S-nitrosylation and S-glutathionylation: Lying at the forefront of redox dichotomy or a visible synergism?

The discovery of novel oxidoreductases and their specific functional revelations as cellular disulfide reductants, S-denitrosylases, or S-deglutathionylases, alongside the well-established major redoxins/antioxidant systems comprising thioredoxin and glutaredoxin, enlarges the spectrum of redox players in the intracellular milieu as well as pushes us to stand at the crossroads concerning the choice of antioxidants that can serve the benefit of catalyzing their cognate protein/non-protein substrates with better efficiencies than the rest. The complexity is extended to exploring the redundancy amongst the redoxin systems and identifying their overlapping or unique substrate preferences to intervene with oxidative or nitrosative stress-induced reversible protein posttranslational modifications such as S-nitrosylation and S-glutathionylation. Contrary to popular expectations of reiterating the theoretical and evidence-based existence of these modifications, the current review aims to take the first leap in delineating the logical reasons behind the competing susceptibility of reactive cysteine thiols toward either or both redox modifications and their subsequent extent of stability in the presence of cellular reductants (thioredoxin, glutaredoxin, thioredoxin-like mimetic or lipoic acid, dihydrolipoic acid, and glutathione), thus rebuilding the underpinnings of a 'redox-interactome' that can further pave the way for the global mapping of ideal substrates exhibiting stringencies or synergism in the context of translational redox research.

De-nitrosylation Coordinates Appressorium Function for Infection of the Rice Blast Fungus

As a signaling molecule, nitric oxide (NO) regulates the development and stress response in different organisms. The major biological activity of NO is protein S-nitrosylation, whose function in fungi remains largely unclear. Here, it is found in the rice blast fungus Magnaporthe oryzae, de-nitrosylation process is essential for functional appressorium formation during infection. Nitrosative stress caused by excessive accumulation of NO is harmful for fungal infection. While the S-nitrosoglutathione reductase GSNOR-mediated de-nitrosylation removes excess NO toxicity during appressorium formation to promote infection. Through an indoTMT switch labeling proteomics technique, 741 S-nitrosylation sites in 483 proteins are identified. Key appressorial proteins, such as Mgb1, MagB, Sps1, Cdc42, and septins, are activated by GSNOR through de-nitrosylation. Removing S-nitrosylation sites of above proteins is essential for proper protein structure and appressorial function. Therefore, GSNOR-mediated de-nitrosylation is an essential regulator for appressorium formation. It is also shown that breaking NO homeostasis by NO donors, NO scavengers, as well as chemical inhibitor of GSNOR, shall be effective methods for fungal disease control.

Redox proteomics of PANC-1 cells reveals the significance of HIF-1 signaling protein oxidation in pancreatic ductal adenocarcinoma pathogenesis

BACKGROUND

Protein cysteine oxidation is substantially involved in various biological and pathogenic processes, but its implications in pancreatic cancer development remains poorly understood.

METHODS AND RESULTS

In this study, we performed a global characterization of protein oxidation targets in PDAC cells through iodoTMT-based quantitative proteomics, which identified over 4300 oxidized cysteine sites in more than 2100 proteins in HPDE6c7 and PANC-1 cells. Among them, 1715 cysteine residues were shown to be differentially oxidized between HPDE6c7 and PANC-1 cells. Also, charged amino acids including aspartate, glutamate and lysine were significantly overrepresented in flanking sequences of oxidized cysteines. Differentially oxidized proteins in PANC-1 cells were enriched in multiple cancer-related biological processes and signaling pathways. Specifically, the HIF-1 signaling proteins exhibited significant oxidation alterations in PANC-1 cells, and the reduced PHD2 oxidation in human PDAC tissues was correlated with lower survival time in pancreatic cancer patients.

CONCLUSION

These investigations provided new insights into protein oxidation-regulated signaling and biological processes during PDAC pathogenesis, which might be further explored for pancreatic cancer diagnosis and treatment.

Protein S-Nitrosation: Biochemistry, Identification, Molecular Mechanisms, and Therapeutic Applications

Protein S-nitrosation (SNO), a posttranslational modification (PTM) of cysteine (Cys) residues elicited by nitric oxide (NO), regulates a wide range of protein functions. As a crucial form of redox-based signaling by NO, SNO contributes significantly to the modulation of physiological functions, and SNO imbalance is closely linked to pathophysiological processes. Site-specific identification of the SNO protein is critical for understanding the underlying molecular mechanisms of protein function regulation. Although careful verification is needed, SNO modification data containing numerous functional proteins are a potential research direction for druggable target identification and drug discovery. Undoubtedly, SNO-related research is meaningful not only for the development of NO donor drugs but also for classic target-based drug design. Herein, we provide a comprehensive summary of SNO, including its origin and transport, identification, function, and potential contribution to drug discovery. Importantly, we propose new views to develop novel therapies based on potential protein SNO-sourced targets.

FAIMS Enhances the Detection of PTM Crosstalk Sites

Protein post-translational modifications (PTMs) enable cells to rapidly change in response to biological stimuli. With hundreds of different PTMs, understanding these control mechanisms is complex. To date, efforts have focused on investigating the effect of a single PTM on protein function. Yet, many proteins contain multiple PTMs. Moreover, one PTM can alter the prevalence of another, a phenomenon termed PTM crosstalk. Understanding PTM crosstalk is critical; however, its detection is challenging since PTMs occur substoichiometrically. Here, we develop an enrichment-free, label-free proteomics method that utilizes high-field asymmetric ion mobility spectrometry (FAIMS) to enhance the detection of PTM crosstalk. We show that by searching for multiple combinations of dynamic PTMs on peptide sequences, a 6-fold increase in candidate PTM crosstalk sites is identified compared with that of standard liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflows. Additionally, by cycling through FAIMS compensation voltages within a single LC-FAIMS-MS/MS run, we show that our LC-FAIMS-MS/MS workflow can increase multi-PTM-containing peptide identifications without additional increases in run times. With 159 novel candidate crosstalk sites identified, we envisage LC-FAIMS-MS/MS to play an important role in expanding the repertoire of multi-PTM identifications. Moreover, it is only by detecting PTM crosstalk that we can "see" the full picture of how proteins are regulated.

Hsp70 in Redox Homeostasis

Cellular redox homeostasis is precisely balanced by generation and elimination of reactive oxygen species (ROS). ROS are not only capable of causing oxidation of proteins, lipids and DNA to damage cells but can also act as signaling molecules to modulate transcription factors and epigenetic pathways that determine cell survival and death. Hsp70 proteins are central hubs for proteostasis and are important factors to ameliorate damage from different kinds of stress including oxidative stress. Hsp70 members often participate in different cellular signaling pathways via their clients and cochaperones. ROS can directly cause oxidative cysteine modifications of Hsp70 members to alter their structure and chaperone activity, resulting in changes in the interactions between Hsp70 and their clients or cochaperones, which can then transfer redox signals to Hsp70-related signaling pathways. On the other hand, ROS also activate some redox-related signaling pathways to indirectly modulate Hsp70 activity and expression. Post-translational modifications including phosphorylation together with elevated Hsp70 expression can expand the capacity of Hsp70 to deal with ROS-damaged proteins and support antioxidant enzymes. Knowledge about the response and role of Hsp70 in redox homeostasis will facilitate our understanding of the cellular knock-on effects of inhibitors targeting Hsp70 and the mechanisms of redox-related diseases and aging.

Current status of PTMs structural databases: applications, limitations and prospects

Protein 3D structures, determined by their amino acid sequences, are the support of major crucial biological functions. Post-translational modifications (PTMs) play an essential role in regulating these functions by altering the physicochemical properties of proteins. By virtue of their importance, several PTM databases have been developed and released in decades, but very few of these databases incorporate real 3D structural data. Since PTMs influence the function of the protein and their aberrant states are frequently implicated in human diseases, providing structural insights to understand the influence and dynamics of PTMs is crucial for unraveling the underlying processes. This review is dedicated to the current status of databases providing 3D structural data on PTM sites in proteins. Some of these databases are general, covering multiple types of PTMs in different organisms, while others are specific to one particular type of PTM, class of proteins or organism. The importance of these databases is illustrated with two major types of in silico applications: predicting PTM sites in proteins using machine learning approaches and investigating protein structure-function relationships involving PTMs. Finally, these databases suffer from multiple problems and care must be taken when analyzing the PTMs data.

Oxidative Modification of Proteins: From Damage to Catalysis, Signaling, and Beyond

Significance: The systematic investigation of oxidative modification of proteins by reactive oxygen species started in 1980. Later, it was shown that reactive nitrogen species could also modify proteins. Some protein oxidative modifications promote loss of protein function, cleavage or aggregation, and some result in proteo-toxicity and cellular homeostasis disruption. Recent Advances: Previously, protein oxidation was associated exclusively to damage. However, not all oxidative modifications are necessarily associated with damage, as with Met and Cys protein residue oxidation. In these cases, redox state changes can alter protein structure, catalytic function, and signaling processes in response to metabolic and/or environmental alterations. This review aims to integrate the present knowledge on redox modifications of proteins with their fate and role in redox signaling and human pathological conditions. Critical Issues: It is hypothesized that protein oxidation participates in the development and progression of many pathological conditions. However, no quantitative data have been correlated with specific oxidized proteins or the progression or severity of pathological conditions. Hence, the comprehension of the mechanisms underlying these modifications, their importance in human pathologies, and the fate of the modified proteins is of clinical relevance. Future Directions: We discuss new tools to cope with protein oxidation and suggest new approaches for integrating knowledge about protein oxidation and redox processes with human pathophysiological conditions. Antioxid. Redox Signal. 35, 1016-1080.

Stability of S-nitrosothiols and S-nitrosylated proteins: A struggle for cellular existence!

Nitric oxide is a well-known gasotransmitter molecule that covalently docks to sulfhydryl groups of proteins resulting in S-nitrosylation of proteins and nonprotein thiols that serve a variety of cellular processes including cGMP signaling, vasodilatation, neurotransmission, ion-channel modulation, and cardiac signaling. S-nitrosylation is an indispensable modification like phosphorylation that directly regulates the functionality of numerous proteins. However, recently there has been a controversy over the stability of S-nitrosylated proteins (PSNOs) within the cell. It has been argued that PSNOs formed within the cell is a transient intermediate step to more stable disulfide formation and disulfides are the predominant end effector modifications in NO-mediated signaling. The present article accumulates state-of-the-art evidence from numerous research that strongly supports the very existence of PSNOs within the cell and attempts to put an end to the controversy. This review illustrates critical points including comparative bond dissociation energies of S-NO bond, the half-life of S-nitrosothiols and PSNOs, cellular concentrations of PSNOs, X ray crystallographic studies on PSNOs, and stability of PSNOs at physiological concentration of antioxidants. These logical evidence cumulatively support the endogenous stability and inevitable existence of PSNOs/RSNOs within the cell that directly regulate the functionality of proteins and provide valuable insight into understanding stable S-nitrosylation mediated cell signaling.

Understanding the role of S-nitrosylation/nitrosative stress in inflammation and the role of cellular denitrosylases in inflammation modulation: Implications in health and diseases

S-nitrosylation is a very fundamental post-translational modification of protein and non-protein thiols due the involvement of it in a variety of cellular processes including activation/inhibition of several ion channels such as ryanodine receptor in the cardiovascular system; blood vessel dilation; cGMP signaling and neurotransmission. S-nitrosothiol homeostasis in the cell is tightly regulated and perturbations in homeostasis result in an altered redox state leading to a plethora of disease conditions. However, the exact role of S-nitrosylated proteins and nitrosative stress metabolites in inflammation and in inflammation modulation is not well-reviewed. The cell utilizes its intricate defense mechanisms i.e. cellular denitrosylases such as Thioredoxin (Trx) and S-nitrosoglutathione reductase (GSNOR) systems to combat nitric oxide (NO) pathology which has also gained current attraction as novel anti-inflammatory molecules. This review attempts to provide state-of-the-art knowledge from past and present research on the mechanistic role of nitrosative stress intermediates (RNS, OONO^-, PSNO) in pulmonary and autoimmune diseases and how cellular denitrosylases particularly GSNOR and Trx via imparting opposing effects can modulate and reduce inflammation in several health and disease conditions. This review would also bring into notice the existing gaps in current research where denitrosylases can be utilized for ameliorating inflammation that would leave avenues for future therapeutic interventions.

Gel-based fluorescent proteomic tools for investigating cell redox signaling. A mini-review

The specific chemical reactivity of thiol groups makes protein cysteines susceptible to reactions with reactive oxygen species (ROS) and reactive nitrogen species (RNS) resulting in the formation of various reversible and irreversible oxidative post-translational modifications (oxPTMs). This review highlights a number of gel-based redox proteomic approaches to detect protein oxPTMs, with particular emphasis on S-nitrosylation, which we believe are currently one of the most accurate way to analyze changes in the redox status of proteins. The information collected in this review relates to the recent progress regarding methods for the enrichment and identification of redox-modified proteins, with an emphasis on fluorescent gel proteomics. Gel-based fluorescent proteomic strategies are low-cost and easy-to-use tools for investigating the thiol proteome and can provide substantial information on redox signaling.

iCysMod: an integrative database for protein cysteine modifications in eukaryotes

As important post-translational modifications, protein cysteine modifications (PCMs) occurring at cysteine thiol group play critical roles in the regulation of various biological processes in eukaryotes. Due to the rapid advancement of high-throughput proteomics technologies, a large number of PCM events have been identified but remain to be curated. Thus, an integrated resource of eukaryotic PCMs will be useful for the research community. In this work, we developed an integrative database for protein cysteine modifications in eukaryotes (iCysMod), which curated and hosted 108 030 PCM events for 85 747 experimentally identified sites on 31 483 proteins from 48 eukaryotes for 8 types of PCMs, including oxidation, S-nitrosylation (-SNO), S-glutathionylation (-SSG), disulfide formation (-SSR), S-sulfhydration (-SSH), S-sulfenylation (-SOH), S-sulfinylation (-SO2H) and S-palmitoylation (-S-palm). Then, browse and search options were provided for accessing the dataset, while various detailed information about the PCM events was well organized for visualization. With human dataset in iCysMod, the sequence features around the cysteine modification sites for each PCM type were analyzed, and the results indicated that various types of PCMs presented distinct sequence recognition preferences. Moreover, different PCMs can crosstalk with each other to synergistically orchestrate specific biological processes, and 37 841 PCM events involved in 119 types of PCM co-occurrences at the same cysteine residues were finally obtained. Taken together, we anticipate that the database of iCysMod would provide a useful resource for eukaryotic PCMs to facilitate related researches, while the online service is freely available at http://icysmod.omicsbio.info.

Stochiometric quantification of the thiol redox proteome of macrophages reveals subcellular compartmentalization and susceptibility to oxidative perturbations

Posttranslational modifications of protein cysteine thiols play a significant role in redox regulation and the pathogenesis of human diseases. Herein, we report the characterization of the cellular redox landscape in terms of quantitative, site-specific occupancies of both S-glutathionylation (SSG) and total reversible thiol oxidation (total oxidation) in RAW 264.7 macrophage cells under basal conditions. The occupancies of thiol modifications for ~4000 cysteine sites were quantified, revealing a mean site occupancy of 4.0% for SSG and 11.9% for total oxidation, respectively. Correlations between site occupancies and structural features such as pKa, relative residue surface accessibility, and hydrophobicity were observed. Proteome-wide site occupancy analysis revealed that the average occupancies of SSG and total oxidation in specific cellular compartments correlate well with the expected redox potentials of respective organelles in macrophages, consistent with the notion of redox compartmentalization. The lowest average occupancies were observed in more reducing organelles such as the mitochondria (non-membrane) and nucleus, while the highest average occupancies were found in more oxidizing organelles such as endoplasmic reticulum (ER) and lysosome. Furthermore, a pattern of subcellular susceptibility to redox changes was observed under oxidative stress induced by exposure to engineered metal oxide nanoparticles. Peroxisome, ER, and mitochondria (membrane) are the organelles which exhibit the most significant redox changes; while mitochondria (non-membrane) and Golgi were observed as the organelles being most resistant to oxidative stress. Finally, it was observed that Cys residues at enzymatic active sites generally had a higher level of occupancy compared to non-active Cys residues within the same proteins, suggesting site occupancy as a potential indicator of protein functional sites. The raw data are available via ProteomeXchange with identifier PXD019913.

Chronic liver disease and impaired hepatic glycogen metabolism in argininosuccinate lyase deficiency

BACKGROUNDLiver disease in urea cycle disorders (UCDs) ranges from hepatomegaly and chronic hepatocellular injury to cirrhosis and end-stage liver disease. However, the prevalence and underlying mechanisms are unclear.METHODSWe estimated the prevalence of chronic hepatocellular injury in UCDs using data from a multicenter, longitudinal, natural history study. We also used ultrasound with shear wave elastography and FibroTest to evaluate liver stiffness and markers of fibrosis in individuals with argininosuccinate lyase deficiency (ASLD), a disorder with high prevalence of elevated serum alanine aminotransferase (ALT). To understand the human observations, we evaluated the hepatic phenotype of the AslNeo/Neo mouse model of ASLD.RESULTSWe demonstrate a high prevalence of elevated ALT in ASLD (37%). Hyperammonemia and use of nitrogen-scavenging agents, 2 markers of disease severity, were significantly (P < 0.001 and P = 0.001, respectively) associated with elevated ALT in ASLD. In addition, ultrasound with shear wave elastography and FibroTest revealed increased echogenicity and liver stiffness, even in individuals with ASLD and normal aminotransferases. The AslNeo/Neo mice mimic the human disorder with hepatomegaly, elevated aminotransferases, and excessive hepatic glycogen noted before death (3-5 weeks of age). This excessive hepatic glycogen is associated with impaired hepatic glycogenolysis and decreased glycogen phosphorylase and is rescued with helper-dependent adenovirus expressing Asl using a liver-specific (ApoE) promoter.CONCLUSIONOur results link urea cycle dysfunction and impaired hepatic glucose metabolism and identify a mouse model of liver disease in the setting of urea cycle dysfunction.TRIAL REGISTRATIONThis study has been registered at ClinicalTrials.gov (NCT03721367, NCT00237315).FUNDINGFunding was provided by NIH, Burroughs Wellcome Fund, NUCDF, Genzyme/ACMG Foundation, and CPRIT.

Quantitative proteomics of synaptosome S-nitrosylation in Alzheimer's disease

Increasing evidence suggests that both synaptic loss and neuroinflammation constitute early pathologic hallmarks of Alzheimer's disease. A downstream event during inflammatory activation of microglia and astrocytes is the induction of nitric oxide synthase type 2, resulting in an increased release of nitric oxide and the post-translational S-nitrosylation of protein cysteine residues. Both early events, inflammation and synaptic dysfunction, could be connected if this excess nitrosylation occurs on synaptic proteins. In the long term, such changes could provide new insight into patho-mechanisms as well as biomarker candidates from the early stages of disease progression. This study investigated S-nitrosylation in synaptosomal proteins isolated from APP/PS1 model mice in comparison to wild type and NOS2^-/- mice, as well as human control, mild cognitive impairment and Alzheimer's disease brain tissues. Proteomics data were obtained using an established protocol utilizing an isobaric mass tag method, followed by nanocapillary high performance liquid chromatography tandem mass spectrometry. Statistical analysis identified the S-nitrosylation sites most likely derived from an increase in nitric oxide (NO) in dependence of presence of AD pathology, age and the key enzyme NOS2. The resulting list of candidate proteins is discussed considering function, previous findings in the context of neurodegeneration, and the potential for further validation studies.

Reduced Basal Nitric Oxide Production Induces Precancerous Mammary Lesions via ERBB2 and TGFβ

One third of newly diagnosed breast cancers in the US are early-stage lesions. The etiological understanding and treatment of these lesions have become major clinical challenges. Because breast cancer risk factors are often linked to aberrant nitric oxide (NO) production, we hypothesized that abnormal NO levels might contribute to the formation of early-stage breast lesions. We recently reported that the basal level of NO in the normal breast epithelia plays crucial roles in tissue homeostasis, whereas its reduction contributes to the malignant phenotype of cancer cells. Here, we show that the basal level of NO in breast cells plummets during cancer progression due to reduction of the NO synthase cofactor, BH₄, under oxidative stress. Importantly, pharmacological deprivation of NO in prepubertal to pubertal animals stiffens the extracellular matrix and induces precancerous lesions in the mammary tissues. These lesions overexpress a fibrogenic cytokine, TGFβ, and an oncogene, ERBB2, accompanied by the occurrence of senescence and stem cell-like phenotype. Consistently, normalization of NO levels in precancerous and cancerous breast cells downmodulates TGFβ and ERBB2 and ameliorates their proliferative phenotype. This study sheds new light on the etiological basis of precancerous breast lesions and their potential prevention by manipulating the basal NO level.

Characterization and identification of lysine glutarylation based on intrinsic interdependence between positions in the substrate sites

Background

Glutarylation, the addition of a glutaryl group (five carbons) to a lysine residue of a protein molecule, is an important post-translational modification and plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified glutarylated peptides increases, it becomes imperative to investigate substrate motifs to enhance the study of protein glutarylation. We carried out a bioinformatics investigation of glutarylation sites based on amino acid composition using a public database containing information on 430 non-homologous glutarylation sites.

Results

The TwoSampleLogo analysis indicates that positively charged and polar amino acids surrounding glutarylated sites may be associated with the specificity in substrate site of protein glutarylation. Additionally, the chi-squared test was utilized to explore the intrinsic interdependence between two positions around glutarylation sites. Further, maximal dependence decomposition (MDD), which consists of partitioning a large-scale dataset into subgroups with statistically significant amino acid conservation, was used to capture motif signatures of glutarylation sites. We considered single features, such as amino acid composition (AAC), amino acid pair composition (AAPC), and composition of k-spaced amino acid pairs (CKSAAP), as well as the effectiveness of incorporating MDD-identified substrate motifs into an integrated prediction model. Evaluation by five-fold cross-validation showed that AAC was most effective in discriminating between glutarylation and non-glutarylation sites, according to support vector machine (SVM).

Conclusions

The SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.677, a specificity of 0.619, an accuracy of 0.638, and a Matthews Correlation Coefficient (MCC) value of 0.28. Using an independent testing dataset (46 glutarylated and 92 non-glutarylated sites) obtained from the literature, we demonstrated that the integrated SVM model could improve the predictive performance effectively, yielding a balanced sensitivity and specificity of 0.652 and 0.739, respectively. This integrated SVM model has been implemented as a web-based system (MDDGlutar), which is now freely available at http://csb.cse.yzu.edu.tw/MDDGlutar/.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2394-9) contains supplementary material, which is available to authorized users.

Computational Structural Biology of S-nitrosylation of Cancer Targets

Nitric oxide (NO) plays an essential role in redox signaling in normal and pathological cellular conditions. In particular, it is well known to react in vivo with cysteines by the so-called S-nitrosylation reaction. S-nitrosylation is a selective and reversible post-translational modification that exerts a myriad of different effects, such as the modulation of protein conformation, activity, stability, and biological interaction networks. We have appreciated, over the last years, the role of S-nitrosylation in normal and disease conditions. In this context, structural and computational studies can help to dissect the complex and multifaceted role of this redox post-translational modification. In this review article, we summarized the current state-of-the-art on the mechanism of S-nitrosylation, along with the structural and computational studies that have helped to unveil its effects and biological roles. We also discussed the need to move new steps forward especially in the direction of employing computational structural biology to address the molecular and atomistic details of S-nitrosylation. Indeed, this redox modification has been so far an underappreciated redox post-translational modification by the computational biochemistry community. In our review, we primarily focus on S-nitrosylated proteins that are attractive cancer targets due to the emerging relevance of this redox modification in a cancer setting.

Specificity in nitric oxide signalling

Reactive nitrogen species (RNS) and their cognate redox signalling networks pervade almost all facets of plant growth, development, immunity, and environmental interactions. The emerging evidence implies that specificity in redox signalling is achieved by a multilayered molecular framework. This encompasses the production of redox cues in the locale of the given protein target and protein tertiary structures that convey the appropriate local chemical environment to support redox-based, post-translational modifications (PTMs). Nascent nitrosylases have also recently emerged that mediate the formation of redox-based PTMs. Reversal of these redox-based PTMs, rather than their formation, is also a major contributor of signalling specificity. In this context, the activities of S-nitrosoglutathione (GSNO) reductase and thioredoxin h5 (Trxh5) are a key feature. Redox signalling specificity is also conveyed by the unique chemistries of individual RNS which is overlaid on the structural constraints imposed by tertiary protein structure in gating access to given redox switches. Finally, the interactions between RNS and ROS (reactive oxygen species) can also indirectly establish signalling specificity through shaping the formation of appropriate redox cues. It is anticipated that some of these insights might function as primers to initiate their future translation into agricultural, horticultural, and industrial biological applications.

ROS and RNS signalling: adaptive redox switches through oxidative/nitrosative protein modifications

Over the last decade, a dual character of cell response to oxidative stress, eustress versus distress, has become increasingly recognized. A growing body of evidence indicates that under physiological conditions, low concentrations of reactive oxygen and nitrogen species (RONS) maintained by the activity of endogenous antioxidant system (AOS) allow reversible oxidative/nitrosative modifications of key redox-sensitive residues in regulatory proteins. The reversibility of redox modifications such as Cys S-sulphenylation/S-glutathionylation/S-nitrosylation/S-persulphidation and disulphide bond formation, or Tyr nitration, which occur through electrophilic attack of RONS to nucleophilic groups in amino acid residues provides redox switches in the activities of signalling proteins. Key requirement for the involvement of the redox modifications in RONS signalling including ROS-MAPK, ROS-PI3K/Akt, and RNS-TNF-α/NF-kB signalling is their specificity provided by a residue microenvironment and reaction kinetics. Glutathione, glutathione peroxidases, peroxiredoxins, thioredoxin, glutathione reductases, and glutaredoxins modulate RONS level and cell signalling, while some of the modulators (glutathione, glutathione peroxidases and peroxiredoxins) are themselves targets for redox modifications. Additionally, gene expression, activities of transcription factors, and epigenetic pathways are also under redox regulation. The present review focuses on RONS sources (NADPH-oxidases, mitochondrial electron-transportation chain (ETC), nitric oxide synthase (NOS), etc.), and their cross-talks, which influence reversible redox modifications of proteins as physiological phenomenon attained by living cells during the evolution to control cell signalling in the oxygen-enriched environment. We discussed recent advances in investigation of mechanisms of protein redox modifications and adaptive redox switches such as MAPK/PI3K/PTEN, Nrf2/Keap1, and NF-κB/IκB, powerful regulators of numerous physiological processes, also implicated in various diseases.

BioMuta and BioXpress: mutation and expression knowledgebases for cancer biomarker discovery

Single-nucleotide variation and gene expression of disease samples represent important resources for biomarker discovery. Many databases have been built to host and make available such data to the community, but these databases are frequently limited in scope and/or content. BioMuta, a database of cancer-associated single-nucleotide variations, and BioXpress, a database of cancer-associated differentially expressed genes and microRNAs, differ from other disease-associated variation and expression databases primarily through the aggregation of data across many studies into a single source with a unified representation and annotation of functional attributes. Early versions of these resources were initiated by pilot funding for specific research applications, but newly awarded funds have enabled hardening of these databases to production-level quality and will allow for sustained development of these resources for the next few years. Because both resources were developed using a similar methodology of integration, curation, unification, and annotation, we present BioMuta and BioXpress as allied databases that will facilitate a more comprehensive view of gene associations in cancer. BioMuta and BioXpress are hosted on the High-performance Integrated Virtual Environment (HIVE) server at the George Washington University at https://hive.biochemistry.gwu.edu/biomuta and https://hive.biochemistry.gwu.edu/bioxpress, respectively.

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions

Background

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM’s function is critical to our ability to manipulate the biological mechanisms of protein.

Results

In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking tools for exploring the structural characteristics of PTMs, is presented. In addition, all tertiary structures of PTM sites on proteins can be visualized using the JSmol program.

Conclusion

Resolving the function of PTM sites is important for understanding the role that proteins play in biological mechanisms. Our work attempted to delineate the structural correlation between PTM sites and PPI or drug-target binding. CurxPTM could help scientists narrow the scope of their PTM research and enhance the efficiency of PTM identification in the face of big proteome data. CruxPTM is now available at http://csb.cse.yzu.edu.tw/CruxPTM/.

Electronic supplementary material

The online version of this article (10.1186/s12918-017-0506-1) contains supplementary material, which is available to authorized users.

S-Nitrosylation inhibits the kinase activity of tomato phosphoinositide-dependent kinase 1 (PDK1)

It is well known that the reactive oxygen species NO can trigger cell death in plants and other organisms, but the underlying molecular mechanisms are not well understood. Here we provide evidence that NO may trigger cell death in tomato (Solanum lycopersicum) by inhibiting the activity of phosphoinositide-dependent kinase 1 (SlPDK1), a conserved negative regulator of cell death in yeasts, mammals, and plants, via S-nitrosylation. Biotin-switch assays indicated that SlPDK1 is a target of S-nitrosylation. Moreover, the kinase activity of SlPDK1 was inhibited by S-nitrosoglutathione in a concentration-dependent manner, indicating that SlPDK1 activity is abrogated by S-nitrosylation. The S-nitrosoglutathione-induced inhibition was reversible in the presence of a reducing agent but additively enhanced by hydrogen peroxide (H₂O₂). Our LC-MS/MS analyses further indicated that SlPDK1 is primarily S-nitrosylated on a cysteine residue at position 128 (Cys¹²⁸), and substitution of Cys¹²⁸ with serine completely abolished SlPDK1 kinase activity, suggesting that S-nitrosylation of Cys¹²⁸ is responsible for SlPDK1 inhibition. In summary, our results establish a potential link between NO-triggered cell death and inhibition of the kinase activity of tomato PDK1.

MDD-Palm: Identification of protein S-palmitoylation sites with substrate motifs based on maximal dependence decomposition

S-palmitoylation, the covalent attachment of 16-carbon palmitic acids to a cysteine residue via a thioester linkage, is an important reversible lipid modification that plays a regulatory role in a variety of physiological and biological processes. As the number of experimentally identified S-palmitoylated peptides increases, it is imperative to investigate substrate motifs to facilitate the study of protein S-palmitoylation. Based on 710 non-homologous S-palmitoylation sites obtained from published databases and the literature, we carried out a bioinformatics investigation of S-palmitoylation sites based on amino acid composition. Two Sample Logo indicates that positively charged and polar amino acids surrounding S-palmitoylated sites may be associated with the substrate site specificity of protein S-palmitoylation. Additionally, maximal dependence decomposition (MDD) was applied to explore the motif signatures of S-palmitoylation sites by categorizing a large-scale dataset into subgroups with statistically significant conservation of amino acids. Single features such as amino acid composition (AAC), amino acid pair composition (AAPC), position specific scoring matrix (PSSM), position weight matrix (PWM), amino acid substitution matrix (BLOSUM62), and accessible surface area (ASA) were considered, along with the effectiveness of incorporating MDD-identified substrate motifs into a two-layered prediction model. Evaluation by five-fold cross-validation showed that a hybrid of AAC and PSSM performs best at discriminating between S-palmitoylation and non-S-palmitoylation sites, according to the support vector machine (SVM). The two-layered SVM model integrating MDD-identified substrate motifs performed well, with a sensitivity of 0.79, specificity of 0.80, accuracy of 0.80, and Matthews Correlation Coefficient (MCC) value of 0.45. Using an independent testing dataset (613 S-palmitoylated and 5412 non-S-palmitoylated sites) obtained from the literature, we demonstrated that the two-layered SVM model could outperform other prediction tools, yielding a balanced sensitivity and specificity of 0.690 and 0.694, respectively. This two-layered SVM model has been implemented as a web-based system (MDD-Palm), which is now freely available at http://csb.cse.yzu.edu.tw/MDDPalm/.

Quantitative proteomic characterization of redox-dependent post-translational modifications on protein cysteines

Protein thiols play a crucial role in redox signaling, in the regulation of enzymatic activity and protein function, and in maintaining redox homeostasis in living systems. The unique chemical reactivity of the thiol group makes protein cysteines susceptible to reactions with reactive oxygen and nitrogen species that form various reversible and irreversible post-translational modifications (PTMs). The reversible PTMs in particular are major components of redox signaling and are involved in the regulation of various cellular processes under physiological and pathological conditions. The biological significance of these redox PTMs in both healthy and disease states has been increasingly recognized. Herein, we review recent advances in quantitative proteomic approaches for investigating redox PTMs in complex biological systems, including general considerations of sample processing, chemical or affinity enrichment strategies, and quantitative approaches. We also highlight a number of redox proteomic approaches that enable effective profiling of redox PTMs for specific biological applications. Although technical limitations remain, redox proteomics is paving the way to a better understanding of redox signaling and regulation in both healthy and disease states.

A New Scheme to Characterize and Identify Protein Ubiquitination Sites

Protein ubiquitination, involving the conjugation of ubiquitin on lysine residue, serves as an important modulator of many cellular functions in eukaryotes. Recent advancements in proteomic technology have stimulated increasing interest in identifying ubiquitination sites. However, most computational tools for predicting ubiquitination sites are focused on small-scale data. With an increasing number of experimentally verified ubiquitination sites, we were motivated to design a predictive model for identifying lysine ubiquitination sites for large-scale proteome dataset. This work assessed not only single features, such as amino acid composition (AAC), amino acid pair composition (AAPC) and evolutionary information, but also the effectiveness of incorporating two or more features into a hybrid approach to model construction. The support vector machine (SVM) was applied to generate the prediction models for ubiquitination site identification. Evaluation by five-fold cross-validation showed that the SVM models learned from the combination of hybrid features delivered a better prediction performance. Additionally, a motif discovery tool, MDDLogo, was adopted to characterize the potential substrate motifs of ubiquitination sites. The SVM models integrating the MDDLogo-identified substrate motifs could yield an average accuracy of 68.70 percent. Furthermore, the independent testing result showed that the MDDLogo-clustered SVM models could provide a promising accuracy (78.50 percent) and perform better than other prediction tools. Two cases have demonstrated the effective prediction of ubiquitination sites with corresponding substrate motifs.

Impact of Nonsynonymous Single-Nucleotide Variations on Post-Translational Modification Sites in Human Proteins

Post-translational modifications (PTMs) are covalent modifications that proteins might undergo following or sometimes during the process of translation. Together with gene diversity, PTMs contribute to the overall variety of possible protein function for a given organism. Single-nucleotide polymorphisms (SNPs) are the most common form of variations found in the human genome, and have been found to be associated with diseases like Alzheimer's disease (AD) and Parkinson's disease (PD), among many others. Studies have also shown that non-synonymous single-nucleotide variation (nsSNV) at the PTM site, which alters the corresponding encoded amino acid in the translated protein sequence, can lead to abnormal activity of a protein and can contribute to a disease phenotype. Significant advances in next-generation sequencing (NGS) technologies and high-throughput proteomics have resulted in the generation of a huge amount of data for both SNPs and PTMs. However, these data are unsystematically distributed across a number of diverse databases. Thus, there is a need for efforts toward data standardization and validation of bioinformatics algorithms that can fully leverage SNP and PTM information for biomedical research. In this book chapter, we will present some of the commonly used databases for both SNVs and PTMs and describe a broad approach that can be applied to many scenarios for studying the impact of nsSNVs on PTM sites of human proteins.

Polyglutamine Tract Expansion Increases S-Nitrosylation of Huntingtin and Ataxin-1

Expansion of the polyglutamine (polyQ) tract in the huntingtin (Htt) protein causes Huntington’s disease (HD), a fatal inherited movement disorder linked to neurodegeneration in the striatum and cortex. S-nitrosylation and S-acylation of cysteine residues regulate many functions of cytosolic proteins. We therefore used a resin-assisted capture approach to identify these modifications in Htt. In contrast to many proteins that have only a single S-nitrosylation or S-acylation site, we identified sites along much of the length of Htt. Moreover, analysis of cells expressing full-length Htt or a large N-terminal fragment of Htt shows that polyQ expansion strongly increases Htt S-nitrosylation. This effect appears to be general since it is also observed in Ataxin-1, which causes spinocerebellar ataxia type 1 (SCA1) when its polyQ tract is expanded. Overexpression of nitric oxide synthase increases the S-nitrosylation of normal Htt and the frequency of conspicuous juxtanuclear inclusions of Htt N-terminal fragments in transfected cells. Taken together with the evidence that S-nitrosylation of Htt is widespread and parallels polyQ expansion, these subcellular changes show that S-nitrosylation affects the biology of this protein in vivo.

DAPPLE 2: a Tool for the Homology-Based Prediction of Post-Translational Modification Sites

The post-translational modification of proteins is critical for regulating their function. Although many post-translational modification sites have been experimentally determined, particularly in certain model organisms, experimental knowledge of these sites is severely lacking for many species. Thus, it is important to be able to predict sites of post-translational modification in such species. Previously, we described DAPPLE, a tool that facilitates the homology-based prediction of one particular post-translational modification, phosphorylation, in an organism of interest using known phosphorylation sites from other organisms. Here, we describe DAPPLE 2, which expands and improves upon DAPPLE in three major ways. First, it predicts sites for many post-translational modifications (20 different types) using data from several sources (15 online databases). Second, it has the ability to make predictions approximately 2-7 times faster than DAPPLE depending on the database size and the organism of interest. Third, it simplifies and accelerates the process of selecting predicted sites of interest by categorizing them based on gene ontology terms, keywords, and signaling pathways. We show that DAPPLE 2 can successfully predict known human post-translational modification sites using, as input, known sites from species that are either closely (e.g., mouse) or distantly (e.g., yeast) related to humans. DAPPLE 2 can be accessed at http://saphire.usask.ca/saphire/dapple2 .

Chemoproteomic Strategy to Quantitatively Monitor Transnitrosation Uncovers Functionally Relevant S-Nitrosation Sites on Cathepsin D and HADH2

S-Nitrosoglutathione (GSNO) is an endogenous transnitrosation donor involved in S-nitrosation of a variety of cellular proteins, thereby regulating diverse protein functions. Quantitative proteomic methods are necessary to establish which cysteine residues are most sensitive to GSNO-mediated transnitrosation. Here, a competitive cysteine-reactivity profiling strategy was implemented to quantitatively measure the sensitivity of >600 cysteine residues to transnitrosation by GSNO. This platform identified a subset of cysteine residues with a high propensity for GSNO-mediated transnitrosation. Functional characterization of previously unannotated S-nitrosation sites revealed that S-nitrosation of a cysteine residue distal to the 3-hydroxyacyl-CoA dehydrogenase type 2 (HADH2) active site impaired catalytic activity. Similarly, S-nitrosation of a non-catalytic cysteine residue in the lysosomal aspartyl protease cathepsin D (CTSD) inhibited proteolytic activation. Together, these studies revealed two previously uncharacterized cysteine residues that regulate protein function, and established a chemical-proteomic platform with capabilities to determine substrate specificity of other cellular transnitrosation agents.

Harnessing Redox Cross-Reactivity To Profile Distinct Cysteine Modifications

Cysteine S-nitrosation and S-sulfination are naturally occurring post-translational modifications (PTMs) on proteins induced by physiological signals and redox stress. Here we demonstrate that sulfinic acids and nitrosothiols react to form a stable thiosulfonate bond, and leverage this reactivity using sulfinate-linked probes to enrich and annotate hundreds of endogenous S-nitrosated proteins. In physiological buffers, sulfinic acids do not react with iodoacetamide or disulfides, enabling selective alkylation of free thiols and site-specific analysis of S-nitrosation. In parallel, S-nitrosothiol-linked probes enable enrichment and detection of endogenous S-sulfinated proteins, confirming that a single sulfinic acid can react with a nitrosothiol to form a thiosulfonate linkage. Using this approach, we find that hydrogen peroxide addition increases S-sulfination of human DJ-1 (PARK7) at Cys106, whereas Cys46 and Cys53 are fully oxidized to sulfonic acids. Comparative gel-based analysis of different mouse tissues reveals distinct profiles for both S-nitrosation and S-sulfination. Quantitative proteomic analysis demonstrates that both S-nitrosation and S-sulfination are widespread, yet exhibit enhanced occupancy on select proteins, including thioredoxin, peroxiredoxins, and other validated redox active proteins. Overall, we present a direct, bidirectional method to profile select redox cysteine modifications based on the unique nucleophilicity of sulfinic acids.

Quantitative Profiling of Protein S-Glutathionylation Reveals Redox-Dependent Regulation of Macrophage Function during Nanoparticle-Induced Oxidative Stress

Engineered nanoparticles (ENPs) are increasingly utilized for commercial and medical applications; thus, understanding their potential adverse effects is an important societal issue. Herein, we investigated protein S-glutathionylation (SSG) as an underlying regulatory mechanism by which ENPs may alter macrophage innate immune functions, using a quantitative redox proteomics approach for site-specific measurement of SSG modifications. Three high-volume production ENPs (SiO2, Fe3O4, and CoO) were selected as representatives which induce low, moderate, and high propensity, respectively, to stimulate cellular reactive oxygen species (ROS) and disrupt macrophage function. The SSG modifications identified highlighted a broad set of redox sensitive proteins and specific Cys residues which correlated well with the overall level of cellular redox stress and impairment of macrophage phagocytic function (CoO > Fe3O4 ≫ SiO2). Moreover, our data revealed pathway-specific differences in susceptibility to SSG between ENPs which induce moderate versus high levels of ROS. Pathways regulating protein translation and protein stability indicative of ER stress responses and proteins involved in phagocytosis were among the most sensitive to SSG in response to ENPs that induce subcytoxic levels of redox stress. At higher levels of redox stress, the pattern of SSG modifications displayed reduced specificity and a broader set pathways involving classical stress responses and mitochondrial energetics (e.g., glycolysis) associated with apoptotic mechanisms. An important role for SSG in regulation of macrophage innate immune function was also confirmed by RNA silencing of glutaredoxin, a major enzyme which reverses SSG modifications. Our results provide unique insights into the protein signatures and pathways that serve as ROS sensors and may facilitate cellular adaption to ENPs, versus intracellular targets of ENP-induced oxidative stress that are linked to irreversible cell outcomes.

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Background

Protein S-sulfenylation is a type of post-translational modification (PTM) involving the covalent binding of a hydroxyl group to the thiol of a cysteine amino acid. Recent evidence has shown the importance of S-sulfenylation in various biological processes, including transcriptional regulation, apoptosis and cytokine signaling. Determining the specific sites of S-sulfenylation is fundamental to understanding the structures and functions of S-sulfenylated proteins. However, the current lack of reliable tools often limits researchers to use expensive and time-consuming laboratory techniques for the identification of S-sulfenylation sites. Thus, we were motivated to develop a bioinformatics method for investigating S-sulfenylation sites based on amino acid compositions and physicochemical properties.

Results

In this work, physicochemical properties were utilized not only to identify S-sulfenylation sites from 1,096 experimentally verified S-sulfenylated proteins, but also to compare the effectiveness of prediction with other characteristics such as amino acid composition (AAC), amino acid pair composition (AAPC), solvent-accessible surface area (ASA), amino acid substitution matrix (BLOSUM62), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM). Various prediction models were built using support vector machine (SVM) and evaluated by five-fold cross-validation. The model constructed from hybrid features, including PSSM and physicochemical properties, yielded the best performance with sensitivity, specificity, accuracy and MCC measurements of 0.746, 0.737, 0.738 and 0.337, respectively. The selected model also provided a promising accuracy (0.693) on an independent testing dataset. Additionally, we employed TwoSampleLogo to help discover the difference of amino acid composition among S-sulfenylation, S-glutathionylation and S-nitrosylation sites.

Conclusion

This work proposed a computational method to explore informative features and functions for protein S-sulfenylation. Evaluation by five-fold cross validation indicated that the selected features were effective in the identification of S-sulfenylation sites. Moreover, the independent testing results demonstrated that the proposed method could provide a feasible means for conducting preliminary analyses of protein S-sulfenylation. We also anticipate that the uncovered differences in amino acid composition may facilitate future studies of the extensive crosstalk among S-sulfenylation, S-glutathionylation and S-nitrosylation.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-2299-1) contains supplementary material, which is available to authorized users.

UbiSite: incorporating two-layered machine learning method with substrate motifs to predict ubiquitin-conjugation site on lysines

Background

The conjugation of ubiquitin to a substrate protein (protein ubiquitylation), which involves a sequential process – E1 activation, E2 conjugation and E3 ligation, is crucial to the regulation of protein function and activity in eukaryotes. This ubiquitin-conjugation process typically binds the last amino acid of ubiquitin (glycine 76) to a lysine residue of a target protein. The high-throughput of mass spectrometry-based proteomics has stimulated a large-scale identification of ubiquitin-conjugated peptides. Hence, a new web resource, UbiSite, was developed to identify ubiquitin-conjugation site on lysines based on large-scale proteome dataset.

Results

Given a total of 37,647 ubiquitin-conjugated proteins, including 128026 ubiquitylated peptides, obtained from various resources, this study carries out a large-scale investigation on ubiquitin-conjugation sites based on sequenced and structural characteristics. A TwoSampleLogo reveals that a significant depletion of histidine (H), arginine (R) and cysteine (C) residues around ubiquitylation sites may impact the conjugation of ubiquitins in closed three-dimensional environments. Based on the large-scale ubiquitylation dataset, a motif discovery tool, MDDLogo, has been adopted to characterize the potential substrate motifs for ubiquitin conjugation. Not only are single features such as amino acid composition (AAC), positional weighted matrix (PWM), position-specific scoring matrix (PSSM) and solvent-accessible surface area (SASA) considered, but also the effectiveness of incorporating MDDLogo-identified substrate motifs into a two-layered prediction model is taken into account. Evaluation by five-fold cross-validation showed that PSSM is the best feature in discriminating between ubiquitylation and non-ubiquitylation sites, based on support vector machine (SVM). Additionally, the two-layered SVM model integrating MDDLogo-identified substrate motifs could obtain a promising accuracy and the Matthews Correlation Coefficient (MCC) at 81.06 % and 0.586, respectively. Furthermore, the independent testing showed that the two-layered SVM model could outperform other prediction tools, reaching at 85.10 % sensitivity, 69.69 % specificity, 73.69 % accuracy and the 0.483 of MCC value.

Conclusion

The independent testing result indicated the effectiveness of incorporating MDDLogo-identified motifs into the prediction of ubiquitylation sites. In order to provide meaningful assistance to researchers interested in large-scale ubiquitinome data, the two-layered SVM model has been implemented onto a web-based system (UbiSite), which is freely available at http://csb.cse.yzu.edu.tw/UbiSite/. Two cases given in the UbiSite provide a demonstration of effective identification of ubiquitylation sites with reference to substrate motifs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0246-z) contains supplementary material, which is available to authorized users.

A new scheme to discover functional associations and regulatory networks of E3 ubiquitin ligases

Background

Protein ubiquitination catalyzed by E3 ubiquitin ligases play important modulatory roles in various biological processes. With the emergence of high-throughput mass spectrometry technology, the proteomics research community embraced the development of numerous experimental methods for the determination of ubiquitination sites. The result is an accumulation of ubiquitinome data, coupled with a lack of available resources for investigating the regulatory networks among E3 ligases and ubiquitinated proteins. In this study, by integrating existing ubiquitinome data, experimentally validated E3 ligases and established protein-protein interactions, we have devised a strategy to construct a comprehensive map of protein ubiquitination networks.

Results

In total, 41,392 experimentally verified ubiquitination sites from 12,786 ubiquitinated proteins of humans have been obtained for this study. Additional 494 E3 ligases along with 1220 functional annotations and 28588 protein domains were manually curated. To characterize the regulatory networks among E3 ligases and ubiquitinated proteins, a well-established network viewer was utilized for the exploration of ubiquitination networks from 40892 protein-protein interactions. The effectiveness of the proposed approach was demonstrated in a case study examining E3 ligases involved in the ubiquitination of tumor suppressor p53. In addition to Mdm2, a known regulator of p53, the investigation also revealed other potential E3 ligases that may participate in the ubiquitination of p53.

Conclusion

Aside from the ability to facilitate comprehensive investigations of protein ubiquitination networks, by integrating information regarding protein-protein interactions and substrate specificities, the proposed method could discover potential E3 ligases for ubiquitinated proteins. Our strategy presents an efficient means for the preliminary screen of ubiquitination networks and overcomes the challenge as a result of limited knowledge about E3 ligase-regulated ubiquitination.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0244-1) contains supplementary material, which is available to authorized users.

dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins

Owing to the importance of the post-translational modifications (PTMs) of proteins in regulating biological processes, the dbPTM (http://dbPTM.mbc.nctu.edu.tw/) was developed as a comprehensive database of experimentally verified PTMs from several databases with annotations of potential PTMs for all UniProtKB protein entries. For this 10th anniversary of dbPTM, the updated resource provides not only a comprehensive dataset of experimentally verified PTMs, supported by the literature, but also an integrative interface for accessing all available databases and tools that are associated with PTM analysis. As well as collecting experimental PTM data from 14 public databases, this update manually curates over 12 000 modified peptides, including the emerging S-nitrosylation, S-glutathionylation and succinylation, from approximately 500 research articles, which were retrieved by text mining. As the number of available PTM prediction methods increases, this work compiles a non-homologous benchmark dataset to evaluate the predictive power of online PTM prediction tools. An increasing interest in the structural investigation of PTM substrate sites motivated the mapping of all experimental PTM peptides to protein entries of Protein Data Bank (PDB) based on database identifier and sequence identity, which enables users to examine spatially neighboring amino acids, solvent-accessible surface area and side-chain orientations for PTM substrate sites on tertiary structures. Since drug binding in PDB is annotated, this update identified over 1100 PTM sites that are associated with drug binding. The update also integrates metabolic pathways and protein-protein interactions to support the PTM network analysis for a group of proteins. Finally, the web interface is redesigned and enhanced to facilitate access to this resource.

MDD-SOH: exploiting maximal dependence decomposition to identify S-sulfenylation sites with substrate motifs

S-sulfenylation (S-sulphenylation, or sulfenic acid), the covalent attachment of S-hydroxyl (-SOH) to cysteine thiol, plays a significant role in redox regulation of protein functions. Although sulfenic acid is transient and labile, most of its physiological activities occur under control of S-hydroxylation. Therefore, discriminating the substrate site of S-sulfenylated proteins is an essential task in computational biology for the furtherance of protein structures and functions. Research into S-sulfenylated protein is currently very limited, and no dedicated tools are available for the computational identification of SOH sites. Given a total of 1096 experimentally verified S-sulfenylated proteins from humans, this study carries out a bioinformatics investigation on SOH sites based on amino acid composition and solvent-accessible surface area. A TwoSampleLogo indicates that the positively and negatively charged amino acids flanking the SOH sites may impact the formulation of S-sulfenylation in closed three-dimensional environments. In addition, the substrate motifs of SOH sites are studied using the maximal dependence decomposition (MDD). Based on the concept of binary classification between SOH and non-SOH sites, Support vector machine (SVM) is applied to learn the predictive model from MDD-identified substrate motifs. According to the evaluation results of 5-fold cross-validation, the integrated SVM model learned from substrate motifs yields an average accuracy of 0.87, significantly improving the prediction of SOH sites. Furthermore, the integrated SVM model also effectively improves the predictive performance in an independent testing set. Finally, the integrated SVM model is applied to implement an effective web resource, named MDD-SOH, to identify SOH sites with their corresponding substrate motifs.

AVAILABILITY AND IMPLEMENTATION

The MDD-SOH is now freely available to all interested users at http://csb.cse.yzu.edu.tw/MDDSOH/. All of the data set used in this work is also available for download in the website.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

CONTACT

francis@saturn.yzu.edu.tw.

SwissPalm: Protein Palmitoylation database

Protein S-palmitoylation is a reversible post-translational modification that regulates many key biological processes, although the full extent and functions of protein S-palmitoylation remain largely unexplored. Recent developments of new chemical methods have allowed the establishment of palmitoyl-proteomes of a variety of cell lines and tissues from different species.  As the amount of information generated by these high-throughput studies is increasing, the field requires centralization and comparison of this information. Here we present SwissPalm ( http://swisspalm.epfl.ch), our open, comprehensive, manually curated resource to study protein S-palmitoylation. It currently encompasses more than 5000 S-palmitoylated protein hits from seven species, and contains more than 500 specific sites of S-palmitoylation. SwissPalm also provides curated information and filters that increase the confidence in true positive hits, and integrates predictions of S-palmitoylated cysteine scores, orthologs and isoform multiple alignments. Systems analysis of the palmitoyl-proteome screens indicate that 10% or more of the human proteome is susceptible to S-palmitoylation. Moreover, ontology and pathway analyses of the human palmitoyl-proteome reveal that key biological functions involve this reversible lipid modification. Comparative analysis finally shows a strong crosstalk between S-palmitoylation and other post-translational modifications. Through the compilation of data and continuous updates, SwissPalm will provide a powerful tool to unravel the global importance of protein S-palmitoylation.

GSHSite: exploiting an iteratively statistical method to identify s-glutathionylation sites with substrate specificity

S-glutathionylation, the covalent attachment of a glutathione (GSH) to the sulfur atom of cysteine, is a selective and reversible protein post-translational modification (PTM) that regulates protein activity, localization, and stability. Despite its implication in the regulation of protein functions and cell signaling, the substrate specificity of cysteine S-glutathionylation remains unknown. Based on a total of 1783 experimentally identified S-glutathionylation sites from mouse macrophages, this work presents an informatics investigation on S-glutathionylation sites including structural factors such as the flanking amino acids composition and the accessible surface area (ASA). TwoSampleLogo presents that positively charged amino acids flanking the S-glutathionylated cysteine may influence the formation of S-glutathionylation in closed three-dimensional environment. A statistical method is further applied to iteratively detect the conserved substrate motifs with statistical significance. Support vector machine (SVM) is then applied to generate predictive model considering the substrate motifs. According to five-fold cross-validation, the SVMs trained with substrate motifs could achieve an enhanced sensitivity, specificity, and accuracy, and provides a promising performance in an independent test set. The effectiveness of the proposed method is demonstrated by the correct identification of previously reported S-glutathionylation sites of mouse thioredoxin (TXN) and human protein tyrosine phosphatase 1b (PTP1B). Finally, the constructed models are adopted to implement an effective web-based tool, named GSHSite (http://csb.cse.yzu.edu.tw/GSHSite/), for identifying uncharacterized GSH substrate sites on the protein sequences.

Site-specific nitrosoproteomic identification of endogenously S-nitrosylated proteins in Arabidopsis

Nitric oxide (NO) regulates multiple developmental events and stress responses in plants. A major biologically active species of NO is S-nitrosoglutathione (GSNO), which is irreversibly degraded by GSNO reductase (GSNOR). The major physiological effect of NO is protein S-nitrosylation, a redox-based posttranslational modification mechanism by covalently linking an NO molecule to a cysteine thiol. However, little is known about the mechanisms of S-nitrosylation-regulated signaling, partly due to limited S-nitrosylated proteins being identified. In this study, we identified 1,195 endogenously S-nitrosylated peptides in 926 proteins from the Arabidopsis (Arabidopsis thaliana) by a site-specific nitrosoproteomic approach, which, to date, is the largest data set of S-nitrosylated proteins among all organisms. Consensus sequence analysis of these peptides identified several motifs that contain acidic, but not basic, amino acid residues flanking the S-nitrosylated cysteine residues. These S-nitrosylated proteins are involved in a wide range of biological processes and are significantly enriched in chlorophyll metabolism, photosynthesis, carbohydrate metabolism, and stress responses. Consistently, the gsnor1-3 mutant shows the decreased chlorophyll content and altered photosynthetic properties, suggesting that S-nitrosylation is an important regulatory mechanism in these processes. These results have provided valuable resources and new clues to the studies on S-nitrosylation-regulated signaling in plants.

Characterization and identification of ubiquitin conjugation sites with E3 ligase recognition specificities

Background

In eukaryotes, ubiquitin-conjugation is an important mechanism underlying proteasome-mediated degradation of proteins, and as such, plays an essential role in the regulation of many cellular processes. In the ubiquitin-proteasome pathway, E3 ligases play important roles by recognizing a specific protein substrate and catalyzing the attachment of ubiquitin to a lysine (K) residue. As more and more experimental data on ubiquitin conjugation sites become available, it becomes possible to develop prediction models that can be scaled to big data. However, no development that focuses on the investigation of ubiquitinated substrate specificities has existed. Herein, we present an approach that exploits an iteratively statistical method to identify ubiquitin conjugation sites with substrate site specificities.

Results

In this investigation, totally 6259 experimentally validated ubiquitinated proteins were obtained from dbPTM. After having filtered out homologous fragments with 40% sequence identity, the training data set contained 2658 ubiquitination sites (positive data) and 5532 non-ubiquitinated sites (negative data). Due to the difficulty in characterizing the substrate site specificities of E3 ligases by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. The profile hidden Markov model (profile HMM) was adopted to construct the predictive models learned from the identified substrate motifs. A five-fold cross validation was then used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 73.07%, 65.46%, and 67.93%, respectively. Additionally, an independent testing set, completely blind to the training data of the predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (76.13%) and outperform other ubiquitination site prediction tool.

Conclusion

A case study demonstrated the effectiveness of the characterized substrate motifs for identifying ubiquitination sites. The proposed method presents a practical means of preliminary analysis and greatly diminishes the total number of potential targets required for further experimental confirmation. This method may help unravel their mechanisms and roles in E3 recognition and ubiquitin-mediated protein degradation.

Protein S-nitrosylation: specificity and identification strategies in plants

The role of nitric oxide (NO) as a major regulator of plant physiological functions has become increasingly evident. To further improve our understanding of its role, within the last few years plant biologists have begun to embrace the exciting opportunity of investigating protein S-nitrosylation, a major reversible NO-dependent post-translational modification (PTM) targeting specific Cys residues and widely studied in animals. Thanks to the development of dedicated proteomic approaches, in particular the use of the biotin switch technique (BST) combined with mass spectrometry, hundreds of plant protein candidates for S-nitrosylation have been identified. Functional studies focused on specific proteins provided preliminary comprehensive views of how this PTM impacts the structure and function of proteins and, more generally, of how NO might regulate biological plant processes. The aim of this review is to detail the basic principle of protein S-nitrosylation, to provide information on the biochemical and structural features of the S-nitrosylation sites and to describe the proteomic strategies adopted to investigate this PTM in plants. Limits of the current approaches and tomorrow's challenges are also discussed.

Characterization and identification of protein O-GlcNAcylation sites with substrate specificity

Background

Protein O-GlcNAcylation, involving the attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues. Elucidation of O-GlcNAcylation sites on proteins is required in order to decipher its crucial roles in regulating cellular processes and aid in drug design. With an increasing number of O-GlcNAcylation sites identified by mass spectrometry (MS)-based proteomics, several methods have been proposed for the computational identification of O-GlcNAcylation sites. However, no development that focuses on the investigation of O-GlcNAcylated substrate motifs has existed. Thus, we were motivated to design a new method for the identification of protein O-GlcNAcylation sites with the consideration of substrate site specificity.

Results

In this study, 375 experimentally verified O-GlcNAcylation sites were collected from dbOGAP, which is an integrated resource for protein O-GlcNAcylation. Due to the difficulty in characterizing the substrate motifs by conventional sequence logo analysis, a recursively statistical method has been applied to obtain significant conserved motifs. To construct the predictive models learned from the identified substrate motifs, we adopted Support Vector Machines (SVMs). A five-fold cross validation was used to evaluate the predictive model, achieving sensitivity, specificity, and accuracy of 0.76, 0.80, and 0.78, respectively. Additionally, an independent testing set, which was really blind to the training data of predictive model, was used to demonstrate that the proposed method could provide a promising accuracy (0.94) and outperform three other O-GlcNAcylation site prediction tools.

Conclusion

This work proposed a computational method to identify informative substrate motifs for O-GlcNAcylation sites. The evaluation of cross validation and independent testing indicated that the identified motifs were effective in the identification of O-GlcNAcylation sites. A case study demonstrated that the proposed method could be a feasible means of conducting preliminary analyses of protein O-GlcNAcylation. We also anticipated that the revealed substrate motif may facilitate the study of extensive crosstalk between O-GlcNAcylation and phosphorylation. This method may help unravel their mechanisms and roles in signaling, transcription, chronic disease, and cancer.

dbSNO 2.0: a resource for exploring structural environment, functional and disease association and regulatory network of protein S-nitrosylation

Given the increasing number of proteins reported to be regulated by S-nitrosylation (SNO), it is considered to act, in a manner analogous to phosphorylation, as a pleiotropic regulator that elicits dual effects to regulate diverse pathophysiological processes by altering protein function, stability, and conformation change in various cancers and human disorders. Due to its importance in regulating protein functions and cell signaling, dbSNO (http://dbSNO.mbc.nctu.edu.tw) is extended as a resource for exploring structural environment of SNO substrate sites and regulatory networks of S-nitrosylated proteins. An increasing interest in the structural environment of PTM substrate sites motivated us to map all manually curated SNO peptides (4165 SNO sites within 2277 proteins) to PDB protein entries by sequence identity, which provides the information of spatial amino acid composition, solvent-accessible surface area, spatially neighboring amino acids, and side chain orientation for 298 substrate cysteine residues. Additionally, the annotations of protein molecular functions, biological processes, functional domains and human diseases are integrated to explore the functional and disease associations for S-nitrosoproteome. In this update, users are allowed to search a group of interested proteins/genes and the system reconstructs the SNO regulatory network based on the information of metabolic pathways and protein-protein interactions. Most importantly, an endogenous yet pathophysiological S-nitrosoproteomic dataset from colorectal cancer patients was adopted to demonstrate that dbSNO could discover potential SNO proteins involving in the regulation of NO signaling for cancer pathways.

Target-selective protein S-nitrosylation by sequence motif recognition

S-nitrosylation is a ubiquitous protein modification emerging as a principal mechanism of nitric oxide (NO)-mediated signal transduction and cell function. S-nitrosylases can use NO synthase (NOS)-derived NO to modify selected cysteines in target proteins. Despite proteomic identification of over a thousand S-nitrosylated proteins, few S-nitrosylases have been identified. Moreover, mechanisms underlying site-selective S-nitrosylation and the potential role of specific sequence motifs remain largely unknown. Here, we describe a stimulus-inducible, heterotrimeric S-nitrosylase complex consisting of inducible NOS (iNOS), S100A8, and S100A9. S100A9 exhibits transnitrosylase activity, shuttling NO from iNOS to the target protein, whereas S100A8 and S100A9 coordinately direct site selection. A family of proteins S-nitrosylated by iNOS-S100A8/A9 were revealed by proteomic analysis. A conserved I/L-X-C-X2-D/E motif was necessary and sufficient for iNOS-S100A8/A9-mediated S-nitrosylation. These results reveal an elusive parallel between protein S-nitrosylation and phosphorylation, namely, stimulus-dependent posttranslational modification of selected targets by primary sequence motif recognition.