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

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.

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Publication Details

Journal
Nature Communications
Published
2024-09-26
DOI
https://doi.org/10.1038/s41467-024-52598-7
Citations
16
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
3.74
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article

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

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16 citations
Nature Communications
Gut microbiota and health
3.74
article

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

Anne Hecksteden, Felix Götzinger, Verena Keller, Tim Berger, Marcin Krawczyk, Andreas Keller, Jacqueline Rehner, Felix Mahfoud, Alexey Gurevich, Tobias A. M. Gulder, Nicole Ludwig, Georges P Schmartz, Chengzhang Fu, Anouck Becker, Martina Seibert, Michael Kunz, Julian D. Hegemann, Sabina Schmitt‐Grohé, Leidy-Alejandra G Molano, Tim Meyer, Robert Bals, Daniel Krug, Marcus M. Unger, Stefan Rupf, Michael Zemlin, Christian Herr, Sören L. Becker, Elias Flockerzi, Sara Fleser, Lisa Diehl, Christine Beemelmanns, Rolf Müller, Madline P. Gund, Berthold Seitz, Jörn M. Schattenberg, Thomas Vogt, Olga V. Kalinina, Sandra Kalefack, Caroline Gevaerd, Kenan A. J. Bozhueyuek, Jörg Reichrath, N. Hanna, Marie-Christin Martin, Matthias Hannig, Marie-Louise Stein
article en
16 citations

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.

Nature CommunicationsVol. 15(1)
Innsbruck Medical University (AT), Institut für Sozialforschung und Sozialwirtschaft (DE), University Dermatology (US), Institute of Medical Microbiology and Hygiene (DE), Helmholtz Institute for Pharmaceutical Research Saarland (DE), Université franco-allemande (DE), Saarland University (DE)
Openalex Percentile: Top 6%
Gut microbiota and health
3.74
DOIOpen Access PDFOpenAlex
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