YCI Laboratory for Next-Generation Proteomics

Accurate and highly complexed protein quantification

We apply various mass-spectrometry-based methods in proteomics analyses of a wide range of samples. Shotgun proteomics is a discovery proteomics method and shows high proteome coverage. Selected reaction monitoring (SRM) is a targeted proteomics strategy and has high sensitivity and specificity. The recently developed data-independent acquisition (DIA) method, Sequential Windowed Acquisition of All Theoretical Fragment Ion Mass Spectra (SWATH-MS), has demonstrated high coverage and data accuracy and has enables precise protein quantification in large number of samples.


Integrative Omics analysis

Mass-spectrometry-based strategies have brought us closer to accurate protein quantification with comprehensiveness in analogy to what next-generation sequencing has provided for transcriptomics. Mechanistic and data-driven approaches can therefore converge to enhance understanding of complex phenotypes if multilevel omics data are integrated at the level of modular networks. Previously in Aebersold lab, we have integrated genetics, transcriptomic, proteomics, metabolomics and phenomics to investigate associated proteotypes with metabolic phenotypes in distinct mice strains from a genetic reference compendium (Wu*&Williams*, et al, Cell. 2014; Williams*&Wu*, et al, Science. 2016). By comparing transcriptomics and proteomics data, we observed nominal correlation between transcript and protein levels of the same gene, indicating the necessity of proteomics measurement in addition to transcriptomics analysis. We have discovered common discrepancies of genetic regulation mechanism between transcript and corresponding protein level. We are interested in integrating multi-omics analysis of biological systems in static and genetically/environmentally perturbed states towards the goal of personalized medicine.


Proteotype states and cellular phenotypes

A proteotype can be described as the state of a proteome that is associate with a specific phenotype. Genetic and external perturbations can change the state of the proteome and such changes cause or correlate with altered phenotypes. Accurate protein quantification enables effective probe of genetic and environmental perturbations. In the Science 2016 paper, we have combined mass spectrometric and computational method, which have enabled reliable protein quantification across a large number of mice cohorts. We established several mechanistic links among genetic loci, protein network states and disease phenotypes based on these highly accurate protein quantification data. We found Ucp1 protein levels being a stronger predictor of final temperature than its transcripts in mice cold test, and we are interested in dissecting correlation between proteotype and phenotype in other systems. We also working on generating association network on protein and transcript levels that show high level of enrichment of functionally related molecules. We are interested in deploying these mass spectrometric and computational methods to analyze tissue samples from aging mice in different genetic and environmental states. Currently, we aim to discover novel associations between proteotype states and aging-related mitochondrial dysfunctions.