Proteases as Therapeutic Targets Against the Parasitic Cnidarian Ceratonova shasta: Characterization of Molecules Key to Parasite Virulence In Salmonid Hosts

Proteases and their inhibitors play critical roles in host-parasite interactions and in the outcomes of infections. Ceratonova shasta is a myxozoan pathogen that causes enteronecrosis in economically important salmonids from the Pacific Northwest of North America. This cnidarian parasite has host-specific genotypes with varying virulence, making it a powerful system to decipher virulence mechanisms in myxozoans. Using C. shasta genome and transcriptome, we identified four proteases of different catalytic types: cathepsin D (aspartic), cathepsin L and Z-like (cysteine) and aminopeptidase-N (metallo); and a stefin (cysteine protease inhibitor), which implied involvement in virulence and hence represent target molecules for the development of therapeutic strategies. We characterized, annotated and modelled their 3D protein structure using bioinformatics and computational tools. We quantified their expression in C. shasta genotype 0 (low virulence, no mortality) and IIR (high virulence and mortality) in rainbow trout Oncorhynchus mykiss, to demonstrate that there are major differences between the genotypes during infection and parasite development. High proliferation of genotype IIR was associated with high expression of the cathepsin D and the stefin, likely correlated with high nutrient demands and to regulate cell metabolism, with upregulation preceding massive proliferation and systemic dispersion. In contrast, upregulation of the cathepsin L and Z-like cysteine proteases may have roles in host immune evasion in genotype 0 infections, which are associated with low proliferation, low inflammation and non-destructive development. In contrast to the other proteases, C. shasta aminopeptidase-N appears to have a prominent role in nematocyst formation in both genotypes, but only during sporogenesis. Homology searches of C. shasta proteases against other myxozoan transcriptomes revealed a high abundance of cathepsin L and aminopeptidase homologs suggesting common gene requirements across species. Our study identified molecules of potential therapeutic significance for aquaculture and serves as a baseline for future research aimed at functional characterisation of these targets.

Protein Structure Prediction and Bioinfamatic Analysis of Novel Fusion Gene IKZF1/Pfas in BPDCN

A novel fusion gene, IKAROS Family Zinc Finger 1 (IKZF1)/Phosphoribosylformylglycinamidine Synthase (PFAS), was identified in a patient diagnosed with Blastic Plasmacytoid Dendritic Cell Neoplasm (BPDCN). Secondary protein structure analysis, 3D protein structure determination and domain analysis revealed loss of the ZnF-C2H2 domains of IKZF1 caused by premature translation termination at amino acid (AA) residue 55, which might cause dysfunction of IKZF1. Bioinformatic analysis was conducted using RNA-seq data for 37 BPDCN samples from the GSE database (GSE62014 and GSE89565) to elucidate the role of IKZF1 in BPDCN. WGCNA showed that IKZF1 expression could be used to categorize BPDCN samples into two distinct clusters (IKZF1 high and IKZF1 low). Differentially expressed genes (DEGs) were identified in these two subgroups and subjected to GO and KEGG analyses. Mitochondrial function-related pathways and ubiquitin-mediated proteolysis were the most enriched pathways in the GO and KEGG analyses, respectively. A PPI network of the DEGs was constructed, and 10 key genes were identified (CSTF2, SF3B1, U2AF2, HNRNPH1, SF3B3, SNRNP200, LSM2, SLU7, CPSF4 and UPF3B). Most of these genes are related to tumorigenesis, cancer metastasis, and hematopoietic malignancies. In conclusion, the novel IKZF1/PFAS fusion gene could cause dysfunction of the IKZF1. The bioinformatic analysis results emphasized the role of IKZF1 in BPDCN and identified 10 key genes closely related to IKZF1, most of which are tumorigenesis-related. Disclosures No relevant conflicts of interest to declare.

Comprehensive Genome-Wide Analysis of The Catalase Enzyme Toolbox In Potato (Solanum Tuberosum L.)

As antioxidant enzymes, catalase (CAT) protects organisms from oxidative stress via the production of reactive oxygen species (ROS). These enzymes play important roles in diverse biological processes. However, little is known about the CAT genes in potato plants despite its important economical rank of this crop in the world. Yet, abiotic and biotic stresses severely hinder growth and development of the plants which affects the production and quality of the crop. To define the possible roles of CAT genes under various stresses, a genome-wide analysis of CAT gene family has been performed in potato plant.In this study, the StCAT gene’s structure, secondary and 3D protein structure, physicochemical properties, synteny analysis, phylogenetic tree and also expression profiling under various developmental and environmental cues were predicted using bioinformatics tools. The expression analysis by RT-PCR was performed using commercial potato cultivar. Three genes encoding StCAT that code for three proteins each of size 492 aa, interrupted by seven introns have been identified in potatoes. StCAT proteins were found to be localized in the peroxisome which is judged as the main H2O2 cell production site during different processes. Many regulating cis-elements related to stress responses and plant hormones signaling were found in the promoter sequence of each gene. The analysis of motifs and phylogenetic trees showed that StCAT are closer to their homologous in S. lycopersicum and share a 41% – 95% identity with other plants’ CATs. Expression profiling revealed that StCAT1 is the constitutively expressive member; while StCAT2 and StCAT3 are the stress-responsive members.

Retinitis pigmentosa and molar tooth sign caused by novel AHI1 compound heterozygote pathogenic variants

Background Joubert syndrome (JS) is a group of rare congenital disorders characterized by cerebellar vermis dysplasia, developmental delay, and retina dysfunctions. Herein, we reported a Chinese patient carrying a new variant in the AHI1 gene with mild JS, and the 3D structure of the affected Jouberin protein was also predicted. Case presentation The patient was a 31-year-old male, who presented difficulty at finding toys at the age of 2 years, night blindness from age of 5 years, intention tremor and walking imbalance from 29 years of age. Tubular visual field and retina pigmentation were observed on ophthalmology examinations, as well as molar tooth sign on brain magnetic resonance imaging (MRI). Whole exome sequence revealed two compound heterozygous variants at c.2105C>T (p.T702M) and c.1330A>T (p.I444F) in AHI1 gene. The latter one was a novel mutation. The 3D protein structure was predicted using I-TASSER and PyMOL, showing structural changes from functional β-sheet and α-helix to non-functional D-loop, respectively. Conclusions Mild JS due to novel variants at T702M and I444F in the AHI1 gene was reported. The 3D-structural changes in Jouberin protein might underlie the pathogenesis of JS.

Identification of Iron-Sulfur (Fe-S) and Zn-binding Sites Within Proteomes Predicted by DeepMind′s AlphaFold2 Program Dramatically Expands the Metalloproteome

DeepMind′s AlphaFold2 software has ushered in a revolution in high quality, 3D protein structure prediction. In very recent work by the DeepMind team, structure predictions have been made for entire proteomes of twenty-one organisms, with >360,000 structures made available for download. Here we show that thousands of novel binding sites for iron-sulfur (Fe-S) clusters and zinc ions can be identified within these predicted structures by exhaustive enumeration of all potential ligand-binding orientations. We demonstrate that AlphaFold2 routinely makes highly specific predictions of ligand binding sites: for example, binding sites that are comprised exclusively of four cysteine sidechains fall into three clusters, representing binding sites for 4Fe-4S clusters, 2Fe-2S clusters, or individual Zn ions. We show further: (a) that the majority of known Fe-S cluster and Zn-binding sites documented in UniProt are recovered by the AlphaFold2 structures, (b) that there are occasional disputes between AlphaFold2 and UniProt with AlphaFold2 predicting highly plausible alternative binding sites, (c) that the Fe-S cluster binding sites that we identify in E. coli agree well with previous bioinformatics predictions, (d) that cysteines predicted here to be part of Fe-S cluster or Zn-binding sites show little overlap with those shown via chemoproteomics techniques to be highly reactive, and (e) that AlphaFold2 occasionally appears to build erroneous disulfide bonds between cysteines that should instead coordinate a ligand. These results suggest that AlphaFold2 could be an important tool for the functional annotation of proteomes, and the methodology presented here is likely to be useful for predicting other ligand-binding sites.

DNA Binding Activity of Marine Shrimp LvProfilin

Shrimp farming is an important business in Thailand and worldwide. The study of molecular biology and biochemical pathway of the key molecules controlling muscle growth is an essential to improve shrimp livestock. Profilin is a pivotal protein in muscle formation, especially actin protein. Its nuclear function has been reported in many species for gene regulation. Here in this work, we characterized the function of LvProfilin, a marine shrimp profilin from Litopenaeus vannamei, both in silico and in vitro. The phylogenetic tree of LvProfilin among organisms and its 3D protein structure showed that LvProfilin was highly conserved among shrimp and arthropods. The homology modeling of its 3D structure revealed 3 alpha-helices and 6 beta-strands similar to most eukaryotic profilins. To interpret its possible function, the gene expression of LvProfilin in various tissues was performed. We found that this gene was expressed in various tissues. This result may imply that LvProfilin could share a common function in all tissues. Nuclear activity has been a promising function of LvProfilin. We performed a DNA/RNA binding prediction analysis using DRNApred. The result indicated that Lysine-90 and Threonine-91 were the putative DNA-binding sites with the probability of 63.12% and 54.16%, respectively. Its binding activity was confirmed in vitro which bound stronger to single strand DNA than double strand DNA. To our best knowledge, this is the first report of DNA binding activity of profilin in invertebrates.

The importance of residue-level filtering, and the Top2018 best-parts dataset of high-quality protein residues

We have curated a high-quality, “best parts” reference dataset of about 3 million protein residues in about 15,000 PDB-format coordinate files, each containing only residues with good electron density support for a physically acceptable model conformation. The resulting pre-filtered data typically contains the entire core of each chain, in quite long continuous fragments. Each reference file is a single protein chain, and the total set of files were selected for low redundancy, high resolution, good MolProbity score, and other chain-level criteria. Then each residue was critically tested for adequate local map quality to firmly support its conformation, which must also be free of serious clashes or covalent-geometry outliers. The resulting Top2018 pre-filtered datasets have been released on the Zenodo online web service and is freely available for all uses under a Creative Commons license. Currently, one dataset is residue-filtered on mainchain plus Cβ atoms, and a second dataset is full-residue filtered; each is available at 4 different sequence-identity levels. Here, we illustrate both statistics and examples that show the beneficial consequences of residue-level filtering. That process is necessary because even the best of structures contain a few highly disordered local regions with poor density and low-confidence conformations that should not be included in reference data. Therefore the open distribution of these very large, pre-filtered reference datasets constitutes a notable advance for structural bioinformatics and the fields that depend upon it.The Top2018 dataset provides the first representative sample of 3D protein structure for which excellence of experimental data constrains the detailed local conformation to be correct for essentially all 3 million residues included. Earlier generations of residue-filtered datasets were central in developing MolProbity validation used worldwide, and now Zenodo has enabled anyone to use out latest version as a sound basis for structural bioinformatics, protein design, prediction, improving biomedically important structures, or other applications.

Structural and functional effects of single nucleotide polymorphism on canine cytochrome b 5 reductase - in silico

The objectives of this study were to investigate the effects of single nucleotide polymorphism in Canine cytochrome b5 reductase using computational methods. Data was obtained from database of National Centre for Biotechnology Information (db SNP) and computational software was used for the analysis. The 3D protein structure was predicted using phyre 2 server. PANTHER analysis predicted the effect of single nucleotide polymorphism (substitution of Isoleucine for Leucine at position 194) as damaging. Analysis using the Mutpred 2 web application also indicated deleterious effects of the amino acid substitution. Molecular mechanisms of structural changes in the amino acid were determined using Mutpred 2 to be altered ordered interface, gain of allosteric sites and altered metal binding. The study indicated that the substitution of Isoleucine by Leucine at position 194 of the amino acid sequence (Ile 194 Leu) resulted in the destabilization of the amino acid structure leading to functional deviation in canine cytochrome b5 reductase.

Best templates outperform homology models in predicting the impact of mutations on protein stability

Motivation: Prediction of protein stability change upon mutation (∆∆G) is crucial for facilitating protein engineering and understanding of protein folding principles. Robust prediction of protein folding free energy change requires the knowledge of protein three-dimensional (3D) structure. Unfortunately, protein 3D structure is not always available. In this case, one can still predict the protein stability change by constructing a homology model of the protein; however, the accuracy of homology model-based ∆∆G predictions is unknown. The perspectives of using 3D structures of the best templates are also unclear. Results: To investigate these questions, we used the most popular and accurate publicly available tools: FoldX for stability change prediction and I-Tasser for homology modeling. We found that both homology models and best templates worsen the ∆∆G prediction, with best templates performing 1.5 times better than homology models. For AlphaFold models, we also found that the best templates seem to outperform protein models. Our findings imply using the 3D structures of the best templates for ∆∆G prediction if the 3D protein structure is unavailable.