Dietary protein source strongly alters gut microbiota composition and function.

The source of protein in a persons diet affects their total life expectancy. However, the mechanisms by which dietary protein sources differentially impact human health and life expectancy are poorly understood. Dietary choices have major impacts on the composition and function of the intestinal microbiota that ultimately mediate host health. This raises the possibility that health outcomes based on dietary protein sources might be driven by interactions between dietary protein and the gut microbiota. In this study, we determine the effects of seven different sources of dietary protein on the gut microbiota in mice. We apply an integrated metagenomics-metaproteomics approach to simultaneously investigate the effects of these dietary protein sources on the gut microbiotas composition and function. The protein abundances measured by metaproteomics can provide microbial species abundances, and evidence for the phenotype of microbiota members on the molecular level because measured proteins allow us to infer the metabolic and physiological processes used by a microbial community. We showed that dietary protein source significantly altered the species composition and overall function of the gut microbiota. Different dietary protein sources led to changes in the abundance of microbial amino acid degrading proteins and proteins involved in the degradation of glycosylations on dietary protein. In particular, brown rice and egg white protein increased the abundance of amino acid degrading enzymes and egg white protein increased the abundance of bacteria and proteins usually associated with the degradation of the intestinal mucus barrier. These results show that dietary protein source can change the gut microbiotas metabolism, which could have major implications in the context of gut microbiota mediated diseases.

Considerations for constructing a protein sequence database for metaproteomics.

Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.

Morphine and high-fat diet differentially alter the gut microbiota composition and metabolic function in lean versus obese mice.

There are known associations between opioids, obesity, and the gut microbiome, but the molecular connection/mediation of these relationships is not understood. To better clarify the interplay of physiological, genetic, and microbial factors, this study investigated the microbiome and host inflammatory responses to chronic opioid administration in genetically obese, diet-induced obese, and lean mice. Samples of feces, urine, colon tissue, and plasma were analyzed using targeted LC-MS/MS quantification of metabolites, immunoassays of inflammatory cytokine levels, genome-resolved metagenomics, and metaproteomics. Genetic obesity, diet-induced obesity, and morphine treatment in lean mice each showed increases in distinct inflammatory cytokines. Metagenomic assembly and binning uncovered over 400 novel gut bacterial genomes and species. Morphine administration impacted the microbiome's composition and function, with the strongest effect observed in lean mice. This microbiome effect was less pronounced than either diet or genetically driven obesity. Based on inferred microbial physiology from the metaproteome datasets, a high-fat diet transitioned constituent microbes away from harvesting diet-derived nutrients and towards nutrients present in the host mucosal layer. Considered together, these results identified novel host-dependent phenotypes, differentiated the effects of genetic obesity versus diet induced obesity on gut microbiome composition and function, and showed that chronic morphine administration altered the gut microbiome.

Metaproteomics reveals persistent and phylum-redundant metabolic functional stability in adult human gut microbiomes of Crohn's remission patients despite temporal variations in microbial taxa, genomes, and proteomes.

BACKGROUND: The gut microbiome plays a fundamental role in the human host's overall health by contributing key biological functions such as expanded metabolism and pathogen defense/immune control. In a healthy individual, the gut microbiome co-exists within the human host in a symbiotic, non-inflammatory relationship that enables mutual benefits, such as microbial degradation of indigestible food products into small molecules that the host can utilize, and enhanced pathogen defense. In abnormal conditions, such as Crohn's disease, this favorable metabolic relationship breaks down and a variety of undesirable activities result, including chronic inflammation and other health-related issues. It has been difficult, however, to elucidate the overall functional characteristics of this relationship because the microbiota can vary substantially in composition for healthy humans and possibly even more in individuals with gut disease conditions such as Crohn's disease. Overall, this suggests that microbial membership composition may not be the best way to characterize a phenotype. Alternatively, it seems to be more informative to examine and characterize the functional composition of a gut microbiome. Towards that end, this study examines 25 metaproteomes measured in several Crohn's disease patients' post-resection surgery across the course of 1 year, in order to examine persistence of microbial taxa, genes, proteins, and metabolic functional distributions across time in individuals whose microbiome might be more variable due to the gut disease condition. RESULTS: The measured metaproteomes were highly personalized, with all the temporally-related metaproteomes clustering most closely by individual. In general, the metaproteomes were remarkably distinct between individuals and to a lesser extent within individuals. This prompted a need to characterize the metaproteome at a higher functional level, which was achieved by annotating identified protein groups with KEGG orthologous groups to infer metabolic modules. At this level, similar and redundant metabolic functions across multiple phyla were observed across time and between individuals. Tracking through these various metabolic modules revealed a clear path from carbohydrate, lipid, and amino acid degradation to central metabolism and finally the production of fermentation products. CONCLUSIONS: The human gut metaproteome can vary quite substantially across time and individuals. However, despite substantial intra-individual variation in the metaproteomes, there is a clear persistence of conserved metabolic functions across time and individuals. Additionally, the persistence of these core functions is redundant across multiple phyla but is not always observable in the same sample. Finally, the gut microbiome's metabolism is not driven by a set of discrete linear pathways but a web of interconnected reactions facilitated by a network of enzymes that connect multiple molecules across multiple pathways.