Creative Proteomics offers integrated multi-omics solutions that examine how dietary components influence host biology at the molecular, cellular, and community (microbiome) levels. This article describes the conceptual framework, technical workflow, analytical services, and practical recommendations for rigorous studies of food functional effects and mechanisms, aimed at biomedical researchers, pharmaceutical R&D teams, and contract research organizations (CROs).
Introduction
Food functional effects refer to measurable biological responses—molecular, cellular, or system-level—triggered by dietary components, food formulations, or nutritional interventions. Mechanistic research seeks to connect observed phenotypes (for example, altered metabolite profiles or immune signals) to causal molecular events such as changes in microbial metabolism, protein expression and modification, gene regulation, or intercellular signaling. Modern mechanism studies use complementary omics layers (microbiome, metabolome, proteome, transcriptome, single-cell and spatial methods) to build an integrated, evidence-based model describing how food components act on biological systems.
Fig 1. An infographics showing the functional components of the food and their potential health benefits to human beings (Nayak S N, et al., 2021).
Technical Workflow for Multi-Omics Food Functionality and Mechanism Analysis
Technical Advantages of Our Multi-Omics Food Functionality and Mechanism Analysis
- Comprehensive Multi-Omics Solutions: One-stop integration of microbiome, proteome, metabolome, lipidome, single-cell, and spatial transcriptomics to uncover mechanistic insights.
- Advanced Analytical Technologies: Equipped with high-resolution LC-MS/MS, next-generation sequencing (NGS), MALDI-TOF, and advanced imaging platforms.
- Customized Experimental Design: Flexible solutions tailored to unique research goals, dietary interventions, and biological systems.
- Robust Bioinformatics Support: Sophisticated data processing pipelines enable multi-omics integration, pathway reconstruction, and biomarker discovery.
Multi-Omics Analysis Service We Provide
- 16S rRNA sequencing, metagenomics, metatranscriptomics.
- Gut microbial composition, microbial metabolic pathways, host–microbe interactions.
- Untargeted and targeted profiling of small molecules and lipid species.
- Uncovering metabolic alterations caused by bioactive compounds and functional foods.
- Global protein expression profiling using LC-MS/MS.
- Post-translational modification (PTM) analysis for phosphorylation, acetylation, glycosylation, and lipidation.
Transcriptomics and Epigenomics
- Bulk RNA-seq for pathway level gene expression profiling.
- Epigenetic assays when nutrient-driven chromatin changes are under investigation.
- scRNA-seq and multi-omic single-cell assays to resolve heterogeneous cellular responses.
- Spatial transcriptomics and imaging-based approaches to map tissue architecture and localized responses.
Data Analysis and Interpretation
- Data Preprocessing: Noise reduction, quality control, normalization
- Statistical Analysis: Differential expression, clustering, and correlation mapping
- Pathway Enrichment Analysis: Identifying affected biological processes and signaling cascades
- Network Biology Modeling: Visualizing complex molecular interactions across omics layers
- Multi-Omics Integration: Combining microbiome, proteome, metabolome, and transcriptome data for systemic insights
Application for Food Functionality and Mechanism Analysis
- Functional Food Development: Validating the biological effects of novel ingredients
- Nutrigenomics Research: Understanding how dietary components influence gene expression
- Gut Microbiota Studies: Exploring diet–microbiome interactions and microbial metabolite contributions
- Immune Regulation Analysis: Characterizing pathways affected by bioactive compounds
- Metabolic Homeostasis Research: Identifying how nutrients modulate energy metabolism and lipid signaling
- Biomarker Discovery: Identifying potential molecular signatures for food-driven biological responses
Sample Requirements (Recommended)
| Sample Type | Minimum Quantity Required | Storage Conditions | Preparation Notes |
|---|---|---|---|
| Serum / Plasma | ≥ 200 µL | -80 °C | Avoid repeated freeze-thaw cycles. |
| Feces | ≥ 200 mg | -80 °C | Snap-freeze immediately after collection; avoid preservatives unless specified. |
| Tissue Samples | ≥ 30 mg | -80 °C or liquid nitrogen | Rinse gently with PBS to remove blood; snap-freeze; store in clean, labeled tubes. |
| Food Extracts | ≥ 500 µL or 500 mg | -20 °C / -80 °C depending on matrix | Use appropriate solvents for extraction; protect from light and oxidation. |
| Microbial Cultures | ≥ 1×10⁸ cells or equivalent biomass | -80 °C | Pellet cultures where possible; store in sterile tubes with cryoprotectant if required. |
Why Choose Creative Proteomics
- Extensive experience supporting food, nutrition, and biotech research.
- Full-suite multi-omics capabilities under one platform.
- Advanced analytical technologies and robust data pipelines.
- Dedicated project managers and personalized technical support.
- Proven track record of delivering high-quality, reproducible results.
References
- Nayak S N, et al. Omics technologies to enhance plant based functional foods: an overview. Frontiers in Genetics, 2021, 12: 742095.
- Su G, et al. Multi-omics in food safety and authenticity in terms of food components. Food Chemistry, 2024, 437: 137943.
- Valdés A, et al. Foodomics: Analytical opportunities and challenges. Analytical Chemistry, 2021, 94(1): 366-381.
Multi-omics analyses reveal relationships among polyphenol-rich oolong tea consumption, gut microbiota, and metabolic profile: A pilot study.
Journal: Food Chemistry
Impact factor: 9.8
Published: 2023
DOI: 10.1016/j.foodchem.2023.136653
Backgrounds
Polyphenol-rich foods and beverages (e.g., teas) are widely linked to gut microbiome modulation and metabolic effects, but human evidence integrating multiple molecular layers remains limited. Using a multi-omics framework, this study assessed how short-term oolong tea intake relates to changes in gut microbiota and host metabolic profiles.
Materials & Methods
Healthy adults consumed oolong tea for 3 weeks in a pre–post (within-subject) design. The team profiled gut microbiota (community composition/diversity) and metabolomics to capture host metabolic shifts; outcomes were analyzed overall and by BMI subgroup.
Results
- Microbiome diversity & composition: Oolong tea intake significantly altered gut microbial diversity (Shannon index reported) and reorganized community structure, enriching Bacteroides and Prevotella and reducing Megamonas.
- Metabolomics: 23 differential metabolites and 10 enriched metabolic pathways were identified after the intervention, indicating shifts in host metabolic status associated with tea consumption.
- Subgroup response: Participants with BMI > 23.9 exhibited larger microbiome responses to the tea intervention than normal-weight counterparts.
Fig 2. Graphical abstract of multi-omics analysis for oolong tea.
Fig 3. Metabolite profiles detected in electrospray ionization in negative ion mode in OT-baseline and OT-outcome groups.
Conclusions
Short-term consumption of polyphenol-rich oolong tea modulated the human gut microbiome and host metabolome, with particularly pronounced microbial shifts in individuals with higher BMI. The multi-omics design strengthened mechanistic insight by linking dietary exposure to coordinated changes across microbial taxa and metabolic pathways, supporting the use of integrated omics to evaluate food functionality in humans.
What specific omics methods are most relevant to studying food mechanisms?
Metabolomics: Captures changes in metabolites following dietary interventions; typically uses NMR or MS for profiling a wide range of small molecules.
Proteomics: Maps protein expression changes and post-translational modifications in response to bioactive food compounds, revealing target pathways.
Microbiome: Uses sequencing techniques to assess how food impacts gut microbial composition and function, which is crucial for gut–host interaction studies.
Epigenomics/Transcriptomics: Elucidates changes in gene regulation and expression influenced by diet, capturing nutrigenomic effects.
How do you validate an omics-derived mechanistic hypothesis?
Use orthogonal experiments: targeted assays (quantitative MS, ELISA), perturbation studies (knockdown/overexpression, inhibitor assays), time-course experiments to establish temporality, and independent cohorts or replication studies to confirm reproducibility.
What are typical turnaround times and cost drivers for multi-omics food mechanism projects?
Turnaround is driven by project scope: single-omics discovery projects may take weeks; integrated multi-omics with bioinformatics can take months. Major cost drivers: number of samples, number of omics layers, depth of sequencing/LC-MS runs, and extent of bespoke bioinformatics/validation work.
Demo: Intermittent fasting-protein is associated with a beneficial profile of gut microbiome and metabolites within a randomized trial.
A human randomized trial using gut microbiome sequencing and untargeted metabolomics showed that specific diets change gut microbial composition and activity and shift blood metabolite patterns, which is linked to improved metabolic health markers.
Fig 4. Factors derived from the integration of the gut microbiome and plasma metabolome (Mohr, et al., 2024).