenal of virulence factors crucial for their pathogenicity. Despite this, the relative contribution of these virulence factors and other genetic changes to the pathogenicity of E. faecalis strains remain poorly understood. Here, we investigated whether specific genomic changes in the genome of E. faecalis isolates influence its pathogenicity-infection of hospitalized and nonhospitalized individuals and the propensity to cause extraintestinal infection and intestinal colonization. Our findings indicate that E. faecalis genetics partially influence the infection of hospitalized and nonhospitalized individuals and the propensity to cause extraintestinal infection, possibly due to gut-to-bloodstream translocation, highlighting the potential substantial role of host and environmental factors, including gut microbiota, on the opportunistic pathogenic lifestyle of this bacterium.

Association between fatty acid metabolism gene mutations and Mycobacterium tuberculosis transmission revealed by whole genome sequencing

BACKGROUND

Fatty acid metabolism greatly promotes the virulence and pathogenicity of Mycobacterium tuberculosis (M.tb). However, the regulatory mechanism of fatty acid metabolism in M.tb remains to be elucidated, and limited evidence about the effects of gene mutations in fatty acid metabolism on the transmission of M.tb was reported.

RESULTS

Overall, a total of 3193 M.tb isolates were included in the study, of which 1596 (50%) were genomic clustered isolates. Most of the tuberculosis isolates belonged to lineage2(n = 2744,85.93%), followed by lineage4(n = 439,13.75%) and lineage3(n = 10,0.31%).Regression results showed that the mutations of gca (136,605, 317G > C, Arg106Pro; OR, 22.144; 95% CI, 2.591-189.272), ogt(1,477,346, 286G > C ,Gly96Arg; OR, 3.893; 95%CI, 1.432-10.583), and rpsA (1,834,776, 1235 C > T, Ala412Val; OR, 3.674; 95% CI, 1.217-11.091) were significantly associated with clustering; mutations in gca and rpsA were also significantly associated with clustering of lineage2. Mutation in arsA(3,001,498, 885 C > G, Thr295Thr; OR, 6.278; 95% CI, 2.508-15.711) was significantly associated with cross-regional clusters. We also found that 20 mutation sites were positively correlated with cluster size, while 11 fatty acid mutation sites were negatively correlated with cluster size.

CONCLUSION

Our research results suggested that mutations in genes related to fatty acid metabolism were related to the transmission of M.tb. This research could help in the future control of the transmission of M.tb.

Evaluating the Sensitivity of Different Molecular Techniques for Detecting Mycobacterium tuberculosis Complex in Patients with Pulmonary Infection

This study aimed to evaluate the accuracy of detecting drug-resistant Mycobacterium tuberculosis complex (MTBC)-specific DNA in sputum specimens from 48 patients diagnosed with pulmonary tuberculosis. The presence of MTBC DNA in the specimens was validated using the GeneXpert MTB/RIF system and compared with a specific PCR assay targeting the IS6110 and the mtp40 gene sequence fragments. Additionally, the results obtained by multiplex PCR assays to detect the most frequently encountered rifampin, isoniazid, and ethambutol resistance-conferring mutations were matched with those obtained by GeneXpert and phenotypic culture-based drug susceptibility tests. Of the 48 sputum samples, 25 were positive for MTBC using the GeneXpert MTB/RIF test. Nevertheless, the IS6110 and mtp40 single-step PCR revealed the IS6110 in 27 of the 48 sputum samples, while the mtp40 gene fragment was found in only 17 of them. Furthermore, multiplex PCR assays detected drug-resistant conferring mutations in 21 (77.8%) of the 27 samples with confirmed MTBC DNA, 10 of which contained single drug-resistant conferring mutations towards ethambutol and two towards rifampin, and the remaining nine contained double-resistant mutations for ethambutol and rifampin. In contrast, only five sputum specimens (18.5%) contained drug-resistant MTBC isolates, and two contained mono-drug-resistant MTBC species toward ethambutol and rifampin, respectively, and the remaining three were designated as multi-drug resistant toward both drugs using GeneXpert and phenotypic culture-based drug susceptibility tests. Such discrepancies in the results emphasize the need to develop novel molecular tests that associate with phenotypic non-DNA-based assays to improve the detection of drug-resistant isolates in clinical specimens in future studies.

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.

Quantitative measurement of antibiotic resistance in Mycobacterium tuberculosis reveals genetic determinants of resistance and susceptibility in a target gene approach

The World Health Organization has a goal of universal drug susceptibility testing for patients with tuberculosis; however, molecular diagnostics to date have focused largely on first-line drugs and predicting binary susceptibilities. We used a multivariable linear mixed model alongside whole genome sequencing and a quantitative microtiter plate assay to relate genomic mutations to minimum inhibitory concentration in 15,211 Mycobacterium tuberculosis patient isolates from 23 countries across five continents. This identified 492 unique MIC-elevating variants across thirteen drugs, as well as 91 mutations likely linked to hypersensitivity. Our results advance genetics-based diagnostics for tuberculosis and serve as a curated training/testing dataset for development of drug resistance prediction algorithms.

Resistance patterns and transmission of mono- and polyresistant TB: clinical impact of WGS

Objectives

Rapidly diagnosing drug-resistant TB is crucial for improving treatment and transmission control. WGS is becoming increasingly accessible and has added value to the diagnosis and treatment of TB. The aim of the study was to perform WGS to determine the rate of false-positive results of phenotypic drug susceptibility testing (pDST) and characterize the molecular mechanisms of resistance and transmission of mono- and polyresistant Mycobacterium (M.) tuberculosis.

Methods

WGS was performed on 53 monoresistant and 25 polyresistant M. tuberculosis isolates characterized by pDST. Sequencing data were bioinformatically processed to infer mutations encoding resistance and determine the origin of resistance and phylogenetic relationship between isolates studied.

Results

The data showed the variable sensitivity and specificity of WGS in comparison with pDST as the gold standard: isoniazid 92.7% and 92.3%; streptomycin 41.9% and 100.0%; pyrazinamide 15% and 94.8%; and ethambutol 75.0% and 98.6%, respectively. We found novel mutations encoding resistance to streptomycin (in gidB) and pyrazinamide (in kefB). Most isolates belonged to lineage 4 (80.1%) and the overall clustering rate was 11.5%. We observed lineage-specific gene variations encoding resistance to streptomycin and pyrazinamide.

Conclusions

This study highlights the clinical potential of WGS in ruling out false-positive drug resistance following phenotypic or genetic drug testing, and recommend this technology together with the WHO catalogue in designing an optimal individualized treatment regimen and preventing the development of MDR TB. Our results suggest that resistance is primarily developed through spontaneous mutations or selective pressure.

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.

Multi-approach methods to predict cryptic carbapenem resistance mechanisms in Klebsiella pneumoniae detected in Central Italy

The rapid emergence of carbapenem-resistant Klebsiella pneumoniae (Kp) strains in diverse environmental niches, even outside of the clinical setting, poses a challenge for the detection and the real-time monitoring of novel antimicrobial resistance trends using molecular and whole genome sequencing-based methods. The aim of our study was to understand cryptic resistance determinants responsible for the phenotypic carbapenem resistance observed in strains circulating in Italy by using a combined approach involving whole genome sequencing (WGS) and genome-wide association study (GWAS). In this study, we collected 303 Kp strains from inside and outside clinical settings between 2018-2022 in the Abruzzo region of Italy. The antimicrobial resistance profile of all isolates was assessed using both phenotypic and bioinformatic methods. We identified 11 strains resistant to carbapenems, which did not carry any known genetic determinants explaining their phenotype. The GWAS results showed that incongruent carbapenem-resistant phenotype was associated specifically with strains with two capsular types, KL13 and KL116 including genes involved in the capsule synthesis, encoding proteins involved in the assembly of the capsule biosynthesis apparatus, capsule-specific sugar synthesis, processing and export, polysaccharide pyruvyl transferase, and lipopolysaccharide biosynthesis protein. These preliminary results confirmed the potential of GWAS in identifying genetic variants present in KL13 and KL116 that could be associated with carbapenem resistance traits in Kp. The implementation of advanced methods, such as GWAS with increased antimicrobial resistance surveillance will potentially improve Kp infection treatment and patient outcomes.

Investigating the composition and recruitment of the mycobacterial ImuA'-ImuB-DnaE2 mutasome

A DNA damage-inducible mutagenic gene cassette has been implicated in the emergence of drug resistance in Mycobacterium tuberculosis during anti-tuberculosis (TB) chemotherapy. However, the molecular composition and operation of the encoded 'mycobacterial mutasome' - minimally comprising DnaE2 polymerase and ImuA' and ImuB accessory proteins - remain elusive. Following exposure of mycobacteria to DNA damaging agents, we observe that DnaE2 and ImuB co-localize with the DNA polymerase III β subunit (β clamp) in distinct intracellular foci. Notably, genetic inactivation of the mutasome in an imuBAAAAGG mutant containing a disrupted β clamp-binding motif abolishes ImuB-β clamp focus formation, a phenotype recapitulated pharmacologically by treating bacilli with griselimycin and in biochemical assays in which this β clamp-binding antibiotic collapses pre-formed ImuB-β clamp complexes. These observations establish the essentiality of the ImuB-β clamp interaction for mutagenic DNA repair in mycobacteria, identifying the mutasome as target for adjunctive therapeutics designed to protect anti-TB drugs against emerging resistance.

Genomic characteristics of Mycobacterium tuberculosis isolates of cutaneous tuberculosis

Objectives

Cutaneous tuberculosis with various manifestations can be divided into several clinical types according to the host's immune status and infective route. However, the etiological factors of this disease remain unclear. The objective of this study is to investigate the pathogens associated with the occurrence and different types of cutaneous tuberculosis.

Methods

58 Mycobacterium tuberculosis strains isolated from cutaneous tuberculosis over the last 20 years were sequenced and analyzed for genomic characteristics including lineage distribution, drug-resistance mutations, and mutations potentially associated with different sites of infection.

Results

The M. tuberculosis strains from four major types of cutaneous tuberculosis and pulmonary tuberculosis shared similar genotypes and genomic composition. The strains isolated from cutaneous tuberculosis had a lower rate of drug resistance. Phylogenic analysis showed cutaneous tuberculosis and pulmonary tuberculosis isolates scattered on the three. Several SNPs in metabolism related genes exhibited a strong correlation with different infection sites.

Conclusions

The different infection sites of TB may barely be affected by large genomic changes in M. tuberculosis isolates, but the significant difference in SNPs of drug resistance gene and metabolism-related genes still deserves more attention.

Evolution and epidemic success of Mycobacterium tuberculosis in eastern China: evidence from a prospective study

BACKGROUND

Lineage distribution of Mycobacterium tuberculosis (Mtb) isolates is strongly associated with geographically distinct human populations, and its transmission can be further impacted by the bacterial genome. However, the epidemic success of Mtb isolates at an individual level was unknown in eastern China. Knowledge regarding the emergence and transmission of Mtb isolates as well as relevant factors may offer a new solution to curb the spread of the disease. Thus, this study aims to reveal the evolution and epidemic success of Mtb isolates in eastern China.

RESULTS

Of initial 1040 isolates, 997 were retained after removing duplicates and those with insufficient sequencing depth. Of the final samples, 733 (73.52%) were from Zhejiang Province, and 264 (26.48%) were from Shanghai City. Lineage 2 and lineage 4 accounted for 80.44% and 19.56%, with common ancestors dating around 7017 years ago and 6882 years ago, respectively. Sub-lineage L2.2 (80.34%) contributed the majority of total isolates, followed by L4.4 (8.93%) and L4.5 (8.43%). Additionally, 51 (5.12%) isolates were identified to be multidrug-resistant (MDR), of which 21 (29.17%) were pre-extensively drug-resistant (pre-XDR). One clade harboring katG S315T mutation may date back to 65 years ago and subsequently acquired mutations conferring resistance to another five antibiotic drugs. The prevalence of compensatory mutation was the highest in pre-XDR isolates (76.19%), followed by MDR isolates (47.06%) and other drug-resistant isolates (20.60%). Time-scaled haplotypic density analyses suggested comparable success indices between lineage 2 and lineage 4 (P = 0.306), and drug resistance did not significantly promote the transmission of Mtb isolates (P = 0.340). But for pre-XDR isolates, we found a higher success index in those with compensatory mutations (P = 0.025). Mutations under positive selection were found in genes associated with resistance to second-line injectables (whiB6) and drug tolerance (prpR) in both lineage 2 and lineage 4.

CONCLUSIONS

Our study demonstrates the population expansion of lineage 2 and lineage 4 in eastern China, with comparable transmission capacity, while accumulation of resistance mutations does not necessarily facilitate the success of Mtb isolates. Compensatory mutations usually accompany drug resistance and significantly contribute to the epidemiological transmission of pre-XDR strains. Prospective molecular surveillance is required to further monitor the emergence and spread of pre-XDR/XDR strains in eastern China.

Whole-genome sequencing and transcriptome-characterized in vitro evolution of aminoglycoside resistance in Mycobacterium tuberculosis

Antibiotic resistance of Mycobacterium tuberculosis (Mtb) is a major public health concern worldwide. Therefore, it is of great significance to characterize the mutational pathways by which susceptible Mtb evolves into drug resistance. In this study, we used laboratory evolution to explore the mutational pathways of aminoglycoside resistance. The level of resistance in amikacin inducing Mtb was also associated with changes in susceptibility to other anti-tuberculosis drugs such as isoniazid, levofloxacin and capreomycin. Whole-genome sequencing (WGS) revealed that the induced resistant Mtb strains had accumulated diverse mutations. We found that rrs A1401G was the predominant mutation in aminoglycoside-resistant clinical Mtb isolates from Guangdong. In addition, this study provided global insight into the characteristics of the transcriptome in four representative induced strains and revealed that rrs mutated and unmutated aminoglycoside-resistant Mtb strains have different transcriptional profiles. WGS analysis and transcriptional profiling of Mtb strains during evolution revealed that Mtb strains harbouring rrs A1401G have an evolutionary advantage over other drug-resistant strains under the pressure of aminoglycosides because of their ultra-high resistance level and low physiological impact on the strain. The results of this study should advance our understanding of aminoglycoside resistance mechanisms.

Evaluation of Nanopore sequencing for Mycobacterium tuberculosis drug susceptibility testing and outbreak investigation: a genomic analysis

BACKGROUND

Mycobacterium tuberculosis whole-genome sequencing (WGS) has been widely used for genotypic drug susceptibility testing (DST) and outbreak investigation. For both applications, Illumina technology is used by most public health laboratories; however, Nanopore technology developed by Oxford Nanopore Technologies has not been thoroughly evaluated. The aim of this study was to determine whether Nanopore sequencing data can provide equivalent information to Illumina for transmission clustering and genotypic DST for M tuberculosis.

METHODS

In this genomic analysis, we analysed 151 M tuberculosis isolates from Madagascar, South Africa, and England, which were collected between 2011 and 2018, using phenotypic DST and matched Illumina and Nanopore data. Illumina sequencing was done with the MiSeq, HiSeq 2500, or NextSeq500 platforms and Nanopore sequencing was done on the MinION or GridION platforms. Using highly reliable PacBio sequencing assemblies and pairwise distance correlation between Nanopore and Illumina data, we optimise Nanopore variant filters for detecting single-nucleotide polymorphisms (SNPs; using BCFtools software). We then used those SNPs to compare transmission clusters identified by Nanopore with the currently used UK Health Security Agency Illumina pipeline (COMPASS). We compared Illumina and Nanopore WGS-based DST predictions using the Mykrobe software and mutation catalogue.

FINDINGS

The Nanopore BCFtools pipeline identified SNPs with a median precision of 99·3% (IQR 99·1-99·6) and recall of 90·2% (88·1-94·2) compared with a precision of 99·6% (99·4-99·7) and recall of 91·9% (87·6-98·6) using the Illumina COMPASS pipeline. Using a threshold of 12 SNPs for putative transmission clusters, Illumina identified 98 isolates as unrelated and 53 as belonging to 19 distinct clusters (size range 2-7). Nanopore reproduced 15 out of 19 clusters perfectly; two clusters were merged into one cluster, one cluster had a single sample missing, and one cluster had an additional sample adjoined. Illumina-based clusters were also closely replicated using a five SNP threshold and clustering accuracy was maintained using mixed Illumina and Nanopore datasets. Genotyping resistance variants with Nanopore was highly concordant with Illumina, having zero discordant SNPs across more than 3000 SNPs and four insertions or deletions (indels), across 60 000 indels.

INTERPRETATION

Illumina and Nanopore technologies can be used independently or together by public health laboratories performing M tuberculosis genotypic DST and outbreak investigations. As a result, clinical and public health institutions making decisions on which sequencing technology to adopt for tuberculosis can base the choice on cost (which varies by country), batching, and turnaround time.

FUNDING

Academy for Medical Sciences, Oxford Wellcome Institutional Strategic Support Fund, and the Swiss South Africa Joint Research Award (Swiss National Science Foundation and South African National Research Foundation).

Diagnosis and biomarkers for ocular tuberculosis: From the present into the future

Tuberculosis is an airborne disease caused by Mycobacterium tuberculosis (Mtb) and can manifest both pulmonary and extrapulmonary disease, including ocular tuberculosis (OTB). Accurate diagnosis and swift optimal treatment initiation for OTB is faced by many challenges combined with the lack of standardized treatment regimens this results in uncertain OTB outcomes. The purpose of this study is to summarize existing diagnostic approaches and recently discovered biomarkers that may contribute to establishing OTB diagnosis, choice of anti-tubercular therapy (ATT) regimen, and treatment monitoring. The keywords ocular tuberculosis, tuberculosis, Mycobacterium, biomarkers, molecular diagnosis, multi-omics, proteomics, genomics, transcriptomics, metabolomics, T-lymphocytes profiling were searched on PubMed and MEDLINE databases. Articles and books published with at least one of the keywords were included and screened for relevance. There was no time limit for study inclusion. More emphasis was placed on recent publications that contributed new information about the pathogenesis, diagnosis, or treatment of OTB. We excluded abstracts and articles that were not written in the English language. References cited within the identified articles were used to further supplement the search. We found 10 studies evaluating the sensitivity and specificity of interferon-gamma release assay (IGRA), and 6 studies evaluating that of tuberculin skin test (TST) in OTB patients. IGRA (Sp = 71-100%, Se = 36-100%) achieves overall better sensitivity and specificity than TST (Sp = 51.1-85.7%; Se = 70.9-98.5%). For nuclear acid amplification tests (NAAT), we found 7 studies on uniplex polymerase chain reaction (PCR) with different Mtb targets, 7 studies on DNA-based multiplex PCR, 1 study on mRNA-based multiplex PCR, 4 studies on loop-mediated isothermal amplification (LAMP) assay with different Mtb targets, 3 studies on GeneXpert assay, 1 study on GeneXpert Ultra assay and 1 study for MTBDRplus assay for OTB. Specificity is overall improved but sensitivity is highly variable for NAATs (excluding uniplex PCR, Sp = 50-100%; Se = 10.5-98%) as compared to IGRA. We also found 3 transcriptomic studies, 6 proteomic studies, 2 studies on stimulation assays, 1 study on intraocular protein analysis and 1 study on T-lymphocyte profiling in OTB patients. All except 1 study evaluated novel, previously undiscovered biomarkers. Only 1 study has been externally validated by a large independent cohort. Future theranostic marker discovery by a multi-omics approach is essential to deepen pathophysiological understanding of OTB. Combined these might result in swift, optimal and personalized treatment regimens to modulate the heterogeneous mechanisms of OTB. Eventually, these studies could improve the current cumbersome diagnosis and management of OTB.

Identifying Candidate Genes Associated with Sporadic Amyotrophic Lateral Sclerosis via Integrative Analysis of Transcriptome-Wide Association Study and Messenger RNA Expression Profile

Amyotrophic lateral sclerosis, a fatal neurodegeneration disease affecting motor neurons in the brain and spinal cord, is difficult to diagnose and treat. The objective of this study is to identify novel candidate genes related to ALS. Transcriptome-wide association study of ALS was conducted by integrating the genome-wide association study summary data (including 1234 ALS patients and 2850 controls) and pre-computed gene expression weights of different tissues. The ALS-associated genes identified by TWAS were further compared with the differentially expressed genes detected by the mRNA expression profiles of the sporadic ALS. Functional enrichment and annotation analysis of identified genes were performed by an R package and the functional mapping and annotation software. TWAS identified 761 significant genes (P_TWAS < 0.05), 627 Gene ontology terms, and 8 Kyoto Encyclopedia of Genes and Genomes pathways for ALS, such as C9orf72, with three expression quantitative trait loci were found significantly: rs2453554 (P_{TWAS CBRS} = 4.68 × 10^-10, P_{TWAS CBRS} = 2.54 × 10^-9), rs10967976 (P_{TWAS CBRS} = 7.85 × 10^-10, P_{TWAS CBRS} = 8.91 × 10^-9, P_{TWAS CBRS} = 1.49 × 10^-7, P_{TWAS CBRS} = 5.59 × 10^-7), rs3849946 (P_{TWAS CBRS} = 7.69 × 10^-4, P_{TWAS YBL} = 4.02 × 10^-2), Mitochondrion (P_adj = 4.22 × 10^-16), and Cell cycle (P_adj = 2.04 × 10^-3). Moreover, 107 common genes, 4 KEGG pathways and 41 GO terms were detected by integrating mRNA expression profiles of sALS, such as CPVL (FC = 2.06, P_mRNA = 6.99 × 10^-6, P_{TWAS CBR} = 2.88 × 10^-2, P_{TWAS CBR} = 4.37 × 10^-2), Pyrimidine Metabolism (P_adj = 2.43 × 10^-2), and Cell Activation (P_adj = 5.54 × 10^-3). Multiple candidate genes and pathways were detected for ALS. Our findings may provide novel clues for understanding the genetic mechanism of ALS.

Virotyping and genetic antimicrobial susceptibility testing of porcine ETEC/STEC strains and associated plasmid types

Introduction

Enterotoxigenic Escherichia coli (ETEC) infections are the most common cause of secretory diarrhea in suckling and post-weaning piglets. For the latter, Shiga toxin-producing Escherichia coli (STEC) also cause edema disease. This pathogen leads to significant economic losses. ETEC/STEC strains can be distinguished from general E. coli by the presence of different host colonization factors (e.g., F4 and F18 fimbriae) and various toxins (e.g., LT, Stx2e, STa, STb, EAST-1). Increased resistance against a wide variety of antimicrobial drugs, such as paromomycin, trimethoprim, and tetracyclines, has been observed. Nowadays, diagnosing an ETEC/STEC infection requires culture-dependent antimicrobial susceptibility testing (AST) and multiplex PCRs, which are costly and time-consuming.

Methods

Here, nanopore sequencing was used on 94 field isolates to assess the predictive power, using the meta R package to determine sensitivity and specificity and associated credibility intervals of genotypes associated with virulence and AMR.

Results

Genetic markers associated with resistance for amoxicillin (plasmid-encoded TEM genes), cephalosporins (ampC promoter mutations), colistin (mcr genes), aminoglycosides (aac(3) and aph(3) genes), florfenicol (floR), tetracyclines (tet genes), and trimethoprim-sulfa (dfrA genes) could explain most acquired resistance phenotypes. Most of the genes were plasmid-encoded, of which some collocated on a multi-resistance plasmid (12 genes against 4 antimicrobial classes). For fluoroquinolones, AMR was addressed by point mutations within the ParC and GyrA proteins and the qnrS1 gene. In addition, long-read data allowed to study the genetic landscape of virulence- and AMR-carrying plasmids, highlighting a complex interplay of multi-replicon plasmids with varying host ranges.

Conclusion

Our results showed promising sensitivity and specificity for the detection of all common virulence factors and most resistance genotypes. The use of the identified genetic hallmarks will contribute to the simultaneous identification, pathotyping, and genetic AST within a single diagnostic test. This will revolutionize future quicker and more cost-efficient (meta)genomics-driven diagnostics in veterinary medicine and contribute to epidemiological studies, monitoring, tailored vaccination, and management.

Prophage-encoded immune evasion factors are critical for Staphylococcus aureus host infection, switching, and adaptation

Staphylococcus aureus is a multi-host pathogen that causes infections in animals and humans globally. The specific genetic loci-and the extent to which they drive cross-species switching, transmissibility, and adaptation-are not well understood. Here, we conducted a population genomic study of 437 S. aureus isolates to identify bacterial genetic variation that determines infection of human and animal hosts through a genome-wide association study (GWAS) using linear mixed models. We found genetic variants tagging φSa3 prophage-encoded immune evasion genes associated with human hosts, which contributed ~99.9% of the overall heritability (~88%), highlighting their key role in S. aureus human infection. Furthermore, GWAS of pairs of phylogenetically matched human and animal isolates confirmed and uncovered additional loci not implicated in GWAS of unmatched isolates. Our findings reveal the loci that are critical for S. aureus host transmissibility, infection, switching, and adaptation and how their spread alters the specificity of host-adapted clones.

Genome-wide association study of Klebsiella pneumoniae identifies variations linked to carbapenems resistance

Klebsiella pneumoniae (KP) is one of the microorganisms that can acquire carbapenem-resistance (CR), and few antimicrobial therapy options exist for infections caused by Carbapenem-Resistant KP (CRKP). In recent years, with the increase of carbapenem resistance rates, treating CRKP has become a serious public health threat in clinical practice. We have collected 2,035 clinical KP isolates from a tertiary hospital in China. Whole genome sequencing data coupled with their binary antimicrobial susceptibility testing data were obtained to conduct the genome-wide association study using a bayesian-based method, including single nucleotide polymorphisms (SNPs) and genes. We identified 28 and 37 potential maker genes associated with imipenem and meropenem resistance, respectively. Among which 19 of them were selected in both drugs by genome-wide association study (GWAS), 11 genes among them were simultaneously validated in independent datasets. These genes were likely related to biofilm formation, efflux pump, and DNA repairing. Moreover, we identified 13 significant CR related SNPs in imipenem or meropenem, with one SNP located in the non-coding region and validated in the independent datasets. Our study indicates complex mechanisms of carbapenems resistance and further investigation of CRKP-related factors are warranted to better understand their contributions to carbapenems resistance. These identified biomarkers may provide targets for future drug interventions or treatments.

Unraveling the mechanisms of intrinsic drug resistance in Mycobacterium tuberculosis

Tuberculosis (TB) is among the most difficult infections to treat, requiring several months of multidrug therapy to produce a durable cure. The reasons necessitating long treatment times are complex and multifactorial. However, one major difficulty of treating TB is the resistance of the infecting bacterium, Mycobacterium tuberculosis (Mtb), to many distinct classes of antimicrobials. This review will focus on the major gaps in our understanding of intrinsic drug resistance in Mtb and how functional and chemical-genetics can help close those gaps. A better understanding of intrinsic drug resistance will help lay the foundation for strategies to disarm and circumvent these mechanisms to develop more potent antitubercular therapies.

Mycobacterium tuberculosis functional genetic diversity, altered drug sensitivity, and precision medicine

In the face of the unrelenting global burden of tuberculosis (TB), antibiotics remain our most effective tools to save lives and control the spread of Mycobacterium tuberculosis (Mtb). However, we confront a dual challenge in our use of antibiotics: simplifying and shortening the TB drug regimen while also limiting the emergence and propagation of antibiotic resistance. This task is now more feasible due to the increasing availability of bacterial genomic data at or near the point of care. These resources create an opportunity to envision how integration of bacterial genetic determinants of antibiotic response into treatment algorithms might transform TB care. Historically, Mtb drug resistance studies focused on mutations in genes encoding antibiotic targets and the resulting increases in the minimal inhibitory concentrations (MICs) above a breakpoint value. But recent progress in elucidating the effects of functional genetic diversity in Mtb has revealed various genetic loci that are associated with drug phenotypes such as low-level MIC increases and tolerance which predict the development of resistance and treatment failure. As a result, we are now poised to advance precision medicine approaches in TB treatment. By incorporating information regarding Mtb genetic characteristics into the development of drug regimens, clinical care which tailors antibiotic treatment to maximize the likelihood of success has come into reach.

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.

WGS-Based Lineage and Antimicrobial Resistance Pattern of Salmonella Typhimurium Isolated during 2000-2017 in Peru

Salmonella Typhimurium is associated with foodborne diseases worldwide, including in Peru, and its emerging antibiotic resistance (AMR) is now a global public health problem. Therefore, country-specific monitoring of the AMR emergence is vital to control this pathogen, and in these aspects, whole genome sequence (WGS)—based approaches are better than gene-based analyses. Here, we performed the antimicrobial susceptibility test for ten widely used antibiotics and WGS-based various analyses of 90 S. Typhimurium isolates (human, animal, and environment) from 14 cities of Peru isolated from 2000 to 2017 to understand the lineage and antimicrobial resistance pattern of this pathogen in Peru. Our results suggest that the Peruvian isolates are of Typhimurium serovar and predominantly belong to sequence type ST19. Genomic diversity analyses indicate an open pan-genome, and at least ten lineages are circulating in Peru. A total of 48.8% and 31.0% of isolates are phenotypically and genotypically resistant to at least one antibiotic, while 12.0% are multi-drug resistant (MDR). Genotype−phenotype correlations for ten tested drugs show >80% accuracy, and >90% specificity. Sensitivity above 90% was only achieved for ciprofloxacin and ceftazidime. Two lineages exhibit the majority of the MDR isolates. A total of 63 different AMR genes are detected, of which 30 are found in 17 different plasmids. Transmissible plasmids such as lncI-gamma/k, IncI1-I(Alpha), Col(pHAD28), IncFIB, IncHI2, and lncI2 that carry AMR genes associated with third-generation antibiotics are also identified. Finally, three new non-synonymous single nucleotide variations (SNVs) for nalidixic acid and eight new SNVs for nitrofurantoin resistance are predicted using genome-wide association studies, comparative genomics, and functional annotation. Our analysis provides for the first time the WGS-based details of the circulating S. Typhimurium lineages and their antimicrobial resistance pattern in Peru.

Transcontinental spread and evolution of Mycobacterium tuberculosis W148 European/Russian clade toward extensively drug resistant tuberculosis

Transmission-driven multi-/extensively drug resistant (M/XDR) tuberculosis (TB) is the largest single contributor to human mortality due to antimicrobial resistance. A few major clades of the Mycobacterium tuberculosis complex belonging to lineage 2, responsible for high prevalence of MDR-TB in Eurasia, show outstanding transnational distributions. Here, we determined factors underlying the emergence and epidemic spread of the W148 clade by genome sequencing and Bayesian demogenetic analyses of 720 isolates from 23 countries. We dated a common ancestor around 1963 and identified two successive epidemic expansions in the late 1980s and late 1990s, coinciding with major socio-economic changes in the post-Soviet Era. These population expansions favored accumulation of resistance mutations to up to 11 anti-TB drugs, with MDR evolving toward additional resistances to fluoroquinolones and second-line injectable drugs within 20 years on average. Timescaled haplotypic density analysis revealed that widespread acquisition of compensatory mutations was associated with transmission success of XDR strains. Virtually all W148 strains harbored a hypervirulence-associated ppe38 gene locus, and incipient recurrent emergence of prpR mutation-mediated drug tolerance was detected. The outstanding genetic arsenal of this geographically widespread M/XDR strain clade represents a “perfect storm” that jeopardizes the successful introduction of new anti-M/XDR-TB antibiotic regimens.

An outbreak of the multidrug-resistant Mycobacterium tuberculosis lineage W148 has spread widely across Russia, Central Asia and Europe. Here, the authors use whole genome sequences of ~700 isolates of this lineage collected over ~20 years to analyze its spread, evolution of drug resistance, and impact of compensatory mutations.

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.

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.

Tuberculosis Phenotypic and Genotypic Drug Susceptibility Testing and Immunodiagnostics: A Review

Tuberculosis (TB), considered an ancient disease, is still killing one person every 21 seconds. Diagnosis of Mycobacterium tuberculosis (M.tb) still has many challenges, especially in low and middle-income countries with high burden disease rates. Over the last two decades, the amount of drug-resistant (DR)-TB cases has been increasing, from mono-resistant (mainly for isoniazid or rifampicin resistance) to extremely drug resistant TB. DR-TB is problematic to diagnose and treat, and thus, needs more resources to manage it. Together with+ TB clinical symptoms, phenotypic and genotypic diagnosis of TB includes a series of tests that can be used on different specimens to determine if a person has TB, as well as if the M.tb strain+ causing the disease is drug susceptible or resistant. Here, we review and discuss advantages and disadvantages of phenotypic vs. genotypic drug susceptibility testing for DR-TB, advances in TB immunodiagnostics, and propose a call to improve deployable and low-cost TB diagnostic tests to control the DR-TB burden, especially in light of the increase of the global burden of bacterial antimicrobial resistance, and the potentially long term impact of the coronavirus disease 2019 (COVID-19) disruption on TB programs.

High clustering rate and genotypic drug-susceptibility screening for the newly recommended anti-tuberculosis drugs among global extensively drug-resistant Mycobacterium tuberculosis isolates

Multidrug-resistant tuberculosis (MDR-TB) and extensively drug-resistant tuberculosis (XDR-TB) make TB difficult to control. Global susceptibility data for six newly recommended anti-TB drugs against M/XDR-TB are still limited. Using publicly available whole-genome sequences, we determined the proportion of 513 phenotypically XDR-TB isolates that carried mutations associated with resistance against these drugs (bedaquiline, clofazimine, linezolid, delamanid, pretomanid and cycloserine). Mutations of Rv0678 and Rv1979c were detected in 69/513 isolates (13.5%) for bedaquiline resistance and 79/513 isolates (15.4%) for clofazimine resistance with additional mmpL5 mutations. Mutations conferring resistance to delamanid were detected in fbiB and ddn genes for 11/513 isolates (2.1%). For pretomanid, a mutation was detected in the ddn gene for 3/513 isolates (0.6%). Nineteen mutations of pykA, cycA, ald, and alr genes, conferring resistance to cycloserine, were found in 153/513 isolates (29.8%). No known mutations associated with linezolid resistance were detected. Cluster analysis showed that 408/513 isolates fell within 99 clusters and that 354 of these isolates were possible primary drug-resistant TB (292 XDR-TB, 57 pre-XDR-TB and 5 MDR-TB). Clonal transmission of primary XDR isolates might contribute significantly to the high prevalence of DR-TB globally.

Loss of RNase J leads to multi-drug tolerance and accumulation of highly structured mRNA fragments in Mycobacterium tuberculosis

Despite the existence of well-characterized, canonical mutations that confer high-level drug resistance to Mycobacterium tuberculosis (Mtb), there is evidence that drug resistance mechanisms are more complex than simple acquisition of such mutations. Recent studies have shown that Mtb can acquire non-canonical resistance-associated mutations that confer survival advantages in the presence of certain drugs, likely acting as stepping-stones for acquisition of high-level resistance. Rv2752c/rnj, encoding RNase J, is disproportionately mutated in drug-resistant clinical Mtb isolates. Here we show that deletion of rnj confers increased tolerance to lethal concentrations of several drugs. RNAseq revealed that RNase J affects expression of a subset of genes enriched for PE/PPE genes and stable RNAs and is key for proper 23S rRNA maturation. Gene expression differences implicated two sRNAs and ppe50-ppe51 as important contributors to the drug tolerance phenotype. In addition, we found that in the absence of RNase J, many short RNA fragments accumulate because they are degraded at slower rates. We show that the accumulated transcript fragments are targets of RNase J and are characterized by strong secondary structure and high G+C content, indicating that RNase J has a rate-limiting role in degradation of highly structured RNAs. Taken together, our results demonstrate that RNase J indirectly affects drug tolerance, as well as reveal the endogenous roles of RNase J in mycobacterial RNA metabolism.

Development of Resistance to Clarithromycin and Amoxicillin-Clavulanic Acid in Lactiplantibacillus plantarum In Vitro Is Followed by Genomic Rearrangements and Evolution of Virulence

Ensuring the safety of the use of probiotics is a top priority. Obviously, in addition to studying the beneficial properties of lactic acid bacteria, considerable attention should be directed to assessing the virulence of microorganisms as well as investigating the possibility of its evolution under conditions of selective pressure. To assess the virulence of probiotics, it is now recommended to analyze the genomes of bacteria in relation to the profiles of the virulome, resistome, and mobilome as well as the analysis of phenotypic resistance and virulence in vitro. However, the corresponding procedure has not yet been standardized, and virulence analysis of strains in vivo using model organisms has not been performed. Our study is devoted to testing the assumption that the development of antibiotic resistance in probiotic bacteria under conditions of selective pressure of antimicrobial drugs may be accompanied by the evolution of virulence. In this regard, special attention is required for the widespread in nature commensals and probiotic bacteria actively used in pharmacology and the food industry. As a result of step-by-step selection from the Lactiplantibacillus plantarum 8p-a3 strain isolated from the "Lactobacterin" probiotic (Biomed, Russia), the L. plantarum 8p-a3-Clr-Amx strain was obtained, showing increased resistance simultaneously to amoxicillin-clavulanic acid and clarithromycin (antibiotics, the combined use of which is widely used for Helicobacter pylori eradication) compared to the parent strain (MIC8p-a3-Clr-Amx of 20 μg/mL and 10 μg/mL, and MIC8p-a3 of 0.5 μg/mL and 0.05 μg/mL, respectively). The results of a comparative analysis of antibiotic-resistant and parental strains indicate that the development of resistance to the corresponding antimicrobial drugs in L. plantarum in vitro is accompanied by the following: (i) significant changes in the genomic profile (point mutations as well as deletions, insertions, duplications, and displacement of DNA sequences) associated in part with the resistome and mobilome; (ii) changes in phenotypic sensitivity to a number of antimicrobial drugs; and (iii) an increase in the level of virulence against Drosophila melanogaster, a model organism for which L. plantarum is considered to be a symbiont. The data obtained by us indicate that the mechanisms of adaptation to antimicrobial drugs in L. plantarum are not limited to those described earlier and determine the need for comprehensive studies of antibiotic resistance scenarios as well as the trajectories of virulence evolution in probiotic bacteria in vivo and in vitro to develop a standardized system for detecting virulent strains of the corresponding microorganisms. IMPORTANCE Ensuring the safety of the use of probiotics is a top priority. We found that increased resistance to popular antimicrobial drugs in Lactiplantibacillus plantarum is accompanied by significant changes in the genomic profile and phenotypic sensitivity to a number of antimicrobial drugs as well as in the level of virulence of this bacterium against Drosophila. The data obtained in our work indicate that the mechanisms of antibiotic resistance in this bacterium are not limited to those described earlier and determine the need for comprehensive studies of the potential for the evolution of virulence in lactic acid bacteria in vivo and in vitro and to develop a reliable control system to detect virulent strains among probiotics.

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.

Distribution of Common and Rare Genetic Markers of Second-Line-Injectable-Drug Resistance in Mycobacterium tuberculosis Revealed by a Genome-Wide Association Study

Point mutations in the rrs gene and the eis promoter are known to confer resistance to the second-line injectable drugs (SLIDs) amikacin (AMK), capreomycin (CAP), and kanamycin (KAN). While mutations in these canonical genes confer the majority of SLID resistance, alternative mechanisms of resistance are not uncommon and threaten effective treatment decisions when using conventional molecular diagnostics. In total, 1,184 clinical Mycobacterium tuberculosis isolates from 7 countries were studied for genomic markers associated with phenotypic resistance. The markers rrs:A1401G and rrs:G1484T were associated with resistance to all three SLIDs, and three known markers in the eis promoter (eis:G-10A, eis:C-12T, and eis:C-14T) were similarly associated with kanamycin resistance (KAN-R). Among 325, 324, and 270 AMK-R, CAP-R, and KAN-R isolates, 274 (84.3%), 250 (77.2%), and 249 (92.3%) harbored canonical mutations, respectively. Thirteen isolates harbored more than one canonical mutation. Canonical mutations did not account for 103 of the phenotypically resistant isolates. A genome-wide association study identified three genes and promoters with mutations that, on aggregate, were associated with unexplained resistance to at least one SLID. Our analysis associated whiB7 5'-untranslated-region mutations with KAN resistance, supporting clinical relevance for this previously demonstrated mechanism of KAN resistance. We also provide evidence for the novel association of CAP resistance with the promoter of the Rv2680-Rv2681 operon, which encodes an exoribonuclease that may influence the binding of CAP to the ribosome. Aggregating mutations by gene can provide additional insight and therefore is recommended for identifying rare mechanisms of resistance when individual mutations carry insufficient statistical power.

Gene evolutionary trajectories in Mycobacterium tuberculosis reveal temporal signs of selection

Genetic differences between different Mycobacterium tuberculosis complex (MTBC) strains determine their ability to transmit within different host populations, their latency times, and their drug resistance profiles. Said differences usually emerge through de novo mutations and are maintained or discarded by the balance of evolutionary forces. Using a dataset of ∼5,000 strains representing global MTBC diversity, we determined the past and present selective forces that have shaped the current variability observed in the pathogen population. We identified regions that have evolved under changing types of selection since the time of the MTBC common ancestor. Our approach highlighted striking differences in the genome regions relevant for host–pathogen interaction and, in particular, suggested an adaptive role for the sensor protein of two-component systems. In addition, we applied our approach to successfully identify potential determinants of resistance to drugs administered as second-line tuberculosis treatments.

The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A genotypic analysis

Background

Molecular diagnostics are considered the most promising route to achieving rapid, universal drug susceptibility testing for Mycobacterium tuberculosiscomplex (MTBC). We aimed to generate a WHO endorsed catalogue of mutations to serve as a global standard for interpreting molecular information for drug resistance prediction.

Methods

A candidate gene approach was used to identify mutations as associated with resistance, or consistent with susceptibility, for 13 WHO endorsed anti-tuberculosis drugs. 38,215 MTBC isolates with paired whole-genome sequencing and phenotypic drug susceptibility testing data were amassed from 45 countries. For each mutation, a contingency table of binary phenotypes and presence or absence of the mutation computed positive predictive value, and Fisher's exact tests generated odds ratios and Benjamini-Hochberg corrected p-values. Mutations were graded as Associated with Resistance if present in at least 5 isolates, if the odds ratio was >1 with a statistically significant corrected p-value, and if the lower bound of the 95% confidence interval on the positive predictive value for phenotypic resistance was >25%. A series of expert rules were applied for final confidence grading of each mutation.

Findings

15,667 associations were computed for 13,211 unique mutations linked to one or more drugs. 1,149/15,667 (7·3%) mutations were classified as associated with phenotypic resistance and 107/15,667 (0·7%) were deemed consistent with susceptibility. For rifampicin, isoniazid, ethambutol, fluoroquinolones, and streptomycin, the mutations' pooled sensitivity was >80%. Specificity was over 95% for all drugs except ethionamide (91·4%), moxifloxacin (91·6%) and ethambutol (93·3%). Only two resistance mutations were classified for bedaquiline, delamanid, clofazimine, and linezolid as prevalence of phenotypic resistance was low for these drugs.

Interpretation

This first WHO endorsed catalogue of molecular targets for MTBC drug susceptibility testing provides a global standard for resistance interpretation. Its existence should encourage the implementation of molecular diagnostics by National Tuberculosis Programmes.

Funding

UNITAID, Wellcome, MRC, BMGF.

Drug resistance prediction and resistance genes identification in Mycobacterium tuberculosis based on a hierarchical attentive neural network utilizing genome-wide variants

Prediction of antimicrobial resistance based on whole-genome sequencing data has attracted greater attention due to its rapidity and convenience. Numerous machine learning-based studies have used genetic variants to predict drug resistance in Mycobacterium tuberculosis (MTB), assuming that variants are homogeneous, and most of these studies, however, have ignored the essential correlation between variants and corresponding genes when encoding variants, and used a limited number of variants as prediction input. In this study, taking advantage of genome-wide variants for drug-resistance prediction and inspired by natural language processing, we summarize drug resistance prediction into document classification, in which variants are considered as words, mutated genes in an isolate as sentences, and an isolate as a document. We propose a novel hierarchical attentive neural network model (HANN) that helps discover drug resistance-related genes and variants and acquire more interpretable biological results. It captures the interaction among variants in a mutated gene as well as among mutated genes in an isolate. Our results show that for the four first-line drugs of isoniazid (INH), rifampicin (RIF), ethambutol (EMB) and pyrazinamide (PZA), the HANN achieves the optimal area under the ROC curve of 97.90, 99.05, 96.44 and 95.14% and the optimal sensitivity of 94.63, 96.31, 92.56 and 87.05%, respectively. In addition, without any domain knowledge, the model identifies drug resistance-related genes and variants consistent with those confirmed by previous studies, and more importantly, it discovers one more potential drug-resistance-related gene.

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.

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world's population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. "Multi-omics" strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of "omics" approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

Application of Amplicon-Based Targeted NGS Technology for Diagnosis of Drug-Resistant Tuberculosis Using FFPE Specimens

Next-generation sequencing (NGS) enables rapid identification of common and rare drug-resistant genetic variations from tuberculosis (TB) patients' sputum samples and MTB isolates. However, whether this technology is effective for formalin-fixed and paraffin-embedded (FFPE) tissues remains unclear. An amplicon-based targeted NGS sequencing panel was developed to predict susceptibility to 9 antituberculosis drugs, including 3 first-line drugs, by directly detecting FFPE tissues. A total of 178 tissue samples from TB patients who underwent phenotypic drug susceptibility test were retrospectively tested from January 2017 to October 2019 in the Department of Pathology, Beijing Chest Hospital, China. Phenotypic drug susceptibility test results were used as the reference standard. We identified 22 high-quality mutations from 178 FFPE tissue samples, including 15 high+moderate+minimal confidence-level mutations associated with drug resistance (rpoB D435V, S450F/L; KatG S315T; inhA-fabG promoter c-15t; embB G406S, M306V; rpsL K43R, K88R, rrs a1401g, a514c; gyrA D94G/Y/A, A90V), 6 mutations not associated with resistance (rpoB D435Y, H445S, L430P, L452P; embB G406A/D), and one mutation site embB M306I defined as indeterminate. Compared to the phenotypic method, sensitivities (95% CI) for rifampicin, isoniazid, and ethambutol were 96% (79.65-99.90%), 93.55% (78.58-99.21%), and 71.43% (35.24-92.44%), respectively; while for second-line drugs, it varied from 23.53% (9.05-47.77%) for capreomycin to 86.84% (72.20-94.72%) for streptomycin. Specificities for all drugs were satisfactory (>94.51%). Therefore, important pathological FFPE tissue samples, despite partially degraded DNA, can be used as essential specimens for molecular diagnosis of drug resistant TB by amplicon-based targeted NGS technology. IMPORTANCE Amplicon-based targeted NGS technology focuses on a set of gene mutations of known or suspected associations with drug susceptibility in Mycobacterium tuberculosis (MTB). This method offers many benefits, such as low sequencing cost, easy customization, high throughput, shorter testing time and not culture dependent. Formalin-fixed and paraffin-embedded (FFPE) tissues are important pathological specimen in diagnosing tuberculous disease because they are noninfectious and provide excellent preservation of tissue morphology with low storage cost. However, the performance of amplicon-based targeted NGS method on FFPE samples has not been reported yet. Therefore, we evaluated the performance of this method using FFPE samples collected from January 2017 to October 2019 in the Department of Pathology, Beijing Chest Hospital, China. We demonstrate that the amplicon-based targeted NGS method performs excellent on FFPE samples, and it can be applied to pathological diagnosis of drug resistant tuberculosis.

Genome-wide association, prediction and heritability in bacteria with application to Streptococcus pneumoniae

Whole-genome sequencing has facilitated genome-wide analyses of association, prediction and heritability in many organisms. However, such analyses in bacteria are still in their infancy, being limited by difficulties including genome plasticity and strong population structure. Here we propose a suite of methods including linear mixed models, elastic net and LD-score regression, adapted to bacterial traits using innovations such as frequency-based allele coding, both insertion/deletion and nucleotide testing and heritability partitioning. We compare and validate our methods against the current state-of-art using simulations, and analyse three phenotypes of the major human pathogen Streptococcus pneumoniae, including the first analyses of minimum inhibitory concentrations (MIC) for penicillin and ceftriaxone. We show that the MIC traits are highly heritable with high prediction accuracy, explained by many genetic associations under good population structure control. In ceftriaxone MIC, this is surprising because none of the isolates are resistant as per the inhibition zone criteria. We estimate that half of the heritability of penicillin MIC is explained by a known drug-resistance region, which also contributes a quarter of the ceftriaxone MIC heritability. For the within-host carriage duration phenotype, no associations were observed, but the moderate heritability and prediction accuracy indicate a moderately polygenic trait.

Molecular Determinants of Ethionamide Resistance in Clinical Isolates of Mycobacterium tuberculosis

Background: Ethionamide and prothionamide are now included in group C of the WHO recommended drugs for the treatment of tuberculosis resistant to rifampicin and multidrug-resistant tuberculosis. The clinical relevance of ethionamide and prothionamide has increased with the wide spread of resistant tuberculosis. Methods: We retrospectively analyzed 349 clinical isolates obtained between 2016 and 2020. The susceptibility to ethionamide was tested using both the Bactec^TM MGIT^TM 960 system and the Sensititre^TM MYCOTB plate. Results: The MIC of ethionamide increases with the total resistance of the isolates in a row from susceptible to XDR strains. A significant part of the isolates have a MIC below the breakpoint: 25%, 36%, and 50% for XDR, pre-XDR, and MDR strains. Sensitivity and specificity of detection of mutations were 96% and 86% using MGIT resistance as a reference. Conclusions: Phenotypic methods for testing ethionamide are imperfectly correlated, and the isolates with MIC of 5 mg/L have the intermediate resistance. A significant proportion of resistant TB cases are susceptible and eligible for ethionamide treatment. Resistance could be explained using only analysis of loci ethA, P_fabG1, and inhA for most isolates in the Moscow region. The promoter mutation P_fabG1 c(-15)t predicts resistance to ethionamide with high specificity but low sensitivity.