Djawed Bennouna is a research scientist (metabolomics) in the Informatics Core within NCATS’ Division of Preclinical Innovation. In this capacity, he focuses on developing and optimizing liquid chromatography–mass spectrometry (LC–MS)-based untargeted metabolomics and lipidomics approaches, which are then applied to measure and compare the changes of numerous metabolites present in biological samples that arise in response to complex and rare diseases. He works in close collaboration with the Analytical Chemistry Core, which provides numerous advanced analytical instruments that facilitate the development of high-throughput automated metabolomics/lipidomics workflows.
Prior to joining NCATS in 2022, Bennouna completed his postdoctoral training in the laboratory of Rachel E. Kopec, Ph.D., in the Department of Human Sciences at The Ohio State University. His research focused primarily on the impact of nutrition on breast cancer chemotherapy–induced cognitive impairment, using targeted and untargeted metabolomics/lipidomics in the brain of murine models and the plasma of breast cancer patients. He identified several dysregulated pathways—including omega-9, purines and kynurenine pathways—that were previously reported in the cerebral tissue and plasma of subjects with Alzheimer’s, Parkinson’s and major depressive disorders. He also worked in collaboration with David L. Stern, Ph.D., on a study of the hijacking process of aphids to induce the development of galls in witch-hazel. Through this study, Bennouna was able to identify the main anthocyanins responsible for the red color of these aphid galls.
After earned his pharmacy degree in 2008, Bennouna went on to obtain master’s degrees in medicinal chemistry from the Faculty of Pharmacy, University of Angers (France) and in metabolomics from the University of Toulouse (France). In 2018, he completed his doctorate in biochemistry and metabolomics from the Faculty of Medicine, Aix-Marseille University, where he studied the effects of the environment and genetics on the expression of health-promoting molecules in Brassica napus seeds. He used a multiomics approach, combining metabolomics and transcriptomics at different tissue levels to understand how these modifications could affect the microbiome and other pathways related to obesity in mice.
Bennouna’s research focuses on developing high-throughput metabolomics/lipidomics workflows to reduce analytical errors and provide high data quality. This includes optimizing chromatographic conditions and mass spectrometry parameters; automating sample extraction by using robots; and processing the generated data using open-source software and scripts developed by the bioinformatics team. This approach is applied to a variety of disciplines that involve cancer and rare diseases to investigate pathway dysregulation and identify new biomarkers.