- Genomics research
A team of Lawrence Berkeley National Laboratory researchers including Trent Northen, Benjamin Bowen, Oliver Reubel, and Markus De Raad have developed technologies for associating metabolites with genes that enable scoring and curating compound identities based on their biological relevance, and/or using compound identities from those tools to connect to genes in their biological samples and potentially formulate hypotheses of gene function. Such results can be used to direct high-throughput biochemical assays to greatly reduce biochemical search space. The Metabolite, Annotation and Gene Integration (MAGI) system is highly relevant to and useful in the fields of genomics, metabolomics, and systems biology. Furthermore, as metabolomics data become more widely available for sequenced organisms, MAGI has the potential to improve the understanding of microbial metabolism, while also providing testable hypotheses for specific biochemical functions.
Metabolomics has been used for obtaining direct measures of metabolic activities from diverse biological systems. However, metabolomics can be limited by ambiguous metabolite identifications. Furthermore, interpretation can be limited by incomplete and inaccurate genome-based predictions of enzyme activities (e.g., gene annotations). In addition, some genes may be poorly annotated. Thus, the understanding of metabolism, such as microbial metabolism, is limited.
STATUS: Published U. S. Patent Application 15/932,459 (Publication No. US2018-0239863). Available for licensing or collaborative research.