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.

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.

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.

Protective major histocompatibility complex allele prevents type 1 diabetes by shaping the intestinal microbiota early in ontogeny.

Certain MHC-II or HLA-D alleles dominantly protect from particular autoimmune diseases. For example, expression of the MHC-II Eα:Eß complex potently protects nonobese diabetic (NOD) mice, which normally lack this isotype, from spontaneous development of type 1 diabetes. However, the underlying mechanisms remain debated. We investigated MHC-II-mediated protection from type 1 diabetes using a previously reported NOD mouse line expressing an Eα transgene and, thereby, the Eα:Eß complex. Eα16/NOD females vertically protected their NOD offspring from diabetes and insulitis, an effect that was dependent on the intestinal microbiota; moreover, they developed autoimmunity when treated with certain antibiotics or raised in a germ-free environment. Genomic and proteomic analyses revealed NOD and Eα16/NOD mice to host mild but significant differences in the intestinal microbiotas during a critical early window of ontogeny, and transfer of cecal contents from the latter to the former suppressed insulitis. Thus, protection from autoimmunity afforded by particular MHC/HLA alleles can operate via intestinal microbes, highlighting potentially important societal implications of treating infants, or even just their pregnant mothers, with antibiotics.

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.

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.

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.

A first immunohistochemistry study of transketolase and transketolase-like 1 expression in canine hyperplastic and neoplastic mammary lesions.

BACKGROUND: Canine mammary tumors represent the most common neoplasm in female dogs, and the discovery of cancer biomarkers and their translation to clinical relevant assays is a key requirement in the war on cancer. Since the description of the 'Warburg effect', the reprogramming of metabolic pathways is considered a hallmark of pathological changes in cancer cells. In this study, we investigate the expression of two cancer-related metabolic enzymes, transketolase (TKT) and transketolase-like 1 (TKTL1), involved in the pentose phosphate pathway (PPP), an alternative metabolic pathway for glucose breakdown that could promote cancer by providing the precursors and energy required for rapidly growing cells. RESULTS: TKT and TKTL1 protein expression was investigated by immunohistochemistry in canine normal (N = 6) and hyperplastic glands (N = 3), as well as in benign (N = 11) and malignant mammary tumors (N = 17). TKT expression was higher in hyperplastic lesions and in both benign and malignant tumors compared to the normal mammary gland, while TKTL1 levels were remarkably higher in hyperplastic lesions, simple adenomas and simple carcinomas than in the normal mammary glands (P < 0.05). CONCLUSIONS: This study reveals that the expression of a key PPP enzyme varies along the evolution of canine mammary neoplastic lesions, and supports a role of metabolic changes in the development of canine mammary tumors.

Proteomic analysis of Rhodotorula mucilaginosa: dealing with the issues of a non-conventional yeast.

Red yeasts ascribed to the species Rhodotorula mucilaginosa are gaining increasing attention, due to their numerous biotechnological applications, spanning carotenoid production, liquid bioremediation, heavy metal biotransformation and antifungal and plant growth-promoting actions, but also for their role as opportunistic pathogens. Nevertheless, their characterization at the 'omic' level is still scarce. Here, we applied different proteomic workflows to R. mucilaginosa with the aim of assessing their potential in generating information on proteins and functions of biotechnological interest, with a particular focus on the carotenogenic pathway. After optimization of protein extraction, we tested several gel-based (including 2D-DIGE) and gel-free sample preparation techniques, followed by tandem mass spectrometry analysis. Contextually, we evaluated different bioinformatic strategies for protein identification and interpretation of the biological significance of the dataset. When 2D-DIGE analysis was applied, not all spots returned a unambiguous identification and no carotenogenic enzymes were identified, even upon the application of different database search strategies. Then, the application of shotgun proteomic workflows with varying levels of sensitivity provided a picture of the information depth that can be reached with different analytical resources, and resulted in a plethora of information on R. mucilaginosa metabolism. However, also in these cases no proteins related to the carotenogenic pathway were identified, thus indicating that further improvements in sequence databases and functional annotations are strictly needed for increasing the outcome of proteomic analysis of this and other non-conventional yeasts. Copyright © 2016 John Wiley & Sons, Ltd.

Protein expression changes induced in a malignant melanoma cell line by the curcumin analogue compound D6.

BACKGROUND: We have previously demonstrated that the hydroxylated biphenyl compound D6 (3E,3'E)-4,4'-(5,5',6,6'-tetramethoxy-[1,1'-biphenyl]-3,3'-diyl)bis(but-3-en-2-one), a structural analogue of curcumin, exerts a strong antitumor activity on melanoma cells both in vitro and in vivo. Although the mechanism of action of D6 is yet to be clarified, this compound is thought to inhibit cancer cell growth by arresting the cell cycle in G2/M phase, and to induce apoptosis through the mitochondrial intrinsic pathway. To investigate the changes in protein expression induced by exposure of melanoma cells to D6, a differential proteomic study was carried out on D6-treated and untreated primary melanoma LB24Dagi cells. METHODS: Proteins were fractionated by SDS-PAGE and subjected to in gel digestion. The peptide mixtures were analyzed by liquid chromatography coupled with tandem mass spectrometry. Proteins were identified and quantified using database search and spectral counting. Proteomic data were finally uploaded into the Ingenuity Pathway Analysis software to find significantly modulated networks and pathways. RESULTS: Analysis of the differentially expressed protein profiles revealed the activation of a strong cellular stress response, with overexpression of several HSPs and stimulation of ubiquitin-proteasome pathways. These were accompanied by a decrease of protein synthesis, evidenced by downregulation of proteins involved in mRNA processing and translation. These findings are consistent with our previous results on gene expression profiling in melanoma cells treated with D6. CONCLUSIONS: Our findings confirm that the curcumin analogue D6 triggers a strong stress response in melanoma cells, turning down majority of cell functions and finally driving cells to apoptosis.

Enrichment or depletion? The impact of stool pretreatment on metaproteomic characterization of the human gut microbiota.

To date, most metaproteomic studies of the gut microbiota employ stool sample pretreatment methods to enrich for microbial components. However, a specific investigation aimed at assessing if, how, and to what extent this may impact on the final taxonomic and functional results is still lacking. Here, stool replicates were either pretreated by differential centrifugation (DC) or not centrifuged. Protein extracts were then processed by filter-aided sample preparation, single-run LC, and high-resolution MS, and the metaproteomic data were compared by spectral counting. DC led to a higher number of identifications, a significantly richer microbial diversity, as well as to reduced information on the nonmicrobial components (host and food) when compared to not centrifuged. Nevertheless, dramatic differences in the relative abundance of several gut microbial taxa were also observed, including a significant change in the Firmicutes/Bacteroidetes ratio. Furthermore, some important microbial functional categories, including cell surface enzymes, membrane-associated proteins, extracellular proteins, and flagella, were significantly reduced after DC. In conclusion, this work underlines that a critical evaluation is needed when selecting the appropriate stool sample processing protocol in the context of a metaproteomic study, depending on the specific target to which the research is aimed. All MS data have been deposited in the ProteomeXchange with identifier PXD001573 (http://proteomecentral.proteomexchange.org/dataset/PXD001573).

Critical comparison of sample preparation strategies for shotgun proteomic analysis of formalin-fixed, paraffin-embedded samples: insights from liver tissue.

BACKGROUND: The growing field of formalin-fixed paraffin-embedded (FFPE) tissue proteomics holds promise for improving translational research. Direct tissue trypsinization (DT) and protein extraction followed by in solution digestion (ISD) or filter-aided sample preparation (FASP) are the most common workflows for shotgun analysis of FFPE samples, but a critical comparison of the different methods is currently lacking. EXPERIMENTAL DESIGN: DT, FASP and ISD workflows were compared by subjecting to the same label-free quantitative approach three independent technical replicates of each method applied to FFPE liver tissue. Data were evaluated in terms of method reproducibility and protein/peptide distribution according to localization, MW, pI and hydrophobicity. RESULTS: DT showed lower reproducibility, good preservation of high-MW proteins, a general bias towards hydrophilic and acidic proteins, much lower keratin contamination, as well as higher abundance of non-tryptic peptides. Conversely, FASP and ISD proteomes were depleted in high-MW proteins and enriched in hydrophobic and membrane proteins; FASP provided higher identification yields, while ISD exhibited higher reproducibility. CONCLUSIONS: These results highlight that diverse sample preparation strategies provide significantly different proteomic information, and present typical biases that should be taken into account when dealing with FFPE samples. When a sufficient amount of tissue is available, the complementary use of different methods is suggested to increase proteome coverage and depth.

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.

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.

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.

Comparison of detergent-based sample preparation workflows for LTQ-Orbitrap analysis of the Escherichia coli proteome.

This work presents a comparative evaluation of several detergent-based sample preparation workflows for the MS-based analysis of bacterial proteomes, performed using the model organism Escherichia coli. Initially, RapiGest- and SDS-based buffers were compared for their protein extraction efficiency and quality of the MS data generated. As a result, SDS performed best in terms of total protein yields and overall number of MS identifications, mainly due to a higher efficiency in extracting high molecular weight (MW) and membrane proteins, while RapiGest led to an enrichment in periplasmic and fimbrial proteins. Then, SDS extracts underwent five different MS sample preparation workflows, including: detergent removal by spin columns followed by in-solution digestion (SC), protein precipitation followed by in-solution digestion in ammonium bicarbonate or urea buffer, filter-aided sample preparation (FASP), and 1DE separation followed by in-gel digestion. On the whole, about 1000 proteins were identified upon LC-MS/MS analysis of all preparations (>1100 with the SC workflow), with FASP producing more identified peptides and a higher mean sequence coverage. Each protocol exhibited specific behaviors in terms of MW, hydrophobicity, and subcellular localization distribution of the identified proteins; a comparative assessment of the different outputs is presented.

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.

Evaluation of the suitability of archival Bouin-fixed paraffin-embedded tissue specimens to proteomic investigation.

Bouin's solution has been used for over a century as a common fixative in several pathology laboratories worldwide. Therefore, a considerable number of Bouin-fixed paraffin-embedded (BFPE) tumor samples of various origin are available in hospital repositories as a powerful information mine for clinical investigations. To date, however, such archived tissues have not been subjected to a systematic study aimed to evaluate their potential use in proteomics. In this report, we investigated whether archival BFPE tissue specimens could be exploited for proteomic studies, upon application of protein extraction and proteomic analysis methods previously optimized for formalin-fixed samples. As a result, gastric BFPE protein extracts exhibited poor suitability for 2D-PAGE analysis, whereas over 300 unique proteins could be successfully detected when extracts were subjected to SDS-PAGE followed by LC-MS/MS (GeLC-MS/MS). Among these, several known markers for gastric cancer and normal gastric functionality were identified, indicative of biological and clinical significance of proteomic data mined from BFPE tissues. A quantitative and qualitative comparison of FFPE and BFPE tissue proteomes was also performed, and results are reported. In conclusion, we demonstrated that BFPE specimens can be analyzed by means of a proteomic approach such as GeLC-MS/MS. Although considerable molecular biases and technical constraints exist, BFPE tissue archives can be fruitfully exploited for gathering proteomic data from particularly precious samples.

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.