Intracellular Metabolite Extraction, Peak Detection with El-MAVEN and Quantification Using Python v2
Year: 2025
Type: preprint
Abstract: This protocol outlines a comprehensive workflow for intracellular metabolite analysis from microbial cultures. It begins with the rapid quenching and extraction of metabolites using a cold solvent mixture of acetonitrile, methanol, and water (2:2:1, v/v/v) to preserve metabolite integrity. After LC-MS analysis, raw data is processed in El-MAVEN for precise peak detection and alignment. The final step involves the absolute quantification of metabolites via a Python-based script that employs external calibration curves. For compounds lacking external standards, the protocol also includes exploratory data analysis, such as generating heatmaps or line plots, to visualize metabolite dynamics across experimental conditions. This approach enables both high-throughput quantification and qualitative exploration across large sample sets.
Authors: Bishal Dev Sharma, Daniel Olson
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
OpenAlex ID: W4413462430