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| Home > Publications database > Metagenome-informed metaproteomics of the human gut microbiome, host, and dietary exposome uncovers signatures of health and inflammatory bowel disease. > print |
| 001 | 298168 | ||
| 005 | 20250224105400.0 | ||
| 024 | 7 | _ | |a 10.1016/j.cell.2024.12.016 |2 doi |
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| 041 | _ | _ | |a English |
| 082 | _ | _ | |a 610 |
| 100 | 1 | _ | |a Valdés-Mas, Rafael |b 0 |
| 245 | _ | _ | |a Metagenome-informed metaproteomics of the human gut microbiome, host, and dietary exposome uncovers signatures of health and inflammatory bowel disease. |
| 260 | _ | _ | |a [Cambridge, Mass.] |c 2025 |b Cell Press |
| 336 | 7 | _ | |a article |2 DRIVER |
| 336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
| 336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1740390794_28160 |2 PUB:(DE-HGF) |
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| 336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
| 500 | _ | _ | |a #LA:D480# / 2025 Feb 20;188(4):1062-1083.e36 |
| 520 | _ | _ | |a Host-microbiome-dietary interactions play crucial roles in regulating human health, yet their direct functional assessment remains challenging. We adopted metagenome-informed metaproteomics (MIM), in mice and humans, to non-invasively explore species-level microbiome-host interactions during commensal and pathogen colonization, nutritional modification, and antibiotic-induced perturbation. Simultaneously, fecal MIM accurately characterized the nutritional exposure landscape in multiple clinical and dietary contexts. Implementation of MIM in murine auto-inflammation and in human inflammatory bowel disease (IBD) characterized a 'compositional dysbiosis' and a concomitant species-specific 'functional dysbiosis' driven by suppressed commensal responses to inflammatory host signals. Microbiome transfers unraveled early-onset kinetics of these host-commensal cross-responsive patterns, while predictive analyses identified candidate fecal host-microbiome IBD biomarker protein pairs outperforming S100A8/S100A9 (calprotectin). Importantly, a simultaneous fecal nutritional MIM assessment enabled the determination of IBD-related consumption patterns, dietary treatment compliance, and small intestinal digestive aberrations. Collectively, a parallelized dietary-bacterial-host MIM assessment functionally uncovers trans-kingdom interactomes shaping gastrointestinal ecology while offering personalized diagnostic and therapeutic insights into microbiome-associated disease. |
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| 650 | _ | 7 | |a biomarker |2 Other |
| 650 | _ | 7 | |a diet |2 Other |
| 650 | _ | 7 | |a inflammatory bowel disease |2 Other |
| 650 | _ | 7 | |a metagenome-informed metaproteomics |2 Other |
| 650 | _ | 7 | |a microbiome |2 Other |
| 700 | 1 | _ | |a Leshem, Avner |b 1 |
| 700 | 1 | _ | |a Zheng, Danping |b 2 |
| 700 | 1 | _ | |a Cohen, Yotam |b 3 |
| 700 | 1 | _ | |a Kern, Lara |b 4 |
| 700 | 1 | _ | |a Zmora, Niv |b 5 |
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| 700 | 1 | _ | |a Katina, Corine |b 7 |
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| 700 | 1 | _ | |a Slamovitz, Fernando |b 17 |
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| 700 | 1 | _ | |a Mor, Uria |b 20 |
| 700 | 1 | _ | |a Dori-Bachash, Mally |b 21 |
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| 700 | 1 | _ | |a Levin, Yishai |b 23 |
| 700 | 1 | _ | |a Atarashi, Koji |b 24 |
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| 700 | 1 | _ | |a Harmelin, Alon |b 27 |
| 700 | 1 | _ | |a Stettner, Noa |b 28 |
| 700 | 1 | _ | |a Chen, Minhu |b 29 |
| 700 | 1 | _ | |a Suez, Jotham |b 30 |
| 700 | 1 | _ | |a Honda, Kenya |b 31 |
| 700 | 1 | _ | |a Lieb, Wolfgang |b 32 |
| 700 | 1 | _ | |a Bang, Corinna |b 33 |
| 700 | 1 | _ | |a Kori, Michal |b 34 |
| 700 | 1 | _ | |a Maharshak, Nitsan |b 35 |
| 700 | 1 | _ | |a Merbl, Yifat |b 36 |
| 700 | 1 | _ | |a Shibolet, Oren |b 37 |
| 700 | 1 | _ | |a Halpern, Zamir |b 38 |
| 700 | 1 | _ | |a Shouval, Dror S |b 39 |
| 700 | 1 | _ | |a Shamir, Raanan |b 40 |
| 700 | 1 | _ | |a Franke, Andre |b 41 |
| 700 | 1 | _ | |a Abdeen, Suhaib K |b 42 |
| 700 | 1 | _ | |a Shapiro, Hagit |b 43 |
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| 700 | 1 | _ | |a Elinav, Eran |0 P:(DE-He78)725ad944da4e1ea60389fe9dbbed2c7c |b 45 |e Last author |u dkfz |
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