Agenda

Different stable isotope labeling strategies coupled to mass spectrometry have been used to measure protein turnover rates in vivo and in vitro. Our group developed Riana (Relative isotope abundance analyzer) which performs isotopomer quantification and kinetic curve fitting in a manner compatible with various SILAC and elemental labeling approaches. Using Riana, we have compared the turnover rates of proteins across four mouse tissues, obtained from the same inbred mouse strain maintained under identical husbandry conditions, measured using either heavy water or heavy lysine as the labeling precursor. We describe an isotopomer selection strategy that can improve the depth of protein turnover quantification in vivo and in vitro.

The process of discovery requires stepping into the unknown and trying to learn something new.  In my experience good notes and thoughtful meditation on results have resulted in the most insightful discoveries.  This suggests a recipe to succeed in proteomics and any research-based career.  I will present a couple of specific examples from my career and try to outline principles that lead to success.  Interestingly, my recipe for success incorporates the essence of a couple frequently repeated idioms.  1. A well-ordered and thoughtful experiment will teach you something regardless of whether it supports your hypothesis.  2. Just because you failed doesn't mean you are a failure.  3. Luck favors the prepared.   In my experience the wealth of information and opportunity for confusion versus discovery in a proteomics experiment increases the value of these ideas.

Biological functions are reflected in the natural variation of proteome configurations across individual cells. Single-cell proteomics methods may decode this variation and empower inference of biological mechanisms with minimal assumptions. This promise is beginning to be realized by sensitive and scalable mass spectrometry methods. Specifically, prioritized single-cell mass spectrometry analysis (pSCoPE) allows for consistent and sensitive analysis of thousands of proteins of biological interest, and multiplexed data independent acquisition methods (plexDIA) afford high throughput and data completeness. These methods have allowed us to interpret protein covariation in different biological systems, including primary macrophages and melanoma cells expressing markers for drug-resistance priming. The focus of the talk will be on conceptual innovations and strategies for data acquisition and interpretation that make single-cell protein analysis accessible, robust and highly quantitative.

Deregulation of kinase function in cell signaling pathways is implicated in numerous cancers. In response, kinase inhibitors (KIs) have been developed to interact with these kinases for highly specific treatment. Though nearly 50 KIs have been FDA-approved, KI monotherapy is seldom curative, likely owing to tumor heterogeneity and acquired resistance. In response, effective combination therapies must be tailored to known resistance mechanisms to efficiently engage with their targets and exploit cellular vulnerabilities. However, standard drug screening tools (e.g., plasma analysis, western blot) are bulk in nature, and no established technology exists to quantify KI target engagement, concomitant with local protein expression, while assessing tumor response heterogeneity. To address these shortcomings, our group has (1) developed protocols to fluorescently label KIs (and other small molecule therapeutics) that mimic the native drug, (2) advanced a novel intracellular paired agent imaging (iPAI) platform to quantify drug target availability (DTA) with these fluorescent KIs, and (3) established and validated a highly multiplexed immunostaining strategy utilizing DNA barcoded antibodies, enabling in situ cyclic immunofluorescence (cyCIF) imaging. In this project, we combine these three complementary innovations into a fluorescence imaging platform we call TRIPODD (Therapeutic Response Imaging through Proteomics and Optical Drug Distribution and binding).Deregulation of kinase function in cell signaling pathways is implicated in numerous cancers. In response, kinase inhibitors (KIs) have been developed to interact with these kinases for highly specific treatment. Though nearly 50 KIs have been FDA-approved, KI monotherapy is seldom curative, likely owing to tumor heterogeneity and acquired resistance. In response, effective combination therapies must be tailored to known resistance mechanisms to efficiently engage with their targets and exploit cellular vulnerabilities. However, standard drug screening tools (e.g., plasma analysis, western blot) are bulk in nature, and no established technology exists to quantify KI target engagement, concomitant with local protein expression, while assessing tumor response heterogeneity. To address these shortcomings, our group has (1) developed protocols to fluorescently label KIs (and other small molecule therapeutics) that mimic the native drug, (2) advanced a novel intracellular paired agent imaging (iPAI) platform to quantify drug target availability (DTA) with these fluorescent KIs, and (3) established and validated a highly multiplexed immunostaining strategy utilizing DNA barcoded antibodies, enabling in situ cyclic immunofluorescence (cyCIF) imaging. In this project, we combine these three complementary innovations into a fluorescence imaging platform we call TRIPODD (Therapeutic Response Imaging through Proteomics and Optical Drug Distribution and binding).