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Quantifying dynamic host‐microbiota signatures of antibiotic‐associated GI infection: What can the host proteome tell us?
Author(s) -
Elias Joshua,
Lichtman Joshua,
Sonnenburg Justin
Publication year - 2015
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.29.1_supplement.575.21
Subject(s) - proteome , host (biology) , biology , microbiology and biotechnology , gut flora , antibiotics , microbiome , clostridium difficile , computational biology , immunology , bioinformatics , genetics
OBJECTIVE Quantify and compare the interactions between resident gastrointestinal (GI) microbiota and host proteins shed into the gut lumen under conditions of antibiotic‐induced infection. METHODS Using mouse models of antibiotic‐associated Salmonella typhimurium and Clostridium difficile infection, we conducted mass spectrometry‐based host‐centric surveys of stool proteins, and microbial community profiling in parallel. Time course profiles allowed us to compare the rates and extents of perturbation and recovery of both microbiota and host proteomes following the administration of two antibiotics, with or without concurrent infection with the enteric pathogens. The influence of fecal transplant on recovery profiles was determined. The resulting pathological proteome and microbiome signatures were further compared with a chemically‐induced colitis model. RESULTS By assessing the protein component of the intestinal mileau contributed by the host in diverse perturbed states, we identified differentiating proteomic signatures that allowed us to stratify recovery states that were not evident through microbe enumeration alone. CONCLUSIONS We conclude that the host‐derived intestinal proteome provides an important route towards discovering mechanisms by which host epithelia shape, and are shaped by changes in the commensal microbiota. This work was supported in part by the Stanford Digestive Disease Center (JEE), the NSF GRFP Fellowship (JSL), and NIH grant (R01‐DK085025)