Abstract
BACKGROUND: Ultra High Resolution (UHR) mass spectrometry systems with Fourier Transform Ion Cyclotron Resonance (FT-ICR) are often used to analyze the composition of complex mixtures of naturally-occurring or isotopically-enriched small molecules, such as metabolite samples for environmental, biological, or paleontological studies. The extremely high resolution of these systems enables simultaneous measurement of the exact masses of tens of thousands of molecular features and accurate determination of chemical formulas based on isotopic fine-structure ratios. To accelerate and streamline analysis of these datasets, automated solutions to rapidly characterize the molecular composition of unknown samples by comparison with known reference databases are needed. RESULTS: Here we present Molecular Isotope Mass Identifier (MIMI), a commandline tool to identify molecules present in complex samples using data from UHR-FT-ICR mass spectrometry. Given a database of known molecules and expected ratios of atomic isotopes in the sample, MIMI first computes theoretical exact masses and expected abundance for all possible isotopic variants in the database. Chemical formulas from publicly available databases and/or custom lists of molecules of interest can be used as reference data for comparison. By default MIMI is configured to use natural isotopic abundances, but its advantage is it can easily accommodate different user-defined isotopic labeling ratios for any element(s). Candidate molecules are first identified in peak lists from UHR-FT-ICR mass spectrometry runs by comparing masses detected in the experimental data with precomputed theoretical masses for all entries in the reference database. Chemical formulas are then verified by counting isotopic fine-structure matches with the theoretical values for all possible molecular isotopic variants and can be further validated by comparing observed vs. expected relative peak heights. We illustrate MIMI’s utility using metabolite data from a cultured diatom sample isolated from seawater in the Arabian Gulf and spiked with (13)C-labeled internal standards, as well as a sample containing naturally-abundant metabolite standards. CONCLUSIONS: We introduce a simple commandline tool, MIMI, that rapidly identifies chemicals present in samples of complex composition using UHR-FT-ICR mass spectrometry data. MIMI can compare measured data against both standard and customized molecular databases and can accommodate natural or user-specified isotope ratios. This software provides a convenient tool for simultaneous determination of natural and isotope-labeled compounds within the same sample, particularly for rapid characterization of complex mixtures of metabolites.