Metaproteomics as a tool to map prebiotic action

Significance of the topic

Metaproteomics provides a direct measurement of microbial community function by identifying and quantifying expressed proteins. This functional readout complements taxonomic and genetic surveys (metagenomics, metatranscriptomics, metabolomics) and is essential for mechanistic understanding of how prebiotics and probiotics alter microbial activity. Reliable metaproteomics workflows enable species-resolved mapping of metabolic pathways, linking specific organisms to metabolite production and ecological outcomes relevant to host health, food science, and bioprocessing.

Study aims and overview

The study set out to develop a robust, high-performance metaproteomics workflow and apply it to ex vivo fecal fermentation experiments testing multiple prebiotic compounds (2’-fucosyllactose, inulin, pectin, resistant dextrose). Objectives included: reproducible sample preparation across diverse microbiome components, deep and quantitative LC–MS/MS acquisition, reliable species-resolved protein identification using a metagenome-assembled genome (MAG) database, and functional interpretation of community responses to prebiotic supplementation.

Methods and experimental design

• Biological model: Fecal material from a single donor incubated ex vivo with prebiotics using SFIR® fermentation technology; time points collected at 0, 6, and 24 hours.
• Sample preparation: Homogenization with a BeatBox device and proteomic sample processing with SP3-iST add-on and iST kits (PreOmics) incorporating reduction, alkylation, digestion and clean-up optimized for mixed microbial cells.
• LC–MS/MS acquisition: 15 µg peptide injections on a 2.1 × 150 mm C18 column (Waters) via a Bruker Elute UHPLC (250 µL/min; 45 min active gradient) coupled to a timsTOF Pro2 mass spectrometer operated in PASEF mode.
• Data analysis: DDA data processed using FragPipe (v23.0) with MSFragger (v4.2). Peptide/protein identification used an individualized metagenome-assembled genome database built from the donor metagenome to increase species-level resolution and reduce false assignments.

Used instrumentation

• SFIR® fermentation system (Cryptobiotix) for ex vivo incubations.
• BeatBox homogenizer for sample disruption.
• SP3-iST workflow and iST kits (PreOmics) for proteomic sample processing.
• UHPLC: Bruker Elute system with Waters 2.1 × 150 mm C18 column.
• Mass spectrometer: Bruker timsTOF Pro2 operated in PASEF acquisition mode.
• Computational tools: FragPipe and MSFragger; metagenome-assembled genome (MAG) database derived from the same donor.

Main results and discussion

• Depth and coverage: The presented workflow achieved deep proteome coverage enabling species-resolved functional analysis. While the introduction cites broader workflow capabilities (hundreds of thousands of peptide identifications and thousands of microbial proteins), the applied fermentation dataset mapped ~35,000 peptides to ~14,800 protein groups across 76 species in the reported experiment.
• Community- and species-level responses to 2’-fucosyllactose (2’-FL): Addition of 2’-FL caused an increase in protein signal and growth/activity of several taxa — 27 of 282 measured species increased 2–8× after 24 h, with overall protein signal rising ~3–5×. Functional annotation indicated activation of fucosylated carbohydrate metabolism.
• Enzymatic and pathway activation: Six distinct fucosidase enzymes showed species-specific regulation. Significant upregulation was observed across fucose-utilization enzymes: 31 fucose isomerases (including two showing >500× induction) and seven fuculose-1-phosphate aldolases (Mediterraneibacter faecis showing >300× induction). Beta-galactosidase diversity was also high (51 identified, 12 exceeding 500× upregulation).
• Butyrate production pathways: Anaerobutyricum hallii demonstrated activation of butyrate-producing pathways with 32 enzymes upregulated (fold-changes between ~157–1,089×), including strong induction of flavodoxin (≈1,089×) and lactate racemase (≈992×), consistent with enhanced short-chain fatty acid (SCFA) biosynthesis potential.
• Prebiotic-specific taxa and proteins: Pectin selectively induced proteins associated with CAG-274, while resistant dextrose primarily stimulated Fusicatenibacter saccharivorans, with multiple carbohydrate-active enzymes and transporters upregulated in those taxa.
• Metabolite links: Indole-3-lactic acid (ILA / IDA) intensities increased in fermentations spiked with inulin and 2’-FL, providing a metabolite-level readout that links proteomic changes to biochemical output.
• Probiotic co-inoculation effects: Strain-dependent outcomes were observed when probiotics were co-inoculated with 2’-FL — Bifidobacterium breve expanded its detectable proteome (64 proteins), Anaerobutyricum soehngenii declined sharply, and Limosilactobacillus fermentum showed minimal detectable proteomic activity.
• Data interpretation challenges: The study highlights common metaproteomics challenges — heterogeneous lysis efficiency across taxa, balancing LC–MS/MS dynamic range and throughput, and the need for stringent FDR control when searching large sequence spaces such as MAG-based databases.

Contributions and practical applications

• Species-resolved functional phenotyping: The workflow enables mapping of which species express which enzymes and pathways in response to prebiotics, allowing mechanistic interpretation beyond taxonomic abundance shifts.
• Prebiotic screening and mechanistic validation: Proteomic signatures (enzyme induction, pathway activation) can validate prebiotic modes of action and identify taxa mediating beneficial metabolites (e.g., butyrate, indole derivatives).
• Strain- and community-level evaluation of probiotics: Proteomics can reveal competitive or cooperative effects of probiotic strains on endogenous microbiota and functional output, supporting formulation and co-administration decisions.
• Translational research and product development: The approach is applicable in R&D for nutritional interventions, microbiome-targeted therapeutics, and quality control when functional readouts are required.

Future trends and potential applications

• Multi-omics integration: Combining metaproteomics with metagenomics, metatranscriptomics and metabolomics will strengthen causal inference between gene potential, expression, and metabolic outcome.
• Improved reference databases: Expanded, high-quality MAGs and strain-resolved protein catalogs will increase identification confidence and sensitivity, enabling finer taxonomic resolution.
• Quantitative advances: Adoption of targeted proteomics, isotopic labeling, or absolute quantification strategies will permit robust estimation of enzyme abundances and flux-related interpretations.
• Acquisition and computational innovation: Wider use of DIA methods, longer LC gradients or ion-mobility separation, and optimized FDR strategies for large search spaces will enhance proteome depth and reproducibility.
• Clinical and personalized applications: Robust, standardized metaproteomics could support personalized nutrition, microbiome-based diagnostics, and monitoring of microbiome-targeted therapies.
• High-throughput screening: Streamlined sample prep and faster LC–MS/MS workflows will permit larger-scale prebiotic/probiotic screens and time-course studies.

Conclusion

This work demonstrates a practical, high-performance metaproteomics workflow capable of delivering species-resolved functional readouts from complex fecal fermentation experiments. The approach revealed prebiotic-specific activation of carbohydrate metabolism, production-linked pathway induction (including butyrate-related enzymes), and metabolite correlations such as indole-3-lactic acid. The study highlights the method's value for mechanistic evaluation of prebiotics and probiotics, while underscoring analytical challenges that future methodological and computational improvements can address to expand translational impact.

Reference

• No external literature list was provided in the source document; methods and findings are attributed to the authors and institutional affiliations reported in the original report.