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Intelectin-2 defends mucosal interfaces by crosslinking mucus and blocking microbial growth. This study reveals that mouse and human intelectin-2 recognizes galactose-rich glycans to bind and target diverse bacteria—uncovering a potent, dual-action lectin that shapes host–microbe balance.

Metagenomic analysis of the gut microbiome of people with human immunodeficiency virus (HIV), from three distinct cohorts, revealed infection- and antiretroviral drug-linked alterations, which may contribute to HIV-associated non-infectious comorbidities.

A new discovery strategy, ‘reverse metabolomics’, facilitates high-throughput matching of mass spectrometry spectra in public untargeted metabolomics datasets, and a proof-of-concept experiment identified an association between microbial bile amidates and inflammatory bowel disease.

Inflammatory bowel diseases (IBD) are associated with increased faecal N-acylethanolamines (NAEs), which are primarily host-produced signalling lipids, in patients and a mouse model of colitis. These metabolites can enhance the growth of bacterial species enriched in IBD faecal samples and are associated with the expression of respiratory chain genes necessary for microbial metabolism of NAEs.

Overall, this study describes the molecular mechanism of a druggable pathway that recapitulates in cellular assays the immunomodulatory effects associated with Akkermansia muciniphila, a prominent member of the gut microbiota.

A computational system termed MetaWIBELE (workflow to identify novel bioactive elements in the microbiome) is used to identify microbial gene products that are potentially bioactive and have a functional role in the pathogenesis of inflammatory bowel disease.

Metabolomics data from germ-free and specific-pathogen-free mice reveal effects of the microbiome on host chemistry, identifying conjugations of bile acids that are also enriched in patients with inflammatory bowel disease or cystic fibrosis.

Obtaining metabolomic data from microbial communities can be costly and difficult, whereas many microbial community sequence datasets are already available. Here Mallick et al. describe a computational approach to predict metabolic features from microbial DNA sequencing information.

Integration of longitudinal gut metagenomic datasets from children in Finland, Estonia and Russian Karelia reveals high strain-level diversity, which consequently impacts the functional capabilities of the early life microbiome.

The oral bacterium Veillonella parvula utilizes inflammation-associated nitrate to facilitate colonization of the intestinal tract, which is observed in a mouse model of colitis and patients with inflammatory bowel disease.

The authors profile stool metagenomics and plasma metabolomics in Tanzanian individuals and uncover a gradient of gut microbial profiles, from rural through urban Tanzania towards Western populations. Integration with ex vivo blood microbial stimulations reveals immune responses associated with histidine and arginine pathways, mediated by Bifidobacterium longum and Akkermansia muciniphila.

The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.

Bacterially produced bile acids inhibit T_H17 cell function, which may be relevant to the pathophysiology of inflammatory disorders such as inflammatory bowel disease.

The microbiota of centenarians (aged 100 years and older) comprise gut microorganisms that are capable of generating unique secondary bile acids, including isoallolithocholic acid, a bile acid with potent antimicrobial effects against Gram-positive—but not Gram-negative—multidrug-resistant pathogens.

A consortium of 11 bacterial strains from the healthy human gut microbiota can strongly induce interferon-γ-producing CD8 T cells in the intestine, and enhance both resistance to bacterial infection and the therapeutic efficacy of immune checkpoint inhibitors.

Using metabolomics and shotgun metagenomics on stool samples from individuals with and without inflammatory bowel disease, metabolites, microbial species and genes associated with disease were identified and validated in an independent cohort.

Extracellular signalling regulates a plethora of multicellular processes. For microbes, maintaining a specific cell–cell signal in an extracellular environment crowded by other species can be extremely challenging. Two recent papers demonstrate how different bacteria have adapted to avoid, or exploit, species cross-signalling.

The Inflammatory Bowel Disease Multi’omics Database includes longitudinal data encompassing a multitude of analyses of stool, blood and biopsies of more than 100 individuals, and provides a comprehensive description of host and microbial activities in inflammatory bowel diseases.

Analysis of paired metagenomes and metatranscriptomes associated with patients with inflammatory bowel disease (IBD) and non-IBD controls over time provides some insights into microbial community variation and potential pathways influencing IBD symptoms.

Bacillus subtilishas emerged as an important model organism for the study of biofilms. In this Review, Kolter, Losick and colleagues discuss the regulation ofB. subtilisbiofilm assembly and highlight two emerging areas in the field: biofilm formation on natural substrates and biofilm disassembly.

An analysis of more than 10,000 metagenomes from the TEDDY study provides a detailed functional profile of the gut microbiome in relation to islet autoimmunity, and supports the protective effects of short-chain fatty acids in early-onset type 1 diabetes.

Perturbations in the intestinal microbiome are implicated in inflammatory bowel disease (IBD). In this Review, Xavier and colleagues highlight current knowledge of gut microbial factors linked to IBD pathogenesis and discuss how multiomics data from large-scale population studies in health and disease have been used to identify specific microbial strains, transcriptional changes and metabolic alterations associated with IBD.