A Multi-Omic View of Host-Pathogen-Commensal Interplay in Salmonella-Mediated Intestinal Infection

Abstract

The potential for commensal microorganisms indigenous to a host (the ‘microbiome’ or ‘microbiota’) to alter infection outcome by influencing host-pathogen interplay is largely unknown. We used a multi-omics “systems” approach, incorporating proteomics, metabolomics, glycomics, and metagenomics, to explore the molecular interplay between the murine host, the pathogen Salmonella enterica serovar Typhimurium (S. Typhimurium), and commensal gut microorganisms during intestinal infection with S. Typhimurium. We find proteomic evidence that S. Typhimurium thrives within the infected 129/SvJ mouse gut without antibiotic pre-treatment, inducing inflammation and disrupting the intestinal microbiome (e.g., suppressing Bacteroidetes and Firmicutes while promoting growth of Salmonella and Enterococcus). Alteration of the host microbiome population structure was highly correlated with gut environmental changes, including the accumulation of metabolites normally consumed by commensal microbiota. Finally, the less characterized phase of S. Typhimurium’s lifecycle was investigated, and both proteomic and glycomic evidence suggests S. Typhimurium may take advantage of increased fucose moieties to metabolize fucose while growing in the gut. The application of multiple omics measurements to Salmonella-induced intestinal inflammation provides insights into complex molecular strategies employed during pathogenesis between host, pathogen, and the microbiome.

Phosphate-Containing Polyethylene Glycol Polymers Prevent Lethal Sepsis by Multidrug-Resistant Pathogens

“…The appearance of pathogenic species was not only related to those injected into the cecum (i.e., MPC) but also to other pathogenic species, like Chronobacter, Enterobacter, E. coli, Salmonella, and Shigella (see Table S2). This effect of the introduction of a pathogenic species uncovering the presence of otherwise-undetect-able other pathogens has been recently described (21). As such, Pi-PEG 15-20 not only prevented colonization of the introduced pathogen community (MPC), but it also suppressed propagation of opportunistic pathogen members of the commensal microflora.…”

“…For all analyses, data acquisition occurred over an m/z range of 400 to 2,000. Raw spectra were searched with MS-GFϩ (20) against a mouse gut commensal metagenome sequence (21), and peptide results were filtered using the MS-GFϩ SpecProb value of Յ1 ϫ 10 Ϫ11 (false-discovery rate, 2.6%). Peptide observation counts and spectral counts were calculated using Microsoft Access, and principal component analysis (PCA) plots were generated using the software Inferno (http://code.google.com/p/inferno4 proteomics/wiki/Introduction).…”

Salmonella Serotype Determination Utilizing High-Throughput Genome Sequencing Data

“…Mouse infections, feces sample preparation, and metagenome sequencing. Mouse infections, feces sample preparation, and DNA extraction were performed as previously described (25). S. enterica serotype Typhimurium strain 14028s was used to orally challenge female, agematched (6-to-8-week-old) 129SvJ mice (25).…”

“…Mouse infections, feces sample preparation, and DNA extraction were performed as previously described (25). S. enterica serotype Typhimurium strain 14028s was used to orally challenge female, agematched (6-to-8-week-old) 129SvJ mice (25). Fecal samples from control mice had not been sequenced and were not available for the current study.…”

A Delicate Balance: Maintaining Mutualism to Prevent Disease

“…Recent studies point to the complex interplay between diet, community complexity, and host immunity in maintaining GI tract microbial homeostasis (Turnbaugh et al, 2009; Jernberg et al, 2007; Deatherage Kaiser et al, 2013). Not surprisingly, diet is an important factor in determining GI community composition.…”