The maternal gut microbiome is a predictor of infant eczema.

Identifying antibiotic resistance genes (ARGs) from metagenomic data is critical for studying antimicrobial resistance across microbial communities and pathogens. However, there is no standardized methodology for ARG annotation. Here, we compare ten commonly used ARG detection pipelines by analysing over 270 million prokaryotic genes from the Global Microbial Gene Catalogue across 13 distinct habitats. We observed up to a 45-fold difference in the number of reported ARGs, with a mean Jaccard index of only 16% between pipelines. Pipeline selection profoundly impacted downstream biological interpretations, with drastic changes to estimates of ARG relative abundance and richness, to the characterization of pan- and core-resistomes, and to the class-level composition of the inferred resistome. ARG detection pipelines make different, defensible trade-offs, and no single approach should be treated as authoritative. Therefore, users should justify and communicate choices carefully, as our analyses show that, taken uncritically, the same data can support conflicting biological and ecological interpretations. ### Competing Interest Statement The authors have declared no competing interest. National Health and Medical Research Council of Australia (NHMRC), 2031902 Australian Research Council (ARC), FT230100724 International Development Research Centre (IDRC), 109304-001 Deutsche Forschungsgemeinschaft (DFG), FO1279/6-1 Bundesministerium für Bildung und Forschung (BMBF), F01KI1909A, 01KI2404B Swedish Research Council (VR), 2024-06123, 2019-00299, 2023-01721 Knut and Alice Wallenberg Foundation, KAW 2020.0239 Swedish Foundation for Strategic Research, FFL21-0174

Workshop at the Banff International Research Station in Banff, Alberta between Feb 8 and Feb 13, 2026: New Mathematical Theory in Eco-Evolutionary Modelling of Host-Symbiont Communities.

New study provides one of the most detailed portraits yet of how different combinations of bacteria in human milk contribute to infants’ gut microbiomes.

Most conversations about breast milk tend to focus on topics like nutrients, antibodies and bonding time rather than bacteria.

In this Consensus Statement, a consortium of microbiome scientists discuss current sequencing data sharing policies and propose the use of a Data Reuse Information (DRI) tag to promote equitable and collaborative data sharing.

In this Consensus Statement, a consortium of microbiome scientists discuss current sequencing data sharing policies and propose the use of a Data Reuse Information (DRI) tag to promote equitable and collaborative data sharing.

This is the first study using detailed retrospective medication usage data from electronic health records to systematically assess the long-term effects of medication usage on the gut microbiome. We identified carryover and additive effects on the gut microbiome for a range of antibiotics and non-antibiotic medications, such as benzodiazepine derivatives, antidepressants and glucocorticoids, among others. These findings highlight a collateral effect of diverse drug classes on the gut microbiome, which warrants accounting for long-term medication usage history when assessing disease-microbiome associations.

Over the past decades, medication use has steadily increased worldwide, with individuals frequently taking multiple medications (polypharmacy), often repeatedly over extended periods of time (1). Yet,...

IntroductionHuman breast milk is a sophisticated and complex biological fluid that provides crucial nutritional, immunological, and microbial benefits to inf...