iMet-Q

iMet-Q performs label-free quantitation of metabolites from full-scan liquid chromatography-mass spectrometry (LC-MS) MS1 data to provide accurate metabolite abundance measurements and charge/isotope characterization.

Key Features:

• Automated Peak Detection and Alignment: Performs peak detection and alignment on full-scan LC-MS MS1 data to support precise quantitation.
• Quantitation Results Summary: Generates summaries of quantitation at both replicate and sample levels reporting ion abundances across conditions.
• Charge State and Isotope Ratio Determination: Identifies charge states and isotope ratios of detected peaks to aid metabolite identification and cross-referencing with databases such as the Human Metabolome Database (HMDB).
• Performance Comparison: Demonstrated smaller quantitation error (12%) in comparative studies using an in-house standard mixture and a public Arabidopsis metabolome dataset versus XCMS, MetAlign, and MZmine 2 for profile and centroid data sets.
• Metabolite Candidate Filtering: Uses isotope ratio calculations to filter candidate metabolites, reducing candidate lists (e.g., from 183 to 89 in a reported study).
• Internal Standard Analysis: Reported minimal abundance variation (≤ 0.19) and high abundance correlation (≥ 0.92) for internal standards, indicating quantitation precision.

Scientific Applications:

• Metabolomics Research: Enables accurate quantification of metabolites for studies of metabolic pathways and biochemical profiling.
• Disease Mechanism Investigation: Supports comparative metabolite abundance analyses relevant to disease mechanism characterization.
• Environmental and Biological Response Studies: Facilitates analysis of biological responses to environmental changes across samples.
• Large-Scale and Comparative Studies: Suited for high-throughput and comparative analyses across multiple samples and conditions.

Methodology:

Automated peak detection and alignment on full-scan LC-MS MS1 data, followed by label-free quantitation at replicate and sample levels, determination of charge states and isotope ratios, and isotope-ratio-based candidate filtering.