CZ Biohub SF Investigator Peter Turnbaugh’s team and the SF Biohub Mass Spec Platform collaborated to investigate the unique metabolism of the prevalent and disease-linked Actinobacterium Eggerthella lenta. The application of stable isotope-resolved metabolomics revealed that E. lenta uses acetate as a key carbon source while catabolizing arginine to generate ATP.
In the first demonstration of diet-induced liver regeneration, this study with Stanford Medicine shows that intermittent fasting spurs rapid liver cell proliferation in mice.
It is commonly assumed that protein concentrations generally remain constant across cells of a given type. CZ Biohub postdoctoral fellow, Mike Lanz demonstrated this is not the case, revealing new dimensions of cellular regulation. This work resulted from a close collaboration with CZ Biohub Investigator Jan Skotheim at Stanford.
Our study bridges a gap in understanding and predicting MHC-II antigen presentation.
Here, we develop a liquid chromatographic-mass spectrometric workflow for untargeted sequence analysis of the urinary peptidome.
Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microorganisms and interactions between microorganisms and their host.
Here, we describe our efforts to optimize purification and mass spectrometer parameters, ultimately allowing us to identify as many as almost 5000 pMHC I and 7400 pMHC II from as little as 2.5 × 107 Raji cells each.
Here, we describe TagGraph, a computational tool that overcomes both challenges with an unrestricted string-based search method that is as much as 350-fold faster than existing approaches, and a probabilistic validation model that we optimized for PTM assignments.
To demonstrate the effectiveness of MS-FLO, we processed 28 biological studies and uploaded raw and results data to the Metabolomics Workbench website, encompassing 1481 chromatograms produced by two different data processing programs used in-house (MZmine2 and later MS-DIAL).
We have investigated the potential of metabolomics to discover blood-based biomarkers relevant to lung cancer screening and early detection.
We provide a freely available computer-generated tandem mass spectral library of 212,516 spectra covering 119,200 compounds from 26 lipid compound classes, including phospholipids, glycerolipids, bacterial lipoglycans and plant glycolipids.