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Decoding the diagnostic and therapeutic potential of microbiota using pan-body pan-disease microbiomics

Authors :
Georges P. Schmartz
Jacqueline Rehner
Madline P. Gund
Verena Keller
Leidy-Alejandra G. Molano
Stefan Rupf
Matthias Hannig
Tim Berger
Elias Flockerzi
Berthold Seitz
Sara Fleser
Sabina Schmitt-Grohé
Sandra Kalefack
Michael Zemlin
Michael Kunz
Felix Götzinger
Caroline Gevaerd
Thomas Vogt
Jörg Reichrath
Lisa Diehl
Anne Hecksteden
Tim Meyer
Christian Herr
Alexey Gurevich
Daniel Krug
Julian Hegemann
Kenan Bozhueyuek
Tobias A. M. Gulder
Chengzhang Fu
Christine Beemelmanns
Jörn M. Schattenberg
Olga V. Kalinina
Anouck Becker
Marcus Unger
Nicole Ludwig
Martina Seibert
Marie-Louise Stein
Nikolas Loka Hanna
Marie-Christin Martin
Felix Mahfoud
Marcin Krawczyk
Sören L. Becker
Rolf Müller
Robert Bals
Andreas Keller
Source :
Nature Communications, Vol 15, Iss 1, Pp 1-13 (2024)
Publication Year :
2024
Publisher :
Nature Portfolio, 2024.

Abstract

Abstract The human microbiome emerges as a promising reservoir for diagnostic markers and therapeutics. Since host-associated microbiomes at various body sites differ and diseases do not occur in isolation, a comprehensive analysis strategy highlighting the full potential of microbiomes should include diverse specimen types and various diseases. To ensure robust data quality and comparability across specimen types and diseases, we employ standardized protocols to generate sequencing data from 1931 prospectively collected specimens, including from saliva, plaque, skin, throat, eye, and stool, with an average sequencing depth of 5.3 gigabases. Collected from 515 patients, these samples yield an average of 3.7 metagenomes per patient. Our results suggest significant microbial variations across diseases and specimen types, including unexpected anatomical sites. We identify 583 unexplored species-level genome bins (SGBs) of which 189 are significantly disease-associated. Of note, the existence of microbial resistance genes in one specimen was indicative of the same resistance genes in other specimens of the same patient. Annotated and previously undescribed SGBs collectively harbor 28,315 potential biosynthetic gene clusters (BGCs), with 1050 significant correlations to diseases. Our combinatorial approach identifies distinct SGBs and BGCs, emphasizing the value of pan-body pan-disease microbiomics as a source for diagnostic and therapeutic strategies.

Subjects

Subjects :
Science

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
edsdoj.bb47b78b5394a2ca2f41acd3fc0cf2a
Document Type :
article
Full Text :
https://doi.org/10.1038/s41467-024-52598-7