LOBSTAHS

LOBSTAHS performs automated screening, annotation, and putative identification of mass spectral features in large high-performance liquid chromatography–mass spectrometry (HPLC-MS) lipidomics datasets.

Key Features:

• High-throughput annotation: Annotates lipids, oxidized lipids, and oxylipins in high-mass-accuracy HPLC-MS datasets.
• Adduct Hierarchy Sequences (LOBSTAHS): Implements adduct hierarchy sequences that use orthogonal screening criteria based on adduct ion formation patterns and other molecular properties to assign compounds.
• Confidence scoring: Provides confidence scores for each assignment to aid evaluation of reliability.
• Customizable databases: Uses two customizable databases (default 14,068 unique entries) that can be generated from user-defined structural criteria and used to produce in silico lipid entries.
• Integration with xcms and CAMERA: Accepts input from datasets processed with xcms and CAMERA.
• Multistage screening: Applies a multistage screening process to filter mass spectral features prior to assignment.

Scientific Applications:

• Marine diatom oxidative-stress profiling: Applied to Phaeodactylum tricornutum to screen over 340,000 mass spectral features induced by oxidative stress, putatively identifying 1,969 unique parent compounds across 21,869 features that passed multistage screening.
• Lipidome remodeling characterization: Enabled detection of carbon-chain elongation across lipid classes and a reallocation of lipidome peak area to triacylglycerols following hydrogen peroxide (H2O2)-induced oxidative stress.

Methodology:

Combines orthogonal screening criteria and adduct hierarchy sequences based on adduct ion formation patterns and molecular properties, applies multistage screening and database-driven assignments using two customizable databases generated from user-provided structural criteria, and operates on high-mass-accuracy HPLC-MS datasets (accepting data processed with xcms and CAMERA).