Full-length Protein Sequences Research Articles

LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language model.

Recent advancements in natural language processing have highlighted the effectiveness of global contextualized representations from protein language models (pLMs) in numerous downstream tasks. Nonetheless, strategies to encode the site-of-interest leveraging pLMs for per-residue prediction tasks, such as crotonylation (Kcr) prediction, remain largely uncharted. Herein, we adopt a range of approaches for utilizing pLMs by experimenting with different input sequence types (full-length protein sequence versus window sequence), assessing the implications of utilizing per-residue embedding of the site-of-interest as well as embeddings of window residues centered around it. Building upon these insights, we developed a novel residual ConvBiLSTM network designed to process window-level embeddings of the site-of-interest generated by the ProtT5-XL-UniRef50 pLM using full-length sequences as input. This model, termed T5ResConvBiLSTM, surpasses existing state-of-the-art Kcr predictors in performance across three diverse datasets. To validate our approach of utilizing full sequence-based window-level embeddings, we also delved into the interpretability of ProtT5-derived embedding tensors in two ways: firstly, by scrutinizing the attention weights obtained from the transformer's encoder block; and secondly, by computing SHAP values for these tensors, providing a model-agnostic interpretation of the prediction results. Additionally, we enhance the latent representation of ProtT5 by incorporating two additional local representations, one derived from amino acid properties and the other from supervised embedding layer, through an intermediate fusion stacked generalization approach, using an n-mer window sequence (or, peptide/fragment). The resultant stacked model, dubbed LMCrot, exhibits a more pronounced improvement in predictive performance across the tested datasets. LMCrot is publicly available at https://github.com/KCLabMTU/LMCrot.

Identification and characterization of genes encoding phosphoinositide-specific phospholipase C revealed role in drought stress condition in cassava (Manihot esculenta)

Phosphoinositide-specific phospholipase C (PI-PLC) has been known as one of the key enzymes that involved in the phospholipid hydrolysis. However, the PI-PLC family in cassava has not been fully recorded. In this study, we reported a comprehensive analysis of the PI-PLC family in cassava assembly based on various bioinformatics tools. Particularly, a total of seven members of the PI-PLC family has been identified and annotated in the cassava genome. By using the full-length protein sequence of each member of the PI-PLC family in cassava, we analyzed the properties of these proteins, including the length, size, iso-electric point, instability index, aliphatic index and grand average of hydropathy. Of our interest, we investigated the expression patterns of genes encoding the PI-PLC family in various major organs/tissues in different conditions. Taken together, our study could provide a solid foundation for the PI-PLC family in cassava for further functional characterization towards the improvements of drought stress tolerance in cassava plants.

Production of monoclonal antibody of heat-labile toxin A subunit to identify enterotoxigenic Escherichia coli by epitope mapping using synthetic peptides.

Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea through two enterotoxins, a heat-labile toxin and a heat-stable toxin. These toxins alter the cellular signaling pathways, ultimately triggering an increase in chloride secretion and watery diarrhea. For the development of an ETEC vaccine, we attempted to construct a peptide-specific monoclonal antibody library against heat-labile enterotoxin A subunit (LT-A) by epitope mapping using synthetic peptides. Sera produced by five mice immunized with recombinant LT-A protein were examined for specific recognition with synthetic 15-mer and 34-mer peptides of LT-A proteins using enzyme-linked immunosorbent assay. The analysis revealed that the synthetic peptides number 8, 16, 24, 33, 36, 38, and 39 reacted with an anti-LT-A polyclonal antibody. For the possible prediction of LT-A epitopes, each full-length protein sequence was subjected to BCPreds analysis and three-dimensional protein structure analysis. The data showed that three peptides (synthetic peptide numbers: 33, 36, and 38-39) have identical antigenic specificities with LT-A protein, suggesting the usefulness of these linear peptide epitopes. Based on these peptides, we produced monoclonal antibodies to improve the specificity of LT-A detection. Monoclonal antibodies produced from two peptides (numbers 33 and 36) showed affinity for an LT-A recombinant antigen. Moreover, peptide epitope prediction analysis showed that the sites of the three peptides were identical to those exhibiting actual antigenicity. Also, it was confirmed that the amino acid sequence that actually showed antigenicity was included in the peptide predicted only by ETEC-LT-A-33. Also, the specificity of the antibody for ETEC-LT-A-33 was validated using bacterial cells, and the neutralizing effect of the antibody was determined by assessing cytokine release in infected HCT-8 cells. The monoclonal antibodies produced in this study are useful toolsfor vaccine production against ETEC and can be used to identify peptide antigencandidates.

InParanoiDB 9: Ortholog Groups for Protein Domains and Full-Length Proteins

Prediction of orthologs is an important bioinformatics pursuit that is frequently used for inferring protein function and evolutionary analyses. The InParanoid database is a well known resource of ortholog predictions between a wide variety of organisms. Although orthologs have historically been inferred at the level of full-length protein sequences, many proteins consist of several independent protein domains that may be orthologous to domains in other proteins in a way that differs from the full-length protein case. To be able to capture all types of orthologous relations, conventional full-length protein orthologs can be complemented with orthologs inferred at the domain level. We here present InParanoiDB 9, covering 640 species and providing orthologs for both protein domains and full-length proteins. InParanoiDB 9 was built using the faster InParanoid-DIAMOND algorithm for orthology analysis, as well as Domainoid and Pfam to infer orthologous domains. InParanoiDB 9 is based on proteomes from 447 eukaryotes, 158 bacteria and 35 archaea, and includes over one billion predicted ortholog groups. A new website has been built for the database, providing multiple search options as well as visualization of groups of orthologs and orthologous domains. This release constitutes a major upgrade of the InParanoid database in terms of the number of species as well as the new capability to operate on the domain level. InParanoiDB 9 is available at https://inparanoidb.sbc.su.se/.

Alignment-free estimation of sequence conservation for identifying functional sites using protein sequence embeddings.

Protein language modeling is a fast-emerging deep learning method in bioinformatics with diverse applications such as structure prediction and protein design. However, application toward estimating sequence conservation for functional site prediction has not been systematically explored. Here, we present a method for the alignment-free estimation of sequence conservation using sequence embeddings generated from protein language models. Comprehensive benchmarks across publicly available protein language models reveal that ESM2 models provide the best performance to computational cost ratio for conservation estimation. Applying our method to full-length protein sequences, we demonstrate that embedding-based methods are not sensitive to the order of conserved elements-conservation scores can be calculated for multidomain proteins in a single run, without the need to separate individual domains. Our method can also identify conserved functional sites within fast-evolving sequence regions (such as domain inserts), which we demonstrate through the identification of conserved phosphorylation motifs in variable insert segments in protein kinases. Overall, embedding-based conservation analysis is a broadly applicable method for identifying potential functional sites in any full-length protein sequence and estimating conservation in an alignment-free manner. To run this on your protein sequence of interest, try our scripts at https://github.com/esbgkannan/kibby.

Spike protein of SARS-CoV-2 Omicron variant: An in-silico study evaluating spike interactions and immune evasion.

The fundamentals of the infectivity and immune evasion of the SARS-CoV-2 Omicron variant are not yet fully understood. Here, we carried out an in-silico study analyzing the spike protein, the protein electrostatic potential, and the potential immune evasion. The analysis was based on the structure of the spike protein from two SARS-CoV-2 variants, the original Wuhan and the Botswana (Omicron). The full-length genome sequences and protein sequences were obtained from databanks. The interaction of the spike proteins with the human Angiotensin Converting Enzyme 2 (ACE2) receptor was evaluated through the open-source software. The Immune Epitope Database was used to analyze the potential immune evasion of the viruses. Our data show that the Omicron spike protein resulted in 37 amino acid changes. The physicochemical properties of the spike had changed, and the electrostatic potentials differed between both variants. This resulted in a decrease in protein interactions, which does not establish a greater interaction with the ACE2 receptor. These changes compromise key receptor-binding motif residues in the SARS-CoV-2 spike protein that interact with neutralizing antibodies and ACE2. These mutations appear to confer enhanced properties of infectivity. The Omicron variant appears to be more effective at evading immune responses.

Multimodal regulation of the osteoclastogenesis process by secreted group IIA phospholipase A2.

Increasing evidence points to the involvement of group IIA secreted phospholipase A2 (sPLA2-IIA) in pathologies characterized by abnormal osteoclast bone-resorption activity. Here, the role of this moonlighting protein has been deepened in the osteoclastogenesis process driven by the RANKL cytokine in RAW264.7 macrophages and bone-marrow derived precursor cells from BALB/cJ mice. Inhibitors with distinct selectivity toward sPLA2-IIA activities and recombinant sPLA2-IIA (wild-type or catalytically inactive forms, full-length or partial protein sequences) were instrumental to dissect out sPLA2-IIA function, in conjunction with reduction of sPLA2-IIA expression using small-interfering-RNAs and precursor cells from Pla2g2a knock-out mice. The reported data indicate sPLA2-IIA participation in murine osteoclast maturation, control of syncytium formation and resorbing activity, by mechanisms that may be both catalytically dependent and independent. Of note, these studies provide a more complete understanding of the still enigmatic osteoclast multinucleation process, a crucial step for bone-resorbing activity, uncovering the role of sPLA2-IIA interaction with a still unidentified receptor to regulate osteoclast fusion through p38 SAPK activation. This could pave the way for the design of specific inhibitors of sPLA2-IIA binding to interacting partners implicated in osteoclast syncytium formation.

Resolving the zinc binding capacity of honey bee vitellogenin and locating its putative binding sites.

The protein vitellogenin (Vg) plays a central role in lipid transportation in most egg-laying animals. High Vg levels correlate with stress resistance and lifespan potential in honey bees (Apis mellifera). Vg is the primary circulating zinc-carrying protein in honey bees. Zinc is an essential metal ion in numerous biological processes, including the function and structure of many proteins. Measurements of Zn2+ suggest a variable number of ions per Vg molecule in different animal species, but the molecular implications of zinc-binding by this protein are not well-understood. We used inductively coupled plasma mass spectrometry to determine that, on average, each honey bee Vg molecule binds 3 Zn2+ -ions. Our full-length protein structure and sequence analysis revealed seven potential zinc-binding sites. These are located in the β-barrel and α-helical subdomains of the N-terminal domain, the lipid binding site, and the cysteine-rich C-terminal region of unknown function. Interestingly, two potential zinc-binding sites in the β-barrel can support a proposed role for this structure in DNA-binding. Overall, our findings suggest that honey bee Vg bind zinc at several functional regions, indicating that Zn2+ -ions are important for many of the activities of this protein. In addition to being potentially relevant for other egg-laying species, these insights provide a platform for studies of metal ions in bee health, which is of global interest due to recent declines in pollinator numbers.

SWEET Gene Family in Sugar Beet (Beta vulgaris): Genome-Wide Survey, Phylogeny and Expression Analysis.

<b>Background and Objective:</b> The SWEET (Sugars Will Eventually be Exported Transporter) proteins play important roles in modulating the growth and development processes in plants. However, little information is available on the SWEET family in sugar beet (<i>Beta vulgaris</i>). The objectives of this present study were to genome-wide identify and characterize the BvSWEET family in sugar beet. <b>Materials and Methods:</b> Based on the available genome, proteome and transcriptome databases of sugar beet, various computational tools have been used to analyze the nucleotide and full-length protein sequences of members of the BvSWEET family. <b>Results:</b> A total of 16 members of the BvSWEET family has been identified in sugar beet at the genome-wide scale. Structural analysis indicated that the BvSWEET family exhibited variable characteristics. Furthermore, the BvSWEET family in sugar beet could be categorized into four distinct groups like in other plant species. Of our interest, we found that some <i>BvSWEET</i> genes exhibited strongly preferential expression in major organs/tissues under adverse environmental stimuli. <b>Conclusion:</b> The results provided a comprehensive foundation for further functional characterization of the <i>BvSWEET </i>gene family.

Highly Robust de Novo Full-Length Protein Sequencing.

Accurate full-length sequencing of a purified unknown protein is still challenging nowadays due to the error-prone mass-spectrometry (MS)-based methods. De novo identified peptide sequence largely contain errors, undermining the accuracy of assembly. Bias on the detectability of the peptides also makes low-coverage regions, resulting in gaps. Although recent advances on multi-enzyme hydrolysis and algorithms showed complete assembly of full-length protein sequences in a few examples, the robustness in practical application is still to be improved. Here, inspired by genome assembly strategies, we demonstrate a contig-scaffolding strategy to assemble protein sequences with high robustness and accuracy. This strategy integrates multiple unspecific hydrolysis methods to minimize the bias in the hydrolysis process. After de novo identification of the peptides, our assembly algorithm, named Multiple Contigs & Scaffolding (MuCS), assembles the peptide sequences in a multistep, i.e., contig-scaffold manner, with error correction in each step. MS data from different hydrolysis experiments complement each other for robust contig extension and error correction. We demonstrated that our strategy on three proteins and three replications all reached 100% coverage (except one with 98.85%) and 98.69-100% accuracy. It can also efficiently deal with the membrane protein, although the transmembrane region was missing due to the limitation of the MS. The three replicates reached 88.85-92.57% coverage and 97.57-100% accuracy. In sum, we provided a practical, robust, and accurate solution for full-length protein sequencing. The MuCS software is available at http://chi-biotech.com/mucs/.

Prediction and Modeling of Protein-Protein Interactions Using "Spotted" Peptides with a Template-Based Approach.

Protein–peptide interactions (PpIs) are a subset of the overall protein–protein interaction (PPI) network in the living cell and are pivotal for the majority of cell processes and functions. High-throughput methods to detect PpIs and PPIs usually require time and costs that are not always affordable. Therefore, reliable in silico predictions represent a valid and effective alternative. In this work, a new algorithm is described, implemented in a freely available tool, i.e., “PepThreader”, to carry out PPIs and PpIs prediction and analysis. PepThreader threads multiple fragments derived from a full-length protein sequence (or from a peptide library) onto a second template peptide, in complex with a protein target, “spotting” the potential binding peptides and ranking them according to a sequence-based and structure-based threading score. The threading algorithm first makes use of a scoring function that is based on peptides sequence similarity. Then, a rerank of the initial hits is performed, according to structure-based scoring functions. PepThreader has been benchmarked on a dataset of 292 protein–peptide complexes that were collected from existing databases of experimentally determined protein–peptide interactions. An accuracy of 80%, when considering the top predicted 25 hits, was achieved, which performs in a comparable way with the other state-of-art tools in PPIs and PpIs modeling. Nonetheless, PepThreader is unique in that it is able at the same time to spot a binding peptide within a full-length sequence involved in PPI and model its structure within the receptor. Therefore, PepThreader adds to the already-available tools supporting the experimental PPIs and PpIs identification and characterization.

Phylogenetic and Evolutionary Analysis of the Late Embryogenesis Abundant (LEA) Gene Product in Poaceae

The late Embryogenesis Abundant (LEA) protein family obtains a group of stress-induced hyper-hydrophilic proteins that accumulate in response to cellular dehydration. They are generally unstructured polypeptides without a well-defined three-dimensional structure and have been identified in a wide range of organisms from bacteria to higher plants. Herein, we made a phylogenetic and evolutionary analysis for LEA proteins in Poaceae. The full-length LEA protein sequences were acquired by performing the sequence search of sequenced hva1 against Poaceae species in the non-redundant protein database by a BlastX search tool. The sequences were aligned with the Clustal Omega tool. The MEME suite searched for conserved blocks among each LEA protein sequence. Also, the evolutionary relationship among the LEA protein sequences evaluates using the MEGA tool. The results display close sequence similarity not only into the species but also between species. The results demonstrated that LEA proteins cluster into two large subgroups. The overall average evolutionary difference in LEA protein sequence pairs estimated as 0.4022 amino acid substitutions per site from averaging over all sequence pairs. The LEA protein sequences contain a significant percentage of glycine residues but lack cysteine and tryptophan residues. The results indicate the occurrence of homologs in the subgroup before the divergence of the species. However, the expansion of the gene number in the Poaceae was approved by the duplication events in the preexisting genes rather than by the appearance of the altered LEA gene. Our data will provide novel insights for further studies of the Late Embryogenesis Abundant protein family in Poaceae.

Different Folding States from the Same Protein Sequence Determine Reversible vs Irreversible Amyloid Fate.

The propensity to self-assemble into amyloid fibrils with a shared cross-β architecture is a generic feature of proteins. Amyloid-related diseases affect millions of people worldwide, yet they are incurable and cannot be effectively prevented, largely due to the irreversible assembly and extraordinary stability of amyloid fibrils. Recent studies suggest that labile amyloids may be possible in certain proteins containing low-complexity domains often involved in the formation of subcellular membraneless organelles. Although the fundamental understanding of this reversible amyloid folding process is completely missing, the current view is that a given protein sequence will result in either irreversible, as in most of the cases, or reversible amyloid fibrils, as in few exceptions. Here we show that two common globular proteins, human lysozyme and its homologue from hen egg white, can self-assemble into both reversible and irreversible amyloid fibrils depending on the folding path followed by the protein. In both folding states, the amyloid nature of the fibrils is demonstrated at the molecular level by its cross-β structure, yet with substantial differences on the mesoscopic polymorphism and the labile nature of the amyloid state. Structural analysis shows that reversible and irreversible amyloid fibrils possess the same full-length protein sequence but different fibril core structures and β-sheet arrangements. These results illuminate a mechanistic link between the reversible and irreversible nature of amyloids and highlight the central role of protein folding states in regulating the lability and reversibility of amyloids.

Transcriptome Analysis and Identification of Lipid Genes in Physaria lindheimeri, a Genetic Resource for Hydroxy Fatty Acids in Seed Oil.

Hydroxy fatty acids (HFAs) have numerous industrial applications but are absent in most vegetable oils. Physaria lindheimeri accumulating 85% HFA in its seed oil makes it a valuable resource for engineering oilseed crops for HFA production. To discover lipid genes involved in HFA synthesis in P. lindheimeri, transcripts from developing seeds at various stages, as well as leaf and flower buds, were sequenced. Ninety-seven percent clean reads from 552,614,582 raw reads were assembled to 129,633 contigs (or transcripts) which represented 85,948 unique genes. Gene Ontology analysis indicated that 60% of the contigs matched proteins involved in biological process, cellular component or molecular function, while the remaining matched unknown proteins. We identified 42 P. lindheimeri genes involved in fatty acid and seed oil biosynthesis, and 39 of them shared 78–100% nucleotide identity with Arabidopsis orthologs. We manually annotated 16 key genes and 14 of them contained full-length protein sequences, indicating high coverage of clean reads to the assembled contigs. A detailed profiling of the 16 genes revealed various spatial and temporal expression patterns. The further comparison of their protein sequences uncovered amino acids conserved among HFA-producing species, but these varied among non-HFA-producing species. Our findings provide essential information for basic and applied research on HFA biosynthesis.

Comparison of different variant sequence types coupled with decoy generation methods used in concatenated target-decoy database searches for proteogenomic research

Concatenated target-decoy database searches are commonly used in proteogenomic research for variant peptide identification. Currently, protein-based and peptide-based sequence databases are applied to store variant sequences for database searches. The protein-based database records a full-length wild-type protein sequence but using the given variant events to replace the original amino acids, whereas the peptide-based database retains only the in silico digested peptides containing the variants. However, the performance of applying various decoy generation methods on the peptide-based variant sequence database is still unclear, compared to the protein-based database. In this paper, we conduct a thorough comparison on target-decoy databases constructed by the above two types of databases coupled with various decoy generation methods for proteogenomic analyses. The results show that for the protein-based variant sequence database, using the reverse or the pseudo reverse method achieves similar performance for variant peptide identification. Furthermore, for the peptide-based database, the pseudo reverse method is more suitable than the widely used reverse method, as shown by identifying 6% more variant PSMs in a HEK293 cell line data set. SignificanceIn our survey of publications on proteogenomic studies, 57% of the studies adopt the peptide-based variant sequence database coupled with the reverse method for decoy generation to construct a target-decoy database for searches. However, our results show that when using the peptide-based variant sequence database, it is better to adopt the pseudo reverse method for generating decoy sequences, to avoid leading to fewer variant peptides being identified.

Revision of the barley WRKY gene family phylogeny and expression analysis of the candidate genes in response to drought

The WRKY belongs to an important plant specific transcription factor families which are involved in response to various environmental stresses, as well as in growth and developmental processes. In the present report, a genome-wide identification and characterization of WRKY gene family in barley led to revision of HvWRKYs to 93 members. The phylogenetic tree was also reconstructed based on the full-length WRKY protein sequences in barley and Arabidopsis. HvWRKYs were classified into three major groups (I, II, and III) and group II was further divided to 5 subgroups (a to e). HvWRKYs were named after this classification. Interestingly, some specific motifs were discovered in subgroups IIa, IIb, and III. Analyzing the available microarray data revealed eight candidate WRKY genes which were up-regulated under drought and salinity stresses compared to the optimum conditions at seedling stage in barley. Expression profiles of these WRKY genes were validated by quantitative real-time PCR. All the investigated candidate genes (HvWRKY_IIc2, HvWRKY_III11, HvWRKY_IIb2, HvWRKY_IId4, HvWRKY_III23, HvWRKY_IIa5 and HvWRKY_IIc19) except for HvWRKY_I8 were significantly up-regulated by drought stress at the seedling stage in drought-tolerant genotype, indicating their role in drought tolerance. We hope the presented information would be helpful toward achieving drought tolerant cultivars through genetic engineering or molecular breeding.

Domainoid: domain-oriented orthology inference

BackgroundOrthology inference is normally based on full-length protein sequences. However, most proteins contain independently folding and recurring regions, domains. The domain architecture of a protein is vital for its function, and recombination events mean individual domains can have different evolutionary histories. It has previously been shown that orthologous proteins may differ in domain architecture, creating challenges for orthology inference methods operating on full-length sequences. We have developed Domainoid, a new tool aiming to overcome these challenges faced by full-length orthology methods by inferring orthology on the domain level. It employs the InParanoid algorithm on single domains separately, to infer groups of orthologous domains.ResultsThis domain-oriented approach allows detection of discordant domain orthologs, cases where different domains on the same protein have different evolutionary histories. In addition to domain level analysis, protein level orthology based on the fraction of domains that are orthologous can be inferred. Domainoid orthology assignments were compared to those yielded by the conventional full-length approach InParanoid, and were validated in a standard benchmark.ConclusionsOur results show that domain-based orthology inference can reveal many orthologous relationships that are not found by full-length sequence approaches.Availabilityhttps://bitbucket.org/sonnhammergroup/domainoid/

In silico epitope prediction and immunogenic analysis for penton base epitope-focused vaccine against hydropericardium syndrome in chicken

Certain strains of fowl adenovirus serotype 4 (FAdV-4) of the family Adenoviridae are recognized to be the causative agents of Hydropericardium Syndrome (HPS) in broiler chicken. Despite the significantly spiking mortality in broilers due to HPS, not much effort has been made to design an effective vaccine against FAdV-4. The combination of immuno- and bioinformatics tools for immunogenic epitope prediction is the most recent concept of vaccine design. It reduces the time and effort required for hunting a potent vaccine candidate and is economical. Previously, we have reported the penton base protein of FAdV-4 to be a candidate for subunit vaccine against HPS. In the present study, we have computationally pre-screened promising B- and T-cell epitopes of the penton base. Multiple methods were employed for linear B-cell epitope identification; BepiPred and five other methods based on physicochemical properties of the amino acids. The penton base was homology modeled by means of Modeller 9.17 and after refinement of the model (by GalaxyRefine web server) ElliPro web tool was used to predict the discontinuous epitopes. NetMHCcons 1.1 and NetMHCIIpan 3.1 servers were used for the likelihood of peptide binding to Major Histocompatibility Complex (MHC) class I & II molecules respectively for T-cell epitope forecast. As a result, we identified the peptide stretch of 1–225 as the most promiscuous B- and T-cell epitope region in penton base Full Length (FL) protein sequence. Escherichia coli based expression vectors were generated containing cloned peptide stretch 1–225 (penton base1–225) and penton base FL gene sequence. The recombinant penton base1–225 and penton base FL proteins were expressed and purified using Escherichia coli-based expression system. Purification yield of penton base1–225 was 3-fold higher compared to penton base FL. These proteins were injected in chickens to determine their competence in protection against HPS. The results showed equal protection level of the two proteins and the commercial inactivated vaccine against FAdV-4 infection. The results suggest the peptide stretch 1–225 of penton base as a valuable candidate for developing an epitope-driven vaccine to combat HPS.

Genome-Wide Identification and Characterization of the UBP Gene Family in Moso Bamboo (Phyllostachys edulis).

The largest group of deubiquitinases—ubiquitin-specific proteases (UBPs)—perform extensive and significant roles in plants, including the regulation of development and stress responses. A comprehensive analysis of UBP genes has been performed in Arabidopsis thaliana, but no systematic study has been conducted in moso bamboo (Phyllostachys edulis). In this study, the genome-wide identification, classification, gene, protein, promoter region characterization, divergence time, and expression pattern analyses of the UBPs in moso bamboo were conducted. In total, 48 putative UBP genes were identified in moso bamboo, which were divided into 14 distinct subfamilies in accordance with a comparative phylogenetic analysis using 132 full-length protein sequences, including 48, 27, 25, and 32 sequences from moso bamboo, A. thaliana, rice (Oryza sativa), and purple false brome (Brachypodium distachyon), respectively. Analyses of the evolutionary patterns and divergence levels revealed that the PeUBP genes experienced a duplication event approximately 15 million years ago and that the divergence between PeUBP and OsUBP occurred approximately 27 million years ago. Additionally, several PeUBP members were significantly upregulated under abscisic acid, methyl jasmonate, and salicylic acid treatments, indicating their potential roles in abiotic stress responses in plants.

Biochemical characterization of recombinant Avihepatovirus 3C protease and its localization

BackgroundThe picornaviral 3C protease mediates viral polyprotein maturation and multiple cleavages of host proteins to modulate viral translation and transcription. The 3C protease has been regarded as a valid target due to its structural similarity among different picornaviruses and minimal sequence similarity with host proteins; therefore, the development of potent inhibitors against the 3C protease as an antiviral drug is ongoing. Duck hepatitis A virus (DHAV) belongs to the Picornavidea family and is a major threat to the poultry industry. To date, little is known about the roles of the DHAV 3C protease plays during infection.MethodsIn this study, we compared the full-length DHAV 3C protein sequence with other 3C sequences to obtain an alignment for the construction of a phylogenetic tree. Then, we expressed and purified recombinant DHAV 3C protease in the BL21 expression system using nickel-NTA affinity chromatography. The optimization of the cleavage assay conditions and the kinetic analysis for DHAV 3C protease were done by in vitro cleavage assays with a fluorogenic peptide respectively. The inhibitory activity of rupintrivir against the DHAV 3C protease was further evaluated. The localization of the 3C protease in infected and transfected cells was determined using immunofluorescence and confocal microscopy.ResultsUnder different expression conditions, the 3C protease was found to be highly expressed after induction with 1 mM IPTG at 16 °C for 10 h. We synthesized a fluorogenic peptide derived from the cleavage site of the DHAV polyprotein and evaluated the protease activity of the DHAV 3C protease for the first time. We used fluorimetric based kinetic analysis to determine kinetic parameters, and Vmax and Km values were determined to be 16.52 nmol/min and 50.78 μM, respectively. Rupintrivir was found to exhibit inhibitory activity against the DHAV 3C protease. Using polyclonal antibody and an indirect immunofluorescence microscopy assay (IFA), it was determined that the DHAV 3C protease was found in the nucleus during infection. In addition, the DHAV 3C protease can enter into the nucleus without the cooperation of viral proteins.ConclusionsThis is the first study to examine the activity of the DHAV 3C protease, and the activity of the DHAV 3C protease is temperature-, pH- and NaCl concentration- dependent. The DHAV 3C protease localizes throughout DHAV-infected cells and can enter into the nucleus in the absence of other viral proteins. The kinetic analysis was calculated, and the Vmax and Km values were 16.52 nmol/min and 50.78 μM, respectively, using the Lineweaver–Burk plot.