Identification, analysis, and prediction of protein ubiquitination sites

SUMOylation of GMFB regulates its stability and function in retinal pigment epithelial cells under hyperglycemia

BACKGROUND

Glia maturation factor beta (GMFB) is a growth and differentiation factor that acts as an intracellular regulator of signal transduction pathways. The small ubiquitin-related modifier (SUMO) modification, SUMOylation, is a posttranslational modification (PTM) that plays a key role in protein subcellular localization, stability, transcription, and enzymatic activity. Recent studies have highlighted the importance of SUMOylation in the inflammation and progression of numerous diseases. However, the relationship between GMFB and SUMOylation is unclear.

RESULTS

Here, we report for the first time that GMFB and SUMO1 are markedly increased in retinal pigment epithelial (RPE) cells at the early stage of diabetes mellitus (DM) under hyperglycemia. The GMFΒ protein could be mono-SUMOylated by SUMO1 at the K20, K35, K58 or K97 sites. SUMOylation of GMFB led to its increased protein stability and subcellular translocation. Furthermore, deSUMOylation of GMFΒ downregulates multiple signaling pathways, including the Jak-STAT signaling pathway, p38 pathway and NF-kappa B signaling pathway.

CONCLUSIONS

This work provides novel insight into the role of SUMOylated GMFB in RPE cells and provides a novel therapeutic target for diabetic retinopathy (DR).

Simulation and Computational Study of RING Domain Mutants of BRCA1 and Ube2k in AD/PD Pathophysiology

Lysine-based post-translational modification (PTM) such as acylation, acetylation, deamination, methylation, SUMOylation, and ubiquitination has proven to be a major regulator of gene expression, chromatin structure, protein stability, protein-protein interaction, protein degradation, and cellular localization. However, besides all the PTMs, ubiquitination stands as the second most common PTM after phosphorylation that is involved in the etiology of neurodegenerative diseases (NDDs) namely, Alzheimer's disease (AD) and Parkinson's disease (PD). NDDs are characterized by the accumulation of misfolded protein aggregates in the brain that lead to disease-related gene mutation and irregular protein homeostasis. The ubiquitin-proteasome system (UPS) is in charge of degrading these misfolded proteins, which involve an interplay of E1, E2, E3, and deubiquitinase enzymes. Impaired UPS has been commonly observed in NDDs and E3 ligases are the key members of the UPS, thus, dysfunction of the same can accelerate the neurodegeneration process. Therefore, the aim of this study is firstly, to find E3 ligases that are common in both AD and PD through data mining. Secondly, to study the impact of mutation on its structure and function. The study deciphered 74 E3 ligases that were common in both AD and PD. Later, 10 hub genes were calculated of which protein-protein interaction, pathway enrichment, lysine site prediction, domain, and motif analysis were performed. The results predicted BRCA1, PML, and TRIM33 as the top three putative lysine-modified E3 ligases involved in AD and PD pathogenesis. However, based on structural characterization, BRCA1 was taken further to study RING domain mutation that inferred K32Y, K32L, K32C, K45V, K45Y, and K45G as potential mutants that alter the structural and functional ability of BRCA1 to interact with Ube2k, E2-conjugating enzyme. The most probable mutant observed after molecular dynamics simulation of 50 ns is K32L. Therefore, our study concludes BRCA1, a potential E3 ligase common in AD and PD, and RING domain mutation at sites K32 and K45 possibly disturbs its interaction with its E2, Ube2k.

Arabidopsis HECT and RING-type E3 Ligases Promote MAPKKK18 Degradation to Regulate Abscisic Acid Signaling

Mitogen-activated protein kinase (MAPK) cascades are conserved signaling pathways that transduce extracellular signals into diverse cellular responses. Arabidopsis MAPKKK18 is a component of the MAPKKK17/18-MKK3-MPK1/2/7/14 cascades, which play critical roles in abscisic acid (ABA) signaling, drought tolerance and senescence. A very important aspect of MAP kinase signaling is both its activation and its termination, which must be tightly controlled to achieve appropriate biological responses. Recently, the ubiquitin-proteasome system (UPS) has received increasing attention as a key mechanism for maintaining the homeostasis of MAPK cascade components and other ABA signaling effectors. Previous studies have shown that the stability of MAPKKK18 is regulated by the UPS via the ABA core pathway. Here, using multiple proteomic approaches, we found that MAPKKK17/18 turnover is tightly controlled by three E3 ligases, UPL1, UPL4 and KEG. We also identified lysines 154 and 237 as critical for MAPKKK18 stability. Taken together, this study sheds new light on the mechanism that controls MAPKKK17/18 activity and function.

Dynamic interactions between SPX proteins, the ubiquitination machinery, and signalling molecules for stress adaptation at a whole-plant level

The plant macronutrient phosphorus is a scarce resource and plant-available phosphate is limiting in most soil types. Generally, a gene regulatory module called the phosphate starvation response (PSR) enables efficient phosphate acquisition by roots and translocation to other organs. Plants growing on moderate to nutrient-rich soils need to co-ordinate availability of different nutrients and repress the highly efficient PSR to adjust phosphate acquisition to the availability of other macro- and micronutrients, and in particular nitrogen. PSR repression is mediated by a small family of single SYG1/Pho81/XPR1 (SPX) domain proteins. The SPX domain binds higher order inositol pyrophosphates that signal cellular phosphorus status and modulate SPX protein interaction with PHOSPHATE STARVATION RESPONSE1 (PHR1), the central transcriptional regulator of PSR. Sequestration by SPX repressors restricts PHR1 access to PSR gene promoters. Here we focus on SPX4 that primarily acts in shoots and sequesters many transcription factors other than PHR1 in the cytosol to control processes beyond the classical PSR, such as nitrate, auxin, and jasmonic acid signalling. Unlike SPX1 and SPX2, SPX4 is subject to proteasomal degradation not only by singular E3 ligases, but also by SCF-CRL complexes. Emerging models for these different layers of control and their consequences for plant acclimation to the environment will be discussed.

NEDD4L intramolecular interactions regulate its auto and substrate NaV1.5 ubiquitination

NEDD4L is a HECT-type E3 ligase that catalyzes the addition of ubiquitin to intracellular substrates such as the cardiac voltage-gated sodium channel, NaV1.5. The intramolecular interactions of NEDD4L regulate its enzymatic activity which is essential for proteostasis. For NaV1.5, this process is critical as alterations in Na+ current is involved in cardiac diseases including arrhythmias and heart failure. In this study, we perform extensive biochemical and functional analyses that implicate the C2 domain and the first WW-linker (1,2-linker) in the autoregulatory mechanism of NEDD4L. Through in vitro and electrophysiological experiments, the NEDD4L 1,2-linker was determined to be important in substrate ubiquitination of NaV1.5. We establish the preferred sites of ubiquitination of NEDD4L to be in the second WW-linker (2,3-linker). Interestingly, NEDD4L ubiquitinates the cytoplasmic linker between the first and second transmembrane domains of the channel (DI-DII) of NaV1.5. Moreover, we design a genetically encoded modulator of Nav1.5 that achieves Na+ current reduction using the NEDD4L HECT domain as cargo of a NaV1.5-binding nanobody. These investigations elucidate the mechanisms regulating the NEDD4 family and furnish a new molecular framework for understanding NaV1.5 ubiquitination.

The GATOR2 complex maintains lysosomal-autophagic function by inhibiting the protein degradation of MiT/TFEs

Lysosomes are central to metabolic homeostasis. The microphthalmia bHLH-LZ transcription factors (MiT/TFEs) family members MITF, TFEB, and TFE3 promote the transcription of lysosomal and autophagic genes and are often deregulated in cancer. Here, we show that the GATOR2 complex, an activator of the metabolic regulator TORC1, maintains lysosomal function by protecting MiT/TFEs from proteasomal degradation independent of TORC1, GATOR1, and the RAG GTPase. We determine that in GATOR2 knockout HeLa cells, members of the MiT/TFEs family are ubiquitylated by a trio of E3 ligases and are degraded, resulting in lysosome dysfunction. Additionally, we demonstrate that GATOR2 protects MiT/TFE proteins in pancreatic ductal adenocarcinoma and Xp11 translocation renal cell carcinoma, two cancers that are driven by MiT/TFE hyperactivation. In summary, we find that the GATOR2 complex has independent roles in TORC1 regulation and MiT/TFE protein protection and thus is central to coordinating cellular metabolism with control of the lysosomal-autophagic system.

The phosphatase DUSP22 inhibits UBR2-mediated K63-ubiquitination and activation of Lck downstream of TCR signalling

DUSP22 is a dual-specificity phosphatase that inhibits T cell activation by inactivating the kinase Lck. Here we show that the E3 ubiquitin ligase UBR2 is a positive upstream regulator of Lck during T-cell activation. DUSP22 dephosphorylates UBR2 at specific Serine residues, leading to ubiquitin-mediated UBR2 degradation. UBR2 is also modified by the SCF E3 ubiquitin ligase complex via Lys48-linked ubiquitination at multiple Lysine residues. Single-cell RNA sequencing analysis and UBR2 loss of function experiments showed that UBR2 is a positive regulator of proinflammatory cytokine expression. Mechanistically, UBR2 induces Lys63-linked ubiquitination of Lck at Lys99 and Lys276 residues, followed by Lck Tyr394 phosphorylation and activation as part of TCR signalling. Inflammatory phenotypes induced by TCR-triggered Lck activation or knocking out DUSP22, are attenuated by genomic deletion of UBR2. UBR2-Lck interaction and Lck Lys63-linked ubiquitination are induced in the peripheral blood T cells of human SLE patients, which demonstrate the relevance of the UBR2-mediated regulation of inflammation to human pathology. In summary, we show here an important regulatory mechanism of T cell activation, which finetunes the balance between T cell response and aggravated inflammation.

Post-translational modifications in stress granule and their implications in neurodegenerative diseases

Stress granules (SGs) arise as formations of mRNAs and proteins in response to translation initiation inhibition during stress. These dynamic compartments adopt a fluidic nature through liquid-liquid phase separation (LLPS), exhibiting a composition subject to constant change within cellular contexts. Research has unveiled an array of post-translational modifications (PTMs) occurring on SG proteins, intricately orchestrating SG dynamics. In the realm of neurodegenerative diseases, pathological mutant proteins congregate into insoluble aggregates alongside numerous SG proteins, manifesting resilience against disassembly. Specific PTMs conspicuously label these aggregates, designating them for subsequent degradation. The strategic manipulation of aberrant SGs via PTMs emerges as a promising avenue for therapeutic intervention. This review discerns recent strides in comprehending the impact of PTMs on LLPS behavior and the assembly/disassembly kinetics of SGs. By delving into the roles of PTMs in governing SG dynamics, we augment our cognizance of the molecular underpinnings of neurodegeneration. Furthermore, we offer invaluable insights into potential targets for therapeutic intervention in neurodegenerative afflictions, encompassing conditions like amyotrophic lateral sclerosis and frontotemporal dementia.

Machine learning-based approaches for ubiquitination site prediction in human proteins

Protein ubiquitination is a critical post-translational modification (PTMs) involved in numerous cellular processes. Identifying ubiquitination sites (Ubi-sites) on proteins offers valuable insights into their function and regulatory mechanisms. Due to the cost- and time-consuming nature of traditional approaches for Ubi-site detection, there has been a growing interest in leveraging artificial intelligence for computer-aided Ubi-site prediction. In this study, we collected experimentally verified Ubi-sites of human proteins from the dbPTM database, then conducted comprehensive state-of-the art computational methods along with standard evaluation metrics and a proper validation strategy for Ubi-site prediction. We presented the effectiveness of our framework by comparing ten machine learning (ML) based approaches in three different categories: feature-based conventional ML methods, end-to-end sequence-based deep learning (DL) techniques, and hybrid feature-based DL models. Our results revealed that DL approaches outperformed the classical ML methods, achieving a 0.902 F1-score, 0.8198 accuracy, 0.8786 precision, and 0.9147 recall as the best performance for a DL model using both raw amino acid sequences and hand-crafted features. Interestingly, our experimental results disclosed that the performance of DL methods had a positive correlation with the length of amino acid fragments, suggesting that utilizing the entire sequence can lead to more accurate predictions in future research endeavors. Additionally, we developed a meticulously curated benchmark for Ubi-site prediction in human proteins. This benchmark serves as a valuable resource for future studies, enabling fair and accurate comparisons between different methods. Overall, our work highlights the potential of ML, particularly DL techniques, in predicting Ubi-sites and furthering our knowledge of protein regulation through ubiquitination in cells.

In-silico assessment of high-risk non-synonymous SNPs in ADAMTS3 gene associated with Hennekam syndrome and their impact on protein stability and function

Hennekam Lymphangiectasia-Lymphedema Syndrome 3 (HKLLS3) is a rare genetical disorder caused by mutations in a few genes including ADAMTS3. It is characterized by lymphatic dysplasia, intestinal lymphangiectasia, severe lymphedema and distinctive facial appearance. Up till now, no extensive studies have been conducted to elucidate the mechanism of the disease caused by various mutations. As a preliminary investigation of HKLLS3, we sorted out the most deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) that might affect the structure and function of ADAMTS3 protein by using a variety of in silico tools. A total of 919 nsSNPs in the ADAMTS3 gene were identified. 50 nsSNPs were predicted to be deleterious by multiple computational tools. 5 nsSNPs (G298R, C567Y, A370T, C567R and G374S) were found to be the most dangerous and can be associated with the disease as predicted by different bioinformatics tools. Modelling of the protein shows it can be divided into segments 1, 2 and 3, which are connected by short loops. Segment 3 mainly consists of loops without substantial secondary structures. With prediction tools and molecular dynamics simulation, some SNPs were found to significantly destabilize the protein structure and disrupt the secondary structures, especially in segment 2. The deleterious effects of mutations in segment 1 are possibly not from destabilization but from other factors such as the change in phosphorylation as suggested by post-translational modification (PTM) studies. This is the first-ever study of ADAMTS3 gene polymorphism, and the predicted nsSNPs in ADAMST3, some of which have not been reported yet in patients, will serve for diagnostic purposes and further therapeutic implications in Hennekam syndrome, contributing to better diagnosis and treatment.

In Silico Analysis of nsSNPs of Human KRAS Gene and Protein Modeling Using Bioinformatic Tools

The KRAS gene belongs to the RAS family and codes for 188 amino acid residues of KRAS protein, with a molecular mass of 21.6 kD. Non-synonymous single-nucleotide polymorphisms (nsSNPs) have been identified within the coding region in which some are associated with different diseases. However, structural changes are not well defined yet. In this study, we first categorized SNPs in the KRAS coding area and then used computational methods to determine their impact on the protein structure and stability. In addition, the three-dimensional model of KRAS was taken from the Protein Data Bank for structural modeling. Furthermore, genomic data were extracted from a variety of sources, including the 1000 Genome Project, dbSNPs, and ENSEMBLE, and assessed through in silico methods. Based on various tools used in this study, 10 out of 48 missense SNPs with rsIDs were found deleterious. The substitution of alanine for proline at position 146 pushed several residues toward the center of the protein. Arginine instead of leucine has a minor effect on protein structure and stability. In addition, the substitution of proline for leucine at the 34th position disrupted the structure and led to a bigger size than the wild-type protein, hence interrupting the protein interaction. Using the well-intended computational approach and applying several bioinformatic tools, we characterized and identified most damaging nsSNPs and further explored the structural dynamics and stability of KRAS protein.

An inclusive study of deleterious missense PAX9 variants using user-friendly tools reveals structural, functional alterations, as well as potential therapeutic targets

Mutations in the PAX9 are responsible for non-syndromic tooth agenesis in humans, although their structural and functional consequences on protein phenotype, stability, and posttranslational modifications (PTMs) have not yet been adequately investigated. This in silico study focuses on retrieving the six most deleterious mutations (L21P, R26W, R28P, G51S, I87F, and K91E) of PAX9 that has been linked to severe oligodontia. Several computational algorithm methods were used to determine the deleterious effects of PAX9 mutations. Analysis of gene ontology, protein interactions, and PTMs indicated significant functional changes caused by PAX9 mutations. The structural superimposition of the wild-type and mutant PAX9 variants revealed structural changes in locations that were present in the structures of all six variations. The conserved domain analysis revealed that the areas shared by all six variations contained unique sections that lacked DNA binding or protein-protein interaction sites, suggesting prospective drug target sites for functional restoration. The protein-protein interaction network showed KDM5B as PAX9's strongest interacting partner similar to MSX1. The PAX9 protein's structural conformations, compactness, stiffness, and function may all be impacted by changes, according to MD simulations. In addition, research on cell lines and animal models may be valuable in establishing their specific roles in functional annotations.

UHRF1/UBE2L6/UBR4-mediated ubiquitination regulates EZH2 abundance and thereby melanocytic differentiation phenotypes in melanoma

Cellular heterogeneity in cancer is linked to disease progression and therapy response, although mechanisms regulating distinct cellular states within tumors are not well understood. We identified melanin pigment content as a major source of cellular heterogeneity in melanoma and compared RNAseq data from high-pigmented (HPCs) and low-pigmented melanoma cells (LPCs), suggesting EZH2 as a master regulator of these states. EZH2 protein was found to be upregulated in LPCs and inversely correlated with melanin deposition in pigmented patient melanomas. Surprisingly, conventional EZH2 methyltransferase inhibitors, GSK126 and EPZ6438, had no effect on LPC survival, clonogenicity and pigmentation, despite fully inhibiting methyltransferase activity. In contrast, EZH2 silencing by siRNA or degradation by DZNep or MS1943 inhibited growth of LPCs and induced HPCs. As the proteasomal inhibitor MG132 induced EZH2 protein in HPCs, we evaluated ubiquitin pathway proteins in HPC vs LPCs. Biochemical assays and animal studies demonstrated that in LPCs, the E2-conjugating enzyme UBE2L6 depletes EZH2 protein in cooperation with UBR4, an E3 ligase, via ubiquitination at EZH2's K381 residue, and is downregulated in LPCs by UHRF1-mediated CpG methylation. Targeting UHRF1/UBE2L6/UBR4-mediated regulation of EZH2 offers potential for modulating the activity of this oncoprotein in contexts in which conventional EZH2 methyltransferase inhibitors are ineffective.

Dissecting the interstrand crosslink DNA repair system of Trypanosoma cruzi

DNA interstrand crosslinks (ICLs) are toxic lesions that can block essential biological processes. Here we show Trypanosoma cruzi, the causative agent of Chagas disease, is susceptible to ICL-inducing compounds including mechlorethamine and novel nitroreductase-activated prodrugs that have potential in treating this infection. To resolve such lesions, cells co-opt enzymes from "classical" DNA repair pathways that alongside dedicated factors operate in replication-dependent and -independent mechanisms. To assess ICL repair in T. cruzi, orthologues of SNM1, MRE11 and CSB were identified and their function assessed. The T. cruzi enzymes could complement the mechlorethamine susceptibility phenotype displayed by corresponding yeast and/or T. brucei null confirming their role as ICL repair factors while GFP-tagged TcSNM1, TcMRE11 and TcCSB were shown to localise to the nuclei of insect and/or intracellular form parasites. Gene disruption demonstrated that while each activity was non-essential for T. cruzi viability, nulls displayed a growth defect in at least one life cycle stage with TcMRE11-deficient trypomastigotes also compromised in mammalian cell infectivity. Phenotyping revealed all nulls were more susceptible to mechlorethamine than controls, a trait complemented by re-expression of the deleted gene. To assess interplay, the gene disruption approach was extended to generate T. cruzi deficient in TcSNM1/TcMRE11 or in TcSNM1/TcCSB. Analysis demonstrated these activities functioned across two ICL repair pathways with TcSNM1 and TcMRE11 postulated to operate in a replication-dependent system while TcCSB helps resolve transcription-blocking lesions. By unravelling how T. cruzi repairs ICL damage, specific inhibitors targeting repair components could be developed and used to increase the potency of trypanocidal ICL-inducing compounds.

Reciprocal regulatory balance within the CLEC16A-RNF41 mitophagy complex depends on an intrinsically disordered protein region

CLEC16A is an E3 ubiquitin ligase that regulates mitochondrial quality control through mitophagy and is associated with over 20 human diseases. CLEC16A forms a complex with another E3 ligase, RNF41, and a ubiquitin-specific peptidase, USP8; however, regions that regulate CLEC16A activity or the assembly of the tripartite mitophagy regulatory complex are unknown. Here, we report that CLEC16A contains an internal intrinsically disordered protein region (IDPR) that is crucial for CLEC16A function and turnover. IDPRs lack a fixed secondary structure and possess emerging, yet still equivocal roles in protein stability, interactions, and enzymatic activity. We find that the internal IDPR of CLEC16A is crucial for its degradation. CLEC16A turnover was promoted by RNF41, which binds and acts upon the internal IDPR to destabilize CLEC16A. Loss of this internal IDPR also destabilized the ubiquitin-dependent tripartite CLEC16A-RNF41-USP8 complex. Finally, the presence of an internal IDPR within CLEC16A was confirmed using NMR and circular dichroism spectroscopy. Together, our studies reveal that an IDPR is essential to control the reciprocal regulatory balance between CLEC16A and RNF41, which could be targeted to improve mitochondrial health in disease.

Monoubiquitinated MxIRT1 acts as an iron receptor to determine MxIRT1 vacuole degradation or plasma membrane recycling via endocytosis

IRON-REGULATED TRANSPORTER 1 (IRT1) is critical for iron uptake in roots, and its exocytosis to the plasma membrane (PM) is regulated by the iron status sensed by the histidine-rich domain (HRM). However, studies on the fate of IRT1 after fusion with PM in response to iron conditions are still limited. In this study, we found that K165 and K196 regulate the monoubiquitination of MxIRT1 (mUb-MxIRT1), which acts as a receptor delivering signals from HRM to downstream effectors such as clathrin to determine the fate of MxIRT1. Iron supply led MxIRT1 in the PM to monoubiquitin-dependent endocytosis which could be inhibited by endocytosis inhibitor TyrA23 or in the double site-directed mutant K165/K196R. Subsequently, the endocytosis pathway to the vacuole was inhibited by vacuolar protease inhibitor Leupeptin in excessive iron conditions and the inability of being able to respond to iron change, indicated by the protein accumulating in the PM, contributed to iron toxicity in K165/K196R transgenic Arabidopsis. With iron availability decreasing again, MxIRT1 could dock close to the PM waiting for to be recycled. Another monoubiquitination site, K26, was necessary for MxIRT1 Endoplasmic Reticulum (ER) export as site-directed mutant K26R lost the ability of PM targeting, and co-localized with the COPII subunit of the coat protein OsSec24. Therefore, after K26-directed ER export and iron-induced PM fusion, mUb-MxIRT1 determines subsequent vacuolar degradation or recycling to the PM via endocytosis for maintaining iron homeostasis.

Insilico prediction and functional analysis of nonsynonymous SNPs in human CTLA4 gene

The CTLA4 receptor is an immune checkpoint involved in the downregulation of T cells. Polymorphisms in this gene have been found to be associated with different diseases like rheumatoid arthritis, autosomal dominant immune dysregulation syndrome, juvenile idiopathic arthritis and autoimmune Addison's disease. Therefore, the identification of polymorphisms that have an effect on the structure and function of CTLA4 gene is important. Here we identified the most damaging missense or non-synonymous SNPs (nsSNPs) that might be crucial for the structure and function of CTLA4 using different bioinformatics tools. These in silico tools included SIFT, PROVEAN, PhD-SNP, PolyPhen-2 followed by MutPred2, I-Mutant 2.0 and ConSurf. The protein structures were predicted using Phyre2 and I-TASSER, while the gene-gene interactions were predicted by GeneMANIA and STRING. Our study identified three damaging missense SNPs rs1553657429, rs1559591863 and rs778534474 in coding region of CTLA4 gene. Among these SNPs the rs1553657429 showed a loss of potential phosphorylation site and was found to be highly conserved. The prediction of gene-gene interaction showed the interaction of CTlA4 with other genes and its importance in different pathways. This investigation of damaging nsSNPs can be considered in future while studying CTLA4 related diseases and can be of great importance in precision medicine.

Thirty years of molecular dynamics simulations on posttranslational modifications of proteins

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

Ubiquitination regulates cytoophidium assembly in Schizosaccharomyces pombe

CTP synthase (CTPS), a metabolic enzyme responsible for the de novo synthesis of CTP, can form filamentous structures termed cytoophidia, which are evolutionarily conserved from bacteria to humans. Here we used Schizosaccharomyces pombe to study the cytoophidium assembly regulation by ubiquitination. We tested the CTP synthase's capacity to be post-translationally modified by ubiquitin or be affected by the ubiquitination state of the cell and showed that ubiquitination is important for the maintenance of the CTPS filamentous structure in fission yeast. We have identified proteins which are in complex with CTPS, including specific ubiquitination regulators which significantly affect CTPS filamentation, and mapped probable ubiquitination targets on CTPS. Furthermore, we discovered that a cohort of deubiquitinating enzymes is important for the regulation of cytoophidium's filamentous morphology. Our study provides a framework for the analysis of the effects that ubiquitination and deubiquitination have on the formation of cytoophidia.

A COP1-GATA2 axis suppresses AR signaling and prostate cancer

Androgen receptor (AR) signaling is crucial for driving prostate cancer (PCa), the most diagnosed and the second leading cause of death in male patients with cancer in the United States. Androgen deprivation therapy is initially effective in most instances of AR-positive advanced or metastatic PCa. However, patients inevitably develop lethal castration-resistant PCa (CRPC), which is also resistant to the next-generation AR signaling inhibitors. Most CRPCs maintain AR expression, and blocking AR signaling remains a main therapeutic approach. GATA2 is a pioneer transcription factor emerging as a key therapeutic target for PCa because it promotes AR expression and activation. While directly inhibiting GATA2 transcriptional activity remains challenging, enhancing GATA2 degradation is a plausible therapeutic strategy. How GATA2 protein stability is regulated in PCa remains unknown. Here, we show that constitutive photomorphogenesis protein 1 (COP1), an E3 ubiquitin ligase, drives GATA2 ubiquitination at K419/K424 for degradation. GATA2 lacks a conserved [D/E](x)xxVP[D/E] degron but uses alternate BR1/BR2 motifs to bind COP1. By promoting GATA2 degradation, COP1 inhibits AR expression and activation and represses PCa cell and xenograft growth and castration resistance. Accordingly, GATA2 overexpression or COP1 mutations that disrupt COP1-GATA2 binding block COP1 tumor-suppressing activities. We conclude that GATA2 is a major COP1 substrate in PCa and that COP1 promotion of GATA2 degradation is a direct mechanism for regulating AR expression and activation, PCa growth, and castration resistance.

The Binding of CSL Proteins to Either Co-Activators or Co-Repressors Protects from Proteasomal Degradation Induced by MAPK-Dependent Phosphorylation

The primary role of Notch is to specify cellular identities, whereby the cells respond to amazingly small changes in Notch signalling activity. Hence, dosage of Notch components is crucial to regulation. Central to Notch signal transduction are CSL proteins: together with respective cofactors, they mediate the activation or the silencing of Notch target genes. CSL proteins are extremely similar amongst species regarding sequence and structure. We noticed that the fly homologue suppressor of hairless (Su(H)) is stabilised in transcription complexes. Using specific transgenic fly lines and HeLa RBPJ^KO cells we provide evidence that Su(H) is subjected to proteasomal degradation with a half-life of about two hours if not protected by binding to co-repressor hairless or co-activator Notch. Moreover, Su(H) stability is controlled by MAPK-dependent phosphorylation, matching earlier data for RBPJ in human cells. The homologous murine and human RBPJ proteins, however, are largely resistant to degradation in our system. Mutating presumptive protein contact sites, however, sensitised RBPJ for proteolysis. Overall, our data highlight the similarities in the regulation of CSL protein stability across species and imply that turnover of CSL proteins may be a conserved means of regulating Notch signalling output directly at the level of transcription.

Hrq1/RECQL4 regulation is critical for preventing aberrant recombination during DNA intrastrand crosslink repair and is upregulated in breast cancer

Human RECQL4 is a member of the RecQ family of DNA helicases and functions during DNA replication and repair. RECQL4 mutations are associated with developmental defects and cancer. Although RECQL4 mutations lead to disease, RECQL4 overexpression is also observed in cancer, including breast and prostate. Thus, tight regulation of RECQL4 protein levels is crucial for genome stability. Because mammalian RECQL4 is essential, how cells regulate RECQL4 protein levels is largely unknown. Utilizing budding yeast, we investigated the RECQL4 homolog, HRQ1, during DNA crosslink repair. We find that Hrq1 functions in the error-free template switching pathway to mediate DNA intrastrand crosslink repair. Although Hrq1 mediates repair of cisplatin-induced lesions, it is paradoxically degraded by the proteasome following cisplatin treatment. By identifying the targeted lysine residues, we show that preventing Hrq1 degradation results in increased recombination and mutagenesis. Like yeast, human RECQL4 is similarly degraded upon exposure to crosslinking agents. Furthermore, over-expression of RECQL4 results in increased RAD51 foci, which is dependent on its helicase activity. Using bioinformatic analysis, we observe that RECQL4 overexpression correlates with increased recombination and mutations. Overall, our study uncovers a role for Hrq1/RECQL4 in DNA intrastrand crosslink repair and provides further insight how misregulation of RECQL4 can promote genomic instability, a cancer hallmark.

RECQL4 is a DNA helicase and functions during DNA replication and repair. While loss-of-function RECQL4 mutations are found in diseases characterized by developmental defects and cancer, such as Rothmund-Thomson syndrome, over-expression of RECQL4 is also observed in cancer, such as breast cancer. Therefore, RECQL4 protein expression must be tightly regulated. Here we used the budding yeast homolog of RECQL4, Hrq1, and discovered that overexpression of Hrq1 protein levels result in increased recombination and mutations, both cancer hallmarks. We find that Hrq1 functions to mediate repair of a specific type of DNA damage, intrastrand crosslinks, which occur when DNA nucleotides on the same strand are chemically linked together. These findings are also conserved in humans suggesting a common mechanism between yeast Hrq1 and human RECQL4. Overall, our study identifies a conserved role for RECQL4 in DNA intrastrand crosslink repair and provides insights into how its misregulation could promote cancer development.

Integrated analysis to study the interplay between post-translational modifications (PTM) in hepatitis C virus proteins and hepatocellular carcinoma (HCC) development

Many PTMs dysregulation is known to be the major cause of many cancers including HCV induced HCC. PTMs of hepatitis C virus (HCV) regions NS3/4A, NS5A and NS5B are crucial for proper protein functions and replication that directly affect the generation of infectious virus particles and completion of its life cycle. In this study, we have performed comprehensive analysis of PTMs within HCV non-structural proteins (NS3/4A, NS5A and NS5B) through bioinformatics analysis to examine post-translational crosstalk between phosphorylation, palmitoylation, methylation, acetylation and ubiquitination sites in selected viral proteins. Our analysis has revealed many highly putative PTMs sites that are also conserved among major genotypes conferring the importance of these sites. We have also analysed viral 3D structures in their modified and unmodified forms to address extent and signatures of structural changes upon PTM. This study provides evidence that PTMs induce significant conformational changes and make viral proteins more stable. To find the potential role of PTMs in HCV induced HCC, docking analysis between selected viral proteins and p38-MAPK has been performed which also confirms their strong association with HCV induced HCC. The major findings proposed that PTMs at specific sites of HCV viral proteins could dysregulate specific pathways that cause the development of HCC.

Identification of the ubiquitin–proteasome pathway domain by hyperparameter optimization based on a 2D convolutional neural network

The major mechanism of proteolysis in the cytosol and nucleus is the ubiquitin–proteasome pathway (UPP). The highly controlled UPP has an effect on a wide range of cellular processes and substrates, and flaws in the system can lead to the pathogenesis of a number of serious human diseases. Knowledge about UPPs provide useful hints to understand the cellular process and drug discovery. The exponential growth in next-generation sequencing wet lab approaches have accelerated the accumulation of unannotated data in online databases, making the UPP characterization/analysis task more challenging. Thus, computational methods are used as an alternative for fast and accurate identification of UPPs. Aiming this, we develop a novel deep learning-based predictor named “2DCNN-UPP” for identifying UPPs with low error rate. In the proposed method, we used proposed algorithm with a two-dimensional convolutional neural network with dipeptide deviation features. To avoid the over fitting problem, genetic algorithm is employed to select the optimal features. Finally, the optimized attribute set are fed as input to the 2D-CNN learning engine for building the model. Empirical evidence or outcomes demonstrates that the proposed predictor achieved an overall accuracy and AUC (ROC) value using 10-fold cross validation test. Superior performance compared to other state-of-the art methods for discrimination the relations UPPs classification. Both on and independent test respectively was trained on 10-fold cross validation method and then evaluated through independent test. In the case where experimentally validated ubiquitination sites emerged, we must devise a proteomics-based predictor of ubiquitination. Meanwhile, we also evaluated the generalization power of our trained modal via independent test, and obtained remarkable performance in term of 0.862 accuracy, 0.921 sensitivity, 0.803 specificity 0.803, and 0.730 Matthews correlation coefficient (MCC) respectively. Four approaches were used in the sequences, and the physical properties were calculated combined. When used a 10-fold cross-validation, 2D-CNN-UPP obtained an AUC (ROC) value of 0.862 predicted score. We analyzed the relationship between UPP protein and non-UPP protein predicted score. Last but not least, this research could effectively analyze the large scale relationship between UPP proteins and non-UPP proteins in particular and other protein problems in general and our research work might improve computational biological research. Therefore, we could utilize the latest features in our model framework and Dipeptide Deviation from Expected Mean (DDE) -based protein structure features for the prediction of protein structure, functions, and different molecules, such as DNA and RNA.

Autophagy Activation Induces p62-Dependent Autophagic Degradation of Dengue Virus Capsid Protein During Infection

In the past decade, dengue virus infection is one of the most prevalent and rapidly spreading arthropod-borne diseases worldwide with about 400 million infections every year. Although it has been reported that the dengue virus could take advantage of autophagy to promote its propagation, the association between selective autophagy and the dengue virus remains largely unclear. Here, we demonstrated that dengue virus capsid protein, the key viral protein for virus assembly, maturation, and replication, underwent autophagic degradation after autophagy activation. Autophagy cargo receptor p62 delivered ubiquitinated capsid protein to autophagosomes for degradation, which could be enhanced by Torin 1 treatments. Further study revealed that the association between p62 and viral capsid protein was dependent on the ubiquitin-binding domain of p62, and the poly-ubiquitin conjugated at lysine 76 of capsid protein served as a recognition signal for autophagy. Consistently, p62 deficiency in Huh7 cells led to the enhancement of dengue virus replication. Our study revealed that p62 targeted dengue virus capsid protein for autophagic degradation in a ubiquitin-dependent manner, which might uncover the potential roles of p62 in restricting dengue virus replication.

PPVED: A machine learning tool for predicting the effect of single amino acid substitution on protein function in plants

Single amino acid substitution (SAAS) produces the most common variant of protein function change under physiological conditions. As the number of SAAS events in plants has increased exponentially, an effective prediction tool is required to help identify and distinguish functional SAASs from the whole genome as either potentially causal traits or as variants. Here, we constructed a plant SAAS database that stores 12 865 SAASs in 6172 proteins and developed a tool called Plant Protein Variation Effect Detector (PPVED) that predicts the effect of SAASs on protein function in plants. PPVED achieved an 87% predictive accuracy when applied to plant SAASs, an accuracy that was much higher than those from six human database software: SIFT, PROVEAN, PANTHER-PSEP, PhD-SNP, PolyPhen-2, and MutPred2. The predictive effect of six SAASs from three proteins in Arabidopsis and maize was validated with wet lab experiments, of which five substitution sites were accurately predicted. PPVED could facilitate the identification and characterization of genetic variants that explain observed phenotype variations in plants, contributing to solutions for challenges in functional genomics and systems biology. PPVED can be accessed under a CC-BY (4.0) license via http://www.ppved.org.cn.

In Silico Analysis Revealed Five Novel High-Risk Single-Nucleotide Polymorphisms (rs200384291, rs201163886, rs193141883, rs201139487, and rs201723157) in ELANE Gene Causing Autosomal Dominant Severe Congenital Neutropenia 1 and Cyclic Hematopoiesis

Single-nucleotide polymorphisms in the ELANE (Elastase, Neutrophil Expressed) gene are associated with severe congenital neutropenia, while the ELANE gene provides instructions for making a protein called neutrophil elastase. We identified disease susceptibility single-nucleotide polymorphisms (SNPs) in the ELANE gene using several computational tools. We used cutting-edge computational techniques to investigate the effects of ELANE mutations on the sequence and structure of the protein. Our study suggested that eight nsSNPs (rs28931611, rs57246956, rs137854448, rs193141883, rs201723157, rs201139487, rs137854451, and rs200384291) are the most deleterious in ELANE gene and disturb protein structure and function. The mutants F218L, R34W, G203S, R193W, and T175M have not yet been identified in patients suffering from SCN and cyclic hematopoiesis, while C71Y, P139R, C151Y, G214R, and G203C reported in our study are already associated with both of the disorders. These mutations are shown to destabilize structure and disrupt ELANE protein activation, splicing, and folding and might diminish trypsin-like serine protease efficiency. Prediction of posttranslation modifications highlighted the significance of deleterious nsSNPs because some of nsSNPs affect potential phosphorylation sites. Gene-gene interactions showed the relation of ELANE with other genes depicting its importance in numerous pathways and coexpressions. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking. This research sheds light on how ELANE failure upon mutation results in disease progression, including congenital neutropenia, and validation of these novel predicted nsSNPs is required through the wet lab.

Novel Disease-Associated Missense Single-Nucleotide Polymorphisms Variants Predication by Algorithms Tools and Molecular Dynamics Simulation of Human TCIRG1 Gene Causing Congenital Neutropenia and Osteopetrosis

T Cell Immune Regulator 1, ATPase H + Transporting V0 Subunit A3 (TCIRG1 gene provides instructions for making one part, the a3 subunit, of a large protein complex known as a vacuolar H + -ATPase (V-ATPase). V-ATPases are a group of similar complexes that act as pumps to move positively charged hydrogen atoms (protons) across membranes. Single amino acid changes in highly conserved areas of the TCIRG1 protein have been linked to autosomal recessive osteopetrosis and severe congenital neutropenia. We used multiple computational approaches to classify disease-prone single nucleotide polymorphisms (SNPs) in TCIRG1. We used molecular dynamics analysis to identify the deleterious nsSNPs, build mutant protein structures, and assess the impact of mutation. Our results show that fifteen nsSNPs (rs199902030, rs200149541, rs372499913, rs267605221, rs374941368, rs375717418, rs80008675, rs149792489, rs116675104, rs121908250, rs121908251, rs121908251, rs149792489 and rs116675104) variants are likely to be highly deleterious mutations as by incorporating them into wild protein they destabilize the wild protein structure and function. They are also located in the V-ATPase I domain, which may destabilize the structure and impair TCIRG1 protein activation, as well as reduce its ATPase effectiveness. These mutants have not yet been identified in patients suffering from CN and osteopetrosis while (G405R, R444L, and D517N) reported in our study are already associated with osteopetrosis. Mutation V52L reported in our study was identified in a patient suspected for CN. Finally, these mutants can help to further understand the broad pool of illness susceptibilities associated with TCIRG1 catalytic kinase domain activation and aid in the development of an effective treatment for associated diseases.

In Silico Analysis Identified Putative Pathogenic Missense nsSNPs in Human SLITRK1 Gene

Human DNA contains several variations, which can affect the structure and normal functioning of a protein. These variations could be single nucleotide polymorphisms (SNPs) or insertion-deletions (InDels). SNPs, as opposed to InDels, are more commonly present in DNA and may cause genetic disorders. In the current study, several bioinformatic tools were used to prioritize the pathogenic variants in the SLITRK1 gene. Out of all of the variants, 16 were commonly predicted to be pathogenic by these tools. All the variants had very low frequency, i.e., <0.0001 in the global population. The secondary structure of all filtered variants was predicted, but no structural change was observed at the site of variation in any variant. Protein stability analysis of these variants was then performed, which determined a decrease in protein stability of 10 of the variants. Amino acid conservation analysis revealed that all the amino acids were highly conserved, indicating their structural and functional importance. Protein 3D structure of wildtype SLITRK1 and all of its variants was predicted using I-TASSER, and the effect of variation on 3D structure of the protein was observed using the Missense3D tool, which presented the probable structural loss in three variants, i.e., Asn529Lys, Leu496Pro and Leu94Phe. The wildtype SLITRK1 protein and these three variants were independently docked with their close interactor protein PTPRD, and remarkable differences were observed in the docking sites of normal and variants, which will ultimately affect the functional activity of the SLITRK1 protein. Previous studies have shown that mutations in SLITRK1 are involved in Tourette syndrome. The present study may assist a molecular geneticist in interpreting the variant pathogenicity in research as well as diagnostic setup.

Development of multivalent vaccine targeting M segment of Crimean Congo Hemorrhagic Fever Virus (CCHFV) using immunoinformatic approaches

Crimean-Congo Hemorrhagic Fever (CCHF) is a tick-borne viral infection with no licensed vaccine or therapeutics available for its treatment. In the present study we have developed the first multi-epitope subunit vaccine effective against all the seven genotypes of CCHF virus (CCHFV). The vaccine contains five B-cell, two MHC-II (HTL), and three MHC-I (CTL) epitopes screened from two structural glycoproteins (Gc and Gn in M segment) of CCHFV with an N-terminus human β-defensin as an adjuvant, as well as an N-terminus EAAAK sequence. The epitopes were rigorously investigated for their antigenicity, allergenicity, IFN gamma induction, anti-inflammatory responses, stability, and toxicity. The three-dimensional structure of the vaccine was predicted and docked with TLR-3, TLR-8, and TLR-9 receptors to find the strength of the binding complexes via molecular dynamics simulation. After codon adaptation, the subunit vaccine construct was developed in a pDual-GC plasmid and has population coverage of 98.47% of the world's population (HLA-I & II combined). The immune simulation studies were carried out on the C-ImmSim in-silico interface showing a marked increase in the production of cellular and humoral response (B-cell and T-cell) as well as TGFβ, IL-2, IL-10, and IL-12 indicating that the proposed vaccine would be able to sufficiently provoke both humoral and cell-mediated immune responses. Thus, making it a new and promising vaccine candidate against CCHFV.

Computational and Experimental Analysis of Genetic Variants

Genomics has grown exponentially over the last decade. Common variants are associated with physiological changes through statistical strategies such as Genome-Wide Association Studies (GWAS) and quantitative trail loci (QTL). Rare variants are associated with diseases through extensive filtering tools, including population genomics and trio-based sequencing (parents and probands). However, the genomic associations require follow-up analyses to narrow causal variants, identify genes that are influenced, and to determine the physiological changes. Large quantities of data exist that can be used to connect variants to gene changes, cell types, protein pathways, clinical phenotypes, and animal models that establish physiological genomics. This data combined with bioinformatics including evolutionary analysis, structural insights, and gene regulation can yield testable hypotheses for mechanisms of genomic variants. Molecular biology, biochemistry, cell culture, CRISPR editing, and animal models can test the hypotheses to give molecular variant mechanisms. Variant characterizations can be a significant component of educating future professionals at the undergraduate, graduate, or medical training programs through teaching the basic concepts and terminology of genetics while learning independent research hypothesis design. This article goes through the computational and experimental analysis strategies of variant characterization and provides examples of these tools applied in publications. © 2022 American Physiological Society. Compr Physiol 12:3303-3336, 2022.

Intrinsically disordered proteins play diverse roles in cell signaling

Abstract

Signaling pathways allow cells to detect and respond to a wide variety of chemical (e.g. Ca²⁺ or chemokine proteins) and physical stimuli (e.g., sheer stress, light). Together, these pathways form an extensive communication network that regulates basic cell activities and coordinates the function of multiple cells or tissues. The process of cell signaling imposes many demands on the proteins that comprise these pathways, including the abilities to form active and inactive states, and to engage in multiple protein interactions. Furthermore, successful signaling often requires amplifying the signal, regulating or tuning the response to the signal, combining information sourced from multiple pathways, all while ensuring fidelity of the process. This sensitivity, adaptability, and tunability are possible, in part, due to the inclusion of intrinsically disordered regions in many proteins involved in cell signaling. The goal of this collection is to highlight the many roles of intrinsic disorder in cell signaling. Following an overview of resources that can be used to study intrinsically disordered proteins, this review highlights the critical role of intrinsically disordered proteins for signaling in widely diverse organisms (animals, plants, bacteria, fungi), in every category of cell signaling pathway (autocrine, juxtacrine, intracrine, paracrine, and endocrine) and at each stage (ligand, receptor, transducer, effector, terminator) in the cell signaling process. Thus, a cell signaling pathway cannot be fully described without understanding how intrinsically disordered protein regions contribute to its function. The ubiquitous presence of intrinsic disorder in different stages of diverse cell signaling pathways suggest that more mechanisms by which disorder modulates intra- and inter-cell signals remain to be discovered.

Graphical abstract

Cdc6 is sequentially regulated by PP2A-Cdc55, Cdc14, and Sic1 for origin licensing in S. cerevisiae

Cdc6, a subunit of the pre-replicative complex (pre-RC), contains multiple regulatory cyclin-dependent kinase (Cdk1) consensus sites, SP or TP motifs. In Saccharomyces cerevisiae, Cdk1 phosphorylates Cdc6-T7 to recruit Cks1, the Cdk1 phospho-adaptor in S phase, for subsequent multisite phosphorylation and protein degradation. Cdc6 accumulates in mitosis and is tightly bound by Clb2 through N-terminal phosphorylation in order to prevent premature origin licensing and degradation. It has been extensively studied how Cdc6 phosphorylation is regulated by the cyclin-Cdk1 complex. However, a detailed mechanism on how Cdc6 phosphorylation is reversed by phosphatases has not been elucidated. Here, we show that PP2ACdc55 dephosphorylates Cdc6 N-terminal sites to release Clb2. Cdc14 dephosphorylates the C-terminal phospho-degron, leading to Cdc6 stabilization in mitosis. In addition, Cdk1 inhibitor Sic1 releases Clb2·Cdk1·Cks1 from Cdc6 to load Mcm2-7 on the chromatin upon mitotic exit. Thus, pre-RC assembly and origin licensing are promoted by phosphatases through the attenuation of distinct Cdk1-dependent Cdc6 inhibitory mechanisms.

E3 ubiquitin ligase SYVN1 is a key positive regulator for GSDMD-mediated pyroptosis

Gasdermin D (GSDMD) participates in the activation of inflammasomes and pyroptosis. Meanwhile, ubiquitination strictly regulates inflammatory responses. However, how ubiquitination regulates Gasdermin D activity is not well understood. In this study, we show that pyroptosis triggered by Gasdermin D is regulated through ubiquitination. Specifically, SYVN1, an E3 ubiquitin ligase of gasdermin D, promotes GSDMD-mediated pyroptosis. SYVN1 deficiency inhibits pyroptosis and subsequent LDH release and PI uptake. SYVN1 directly interacts with GSDMD, and mediates K27-linked polyubiquitination of GSDMD on K203 and K204 residues, promoting GSDMD-induced pyroptotic cell death. Thus, our findings revealed the essential role of SYVN1 in GSDMD-mediated pyroptosis. Overall, GSDMD ubiquitination is a potential therapeutic module for inflammatory diseases.

TUNAR lncRNA Encodes a Microprotein that Regulates Neural Differentiation and Neurite Formation by Modulating Calcium Dynamics

Long noncoding RNAs (lncRNAs) are regulatory molecules which have been traditionally considered as “non-coding”. Strikingly, recent evidence has demonstrated that many non-coding regions, including lncRNAs, do in fact contain small-open reading frames that code for small proteins that have been called microproteins. Only a few of them have been characterized so far, but they display key functions in a wide variety of cellular processes. Here, we show that TUNAR lncRNA encodes an evolutionarily conserved microprotein expressed in the nervous system that we have named pTUNAR. pTUNAR deficiency in mouse embryonic stem cells improves their differentiation potential towards neural lineage both in vitro and in vivo. Conversely, pTUNAR overexpression impairs neuronal differentiation by reduced neurite formation in different model systems. At the subcellular level, pTUNAR is a transmembrane protein that localizes in the endoplasmic reticulum and interacts with the calcium transporter SERCA2. pTUNAR overexpression reduces cytoplasmatic calcium, consistent with a possible role of pTUNAR as an activator of SERCA2. Altogether, our results suggest that our newly discovered microprotein has an important role in neural differentiation and neurite formation through the regulation of intracellular calcium. From a more general point of view, our results provide a proof of concept of the role of lncRNAs-encoded microproteins in neural differentiation.

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

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

Strategies for Efficient Expression of Heterologous Monosaccharide Transporters in Saccharomyces cerevisiae

In previous work, we developed a Saccharomyces cerevisiae strain (DLG-K1) lacking the main monosaccharide transporters (hxt-null) and displaying high xylose reductase, xylitol dehydrogenase and xylulokinase activities. This strain proved to be a useful chassis strain to study new glucose/xylose transporters, as SsXUT1 from Scheffersomyces stipitis. Proteins with high amino acid sequence similarity (78–80%) to SsXUT1 were identified from Spathaspora passalidarum and Spathaspora arborariae genomes. The characterization of these putative transporter genes (SpXUT1 and SaXUT1, respectively) was performed in the same chassis strain. Surprisingly, the cloned genes could not restore the ability to grow in several monosaccharides tested (including glucose and xylose), but after being grown in maltose, the uptake of ¹⁴C-glucose and ¹⁴C-xylose was detected. While SsXUT1 lacks lysine residues with high ubiquitinylation potential in its N-terminal domain and displays only one in its C-terminal domain, both SpXUT1 and SaXUT1 transporters have several such residues in their C-terminal domains. A truncated version of SpXUT1 gene, deprived of the respective 3′-end, was cloned in DLG-K1 and allowed growth and fermentation in glucose or xylose. In another approach, two arrestins known to be involved in the ubiquitinylation and endocytosis of sugar transporters (ROD1 and ROG3) were knocked out, but only the rog3 mutant allowed a significant improvement of growth and fermentation in glucose when either of the XUT permeases were expressed. Therefore, for the efficient heterologous expression of monosaccharide (e.g., glucose/xylose) transporters in S. cerevisiae, we propose either the removal of lysines involved in ubiquitinylation and endocytosis or the use of chassis strains hampered in the specific mechanism of membrane protein turnover.

A Caps-Ubi Model for Protein Ubiquitination Site Prediction

Ubiquitination, a widespread mechanism of regulating cellular responses in plants, is one of the most important post-translational modifications of proteins in many biological processes and is involved in the regulation of plant disease resistance responses. Predicting ubiquitination is an important technical method for plant protection. Traditional ubiquitination site determination methods are costly and time-consuming, while computational-based prediction methods can accurately and efficiently predict ubiquitination sites. At present, capsule networks and deep learning are used alone for prediction, and the effect is not obvious. The capsule network reflects the spatial position relationship of the internal features of the neural network, but it cannot identify long-distance dependencies or focus on amino acids in protein sequences or their degree of importance. In this study, we investigated the use of convolutional neural networks and capsule networks in deep learning to design a novel model "Caps-Ubi," first using the one-hot and amino acid continuous type hybrid encoding method to characterize ubiquitination sites. The sequence patterns, the dependencies between the encoded protein sequences and the important amino acids in the captured sequences, were then focused on the importance of amino acids in the sequences through the proposed Caps-Ubi model and used for multispecies ubiquitination site prediction. Through relevant experiments, the proposed Caps-Ubi method is superior to other similar methods in predicting ubiquitination sites.

GIpred: a computational tool for prediction of GIGANTEA proteins using machine learning algorithm

In plants, GIGANTEA (GI) protein plays different biological functions including carbon and sucrose metabolism, cell wall deposition, transpiration and hypocotyl elongation. This suggests that GI is an important class of proteins. So far, the resource-intensive experimental methods have been mostly utilized for identification of GI proteins. Thus, we made an attempt in this study to develop a computational model for fast and accurate prediction of GI proteins. Ten different supervised learning algorithms i.e., SVM, RF, JRIP, J48, LMT, IBK, NB, PART, BAGG and LGB were employed for prediction, where the amino acid composition (AAC), FASGAI features and physico-chemical (PHYC) properties were used as numerical inputs for the learning algorithms. Higher accuracies i.e., 96.75% of AUC-ROC and 86.7% of AUC-PR were observed for SVM coupled with AAC + PHYC feature combination, while evaluated with five-fold cross validation. With leave-one-out cross validation, 97.29% of AUC-ROC and 87.89% of AUC-PR were respectively achieved. While the performance of the model was evaluated with an independent dataset of 18 GI sequences, 17 were observed as correctly predicted. We have also performed proteome-wide identification of GI proteins in wheat, followed by functional annotation using Gene Ontology terms. A prediction server "GIpred" is freely accessible at http://cabgrid.res.in:8080/gipred/ for proteome-wide recognition of GI proteins.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12298-022-01130-6.

Computational identification of human ubiquitination sites using convolutional and recurrent neural networks

Ubiquitination is a very important protein post-translational modification in humans, which is closely related to many human diseases such as cancers. Although some methods have been elegantly proposed to predict human ubiquitination sites, the accuracy of these methods is generally not very satisfactory. In order to improve the prediction accuracy of human ubiquitination sites, we propose a new ensemble method HUbipPred, which takes the binary encoding and physicochemical properties of amino acids as training features, and integrates two intensively trained convolutional neural networks and two recurrent neural networks to build the model. Finally, HUbiPred achieves AUC values of 0.852 and 0.844 in five-fold cross-validation and independent tests, respectively, which greatly improves the prediction accuracy compared to previous predictors. We also analyze the physicochemical properties of amino acids around ubiquitination sites, study the important roles of architectures (i.e., convolution, long short-term memory (LSTM) and fully connected hidden layers) in the networks for prediction performance, and also predict potential ubiquitination sites in humans using HUbiPred. The training and test datasets, predicted human ubiquitination sites, and source codes of HUbiPred are publicly available at https://github.com/amituofo-xf/HUbiPred.

Effect of Disease Causing Missense Mutations on Intrinsically Disordered Regions in Proteins

BACKGROUND

It is well known that disease-causing missense mutations (DCMMs) reduce the structural stability/integrity of the proteins with well-defined 3D structures, thereby impacting their molecular functions. However, it is not known in what way DCMMs affect the intrinsically disordered proteins (IDPs) that do not adopt well defined stable 3D structures.

METHODS

In order to investigate how DCMMs may impact intrinsically disordered regions (IDRs) in proteins, we undertook Molecular Dynamics (MD) based studies on three different examples of functionally important IDRs with known DCMMs. Our studies revealed that the functional impact of DCMMs is in reducing the conformational heterogeneity of IDRs, which is intrinsic and quintessential for their multi-faceted cellular roles.

RESULTS

These results are reinforced by energy landscapes of the wildtype and mutant IDRs where the former is characterized by many local minima separated by low barriers, whereas the latter are characterized by one global minimum and several local minima separated by high energy barriers. Our MD based studies also indicate that DCMMs stabilize very few structural possibilities of IDRs either by the newly formed interactions induced by the substituted side chains or by means of restricted or increased flexibilities of the backbone conformations at the mutation sites.

CONCLUSION

Furthermore, the structural possibilities stabilized by DCMMs do not support the native functional roles of the IDRs, thereby leading to disease conditions.

Understanding the impact of missense mutations on the structure and function of the EDA gene in X-linked hypohidrotic ectodermal dysplasia: A bioinformatics approach

X-linked hypohidrotic dysplasia (XLHED), caused by mutations in the EDA gene, is a rare genetic disease that affects the development and function of the teeth, hair, nails, and sweat glands. The structural and functional consequences of caused by an ectodysplasin-A (EDA) mutations on protein phenotype, stability, and posttranslational modifications (PTMs) have not been well investigated. The present investigation involves five missense mutations that cause XLHED (L56P, R155C, P220L, V251M, and V322A) in different domains of EDA (TM, furin, collagen, and tumor necrosis factor [TNF]) from previously published papers. The deleterious nature of EDA mutant variants was identified using several computational algorithm tools. The point mutations induce major drifts in the structural flexibility of EDA mutant variants and have a negative impact on their stability, according to the 3D protein modeling tool assay. Using the molecular docking technique, EDA/EDA variants were docked to 10 EDA interacting partners, retrieved from the STRING database. We found a novel biomarker CD68 by molecular docking analysis, suggesting all five EDA variants had lower affinity for EDAR, EDA2R, and CD68, implying that they would affect embryonic signaling between the ectodermal and mesodermal cell layers. In silico research such as gene ontology, subcellular localization, protein-protein interaction, and PTMs investigations indicates major functional alterations would occur in EDA variants. According to molecular simulations, EDA variants influence the structural conformation, compactness, stiffness, and function of the EDA protein. Further studies on cell line and animal models might be useful in determining their specific roles in functional annotations.

Computational algorithmic and molecular dynamics study of functional and structural impacts of non-synonymous single nucleotide polymorphisms in human DHFR gene

Human dihydrofolate reductase (DHFR) is a conserved enzyme that is central to folate metabolism and is widely targeted in pathogenic diseases as well as cancers. Although studies have reported the fact that genetic mutations in DHFR leads to a rare autosomal recessive inborn error of folate metabolism and drug resistance, there is a lack of an extensive study on how the deleterious non-synonymous SNPs (nsSNPs) disrupt its phenotypic effects. In this study, we aim at discovering the structural and functional consequences of nsSNPs in DHFR by employing a combined computational approach consisting of ten recently developed in silico tools for identification of damaging nsSNPs and molecular dynamics (MD) simulation for getting deeper insights into the magnitudes of damaging effects. Our study revealed the presence of 12 most deleterious nsSNPs affecting the native phenotypic effects, with three (R71T, G118D, Y122D) identified in the co-factor and ligand binding active sites. MD simulations also suggested that these three SNPs particularly Y122D, alter the overall structural flexibility and dynamics of the native DHFR protein which can provide more understandings into the crucial roles of these mutants in influencing the loss of DHFR function.

An Ensemble Deep Learning based Predictor for Simultaneously Identifying Protein Ubiquitylation and SUMOylation Sites

BACKGROUND

Several computational tools for predicting protein Ubiquitylation and SUMOylation sites have been proposed to study their regulatory roles in gene location, gene expression, and genome replication. However, existing methods generally rely on feature engineering, and ignore the natural similarity between the two types of protein translational modification. This study is the first all-in-one deep network to predict protein Ubiquitylation and SUMOylation sites from protein sequences as well as their crosstalk sites simultaneously. Our deep learning architecture integrates several meta classifiers that apply deep neural networks to protein sequence information and physico-chemical properties, which were trained on multi-label classification mode for simultaneously identifying protein Ubiquitylation and SUMOylation as well as their crosstalk sites.

RESULTS

The promising AUCs of our method on Ubiquitylation, SUMOylation and crosstalk sites achieved 0.838, 0.888, and 0.862 respectively on tenfold cross-validation. The corresponding APs reached 0.683, 0.804 and 0.552, which also validated our effectiveness.

CONCLUSIONS

The proposed architecture managed to classify ubiquitylated and SUMOylated lysine residues along with their crosstalk sites, and outperformed other well-known Ubiquitylation and SUMOylation site prediction tools.

Ubiquitin-dependent Argonauteprotein MEL1 degradation is essential for rice sporogenesis and phasiRNA target regulation

MEIOSIS ARRESTED AT LEPTOTENE1 (MEL1), a rice (Oryza sativa) Argonaute (AGO) protein, has been reported to function specifically at premeiotic and meiotic stages of germ cell development and is associated with a novel class of germ cell-specific small noncoding RNAs called phased small RNAs (phasiRNAs). MEL1 accumulation is temporally and spatially regulated and is eliminated after meiosis. However, the metabolism and turnover (i.e. the homeostasis) of MEL1 during germ cell development remains unknown. Here, we show that MEL1 is ubiquitinated and subsequently degraded via the proteasome pathway in vivo during late sporogenesis. Abnormal accumulation of MEL1 after meiosis leads to a semi-sterile phenotype. We identified a monocot-specific E3 ligase, XBOS36, a CULLIN RING-box protein, that is responsible for the degradation of MEL1. Ubiquitination at four K residues at the N terminus of MEL1 by XBOS36 induces its degradation. Importantly, inhibition of MEL1 degradation either by XBOS36 knockdown or by MEL1 overexpression prevents the formation of pollen at the microspore stage. Further mechanistic analysis showed that disrupting MEL1 homeostasis in germ cells leads to off-target cleavage of phasiRNA target genes. Our findings thus provide insight into the communication between a monocot-specific E3 ligase and an AGO protein during plant reproductive development.

MYD88 L265P elicits mutation-specific ubiquitination to drive NF-κB activation and lymphomagenesis

Myeloid differentiation primary response protein 88 (MYD88) is a critical universal adapter that transduces signaling from Toll-like and interleukin receptors to downstream nuclear factor-κB (NF-κB). MYD88L265P (leucine changed to proline at position 265) is a gain-of-function mutation that occurs frequently in B-cell malignancies such as Waldenstrom macroglobulinemia. In this study, E3 ligase RING finger protein family 138 (RNF138) catalyzed K63-linked nonproteolytic polyubiquitination of MYD88L265P, resulting in enhanced recruitment of interleukin-1 receptor-associated kinases and elevated NF-κB activation. However, RNF138 had little effect on wild-type MYD88 (MYD88WT). With either RNF138 knockdown or mutation on MYD88 ubiquitination sites, MYD88L265P did not constitutively activate NF-κB. A20, a negative regulator of NF-κB signaling, mediated K48-linked polyubiquitination of RNF138 for proteasomal degradation. Depletion of A20 further augmented MYD88L265P-mediated NF-κB activation and lymphoma growth. Furthermore, A20 expression correlated negatively with RNF138 expression and NF-κB activation in lymphomas with MYD88L265P and in those without. Strikingly, RNF138 expression correlated positively with NF-κB activation in lymphomas with MYD88L265P, but not in those without it. Our study revealed a novel mutation-specific biochemical reaction that drives B-cell oncogenesis, providing a therapeutic opportunity for targeting oncogenic MYD88L265P, while sparing MYD88WT, which is critical to innate immunity.

The investigation of nonsynonymous SNPs of human SLC6A4 gene associated with depression: An in silico approach

Genetic polymorphism of the SLC6A4 gene is associated with several behavioral disorders, including depression. Since studying the total nonsynonymous single nucleotide polymorphisms (nsSNPs) of the SLC6A4 gene at the population level is a difficult task, we aim to utilize in silico approach to detect the most deleterious nsSNPs of the SLC6A4 gene. In our study, 7 computational tools were used in the initial stage, including SIFT, Polyphen-2, PROVEAN, SNAP2, PhD-SNP, PANTHER, and SNPs&GO to find out the most damaging nsSNPs. In the second phase, we performed structural, functional, and stability analysis of SLC6A4 protein by popular computation tools, including I-Mutant 2.0 and MutPred2. Also, the ConSurf server was utilized to find the conserved region of the SLC6A4 protein to determine the relationship between these conserved regions with high-risk nsSNPs. Based on these analyses, 5 high-risk mutations of the SLC6A4 protein were selected. Then, we carried out comparative modeling by using the Robetta server and aligned the mutant protein model with the native protein structure. Later, we performed the post-translational modification and functional domain analysis of the SLC6A4 protein. This study concludes that Arginine → Tryptophan at position 79 and Arginine → Cysteine at position 104 are the two significant mutations in SLC6A4 protein which might play an essential role in causing diseases. Future studies should take these high-risk nsSNPs (rs1221448303, rs200953188) into consideration while exploring diseases related to the SLC6A4 gene. Besides, our research is the first-ever comprehensive in silico investigation of the SLC6A4 gene. Thus, the findings of this study could be beneficial for developing precision medicines against diseases caused by SLC6A4 malfunction. Furthermore, extensive wet-lab research and experiments on various model organisms might be helpful to investigate the precise role of these damaging nsSNPs of the SLC6A4 gene.