The intestinal epithelium is exposed to diverse combinations of microbiota-derived compounds; however, the mechanisms by which the host integrates these signals remain poorly defined. Studying two highly abundant microbial metabolites, we identified the purine metabolite hypoxanthine as an effector metabolite that directly drives signaling and the short-chain fatty acid butyrate as a regulatory metabolite that conditions host responsiveness. Specifically, hypoxanthine activates the adenosine A1 receptor–TRPC4 axis in enterochromaffin (EC) cells, triggering calcium influx and serotonin release resulting in accelerated gastrointestinal transit locally and increased platelet activation systemically. In contrast, butyrate epigenetically upregulates specific G protein–coupled receptors and ion channels to enhance response to hypoxanthine and the neurotransmitters norepinephrine and dopamine. These findings define a cooperative signaling framework and highlight the role of EC cells as a distinct epithelial signaling hub that senses and integrates microbial metabolite signals to drive physiological responses. Our findings provide a mechanistic foundation for therapeutic strategies that leverage combinatorial microbial signaling.
Gut microbiome signatures during acute infection are associated with long COVID
Clinical Trial: Multi‐Strain Probiotic Improves Bile Acid Profile, Microbiome, and Metabolomic Parameters in Patients With History of Bile Acid Malabsorption—A Randomized, Controlled Trial
ABSTRACT Background Bile acid (BA) malabsorption (BAM) is a common cause of chronic diarrhoea and may occur in some patients due to abnormalities of the gut microbiota. Effects of probiotics on faecal secretory BAs, particularly the primary BA, chenodeoxycholic acid, are unclear. Aim/Methods We conducted a randomized, double‐blind, placebo‐controlled trial of the De Simone formulation 8‐strain probiotic in 24 patients previously diagnosed with BAM. Patients were randomized to 3 weeks of the probiotic (900 billion bacteria) or placebo (maltose), both administered three times daily. Symptoms, serum 7 α C4, faecal primary BAs, intestinal permeability by 13 C‐mannitol‐lactulose test (0.1 and 1 g of the sugars respectively) over 24 h, faecal short chain fatty acids (SCFA), microbiome, and metabolome were assessed at baseline and post‐intervention. Results Data from 22 patients were included. Probiotic supplementation was associated with a significant decrease in % faecal primary BAs (chenodeoxycholic acid and cholic acid) with median change from baseline −5.7 [IQR −10.3, 0.9]% compared to 9.8 [IQR 0.2, 20.6]% on placebo ( p = 0.012). The faecal microbiome was significantly different in the probiotic group after intervention, driven by probiotic‐specific species. There were no significant differences in symptoms, intestinal permeability, or SCFA. However, there was a numerical difference in the changes from baseline in 0‐2 h 13 C‐mannitol excretion −1.9 [−13.9, 4.2] mg for the probiotic and 1.0 (−0.5, 12.7) mg for placebo ( p = 0.084). Conclusions The De Simone formulation probiotic induced significant microbiome and metabolome changes in patients with BAM, ultimately leading to a decrease in % faecal primary BAs and possible reduction in intestinal permeability. Clinical Trials.gov registration NCT #06609148, January 2, 2025.
Robust taxonomic classification in gut and vaginal microbiomes demonstrated through benchmarking with age-specific synthetic communities
Abstract Accurate taxonomic profiling of human microbiomes is essential for advancing research and understanding the complex role microbial communities play in human health. When using shotgun metagenomics, the sequencing data is analyzed through metagenomic pipelines, which incorporate various open-source tools and classify microbes based on matched paired-end DNA reads. However, differences in sequencing and computational approaches can produce substantially different microbiome profiles from the same sample, making validation critical. One approach for validation is benchmarking with realistic mock communities, but this remains relatively rare. Additionally, existing benchmarks often overlook microbiome variability across life stages and body sites, limiting their clinical and research utility. Here, we developed age- and body site-stratified synthetic metagenomes, enabling context-aware benchmarking of microbiome pipelines. Using novelty-based sampling to prioritize microbial diversity and minimize redundancy among selected samples, we selected 300 representative, real biological samples spanning six categories: adult, child, toddler, and infant (>6 months and <6 months) gut samples, as well as adult vaginal samples. We validated three pipelines, Tiny Health’s proprietary Metagenomic Classifier v2 (THMCv2), MetaPhlAn4, and Kraken2+Bracken, using precision, recall, F1 score, and area under the precision-recall curve (AUPR) across age groups and sample types. THMCv2 demonstrated higher recall and F1 scores, detecting more taxa across sample types and ages, while MetaPhlAn4 achieved the highest precision. THMCv2 also achieved the highest area under the precision-recall curve, reflecting peak performance across both abundant and rare species. When analyses were weighted by abundance, THMCv2 and MetaPhlAn4 each characterized the mock community nearly perfectly. Errors for THMCv2 were largely restricted to very low-abundance taxa (<0.001%), whereas MetaPhlAn4 occasionally produced false positives for higher-abundance taxa. Species-level analyses of clinically relevant microbes confirmed these patterns, with THMCv2 demonstrating higher sensitivity, MetaPhlAn4 higher specificity, and Kraken2 lower overall performance. These results demonstrate clear precision-recall trade-offs in metagenomic profiling. This benchmarking framework provides a reproducible approach for evaluating pipeline performance across diverse microbiome contexts and life stages.
Age-specific early-life gut microbiome associations with eczema and food allergies during early immune development
Introduction Eczema and food allergy commonly emerge during infancy and are linked to changes in the gut microbiome, yet it remains unclear when microbiome differences associated with allergic disease first appear during development. Methods We analyzed age-stratified shotgun metagenomic data from 97 children aged 4–36 months, including physician-confirmed cases of eczema or food allergy and non-allergic controls, excluding recent antibiotic or probiotic exposure. Microbial taxa, functional pathways, and composite microbiome metrics were evaluated across three developmental stages: early infancy (4–6 months), mid-infancy (6–12 months), and toddlerhood (12–36 months). Results Differences between allergic and non-allergic children were minimal before 6 months of age but became more apparent during mid-infancy and persisted into toddlerhood. Allergic conditions were associated with reduced abundance of fiber-fermenting and butyrate-producing taxa, enrichment of facultative and inflammation-associated microbes, lower microbiome maturation scores, and shifts in metabolic and inflammatory functional capacity. Discussion These findings suggest that gut microbiome divergence associated with allergic disease becomes more apparent during mid-infancy, highlighting a developmentally relevant period for understanding early immune disruption. The results support further longitudinal and interventional studies aimed at clarifying whether earlier microbiome-targeted strategies may help modify progression along the atopic march.
Compositional and functional differences of gut microbiome and metabolome inform pathogenesis of cholestatic liver disease
AbstractBackgroundInfants born via Cesarean section (C‐section) often have a distinct gut microbiome and higher risks of atopic and immune‐related conditions than vaginally delivered infants. We evaluated whether a microbiome‐based program could shift gut microbiome composition and improve microbiome‐associated health outcomes in C‐section born infants.MethodsThis open‐label, randomized, controlled trial included full‐term C‐section‐born infants aged 0–3 months, randomized to an intervention (n = 25) or control arm (n = 29). Over 6 months, the intervention arm received two microbiome reports, personalized recommendations based on their microbiome, educational materials, and coaching calls focused on microbiome health. Parents reported health conditions via surveys. Primary outcome: Difference between study arms in relative abundance of key gut microbiome taxa and functional genes. Other outcomes: Changes in a C‐section index—a taxonomy‐based metric comparing C‐section‐associated taxa to vaginally‐associated taxa—and prevalence of atopic conditions.ResultsCompared to controls, the intervention arm had higher Bifidobacterium (p = .025, q = .121) and higher abundance of genes associated with human milk oligosaccharide degradation (e.g., α‐L‐fucosidase, p = .019, q = .046) at timepoint 2. In the intervention arm, the C‐section index decreased to a level similar to vaginally born infants (p = .807, q = .807). At the end of the intervention, atopic dermatitis prevalence was lower in the intervention arm than in controls (odds ratio, 0.17 [95% CI, 0.023–0.723], p = .031).ConclusionA personalized microbiome‐based program can modulate the gut microbiome of C‐section‐born infants and may reduce the risk of atopic conditions (ClinicalTrials.gov: NCT06424691).