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doi:10.22028/D291-47919 | Titel: | Decoding the diagnostic and therapeutic potential of microbiota using pan-body pan-disease microbiomics |
| VerfasserIn: | Schmartz, Georges P Rehner, Jacqueline Gund, Madline P Keller, Verena Molano, Leidy-Alejandra G Rupf, Stefan Hannig, Matthias Berger, Tim Flockerzi, Elias Seitz, Berthold Fleser, Sara Schmitt-Grohé, Sabina Kalefack, Sandra Zemlin, Michael Kunz, Michael Götzinger, Felix Gevaerd, Caroline Vogt, Thomas Reichrath, Jörg Diehl, Lisa Hecksteden, Anne Meyer, Tim Herr, Christian Gurevich, Aleksei Krug, Daniel Hegemann, Julian Bozhueyuek, Kenan Gulder, Tobias A M Fu, Chengzhang Beemelmanns, Christine Schattenberg, Jörn M Kalinina, Olga V Becker, Anouck Unger, Marcus Ludwig, Nicole Seibert, Martina Stein, Marie-Louise Hanna, Nikolas Loka Martin, Marie-Christin Mahfoud, Felix Krawczyk, Marcin Becker, Sören L Müller, Rolf Bals, Robert Keller, Andreas |
| Sprache: | Englisch |
| Titel: | Nature communications |
| Bandnummer: | 15 |
| Heft: | 1 |
| Verlag/Plattform: | Springer Nature |
| Erscheinungsjahr: | 2024 |
| DDC-Sachgruppe: | 004 Informatik |
| Dokumenttyp: | Konferenzbeitrag (in einem Konferenzband / InProceedings erschienener Beitrag) |
| 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. |
| DOI der Erstveröffentlichung: | 10.1038/s41467-024-52598-7 |
| URL der Erstveröffentlichung: | https://www.nature.com/articles/s41467-024-52598-7 |
| Link zu diesem Datensatz: | urn:nbn:de:bsz:291--ds-479194 hdl:20.500.11880/41924 http://dx.doi.org/10.22028/D291-47919 |
| ISSN: | 2041-1723 |
| Datum des Eintrags: | 28-Mai-2026 |
| Fakultät: | MI - Fakultät für Mathematik und Informatik |
| Fachrichtung: | MI - Informatik |
| Professur: | MI - Jun.-Prof. Alexey Gurevich |
| Sammlung: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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