A team of researchers at the University of California, Riverside, led by biochemistry assistant professor Daniel Petras, has created a new computational tool for analyzing large sets of data in the field of metabolomics. Metabolomics is the study of small molecules found in cells, biofluids, tissues, and ecosystems. The team recently used this tool to analyze pollutants in seawater off the coast of Southern California. This tool allowed them to quickly identify the chemical profiles of coastal environments and pinpoint potential sources of pollution.
According to Petras, understanding how pollutants enter ecosystems is crucial for environmental health. The sheer chemical diversity of the ocean makes it challenging to identify important molecules related to pollution. However, the team’s new protocol speeds up the process, allowing for faster comprehension of ocean pollution issues. The protocol, outlined in the journal Nature Protocols, is designed for both experienced researchers and students, making it an accessible resource for those new to the field of metabolomics.
The team’s computational workflow includes a user-friendly web application with a graphical interface, making metabolomics data analysis easy for non-experts. Coauthor Mingxun Wang, an assistant professor of computer science and engineering at UCR, emphasizes that the tool caters to researchers of all levels, from beginners to experts. The software is designed to work in conjunction with molecular networking software developed by Wang’s group, enhancing data processing and analysis efficiency.
The research paper is part of the Virtual Multiomics Lab (VMOL), a collaborative platform involving over 50 scientists worldwide. VMOL aims to simplify chemical analysis and promote collaboration among researchers regardless of their background or resources. Doctoral student Abzer Pakkir Shah, the paper’s first author, highlights the impact of VMOL in providing training in computational mass spectrometry and data science, fostering global research projects.
All software developed by the team is freely available to the public, reflecting their commitment to open-access science. Petras believes that the protocol will benefit environmental researchers, biomedical scientists, and those conducting clinical microbiome studies. The tool’s versatility extends to various fields and sample types, such as combinatorial chemistry, doping analysis, and contamination detection in food and pharmaceuticals.
Petras, with a background in biotechnology and biochemistry, has focused his research on environmental metabolomics methods. His lab at UCR specializes in mass spectrometry-based techniques for visualizing and assessing chemical interactions in microbial communities. The team’s paper, titled “Statistical analysis of feature-based molecular networking results from non-targeted metabolomics data,” showcases their innovative approach to data analysis in metabolomics research.
