Sequence Alignment Research Articles

Molecular Identification and Genetic Diversity Analysis of Papaya Leaf Curl China Virus Infecting Ageratum conyzoides.

Papaya leaf curl China virus (PaLCuCNV) is a damaging plant pathogen causing substantial losses to crop. The complete genomes of three PaLCuCNV isolates from Ageratum conyzoides were obtained and combined with the 68 reference isolates in GenBank for comprehensive genetic diversity analyses using specialized computational tools. Sequence alignment revealed nucleotide sequence similarity ranging from 85.3% to 99.9% among 71 PaLCuCNV isolates. Employing phylogenetic analysis, 71 PaLCuCNV sequences were clustered into five groups, with no significant correlation observed between genetic differentiation and either host species or geographical origin. Additionally, 13 recombination events across all PaLCuCNV isolates were identified. Genetic diversity analysis indicated the ongoing expansion and evolution of PaLCuCNV populations, supported by a neutral model. Moreover, significant genetic differentiation was observed among distinct viral populations, primarily attributed to genetic drift. Overall, our findings provide valuable insights into the detection, genetic variation, and evolutionary dynamics of PaLCuCNV.

Molecular depiction and functional delineation of E3 ubiquitin ligase MARCH5 in yellowtail clownfish (Amphiprion clarkii).

Membrane-associated Ring-CH 5 (MARCH5) is a mitochondrial E3 ubiquitin ligase playing a key role in the regulation of mitochondrial dynamics. In mammals, MARCH5 negatively regulates mitochondrial antiviral signaling (MAVS) protein aggregation during viral infection and hampers downstream type I interferon signaling to prevent excessive immune activation. However, its precise functional role in the teleost immune system remains unclear. This study investigated the molecular characteristics and immune response of the MARCH5 ortholog in Amphiprion clarkii (A. clarkii; AcMARCH5). The predicted AcMARCH5 protein sequence consists of 287 amino acids with a molecular weight of 32.02 kDa and a theoretical isoelectric point of 9.11. It contains four C-terminal transmembrane (TM) domains and an N-terminal RING cysteine-histidine (CH) domain, which directly regulates ubiquitin transfer. Multiple sequence alignment revealed a high level of conservation between AcMARCH5 and its orthologs in other vertebrate species. Under normal physiological conditions, AcMARCH5 showed the highest mRNA expression in the muscle, brain, and kidney tissues of A. clarkii. Upon stimulation with polyinosinic:polycytidylic acid (Poly I:C), lipopolysaccharide (LPS), and Vibrio harveyi, AcMARCH5 expression was drastically modulated. Functional assays showed that overexpression of AcMARCH5 in fathead minnow (FHM) cells downregulated antiviral gene expression, accompanied by enhanced viral hemorrhagic septicemia virus (VHSV) replication. In murine macrophages, AcMARCH5 overexpression markedly reduced the production of pro-inflammatory cytokines in response to poly I:C treatment. Additionally, AcMARCH5 exhibited an anti-apoptotic effect in H2O2-treated FHM cells. Collectively, these results suggest that AcMARCH5 may play a role in maintaining cellular homeostasis under disease and stress conditions in A. clarkii.

Sequence analysis of the GP5 protein of porcine reproductive and respiratory syndrome virus in Vietnam from 2007 to 2023.

Porcine reproductive and respiratory syndrome virus (PRRSV) is the causative agent 13 of porcine reproductive and respiratory syndrome (PRRS), which is one of the most economically 14 devastating viruses in the Vietnamese swine industry. With a view toward determining the 15 genetic variation among PRRSV strains in Vietnam, we examined 271 PRRSV GP5 protein 16 sequences obtained from strains isolated in Vietnam from 2007 to 2023, for which we constructed 17 phylogenetic trees. Additionally, a collection of 52 PRRSV-1 strains and 80 PRRSV-2 strains 18 isolated in different years were specifically selected for nucleotide and amino acid homology analysis 19 and amino acid sequence alignment. The results revealed 76.1%-100.0% nucleotide and 20 75.2%-100.0% amino acid homologies for the PRRSV-1 GP5 gene, and 81.8%-100.0% nucleotide 21 and 81.1%-100.0% amino acid homologies for the PRRSV-2 GP5 gene. Amino acid mutation sites 22 in PRRSV-2 were found to be primarily distributed in the signal peptide region, antigenic sites, two 23 T-cell antigen regions, two highly variable regions (HVRs), and in the vicinity of the neutralizing 24 epitope, with a deletion mutation occurring in the neutralizing epitope, whereas amino acid mutations 25 in the PRRSV-1 sequences were found to occur predominantly in two T-cell epitopes. Genetic 26 analysis revealed that PRRSV-1 strains in Vietnam are of subtype 1 (Global), whereas PRRSV-2 27 strains are categorized into sublineages L1A, L5A, and L8E, with L8E being the predominantly 28 prevalent strain at present. Recombination analyses indicated that no significant recombination 29 events have occurred in any of the assessed 271 Vietnamese PRRSV strains. Our 30 analyses of 271 Vietnamese PRRSV strains have yielded valuable insights regarding the 31 epidemiological trends and genetic dynamics of PRRSV in Vietnam, and will provide a theoretical 32 basis for formulating prevention and control measures for PRRS and the development of PRRS 33 vaccines.

Characterization of the Three DHFRs and K65P Variant: Enhanced Substrate Affinity and Molecular Dynamics Analysis.

Dihydrofolate reductase (DHFR) is ubiquitously present in all living organisms and plays a crucial role in the growth of the fungal pathogen R.solani. Sequence alignment confirmed the evolutionary conservation of the essential lid domain, with the amino acid 'P' within the PEKN lid domain appearing with a frequency of 89.5% in higher organisms and 11.8% in lower organisms. Consequently, a K65P variant was introduced into R.solani DHFR (rDHFR). Subsequent enzymatic kinetics assays were conducted for human DHFR (hDHFR), rDHFR, E. coli DHFR (eDHFR), and the K65P variant. hDHFR exhibited the highest kcat of 0.95s-1, followed by rDHFR with 0.14s-1, while eDHFR displayed the lowest kcat of 0.09s-1. Remarkably, the K65P variant induced a significant reduction in Km, resulting in a 1.8-fold enhancement in catalytic efficiency (kcat/Km) relative to the wild type. Differential scanning fluorimetry and binding free energy calculations confirmed the enhanced substrate affinity for both folate and NADPH in the K65P variant. These results suggest that the K65P mutation enhances substrate affinity and catalytic efficiency in DHFR, highlighting the evolutionary and functional importance of the K65 residue.

Performance of somatic structural variant calling in lung cancer using Oxford Nanopore sequencing technology

BackgroundLung cancer is a heterogeneous disease and the primary cause of cancer-related mortality worldwide. Somatic mutations, including large structural variants, are important biomarkers in lung cancer for selecting targeted therapy. Genomic studies in lung cancer have been conducted using short-read sequencing. Emerging long-read sequencing technologies are a promising alternative to study somatic structural variants, however there is no current consensus on how to process data and call somatic events. In this study, we preformed whole genome sequencing of lung cancer and matched non-tumour samples using long and short read sequencing to comprehensively benchmark three sequence aligners and seven structural variant callers comprised of generic callers (SVIM, Sniffles2, DELLY in generic mode and cuteSV) and somatic callers (Severus, SAVANA, nanomonsv and DELLY in somatic modes).ResultsDifferent combinations of aligners and variant callers influenced somatic structural variant detection. The choice of caller had a significant influence on somatic structural variant detection in terms of variant type, size, sensitivity, and accuracy. The performance of each variant caller was assessed by comparing to somatic structural variants identified by short-read sequencing. When compared to somatic structural variants detected with short-read sequencing, more events were detected with long-read sequencing. The mean recall of somatic variant events identified by long-read sequencing was higher for the somatic callers (72%) than generic callers (53%). Among the somatic callers when using the minimap2 aligner, SAVANA and Severus achieved the highest recall at 79.5% and 79.25% respectively, followed by nanomonsv with a recall of 72.5%.ConclusionLong-read sequencing can identify somatic structural variants in clincal samples. The longer reads have the potential to improve our understanding of cancer development and inform personalized cancer treatment.

Bioinformatics Tools Assist in The Screening of Potential Porcine-Specific Peptide Biomarkers of Gelatin and Collagen For Halal Authentication

Gelatin and collagen are two animal-derived ingredients that are widely used in various industries. Both have distinctive physico-chemical characteristic that made them ingredients of interest for many industrial players to be applied as there are vast arrays of usage in the food, cosmetic and biomedical fields. However, the origin of gelatin and collagen poses ethical and religious concerns, especially for Muslims and Jews who have restrictions on food consumption. Porcine by-products are of concern for religious and health reasons, and there is a demand for precise and reliable detection techniques. The limitation of DNA detection is due to extreme environment in food processing which results in low extractability of DNA. Therefore, peptide-based detection using mass spectrometry is required. However, identify the suitable marker is like searching needle in haystacks. Hence, combination of bioinformatics and mass spectrometry is proposed. This study aims to identify the specific peptide biomarkers by employing bioinformatics technique which can be applied to identify gelatin and collagen sources with the aid of mass spectrometry. In these approach, combination of Petunia Trans-Proteomic Pipeline (TPP, version 5.2.0) and sequence alignment ClustalW were applied to facilitate the MS data (LC-QTOF-MS) and peptide identification. As a result, 69 fasta file of protein sequence from both UniProtKB and NCBInr have been collected, 81 collagen peptides sequence and 118 gelatine peptides has been attainable that have the potential to distinguish different species. In conclusion, in silico protein sequence approaches helps to enable rapid screening of proteotypic peptides that can serve as species biomarkers proficiently.

Computational Analysis and Inhibition Study of Carbonic Anhydrase from Azadirachta indica Leaves

Introduction: Carbonic anhydrase (CA) has been an enzyme of great interest for its application in carbon dioxide sequestration. A total of 66 protein sequences of plant CAs were computationally analyzed and submitted to bioinformatics for motif and domain identification, multiple sequence alignment, and phylogenetic analysis. Method: The current work aims to extend knowledge among researchers in better understanding the structure of AZDI CA by analyzing its physicochemical properties, secondary structure prediction, 3D modeling of protein sequence, and its validation using a variety of conventional computational methods. Results: The accuracy of the predicted 3D structure checked by the Ramachandran plot generated by PROCHECK showed that for the CA protein sequence 93.1%, was observed in the most favored regions, VERIFY 3D 69.44% and ERRAT 98.09%. AZDI CA was docked with various anions and sulphonamide derivatives to study their inhibitory effect and calculate binding energy by using Autodock 4.2. Ethoxzolamide is found to be a better inhibitor of AZDI CA with binding energy -8.71 kCal/mol and KI value 0.0004 mM. Further MD simulation of the docked complex of ethoxzolamide with AZDI CA was done using SCHRODINGER DESMOND software. Conclusion: The outcomes of this research will have a significant influence on biochemistry, biotechnology, and potential applications of AZDI CA and similar plant CAs in determining potent inhibitors for drug targets in treating various diseases.

Outbreak of SARS-CoV-2 variants in Iraqi Kurdistan region

Introduction: Coronavirus disease 2019 (COVID-19) first appeared in Iraq, including the Iraqi Kurdistan region governorates, in March 2020. Methodology: 48,494 samples were collected from public hospitals in the Kurdish governates from February 2021 to May 2022. Viral RNA was extracted, and real time quantitative polymerase chain reaction (RT-PCR) was used to detect the COVID-19 variants. Statistical analysis of patients’ clinical data was performed. Results: The RT-PCR results identified the Alpha (B.1.1.7), Delta (B.1.617.2), and Omicron (B.1.1.529) variants in the Kurdistan governorates. Young adults (20-39 years) had significantly higher rate of infection than children (1-11 months) and older adults (80-89 years). The Delta wave was more contiguous, spread more easily, and more fatal than the Alpha and Omicron waves. The highest number of COVID-19 cases was reported in Sulaymaniyah and Duhok; and the highest death rate was reported in Sulaymaniyah. The death rate in males was higher than in females, especially among older people. Fatigue, cough, and fever were common symptoms among the three variants. The phylogenetic tree revealed that the L-type of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was a descendant of the S-type at an early stage of evolution. The L-type could spread faster in Kurdistan. Multiple sequence alignment (MSA) confirmed that all L-type variants in different countries were 100% similar in sequence, and all were mutated in the regions 8782: ORF1ab and 28144: ORF8 703. Conclusions: This study described the COVID-19 waves, pathogenesis, and evolution of the virus in the Iraqi Kurdistan region.

Epidemiology, genetic characterization and population structure analysis of lumpy skin disease virus from North India.

Lumpy skin disease (LSD) is a transboundary, viral disease of cattle with a significant economic impact on the livestock industry. This study describes the epidemiological investigations of outbreaks of LSD that occurred in 2022 in three Indian states viz., Haryana, Himachal Pradesh and Rajasthan and the genetic characterization of Lumpy skin disease viruses (LSDVs). Also, the population structure analysis of LSDVs was carried out. Out of 138 scab samples tested from suspected cattle for LSDV, 106 were found positive. Of these, nine representative scab samples were further genetically characterized. Phylogenetic analysis based on the P32 and EEV gene sequences depicted that the LSDV strains of the present study had nucleotide identity of 100% and 99.10-99.45%, respectively with the LSDV/2019 field strains of India. Multiple sequence alignment of the EEV glycoprotein gene sequences revealed nucleotide polymorphisms at three positions viz., G178A, G253A and A459G in circulating LSDV/2022 field strains. Based on the median joining network analysis of the EEV gene, 12 haplotypes were identified among the LSDV populations. Population structure analysis corresponding to the EEV gene revealed high haplotype (0.8486 ± 0.026) and low nucleotide diversities (0.00636 ± 0.0006) and negative values for neutrality indices, indicating a high number of closely related haplotypes and the studied population may have undergone a recent expansion. The findings will help in understanding the distribution and dynamics of LSDV populations, which will prove pivotal in designing and implementing effective management and control strategies.

Wfold: A new method for predicting RNA secondary structure with deep learning

Precise estimations of RNA secondary structures have the potential to reveal the various roles that non-coding RNAs play in regulating cellular activity. However, the mainstay of traditional RNA secondary structure prediction methods relies on thermos-dynamic models via free energy minimization, a laborious process that requires a lot of prior knowledge. Here, RNA secondary structure prediction using Wfold, an end-to-end deep learning-based approach, is suggested. Wfold is trained directly on annotated data and base-pairing criteria. It makes use of an image-like representation of RNA sequences, which an enhanced U-net incorporated with a transformer encoder can process effectively. Wfold eventually increases the accuracy of RNA secondary structure prediction by combining the benefits of self-attention mechanism's mining of long-range information with U-net's ability to gather local information. We compare Wfold's performance using RNA datasets that are within and across families. When trained and evaluated on different RNA families, it achieves a similar performance as the traditional methods, but dramatically outperforms the state-of-the-art methods on within-family datasets. Moreover, Wfold can also reliably forecast pseudoknots. The findings imply that Wfold may be useful for improving sequence alignment, functional annotations, and RNA structure modeling.

The impact of host microRNAs on the development of conserved mutations of SARS-CoV-2.

SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has undergone various genetic alterations due to evolutionary pressures exerted by host cells, including intracellular antiviral mechanisms such as targeting by human microRNAs (miRNAs). This study investigates the impact of miRNAs hsa-miR-3132 and hsa-miR-4650 on the viral genome. Sequence alignment revealed conserved mutations in the binding sites of these miRNAs in adapted strains compared to the original Wuhan-Hu-1 strain, leading to their deletion. Despite modest expression of these miRNAs in SARS-CoV-2 target tissues, their efficacy against mutant strains is reduced due to the loss of binding sites. Structural analysis indicates that the mutant genome is more stable than the Wuhan-Hu-1 genome. Luciferase and virus titration assays demonstrate that hsa-miR-3132 and hsa-miR-4650 effectively target the Nsp3 gene in the Wuhan-Hu-1 strain but not in mutant strains lacking their binding sites. These findings suggest that the observed mutations help the virus evade selective pressure from human miRNAs, contributing to its adaptation.

Integration Linkage Mapping and Comparative Transcriptome Analysis to Dissect the Genetic Basis of Rice Salt Tolerance Associated with the Germination Stage.

Soil salinity poses a serious threat to rice production. The salt tolerance of rice at the germination stage is one of the major determinants of stable stand establishment, which is very important for direct seeding in saline soil. The complexity and polygenic nature of salt tolerance have limited the efficiency of discovering and cloning key genes in rice. In this study, an RIL population with an ultra-high-density genetic map was employed to investigate the salt-tolerant genetic basis in rice, and a total of 20 QTLs were detected, including a major and stable QTL (qRCL3-1). Subsequently, salt-specific DEGs from a comparative transcriptome analysis were overlaid onto annotated genes located on a stable QTL interval, and eight putative candidate genes were further identified. Finally, from the sequence alignment and variant analysis, OsCam1-1 was confirmed to be the most promising candidate gene for regulating salinity tolerance in rice. This study provides important information for elucidating the genetic and molecular basis of rice salt tolerance at the germination stage, and the genes detected here will be useful for improvements in rice salt tolerance.

Characterisation of seryl tRNA synthetase (srs-2) in Haemonchus contortus and Teladorsagia circumcincta

The aim of the study was to purify and characterise recombinant proteins with the potential as an anti-parasite vaccine. Full-length cDNAs encoding seryl-tRNA synthetase (srs-2) were cloned from Haemonchus contortus (HcSRS-2) and Teladorsagia circumcincta (TcSRS-2). TcSRS-2 and HcSRS-2 cDNA (1458bp) encoded proteins of 486 amino acids, each of which was present as a single band of about 55 kDa on SDS-PAGE. Multiple alignments of the protein sequences showed homology of 94% between TcSRS-2 and HcSRS-2, 76–93% with SRS-2s of eight nematodes and 68% with Mus musculus SRS-2. The predicted three-dimensional structures revealed an overall structural homology of TcSRS-2 and HcSRS-2, highly conserved binding and catalytic sites, and minor differences in the tautomerase binding site residues in other nematode SRS-2 homologues. A phylogenetic tree was constructed using helminth and mammalian SRS-2 sequences. Soluble C-terminal SRS-2 proteins were expressed in Escherichia coli strain AY2.4 and purified. Recombinant HcSRS-2 assay shows that the recombinant enzyme was active and stable. The Km and Vmax for ATP were 3.9 ± 1.0 μM and 2.7 ± 0.1 μmol min−1 mg−1 protein, respectively. Antibodies in serum and saliva from field-immune, but not nematode-naïve, sheep recognised recombinant HcSRS-2 and TcSRS-2 in enzyme-linked immunosorbent assays. Recognition of the recombinant proteins by antibodies generated by exposure of sheep to the native enzyme indicates similar antigenicity of the two proteins.

Genome mining of Bacillus thuringiensis strain SY49.1 reveals novel candidate pesticidal and bioactive compounds.

Bacillus thuringiensis SY49.1 (Bt SY49.1) strain has promising insecticidal and fungicidal activity against phytopathogens and pests. Therefore, we selected this strain for whole-genome sequencing (WGS), annotation and analysis, with the aim of identifying genes responsible for producing putative pesticidal toxins, antimicrobial metabolites and plant growth-promoting features. Our results showed that the SY49.1 genome is 6. 32 Mbp long with a GC content of 34.68%. Genome mining revealed the presence of multiple gene inventories for the biosynthesis of bioactive compounds such as insecticidal delta endotoxins, secondary metabolites, and several plant growth-promoting proteins. Multiple sequence alignment revealed residue variations in the toxic core of Cry1Ab when compared with known Cry1Ab sequences from Bt nomenclature databases. This suggests that the cry1Ab of SY49.1 is a new kind of its group. Among the predicted secondary metabolites, we found a kurstakin with a predicted peptide that differs from the known kurstakin peptide available in the NORINE database. In addition, lipopeptides extracted from SY49.1 suppressed the growth of Verticillium dahliae and Fusarium oxysporum. We anticipate that the complete genome of Bt SY49.1 may provide a model for properly understanding and studying antimicrobial compound mining, genetic diversity among the B. cereus group, and pathogenicity against insects. This is the first report on the WGS and mining of the Bt strain isolated from Turkey. © 2024 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Diversity, Distribution and Structural Prediction of the Pathogenic Bacterial Effectors EspN and EspS.

Many Gram-negative enterobacteria translocate virulence proteins (effectors) into intestinal epithelial cells using a type III secretion system (T3SS) to subvert the activity of various cell functions possess. Many T3SS effectors have been extensively characterized, but there are still some effector proteins whose functional information is completely unknown. In this study, two predicted effectors of unknown function, EspN and EspS (Escherichia coli secreted protein N and S), were selected for analysis of translocation, distribution and structure prediction. The TEM1 (β-lactamase) translocation assay was performed, which showed that EspN and EspS are translocated into host cells in a T3SS-dependent manner during bacterial infection. A phylogenetic tree analysis revealed that homologs of EspN and EspS are widely distributed in pathogenic bacteria. Multiple sequence alignment revealed that EspN and its homologs share a conserved C-terminal region (673-1133 a.a.). Furthermore, the structure of EspN (673-1133 a.a.) was also predicted and well-defined, which showed that it has three subdomains connected by a loop region. EspS and its homologs share a sequence-conserved C-terminal (146-291 a.a.). The predicted structure of EspS (146-291 a.a.) is composed of a β-sheet consisting of four β-strands and several short helices, which has a TM score of 0.5014 with the structure of the Vibrio cholerae RTX cysteine protease domain (PDBID: 3eeb). These results suggest that EspN and EspS may represent two important classes of T3SS effectors associated with pathogen virulence, and our findings provide important clues to understanding the potential functions of EspN and EspS.

Rapid SARS-CoV-2 surveillance using clinical, pooled, or wastewater sequence as a sensor for population change.

The COVID-19 pandemic has highlighted the critical role of genomic surveillance for guiding policy and control. Timeliness is key, but sequence alignment and phylogeny slow most surveillance techniques. Millions of SARS-CoV-2 genomes have been assembled. Phylogenetic methods are ill equipped to handle this sheer scale. We introduce a pangenomic measure that examines the information diversity of a k-mer library drawn from a country's complete set of clinical, pooled, or wastewater sequence. Quantifying diversity is central to ecology. Hill numbers, or the effective number of species in a sample, provide a simple metric for comparing species diversity across environments. The more diverse the sample, the higher the Hill number. We adopt this ecological approach and consider each k-mer an individual and each genome a transect in the pangenome of the species. Structured in this way, Hill numbers summarize the temporal trajectory of pandemic variants, collapsing each day's assemblies into genome equivalents. For pooled or wastewater sequence, we instead compare days using survey sequence divorced from individual infections. Across data from the UK, USA, and South Africa, we trace the ascendance of new variants of concern as they emerge in local populations well before these variants are named and added to phylogenetic databases. Using data from San Diego wastewater, we monitor these same population changes from raw, unassembled sequence. This history of emerging variants senses all available data as it is sequenced, intimating variant sweeps to dominance or declines to extinction at the leading edge of the COVID-19 pandemic.

ProT-Diff: A Modularized and Efficient Strategy for De Novo Generation of Antimicrobial Peptide Sequences by Integrating Protein Language and Diffusion Models.

Antimicrobial peptides (AMPs) are a promising solution for treating antibiotic-resistant pathogens. However, efficient generation of diverse AMPs without prior knowledge of peptide structures or sequence alignments remains a challenge. Here, ProT-Diff is introduced, a modularized deep generative approach that combines a pretrained protein language model with a diffusion model for the de novo generation of AMPs sequences. ProT-Diff generates thousands of AMPs with diverse lengths and structures within a few hours. After silico physicochemical screening, 45 peptides are selected for experimental validation. Forty-four peptides showed antimicrobial activity against both gram-positive or gram-negative bacteria. Among broad-spectrum peptides, AMP_2 exhibited potent antimicrobial activity, low hemolysis, and minimal cytotoxicity. An in vivo assessment demonstrated its effectiveness against a drug-resistant E. coli strain in acute peritonitis. This study not only introduces a viable and user-friendly strategy for de novo generation of antimicrobial peptides, but also provides potential antimicrobial drug candidates with excellent activity. It is believed that this study will facilitate the development of other peptide-based drug candidates in the future, as well as proteins with tailored characteristics.

Development and experimental validation of computational methods for human antibody affinity enhancement.

High affinity is crucial for the efficacy and specificity of antibody. Due to involving high-throughput screens, biological experiments for antibody affinity maturation are time-consuming and have a low success rate. Precise computational-assisted antibody design promises to accelerate this process, but there is still a lack of effective computational methods capable of pinpointing beneficial mutations within the complementarity-determining region (CDR) of antibodies. Moreover, random mutations often lead to challenges in antibody expression and immunogenicity. In this study, to enhance the affinity of a human antibody against avian influenza virus, a CDR library was constructed and evolutionary information was acquired through sequence alignment to restrict the mutation positions and types. Concurrently, a statistical potential methodology was developed based on amino acid interactions between antibodies and antigens to calculate potential affinity-enhanced antibodies, which were further subjected to molecular dynamics simulations. Subsequently, experimental validation confirmed that a point mutation enhancing 2.5-fold affinity was obtained from 10 designs, resulting in the antibody affinity of 2nM. A predictive model for antibody-antigen interactions based on the binding interface was also developed, achieving an Area Under the Curve (AUC) of 0.83 and a precision of 0.89 on the test set. Lastly, a novel approach involving combinations of affinity-enhancing mutations and an iterative mutation optimization scheme similar to the Monte Carlo method were proposed. This study presents computational methods that rapidly and accurately enhance antibody affinity, addressing issues related to antibody expression and immunogenicity.

Identification of three novel linear B-cell epitopes on VP7 of African horse sickness virus using monoclonal antibodies

African horse sickness (AHS) is an acute and subacute infectious disease of equine species caused by the African horse sickness virus (AHSV). The VP7 of AHSV is a group-specific protein conserved in all serotypes and is an excellent candidate for the serological diagnosis and an AHS vaccine component. However, to date, B-cell epitopes on the AHSV VP7 recognized by humoral immune responses remain unclear. This study expressed the recombinant AHSV VP7 soluble in Escherichia coli and purified it for mouse immunization. Four monoclonal antibodies (mAbs) were screened and identified by hybridoma cell fusion, clonal purification, and immunological assays. The B-cell epitopes, recognized by monoclonal antibodies 4B5, 3G10, 3D7, and 4D6, were identified by a series of truncated overlapping peptides expressed as glutathione S-transferase (GST)-fusion proteins. The results revealed that 4B5 recognized the 124VQTGRYAGA132 motif, 3G10 recognized the 140RYYVPQGRT148 motif, while 3D7 and 4D6 recognized the 292QPINPPIFP300 motif. Amino acid sequence alignment indicated that three novel B-cell epitopes were conserved among various AHSV serotypes but unconserved in other orbiviruses, such as the bluetongue and epidemic hemorrhagic disease viruses. This study informs on the antigenic epitopes of AHSV VP7, facilitating future investigations into the serological diagnosis method and epitope-based vaccines against AHSV.

Impact of phylogeny on the inference of functional sectors from protein sequence data.

Statistical analysis of multiple sequence alignments of homologous proteins has revealed groups of coevolving amino acids called sectors. These groups of amino-acid sites feature collective correlations in their amino-acid usage, and they are associated to functional properties. Modeling showed that nonlinear selection on an additive functional trait of a protein is generically expected to give rise to a functional sector. These modeling results motivated a principled method, called ICOD, which is designed to identify functional sectors, as well as mutational effects, from sequence data. However, a challenge for all methods aiming to identify sectors from multiple sequence alignments is that correlations in amino-acid usage can also arise from the mere fact that homologous sequences share common ancestry, i.e. from phylogeny. Here, we generate controlled synthetic data from a minimal model comprising both phylogeny and functional sectors. We use this data to dissect the impact of phylogeny on sector identification and on mutational effect inference by different methods. We find that ICOD is most robust to phylogeny, but that conservation is also quite robust. Next, we consider natural multiple sequence alignments of protein families for which deep mutational scan experimental data is available. We show that in this natural data, conservation and ICOD best identify sites with strong functional roles, in agreement with our results on synthetic data. Importantly, these two methods have different premises, since they respectively focus on conservation and on correlations. Thus, their joint use can reveal complementary information.