Systematic analysis of the in situ crosstalk of tyrosine modifications reveals no additional natural selection on multiply modified residues

HIV-1 neutralizing antibodies in SHIV-infected macaques recapitulate structurally divergent modes of human V2 apex recognition with a single D gene

Broadly neutralizing antibodies targeting the V2 apex of the HIV-1 envelope trimer are among the most common specificities elicited in HIV-1-infected humans and simian-human immunodeficiency virus (SHIV)-infected macaques. To gain insight into the prevalent induction of these antibodies, we isolated and characterized 11 V2 apex-directed neutralizing antibody lineages from SHIV-infected rhesus macaques. Remarkably, all SHIV-induced V2 apex lineages were derived from reading frame two of the rhesus DH3-15*01 gene. Cryo-EM structures of envelope trimers in complex with antibodies from nine rhesus lineages revealed modes of recognition that mimicked three canonical human V2 apex-recognition modes. Notably, amino acids encoded by DH3-15*01 played divergent structural roles, inserting into a hole at the trimer apex, H-bonding to an exposed strand, or forming part of a loop scaffold. Overall, we identify a DH3-15*01-signature for rhesus V2 apex broadly neutralizing antibodies and show that highly selected genetic elements can play multiple roles in antigen recognition.

Highlights

Isolated 11 V2 apex-targeted HIV-neutralizing lineages from 10 SHIV-infected Indian-origin rhesus macaquesCryo-EM structures of Fab-Env complexes for nine rhesus lineages reveal modes of recognition that mimic three modes of human V2 apex antibody recognitionAll SHIV-elicited V2 apex lineages, including two others previously published, derive from the same DH3-15*01 gene utilizing reading frame twoThe DH3-15*01 gene in reading frame two provides a necessary, but not sufficient, signature for V2 apex-directed broadly neutralizing antibodiesStructural roles played by DH3-15*01-encoded amino acids differed substantially in different lineages, even for those with the same recognition modePropose that the anionic, aromatic, and extended character of DH3-15*01 in reading frame two provides a selective advantage for V2 apex recognition compared to B cells derived from other D genes in the naïve rhesus repertoireDemonstrate that highly selected genetic elements can play multiple roles in antigen recognition, providing a structural means to enhance recognition diversity.

Enhanced SLC35B2/SAV1 sulfation axis promotes tumor growth by inhibiting Hippo signaling in HCC

BACKGROUND AND AIMS

Protein tyrosine sulfation (PTS) is a common posttranslational modification that regulates a variety of physiological and pathological processes. However, the role of PTS in cancer remains poorly understood. The goal of this study was to determine whether and how PTS plays a role in HCC progression.

APPROACH AND RESULTS

By mass spectrometry and bioinformatics analysis, we identified SAV1 as a novel substrate of PTS in HCC. Oxidative stress upregulates the transcription of SLC35B2, a Golgi-resident transporter of sulfate donor 3'-phosphoadenosine 5'-phosphosulfate, leading to increased sulfation of SAV1. Sulfation of SAV1 disrupts the formation of the SAV1-MST1 complex, resulting in a decrease of MST1 phosphorylation and subsequent inactivation of Hippo signaling. These molecular events ultimately foster the growth of HCC cells both in vivo and in vitro. Moreover, SLC35B2 is a novel transcription target gene of the Hippo pathway, constituting a positive feedback loop that facilitates HCC progression under oxidative stress.

CONCLUSIONS

Our findings reveal a regulatory mechanism of the SLC35B2/SAV1 sulfation axis in response to oxidative stress, highlighting its potential as a promising therapeutic target for HCC.

Sulfoproteomics Workflow with Precursor Ion Accurate Mass Shift Analysis Reveals Novel Tyrosine Sulfoproteins in the Golgi

Tyrosine sulfation in the Golgi of secreted and membrane proteins is an important post-translational modification (PTM). However, its labile nature has limited analysis by mass spectrometry (MS), a major reason why no sulfoproteome studies have been previously reported. Here, we show that a phosphoproteomics experimental workflow, which includes serial enrichment followed by high resolution, high mass accuracy MS, and tandem MS (MS/MS) analysis, enables sulfopeptide coenrichment and identification via accurate precursor ion mass shift open MSFragger database search. This approach, supported by manual validation, allows the confident identification of sulfotyrosine-containing peptides in the presence of high levels of phosphorylated peptides, thus enabling these two sterically and ionically similar isobaric PTMs to be distinguished and annotated in a single proteomic analysis. We applied this approach to isolated interphase and mitotic rat liver Golgi membranes and identified 67 tyrosine sulfopeptides, corresponding to 26 different proteins. This work discovered 23 new sulfoproteins with functions related to, for example, Ca2+-binding, glycan biosynthesis, and exocytosis. In addition, we report the first preliminary evidence for crosstalk between sulfation and phosphorylation in the Golgi, with implications for functional control.

Inhibition of the SLC35B2-TPST2 Axis of Tyrosine Sulfation Attenuates the Growth and Metastasis of Pancreatic Ductal Adenocarcinom

BACKGROUND & AIMS

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer deaths in the United States. Tyrosine sulfation, catalyzed by the tyrosylprotein sulfotransferase 2 (TPST2), is a post-translational modification essential for protein-protein interactions and cellular functions. Solute carrier family 35 member B (SLC35B2) is a key transporter that transports the universal sulfate donor 3'-phosphoadenosine 5'-phosphosulfate into the Golgi apparatus where the protein sulfation occurs. The goal of this study was to determine whether and how the SLC35B2-TPST2 axis of tyrosine sulfation plays a role in PDAC.

METHODS

Gene expression was analyzed in PDAC patients and mice. Human PDAC MIA PaCa-2 and PANC-1 cells were used for in vitro studies. TPST2-deficient MIA PaCa-2 cells were generated to assess xenograft tumor growth in vivo. Mouse PDAC cells derived from the KrasLSL-G12D/+;Tp53L/+;Pdx1-Cre (KPC) mice were used to generate Tpst2 knockout KPC cells to evaluate tumor growth and metastasis in vivo.

RESULTS

High expressions of SLC35B2 and TPST2 were correlated with poor PDAC patient survival. Knocking down SLC35B2 or TPST2, or pharmacologicically inhibiting sulfation, resulted in the inhibition of PDAC cell proliferation and migration in vitro. TPST2-deficient MIA PaCa-2 cells showed inhibited xenograft tumor growth. Orthotopic inoculation of Tpst2 knockout KPC cells in mice showed inhibition of primary tumor growth, local invasion, and metastasis. Mechanistically, the integrin β4 was found to be a novel substrate of TPST2. Inhibition of sulfation destabilizes integrin β4 protein, which may have accounted for the suppression of metastasis.

CONCLUSIONS

Targeting the SLC35B2-TPST2 axis of tyrosine sulfation may represent a novel approach for therapeutic intervention of PDAC.

A Germline-Targeting Chimpanzee SIV Envelope Glycoprotein Elicits a New Class of V2-Apex Directed Cross-Neutralizing Antibodies

HIV-1 and its SIV precursors share a broadly neutralizing antibody (bNAb) epitope in variable loop 2 (V2) at the envelope glycoprotein (Env) trimer apex. Here, we tested the immunogenicity of germ line-targeting versions of a chimpanzee SIV (SIVcpz) Env in human V2-apex bNAb heavy-chain precursor-expressing knock-in mice and as chimeric simian-chimpanzee immunodeficiency viruses (SCIVs) in rhesus macaques (RMs). Trimer immunization of knock-in mice induced V2-directed NAbs, indicating activation of V2-apex bNAb precursor-expressing mouse B cells. SCIV infection of RMs elicited high-titer viremia, potent autologous tier 2 neutralizing antibodies, and rapid sequence escape in the canonical V2-apex epitope. Six of seven animals also developed low-titer heterologous plasma breadth that mapped to the V2-apex. Antibody cloning from two of these animals identified multiple expanded lineages with long heavy chain third complementarity determining regions that cross-neutralized as many as 7 of 19 primary HIV-1 strains, but with low potency. Negative stain electron microscopy (NSEM) of members of the two most cross-reactive lineages confirmed V2 targeting but identified an angle of approach distinct from prototypical V2-apex bNAbs, with antibody binding either requiring or inducing an occluded-open trimer. Probing with conformation-sensitive, nonneutralizing antibodies revealed that SCIV-expressed, but not wild-type SIVcpz Envs, as well as a subset of primary HIV-1 Envs, preferentially adopted a more open trimeric state. These results reveal the existence of a cryptic V2 epitope that is exposed in occluded-open SIVcpz and HIV-1 Env trimers and elicits cross-neutralizing responses of limited breadth and potency. IMPORTANCE An effective HIV-1 vaccination strategy will need to stimulate rare precursor B cells of multiple bNAb lineages and affinity mature them along desired pathways. Here, we searched for V2-apex germ line-targeting Envs among a large set of diverse primate lentiviruses and identified minimally modified versions of one chimpanzee SIV Env that bound several human V2-apex bNAb precursors and stimulated one of these in a V2-apex bNAb precursor-expressing knock-in mouse. We also generated chimeric simian-chimpanzee immunodeficiency viruses and showed that they elicit low-titer V2-directed heterologous plasma breadth in six of seven infected rhesus macaques. Characterization of this antibody response identified a new class of weakly cross-reactive neutralizing antibodies that target the V2-apex, but only in occluded-open Env trimers. The existence of this cryptic epitope, which in some Env backgrounds is immunodominant, needs to be considered in immunogen design.

"Glyco-sulfo barcodes" regulate chemokine receptor function

Chemokine ligands and receptors regulate the directional migration of leukocytes. Post-translational modifications of chemokine receptors including O-glycosylation and tyrosine sulfation have been reported to regulate ligand binding and resulting signaling. Through in silico analyses, we determined potential conserved O-glycosylation and sulfation sites on human and murine CC chemokine receptors. Glyco-engineered CHO cell lines were used to measure the impact of O-glycosylation on CC chemokine receptor CCR5, while mutation of tyrosine residues and treatment with sodium chlorate were performed to determine the effect of tyrosine sulfation. Changing the glycosylation or tyrosine sulfation on CCR5 reduced the receptor signaling by the more positively charged CCL5 and CCL8 more profoundly compared to the less charged CCL3. The loss of negatively charged sialic acids resulted only in a minor effect on CCL3-induced signal transduction. The enzymes GalNAc-T1 and GalNAc-T11 were shown to be involved in the process of chemokine receptor O-glycosylation. These results indicate that O-glycosylation and tyrosine sulfation are involved in the fine-tuning and recognition of chemokine interactions with CCR5 and the resulting signaling.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

Posttranslational modifications (PTMs) are an integral component to how cells respond to perturbation. While experimental advances have enabled improved PTM identification capabilities, the same throughput for characterizing how structural changes caused by PTMs equate to altered physiological function has not been maintained. In this Perspective, we cover the history of computational modeling and molecular dynamics simulations which have characterized the structural implications of PTMs. We distinguish results from different molecular dynamics studies based upon the timescales simulated and analysis approaches used for PTM characterization. Lastly, we offer insights into how opportunities for modern research efforts on in silico PTM characterization may proceed given current state-of-the-art computing capabilities and methodological advancements.

Engineering of HIV-1 neutralizing antibody CAP256V2LS for manufacturability and improved half life

The broadly neutralizing antibody (bNAb) CAP256-VRC26.25 has exceptional potency against HIV-1 and has been considered for clinical use. During the characterization and production of this bNAb, we observed several unusual features. First, the antibody appeared to adhere to pipette tips, requiring tips to be changed during serial dilution to accurately measure potency. Second, during production scale-up, proteolytic cleavage was discovered to target an extended heavy chain loop, which was attributed to a protease in spent medium from 2-week culture. To enable large scale production, we altered the site of cleavage via a single amino acid change, K100mA. The resultant antibody retained potency and breadth while avoiding protease cleavage. We also added the half-life extending mutation LS, which improved the in vivo persistence in animal models, but did not impact neutralization activity; we observed the same preservation of neutralization for bNAbs VRC01, N6, and PGDM1400 with LS on a 208-virus panel. The final engineered antibody, CAP256V2LS, retained the extraordinary neutralization potency of the parental antibody, had a favorable pharmacokinetic profile in animal models, and was negative in in vitro assessment of autoreactivity. CAP256V2LS has the requisite potency, developability and suitability for scale-up, allowing its advancement as a clinical candidate.

Targeting the YXXΦ Motifs of the SARS Coronaviruses 1 and 2 ORF3a Peptides by In Silico Analysis to Predict Novel Virus-Host Interactions

The emerging SARS-CoV and SARS-CoV-2 belong to the family of "common cold" RNA coronaviruses, and they are responsible for the 2003 epidemic and the current pandemic with over 6.3 M deaths worldwide. The ORF3a gene is conserved in both viruses and codes for the accessory protein ORF3a, with unclear functions, possibly related to viral virulence and pathogenesis. The tyrosine-based YXXΦ motif (Φ: bulky hydrophobic residue-L/I/M/V/F) was originally discovered to mediate clathrin-dependent endocytosis of membrane-spanning proteins. Many viruses employ the YXXΦ motif to achieve efficient receptor-guided internalisation in host cells, maintain the structural integrity of their capsids and enhance viral replication. Importantly, this motif has been recently identified on the ORF3a proteins of SARS-CoV and SARS-CoV-2. Given that the ORF3a aa sequence is not fully conserved between the two SARS viruses, we aimed to map in silico structural differences and putative sequence-driven alterations of regulatory elements within and adjacently to the YXXΦ motifs that could predict variations in ORF3a functions. Using robust bioinformatics tools, we investigated the presence of relevant post-translational modifications and the YXXΦ motif involvement in protein-protein interactions. Our study suggests that the predicted YXXΦ-related features may confer specific-yet to be discovered-functions to ORF3a proteins, significant to the new virus and related to enhanced propagation, host immune regulation and virulence.

PhosVarDeep: deep-learning based prediction of phospho-variants using sequence information

Human DNA sequencing has revealed numerous single nucleotide variants associated with complex diseases. Researchers have shown that these variants have potential effects on protein function, one of which is to disrupt protein phosphorylation. Based on conventional machine learning algorithms, several computational methods for predicting phospho-variants have been developed, but their performance still leaves considerable room for improvement. In recent years, deep learning has been successfully applied in biological sequence analysis with its efficient sequence pattern learning ability, which provides a powerful tool for improving phospho-variant prediction based on protein sequence information. In the study, we present PhosVarDeep, a novel unified deep-learning framework for phospho-variant prediction. PhosVarDeep takes reference and variant sequences as inputs and adopts a Siamese-like CNN architecture containing two identical subnetworks and a prediction module. In each subnetwork, general phosphorylation sequence features are extracted by a pre-trained sequence feature encoding network and then fed into a CNN module for capturing variant-aware phosphorylation sequence features. After that, a prediction module is introduced to integrate the outputs of the two subnetworks and generate the prediction results of phospho-variants. Comprehensive experimental results on phospho-variant data demonstrates that our method significantly improves the prediction performance of phospho-variants and compares favorably with existing conventional machine learning methods.

Human transitional and IgMlow mature naïve B cells preserve permissive B-cell receptors

The level of immunoglobulin M (IgM) displayed on the surface of peripheral blood B cells exhibits a broad dynamic range and has been associated with both development and selection. To determine whether IgM surface expression associates with distinct immunoglobulin heavy‐chain (IGH) repertoire properties, we performed deep IgM sequencing of peripheral blood transitional and mature naïve B cells in the upper and lower quartiles of surface IgM expression for 12 healthy donors. Mature naïve B cells within the lowest quartile for surface IgM expression displayed more diverse IGH features including increased complementarity‐determining region 3 length, IGHJ6 segment usage and aromatic amino acids compared with mature naïve B cells with high surface IgM. There were no differences between IGH repertoires for transitional B cells with high or low surface IgM. These findings suggest that a selection checkpoint during progression of transitional to mature naïve B cells reduces the breadth of the IGH repertoire among high surface IgM B cells but that diversity is preserved in B cells expressing low levels of surface IgM.

Overexpression of MdCPK1a gene, a calcium dependent protein kinase in apple, increase tobacco cold tolerance via scavenging ROS accumulation

Calcium-dependent protein kinases (CDPKs) are important calcium receptors, which play a crucial part in the process of sensing and decoding intracellular calcium signals during plant development and adaptation to various environmental stresses. In this study, a CDPK gene MdCPK1a, was isolated from apple (Malus×domestica) which contains 1701bp nucleotide and encodes a protein of 566 amino acid residues, and contains the conserved domain of CDPKs. The transient expression and western blot experiment showed that MdCPK1a protein was localized in the nucleus and cell plasma membrane. Ectopic expression of MdCPK1a in Nicotiana benthamiana increased the resistance of the tobacco plants to salt and cold stresses. The mechanism of MdCPK1a regulating cold resistance was further investigated. The overexpressed MdCPK1a tobacco plants had higher survival rates and longer root length than wild type (WT) plants under cold stress, and the electrolyte leakages (EL), the content of malondialdehyde (MDA) and reactive oxygen species (ROS) were lower, and accordingly, antioxidant enzyme activities, such as superoxide dismutase (SOD), peroxidase (POD) and catalase (CAT) were higher, suggesting the transgenic plants suffered less chilling injury than WT plants. Moreover, the transcript levels of ROS-scavenging and stress-related genes were higher in the transgenic plants than those in WT plants whether under normal conditions or cold stress. The above results suggest that the improvement of cold tolerance in MdCPK1a-overexpressed plants was due to scavenging ROS accumulation and modulating the expression of stress-related genes.

DeepPhos: prediction of protein phosphorylation sites with deep learning

Motivation

Phosphorylation is the most studied post-translational modification, which is crucial for multiple biological processes. Recently, many efforts have been taken to develop computational predictors for phosphorylation site prediction, but most of them are based on feature selection and discriminative classification. Thus, it is useful to develop a novel and highly accurate predictor that can unveil intricate patterns automatically for protein phosphorylation sites.

Results

In this study we present DeepPhos, a novel deep learning architecture for prediction of protein phosphorylation. Unlike multi-layer convolutional neural networks, DeepPhos consists of densely connected convolutional neuron network blocks which can capture multiple representations of sequences to make final phosphorylation prediction by intra block concatenation layers and inter block concatenation layers. DeepPhos can also be used for kinase-specific prediction varying from group, family, subfamily and individual kinase level. The experimental results demonstrated that DeepPhos outperforms competitive predictors in general and kinase-specific phosphorylation site prediction.

Availability and implementation

The source code of DeepPhos is publicly deposited at https://github.com/USTCHIlab/DeepPhos.

Supplementary information

Supplementary data are available at Bioinformatics online.

mUSP: a high-accuracy map of the in situ crosstalk of ubiquitylation and SUMOylation proteome predicted via the feature enhancement approach

Reversible post-translational modification (PTM) orchestrates various biological processes by changing the properties of proteins. Since many proteins are multiply modified by PTMs, identification of PTM crosstalk site has emerged to be an intriguing topic and attracted much attention. In this study, we systematically deciphered the in situ crosstalk of ubiquitylation and SUMOylation that co-occurs on the same lysine residue. We first collected 3363 ubiquitylation-SUMOylation (UBS) crosstalk site on 1302 proteins and then investigated the prime sequence motifs, the local evolutionary degree and the distribution of structural annotations at the residue and sequence levels between the UBS crosstalk and the single modification sites. Given the properties of UBS crosstalk sites, we thus developed the mUSP classifier to predict UBS crosstalk site by integrating different types of features with two-step feature optimization by recursive feature elimination approach. By using various cross-validations, the mUSP model achieved an average area under the curve (AUC) value of 0.8416, indicating its promising accuracy and robustness. By comparison, the mUSP has significantly better performance with the improvement of 38.41 and 51.48% AUC values compared to the cross-results by the previous single predictor. The mUSP was implemented as a web server available at http://bioinfo.ncu.edu.cn/mUSP/index.html to facilitate the query of our high-accuracy UBS crosstalk results for experimental design and validation.

Functional Proteomic Analysis to Characterize Signaling Crosstalk

The biological activities of a cell are determined by its response to external stimuli. The signals are transduced from either intracellular or extracellular milieu through networks of multi-protein complexes and post-translational modifications of proteins (PTMs). Most PTMs including phosphorylation, acetylation, ubiquitination, and SUMOylation, among others, modulate activities of proteins and regulate biological processes such as proliferation, differentiation, as well as host pathogen interaction. Conventionally, reverse genetics analysis and single molecule-based studies were employed to identify and characterize the function of PTMs and enzyme-substrate networks regulated by them. With the advent of high-throughput technologies, it is now possible to identify and quantify thousands of PTM sites in a single experiment. Here, we discuss recent advances in enrichment strategies of various PTMs. We also describe a method for the identification and relative quantitation of proteins using a tandem mass tag labeling approach combined with serial enrichment of phosphorylation, acetylation and succinylation using antibody enrichment strategy.

New insights into the heat responses of grape leaves via combined phosphoproteomic and acetylproteomic analyses

Heat stress is a serious and widespread threat to the quality and yield of many crop species, including grape (Vitis vinifera L.), which is cultivated worldwide. Here, we conducted phosphoproteomic and acetylproteomic analyses of leaves of grape plants cultivated under four distinct temperature regimes. The phosphorylation or acetylation of a total of 1011 phosphoproteins with 1828 phosphosites and 96 acetyl proteins with 148 acetyl sites changed when plants were grown at 35 °C, 40 °C, and 45 °C in comparison with the proteome profiles of plants grown at 25 °C. The greatest number of changes was observed at the relatively high temperatures. Functional classification and enrichment analysis indicated that phosphorylation, rather than acetylation, of serine/arginine-rich splicing factors was involved in the response to high temperatures. This finding is congruent with previous observations by which alternative splicing events occurred more frequently in grapevine under high temperature. Changes in acetylation patterns were more common than changes in phosphorylation patterns in photosynthesis-related proteins at high temperatures, while heat-shock proteins were associated more with modifications involving phosphorylation than with those involving acetylation. Nineteen proteins were identified with changes associated with both phosphorylation and acetylation, which is consistent with crosstalk between these posttranslational modification types.

Recent advances in phosphoproteomics and application to neurological diseases

Phosphorylation has an incredible impact on the biological behavior of proteins, altering everything from intrinsic activity to cellular localization and complex formation. It is no surprise then that this post-translational modification has been the subject of intense study and that, with the advent of faster, more accurate instrumentation, the number of large-scale mass spectrometry-based phosphoproteomic studies has swelled over the past decade. Recent developments in sample preparation, phosphorylation enrichment, quantification, and data analysis strategies permit both targeted and ultra-deep phosphoproteome profiling, but challenges remain in pinpointing biologically relevant phosphorylation events. We describe here technological advances that have facilitated phosphoproteomic analysis of cells, tissues, and biofluids and note applications to neuropathologies in which the phosphorylation machinery may be dysregulated, much as it is in cancer.

A novel chlorination-induced ribonuclease YabJ from Staphylococcus aureus

The characteristic fold of a protein is the decisive factor for its biological function. However, small structural changes to amino acids can also affect their function, for example in the case of post-translational modification (PTM). Many different types of PTMs are known, but for some, including chlorination, studies elucidating their importance are limited. A recent study revealed that the YjgF/YER057c/UK114 family (YjgF family) member RidA from Escherichia coli shows chaperone activity after chlorination. Thus, to identify the functional and structural differences of RidA upon chlorination, we studied an RidA homolog from Staphylococcus aureus: YabJ. The overall structure of S. aureus YabJ was similar to other members of the YjgF family, showing deep pockets on its surface, and the residues composing the pockets were well conserved. S. aureus YabJ was highly stable after chlorination, and the chlorinated state is reversible by treatment with DTT. However, it shows no chaperone activity after chlorination. Instead, YabJ from S. aureus shows chlorination-induced ribonuclease activity, and the activity is diminished after subsequent reduction. Even though the yabJ genes from Staphylococcus and Bacillus are clustered with regulators that are expected to code nucleic acid-interacting proteins, the nucleic acid-related activity of bacterial RidA has not been identified before. From our study, we revealed the structure and function of S. aureus YabJ as a novel chlorination-activated ribonuclease. The present study will contribute to an in-depth understanding of chlorination as a PTM.

SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites

Protein S-sulfenylation, which results from oxidation of free thiols on cysteine residues, has recently emerged as an important post-translational modification that regulates the structure and function of proteins involved in a variety of physiological and pathological processes. By altering the size and physiochemical properties of modified cysteine residues, sulfenylation can impact the cellular function of proteins in several different ways. Thus, the ability to rapidly and accurately identify putative sulfenylation sites in proteins will provide important insights into redox-dependent regulation of protein function in a variety of cellular contexts. Though bottom-up proteomic approaches, such as tandem mass spectrometry (MS/MS), provide a wealth of information about global changes in the sulfenylation state of proteins, MS/MS-based experiments are often labor-intensive, costly and technically challenging. Therefore, to complement existing proteomic approaches, researchers have developed a series of computational tools to identify putative sulfenylation sites on proteins. However, existing methods often suffer from low accuracy, specificity, and/or sensitivity. In this study, we developed SVM-SulfoSite, a novel sulfenylation prediction tool that uses support vector machines (SVM) to identify key determinants of sulfenylation among five feature classes: binary code, physiochemical properties, k-space amino acid pairs, amino acid composition and high-quality physiochemical indices. Using 10-fold cross-validation, SVM-SulfoSite achieved 95% sensitivity and 83% specificity, with an overall accuracy of 89% and Matthew’s correlation coefficient (MCC) of 0.79. Likewise, using an independent test set of experimentally identified sulfenylation sites, our method achieved scores of 74%, 62%, 80% and 0.42 for accuracy, sensitivity, specificity and MCC, with an area under the receiver operator characteristic (ROC) curve of 0.81. Moreover, in side-by-side comparisons, SVM-SulfoSite performed as well as or better than existing sulfenylation prediction tools. Together, these results suggest that our method represents a robust and complementary technique for advanced exploration of protein S-sulfenylation.

A disordered acidic domain in GPIHBP1 harboring a sulfated tyrosine regulates lipoprotein lipase

The intravascular processing of triglyceride-rich lipoproteins depends on lipoprotein lipase (LPL) and GPIHBP1, a membrane protein of endothelial cells that binds LPL within the subendothelial spaces and shuttles it to the capillary lumen. In the absence of GPIHBP1, LPL remains mislocalized within the subendothelial spaces, causing severe hypertriglyceridemia (chylomicronemia). The N-terminal domain of GPIHBP1, an intrinsically disordered region (IDR) rich in acidic residues, is important for stabilizing LPL's catalytic domain against spontaneous and ANGPTL4-catalyzed unfolding. Here, we define several important properties of GPIHBP1's IDR. First, a conserved tyrosine in the middle of the IDR is posttranslationally modified by O-sulfation; this modification increases both the affinity of GPIHBP1-LPL interactions and the ability of GPIHBP1 to protect LPL against ANGPTL4-catalyzed unfolding. Second, the acidic IDR of GPIHBP1 increases the probability of a GPIHBP1-LPL encounter via electrostatic steering, increasing the association rate constant (k_on) for LPL binding by >250-fold. Third, we show that LPL accumulates near capillary endothelial cells even in the absence of GPIHBP1. In wild-type mice, we expect that the accumulation of LPL in close proximity to capillaries would increase interactions with GPIHBP1. Fourth, we found that GPIHBP1's IDR is not a key factor in the pathogenicity of chylomicronemia in patients with the GPIHBP1 autoimmune syndrome. Finally, based on biophysical studies, we propose that the negatively charged IDR of GPIHBP1 traverses a vast space, facilitating capture of LPL by capillary endothelial cells and simultaneously contributing to GPIHBP1's ability to preserve LPL structure and activity.

PTM-ssMP: A Web Server for Predicting Different Types of Post-translational Modification Sites Using Novel Site-specific Modification Profile

Protein post-translational modifications (PTMs) are chemical modifications of a protein after its translation. Owing to its play an important role in deep understanding of various biological processes and the development of effective drugs, PTM site prediction have become a hot topic in bioinformatics. Recently, many online tools are developed to prediction various types of PTM sites, most of which are based on local sequence and some biological information. However, few of existing tools consider the relations between different PTMs for their prediction task. Here, we develop a web server called PTM-ssMP to predict PTM site, which adopts site-specific modification profile (ssMP) to efficiently extract and encode the information of both proximal PTMs and local sequence simultaneously. In PTM-ssMP we provide efficient prediction of multiple types of PTM site including phosphorylation, lysine acetylation, ubiquitination, sumoylation, methylation, O-GalNAc, O-GlcNAc, sulfation and proteolytic cleavage. To assess the performance of PTM-ssMP, a large number of experimentally verified PTM sites are collected from several sources and used to train and test the prediction models. Our results suggest that ssMP consistently contributes to remarkable improvement of prediction performance. In addition, results of independent tests demonstrate that PTM-ssMP compares favorably with other existing tools for different PTM types. PTM-ssMP is implemented as an online web server with user-friendly interface, which is freely available at http://bioinformatics.ustc.edu.cn/PTM-ssMP/index/.

Proteomic analysis and prediction of amino acid variations that influence protein posttranslational modifications

Accumulative studies have indicated that amino acid variations through changing the type of residues of the target sites or key flanking residues could directly or indirectly influence protein posttranslational modifications (PTMs) and bring about a detrimental effect on protein function. Computational mutation analysis can greatly narrow down the efforts on experimental work. To increase the utilization of current computational resources, we first provide an overview of computational prediction of amino acid variations that influence protein PTMs and their functional analysis. We also discuss the challenges that are faced while developing novel in silico approaches in the future. The development of better methods for mutation analysis-related protein PTMs will help to facilitate the development of personalized precision medicine.

HIV Envelope Glycoform Heterogeneity and Localized Diversity Govern the Initiation and Maturation of a V2 Apex Broadly Neutralizing Antibody Lineage

Understanding how broadly neutralizing antibodies (bnAbs) to HIV envelope (Env) develop during natural infection can help guide the rational design of an HIV vaccine. Here, we described a bnAb lineage targeting the Env V2 apex and the Ab-Env co-evolution that led to development of neutralization breadth. The lineage Abs bore an anionic heavy chain complementarity-determining region 3 (CDRH3) of 25 amino acids, among the shortest known for this class of Abs, and achieved breadth with only 10% nucleotide somatic hypermutation and no insertions or deletions. The data suggested a role for Env glycoform heterogeneity in the activation of the lineage germline B cell. Finally, we showed that localized diversity at key V2 epitope residues drove bnAb maturation toward breadth, mirroring the Env evolution pattern described for another donor who developed V2-apex targeting bnAbs. Overall, these findings suggest potential strategies for vaccine approaches based on germline-targeting and serial immunogen design.

The rice cold-responsive calcium-dependent protein kinase OsCPK17 is regulated by alternative splicing and post-translational modifications

Plant calcium-dependent protein kinases (CDPKs) are key proteins implicated in calcium-mediated signaling pathways of a wide range of biological events in the organism. The action of each particular CDPK is strictly regulated by many mechanisms in order to ensure an accurate signal translation and the activation of the adequate response processes. In this work, we investigated the regulation of a CDPK involved in rice cold stress response, OsCPK17, to better understand its mode of action. We identified two new alternative splicing (AS) mRNA forms of OsCPK17 encoding truncated versions of the protein, missing the CDPK activation domain. We analyzed the expression patterns of all AS variants in rice tissues and examined their subcellular localization in onion epidermal cells. The results indicate that the AS of OsCPK17 putatively originates truncated forms of the protein with distinct functions, and different subcellular and tissue distributions. Additionally, we addressed the regulation of OsCPK17 by post-translational modifications in several in vitro experiments. Our analysis indicated that OsCPK17 activity depends on its structural rearrangement induced by calcium binding, and that the protein can be autophosphorylated. The identified phosphorylation sites mostly populate the OsCPK17 N-terminal domain. Exceptions are phosphosites T107 and S136 in the kinase domain and S558 in the C-terminal domain. These phosphosites seem conserved in CDPKs and may reflect a common regulatory mechanism for this protein family.

Understanding the chemically-reactive proteome

The reactivity of amino acid residues in proteins is context-dependent and difficult to predict. Chemical biology can be used to understand the chemical modifications of proteins to help elucidate the nature of the reactive proteome. The resulting insights can be applied to pharmacoproteomics, target identification and molecular pathology.

Prediction of post-translational modification sites using multiple kernel support vector machine

Protein post-translational modification (PTM) is an important mechanism that is involved in the regulation of protein function. Considering the high-cost and labor-intensive of experimental identification, many computational prediction methods are currently available for the prediction of PTM sites by using protein local sequence information in the context of conserved motif. Here we proposed a novel computational method by using the combination of multiple kernel support vector machines (SVM) for predicting PTM sites including phosphorylation, O-linked glycosylation, acetylation, sulfation and nitration. To largely make use of local sequence information and site-modification relationships, we developed a local sequence kernel and Gaussian interaction profile kernel, respectively. Multiple kernels were further combined to train SVM for efficiently leveraging kernel information to boost predictive performance. We compared the proposed method with existing PTM prediction methods. The experimental results revealed that the proposed method performed comparable or better performance than the existing prediction methods, suggesting the feasibility of the developed kernels and the usefulness of the proposed method in PTM sites prediction.

Bioinformatics Analysis of Functional Associations of PTMs

Post-translational modifications (PTMs) are an important source of protein regulation; they fine-tune the function, localization, and interaction with other molecules of the majority of proteins and are partially responsible for their multifunctionality. Usually, proteins have several potential modification sites, and their patterns of occupancy are associated with certain functional states. These patterns imply cross talk among PTMs within and between proteins, the majority of which are still to be discovered. Several methods detect associations between PTMs; these have recently combined into a global resource, the PTMcode database, which contains already known and predicted functional associations between pairs of PTMs from more than 45,000 proteins in 19 eukaryotic species.

A novel method for predicting post-translational modifications on serine and threonine sites by using site-modification network profiles

Post-translational modifications (PTMs) regulate many aspects of biological behaviours including protein-protein interactions and cellular processes. Identification of PTM sites is helpful for understanding the PTM regulatory mechanisms. The PTMs on serine and threonine sites include phosphorylation, O-linked glycosylation and acetylation. Although a lot of computational approaches have been developed for PTM site prediction, currently most of them generate the predictive models by employing only local sequence information and few of them consider the relationship between different PTMs. In this paper, by adopting the site-modification network (SMNet) profiles that efficiently incorporate in situ PTM information, we develop a novel method to predict PTM sites on serine and threonine. PTM data are collected from various PTM databases and the SMNet is built to reflect the relationship between multiple PTMs, from which SMNet profiles are extracted to train predictive models based on SVM. Performance analysis of the SVM models shows that the SMNet profiles play an important role in accurately predicting PTM sites on serine and threonine. Furthermore, the proposed method is compared with existing PTM prediction approaches. The results from 10-fold cross-validation demonstrate that the proposed method with SMNet profiles performs remarkably better than existing methods, suggesting the power of SMNet profiles in identifying PTM sites.

iSulf-Cys: Prediction of S-sulfenylation Sites in Proteins with Physicochemical Properties of Amino Acids

Cysteine S-sulfenylation is an important post-translational modification (PTM) in proteins, and provides redox regulation of protein functions. Bioinformatics and structural analyses indicated that S-sulfenylation could impact many biological and functional categories and had distinct structural features. However, major limitations for identifying cysteine S-sulfenylation were expensive and low-throughout. In view of this situation, the establishment of a useful computational method and the development of an efficient predictor are highly desired. In this study, a predictor iSulf-Cys which incorporated 14 kinds of physicochemical properties of amino acids was proposed. With the 10-fold cross-validation, the value of area under the curve (AUC) was 0.7155 ± 0.0085, MCC 0.3122 ± 0.0144 on the training dataset for 20 times. iSulf-Cys also showed satisfying performance in the independent testing dataset with AUC 0.7343 and MCC 0.3315. Features which were constructed from physicochemical properties and position were carefully analyzed. Meanwhile, a user-friendly web-server for iSulf-Cys is accessible at http://app.aporc.org/iSulf-Cys/.

A novel network-based computational method to predict protein phosphorylation on tyrosine sites

Phosphorylation plays a great role in regulating a variety of cellular processes and the identification of tyrosine phosphorylation sites is fundamental for understanding the post-translational modification (PTM) regulation processes. Although a lot of computational methods have been developed, most of them only concern local sequence information and few studies focus on the tyrosine sites with in situ PTM information, which refers to different types of PTM occurring on the same modification site. In this study, by constructing the site-modification network that efficiently incorporates in situ PTM information, we introduce a novel network-based computational method, site-modification network-based inference (SMNBI) to predict tyrosine phosphorylation. In order to verify the effectiveness of the proposed method, we compare it with other network-based computational methods. The results clearly show the superior performance of SMNBI. Besides, we extensively compare SMNBI with other sequence-based methods including SVM and Bayesian decision theory. The evaluation demonstrates the power of site-modification network in predicting tyrosine phosphorylation. The proposed method is freely available at http://bioinformatics.ustc.edu.cn/smnbi/ .

Systematic Analysis and Prediction of In Situ Cross Talk of O-GlcNAcylation and Phosphorylation

Reversible posttranslational modification (PTM) plays a very important role in biological process by changing properties of proteins. As many proteins are multiply modified by PTMs, cross talk of PTMs is becoming an intriguing topic and draws much attention. Currently, lots of evidences suggest that the PTMs work together to accomplish a specific biological function. However, both the general principles and underlying mechanism of PTM crosstalk are elusive. In this study, by using large-scale datasets we performed evolutionary conservation analysis, gene ontology enrichment, motif extraction of proteins with cross talk of O-GlcNAcylation and phosphorylation cooccurring on the same residue. We found that proteins with in situ O-GlcNAc/Phos cross talk were significantly enriched in some specific gene ontology terms and no obvious evolutionary pressure was observed. Moreover, 3 functional motifs associated with O-GlcNAc/Phos sites were extracted. We further used sequence features and GO features to predict O-GlcNAc/Phos cross talk sites based on phosphorylated sites and O-GlcNAcylated sites separately by the use of SVM model. The AUC of classifier based on phosphorylated sites is 0.896 and the other classifier based on GlcNAcylated sites is 0.843. Both classifiers achieved a relatively better performance compared with other existing methods.

Identification and analysis of the N(6)-methyladenosine in the Saccharomyces cerevisiae transcriptome

Knowledge of the distribution of N⁶-methyladenosine (m⁶A) is invaluable for understanding RNA biological functions. However, limitation in experimental methods impedes the progress towards the identification of m⁶A site. As a complement of experimental methods, a support vector machine based-method is proposed to identify m⁶A sites in Saccharomyces cerevisiae genome. In this model, RNA sequences are encoded by their nucleotide chemical property and accumulated nucleotide frequency information. It is observed in the jackknife test that the accuracy achieved by the proposed model in identifying the m⁶A site was 78.15%. For the convenience of experimental scientists, a web-server for the proposed model is provided at http://lin.uestc.edu.cn/server/m6Apred.php.

Suberoylanilide hydroxamic acid treatment reveals crosstalks among proteome, ubiquitylome and acetylome in non-small cell lung cancer A549 cell line

Suberoylanilide hydroxamic acid (SAHA) is a well-known histone deacetylase (HDAC) inhibitor and has been used as practical therapy for breast cancer and non-small cell lung cancer (NSCLC). It is previously demonstrated that SAHA treatment could extensively change the profile of acetylome and proteome in cancer cells. However, little is known about the impact of SAHA on other protein modifications and the crosstalks among different modifications and proteome, hindering the deep understanding of SAHA-mediated cancer therapy. In this work, by using SILAC technique, antibody-based affinity enrichment and high-resolution LC-MS/MS analysis, we investigated quantitative proteome, acetylome and ubiquitylome as well as crosstalks among the three datasets in A549 cells toward SAHA treatment. In total, 2968 proteins, 1099 acetylation sites and 1012 ubiquitination sites were quantified in response to SAHA treatment, respectively. With the aid of intensive bioinformatics, we revealed that the proteome and ubiquitylome were negatively related upon SAHA treatment. Moreover, the impact of SAHA on acetylome resulted in 258 up-regulated and 99 down-regulated acetylation sites at the threshold of 1.5 folds. Finally, we identified 55 common sites with both acetylation and ubiquitination, among which ubiquitination level in 43 sites (78.2%) was positive related to acetylation level.