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In silico typing maps the natural diversity of Escherichia coli transporter-dependent capsules

Abstract:
Serotyping identifies bacterial variants based on surface antigens, traditionally using antibody-based assays, but has been increasingly replaced by in silico methods that infer serotypes from genomic sequences for faster, scalable and more reproducible analyses. However, traditional Escherichia coli capsule serotyping has largely fallen out of use since the 1990s, leaving gaps in our knowledge of capsule genetics, diversity, distribution and epidemiology. As capsules influence bacterial interactions with phages, host immune systems and the environment, this gap limits our understanding of E. coli ecology and pathogenicity as well as vaccine and diagnostic development. Here we established a definitive genotype–serotype map for 35 serologically identified and structurally characterized transporter-dependent capsules. We then surveyed 37,723 E. coli genomes, cataloguing 85 transporter-dependent capsule types (K-types), including 55 types that were not part of the reference collection. We leveraged this catalogue to develop a hidden Markov model-based in silico serotyping tool, kTYPr, and applied it to curated sets of 24,015 E. coli genomes and 2,762 metagenome-assembled genomes spanning diverse environmental and clinical sources. We found previously uncharacterized K-types enriched in undersampled environments and associated with E. coli disease. This study expands our understanding of E. coli surface structures, supporting efforts for precision targeting with phage therapy or vaccines.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1038/s41564-026-02323-5

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Role:
Author
ORCID:
0000-0002-1542-5912
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Role:
Author
ORCID:
0000-0001-8239-0353
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Role:
Author
ORCID:
0009-0004-0660-4283
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Role:
Author
ORCID:
0000-0003-4777-2916


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Funder identifier:
https://ror.org/033ztm745


Publisher:
Nature Research
Journal:
Nature Microbiology More from this journal
Volume:
11
Issue:
5
Pages:
1217-1232
Publication date:
2026-04-23
Acceptance date:
2026-03-13
DOI:
EISSN:
2058-5276
ISSN:
2058-5276


Language:
English
Keywords:
Source identifiers:
4042883
Deposit date:
2026-05-13
ARK identifier:
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