Metaproteomic portrait of the healthy human gut microbiota.

Gut metaproteomics can provide direct evidence of microbial functions actively expressed in the colonic environments, contributing to clarify the role of the gut microbiota in human physiology. In this study, we re-analyzed 10 fecal metaproteomics datasets of healthy individuals from different continents and countries, with the aim of identifying stable and variable gut microbial functions and defining the contribution of specific bacterial taxa to the main metabolic pathways. The "core" metaproteome included 182 microbial functions and 83 pathways that were identified in all individuals analyzed. Several enzymes involved in glucose and pyruvate metabolism, along with glutamate dehydrogenase, acetate kinase, elongation factors G and Tu and DnaK, were the proteins with the lowest abundance variability in the cohorts under study. On the contrary, proteins involved in chemotaxis, response to stress and cell adhesion were among the most variable functions. Random-effect meta-analysis of correlation trends between taxa, functions and pathways revealed key ecological and molecular associations within the gut microbiota. The contribution of specific bacterial taxa to the main biological processes was also investigated, finding that Faecalibacterium is the most stable genus and the top contributor to anti-inflammatory butyrate production in the healthy gut microbiota. Active production of other mucosal immunomodulators facilitating host tolerance was observed, including Roseburia flagellin and lipopolysaccharide biosynthetic enzymes expressed by members of Bacteroidota. Our study provides a detailed picture of the healthy human gut microbiota, contributing to unveil its functional mechanisms and its relationship with nutrition, immunity, and environmental stressors.

Metaproteomic Analysis of Fecal Samples from Human Subjects and Rodent Models.

Fecal metaproteomics is a useful approach to measure changes in microbial and host protein abundance and to infer which members of the gut microbiota are involved in specific functions and pathways. This chapter describes a protocol enabling analysis and characterization of fecal metaproteomes, successfully applied to human, mouse, and rat stool samples. The protocol combines mechanical and thermal treatments for protein extraction, a centrifugal filter-based procedure for cleanup and digestion, long-gradient liquid chromatography for peptide separation, and high-resolution mass spectrometry for peptide detection.

Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics.

The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.

Metaproteomic assessment of gut microbial and host functional perturbations in Helicobacter pylori-infected patients subjected to an antimicrobial protocol.

The impact of therapeutic interventions on the human gut microbiota (GM) is a clinical issue of paramount interest given the strong interconnection between microbial dynamics and human health. Orally administered antibiotics are known to reduce GM biomass and modify GM taxonomic profile. However, the impact of antimicrobial therapies on GM functions and biochemical pathways has scarcely been studied. Here, we characterized the fecal metaproteome of 10 Helicobacter pylori-infected patients before (T0) and after 10 days (T1) of a successful quadruple therapy (bismuth, tetracycline, metronidazole, and rabeprazole) and 30 days after therapy cessation (T2), to investigate how GM and host functions change during the eradication and healing processes. At T1, the abundance ratio between microbial and host proteins was reversed compared with that at T0 and T2. Several pathobionts (including Klebsiella, Proteus, Enterococcus, Muribaculum, and Enterocloster) were increased at T1. Therapy reshaped the relative contributions of the functions required to produce acetate, propionate, and butyrate. Proteins related to the uptake and processing of complex glycans were increased. Microbial cross-feeding with sialic acid, fucose, and rhamnose was enhanced, whereas hydrogen sulfide production was reduced. Finally, microbial proteins involved in antibiotic resistance and inflammation were more abundant after therapy. Moreover, a reduction in host proteins with known roles in inflammation and H. pylori-mediated carcinogenesis was observed. In conclusion, our results support the use of metaproteomics to monitor drug-induced remodeling of GM and host functions, opening the way for investigating new antimicrobial therapies aimed at preserving gut environmental homeostasis.

Unipept Desktop 2.0: Construction of Targeted Reference Protein Databases for Metaproteogenomics Analyses.

Unipept Desktop 2.0 is the most recent iteration of the Unipept Desktop tool that adds support for the analysis of metaproteogenomics datasets. Unipept Desktop now supports the automatic construction of targeted protein reference databases that only contain proteins (originating from the UniProtKB resource) associated with a predetermined list of taxa. This improves both the taxonomic and functional resolution of a metaproteomic analysis and yields several technical advantages. By limiting the proteins present in a reference database, it is also possible to perform (meta)proteogenomics analyses. Since the protein reference database resides on the user's local machine, they have complete control over the database used during an analysis. Data no longer need to be transmitted over the Internet, decreasing the time required for an analysis and better safeguarding privacy-sensitive data. As a proof of concept, we present a case study in which a human gut metaproteome dataset is analyzed with Unipept Desktop 2.0 using different targeted databases based on matched 16S rRNA gene sequencing data.

Meta4P: A User-Friendly Tool to Parse Label-Free Quantitative Metaproteomic Data and Taxonomic/Functional Annotations.

We present Meta4P (MetaProteins-Peptides-PSMs Parser), an easy-to-use bioinformatic application designed to integrate label-free quantitative metaproteomic data with taxonomic and functional annotations. Meta4P can retrieve, filter, and process identification and quantification data from three levels of inputs (proteins, peptides, PSMs) in different file formats. Abundance data can be combined with taxonomic and functional information and aggregated at different and customizable levels, including taxon-specific functions and pathways. Meta4P output tables, available in various formats, are ready to be used as inputs for downstream statistical analyses. This user-friendly tool is expected to provide a useful contribution to the field of metaproteomic data analysis, helping make it more manageable and straightforward.

Metagenomic Changes of Gut Microbiota following Treatment of Helicobacter pylori Infection with a Simplified Low-Dose Quadruple Therapy with Bismuth or Lactobacillus reuteri.

BACKGROUND: Probiotic supplementation to antibiotic regimens against Helicobacter pylori infection has been proposed to improve eradication rate and to decrease detrimental effects on gut microbiota. AIMS: To evaluate microbiota modifications due to a low-dose quadruple therapy with bismuth or Lactobacillus reuteri. METHODS: Forty-six patients infected with H. pylori were prospectively enrolled in a single-centre, randomized controlled trial to receive b.i.d. with meals for 10 days low-dose quadruple therapy consisting of rabeprazole 20 mg and bismuth (two capsules of Pylera® plus 250 mg each of tetracycline and metronidazole), or the same dose of rabeprazole and antibiotics plus Gastrus® (L. reuteri), one tablet twice-a-day for 27 days. Stool samples were collected at the enrolment, at the end and 30-40 days after the treatment. Gut microbiota composition was investigated with 16S rRNA gene sequencing. RESULTS: Eradication rate was by ITT 78% in both groups, and by PP analysis 85.7% and 95.5% for Gastrus® and bismuth group, respectively. Alpha and beta diversity decreased at the end of treatment and was associated with a reduction of bacterial genera beneficial for gut homeostasis, which was rescued 30-40 days later in both groups, suggesting a similar impact of the two regimens in challenging bacterial community complexity. CONCLUSIONS: Low-dose bismuth quadruple therapy proved to be effective with lower costs and amount of antibiotics and bismuth. Gastrus® might be an option for patients with contraindications to bismuth. L. reuteri was unable to significantly counteract dysbiosis induced by antibiotics. How to administer probiotics to prevent gut microbiota alterations remains an open question.

Metaproteomic Profile of the Colonic Luminal Microbiota From Patients With Colon Cancer.

Recent studies have provided evidence of interactions among the gut microbiota (GM), local host immune cells, and intestinal tissues in colon carcinogenesis. However, little is known regarding the functions exerted by the GM in colon cancer (CC), particularly with respect to tumor clinical classification and lymphocyte infiltration. In addition, stool, usually employed as a proxy of the GM, cannot fully represent the original complexity of CC microenvironment. Here, we present a pilot study aimed at characterizing the metaproteome of CC-associated colonic luminal contents and identifying its possible associations with CC clinicopathological features. Colonic luminal contents were collected from 24 CC tissue specimens immediately after surgery. Samples were analyzed by shotgun metaproteomics. Almost 30,000 microbial peptides were quantified in the samples, enabling the achievement of the taxonomic and functional profile of the tumor-associated colonic luminal metaproteome. Upon sample aggregation based on tumor stage, grade, or tumor-infiltrating lymphocytes (TILs), peptide sets enabling discrimination of sample groups were identified through discriminant analysis (DA). As a result, Bifidobacterium and Bacteroides fragilis were significantly enriched in high-stage and high-grade CC, respectively. Among metabolic functions, formate-tetrahydrofolate ligase was significantly associated with high-stage CC. Finally, based on the results of this pilot study, we assessed the optimal sample size for differential metaproteomic studies analyzing colonic luminal contents. In conclusion, we provide a detailed picture of the microbial and host components of the colonic luminal proteome and propose promising associations between GM taxonomic/functional features and CC clinicopathological features. Future studies will be needed to verify the prognostic value of these data and to fully exploit the potential of metaproteomics in enhancing our knowledge concerning CC progression.

The Metaproteomics Initiative: a coordinated approach for propelling the functional characterization of microbiomes.

Through connecting genomic and metabolic information, metaproteomics is an essential approach for understanding how microbiomes function in space and time. The international metaproteomics community is delighted to announce the launch of the Metaproteomics Initiative (www.metaproteomics.org), the goal of which is to promote dissemination of metaproteomics fundamentals, advancements, and applications through collaborative networking in microbiome research. The Initiative aims to be the central information hub and open meeting place where newcomers and experts interact to communicate, standardize, and accelerate experimental and bioinformatic methodologies in this field. We invite the entire microbiome community to join and discuss potential synergies at the interfaces with other disciplines, and to collectively promote innovative approaches to gain deeper insights into microbiome functions and dynamics. Video Abstract.

Critical Assessment of MetaProteome Investigation (CAMPI): a multi-laboratory comparison of established workflows.

Metaproteomics has matured into a powerful tool to assess functional interactions in microbial communities. While many metaproteomic workflows are available, the impact of method choice on results remains unclear. Here, we carry out a community-driven, multi-laboratory comparison in metaproteomics: the critical assessment of metaproteome investigation study (CAMPI). Based on well-established workflows, we evaluate the effect of sample preparation, mass spectrometry, and bioinformatic analysis using two samples: a simplified, laboratory-assembled human intestinal model and a human fecal sample. We observe that variability at the peptide level is predominantly due to sample processing workflows, with a smaller contribution of bioinformatic pipelines. These peptide-level differences largely disappear at the protein group level. While differences are observed for predicted community composition, similar functional profiles are obtained across workflows. CAMPI demonstrates the robustness of present-day metaproteomics research, serves as a template for multi-laboratory studies in metaproteomics, and provides publicly available data sets for benchmarking future developments.

Time-restricted feeding induces Lactobacillus- and Akkermansia-specific functional changes in the rat fecal microbiota.

Diet is a key factor influencing gut microbiota (GM) composition and functions, which in turn affect host health. Among dietary regimens, time-restricted (TR) feeding has been associated to numerous health benefits. The impact of TR feeding on the GM composition has been mostly explored by means of metagenomic sequencing. To date, however, little is known about the modulation of GM functions by this dietary regimen. Here, we analyzed the effects of TR feeding on GM functions by evaluating protein expression changes in a rat model through a metaproteomic approach. We observed that TR feeding has a relevant impact on GM functions, specifically leading to an increased abundance of several enzymes involved in carbohydrate and protein metabolism and expressed by Lactobacillus spp. and Akkermansia muciniphila. Taken together, these results contribute to deepening our knowledge about the key relationship between diet, GM, and health.

Comparative Evaluation of MaxQuant and Proteome Discoverer MS1-Based Protein Quantification Tools.

MS1-based label-free quantification can compare precursor ion peaks across runs, allowing reproducible protein measurements. Among bioinformatic platforms enabling MS1-based quantification, MaxQuant (MQ) is one of the most used, while Proteome Discoverer (PD) has recently introduced the Minora tool. Here, we present a comparative evaluation of six MS1-based quantification methods available in MQ and PD. Intensity (MQ and PD) and area (PD only) of the precursor ion peaks were measured and then subjected or not to normalization. The six methods were applied to data sets simulating various differential proteomics scenarios and covering a wide range of protein abundance ratios and amounts. PD outperformed MQ in terms of quantification yield, dynamic range, and reproducibility, although neither platform reached a fully satisfactory quality of measurements at low-abundance ranges. PD methods including normalization were the most accurate in estimating the abundance ratio between groups and the most sensitive when comparing groups with a narrow abundance ratio; on the contrary, MQ methods generally reached slightly higher specificity, accuracy, and precision values. Moreover, we found that applying an optimized log ratio-based threshold can maximize specificity, accuracy, and precision. Taken together, these results can help researchers choose the most appropriate MS1-based protein quantification strategy for their studies.

Fecal Microbiota Signatures in Celiac Disease Patients With Poly-Autoimmunity.

To date, reliable tests enabling the identification of celiac disease (CD) patients at a greater risk of developing poly-autoimmune diseases are not yet available. We therefore aimed to identify non-invasive microbial biomarkers, useful to implement diagnosis of poly-autoimmunity. Twenty CD patients with poly-autoimmunity (cases) and 30 matched subjects affected exclusively by CD (controls) were selected. All patients followed a varied gluten-free diet for at least 1 year. Fecal microbiota composition was characterized using bacterial 16S ribosomal RNA gene sequencing. Significant differences in gut microbiota composition between CD patients with and without poly-autoimmune disease were found using the edgeR algorithm. Spearman correlations between gut microbiota and clinical, demographic, and anthropometric data were also examined. A significant reduction of Bacteroides, Ruminococcus, and Veillonella abundances was found in CD patients with poly-autoimmunity compared to the controls. Bifidobacterium was specifically reduced in CD patients with Hashimoto's thyroiditis and its abundance correlated negatively with abdominal circumference values in patients affected exclusively by CD. In addition, the duration of CD correlated with the abundance of Firmicutes (negatively) and Odoribacter (positively), whereas the abundance of Desulfovibrionaceae correlated positively with the duration of poly-autoimmunity. This study provides supportive evidence that specific variations of gut microbial taxa occur in CD patients with poly-autoimmune diseases. These findings open the way to future validation studies on larger cohorts, which might in turn lead to promising diagnostic applications.

Fecal Metaproteomic Analysis Reveals Unique Changes of the Gut Microbiome Functions After Consumption of Sourdough Carasau Bread.

Sourdough-leavened bread (SB) is acknowledged for its great variety of valuable effects on consumer's metabolism and health, including a low glycemic index and a reduced content of the possible carcinogen acrylamide. Here, we aimed to investigate how these effects influence the gut microbiota composition and functions. Therefore, we subjected rats to a diet supplemented with SB, baker's yeast leavened bread (BB), or unsupplemented diet (chow), and, after 4 weeks of treatment, their gut microbiota was analyzed using a metaproteogenomic approach. As a result, diet supplementation with SB led to a reduction of specific members of the intestinal microbiota previously associated to low protein diets, namely Alistipes and Mucispirillum, or known as intestinal pathobionts, i.e., Mycoplasma. Concerning functions, asparaginases expressed by Bacteroides were observed as more abundant in SB-fed rats, leading to hypothesize that in their colonic microbiota the enzyme substrate, asparagine, was available in higher amounts than in BB- and chow-fed rats. Another group of protein families, expressed by Clostridium, was detected as more abundant in animal fed SB-supplemented diet. Of these, manganese catalase, small acid-soluble proteins (SASP), Ser/Thr kinase PrkA, and V-ATPase proteolipid subunit have been all reported to take part in Clostridium sporulation, strongly suggesting that the diet supplementation with SB might promote environmental conditions inducing metabolic dormancy of Clostridium spp. within the gut microbiota. In conclusion, our data describe the effects of SB consumption on the intestinal microbiota taxonomy and functions in rats. Moreover, our results suggest that a metaproteogenomic approach can provide evidence of the interplay between metabolites deriving from bread digestion and microbial metabolism.

Unipept 4.0: Functional Analysis of Metaproteome Data.

Unipept ( https://unipept.ugent.be ) is a web application for metaproteome data analysis, with an initial focus on tryptic-peptide-based biodiversity analysis of MS/MS samples. Because the true potential of metaproteomics lies in gaining insight into the expressed functions of complex environmental samples, the 4.0 release of Unipept introduces complementary functional analysis based on GO terms and EC numbers. Integration of this new functional analysis with the existing biodiversity analysis is an important asset of the extended pipeline. As a proof of concept, a human faecal metaproteome data set from 15 healthy subjects was reanalyzed with Unipept 4.0, yielding fast, detailed, and straightforward characterization of taxon-specific catalytic functions that is shown to be consistent with previous results from a BLAST-based functional analysis of the same data.

Caloric restriction promotes functional changes involving short-chain fatty acid biosynthesis in the rat gut microbiota.

Caloric restriction (CR) is known to promote health and longevity, likely via modification of the gut microbiota (GM). However, functional and metabolic changes induced in the GM during CR are still unidentified. Here, we investigated the short- and long-term effects of CR on the rat GM using a metaproteogenomic approach. We show that a switch from ad libitum (AL) low fat diet to CR in young rats is able to induce rapid and deep changes in their GM metaproteomic profile, related to a reduction of the Firmicutes/Bacteroidetes ratio and an expansion of lactobacilli. Specifically, we observed a significant change in the expression of the microbial enzymes responsible for short-chain fatty acid biosynthesis, with CR boosting propionogenesis and limiting butyrogenesis and acetogenesis. Furthermore, these CR-induced effects were maintained up to adulthood and started to be reversed after a short-term diet change. We also found that CR alters the abundance of an array of host proteins released in stool, mainly related to epithelial barrier integrity and inflammation. Hence, our results provide thorough information about CR-induced modifications to GM and host functional activity, and might constitute the basis for novel GM-based approaches aimed at monitoring the effectiveness of dietary interventions.

Clostridial Butyrate Biosynthesis Enzymes Are Significantly Depleted in the Gut Microbiota of Nonobese Diabetic Mice.

Increasing evidence suggests that the intestinal microbiota is involved in the pathogenesis of type 1 diabetes (T1D). Here we sought to determine which gut microbial taxa and functions vary between nonobese diabetic (NOD) mice and genetically modified NOD mice protected from T1D (Eα16/NOD) at 10 weeks of age in the time window between insulitis development and T1D onset. The gut microbiota of NOD mice were investigated by analyzing stool samples with a metaproteogenomic approach, comprising both 16S rRNA gene sequencing and microbial proteome profiling through high-resolution mass spectrometry. A depletion of Firmicutes (particularly, several members of Lachnospiraceae) in the NOD gut microbiota was observed compared to the level in the Eα16/NOD mice microbiota. Moreover, the analysis of proteins actively produced by the gut microbiota revealed different profiles between NOD and Eα16/NOD mice, with the production of butyrate biosynthesis enzymes being significantly reduced in diabetic mice. Our results support a model for gut microbiota influence on T1D development involving bacterium-produced metabolites as butyrate.IMPORTANCE Alterations of the gut microbiota early in age have been hypothesized to impact T1D autoimmune pathogenesis. In the NOD mouse model, protection from T1D has been found to operate via modulation of the composition of the intestinal microbiota during a critical early window of ontogeny, although little is known about microbiota functions related to T1D development. Here, we show which gut microbial functions are specifically associated with protection from T1D in the time window between insulitis development and T1D onset. In particular, we describe that production of butyrate biosynthesis enzymes is significantly reduced in NOD mice, supporting the hypothesis that modulating the gut microbiota butyrate production may influence T1D development.

Metagenomic Taxonomy-Guided Database-Searching Strategy for Improving Metaproteomic Analysis.

Metaproteomics provides a direct measure of the functional information by investigating all proteins expressed by a microbiota. However, due to the complexity and heterogeneity of microbial communities, it is very hard to construct a sequence database suitable for a metaproteomic study. Using a public database, researchers might not be able to identify proteins from poorly characterized microbial species, while a sequencing-based metagenomic database may not provide adequate coverage for all potentially expressed protein sequences. To address this challenge, we propose a metagenomic taxonomy-guided database-search strategy (MT), in which a merged database is employed, consisting of both taxonomy-guided reference protein sequences from public databases and proteins from metagenome assembly. By applying our MT strategy to a mock microbial mixture, about two times as many peptides were detected as with the metagenomic database only. According to the evaluation of the reliability of taxonomic attribution, the rate of misassignments was comparable to that obtained using an a priori matched database. We also evaluated the MT strategy with a human gut microbial sample, and we found 1.7 times as many peptides as using a standard metagenomic database. In conclusion, our MT strategy allows the construction of databases able to provide high sensitivity and precision in peptide identification in metaproteomic studies, enabling the detection of proteins from poorly characterized species within the microbiota.

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.

The Sarda Sheep Host Fecal Proteome.

The first characterization of the sheep fecal microbiota was recently reported, as obtained by using a multi meta-omic approach. Here, the mass spectra generated by single-run LC/high-resolution MS in the context of that study were reanalyzed using a host-specific database, in order to gain insights for the first time into the host fecal proteome of healthy Sarda sheep. On the whole, 5349 non-redundant tryptic peptide sequences were identified, belonging to 1046 different proteins. The "core" fecal proteome (common to all animals) comprised 431 proteins, mainly related to biological processes as immune response and proteolysis. Proteins involved in the immune/inflammatory response and peptidases were specifically investigated. This dataset provides novel insights into the repertoire of proteins secreted in the sheep intestinal lumen, and constitutes the basis for future shotgun and targeted proteomics studies aimed at monitoring changes in the sheep fecal proteome in response to production variables, infectious/inflammatory states, and variations in the gut microbiota. Data are available via ProteomeXchange with identifier PXD006145.