Blood & Plasma & Serum Metabolomics Service

What is Blood / Plasma / Serum Metabolomics and Why Choose These Matrices?

Blood, plasma, and serum are among the most informative and widely used matrices in metabolomics. They integrate metabolites from multiple organs and the microbiome, providing a systemic snapshot of physiological and metabolic states. Compared with tissues, blood sampling is less invasive, more repeatable, and suitable for large-scale or longitudinal studies.

With high-resolution mass spectrometry, these matrices enable:

• Comprehensive profiling across amino acids, lipids, bile acids, and more
• Sensitive detection of biological responses to compounds, nutrition, or environmental exposures
• Robust integration with other omics for systems-level insights

Plasma (anticoagulated supernatant) and serum (post-clot fraction) each have unique characteristics, but both offer well-established, standardized protocols that support consistent, comparable, and decision-ready metabolomics data.

How to Choose Between Blood / Plasma / Serum?

Comprehensive Blood, Plasma & Serum Metabolomics Solutions

Untargeted Metabolomics

• Broad-spectrum metabolite profiling using LC–MS (HILIC/RP, ESI±) and GC–MS (EI).
• Captures a wide range of small molecules, from amino acids and organic acids to sugars and lipids.
• Ideal for exploratory studies, biomarker discovery, and hypothesis generation.

Targeted Metabolomics

• Precision quantitation with LC–MS/MS (MRM/SRM, Triple Quad).
• Flexible panels for amino acids, bile acids, acylcarnitines, TCA intermediates, biogenic amines, vitamins, and more.
• Suitable for hypothesis-driven studies, pathway validation, and cross-cohort comparisons.

Stable Isotope Tracing (Optional)

• Enables analysis of metabolic flux and pathway routing.
• Supports mechanistic studies in preclinical and experimental systems.

Bioinformatics & Statistical Support

• Advanced data processing, normalization, and metabolite annotation.
• Comprehensive statistical and pathway analyses to contextualize results.
• Designed to integrate seamlessly with multi-omics datasets.

Why Choose Our Metabolomics Analysis: Key Advantages

• Broad Metabolite Coverage

Untargeted LC–MS and GC–MS can detect >1,000 metabolites/features, spanning amino acids, organic acids, nucleotides, sugars, bile acids, and lipids.

• High Sensitivity & Reproducibility

Targeted LC–MS/MS achieves nM–pM detection limits with typical CV ≤15–20%, ensuring robust quantitation.

• Efficient Sample Use

Workflows require only 50–200 μL per channel, enabling analysis of valuable or limited-volume samples.

• Scalable Throughput

Automated pipelines process hundreds of samples per week, supporting both pilot and large-cohort studies.

• Pathway-Level Insights

Profiles map to 50+ metabolic pathways, enabling system-level interpretation and integration with other omics.

• Cross-Study Comparability

Plasma and serum are the most common matrices in metabolomics publications, ensuring alignment with public datasets and literature.

Analytical Platforms for Blood, Plasma and Serum Metabolomics Services

Orbitrap Exploris 240 (Figure from Thermo)

Agilent 7890B-5977B (Figure from Agilent)

SCIEX Triple Quad™ 6500+ (Figure from Sciex)

Agilent 6495C Triple quadrupole (Figure from Agilent)

How Our Blood, Plasma & Serum Metabolomics Assay Works — Step-by-Step Process

1

Consultation & Study Design

Understand research objectives (exploratory vs. targeted). Advise on matrix selection (blood, plasma, or serum) and analytical strategy. Provide guidelines for sample collection, anticoagulant choice, and storage.

2

Sample Submission & Quality Check

Receive and register samples under strict cold-chain conditions. Assess sample integrity (e.g., volume, hemolysis, lipemia). Document metadata (collection time, fasting status, storage history).

3

Sample Preparation & Extraction

Apply matrix-specific extraction protocols (polar vs. non-polar). Spike with isotopically labeled internal standards. Process blanks and pooled QCs alongside study samples.

4

Instrumental Analysis

• Untargeted: High-resolution LC–MS and GC–MS for broad coverage.
• Targeted: Triple quadrupole LC–MS/MS (MRM/SRM) for absolute quantitation.
• Optional: Stable isotope tracing for flux studies.
• Randomized run order and repeated QC injections to monitor system stability.

5

Data Processing & Identification

Convert raw files into open formats (e.g., mzML). Perform peak picking, alignment, normalization, and drift correction. Annotate metabolites with reference standards, spectral libraries, and MSI confidence levels.

6

Statistical & Pathway Analysis

Apply univariate and multivariate statistics (PCA, PLS-DA, volcano plots). Conduct pathway enrichment using KEGG, Reactome, and LIPID MAPS. Highlight significant metabolites and biological themes relevant to the study.

Sample Requirements for Metabolomics Service

*Volumes are per single analytical channel. For multi-channel designs (e.g., untargeted + targeted + GC–MS), sum the volumes and add 10–20% reserve for repeats/QC.

General Rules for Sample Handling

• Aliquot: 50–100 μL per cryovial; prepare enough to avoid repeat freeze–thaw.
• Storage: Low-bind screw-cap tubes, -80°C; ship on dry ice.
• Metadata: Record anticoagulant type, hemolysis/lipemia, diet/fasting, clot time (serum), storage history.
• Consistency: Use one matrix + one anticoagulant across the study.
• Micro-volume: Low-volume workflows available on request.

Deliverables: What You Receive from Our Blood / Plasma / Serum Metabolomics Analysis

• Raw data files: instrument vendor formats (e.g., .raw, .wiff) and converted open formats (.mzML*).
• Processed datasets: feature/peak tables with retention time, m/z, intensities, and metabolite annotations (with MSI confidence levels).
• Quantitative results: absolute concentrations for targeted panels; normalized relative abundances for untargeted assays.
• QC reports: summaries of internal standards, pooled QCs, blanks, and key acceptance metrics (mass accuracy, %CV, retention time stability).
• Statistical outputs: PCA, PLS-DA, volcano plots, clustering heatmaps, and pathway enrichment results (KEGG, Reactome, LIPID MAPS).

LC–MS TIC (0–20 min); multiple resolved peaks with a stable baseline.

GC–MS TIC (0–30 min); sharp Gaussian peaks with low-noise baseline.

PCA score plot; clear group separation along PC1/PC2 and tight QC clustering.

Volcano plot of differential metabolites; significant up/down features highlighted and labeled.