Biology subjects

Coburn, B.

Publications and source records attributed to Coburn, B..

6 recordsLinked to original sources

bioRxiv2026

Peripheral microbial metabolites as indicators of gut microbiome disruption: systematic review and meta-analysis

BackgroundGut microbiome disruption is often characterized by loss of obligate anaerobic bacteria, which may lead to altered production of microbial metabolites that can be detected peripherally. The application of widely used sequencing-based microbiome analyses to clinical settings is limited by cost, turnaround time, and challenges with patients with very low stool output. Since some products of strictly bacterial metabolism detectable in blood, peripheral metabolites may provide a potentially rapid and scalable indicator of gut microbiome composition and function. We performed a systematic review and meta-analysis of studies reporting circulating microbial metabolites and gut microbiome composition to evaluate whether peripheral microbial metabolites could identify gut microbiome perturbation. ResultsCandidate metabolites were identified systematically across an independent set of studies reporting metabolite-microbiome associations, enabling assessment of reproducibility across disease states and cohorts. We performed a meta-analysis of 19 human cohorts comprising 3242 participants with paired blood metabolite and stool microbiome data. Anaerobe depletion (obligate anaerobe relative abundance <0.70 by sequencing) was associated with decreased products of anaerobic microbial metabolism. Combinations of metabolites distinguished individuals with anaerobe-depleted microbiomes from those without. Circulating metabolite levels distinguished between cases and controls with similar performance as gut microbiome composition across a range of health/disease states, and changed markedly within patients experiencing gut anaerobe depletion after antibiotic exposure. ConclusionsCirculating microbial metabolites are potentially informative indicators of gut microbiome disruption and may serve as a rapid and method for patient stratification in clinical trials or acute care settings. ImportanceCirculating microbial metabolites represent a practical and scalable approach to detecting significant gut microbiome disruption, particularly loss of obligate anaerobes. Unlike stool-based sequencing, which can be logistically challenging and slow, blood-based metabolite profiling could be actionably integrated into existing clinical workflows. Our findings suggest metabolites capture compositional consequences of microbiome collapse, with performance comparable to direct microbiome profiling in distinguishing disease states. Enabling diagnostic enrichment and real-time monitoring of microbiome injury (e.g., during antibiotic use or critical illness) has potential implications for both clinical care and research, including selection of patients for investigation of microbiome-targeted therapies. With further validation, circulating metabolites could provide an accessible surrogate for gut microbiome composition in settings where sequencing is impractical.

microbiology↗

bioRxiv2025

Assessment of ecological fidelity of human microbiome-associated mice in observational studies and an interventional trial

Composition and function of the gut microbiome is associated with diverse health conditions and treatment responses. Human microbiota-associated (HMA) mouse models are used to establish causal links for these associations but have important limitations. We assessed the fidelity of HMA mouse models to recapitulate ecological responses to a microbial consortium using stools collected from a human clinical trial. HMA mice were generated using different routes of consortium exposure and their ecological features were compared to human donors by metagenomic sequencing. HMA mice were more similar in gut composition to other mice than their respective human donors, with taxa including Akkermansia muciniphila and Bacteroides species enriched in mouse recipients. A limited repertoire of microbes was able to engraft into HMA mice regardless of route of consortium exposure. In publicly available HMA mouse datasets from four distinct health conditions, we confirmed our observation that a taxonomically restricted set of microbes reproducibly engrafts in HMA mice and observed that stool microbiome composition of HMA mice were more like other mice than their human donor. Our data suggest that HMA mice are limited models to assess the ecological impact of microbial consortia, with ecological effects in HMA mice being more strongly associated with host species than donor stool ecology or ecological responses to treatment in humans. Comparisons to published studies suggest this may be due to comparatively large host-species effects that overwhelm ecological effects of treatment in humans that HMA models aim to recapitulate. ImportanceHuman microbiota-associated (HMA) mice are models that better represent human gut ecology compared to conventional laboratory mice and are commonly used to test the effect of the gut microbiome on disease or treatment response. We evaluated the fidelity of using HMA mice as avatars of ecological response to a human microbial consortium, MET4. Our results show that HMA mice in our cohort and across other published studies are more similar to each other than the human donors or inoculum they are derived from and harbour a taxonomically restricted gut microbiome. These findings highlight the limitations of HMA mice in evaluating the ecological effects of complex human microbiome-targeting interventions, such as microbial consortia.

microbiology↗

bioRxiv2022

Alterations in intestinal Proteobacteria and antimicrobial resistance gene burden in individuals administered microbial ecosystem therapeutic (MET-2) for recurrent Clostridioides difficile infection

Intestinal colonisation with pathogens and antimicrobial resistant organisms (AROs) is associated with increased risk of infection. Fecal microbiota transplant (FMT) has successfully been used to cure recurrent Clostridioides difficile infection (rCDI) and to decolonise intestinal AROs. However, FMT has significant practical barriers to implementation. A microbial consortium, microbial ecosystem therapeutic (MET)-2, is an alternative to FMT for the treatment of rCDI. It is unknown whether MET-2 is associated with decreases in pathogens and antimicrobial resistance genes (ARGs). We conducted a post-hoc metagenomic analysis of stool collected from two interventional studies of MET-2 (published) and FMT (unpublished) for rCDI treatment to understand if MET-2 had similar effects to FMT for decreasing pathogens and ARGs as well as increasing anaerobes. Patients were included in the current study if baseline stool had Proteobacteria relative abundance [≥]10% by metagenomic sequencing. We assessed pre- and post-treatment Proteobacteria, obligate anaerobe and butyrate-producer relative abundances and total ARGs. MET-2 and FMT were associated with decreases in Proteobacteria relative abundance as well as increases in obligate anaerobe and butyrate-producer relative abundances. The microbiota response remained stable over 4 or 6 months for MET-2 and FMT, respectively. MET-2, but not FMT, was associated with a decrease in the total number of ARGs. MET-2 is a potential therapeutic strategy for ARO/ARG decolonisation and anaerobe repletion.

microbiology↗

bioRxiv2021

Performance characteristics of next-generation sequencing for antimicrobial resistance gene detection in genomes and metagenomes

Short-read sequencing provides a culture-independent method for the detection of antimicrobial resistance (AMR) genes from single bacterial genomes and metagenomic samples. However, the performance characteristics of these approaches have not been systematically characterized. We compared assembly- and read-based approaches to determine sensitivity, positive predictive value, and sequencing limits of detection required for AMR gene detection in an Escherichia coli ST38 isolate spiked into a synthetic microbial community at varying abundances. Using an assembly-based method the limit of detection was 15X genome coverage. We are confident in AMR gene detection at target relative abundances of 100% to 1%, where a target abundance of 1% would require assembly of approximately 30 million reads to achieve 15X target coverage. Recent studies assessing AMR gene content in metagenomic samples may be inadequately sequenced to achieve high sensitivity. Our study informs future sequencing projects and analytical strategies for genomic and metagenomic AMR gene detection.

bioinformatics↗

bioRxiv2020

Two-target quantitative PCR to predict library composition for shallow shotgun sequencing

Shotgun sequencing enables retrieving high resolution information 40 from complex microbial communities. However, the technique is limited by missing information about host-to-microbe ratios observed in different sample types. This makes it challenging to plan sequencing experiments, especially in the context of high sample multiplexing and/or limited sequencing output. We evaluated a qPCR-based assay to predict host-to microbe ratio prior to sequencing. Using a two-target assay aimed at conserved human and bacterial genes, we predicted human-to-microbe ratios in two sample types and validated it on independently collected samples. The assay enabled accurate prediction for a broad range of sample compositions.

microbiology↗

bioRxiv2018

A Genome-Wide Association Analysis Reveals a Role for Recombination in the Evolution of Antimicrobial Resistance in Burkholderia multivorans

Cystic fibrosis (CF) lung infections caused by members of the Burkholderia cepacia complex, such as Burkholderia multivorans, are associated with high rates of mortality and morbidity. We performed a population genomic study of 111 B. multivorans sputum isolates from a single CF patient through three stages of infection including the initial incident infection, deep sampling of a one-year period of chronic infection, and deep sampling of a post-transplant recolonization. We reconstructed the evolutionary history of the population and used a lineage-controlled genome-wide association study (GWAS) approach to identify genetic variants associated with antibiotic resistance. We found that the incident isolate was more susceptible to agents from three antimicrobial classes ({beta}-lactams, aminoglycosides, quinolones), while the chronic isolates diversified into distinct genetic lineages with reduced antimicrobial susceptibility to the same agents. The post-transplant reinfection isolates displayed genetic and phenotypic signatures that were distinct from sputum isolates from all CF lung specimens. There were numerous examples of parallel pathoadaptation, in which individual loci, or even the same codon, were independently mutated multiple times. This set of loci was enriched for functions associated with virulence and resistance. Our GWAS approach identified one variant in the ampD locus (which was independently mutated four times in our dataset) associated with resistance to {beta}-lactams, and two non-synonymous polymorphisms associated with resistance to both aminoglycosides and quinolones, affecting an araC family transcriptional regulator, which was independently mutated three times, and an outer member porin, which was independently mutated twice. We also performed recombination analysis and identified a minimum of 14 recombination events. Parallel pathoadaptive loci and polymorphisms associated with {beta}-lactam resistance were over-represented in these recombinogenic regions. This study illustrates the power of deep, longitudinal sampling coupled with evolutionary and lineage-corrected GWAS analyses to reveal how pathogens adapt to their hosts.

evolutionary biology↗