Polar Metabolites Analysis Service

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What Are Polar Metabolites and Why Analyze Them

Polar metabolites are small, water-soluble molecules that drive core biochemistry. They include amino acids, organic acids, nucleotides, and sugar phosphates. Together, they reflect glycolysis, the TCA cycle, and redox balance.

Polar metabolites analysis uncovers real-time pathway shifts under treatments or stress. It helps explain cellular energy use, biosynthetic demand, and cofactor status. These readouts support mechanism studies, bioprocess control, and quality assessment.

Because these compounds are highly hydrophilic, standard reversed-phase methods struggle. Dedicated workflows—such as HILIC-LC paired with mass spectrometry—improve retention, sensitivity, and coverage for confident decision-making.

Problems We Help You Solve

Creative Proteomics helps research teams overcome common challenges in polar metabolite analysis:

Inconsistent quantification across complex biological matrices
Low signal intensity for hydrophilic compounds in standard LC–MS workflows
Missing data points due to poor retention or early elution
Difficulty comparing studies due to batch effects and platform variability
Unclear metabolite identities in untargeted datasets
Limited panel coverage in pathway-specific studies

Our platform is designed to deliver high-confidence, decision-ready data even from challenging samples.

Our Polar Metabolite Analysis Capabilities

Targeted Metabolite Quantification
Absolute or relative quantification of key polar metabolites using internal standards and calibration curves.
Untargeted Polar Metabolomics
Broad-spectrum profiling to uncover metabolic shifts, differential features, or unknown biomarkers.
Pathway-Specific Panels
Focused analysis of glycolysis, TCA cycle, pentose phosphate pathway, amino acid metabolism, or nucleotide turnover.
Isotope-Labeled Metabolic Flux Analysis
¹³C/¹⁵N tracer experiments to track flux through central metabolic pathways under defined conditions.
Matrix-Specific Method Development
Custom optimization for plasma, serum, urine, tissue, cell lysate, microbial broth, or plant material to ensure compatibility and reproducibility.

Full List of Detectable Polar Metabolites

Our platform supports broad, research-grade coverage of polar metabolites. The table lists representative compounds by pathway or class. It is not exhaustive. If your target is missing, contact us for a custom panel or method fit.

Category	Representative Analytes
Central Carbon-Glycolysis / Gluconeogenesis	Glucose, Glucose-6-phosphate, Fructose-6-phosphate, Fructose-1,6-bisphosphate, Glyceraldehyde-3-phosphate, Dihydroxyacetone phosphate, 3-Phosphoglycerate, 2-Phosphoglycerate, Phosphoenolpyruvate, Pyruvate, Lactate
Pentose Phosphate Pathway (PPP)	Ribose-5-phosphate, Ribulose-5-phosphate, Xylulose-5-phosphate, Sedoheptulose-7-phosphate, Erythrose-4-phosphate, 6-Phosphogluconate
TCA Cycle & Anaplerosis	Citrate, Isocitrate, α-Ketoglutarate, Succinyl-CoA, Succinate, Fumarate, Malate, Oxaloacetate, Acetyl-CoA, Citraconate, Itaconate
Amino Acids & Derivatives	Alanine, Arginine, Asparagine, Aspartate, Cysteine, Glutamate, Glutamine, Glycine, Histidine, Isoleucine, Leucine, Lysine, Methionine, Phenylalanine, Proline, Serine, Threonine, Tryptophan, Tyrosine, Valine, Hydroxyproline, GABA
Urea Cycle & Nitrogen Metabolism	Ornithine, Citrulline, Argininosuccinate, Urea, Ammonium, Creatine, Creatinine
Nucleotides (Ribo/Deoxyribo) & Bases	AMP/ADP/ATP, GMP/GDP/GTP, CMP/CDP/CTP, UMP/UDP/UTP, dAMP/dADP/dATP, dGMP/dGDP/dGTP, dCMP/dCDP/dCTP, dTMP/dTDP/dTTP, Inosine, Hypoxanthine, Xanthine, Adenosine, Guanosine, Cytidine, Uridine
Nucleotide Sugars	UDP-Glucose, UDP-Galactose, UDP-N-acetylglucosamine (UDP-GlcNAc), UDP-N-acetylgalactosamine (UDP-GalNAc), UDP-Glucuronic acid, CDP-Choline, CMP-Neu5Ac
Coenzymes & Acyl-CoAs*	Coenzyme A, Acetyl-CoA, Succinyl-CoA, Malonyl-CoA, Propionyl-CoA, Butyryl-CoA, Isobutyryl-CoA, Crotonyl-CoA
Redox Cofactors & Thiols	NAD⁺/NADH, NADP⁺/NADPH, FAD, FMN, Glutathione (GSH/GSSG), Cystine, Cystathionine, Thioredoxin (peptide-level optional)
One-Carbon & Methylation	SAM (S-adenosylmethionine), SAH, Homocysteine, Methionine, 5-Methyl-THF (coverage method-dependent), Choline, Betaine
Organic Acids (Broad)	Acetate, Formate, Propionate, Butyrate, Glyoxylate, Tartrate, Malonate, Pyroglutamate, 3-Hydroxybutyrate
Osmolytes & Quaternary Amines	Choline, Betaine, Carnitine, Acetylcarnitine, Trimethylamine N-oxide (TMAO), Taurine
Polyamines & Biogenic Amines	Putrescine, Spermidine, Spermine, Agmatine, Ethanolamine
Sugar Alcohols & Polyols	Inositol (myo-/scyllo-), Sorbitol, Mannitol, Glycerol
Sugar Derivatives	N-Acetylglucosamine (free), N-Acetylgalactosamine (free), Glucosamine, Galactosamine
Vitamins & Water-Soluble Cofactors†	Thiamine (B1), Riboflavin (B2), Niacinamide/Nicotinic acid (B3), Pantothenate (B5), Pyridoxal-5'-phosphate (B6), Biotin (B7), Folates†, Ascorbate
Miscellaneous Polar Compounds	Uric acid, Allantoin, Inosine monophosphate (IMP), 3-Methylhistidine, Trimethyllysine

* Acyl-CoA species require dedicated extraction and LC methods.

† Certain folates and labile vitamers may need targeted stabilization and protected handling.

Note: This is a partial, representative list. We routinely expand or customize panels for specific species, matrices, or pathways. If you do not see your target, contact us to discuss feasibility and method development.

Why Choose Our Polar Metabolite Analysis Service?

Quantitative linearity

Multi-point calibration typically achieves R² ≥ 0.995 across working ranges.

Low variability

System suitability and pooled-QC controls keep inter-batch CV commonly ≤ 15%.

Sensitive detection

Optimized HILIC–MS/MS methods reach femtomole to low-picomole on-column limits.

Retention confidence

RT windows locked with internal standards reduce mismatches and carryover risk.

Isotope normalization

Stable-isotope spikes correct matrix effects for more reliable concentrations.

Batch comparability

Drift correction and RT alignment improve cross-study comparability and trend analysis.

Coverage depth

Curated panels span central carbon, nucleotides, sugar phosphates, and thiol/redox species.

LC–MS/MS Platforms and Detection Parameters for Polar Metabolites

Our polar metabolite analysis service is built on a robust LC–MS/MS framework designed to handle the chemical diversity and hydrophilicity of low-abundance metabolites. All analyses are conducted under strict quality controls to ensure accuracy, sensitivity, and reproducibility across sample types.

We primarily use hydrophilic interaction liquid chromatography (HILIC) coupled with:

Orbitrap Exploris 480

High-resolution mass spectrometry (HRMS) for untargeted profiling and metabolite identification.

Mass accuracy: < 2 ppm
Resolution: up to 480,000 FWHM

SCIEX Triple Quad™ 6500 Plus

Targeted MRM-based quantification with high sensitivity and low background noise.

Dynamic range: > 10⁵
Inter-batch RSD: ≤ 15% (QC-controlled)

Separation is optimized using 2.1 × 100 mm HILIC columns (1.7 µm), with temperature control (±0.1 °C) to stabilize retention times. Internal standards and pooled QC samples are included in every batch to support multi-point calibration (R² ≥ 0.995) and accurate cross-sample comparisons.

Orbitrap Exploris 480 (Figure from Thermo)

SCIEX Triple Quad™ 6500+ (Figure from Sciex)

Polar Metabolite Analysis Workflow: Step by Step

Scope & Panel Definition

Confirm target pathways, matrices, targeted vs untargeted goals, and internal standards strategy.

Sample Intake & Pre-Analytical QC

Verify labeling, storage conditions, and aliquot integrity; add process controls and pooled QC.

Extraction & Quenching

Perform cold methanol/water quench, protein precipitation, and optional SPE or filtration to reduce matrix load.

Chromatography Setup

Select HILIC or ion-pair reversed-phase methods; lock retention windows using reference standards.

MS Acquisition

Run targeted MRM/PRM for quantification and HRMS (DDA/DIA) for discovery; include bracketed QC injections for drift monitoring.

Data Reduction & QC Review

Execute peak picking, isotope-normalized quantification, calibration fitting, RT alignment, and batch correction with predefined acceptance criteria.

Pathway Interpretation & Reporting

Map significant changes to metabolic networks; compile figures and tables for immediate downstream use.

Sample Requirements for Polar Metabolites Profiling

The following guidelines help protect labile polar compounds and ensure high-quality data. If your matrix differs or input is limited, contact us for a fit-for-purpose plan.

Sample Type	Minimum Amount	Container	Pretreatment	Storage	Shipping
Plasma / Serum	100 µL	Screw-cap cryovial	Fast separation from cells; avoid hemolysis	−80 °C	Dry ice
Whole Blood	300 µL	EDTA tube + cryovial	Immediate cold quench, spin ≤10 min	−80 °C	Dry ice
Urine	500 µL	Screw-cap cryovial	Mix well; avoid preservatives	−80 °C	Dry ice
Tissue (mammalian)	50–100 mg	Pre-cooled cryotube	Snap-freeze in liquid N₂; no buffer	−80 °C	Dry ice
Cell Pellet	≥1×10⁶ cells	Cryovial	Wash in cold PBS; remove supernatant fully	−80 °C	Dry ice
Microbial Pellet	Wet pellet from 10–20 mL culture	Cryovial	Rapid chill; remove media thoroughly	−80 °C	Dry ice
Plant Material	100–200 mg	Pre-cooled cryotube	Flash-freeze; avoid water rinses	−80 °C	Dry ice
Culture Supernatant / Media	1–2 mL	Screw-cap tube	Clarify by cold spin; no additives	−80 °C	Dry ice
Extracts (if self-prepared)	100–200 µL	LC-compatible vial	80% MeOH/H₂O, cold; no salts/detergents	−80 °C	Dry ice

What You Receive: Deliverables from Our Polar Metabolite Analysis

Raw LC–MS/MS files (.raw/.wiff) with run logs
Quant tables (peak areas, concentrations) with internal-standard normalization, calibration fit, QC flags (CSV/XLSX)
ID evidence (retention time, precursor/fragment ions, mass error, reference match notes)
QC summary (pooled-QC trends, RT stability, carryover checks, batch diagnostics)
Figures (annotated chromatograms, MS/MS spectra, PCA/volcano plots, pathway overlays)
Methods brief (column, mobile phase, key MS parameters, processing settings)
README & data dictionary (file map, variable definitions, units)

Overlayed EIC traces of lactate demonstrating consistent retention time and peak intensity across QC and replicate injections

Extracted Ion Chromatogram (EIC) Overlays

Scatter plot showing linear calibration fit and residual plot verifying high correlation and homoscedasticity for polar metabolite quantification.

Calibration Curve with Residual Plot

PCA score plot showing tight QC clustering and distinct sample group separation, indicating consistent analytical performance.

PCA Score Plot (QC vs. Samples)

Central carbon metabolism map with glycolysis, PPP, and TCA nodes colored by log₂ fold-change to visualize metabolic shifts.

Metabolic Pathway Impact Map

Applications of Polar Metabolites Analysis in Research and Industry

Metabolic Pathway Mapping

Investigation of polar metabolites to reconstruct metabolic networks and understand cellular processes in model organisms.

Environmental Monitoring

Analysis of polar metabolites in environmental samples (e.g., water, soil) to assess ecosystem health and detect pollutants.

Biofuel Production

Monitoring of microbial metabolic pathways for the development of efficient biofuel production processes from renewable resources.

Food Quality Control

Detection of polar metabolites in food products to ensure freshness, flavor consistency, and quality during production and storage.

Agricultural Research

Study of plant metabolic profiles to understand responses to stress, optimize crop yield, and enhance plant resilience.

Drug Mechanism Studies

Track intracellular metabolite shifts to uncover target-related metabolic disruptions.

Why use HILIC–LC–MS for polar metabolites?

Because highly hydrophilic analytes elute early or co-elute in reversed-phase; HILIC improves retention, separation of isomers, and coverage for small polar compounds, especially when paired with high-resolution MS.

Targeted vs. untargeted metabolomics—how do I choose?

Use targeted when you need precise quantification of a defined panel with internal standards; use untargeted to discover broad pathway shifts and unknowns—many labs combine both sequentially or in hybrid workflows.

How do you control matrix effects and ion suppression?

Matrix-matched calibration, stable-isotope internal standards, blanks, and post-acquisition normalization with pooled QC samples reduce bias and improve quantitative reliability.

What QC design do you use to ensure reproducibility?

We incorporate pooled QC injections at intervals to track drift, assess precision, and enable correction; this approach is widely recommended in LC–MS metabolomics.

Do I need isotope-labeled standards for every metabolite?

Not necessarily; a rational set of labeled surrogates and check standards can anchor quantification and method performance across classes when one-to-one standards are impractical.

Which sample types are suitable for polar metabolomics?

Common matrices include plasma/serum, urine, tissues, cells, microbes, and plant material; protocols typically use cold organic quenching and HILIC-MS in positive/negative modes.

How are batch effects handled across large studies?

Retention-time alignment, intensity drift correction using pooled QC, and standardized acquisition sequences (samples interleaved with QCs and blanks) are standard practice.

Can you resolve near-isomers (e.g., sugar phosphates)?

Yes—HILIC chemistries and optimized MS/MS fragments improve separation and identification confidence for isomeric sugar phosphates and related polar intermediates.

What information accompanies identifications beyond m/z?

High-resolution mass accuracy, retention time against libraries, and MS/MS spectral matching (with ppm error and fragment annotation) underpin assignment confidence.

Can results be integrated with other omics?

Processed matrices with standardized IDs and QC metrics are designed for downstream pathway mapping and multi-omics correlation in established workflows.

MS-CETSA functional proteomics uncovers new DNA-repair programs leading to Gemcitabine resistance

Nordlund, P., Liang, Y. Y., Khalid, K., Van Le, H., Teo, H. M., Raitelaitis, M., ... & Prabhu, N.

Journal: Research Square

Year: 2024

DOI: https://doi.org/10.21203/rs.3.rs-4820265/v1

High Levels of Oxidative Stress Early after HSCT Are Associated with Later Adverse Outcomes

Cook, E., Langenberg, L., Luebbering, N., Ibrahimova, A., Sabulski, A., Lake, K. E., ... & Davies, S. M.

Journal:Transplantation and Cellular Therapy

Year: 2024

DOI: https://doi.org/10.1016/j.jtct.2023.12.096

Multiomics of a rice population identifies genes and genomic regions that bestow low glycemic index and high protein content

Badoni, S., Pasion-Uy, E. A., Kor, S., Kim, S. R., Tiozon Jr, R. N., Misra, G., ... & Sreenivasulu, N.

Journal: Proceedings of the National Academy of Sciences

Year: 2024

DOI: https://doi.org/10.1073/pnas.2410598121

The Brain Metabolome Is Modified by Obesity in a Sex-Dependent Manner

Norman, J. E., Milenkovic, D., Nuthikattu, S., & Villablanca, A. C.

Journal: International Journal of Molecular Sciences

Year: 2024

DOI: https://doi.org/10.3390/ijms25063475

UDP-Glucose/P2Y14 Receptor Signaling Exacerbates Neuronal Apoptosis After Subarachnoid Hemorrhage in Rats

Kanamaru, H., Zhu, S., Dong, S., Takemoto, Y., Huang, L., Sherchan, P., ... & Zhang, J. H.

Journal: Stroke

Year: 2024

DOI: https://doi.org/10.1161/STROKEAHA.123.044422

Pan-lysyl oxidase inhibition disrupts fibroinflammatory tumor stroma, rendering cholangiocarcinoma susceptible to chemotherapy

Burchard, P. R., Ruffolo, L. I., Ullman, N. A., Dale, B. S., Dave, Y. A., Hilty, B. K., ... & Hernandez-Alejandro, R.

Journal: Hepatology Communications

Year: 2024

DOI: https://doi.org/10.1097/HC9.0000000000000502

Comparative metabolite profiling of salt sensitive Oryza sativa and the halophytic wild rice Oryza coarctata under salt stress

Tamanna, N., Mojumder, A., Azim, T., Iqbal, M. I., Alam, M. N. U., Rahman, A., & Seraj, Z. I.

Journal: Plant‐Environment Interactions

Year: 2024

DOI: https://doi.org/10.1002/pei3.10155

Teriflunomide/leflunomide synergize with chemotherapeutics by decreasing mitochondrial fragmentation via DRP1 in SCLC

Mirzapoiazova, T., Tseng, L., Mambetsariev, B., Li, H., Lou, C. H., Pozhitkov, A., ... & Salgia, R.

Journal: iScience

Year: 2024

DOI: https://doi.org/10.1016/j.isci.2024.110132

Physiological, transcriptomic and metabolomic insights of three extremophyte woody species living in the multi-stress environment of the Atacama Desert

Gajardo, H. A., Morales, M., Larama, G., Luengo-Escobar, A., López, D., Machado, M., ... & Bravo, L. A.

Journal: Planta

Year: 2024

DOI: https://doi.org/10.1007/s00425-024-04484-1

A personalized probabilistic approach to ovarian cancer diagnostics

Ban, D., Housley, S. N., Matyunina, L. V., McDonald, L. D., Bae-Jump, V. L., Benigno, B. B., ... & McDonald, J. F.

Journal: Gynecologic Oncology

Year: 2024

DOI: https://doi.org/10.1016/j.ygyno.2023.12.030

Glucocorticoid-induced osteoporosis is prevented by dietary prune in female mice

Chargo, N. J., Neugebauer, K., Guzior, D. V., Quinn, R. A., Parameswaran, N., & McCabe, L. R.

Journal: Frontiers in Cell and Developmental Biology

Year: 2024

DOI: https://doi.org/10.3389/fcell.2023.1324649

Proteolytic activation of fatty acid synthase signals pan-stress resolution

Wei, H., Weaver, Y. M., Yang, C., Zhang, Y., Hu, G., Karner, C. M., ... & Weaver, B. P.

Journal: Nature Metabolism

Year: 2024

DOI: https://doi.org/10.1038/s42255-023-00939-z

Quantifying forms and functions of intestinal bile acid pools in mice

Sudo, K., Delmas-Eliason, A., Soucy, S., Barrack, K. E., Liu, J., Balasubramanian, A., … & Sundrud, M. S.

Journal: bioRxiv

Year: 2024

DOI: https://doi.org/10.1101/2024.02.16.580658

Elevated SLC7A2 expression is associated with an abnormal neuroinflammatory response and nitrosative stress in Huntington's disease

Gaudet, I. D., Xu, H., Gordon, E., Cannestro, G. A., Lu, M. L., & Wei, J.

Journal: Journal of Neuroinflammation

Year: 2024

DOI: https://doi.org/10.1186/s12974-024-03038-2

Thermotolerance capabilities, blood metabolomics, and mammary gland hemodynamics and transcriptomic profiles of slick-haired Holstein cattle during mid lactation in Puerto Rico

Contreras-Correa, Z. E., Sánchez-Rodríguez, H. L., Arick II, M. A., Muñiz-Colón, G., & Lemley, C. O.

Journal: Journal of Dairy Science

Year: 2024

DOI: https://doi.org/10.3168/jds.2023-23878

DNA stimulates SIRT6 to mono-ADP-ribosylate proteins within histidine repeats

Pederson, N. J., & Diehl, K. L.

Journal: bioRxiv

Year: 2024

DOI: https://doi.org/10.1101/2024.07.31.606047

Glycine supplementation can partially restore oxidative stress-associated glutathione deficiency in ageing cats

Ruparell, A., Alexander, J. E., Eyre, R., Carvell-Miller, L., Leung, Y. B., Evans, S. J., ... & Watson, P.

Journal: British Journal of Nutrition

Year: 2024

DOI: https://doi.org/10.1017/S0007114524000370

Untargeted metabolomics reveal sex-specific and non-specific redox-modulating metabolites in kidneys following binge drinking

Rafferty, D., de Carvalho, L. M., Sutter, M., Heneghan, K., Nelson, V., Leitner, M., ... & Puthanveetil, P.

Journal: Redox Experimental Medicine

Year: 2023

DOI: https://doi.org/10.1530/REM-23-0005

Sex modifies the impact of type 2 diabetes mellitus on the murine whole brain metabolome

Norman, J. E., Nuthikattu, S., Milenkovic, D., & Villablanca, A. C.

Journal: Metabolites

Year: 2023

DOI: https://doi.org/10.3390/metabo13091012

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

Liu, J. T., Doueiry, C., Jiang, Y. L., Blaszkiewicz, J., Lamprecht, M. P., Heslop, J. A., ... & Duncan, S. A.

Journal: Communications Biology

Year: 2023

DOI: https://doi.org/10.1038/s42003-023-04739-9

Methyl donor supplementation reduces phospho‐Tau, Fyn and demethylated protein phosphatase 2A levels and mitigates learning and motor deficits in a mouse model of tauopathy

van Hummel, A., Taleski, G., Sontag, J. M., Feiten, A. F., Ke, Y. D., Ittner, L. M., & Sontag, E.

Journal: Neuropathology and Applied Neurobiology

Year: 2023

DOI: https://doi.org/10.1111/nan.12931

Sex hormones, sex chromosomes, and microbiota: identification of Akkermansia muciniphila as an estrogen-responsive bacterium

Sakamuri, A., Bardhan, P., Tummala, R., Mauvais-Jarvis, F., Yang, T., Joe, B., & Ogola, B. O.

Journal: Microbiota and Host

Year: 2023

DOI: https://doi.org/10.1530/MAH-23-0010

Living in extreme environments: a photosynthetic and desiccation stress tolerance trade-off story, but not for everyone

Gajardo, H. A., Morales, M., López, D., Luengo-Escobar, M., Machado, A., Nunes-Nesi, A., ... & Bravo, L.

Journal: Authorea Preprints

Year: 2023

DOI: https://doi.org/10.22541/au.168311184.42382633/v2

Resting natural killer cell homeostasis relies on tryptophan/NAD+ metabolism and HIF‐1α

Pelletier, A., Nelius, E., Fan, Z., Khatchatourova, E., Alvarado‐Diaz, A., He, J., ... & Stockmann, C.

Journal: EMBO Reports

Year: 2023

DOI: https://doi.org/10.15252/embr.202256156

Function and regulation of a steroidogenic CYP450 enzyme in the mitochondrion of Toxoplasma gondii

Asady, B., Sampels, V., Romano, J. D., Levitskaya, J., Lige, B., Khare, P., ... & Coppens, I.

Journal: PLoS Pathogens

Year: 2023

DOI: https://doi.org/10.1371/journal.ppat.1011566