A research team led by scientists at the University of California, Riverside, has developed a computational workflow for analyzing large data sets in the field of metabolomics, the study of small molecules found within cells, biofluids, tissues, and entire ecosystems. The team applied this new computational tool to analyze pollutants in seawater in Southern California, capturing the chemical profiles of coastal environments and highlighting potential sources of pollution. Understanding how pollutants get introduced into the ecosystem is vital for environmental health, and the protocol developed by the team greatly speeds up this process by efficiently sorting the data.
The protocol, designed for both experienced researchers and for educational purposes, includes an accessible web application with a graphical user interface that makes metabolomics data analysis available for non-experts. Coauthor Mingxun Wang, an assistant professor of computer science and engineering at UCR, emphasizes that this tool is suitable for a broad range of researchers, from beginners to experts. It accelerates reproducible data analysis and enables the sharing of statistical data analysis workflows and results. The research paper serves as a large educational resource organized through a virtual research group called Virtual Multiomics Lab (VMOL), with more than 50 scientists participating worldwide. VMOL aims to simplify and democratize the chemical analysis process, making it accessible to researchers regardless of their background or resources.
All software developed by the team is free and publicly available, with the software development initiated during a summer school for non-targeted metabolomics at the University of Tübingen where VMOL was also launched. The team’s protocol is expected to be useful for environmental researchers, scientists in the biomedical field, and researchers involved in clinical studies in microbiome science. The versatility of the protocol extends to various fields and sample types, including combinatorial chemistry, doping analysis, and trace contamination of food, pharmaceuticals, and industrial products. Daniel Petras, the leader of the research team, received his master’s degree in biotechnology and his doctoral degree in biochemistry, focusing on the development of large-scale environmental metabolomics methods. He joined UCR in January 2024 to continue his research on mass spectrometry-based methods.
Abzer Pakkir Shah, a doctoral student in Petras’ group and the first author of the research paper, highlights the impact of VMOL in involving experts and students worldwide in collaborative science. VMOL provides training in computational mass spectrometry and data science and aims to launch virtual research projects as a new form of collaborative science. By removing physical and economic barriers, VMOL aims to democratize chemical analysis worldwide, making it accessible to researchers regardless of their background. Through the development of the computational workflow and accessible tools, the team aims to accelerate understanding of problems related to pollution and other environmental issues. The protocol developed by the team has potential applications in various fields, emphasizing the importance of data analysis in gaining insights into complex chemical systems.