The June 10, 2016 online issue of the journal Science features work co-authored by Dr. Nicola Zamboni, a researcher at the ETH, Zurich, as well as GMet co-founder and leader in the field of metabolomics.
The publication was released by a collaborative team, including the laboratories of Professor Ruedi Aebersold and Johan Auwerx, and is entitled “Systems proteomics of liver mitochondria function” (Science, vol. 352). The study employed multiple levels of analysis, including genomic, transcriptomic, proteomic, and metabolomic data sets from 386 individuals in 80 cohorts of the BXD mouse genetic reference population, to gain a systems level understanding of mouse liver mitochondrial function and fitness.
This scale of multi-omics research benefits tremendously from the ability to rapidly delivery high-resolution non-targeted metabolomics data from the FIA-ToF platform. I think it is a good model for the kinds of studies that we can begin to do in human populations.
—Dr. Nicola Zamboni
The research article summary published in the same issue of science summarizes the findings at a high level: “Overall, these findings indicate that data generated by next-generation proteomics and metabolomics techniques have reached a quality and scope to complement transcriptomics, genomics, and phenomics for transomic analyses of complex traits.”
We encourage you to take a look at the original article: http://dx.doi.org/10.1126/science.aad0189.
The high-resolution, non-targeted metabolomics approach used in this Science article was uniquely developed by members of the GMet team at the ETH, and is the same method we have employed for multiple General Metabolics customers.
If you have research questions that would benefit from a similar approach, please contact us for additional information about high-throughput metabolomics.
