Your Guide to Metabolomics

Study Design Success Series

Before you embark on a metabolomics study, there are several important considerations you should make—especially if you are going to work with a vendor to complete your study. In this series, we walk you through everything you need to know to ensure the success of your metabolomics study, including what to expect when working with Metabolon, at every step of the way—from designing your study to interpreting your data.

Chapters Guide

Chapter 0 — Your Guide to a Successful Metabolomic Study

Your Guide to a Successful Metabolomic Study will equip researchers to leverage metabolomics in their labs and workflows for a variety of indications throughout the life sciences. In particular, we will cover how to select metabolites, targeted versus untargeted analysis, appropriate technology and instrumentation, study design, control versus variant analysis, sample types, sample preparation, and effective analysis of metabolomics results.

Chapter 1 — Top 8 Questions to Ask Your Metabolomics Provider

Before you embark on a metabolomics study, there are several important considerations you should make—especially if you are going to work with a vendor to complete your study. Here, we arm you with the most important questions you need to ask in order to find the right vendor and complete your metabolomics study with confidence.

Chapter 2 — Metabolomics Study Workflow

Now that we’ve reviewed some of the most important considerations to make when deciding who to work with for your metabolomics studies (if you will not perform your studies in-house), it’s time to dive deep into the metabolomics study workflow. In this chapter, we provide an overview of each step in the workflow, from study design to data analysis and interpretation, and how Metabolon can help you each step of the way.

Chapter 3 — Building Your Metabolomic Study

As we discussed in the previous chapter of this guide, conducting a successful metabolomics analysis and interpretation begins with a well-designed study. There are a number of factors to consider when designing your study to ensure your protocol delivers high-quality results for drawing actionable insights. In this chapter, we’ll go over each of these factors, breaking the process down into simple steps with clear, easy-to-follow advice.

Chapter 4 — Sample Types for Metabolomics

In this chapter, we will take a closer look at the most common types of samples used in metabolomic studies. Many of the samples we will cover are human or animal in origin but can also include environmental samples, such as soil and water.

Chapter 5 — Metabolomics Sample Preparation, Storage, and Transportation

Regardless of the sample type, robust sample collection and transportation procedures must be established to preserve sample integrity. Failing to do so raises the risk of data variability, instrument interferences, and metabolite degradation. In this chapter, we provide an overview of the common steps underlying sample preparation, storage, and transportation.

Chapter 6 — Metabolomics Study Analysis, Interpretation, and Insights

Next comes the exciting moment when your data is returned! As you dive into the numbers, Metabolon scientists will help you turn your results into a story. In this chapter, we will go over the deliverables of your study analysis, interpretation, and insights.

Chapter 7 — The End of This Guide, The Beginning of Your Own Metabolomics studies

You are now equipped to build a metabolomics experimental workflow; we encourage you to refer to the previous chapters of this guide at any time and contact us for further information. Here’s a quick review of the main points of discussion in each chapter that you can use to find what you need quickly.

See how Metabolon can advance your path to preclinical and clinical insights

Why Metabolon?

Once you see the full value of metabolomics, the only remaining question is who does it best? While many laboratories have metabolite profiling or analytical chemistry capabilities, comprehensive metabolomics technologies are extremely rare. Accurate, unbiased metabolite identification across the entire metabolome introduces signal-to-noise challenges that very few labs are equipped to handle. Also, translating massive quantities of data into actionable information is slow, if not impossible, for most because proper interpretation takes two things that are in short supply: experience and a comprehensive database.

Only Metabolon has all four core metabolomics capabilities

R

Coverage

Ability to interrogate thousands of metabolites across diverse biochemical space, revealing new insights and opportunities

R

Comparability

Ability to integrate the data from different studies into the same dataset, in different geographies, among different patients over time

R

Competency

Ability to inform on proper study design, generate high‐quality data, derive biological insights, and make actionable recommendations

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Capacity

Ability to process hundreds of thousands of samples quickly and cost‐efficiently to service rapidly growing demand

Partner with Metabolon to access:

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A library of 5,400+ known metabolites, 2,000 in human plasma, all referenced in the context of biochemical pathways

  • That’s 5x the metabolites of the closest competitor
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Unparalleled depth and breadth of experience analyzing and interpreting metabolomic data to find meaningful results

  • 10,000+ projects with hundreds of clients
  • 3,500+ publications covering 500 diseases, including numerous peer-reviewed journals such as Cell, Nature and Science
  • Nearly 40 PhDs in data science, molecular biology, and biochemistry

Using our robust platform and visualization tools, our experts are uniquely able to tell you more about your molecule and develop assay panels to help you zero in on the results you need.

Contact Us

Talk with an expert

Request a quote for our services, get more information on sample types and handling procedures, request a letter of support, or submit a question about how metabolomics can advance your research.

Corporate Headquarters

617 Davis Drive, Suite 100
Morrisville, NC 27560

Mailing Address:
P.O. Box 110407
Research Triangle Park, NC 27709

+1 (919) 572-1711

+1 (919) 572-1721

International Headquarters

Metabolon GmbH

Zeppelinstraße 3
85399 Hallbergmoos
Germany

+49 89 99017752

References

1. Zgoda-Pols, J.R., et al., Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: investigation of nicotinic acid receptor agonists. Toxicol Appl Pharmacol, 2011. 255(1): p. 48-56.

2. Bryant, J.A., et al., The impact of an oral purified microbiome therapeutic on the gastrointestinal microbiome. Nat Med, 2026. 32(1): p. 186-196

3. McGovern, B .H., et al., SER-109, an Investigational Microbiome Drugto Reduce Recurrence After Clostridioides difficile Infection: Lessons Learned From a Phase 2 Trial. Clin Infect Dis, 2021. 72(12): p. 2132-2140.

4. Feuerstadt, P., et al., SER-109, an Oral Microbiome Therapy for Recurrent Clostridioides difficile Infection. N Engl J Med, 2022. 386(3): p. 220-229.

5. Hu, Z., et al., Targeted metabolomics reveals novel diagnostic biomarkers for colorectal cancer. Mol Oncol, 2025. 19(6): p. 1737-1750.

6. Butler, F.M., et al., Vegetarian Dietary Patterns and Diet-Related Metabolites Are Associated With Kidney Function in the Adventist Health Study-2 Cohort. J Ren Nutr, 2025.

7. Stanford, J., et al., Metabolomic Profiling and Diet Quality Scoring in a Randomized Crossover Trial of Healthy and Typical Dietary Patterns. Mol Nutr Food Res, 2025 . 69(23): p. e70271.

8. O’Connor, L.E., et al., Metabolomic Profiling of an Ultraprocessed Dietary Pattern in a Domiciled Randomized Controlled Crossover Feeding Trial. J Nutr, 2023. 153(8): p. 2181-2192.

9. Fritsch, D.A., et al., Microbiome function underpins the efficacy of a fiber-supplemented dietary intervention in dogs with chronic large bowel diarrhea. BMC Vet Res, 2022. 18(1): p. 245.

10. Leal, L.N., et al., Preweaning nutrient supply improves lactation productivity and reduces the risk of culling in Holstein cows. J Dairy Sci, 2025. 108(6): p. 5875-5888.

11. Ahsin, M., et al., Soil and pasture health underlie improved beef nutrient density determined by untargeted metabolomics in Southern US grass finished beef systems. NPJ Sci Food, 2025. 9(1): p. 151.

12. Yin, W., et al., Plasma lipid profiling across species for the identification of optimal animal models of human dyslipidemia. J Lipid Res, 2012. 53(1): p. 51-65.

13. Porter, F .D., et al., Cholesterol oxidation products are sensitive and specific blood-based biomarkers for Niemann-Pick C1 disease. Sci Transl Med, 2010. 2(56): p. 56ra81.

14. Needham, B .D., et al., Plasma and Fecal Metabolite Profiles in Autism Spectrum Disorder. Biol Psychiatry, 2021. 89(5): p. 451-462

15. Li, C., et al., Estradiol and mTORC2 cooperate to enhance prostaglandin biosynthesis and tumorigenesis in TSC2-deficient LAM cells. J Exp Med, 2014. 211(1): p. 15-28.

16. Green, P.G., et al., Metabolic flexibility and reverse remodelling of the failing human heart. Eur Heart J, 2025. 46(25): p. 2422-2433.

17. Maekawa, H., et al., SGLT2 inhibition protects kidney function by SAM-dependent epigenetic repression of inflammatory genes under metabolic stress. J Clin Invest, 2025. 135(19).

18. Wu, D., et al., Integrated screens reveal that guanine nucleotide depletion, which is irreversible via targeting IMPDH2, inhibits pancreatic cancer and potentiates KRAS inhibition. Gut, 2026.

19. Schwerdtfeger, L.A., et al., Gut microbiota and metabolites are linked to disease progression in multiple sclerosis. Cell Rep Med, 2025. 6(4): p. 102055.

20. Wu, H., et al., Microbiome-metabolome dynamics associated with impaired glucose control and responses to lifestyle changes. Nat Med, 2025. 31(7): p. 2222-2231.

21. Jacobs, J.P., et al., Cognitive behavioral therapy for irritable bowel syndrome induces bidirectional alterations in the brain-gut-microbiome axis associated with gastrointestinal symptom improvement. Microbiome, 2021. 9(1): p. 236.

22. Pietzner, M., et al., Plasma metabolites to profile pathways in noncommunicable disease multimorbidity. Nat Med, 2021. 27(3): p. 471-479.

23. Faquih, T.O., et al., Robust Metabolomic Age Prediction Based on a Wide Selection of Metabolites. J Gerontol A Biol Sci Med Sci, 2025. 80(3).

24. Scherer, N., et al., Coupling metabolomics and exome sequencing reveals graded effects of rare damaging heterozygous variants on gene function and human traits. Nat Genet, 2025. 57(1): p. 193-205.

25. Holmes, Z.C., et al., Untargeted metabolomic analysis of human milk from healthy mothers reveals drivers of metabolite variability. Sci Rep, 2024. 14(1): p. 20827.

26. Titz, B., et al., Implications of Ocular Confounding Factors for Aqueous Humor Proteomic and Metabolomic Analyses in Retinal Diseases. Transl Vis Sci Technol, 2024. 13(6): p. 17.

27. Bloom, S.M., et al., Cysteine dependence of Lactobacillus iners is a potential therapeutic target for vaginal microbiota modulation. Nat Microbiol, 2022. 7(3): p. 434-450.

28. Leimer, E.M., et al., Lipid profile of human synovial fluid following intra-articular ankle fracture. J Orthop Res, 2017. 35(3): p. 657-666.