Roadmap to functional characterization of the human intestinal microbiota in its interaction with the host.

It is known for more than 100 years that the intestinal microbes are important for the host's health and the last decade this is being intensely studied with a focus on the mechanistic aspects. Among the fundamental functions of the intestinal microbiome are the priming of the immune system, the production of essential vitamins and the energy harvest from foods. By now, several dozens of diseases, both intestinal and non-intestinal related, have been associated with the intestinal microbiome. Initially, this was based on the description of the composition between groups of different health status or treatment arms based on phylogenetic approaches based on the 16S rRNA gene sequences. This way of analysis has mostly moved to the analysis of all the genes or transcripts of the microbiome i.e. metagenomics and meta-transcriptomics. Differences are regularly found but these have to be taken with caution as we still do not know what the majority of genes of the intestinal microbiome are capable of doing. To circumvent this caveat researchers are studying the proteins and the metabolites of the microbiome and the host via metaproteomics and metabolomics approaches. However, also here the complexity is high and only a fraction of signals obtained with high throughput instruments can be identified and assigned to a known protein or molecule. Therefore, modern microbiome research needs advancement of existing and development of new analytical techniques. The usage of model systems like intestinal organoids where samples can be taken and processed rapidly as well as microfluidics systems may help. This review aims to elucidate what we know about the functionality of the human intestinal microbiome, what technologies are advancing this knowledge, and what innovations are still required to further evolve this actively developing field.

Survey of metaproteomics software tools for functional microbiome analysis.

To gain a thorough appreciation of microbiome dynamics, researchers characterize the functional relevance of expressed microbial genes or proteins. This can be accomplished through metaproteomics, which characterizes the protein expression of microbiomes. Several software tools exist for analyzing microbiomes at the functional level by measuring their combined proteome-level response to environmental perturbations. In this survey, we explore the performance of six available tools, to enable researchers to make informed decisions regarding software choice based on their research goals. Tandem mass spectrometry-based proteomic data obtained from dental caries plaque samples grown with and without sucrose in paired biofilm reactors were used as representative data for this evaluation. Microbial peptides from one sample pair were identified by the X! tandem search algorithm via SearchGUI and subjected to functional analysis using software tools including eggNOG-mapper, MEGAN5, MetaGOmics, MetaProteomeAnalyzer (MPA), ProPHAnE, and Unipept to generate functional annotation through Gene Ontology (GO) terms. Among these software tools, notable differences in functional annotation were detected after comparing differentially expressed protein functional groups. Based on the generated GO terms of these tools we performed a peptide-level comparison to evaluate the quality of their functional annotations. A BLAST analysis against the NCBI non-redundant database revealed that the sensitivity and specificity of functional annotation varied between tools. For example, eggNOG-mapper mapped to the most number of GO terms, while Unipept generated more accurate GO terms. Based on our evaluation, metaproteomics researchers can choose the software according to their analytical needs and developers can use the resulting feedback to further optimize their algorithms. To make more of these tools accessible via scalable metaproteomics workflows, eggNOG-mapper and Unipept 4.0 were incorporated into the Galaxy platform.

Disseminating Metaproteomic Informatics Capabilities and Knowledge Using the Galaxy-P Framework.

The impact of microbial communities, also known as the microbiome, on human health and the environment is receiving increased attention. Studying translated gene products (proteins) and comparing metaproteomic profiles may elucidate how microbiomes respond to specific environmental stimuli, and interact with host organisms. Characterizing proteins expressed by a complex microbiome and interpreting their functional signature requires sophisticated informatics tools and workflows tailored to metaproteomics. Additionally, there is a need to disseminate these informatics resources to researchers undertaking metaproteomic studies, who could use them to make new and important discoveries in microbiome research. The Galaxy for proteomics platform (Galaxy-P) offers an open source, web-based bioinformatics platform for disseminating metaproteomics software and workflows. Within this platform, we have developed easily-accessible and documented metaproteomic software tools and workflows aimed at training researchers in their operation and disseminating the tools for more widespread use. The modular workflows encompass the core requirements of metaproteomic informatics: (a) database generation; (b) peptide spectral matching; (c) taxonomic analysis and (d) functional analysis. Much of the software available via the Galaxy-P platform was selected, packaged and deployed through an online metaproteomics "Contribution Fest" undertaken by a unique consortium of expert software developers and users from the metaproteomics research community, who have co-authored this manuscript. These resources are documented on GitHub and freely available through the Galaxy Toolshed, as well as a publicly accessible metaproteomics gateway Galaxy instance. These documented workflows are well suited for the training of novice metaproteomics researchers, through online resources such as the Galaxy Training Network, as well as hands-on training workshops. Here, we describe the metaproteomics tools available within these Galaxy-based resources, as well as the process by which they were selected and implemented in our community-based work. We hope this description will increase access to and utilization of metaproteomics tools, as well as offer a framework for continued community-based development and dissemination of cutting edge metaproteomics software.

Faecal Metaproteomic Analysis Reveals a Personalized and Stable Functional Microbiome and Limited Effects of a Probiotic Intervention in Adults.

Recent metagenomic studies have demonstrated that the overall functional potential of the intestinal microbiome is rather conserved between healthy individuals. Here we assessed the biological processes undertaken in-vivo by microbes and the host in the intestinal tract by conducting a metaproteome analysis from a total of 48 faecal samples of 16 healthy adults participating in a placebo-controlled probiotic intervention trial. Half of the subjects received placebo and the other half consumed Lactobacillus rhamnosus GG for three weeks (1010 cfu per day). Faecal samples were collected just before and at the end of the consumption phase as well as after a three-week follow-up period, and were processed for microbial composition and metaproteome analysis. A common core of shared microbial protein functions could be identified in all subjects. Furthermore, we observed marked differences in expressed proteins between subjects that resulted in the definition of a stable and personalized microbiome both at the mass-spectrometry-based proteome level and the functional level based on the KEGG pathway analysis. No significant changes in the metaproteome were attributable to the probiotic intervention. A detailed taxonomic assignment of peptides and comparison to phylogenetic microarray data made it possible to evaluate the activity of the main phyla as well as key species, including Faecalibacterium prausnitzii. Several correlations were identified between human and bacterial proteins. Proteins of the human host accounted for approximately 14% of the identified metaproteome and displayed variations both between and within individuals. The individually different human intestinal proteomes point to personalized host-microbiota interactions. Our findings indicate that analysis of the intestinal metaproteome can complement gene-based analysis and contributes to a thorough understanding of the activities of the microbiome and the relevant pathways in health and disease.

Colonic metaproteomic signatures of active bacteria and the host in obesity.

Obesity is associated with the intestinal microbiota in humans but the underlying mechanisms are yet to be fully understood. Our previous phylogenetic study showed that the faecal microbiota profiles of nonobese versus obese and morbidly obese individuals differed. Here, we have extended this analysis with a characterization of the faecal metaproteome, in order to detect differences at a functional level. Proteins were extracted from crude faecal samples of 29 subjects, separated by 1D gel electrophoresis and characterized using RP LC-MS/MS. The peptide data were analyzed in database searches with two complementary algorithms, OMSSA and X!Tandem, to increase the number of identifications. Evolutionary genealogy of genes: nonsupervised orthologous groups (EggNOG) database searches resulted in the functional annotation of over 90% of the identified microbial and human proteins. Based on both bacterial and human proteins, a clear clustering of obese and nonobese samples was obtained that exceeded the phylogenetic separation in dimension. Moreover, integration of the metaproteomics and phylogenetic datasets revealed notably that the phylum Bacteroidetes was metabolically more active in the obese than nonobese subjects. Finally, significant correlations between clinical measurements and bacterial gene functions were identified. This study emphasizes the importance of integrating data of the host and microbiota to understand their interactions.

Navigating through metaproteomics data: a logbook of database searching.

Metaproteomic research involves various computational challenges during the identification of fragmentation spectra acquired from the proteome of a complex microbiome. These issues are manifold and range from the construction of customized sequence databases, the optimal setting of search parameters to limitations in the identification search algorithms themselves. In order to assess the importance of these individual factors, we studied the effect of strategies to combine different search algorithms, explored the influence of chosen database search settings, and investigated the impact of the size of the protein sequence database used for identification. Furthermore, we applied de novo sequencing as a complementary approach to classic database searching. All evaluations were performed on a human intestinal metaproteome dataset. Pyrococcus furiosus proteome data were used to contrast database searching of metaproteomic data to a classic proteomic experiment. Searching against subsets of metaproteome databases and the use of multiple search engines increased the number of identifications. The integration of P. furiosus sequences in a metaproteomic sequence database showcased the limitation of the target-decoy-controlled false discovery rate approach in combination with large sequence databases. The selection of varying search engine parameters and the application of de novo sequencing represented useful methods to increase the reliability of the results. Based on our findings, we provide recommendations for the data analysis that help researchers to establish or improve analysis workflows in metaproteomics.

Metaproteomics of our microbiome - developing insight in function and activity in man and model systems.

We are all colonized by a large microbiome, a complex set of microbes that have intimate associations with us. Culture-based approaches have provided insights in the complexity of the microbial communities living on surfaces inside and outside the body. However, the application of high-throughput sequencing technologies has identified large numbers of community members at both the phylogenetic and the (meta-)genome level. The latter allowed defining a reference set of several millions of mainly bacterial genes and provided the basis for developing approaches to target the activity and function of the human microbiome with proteomic techniques. Moreover, recent improvements in protein and peptide separation efficiencies and highly accurate mass spectrometers have promoted the field of metaproteomics, the study of the collective proteome of microbial communities. We here review the approaches that have been developed to study the human metaproteomes, focusing on intestinal tract and body fluids. Moreover, we complement these by considering metaproteomic studies in mouse and other model systems offering the option to study single species or simple consortia. Finally, we discuss present and future avenues that may be used to advance the application of metaproteomic approaches to further improve our understanding of the microbes inside and around our body. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Comparative metaproteomics and diversity analysis of human intestinal microbiota testifies for its temporal stability and expression of core functions.

The human intestinal tract is colonized by microbial communities that show a subject-specific composition and a high-level temporal stability in healthy adults. To determine whether this is reflected at the functional level, we compared the faecal metaproteomes of healthy subjects over time using a novel high-throughput approach based on denaturing polyacrylamide gel electrophoresis and liquid chromatography-tandem mass spectrometry. The developed robust metaproteomics workflow and identification pipeline was used to study the composition and temporal stability of the intestinal metaproteome using faecal samples collected from 3 healthy subjects over a period of six to twelve months. The same samples were also subjected to DNA extraction and analysed for their microbial composition and diversity using the Human Intestinal Tract Chip, a validated phylogenetic microarray. Using metagenome and single genome sequence data out of the thousands of mass spectra generated per sample, approximately 1,000 peptides per sample were identified. Our results indicate that the faecal metaproteome is subject-specific and stable during a one-year period. A stable common core of approximately 1,000 proteins could be recognized in each of the subjects, indicating a common functional core that is mainly involved in carbohydrate transport and degradation. Additionally, a variety of surface proteins could be identified, including potential microbes-host interacting components such as flagellins and pili. Altogether, we observed a highly comparable subject-specific clustering of the metaproteomic and phylogenetic profiles, indicating that the distinct microbial activity is reflected by the individual composition.