National Center for Quantitative Biology of Complex Systems

PROJECT SUMMARY – DRIVING BIOMEDICAL PROJECTS The high-level goals of our Resource are to accelerate the pace, depth, and accuracy of protein and PTM quantification, and to empower the scientific community to make new, impactful discoveries with these technologies. Initially, our TR&Ds were influenced by a clear need in the broad field of metabolism for new technologies that could accelerate discovery. Using our expertise in this field, we recruited world-class scientists who devised projects that served as robust testbeds for our TR&Ds. Many of these projects have been driven to completion while others have remained active and have influenced new TR&Ds. These interactions – and the broad utility of our technologies – have led to a natural expansion of our focus areas. We have also become better calibrated on our capabilities and bandwidth, allowing us to shoulder a broad swath of projects with efficiency and high success rates. For Cycle 2, two overarching DBP themes motivate our Resource’s technology development: Theme 1. New, metabolite-derived post-translational modifications (PTMs). The ability of PTMs such as phosphorylation and ubiquitylation to regulate signaling and protein turnover has long been established, and we have accelerated discoveries in this space through our original DBPs. Now, the scientific community is experiencing a renaissance of interest in how understudied modifications exert control over protein function in diverse cell biological contexts. These include methylation, acylation, glycosylation, and hydroxylation. Additionally, modifications to other biological species, such as glycosylated nucleic acids, are emerging as exciting, unexplored areas of biology. Many of these modifications are directly derived from central metabolites, thus intimately linking them to the metabolic state of the cell. Theme 2. Large-scale systems and multi-omics analyses to explore physiology and metabolism. The sequencing of the human genome, a watershed moment for biology, set a framework for deep understanding of genes and their functions. Next-generation sequencing has greatly accelerated our ability to measure the expression levels of these genes, thereby giving us a surface- level understanding of how cellular processes are changing under contrasting states. Nonetheless, myriad large- scale analyses have revealed a marginal protein/RNA correlation (R ~ 0.5), demonstrating the need for protein measurements of comparable depth and precision. Similarly, comprehensive analyses of lipid and metabolite abundance have revealed that protein expression alone is insufficient to predict metabolite levels, which are further affected by protein modifications and substrate availability, among other influences. Collectively, these observations have mandated the development of integrated, multi-omic analyses that provide a more holistic picture of a biological state.