Identification of bacterial determinants of tuberculosis infection and treatment outcomes: a phenogenomic analysis of clinical strains.

BACKGROUND: Bacterial diversity could contribute to the diversity of tuberculosis infection and treatment outcomes observed clinically, but the biological basis of this association is poorly understood. The aim of this study was to identify associations between phenogenomic variation in Mycobacterium tuberculosis and tuberculosis clinical features. METHODS: We developed a high-throughput platform to define phenotype-genotype relationships in M tuberculosis clinical isolates, which we tested on a set of 158 drug-sensitive M tuberculosis strains sampled from a large tuberculosis clinical study in Ho Chi Minh City, Viet Nam. We tagged the strains with unique genetic barcodes in multiplicate, allowing us to pool the strains for in-vitro competitive fitness assays across 16 host-relevant antibiotic and metabolic conditions. Relative fitness was quantified by deep sequencing, enumerating output barcode read counts relative to input normalised values. We performed a genome-wide association study to identify phylogenetically linked and monogenic mutations associated with the in-vitro fitness phenotypes. These genetic determinants were further associated with relevant clinical outcomes (cavitary disease and treatment failure) by calculating odds ratios (ORs) with binomial logistic regressions. We also assessed the population-level transmission of strains associated with cavitary disease and treatment failure using terminal branch length analysis of the phylogenetic data. FINDINGS: M tuberculosis clinical strains had diverse growth characteristics in host-like metabolic and drug conditions. These fitness phenotypes were highly heritable, and we identified monogenic and phylogenetically linked variants associated with the fitness phenotypes. These data enabled us to define two genetic features that were associated with clinical outcomes. First, mutations in Rv1339, a phosphodiesterase, which were associated with slow growth in glycerol, were further associated with treatment failure (OR 5·34, 95% CI 1·21-23·58, p=0·027). Second, we identified a phenotypically distinct slow-growing subclade of lineage 1 strains (L1.1.1.1) that was associated with cavitary disease (OR 2·49, 1·11-5·59, p=0·027) and treatment failure (OR 4·76, 1·53-14·78, p=0·0069), and which had shorter terminal branch lengths on the phylogenetic tree, suggesting increased transmission. INTERPRETATION: Slow growth under various antibiotic and metabolic conditions served as in-vitro intermediate phenotypes underlying the association between M tuberculosis monogenic and phylogenetically linked mutations and outcomes such as cavitary disease, treatment failure, and transmission potential. These data suggest that M tuberculosis growth regulation is an adaptive advantage for bacterial success in human populations, at least in some circumstances. These data further suggest markers for the underlying bacterial processes that contribute to these clinical outcomes. FUNDING: National Health and Medical Research Council/A∗STAR, National Institutes of Allergy and Infectious Diseases, National Institute of Child Health and Human Development, and the Wellcome Trust Fellowship in Public Health and Tropical Medicine.

Randomized Placebo-Controlled, Biomarker-Stratified Phase Ib Microbiome Modulation in Melanoma: Impact of Antibiotic Preconditioning on Microbiome and Immunity.

Gut-microbiota modulation shows promise in improving immune-checkpoint blockade (ICB) response; however, precision biomarker-driven, placebo-controlled trials are lacking. We performed a multicenter, randomized placebo-controlled, biomarker-stratified phase I trial in patients with ICB-naïve metastatic melanoma using SER-401, an orally delivered Firmicutes-enriched spore formulation. Fecal microbiota signatures were characterized at baseline; patients were stratified by high versus low Ruminococcaceae abundance prior to randomization to the SER-401 arm (oral vancomycin-preconditioning/SER-401 alone/nivolumab + SER-401), versus the placebo arm [placebo antibiotic/placebo microbiome modulation (PMM)/nivolumab + PMM (NCT03817125)]. Analysis of 14 accrued patients demonstrated that treatment with SER-401 + nivolumab was safe, with an objective response rate of 25% in the SER-401 arm and 67% in the placebo arm (though the study was under-powered related to poor accrual during the COVID-19 pandemic). Translational analyses demonstrated that vancomycin preconditioning was associated with the disruption of the gut microbiota and impaired immunity, with incomplete recovery at ICB administration (particularly in patients with high baseline Ruminococcaceae). These results have important implications for future microbiome modulation trials. SIGNIFICANCE: This first-of-its-kind, placebo-controlled, randomized biomarker-driven microbiome modulation trial demonstrated that vancomycin + SER-401 and anti-PD-1 are safe in melanoma patients. Although limited by poor accrual during the pandemic, important insights were gained via translational analyses, suggesting that antibiotic preconditioning and interventional drug dosing regimens should be carefully considered when designing such trials.

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

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

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

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

High-throughput phenogenotyping of Mycobacteria tuberculosis clinical strains reveals bacterial determinants of treatment outcomes.

Background: Combatting the tuberculosis (TB) epidemic caused by Mycobacterium tuberculosis ( Mtb ) necessitates a better understanding of the factors contributing to patient clinical outcomes and transmission. While host and environmental factors have been evaluated, the impact of Mtb genetic background and phenotypic diversity is underexplored. Previous work has made associations between Mtb genetic lineages and some clinical and epidemiological features, but the bacterial traits underlying these connections are largely unknown. Methods: We developed a high-throughput functional genomics platform for defining genotype-phenotype relationships across a panel of Mtb clinical isolates. These phenotypic fitness profiles function as intermediate traits which can be linked to Mtb genetic variants and associated with clinical and epidemiological outcomes. We applied this approach to a collection of 158 Mtb strains from a study of Mtb transmission in Ho Chi Minh City, Vietnam. Mtb strains were genetically tagged in multiplicate, which allowed us to pool the strains and assess in vitro competitive fitness using deep sequencing across a set of 14 host-relevant antibiotic and metabolic conditions. Phylogenetic and monogenic associations with these intermediate traits were identified and then associated with clinical outcomes. Findings: Mtb clinical strains have a broad range of growth and drug response dynamics that can be clustered by their phylogenetic relationships. We identified novel monogenic associations with Mtb fitness in various metabolic and antibiotic conditions. Among these, we find that mutations in Rv1339 , a phosphodiesterase, which were identified through their association with slow growth in glycerol, are further associated with treatment failure. We also identify a previously uncharacterized subclade of Lineage 1 strains (L1.1.1.1) that is phenotypically distinguished by slow growth under most antibiotic and metabolic stress conditions in vitro . This clade is associated with cavitary disease, treatment failure, and demonstrates increased transmission potential. Interpretation: High-throughput phenogenotyping of Mtb clinical strains enabled bacterial intermediate trait identification that can provide a mechanistic link between Mtb genetic variation and patient clinical outcomes. Mtb strains associated with cavitary disease, treatment failure, and transmission potential display intermediate phenotypes distinguished by slow growth under various antibiotic and metabolic conditions. These data suggest that Mtb growth regulation is an adaptive advantage for host bacterial success in human populations, in at least some circumstances. These data further suggest markers for the underlying bacterial processes that govern these clinical outcomes. Funding: National Institutes of Allergy and Infectious Diseases: P01 AI132130 (SS, SMF); P01 AI143575 (XW, SMF); U19 AI142793 (QL, SMF); 5T32AI132120-03 (SS); 5T32AI132120-04 (SS); 5T32AI049928-17 (SS) Wellcome Trust Fellowship in Public Health and Tropical Medicine: 097124/Z/11/Z (NTTT) National Health and Medical Research Council (NHMRC)/A*STAR joint call: APP1056689 (SJD) The funding sources had no involvement in study methodology, data collection, analysis, and interpretation nor in the writing or submission of the manuscript. Research in context: Evidence before this study: We used different combinations of the words mycobacterium tuberculosis, tuberculosis, clinical strains, intermediate phenotypes, genetic barcoding, phenogenomics, cavitary disease, treatment failure, and transmission to search the PubMed database for all studies published up until January 20 th , 2022. We only considered English language publications, which biases our search. Previous work linking Mtb determinants to clinical or epidemiological data has made associations between bacterial lineage, or less frequently, genetic polymorphisms to in vitro or in vivo models of pathogenesis, transmission, and clinical outcomes such as cavitary disease, treatment failure, delayed culture conversion, and severity. Many of these studies focus on the global pandemic Lineage 2 and Lineage 4 Mtb strains due in part to a deletion in a polyketide synthase implicated in host-pathogen interactions. There are a number of Mtb GWAS studies that have led to novel genetic determinants of in vitro drug resistance and tolerance. Previous Mtb GWAS analyses with clinical outcomes did not experimentally test any predicted phenotypes of the clinical strains. Published laboratory-based studies of Mtb clinical strains involve relatively small numbers of strains, do not identify the genetic basis of relevant phenotypes, or link findings to the corresponding clinical outcomes. There are two recent studies of other pathogens that describe phenogenomic analyses. One study of 331 M. abscessus clinical strains performed one-by-one phenotyping to identify bacterial features associated with clearance of infection and another details a competition experiment utilizing three barcoded Plasmodium falciparum clinical isolates to assay antimalarial fitness and resistance. Added value of this study: We developed a functional genomics platform to perform high-throughput phenotyping of Mtb clinical strains. We then used these phenotypes as intermediate traits to identify novel bacterial genetic features associated with clinical outcomes. We leveraged this platform with a sample of 158 Mtb clinical strains from a cross sectional study of Mtb transmission in Ho Chi Minh City, Vietnam. To enable high-throughput phenotyping of large numbers of Mtb clinical isolates, we applied a DNA barcoding approach that has not been previously utilized for the high-throughput analysis of Mtb clinical strains. This approach allowed us to perform pooled competitive fitness assays, tracking strain fitness using deep sequencing. We measured the replicative fitness of the clinical strains in multiplicate under 14 metabolic and antibiotic stress condition. To our knowledge, this is the largest phenotypic screen of Mtb clinical isolates to date. We performed bacterial GWAS to delineate the Mtb genetic variants associated with each fitness phenotype, identifying monogenic associations with several conditions. We then defined Mtb phenotypic and genetic features associated with clinical outcomes. We find that a subclade of Mtb strains, defined by variants largely involved in fatty acid metabolic pathways, share a universal slow growth phenotype that is associated with cavitary disease, treatment failure and increased transmission potential in Vietnam. We also find that mutations in Rv1339 , a poorly characterized phosphodiesterase, also associate with slow growth in vitro and with treatment failure in patients. Implications of all the available evidence: Phenogenomic profiling demonstrates that Mtb strains exhibit distinct growth characteristics under metabolic and antibiotic stress conditions. These fitness profiles can serve as intermediate traits for GWAS and association with clinical outcomes. Intermediate phenotyping allows us to examine potential processes by which bacterial strain differences contribute to clinical outcomes. Our study identifies clinical strains with slow growth phenotypes under in vitro models of antibiotic and host-like metabolic conditions that are associated with adverse clinical outcomes. It is possible that the bacterial intermediate phenotypes we identified are directly related to the mechanisms of these outcomes, or they may serve as markers for the causal yet unidentified bacterial determinants. Via the intermediate phenotyping, we also discovered a surprising diversity in Mtb responses to the new anti-mycobacterial drugs that target central metabolic processes, which will be important in considering roll-out of these new agents. Our study and others that have identified Mtb determinants of TB clinical and epidemiological phenotypes should inform efforts to improve diagnostics and drug regimen design.

Tuberculosis treatment failure associated with evolution of antibiotic resilience.

The widespread use of antibiotics has placed bacterial pathogens under intense pressure to evolve new survival mechanisms. Genomic analysis of 51,229 Mycobacterium tuberculosis (Mtb)clinical isolates has identified an essential transcriptional regulator, Rv1830, herein called resR for resilience regulator, as a frequent target of positive (adaptive) selection. resR mutants do not show canonical drug resistance or drug tolerance but instead shorten the post-antibiotic effect, meaning that they enable Mtb to resume growth after drug exposure substantially faster than wild-type strains. We refer to this phenotype as antibiotic resilience. ResR acts in a regulatory cascade with other transcription factors controlling cell growth and division, which are also under positive selection in clinical isolates of Mtb. Mutations of these genes are associated with treatment failure and the acquisition of canonical drug resistance.

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.

Roles of bacteriophages, plasmids and CRISPR immunity in microbial community dynamics revealed using time-series integrated meta-omics.

Viruses and plasmids (invasive mobile genetic elements (iMGEs)) have important roles in shaping microbial communities, but their dynamic interactions with CRISPR-based immunity remain unresolved. We analysed generation-resolved iMGE-host dynamics spanning one and a half years in a microbial consortium from a biological wastewater treatment plant using integrated meta-omics. We identified 31 bacterial metagenome-assembled genomes encoding complete CRISPR-Cas systems and their corresponding iMGEs. CRISPR-targeted plasmids outnumbered their bacteriophage counterparts by at least fivefold, highlighting the importance of CRISPR-mediated defence against plasmids. Linear modelling of our time-series data revealed that the variation in plasmid abundance over time explained more of the observed community dynamics than phages. Community-scale CRISPR-based plasmid-host and phage-host interaction networks revealed an increase in CRISPR-mediated interactions coinciding with a decrease in the dominant 'Candidatus Microthrix parvicella' population. Protospacers were enriched in sequences targeting genes involved in the transmission of iMGEs. Understanding the factors shaping the fitness of specific populations is necessary to devise control strategies for undesirable species and to predict or explain community-wide phenotypes.

Mutations in dnaA and a cryptic interaction site increase drug resistance in Mycobacterium tuberculosis.

Genomic dissection of antibiotic resistance in bacterial pathogens has largely focused on genetic changes conferring growth above a single critical concentration of drug. However, reduced susceptibility to antibiotics-even below this breakpoint-is associated with poor treatment outcomes in the clinic, including in tuberculosis. Clinical strains of Mycobacterium tuberculosis exhibit extensive quantitative variation in antibiotic susceptibility but the genetic basis behind this spectrum of drug susceptibility remains ill-defined. Through a genome wide association study, we show that non-synonymous mutations in dnaA, which encodes an essential and highly conserved regulator of DNA replication, are associated with drug resistance in clinical M. tuberculosis strains. We demonstrate that these dnaA mutations specifically enhance M. tuberculosis survival during isoniazid treatment via reduced expression of katG, the activator of isoniazid. To identify DnaA interactors relevant to this phenotype, we perform the first genome-wide biochemical mapping of DnaA binding sites in mycobacteria which reveals a DnaA interaction site that is the target of recurrent mutation in clinical strains. Reconstructing clinically prevalent mutations in this DnaA interaction site reproduces the phenotypes of dnaA mutants, suggesting that clinical strains of M. tuberculosis have evolved mutations in a previously uncharacterized DnaA pathway that quantitatively increases resistance to the key first-line antibiotic isoniazid. Discovering genetic mechanisms that reduce drug susceptibility and support the evolution of high-level drug resistance will guide development of biomarkers capable of prospectively identifying patients at risk of treatment failure in the clinic.

A natural polymorphism of Mycobacterium tuberculosis in the esxH gene disrupts immunodomination by the TB10.4-specific CD8 T cell response.

CD8 T cells provide limited protection against Mycobacterium tuberculosis (Mtb) infection in the mouse model. As Mtb causes chronic infection in mice and humans, we hypothesize that Mtb impairs T cell responses as an immune evasion strategy. TB10.4 is an immunodominant antigen in people, nonhuman primates, and mice, which is encoded by the esxH gene. In C57BL/6 mice, 30-50% of pulmonary CD8 T cells recognize the TB10.44-11 epitope. However, TB10.4-specific CD8 T cells fail to recognize Mtb-infected macrophages. We speculate that Mtb elicits immunodominant CD8 T cell responses to antigens that are inefficiently presented by infected cells, thereby focusing CD8 T cells on nonprotective antigens. Here, we leverage naturally occurring polymorphisms in esxH, which frequently occur in lineage 1 strains, to test this "decoy hypothesis". Using the clinical isolate 667, which contains an EsxHA10T polymorphism, we observe a drastic change in the hierarchy of CD8 T cells. Using isogenic Erd.EsxHA10T and Erd.EsxHWT strains, we prove that this polymorphism alters the hierarchy of immunodominant CD8 T cell responses. Our data are best explained by immunodomination, a mechanism by which competition for APC leads to dominant responses suppressing subdominant responses. These results were surprising as the variant epitope can bind to H2-Kb and is recognized by TB10.4-specific CD8 T cells. The dramatic change in TB10.4-specific CD8 responses resulted from increased proteolytic degradation of A10T variant, which destroyed the TB10.44-11epitope. Importantly, this polymorphism affected T cell priming and recognition of infected cells. These data support a model in which nonprotective CD8 T cells become immunodominant and suppress subdominant responses. Thus, polymorphisms between clinical Mtb strains, and BCG or H37Rv sequence-based vaccines could lead to a mismatch between T cells that are primed by vaccines and the epitopes presented by infected cells. Reprograming host immune responses should be considered in the future design of vaccines.

Structural and functional insight into the Mycobacterium tuberculosis protein PrpR reveals a novel type of transcription factor.

The pathogenicity of Mycobacterium tuberculosis depends upon its ability to catabolize host cholesterol. Upregulation of the methylcitrate cycle (MCC) is required to assimilate and detoxify propionyl-CoA, a cholesterol degradation product. The transcription of key genes prpC and prpD in MCC is activated by MtPrpR, a member of a family of prokaryotic transcription factors whose structures and modes of action have not been clearly defined. We show that MtPrpR has a novel overall structure and directly binds to CoA or short-chain acyl-CoA derivatives to form a homotetramer that covers the binding cavity and locks CoA tightly inside the protein. The regulation of this process involves a [4Fe4S] cluster located close to the CoA-binding cavity on a neighboring chain. Mutations in the [4Fe4S] cluster binding residues rendered MtPrpR incapable of regulating MCC gene transcription. The structure of MtPrpR without the [4Fe4S] cluster-binding region shows a conformational change that prohibits CoA binding. The stability of this cluster means it is unlikely a redox sensor but may function by sensing ambient iron levels. These results provide mechanistic insights into this family of critical transcription factors who share similar structures and regulate gene transcription using a combination of acyl-CoAs and [4Fe4S] cluster.

Bacterial Genome-Wide Association Identifies Novel Factors That Contribute to Ethionamide and Prothionamide Susceptibility in Mycobacterium tuberculosis.

In Mycobacterium tuberculosis, recent genome-wide association studies have identified a novel constellation of mutations that are correlated with high-level drug resistances. Interpreting the functional importance of the new resistance-associated mutations has been complicated, however, by a lack of experimental validation and a poor understanding of the epistatic factors influencing these correlations, including strain background and programmatic variation in treatment regimens. Here we perform a genome-wide association analysis in a panel of Mycobacterium tuberculosis strains from China to identify variants correlated with resistance to the second-line prodrug ethionamide (ETH). Mutations in a bacterial monooxygenase, Rv0565c, are significantly associated with ETH resistance. We demonstrate that Rv0565c is a novel activator of ETH, independent of the two known activators, EthA and MymA. Clinically prevalent mutations abrogate Rv0565c function, and deletion of Rv0565c confers a consistent fitness benefit on M. tuberculosis in the presence of partially inhibitory doses of ETH. Interestingly, Rv0565c activity affects susceptibility to prothionamide (PTH), the ETH analog used in China, to a greater degree. Further, clinical isolates vary in their susceptibility to both ETH and PTH, to an extent that correlates with the total expression of ETH/PTH activators (EthA, MymA, and Rv0565c). These results suggest that clinical strains considered susceptible to ETH/PTH are not equally fit during treatment due to both Rv0565c mutations and more global variation in the expression of the prodrug activators.IMPORTANCE Phenotypic antibiotic susceptibility testing in Mycobacterium tuberculosis is slow and cumbersome. Rapid molecular diagnostics promise to help guide therapy, but such assays rely on complete knowledge of the molecular determinants of altered antibiotic susceptibility. Recent genomic studies of antibiotic-resistant M. tuberculosis have identified several candidate loci beyond those already known to contribute to antibiotic resistance; however, efforts to provide experimental validation have lagged. Our study identifies a gene (Rv0565c) that is associated with resistance to the second-line antibiotic ethionamide at a population level. We then use bacterial genetics to show that the variants found in clinical strains of M. tuberculosis improve bacterial survival after ethionamide exposure.

Rifampicin and rifabutin resistance in 1003 Mycobacterium tuberculosis clinical isolates.

OBJECTIVES: Drug-resistant TB remains a public health challenge. Rifamycins are among the most potent anti-TB drugs. They are known to target the RpoB subunit of RNA polymerase; however, our understanding of how rifamycin resistance is genetically encoded remains incomplete. Here we investigated rpoB genetic diversity and cross-resistance between the two rifamycin drugs rifampicin and rifabutin. METHODS: We performed WGS of 1003 Mycobacterium tuberculosis clinical isolates and determined MICs of both rifamycin agents on 7H10 agar using the indirect proportion method. We generated rpoB mutants in a laboratory strain and measured their antibiotic susceptibility using the alamarBlue reduction assay. RESULTS: Of the 1003 isolates, 766 were rifampicin resistant and 210 (27%) of these were rifabutin susceptible; 102/210 isolates had the rpoB mutation D435V (Escherichia coli D516V). Isolates with discordant resistance were 17.2 times more likely to harbour a D435V mutation than those resistant to both agents (OR 17.2, 95% CI 10.5-27.9, P value <10-40). Compared with WT, the D435V in vitro mutant had an increased IC50 of both rifamycins; however, in both cases to a lesser degree than the S450L (E. coli S531L) mutation. CONCLUSIONS: The observation that the rpoB D435V mutation produces an increase in the IC50 of both drugs contrasts with findings from previous smaller studies that suggested that isolates with the D435V mutation remain rifabutin susceptible despite being rifampicin resistant. Our finding thus suggests that the recommended critical testing concentration for rifabutin should be revised.

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

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

First draft genome sequence of a strain belonging to the Zoogloea genus and its gene expression in situ.

The Gram-negative beta-proteobacterium Zoogloea sp. LCSB751 (LMG 29444) was newly isolated from foaming activated sludge of a municipal wastewater treatment plant. Here, we describe its draft genome sequence and annotation together with a general physiological and genomic analysis, as the first sequenced representative of the Zoogloea genus. Moreover, Zoogloea sp. gene expression in its environment is described using metatranscriptomic data obtained from the same treatment plant. The presented genomic and transcriptomic information demonstrate a pronounced capacity of this genus to synthesize poly-ß-hydroxyalkanoate within wastewater.

Digitally Barcoding Mycobacterium tuberculosis Reveals In Vivo Infection Dynamics in the Macaque Model of Tuberculosis.

Infection with Mycobacterium tuberculosis causes a spectrum of outcomes; the majority of individuals contain but do not eliminate the infection, while a small subset present with primary active tuberculosis (TB) disease. This variability in infection outcomes is recapitulated at the granuloma level within each host, such that some sites of infection can be fully cleared while others progress. Understanding the spectrum of TB outcomes requires new tools to deconstruct the mechanisms underlying differences in granuloma fate. Here, we use novel genome-encoded barcodes to uniquely tag individual M. tuberculosis bacilli, enabling us to quantitatively track the trajectory of each infecting bacterium in a macaque model of TB. We also introduce a robust bioinformatics pipeline capable of identifying and counting barcode sequences within complex mixtures and at various read depths. By coupling this tagging strategy with serial positron emission tomography coregistered with computed tomography (PET/CT) imaging of lung pathology in macaques, we define a lesional map of M. tuberculosis infection dynamics. We find that there is no significant infection bottleneck, but there are significant constraints on productive bacterial trafficking out of primary granulomas. Our findings validate our barcoding approach and demonstrate its utility in probing lesion-specific biology and dissemination. This novel technology has the potential to greatly enhance our understanding of local dynamics in tuberculosis.IMPORTANCE Classically, M. tuberculosis infection was thought to result in either latent infection or active disease. More recently, the field has recognized that there is a spectrum of M. tuberculosis infection clinical outcomes. Within a single host, this spectrum is recapitulated at the granuloma level, where there can simultaneously be lesional sterilization and poorly contained disease. To better understand the lesional biology of TB infection, we digitally barcoded M. tuberculosis to quantitatively track the fate of each infecting bacterium. By combining this technology with serial PET-CT imaging, we can dynamically track both bacterial populations and granuloma trajectories. We demonstrate that there is little constraint on the bacterial population at the time of infection. However, the granuloma imposes a strong bottleneck on dissemination, and the subset of granulomas at risk of dissemination can be distinguished by physical features.

More than 50% of Clostridium difficile Isolates from Pet Dogs in Flagstaff, USA, Carry Toxigenic Genotypes.

Nosocomial acquisition of Clostridium difficile is well documented, yet recent studies have highlighted the importance of community acquired infections and identified community associated reservoirs for this pathogen. Multiple studies have implicated companion pets and farm animals as possible sources of community acquired C. difficile infections in humans. To explore the potential role of pet dogs in human C. difficile infections we systematically collected canine fecal samples (n = 197) in Flagstaff, AZ. Additionally, nineteen fecal samples were collected at a local veterinary clinic from diarrheic dogs. We used these combined samples to investigate important questions regarding C. difficile colonization in pet canines: 1) What is the prevalence and diversity of C. difficile in this companion pet population, and 2) Do C. difficile isolates collected from canines genetically overlap with isolates that cause disease in humans? We used a two-step sequence typing approach, including multilocus sequence typing to determine the overall genetic diversity of C. difficile present in Flagstaff canines, and whole-genome sequencing to assess the fine-scale diversity patterns within identical multilocus sequence types from isolates obtained within and among multiple canine hosts. We detected C. difficile in 17% of the canine fecal samples with 10% containing toxigenic strains that are known to cause human disease. Sequencing analyses revealed similar genotypes in dogs and humans. These findings suggest that companion pets are a potential source of community acquired C. difficile infections in humans.

NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats.

Whole-genome sequencing (WGS) of bacterial isolates has become standard practice in many laboratories. Applications for WGS analysis include phylogeography and molecular epidemiology, using single nucleotide polymorphisms (SNPs) as the unit of evolution. NASP was developed as a reproducible method that scales well with the hundreds to thousands of WGS data typically used in comparative genomics applications. In this study, we demonstrate how NASP compares with other tools in the analysis of two real bacterial genomics datasets and one simulated dataset. Our results demonstrate that NASP produces similar, and often better, results in comparison with other pipelines, but is much more flexible in terms of data input types, job management systems, diversity of supported tools and output formats. We also demonstrate differences in results based on the choice of the reference genome and choice of inferring phylogenies from concatenated SNPs or alignments including monomorphic positions. NASP represents a source-available, version-controlled, unit-tested method and can be obtained from tgennorth.github.io/NASP.

Detection of Low-Level Mixed-Population Drug Resistance in Mycobacterium tuberculosis Using High Fidelity Amplicon Sequencing.

Undetected and untreated, low-levels of drug resistant (DR) subpopulations in clinical Mycobacterium tuberculosis (Mtb) infections may lead to development of DR-tuberculosis, potentially resulting in treatment failure. Current phenotypic DR susceptibility testing has a theoretical potential for 1% sensitivity, is not quantitative, and requires several weeks to complete. The use of "single molecule-overlapping reads" (SMOR) analysis with next generation DNA sequencing for determination of ultra-rare target alleles in complex mixtures provides increased sensitivity over standard DNA sequencing. Ligation free amplicon sequencing with SMOR analysis enables the detection of resistant allele subpopulations at ≥0.1% of the total Mtb population in near real-time analysis. We describe the method using standardized mixtures of DNA from resistant and susceptible Mtb isolates and the assay's performance for detecting ultra-rare DR subpopulations in DNA extracted directly from clinical sputum samples. SMOR analysis enables rapid near real-time detection and tracking of previously undetectable DR sub-populations in clinical samples allowing for the evaluation of the clinical relevance of low-level DR subpopulations. This will provide insights into interventions aimed at suppressing minor DR subpopulations before they become clinically significant.

Comparative integrated omics: identification of key functionalities in microbial community-wide metabolic networks.

BACKGROUND: Mixed microbial communities underpin important biotechnological processes such as biological wastewater treatment (BWWT). A detailed knowledge of community structure and function relationships is essential for ultimately driving these systems towards desired outcomes, e.g., the enrichment in organisms capable of accumulating valuable resources during BWWT. METHODS: A comparative integrated omic analysis including metagenomics, metatranscriptomics and metaproteomics was carried out to elucidate functional differences between seasonally distinct oleaginous mixed microbial communities (OMMCs) sampled from an anoxic BWWT tank. A computational framework for the reconstruction of community-wide metabolic networks from multi-omic data was developed. These provide an overview of the functional capabilities by incorporating gene copy, transcript and protein abundances. To identify functional genes, which have a disproportionately important role in community function, we define a high relative gene expression and a high betweenness centrality relative to node degree as gene-centric and network topological features, respectively. RESULTS: Genes exhibiting high expression relative to gene copy abundance include genes involved in glycerolipid metabolism, particularly triacylglycerol lipase, encoded by known lipid accumulating populations, e.g., CandidatusMicrothrix parvicella. Genes with a high relative gene expression and topologically important positions in the network include genes involved in nitrogen metabolism and fatty acid biosynthesis, encoded by Nitrosomonas spp. and Rhodococcus spp. Such genes may be regarded as 'keystone genes' as they are likely to be encoded by keystone species. CONCLUSION: The linking of key functionalities to community members through integrated omics opens up exciting possibilities for devising prediction and control strategies for microbial communities in the future.