GPS 2.0, a tool to predict kinase-specific phosphorylation sites in hierarchy

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.

Mitochondrial Raf1 Regulates Glutamine Catabolism

Raf kinases play vital roles in normal mitogenic signaling and cancer, however, the identities of functionally important Raf-proximal proteins throughout the cell are not fully known. Raf1 proximity proteomics/BioID in Raf1-dependent cancer cells unexpectedly identified Raf1-adjacent proteins known to reside in the mitochondrial matrix. Inner-mitochondrial localization of Raf1 was confirmed by mitochondrial purification and super-resolution microscopy. Inside mitochondria, Raf1 associated with glutaminase (GLS) in diverse human cancers and enabled glutaminolysis, an important source of biosynthetic precursors in cancer. These impacts required Raf1 kinase activity and were independent of canonical MAP kinase pathway signaling. Kinase-dead mitochondrial matrix-localized Raf1 impaired glutaminolysis and tumorigenesis in vivo. These data indicate that Raf1 localizes inside mitochondria where it interacts with GLS to engage glutamine catabolism and support tumorigenesis.

Attenphos: General Phosphorylation Site Prediction Model Based on Attention Mechanism

Phosphorylation site prediction has important application value in the field of bioinformatics. It can act as an important reference and help with protein function research, protein structure research, and drug discovery. So, it is of great significance to propose scientific and effective calculation methods to accurately predict phosphorylation sites. In this study, we propose a new method, Attenphos, based on the self-attention mechanism for predicting general phosphorylation sites in proteins. The method not only captures the long-range dependence information of proteins but also better represents the correlation between amino acids through feature vector encoding transformation. Attenphos takes advantage of the one-dimensional convolutional layer to reduce the number of model parameters, improve model efficiency and prediction accuracy, and enhance model generalization. Comparisons between our method and existing state-of-the-art prediction tools were made using balanced datasets from human proteins and unbalanced datasets from mouse proteins. We performed prediction comparisons using independent test sets. The results showed that Attenphos demonstrated the best overall performance in the prediction of Serine (S), Threonine (T), and Tyrosine (Y) sites on both balanced and unbalanced datasets. Compared to current state-of-the-art methods, Attenphos has significantly higher prediction accuracy. This proves the potential of Attenphos in accelerating the identification and functional analysis of protein phosphorylation sites and provides new tools and ideas for biological research and drug discovery.

Cell Cycle-Specific Protein Phosphatase 1 (PP1) Substrates Identification Using Genetically Modified Cell Lines

The identification of protein phosphatase 1 (PP1) holoenzyme substrates has proven to be a challenging task. PP1 can form different holoenzyme complexes with a variety of regulatory subunits, and many of those are cell cycle regulated. Although several methods have been used to identify PP1 substrates, their cell cycle specificity is still an unmet need. Here, we present a new strategy to investigate PP1 substrates throughout the cell cycle using clustered regularly interspersed short palindromic repeats (CRISPR)-Cas9 genome editing and generate cell lines with endogenously tagged PP1 regulatory subunit (regulatory interactor of protein phosphatase one, RIPPO). RIPPOs are tagged with the auxin-inducible degron (AID) or ascorbate peroxidase 2 (APEX2) modules, and PP1 substrate identification is conducted by SILAC proteomic-based approaches. Proteins in close proximity to RIPPOs are first identified through mass spectrometry (MS) analyses using the APEX2 system; then a list of differentially phosphorylated proteins upon RIPPOs rapid degradation (achieved via the AID system) is compiled via SILAC phospho-mass spectrometry. The "in silico" overlap between the two proteomes will be enriched for PP1 putative substrates. Several methods including fluorescence resonance energy transfer (FRET), proximity ligation assays (PLA), and in vitro assays can be used as substrate validations approaches.

MAP kinases may mediate regulation of the cell cycle in rice by E2F2 phosphorylation

E2F is the key transcription factor that determines the proliferative status of cells by regulating the G1/S phase of the cell cycle. In this study, we show that in rice (Oryza sativa), OsE2F2 is a phosphorylation target of MAP kinases. The MAP kinases OsMPK3, OsMPK4, and OsMPK6 interact with and phosphorylate OsE2F2. Next, we determined the serine and threonine residues that could play a role in the phosphorylation of OsE2F2. Subsequently, our study suggests a possible link between MAP kinase-mediated OsE2F2 phosphorylation and its impact on DNA proliferation in the roots of rice seedlings. Finally, we found positive feedback regulation of OsMPK4 by OsE2F2. Therefore, our study hints at the potential impact of MAP kinase signaling on the cell cycle of rice plants.

A Review of Machine Learning and Algorithmic Methods for Protein Phosphorylation Site Prediction

Post-translational modifications (PTMs) have key roles in extending the functional diversity of proteins and, as a result, regulating diverse cellular processes in prokaryotic and eukaryotic organisms. Phosphorylation modification is a vital PTM that occurs in most proteins and plays a significant role in many biological processes. Disorders in the phosphorylation process lead to multiple diseases, including neurological disorders and cancers. The purpose of this review is to organize this body of knowledge associated with phosphorylation site (p-site) prediction to facilitate future research in this field. At first, we comprehensively review all related databases and introduce all steps regarding dataset creation, data preprocessing, and method evaluation in p-site prediction. Next, we investigate p-site prediction methods, which are divided into two computational groups: algorithmic and machine learning (ML). Additionally, it is shown that there are basically two main approaches for p-site prediction by ML: conventional and end-to-end deep learning methods, both of which are given an overview. Moreover, this review introduces the most important feature extraction techniques, which have mostly been used in p-site prediction. Finally, we create three test sets from new proteins related to the released version of the database of protein post-translational modifications (dbPTM) in 2022 based on general and human species. Evaluating online p-site prediction tools on newly added proteins introduced in the dbPTM 2022 release, distinct from those in the dbPTM 2019 release, reveals their limitations. In other words, the actual performance of these online p-site prediction tools on unseen proteins is notably lower than the results reported in their respective research papers.

Transcriptional Regulation of the Human 5-HT1A Receptor Gene by Lithium: Role of Deaf1 and GSK3β

Serotonin 1A (5-HT1A) autoreceptors located on serotonin neurons inhibit their activity, and their upregulation has been implicated in depression, suicide and resistance to antidepressant treatment. Conversely, post-synaptic 5-HT1A heteroreceptors are important for antidepressant response. The transcription factor deformed epidermal autoregulatory factor 1 (Deaf1) acts as a presynaptic repressor and postsynaptic enhancer of 5-HT1A transcription, but the mechanism is unclear. Because Deaf1 interacts with and is phosphorylated by glycogen synthase kinase 3β (GSK3β)-a constitutively active protein kinase that is inhibited by the mood stabilizer lithium at therapeutic concentrations-we investigated the role of GSK3β in Deaf1 regulation of human 5-HT1A transcription. In 5-HT1A promoter-reporter assays, human HEK293 kidney and 5-HT1A-expressing SKN-SH neuroblastoma cells, transfection of Deaf1 reduced 5-HT1A promoter activity by ~45%. To identify potential GSK3β site(s) on Deaf1, point mutations of known and predicted phosphorylation sites on Deaf1 were tested. Deaf1 repressor function was not affected by any of the mutants tested except the Y300F mutant, which augmented Deaf1 repression. Both lithium and the selective GSK3 inhibitors CHIR-99021 and AR-014418 attenuated and reversed Deaf1 repression compared to vector. This inhibition was at concentrations that maximally inhibit GSK3β activity as detected by the GSK3β-sensitive TCF/LEF reporter construct. Our results support the hypothesis that GSK3β regulates the activity of Deaf1 to repress 5-HT1A transcription and provide a potential mechanism for actions of GSK3 inhibitors on behavior.

KSFinder-a knowledge graph model for link prediction of novel phosphorylated substrates of kinases

Background

Aberrant protein kinase regulation leading to abnormal substrate phosphorylation is associated with several human diseases. Despite the promise of therapies targeting kinases, many human kinases remain understudied. Most existing computational tools predicting phosphorylation cover less than 50% of known human kinases. They utilize local feature selection based on protein sequences, motifs, domains, structures, and/or functions, and do not consider the heterogeneous relationships of the proteins. In this work, we present KSFinder, a tool that predicts kinase-substrate links by capturing the inherent association of proteins in a network comprising 85% of the known human kinases. We also postulate the potential role of two understudied kinases based on their substrate predictions from KSFinder.

Methods

KSFinder learns the semantic relationships in a phosphoproteome knowledge graph using a knowledge graph embedding algorithm and represents the nodes in low-dimensional vectors. A multilayer perceptron (MLP) classifier is trained to discern kinase-substrate links using the embedded vectors. KSFinder uses a strategic negative generation approach that eliminates biases in entity representation and combines data from experimentally validated non-interacting protein pairs, proteins from different subcellular locations, and random sampling. We assess KSFinder's generalization capability on four different datasets and compare its performance with other state-of-the-art prediction models. We employ KSFinder to predict substrates of 68 "dark" kinases considered understudied by the Illuminating the Druggable Genome program and use our text-mining tool, RLIMS-P along with manual curation, to search for literature evidence for the predictions. In a case study, we performed functional enrichment analysis for two dark kinases - HIPK3 and CAMKK1 using their predicted substrates.

Results

KSFinder shows improved performance over other kinase-substrate prediction models and generalized prediction ability on different datasets. We identified literature evidence for 17 novel predictions involving an understudied kinase. All of these 17 predictions had a probability score ≥0.7 (nine at >0.9, six at 0.8-0.9, and two at 0.7-0.8). The evaluation of 93,593 negative predictions (probability ≤0.3) identified four false negatives. The top enriched biological processes of HIPK3 substrates relate to the regulation of extracellular matrix and epigenetic gene expression, while CAMKK1 substrates include lipid storage regulation and glucose homeostasis.

Conclusions

KSFinder outperforms the current kinase-substrate prediction tools with higher kinase coverage. The strategically developed negatives provide a superior generalization ability for KSFinder. We predicted substrates of 432 kinases, 68 of which are understudied, and hypothesized the potential functions of two dark kinases using their predicted substrates.

De Novo Linear Phosphorylation Site Motifs for BCR-ABL Kinase Revealed by Phospho-Proteomics in Yeast

BCR-ABL is the oncogenic fusion product of tyrosine kinase ABL1 and a highly frequent driver of acute lymphocytic leukemia (ALL) and chronic myeloid leukemia (CML). The kinase activity of BCR-ABL is strongly elevated; however, changes of substrate specificity in comparison to wild-type ABL1 kinase are less well characterized. Here, we heterologously expressed full-length BCR-ABL kinases in yeast. We exploited the proteome of living yeast as an in vivo phospho-tyrosine substrate for assaying human kinase specificity. Phospho-proteomic analysis of ABL1 and BCR-ABL isoforms p190 and p210 yielded a high-confidence data set of 1127 phospho-tyrosine sites on 821 yeast proteins. We used this data set to generate linear phosphorylation site motifs for ABL1 and the oncogenic ABL1 fusion proteins. The oncogenic kinases yielded a substantially different linear motif when compared to ABL1. Kinase set enrichment analysis with human pY-sites that have high linear motif scores well-recalled BCR-ABL driven cancer cell lines from human phospho-proteome data sets.

The autism-associated loss of δ-catenin functions disrupts social behavior

δ-catenin is expressed in excitatory synapses and functions as an anchor for the glutamatergic AMPA receptor (AMPAR) GluA2 subunit in the postsynaptic density. The glycine 34 to serine (G34S) mutation in the δ-catenin gene has been found in autism spectrum disorder (ASD) patients and results in loss of δ-catenin functions at excitatory synapses, which is presumed to underlie ASD pathogenesis in humans. However, how the G34S mutation causes loss of δ-catenin functions to induce ASD remains unclear. Here, using neuroblastoma cells, we identify that the G34S mutation increases glycogen synthase kinase 3β (GSK3β)-dependent δ-catenin degradation to reduce δ-catenin levels, which likely contributes to the loss of δ-catenin functions. Synaptic δ-catenin and GluA2 levels in the cortex are significantly decreased in mice harboring the δ-catenin G34S mutation. The G34S mutation increases glutamatergic activity in cortical excitatory neurons while it is decreased in inhibitory interneurons, indicating changes in cellular excitation and inhibition. δ-catenin G34S mutant mice also exhibit social dysfunction, a common feature of ASD. Most importantly, pharmacological inhibition of GSK3β activity reverses the G34S-induced loss of δ-catenin function effects in cells and mice. Finally, using δ-catenin knockout mice, we confirm that δ-catenin is required for GSK3β inhibition-induced restoration of normal social behavior in δ-catenin G34S mutant animals. Taken together, we reveal that the loss of δ-catenin functions arising from the ASD-associated G34S mutation induces social dysfunction via alterations in glutamatergic activity and that GSK3β inhibition can reverse δ-catenin G34S-induced synaptic and behavioral deficits.

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.

Naturally occurring substitution of an amino acid in a plant virus gene-silencing suppressor enhances viral adaptation to increasing thermal stress

Cereal yellow dwarf virus (CYDV-RPV) encodes a P0 protein that functions as a viral suppressor of RNA silencing (VSR). The strength of silencing suppression is highly variable among CYDV-RPV isolates. In this study, comparison of the P0 sequences of CYDV-RPV isolates and mutational analysis identified a single C-terminal amino acid that influenced P0 RNA-silencing suppressor activity. A serine at position 247 was associated with strong suppressor activity, whereas a proline at position 247 was associated with weak suppressor activity. Amino acid changes at position 247 did not affect the interaction of P0 with SKP1 proteins from Hordeum vulgare (barley) or Nicotiana benthamiana. Subsequent studies found P0 proteins containing a P247 residue were less stable than the P0 proteins containing an S247 residue. Higher temperatures contributed to the lower stability and in planta and the P247 P0 proteins were subject to degradation via the autophagy-mediated pathway. A P247S amino acid residue substitution in P0 increased CYDV-RPV replication after expression in agroinfiltrated plant leaves and increased viral pathogenicity of P0 generated from the heterologous Potato virus X expression vector system. Moreover, an S247 CYDV-RPV could outcompete the P247 CYDV-RPV in a mixed infection in natural host at higher temperature. These traits contributed to increased transmission by aphid vectors and could play a significant role in virus competition in warming climates. Our findings underscore the capacity of a plant RNA virus to adapt to climate warming through minor genetic changes in gene-silencing suppressor, resulting in the potential for disease persistence and prevalence.

From prediction to function: Current practices and challenges towards the functional characterization of type III effectors

The type III secretion system (T3SS) is a well-studied pathogenicity determinant of many bacteria through which effectors (T3Es) are translocated into the host cell, where they exercise a wide range of functions to deceive the host cell's immunity and to establish a niche. Here we look at the different approaches that are used to functionally characterize a T3E. Such approaches include host localization studies, virulence screenings, biochemical activity assays, and large-scale omics, such as transcriptomics, interactomics, and metabolomics, among others. By means of the phytopathogenic Ralstonia solanacearum species complex (RSSC) as a case study, the current advances of these methods will be explored, alongside the progress made in understanding effector biology. Data obtained by such complementary methods provide crucial information to comprehend the entire function of the effectome and will eventually lead to a better understanding of the phytopathogen, opening opportunities to tackle it.

The autism-associated loss of δ-catenin functions disrupts social behaviors

δ-catenin is expressed in excitatory synapses and functions as an anchor for the glutamatergic AMPA receptor (AMPAR) GluA2 subunit in the postsynaptic density. The glycine 34 to serine (G34S) mutation in the δ-catenin gene is found in autism spectrum disorder (ASD) patients and induces loss of δ-catenin functions at excitatory synapses, which is presumed to underlie ASD pathogenesis in humans. However, how the G34S mutation causes loss of δ-catenin functions to induce ASD remains unclear. Here, using neuroblastoma cells, we discover that the G34S mutation generates an additional phosphorylation site for glycogen synthase kinase 3β (GSK3β). This promotes δ-catenin degradation and causes the reduction of δ-catenin levels, which likely contributes to the loss of δ-catenin functions. Synaptic δ-catenin and GluA2 levels in the cortex are significantly decreased in mice harboring the δ-catenin G34S mutation. The G34S mutation increases glutamatergic activity in cortical excitatory neurons while it is decreased in inhibitory interneurons, indicating changes in cellular excitation and inhibition. δ-catenin G34S mutant mice also exhibit social dysfunction, a common feature of ASD. Most importantly, inhibition of GSK3β activity reverses the G34S-induced loss of δ-catenin function effects in cells and mice. Finally, using δ-catenin knockout mice, we confirm that δ-catenin is required for GSK3β inhibition-induced restoration of normal social behaviors in δ-catenin G34S mutant animals. Taken together, we reveal that the loss of δ-catenin functions arising from the ASD-associated G34S mutation induces social dysfunction via alterations in glutamatergic activity and that GSK3β inhibition can reverse δ-catenin G34S-induced synaptic and behavioral deficits.

Significance Statement

δ-catenin is important for the localization and function of glutamatergic AMPA receptors at synapses in many brain regions. The glycine 34 to serine (G34S) mutation in the δ-catenin gene is found in autism patients and results in the loss of δ-catenin functions. δ-catenin expression is also closely linked to other autism-risk genes involved in synaptic structure and function, further implying that it is important for the autism pathophysiology. Importantly, social dysfunction is a key characteristic of autism. Nonetheless, the links between δ-catenin functions and social behaviors are largely unknown. The significance of the current research is thus predicated on filling this gap by discovering the molecular, cellular, and synaptic underpinnings of the role of δ-catenin in social behaviors.

Mechanism of PKCε regulation of cardiac GIRK channel gating

G-protein-gated inwardly rectifying potassium (GIRK) channel activity is regulated by the membrane phospholipid, phosphatidylinositol-4,5-bisphosphate (PI 4,5P2). Constitutive activity of cardiac GIRK channels in atrial myocytes, that is implicated in atrial fibrillation (AF), is mediated via a protein kinase C-ε (PKCε)-dependent mechanism. The novel PKC isoform, PKCε, is reported to enhance the activity of cardiac GIRK channels. Here, we report that PKCε stimulation leads to activation of GIRK channels in mouse atria and in human stem cell-derived atrial cardiomyocytes (iPSCs). We identified residue GIRK4(S418) which when mutated to Ala abolished, or to Glu, mimicked the effects of PKCε on GIRK currents. PKCε strengthened the interactions of the cardiac GIRK isoforms, GIRK4 and GIRK1/4 with PIP2, an effect that was reversed in the GIRK4(S418A) mutant. This mechanistic insight into the PKCε-mediated increase in channel activity because of GIRK4(S418) phosphorylation, provides a precise druggable target to reverse AF-related pathologies due to GIRK overactivity.

MEKs/ERKs-mediated FBXO1/E2Fs interaction interference modulates G1/S cell cycle transition and cancer cell proliferation

E2F 1, 2, and 3a, (refer to as E2Fs) are a subfamily of E2F transcription factor family that play essential roles in cell-cycle progression, DNA replication, DNA repair, apoptosis, and differentiation. Although the transcriptional regulation of E2Fs has focused on pocket protein retinoblastoma protein complex, recent studies indicate that post-translational modification and stability regulation of E2Fs play key roles in diverse cellular processes. In this study, we found that FBXO1, a component of S-phase kinase-associated protein 1 (SKP1)-cullin 1-F-box protein (SCF) complex, is an E2Fs binding partner. Furthermore, FBXO1 to E2Fs binding induced K48 ubiquitination and subsequent proteasomal degradation of E2Fs. Binding domain analysis indicated that the Arg (R)/Ile (I) and R/Val (V) motifs, which are located in the dimerization domain of E2Fs, of E2F 1 and 3a and E2F2, respectively, acted as degron motifs (DMs) for FBXO1. Notably, RI/AA or RV/AA mutation in the DMs reduced FBXO1-mediated ubiquitination and prolonged the half-lives of E2Fs. Importantly, the stabilities of E2Fs were affected by phosphorylation of threonine residues located near RI and RV residues of DMs. Phosphorylation prediction database analysis and specific inhibitor analysis revealed that MEK/ERK signaling molecules play key roles in FBXO1/E2Fs' interaction and modulate E2F protein turnover. Moreover, both elevated E2Fs protein levels by knockdown of FBXO1 and decreased E2Fs protein levels by sh-E2F3a delayed G₁/S cell cycle transition, resulting in inhibition of cancer cell proliferation. These results demonstrated that FBXO1-E2Fs axis-mediated precise E2Fs stability regulation plays a key role in cell proliferation via G₁/S cell cycle transition.

A Novel Capsule Network with Attention Routing to Identify Prokaryote Phosphorylation Sites

By denaturing proteins and promoting the formation of multiprotein complexes, protein phosphorylation has important effects on the activity of protein functional molecules and cell signaling. The regulation of protein phosphorylation allows microbes to respond rapidly and reversibly to specific environmental stimuli or niches, which is closely related to the molecular mechanisms of bacterial drug resistance. Accurate prediction of phosphorylation sites (p-site) of prokaryotes can contribute to addressing bacterial resistance and providing new perspectives for developing novel antibacterial drugs. Most existing studies focus on human phosphorylation sites, while tools targeting phosphorylation site identification of prokaryotic proteins are still relatively scarce. This study designs a capsule network-based prediction technique for p-site in prokaryotes. To address the poor scalability and unreliability of dynamic routing processes in the output space of capsule networks, a more reliable way is introduced to learn the consistency between capsules. We incorporate a self-attention mechanism into the routing algorithm to capture the global information of the capsule, reducing the computational effort while enriching the representation capability of the capsule. Aiming at the weak robustness of the model, EcapsP improves the prediction accuracy and stability by introducing shortcuts and unconditional reconfiguration. In addition, the study compares and analyzes the prediction performance based on word vectors, physicochemical properties, and mixing characteristics in predicting serine (Ser/S), threonine (Thr/T), and tyrosine (Tyr/Y) p-site. The comprehensive experimental results show that the accuracy of the developed technique is close to 70% for the identification of the three phosphorylation sites in prokaryotes. Importantly, in side-by-side comparisons with other state-of-the-art predictors, our method improves the Matthews correlation coefficient (MCC) by approximately 7%. The results demonstrate the superiority of EcapsP in terms of high performance and reliability.

Amplification of olfactory signals by Anoctamin 9 is important for mammalian olfaction

Sensing smells of foods, prey, or predators determines animal survival. Olfactory sensory neurons in the olfactory epithelium (OE) detect odorants, where cAMP and Ca2+ play a significant role in transducing odorant inputs to electrical activity. Here we show Anoctamin 9, a cation channel activated by cAMP/PKA pathway, is expressed in the OE and amplifies olfactory signals. Ano9-deficient mice had reduced olfactory behavioral sensitivity, electro-olfactogram signals, and neural activity in the olfactory bulb. In line with the difference in olfaction between birds and other vertebrates, chick ANO9 failed to respond to odorants, whereas chick CNGA2, a major transduction channel, showed greater responses to cAMP. Thus, we concluded that the signal amplification by ANO9 is important for mammalian olfactory transduction.

ATM/ATR kinases link the synaptonemal complex and DNA double-strand break repair pathway choice

DNA double-strand breaks (DSBs) are deleterious lesions, which must be repaired precisely to maintain genomic stability. During meiosis, programmed DSBs are repaired via homologous recombination (HR) while repair using the nonhomologous end joining (NHEJ) pathway is inhibited, thereby ensuring crossover formation and accurate chromosome segregation.1,2 How DSB repair pathway choice is implemented during meiosis is unknown. In C. elegans, meiotic DSB repair takes place in the context of the fully formed, highly dynamic zipper-like structure present between homologous chromosomes called the synaptonemal complex (SC).3,4,5,6,7,8,9 The SC consists of a pair of lateral elements bridged by a central region composed of the SYP proteins in C. elegans. How the structural components of the SC are regulated to maintain the architectural integrity of the assembled SC around DSB repair sites remained unclear. Here, we show that SYP-4, a central region component of the SC, is phosphorylated at Serine 447 in a manner dependent on DSBs and the ATM/ATR DNA damage response kinases. We show that this SYP-4 phosphorylation is critical for preserving the SC structure following exogenous (γ-IR-induced) DSB formation and for promoting normal DSB repair progression and crossover patterning following SPO-11-dependent and exogenous DSBs. We propose a model in which ATM/ATR-dependent phosphorylation of SYP-4 at the S447 site plays important roles both in maintaining the architectural integrity of the SC following DSB formation and in warding off repair via the NHEJ repair pathway, thereby preventing aneuploidy.

Global Phosphoproteomics Unveils Kinase-Regulated Networks in Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is an autoimmune disorder characterized by immune complex deposition in multiple organs. Despite the severe symptoms caused by it, the underlying mechanisms of SLE, especially phosphorylation-dependent regulatory networks remain elusive. Herein, by combining high-throughput phosphoproteomics with bioinformatics approaches, we established the global phosphoproteome landscape of the peripheral blood mononuclear cells from a large number of SLE patients, including the remission stage (SLE_S), active stage (SLE_A), rheumatoid arthritis, and healthy controls, and thus a deep mechanistic insight into SLE signaling mechanism was yielded. Phosphorylation upregulation was preferentially in patients with SLE (SLE_S and SLE_A) compared with healthy controls and rheumatoid arthritis populations, resulting in an atypical enrichment in cell adhesion and migration signatures. Several specifically upregulated phosphosites were identified, and the leukocyte transendothelial migration pathway was enriched in the SLE_A group by expression pattern clustering analysis. Phosphosites identified by 4D-label-free quantification unveiled key kinases and kinase-regulated networks in SLE, then further validated by parallel reaction monitoring. Some of these validated phosphosites including vinculin S275, vinculin S579 and transforming growth factor beta-1-induced transcript 1 S68, primarily were phosphorylation of Actin Cytoskeleton -related proteins. Some predicted kinases including MAP3K7, TBK1, IKKβ, and GSK3β, were validated by Western blot using kinases phosphorylation sites-specific antibodies. Taken together, the study has yielded fundamental insights into the phosphosites, kinases, and kinase-regulated networks in SLE. The map of the global phosphoproteomics enables further understanding of this disease and will provide great help for seeking more potential therapeutic targets for SLE.

Gut bacteria alleviate smoking-related NASH by degrading gut nicotine

Tobacco smoking is positively correlated with non-alcoholic fatty liver disease (NAFLD)^1-5, but the underlying mechanism for this association is unclear. Here we report that nicotine accumulates in the intestine during tobacco smoking and activates intestinal AMPKα. We identify the gut bacterium Bacteroides xylanisolvens as an effective nicotine degrader. Colonization of B. xylanisolvens reduces intestinal nicotine concentrations in nicotine-exposed mice, and it improves nicotine-exacerbated NAFLD progression. Mechanistically, AMPKα promotes the phosphorylation of sphingomyelin phosphodiesterase 3 (SMPD3), stabilizing the latter and therefore increasing intestinal ceramide formation, which contributes to NAFLD progression to non-alcoholic steatohepatitis (NASH). Our results establish a role for intestinal nicotine accumulation in NAFLD progression and reveal an endogenous bacterium in the human intestine with the ability to metabolize nicotine. These findings suggest a possible route to reduce tobacco smoking-exacerbated NAFLD progression.

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.

KinasePhos 3.0: Redesign and Expansion of the Prediction on Kinase-specific Phosphorylation Sites

The purpose of this work is to enhance KinasePhos, a machine learning-based kinase-specific phosphorylation site prediction tool. Experimentally verified kinase-specific phosphorylation data were collected from PhosphoSitePlus, UniProtKB, the Group-based Prediction System 5.0, and Phospho.ELM. In total, 41,421 experimentally verified kinase-specific phosphorylation sites were identified. A total of 1380 unique kinases were identified, including 753 with existing classification information from KinBase and the remaining 627 annotated by building a phylogenetic tree. Based on this kinase classification, a total of 771 predictive models were built at the individual, family, and group levels, using at least 15 experimentally verified substrate sites in positive training datasets. The improved models demonstrated their effectiveness compared with other prediction tools. For example, the prediction of sites phosphorylated by the protein kinase B, casein kinase 2, and protein kinase A families had accuracies of 94.5%, 92.5%, and 90.0%, respectively. The average prediction accuracy for all 771 models was 87.2%. For enhancing interpretability, the SHapley Additive exPlanations (SHAP) method was employed to assess feature importance. The web interface of KinasePhos 3.0 has been redesigned to provide comprehensive annotations of kinase-specific phosphorylation sites on multiple proteins. Additionally, considering the large scale of phosphoproteomic data, a downloadable prediction tool is available at https://awi.cuhk.edu.cn/KinasePhos/download.html or https://github.com/tom-209/KinasePhos-3.0-executable-file.

Deep Learning-Based Advances In Protein Posttranslational Modification Site and Protein Cleavage Prediction

Posttranslational modification (PTM ) is a ubiquitous phenomenon in both eukaryotes and prokaryotes which gives rise to enormous proteomic diversity. PTM mostly comes in two flavors: covalent modification to polypeptide chain and proteolytic cleavage. Understanding and characterization of PTM is a fundamental step toward understanding the underpinning of biology. Recent advances in experimental approaches, mainly mass-spectrometry-based approaches, have immensely helped in obtaining and characterizing PTMs. However, experimental approaches are not enough to understand and characterize more than 450 different types of PTMs and complementary computational approaches are becoming popular. Recently, due to the various advancements in the field of Deep Learning (DL), along with the explosion of applications of DL to various fields, the field of computational prediction of PTM has also witnessed the development of a plethora of deep learning (DL)-based approaches. In this book chapter, we first review some recent DL-based approaches in the field of PTM site prediction. In addition, we also review the recent advances in the not-so-studied PTM , that is, proteolytic cleavage predictions. We describe advances in PTM prediction by highlighting the Deep learning architecture, feature encoding, novelty of the approaches, and availability of the tools/approaches. Finally, we provide an outlook and possible future research directions for DL-based approaches for PTM prediction.

Phosphoproteome reveals molecular mechanisms of aberrant rhythm in neurotransmitter-mediated islet hormone secretion in diabetic mice

BACKGROUND

Acetylcholine (ACh) and norepinephrine (NE) are representative neurotransmitters of parasympathetic and sympathetic nerves, respectively, that antagonize each other to coregulate internal body functions. This also includes the control of different kinds of hormone secretion from pancreatic islets. However, the molecular mechanisms have not been fully elucidated, and whether innervation in islets is abnormal in diabetes mellitus also remains unclear.

METHODS AND RESULTS

Immunofluorescence colocalization and islet perfusion were performed and the results demonstrated that ACh/NE and their receptors were highly expressed in islet and rapidly regulated different hormones secretion. Phosphorylation is considered an important posttranslational modification in islet innervation and it was identified by quantitative proteomic and phosphoproteomic analyses in this study. The phosphorylated islet proteins were found involved in many biological and pathological processes, such as synaptic signalling transduction, calcium channel opening and insulin signalling pathway. Then, the kinases were predicted by motif analysis and further screened and verified by kinase-specific siRNAs in different islet cell lines (αTC1-6, Min6 and TGP52). After functional verification, Ksr2 and Pkacb were considered the key kinases of ACh and NE in insulin secretion, and Cadps, Mlxipl and Pdcd4 were the substrates of these kinases measured by immunofluorescence co-staining. Then, the decreased expression of receptors, kinases and substrates of ACh and NE were found in diabetic mice and the aberrant rhythm in insulin secretion could be improved by combined interventions on key receptors (M3 (pilocarpine) or α2a (guanfacine)) and kinases (Ksr2 or Pkacb).

CONCLUSIONS

Abnormal innervation was closely associated with the degree of islet dysfunction in diabetic mice and the aberrant rhythm in insulin secretion could be ameliorated significantly after intervention with key receptors and kinases in the early stage of diabetes mellitus, which may provide a promising therapeutic strategy for diabetes mellitus in the future.

Axonal transport of late endosomes and amphisomes is selectively modulated by local Ca2+ efflux and disrupted by PSEN1 loss of function

Dysfunction and mistrafficking of organelles in autophagy- and endosomal-lysosomal pathways are implicated in neurodegenerative diseases. Here, we reveal selective vulnerability of maturing degradative organelles (late endosomes/amphisomes) to disease-relevant local calcium dysregulation. These organelles undergo exclusive retrograde transport in axons, with occasional pauses triggered by regulated calcium efflux from agonist-evoked transient receptor potential cation channel mucolipin subfamily member 1 (TRPML1) channels-an effect greatly exaggerated by exogenous agonist mucolipin synthetic agonist 1 (ML-SA1). Deacidification of degradative organelles, as seen after Presenilin 1 (PSEN1) loss of function, induced pathological constitutive "inside-out" TRPML1 hyperactivation, slowing their transport comparably to ML-SA1 and causing accumulation in dystrophic axons. The mechanism involved calcium-mediated c-Jun N-terminal kinase (JNK) activation, which hyperphosphorylated dynein intermediate chain (DIC), reducing dynein activity. Blocking TRPML1 activation, JNK activity, or DIC1B serine-80 phosphorylation reversed transport deficits in PSEN1 knockout neurons. Our results, including features demonstrated in Alzheimer-mutant PSEN1 knockin mice, define a mechanism linking dysfunction and mistrafficking in lysosomal pathways to neuritic dystrophy under neurodegenerative conditions.

TransPhos: A Deep-Learning Model for General Phosphorylation Site Prediction Based on Transformer-Encoder Architecture

Protein phosphorylation is one of the most critical post-translational modifications of proteins in eukaryotes, which is essential for a variety of biological processes. Plenty of attempts have been made to improve the performance of computational predictors for phosphorylation site prediction. However, most of them are based on extra domain knowledge or feature selection. In this article, we present a novel deep learning-based predictor, named TransPhos, which is constructed using a transformer encoder and densely connected convolutional neural network blocks, for predicting phosphorylation sites. Data experiments are conducted on the datasets of PPA (version 3.0) and Phospho. ELM. The experimental results show that our TransPhos performs better than several deep learning models, including Convolutional Neural Networks (CNN), Long-term and short-term memory networks (LSTM), Recurrent neural networks (RNN) and Fully connected neural networks (FCNN), and some state-of-the-art deep learning-based prediction tools, including GPS2.1, NetPhos, PPRED, Musite, PhosphoSVM, SKIPHOS, and DeepPhos. Our model achieves a good performance on the training datasets of Serine (S), Threonine (T), and Tyrosine (Y), with AUC values of 0.8579, 0.8335, and 0.6953 using 10-fold cross-validation tests, respectively, and demonstrates that the presented TransPhos tool considerably outperforms competing predictors in general protein phosphorylation site prediction.

Integrated Proteomics-Based Physical and Functional Mapping of AXL Kinase Signaling Pathways and Inhibitors Define Its Role in Cell Migration

To better understand the signaling complexity of AXL, a member of the tumor-associated macrophage (TAM) receptor tyrosine kinase family, we created a physical and functional map of AXL signaling interactions, phosphorylation events, and target-engagement of three AXL tyrosine kinase inhibitors (TKI). We assessed AXL protein complexes using proximity-dependent biotinylation (BioID), effects of AXL TKI on global phosphoproteins using mass spectrometry, and target engagement of AXL TKI using activity-based protein profiling. BioID identifies AXL-interacting proteins that are mostly involved in cell adhesion/migration. Global phosphoproteomics show that AXL inhibition decreases phosphorylation of peptides involved in phosphatidylinositol-mediated signaling and cell adhesion/migration. Comparison of three AXL inhibitors reveals that TKI RXDX-106 inhibits pAXL, pAKT, and migration/invasion of these cells without reducing their viability, while bemcentinib exerts AXL-independent phenotypic effects on viability. Proteomic characterization of these TKIs demonstrates that they inhibit diverse targets in addition to AXL, with bemcentinib having the most off-targets. AXL and EGFR TKI cotreatment did not reverse resistance in cell line models of erlotinib resistance. However, a unique vulnerability was identified in one resistant clone, wherein combination of bemcentinib and erlotinib inhibited cell viability and signaling. We also show that AXL is overexpressed in approximately 30% to 40% of nonsmall but rarely in small cell lung cancer. Cell lines have a wide range of AXL expression, with basal activation detected rarely.

IMPLICATIONS

Our study defines mechanisms of action of AXL in lung cancers which can be used to establish assays to measure drug targetable active AXL complexes in patient tissues and inform the strategy for targeting it's signaling as an anticancer therapy.

DNA-PKcs interacts with and phosphorylates Fis1 to induce mitochondrial fragmentation in tubular cells during acute kidney injury

The catalytic subunit of DNA-dependent protein kinase (DNA-PKcs) regulates cell death. We sought to determine whether DNA-PKcs played a role in the tubular damage that occurs during acute kidney injury (AKI) induced by LPS injection (to mimic sepsis), cisplatin administration, or renal ischemia/reperfusion injury. Although DNA-PKcs normally localizes to the nucleus, we detected cytoplasmic DNA-PKcs in mouse kidney tissues and urinary sediments of human patients with septic AKI. Increased cytoplasmic amounts of DNA-PKcs correlated with renal dysfunction. Tubule cell-specific DNA-PKcs deletion attenuated AKI-mediated tubular cell death and changes in the abundance of various proteins with mitochondrial functions or roles in apoptotic pathways. DNA-PKcs interacted with Fis1 and phosphorylated it at Thr³⁴ in its TQ motif, which increased the affinity of Fis1 for Drp1 and induced mitochondrial fragmentation. Knockin mice expressing a nonphosphorylatable T34A mutant exhibited improved renal function and histological features and reduced mitochondrial fragmentation upon induction of AKI. Phosphorylation of Thr³⁴ in Fis1 was detectable in urinary sediments of human patients with septic AKI and correlated with renal dysfunction. Our findings provide insight into the role of cytoplasmic DNA-PKcs and phosphorylated Fis1 in AKI development.

Identification and in silico Analysis of Nonsense SNPs of Human Colorectal Cancer Protein

Colorectal cancer (CRC) is the third most prevalent disease in the world, with an estimated 1.2 million new cases each year. Spontaneous CRCs account for around 70% of all CRCs, are caused by somatic mutations. Minor variations or single-nucleotide polymorphisms (SNPs) in oncogene or tumor-suppressor genes cause familial CRC. MSH2 and MSH6 genes are located on chromosome 2. These genes products are involved in the repair of DNA replication defects. If these proteins are changed, the replication errors are not rectified, resulting in damaged DNA leading to colorectal cancer. We employed a variety of computational methodologies to find nsSNPs that are harmful to the structure and function of the MSH6 protein and could be causing CRC in our study. SIFT, PROVEAN, Poly- Phen-2, PhD-SNP, and SNPs&GO were among the in silico methods used to do the computational research. According to the findings, mutations of G932Q, E1234Q, and F1104Q are important alterations in native MSH6 protein rs35717727 that may contribute to its dysfunction and, ultimately, disease. The study also provided three-dimensional structures of the native MSH6 protein and mutations. These nsSNPs should be considered as key target mutations in many disorders involving MSH6 dysfunction in future studies. This is the first thorough study to use in silico technologies to assess MSH6 gene variants, and it will be extremely useful in planning largescale investigations and developing precision medicines to treat disorders caused by these polymorphisms. Additionally, animal models of various autoimmune disorders with these mutations could aid in determining their precise involvement.

GPS-Uber: a hybrid-learning framework for prediction of general and E3-specific lysine ubiquitination sites

As an important post-translational modification, lysine ubiquitination participates in numerous biological processes and is involved in human diseases, whereas the site specificity of ubiquitination is mainly decided by ubiquitin-protein ligases (E3s). Although numerous ubiquitination predictors have been developed, computational prediction of E3-specific ubiquitination sites is still a great challenge. Here, we carefully reviewed the existing tools for the prediction of general ubiquitination sites. Also, we developed a tool named GPS-Uber for the prediction of general and E3-specific ubiquitination sites. From the literature, we manually collected 1311 experimentally identified site-specific E3-substrate relations, which were classified into different clusters based on corresponding E3s at different levels. To predict general ubiquitination sites, we integrated 10 types of sequence and structure features, as well as three types of algorithms including penalized logistic regression, deep neural network and convolutional neural network. Compared with other existing tools, the general model in GPS-Uber exhibited a highly competitive accuracy, with an area under curve values of 0.7649. Then, transfer learning was adopted for each E3 cluster to construct E3-specific models, and in total 112 individual E3-specific predictors were implemented. Using GPS-Uber, we conducted a systematic prediction of human cancer-associated ubiquitination events, which could be helpful for further experimental consideration. GPS-Uber will be regularly updated, and its online service is free for academic research at http://gpsuber.biocuckoo.cn/.

USP10 regulates B cell response to SARS-CoV-2 or HIV-1 nanoparticle vaccines through deubiquitinating AID

Activation-induced cytidine deaminase (AID) initiates class-switch recombination and somatic hypermutation (SHM) in antibody genes. Protein expression and activity are tightly controlled by various mechanisms. However, it remains unknown whether a signal from the extracellular environment directly affects the AID activity in the nucleus where it works. Here, we demonstrated that a deubiquitinase USP10, which specifically stabilizes nuclear AID protein, can translocate into the nucleus after AKT-mediated phosphorylation at its T674 within the NLS domain. Interestingly, the signals from BCR and TLR1/2 synergistically promoted this phosphorylation. The deficiency of USP10 in B cells significantly decreased AID protein levels, subsequently reducing neutralizing antibody production after immunization with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) or human immunodeficiency virus type 1 (HIV-1) nanoparticle vaccines. Collectively, we demonstrated that USP10 functions as an integrator for both BCR and TLR signals and directly regulates nuclear AID activity. Its manipulation could be used for the development of vaccines and adjuvants.

A Pretrained ELECTRA Model for Kinase-Specific Phosphorylation Site Prediction

Phosphorylation plays a vital role in signal transduction and cell cycle. Identifying and understanding phosphorylation through machine-learning methods has a long history. However, existing methods only learn representations of a protein sequence segment from a labeled dataset itself, which could result in biased or incomplete features, especially for kinase-specific phosphorylation site prediction in which training data are typically sparse. To learn a comprehensive contextual representation of a protein sequence segment for kinase-specific phosphorylation site prediction, we pretrained our model from over 24 million unlabeled sequence fragments using ELECTRA (Efficiently Learning an Encoder that Classifies Token Replacements Accurately). The pretrained model was applied to kinase-specific site prediction of kinases CDK, PKA, CK2, MAPK, and PKC. The pretrained ELECTRA model achieves 9.02% improvement over BERT and 11.10% improvement over MusiteDeep in the area under the precision-recall curve on the benchmark data.

The Role of the CREB Protein Family Members and the Related Transcription Factors in Radioresistance Mechanisms

In the framework of space flight, the risk of radiation carcinogenesis is considered a "red" risk due to the high likelihood of occurrence as well as the high potential impact on the quality of life in terms of disease-free survival after space missions. The cyclic AMP response element-binding protein (CREB) is overexpressed both in haematological malignancies and solid tumours and its expression and function are modulated following irradiation. The CREB protein is a transcription factor and member of the CREB/activating transcription factor (ATF) family. As such, it has an essential role in a wide range of cell processes, including cell survival, proliferation, and differentiation. Among the CREB-related nuclear transcription factors, NF-κB and p53 have a relevant role in cell response to ionising radiation. Their expression and function can decide the fate of the cell by choosing between death or survival. The aim of this review was to define the role of the CREB/ATF family members and the related transcription factors in the response to ionising radiation of human haematological malignancies and solid tumours.

Responses of JNK signaling pathway to the toxic dinoflagellate Prorocentrum lima in the mussel Perna viridis

Diarrheic shellfish poisoning (DSP) toxins are widely distributed over the world, causing diarrhea, vomiting, and even tumor in human. However, bivalves, the main carrier of the DSP toxins, have some tolerant mechanisms to DSP toxins, though it remains unclear. In this study, we scrutinized the role of Jun N-terminal kinases (JNK) in tolerance of DSP toxins and the relationship between JNK, apoptosis and nuclear factor E2-related factor/antioxidant response element (Nrf2/ARE) pathways. We found that the phosphorylated level of JNK protein was significantly increased both in hemocytes (6 h) and gills (3 h) of the mussel Perna viridis after short-term exposure to DSP toxins-producing dinoflagellate Prorocentrum lima. Exposure of P. lima induced oxidative stress in mussels. Hemocytes and gills displayed different sensitivities to the cytotoxicity of DSP toxins. Exposure of P. lima activated caspase-3 and induced apoptosis in gills but did not induce caspase-3 and apoptosis in hemocytes. The short-term exposure of P. lima could activate Nrf2/ARE signaling pathway in hemocytes (6 h), while longer-term exposure could induce glutathione reductase (GR) expression in hemocytes (96 h) and glutathione-S-transferases (GST) in gills (96 h). Based on the phylogenetic tree of Nrf2, Nrf2 in P. viridis was closely related to that in other mussels, especially Mytilus coruscus, but far from that in Mus musculus. The most likely phosphorylated site of Nrf2 in the mussels P. viridis is threonine 504 for JNK, which is different from that in M. musculus. Taken all together, the tolerant mechanism of P. viridis to DSP toxins might be involved in JNK and Nrf2/ARE signaling pathways, and JNK play a key role in the mechanism. Our findings provide a new clue to further understand tolerant mechanisms of bivalves to DSP toxins.

Site-specific phosphorylation of PSD-95 dynamically regulates the postsynaptic density as observed by phase separation

Postsynaptic density protein 95 is a key scaffolding protein in the postsynaptic density of excitatory glutamatergic neurons, organizing signaling complexes primarily via its three PSD-95/Discs-large/Zona occludens domains. PSD-95 is regulated by phosphorylation, but technical challenges have limited studies of the molecular details. Here, we genetically introduced site-specific phosphorylations in single, tandem, and full-length PSD-95 and generated a total of 11 phosphorylated protein variants. We examined how these phosphorylations affected binding to known interaction partners and the impact on phase separation of PSD-95 complexes and identified two new phosphorylation sites with opposing effects. Phosphorylation of Ser78 inhibited phase separation with the glutamate receptor subunit GluN2B and the auxiliary protein stargazin, whereas phosphorylation of Ser116 induced phase separation with stargazin only. Thus, by genetically introducing phosphoserine site-specifically and exploring the impact on phase separation, we have provided new insights into the regulation of PSD-95 by phosphorylation and the dynamics of the PSD.

MPS1 is involved in the HPV16-E7-mediated centrosomes amplification

Background

It has been reported that the oncoprotein E7 from human papillomavirus type 16 (HPV16-E7) can induce the excessive synthesis of centrosomes through the increase in the expression of PLK4, which is a transcriptional target of E2F1. On the other hand, it has been reported that increasing MPS1 protein stability can also generate an excessive synthesis of centrosomes. In this work, we analyzed the possible role of MPS1 in the amplification of centrosomes mediated by HPV16-E7.

Results

Employing qRT-PCR, Western Blot, and Immunofluorescence techniques, we found that E7 induces an increase in the MPS1 transcript and protein levels in the U2OS cell line, as well as protein stabilization. Besides, we observed that inhibiting the expression of MPS1 in E7 protein-expressing cells leads to a significant reduction in the number of centrosomes.

Conclusions

These results indicate that the presence of the MPS1 protein is necessary for E7 protein to increase the number of centrosomes, and possible implications are discussed.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13008-021-00074-9.

The circadian clock gene circuit controls protein and phosphoprotein rhythms in Arabidopsis thaliana

Twenty-four-hour, circadian rhythms control many eukaryotic mRNA levels, whereas the levels of their more stable proteins are not expected to reflect the RNA rhythms, emphasizing the need to test the circadian regulation of protein abundance and modification. Here we present circadian proteomic and phosphoproteomic time series from Arabidopsis thaliana plants under constant light conditions, estimating that just 0.4% of quantified proteins but a much larger proportion of quantified phospho-sites were rhythmic. Approximately half of the rhythmic phospho-sites were most phosphorylated at subjective dawn, a pattern we term the “phospho-dawn.” Members of the SnRK/CDPK family of protein kinases are candidate regulators. A CCA1-overexpressing line that disables the clock gene circuit lacked most circadian protein phosphorylation. However, the few phospho-sites that fluctuated despite CCA1-overexpression still tended to peak in abundance close to subjective dawn, suggesting that the canonical clock mechanism is necessary for most but perhaps not all protein phosphorylation rhythms. To test the potential functional relevance of our datasets, we conducted phosphomimetic experiments using the bifunctional enzyme fructose-6-phosphate-2-kinase/phosphatase (F2KP), as an example. The rhythmic phosphorylation of diverse protein targets is controlled by the clock gene circuit, implicating posttranslational mechanisms in the transmission of circadian timing information in plants.

•

Circadian (phospho)proteomics time courses of plants with or without functional clock.

•

Most protein abundance/phosphorylation rhythms require a transcriptional oscillator.

•

The majority of rhythmic phosphosites peak around subjective dawn (“phospho-dawn”).

•

A phosphorylated serine of the metabolic enzyme F2KP has functional relevance.

TMEM16A/ANO1: Current Strategies and Novel Drug Approaches for Cystic Fibrosis

Cystic fibrosis (CF) is the most common of rare hereditary diseases in Caucasians, and it is estimated to affect 75,000 patients globally. CF is a complex disease due to the multiplicity of mutations found in the CF transmembrane conductance regulator (CFTR) gene causing the CFTR protein to become dysfunctional. Correctors and potentiators have demonstrated good clinical outcomes for patients with specific gene mutations; however, there are still patients for whom those treatments are not suitable and require alternative CFTR-independent strategies. Although CFTR is the main chloride channel in the lungs, others could, e.g., anoctamin-1 (ANO1 or TMEM16A), compensate for the deficiency of CFTR. This review summarizes the current knowledge on calcium-activated chloride channel (CaCC) ANO1 and presents ANO1 as an exciting target in CF.

P90 ribosomal S6 kinase confers cancer cell survival by mediating checkpoint kinase 1 degradation in response to glucose stress

In solid tumors, cancer cells have devised multiple approaches to survival and proliferate in response to glucose starvation that is often observed in solid tumor microenvironments. However, the precise mechanisms are far less known. Herein, we report that glucose deprivation activates 90‐kDa ribosomal S6 kinase (p90 RSK), a highly conserved Ser/Thr kinase, and activated p90 RSK promotes cancer cell survival. Mechanistically, activated p90 RSK by glucose deprivation phosphorylates checkpoint kinase 1 (CHK1), a key transducer in checkpoint signaling pathways, at Ser280 and triggers CHK1 ubiquitination mediated by SCF^β‐TrCP ubiquitin ligase and proteasomal degradation, subsequently suppressing cancer cell apoptosis induced by glucose deprivation. Importantly, we identified an inverse correlation between p90 RSK activity and CHK1 levels within the solid tumor mass, with lower levels of CHK1 and higher activity of p90 RSK in the center of the tumor where low glucose concentrations are often observed. Thus, our study indicates that p90 RSK promotes CHK1 phosphorylation at Ser280 and its subsequent degradation, which allows cancer cells to escape from checkpoint signals under the stress of glucose deprivation, leading to cell survival and thus contributing to tumorigenesis.

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.

Krüppel-homolog 1 exerts anti-metamorphic and vitellogenic functions in insects via phosphorylation-mediated recruitment of specific cofactors

Background

The zinc-finger transcription factor Krüppel-homolog 1 (Kr-h1) exerts a dual regulatory role during insect development by preventing precocious larval/nymphal metamorphosis and in stimulating aspects of adult reproduction such as vitellogenesis. However, how Kr-h1 functions both as a transcriptional repressor in juvenile metamorphosis and an activator in adult reproduction remains elusive. Here, we use the insect Locusta migratoria to dissect the molecular mechanism by which Kr-h1 functions as activator and repressor at these distinct developmental stages.

Results

We report that the kinase PKCα triggers Kr-h1 phosphorylation at the amino acid residue Ser¹⁵⁴, a step essential for its dual functions. During juvenile stage, phosphorylated Kr-h1 recruits a corepressor, C-terminal binding protein (CtBP). The complex of phosphorylated Kr-h1 and CtBP represses the transcription of Ecdysone induced protein 93F (E93) and consequently prevents the juvenile-to-adult transition. In adult insects, phosphorylated Kr-h1 recruits a coactivator, CREB-binding protein (CBP), and promotes vitellogenesis by inducing the expression of Ribosomal protein L36. Furthermore, Kr-h1 phosphorylation with the concomitant inhibition of E93 transcription is evolutionarily conserved across insect orders.

Conclusion

Our results suggest that Kr-h1 phosphorylation is indispensable for the recruitment of transcriptional cofactors, and for its anti-metamorphic and vitellogenic actions in insects. Our data shed new light on the understanding of Kr-h1 regulation and function in JH-regulated insect metamorphosis and reproduction.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12915-021-01157-3.

NLRP3 phosphorylation in its LRR domain critically regulates inflammasome assembly

NLRP3 controls the secretion of inflammatory cytokines IL-1β/18 and pyroptosis by assembling the inflammasome. Upon coordinated priming and activation stimuli, NLRP3 recruits NEK7 within hetero-oligomers that nucleate ASC and caspase-1 filaments, but the apical molecular mechanisms underlying inflammasome assembly remain elusive. Here we show that NEK7 recruitment to NLRP3 is controlled by the phosphorylation status of NLRP3 S803 located within the interaction surface, in which NLRP3 S803 is phosphorylated upon priming and later dephosphorylated upon activation. Phosphomimetic substitutions of S803 abolish NEK7 recruitment and inflammasome activity in macrophages in vitro and in vivo. In addition, NLRP3-NEK7 binding is also essential for NLRP3 deubiquitination by BRCC3 and subsequently inflammasome assembly, with NLRP3 phosphomimetic mutants showing enhanced ubiquitination and degradation than wildtype NLRP3. Finally, we identify CSNK1A1 as the kinase targeting NLRP3 S803. Our findings thus reveal NLRP3 S803 phosphorylation status as a druggable apical molecular mechanism controlling inflammasome assembly.

Nlrp3 inflammasome activation requires Nek7 recruitment to drive ASC speck formation. Here the authors show how Nlrp3 phosphorylation events control this Nek7 recruitment.

The conformational and mutational landscape of the ubiquitin-like marker for autophagosome formation in cancer

Macroautophagy/autophagy is a cellular process to recycle damaged cellular components, and its modulation can be exploited for disease treatments. A key autophagy player is the ubiquitin-like protein MAP1LC3B/LC3B. Mutations and changes in MAP1LC3B expression occur in cancer samples. However, the investigation of the effects of these mutations on MAP1LC3B protein structure is still missing. Despite many LC3B structures that have been solved, a comprehensive study, including dynamics, has not yet been undertaken. To address this knowledge gap, we assessed nine physical models for biomolecular simulations for their capabilities to describe the structural ensemble of MAP1LC3B. With the resulting MAP1LC3B structural ensembles, we characterized the impact of 26 missense mutations from pan-cancer studies with different approaches, and we experimentally validated our prediction for six variants using cellular assays. Our findings shed light on damaging or neutral mutations in MAP1LC3B, providing an atlas of its modifications in cancer. In particular, P32Q mutation was found detrimental for protein stability with a propensity to aggregation. In a broader context, our framework can be applied to assess the pathogenicity of protein mutations or to prioritize variants for experimental studies, allowing to comprehensively account for different aspects that mutational events alter in terms of protein structure and function.Abbreviations: ATG: autophagy-related; Cα: alpha carbon; CG: coarse-grained; CHARMM: Chemistry at Harvard macromolecular mechanics; CONAN: contact analysis; FUNDC1: FUN14 domain containing 1; FYCO1: FYVE and coiled-coil domain containing 1; GABARAP: GABA type A receptor-associated protein; GROMACS: Groningen machine for chemical simulations; HP: hydrophobic pocket; LIR: LC3 interacting region; MAP1LC3B/LC3B microtubule associated protein 1 light chain 3 B; MD: molecular dynamics; OPTN: optineurin; OSF: open software foundation; PE: phosphatidylethanolamine, PLEKHM1: pleckstrin homology domain-containing family M 1; PSN: protein structure network; PTM: post-translational modification; SA: structural alphabet; SLiM: short linear motif; SQSTM1/p62: sequestosome 1; WT: wild-type.

Molecular and pharmacological characterization of biogenic amine receptors from the diamondback moth, Plutella xylostella

BACKGROUD

Insect biogenic amines play important roles in mediating behavioral and physiological processes. They exert their effects by binding to biogenic amine receptors (BARs), which are specific receptor proteins in the G-protein-coupled receptor superfamily. BAR genes have been cloned and characterized from multiple model insects, including Drosophila melanogaster, Anopheles gambiae, Bombyx mori, Apis mellifera and Tribolium castaneum. However, relatively little work has addressed the molecular properties, expression profiles, and pharmacological characterization of BARs from other insects, including important pests.

RESULTS

In this study, we cloned 17 genes encoding putative biogenic amine receptor proteins from Plutella xylostella, a global pest of Brassica crops. These PxBAR genes were five octopamine receptors (PxOA1, PxOA2B1, PxOA2B2, PxOA2B3, and PxOA3), three tyramine receptors (PxTAR1A, PxTAR1B, and PxTAR2), four dopamine receptors (PxDOP1, PxDOP2, PxDOP3, and PxDopEcR), and five serotonin receptors (Px5-HT_1A , Px5-HT_1B , Px5-HT_2A , Px5-HT_2B , and Px5-HT₇ ). All PxBARs showed considerable sequence identity with orthologous BARs, and phylogenetic analysis clustered the receptors within their respective groups while preserving organismal evolutionary relationships. We investigated their molecular properties and expression profiles, and pharmacologically characterized the dopamine receptor, PxDOP2.

CONCLUSIONS

Our study provides important information and resources on biogenic amine receptors from P. xylostella, which suggests potential target sites for controlling this pest species. © 2021 Society of Chemical Industry.

Aurora a kinase (AURKA) is required for male germline maintenance and regulates sperm motility in the mouse

Aurora A kinase (AURKA) is an important regulator of cell division and is required for assembly of the mitotic spindle. We recently reported the unusual finding that this mitotic kinase is also found on the sperm flagellum. To determine its requirement in spermatogenesis, we generated conditional knockout animals with deletion of the Aurka gene in either spermatogonia or spermatocytes to assess its role in mitotic and postmitotic cells, respectively. Deletion of Aurka in spermatogonia resulted in disappearance of all developing germ cells in the testis, as expected given its vital role in mitotic cell division. Deletion of Aurka in spermatocytes reduced testis size, sperm count, and fertility, indicating disruption of meiosis or an effect on spermiogenesis in developing mice. Interestingly, deletion of Aurka in spermatocytes increased apoptosis in spermatocytes along with an increase in the percentage of sperm with abnormal morphology. Despite the increase in abnormal sperm, sperm from spermatocyte Aurka knockout mice displayed increased progressive motility. In addition, sperm lysate prepared from Aurka knockout animals had decreased protein phosphatase 1 (PP1) activity. Together, our results show that AURKA plays multiple roles in spermatogenesis, from mitotic divisions of spermatogonia to sperm morphology and motility.

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.

Stromal induction of BRD4 phosphorylation Results in Chromatin Remodeling and BET inhibitor Resistance in Colorectal Cancer

BRD4, a Bromodomain and Extraterminal (BET) protein family member, is a promising anti-cancer drug target. However, resistance to BET inhibitors targeting BRD4 is common in solid tumors. Here, we show that cancer-associated fibroblast (CAF)-activated stromal signaling, interleukin-6/8-JAK2, induces BRD4 phosphorylation at tyrosine 97/98 in colorectal cancer, resulting in BRD4 stabilization due to interaction with the deubiquitinase UCHL3. BRD4 phosphorylation at tyrosine 97/98 also displays increased binding to chromatin but reduced binding to BET inhibitors, resulting in resistance to BET inhibitors. We further show that BRD4 phosphorylation promotes interaction with STAT3 to induce chromatin remodeling through concurrent binding to enhancers and super-enhancers, supporting a tumor-promoting transcriptional program. Inhibition of IL6/IL8-JAK2 signaling abolishes BRD4 phosphorylation and sensitizes BET inhibitors in vitro and in vivo. Our study reveals a stromal mechanism for BRD4 activation and BET inhibitor resistance, which provides a rationale for developing strategies to treat CRC more effectively.

BRD4 has a pro-tumorigenic role but non-cell-autonomous mechanisms of BRD4 activation need to be elucidated. Here the authors unravel a mechanism by which CAFs activate BRD4 and induce resistance to BET inhibitors in cancer cells through IL6/IL8 signaling.

Metformin activates chaperone-mediated autophagy and improves disease pathologies in an Alzheimer disease mouse model

Chaperone-mediated autophagy (CMA) is a lysosome-dependent selective degradation pathway implicated in the pathogenesis of cancer and neurodegenerative diseases. However, the mechanisms that regulate CMA are not fully understood. Here, using unbiased drug screening approaches, we discover Metformin, a drug that is commonly the first medication prescribed for type 2 diabetes, can induce CMA. We delineate the mechanism of CMA induction by Metformin to be via activation of TAK1-IKKα/β signaling that leads to phosphorylation of Ser85 of the key mediator of CMA, Hsc70, and its activation. Notably, we find that amyloid-beta precursor protein (APP) is a CMA substrate and that it binds to Hsc70 in an IKKα/β-dependent manner. The inhibition of CMA-mediated degradation of APP enhances its cytotoxicity. Importantly, we find that in the APP/PS1 mouse model of Alzheimer’s disease (AD), activation of CMA by Hsc70 overexpression or Metformin potently reduces the accumulated brain Aβ plaque levels and reverses the molecular and behavioral AD phenotypes. Our study elucidates a novel mechanism of CMA regulation via Metformin-TAK1-IKKα/β-Hsc70 signaling and suggests Metformin as a new activator of CMA for diseases, such as AD, where such therapeutic intervention could be beneficial.