Prediction of redox-sensitive cysteines using sequential distance and other sequence-based features

An exploratory in silico comparison of open-source codon harmonization tools

BACKGROUND

Not changing the native constitution of genes prior to their expression by a heterologous host can affect the amount of proteins synthesized as well as their folding, hampering their activity and even cell viability. Over the past decades, several strategies have been developed to optimize the translation of heterologous genes by accommodating the difference in codon usage between species. While there have been a handful of studies assessing various codon optimization strategies, to the best of our knowledge, no research has been performed towards the evaluation and comparison of codon harmonization algorithms. To highlight their importance and encourage meaningful discussion, we compared different open-source codon harmonization tools pertaining to their in silico performance, and we investigated the influence of different gene-specific factors.

RESULTS

In total, 27 genes were harmonized with four tools toward two different heterologous hosts. The difference in %MinMax values between the harmonized and the original sequences was calculated (ΔMinMax), and statistical analysis of the obtained results was carried out. It became clear that not all tools perform similarly, and the choice of tool should depend on the intended application. Almost all biological factors under investigation (GC content, RNA secondary structures and choice of heterologous host) had a significant influence on the harmonization results and thus must be taken into account. These findings were substantiated using a validation dataset consisting of 8 strategically chosen genes.

CONCLUSIONS

Due to the size of the dataset, no complex models could be developed. However, this initial study showcases significant differences between the results of various codon harmonization tools. Although more elaborate investigation is needed, it is clear that biological factors such as GC content, RNA secondary structures and heterologous hosts must be taken into account when selecting the codon harmonization tool.

Oxidative Post-Translational Modifications: A Focus on Cysteine S-Sulfhydration and the Regulation of Endothelial Fitness

Significance: Changes in the oxidative balance can affect cellular physiology and adaptation through redox signaling. The endothelial cells that line blood vessels are particularly sensitive to reactive oxygen species, which can alter cell function by a number of mechanisms, including the oxidative post-translational modification (oxPTM) of proteins on critical cysteine thiols. Such modifications can act as redox-switches to alter the function of targeted proteins. Recent Advances: Mapping the cysteine oxPTM proteome and characterizing the effects of individual oxPTMs to gain insight into consequences for cellular responses has proven challenging. A recent addition to the list of reversible oxPTMs that contributes to cellular redox homeostasis is persulfidation or S-sulfhydration. Critical Issues: It has been estimated that up to 25% of proteins are S-sulfhydrated, making this modification almost as abundant as phosphorylation. In the endothelium, persulfides are generated by the trans-sulfuration pathway that catabolizes cysteine and cystathionine to generate hydrogen sulfide (H₂S) and H₂S-related sulfane sulfur compounds (H₂S_n). This pathway is of particular importance for the vascular system, as the enzyme cystathionine γ lyase (CSE) in endothelial cells accounts for a significant portion of total vascular H₂S/H₂S_n production. Future Directions: Impaired CSE activity in endothelial dysfunction has been linked with marked changes in the endothelial cell S-sulfhydrome and can contribute to the development of atherosclerosis and hypertension. It will be interesting to determine how changes in the S-sulfhydration of specific networks of proteins contribute to endothelial cell physiology and pathophysiology. Antioxid. Redox Signal. 35, 1494-1514.

Stoichiometric Thiol Redox Proteomics for Quantifying Cellular Responses to Perturbations

Post-translational modifications regulate the structure and function of proteins that can result in changes to the activity of different pathways. These include modifications altering the redox state of thiol groups on protein cysteine residues, which are sensitive to oxidative environments. While mass spectrometry has advanced the identification of protein thiol modifications and expanded our knowledge of redox-sensitive pathways, the quantitative aspect of this technique is critical for the field of redox proteomics. In this review, we describe how mass spectrometry-based redox proteomics has enabled researchers to accurately quantify the stoichiometry of reversible oxidative modifications on specific cysteine residues of proteins. We will describe advancements in the methodology that allow for the absolute quantitation of thiol modifications, as well as recent reports that have implemented this approach. We will also highlight the significance and application of such measurements and why they are informative for the field of redox biology.

Unbiased Detection of Cysteine Sulfenic Acid by 473 nm Photodissociation Mass Spectrometry: Toward Facile In Vivo Oxidative Status of Plasma Proteins

Cysteine (Cys) is prone to diverse post-translational modifications in proteins, including oxidation into sulfenic acid (Cys-SOH) by reactive oxygen species generated under oxidative stress. Detection of low-concentration and metastable Cys-SOH within complex biological matrices is challenging due to the dynamic concentration range of proteins in the samples. Herein, visible laser-induced dissociation (LID) implemented in a mass spectrometer was used for streamlining the detection of Cys oxidized proteins owing to proper derivatization of Cys-SOH with a chromophore tag functionalized with a cyclohexanedione group. Once grafted, peptides undergo a high fragmentation yield under LID, leading concomitantly to informative backbone ions and to a chromophore reporter ion. Seventy-nine percent of the Cys-containing tryptic peptides derived from human serum albumin and serotransferrin tracked by parallel reaction monitoring (PRM) were detected as targets subjected to oxidation. These candidates as well as Cys-containing peptides predicted by in silico trypsin digestion of five other human plasma proteins were then tracked in real plasma samples to pinpoint the endogenous Cys-SOH subpopulation. Most of the targeted peptides were detected in all plasma samples by LID-PRM, with significant differences in their relative amounts. By eliminating the signal of interfering co-eluted compounds, LID-PRM surpasses conventional HCD (higher-energy collisional dissociation)-PRM in detecting grafted Cys-SOH-containing peptides and allows now to foresee clinical applications in large human cohorts.

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.

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations

Redox-sensitive cysteine (RSC) thiol contributes to many biological processes. The identification of RSC plays an important role in clarifying some mechanisms of redox-sensitive factors; nonetheless, experimental investigation of RSCs is expensive and time-consuming. The computational approaches that quickly and accurately identify candidate RSCs using the sequence information are urgently needed. Herein, an improved and robust computational predictor named IRC-Fuse was developed to identify the RSC by fusing of multiple feature representations. To enhance the performance of our model, we integrated the probability scores evaluated by the random forest models implementing different encoding schemes. Cross-validation results exhibited that the IRC-Fuse achieved accuracy and AUC of 0.741 and 0.807, respectively. The IRC-Fuse outperformed exiting methods with improvement of 10% and 13% on accuracy and MCC, respectively, over independent test data. Comparative analysis suggested that the IRC-Fuse was more effective and promising than the existing predictors. For the convenience of experimental scientists, the IRC-Fuse online web server was implemented and publicly accessible at http://kurata14.bio.kyutech.ac.jp/IRC-Fuse/ .

Redox Post-translational Modifications of Protein Thiols in Brain Aging and Neurodegenerative Conditions-Focus on S-Nitrosation

Reactive oxygen species and reactive nitrogen species (RONS) are by-products of aerobic metabolism. RONS trigger a signaling cascade that can be transduced through oxidation-reduction (redox)-based post-translational modifications (redox PTMs) of protein thiols. This redox signaling is essential for normal cellular physiology and coordinately regulates the function of redox-sensitive proteins. It plays a particularly important role in the brain, which is a major producer of RONS. Aberrant redox PTMs of protein thiols can impair protein function and are associated with several diseases. This mini review article aims to evaluate the role of redox PTMs of protein thiols, in particular S-nitrosation, in brain aging, and in neurodegenerative diseases. It also discusses the potential of using redox-based therapeutic approaches for neurodegenerative conditions.

Roles of Reactive Oxygen Species in Cardiac Differentiation, Reprogramming, and Regenerative Therapies

Reactive oxygen species (ROS) have been implicated in mechanisms of heart development and regenerative therapies such as the use of pluripotent stem cells. The roles of ROS mediating cell fate are dependent on the intensity of stimuli, cellular context, and metabolic status. ROS mainly act through several targets (such as kinases and transcription factors) and have diverse roles in different stages of cardiac differentiation, proliferation, and maturation. Therefore, further detailed investigation and characterization of redox signaling will help the understanding of the molecular mechanisms of ROS during different cellular processes and enable the design of targeted strategies to foster cardiac regeneration and functional recovery. In this review, we focus on the roles of ROS in cardiac differentiation as well as transdifferentiation (direct reprogramming). The potential mechanisms are discussed in regard to ROS generation pathways and regulation of downstream targets. Further methodological optimization is required for translational research in order to robustly enhance the generation efficiency of cardiac myocytes through metabolic modulations. Additionally, we highlight the deleterious effect of the host's ROS on graft (donor) cells in a paracrine manner during stem cell-based implantation. This knowledge is important for the development of antioxidant strategies to enhance cell survival and engraftment of tissue engineering-based technologies. Thus, proper timing and level of ROS generation after a myocardial injury need to be tailored to ensure the maximal efficacy of regenerative therapies and avoid undesired damage.

Redox Systems Biology: Harnessing the Sentinels of the Cysteine Redoxome

Significance: Cellular redox processes are highly interconnected, yet not in equilibrium, and governed by a wide range of biochemical parameters. Technological advances continue refining how specific redox processes are regulated, but broad understanding of the dynamic interconnectivity between cellular redox modules remains limited. Systems biology investigates multiple components in complex environments and can provide integrative insights into the multifaceted cellular redox state. This review describes the state of the art in redox systems biology as well as provides an updated perspective and practical guide for harnessing thousands of cysteine sensors in the redoxome for multiparameter characterization of cellular redox networks. Recent Advances: Redox systems biology has been applied to genome-scale models and large public datasets, challenged common conceptions, and provided new insights that complement reductionist approaches. Advances in public knowledge and user-friendly tools for proteome-wide annotation of cysteine sentinels can now leverage cysteine redox proteomics datasets to provide spatial, functional, and protein structural information. Critical Issues: Careful consideration of available analytical approaches is needed to broadly characterize the systems-level properties of redox signaling networks and be experimentally feasible. The cysteine redoxome is an informative focal point since it integrates many aspects of redox biology. The mechanisms and redox modules governing cysteine redox regulation, cysteine oxidation assays, proteome-wide annotation of the biophysical and biochemical properties of individual cysteines, and their clinical application are discussed. Future Directions: Investigating the cysteine redoxome at a systems level will uncover new insights into the mechanisms of selectivity and context dependence of redox signaling networks.

Structural Insights Into TDP-43 and Effects of Post-translational Modifications

Transactive response DNA binding protein (TDP-43) is a key player in neurodegenerative diseases. In this review, we have gathered and presented structural information on the different regions of TDP-43 with high resolution structures available. A thorough understanding of TDP-43 structure, effect of modifications, aggregation and sites of localization is necessary as we develop therapeutic strategies targeting TDP-43 for neurodegenerative diseases. We discuss how different domains as well as post-translational modification may influence TDP-43 overall structure, aggregation and droplet formation. The primary aim of the review is to utilize structural insights as we develop an understanding of the deleterious behavior of TDP-43 and highlight locations of established and proposed post-translation modifications. TDP-43 structure and effect on localization is paralleled by many RNA-binding proteins and this review serves as an example of how structure may be modulated by numerous compounding elements.

Interplay Between Mitochondrial Peroxiredoxins and ROS in Cancer Development and Progression

Mitochondria are multifunctional cellular organelles that are major producers of reactive oxygen species (ROS) in eukaryotes; to maintain the redox balance, they are supplemented with different ROS scavengers, including mitochondrial peroxiredoxins (Prdxs). Mitochondrial Prdxs have physiological and pathological significance and are associated with the initiation and progression of various cancer types. In this review, we have focused on signaling involving ROS and mitochondrial Prdxs that is associated with cancer development and progression. An upregulated expression of Prdx3 and Prdx5 has been reported in different cancer types, such as breast, ovarian, endometrial, and lung cancers, as well as in Hodgkin's lymphoma and hepatocellular carcinoma. The expression of Prdx3 and Prdx5 in different types of malignancies involves their association with different factors, such as transcription factors, micro RNAs, tumor suppressors, response elements, and oncogenic genes. The microenvironment of mitochondrial Prdxs plays an important role in cancer development, as cancerous cells are equipped with a high level of antioxidants to overcome excessive ROS production. However, an increased production of Prdx3 and Prdx5 is associated with the development of chemoresistance in certain types of cancers and it leads to further complications in cancer treatment. Understanding the interplay between mitochondrial Prdxs and ROS in carcinogenesis can be useful in the development of anticancer drugs with better proficiency and decreased resistance. However, more targeted studies are required for exploring the tumor microenvironment in association with mitochondrial Prdxs to improve the existing cancer therapies and drug development.

Residue Adjacency Matrix Based Feature Engineering for Predicting Cysteine Reactivity in Proteins

Free radicals that form from reactive species of nitrogen and oxygen can react dangerously with cellular components and are involved with the pathogenesis of diabetes, cancer, Parkinson's, and heart disease. Cysteine amino acids, due to their reactive nature, are prone to oxidation by these free radicals. Determining which cysteines oxidize within proteins is crucial to our understanding of these chronic diseases. Wet lab techniques, like differential alkylation, to determine which cysteines oxidize are often expensive and time-consuming. We utilize machine learning as a fast and inexpensive approach to identifying cysteines with oxidative capabilities. We created the original features RAMmod and RAMseq for use in classification. We also incorporated well-known features such as PROPKA, SASA, PSS, and PSSM. Our algorithm requires only the protein sequence to operate; however, we do use template matching by MODELLER to acquire 3D coordinates for additional feature extraction. There was a mean improvement of RAM over N6C by 22.04% MCC. It was statistically significant with a p-value of 0.015. RAM provided a significant increase over PSSM with a p-value of 0.040 and an average 70.09% improvement MCC.

Redox Signaling by Reactive Electrophiles and Oxidants

The concept of cell signaling in the context of nonenzyme-assisted protein modifications by reactive electrophilic and oxidative species, broadly known as redox signaling, is a uniquely complex topic that has been approached from numerous different and multidisciplinary angles. Our Review reflects on five aspects critical for understanding how nature harnesses these noncanonical post-translational modifications to coordinate distinct cellular activities: (1) specific players and their generation, (2) physicochemical properties, (3) mechanisms of action, (4) methods of interrogation, and (5) functional roles in health and disease. Emphasis is primarily placed on the latest progress in the field, but several aspects of classical work likely forgotten/lost are also recollected. For researchers with interests in getting into the field, our Review is anticipated to function as a primer. For the expert, we aim to stimulate thought and discussion about fundamentals of redox signaling mechanisms and nuances of specificity/selectivity and timing in this sophisticated yet fascinating arena at the crossroads of chemistry and biology.

Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate

The function of a protein is of great interest in the cutting-edge research of biological mechanisms, disease development and drug/target discovery. Besides experimental explorations, a variety of computational methods have been designed to predict protein function. Among these in silico methods, the prediction of BLAST is based on protein sequence similarity, while that of machine learning is also based on the sequence, but without the consideration of their similarity. This unique characteristic of machine learning makes it a good complement to BLAST and many other approaches in predicting the function of remotely relevant proteins and the homologous proteins of distinct function. However, the identification accuracies of these in silico methods and their false discovery rate have not yet been assessed so far, which greatly limits the usage of these algorithms. Herein, a comprehensive comparison of the performances among four popular prediction algorithms (BLAST, SVM, PNN and KNN) was conducted. In particular, the performance of these methods was systematically assessed by four standard statistical indexes based on the independent test datasets of 93 functional protein families defined by UniProtKB keywords. Moreover, the false discovery rates of these algorithms were evaluated by scanning the genomes of four representative model organisms (Homo sapiens, Arabidopsis thaliana, Saccharomyces cerevisiae and Mycobacterium tuberculosis). As a result, the substantially higher sensitivity of SVM and BLAST was observed compared with that of PNN and KNN. However, the machine learning algorithms (PNN, KNN and SVM) were found capable of substantially reducing the false discovery rate (SVM < PNN < KNN). In sum, this study comprehensively assessed the performance of four popular algorithms applied to protein function prediction, which could facilitate the selection of the most appropriate method in the related biomedical research.