Development and Application of Complementary Protein Stability Profiling Techniques for Protein Target Identification and Biomarker Discovery

Abstract

Protein stability profiling techniques, including stability of proteins from rates of oxidation (SPROX), thermal proteome profiling (TPP), and limited proteolysis (LiP), have created a new toolbox for making protein folding stability measurements on the proteomic scale. Despite the broad usage of these techniques in an increasingly large number of applications, few studies have been reported in which more than one of these techniques have been used for the same application. Therefore, detailed information about the complementarity of these different experimental approaches is lacking. A major focus of the work described in this thesis is the comparative analysis of these different experimental strategies in different application areas. Described in Chapter 2 of this dissertation is a new experimental workflow for multiplexing TPP analyses that is also amenable to SPROX analyses. In a proof-of-principle study, this new workflow (termed, "one-pot" workflow) was demonstrated to significantly reduce the instrument time and cost of materials by 10-fold, which consequentially enabled enhanced multiplexing compared to traditional protein stability profiling analysis. This "one-pot" workflow, which is also amenable to SPROX analysis, makes feasible the acquisition of protein stability profiling data from multiple biological replicates and even multiple techniques (e.g., SPROX and TPP) in a given application. Described in Chapters 3, 4, and 5 of this dissertation are applications of SPROX, TPP, and LiP to a series of protein target discovery projects involving several different small molecule drugs with known biological activities but unknown modes of action. These applications included the use of multiple energetics-based techniques and in some cases included the "one-pot" workflow, to identify the protein targets of the bioactive small molecules. These results of these studies included: i) identification of TCP-1 as the anti-malarial target of clemastine in a Plasmodium falciparum (Pf) cell lysate; ii) identification of potential Pf protein targets of several additional anti-malarial drugs; iii) identification of Rab-1A as the anti-Parkinson target of NAB1; iv) identification of potential protein targets of anti-salmonella drugs in a complex host-pathogen system; and v) identification of the interactome of CoA and de-phosphorylated CoA in mammalian cells. The results of these protein target discovery studies not only helped elucidate the molecular basis of the biological activities of the above small molecules, but the results also demonstrated the power of using multiple protein stability profiling techniques to deconvolute protein targets and identify small molecule interactomes.The final chapter of this dissertation describes the use of protein stability profiling methods, including the "one-pot" SPROX and TPP workflows as well as LiP, to identify potential prognostic biomarkers of oxaliplatin resistance in colorectal cancer. The goal of this work was to identify the overlapping protein hits identified in SPROX, TPP, and LiP analyses of oxaliplatin resistant and sensitive colorectal cancer cell lines (n=3 cell line comparisons) and patient-derived xenograft mouse models of oxaliplatin resistance and sensitivity (n= 1 mouse model comparison). Ultimately, 23 differentially stabilized proteins were identified with differential stability in at least 2 techniques and consistent results in both cell culture models and PDX mouse models. These 23 proteins included 9 proteins being previously connected to cancer chemo-resistance. One of these 9 differentially stabilized proteins, major vault protein (MVP), was further investigated to elucidate its role on colorectal cancer chemoresistance. This research demonstrated that complementary protein stability profiling is a complementary approach to identify potential prognostic biomarkers and shed light on understanding the molecular mechanism of colorectal cancer chemoresistance. In conclusion, the work in this dissertation described an integrated workflow for energetics-based proteomic techniques that can be used for target deconvolution and biomarker identification in complex biological systems.