Multi-omics Analysis Workflow
A visual guide to the concepts, technologies, and detailed methodologies in discovery metabolomics.
1. Background & Core Technologies
Global Untargeted Metabolomics
Simultaneous and unbiased analysis of all small molecule metabolites in a sample to investigate qualitative changes after stimulation or disturbance.
LC-MS Metabolomics
Combines Liquid Chromatography (separation) with Mass Spectrometry (detection). Ideal for thermally unstable, less volatile, and larger molecules.
GC-MS Metabolomics
Combines Gas Chromatography (separation) with Mass Spectrometry (detection). A powerful tool for complex compound analysis which enhance sensitivity.
2. Application Fields
⚕️Medical Research
- Disease marker screening
- Investigation of etiological & pathological mechanisms
- Disease diagnosis and typing
- Clinical efficacy & pharmaco-toxicological evaluation
🔬Life Science Research
- Abiotic environment relationships
- Metabolic pathway & functional genomics research
- Plant, microorganism, and medicinal plant research
- Phenotype identification
🍎 Nutrition & Food Science
- Assess food quality & authenticity
- Ensure food safety by detecting contaminants
- Understand diet & health impacts
- Enable personalized nutrition
🌍 Environmental Science
- Monitor ecosystem health
- Assess toxic effects of ecotoxicology
- Identify biomarkers that represent environmental toxins
- Enhancing investigation in bioremediation
3. Key Advantages of multi-omics services
Urgent Service
Untargeted compounds analysis available within 5 working days.
High Sensitivity
Up to 1 ppb for caffeine standard and 0.6 ppb for abscisic acid.
Advanced Equipment & Platforms
Utilizes high-end equipment like the Orbitrap Exploris and Thermo Q Exactive™ series for high-resolution analysis.
Comprehensive & Accurate Annotation
Employs multiple databases to achieve 100% annotation of detected substances with high accuracy. Licensed databases are available.
Reliable and Validated Results
Ensures dependability through strict method validation and multiple layers of quality control.
Flexible and Efficient Analysis
Allows one-time analysis with adjustable parameters, avoiding the need to repeat experiments.
Powerful Multi-Omics Integration
Full-target annotation provides comprehensive info for integration with genomics and proteomics.
Personalized Bioinformatics & Support
A professional team provides customized data analysis and full after-sales service.
Comprehensive Biological Insight
Combining multi-omics data provides a complete, multi-layered view of biological processes, allowing researchers to see the larger picture of how a system functions.
Customized Services
Peptide mapping for glycomics profiling, monoclonal antibody characterization, Neoantigen peptide mass spectrometry, LC-MS/MS for in vivo pharmacokinetics, and others.
4. High-Level Research Process
1Experimental design
2Sample collection
3Metabolite extraction
4Metabolite detection
5Data quality control
6Data analysis
7Biological interpretation
5. Case Studies & Specific Methodologies
Watermeal (Hyper-gravity): Metabolomics & Lipidomics
Methanol/formic acid, SPE cleanup.
Thermo Q-Exactive Orbitrap.
Hypersil GOLD™ (Metabolomics), CSH C18 (Lipidomics).
High resolution, Pos/Neg modes.
Compound Discoverer, LipidSearch.
mzCloud, ChemSpider, KEGG.
MetaX, normalization, t-tests.
View Key Results ▶
Key Findings:
- Hyper-gravity induced significant changes in amino acid metabolism, particularly proline and arginine, indicating a stress response.
- Major alterations were observed in membrane lipid composition, with an increase in saturated fatty acids, suggesting a mechanism to maintain membrane integrity under high-g forces.
- Pathway analysis revealed upregulation of antioxidant pathways (e.g., glutathione metabolism) to counteract oxidative stress.
Data Visualizations:
Chromatogram: Separates and displays detected chemical compounds as peaks over time.
Bubble Plot: Shows the change in lipid amounts versus their statistical significance, where larger bubbles indicate more significant changes.
Hierarchical Clustering: Compares metabolite abundance between the Control and Hyper-gravity groups using a color scale and clusters similar items together.
SARS-CoV-2 in hamster model: Proteomics & Metabolomics
EasyPep™ Kit, Trypsin/Lys-C digestion.
Methanol mixture extraction.
Orbitrap Exploris™ 480.
PepMap™ (Proteomics), Accucore C18 (Metabolomics).
Proteome Discoverer, Compound Discoverer.
UniProt, mzCloud, ChemSpider.
SEQUEST™ HT, 1% FDR, t-tests.
View Key Results ▶
Key Findings:
- Proteomics identified significant upregulation of proteins involved in neuro-inflammatory pathways (e.g., IFN signaling) in response to both variants, with a stronger response to Delta.
- Metabolomics revealed a disruption in brain energy metabolism, including altered levels of TCA cycle intermediates and neurotransmitter precursors like tryptophan.
- Integrated analysis showed a correlation between specific viral proteins and host metabolic dysregulation, pointing to potential mechanisms of neuropathology.
Data Visualizations:
Volcano Plot: Identifies significant molecular changes by plotting their magnitude (fold change) against statistical significance (p-value).
Pathway Analysis: Shows connections between key genes/proteins and their biological pathways to understand the functional impact of changes.
Correlation Heatmap: Visualizes the similarity and reproducibility between all samples, with color indicating the strength of the correlation.
Clinical samples (Human serum) with MAFLD
Cold precipitation, SPE cleanup.
Orbitrap Exploris™ 240.
Hypersil GOLD™, 20-min gradient.
HESI source, High-res, DDA with AcquireX.
Compound Discoverer™.
mzCloud, ChemSpider.
5 ppm mass deviation, S/N ratio 2.
Normalization, PCA, OPLS-DA.
View Key Results ▶
Key Findings:
- OPLS-DA modeling successfully distinguished between patient groups based on their metabolic profiles.
- Key differentiating metabolites included specific acylcarnitines, bile acids, and phosphatidylcholines, indicating widespread lipid dysregulation in MAFLD and HIV comorbidity.
- Pathway analysis highlighted significant alterations in fatty acid oxidation and bile acid biosynthesis, providing potential biomarkers for disease progression.
Data Visualizations:
Box Plot: Compares the distribution and consistency of all measured metabolites between the MAFLD and MAFLD with HIV groups.
PCA Plot: Visualizes sample clustering to see if groups separate based on their overall metabolic profile.
S-Plot: Identifies the key metabolites that are most responsible for the group separation seen in the PCA plot.
Golden mushroom: Metabolomics with AI-pharmacokinetic prediction
Water-ethanol solution, SPE cleanup.
Thermo Q Exactive-X Orbitrap.
Hypersil GOLD™ C18, 20-min run.
High-res, Pos/Neg, top 20 DDA.
Compound Discoverer, AIDDISON™.
mzCloud, ChemSpider, Natural Products Atlas.
5 ppm tolerance, S/N 1.5.
GMM, PCA, UMAP.
View Key Results ▶
Key Findings:
- High-resolution LC-MS/MS analysis identified 1,025 distinct molecular features in the extract.
- An AI-driven ADMET profile and pharmacokinetic clustering prioritized a subset of 27 compounds with optimal drug-like properties.
- Multi-target molecular docking identified the most promising lead candidates across three key anti-diabetic enzymes: DPP4, α-amylase, and α-glucosidase.
Data Visualizations:
Mass Spectrum: This plot identifies individual compounds by their unique mass-to-charge ratio (m/z), which helps confirm their chemical structure.
Enzyme Inhibition Assay: This chart shows that the mushroom extract significantly reduces the activity of key anti-diabetic enzymes, demonstrating its inhibitory potential.
PCA-Plot: This plot clusters metabolites based on their drug-like properties, helping to visually identify groups of promising compounds for further investigation.
leaching precious metals from waste printed circuit boards: Metabolomics
Bacterial supernatants, SPE cleanup.
Thermo Q-Exactive Orbitrap.
Hypersil GOLD™ C18.
Positive mode, MS and DDA MS/MS.
Compound Discoverer.
mzCloud, ChemSpider.
Significant difference (p<0.01) after correction.
ANOVA with Tukey's HSD & correction.
View Key Results ▶
Key Findings:
- A novel stepwise bioleaching process was developed to maximize metal recovery from Waste Printed Circuit Boards (WPCBs).
- Pretreating WPCBs with ball milling and ozonation significantly enhanced the stepwise process, improving metal extraction yield, a total final gold recovery of 93%.
- Metabolomics analysis identified N⁸-acetylspermidine as a key metabolite produced by all tested bacteria.
- Confirmed that N⁸-acetylspermidine reduce the precipitation of gold ions from the solution, unreported phenomenon in bioleaching.
Data Visualizations:
Bioleaching Efficiency: This chart compares how effectively different bacteria extract copper from electronic waste, highlighting that the C. funkei strain performs best among the single cultures.
Stepwise Bioleaching Comparison: This chart demonstrates that a multi-step leaching process (right side) extracts significantly more copper than any single-step method (left side).
Hierarchical Clustering: This heat map compares metabolite abundance across different bacterial cultures and a control. It clusters groups with similar profiles, revealing the unique chemical signature of each bacterium