Metabolomics and bioinformatics service platforms
Metabolomics Australia (MA) is a collaboration between the University of Melbourne, University of Queensland, University of Western Australia, Murdoch University and the AWRI that provides academia and industry with access to specialised analytical technologies for the measurement of small molecules.
As Australia’s sole full-service metabolomics platform, MA is a key contributor to metabolomics-based innovations, supporting translation of metabolomics concepts in biomolecular research and providing end-users with expertise in design of experiments, method development, validation and data analysis, together with customised bioinformatics solutions, training and support. The AWRI focuses on the metabolomics of agricultural products, foods and beverages, and microorganisms, areas of strategic and economic importance to Australia.
In 2017/2018 Metabolomics SA successfully completed 91 jobs, with a total of 2,421 samples analysed, an increase in sample numbers of 30% compared to the previous financial year. Specifically, the number of samples analysed for external clients increased by 41%, which was reflected in a 46% increase in revenue. This excellent result was achieved despite two staff being on parental leave from February 2018.
Services were provided for researchers and industry working in the fields of food and beverages, agriculture, plant metabolomics and biomedical sciences. Collaborations with external researchers resulted in method development in the fields of lipidomics and biomedical sciences. One example is a collaboration established with Prof. David Lynn and Dr Miriam Lynn from SAHMRI for a project monitoring short-chain fatty acids (SCFAs) in biological extracts. Metabolomics SA contributed method development for the extraction and quantitation of SCFAs via GC-MS. An application for an NHMRC grant has been submitted by SAHMRI.
In 2017/2018 Metabolomics SA had two visitors: Kimmo Siren, a PhD student from Germany working on Riesling juice, and Dr Marc Pignitter, Assistant Professor from the University of Vienna, Austria. The collaboration allowed development of an LC-MS method for lipid profiling in grapeseed oil, with particular focus on triglyceride oxidation products.
New scripts and tools were developed to improve data processing work¬flows (data normality evaluation, equality of variance test, pairwise t test) and compound identification. R-based scripts were developed to extract LC-MS and LC-MS/MS spectra of standard compounds analysed. Additional coding efforts allowed translation of the obtained data into National Institute of Standards and Technology (NIST)-compatible files, so that the NIST search algorithm could be used to perform library matching and compound identification of key markers. A data processing workflow known as MStractor was implemented with Lobstahs, an R package for screening, annotation and putative identification of mass spectral features in lipid datasets.