Waters recently collaborated with Stephen O’Shea, Ph.D., associate professor of chemistry at Roger Williams University, on a metabolic profiling project. The collaborators developed two different workflows—a targeted and a nontargeted approach.“We developed these workflows for the purpose of resolving metabolic-profiling challenges,” explained Kate Yu, principal scientist at Waters, who is a member of the metabolic profiling business development group that worked on the project.
The entire workflow is called UPLC-QTof-MSE coupled with multivariate statistical analysis for sample profiling. In this workflow, Waters’ Acquity UltraPerformance LC (UPLC) system and Waters’ Synapt mass spectrometer were employed for the metabolic profiling.
“One of the key components was MarkerLnx software, which allows us to identify the key biomarkers from complex samples,” Yu said. When these samples are separated on UPLC you can see that they are complex, but when you dig down deeper into the chromatogram by using multivariate statistical analysis, for example, you will be able to clearly identify more key biomarkers by using their exact mass.”
Dr. O’Shea is working on developing an aquaculture system for breeding clownfish for use as domestic pets and as model species for other marine tropical fish. “Our targeted analysis focused on developing proper feeds, which have a specific fatty acid component, for these fish,” said Dr. O’Shea, who added that, traditionally, fatty acid analysis had been performed using an HPLC/quadrupole MS before this collaboration work.
With UPLC-QTof-MSE, the analysis is performed faster and with less starting material, which is why the collaboration was undertaken. Using nontargeted analysis on whole fish eggs, the team was able to establish biomarkers to determine the identity of required dietary components, which will enable them to develop better diets for breeding.
“The fish eggs have a nine-day incubation and we were able to do metabolic profiling with Waters technology over that nine-day period, i.e., to see changes in metabolite levels over that period and also pick up major biomarkers that could be investigated.”