Biology subjects

Dunstan, S. J.

Publications and source records attributed to Dunstan, S. J..

8 recordsLinked to original sources

bioRxiv2026

Structural variation shapes regulatory and evolutionary diversity at the HLA locus

The human leukocyte antigen (HLA) region is among the most polymorphic loci in the human genome and plays a central role in immune function, yet the contribution of structural variation to its genetic and regulatory diversity remains poorly characterised. Using 460 phased, near-complete human genome assemblies from globally diverse populations, we systematically mapped structural variation and gene content across the HLA locus. We show that the HLA region contains substantially more structural variation than any other region of chromosome 6. At the HLA class II locus, all individuals could be assigned to one of 13 distinct HLA-DR-DQ structural haplotypes, whereas the HLA-A region comprised four major haplotypes, which we found to be interspersed among non-human primate lineages. These structural haplotypes exhibit marked differences in population frequency and show increasing allelic diversity over European prehistory. Integration of Iso-Seq and RNA-Seq data revealed that structural haplotypes are associated with differences in HLA gene expression, suggesting that structural variation directly influences immune gene regulation. Together, our results identify structural variation as a key and previously underappreciated contributor to HLA regulatory diversity, with broad functional and evolutionary implications for human immunity. Manuscript summaryStructural variation drives HLA haplotype diversity and gene expression differences across global human populations.

bioinformatics↗

bioRxiv2025

Host oxidative stress primes mycobacteria for rapid antibiotic resistance evolution

The rapid emergence of multidrug-resistant Mycobacterium tuberculosis (Mtb) threatens global TB control, yet the mechanisms enabling rapid evolution of drug resistance in Mtb remain poorly understood. Here we reveal that pre-existing mutations in oxidative stress response genes create permissive genomic backgrounds that accelerate high-level isoniazid resistance (INHR) without fitness costs, challenging the paradigm that resistance mutations always precede their fitness compensatory adaptations. Using M. smegmatis mc2155 (Msm) as a model, we show that brief exposure to sublethal INH (2x IC50) enriches for "low-level resistance and tolerance" (LLRT) mutants in a single step. These LLRT mutants, particularly those with ohrR loss-of-function mutations, acquire high-level resistance (> 500x IC50) at 6-fold higher rates than wildtype, primarily through otherwise-deleterious mycothiol biosynthesis mutations that become tolerable in the oxidative stress-buffered background. Crucially, we demonstrate that sublethal oxidative stress alone, mimicking host immune pressure, nearly tripled the rate of INH resistance evolution in Msm. Bayesian analysis of 1,578 clinical Mtb isolates from Vietnam confirmed that mutations in oxidative stress response genes were significantly associated with the emergence of INHR strains (p-value = 1.09x10-7). Independently, reanalysis of genome-wide CRISPRi screens revealed that the OSR network and high Bayes probability genes are functionally associated with treatment escape and survival with multiple antibiotics, including isoniazid, rifampicin, ethambutol, bedaquiline, vancomycin, clarithromycin, linezolid, and streptomycin. Our findings that host-imposed oxidative stress and inadequate drug penetration may synergistically prime Mtb populations for rapid resistance evolution suggest that targeting pre-resistance mechanisms, such as oxidative stress defenses, could help slow the emergence of antibiotic resistance in tuberculosis.

microbiology↗

bioRxiv2025

Genome graphs reveal the importance of structural variation in Mycobacterium tuberculosis evolution and drug resistance

Structural variants (SVs) are increasingly recognized as key drivers of bacterial evolution, yet their role has not been explored thoroughly. This is due to limitations in traditional short-read sequencing and linear reference-based analyses, which can miss complex structural changes. Tuberculosis (TB), a disease caused by Mycobacterium tuberculosis (Mtb), remains a major global health concern. In this study, we harness long-read sequencing technologies and genome graph tools to construct a Mtb pangenome reference graph (PRG) from 859 high-quality, diverse, long-read assemblies. To enable accurate genotyping of SVs leveraging the PRG, we developed miniwalk, a tool that outperforms a traditional linear genome-based approach in precision for SV detection. We characterize patterns of structural variation genome-wide, revealing a virulence-associated ESX-5 deletion to be recurrent across the phylogeny, and fixed in a sub-lineage of L4. Systematic screens for additional genes that are recurrently affected by SVs implicated those related to metal homeostasis, including a copper exporter fixed in the widely distributed L1.2.1 sub-lineage. Lastly, we genotyped 41,134 isolates and found SVs putatively associated with resistance to various first and second-line drugs. These findings underscore the broader role of SVs in shaping Mtb diversity, highlighting their importance in both understanding evolution and designing strategies to combat drug-resistant TB.

genomics↗

bioRxiv2025

Evolution of Mycobacterium tuberculosis transcription regulation is associated with increased transmission and drug resistance

Mycobacterium tuberculosis (Mtb) has co-evolved with humans for thousands of years causing variation in virulence, transmissibility, and disease phenotypes. To identify bacterial contributors to phenotypic diversity, we developed new RNA-seq and phylogenomic tools to capture hundreds of Mtb isolate transcriptomes, link transcriptional and genetic variation, and find associations between variants and epidemiologic traits. Across 274 Mtb clinical isolates, we uncovered unexpected diversity in expression of virulence genes which we linked to known and previously unrecognized regulators. Surprisingly, we found that many isolates harbor variants associated with decreased expression of EsxA (Esat6) and EsxB (Cfp10), which are virulence effectors, dominant T cell antigens, and immunodiagnostic targets. Across >55,000 isolates, these variants associate with increased transmissibility, especially in drug resistant Mtb strains. Our data suggest expression of key Mtb virulence genes is evolving across isolates in part to optimize fitness under drug pressure, with sobering implications for immunodiagnostics and next-generation vaccines.

microbiology↗

bioRxiv2023

Disruption of Aldehyde Dehydrogenase 2 protects against 1 bacterial infection

The ALDH2*2 (rs671) variant present in >500 million individuals reduces ALDH2 function, impairing aldehyde detoxification. While aldehyde accumulation in these individuals is associated with numerous negative health consequences, a previous study showed a cohort of ALDH2*2 carriers are less likely to develop active pulmonary tuberculosis. Here, we present additional human data that support this finding and show ALDH2-deficiency in mice provides a fitness advantage during bacterial infections. We found aldehydes normally detoxified by ALDH2 killed the bacterial pathogens Mycobacterium tuberculosis and Francisella tularensis. Infected macrophages from Aldh2-/-mice had higher levels of formaldehyde and 4-hydroxynonenal, which enhanced their microbicidal capacity. Aldh2-/- mice were more resistant to infection with Mycobacterium tuberculosis and Francisella tularensis than parental mice and displayed elevated inflammatory cytokine and chemokine levels, accompanied by an increased accumulation of inflammatory monocytes and macrophages. These findings support a model in which host-derived aldehydes are robust innate immune effectors, limiting bacterial infection through both direct microbicidal activity and immune modulation. Collectively, this work may explain why the ALDH2*2 allele was selected for in humans.

microbiology↗

bioRxiv2023

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

BackgroundCombatting 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. MethodsWe 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. FindingsMtb 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. InterpretationHigh-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. FundingNational 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 contextO_ST_ABSEvidence before this studyC_ST_ABSWe 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 20th, 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 studyWe 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 evidencePhenogenomic 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.

microbiology↗

bioRxiv2022

Direct inference and control of genetic population structure from RNA sequencing data

RNAseq data can be used to infer genetic variants, yet its use for estimating genetic population structure remains underexplored. Here, we construct a freely available computational tool (RGStraP) to estimate RNAseq-based genetic principal components (RG-PCs) and assess whether RG-PCs can be used to control for population structure in gene expression analyses. Using whole blood samples from understudied Nepalese populations and the Geuvadis study, we show that RG-PCs had comparable results to paired array-based genotypes, with high genotype concordance and high correlations of genetic principal components, capturing subpopulations within the dataset. In differential gene expression analysis, we found that inclusion of RG-PCs as covariates reduced test statistic inflation. Our paper demonstrates that genetic population structure can be directly inferred and controlled for using RNAseq data, thus facilitating improved retrospective and future analyses of transcriptomic data.

bioinformatics↗

bioRxiv2016

Genomic analysis of Mycobacterium tuberculosis reveals complex etiology of tuberculosis in Vietnam including frequent introduction and transmission of Beijing lineage and positive selection for EsxW Beijing variant

Introduction Introduction Accession codes AUTHOR CONTRIBUTIONS COMPETING FINANCIAL INTERESTS Online Methods References Tuberculosis (TB) is a leading cause of death from infectious disease and the global burden is now higher than at any point in history 1,2 Despite coordinated efforts to control TB transmission, the factors contributing to its successful spread remain poorly understood. Vietnam is identified as one of 30 high burden countries for TB and MDR-TB with an incidence of 137 TB cases per 100,000 individuals in 2015 2 Recent phylogenomic analyses of the causative agent Mycobacterium tuberculosis (Mtb) in other high-prevalence regions have provided insights into the complex processes underlying TB transmission ...

genomics↗