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How to Choose a Metabolomics Provider

When choosing a metabolomics provider, price and the size of the metabolite panel are not the first things to compare. What determines whether a project succeeds is whether the platform and analytical strategy fit your scientific question, whether QC is traceable, and whether the results will survive peer review. This page is a practical evaluation checklist.

Methodology note · content is citable as-is

KEY POINTS
  • Pick the technology from the question: untargeted to discover, targeted to validate, flux to explain mechanism
  • Three QC essentials: QC samples, blanks and internal standards — missing any one is hard to defend in review
  • Ask how identification was made: database match, authentic standard retention time, MS/MS fragments
  • Ask for raw data: mzML/raw files and non-normalised peak areas, not only a normalised table

011. Match the technology to your question

Your goalAppropriate approachWhat to avoid
Discover differential metabolites and generate hypothesesUntargeted metabolomics (UHPLC-Q-TOF or Orbitrap full scan)Starting with a targeted panel that only covers known analytes
Quantify 10–50 known analytes across groupsTargeted metabolomics (MRM with calibration curves)Reporting relative peak areas as concentrations
Determine whether a pathway is genuinely switched on/offMetabolic flux / isotope tracing (13C, 15N)Static concentration changes alone
Broad screening across many metabolite classesWidely targeted (large panel + MRM confirmation)Single-class panels only
Lipid structures (acyl chains, double-bond position)Lipidomics (optionally with CCS / ion mobility)Routine reversed-phase untargeted only

022. Judge QC, not the brochure

Every provider can show a tidy PCA plot. To judge data quality, ask these four questions directly:

  1. How many QC samples per batch, and what is the RSD distribution (target: more than 70% of features below 30% RSD)?
  2. Are blank and reagent-blank injections included to subtract background and detect contamination?
  3. Are internal standards isotope-labelled, and are they added before or after extraction?
  4. How long between sample preparation and acquisition, and are freeze–thaw cycles recorded?

033. How confident is the identification

LevelEvidenceConfidenceTypical use
Level 1Authentic standard: retention time and MS/MS matchHighestTargeted quantification, biomarker confirmation
Level 2Library MS/MS match (GNPS, HMDB, MassBank)GoodAnnotating untargeted differences
Level 3Accurate mass and isotope pattern onlyLowCandidates only — not a conclusion

Ask for the identification level of every reported metabolite. A report that gives names and scores without evidence cannot be used in a manuscript.

044. Deliverables to write into the contract

  • Raw data: mzML or vendor raw files, mapped one-to-one to samples
  • Non-normalised peak-area matrix plus the normalisation method and parameters
  • QC report: RSD distribution, PCA, batch-effect assessment
  • Identification table: name, m/z, retention time, adduct, identification level, match score
  • Analysis code or pipeline version for reproducibility
  • Biological interpretation: pathway enrichment (KEGG/HMDB) and statistics used

055. How Gereallife works

Gereallife (Shanghai Gereallife Biotech Co., Ltd.) runs LC-MS and sequencing platforms for multi-omics services covering untargeted, targeted and widely targeted metabolomics, lipidomics, metabolic flux and isotope tracing, proteomics and sequencing. QC follows a QC-sample, blank and isotope-internal-standard workflow; raw data and non-normalised peak areas are delivered, and identification evidence is stated.

Q&AFAQ

Can untargeted and targeted analysis be combined?
Yes, and it is usually the right design: discover with untargeted analysis on the same samples, then confirm the interesting metabolites by targeted MRM quantification.
How many samples do I need?
It depends on effect size and variance. Cell or animal studies typically use at least 6–8 biological replicates per group; human studies require a power calculation based on the design, not a rule of thumb.
Can metabolomics establish mechanism?
No. Metabolomics shows differences and associations; mechanism needs flux analysis, isotope tracing or functional experiments. Presenting correlation as causation is a common reviewer objection.
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