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Kotaka, M.

Publications and source records attributed to Kotaka, M..

2 recordsLinked to original sources

Path-dependent recovery of the gut microbiome after antibiotics emerges from coupled ecological and evolutionary dynamics

Recovery of the gut microbiome after antibiotic exposure is often incomplete and variable, and the processes underlying this variation remain unclear. We performed longitudinal shotgun metagenomic sequencing of 2876 daily fecal samples from replicated humanized and conventional mouse cohorts exposed to controlled antibiotic perturbations. Metagenomic profiling recapitulated ecological trajectories previously observed by 16S sequencing, while revealing extensive strain-level dynamics, including reproducible sweeps of standing variants and de novo mutations in antibiotic target sites and regulatory loci. We also identified genetic changes whose effects depended on community composition, competitive release, and perturbation history. Cross-housing experiments revealed bidirectional strain transfer, with antibiotic-induced niche clearance enabling replacement of resident strains. In parallel, phage dynamics were heterogeneous and clustered by cage. Together, these findings show that post-antibiotic microbiome recovery is a path-dependent process shaped by selection, transmission, and phage activity, producing divergent outcomes even among closely matched communities exposed to the same perturbations.

microbiology↗

Eubiota: Modular Agentic AI for Autonomous Discovery in the Gut Microbiome

The gut microbiome regulates many aspects of human biology, including immunity and inflammatory diseases, yet mechanistic discovery and translation remain constrained by fragmented workflows and manual hypothesis integration. Here, we present Eubiota, an open-source modular agentic framework that decomposes microbiome inquiry using specialized agents for planning, execution, verification, and grounded synthesis. Coordinated through shared memory and domain-specific tools, Eubiota employs reinforcement learning to optimize multi-turn reasoning, achieving 87.7% benchmark accuracy and outperforming GPT-5.1 by 10.4%. Across four case studies, Eubiota enabled end-to-end discovery with experimental validation. Screening nearly 2,000 bacterial genes, Eubiota identified the uvr-ruv DNA repair axis as a fitness determinant under inflammatory stress, validated using transposon mutants and IBD metagenomes. It further designed a four-strain consortium that attenuated colitis severity in mice and generated a commensal-sparing antibiotic cocktail, demonstrating its utility in addressing community-level design challenges at cellular and molecular levels. Finally, Eubiota discovered diet-associated metabolites that suppress NF-{kappa}B signaling. Together, these results establish Eubiota as a scalable, tool-grounded scientific copilot for mechanistically driven microbiome discovery.

bioinformatics↗