Global analysis of phosphorylation networks in humans

Modulating the phosphorylation status of target proteins through bifunctional molecules

Phosphorylation is an important form of protein post-translational modification (PTM) in cells. Dysregulation of phosphorylation is closely associated with many diseases. Because the regulation of proteins of interest (POIs) by chemically induced proximity (CIP) strategies has been widely validated, regulating the phosphorylation status of POIs by phosphorylation-regulating bifunctional molecules (PBMs) emerges as an alternative paradigm. PBMs promote the spatial proximity of POIs to kinases/phosphatases, and thus alter the phosphorylation state of POIs. Herein, we describe the history and current status of PBMs, analyze in detail the general design principles and specific applications of PBMs, assess their current advantages, possible challenges and limitations, and propose future directions for PBMs, which will stimulate interest in PBM research.

Final step of B-cell differentiation into plasmablasts; the right time to activate plasma cell PIM2 kinase

The differentiation of B cells into antibody-secreting plasma cells is a complex process that involves extensive changes in morphology, lifespan, and cellular metabolism to support the high rates of antibody production. During the final stage of differentiation, B cells undergo significant expansion of their endoplasmic reticulum and mitochondria, which induces cellular stress and may lead to cell death in absence of effective inhibition of the apoptotic pathway. These changes are tightly regulated at transcriptional and epigenetic levels, as well as at post-translational level, with protein modifications playing a critical role in the process of cellular modification and adaptation. Our recent research has highlighted the pivotal role of the serine/threonine kinase PIM2 in B cell differentiation, from commitment stage to plasmablast and maintenance of expression in mature plasma cells. PIM2 has been shown to promote cell cycle progression during the final stage of differentiation and to inhibit Caspase 3 activation, raising the threshold for apoptosis. In this review, we examine the key molecular mechanisms controlled by PIM2 that contribute to plasma cell development and maintenance.

PPICT: an integrated deep neural network for predicting inter-protein PTM cross-talk

Post-translational modifications (PTMs) fine-tune various signaling pathways not only by the modification of a single residue, but also by the interplay of different modifications on residue pairs within or between proteins, defined as PTM cross-talk. As a challenging question, less attention has been given to PTM dynamics underlying cross-talk residue pairs and structural information underlying protein-protein interaction (PPI) graph, limiting the progress in this PTM functional research. Here we propose a novel integrated deep neural network PPICT (Predictor for PTM Inter-protein Cross-Talk), which predicts PTM cross-talk by combining protein sequence-structure-dynamics information and structural information for PPI graph. We find that cross-talk events preferentially occur among residues with high co-evolution and high potential in allosteric regulation. To make full use of the complex associations between protein evolutionary and biophysical features, and protein pair features, a heterogeneous feature combination net is introduced in the final prediction of PPICT. The comprehensive test results show that the proposed PPICT method significantly improves the prediction performance with an AUC value of 0.869, outperforming the existing state-of-the-art methods. Additionally, the PPICT method can capture the potential PTM cross-talks involved in the functional regulatory PTMs on modifying enzymes and their catalyzed PTM substrates. Therefore, PPICT represents an effective tool for identifying PTM cross-talk between proteins at the proteome level and highlights the hints for cross-talk between different signal pathways introduced by PTMs.

Integrated Stress Response in Neuronal Pathology and in Health

Neurodegeneration involves progressive pathological loss of a specific population of neurons, glial activation, and dysfunction of myelinating oligodendrocytes leading to cognitive impairment and altered movement, breathing, and senses. Neuronal degeneration is a hallmark of aging, stroke, drug abuse, toxic chemical exposure, viral infection, chronic inflammation, and a variety of neurological diseases. Accumulation of intra- and extracellular protein aggregates is a common characteristic of cell pathologies. Excessive production of reactive oxygen species and nitric oxide, induction of endoplasmic reticulum stress, and accumulation of misfolded protein aggregates have been shown to trigger a defensive mechanism called integrated stress response (ISR). Activation of ISR is important for synaptic plasticity in learning and memory formation. However, sustaining of ISR may lead to the development of neuronal pathologies and altered patterns in behavior and perception.

KEA3: improved kinase enrichment analysis via data integration

Phosphoproteomics and proteomics experiments capture a global snapshot of the cellular signaling network, but these methods do not directly measure kinase state. Kinase Enrichment Analysis 3 (KEA3) is a webserver application that infers overrepresentation of upstream kinases whose putative substrates are in a user-inputted list of proteins. KEA3 can be applied to analyze data from phosphoproteomics and proteomics studies to predict the upstream kinases responsible for observed differential phosphorylations. The KEA3 background database contains measured and predicted kinase-substrate interactions (KSI), kinase-protein interactions (KPI), and interactions supported by co-expression and co-occurrence data. To benchmark the performance of KEA3, we examined whether KEA3 can predict the perturbed kinase from single-kinase perturbation followed by gene expression experiments, and phosphoproteomics data collected from kinase-targeting small molecules. We show that integrating KSIs and KPIs across data sources to produce a composite ranking improves the recovery of the expected kinase. The KEA3 webserver is available at https://maayanlab.cloud/kea3.

Assessing the activation/inhibition of tyrosine kinase-related pathways with a newly developed platform

The phosphorylation of cellular proteins plays a crucial role in the transduction of various signals from outside the cell into the nucleus. The signals are transduced by phosphorylation chain reactions within multiple pathways; however, determining which pathways are responsible for each defined signal has proven challenging. To estimate the activity of each pathway, we developed a phosphorylation array platform comprising a protein array with 1200 proteins belonging to 376 signalling pathways and an analytical method to estimate pathway activity based on the phosphorylation levels of proteins. The performance of our system was assessed by reconstructing kinase-substrate relationships, as well as by estimating pathway activity upon epidermal growth factor (EGF) stimulation and the pharmacological inhibition of epidermal growth factor receptor (EGFR). As a result, kinase-substrate relationships were reliably reconstructed based on the precise measurement of phosphorylation levels of constituent proteins on the array. Furthermore, the pathway activities associated with EGF stimulation and EGFR inhibition were successfully traced through the related pathways from the outer membrane to the nucleus along a time course. Thus, our phosphorylation array system can effectively assess the activity of specific signalling pathways that are perturbed by extracellular stimuli, such as various drugs.

The integrated stress response: From mechanism to disease

Protein quality control is essential for the proper function of cells and the organisms that they make up. The resulting loss of proteostasis, the processes by which the health of the cell's proteins is monitored and maintained at homeostasis, is associated with a wide range of age-related human diseases. Here, we highlight how the integrated stress response (ISR), a central signaling network that responds to proteostasis defects by tuning protein synthesis rates, impedes the formation of long-term memory. In addition, we address how dysregulated ISR signaling contributes to the pathogenesis of complex diseases, including cognitive disorders, neurodegeneration, cancer, diabetes, and metabolic disorders. The development of tools through which the ISR can be modulated promises to uncover new avenues to diminish pathologies resulting from it for clinical benefit.

Convergent Identification and Interrogation of Tumor-Intrinsic Factors that Modulate Cancer Immunity In Vivo

The genetic makeup of cancer cells directs oncogenesis and influences the tumor microenvironment. In this study, we massively profiled genes that functionally drive tumorigenesis using genome-scale in vivo CRISPR screens in hosts with different levels of immunocompetence. As a convergent hit from these screens, Prkar1a mutant cells are able to robustly outgrow as tumors in fully immunocompetent hosts. Functional interrogation showed that Prkar1a loss greatly altered the transcriptome and proteome involved in inflammatory and immune responses as well as extracellular protein production. Single-cell transcriptomic profiling and flow cytometry analysis mapped the tumor microenvironment of Prkar1a mutant tumors and revealed the transcriptomic alterations in host myeloid cells. Taken together, our data suggest that tumor-intrinsic mutations in Prkar1a lead to drastic alterations in the genetic program of cancer cells, thereby remodeling the tumor microenvironment.

Next-Generation Genome-Scale Models Incorporating Multilevel 'Omics Data: From Yeast to Human

Genome-scale modelling in eukaryotes has been pioneered by the yeast Saccharomyces cerevisiae. Early metabolic networks have been reconstructed based on genome sequence and information accumulated in the literature on biochemical reactions. Protein-protein interaction networks have been constructed based on experimental observations such as yeast-2-hybrid method. Gene regulatory networks were based on a variety of data types, including information on TF-promoter binding and gene coexpression. The aforementioned networks have been improved gradually, and methods for their integration were developed. Incorporation of omics data including genomics, metabolomics, transcriptomics, fluxome, and phosphoproteome led to next-generation genome-scale models. The methods tested on yeast have later been implemented in human, further, cellular components found to be important in yeast physiology under (ab)normal conditions, and (dis)regulation mechanisms in yeast shed light to the healthy and disease states in human. This chapter provides a historical perspective on next-generation genome-scale models incorporating multilevel 'omics data, from yeast to human.

Signaling Architectures that Transmit Unidirectional Information Despite Retroactivity

A signaling pathway transmits information from an upstream system to downstream systems, ideally in a unidirectional fashion. A key obstacle to unidirectional transmission is retroactivity, the additional reaction flux that affects a system once its species interact with those of downstream systems. This raises the fundamental question of whether signaling pathways have developed specialized architectures that overcome retroactivity and transmit unidirectional signals. Here, we propose a general procedure based on mathematical analysis that provides an answer to this question. Using this procedure, we analyze the ability of a variety of signaling architectures to transmit one-way (from upstream to downstream) signals, as key biological parameters are tuned. We find that single stage phosphorylation and phosphotransfer systems that transmit signals from a kinase show a stringent design tradeoff that hampers their ability to overcome retroactivity. Interestingly, cascades of these architectures, which are highly represented in nature, can overcome this tradeoff and thus enable unidirectional transmission. By contrast, phosphotransfer systems, and single and double phosphorylation cycles that transmit signals from a substrate, are unable to mitigate retroactivity effects, even when cascaded, and hence are not well suited for unidirectional information transmission. These results are largely independent of the specific reaction-rate constant values, and depend on the topology of the architectures. Our results therefore identify signaling architectures that, allowing unidirectional transmission of signals, embody modular processes that conserve their input/output behavior across multiple contexts. These findings can be used to decompose natural signal transduction networks into modules, and at the same time, they establish a library of devices that can be used in synthetic biology to facilitate modular circuit design.

Novel Noncatalytic Substrate-Selective p38α-Specific MAPK Inhibitors with Endothelial-Stabilizing and Anti-Inflammatory Activity

The p38 MAPK family is composed of four kinases of which p38α/MAPK14 is the major proinflammatory member. These kinases contribute to many inflammatory diseases, but the currently available p38 catalytic inhibitors (e.g., SB203580) are poorly effective and cause toxicity. We reasoned that the failure of catalytic p38 inhibitors may derive from their activity against noninflammatory p38 isoforms (e.g., p38β/MAPK11) and loss of all p38α-dependent responses, including anti-inflammatory, counterregulatory responses via mitogen- and stress-activated kinase (MSK) 1/2 and Smad3. We used computer-aided drug design to target small molecules to a pocket near the p38α glutamate-aspartate (ED) substrate-docking site rather than the catalytic site, the sequence of which had only modest homology among p38 isoforms. We identified a lead compound, UM101, that was at least as effective as SB203580 in stabilizing endothelial barrier function, reducing inflammation, and mitigating LPS-induced mouse lung injury. Differential scanning fluorimetry and saturation transfer difference-nuclear magnetic resonance demonstrated specific binding of UM101 to the computer-aided drug design-targeted pockets in p38α but not p38β. RNA sequencing analysis of TNF-α-stimulated gene expression revealed that UM101 inhibited only 28 of 61 SB203580-inhibited genes and 7 of 15 SB203580-inhibited transcription factors, but spared the anti-inflammatory MSK1/2 pathway. We provide proof of principle that small molecules that target the ED substrate-docking site may exert anti-inflammatory effects similar to the catalytic p38 inhibitors, but their isoform specificity and substrate selectivity may confer inherent advantages over catalytic inhibitors for treating inflammatory diseases.

A Human Proteome Array Approach to Identifying Key Host Proteins Targeted by Toxoplasma Kinase ROP18

Toxoplasma kinase ROP18 is a key molecule responsible for the virulence of Toxoplasma gondii; however, the mechanisms by which ROP18 exerts parasite virulence via interaction with host proteins remain limited to a small number of identified substrates. To identify a broader array of ROP18 substrates, we successfully purified bioactive mature ROP18 and used it to probe a human proteome array. Sixty eight new putative host targets were identified. Functional annotation analysis suggested that these proteins have a variety of functions, including metabolic process, kinase activity and phosphorylation, cell growth, apoptosis and cell death, and immunity, indicating a pleiotropic role of ROP18 kinase. Among these proteins, four candidates, p53, p38, UBE2N, and Smad1, were further validated. We demonstrated that ROP18 targets p53, p38, UBE2N, and Smad1 for degradation. Importantly, we demonstrated that ROP18 phosphorylates Smad1 Ser-187 to trigger its proteasome-dependent degradation. Further functional characterization of the substrates of ROP18 may enhance understanding of the pathogenesis of Toxoplasma infection and provide new therapeutic targets. Similar strategies could be used to identify novel host targets for other microbial kinases functioning at the pathogen-host interface.

K-BILDS: A Kinase Substrate Discovery Tool

Kinases catalyze protein phosphorylation to regulate cell signaling events. However, identifying kinase substrates is challenging due to the often low abundance and dynamic nature of protein phosphorylation. Development of novel techniques to identify kinase substrates is necessary. Here, we report kinase-catalyzed biotinylation with inactivated lysates for discovery of substrates (K-BILDS) as a tool to identify direct substrates of a kinase. As a proof of concept, K-BILDS was applied to cAMP-dependent protein kinase A (PKA) with HeLa cell lysates. Subsequent enrichment and MS/MS analysis identified 279 candidate PKA substrates, including 56 previously known PKA substrates. Of the candidate substrates, nuclear autoantigenic sperm protein (NASP), BCL2-associated athanogene 3 (BAG3), and 14-3-3 protein Tau (YWHAQ) were validated as novel PKA substrates. K-BILDS provides a valuable tool to identify direct substrates of any protein kinase.

Quantifying Kinase-Specific Phosphorylation Stoichiometry Using Stable Isotope Labeling In a Reverse In-Gel Kinase Assay

Despite recent advancements in large-scale phosphoproteomics, methods to quantify kinase-specific phosphorylation stoichiometry of protein substrates are lacking. We developed a method to quantify kinase-specific phosphorylation stoichiometry by combining the reverse in-gel kinase assay (RIKA) with high-resolution liquid chromatography-mass spectrometry (LC-MS). Beginning with predetermined ratios of phosphorylated to nonphosphorylated protein kinase CK2 (CK2) substrate molecules, we employed ¹⁸O-labeled adenosine triphosphate (¹⁸O-ATP) as the phosphate donor in a RIKA, then quantified the ratio of ¹⁸O- versus ¹⁶O-labeled tryptic phosphopeptide using high mass accuracy mass spectrometry (MS). We demonstrate that the phosphorylation stoichiometry determined by this method across a broad percent phosphorylation range correlated extremely well with the predicted value (correlation coefficient = 0.99). This approach provides a quantitative alternative to antibody-based methods of determining the extent of phosphorylation of a substrate pool.

Systematic Prediction of Scaffold Proteins Reveals New Design Principles in Scaffold-Mediated Signal Transduction

Scaffold proteins play a crucial role in facilitating signal transduction in eukaryotes by bringing together multiple signaling components. In this study, we performed a systematic analysis of scaffold proteins in signal transduction by integrating protein-protein interaction and kinase-substrate relationship networks. We predicted 212 scaffold proteins that are involved in 605 distinct signaling pathways. The computational prediction was validated using a protein microarray-based approach. The predicted scaffold proteins showed several interesting characteristics, as we expected from the functionality of scaffold proteins. We found that the scaffold proteins are likely to interact with each other, which is consistent with previous finding that scaffold proteins tend to form homodimers and heterodimers. Interestingly, a single scaffold protein can be involved in multiple signaling pathways by interacting with other scaffold protein partners. Furthermore, we propose two possible regulatory mechanisms by which the activity of scaffold proteins is coordinated with their associated pathways through phosphorylation process.

Despite their importance in the signaling transduction, there is no systematic effort in identifying and characterizing the scaffold proteins in humans. In this work, we predicted scaffold proteins by integrating the available protein-protein interactions and kinase-substrate relationships. The predicted scaffold proteins showed characteristics for known scaffold proteins, suggesting the fidelity of our prediction. More importantly, the systematic prediction of scaffold proteins provides biological insights in the scaffold-mediated signal transduction. We found that scaffold proteins are likely to form complexes, suggesting that scaffold proteins could participate in diverse signaling pathways through the combinatorial interactions among scaffold proteins. Furthermore, the regulation of scaffold proteins’ activities has not been extensively studied. Our bioinformatics analysis proposed that scaffold proteins themselves might be regulated through phosphorylation process.

Toward a systems-level view of dynamic phosphorylation networks

To better understand how cells sense and respond to their environment, it is important to understand the organization and regulation of the phosphorylation networks that underlie most cellular signal transduction pathways. These networks, which are composed of protein kinases, protein phosphatases and their respective cellular targets, are highly dynamic. Importantly, to achieve signaling specificity, phosphorylation networks must be regulated at several levels, including at the level of protein expression, substrate recognition, and spatiotemporal modulation of enzymatic activity. Here, we briefly summarize some of the traditional methods used to study the phosphorylation status of cellular proteins before focusing our attention on several recent technological advances, such as protein microarrays, quantitative mass spectrometry, and genetically-targetable fluorescent biosensors, that are offering new insights into the organization and regulation of cellular phosphorylation networks. Together, these approaches promise to lead to a systems-level view of dynamic phosphorylation networks.