Biology subjects

Lynch, S. V.

Publications and source records attributed to Lynch, S. V..

4 recordsLinked to original sources

bioRxiv2026

Carbohydrate Metabolism Differs in Infants by Asthma-risk Status and is Associated with the Functional Potential of Bacteroides cellulosilyticus

2.Childhood atopic disease is linked to delayed gut microbiome development and metabolic dysfunction, however microbial drivers remain unclear. To explore microbial correlates of asthma risk during a time of active gut microbiome development, we analyzed stool from 6-month-old infants at high asthma risk (HR) or healthy controls (HC), using Genome-resolved metagenomics (HR=7; HC=12) and untargeted metabolomics (HR=11; HC=15). We recovered 82 bacterial species-level metagenomic-assembled genomes (MAGs). Global Taxonomic composition did not differ by asthma risk. Anticipating that key differences might associate with specific genomes, a machine-learning approach pinpointed Bacteroides cellulosilyticus, Hungatella effluvii, and Enterocloster aldenensis as linked with asthma risk status. All three species were more abundant in HC infants and the B. cellulosilyticus genome was enriched for carbohydrate metabolism genes relative to other MAGs. Metabolomic profiling revealed variance associated with asthma risk (PERMANOVA, R2 =0.069, p=0.016). HR fecal metabolomes were enriched in simple sugars, whereas HC contained more nitrogenous compounds. Integrative genome-metabolic modeling of compounds that significantly differentiate asthma-risk groups revealed risk-dependent interactions with community-encoded metabolic potential (CEP), for arabinose and agmatine, whose fecal concentrations are linked with B. cellulosilyticus and H. effluvii functional traits respectively. These findings suggest that microbial-influenced metabolic differences associate with asthma risk at 6 months, with B. cellulosilyticus and H. effluvii emerging as candidate bacteria influencing this observed metabolic remodeling. 3. Impact statementLeveraging a random forest classifier, we identified three bacterial species (Bacteroides cellulosilyticus, Hungatella effluvii, and Enterocloster aldenensis) as distinguishing features enriched in healthy 6-month old infant microbiomes compared to those at high risk of asthma development (HR). We developed an approach to integrate metabolomics and metagenomic-derived microbiome community encoded potential (CEP) with clinical outcomes to identify fecal metabolites whose concentrations are likely to be influenced by the microbiome. Fecal arabinose concentrations were positively associated with CEP in healthy infants, but not in HR subjects who exhibited elevated concentrations irrespective of CEP. These data implicate microbial activity as a contributor to the concentration of this metabolite in healthy but not HR infants. With a leave-one-out-cross-validation, we identified B. cellulosilyticus as a contributor to fecal arabinose concentrations. Our data indicate that microbial functional deficits in HR infants is associated with altered gut metabolic dysfunction during microbiome maturation. 4. Data summaryDurack et. al [1] is the source of the metabolomics data utilized in this study. The authors confirm that all other supporting data, code and protocols have been provided within the article or through supplementary data files.

microbiology↗

bioRxiv2025

CD38 expression by neonatal human naïve CD4+ T cells shapes their distinct metabolic state and high regulatory T cell potential

Neonatal life is marked by rapid antigen exposure, necessitating establishment of peripheral immune tolerance via conversion of naive CD4+ T cells into regulatory T cells (Tregs). Here, we demonstrate heighted capacity for FOXP3 expression and tolerogenic function among cord blood versus adult blood naive CD4+ T cells and that this is linked to their unique metabolic profile and elevated expression of the NADase, CD38. Early life naive CD4+ T cells demonstrate a metabolic preference for glycolysis, which directly facilitates their differentiation trajectory. We reveal an age-dependent gradient in CD38 levels on naive CD4+ T cells and show that high CD38 expression contributes to both the glycolytic state and tolerogenic potential of neonatal CD4+ T cells, effects that are mediated at least in part via the NAD-dependent deacetylase SIRT1. Thus, the early life window for peripheral tolerance in humans is critically enabled by the immunometabolic state of the naive CD4+ compartment.

immunology↗

bioRxiv2022

Mild SARS-CoV-2 infection results in long-lasting microbiota instability

Viruses targeting mammalian cells can indirectly alter the gut microbiota, potentially compounding their phenotypic effects. Multiple studies have observed a disrupted gut microbiota in severe cases of SARS-CoV-2 infection that require hospitalization. Yet, despite demographic shifts in disease severity resulting in a large and continuing burden of non-hospitalized infections, we still know very little about the impact of mild SARS-CoV-2 infection on the gut microbiota in the outpatient setting. To address this knowledge gap, we longitudinally sampled 14 SARS-CoV-2 positive subjects who remained outpatient and 4 household controls. SARS-CoV-2 cases exhibited a significantly less stable gut microbiota relative to controls, as long as 154 days after their positive test. These results were confirmed and extended in the K18-hACE2 mouse model, which is susceptible to SARS-CoV-2 infection. All of the tested SARS-CoV-2 variants significantly disrupted the mouse gut microbiota, including USA-WA1/2020 (the original variant detected in the United States), Delta, and Omicron. Surprisingly, despite the fact that the Omicron variant caused the least severe symptoms in mice, it destabilized the gut microbiota and led to a significant depletion in Akkermansia muciniphila. Furthermore, exposure of wild-type C57BL/6J mice to SARS-CoV-2 disrupted the gut microbiota in the absence of severe lung pathology. IMPORTANCETaken together, our results demonstrate that even mild cases of SARS-CoV-2 can disrupt gut microbial ecology. Our findings in non-hospitalized individuals are consistent with studies of hospitalized patients, in that reproducible shifts in gut microbial taxonomic abundance in response to SARS-CoV-2 have been difficult to identify. Instead, we report a long-lasting instability in the gut microbiota. Surprisingly, our mouse experiments revealed an impact of the Omicron variant, despite producing the least severe symptoms in genetically susceptible mice, suggesting that despite the continued evolution of SARS-CoV-2 it has retained its ability to perturb the intestinal mucosa. These results will hopefully renew efforts to study the mechanisms through which Omicron and future SARS-CoV-2 variants alter gastrointestinal physiology, while also considering the potentially broad consequences of SARS-CoV-2-induced microbiota instability for host health and disease.

microbiology↗

bioRxiv2018

Neonatal gut-microbiome-derived 12,13 DiHOME impedes tolerance and promotes childhood atopy and asthma

Neonates at risk of childhood atopy and asthma are characterized by gut microbiome perturbation and fecal enrichment of 12,13 DiHOME(1); however, the underlying mechanism and source of this metabolite remain poorly understood. Here we show that 12,13 DiHOME treatment of human dendritic cells altered peroxisome proliferator-activated receptor {gamma} regulated gene expression and decreased immune tolerance. In mice, 12,13 DiHOME treatment prior to airway challenge exacerbated pulmonary inflammation and decreased lung regulatory T cells. Neonatal fecal metagenomic sequencing revealed putative bacterial sources of 12,13 DiHOME. In our cohort, three bacterial genes and their product, 12,13 DiHOME, are associated with increased odds of childhood atopy or asthma, suggesting that early-life gut-microbiome risk factors may shape immune tolerance and identify high-risk neonates years in advance of clinical symptoms.\n\nOne Sentence SummaryEarly-life gut-microbiome risk factors may shape immune tolerance and identify neonates at high-risk of disease.

microbiology↗