Kinobead/LC-MS Phosphokinome Profiling Enables Rapid Analyses of Kinase-Dependent Cell Signaling Networks

Proteomic approaches for protein kinase substrate identification in Apicomplexa

Apicomplexa is a phylum of protist parasites, notable for causing life-threatening diseases including malaria, toxoplasmosis, cryptosporidiosis, and babesiosis. Apicomplexan pathogenesis is generally a function of lytic replication, dissemination, persistence, host cell modification, and immune subversion. Decades of research have revealed essential roles for apicomplexan protein kinases in establishing infections and promoting pathogenesis. Protein kinases modify their substrates by phosphorylating serine, threonine, tyrosine, or other residues, resulting in rapid functional changes in the target protein. Post-translational modification by phosphorylation can activate or inhibit a substrate, alter its localization, or promote interactions with other proteins or ligands. Deciphering direct kinase substrates is crucial to understand mechanisms of kinase signaling, yet can be challenging due to the transient nature of kinase phosphorylation and potential for downstream indirect phosphorylation events. However, with recent advances in proteomic approaches, our understanding of kinase function in Apicomplexa has improved dramatically. Here, we discuss methods that have been used to identify kinase substrates in apicomplexan parasites, classifying them into three main categories: i) kinase interactome, ii) indirect phosphoproteomics and iii) direct labeling. We briefly discuss each approach, including their advantages and limitations, and highlight representative examples from the Apicomplexa literature. Finally, we conclude each main category by introducing prospective approaches from other fields that would benefit kinase substrate identification in Apicomplexa.

Recruitment of BAG2 to DNAJ-PKAc scaffolds promotes cell survival and resistance to drug-induced apoptosis in fibrolamellar carcinoma

The DNAJ-PKAc fusion kinase is a defining feature of fibrolamellar carcinoma (FLC). FLC tumors are notoriously resistant to standard chemotherapies, with aberrant kinase activity assumed to be a contributing factor. By combining proximity proteomics, biochemical analyses, and live-cell photoactivation microscopy, we demonstrate that DNAJ-PKAc is not constrained by A-kinase anchoring proteins. Consequently, the fusion kinase phosphorylates a unique array of substrates, including proteins involved in translation and the anti-apoptotic factor Bcl-2-associated athanogene 2 (BAG2), a co-chaperone recruited to the fusion kinase through association with Hsp70. Tissue samples from patients with FLC exhibit increased levels of BAG2 in primary and metastatic tumors. Furthermore, drug studies implicate the DNAJ-PKAc/Hsp70/BAG2 axis in potentiating chemotherapeutic resistance. We find that the Bcl-2 inhibitor navitoclax enhances sensitivity to etoposide-induced apoptosis in cells expressing DNAJ-PKAc. Thus, our work indicates BAG2 as a marker for advanced FLC and a chemotherapeutic resistance factor in DNAJ-PKAc signaling scaffolds.

A strategy to disentangle direct and indirect effects on (de)phosphorylation by chemical modulators of the phosphatase PP1 in complex cellular contexts

Chemical activators and inhibitors are useful probes to identify substrates and downstream effects of enzymes; however, due to the complex signaling environment within cells, it is challenging to distinguish between direct and indirect effects. This is particularly the case for phosphorylation, where a single (de)phosphorylation event can trigger rapid changes in many other phosphorylation sites. An additional complication arises when a single catalytic entity, which acts in the form of many different holoenzymes with different substrates, is activated or inhibited, as it is unclear which holoenzymes are affected, and in turn which of their substrates are (de)phosphorylated. Direct target engaging MS-based technologies to study targets of drugs do not address these challenges. Here, we tackle this by studying the modulation of protein phosphatase-1 (PP1) activity by PP1-disrupting peptides (PDPs), as well as their selectivity toward PP1, by using a combination of mass spectrometry-based experiments. By combining cellular treatment with the PDP with in vitro dephosphorylation by the enzyme, we identify high confidence substrate candidates and begin to separate direct and indirect effects. Together with experiments analyzing which holoenzymes are particularly susceptible to this treatment, we obtain insights into the effect of the modulator on the complex network of protein (de)phosphorylation. This strategy holds promise for enhancing our understanding of PP1 in particular and, due to the broad applicability of the workflow and the MS-based read-out, of chemical modulators with complex mode of action in general.

Multiplexed kinase interactome profiling quantifies cellular network activity and plasticity

Dynamic changes in protein-protein interaction (PPI) networks underlie all physiological cellular functions and drive devastating human diseases. Profiling PPI networks can, therefore, provide critical insight into disease mechanisms and identify new drug targets. Kinases are regulatory nodes in many PPI networks; yet, facile methods to systematically study kinase interactome dynamics are lacking. We describe kinobead competition and correlation analysis (kiCCA), a quantitative mass spectrometry-based chemoproteomic method for rapid and highly multiplexed profiling of endogenous kinase interactomes. Using kiCCA, we identified 1,154 PPIs of 238 kinases across 18 diverse cancer lines, quantifying context-dependent kinase interactome changes linked to cancer type, plasticity, and signaling states, thereby assembling an extensive knowledgebase for cell signaling research. We discovered drug target candidates, including an endocytic adapter-associated kinase (AAK1) complex that promotes cancer cell epithelial-mesenchymal plasticity and drug resistance. Our data demonstrate the importance of kinase interactome dynamics for cellular signaling in health and disease.

KiRNet: Kinase-centered network propagation of pharmacological screen results

The ever-increasing size and scale of biological information have popularized network-based approaches as a means to interpret these data. We develop a network propagation method that integrates kinase-inhibitor-focused functional screens with known protein-protein interactions (PPIs). This method, dubbed KiRNet, uses an a priori edge-weighting strategy based on node degree to establish a pipeline from a kinase inhibitor screen to the generation of a predictive PPI subnetwork. We apply KiRNet to uncover molecular regulators of mesenchymal cancer cells driven by overexpression of Frizzled 2 (FZD2). KiRNet produces a network model consisting of 166 high-value proteins. These proteins exhibit FZD2-dependent differential phosphorylation, and genetic knockdown studies validate their role in maintaining a mesenchymal cell state. Finally, analysis of clinical data shows that mesenchymal tumors exhibit significantly higher average expression of the 166 corresponding genes than epithelial tumors for nine different cancer types.

Phosphoproteomic Analysis as an Approach for Understanding Molecular Mechanisms of cAMP-Dependent Actions

In recent years, highly sensitive mass spectrometry-based phosphoproteomic analysis is beginning to be applied to identification of protein kinase substrates altered downstream of increased cAMP. Such studies identify a very large number of phosphorylation sites regulated in response to increased cAMP. Therefore, we now are tasked with the challenge of determining how many of these altered phosphorylation sites are relevant to regulation of function in the cell. This minireview describes the use of phosphoproteomic analysis to monitor the effects of cyclic nucleotide phosphodiesterase (PDE) inhibitors on cAMP-dependent phosphorylation events. More specifically, it describes two examples of this approach carried out in the authors' laboratories using the selective PDE inhibitor approach. After a short discussion of several likely conclusions suggested by these analyses of cAMP function in steroid hormone-producing cells and also in T-cells, it expands into a discussion about some newer and more speculative interpretations of the data. These include the idea that multiple phosphorylation sites and not a single rate-limiting step likely regulate these and, by analogy, many other cAMP-dependent pathways. In addition, the idea that meaningful regulation requires a high stoichiometry of phosphorylation to be important is discussed and suggested to be untrue in many instances. These new interpretations have important implications for drug design, especially for targeting pathway agonists. SIGNIFICANCE STATEMENT: Phosphoproteomic analyses identify thousands of altered phosphorylation sites upon drug treatment, providing many possible regulatory targets but also highlighting questions about which phosphosites are functionally important. These data imply that multistep processes are regulated by phosphorylation at not one but rather many sites. Most previous studies assumed a single step or very few rate-limiting steps were changed by phosphorylation. This concept should be changed. Previous interpretations also assumed substoichiometric phosphorylation was not of regulatory importance. This assumption also should be changed.

Pharmacoproteomics Identifies Kinase Pathways that Drive the Epithelial-Mesenchymal Transition and Drug Resistance in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a complex and deadly disease lacking druggable genetic mutations. The limited efficacy of systemic treatments for advanced HCC implies that predictive biomarkers and drug targets are urgently needed. Most HCC drugs target protein kinases, indicating that kinase-dependent signaling networks drive HCC progression. To identify HCC signaling networks that determine responses to kinase inhibitors (KIs), we apply a pharmacoproteomics approach integrating kinome activity in 17 HCC cell lines with their responses to 299 KIs, resulting in a comprehensive dataset of pathway-based drug response signatures. By profiling patient HCC samples, we identify signatures of clinical HCC drug responses in individual tumors. Our analyses reveal kinase networks promoting the epithelial-mesenchymal transition (EMT) and drug resistance, including a FZD2-AXL-NUAK1/2 signaling module, whose inhibition reverses the EMT and sensitizes HCC cells to drugs. Our approach identifies cancer drug targets and molecular signatures of drug response for personalized oncology.