Biology subjects

Koh, A. Y.

Publications and source records attributed to Koh, A. Y..

12 recordsLinked to original sources

bioRxiv2026

Population genomics of skin Staphylococcus reveals disease-associated restructuring of species and strain diversity

Whole genome sequences of microbial isolates are essential to link microbial diversity to population and community ecology, because metagenomics alone cannot resolve strain-level variation, particularly in complex and mobile genetic elements that confer strain-specific traits such as virulence. We cultured and whole-genome sequenced 2,920 Staphylococcus isolates from healthy subjects and patients with Dariers disease and congenital ichthyosis. Our results show that disease imposes selection at the species level, while strain populations within those species diversify across individuals in a manner consistent with ecological drift, resulting in increased interpersonal heterogeneity of strain composition. Despite this variability, strain populations converged on shared functional traits, suggesting constraints imposed by the disease environment. We further examined key functional elements of clinical and ecological relevance, including the agr quorum sensing system, the mobile genetic element SCCmec that carries methicillin resistance, and CRISPR/Cas systems, contextualizing these features both within isolate population structure and the surrounding microbial community using metagenomic data. We found disease-dependent enrichment of virulence genes, striking species-specific phylogenetic sorting of agr variants, unexpected modularity of previously undocumented SCCmec elements in diseased skin, and links between phages in the microbiota and CRISPR spacers in the isolate genomes. Taken together, our integrated, large-scale analysis of isolate genomics and metagenomics reveals that skin disease restructures staphylococcal strain populations through combined effects of selection, drift, and functional constraint. One line summaryWhole-genome sequencing of 2,920 skin Staphylococcus isolates shows that disease selects at the species level while reshaping strain populations and their functional diversity within hosts.

microbiology↗

bioRxiv2026

A microbiota-derived bile acid overcomes antibiotic-induced hyporesponsiveness to immune checkpoint therapy by enhancing CD8+ T cell antitumor immunity

Gut microbiota are critical determinants of effective immune checkpoint therapy (ICT), yet the microbial mediators and host mechanisms that enhance antitumor immunity remain poorly understood. Here, we identify the microbiota-derived bile acid taurodeoxycholic acid (TDCA) as a metabolite associated with immune checkpoint therapy (ICT) response. TDCA administration alone is sufficient to overcome antibiotic-induced ICT hyporesponsiveness across multiple murine tumor models. Mechanistically, TDCA directly enhances CD8 T cell-mediated antitumor immunity, increasing cytotoxicity. These effects required signaling through the bile acid receptor TGR5. Together, these findings reveal TDCA as a gut microbial metabolite that restores ICT efficacy after antibiotic disruption by directly augmenting CD8 T cell anti-tumor activity. This work supports metabolite replacement as a therapeutic strategy to mitigate antibiotic-associated loss of cancer immunotherapy response. SignificanceTDCA is a microbiota-derived metabolite that restores immune checkpoint therapy efficacy after antibiotic disruption by directly enhancing CD8 T-cell-mediated anti-tumor immunity through bile acid receptor TGR5 signaling. Our findings suggest that supplementation with defined microbial metabolites can mitigate antibiotic-associated loss of immunotherapy response without requiring broader microbiome reconstitution.

cancer biology↗

bioRxiv2025

Timing of immune checkpoint blockade shapes anti-tumor immunity via a clock-dependent chemokine axis

Circadian clocks regulate immunity, yet how they shape the tumor immune microenvironment and influence cancer immunotherapy remains unclear. Here, we show that tumor immune infiltration and immune checkpoint inhibitor efficacy vary by time of day in mice, driven by intrinsic clocks in dendritic cells and CD8+ T cells. Time-of-day modulates the abundance, spatial organization, and cytokine-chemokine production of tumor-infiltrating immune cells. Mechanistically, dendritic cell clocks control expression of Cx3cl1, driving recruitment of CX3CR1+CD8+ T cells and thereby reshaping the tumor immune microenvironment to enhance immunotherapy efficacy. Disruption of this axis abolishes time-of-day-dependent differences in treatment response. These findings identify a circadian mechanism of immune cell recruitment to tumors and provide mechanistic insight into clinical observations linking treatment timing to immunotherapy outcomes. One sentence summaryTime of day determines cancer immunotherapy efficacy through a circadian clock-dependent chemokine axis.

immunology↗

bioRxiv2025

The gut microbiota directs vitamin A flux to regulate intestinal T cell development

The intestinal microbiota shapes adaptive immunity, but the mechanisms remain incompletely defined. Here, we show that the microbiota initiates the movement of retinoids--dietary vitamin A derivatives including retinol and retinoic acid--through a sequential pathway from epithelial cells to myeloid cells and ultimately to T cells in the mesenteric lymph nodes (mLNs). This cellular axis is traversed over three days. Microbe-associated molecular patterns (MAMPs) initiate retinoid flux by inducing expression of serum amyloid A (SAA) proteins. These epithelial retinol-binding proteins are necessary and sufficient for epithelial-to-myeloid cell retinoid transfer and for myeloid cell migration to the mLNs. In the mLNs, microbial antigen drives retinoid transfer from myeloid cells to developing T cells, culminating in T cell retinoid uptake and transcriptional programming. This pathway is activated during postnatal development, when gut adaptive immunity is first established. These findings reveal that the microbiota programs intestinal adaptive immunity by regulating immune cell access to a nutrient-derived developmental signal. HighlightsO_LIThe gut microbiota enables vitamin A flux to developing intestinal CD4 T cells. C_LIO_LIMicrobiota-induced SAA initiates vitamin A flux along a gut myeloid-T cell axis. C_LIO_LIMicrobial molecular patterns and antigen drive distinct steps of vitamin A flux. C_LIO_LIMicrobiota-driven vitamin A flux programs intestinal T cell homing and maturation. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/674524v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@13b3906org.highwire.dtl.DTLVardef@11ceee3org.highwire.dtl.DTLVardef@87913forg.highwire.dtl.DTLVardef@50c9a0_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

Microbiota-derived short-chain fatty acids mediate Candida albicans gastrointestinal colonization resistance

The gut microbiota plays a critical role in constraining Candida albicans (Ca) colonization of the gastrointestinal (GI) tract, a key precursor to disseminated fungal infection in immunocompromised hosts. Depletion of commensal microbiota increases Ca burden and promotes dissemination, yet the mechanisms of microbiota-mediated Ca colonization resistance remain poorly defined. Here, we show that gut microbiota-derived short-chain fatty acids (SCFAs) directly inhibit Ca growth by impairing hexose uptake, disrupting central carbon metabolism, and inducing intracellular acidification. In vivo, SCFAs enhance Ca colonization resistance only in the presence of an intact gut microbiome, which is required to drive SCFA-induced taxonomic shifts that further augment resistance. Commensal microbiota lacking SCFA production exhibit diminished capacity to restrict Ca colonization, while prebiotic therapy that increases luminal SCFA levels enhances Ca clearance. These findings define a critical microbiota-metabolite mechanism underlying Ca colonization resistance and suggest strategies to modulate GI fungal burden and prevent invasive disease.

microbiology↗

bioRxiv2024

An IL-17-DUOX2 axis controls gastrointestinal colonization by Candida albicans

Candida albicans is a ubiquitous fungus in the human gut microbiome as well as a prevalent cause of opportunistic mucosal and systemic disease. There is currently little understanding, however, as to how crosstalk between C. albicans and the host regulates colonization of this key niche. Here, we performed expression profiling on ileal and colonic tissues in germ-free mice colonized with C. albicans to define the global response to this fungus. We reveal that Duox2 and Duoxa2, encoding dual NADPH oxidase activity, are upregulated in both the ileum and colon, and that induction requires the C. albicans yeast-hyphal transition and the hyphal-specific toxin candidalysin. Hosts lacking the IL-17 receptor failed to upregulate Duox2/Duoxa2 in response to C. albicans, while addition of IL-17A to colonoids induced these genes together with the concomitant production of hydrogen peroxide. To directly define the role of Duox2/Duoxa2 in fungal colonization, antibiotic-treated mice lacking intestinal DUOX2 activity were evaluated for C. albicans colonization and host responses. Surprisingly, loss of DUOX2 function reduced fungal colonization at extended time points (>17 days colonization) and increased the proportion of hyphal cells in the gut. IL-17A levels were also elevated in C. albicans-colonized mice lacking functional DUOX2 highlighting cross-regulation between this cytokine and DUOX2. Together, these experiments reveal novel links between fungal cells, candidalysin toxin and the host IL-17-DUOX2 axis, and that a complex interplay between these factors regulates C. albicans filamentation and colonization in the gut.

immunology↗

bioRxiv2023

IsoAnalytics: A Single-cell Proteomics Web Server

MotivationSingle-cell proteomics provide unprecedented resolution to examine biological processes. Customized data analysis and facile data visualization are crucial for scientific discovery. Further, userfriendly data analysis and visualization software that is easily accessible for the general scientific community is essential. ResultsWe have created a web server, IsoAnalytics, that gives users without computational or bioinformatics background the ability to directly analyze and interactively visualize data obtained from the Isoplexis single cell technology platform. We envision this open-sourced web server will increase research productivity and serve as a free, competitive alternative for single-cell proteomics research. ContactAndrew.Koh@utsouthwestern.edu and Xiaowei.Zhan@utsouthwestern.edu AvailabilityIsoAnalytics is free and available at: https://cdc.biohpc.swmed.edu/isoplexis/ and is implemented in Python, with all major browsers supported. Code for IsoAnalytics is free and available at: https://github.com/zhanxw/Isoplexis_Data_Analysis. Supplementary InformationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

MB-SupCon: Microbiome-based predictive models via Supervised Contrastive Learning

Human microbiome consists of trillions of microorganisms. Microbiota can modulate the host physiology through molecule and metabolite interactions. Integrating microbiome and metabolomics data have the potential to predict different diseases more accurately. Yet, most datasets only measure microbiome data but without paired metabolome data. Here, we propose a novel integrative modeling framework, Microbiome-based Supervised Contrastive Learning Framework (MB-SupCon). MB-SupCon integrates microbiome and metabolome data to generate microbiome embeddings, which can be used to improve the prediction accuracy in datasets that only measure microbiome data. As a proof of concept, we applied MB-SupCon on 720 samples with paired 16S microbiome data and metabolomics data from patients with type 2 diabetes. MB-SupCon outperformed existing prediction methods and achieves high average prediction accuracies for insulin resistance status (84.62%), sex (78.98%), and race (80.04%). Moreover, the microbiome embeddings form separable clusters for different covariate groups in the lower-dimensional space, which enhances data visualization. We also applied MB-SupCon on a large inflammatory bowel disease study and observed similar advantages. Thus, MB-SupCon could be broadly applicable to improve microbiome prediction models in multi-omics disease studies.

bioinformatics↗

bioRxiv2021

Candida albicans Isolates 529L and CHN1 Exhibit Stable Colonization of the Murine Gastrointestinal Tract

Candida albicans is a pathobiont that colonizes multiple niches in the body including the gastrointestinal (GI) tract, but is also responsible for both mucosal and systemic infections. Despite its prevalence as a human commensal, the murine GI tract is generally refractory to colonization with the C. albicans reference isolate SC5314. Here, we identify two C. albicans isolates, 529L and CHN1, that stably colonize the murine GI tract in three different animal facilities under conditions where SC5314 is lost from this niche. Analysis of the bacterial microbiota did not show notable differences between mice colonized with the three C. albicans strains. We compared the genotypes and phenotypes of these three strains and identified thousands of SNPs and multiple phenotypic differences, including their ability to grow and filament in response to nutritional cues. Despite striking filamentation differences under laboratory conditions, however, analysis of cell morphology in the GI tract revealed that the three isolates exhibited similar filamentation properties in this in vivo niche. Notably, we found that SC5314 is more sensitive to the antimicrobial peptide CRAMP, and the use of CRAMP-deficient mice increased the ability of SC5314 to colonize the GI tract relative to CHN1 and 529L. These studies provide new insights into how strain-specific differences impact C. albicans traits in the host and advance CHN1 and 529L as relevant strains to study C. albicans pathobiology in its natural host niche. IMPORTANCEUnderstanding how fungi colonize the GI tract is increasingly recognized as highly relevant to human health. The animal models used to study Candida albicans commensalism commonly rely on altering the host microbiome (via antibiotic treatment or defined diets) to establish successful GI colonization by the C. albicans reference isolate SC5314. Here, we characterize two C. albicans isolates that can colonize the murine GI tract without antibiotic treatment and can therefore be used as tools for studying fungal commensalism. Importantly, experiments were replicated in three different animal facilities and utilized three different mouse strains. Differential colonization between fungal isolates was not associated with alterations in the bacterial microbiome but rather with distinct responses to CRAMP, a host antimicrobial peptide. This work emphasizes the importance of C. albicans intra-species variation as well as host anti-microbial defense mechanisms in defining commensal interactions.

microbiology↗

bioRxiv2020

The highly evolvable nature of the antibiotic efflux protein TolC limits use of phages and bacterial toxins as antibacterial agents

Bacteriophages and bacterial toxins are promising antibacterial agents to treat infections caused by multidrug resistant (MDR) bacteria. In fact, bacteriophages have recently been successfully used to treat life-threatening infections caused by MDR bacteria [1-3]. One potential problem with using these antibacterial agents is the evolution of resistance against them in the long term. Here, we studied the fitness landscape of the Escherichia coli TolC protein, an outer membrane protein that is exploited by a pore forming toxin called colicin E1 and by TLS-phage [4, 5]. By systematically assessing the distribution of fitness effects (DFEs) of ~9,000 single amino acid replacements in TolC using either positive (antibiotics and bile salts) or negative (colicin E1 and TLS-phage) selection pressures, we quantified evolvability of the TolC. We demonstrated that the TolC is highly optimized for the efflux of antibiotics and bile salts. In contrast, under colicin E1 and TLS phage selection, TolC sequence is very sensitive to mutation. Our findings suggest that TolC is a highly evolvable target limiting the potential clinical use of bacteriophages and bacterial toxins.

systems biology↗

bioRxiv2020

HARMONIES: A Hybrid Approach for Microbiome Networks Inference via Exploiting Sparsity

The human microbiome is a collection of microorganisms. They form complex communities and collectively affect host health. Recently, the advances in next-generation sequencing technology enable the high-throughput profiling of the human microbiome. This calls for a statistical model to construct microbial networks from the microbiome sequencing count data. As microbiome count data are high-dimensional and suffer from uneven sampling depth, over-dispersion, and zero-inflation, these characteristics can bias the network estimation and require specialized analytical tools. Here we propose a general framework, HARMONIES, a Hybrid Approach foR MicrobiOme Network Inferences via Exploiting Sparsity, to infer a sparse microbiome network. HARMONIES first utilizes a zero-inflated negative binomial (ZINB) distribution to model the skewness and excess zeros in the microbiome data, as well as incorporates a stochastic process prior for sample-wise normalization. This approach infers a sparse and stable network by imposing non-trivial regularizations based on the Gaussian graphical model. In comprehensive simulation studies, HARMONIES outperformed four other commonly used methods. When using published microbiome data from a colorectal cancer study, it discovered a novel community with disease-enriched bacteria. In summary, HARMONIES is a novel and useful statistical framework for microbiome network inference, and it is available at https://github.com/shuangj00/HARMONIES.

bioinformatics↗

bioRxiv2019

MetaPrism: A Toolkit for Joint Taxa/Gene Analysis of Metagenomic Sequencing Data

BackgroundIn microbiome research, metagenomic sequencing generates enormous amounts of data. These data are typically classified into taxa for taxonomy analysis, or into genes for functional analysis. However, a joint analysis where the reads are classified into taxa-specific genes is often overlooked. ResultTo enable the analysis of this biologically meaningful feature, we developed a novel bioinformatic toolkit, MetaPrism, which can analyze sequence reads for a set of joint taxa/gene analyses: 1) classify sequence reads and estimate the abundances for taxa-specific genes; 2) tabularize and visualize taxa-specific gene abundances; 3) compare the abundances between groups, and 4) build prediction models for clinical outcome. We illustrated these functions using a published microbiome metagenomics dataset from patients treated with immune checkpoint inhibitor therapy and showed the joint features can serve as potential biomarkers to predict therapeutic responses. ConclusionsMetaPrism is a toolkit for joint taxa and gene analysis. It offers biological insights on the taxa-specific genes on top of the taxa-alone or gene-alone analysis. MetaPrism is open source software and freely available at https://github.com/jiwoongbio/MetaPrism. The example script to reproduce the manuscript is also provided in the above code repository.

bioinformatics↗