Systematic analysis of protein phosphorylation networks from phosphoproteomic data

Proteomic and Phosphoproteomic Profiling of Matrix Stiffness-Induced Stemness-Dormancy State Transition in Breast Cancer Cells

The dormancy of cancer stem cells is a major factor leading to drug resistance and a high rate of late recurrence and mortality in estrogen receptor-positive (ER+) breast cancer. Previously, we demonstrated that a stiffer matrix induces tumor cell dormancy and drug resistance, whereas a softened matrix promotes tumor cells to exhibit a stem cell state with high proliferation and migration. In this study, we present a comprehensive analysis of the proteome and phosphoproteome in response to gradient changes in matrix stiffness, elucidating the mechanisms behind cell dormancy-induced drug resistance. Overall, we found that antiapoptotic and membrane transport processes may be involved in the mechanical force-induced dormancy resistance of ER+ breast cancer cells. Our research provides new insights from a holistic proteomic and phosphoproteomic perspective, underscoring the significant role of mechanical forces stemming from the stiffness of the surrounding extracellular matrix as a critical regulatory factor in the tumor microenvironment.

In-silico screening of missense nsSNPs in Delta-opioid receptor protein and their restoring tendency on MCRT interaction; focusing on dynamic nature

Delta-opioid receptor protein (OPRD1) is one of the potential targets for treating pain. The presently available opioid agonists are known to cause unnecessary side effects. To discover a novel opioid agonist, our research group has synthesized a chimeric peptide MCRT and proved its potential activity through in vivo analysis. Non-synonymous SNPs (nsSNPs) missense mutations affect the functionality and stability of proteins leading to diseases. The current research was focused on understanding the role of MCRT in restoring the binding tendency of OPRD1 nsSNPs missense mutations on dynamic nature in comparison with Deltorphin-II and morphiceptin. The deleterious effects of nsSNPs were analyzed using various bioinformatics tools for predicting structural, functional, and oncogenic influence. The shortlisted nine nsSNPs were predicted for allergic reactions, domain changes, post-translation modification, multiple sequence alignment, secondary structure, molecular dynamic simulation (MDS), and peptide docking influence. Further, the docked complex of three shortlisted deleterious nsSNPs was analyzed using an MDS study, and the highly deleterious shortlisted nsSNP A149T was further analyzed for higher trajectory analysis. MCRT restored the binding tendency influence caused by nsSNPs on the dynamics of stability, functionality, binding affinity, secondary structure, residues connection, motion, and folding of OPRD1 protein.

Quantitative Phosphoproteomic Profiling of Mouse Sperm Maturation in Epididymis Revealed Kinases Important for Sperm Motility

Transcriptionally and translationally silent sperm undergo functional maturation during epididymis traverse, which provides sperm ability to move and is crucial for successful fertilization. However, the molecular mechanisms governing sperm maturation remain poorly understood, especially at the protein post-translational modification level. In this study, we conducted a comprehensive quantitative phosphoproteomic analysis of mouse epididymal sperm from different regions (caput, corpus, and cauda) to unveil the dynamics of protein phosphorylation during sperm maturation. We identified 6447 phosphorylation sites in 1407 phosphoproteins, and 345 phosphoproteins were differentially phosphorylated between caput and cauda sperm. Gene ontology and KEGG pathway analyses showed enrichment of differentially phosphorylated proteins in energy metabolism, sperm motility, and fertilization. Kinase substrate network analysis followed by inhibition assay and quantitative phosphoproteomics analysis showed that TSSK2 kinase is important for sperm motility and progressive motility. This study systemically characterized the intricate phosphorylation regulation during sperm maturation in the mouse epididymis, which can be a basis to elucidate sperm motility acquisition, and to offer potential targets for male contraception and the treatment of male infertility.

MAPK/ERK-PK(Ser11) pathway regulates divergent thermal metabolism of two congeneric oyster species

Pyruvate kinase (PK), as a key rate-limiting enzyme in glycolysis, has been widely used to assess the stress tolerance and sensitivity of organisms. However, its phosphorylation regulatory mechanisms mainly focused on human cancer research, with no reports in marine organisms. In this study, we firstly reported a conserved PK Ser11 phosphorylation site in mollusks, which enhanced enzyme activity by promoting substrate binding, thereby regulating divergent thermal metabolism of two allopatric congeneric oyster species with differential habitat temperature. It was phosphorylated by ERK kinase, and regulated by the classical MAPK pathway. The MAPK/ERK-PK signaling cascade responded to increased environmental temperature and exhibited stronger activation pattern in the relatively thermotolerant species (Crassostrea angulata), indicating its involvement in shaping temperature adaptation. These findings highlight the presence of complex and unique phosphorylation-mediated signaling transduction mechanisms in marine organisms, and provide new insights into the evolution and function of the crosstalk between classical pathways.

ROCK1 inhibition improves wound healing in diabetes via RIPK4/AMPK pathway

Refractory wounds are a severe complication of diabetes mellitus that often leads to amputation because of the lack of effective treatments and therapeutic targets. The pathogenesis of refractory wounds is complex, involving many types of cells. Rho-associated protein kinase-1 (ROCK1) phosphorylates a series of substrates that trigger downstream signaling pathways, affecting multiple cellular processes, including cell migration, communication, and proliferation. The present study investigated the role of ROCK1 in diabetic wound healing and molecular mechanisms. Our results showed that ROCK1 expression significantly increased in wound granulation tissues in diabetic patients, streptozotocin (STZ)-induced diabetic mice, and db/db diabetic mice. Wound healing and blood perfusion were dose-dependently improved by the ROCK1 inhibitor fasudil in diabetic mice. In endothelial cells, fasudil and ROCK1 siRNA significantly elevated the phosphorylation of adenosine monophosphate-activated protein kinase at Thr172 (pThr172-AMPKα), the activity of endothelial nitric oxide synthase (eNOS), and suppressed the levels of mitochondrial reactive oxygen species (mtROS) and nitrotyrosine formation. Experiments using integrated bioinformatics analysis and coimmunoprecipitation established that ROCK1 inhibited pThr172-AMPKα by binding to receptor-interacting serine/threonine kinase 4 (RIPK4). These results suggest that fasudil accelerated wound repair and improved angiogenesis at least partially through the ROCK1/RIPK4/AMPK pathway. Fasudil may be a potential treatment for refractory wounds in diabetic patients.

PhosAF: An integrated deep learning architecture for predicting protein phosphorylation sites with AlphaFold2 predicted structures

Phosphorylation is indispensable in comprehending biological processes, while biological experimental methods for identifying phosphorylation sites are tedious and arduous. With the rapid growth of biotechnology, deep learning methods have made significant progress in site prediction tasks. Nevertheless, most existing predictors only consider protein sequence information, that limits the capture of protein spatial information. Building upon the latest advancement in protein structure prediction by AlphaFold2, a novel integrated deep learning architecture PhosAF is developed to predict phosphorylation sites in human proteins by integrating CMA-Net and MFC-Net, which considers sequence and structure information predicted by AlphaFold2. Here, CMA-Net module is composed of multiple convolutional neural network layers and multi-head attention is appended to obtaining the local and long-term dependencies of sequence features. Meanwhile, the MFC-Net module composed of deep neural network layers is used to capture the complex representations of evolutionary and structure features. Furthermore, different features are combined to predict the final phosphorylation sites. In addition, we put forward a new strategy to construct reliable negative samples via protein secondary structures. Experimental results on independent test data and case study indicate that our model PhosAF surpasses the current most advanced methods in phosphorylation site prediction.

A Histone Methylation-MAPK Signaling Axis Drives Durable Epithelial-Mesenchymal Transition in Hypoxic Pancreatic Cancer

The tumor microenvironment in pancreatic ductal adenocarcinoma (PDAC) plays a key role in tumor progression and response to therapy. The dense PDAC stroma causes hypovascularity, which leads to hypoxia. Here, we showed that hypoxia drives long-lasting epithelial-mesenchymal transition (EMT) in PDAC primarily through a positive-feedback histone methylation-MAPK signaling axis. Transformed cells preferentially underwent EMT in hypoxic tumor regions in multiple model systems. Hypoxia drove a cell autonomous EMT in PDAC cells, which, unlike EMT in response to growth factors, could last for weeks. Furthermore, hypoxia reduced histone demethylase KDM2A activity, suppressed PP2 family phosphatase expression, and activated MAPKs to post-translationally stabilize histone methyltransferase NSD2, leading to an H3K36me2-dependent EMT in which hypoxia-inducible factors played only a supporting role. Hypoxia-driven EMT could be antagonized in vivo by combinations of MAPK inhibitors. Collectively, these results suggest that hypoxia promotes durable EMT in PDAC by inducing a histone methylation-MAPK axis that can be effectively targeted with multidrug therapies, providing a potential strategy for overcoming chemoresistance.

SIGNIFICANCE

Integrated regulation of histone methylation and MAPK signaling by the low-oxygen environment of pancreatic cancer drives long-lasting EMT that promotes chemoresistance and shortens patient survival and that can be pharmacologically inhibited. See related commentary by Wirth and Schneider, p. 1739.

Multi-omics characterization of esophageal squamous cell carcinoma identifies molecular subtypes and therapeutic targets

Esophageal squamous cell carcinoma (ESCC) is the predominant form of esophageal cancer and is characterized by an unfavorable prognosis. To elucidate the distinct molecular alterations in ESCC and investigate therapeutic targets, we performed a comprehensive analysis of transcriptomics, proteomics, and phosphoproteomics data derived from 60 paired treatment-naive ESCC and adjacent nontumor tissue samples. Additionally, we conducted a correlation analysis to describe the regulatory relationship between transcriptomic and proteomic processes, revealing alterations in key metabolic pathways. Unsupervised clustering analysis of the proteomics data stratified patients with ESCC into 3 subtypes with different molecular characteristics and clinical outcomes. Notably, subtype III exhibited the worst prognosis and enrichment in proteins associated with malignant processes, including glycolysis and DNA repair pathways. Furthermore, translocase of inner mitochondrial membrane domain containing 1 (TIMMDC1) was validated as a potential prognostic molecule for ESCC. Moreover, integrated kinase-substrate network analysis using the phosphoproteome nominated candidate kinases as potential targets. In vitro and in vivo experiments further confirmed casein kinase II subunit α (CSNK2A1) as a potential kinase target for ESCC. These underlying data represent a valuable resource for researchers that may provide better insights into the biology and treatment of ESCC.

Silencing of the PHLDA1 leads to global proteome changes and differentiation pathways of human neuroblastoma cells

Neuroblastoma (NB) is the most common extracranial pediatric solid tumor originating from the abnormal development of cells of the sympathoadrenal lineage of the neural crest. Targeting GD2 ganglioside (GD2), a glycolipid expressed on neuroblastoma cells, with GD2 ganglioside-recognizing antibodies affects several pivotal signaling routes that drive or influence the malignant phenotype of the cells. Previously performed gene expression profiling helped us to identify the PHLDA1 (pleckstrin homology-like domain family A member 1) gene as the most upregulated gene in the IMR-32 human neuroblastoma cells treated with the mouse 14G2a monoclonal antibody. Mass spectrometry-based proteomic analyses were applied to better characterize a role of PHLDA1 protein in the response of neuroblastoma cells to chimeric ch14.18/CHO antibody. Additionally, global protein expression profile analysis in the IMR-32 cell line with PHLDA1 silencing revealed the increase in biological functions of mitochondria, accompanied by differentiation-like phenotype of the cells. Moreover, mass spectrometry analysis of the proteins co-immunoprecipitated using anti-PHLDA1-specific antibody, selected a group of possible PHLDA1 binding partners. Also, a more detailed analysis suggested that PHLDA1 interacts with the DCAF7/AUTS2 complex, a key component of neuronal differentiation in vitro. Importantly, our results indicate that PHLDA1 silencing enhances the EGF receptor signaling pathway and combinatory treatment of gefitinib and ch14.18/CHO antibodies might be beneficial for neuroblastoma patients. Data are available via ProteomeXchange with the identifier PXD044319.

Pharmacological approaches to understanding protein kinase signaling networks

Protein kinases play vital roles in controlling cell behavior, and an array of kinase inhibitors are used successfully for treatment of disease. Typical drug development pipelines involve biological studies to validate a protein kinase target, followed by the identification of small molecules that effectively inhibit this target in cells, animal models, and patients. However, it is clear that protein kinases operate within complex signaling networks. These networks increase the resilience of signaling pathways, which can render cells relatively insensitive to inhibition of a single kinase, and provide the potential for pathway rewiring, which can result in resistance to therapy. It is therefore vital to understand the properties of kinase signaling networks in health and disease so that we can design effective multi-targeted drugs or combinations of drugs. Here, we outline how pharmacological and chemo-genetic approaches can contribute to such knowledge, despite the known low selectivity of many kinase inhibitors. We discuss how detailed profiling of target engagement by kinase inhibitors can underpin these studies; how chemical probes can be used to uncover kinase-substrate relationships, and how these tools can be used to gain insight into the configuration and function of kinase signaling networks.

VIPpred: a novel model for predicting variant impact on phosphorylation events driving carcinogenesis

Disrupted protein phosphorylation due to genetic variation is a widespread phenomenon that triggers oncogenic transformation of healthy cells. However, few relevant phosphorylation disruption events have been verified due to limited biological experimental methods. Because of the lack of reliable benchmark datasets, current bioinformatics methods primarily use sequence-based traits to study variant impact on phosphorylation (VIP). Here, we increased the number of experimentally supported VIP events from less than 30 to 740 by manually curating and reanalyzing multi-omics data from 916 patients provided by the Clinical Proteomic Tumor Analysis Consortium. To predict VIP events in cancer cells, we developed VIPpred, a machine learning method characterized by multidimensional features that exhibits robust performance across different cancer types. Our method provided a pan-cancer landscape of VIP events, which are enriched in cancer-related pathways and cancer driver genes. We found that variant-induced increases in phosphorylation events tend to inhibit the protein degradation of oncogenes and promote tumor suppressor protein degradation. Our work provides new insights into phosphorylation-related cancer biology as well as novel avenues for precision therapy.

A plant protein farnesylation system in prokaryotic cells reveals Arabidopsis AtJ3 produced and farnesylated in E. coli maintains its function of protecting proteins from heat inactivation

BACKGROUND

Protein farnesylation involves the addition of a 15-carbon polyunsaturated farnesyl group to proteins whose C-terminus ends with a CaaX motif. This post-translational protein modification is catalyzed by a heterodimeric protein, i.e., farnesyltransferase (PFT), which is composed of an α and a β subunit. Protein farnesylation in plants is of great interest because of its important roles in the regulation of plant development, responses to environmental stresses, and defense against pathogens. The methods traditionally used to verify whether a protein is farnesylated often require a specific antibody and involve isotope labeling, a tedious and time-consuming process that poses hazardous risks.

RESULTS

Since protein farnesylation does not occur in prokaryotic cells, we co-expressed a known PFT substrate (i.e., AtJ3) and both the α and β subunits of Arabidopsis PFT in E. coli in this study. Farnesylation of AtJ3 was detected using electrophoretic mobility using SDS-PAGE and confirmed using mass spectrometry. AtJ3 is a member of the heat shock protein 40 family and interacts with Arabidopsis HSP70 to protect plant proteins from heat-stress-induced denaturation. A luciferase-based protein denaturation assay demonstrated that farnesylated AtJ3 isolated from E. coli maintained this ability. Interestingly, farnesylated AtJ3 interacted with E. coli HSP70 as well and enhanced the thermotolerance of E. coli. Meanwhile, AtFP3, another known PFT substrate, was farnesylated when co-expressed with AtPFTα and AtPFTβ in E. coli. Moreover, using the same strategy to co-express rice PFT α and β subunit and a potential PFT target, it was confirmed that OsDjA4, a homolog of AtJ3, was farnesylated.

CONCLUSION

We developed a protein farnesylation system for E. coli and demonstrated its applicability and practicality in producing functional farnesylated proteins from both mono- and dicotyledonous plants.

Proteomics and phosphoproteomics profiling in glutamatergic neurons and microglia in an iPSC model of Jansen de Vries Syndrome

Background

Jansen de Vries Syndrome (JdVS) is a rare neurodevelopmental disorder (NDD) caused by gain-of-function (GOF) truncating mutations in PPM1D exons 5 or 6. PPM1D is a serine/threonine phosphatase that plays an important role in the DNA damage response (DDR) by negatively regulating TP53 (P53). JdVS-associated mutations lead to the formation of a truncated PPM1D protein that retains catalytic activity and has a GOF effect because of reduced degradation. Somatic PPM1D exons 5 and 6 truncating mutations are well-established factors in a number of cancers, due to excessive dephosphorylation and reduced function of P53 and other substrates involved in DDR. Children with JdVS have a variety of neurodevelopmental, psychiatric, and physical problems. In addition, a small fraction has acute neuropsychiatric decompensation apparently triggered by infection or severe non-infectious environmental stress factors.

Methods

To understand the molecular basis of JdVS, we developed an induced pluripotent stem cell (iPSC) model system. iPSCs heterozygous for the truncating variant (PPM1D+/tr), were made from a patient, and control lines engineered using CRISPR-Cas9 gene editing. Proteomics and phosphoprotemics analyses were carried out on iPSC-derived glutamatergic neurons and microglia from three control and three PPM1D+/tr iPSC lines. We also analyzed the effect of the TLR4 agonist, lipopolysaccharide, to understand how activation of the innate immune system in microglia could account for acute behavioral decompensation.

Results

One of the major findings was the downregulation of POGZ in unstimulated microglia. Since loss-of-function variants in the POGZ gene are well-known causes of autism spectrum disorder, the decrease in PPM1D+/tr microglia suggests this plays a role in the neurodevelopmental aspects of JdVS. In addition, neurons, baseline, and LPS-stimulated microglia show marked alterations in the expression of several E3 ubiquitin ligases, most notably UBR4, and regulators of innate immunity, chromatin structure, ErbB signaling, and splicing. In addition, pathway analysis points to overlap with neurodegenerative disorders.

Limitations

Owing to the cost and labor-intensive nature of iPSC research, the sample size was small.

Conclusions

Our findings provide insight into the molecular basis of JdVS and can be extrapolated to understand neuropsychiatric decompensation that occurs in subgroups of patients with ASD and other NDDs.

mTORC2-NDRG1-CDC42 axis couples fasting to mitochondrial fission

Fasting triggers diverse physiological adaptations including increases in circulating fatty acids and mitochondrial respiration to facilitate organismal survival. The mechanisms driving mitochondrial adaptations and respiratory sufficiency during fasting remain incompletely understood. Here we show that fasting or lipid availability stimulates mTORC2 activity. Activation of mTORC2 and phosphorylation of its downstream target NDRG1 at serine 336 sustains mitochondrial fission and respiratory sufficiency. Time-lapse imaging shows that NDRG1, but not the phosphorylation-deficient NDRG1^Ser336Ala mutant, engages with mitochondria to facilitate fission in control cells, as well as in those lacking DRP1. Using proteomics, a small interfering RNA screen, and epistasis experiments, we show that mTORC2-phosphorylated NDRG1 cooperates with small GTPase CDC42 and effectors and regulators of CDC42 to orchestrate fission. Accordingly, Rictor^KO, NDRG1^Ser336Ala mutants and Cdc42-deficient cells each display mitochondrial phenotypes reminiscent of fission failure. During nutrient surplus, mTOR complexes perform anabolic functions; however, paradoxical reactivation of mTORC2 during fasting unexpectedly drives mitochondrial fission and respiration.

Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery

Protein phosphorylation is a key post-translational modification (PTM) that is a central regulatory mechanism of many cellular signaling pathways. Several protein kinases and phosphatases precisely control this biochemical process. Defects in the functions of these proteins have been implicated in many diseases, including cancer. Mass spectrometry (MS)-based analysis of biological samples provides in-depth coverage of phosphoproteome. A large amount of MS data available in public repositories has unveiled big data in the field of phosphoproteomics. To address the challenges associated with handling large data and expanding confidence in phosphorylation site prediction, the development of many computational algorithms and machine learning-based approaches have gained momentum in recent years. Together, the emergence of experimental methods with high resolution and sensitivity and data mining algorithms has provided robust analytical platforms for quantitative proteomics. In this review, we compile a comprehensive collection of bioinformatic resources used for the prediction of phosphorylation sites, and their potential therapeutic applications in the context of cancer.

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.

Proteomic and phosphoproteomic characteristics of the cortex, hippocampus, thalamus, lung, and kidney in COVID-19-infected female K18-hACE2 mice

BACKGROUND

Neurological damage caused by coronavirus disease 2019 (COVID-19) has attracted increasing attention. Recently, through autopsies of patients with COVID-19, the direct identification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in their central nervous system (CNS) has been reported, indicating that SARS-CoV-2 might directly attack the CNS. The need to prevent COVID-19-induced severe injuries and potential sequelae is urgent, requiring the elucidation of large-scale molecular mechanisms in vivo.

METHODS

In this study, we performed liquid chromatography-mass spectrometry-based proteomic and phosphoproteomic analyses of the cortex, hippocampus, thalamus, lungs, and kidneys of SARS-CoV-2-infected K18-hACE2 female mice. We then performed comprehensive bioinformatic analyses, including differential analyses, functional enrichment, and kinase prediction, to identify key molecules involved in COVID-19.

FINDINGS

We found that the cortex had higher viral loads than did the lungs, and the kidneys did not have SARS-COV-2. After SARS-CoV-2 infection, RIG-I-associated virus recognition, antigen processing and presentation, and complement and coagulation cascades were activated to different degrees in all five organs, especially the lungs. The infected cortex exhibited disorders of multiple organelles and biological processes, including dysregulated spliceosome, ribosome, peroxisome, proteasome, endosome, and mitochondrial oxidative respiratory chain. The hippocampus and thalamus had fewer disorders than did the cortex; however, hyperphosphorylation of Mapt/Tau, which may contribute to neurodegenerative diseases, such as Alzheimer's disease, was found in all three brain regions. Moreover, SARS-CoV-2-induced elevation of human angiotensin-converting enzyme 2 (hACE2) was observed in the lungs and kidneys, but not in the three brain regions. Although the virus was not detected, the kidneys expressed high levels of hACE2 and exhibited obvious functional dysregulation after infection. This indicates that SARS-CoV-2 can cause tissue infections or damage via complicated routes. Thus, the treatment of COVID-19 requires a multipronged approach.

INTERPRETATION

This study provides observations and in vivo datasets for COVID-19-associated proteomic and phosphoproteomic alterations in multiple organs, especially cerebral tissues, of K18-hACE2 mice. In mature drug databases, the differentially expressed proteins and predicted kinases in this study can be used as baits to identify candidate therapeutic drugs for COVID-19. This study can serve as a solid resource for the scientific community. The data in this manuscript will serve as a starting point for future research on COVID-19-associated encephalopathy.

FUNDING

This study was supported by grants from the Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences, the National Natural Science Foundation of China, and the Natural Science Foundation of Beijing.

Temperature-induced embryonic diapause in chickens is mediated by PKC-NF-κB-IRF1 signaling

BACKGROUND

Embryonic diapause (dormancy) is a state of temporary arrest of embryonic development that is triggered by unfavorable conditions and serves as an evolutionary strategy to ensure reproductive survival. Unlike maternally-controlled embryonic diapause in mammals, chicken embryonic diapause is critically dependent on the environmental temperature. However, the molecular control of diapause in avian species remains largely uncharacterized. In this study, we evaluated the dynamic transcriptomic and phosphoproteomic profiles of chicken embryos in pre-diapause, diapause, and reactivated states.

RESULTS

Our data demonstrated a characteristic gene expression pattern in effects on cell survival-associated and stress response signaling pathways. Unlike mammalian diapause, mTOR signaling is not responsible for chicken diapause. However, cold stress responsive genes, such as IRF1, were identified as key regulators of diapause. Further in vitro investigation showed that cold stress-induced transcription of IRF1 was dependent on the PKC-NF-κB signaling pathway, providing a mechanism for proliferation arrest during diapause. Consistently, in vivo overexpression of IRF1 in diapause embryos blocked reactivation after restoration of developmental temperatures.

CONCLUSIONS

We concluded that embryonic diapause in chicken is characterized by proliferation arrest, which is the same with other spices. However, chicken embryonic diapause is strictly correlated with the cold stress signal and mediated by PKC-NF-κB-IRF1 signaling, which distinguish chicken diapause from the mTOR based diapause in mammals.

Using transcriptomics, proteomics and phosphoproteomics as new approach methodology (NAM) to define biological responses for chemical safety assessment

Omic-based technologies are of particular interest and importance for hazard identification and health risk characterization of chemicals. Their application in the new approach methodologies (NAMs) anchored on cellular toxicity pathways is based on the premise that any apical health endpoint change must be underpinned by some alterations at the omic levels. In the present study we examined the cellular responses to two chemicals, caffeine and coumarin, by generating and integrating multi-omic data from multi-dose and multi-time point transcriptomic, proteomic and phosphoproteomic experiments. We showed that the methodology presented here was able to capture the complete chain of events from the first chemical-induced changes at the phosphoproteome level, to changes in gene expression, and lastly to changes in protein abundance, each with vastly different points of departure (PODs). In HepG2 cells we found that the metabolism of lipids and general cellular stress response to be the dominant biological processes in response to caffeine and coumarin exposure, respectively. The phosphoproteomic changes were detected early in time, at very low doses and provided a fast, adaptive cellular response to chemical exposure with 7-37-fold lower points of departure comparing to the transcriptomics. Changes in protein abundance were found much less frequently than transcriptomic changes. While challenges remain, our study provides strong and novel evidence supporting the notion that these three omic technologies can be used in an integrated manner to facilitate a more complete understanding of pathway perturbations and POD determinations for risk assessment of chemical exposures.

Prediction of Kinase-Substrate Associations Using The Functional Landscape of Kinases and Phosphorylation Sites

Protein phosphorylation is a key post-translational modification that plays a central role in many cellular processes. With recent advances in biotechnology, thousands of phosphorylated sites can be identified and quantified in a given sample, enabling proteome-wide screening of cellular signaling. However, for most (> 90%) of the phosphorylation sites that are identified in these experiments, the kinase(s) that target these sites are unknown. To broadly utilize available structural, functional, evolutionary, and contextual information in predicting kinase-substrate associations (KSAs), we develop a network-based machine learning framework. Our framework integrates a multitude of data sources to characterize the landscape of functional relationships and associations among phosphosites and kinases. To construct a phosphosite-phosphosite association network, we use sequence similarity, shared biological pathways, co-evolution, co-occurrence, and co-phosphorylation of phosphosites across different biological states. To construct a kinase-kinase association network, we integrate protein-protein interactions, shared biological pathways, and membership in common kinase families. We use node embeddings computed from these heterogeneous networks to train machine learning models for predicting kinase-substrate associations. Our systematic computational experiments using the PhosphositePLUS database shows that the resulting algorithm, NetKSA, outperforms two state-of-the-art algorithms, including KinomeXplorer and LinkPhinder, in overall KSA prediction. By stratifying the ranking of kinases, NetKSA also enables annotation of phosphosites that are targeted by relatively less-studied kinases.Availability: The code and data are available at compbio.case.edu/NetKSA/.

Multi-omics profiling visualizes dynamics of cardiac development and functions

Cardiogenesis is a tightly regulated dynamic process through a continuum of differentiation and proliferation events. Key factors and pathways governing this process remain incompletely understood. Here, we investigate mice hearts from embryonic day 10.5 to postnatal week 8 and dissect developmental changes in phosphoproteome-, proteome-, metabolome-, and transcriptome-encompassing cardiogenesis and cardiac maturation. We identify mitogen-activated protein kinases as core kinases involved in transcriptional regulation by mediating the phosphorylation of chromatin remodeling proteins during early cardiogenesis. We construct the reciprocal regulatory network of transcription factors (TFs) and identify a series of TFs controlling early cardiogenesis involved in cycling-dependent proliferation. After birth, we identify cardiac resident macrophages with high arachidonic acid metabolism activities likely involved in the clearance of injured apoptotic cardiomyocytes. Together, our comprehensive multi-omics data offer a panoramic view of cardiac development and maturation that provides a resource for further in-depth functional exploration.

Characterization of the RAS/RAF/ERK Signal Cascade as a Novel Regulating Factor in Alpha-Amanitin-Induced Cytotoxicity in Huh-7 Cells

The well-known hepatotoxicity mechanism resulting from alpha-amanitin (α-AMA) exposure arises from RNA polymerase II (RNAP II) inhibition. RNAP Ⅱ inhibition occurs through the dysregulation of mRNA synthesis. However, the signaling pathways in hepatocytes that arise from α-AMA have not yet been fully elucidated. Here, we identified that the RAS/RAF/ERK signaling pathway was activated through quantitative phosphoproteomic and molecular biological analyses in Huh-7 cells. Bioinformatics analysis showed that α-AMA exposure increased protein phosphorylation in a time-dependent α-AMA exposure. In addition, phosphorylation increased not only the components of the ERK signaling pathway but also U2AF65 and SPF45, known splicing factors. Therefore, we propose a novel mechanism of α-AMA as follows. The RAS/RAF/ERK signaling pathway involved in aberrant splicing events is activated by α-AMA exposure followed by aberrant splicing events leading to cell death in Huh-7 cells.

Proteomic and Phosphoproteomic Profiling Reveals the Oncogenic Role of Protein Kinase D Family Kinases in Cholangiocarcinoma

Cholangiocarcinoma (CCA) is a lethal malignancy in the hepatobiliary system, with dysregulated protein expression and phosphorylation signaling. However, the protein and phosphorylation signatures of CCAs are little-known. Here, we performed the proteomic and phosphoproteomic profiling of tumors and normal adjacent tissues (NATs) from patients with CCA and predicted eleven PKs high-potentially related to CCA with a comprehensive inference of the functional protein kinases (PKs) (CifPK) pipeline. Besides the two known CCA-associated PKs, we screened the remaining candidates and uncovered five PKs as novel regulators in CCA. Specifically, the protein kinase D (PKD) family members, including PRKD1, PRKD2, and PRKD3, were identified as critical regulators in CCA. Moreover, the pan-inhibitor of the PKD family, 1-naphthyl PP1 (1-NA-PP1), was validated as a potent agent for inhibiting the proliferation, migration, and invasion ability of CCA cells. This study reveals new PKs associated with CCA and suggests PRKD kinases as novel treatment targets for CCA.

Proteomics and phosphoproteomics of chordoma biopsies reveal alterations in multiple pathways and aberrant kinases activities

Background

Chordoma is a slow-growing but malignant subtype of bone sarcoma with relatively high recurrence rates and high resistance to chemotherapy. It is urgent to understand the underlying regulatory networks to determine more effective potential targets. Phosphorylative regulation is currently regarded as playing a significant role in tumorigenesis, and the use of tyrosine kinase inhibitors in clinical practice has yielded new promise for the treatment of a variety of sarcoma types.

Materials and methods

We performed comprehensive proteomic and phosphoproteomic analyses of chordoma using four-dimensional label-free liquid chromatography–tandem mass spectrometry (LC-MS/MS) and bioinformatics analysis. The potential aberrantly expressed kinases and their functions were validated using western blotting and CCK-8 assays.

Results

Compared with paired normal muscle tissues, 1,139 differentially expressed proteins (DEPs) and 776 differentially phosphorylated proteins (DPPs) were identified in chordoma tumor tissues. The developmentally significant Wnt-signaling pathway and oxidative phosphorylation were aberrant in chordoma. Moreover, we predicted three kinases (AURA, CDK9, and MOK) with elevated activity by kinase-pathway network analysis (KiPNA) and verified their increased expression levels. The knockdown of these kinases markedly suppressed chordoma cell growth, and this was also the case for cells treated with the CDK9 inhibitor AZD4573. We additionally examined 208 proteins whose expression and phosphorylation levels were synergetically altered.

Conclusions

We herein depicted the collective protein profiles of chordomas, providing insight into chordomagenesis and the potential development of new therapeutic targets.

qPTM: an updated database for PTM dynamics in human, mouse, rat and yeast

Post-translational modifications (PTMs) are critical molecular mechanisms that regulate protein functions temporally and spatially in various organisms. Since most PTMs are dynamically regulated, quantifying PTM events under different states is crucial for understanding biological processes and diseases. With the rapid development of high-throughput proteomics technologies, massive quantitative PTM proteome datasets have been generated. Thus, a comprehensive one-stop data resource for surfing big data will benefit the community. Here, we updated our previous phosphorylation dynamics database qPhos to the qPTM (http://qptm.omicsbio.info). In qPTM, 11 482 553 quantification events among six types of PTMs, including phosphorylation, acetylation, glycosylation, methylation, SUMOylation and ubiquitylation in four different organisms were collected and integrated, and the matched proteome datasets were included if available. The raw mass spectrometry based false discovery rate control and the recurrences of identifications among datasets were integrated into a scoring system to assess the reliability of the PTM sites. Browse and search functions were improved to facilitate users in swiftly and accurately acquiring specific information. The results page was revised with more abundant annotations, and time-course dynamics data were visualized in trend lines. We expected the qPTM database to be a much more powerful and comprehensive data repository for the PTM research community.

Revealing phosphorylation regulatory networks during embryogenesis of honey bee worker and drone (Apis mellifera)

Protein phosphorylation is known to regulate a comprehensive scenario of critical cellular processes. However, phosphorylation-mediated regulatory networks in honey bee embryogenesis are mainly unknown. We identified 6342 phosphosites from 2438 phosphoproteins and predicted 168 kinases in the honey bee embryo. Generally, the worker and drone develop similar phosphoproteome architectures and major phosphorylation events during embryogenesis. In 24 h embryos, protein kinases A play vital roles in regulating cell proliferation and blastoderm formation. At 48–72 h, kinase subfamily dual-specificity tyrosine-regulated kinase, cyclin-dependent kinase (CDK), and induced pathways related to protein synthesis and morphogenesis suggest the centrality to enhance the germ layer development, organogenesis, and dorsal closure. Notably, workers and drones formulated distinct phosphoproteome signatures. For 24 h embryos, the highly phosphorylated serine/threonine-protein kinase minibrain, microtubule-associated serine/threonine-protein kinase 2 (MAST2), and phosphorylation of mitogen-activated protein kinase 3 (MAPK3) at Thr564 in workers, are likely to regulate the late onset of cell proliferation; in contrast, drone embryos enhanced the expression of CDK12, MAPK3, and MAST2 to promote the massive synthesis of proteins and cytoskeleton. In 48 h, the induced serine/threonine-protein kinase and CDK12 in worker embryos signify their roles in the construction of embryonic tissues and organs; however, the highly activated kinases CDK1, raf homolog serine/threonine-protein kinase, and MAST2 in drone embryos may drive the large-scale establishment of tissues and organs. In 72 h, the activated pathways and kinases associated with cell growth and tissue differentiation in worker embryos may promote the configuration of rudimentary organs. However, kinases implicated in cytoskeleton organization in drone embryos may drive the blastokinesis and dorsal closure. Our hitherto most comprehensive phosphoproteome offers a valuable resource for signaling research on phosphorylation dynamics in honey bee embryos.

PIM1 promotes hepatic conversion by suppressing reprogramming-induced ferroptosis and cell cycle arrest

Protein kinase-mediated phosphorylation plays a critical role in many biological processes. However, the identification of key regulatory kinases is still a great challenge. Here, we develop a trans-omics-based method, central kinase inference, to predict potentially key kinases by integrating quantitative transcriptomic and phosphoproteomic data. Using known kinases associated with anti-cancer drug resistance, the accuracy of our method denoted by the area under the curve is 5.2% to 29.5% higher than Kinase-Substrate Enrichment Analysis. We further use this method to analyze trans-omic data in hepatocyte maturation and hepatic reprogramming of human dermal fibroblasts, uncovering 5 kinases as regulators in the two processes. Further experiments reveal that a serine/threonine kinase, PIM1, promotes hepatic conversion and protects human dermal fibroblasts from reprogramming-induced ferroptosis and cell cycle arrest. This study not only reveals new regulatory kinases, but also provides a helpful method that might be extended to predict central kinases involved in other biological processes.

Global phosphoproteomic analysis identified key kinases regulating male meiosis in mouse

Meiosis, a highly conserved process in organisms from fungi to mammals, is subjected to protein phosphorylation regulation. Due to the low abundance of phosphorylation, there is a lack of systemic characterization of phosphorylation regulation of meiosis in mammals. Using the phosphoproteomic approach, we profiled large-scale phosphoproteome of purified primary spermatocytes undergoing meiosis I, and identified 14,660 phosphorylation sites in 4419 phosphoproteins. Kinase-substrate phosphorylation network analysis followed by in vitro meiosis study showed that CDK9 was essential for meiosis progression to metaphase I and had enriched substrate phosphorylation sites in proteins involved in meiotic cell cycle. In addition, histones and epigenetic factors were found to be widely phosphorylated. Among those, HASPIN was found to be essential for male fertility. Haspin knockout led to misalignment of chromosomes, apoptosis of metaphase spermatocytes and a decreased number of sperm by deregulation of H3T3ph, chromosomal passenger complex (CPC) and spindle assembly checkpoint (SAC). The complicated protein phosphorylation and its important regulatory functions in meiosis indicated that in-depth studies of phosphorylation-mediated signaling could help us elucidate the mechanisms of meiosis.

DeepDA-Ace: A Novel Domain Adaptation Method for Species-Specific Acetylation Site Prediction

Protein lysine acetylation is an important type of post-translational modification (PTM), and it plays a crucial role in various cellular processes. Recently, although many researchers have focused on developing tools for acetylation site prediction based on computational methods, most of these tools are based on traditional machine learning algorithms for acetylation site prediction without species specificity, still maintained as a single prediction model. Recent studies have shown that the acetylation sites of distinct species have evident location-specific differences; however, there is currently no integrated prediction model that can effectively predict acetylation sites cross all species. Therefore, to enhance the scope of species-specific level, it is necessary to establish a framework for species-specific acetylation site prediction. In this work, we propose a domain adaptation framework DeepDA-Ace for species-specific acetylation site prediction, including Rattus norvegicus, Schistosoma japonicum, Arabidopsis thaliana, and other types of species. In DeepDA-Ace, an attention based densely connected convolutional neural network is designed to capture sequence features, and the semantic adversarial learning strategy is proposed to align features of different species so as to achieve knowledge transfer. The DeepDA-Ace outperformed both the general prediction model and fine-tuning based species-specific model across most types of species. The experiment results have demonstrated that DeepDA-Ace is superior to the general and fine-tuning methods, and its precision exceeds 0.75 on most species. In addition, our method achieves at least 5% improvement over the existing acetylation prediction tools.

Cold atmospheric plasmas target breast cancer stemness via modulating AQP3-19Y mediated AQP3-5K and FOXO1 K48-ubiquitination

Cold atmospheric plasma (CAP) is selective against many cancers with little side effect, yet its molecular mechanism remains unclear. Through whole transcriptome sequencing followed by assays in vitro, in vivo and using clinical samples, we propose CAP as a promising onco-therapy targeting cancer stemness via the AQP3/FOXO1 axis. CAP-generated reactive species penetrated cells via AQP3 and suppressed RPS6KA3, a shared kinase of AQP3 and FOXO1. Reduced AQP3-19Y phosphorylation suppressed SCAF11-mediated AQP3-5K K48-ubiquitination that led to sabotaged FOXO1 stability. Inhibited FOXO1 phosphorylation retarded its regulatory activities in maintaining cancer stemness including ALDH1 and IL6. Enhanced anti-cancer efficacy was observed through combining CAP with Atorvastatin in vitro and in vivo. We propose CAP as a 'selective' onco-therapeutic against cancer stemness, with the AQP3/FOXO1 axis being one molecular mechanism. We report SCAF11 as an E3 ubiquitin ligase of both AQP3 and FOXO1, identify AQP3-5K as an AQP3 K48-ubiquitination site, and emphasize the essential role of AQP3-19Y in this process. We reposition Atorvastatin into the onco-therapeutic portfolio by synergizing it with CAP towards enhanced efficacy. We anticipate the efficacy of CAP in targeting malignancies of high stemness alone or as an adjuvant therapy towards the hope of ultimate cancer cure.

Interactions, structural aspects, and evolutionary perspectives of the yeast 'START'-regulatory network

Molecular signal transduction networks which conduct transcription at the G1 to S phase transition of the eukaryotic cell division cycle have been identified in diverse taxa from mammals to baker´s yeast with analogous functional organization. However, regarding some network components, such as the transcriptional regulators STB1 and WHI5, only few orthologs exist which are confined to individual Saccharomycotina species. While Whi5 has been characterized as yeast analog of human Rb protein, in the particular case of Stb1 (Sin three binding protein 1) identification of functional analogs emerges as difficult because to date its exact functionality still remains obscured. By aiming to resolve Stb1´s enigmatic role this Perspectives article especially surveys works covering relations between Cyclin/CDKs, the heteromeric transcription factor complexes SBF (Swi4/Swi6) and MBF (Mbp1/Swi6), as well as additional coregulators (Whi5, Sin3, Rpd3, Nrm1) which are collectively associated with the orderly transcription at 'Start' of the Saccharomyces cerevisiae cell cycle. In this context, interaction capacities of the Sin3-scaffold protein are widely surveyed because its four PAH domains (Paired Amphiphatic Helix) represent a 'recruitment-code' for gene-specific targeting of repressive histone deacetylase activity (Rpd3) via different transcription factors. Here Stb1 plays a role in Sin3´s action on transcription at the G1/S-boundary. Through bioinformatic analyses a potential Sin3-interaction domain (SID) was detected in Stb1, and beyond that, connections within the G1/S-regulatory network are discussed in structural and evolutionary context thereby providing conceptual perspectives.

Quantitative phosphoproteomics reveals GSK3A substrate network is involved in the cryodamage of sperm motility

During sperm cryopreservation, the most significant phenotype of cryodamage is the decrease in sperm motility. Several proteomics studies have already been performed to search for key regulators at the protein level. However, sperm functions are known to be highly regulated by phosphorylation signaling. Here, we constructed a quantitative phosphoproteome to investigate the expression change of phosphorylated sites during sperm cryopreservation. A total of 3107 phosphorylated sites are identified and 848 of them are found to be significantly differentially expressed (DE). Bioinformatics analysis showed that the corresponding genes of these regulated sites are highly associated with sperm motility, providing a connection between the molecular basis and the phenotype of cryodamage. We then performed kinase enrichment analysis and successfully identified glycogen synthase kinase-3α (GSK3A) as the key kinase that may play an important role in the regulation of sperm motility. We further constructed a GSK3A centric network that could help us better understand the molecular mechanism of cryodamage in sperm motility. Finally, we also verified that GSK3A was abnormally activated during this process. The presented phosphoproteome and functional associations provide abundant research resources for us to learn the regulation of sperm functions, as well as to optimize the cryoprotectant for sperm cryopreservation.

PKSPS: a novel method for predicting kinase of specific phosphorylation sites based on maximum weighted bipartite matching algorithm and phosphorylation sequence enrichment analysis

With the development of biotechnology, a large number of phosphorylation sites have been experimentally confirmed and collected, but only a few of them have kinase annotations. Since experimental methods to detect kinases at specific phosphorylation sites are expensive and accidental, some computational methods have been proposed to predict the kinase of these sites, but most methods only consider single sequence information or single functional network information. In this study, a new method Predicting Kinase of Specific Phosphorylation Sites (PKSPS) is developed to predict kinases of specific phosphorylation sites in human proteins by combining PKSPS-Net with PKSPS-Seq, which considers protein-protein interaction (PPI) network information and sequence information. For PKSPS-Net, kinase-kinase and substrate-substrate similarity are quantified based on the topological similarity of proteins in the PPI network, and maximum weighted bipartite matching algorithm is proposed to predict kinase-substrate relationship. In PKSPS-Seq, phosphorylation sequence enrichment analysis is used to analyze the similarity of local sequences around phosphorylation sites and predict the kinase of specific phosphorylation sites (KSP). PKSPS has been proved to be more effective than the PKSPS-Net or PKSPS-Seq on different sets of kinases. Further comparison results show that the PKSPS method performs better than existing methods. Finally, the case study demonstrates the effectiveness of the PKSPS in predicting kinases of specific phosphorylation sites. The open source code and data of the PKSPS can be obtained from https://github.com/guoxinyunncu/PKSPS.

A novel phosphoproteomic landscape evoked in response to type I interferon in the brain and in glial cells

BACKGROUND

Type I interferons (IFN-I) are key responders to central nervous system infection and injury and are also increased in common neurodegenerative diseases. Their effects are primarily mediated via transcriptional regulation of several hundred interferon-regulated genes. In addition, IFN-I activate several kinases including members of the MAPK and PI3K families. Yet, how changes to the global protein phosphoproteome contribute to the cellular response to IFN-I is unknown.

METHODS

The cerebral phosphoproteome of mice with brain-targeted chronic production of the IFN-I, IFN-α, was obtained. Changes in phosphorylation were analyzed by ontology and pathway analysis and kinase enrichment predictions. These were verified by phenotypic analysis, immunohistochemistry and immunoblots. In addition, primary murine microglia and astrocytes, the brain's primary IFN-I-responding cells, were acutely treated with IFN-α and the global phosphoproteome was similarly analyzed.

RESULTS

We identified widespread protein phosphorylation as a novel mechanism by which IFN-I mediate their effects. In our mouse model for IFN-I-induced neurodegeneration, protein phosphorylation, rather than the proteome, aligned with the clinical hallmarks and pathological outcome, including impaired development, motor dysfunction and seizures. In vitro experiments revealed extensive and rapid IFN-I-induced protein phosphorylation in microglia and astrocytes. Response to acute IFN-I stimulation was independent of gene expression and mediated by a small number of kinase families. The changes in the phosphoproteome affected a diverse range of cellular processes and functional analysis suggested that this response induced an immediate reactive state and prepared cells for subsequent transcriptional responses.

CONCLUSIONS

Our studies reveal a hitherto unappreciated role for changes in the protein phosphorylation landscape in cellular responses to IFN-I and thus provide insights for novel diagnostic and therapeutic strategies for neurological diseases caused by IFN-I.

Kynurenine derivative 3-HAA is an agonist ligand for transcription factor YY1

The 3-hydroxyanthranilic acid (3-HAA), a derivative of kynurenine, was reported to suppress tumor growth. However, the function of 3-HAA largely remains unclear. Here, we report that 3-hydroxyanthranilic acid (3-HAA) is lower in tumor cells, while adding exogenous 3-HAA induces apoptosis in hepatocellular carcinoma by binding YY1. This 3-HAA binding of YY1 leads to phosphorylation of YY1 at the Thr 398 by PKCζ, concomitantly enhances YY1 chromatin binding activity to increase expression of target genes. These findings demonstrate that 3-HAA is a ligand of YY1, suggesting it is a promising therapeutic candidate for HCC.

PhosIDN: an integrated deep neural network for improving protein phosphorylation site prediction by combining sequence and protein-protein interaction information

Motivation

Phosphorylation is one of the most studied post-translational modifications, which plays a pivotal role in various cellular processes. Recently, deep learning methods have achieved great success in prediction of phosphorylation sites, but most of them are based on convolutional neural network that may not capture enough information about long-range dependencies between residues in a protein sequence. In addition, existing deep learning methods only make use of sequence information for predicting phosphorylation sites, and it is highly desirable to develop a deep learning architecture that can combine heterogeneous sequence and protein–protein interaction (PPI) information for more accurate phosphorylation site prediction.

Results

We present a novel integrated deep neural network named PhosIDN, for phosphorylation site prediction by extracting and combining sequence and PPI information. In PhosIDN, a sequence feature encoding sub-network is proposed to capture not only local patterns but also long-range dependencies from protein sequences. Meanwhile, useful PPI features are also extracted in PhosIDN by a PPI feature encoding sub-network adopting a multi-layer deep neural network. Moreover, to effectively combine sequence and PPI information, a heterogeneous feature combination sub-network is introduced to fully exploit the complex associations between sequence and PPI features, and their combined features are used for final prediction. Comprehensive experiment results demonstrate that the proposed PhosIDN significantly improves the prediction performance of phosphorylation sites and compares favorably with existing general and kinase-specific phosphorylation site prediction methods.

Availability and implementation

PhosIDN is freely available at https://github.com/ustchangyuanyang/PhosIDN.

Supplementary information

Supplementary data are available at Bioinformatics online.

Insulin signaling regulates longevity through protein phosphorylation in Caenorhabditis elegans

Insulin/IGF-1 Signaling (IIS) is known to constrain longevity by inhibiting the transcription factor FOXO. How phosphorylation mediated by IIS kinases regulates lifespan beyond FOXO remains unclear. Here, we profile IIS-dependent phosphorylation changes in a large-scale quantitative phosphoproteomic analysis of wild-type and three IIS mutant Caenorhabditis elegans strains. We quantify more than 15,000 phosphosites and find that 476 of these are differentially phosphorylated in the long-lived daf-2/insulin receptor mutant. We develop a machine learning-based method to prioritize 25 potential lifespan-related phosphosites. We perform validations to show that AKT-1 pT492 inhibits DAF-16/FOXO and compensates the loss of daf-2 function, that EIF-2α pS49 potently inhibits protein synthesis and daf-2 longevity, and that reduced phosphorylation of multiple germline proteins apparently transmits reduced DAF-2 signaling to the soma. In addition, an analysis of kinases with enriched substrates detects that casein kinase 2 (CK2) subunits negatively regulate lifespan. Our study reveals detailed functional insights into longevity.

Computational Phosphorylation Network Reconstruction: An Update on Methods and Resources

Most proteins undergo some form of modification after translation, and phosphorylation is one of the most relevant and ubiquitous post-translational modifications. The succession of protein phosphorylation and dephosphorylation catalyzed by protein kinase and phosphatase, respectively, constitutes a key mechanism of molecular information flow in cellular systems. The protein interactions of kinases, phosphatases, and their regulatory subunits and substrates are the main part of phosphorylation networks. To elucidate the landscape of phosphorylation events has been a central goal pursued by both experimental and computational approaches. Substrate specificity (e.g., sequence, structure) or the phosphoproteome has been utilized in an array of different statistical learning methods to infer phosphorylation networks. In this chapter, different computational phosphorylation network inference-related methods and resources are summarized and discussed.

Investigating Post-translational Modifications in Neuropsychiatric Disease: The Next Frontier in Human Post-mortem Brain Research

Gene expression and translation have been extensively studied in human post-mortem brain tissue from subjects with psychiatric disease. Post-translational modifications (PTMs) have received less attention despite their implication by unbiased genetic studies and importance in regulating neuronal and circuit function. Here we review the rationale for studying PTMs in psychiatric disease, recent findings in human post-mortem tissue, the required controls for these types of studies, and highlight the emerging mass spectrometry approaches transforming this research direction.

Characterization of Kinase Expression Related to Increased Migration of PC-3M Cells Using Global Comparative Phosphoproteome Analysis

BACKGROUND/AIM

Prostate cancer (PCa) is the second-most commonly occurring cancer among men, worldwide. Although the mechanisms associated with the progression of castration-resistant prostate cancer (CRPC) have been widely studied, the mechanism associated with more distant metastases from the bone remains unknown. This study aimed to characterize potential pathogenic kinases associated with highly metastatic PCa, that may regulate phosphorylation in extensively involved and diverse signaling pathways that are associated with the development of various cancers.

MATERIALS AND METHODS

A mass spectrometry (MS)-based comparative phosphoproteome strategy was utilized to identify differentially expressed kinases between the highly aggressive PCa cell-lines PC-3 and PC-3M.

RESULTS

Among 2,968 phosphorylation sites in PCa cells, 151 differently expressed phosphoproteins were identified. Seven motifs: -SP-, -SxxE-, -PxS-, -PxSP-, -SxxK-, -SPxK-, and -SxxxxxP- were found to be highly expressed in PC-3M cells. Based on these motifs, the kinases p21-activated kinase (PAK)2, Ste20-like kinase (SLK), mammalian Ste20-like kinase (MST)4, mitogen-activated kinase kinase (MAP2K)2, and A-Raf proto-oncogene serine/threonine kinase (ARAF) were up-regulated in PC-3M cells.

CONCLUSION

PAK2, SLK, MST4, MAP2K2, and ARAF are kinases that are potentially associated with the progression of increased migration in PC-3M cells and may represent molecule regulators or drug targets for highly metastatic PCa therapy.

Proteomic and phosphoproteomic profiles of Sertoli cells in buffalo

Sertoli cells provide nutrients and support for germ cell differentiation and maintain a stable microenvironment for spermatogenesis. Comprehensive identification of Sertoli cellular proteins is important in understanding spermatogenesis. In this study, we performed an integrative analysis of the proteome and phosphoproteome to explore the role of Sertoli cells in spermatogenesis. A total of 2912 and 753 proteins were identified from the proteome and phosphoproteome in Sertoli cells, respectively; 438 proteins were common to the proteome and phosphoproteome. Data are available via ProteomeXchange with identifier PXD024984. In the proteome, ACTG1, ACTB, ACTA2, MYH9 were the most abundant proteins. Gene Ontology (GO) analysis indicated that most of the proteins were involved in the processes of localization, biosynthesis, gene expression, and transport. In addition, some of the proteins related to Sertoli cell functions were also enriched. In the phosphoproteome, most of the proteins were involved in gene expression and the RNA metabolic process; the pathways mainly involved the spliceosome, mitogen-activated protein kinase signaling pathway, focal adhesion, and tight junctions. The pleckstrin homology-like domain is the most highly enriched protein domain in phosphoproteins. Cyclin-dependent kinases and protein kinases C were found to be highly active kinases in the kinase-substrate network analysis. Ten proteins most closely related to network stability were found in the analysis of the network interactions of proteins identified jointly in the phosphoproteome and proteome. Through immunohistochemistry and immunofluorescence verification of vimentin, it was found that there were localization differences between phosphorylated and non-phosphorylated vimentin in testicular tissue. This study is the first in-depth proteomic and phosphoproteomic analysis of buffalo testicular Sertoli cells. The results provide insight into the role of Sertoli cells in spermatogenesis and provide clues for further study of male reproduction.

Comprehensive bioinformatics analysis reveals kinase activity profiling associated with heart failure

Heart failure is a complex clinical syndrome originating from cardiac injury, which leads to considerable morbidity and mortality. Among the dynamic molecular adaptations occurring in heart failure development, aggravation of the disease is often attributed to global or local abnormality of the kinase. Therefore, the overall monitoring of kinase activity is indispensable. In this study, a bioinformatics analysis method was developed to conduct deep mining of transcriptome and phosphoproteome in failing heart tissue. A total of 982 differentially expressed genes and 9781 phosphorylation sites on 3252 proteins were identified. Via upstream regulator relations and kinase-substrate relations, a dendrogram of kinases can be constructed to monitor its abnormality. The results show that, on the dendrogram, the distribution of kinases demonstrated complex kinase activity changes and certain rules that occur during heart failure. Finally, we also identified the hub kinases in heart failure and verified the expression of these kinases by reverse-transcription polymerase chain reaction and Western blot analysis. In conclusion, for the first time, we have systematically analyzed the differences in kinases during heart failure and provided an unprecedented breadth of multi-omics data. These results can bring about a sufficient data foundation and novel research perspectives.

Drug Discovery in Liver Disease Using Kinome Profiling

The liver is one of the most important organs, playing critical roles in maintaining biochemical homeostasis. Accordingly, disease of the liver is often debilitating and responsible for untold human misery. As biochemical nexus, with kinases being master regulators of cellular biochemistry, targeting kinase enzymes is an obvious avenue for treating liver disease. Development of such therapy, however, is hampered by the technical difficulty of obtaining comprehensive insight into hepatic kinase activity, a problem further compounded by the often unique aspects of hepatic kinase activities, which makes extrapolations from other systems difficult. This consideration prompted us to review the current state of the art with respect to kinome profiling approaches towards the hepatic kinome. We observe that currently four different approaches are available, all showing significant promise. Hence we postulate that insight into the hepatic kinome will quickly increase, leading to rational kinase-targeted therapy for different liver diseases.

Phosphorylation of SNX27 by MAPK11/14 links cellular stress-signaling pathways with endocytic recycling

Endocytosed proteins can be delivered to lysosomes for degradation or recycled to either the trans-Golgi network or the plasma membrane. It remains poorly understood how the recycling versus degradation of cargoes is determined. Here, we show that multiple extracellular stimuli, including starvation, LPS, IL-6, and EGF treatment, can strongly inhibit endocytic recycling of multiple cargoes through the activation of MAPK11/14. The stress-induced kinases in turn directly phosphorylate SNX27, a key regulator of endocytic recycling, at serine 51 (Ser51). Phosphorylation of SNX27 at Ser51 alters the conformation of its cargo-binding pocket and decreases the interaction between SNX27 and cargo proteins, thereby inhibiting endocytic recycling. Our study indicates that endocytic recycling is highly dynamic and can crosstalk with cellular stress–signaling pathways. Suppression of endocytic recycling and enhancement of receptor lysosomal degradation serve as new mechanisms for cells to cope with stress and save energy.

A facile "one-material" strategy for tandem enrichment of small extracellular vesicles phosphoproteome

Small extracellular vesicles (SEVs), are cell-derived, membrane-enclosed nanometer-sized vesicles that play vital roles in many biological processes. Recent years, more and more evidences proved that small EVs have close relationship with many diseases such as cancers and Alzheimer's disease. The use of phosphoproteins in SEVs as potential biomarkers is a promising new choice for early diagnosis and prognosis of cancer. However, current techniques for SEVs isolation still facing many challenges, such as highly instrument dependent, time consuming and insufficient purity. Furthermore, complex enrichment procedures and low microgram amounts of proteins available from clinical sources largely limit the throughput and the coveage depth of SEVs phosphoproteome mapping. Here, we synthesized Ti⁴⁺-modified magnetic graphene-oxide composites (GFST) and developed a "one-material" strategy for facile and efficient phosphoproteome enrichment and identification in SEVs from human serum. By taking advantage of chelation and electrostatic interactions between metal ions and phosphate groups, GFST shows excellent performance in both SEVs isolation and phosphopeptide enrichment. Close to 85% recovery is achieved within a few minutes by simple incubation with GFST and magnetic separation. Proteome profiling of the isolated serum SEVs without phosphopeptide enrichment results in 515 proteins, which is approximately one-fold more than those otained by ultracentrifugation or coprecipitation kits. Further application of GFST in one-material-based enrichment led to identification of 859 phosphosites in 530 phosphoproteins. Kinase-substrate correlation analysis reveals enriched substrates of CAMK in serum SEVs phosphoproteome. Therefore, we expect that the low instrument dependency and the limited sample requirement of this new strategy may facilitate clinical investigations in SEV-based transportation of abnormal kinases and substrates for drug target discovery and cancer monitoring.

Relationships between DNA repair and RTK-mediated signaling pathways

Receptor Tyrosine Kinases (RTK) are an important family involved in numerous signaling pathways essential for proliferation, cell survival, transcription or cell-cycle regulation. Their role and involvement in cancer cell survival have been widely described in the literature, and are generally associated with overexpression and/or excessive activity in the cancer pathology. Because of these characteristics, RTKs are relevant targets in the fight against cancer. In the last decade, increasingly numerous works describe the role of RTK signaling in the modulation of DNA repair, thus providing evidence of the relationship between RTKs and the protein actors in the repair pathways. In this review, we propose a summary of RTKs described as potential modulators of double-stranded DNA repair pathways in order to put forward new lines of research aimed at the implementation of new therapeutic strategies targeting both DNA repair pathways and RTK-mediated signaling pathways.

Reduced mitochondrial resilience enables non-canonical induction of apoptosis after TNF receptor signaling in virus-infected hepatocytes

BACKGROUND & AIMS

Selective elimination of virus-infected hepatocytes occurs through virus-specific CD8 T cells recognizing peptide-loaded MHC molecules. Herein, we report that virus-infected hepatocytes are also selectively eliminated through a cell-autonomous mechanism.

METHODS

We generated recombinant adenoviruses and genetically modified mouse models to identify the molecular mechanisms determining TNF-induced hepatocyte apoptosis in vivo and used in vivo bioluminescence imaging, immunohistochemistry, immunoblot analysis, RNAseq/proteome/phosphoproteome analyses, bioinformatic analyses, mitochondrial function tests.

RESULTS

We found that TNF precisely eliminated only virus-infected hepatocytes independently of local inflammation and activation of immune sensory receptors. TNF receptor I was equally relevant for NF-kB activation in healthy and infected hepatocytes, but selectively mediated apoptosis in infected hepatocytes. Caspase 8 activation downstream of TNF receptor signaling was dispensable for apoptosis in virus-infected hepatocytes, indicating an unknown non-canonical cell-intrinsic pathway promoting apoptosis in hepatocytes. We identified a unique state of mitochondrial vulnerability in virus-infected hepatocytes as the cause for this non-canonical induction of apoptosis through TNF. Mitochondria from virus-infected hepatocytes showed normal biophysical and bioenergetic functions but were characterized by reduced resilience to calcium challenge. In the presence of unchanged TNF-induced signaling, reactive oxygen species-mediated calcium release from the endoplasmic reticulum caused mitochondrial permeability transition and apoptosis, which identified a link between extrinsic death receptor signaling and cell-intrinsic mitochondrial-mediated caspase activation.

CONCLUSION

Our findings reveal a novel concept in immune surveillance by identifying a cell-autonomous defense mechanism that selectively eliminates virus-infected hepatocytes through mitochondrial permeability transition.

LAY SUMMARY

The liver is known for its unique immune functions. Herein, we identify a novel mechanism by which virus-infected hepatocytes can selectively eliminate themselves through reduced mitochondrial resilience to calcium challenge.

GasPhos: Protein Phosphorylation Site Prediction Using a New Feature Selection Approach with a GA-Aided Ant Colony System

Protein phosphorylation is one of the most important post-translational modifications, and many biological processes are related to phosphorylation, such as DNA repair, transcriptional regulation and signal transduction and, therefore, abnormal regulation of phosphorylation usually causes diseases. If we can accurately predict human phosphorylation sites, this could help to solve human diseases. Therefore, we developed a kinase-specific phosphorylation prediction system, GasPhos, and proposed a new feature selection approach, called Gas, based on the ant colony system and a genetic algorithm and used performance evaluation strategies focused on different kinases to choose the best learning model. Gas uses the mean decrease Gini index (MDGI) as a heuristic value for path selection and adopts binary transformation strategies and new state transition rules. GasPhos can predict phosphorylation sites for six kinases and showed better performance than other phosphorylation prediction tools. The disease-related phosphorylated proteins that were predicted with GasPhos are also discussed. Finally, Gas can be applied to other issues that require feature selection, which could help to improve prediction performance. GasPhos is available at http://predictor.nchu.edu.tw/GasPhos.

Novel targets identified by integrated proteomic and phosphoproteomic analysis in spermatogenesis of swamp buffalo (Bubalus bubalis)

To understand mechanisms of spermatogenesis, the proteome and the phosphoproteome in prepubertal and pubertal swamp buffalo (Bubalus bubalis) testes were analyzed using tandem mass tag (TMT) coupled with liquid chromatography-tandem mass spectrometry (LC–MS/MS). In prepubertal testes, 80 proteins were overexpressed, 148 proteins were underexpressed, and 139 and 142 protein sites had higher and lower phosphorylation, respectively, compared to the levels in pubertal testes. Several of these proteins were associated with reproductive processes such as sexual reproduction, spermatogenesis, fertilization, and spermatid development. In particular, outer dense fiber protein 1 (ODF1), protein maelstrom homolog (MAEL), actin-like protein 7B (ACTL7B), tyrosine-(Y)-phosphorylation regulated (CABYR), and tripartite motif containing 36 (TRIM36) were upregulated with age at both the proteome and phosphoproteome levels. Combining proteome and phosphoproteome analysis can be effectively applied to study the protein/phosphorylation patterns of buffalo testes. These data provide new regulatory candidates and evidence for a complex network in spermatogenesis in buffalo testes, and serve as an important resource for exploring the physiological mechanism of spermatogenesis in mammals.