MetEx

MetEx analyzes LC-MS and UPLC-Qtof-MS metabolomics datasets to process retention time, mass-to-charge ratio (m/z), and MS intensity features for prioritization, library-based dereplication, and identification of elicitor-induced microbial secondary metabolites.

Key Features:

• Visualization and multidimensional analysis: Processes retention time, mass-to-charge ratio (m/z), and MS intensity across multiple conditions or elicitors to enable multidimensional analysis.
• Three-dimensional mapping and slicing: Constructs three-dimensional maps of feature space and extracts two-dimensional slices for focused examination and prioritization.
• Elicitor chemotype organization: Organizes datasets by elicitor chemotypes to compare condition-specific metabolite responses.
• Customizable library-based dereplication: Performs library-based dereplication against customizable compound libraries to identify known metabolites.
• Automated lead selection: Implements an automated scoring system to prioritize candidate metabolites (leads) for follow-up.
• High-throughput screen support: Handles UPLC-Qtof-MS datasets from high-throughput elicitor screens, exemplified by analyses of Burkholderia gladioli exposed to 750 elicitors.

Scientific Applications:

• High-throughput elicitor screening: Facilitates identification of elicitors that trigger cryptic metabolite groups in microbial secondary metabolism, as demonstrated with Burkholderia gladioli screened against 750 elicitors using UPLC-Qtof-MS.
• Natural product discovery and dereplication: Supports prioritization and dereplication workflows to accelerate discovery of novel natural products from microbial sources.

Methodology:

Leverages UPLC-MS-guided high-throughput screening methodologies and integrates advanced bioinformatics techniques to manage and interpret large-scale metabolomics data.