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Metabolic Research

IROA® Biochemical Quantitation Kits

IROA® Biochemical Quantitation Kits

  • IROA® Biochemical Quantitation Kits
An innovative technology termed isotopic ratio outlier analysis (IROA) was developed to overcome the analytical challenges associated with current, stable isotope-labeled compounds used in untargeted/targeted metabolic profiling. These challenges minimally pertain to analytical variance, artifactual peaks, and metabolite identification. The IROA method uses metabolic incorporation of heavy (95% 13C) and light (5% 13C) nutrients, such as D-glucose and other carbon energy sources, to give rise to unique labeling patterns that can be readily identified and distinguished by mass spectrometry. Such a method would be useful in interlaboratory quantitative evaluations, if widely available. 
CIL is proud to offer a series of IROA® Biochemical Quantitation Kits for metabolic profiling of various cell populations and biological samples. 
These kits contain the reagents and tools necessary for the successful metabolic labeling, identification, and quantitation of metabolites in various cell populations. Refer to product list for details. 

Kit Features and Benefits

  • Eliminates technical and analytical variance → increases reliability
  • Removes artifacts and noise → increases precision and determination of metabolome
  • Reproducible identification of knowns/unknowns
  • Accurate, relative quantitation
  • Automated solution (via software) → saves time
  • Easy statistical interpretation of sample results
  • Broad applicability with experimental perturbations being user-defined



  IROA® Biochemical Quantitation Kits

  Sets, Mixes, and Kits for MS 'Omics and MS/MS Screening

  Stable Isotope Standards for Mass Spectrometry



Frequently Asked Questions 

What does the IROA protocol involve?

In the basic protocol, biomolecules in two cell populations (control and experimental) are randomly labeled with stable 13C (95% and 5% labeled media for the control and experimental groups, respectively). After a defined incubation period, the experimental group is perturbed (through a chemical, genetic, or environmental stressor) before uniform mixing, sample preparation, and LC- or GC-MS analysis. For more information, please see the seminal reference by de Jong et al. in the list below and the experimental figure in the IROA® Biochemical Quantitation Kits flyer.

What does IROA’s ClusterFinder™ software and portal provide?

The software automates peak identification and quantitation from the raw MS data, while providing tools for statistical analysis and interpretation. The integrated Assay Portal enables basic statistics (e.g., regressions and variances) and analysis (e.g., principal component, random forest, and correlation), along with summary plots (e.g., volcano, hybrid, and metabolic mapping) of the distributions.

What are acceptable MS data formats for ClusterFinder™?

ClusterFinder directly supports the following MS data file formats: mzXML, mzML, and mzDATA, although mzXML is preferable and the data should be centroided. Note: all major instrument vendors provide software for converting their proprietary data files into one of the formats supported by ClusterFinder. It must also be noted that although ClusterFinder does not currently support GC-MS data inputs, these kits have been applied to metabolomic GC-MS applications (see Qiu et al. reference in the list below).

How is the issue of sample-to-sample variance overcome with the IROA protocol?

Ion suppression, stemming from the variability of ionization efficiency, is one of the biggest problems facing mass spectrometry data interpretation. There is no sample-to-sample variance in the IROA datasets because the experimental and control samples are prepped and analyzed together. Further, since the protein standards and analytes are chemically identical and measured in an identical environment, they share identical ionization efficiencies making the measurements more accurate.

How many samples can be minimally analyzed with IROA’s 300 biochemical quantitation kit? Also, what is the per-sample cost?

The labeling media supplied with these kits can minimally accommodate 46 experimental and 46 control cell sample analyses. Procedurally, using a six-well plate and 3 mL of media /sample/well/passage is sufficient for five cell doublings to assure full label incorporation. This assumes a total volume of 278 mL media (250 mL plus 28 mL dialyzed fetal bovine serum), 2.5 generations per passage or a total 6 mL per sample. As a general guideline, LC-MS injections of 2 or 4 μL for positive or negative ESI, respectively, are recommended from a final volume of 500 μL in the six-well plate. This equates to approximately $40 USD per experimental sample and includes the software for analysis. Note that for this minimalist discussion, there is sufficient volume in each well for both positive and negative analysis as well as HILIC or other analyses.



Carey, J.; Nguyen, T.; Korchak, J.; et al. 2019. An isotopic ratio outlier analysis approach for global metabolomics of biosynthetically talented actinomycetes. Metabolites, 9(9), 181. PMID: 31510039

Wang, B.; Sandre, O.; Wang, K.; et al. 2019. Auto-degradable and biocompatible superparamagnetic iron oxide nanoparticles/polypeptides colloidal polyion complexes with high density of magnetic material. Mater Sci Eng C Mater Biol Appl, 104, 109920. PMID: 31500039

Vlahakis, C.; Hazebroek, J.; Beecher, C.; et al. 2019. Isotopic ratio outlier analysis improves metabolomics prediction of nitrogen treatment in maize. Phytochemistry, 164, 130-135. PMID: 31128492

Rahman, M.A.; Akond, M.; Babar, M.A.; et al. 2017. LC-HRMS based non-targeted metabolomic profiling of wheat Triticum aestivum under post-anthesis drought stress. Am J Plant Sci, 8, 3024-3061. DOI: 10.4236/ajps.2017.812205

Viant, M.R.; Kurland, I.J.; Jones, M.R.; et al. 2017. How close are we to complete annotation of metabolomes? Curr Opin Chem Biol, 36, 64-69. PMID: 28113135

Qiu, Y.; Moir R.; Willis, I.; et al. 2016. Isotopic ratio outlier analysis of the S. cerevisiae metabolome using accurate mass gas chromatography/time-of-flight mass spectrometry: a new method for discovery.  Anal Chem, 88(5), 2747-2754. PMID: 26820234

Clendinen, C.S.; Stupp, G.S.; Ajredini, R.; et al. 2015. An overview of methods using 13C for improved compound identification in metabolomics and natural products. Front Plant Sci, 6, 611. PMID: 26379677

Edison, A.S.; Clendinen, C.S.; Ajredini, R.; Beecher, C., et al. 2015. Metabolomics and natural-products strategies to study chemical ecology in nematodes. Integr Comp Biol, 55(3), 478-485. PMID: 26141866

Stupp, G.S.; Clendinen, C.S.; Ajredini, R.; et al. 2013. Isotopic ratio outlier snalysis global metabolomics of Caenorhabditis elegansAnal Chem85(24), 11858-11865. PMID: 24274725

de Jong, F.A.; Beecher, C. 2012. Addressing the current bottlenecks of metabolomics: Isotopic Ratio Outlier Analysis™, an isotopic-labeling technique for accurate biochemical profiling. Bioanalysis, 4(18), 2303-2314. PMID: 23046270


Krista Backiel

Krista Backiel

Marketing Manager and Metabolomics Manager

Krista Backiel is responsible for managing and promoting products that are utilized in metabolomics and clinical/diagnostic MS. She spends a lot of her time developing new products to assist customers in their diverse research efforts.

Andrew Percy, PhD

Andrew Percy, PhD

Senior Applications Chemist – Mass Spectrometry

Dr. Andrew Percy is the Senior Applications Chemist for Mass Spectrometry and the MS ‘Omics Product Manager at CIL. His responsibilities minimally involve providing technical support, overseeing product development, identifying new product market opportunities, assisting in the analysis of product-related applications, and writing/reviewing marketing literature.