Cell Metabolomics Services — Targeted & Untargeted LC-MS/MS Metabolomics for Cellular Research

What is actually happening inside your cells right now? Transcriptomics tells you what could happen. Proteomics tells you what machinery is present. But only the metabolome — the ATP being consumed, the lactate being secreted, the acetyl-CoA being channeled into the TCA cycle — tells you what the cell is doing.

That is the value of cell metabolomics: a direct readout of metabolic pathway activity, substrate utilization, and the integrated response to genetic, pharmacological, or environmental perturbation. Our platform covers the full range — from targeted quantification of glycolysis, TCA cycle, and energy cofactor panels to untargeted global profiling and subcellular organelle metabolomics — on a single LC-MS/MS platform with pooled QC validation. For stable isotope tracing experiments, our metabolic flux analysis service captures ¹³C isotopologue distributions in central carbon intermediates. Need subpopulation resolution? Our single cell metabolomics service pushes profiling to individual cell level. For pathway-specific absolute quantification, see our targeted metabolomics service.

Our Cellular Metabolomics Capabilities — Targeted Quantification, Global Profiling & Subcellular Analysis

Key Challenges in Cell Metabolomics and How We Solve Them

• Metabolite Quenching & Turnover Artifacts — ATP has a half-life under 2 seconds in harvested cells; NADH is similar. If your quenching protocol takes minutes instead of seconds, you are not measuring metabolism — you are measuring degradation. Our cold methanol protocol completes quenching in under 30 seconds from dish to −80°C, validated at >95% recovery of ATP/ADP ratios versus fast-filtration reference methods.
• Low Biomass from Rare Cell Populations — FACS-sorted subsets, primary isolates, laser-capture microdissection — these yield micrograms of material, not milligrams. Standard extraction workflows drown the signal. Our micro-scale protocols handle inputs as low as 1×10⁵ cells, with MRM sensitivity down to 0.1 ng/mL, making pooling unnecessary for most targeted panels.
• Media Interference in Conditioned Media Analysis — FBS contains hundreds of metabolites. Without proper subtraction, you cannot distinguish what the cell secreted from what the serum contributed. We use dialyzed serum controls and media-blank subtraction as standard for exometabolome workflows — a simple step that many labs skip.
• Culture-Induced Metabolic Drift — Passage 5 cells are not metabolically identical to passage 25 cells. Confluence at harvest matters. Serum lot matters. We document these variables per sample and recommend n ≥ 6 biological replicates from independent wells — the minimum needed to resolve treatment effects from culture noise in most cell models.
• Multi-Omics Data Integration — A metabolite list alone does not tell you why the change happened. Is it transcriptional? Post-translational? Substrate-limited? Coordinated sampling for metabolomics, proteomics, and transcriptomics from the same experiment enables cross-platform correlation, and our multi-omics integration service provides the analytical framework to connect these layers.

Service Scope — Cell Metabolomics Panels & Analytical Coverage

Our cell metabolomics services cover the following analytical panels and metabolite categories. Each panel is optimized for cell extract matrices with pooled QC validation. Panels can be ordered individually or combined for broader metabolic coverage.

Core Quantification Panels

Advanced & Specialized Workflows

Instrumentation & Method Performance for Cell Metabolomics

Subcellular Fractionation

Differential centrifugation with OptiPrep density gradient enrichment. Mitochondrial, nuclear, cytosolic, and membrane fractions isolated from cell homogenates; organelle purity validated by western blot (COX IV, Lamin B1, GAPDH, Na+/K+-ATPase markers) per preparation.

Internal Standards & Calibration

• Internal Standards: Isotope-labeled analogs spiked at extraction for each metabolite class (¹³C/²H-labeled central carbon metabolites, ¹³C/¹⁵N-labeled amino acids, ¹³C-labeled energy cofactors)
• Calibration Strategy: 8-point standard curves, matrix-matched in cell extract
• System Suitability: Retention time stability (±0.1 min), mass accuracy (<5 ppm), ion ratio QC, carryover checks — at batch start and end

Data Processing & Metabolite Identification

• Targeted: Skyline / MultiQuant for automated peak integration with manual review
• Untargeted: XCMS / MS-DIAL for feature detection, peak alignment, gap-filling
• Identification: MS/MS spectral matching against HMDB, METLIN, and in-house libraries (matching score ≥ 0.7)
• QC Correction: Signal drift modeled and removed via LOESS fitting to pooled QC injections distributed across the batch; metabolites exceeding 30% RSD in pooled QCs are flagged in the final report

SCIEX QTRAP 6500+ Triple Quadrupole LC-MS/MS — primary platform for scheduled MRM targeted quantification (Figure from SCIEX)

Thermo Scientific Q-Exactive Orbitrap MS — high-resolution platform for untargeted discovery workflows (Figure from Thermo Fisher)

Cell Metabolomics Analysis Workflow — From Cell Culture to Biological Interpretation

1

Study Design & Cell Culture Consultation

We work with you to define cell line selection, treatment conditions, time points, replicates (n ≥ 6), and controls. Culture variables — passage number, confluence at harvest, serum lot, mycoplasma status — are documented and standardized to minimize pre-analytical variability. For subcellular studies, we recommend the optimal fractionation strategy based on target organelles and pathway focus.

2

Cell Harvesting & Metabolite Quenching

• Adherent cells: Cold PBS wash → methanol quenching (−80°C) on dish → scrape-and-transfer within 30 s
• Suspension cells: Rapid centrifugation → pellet flash-frozen in liquid N₂
• Conditioned media collected separately for exometabolome analysis
• Cell count and viability recorded per sample for normalization
• Isotope-labeled internal standards spiked at extraction

3

Metabolite Extraction & Subcellular Fractionation (Optional)

• Biphasic extraction (methanol/water/chloroform) for polar and non-polar metabolites; protein normalization from interphase pellet
• Subcellular fractionation (optional): Differential centrifugation yields nuclear, mitochondrial, microsomal/membrane, and cytosolic fractions
• Organelle purity validated by western blot (COX IV, Lamin B1, GAPDH, Na+/K+-ATPase)

4

LC-MS/MS Data Acquisition

• Targeted: UPLC-MRM/MS with scheduled acquisition
• Untargeted: High-resolution Orbitrap DDA with polarity switching (HILIC + C18, 20-min gradient)
• Pooled QCs every 8 samples; extraction and solvent blanks at batch start and end
• System suitability: RT stability ±0.1 min, mass accuracy <5 ppm

5

Quality Control & Data Processing

• Automated peak integration with manual analyst review
• RSD >30% in pooled QCs → flagged; QC-LOESS drift correction across long sequences
• Calibration curve evaluation: R² and back-calculated accuracy per analyte
• Untargeted: Feature filtering, peak alignment, gap-filling, MS/MS library matching (HMDB, METLIN, in-house)

6

Statistical Analysis & Biological Interpretation

• Univariate: t-test, ANOVA with FDR correction, fold-change analysis, volcano plots
• Multivariate: PCA, PLS-DA, OPLS-DA with permutation testing and VIP scoring
• Pathway enrichment: KEGG, Reactome, MetaboAnalyst, and MSEA
• Integrated KEGG pathway maps with fold-change coloring
• Publication-ready figure generation

Why Choose Our Cell Metabolomics Services?

• Subcellular Metabolomics
  Whole-cell extracts average the compartment-specific signals that matter most. Our validated fractionation protocol isolates mitochondria, nuclei, cytosol, and membranes — each confirmed by organelle-marker western blot — so you see TCA cycle activity where it happens, nuclear acetyl-CoA pools where epigenetics is regulated, and cytosolic glycolysis separate from mitochondrial oxidation. This is not a niche add-on; for many questions it is the difference between signal and noise.
• Targeted + Untargeted from One Pellet
  Split a single cell extract for both absolute quantification of known pathways and discovery profiling of the unexpected. Targeted gives you concentration numbers reviewers demand (pmol/10⁶ cells, R² ≥ 0.99); untargeted catches the metabolite changes you did not hypothesize. Run both and correlate the results — regulated pathways validate each other.
• Rigorous QC, Documented
  Pooled QCs every 8 samples. Isotope-labeled IS in every tube. Extraction blanks. System suitability before and after each batch. QC-LOESS drift correction. RSD flags at 30%. If a metabolite fails QC, you know before you interpret it — and every metric is in the report for your methods section and reviewer scrutiny.
• Cell Type Experience Matters
  Protocols we validate on HeLa do not automatically transfer to primary neurons or suspension T cells. We maintain optimized extraction and quenching SOPs per cell category — cancer lines, primary cells, stem cells, immune subsets, 3D cultures — and we match the protocol to your model during study design, not after the first batch fails.
• True Multi-Omics Integration
  Metabolomics answers "what changed." To answer "why," coordinate with proteomics and lipidomics from parallel pellets of the same experiment. Same cells, same time points, same biological noise — different analytical windows. Cross-platform correlation analysis connects metabolite shifts to enzyme abundance changes directly.
• PhD-Level Support, Start to Finish
  Study design. Cell culture prep. Quenching validation. Panel selection. Data QC review. Multivariate modeling. Pathway interpretation. Figure preparation. Your project has a dedicated scientist who understands the biology, not just the chromatography.

Applications of Cell Metabolomics — From Cancer Biology to Drug Discovery

Supported Cell Types & Culture Models

Cell Metabolomics Data Deliverables & Analysis Report

Scheduled MRM chromatogram overlay: simultaneous detection of 40+ central carbon metabolites in HeLa cell extract across a 20-minute LC-MS/MS run, demonstrating resolved glycolytic and TCA cycle intermediates.

8-point ATP calibration curve (R² = 0.999) in HeLa cell extract matrix with isotope-labeled ATP-¹³C₁₀ internal standard, demonstrating linear range spanning 4 orders of magnitude and QC accuracy within 95–105%.

PCA scores plot showing tight clustering of pooled QC samples (center, green) confirming instrument stability across a 96-sample cell metabolomics batch, with clear biological group separation between control and treated conditions.

KEGG pathway enrichment network map showing significantly altered metabolic pathways in cancer cell metabolomics, with node size proportional to pathway impact and color intensity reflecting fold-change direction.

Case Study — iPSC-Derived Hepatocyte Drug Screening with Targeted Metabolomics

A human iPSC-derived hepatocyte screen identifies compounds that inhibit production of Apolipoprotein B

Liu, J.T., Doueiry, C., Jiang, Y.L., et al. | Communications Biology, 2023

DOI: 10.1038/s42003-023-04739-9

Background

Excess Apolipoprotein B (ApoB) drives LDL cholesterol accumulation and cardiovascular disease risk. Small-molecule inhibitors of ApoB secretion represent an attractive therapeutic strategy — but primary human hepatocytes, the gold-standard model, are scarce, donor-variable, and lose function within days in culture. Human iPSC-derived hepatocytes (hiPSC-Heps) offer a replenishable, genetically human alternative, yet had not been systematically validated for metabolic drug screening at scale.

Challenge: Establish a high-throughput, human-relevant hepatocyte screening platform that recapitulates hepatic lipid metabolism and ApoB secretion, and validate it with targeted metabolomic readouts that confirm on-target pharmacology.

Findings (from the published study)

• hiPSC-Heps were differentiated, characterized for hepatocyte markers, and deployed in a 384-well format screen of 6,000+ compounds for ApoB-lowering activity.
• Multiple hit compounds were identified that reduced ApoB secretion without cytotoxicity, confirmed by orthogonal ELISA and metabolic assays.
• Targeted bile acid quantification by LC-MS/MS — performed by Creative Proteomics — measured 9 bile acid species (cholic acid, glycocholic acid, glycochenodeoxycholic acid, taurocholic acid, chenodeoxycholic acid, taurochenodeoxycholic acid, deoxycholic acid, glycodeoxycholic acid, taurodeoxycholic acid) in conditioned media from compound-treated hiPSC-Heps.
• Bile acid profiles confirmed that hepatic metabolic function was preserved in the iPSC model and that hit compounds modulated bile acid metabolism alongside ApoB secretion — demonstrating coordinated lipid pathway effects.
• The study validates hiPSC-Heps as a scalable, human-relevant platform for metabolic drug discovery, bridging the gap between immortalized cell lines and primary human tissue.

Process Insight

This study established a workflow connecting iPSC differentiation QC, high-content screening, ELISA-based ApoB quantification, and targeted LC-MS/MS metabolomic validation — all within the same cellular model. The integration of bile acid profiling with ApoB secretion data provided a richer pharmacological picture than either readout alone, distinguishing compounds that specifically target ApoB processing from those that broadly disrupt hepatocyte lipid metabolism.

Where Our Cell Metabolomics Service Fits

Creative Proteomics supports cell-based drug screening programs with targeted metabolomics readouts that complement phenotypic screening:

• Targeted bile acid, central carbon, energy cofactor, and lipid mediator panels — from the same conditioned media or cell pellet — to characterize compound mechanism of action beyond the primary screen readout.
• LC-MS/MS (MRM) with isotope-dilution absolute quantification, delivering concentration data (pmol/10⁶ cells) suitable for dose-response modeling, cross-compound comparisons, and regulatory documentation.
• Cell-type-matched protocols including validated quenching and extraction SOPs for iPSC-derived models, primary cells, and 3D organoids — ensuring data quality from human-relevant cell platforms, not just immortalized lines.

Reference

1. Liu, J.T., Doueiry, C., Jiang, Y.L., et al. A human iPSC-derived hepatocyte screen identifies compounds that inhibit production of Apolipoprotein B. Communications Biology 6, 452 (2023).

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