A guide to reverse metabolomics-a framework for big data discovery strategy.

Untargeted metabolomics is evolving into a field of big data science. There is a growing interest within the metabolomics community in mining tandem mass spectrometry (MS/MS)-based data from public repositories. In traditional untargeted metabolomics, samples to address a predefined question are collected and liquid chromatography with MS/MS data are generated.

To Impute or Not To Impute in Untargeted Metabolomics─That is the Compositional Question.

Untargeted metabolomics often produce large datasets with missing values. These missing values are derived from biological or technical factors and can undermine statistical analyses and lead to biased biological interpretations. Imputation methods, such as -Nearest Neighbors (kNN) and Random Forest (RF) regression, are commonly used, but their effects vary depending on the type of missing data, e.

The microbiome diversifies -acyl lipid pools - including short-chain fatty acid-derived compounds.

-acyl lipids are important mediators of several biological processes including immune function and stress response. To enhance the detection of -acyl lipids with untargeted mass spectrometry-based metabolomics, we created a reference spectral library retrieving -acyl lipid patterns from 2,700 public datasets, identifying 851 -acyl lipids that were detected 356,542 times. 777 are not documented in lipid structural databases, with 18% of these derived from short-chain fatty acids and found in the digestive tract and other organs.

Empirically establishing drug exposure records directly from untargeted metabolomics data.

Despite extensive efforts, extracting information on medication exposure from clinical records remains challenging. To complement this approach, we developed the tandem mass spectrometry (MS/MS) based GNPS Drug Library. This resource integrates MS/MS data for drugs and their metabolites/analogs with controlled vocabularies on exposure sources, pharmacologic classes, therapeutic indications, and mechanisms of action.