Birgit Schilling (The Buck Institute)
Post-translational modifications (PTMs) dynamically regulate proteins and pathways through immediate signaling cascades and resulting changes in protein function or activity. To explore the dynamic changes of lysine succinylation, we optimized a powerful emerging strategy coupling PTM enrichment and refined spectral library-free data-independent acquisition (DIA) workflows for accurate quantification. After peptide enrichment using PTMScan immunoaffinity beads (CST), samples were analyzed by data-independent acquisition (DIA) on an Orbitrap Eclipse Tribrid platform, and data were processed and quantified without pre-existing spectral libraries using directDIA (Biognosys). We are reducing MS instrument time and are limiting PTM sample amount needed by circumventing DDA scans and using the DIA files to directly build spectral libraries. We have utilized these methods to examine precious biological samples and have detected thousands of succinylated or malonylated lysines from multiple organs, such as brain, liver, and kidney providing a large amount of tissue specific changes and acylation profiles (in mice and non-human primates). One study examined the succinylome profile during acute kidney injury and the effects of a nutritional supplement on recovery in mice. Here, using Spectronaut (Biognosys) we identified, quantified, and localized 3,666 succinylated sites in total. We also determined that the diet induced significant hypersuccinylation of 1,085 sites which effectively remodeled the succinylome completely, however, this treatment barely affected the proteome, as on the protein level only 26 proteins were significantly altered. Spectral library free directDIA workflows are highly efficient and have allowed us to make optimize and increase throughput for our PTM analysis workflows.
Mario Leutert (Judit Villén Lab – University of Washington)
The development of mass spectrometry-based phosphoproteomics has substantially expanded our understanding of cellular processes regulated by protein phosphorylation. However, most phosphoproteomic studies are low dimensional (<5 conditions) due to analytical limitations. Phosphoproteomic profiling at much higher dimensionality is required to obtain systematic insight into the architecture and function of phosphorylation-dependent signaling networks. Here we present a high-dimensional quantitative phosphoproteomic-perturbation atlas in Saccharomyces cerevisiae at large scale (>100 perturbations, ~600 samples). We applied a combination of novel methods for automated sample-preparation, prioritization of functional phosphosites by machine learning and advanced data-analysis to overcome current limitations in large-scale phosphoproteomics. Integrating this massive quantitative resource gave us the unique opportunity to systematically elucidate signaling modules, profile kinase activities, and predict functional phosphorylation sites at organismal scale.
Short-Bio Birgit Schilling
Dr. Schilling is an Associate Professor and the Director of the Mass Spectrometry Core at the Buck Institute for Research on Aging in California, and she is also an Adjunct Professor at the University of Southern California (USC). The Schilling lab develops and implements advanced innovative protein analytical technologies (including quantitative proteomics, posttranslational modifications, protein dynamics and biomarker discovery) to advance basic biology and biomedical research related to aging research. Several research projects include investigation of protein phosphorylation, acylation, and other posttranslational modifications, as well as differential expression of proteins during disease and aging processes. We are particularly interested in deciphering underlying mechanisms of senescence during aging, and we have developed MS methodologies to quantitatively analyze protein secretomes, secreted exosomes and to perform accurate quantitative protein expression workflows. The Schilling lab has adopted several novel proteomic technologies with comprehensive and extremely sensitive quantification capabilities, and these are particularly applicable for the proposed project. We are using proteomic data-independent acquisitions (DIA), or SWATH which allows us to accurately determine changes in relative protein expression level between multiple different conditions. A key interest is in finding senescence-derived biomarker candidates for aging.
Short-Bio Mario Leutert
Mario Leutert received his bachelor’s and master’s degree in biotechnology from ETH Zurich and earned his PhD in Molecular Life Sciences from the University of Zurich. Dr. Leutert is currently a post-doctoral researcher in the Department of Genome Sciences at the University of Washington in the Laboratory of Dr. Judit Villén. His research focuses on the investigation of cellular signal transduction pathways. He aims to better understand the wiring diagram of the cell with the goal to reveal molecular mechanisms that lead to disease and aging. To achieve this Dr. Leutert is involved in developing and applying mass spectrometry-based proteomic technologies to perform large-scale quantitative experiments in different biological model systems. Specific areas of interest are post-translational modifications of proteins by kinases and ADP-ribosyl transferases, development of new proteomic workflows, integration of large-scale multidimensional proteomic measurements, mitochondrial disease models, and loss of proteome integrity during aging.
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