Project description:Untargeted-metabolomics LC-MS/MS analysis of commercial natural products pool, analyzed with different DDA settings with the objective to find the best one.
Project description:Comparison of gene expression of exposed versus non-exposed Oncorhynchus mykiss hepatocytes to four model chemicals and a synthetic mixture. Hepatocytes were exposed for 24 hours to a single chemical and a synthetic mixture of 10 nM 17 alpha-ethinylestradiol (EE2), 0.75 nM 2,3,7,8-tetrachloro-di-benzodioxin (TCDD), 100 μM paraquat and 0.75 μM 4-nitroquinoline-1-oxide (NQO). Keywords: Exposed vs. control
Project description:Time and concentration dependent transcriptome signatures in the ZFE of a mixture consisting of diruon, diclofenac and naproxen. Mixture composition: diuron 11%; diclofenac 2.6%; naproxen 86.4% Keywords: Expression profiling by array
Project description:The history of lichen compound identification has long relied on techniques such as spot tests and TLC, which have been surpassed in sensitivity and accuracy by modern metabolomic techniques such as high-resolution MS/MS. In 2019, Olivier-Jimenez et al. released the Lichen DataBase (LDB), a library containing the Q-TOF MS/MS spectra of 251 metabolites on the MetaboLights and GNPS platforms, that has been widely used for the identification of lichen-derived unknowns. To increase the compound coverage, we have generated the Orbitrap MS/MS spectra of a further 534 lichen-derived compounds from the metabolite library of Jack Elix, housed at the CANB herbarium (Canberra, Australia). This included 399 unique metabolites that are not in the LDB, bringing the total number combined to 650. Technical validation was achieved by investigating the compounds in three Australian lichen extracts using the Library Search and Molecular Networking tools on the GNPS platform. This update provides a much larger database for lichen compound identification, which we envisage will allow refining the lichen chemotaxonomy framework and contribute to compound discovery.