Quantitative Metabolome Analysis Based on Chromatographic Peak Reconstruction in Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry

Abstract

Generating precise and accurate quantitative information on metabolomic changes in comparative samples is important for metabolomics research where technical variations in the metabolomic data should be minimized in order to reveal biological changes. We report a method and software program, IsoMS-Quant, for extracting quantitative information from a metabolomic data set generated by chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). Unlike previous work of relying on mass spectral peak ratio of the highest intensity peak pair to measure relative quantity difference of a differentially labeled metabolite, this new program reconstructs the chromatographic peaks of the light- and heavy-labeled metabolite pair and then calculates the ratio of their peak areas to represent the relative concentration difference in two comparative samples. Using chromatographic peaks to perform relative quantification is shown to be more precise and accurate. IsoMS-Quant is integrated with IsoMS for picking peak pairs and Zero-fill for retrieving missing peak pairs in the initial peak pairs table generated by IsoMS to form a complete tool for processing CIL LC-MS data. This program can be freely downloaded from the www.MyCompoundID.org web site for noncommercial use.

Metabolite Analysis and Histology on the Exact Same Tissue: Comprehensive Metabolomic Profiling and Metabolic Classification of Prostate Cancer

“…To perform metabolomic profiling from extracts prepared by mPREF, we developed and applied a high-performance CIL LC-MS method91718 to overcome the technical issues related to sample normalization, metabolite quantification and metabolite detection. The total amount of metabolites in the extracts of tissues with varying sizes and compositions can vary greatly (Fig.…”

“…The same peak pairs across different samples were aligned together to produce a metabolite-intensity table using IsoMS-align. Missing values in the table were then refilled from the raw LC-MS data using the Zero-fill program18. Both training and validation datasets were processed using the same protocol.…”

Profiling novel metabolic biomarkers for Parkinson's disease using in‐depth metabolomic analysis

“…The missing ratio values were filled back by using the Zero‐fill program . IsoMS‐Quant was used to generate the final metabolite‐intensity table, which was exported to SIMCA‐P+ 12 (Umetrics AB, Umeå, Sweden) for analysis. We followed the method described in the work of LeWitt and colleagues for statistical analysis (Supplemental Note S1.3).…”

Chemical Isotope Labeling LC-MS for Monitoring Disease Progression and Treatment in Animal Models: Plasma Metabolomics Study of Osteoarthritis Rat Model

“…We used a zero-filling program63 to search for the missing values in the raw mass spectral data and, if found, a peak ratio was calculated from the mass spectrum and added to the peak ratio table. Finally, IsoMS-Quant was used determine the chromatography-peak-intensity ratio of a 12 C-/ 13 C-pair64.…”