Metabolomics Analysis and IROA

Metabolomics is a field of scientific study that analyses the chemical processes of cell metabolism. It studies the complete set of metabolites contained in an organism’s biofluids, cells and tissues to provide insights to understand cellular processes, physiological stressors and as a tool for biomarker discovery. Metabolites tell us the exact physiological state of an organism. Although it is a fast-emerging field, there are still many associated bottlenecks to overcome. Issues of analytical variability, ion suppression, and metabolite identification still plague metabolomics investigators.

IROA is a simple and direct technique using standards for metabolomics analysis, streamlining the workflow.  We use Internal Standards (IS) that have unique isotopic labels, specifically 95% and 5% U-13C, to improve metabolomic identification and quantitative reproducibility and accuracy. The IS peak shapes are mathematically calculable using mass spectrometry.  ClusterFinder software finds, identifies, and quantitates these specific peaks. Algorithms also correct for ion suppression correction and normalize samples using the qualities inherent in the IS peaks.

How are these unique labels made? Compounds are randomly and universally labeled and the relative abundances of the isotopes of carbon are altered; enriched in one particular isotope and depleted in its other isotopic form.  For example, 95% U-13C6-Glucose is not actually 95% 13C6 and 5% 12C6.  Instead, each carbon atom position (1,2,3,4,5,6) has a 95% chance of being 13C labeled and a 5% chance of being 12C.  Compounds such as 5% and 95% U-13C6-Glucose are specially made for IROA Technologies LLC by Cambridge Isotope Technologies, Inc.

How are they used? IROA utilizes pre-labeled complex Internal Standards for semi-targeted analysis allowing the researcher to search for compounds using the Iinternal Sstandard pre-built library, PubChem, and any libraries that the user has available.

The IROA ClusterFinder™ software tool characterizes peaks (as either artifacts, Internal Standards (controls), or experimental compounds), removes artifacts, and performs peak correlation analysis to associate adducts with their fragments. It calculates carbon number and molecular formula, quantitates the ratio of control (C12) to experimental (C13), corrects for ion suppression, and normalizes each dataset.

13C labeled Yeast Extract Makes a Great Internal Standard for Metabolomics Workflows 

Many standards are used as external calibrants because they usually have a natural-abundance isotopic balance and cannot be added to matrices containing the same molecules as they are not distinguishable.  A good internal standard (one you can spike into samples) should be chemically similar to the matrix you are analyzing to be able to accurately identify and measure as many metabolites as possible.  A great internal standard can account for matrix-induced ion suppression, chromatographic quality, and analytical drift, and can be used to normalize samples.

Why Use Labeled Yeast Extract as an Internal Standard?

Yeast extract contains many different key primary metabolites including amino acids and derivatives, carbohydrates, vitamins, nucleotide/nucleosides, coenzymes, organic acids and derivatives, lipid-like molecules, polyamines, and peptides.   Yeast can be easily grown and fully labeled in large fermentation batches using U-13C6-labeled glucose as the sole carbon source.  Large quantities of stable 13C labeled yeast extract can be prepared and properly stored to use for LC-MS/MS Metabolomic Workflows.

What makes IROA 13C labeled Yeast Extract the Best Internal Standard for Metabolomic Workflows?

The IROA-based 13C labeled Yeast Extract Workflow) is a protocol based on demonstrated principles that serve to correct the systemic errors introduced during sample preparation (using Dual-MSTUS normalization) or within the mass spectral instrumentation (using suppression-correction algorithms).

The Workflow  is based on a set of  (5 atom%13C and 95 atom%13C) calibrated Yeast Standards which contain hundreds of carefully LC-MS/MS characterized yeast metabolites. A  LC MS/MS Retention Time (RT) verified-identity “library” of m/z and physical characteristics for all IROA peaks has already been uploaded in the ClusterFinder software provided with the Workflow kit.  These include fragments that also have the unique IROA ratio pattern derived from their parent peaks and identified using the “peak correlation” ClusterFinder module.

IROA isotopically-labeled internal standards suffer the same matrix-induced ion suppression, source modification, or chemical transformation.  Measurements accurately reflect the changes in concentration due to ion suppression and are therefore used to correct these variances.  A “Dual MSTUS*” algorithm is used for normalization of the total area under the curve (AUC) for all natural abundance suppression-corrected peaks to the total AUC of their corresponding IROA-IS peaks which allows for normalization of samples to a true Standard, i.e. that is the same every day. 

The IROA 13C labeled yeast extract Workflow provides for complete verifiable compound identification and quantitation (suppression-corrected). It also normalizes samples against one another (corrects for inherent sample variations, e.g. from dilution, or size).  ClusterFinder reports the raw data, suppression-corrected data, and normalized data.

For additional information and background information on our Metabolomic workflow, please refer to TruQuant.