m+Medelevator.RU
← Поиск публикаций
bioRxiv : the preprint server for biology · 2026

AllTheBacteria: a community resource empowers biology and discovers novel peptide antibiotics.

СтатьяПрепринтНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Hunt Martin, Torres Marcelo D T, Alikhan Nabil-Fareed, Anderson Daniel, Andreani Maria Luiza, Blom Josefin, Bouras George, Brinkman Fiona S L, Carroll Laura M, Croxen Matthew A, Floto R Andres, Hall Michael B, Hawkey Jane, Horsfield Samuel T, Jia Baofeng, Lacey Jake A, Lee Hyun-Su, Lima Leandro, MacAlasdair Neil, Mallawaarachchi Sudaraka, Matlock William, Moustafa Ahmed M, Petit Robert, Ramnath Vignesh, Raghuram Vishnu, Russell Matthew J, Sanderson Theo, Saratto Timo, Schwengers Oliver, Seemann Torsten, Shaw Liam P, Shen Wei, Thomson Nicholas, Tonkin-Hill Gerry, Toussaint Jackie, Viet Thanh Le, von Wachsmann Johanna, Wan Fangping, Weimann Aaron, Wheatley Rachel M, Wiatrak Maciej, Xie Ouli, de la Fuente-Nunez Cesar, Lees John A, Iqbal Zamin

Аннотация

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 uniformly assembled, quality controlled, annotated or searchable at scale. Here we present AllTheBacteria, an open, community-built resource that transforms public bacterial short-read whole-genome sequencing reads into a uniformly processed discovery platform. The current analysed release contains 2,440,377 high-quality bacterial and archaeal genomes from 11,273 species, together with standardized taxonomic assignments, genome annotations, antimicrobial resistance calls, antiphage-defence annotations, protein structure predictions and AI-ready sequence tables. We show that this infrastructure enables applications that would otherwise be impractical, from global sequence search and outbreak contextualization to pangenome method development, antimicrobial resistance reservoir mapping and antiphage-defence ecology. As a stringent experimental demonstration, we mined 3,919,096 encrypted peptide fragments from AllTheBacteria proteomes using our deep learning model APEX 1.1, identifying 1,867 candidates with predicted antimicrobial activity. We synthesized 24 representative peptides and tested them against 20 clinically relevant bacterial strains, including antibiotic-resistant pathogens. Multiple peptides showed low-micromolar activity, membrane-responsive conformational transitions and selective envelope perturbation. A lead molecule, ATB20, reduced Acinetobacter baumannii burden in a murine skin abscess model with efficacy comparable to polymyxin B and no overt toxicity. Together, these results establish AllTheBacteria as both a foundational community resource for microbiology and a renewable engine for AI-guided antimicrobial discovery.

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты