Decoding the diagnostic and therapeutic potential of microbiota using pan-body pan-disease microbiomics
| Title: | 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) |
| Publisher Information: | Nature Portfolio, 2024. |
| Publication Year: | 2024 |
| Collection: | LCC:Science |
| Subject Terms: | Science |
| Description: | 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. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2041-1723 |
| Relation: | https://doaj.org/toc/2041-1723 |
| DOI: | 10.1038/s41467-024-52598-7 |
| Access URL: | https://doaj.org/article/ebb47b78b5394a2ca2f41acd3fc0cf2a |
| Accession Number: | edsdoj.bb47b78b5394a2ca2f41acd3fc0cf2a |
| Database: | Directory of Open Access Journals |