Project Summary The broad goal of our lab is to obtain a systems-level understanding of cellular organization and develop proteomics technology that facilitates this research. Thanks to the human genome project, we have a nearly complete parts list of all molecules making up cells, but we still very poorly understand how these molecules come together and elegantly organize into a living system. So far, this organization has been studied mainly by looking carefully at one protein at a time. While this approach has been tremendously successful, it cannot address the higher levels of complexity in biological systems that arise from the interplay of a myriad of components. Looking at one molecule at a time can severely hinder understanding biology. Instead, we investigate the entire system all at once. Recent progress in multiplexed proteomics enables us to observe thousands of proteins simultaneously among multiple conditions. Combined with classical biochemical approaches, we can reveal collective behavior and emergent properties that we would not have discovered otherwise. My lab is broadly interested in systems-level cellular organization. Towards this goal, this proposal contains two parts. The first part of this proposal outlines how we intend to improve quantitative proteomics technology. Proteomics has become very powerful. Nevertheless, severe shortcomings concerning sensitivity, data quality, and accessibility remain. We strive to address these problems. Over the last year, we have developed a new method for quantitative shotgun proteomics (TMTproC), producing data with unmatched sensitivity and measurement quality while reducing cost. Next, we aim to make TMTproC compatible with entry-level mass spectrometers, which has the potential to democratize quantitative proteomics. Furthermore, we propose to fuse TMTproC with data-independent acquisition (DIA). We anticipate that this will fuse the benefits of both approaches: a method delivering the exquisite measurement quality of multiplexed proteomics with the infinite scalability of DIA. The second part describes how we aim to apply our technological advances toward understanding systems-level mechanisms. First, we will integrate passive diffusion and active transport models through the nuclear pore to predict how the entire proteome partitions between the nucleus and cytoplasm. Second, we aim to integrate all levels of protein abundance control aspects for every gene – transcription, translation, and protein degradation. We will focus on protein turnover, the technically most difficult to measure of these parameters. Ultimately, we aim to determine how protein expression levels are controlled for each gene as a fertilized zygote develops into an embryo with a fully defined body plan. These measurements will provide us with fundamental insight into the regulation and organization of developing embryos in health and disease.