GPS-YNO2: computational prediction of tyrosine nitration sites in proteins

NTpred: a robust and precise machine learning framework for in silico identification of Tyrosine nitration sites in protein sequences

Post-translational modifications (PTMs) either enhance a protein's activity in various sub-cellular processes, or degrade their activity which leads toward failure of intracellular processes. Tyrosine nitration (NT) modification degrades protein's activity that initiates and propagates various diseases including neurodegenerative, cardiovascular, autoimmune diseases and carcinogenesis. Identification of NT modification supports development of novel therapies and drug discoveries for associated diseases. Identification of NT modification in biochemical labs is expensive, time consuming and error-prone. To supplement this process, several computational approaches have been proposed. However these approaches fail to precisely identify NT modification, due to the extraction of irrelevant, redundant and less discriminative features from protein sequences. This paper presents the NTpred framework that is competent in extracting comprehensive features from raw protein sequences using four different sequence encoders. To reap the benefits of different encoders, it generates four additional feature spaces by fusing different combinations of individual encodings. Furthermore, it eradicates irrelevant and redundant features from eight different feature spaces through a Recursive Feature Elimination process. Selected features of four individual encodings and four feature fusion vectors are used to train eight different Gradient Boosted Tree classifiers. The probability scores from the trained classifiers are utilized to generate a new probabilistic feature space, which is used to train a Logistic Regression classifier. On the BD1 benchmark dataset, the proposed framework outperforms the existing best-performing predictor in 5-fold cross validation and independent test evaluation with combined improvement of 13.7% in MCC and 20.1% in AUC. Similarly, on the BD2 benchmark dataset, the proposed framework outperforms the existing best-performing predictor with combined improvement of 5.3% in MCC and 1.0% in AUC. NTpred is publicly available for further experimentation and predictive use at: https://sds_genetic_analysis.opendfki.de/PredNTS/.

Characterization of leucine aminopeptidase (LAP) activity in sweet pepper fruits during ripening and its inhibition by nitration and reducing events

KEY MESSAGE

Pepper fruits contain two leucine aminopeptidase (LAP) genes which are differentially modulated during ripening and by nitric oxide. The LAP activity increases during ripening but is negatively modulated by nitration. Leucine aminopeptidase (LAP) is an essential metalloenzyme that cleaves N-terminal leucine residues from proteins but also metabolizes dipeptides and tripeptides. LAPs play a fundamental role in cell protein turnover and participate in physiological processes such as defense mechanisms against biotic and abiotic stresses, but little is known about their involvement in fruit physiology. This study aims to identify and characterize genes encoding LAP and evaluate their role during the ripening of pepper (Capsicum annuum L.) fruits and under a nitric oxide (NO)-enriched environment. Using a data-mining approach of the pepper plant genome and fruit transcriptome (RNA-seq), two LAP genes, designated CaLAP1 and CaLAP2, were identified. The time course expression analysis of these genes during different fruit ripening stages showed that whereas CaLAP1 decreased, CaLAP2 was upregulated. However, under an exogenous NO treatment of fruits, both genes were downregulated. On the contrary, it was shown that during fruit ripening LAP activity increased by 81%. An in vitro assay of the LAP activity in the presence of different modulating compounds including peroxynitrite (ONOO-), NO donors (S-nitrosoglutathione and nitrosocyteine), reducing agents such as reduced glutathione (GSH), L-cysteine (L-Cys), and cyanide triggered a differential response. Thus, peroxynitrite and reducing compounds provoked around 50% inhibition of the LAP activity in green immature fruits, whereas cyanide upregulated it 1.5 folds. To our knowledge, this is the first characterization of LAP in pepper fruits as well as of its regulation by diverse modulating compounds. Based on the capacity of LAP to metabolize dipeptides and tripeptides, it could be hypothesized that the LAP might be involved in the GSH recycling during the ripening process.

A metabolic perspective on nitric oxide function in melanoma

Nitric oxide (NO) generated from nitric oxide synthase (NOS) exerts a dichotomous effect in melanoma, suppressing or promoting tumor progression. This dichotomy is thought to depend on the intracellular NO concentration and the cell type in which it is generated. Due to its central role in the metabolism of multiple critical constituents involved in signaling and stress, it is crucial to explore NO's contribution to the metabolic dysfunction of melanoma. This review will discuss many known metabolites linked to NO production in melanoma. We discuss the synthesis of these metabolites, their role in biochemical pathways, and how they alter the biological processes observed in the melanoma tumor microenvironment. The metabolic pathways altered by NO and the corresponding metabolites reinforce its dual role in melanoma and support investigating this effect for potential avenues of therapeutic intervention.

Reactive oxygen species- and nitric oxide-dependent regulation of ion and metal homeostasis in plants

Deterioration and impoverishment of soil, caused by environmental pollution and climate change, result in reduced crop productivity. To adapt to hostile soils, plants have developed a complex network of factors involved in stress sensing, signal transduction, and adaptive responses. The chemical properties of reactive oxygen species (ROS) and reactive nitrogen species (RNS) allow them to participate in integrating the perception of external signals by fine-tuning protein redox regulation and signal transduction, triggering specific gene expression. Here, we update and summarize progress in understanding the mechanistic basis of ROS and RNS production at the subcellular level in plants and their role in the regulation of ion channels/transporters at both transcriptional and post-translational levels. We have also carried out an in silico analysis of different redox-dependent modifications of ion channels/transporters and identified cysteine and tyrosine targets of nitric oxide in metal transporters. Further, we summarize possible ROS- and RNS-dependent sensors involved in metal stress sensing, such as kinases and phosphatases, as well as some ROS/RNS-regulated transcription factors that could be involved in metal homeostasis. Understanding ROS- and RNS-dependent signaling events is crucial to designing new strategies to fortify crops and improve plant tolerance of nutritional imbalance and metal toxicity.

Unveiling the human nitroproteome: Protein tyrosine nitration in cell signaling and cancer

Covalent amino acid modification significantly expands protein functional capability in regulating biological processes. Tyrosine residues can undergo phosphorylation, sulfation, adenylation, halogenation, and nitration. These posttranslational modifications (PTMs) result from the actions of specific enzymes: tyrosine kinases, tyrosyl-protein sulfotransferase(s), adenylate transferase(s), oxidoreductases, peroxidases, and metal-heme containing proteins. Whereas phosphorylation, sulfation, and adenylation modify the hydroxyl group of tyrosine, tyrosine halogenation and nitration target the adjacent carbon residues. Because aberrant tyrosine nitration has been associated with human disorders and with animal models of disease, we have created an updated and curated database of 908 human nitrated proteins. We have also analyzed this new resource to provide insight into the role of tyrosine nitration in cancer biology, an area that has not previously been considered in detail. Unexpectedly, we have found that 879 of the 1971 known sites of tyrosine nitration are also sites of phosphorylation suggesting an extensive role for nitration in cell signaling. Overall, the review offers several forward-looking opportunities for future research and new perspectives for understanding the role of tyrosine nitration in cancer biology.

EhSir2c, a Sir2 homolog from the human pathogen Entamoeba histolytica interacts with a DNA repair protein, EhRAD23: Protein-protein interaction, docking and functional study

Chromosome segregation is a crucial phenomenon in the cell cycle and defects in genome segregation result in an abnormality in various cellular events. Unlike higher eukaryotes, chromosome segregation and a number of cell cycle events are unusual in the protozoan parasite Entamoeba histolytica (E. histolytica). Characterization of Sir2 proteins from E. histolytica may reveal its unique cellular events as they play role in diverse cellular processes including chromosome segregation. E. histolytica has four homologs of Sir2 proteins. EhSir2a and EhSir2b show sequence similarity towards eukaryotic Sir2 homologs, whereas EhSir2c and EhSir2d are more like prokaryotic sirtuins. Using both computational and experimental methods, EhSir2c has been characterized in this study. The three-dimensional structure of EhSir2c is predicted by homology modelling. The protein interactors of EhSir2c have been identified by yeast-two-hybrid screening against the cDNA library of E. histolytica. We have identified a novel interactor, EhRAD23 which is a homolog of UV excision repair protein RAD23. The interaction of EhSir2c and EhRAD23 was validated by pull-down assay. UV-C irradiation up-regulates the relative expression of EhSir2c, suggesting the necessity of EhSir2c in UV-induced stress in this parasite.Communicated by Ramaswamy H. Sarma.

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.

Accurately predicting nitrosylated tyrosine sites using probabilistic sequence information

Post-translational modification (PTM) is defined as the enzymatic changes of proteins after the translation process in protein biosynthesis. Nitrotyrosine, which is one of the most important modifications of proteins, is interceded by the active nitrogen molecule. It is known to be associated with different diseases including autoimmune diseases characterized by chronic inflammation and cell damage. Currently, nitrotyrosine sites are identified using experimental approaches which are laborious and costly. In this study, we propose a new machine learning method called PredNitro to accurately predict nitrotyrosine sites. To build PredNitro, we use sequence coupling information from the neighboring amino acids of tyrosine residues along with a support vector machine as our classification technique.Our results demonstrates that PredNitro achieves 98.0% accuracy with more than 0.96 MCC and 0.99 AUC in both 5-fold cross-validation and jackknife cross-validation tests which are significantly better than those reported in previous studies. PredNitro is publicly available as an online predictor at: http://103.99.176.239/PredNitro.

MSD2, an apoplastic Mn-SOD, contributes to root skotomorphogenic growth by modulating ROS distribution in Arabidopsis

Reactive oxygen species (ROS) play essential roles as a second messenger in various physiological processes in plants. Due to their oxidative nature, ROS can also be harmful. Thus, the generation and homeostasis of ROS are tightly controlled by multiple enzymes. Membrane-localized NADPH oxidases are well known to generate ROS during developmental and stress responses, but the metabolic pathways of the superoxide (O2^-) generated by them in the apoplast are poorly understood, and the identity of the apoplastic superoxide dismutase (SOD) is unknown in Arabidopsis. Here, we show that a putative manganese SOD, MSD2 is secreted and possesses a SOD activity that can be inhibited by nitration at tyrosine 68. The expression of MSD2 in roots is light condition-dependent, suggesting that MSD2 may act on ROS metabolism in roots during the light-to-dark transition. Root architecture is governed by ROS distribution that exhibits opposite gradient of H₂O₂ and O2^-, which is indeed altered in etiolated msd2 mutants and accompanied by changes in the onset of differentiation. These results provide a missing link in our understanding of ROS metabolism and suggest that MSD2 plays a role in root skotomorphogenesis by regulating ROS distribution, thereby playing a pivotal role in plant growth and development.

Antibodies against 4 Atypical Post-Translational Protein Modifications in Patients with Rheumatoid Arthritis

Patients with rheumatoid arthritis (RA) show autoantibodies against post-translational protein modifications (PTMs), such as anti-citrullinated protein antibodies. However, the range of recognized PTMs is unknown. Here, we addressed four PTMs: chlorination, non-enzymatic glycation, nitration, and homocysteinylation, identified as targets of atypical RA autoantibodies in studies whose protocols we have followed. The modified antigens included collagen type II, an extract of synovial proteins and a selection of peptides. We interpreted the results according to the optical density (OD) obtained in an enzyme-linked immunosorbent assay ( ELISA) with the modified antigen and the corrected OD obtained after subtracting the reactivity against the unmodified antigen. The results showed evidence of specific antibodies against glycated collagen type II, as the corrected ODs were higher in the 182 patients with RA than in the 164 healthy controls (p = 0.0003). However, the relevance of these antibodies was doubtful because the magnitude of the specific signal was small (median OD = 0.072 vs. 0.027, respectively). There were no specific antibodies against any of the other three PTMs. Therefore, our results showed that the four PTMs are not inducing a significant autoantibody response in patients with RA. These results indicated that the repertoire of PTM autoantigens in RA is restricted.

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.

SSKM_Succ: A Novel Succinylation Sites Prediction Method Incorporating K-Means Clustering With a New Semi-Supervised Learning Algorithm

Protein succinylation is a type of post-translational modification (PTM) that occurs on lysine sites and plays a key role in protein conformation regulation and cellular function control. When training in computational method, it is difficult to designate negative samples because of the uncertainty of non-succinylation lysine sites, and if not handled properly, it may affect the performance of computational models dramatically. Therefore, we propose a new semi-supervised learning method to identify reliable non-succinylation lysine sites as negative samples. This method, named SSKM_Succ, also employs K-means clustering to divide data into 5 clusters. Besides, information of proximal PTMs and three kinds of sequence features (grey pseudo amino acid composition, K-space and position-special amino acid propensity) are utilized to formulate protein. Then, we perform a two-step feature selection to remove redundant features and construct the optimization model for each cluster. Finally, support vector machine is applied to construct a prediction model for each cluster. Promising results are obtained by this method with an accuracy of 80.18 percent for succinylation sites on the independent testing dataset. Meanwhile, we compare the result with other existing tools, and it shows that our method is promising for predicting succinylation sites. Through analysis, we further verify that succinylated protein has potential effects on amino acid degradation and fatty acid metabolism, and speculate that protein succinylation may be closely related to neurodegenerative diseases. The code of SSKM_Succ is available on the web https://github.com/yangyq505/SSKM_Succ.git.

Computational prediction of NO-dependent posttranslational modifications in plants: Current status and perspectives

The perception and transduction of nitric oxide (NO) signal is achieved by NO-dependent posttranslational modifications (PTMs) among which S-nitrosation and tyrosine nitration has biological significance. In plants, 100-1000 S-nitrosated and tyrosine nitrated proteins have been identified so far by mass spectrometry. The determination of NO-modified protein targets/amino acid residues is often methodologically challenging. In the past decade, the growing demand for the knowledge of S-nitrosated or tyrosine nitrated sites has motivated the introduction of bioinformatics tools. For predicting S-nitrosation seven computational tools have been developed (GPS-SNO, SNOSite, iSNO-PseACC, iSNO-AAPAir, PSNO, PreSNO, RecSNO). Four predictors have been developed for indicating tyrosine nitration sites (GPS-YNO2, iNitro-Tyr, PredNTS, iNitroY-Deep), and one tool (DeepNitro) predicts both NO-dependent PTMs. The advantage of these computational tools is the fast provision of large amount of information. In this review, the available software tools have been tested on plant proteins in which S-nitrosated or tyrosine nitrated sites have been experimentally identified. The predictors showed distinct performance and there were differences from the experimental results partly due to the fact that the three-dimensional protein structure is not taken into account by the computational tools. Nevertheless, the predictors excellently establish experiments, and it is suggested to apply all available tools on target proteins and compare their results. In the future, computational prediction must be developed further to improve the precision with which S-nitrosation/tyrosine nitration-sites are identified.

Clinical relevance of nitrated beta 2-glycoprotein I in antiphospholipid syndrome: Implications for thrombosis risk

Β₂-Glycoprotein I (β₂GPI) is an important anti-thrombotic protein and is the major auto-antigen in the antiphospholipid syndrome (APS). The clinical relevance of nitrosative stress in post translational modification of β₂GPI was examined.The effects of nitrated (n)β₂GPI on its anti-thrombotic properties and its plasma levels in primary and secondary APS were determined with appropriate clinical control groups. β2-glycoprotein I was nitrated at tyrosines 218, 275 and 309. β₂-glycoprotein I binds to lipid peroxidation modified products through Domains IV and V. Nitrated β₂GPI loses this binding (p < 0.05) and had diminished activity in inhibiting platelet adhesion to vWF under high shear flow (p < 0.01). Levels of nβ₂GPI were increased in patients with primary APS compared to patients with either secondary APS (p < 0.05), autoimmune disease without APS (p < 0.05) or non-autoimmune patients with arterial thrombosis (p < 0.01) and healthy individuals (p < 0.05).In conclusion tyrosine nitration of plasma β₂GPI is demonstrated and has important implications with regards to the pathophysiology of platelet mediated thrombosis in APS. Elevated plasma levels of nβ₂GPI in primary APS may be a risk factor for thrombosis warranting further investigation.

PredNTS: Improved and Robust Prediction of Nitrotyrosine Sites by Integrating Multiple Sequence Features

Nitrotyrosine, which is generated by numerous reactive nitrogen species, is a type of protein post-translational modification. Identification of site-specific nitration modification on tyrosine is a prerequisite to understanding the molecular function of nitrated proteins. Thanks to the progress of machine learning, computational prediction can play a vital role before the biological experimentation. Herein, we developed a computational predictor PredNTS by integrating multiple sequence features including K-mer, composition of k-spaced amino acid pairs (CKSAAP), AAindex, and binary encoding schemes. The important features were selected by the recursive feature elimination approach using a random forest classifier. Finally, we linearly combined the successive random forest (RF) probability scores generated by the different, single encoding-employing RF models. The resultant PredNTS predictor achieved an area under a curve (AUC) of 0.910 using five-fold cross validation. It outperformed the existing predictors on a comprehensive and independent dataset. Furthermore, we investigated several machine learning algorithms to demonstrate the superiority of the employed RF algorithm. The PredNTS is a useful computational resource for the prediction of nitrotyrosine sites. The web-application with the curated datasets of the PredNTS is publicly available.

3-Nitrotyrosine and related derivatives in proteins: precursors, radical intermediates and impact in function

Oxidative post-translational modification of proteins by molecular oxygen (O2)- and nitric oxide (•NO)-derived reactive species is a usual process that occurs in mammalian tissues under both physiological and pathological conditions and can exert either regulatory or cytotoxic effects. Although the side chain of several amino acids is prone to experience oxidative modifications, tyrosine residues are one of the preferred targets of one-electron oxidants, given the ability of their phenolic side chain to undergo reversible one-electron oxidation to the relatively stable tyrosyl radical. Naturally occurring as reversible catalytic intermediates at the active site of a variety of enzymes, tyrosyl radicals can also lead to the formation of several stable oxidative products through radical-radical reactions, as is the case of 3-nitrotyrosine (NO2Tyr). The formation of NO2Tyr mainly occurs through the fast reaction between the tyrosyl radical and nitrogen dioxide (•NO2). One of the key endogenous nitrating agents is peroxynitrite (ONOO-), the product of the reaction of superoxide radical (O2•-) with •NO, but ONOO--independent mechanisms of nitration have been also disclosed. This chemical modification notably affects the physicochemical properties of tyrosine residues and because of this, it can have a remarkable impact on protein structure and function, both in vitro and in vivo. Although low amounts of NO2Tyr are detected under basal conditions, significantly increased levels are found at pathological states related with an overproduction of reactive species, such as cardiovascular and neurodegenerative diseases, inflammation and aging. While NO2Tyr is a well-established stable oxidative stress biomarker and a good predictor of disease progression, its role as a pathogenic mediator has been laboriously defined for just a small number of nitrated proteins and awaits further studies.

Ubiquitinome Profiling Reveals the Landscape of Ubiquitination Regulation in Rice Young Panicles

Ubiquitination, an essential post-transcriptional modification (PTM), plays a vital role in nearly every biological process, including development and growth. Despite its functions in plant reproductive development, its targets in rice panicles remain unclear. In this study, we used proteome-wide profiling of lysine ubiquitination in rice (O. sativa ssp. indica) young panicles. We created the largest ubiquitinome dataset in rice to date, identifying 1638 lysine ubiquitination sites on 916 unique proteins. We detected three conserved ubiquitination motifs, noting that acidic glutamic acid (E) and aspartic acid (D) were most frequently present around ubiquitinated lysine. Enrichment analysis of Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of these ubiquitinated proteins revealed that ubiquitination plays an important role in fundamental cellular processes in rice young panicles. Interestingly, enrichment analysis of protein domains indicated that ubiquitination was enriched on a variety of receptor-like kinases and cytoplasmic tyrosine and serine-threonine kinases. Furthermore, we analyzed the crosstalk between ubiquitination, acetylation, and succinylation, and constructed a potential protein interaction network within our rice ubiquitinome. Moreover, we identified ubiquitinated proteins related to pollen and grain development, indicating that ubiquitination may play a critical role in the physiological functions in young panicles. Taken together, we reported the most comprehensive lysine ubiquitinome in rice so far, and used it to reveal the functional role of lysine ubiquitination in rice young panicles.

Computational analysis of hereditary spastic paraplegia mutations in the kinesin motor domains of KIF1A and KIF5A

Hereditary spastic paraplegias (HSPs) are a genetically heterogeneous collection of neurodegenerative disorders categorized by progressive lower-limb spasticity and frailty. The complex HSP forms are characterized by various neurological features including progressive spastic weakness, urinary sphincter dysfunction, extra pyramidal signs and intellectual disability (ID). The kinesin superfamily proteins (KIFs) are microtubule-dependent molecular motors involved in intracellular transport. Kinesins directionally transport membrane vesicles, protein complexes, and mRNAs along neurites, thus playing important roles in neuronal development and function. Recent genetic studies have identified kinesin mutations in patients with HSPs. In this study, we used the computational approaches to investigate the 40 missense mutations associated with HSP and ID in KIF1A and KIF5A. We performed homology modeling to construct the structures of kinesin–microtubule binding domain and kinesin–tubulin complex. We applied structure-based energy calculation methods to determine the effects of missense mutations on protein stability and protein–protein interaction. The results revealed that the most of disease-causing mutations could change the folding free energy of kinesin motor domain and the binding free energy of kinesin–tubulin complex. We found that E253K associated with ID in KIF1A decrease the protein stability of kinesin motor domains. We showed that the HSP mutations located in kinesin–tubulin complex interface, such as K253N and R280C in KIF5A, can destabilize the kinesin–tubulin complex. The computational analysis provides useful information for understanding the roles of kinesin mutations in the development of ID and HSPs.

Tyr-nitration in maize CDKA;1 results in lower affinity for ATP binding

Cyclin-dependent kinase A (CDKA) is a key component for cell cycle progression. The catalytic kinase activity depends on the protein's ability to form an active complex with cyclins and on phosphoregulatory mechanisms. Cell cycle arrest and plant growth impairment under abiotic stress have been linked to different molecular processes triggered by increased levels of reactive oxygen and nitrogen species (ROS and RNS). Among these, posttranslational modifications (PTMs) of key proteins such as CDKA;1 may be of significance. Herein, isolated maize embryo axes were subjected to sodium nitroprusside (SNP) as an inductor of nitrosative conditions to evaluate if CDKA;1 protein was a target for RNS. A high degree of protein nitration was detected; this included the specific Tyr-nitration of CDKA;1. Tyr15 and Tyr19, located at the ATP-binding site, were the selective targets for nitration according to both in silico analysis using the predictive software GPS-YNO₂, and in vitro mass spectrometry studies of recombinant nitrated ZmCDKA;1. Spectrofluorometric measurements demonstrated a reduction of ZmCDKA;1-NO₂ affinity for ATP. From these results, we conclude that Tyr nitration in CDKA;1 could act as an active modulator of cell cycle progression during redox stress.

An Information Entropy-Based Approach for Computationally Identifying Histone Lysine Butyrylation

Butyrylation plays a crucial role in the cellular processes. Due to limit of techniques, it is a challenging task to identify histone butyrylation sites on a large scale. To fill the gap, we propose an approach based on information entropy and machine learning for computationally identifying histone butyrylation sites. The proposed method achieves 0.92 of area under the receiver operating characteristic (ROC) curve over the training set by 3-fold cross validation and 0.80 over the testing set by independent test. Feature analysis implies that amino acid residues in the down/upstream of butyrylation sites would exhibit specific sequence motif to a certain extent. Functional analysis suggests that histone butyrylation was most possibly associated with four pathways (systemic lupus erythematosus, alcoholism, viral carcinogenesis and transcriptional misregulation in cancer), was involved in binding with other molecules, processes of biosynthesis, assembly, arrangement or disassembly and was located in such complex as consists of DNA, RNA, protein, etc. The proposed method is useful to predict histone butyrylation sites. Analysis of feature and function improves understanding of histone butyrylation and increases knowledge of functions of butyrylated histones.

Ganglioside Synthesis by Plasma Membrane-Associated Sialyltransferase in Macrophages

Gangliosides are constituents of the mammalian cell membranes and participate in the inflammatory response. However, little is known about the presence and enzymatic activity of ganglioside sialyltransferases at the cell surface of macrophages, one of the most important immune cells involved in the innate inflammatory process. In the present study, using biochemical and fluorescent microscopy approaches, we found that endogenous ST8Sia-I is present at the plasma membrane (ecto-ST8Sia-I) of murine macrophage RAW264.7 cells. Moreover, ecto-ST8Sia-I can synthetize GD3 ganglioside at the cell surface in lipopolysaccharide (LPS)-stimulated macrophages even when LPS-stimulated macrophages reduced the total ST8Sia-I expression levels. Besides, cotreatment of LPS with an inhibitor of nitric oxide (NO) synthase recovered the ecto-ST8Sia-I expression, suggesting that NO production is involved in the reduction of ST8Sia-I expression. The diminution of ST8Sia-I expression in LPS-stimulated macrophages correlated with a reduction of GD3 and GM1 gangliosides and with an increment of GD1a. Taken together, the data supports the presence and activity of sialyltransferases at the plasma membrane of RAW264.7 cells. The variations of ecto-ST8Sia-I and ganglioside levels in stimulated macrophages constitutes a promissory pathway to further explore the physiological role of this and others ganglioside metabolism-related enzymes at the cell surface during the immune response.

milRNApredictor: Genome-free prediction of fungi milRNAs by incorporating k-mer scheme and distance-dependent pair potential

MicroRNA-like small RNAs (milRNAs) with length of 21-22 nucleotides are a type of small non-coding RNAs that are firstly found in Neurospora crassa in 2010. Identifying milRNAs of species without genomic information is a difficult problem. Here, knowledge-based energy features are developed to identify milRNAs by tactfully incorporating k-mer scheme and distance-dependent pair potential. Compared with k-mer scheme, features developed here can alleviate the inherent curse of dimensionality in k-scheme once k becomes large. In addition, milRNApredictor built on novel features performs comparably to k-mer scheme, and achieves sensitivity of 74.21%, and specificity of 75.72% based on 10-fold cross-validation. Furthermore, for novel miRNA prediction, there exists high overlap of results from milRNApredictor and state-of-the-art mirnovo. However, milRNApredictor is simpler to use with reduced requirements of input data and dependencies. Taken together, milRNApredictor can be used to de novo identify fungi milRNAs and other very short small RNAs of non-model organisms.

Boosting phosphorylation site prediction with sequence feature-based machine learning

Protein phosphorylation is one of the essential posttranslation modifications playing a vital role in the regulation of many fundamental cellular processes. We propose a LightGBM-based computational approach that uses evolutionary, geometric, sequence environment, and amino acid-specific features to decipher phosphate binding sites from a protein sequence. Our method, while compared with other existing methods on 2429 protein sequences taken from standard Phospho.ELM (P.ELM) benchmark data set featuring 11 organisms reports a higher F₁ score = 0.504 (harmonic mean of the precision and recall) and ROC AUC = 0.836 (area under the curve of the receiver operating characteristics). The computation time of our proposed approach is much less than that of the recently developed deep learning-based framework. Structural analysis on selected protein sequences informs that our prediction is the superset of the phosphorylation sites, as mentioned in P.ELM data set. The foundation of our scheme is manual feature engineering and a decision tree-based classification. Hence, it is intuitive, and one can interpret the final tree as a set of rules resulting in a deeper understanding of the relationships between biophysical features and phosphorylation sites. Our innovative problem transformation method permits more control over precision and recall as is demonstrated by the fact that if we incorporate output probability of the existing deep learning framework as an additional feature, then our prediction improves (F₁ score = 0.546; ROC AUC = 0.849). The implementation of our method can be accessed at http://cse.iitkgp.ac.in/~pralay/resources/PPSBoost/ and is mirrored at https://cosmos.iitkgp.ac.in/PPSBoost.

Activation of the TRKB receptor mediates the panicolytic-like effect of the NOS inhibitor aminoguanidine

Nitric oxide (NO) triggers escape reactions in the dorsal periaqueductal gray matter (dPAG), a core structure mediating panic-associated response, and decreases the release of BDNF in vitro. BDNF mediates the panicolytic effect induced by antidepressant drugs and produces these effects per se when injected into the dPAG. Based on these findings, we hypothesize that nitric oxide synthase (NOS) inhibitors would have panicolytic properties associated with increased BDNF signaling in the dPAG. We observed that the repeated (7 days), but not acute (1 day), systemic administration of the NOS inhibitor aminoguanidine (AMG; 15 mg/kg/day) increased the latency to escape from the open arm of the elevated T-maze (ETM) and inhibited the number of jumps in hypoxia-induced escape reaction in rats, suggesting a panicolytic-like effect. Repeated, but not acute, AMG administration (15 mg/kg) also decreased nitrite levels and increased TRKB phosphorylation at residues Y706/7 in the dPAG. Notwithstanding the lack of AMG effect on total BDNF levels in this structure, the microinjection of the TRK antagonist K252a into the dPAG blocked the anti-escape effect of this drug in the ETM. Taken together our data suggest that the inhibition of NO production by AMG increases the levels of pTRKB, which is required for the panicolytic-like effect observed.

Strigolactone-nitric oxide interplay in plants: The story has just begun

Both strigolactones (SLs) and nitric oxide (NO) are regulatory signals with diverse roles during plant development and stress responses. This review aims to discuss the so far available data regarding SLs-NO interplay in plant systems. The majority of the few articles dealing with SL-NO interplay focuses on the root system and it seems that NO can be an upstream negative regulator of SL biosynthesis or an upstream positive regulator of SL signaling depending on the nutrient supply. From the so far published results it is clear that NO modifies the activity of target proteins involved in SL biosynthesis or signaling which may be a physiologically relevant interaction. Therefore, in silico analysis of NO-dependent posttranslational modifications in SL-related proteins was performed using computational prediction tools and putative NO-target proteins were specified. The picture is presumably more complicated, since also SL is able to modify NO levels. As a confirmation, author detected NO levels in different organs of max1-1 and max2-1 Arabidopsis and compared to the wild-type these mutants showed enhanced NO levels in their root tips indicating the negative effect of endogenous SLs on NO metabolism. Exogenous SL analogue-triggered NO production seems to contradict the results of the genetic study, which is an inconsistency should be taken into consideration in the future. In the coming years, the link between SL and NO signaling in further physiological processes should be examined and the possibilities of NO-dependent posttranslational modifications of SL biosynthetic and signaling proteins should be looked more closely.

Role of Ca2+ in Mediating Plant Responses to Extracellular ATP and ADP

Among the most recently discovered chemical regulators of plant growth and development are extracellular nucleotides, especially extracellular ATP (eATP) and extracellular ADP (eADP). Plant cells release ATP into their extracellular matrix under a variety of different circumstances, and this eATP can then function as an agonist that binds to a specific receptor and induces signaling changes, the earliest of which is an increase in the concentration of cytosolic calcium ([Ca2+]cyt). This initial change is then amplified into downstream-signaling changes that include increased levels of reactive oxygen species and nitric oxide, which ultimately lead to major changes in the growth rate, defense responses, and leaf stomatal apertures of plants. This review presents and discusses the evidence that links receptor activation to increased [Ca2+]cyt and, ultimately, to growth and diverse adaptive changes in plant development. It also discusses the evidence that increased [Ca2+]cyt also enhances the activity of apyrase (nucleoside triphosphate diphosphohydrolase) enzymes that function in multiple subcellular locales to hydrolyze ATP and ADP, and thus limit or terminate the effects of these potent regulators.

Nitric oxide responses in Arabidopsis hypocotyls are mediated by diverse phytohormone pathways

Plants are often exposed to high levels of nitric oxide (NO) that affects development and stress-triggered responses. However, the way in which plants sense NO is still largely unknown. Here we combine the analysis of early changes in the transcriptome of plants exposed to a short acute pulse of exogenous NO with the identification of transcription factors (TFs) involved in NO sensing. The NO-responsive transcriptome was enriched in hormone homeostasis- and signaling-related genes. To assess events involved in NO sensing in hypocotyls, we used a functional sensing assay based on the NO-induced inhibition of hypocotyl elongation in etiolated seedlings. Hormone-related mutants and the TRANSPLANTA collection of transgenic lines conditionally expressing Arabidopsis TFs were screened for NO-triggered hypocotyl shortening. These approaches allowed the identification of hormone-related TFs, ethylene perception and signaling, strigolactone biosynthesis and signaling, and salicylate production and accumulation that are essential for or modulate hypocotyl NO sensing. Moreover, NO inhibits hypocotyl elongation through the positive and negative regulation of some abscisic acid (ABA) receptors and transcripts encoding brassinosteroid signaling components thereby also implicating these hormones in NO sensing.

DeepNitro: Prediction of Protein Nitration and Nitrosylation Sites by Deep Learning

Protein nitration and nitrosylation are essential post-translational modifications (PTMs) involved in many fundamental cellular processes. Recent studies have revealed that excessive levels of nitration and nitrosylation in some critical proteins are linked to numerous chronic diseases. Therefore, the identification of substrates that undergo such modifications in a site-specific manner is an important research topic in the community and will provide candidates for targeted therapy. In this study, we aimed to develop a computational tool for predicting nitration and nitrosylation sites in proteins. We first constructed four types of encoding features, including positional amino acid distributions, sequence contextual dependencies, physicochemical properties, and position-specific scoring features, to represent the modified residues. Based on these encoding features, we established a predictor called DeepNitro using deep learning methods for predicting protein nitration and nitrosylation. Using n-fold cross-validation, our evaluation shows great AUC values for DeepNitro, 0.65 for tyrosine nitration, 0.80 for tryptophan nitration, and 0.70 for cysteine nitrosylation, respectively, demonstrating the robustness and reliability of our tool. Also, when tested in the independent dataset, DeepNitro is substantially superior to other similar tools with a 7%−42% improvement in the prediction performance. Taken together, the application of deep learning method and novel encoding schemes, especially the position-specific scoring feature, greatly improves the accuracy of nitration and nitrosylation site prediction and may facilitate the prediction of other PTM sites. DeepNitro is implemented in JAVA and PHP and is freely available for academic research at http://deepnitro.renlab.org.

MusiteDeep: a deep-learning framework for general and kinase-specific phosphorylation site prediction

Motivation

Computational methods for phosphorylation site prediction play important roles in protein function studies and experimental design. Most existing methods are based on feature extraction, which may result in incomplete or biased features. Deep learning as the cutting-edge machine learning method has the ability to automatically discover complex representations of phosphorylation patterns from the raw sequences, and hence it provides a powerful tool for improvement of phosphorylation site prediction.

Results

We present MusiteDeep, the first deep-learning framework for predicting general and kinase-specific phosphorylation sites. MusiteDeep takes raw sequence data as input and uses convolutional neural networks with a novel two-dimensional attention mechanism. It achieves over a 50% relative improvement in the area under the precision-recall curve in general phosphorylation site prediction and obtains competitive results in kinase-specific prediction compared to other well-known tools on the benchmark data.

Availability and implementation

MusiteDeep is provided as an open-source tool available at https://github.com/duolinwang/MusiteDeep.

Contact

xudong@missouri.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification, characterization, and expression analysis of calmodulin and calmodulin-like genes in grapevine (Vitis vinifera) reveal likely roles in stress responses

Calcium (Ca²⁺) is an ubiquitous key second messenger in plants, where it modulates many developmental and adaptive processes in response to various stimuli. Several proteins containing Ca²⁺ binding domain have been identified in plants, including calmodulin (CaM) and calmodulin-like (CML) proteins, which play critical roles in translating Ca²⁺ signals into proper cellular responses. In this work, a genome-wide analysis conducted in Vitis vinifera identified three CaM- and 62 CML-encoding genes. We assigned gene family nomenclature, analyzed gene structure, chromosomal location and gene duplication, as well as protein motif organization. The phylogenetic clustering revealed a total of eight subgroups, including one unique clade of VviCaMs distinct from VviCMLs. VviCaMs were found to contain four EF-hand motifs whereas VviCML proteins have one to five. Most of grapevine CML genes were intronless, while VviCaMs were intron rich. All the genes were well spread among the 19 grapevine chromosomes and displayed a high level of duplication. The expression profiling of VviCaM/VviCML genes revealed a broad expression pattern across all grape organs and tissues at various developmental stages, and a significant modulation in biotic stress-related responses. Our results highlight the complexity of CaM/CML protein family also in grapevine, supporting the versatile role of its different members in modulating cellular responses to various stimuli, in particular to biotic stresses. This work lays the foundation for further functional and structural studies on specific grapevine CaMs/CMLs in order to better understand the role of Ca²⁺-binding proteins in grapevine and to explore their potential for further biotechnological applications.

NTyroSite: Computational Identification of Protein Nitrotyrosine Sites Using Sequence Evolutionary Features

Nitrotyrosine is a product of tyrosine nitration mediated by reactive nitrogen species. As an indicator of cell damage and inflammation, protein nitrotyrosine serves to reveal biological change associated with various diseases or oxidative stress. Accurate identification of nitrotyrosine site provides the important foundation for further elucidating the mechanism of protein nitrotyrosination. However, experimental identification of nitrotyrosine sites through traditional methods are laborious and expensive. In silico prediction of nitrotyrosine sites based on protein sequence information are thus highly desired. Here, we report a novel predictor, NTyroSite, for accurate prediction of nitrotyrosine sites using sequence evolutionary information. The generated features were optimized using a Wilcoxon-rank sum test. A random forest classifier was then trained using these features to build the predictor. The final NTyroSite predictor achieved an area under a receiver operating characteristics curve (AUC) score of 0.904 in a 10-fold cross-validation test. It also significantly outperformed other existing implementations in an independent test. Meanwhile, for a better understanding of our prediction model, the predominant rules and informative features were extracted from the NTyroSite model to explain the prediction results. We expect that the NTyroSite predictor may serve as a useful computational resource for high-throughput nitrotyrosine site prediction. The online interface of the software is publicly available at https://biocomputer.bio.cuhk.edu.hk/NTyroSite/.

p66Shc Inactivation Modifies RNS Production, Regulates Sirt3 Activity, and Improves Mitochondrial Homeostasis, Delaying the Aging Process in Mouse Brain

Programmed and damage aging theories have traditionally been conceived as stand-alone schools of thought. However, the p66Shc adaptor protein has demonstrated that aging-regulating genes and reactive oxygen species (ROS) are closely interconnected, since its absence modifies metabolic homeostasis by providing oxidative stress resistance and promoting longevity. p66Shc(-/-) mice are a unique opportunity to further comprehend the bidirectional relationship between redox homeostasis and the imbalance of mitochondrial biogenesis and dynamics during aging. This study shows that brain mitochondria of p66Shc(-/-) aged mice exhibit a reduced alteration of redox balance with a decrease in both ROS generation and its detoxification activity. We also demonstrate a strong link between reactive nitrogen species (RNS) and mitochondrial function, morphology, and biogenesis, where low levels of ONOO- formation present in aged p66Shc(-/-) mouse brain prevent protein nitration, delaying the loss of biological functions characteristic of the aging process. Sirt3 modulates age-associated mitochondrial biology and function via lysine deacetylation of target proteins, and we show that its regulation depends on its nitration status and is benefited by the improved NAD+/NADH ratio in aged p66Shc(-/-) brain mitochondria. Low levels of protein nitration and acetylation could cause the metabolic homeostasis maintenance observed during aging in this group, thus increasing its lifespan.

S-nitroso- and nitro- proteomes in the olive (Olea europaea L.) pollen. Predictive versus experimental data by nano-LC-MS

The data presented here are related to the research article entitled "Generation of nitric oxide by olive (Olea europaea L.) pollen during in vitro germination and assessment of the S-nitroso- and nitro-proteomes by computational predictive methods" doi:10.1016/j.niox.2017.06.005 (Jimenez-Quesada et al., 2017) [1]. Predicted cysteine S-nitrosylation and Tyr-nitration sites in proteins derived from a de novo assembled and annotated pollen transcriptome from olive tree (Olea europaea L.) were obtained after using well-established predictive tools in silico. Predictions were performed using both default and highly restrictive thresholds. Numerous gene products identified with these characteristics are listed here. An experimental validation of the data, consisting in nano-LC-MS (Liquid Chromatography-Mass Spectrometry) determination of olive pollen proteins after immunoprecipitation with antibodies to anti-S-nitrosoCys and anti-3-NT (NitroTyrosine) allowed identification of numerous proteins subjected to these two post-translational modifications, which are listed here together with information regarding their cross-presence among the predictions.

Accurate prediction of subcellular location of apoptosis proteins combining Chou's PseAAC and PsePSSM based on wavelet denoising

Apoptosis proteins subcellular localization information are very important for understanding the mechanism of programmed cell death and the development of drugs. The prediction of subcellular localization of an apoptosis protein is still a challenging task because the prediction of apoptosis proteins subcellular localization can help to understand their function and the role of metabolic processes. In this paper, we propose a novel method for protein subcellular localization prediction. Firstly, the features of the protein sequence are extracted by combining Chou's pseudo amino acid composition (PseAAC) and pseudo-position specific scoring matrix (PsePSSM), then the feature information of the extracted is denoised by two-dimensional (2-D) wavelet denoising. Finally, the optimal feature vectors are input to the SVM classifier to predict subcellular location of apoptosis proteins. Quite promising predictions are obtained using the jackknife test on three widely used datasets and compared with other state-of-the-art methods. The results indicate that the method proposed in this paper can remarkably improve the prediction accuracy of apoptosis protein subcellular localization, which will be a supplementary tool for future proteomics research.

Selective nitration of PsbO1, PsbO2, and PsbP1 decreases PSII oxygen evolution and photochemical efficiency in intact leaves of Arabidopsis

Exposure of intact Arabidopsis leaves to 40 ppm nitrogen dioxide (NO₂) in light resulted almost exclusively in nitration of PsbO1, PsbO2, and PsbP1 of photosystem II (PSII), with minor nitration of four non-PS II proteins, including peroxiredoxin II E, as reported previously. Our previous findings that light-triggered selective nitration of PsbO1 decreased oxygen evolution and that inhibition of photoelectric electron transport inhibited nitration of PsbO1 implied that the nitratable tyrosine residue of PsbO1 is redox-active. However, whether the nitratable tyrosine residues of PsbO2 and PsbP1 are redox-active is unknown. In this study, we determined the oxygen evolution and maximal photochemical efficiency of PSII in intact Arabidopsis leaves following exposure to 40 ppm NO₂ in light and found that these parameters were decreased to 60 and 70% of the non-exposed control, respectively. Because PsbO1, PsbO2, and PsbP1 accounted for > 80% of anti-3-nitrotyrosine antibody signal intensities, observed decreases in the oxygen evolution and maximal photochemical efficiency of PSII were mainly attributable to nitration of the tyrosine residues of these PSII proteins. Thus, it is postulated that nitratable tyrosine residues of PsbO2 and PsbP1 are redox-active, as in the case of PsbO1. A new hypothetical model is proposed.

The role of nitric oxide in melanoma

Nitric oxide (NO) is a small gaseous signaling molecule that mediates its effects in melanoma through free radical formation and enzymatic processes. Investigations have demonstrated multiple roles for NO in melanoma pathology via immune surveillance, apoptosis, angiogenesis, melanogenesis, and on the melanoma cell itself. In general, elevated levels of NO prognosticate a poor outcome for melanoma patients. However, there are processes where the relative concentration of NO in different environments may also serve to limit melanoma proliferation. This review serves to outline the roles of NO in melanoma development and proliferation. As demonstrated by multiple in vivo murine models and observations from human tissue, NO may promote melanoma formation and proliferation through its interaction via inhibitory immune cells, inhibition of apoptosis, stimulation of pro-tumorigenic cytokines, activation of tumor associated macrophages, alteration of angiogenic processes, and stimulation of melanoma formation itself.

Generation of nitric oxide by olive (Olea europaea L.) pollen during in vitro germination and assessment of the S-nitroso- and nitro-proteomes by computational predictive methods

Nitric oxide is recognized as a signaling molecule involved in a broad range of physiological processes in plants including sexual reproduction. NO has been detected in the pollen grain at high levels and regulates pollen tube growth. Previous studies demonstrated that NO as well as ROS are produced in the olive reproductive tissues in a stage- and tissue-specific manner. The aim of this study was to assess the production of NO throughout the germination of olive (Olea europaea L.) pollen in vitro. The NO fluorescent probe DAF-2DA was used to image NO production in situ, which was correlated to pollen viability. Moreover, by means of a fluorimetric assay we showed that growing pollen tubes release NO. GSNO -a mobile reservoir of NO, formed by the S-nitrosylation of NO with reduced glutathione (GSH) - was for the first time detected and quantified at different stages of pollen tube growth using a LC-ES/MS analysis. Exogenous NO donors inhibited both pollen germination and pollen tube growth and these effects were partially reverted by the specific NO-scavenger c-PTIO. However, little is known about how NO affects the germination process. With the aim of elucidating the putative relevance of protein S-nitrosylation and Tyr-nitration as important post-translational modifications in the development and physiology of the olive pollen, a de novo assembled and annotated reproductive transcriptome from olive was challenged in silico for the putative capability of transcripts to become potentially modified by S-nitrosylation/Tyr-nitration according to well-established criteria. Numerous gene products with these characteristics were identified, and a broad discussion as regards to their potential role in plant reproduction was built after their functional classification. Moreover, the importance of both S-nitrosylation/Tyr-nitrations was experimentally assessed and validated by using Western blotting, immunoprecipitation and proteomic approaches.

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.

Protein tyrosine nitration in plants: Present knowledge, computational prediction and future perspectives

Nitric oxide (NO) and related molecules (reactive nitrogen species) regulate diverse physiological processes mainly through posttranslational modifications such as protein tyrosine nitration (PTN). PTN is a covalent and specific modification of tyrosine (Tyr) residues resulting in altered protein structure and function. In the last decade, great efforts have been made to reveal candidate proteins, target Tyr residues and functional consequences of nitration in plants. This review intends to evaluate the accumulated knowledge about the biochemical mechanism, the structural and functional consequences and the selectivity of plants' protein nitration and also about the decomposition or conversion of nitrated proteins. At the same time, this review emphasizes yet unanswered or uncertain questions such as the reversibility/irreversibility of tyrosine nitration, the involvement of proteasomes in the removal of nitrated proteins or the effect of nitration on Tyr phosphorylation. The different NO producing systems of algae and higher plants raise the possibility of diversely regulated protein nitration. Therefore studying PTN from an evolutionary point of view would enrich our present understanding with novel aspects. Plant proteomic research can be promoted by the application of computational prediction tools such as GPS-YNO₂ and iNitro-Tyr software. Using the reference Arabidopsis proteome, Authors performed in silico analysis of tyrosine nitration in order to characterize plant tyrosine nitroproteome. Nevertheless, based on the common results of the present prediction and previous experiments the most likely nitrated proteins were selected thus recommending candidates for detailed future research.

Molecular modeling in the age of clinical genomics, the enterprise of the next generation

Protein modeling and molecular dynamics hold a unique toolset to aide in the characterization of clinical variants that may result in disease. Not only do these techniques offer the ability to study under characterized proteins, but they do this with the speed that is needed for time-sensitive clinical cases. In this paper we retrospectively study a clinical variant in the XIAP protein, C203Y, while addressing additional variants seen in patients with similar gastrointestinal phenotypes as the C203Y mutation. In agreement with the clinical tests performed on the C203Y patient, protein modeling and molecular dynamics suggest that direct interactions with RIPK2 and Caspase3 are altered by the C203Y mutation and subsequent loss of Zn coordination in the second BIR domain of XIAP. Interestingly, the variant does not appear to alter interactions with SMAC, resulting in further damage to the caspase and NOD2 pathways. To expand the computational strategy designed when studying XIAP, we have applied the molecular modeling tools to a list of 140 variants seen in CFTR associated with cystic fibrosis, and a list of undiagnosed variants in 17 different genes. This paper shows the exciting applications of molecular modeling in the classification and characterization of genetic variants identified in next generation sequencing. Graphical abstract XIAP in Caspase 3 and NOD2 signaling pathways.

Germline and somatic mutations in the MTOR gene in focal cortical dysplasia and epilepsy

Objective:

To assess the prevalence of somatic MTOR mutations in focal cortical dysplasia (FCD) and of germline MTOR mutations in a broad range of epilepsies.

Methods:

We collected 20 blood-brain paired samples from patients with FCD and searched for somatic variants using deep-targeted gene panel sequencing. Germline mutations in MTOR were assessed in a French research cohort of 93 probands with focal epilepsies and in a diagnostic Danish cohort of 245 patients with a broad range of epilepsies. Data sharing among collaborators allowed us to ascertain additional germline variants in MTOR.

Results:

We detected recurrent somatic variants (p.Ser2215Phe, p.Ser2215Tyr, and p.Leu1460Pro) in the MTOR gene in 37% of participants with FCD II and showed histologic evidence for activation of the mTORC1 signaling cascade in brain tissue. We further identified 5 novel de novo germline missense MTOR variants in 6 individuals with a variable phenotype from focal, and less frequently generalized, epilepsies without brain malformations, to macrocephaly, with or without moderate intellectual disability. In addition, an inherited variant was found in a mother–daughter pair with nonlesional autosomal dominant nocturnal frontal lobe epilepsy.

Conclusions:

Our data illustrate the increasingly important role of somatic mutations of the MTOR gene in FCD and germline mutations in the pathogenesis of focal epilepsy syndromes with and without brain malformation or macrocephaly.

Oxidative Stress Alters the Morphology and Toxicity of Aortic Medial Amyloid

The aggregation and fibril deposition of amyloid proteins have been implicated in a range of neurodegenerative and vascular diseases, and yet the underlying molecular mechanisms are poorly understood. Here, we use a combination of cell-based assays, biophysical analysis, and atomic force microscopy to investigate the potential involvement of oxidative stress in aortic medial amyloid (AMA) pathogenesis and deposition. We show that medin, the main constituent of AMA, can induce an environment rich in oxidative species, increasing superoxide and reducing bioavailable nitric oxide in human cells. We investigate the role that this oxidative environment may play in altering the aggregation process of medin and identify potential posttranslational modification sites where site-specific modification and interaction can be unambiguously demonstrated. In an oxidizing environment, medin is nitrated at tyrosine and tryptophan residues, with resultant effects on morphology that lead to longer fibrils with increased toxicity. This provides further motivation to investigate the role of oxidative stress in AMA pathogenicity.

The susceptibility of plasma coagulation factor XI to nitration and peroxynitrite action

Coagulation factor XI is present in blood plasma as the zymogen, like other serine proteases of hemostatic system, but as the only coagulation factor forms 140-160kDa homodimers. Its activation is induced by thrombin, and a positive feedback increases the generation of the extra thrombin. Experimental and clinical observations confirm protective roles of factor XI deficiencies in certain types of thromboembolic disorders. Thromboembolism still causes serious problems for modern civilization. Diseases associated with the blood coagulation system are often associated with inflammation and oxidative stress. Peroxynitrite is produced from nitric oxide and superoxide in inflammatory diseases. The aim of the current study is to evaluate effects of nitrative stress triggered by peroxynitrite on coagulation factor XI in human plasma employing biochemical and bioinformatic methods. The amidolytic assay shows increase in factor XI activity triggered by peroxynitrite. Peroxynitrite interferes factor XI by nitration and fragmentation, which is demonstrated by immunoprecipitation followed by western blotting. Nitrated factor XI is even present in control blood plasma. The results suggest possible modifications of factor XI on the molecular level. Computer simulations show tyrosine residues as targets of peroxynitrite action. The modifications induced by peroxynitrite in factor XI might be important in thrombotic disorders.

Implication of nitric oxide (NO) in excess element-induced morphogenic responses of the root system

Extremes of metal and non-metal elements in the soils create a stressful environment and plants exposed to sub-lethal abiotic stress conditions show a broad range of morphogenic responses designated as stress-induced morphogenic response (SIMR). Being the first plant organ directly contacting with elevated doses of elements, the root system shows remarkable symptoms and deserves special attention. In the signalling of root SIMR, the involvement of phytohormones (especially auxin) and reactive oxygen species (ROS) has been earlier suggested. Emerging evidence supports that nitric oxide (NO) and related molecules (reactive nitrogen species, RNS) are integral signals of root system development, and they are active components of heavy metal-induced stress responses as well. Based on these, the main scope of this review is to demonstrate the contribution of NO/RNS to the emergence of excess element-induced root morphogenic responses. The SIMR-like root system of lead-treated Arabidopsis thaliana contained elevated NO levels compared to the root not showing SIMR. In NO-deficient nia1nia2 plants, the degree of selenium-induced root SIMR was, in some characteristics altered compared to the wild-type. Moreover, among the molecular elements of SIMR several potential candidates of NO-dependent S-nitrosylation or tyrosine nitration have been found using computational prediction. The demonstrated literature data together with own experimental results strongly outline that NO/RNS are regulating signals in the development of root SIMR in case of excess metal and non-metal elements. This also reveals a new role of NO in acclimation emphasizing its importance in defence mechanisms against abiotic stresses.