Project description:A study to investigate the effect of small molecule lipid inducing compounds that leads to hyper-accumulation of lipids in N replete cells of Chlamydomonas reinhardtii. These compounds were identified through a high throughput screening designed for that purpose. The highthrouhput screen (HTS) evaluated 43,783 compounds and identified 367 primary hits. These 367 hits were further retested using a 8-point dilution series (from 0.25 to 30 uM) and verified the activity of 243 compounds that induce the hyper lipid accumulating phenotype in algae. Once the hit compounds were identified and confirmed, we then performed extensive chemoinformatics analysis to look for common scaffolds and identified several common substructures. We then selected 15 top performing compounds from 5 diverse structural groups and tested for biochemical parameters such as growth, lipid accumulating capacity, effect on photosynthetic rates, respiration rates, oxygen consumption rates, analysis of different lipid species to identify and quantify fatty acid species using GC-MS, transcriptome analysis using next generation sequencing (RNASeq), untargeted metabolomics using LC-MS, lipidome analysis using FT-ICR MS. To understand the global changes in the proteome, 2 structurally different compounds were selected and compared to the control without compound treatment.
Project description:Matrix-assisted laser desorption/ionization mass spectrometry imaging allows for the study of metabolic activity in the tumor microenvironment of brain cancers. The detectable metabolites within these tumors are contingent upon the choice of matrix, deposition technique, and polarity setting. In this study, we compared the performance of three different matrices, two deposition techniques, and the use of positive and negative polarity in two different brain cancer types and across two species. Optimal combinations were confirmed by a comparative analysis of lipid and small-molecule abundance by using liquid chromatography-mass spectrometry and RNA sequencing to assess differential metabolites and enzymes between normal and tumor regions. Our findings indicate that in the tumor-bearing brain, the recrystallized α-cyano-4-hydroxycinnamic acid matrix with positive polarity offered superior performance for both detected metabolites and consistency with other techniques. Beyond these implications for brain cancer, our work establishes a workflow to identify optimal matrices for spatial metabolomics studies.