The analysis presented in this Brief Communication shows that, despite their complexity, current deep learning models do not outperform linear baselines in predicting gene perturbation effects, thus e...

Unified bacterial strain taxonomies are needed for coherent communication of findings in microbiological research. This Essay provides an overview of a novel bacterial strain taxonomy and describes ho...

Public microbial genomes encode an immense record of biological diversity, evolution and molecular function, but much of this information remains difficult to reuse because raw sequencing data are not...

ALT: Muppet Doctor Gives Thumbs Up

Nature Microbiology, Published online: 22 June 2026; doi:10.1038/s41564-026-02390-8The microbiome plays a significant yet underexplored role in antimicrobial resistance by influencing ecological and evolutionary processes. This Perspective proposes a framework to integrate microbiome–AMR interactions into predictive models while highlighting key mechanisms and data gaps to improve resistance understanding and interventions.

Background Urinary tract infections (UTIs) represent a major public health concern, increasingly complicated by rising antibiotic resistance, diminishing treatment efficacy, and increasing prevalence ...

Sequencing-based wastewater surveillance is emerging as an important tool in pathogen-agnostic threat detection, potentially enabling early identification before capture through clinical surveillance ...

Background Single cell genomics has revolutionized microbial sequencing, but complete coverage of genomes in complex microbiomes is imperfect due to enormous variation in organismal abundance and amplification bias. Empirical methods that complement rapidly improving bioinformatic tools will improve characterization of microbiomes and facilitate better genome coverage for low abundance microbes. Methods We describe a new approach to sequencing individual species from microbiomes that combines antibody phage display against intact bacteria with fluorescence activated cell sorting (FACS). Single chain (scFv) antibodies are selected using phage display against a bacteria or microbial community, resulting in species-specific antibodies that can be used in FACS for relative quantification of an organism in a community, as well as enrichment or depletion prior to genome sequencing. Results We selected antibodies against Lactobacillus acidophilus and demonstrate a FACS-based approach for identification and enrichment of the organism from both laboratory-cultured and commercially derived bacterial mixtures. The ability to selectively enrich for L. acidophilus when it is present at a very low abundance (<0.2%) leads to complete (>99.8%) de novo genome coverage whereas the standard single-cell sequencing approach is incomplete (<68%). We show that specific antibodies can be selected against L. acidophilus when the monoculture is used as antigen as well as when a community of 10 closely related species is used demonstrating that in principal antibodies can be generated against individual organisms within microbial communities. Conclusions The approach presented here demonstrates that phage-selected antibodies against bacteria enable identification, enrichment of rare species, and depletion of abundant organisms making it tractable to virtually any microbe or microbial community. Combining antibody specificity with FACS provides a new approach for characterizing and manipulating microbial communities prior to genome sequencing.

Interactive exploration of large phylogenetic trees

Inactivation of chromosomal genes through plasmid-encoded IS elements is an extended mechanism of antimicrobial resistance evolution in bacteria.

Sequencing-based surveillance can enable rapid and sensitive detection of environmental pathogens. The Oslofjord inlet is relatively narrow and is exposed to substantial human activity, including occa...

Changelog SeqKit is 10 years old! SeqKit v2.13.0 - 2026-02-28 seqkit: add support for reading and writing LZ4 compression format. new command: seqkit sample2: improved seqkit sample by @stahiga....