Peer Bork B

The paper surveys global prokaryotic carbon fixation pathways, revealing an oxygen-tolerant rTCA cycle in surface ocean Campylobacterota lineages.

The paper identifies and characterizes a non-canonical bacterial protein translocation-folding complex using cryo-electron tomography, proteomics, and structure prediction in Mycoplasma pneumoniae.

The paper catalogs diazotroph genomes and analyzes their distribution across environments, identifying freshwater and sedimentary ecosystems as key nitrogen-fixation reservoirs.

The paper identifies a diverse microbial reservoir in the ultrasmall ocean fraction, including nitrogen-fixing diazotrophs, with implications for global biogeochemical cycles.

The paper examines latitudinal diversity gradients in the ocean microbiome, finding they are not universal but vary by taxa and environmental factors.

The paper introduces microntology, a controlled vocabulary for microbial habitats, and provides annotations for over 300,000 metagenomic samples.

This study examines how preoperative biliary stenting affects gut microbiota and bile acid metabolism in pancreatic cancer patients, finding reduced diversity and impaired metabolism linked to postoperative complications.

The paper analyzes planetary microbiome structure and gene flow across habitats using metagenomic data, identifying generalist microbes as key drivers of gene transfer.

Metalog manually curates and harmonises contextual metadata for 110,733 metagenomic samples from humans, animals, ocean water and other environments, linked to taxonomic profiles and SPIRE genomes.

The paper introduces the JEDI marker as a universal biodiversity measure, demonstrating its applicability across ecological scales and providing an automated bioinformatic workflow for standardized analysis.

The paper shows that Fgf3 in zebrafish lateral line organogenesis represses target genes through nuclear accumulation, distinct from its extracellular signaling role.

The paper quantifies discoverable bacterial and archaeal diversity in metagenomes, finding many novel phyla and genera hidden in current data.

This study identifies nitroxoline's broad antibacterial activity against Gram-negative bacteria, its mode of action involving metal homeostasis and outer membrane disruption, and resistance mechanisms across multiple species.

This study analyzes diatom diversity and abundance in the global ocean using Tara Oceans data, identifying key environmental drivers and community patterns.

The paper maps antibiotic cross-resistance and collateral sensitivity interactions using chemical genetic data and validates findings experimentally.

This study shows that fecal microbial load, not disease, is the main driver of gut microbiome changes and identifies it as a major confounder in microbiome studies.

The paper constructs a global microbial small ORFs catalogue and identifies a tool for annotating small proteins in microbial genomes.

The paper refines enterotypes in global fecal metagenomes using fuzzy clustering and introduces an Enterotype Dysbiosis Score to assess disease associations.

The paper uses machine learning to predict antimicrobial peptides from microbiome data, identifies novel peptides, and validates their antibacterial activity against drug-resistant pathogens.

The paper shows how species in gut bacterial communities can survive or go extinct based on resource availability and metabolic interactions, identifying emergent survival and community-driven extinctions.

The paper identifies four stable fungal enterotypes in the human gut mycobiome, showing age preference and disease associations.

The paper uses long-read sequencing to show that most gut phages are methylated, with many encoding their own methyltransferases, suggesting methylation helps phages evade host defenses.

The paper uses multiomics and quantitative modeling to determine how diet, host, and microbiota contribute to the host metabolome in gnotobiotic mice.

The paper develops a method combining phage enrichment and long-read sequencing to recover more complete gut phage genomes from fecal samples, identifying a megabase phage and revealing hidden diversity.

The paper identifies 18 cell types in sponges, including neuroid cells with synaptic gene expression, suggesting early neuro-immune system evolution.

Rebuilt on eggNOG v5, eggNOG-mapper v2 raises average annotation rate by 608% over v1 and adds Prodigal gene calling, pairwise ortholog reports, and PFAM/SMART domain prediction.

GUNC detects and quantifies chimerism in prokaryotic genomes by analyzing contig lineage homogeneity, improving genome quality.

This paper introduces Swarm Learning, a decentralized machine learning approach for disease classification using transcriptomic data, demonstrating its effectiveness in developing classifiers for COVID-19, tuberculosis, and leukemias while preserving privacy.

The paper introduces mOTUs3, a tool for reference genome-independent taxonomic profiling of metagenomes, improving accuracy and coverage for underexplored microbiomes.

The paper introduces SIAMCAT, a machine-learning toolbox for metagenomics analysis, showing it can identify disease-specific and shared biomarkers across studies.