New Perspectives, Opportunities, and Challenges in Exploring the Human Protein Kinome.

The human protein kinome comprises 535 proteins that, with the exception of approximately 50 pseudokinases, control intracellular signaling networks by catalyzing the phosphorylation of multiple protein substrates. While a major research focus of the last 30 years has been cancer-associated Tyr and Ser/Thr kinases, over 85% of the kinome has been identified to be dysregulated in at least one disease or developmental disorder. Despite this remarkable statistic, for the majority of protein kinases and pseudokinases, there are currently no inhibitors progressing toward the clinic, and in most cases, details of their physiologic and pathologic mechanisms remain at least partially obscure. By curating and annotating data from the literature and major public databases of phosphorylation sites, kinases, and disease associations, we generate an unbiased resource that highlights areas of unmet need within the kinome. We discuss strategies and challenges associated with characterizing catalytic and noncatalytic outputs in cells, and describe successes and new frontiers that will support more comprehensive cancer-targeting and therapeutic evaluation in the future. Cancer Res; 78(1); 15-29. ©2017 AACR

Multi-omic Profiling Reveals Dynamics of the Phased Progression of Pluripotency

Pluripotency is highly dynamic and progresses through a continuum of pluripotent stem cell states. The two states that bookend the pluripotency continuum, naive and primed, are well characterized, but our understanding of the intermediate states and transitions between them remains incomplete. Here, we dissect the dynamics of pluripotent state transitions underlying pre- to post-implantation epiblast differentiation. Through comprehensive mapping of the proteome, phosphoproteome, transcriptome, and epigenome of embryonic stem cells transitioning from naive to primed pluripotency, we find that rapid, acute, and widespread changes to the phosphoproteome precede ordered changes to the epigenome, transcriptome, and proteome. Reconstruction of the kinase-substrate networks reveals signaling cascades, dynamics, and crosstalk. Distinct waves of global proteomic changes mark discrete phases of pluripotency, with cell-state-specific surface markers tracking pluripotent state transitions. Our data provide new insights into multi-layered control of the phased progression of pluripotency and a foundation for modeling mechanisms regulating pluripotent state transitions (www.steamcellatlas.org)

Positive-unlabeled ensemble learning for kinase substrate prediction from dynamic phosphoproteomics data

Motivation: Protein phosphorylation is a post-translational modification that underlines various aspects of cellular signaling. A key step to reconstructing signaling networks involves identification of the set of all kinases and their substrates. Experimental characterization of kinase substrates is both expensive and time-consuming. To expedite the discovery of novel substrates, computational approaches based on kinase recognition sequence (motifs) from known substrates, protein structure, interaction and co-localization have been proposed. However, rarely do these methods take into account the dynamic responses of signaling cascades measured from in vivo cellular systems. Given that recent advances in mass spectrometry-based technologies make it possible to quantify phosphorylation on a proteome-wide scale, computational approaches that can integrate static features with dynamic phosphoproteome data would greatly facilitate the prediction of biologically relevant kinase-specific substrates. Results: Here, we propose a positive-unlabeled ensemble learning approach that integrates dynamic phosphoproteomics data with static kinase recognition motifs to predict novel substrates for kinases of interest. We extended a positive-unlabeled learning technique for an ensemble model, which significantly improves prediction sensitivity on novel substrates of kinases while retaining high specificity. We evaluated the performance of the proposed model using simulation studies and subsequently applied it to predict novel substrates of key kinases relevant to insulin signaling. Our analyses show that static sequence motifs and dynamic phosphoproteomics data are complementary and that the proposed integrated model performs better than methods relying only on static information for accurate prediction of kinase-specific substrates

PHOSPHORYLATION AND BEYOND: EXPLORATION OF TOR-MEDIATED PTM SIGNALING IN CHLAMYDOMONAS REINHARDTII

Target of rapamycin (TOR) is a highly conserved master regulatory kinase involved in the control of most essential biological processes including cell growth, nutrient sensing, and autophagy. While TOR is well-studied in mammalian species and yeast, comparatively little is known about its regulatory roles in other organisms, particularly in phototrophs. To fill this knowledge gap, the plant community is applying -omic strategies to assess the role of TOR in regulating metabolic pathways, particularly proteomics, which provides insight into expression levels and modifications that is missing in other techniques. Post-translational modifications (PTMs) to activate/deactivate functional proteins are an essential component of cellular signaling used by TOR and other regulators. This has propelled innovations in PTM analysis to probe metabolic pathways. Chlamydomonas reinhardtii is a model phototroph that is easily culturable and has a fully sequenced genome, making it an attractive organism for studying algal TOR signaling. The aim of this dissertation is to establish and apply PTM-focused proteomic methods in Chlamydomonas to characterize the role of protein phosphorylation and reversible oxidation in TOR’s regulation of signaling networks.First, this work investigates reversible oxidation sites under the control of TOR in Chlamydomonas through a quantitative inhibition study (Chapter 2). Next, a quantitative workflow for phosphopeptide analysis in Chlamydomonas that can be used to assess phosphorylative TOR signaling is described in detail with technical replicates to assess its overall reproducibility (Chapter 3). Application of the quantitative phosphoproteomic pipeline was then employed to study the impact of inositol polyphosphates on TOR signaling (Chapter 4). Techniques for performing in vitro kinase screening to identify direct targets of phosphorylation, are discussed including heterologous expression of kinase samples, preparation of a library of potential targets, screening parameters, and sample preparation for LC-MS/MS analysis (Chapter 5). This workflow provides insight into signaling pathways that cannot be gleaned from proteomic in vivo studies alone. Using these techniques, this kinase screening platform was validated using the pyruvate dehydrogenase kinase of Arabidopsis thaliana, and then applied to attempt to identify putative direct targets of Chlamydomonas TOR (Chapter 6). While this technique was unable to identify direct TOR targets, the success of the validation suggests that with further optimization of the expression and purification of the kinase construct, screening of TOR may be possible. Combined, the work shared herein highlights the importance of TOR in algal signaling and provides valuable information on the regulatory modifications under TOR control.Doctor of Philosoph