Biology subjects

Xavier, J. B.

Publications and source records attributed to Xavier, J. B..

7 recordsLinked to original sources

bioRxiv2026

Resource-access breadth marks protective strains against toxigenic Clostridioides difficile

Antibiotic disruption of gut microbiota creates opportunities for toxigenic Clostridioides difficile. One strategy is to occupy this niche with a non-toxigenic or weakly virulent strain, but even strains that cause little disease may fail to compete during pathogen challenge. We screened 21 sequence type 1 (ST1) isolates for their ability to protect mice co-colonized with toxigenic VPI10463, separating disease potential from protection. Some strains, such as ST1-75, caused little disease and protected, whereas others, such as ST1-68, caused little disease but failed to protect. Metabolomics showed that ST1-75 depleted more proline than ST1-68, whereas another protective strain, ST1-6, had a different metabolic profile; both protective strains nevertheless responded to many substrates. Substrate-utilization profiling revealed that protection across the 21 isolates correlated with amino-acid overlap with VPI10463, but not overall nutrient overlap or shared genome-encoded protein families. Relative amino-acid access explained variation beyond mono-colonization disease potential, and a consumer-resource model showed how nutrient overlap together with additional resource access can support persistence during competition. Additional experiments support that ST1-mediated protection occurs even in the absence of mature B and T cells. These findings distinguish low disease potential from protection, link protection to strain competition, and identify relative resource access as an informative phenotype for prioritizing strains for biotherapeutic testing.

microbiology↗

bioRxiv2025

Intracellular acidification by bacteria-derived valeric acid is a mechanism of trans-kingdom ecology against Candida parapsilosis colonization

In hematopoietic cell transplant patients, intestinal Candida parapsilosis expansion and translocation cause life-threatening candidemia, yet how commensal intestinal bacteria prevent Candida expansion remains incompletely defined. Here, we trained a machine learning model on supernatant metabolomic profiles of commensal bacteria to identify bacteria-derived inhibitors of fungal growth, with valeric and butyric acid as top hits. Experimental validation confirmed in silico predictions in three systems. First, in patient fecal samples, valeric and butyric acid levels inversely correlated with C. parapsilosis growth. Second, in vitro, valeric acid potently inhibited C. parapsilosis growth by causing intracellular acidification. Third, administration of glycerol valerate, and free or microencapsulated valeric acid blunted C. parapsilosis growth at murine intestinal sites where valeric acid could be detected. Thus, machine learning could identify a mechanistic driver of trans-kingdom ecology limiting C. parapsilosis intestinal expansion and may inform strategies to reduce patient risk of developing candidiasis during high-risk periods.

microbiology↗

bioRxiv2022

The TaxUMAP atlas: efficient display of large clinical microbiome data reveals ecological competition involved in protection against bacteremia

The microbiome is associated with health and disease, but causal effects are hard to quantify-- especially in humans where controlled experiments are nearly impossible. Akin to natural experiments, closely monitored patients offer an alternative to characterize microbiome effects. We present TaxUMAP, a taxonomically-informed visualization method to effectively display diverse microbiome states. TaxUMAP charts a microbiome atlas from 1,870 cancer patients as they progress through therapy-induced perturbations, and quantifies the microbiome contribution to patients risk for life-threatening bacteremia. We find that the lowest diversity states (gut dominations) that follow antibiotic treatments are stable, and that diverse communities harbor more diverse antimicrobial resistance genes than dominations. We reveal that certain Klebsiella species are associated with reduced risk for bacteremia, an effect driven by bacterial competition that we validate experimentally in vitro and in vivo. TaxUMAP effectively maps longitudinal microbiome data that can facilitate research into causal microbiome effects on human health. HIGHLIGHTSO_LITaxUMAP charts an atlas of patients microbiome states and their clinical context to reveal new causal effects. C_LIO_LIAntibiotics deplete the biodiversity and reduce the number of different antimicrobial resistance genes in the gut microbiome. C_LIO_LICertain Klebsiella species are associated with lower risk of bacteremia by other gut-borne pathogens. C_LIO_LIThese Klebsiella outcompete other gram-negative pathogens in vivo. C_LI

microbiology↗

bioRxiv2019

The gut microbiota influences circulatory immune cell dynamics in humans

The gut microbiota influences development and homeostasis of the mammalian immune system1-3, can alter immune cell compositions in mice4-7, and is associated with responses to immunotherapy that rely on the activity of peripheral immune cells8-12. Still, our understanding of how the microbiota modulates immune cells dynamics remains limited, particularly in humans where a lack of deliberate manipulations makes inference challenging. Here we study hundreds of hospitalized--and closely monitored--patients receiving hematopoietic cell transplantation as they recover from chemotherapy and stem cell engraftment. This aggressive treatment causes large shifts in both circulatory immune cell and microbiota populations, allowing the relationships between the two to be studied simultaneously. We analyzed daily changes in white blood cells from 2,235 patients, and 10,680 longitudinal microbiota samples to identify bacteria associated with those changes. Bayesian inference and validation across patient cohorts revealed consistent associations between gut bacteria and white blood cell dynamics in the context of immunomodulatory medications, clinical metadata and homeostatic feedbacks. We contrasted the potency of fermentatively active, obligate anaerobic bacteria with that of medications with known immunomodulatory mechanism to estimate the potential of the microbiota to influence peripheral immune cell dynamics. Our analysis establishes and quantifies the link between the gut microbiota and the human immune system, with implications for microbiota-driven modulation of immunity.

microbiology↗

bioRxiv2019

Antibiotic-induced shifts in fecal microbiota density and composition during hematopoietic stem cell transplantation

BackgroundDramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these dynamic changes at high-resolution through daily stool sampling and assess the impact of individual antibiotics on those changes.\n\nMethodsWe collected 272 longitudinal stool samples (with mostly daily frequency) from 18 patients undergoing HCT and determined their composition by multi-parallel 16S rRNA gene sequencing, as well as density of bacteria in stool by qPCR. We calculated microbiota volatility to quantify rapid shifts and developed a new dynamic systems inference method to assess the specific impact of antibiotics.\n\nResultsThe greatest shifts in microbiota composition occurred between stem cell infusion and reconstitution of healthy immune cells. Piperacillin-tazobactam caused the most severe declines among obligate anaerobes.\n\nConclusionsOur approach of daily sampling, bacterial density determination and dynamic systems modeling allowed us to infer the independent effects of specific antibiotics on the microbiota of HCT patients.

microbiology↗

bioRxiv2017

The Vibrio cholerae Type VI Secretion System Can Modulate Host Intestinal Mechanics to Displace Commensal Gut Bacteria

Host-associated microbiota help defend against bacterial pathogens; the mechanisms that pathogens possess to overcome this defense, however, remain largely unknown. We developed a zebrafish model and used live imaging to directly study how the human pathogen Vibrio cholerae invades the intestine. The gut microbiota of fish mono-colonized by commensal strain Aeromonas veronii was displaced by V. cholerae expressing its Type VI Secretion System (T6SS), a syringe-like apparatus that deploys effector proteins into target cells. Surprisingly, displacement was independent of T6SS-mediated killing of Aeromonas, driven instead by T6SS-induced enhancement of zebrafish intestinal movements that led to expulsion of the resident commensal by the host. Deleting an actin crosslinking domain from the T6SS apparatus returned intestinal motility to normal and thwarted expulsion, without weakening V. cholerae's ability to kill Aeromonas in vitro. Our finding that bacteria can manipulate host physiology to influence inter-microbial competition has implications for both pathogenesis and microbiome engineering.

microbiology↗

bioRxiv2017

A simple rule for the evolution of fast dispersal at the edge of expanding populations

Predicting evolution of expanding populations is critical to control biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this survival of the fastest? We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into an hy-perswarmer mutant which disperses[~] 100% faster but pays a growth cost of [~] 10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: [Formula]. A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species (v1); this simple condition (v2 > v1) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.

evolutionary biology↗