Author: Caimei Li, Senior Scientist at Creative Proteomics (LinkedIn). RUO. Last updated: January 2026
The Creative Proteomics Metabolomics Team comprises PhD‑ and MSc‑level scientists, senior LC–MS analysts, and sample logistics specialists with extensive hands‑on experience in bioanalytical workflows. Our intake procedures and methods are governed by documented SOPs and an internal QA review process; the laboratory follows ISO‑aligned quality management practices. These credentials and systems support reproducible pre‑analytical handling and inform the practical, operational checklist below.
Disclosure: This article provides RUO, non‑diagnostic guidance.
Quick Start: The 60‑Second Sample Checklist
If you've only got a minute, confirm these six items before shipping. It's the fastest way to avoid preventable delays and re‑runs.
- Sample volume meets matrix minimum; reserve extra for re‑run.
- Tube type/additives are uniform across the study (record vendor/lot).
- Processing timeline captured: draw→centrifuge→aliquot→freeze within stated windows.
- Storage temperature appropriate for duration (−80 °C long‑term); aliquots to limit freeze–thaw.
- Randomization and batch notes prepared; plan pooled QC cadence.
- Metadata template completed and mapped 1:1 to Sample IDs.
Light CTA: For scope alignment and intake readiness, see our metabolomics services.
Untargeted metabolomics sample checklist covering volume, tubes, storage, freeze–thaw, randomization, and metadata.
Why Sample Handling Matters More in Untargeted Metabolomics
Small molecules are reactive and dynamic. Delays, temperature excursions, or the wrong additives can reshape metabolite profiles, reducing peak areas and detection rates. Proper handling preserves features, reduces missing values, and makes batch correction work better.
Proper sample handling improves feature detection and reduces missing values in untargeted metabolomics.
According to community QA surveys and facility guidance, rapid processing and consistent consumables reduce batch effects and lower re‑run risk. See for example the pooled‑QC run‑order norms summarized by Broeckling et al. in 2023 and delayed‑processing impacts reported by Debik et al. (2022) in Analytical Chemistry.
Standards Mapping: How this checklist aligns with community guidelines
- Metadata and submission format: Our CSV header fields (Sample_ID, matrix, timestamps, processing, storage, freeze–thaw, run‑order, QC plan) map directly to ISA‑Tab Investigation/Study/Assay structure used by MetaboLights. See EMBL‑EBI's 2024 MetaboLights ISA‑Tab submission page for required descriptors and FAIR metadata expectations.
- QC cadence and batch design: The pooled‑QC every ~6–10 injections, blanks at method changes, and bookend QCs recommended here are consistent with Kirwan et al.'s 2022 mQACC QA/QC reporting recommendations in Analytical Chemistry, which emphasize routine pooled QCs, system‑suitability checks, and explicit acceptance criteria over prescriptive fixed frequencies.
- Reporting essentials and ID levels: Recording tube/additive, centrifugation force/time, time‑to‑freezer, storage temperature/duration, and declaring metabolite identification confidence (Levels 1–4) follows Sumner et al.'s 2007 MSI minimum reporting standards (Metabolomics), the foundational community guidance for untargeted LC–MS studies.
Minimum Sample Volume by Matrix for Untargeted Metabolomics Service (Serum, Plasma, Urine, Tissue, Cells, CSF)
Use these ranges as practical planning anchors. Actual needs vary by platform and study goals. When feasible, keep reserve aliquots for re‑runs and orthogonal assays.
| Matrix | Minimum (commonly required) | Recommended (best practice) | Notes |
|---|---|---|---|
| Serum | 200 µL | ≥ 500 µL | Supports duplicates and QC pool; record clot time. |
| Plasma (EDTA/heparin) | 200 µL | ≥ 500 µL | Keep anticoagulant uniform across cohorts. |
| Urine | 1 mL | ≥ 2–5 mL | Normalize to creatinine/osmolality if needed. |
| Tissue | 100–200 mg | ≥ 200–300 mg | Snap‑freeze; consider tissue type water content. |
| Cultured cells | 1–2 million | ≥ 2–5 million | Log cell line, passage, confluency. |
| CSF | 300 µL | ≥ 500 µL | If limited, prioritize aliquoting to minimize thaw. |
Recommended sample volume by matrix for untargeted metabolomics service planning and re‑run readiness.
Minimum vs Recommended reflects what is commonly required for interpretable data versus what tends to reduce variability and re‑work in metabolomics lab services.
Tube Type and Additives: What to Use—and What to Avoid
For blood‑derived samples, choose serum vs plasma based on study norms, then keep it consistent. EDTA plasma is widely used for LC–MS untargeted work; heparin plasma is also acceptable. Avoid switching anticoagulants mid‑study and avoid citrate/ACD for untargeted LC–MS due to additive signals and profile divergence.
Tube and additive selection workflow to reduce variability in metabolomics lab services.
- Minimum (commonly required): Uniform tube type/additive within a study; label tube type on forms; capture vendor and lot in metadata.
- Recommended/Strongly recommended: If using plasma, pre‑chill, process promptly, and aim for platelet‑poor or platelet‑free plasma with harmonized centrifugation settings across sites.
Note: For NMR‑only projects, EDTA peaks can interfere; align tube choice with platform. When in doubt, ask for a feasibility review before collection.
Processing Timeline: Centrifugation, Aliquoting, and Time‑to‑Freezer
Time is your most important variable. Document timestamps and keep windows tight.
A practical processing timeline that supports stable metabolite profiles in untargeted metabolomics.
- Minimum (commonly required):
- Blood to centrifuge: within ~30–60 min (serum requires clotting time; plasma keep chilled).
- Centrifugation: ~1500–2000 × g for 10–15 min; note temperature and brake settings.
- Aliquot and freeze at −80 °C as soon as possible; record time‑to‑freezer.
- Recommended/Strongly recommended:
- For platelet‑poor plasma: consider a second spin (~2000–3000 × g, 10 min) or a high‑g step (~4000 × g) with harmonized SOPs.
- Pre‑label solvent‑resistant tubes; aliquot single‑use volumes (e.g., 200–500 µL).
- Snap‑freeze tissue/cell pellets in LN₂ before −80 °C storage.
Storage and Shipping: Temperature, Dry Ice, and Packaging Rules
Match storage to holding time, and package for delays.
Dry‑ice shipping setup that protects sample integrity for untargeted metabolomics service workflows.
- Minimum (commonly required): • Long‑term −80 °C for raw biofluids, tissue, and cell pellets; document storage duration.
- Ship on dry ice with primary leak‑proof tubes inside secondary containment with absorbent; use an insulated shipper.
- Recommended/Strongly recommended: • Plan Mon–Tue arrivals; avoid holidays; include a temperature indicator/logger.
- Label "UN 1845 Dry Ice/Carbon Dioxide, Solid" with net dry ice weight; add Class 9 label and full addresses per carrier rules.
- Add extra dry ice to buffer 24–72 h delays; email tracking and packing list ahead of shipment.
Freeze–Thaw Limits: What's Safe, What's Risky
Every thaw adds risk. Some lipid classes and labile metabolites shift after only 1–2 cycles.
Freeze–thaw cycles can reduce data stability and increase missing values in untargeted metabolomics.
- Minimum (commonly required): Track freeze–thaw count for each aliquot in metadata.
- Strongly recommended: ≤1 freeze–thaw per aliquot for untargeted LC–MS. Use single‑use aliquots; quick thaw, process immediately; never refreeze pooled QC.
A conservative reading of recent public studies yields cautious benchmarks: one EDTA‑plasma series (24 donors, 1,026 compounds) found ~2% of metabolites shifted after three freeze–thaw cycles, while larger urine cohorts reported <0.3% of features affected after four cycles; reported magnitudes and directions depend on metabolite class, freezing/thawing method, and platform. See Goodman et al. 2021, Buchanan et al. 2022 and Chen et al. 2022. These study‑specific results support a conservative, RUO‑aware rule: aim for ≤1 freeze–thaw per aliquot and record any additional cycles for risk assessment.
Randomization and Batch Design: How to Reduce Batch Effects Upfront
Prevent group labels from becoming batch labels. Interleave cases/controls and place pooled QC regularly.
Example randomization and QC placement to reduce batch effects in metabolomics lab services.
- Minimum (commonly required): Provide a run‑order plan; include pooled QC and blanks per batch.
- Recommended/Strongly recommended: Interleave groups; stratify by key covariates (site, sex, age); inject pooled QC every ~6–10 samples with bookend QCs; add bridge QC across batches.
Micro‑example (compatible with Creative Proteomics intake): For 96 injections, alternate Case/Control with a pooled QC every 8 samples; include blanks after QCs and at method changes; repeat two pooled QCs at sequence start and end. For discovery‑only runs, this cadence balances drift monitoring with throughput. For more context on study design options, see our untargeted metabolomics service.
Metadata Template: What We Need to Interpret Results Correctly
Complete metadata enables traceability and robust statistics. Copy/paste the header and adapt as needed.
A metadata template helps untargeted metabolomics service teams control confounders and improve interpretation.
CSV header (Minimum fields first):
Sample_ID,Matrix,Collection_DateTime,Fasting_Status,Recent_Medications,Site_ID,Collection_Batch,Time_to_Centrifuge_min,Centrifuge_xg,Centrifuge_min,Processing_Temp,Time_to_Freezer_min,Aliquot_Count,Aliquot_Volume_uL,Tube_Type,Additive,Vendor,Lot,Storage_Temp_C,Storage_Duration_days,FreezeThaw_Count,Group,Batch,Randomization_Scheme,QC_Plan,Notes
Example row (illustrative):
S001,Plasma,2026-01-14 08:32,Overnight,None,HospA,CB01,25,1800,12,4C,75,4,250,Cryovial,EDTA,Greiner,LOT1234,-80,28,0,Case,B1,Interleaved_case_control,QC_every_8_injections,Platelet-poor plasma
Strongly recommended optional fields: age, sex, BMI, diet notes, hemolysis flag, storage location, thaw method.
Sample Intake Checklist (Download‑free) + Common Rejection Reasons
Before shipment, run a final intake check. If any item is at risk, contact us for a quick feasibility/risk review.
Common sample submission issues that delay untargeted metabolomics service timelines—and how to avoid them.
- Minimum (commonly required): Sample IDs map 1:1 to metadata; matrix and tube type declared; storage/temperature documented; volumes meet minima; shipping on dry ice with secondary containment.
- Recommended/Strongly recommended: Consistent tube/additive per cohort; −80 °C storage for long‑term; ≤1 freeze–thaw; pooled QC plan attached; declare lot numbers and processing timestamps.
Common rejection or rework triggers (with typical remediation):
- Insufficient volume or mass → provide reserve aliquots or recollect if critical.
- Warm on arrival/ice depleted → provide temperature excursion details; risk assessment required; may accept with caveats.
- Missing metadata or unlabeled tubes → submit completed template; reconcile IDs before intake.
- Mixed anticoagulants within a cohort → document and stratify, or recollect for consistency.
- Excess freeze–thaw or visible hemolysis/contamination → risk assessment; recollection may be advised.
Next steps: If you need a quick sample plan review, you can request it via our metabolomics services page. We keep this checklist ungated for easy copy/paste and printing.
References
- Delayed processing effects (Debik et al., 2022, Analytical Chemistry): Processing delays can shift metabolite profiles.
- QC cadence norms (Broeckling et al., 2023): Community survey on pooled QC placement and batch design.
- Serum vs plasma considerations (Vignoli et al., 2022): Comparative metabolomics of serum, EDTA, and heparin plasma.
- Dry ice packaging and labeling: University EHS quick guide for UN1845 dry ice shipments; IATA DGR addendum (Class 9 labeling).
