Yeast Extract Kits

The yeast extracts – U-13C (ISO1 or L-ISO1) and unlabeled (ISO1-UNL and L-ISO1-UNL) – are designed for internal standardization (i.e., matrix spike-in) quantitation experiments and for quality control evaluations in untargeted and targeted metabolomics. The compounds in these extracts span broad metabolic classes (e.g., amino and organic acids, sugar phosphates, coenzymes) that are linked to various biochemical pathways (e.g., citrate and glyoxylate cycle, amino acid and nucleotide metabolism, pentose phosphate) and cellular/molecular processes (e.g., immune system, blood coagulation, DNA metabolism). These metabolites have been rigorously characterized by several LC-/GC-MS methodologies and are amenable to a variety of research uses after simple reconstitution.

Kit Contents

  • Dried-down yeast extract(s) as U-13C and/or unlabeled.

  • Document package (supplied via QR code). Package includes user manual, which contains example procedures and LC-MS methods for user references.

Related Resources

Metabolite and Lipid Yeast Extracts

All extracts are produced by ISOtopic Solutions. For additional information on these products, please visit ISOtopic Solutions.

Related Products

Frequently Asked Questions

What part of the life cycle is the yeast extract from? The yeast (Pichia pastoris, strain CBS 7435) is in the exponential growth phase. In this phase, the cell is using most of the available substrate to reproduce. The doubling time for the yeast strain employed is a little less than 3 hours. Exponential growth is ensured through verification of the OD 600 measurements during fermentation. The extract preparation is detailed in PMID: 23086617.  

What does the “U” in U-13C (98%) refer to? The “U” denotes a uniformly labeled compound. For example, NADP+ with a formula C21H29N7O17P3 has 21 C in its 13C-labeled form.

What is the recommended procedure for dissolving the dried metabolite yeast extracts? The recommended procedure for solubilizing ISO1 and ISO1-UNL is as follows:

1. Reconstitute the extract in 2 mL solvent (e.g.; water, 50% methanol).
2. Vigorously shake by hand with intermittent high-speed vortexing (for a minimum of 2 min).
3. Centrifuge at 20°C for 5 min at 4000 rcf.
4. The clear standard solution can then be diluted (1/10 v/v) for direct use or prepared further for calibration and matrix addition.

A video demonstration of this procedure is shown in the resources section above.

What sample types have these yeast extracts been measured in? The extracts have been applied to human tissues (e.g., plasma) and cells (e.g., colon cancer) for QC or quantitative analysis by a variety of LC- and GC-MS methods. Outlined in the user manual (supplied with the kit shipment via QR code) of ISO1, for example, are three application examples that utilize isotope ratio analysis for absolute or relative metabolite quantification.

What are the commonly identified analytes in the yeast extracts? A tabulated list of analytes or fatty acids/lipids observed across routine, batch-to-batch measurements is indicated in their respective sections of the Stable Isotope-Labeled Mixtures, Sets, and Kits catalog. This list is not finite, as other analytes have been identified with alternate protocols (e.g., coenzyme As – acetyl, malonyl, propionyl; glucose-1-phosphate; fructose-1-phosphate). Please inquire if other analytes are of interest, and we will investigate.

Example References

Turtoi, E.; Jeudy, J.; Henry, S.; et al. 2023. Analysis of polar primary metabolites in biological samples using targeted metabolomics and LC-MS. STAR Protoc, 4(3), 102400-102422. PMID: 37590149
Serafimov, K.; Lämmerhofer, M. 2022. Metabolic profiling workflow for cell extracts by targeted hydrophilic interaction liquid chromatography-tandem mass spectrometry. J Chromatogr A, 1684, 463556-463555. 
PMID: 36265203
 Li, P.; Su, M.; Chatterjee, M.; et al. 2022. Targeted analysis of sugar phosphates from glycolysis pathway by phosphate methylation with liquid chromatography coupled to tandem mass spectrometry. Anal Chim Acta, 1221, 340099-34109.
PMID: 35934345
Reiter, A.; Asgari, J.; Wiechert, W.; et al. 2022. Metabolic footprinting of microbial systems based on comprehensive in silico predictions of MS/MS relevant data. Metabolites, 12(3), 257-280. PMID: 35323700
Zhao, X.; Golic, F.T.; Harrison, B.R.; et al. 2022. The metabolome as a biomarker of aging in Drosophila melanogaster. Aging Cell, 21(2), e13548-13561. PMID: 35019203
Rampler, E.; Hermann, G.; Grabmann, G.; et al. 2021. Benchmarking non-targeted metabolomics using yeast-derived libraries. Metabolites, 11(3), 160-179. PMID: 33802096 
Castoldi, A.; Monteiro, L.B.; van Teijlingen Bakker, N.; et al. 2020. Triacylglycerol synthesis enhances macrophage inflammatory function. Nat Commun, 11(1), 4107. PMID: 32796836 
Mairinger, T.; Weiner, M.; Hann, S.; et al. 2020. Selective and accurate quantification of N-acetylglucosamine in biotechnological cell samples via GC-MS/MS and GC-TOFMS. Anal Chem, 92(7), 4875-4883. PMID: 32096989 
Rusz, M.; Rampler, E.; Keppler, B.K.; et al. 2019. Single spheroid metabolomics: optimizing sample preparation of three-dimensional multicellular tumor spheroids. Metabolites, 9(12). 304. PMID: 31847430 
Zhang, Y.; Vera, J.M.; Xie, D.; et al. 2019. Multiomic fermentation using chemically defined synthetic hydrolyzates revealed multiple effects of lignocellulose-derived inhibitors on cell physiology and xylose utilization in Zymomonas mobilis. Front Microbiol, 10, 2596. PMID: 31787963 
Galvez, L.; Rusz, M.; Schwaiger-Haber, M.; et al. 2019. Preclinical studies on metal based anticancer drugs as enabled by integrated metallomics and metabolomics. Metallomics, 11(10), 1716-1728. PMID: 31497817 
Si-Hung, L.; Troyer, C.; Causon, T.; et al. 2019. Sensitive quantitative analysis of phosphorylated primary metabolites using selective metal oxide enrichment and GC- and IC-MS/MS. Talanta, 205, 120147. PMID: 31450417 
van Tol, W.; van Scherpenzeel, M.; Alsady, M.; et al. 2019. Cytidine diphosphate-ribitol analysis for diagnostics and treatment monitoring of cytidine diphosphate-l-ribitol pyrophosphorylase A muscular dystrophy. Clin Chem, 65(10), 1295-1306.  PMID: 31375477 
Causon, T.J.; Si-Hung, L.; Newton, K.; et al. 2019. Fundamental study of ion trapping and multiplexing using drift tube-ion mobility time-of-flight mass spectrometry for non-targeted metabolomics. Anal Bioanal Chem, 411(24), 6265-6274. PMID: 31302708 
Sullivan, M.R; Danai, L.V.; Lewis, C.A.; et al. 2019. Quantification of microenvironmental metabolites in murine cancers reveals determinants of tumor nutrient availability. Elife, 8, e44235. PMID: 30990168 
Demarest, T.G.; Truong, G.T.D.; Lovett, J.; et al. 2019. Assessment of NAD+ metabolism in human cell cultures, erythrocytes, cerebrospinal fluid and primate skeletal muscle. Anal Biochem, 572, 1-8. PMID: 30822397 
Hermann, G.; Schwaiger, M.; Volejnik, P.; et al. 2018. 13C-labelled yeast as internal standard for LC-MS/MS and LC high resolution MS-based amino acid quantification in human plasma. J Pharm Biomed Anal, 155, 329-334. PMID: 29704823 
Guijas, C.; Montenegro-Burke, J.R.; Domingo-Almenara, X.; et al. 2018. METLIN: A technology platform for identifying knowns and unknowns. Anal Chem, 90(5), 3156-3164. PMID: 29381867 
Si-Hung, L.; Causon, T.J.; Hann, S. 2017. Comparison of fully wettable RPLC stationary phases for LC-MS-based cellular metabolomics. Electrophoresis, 38(18), 2287-2295. PMID: 28691762 
Schwaiger, M.; Rampler, E.; Hermann, G., et al. 2017. Anion-exchange chromatography coupled to high-resolution mass spectrometry: a powerful tool for merging targeted and non-targeted metabolomics. Anal Chem, 89(14), 7667-7674. PMID: 28581703 
Ortmayr, K.; Hann, S.; Koellensperger, G. 2015. Complementing reversed-phase selectivity with porous graphitized carbon to increase the metabolome coverage in an on-line two-dimensional LC-MS setup for metabolomics. Analyst, 140(10), 3465-3473. PMID: 25824707