Amino Acid Mutations In Proteins Research Articles

Epidemiology and Genetic Characterization of Porcine Parvovirus 7 Recovered from Swine in Hunan, China.

Porcine parvovirus 7 (PPV7) was first discovered in swine in 2016, and PPV7 infection has been detected in aborted pig fetuses and in sows that experienced reproductive failure. The objective of this study was to report the prevalence and genetic characterization of PPV7 in Hunan, China. Seventy of the four hundred and twenty-two (16.6%) serum, semen, and tissue samples collected from pigs were positive for PPV7. One complete PPV7 strain and eighteen complete cap gene sequences were obtained; nucleotide and amino acid identity among the nineteen Cap sequences were 88.1-99.4% and 88.1-100%, respectively. They shared identity with previously discovered sequences ranging from 86.6 to 98.9% and 83.7 to 99.8% at the nucleotide- and amino acid-level, respectively. The phylogenetic tree analysis exhibited that PPV7 strains had two major groups based on the presence or absence of five amino acid (181-185) insertions on the Cap protein. Analysis of the Cap protein demonstrated that PPV7 Cap had significant variability, implying that PPV7 evolved at high substitution rates. Substantial variations of that PPV7 Cap may enable the emergence of newly mutated capsid profiles due to its viral adaptation to host responses. Furthermore, antigenic alteration owing to PPV7 Cap protein amino acid mutations at immune epitopes may enable viruses to escape from the host's immune system. This study determined the prevalence and genetic characteristics of PPV7 circulating in swine in Hunan, China, and provided the impetus and basis to further investigate the pathogenicity and epidemiology of PPV7.

Serial cell culture passaging in vitro led to complete attenuation and changes in the characteristic features of a virulent porcine deltacoronavirus strain.

Porcine deltacoronavirus (PDCoV) is an important enteric coronavirus that has caused enormous economic losses in the pig industry worldwide. However, no commercial vaccine is currently available. Therefore, developing a safe and efficacious live-attenuated vaccine candidate is urgently needed. In this study, the PDCoV strain CH/XJYN/2016 was continuously passaged in LLC-PK cells until passage 240, and the virus growth kinetics in cell culture, pathogenicity in neonatal piglets, transcriptome differences after LLC-PK infection, changes in the functional characteristics of the spike (S) protein in the high- and low-passage strains, genetic variation of the virus genome, resistance to pepsin and acid, and protective effects of this strain when used as a live-attenuated vaccine were examined. The results of animal experiments demonstrated that the virulent PDCoV strain CH/XJYN/2016 was completely attenuated and not pathogenic in piglets following serial cell passage. Genome sequence analysis showed that amino acid mutations in nonstructural proteins were mainly concentrated in Nsp3, structural protein mutations were mainly concentrated in the S protein, and the N, M, and E genes were conserved. Transcriptome comparison revealed that compared with negative control cells, P10-infected LLC-PK cells had the most differentially expressed genes (DEGs), while P0 and P240 had the least number of DEGs. Analysis of trypsin dependence and related structural differences revealed that the P10 S protein interacted more strongly with trypsin and that the P120 S protein interacted more strongly with the APN receptor. Moreover, the infectivity of P240 was not affected by pepsin but was significantly decreased after exposure to low pH. Furthermore, the P240-based live-attenuated vaccine provided complete protection to piglets against the challenge of virulent PDCoV. In conclusion, we showed that a PDCoV strain was completely attenuated through serial passaging in vitro. These results provide insights into the potential molecular mechanisms of PDCoV attenuation and the development of a promising live-attenuated PDCoV vaccine.IMPORTANCEPorcine deltacoronavirus (PDCoV) is one of the most important enteropathogenic pathogens that cause diarrhea in pigs of various ages, especially in suckling piglets, and causes enormous economic losses in the global commercial pork industry. There are currently no effective measures to prevent and control PDCoV. As reported in previous porcine epidemic diarrhea virus (PEDV) and transmissible gastroenteritis virus studies, inactivated vaccines usually elicit less robust protective immune responses than live-attenuated vaccines in native sows. Therefore, identifying potential attenuation mechanisms, gene evolution, pathogenicity differences during PDCoV passaging, and immunogenicity as live-attenuated vaccines is important for elucidating the mechanism of attenuation and developing safe and effective vaccines for virulent PDCoV strains. In this study, we demonstrated that the virulence of the PDCoV strain CH/XJYN/2016 was completely attenuated following serial cell passaging in vitro, and changes in the biological characteristics and protection efficacy of the strain were evaluated. Our results help elucidate the mechanism of PDCoV attenuation and support the development of appropriate designs for the study of live PDCoV vaccines.

HERMES: Holographic Equivariant neuRal network model for Mutational Effect and Stability prediction.

Predicting the stability and fitness effects of amino acid mutations in proteins is a cornerstone of biological discovery and engineering. Various experimental techniques have been developed to measure mutational effects, providing us with extensive datasets across a diverse range of proteins. By training on these data, traditional computational modeling and more recent machine learning approaches have advanced significantly in predicting mutational effects. Here, we introduce HERMES, a 3D rotationally equivariant structure-based neural network model for mutational effect and stability prediction. Pre-trained to predict amino acid propensity from its surrounding 3D structure, HERMES can be fine-tuned for mutational effects using our open-source code. We present a suite of HERMES models, pre-trained with different strategies, and fine-tuned to predict the stability effect of mutations. Benchmarking against other models shows that HERMES often outperforms or matches their performance in predicting mutational effect on stability, binding, and fitness. HERMES offers versatile tools for evaluating mutational effects and can be fine-tuned for specific predictive objectives.

Deciphering the Genetic Variation: A Comparative Analysis of Parental and Attenuated Strains of the QXL87 Vaccine for Infectious Bronchitis.

The QXL87 live attenuated vaccine strain for infectious bronchitis represents the first approved QX type (GI-19 lineage) vaccine in China. This strain was derived from the parental strain CK/CH/JS/2010/12 through continuous passage in SPF chicken embryos. To elucidate the molecular mechanism behind its attenuation, whole-genome sequencing was conducted on both the parental and attenuated strains. Analysis revealed 145 nucleotide mutations in the attenuated strain, leading to 48 amino acid mutations in various proteins, including Nsp2 (26), Nsp3 (14), Nsp4 (1), S (4), 3a (1), E (1), and N (1). Additionally, a frameshift mutation caused by a single base insertion in the ORFX resulted in a six-amino-acid extension. Subsequent comparison of post-translational modification sites, protein structure, and protein-protein binding sites between the parental and attenuated strains identified three potential virulence genes: Nsp2, Nsp3, and S. The amino acid mutations in these proteins not only altered their conformation but also affected the distribution of post-translational modification sites and protein-protein interaction sites. Furthermore, three potential functional mutation sites-P106S, A352T, and L472F, all located in the Nsp2 protein-were identified through PROVEAN, PolyPhen, and I-Mutant. Overall, our findings suggest that Nsp2, Nsp3, and S proteins may play a role in modulating IBV pathogenicity, with a particular focus on the significance of the Nsp2 protein. This study contributes to our understanding of the molecular mechanisms underlying IBV attenuation and holds promise for the development of safer live attenuated IBV vaccines using reverse genetic approaches.

Generation of novel respiratory syncytial virus vaccine candidate antigens that can induce high levels of prefusion-specific antibodies

Respiratory syncytial virus (RSV) infection is an acute respiratory infection caused by RSV. It occurs worldwide, and for over 50 years, several attempts have been made to research and develop vaccines to prevent RSV infection; effective preventive vaccines are eagerly awaited. The RSV fusion (F) protein, which has gained attention as a vaccine antigen, causes a dynamic structural change from the preF to postF state. Therefore, the structural changes in proteins must be regulated to produce a vaccine antigen that can efficiently induce antibodies with high virus-neutralizing activity. We successfully discovered several mutations that stabilized the antigen site Ø in the preF state, trimerized it, and improved the level of protein expression through observation and computational analysis of the RSV-F protein structure and amino acid mutation analysis of RSV strains. The four RSV-F protein mutants that resulted from the combination of these effective mutations stably conserved a wide range of preF- and trimeric preF-specific epitopes with high virus-neutralizing activity. Absorption assay using human serum revealed that mutants constructed bound to antibodies with virus-neutralizing activity that were induced by natural RSV infection, whereas they hardly bound to anti-postF antibodies without virus-neutralizing activity. Furthermore, mouse immunization demonstrated that our constructed mutants induced a high percentage of antibodies that bind to the preF-specific antigen site. These characteristics suggest that the mutants constructed can be superior vaccine antigens from the viewpoint of RSV infection prevention effect and safety.

Validating the Distinctiveness of the Omicron Lineage within the SARSCov-2 based on Protein Language Models

Introduction: Variants of concern were identified in severe acute respiratory syndrome coronavirus 2, namely Alpha, Beta, Gamma, Delta, and Omicron. This study explores the mutations of the Omicron lineage and its differences from other lineages through a protein language model. Methods: By inputting the severe acute respiratory syndrome coronavirus 2 wild-type sequence into the protein language model evolving pre-trained models-1v, this study obtained the score for each position mutating to other amino acids and calculated the overall trend of a new variant of concern mutation scores. objective: Analyze the differences in the number of Omicron amino acid mutations compared to the other four VOC mutations using statistical methods, and use the protein language model esm-1v to analyze the specificity of Omicron amino acid mutations. Results: It is found that when the proportion of unobserved mutations to observed mutations is 4:15, Omicron still generates a large number of newly emerging mutations. It was found that the overall score for the Omicron family is low, and the overall ranking for the Omicron family is low. Conclusion: Mutations in the Omicron lineage are different from amino acid mutations in other lineages. The findings of this paper deepen the understanding of the spatial distribution of spike protein amino acid mutations and overall trends of newly emerging mutations corresponding to different variants of concern. This also provides insights into simulating the evolution of the Omicron lineage.

Genotypic diversity and recombination of norovirus GI.6[P11] associated acute gastroenteritis outbreaks in Beijing, China, from 2016 to 2019.

Norovirus (NoV) is the leading pathogen responsible for global acute gastroenteritis (AGE) outbreaks and sporadic cases. NoV evolves through gene mutation and recombination, leading to the emergence of new strains capable of causing global epidemics. This study aimed to learn the epidemiological characteristics of 39 GI.6[P11] NoV outbreaks in Beijing, China, from 2016 to 2019 and to analyze the genetic diversity and phylogenetic process of GI.6[P11] strains. The Bayesian phylogenetic analysis of partial VP1 and RNA-dependent RNA polymerase (RdRp) genes showed that GI.6[P11] strains were clustered into four subclades. Eleven whole genome sequences were obtained through the amplicon sequencing with 16 pairs of newly designed primers. The phylogenetic trees based on the whole genome and ORF1, 2, and 3 showed that the clustering of the 11 strains was consistent with that of partial VP1 and RdRp genes. The Bayesian inference revealed that the most recent ancestor (TMRCA) for the four subclades of the phylogenetic tree based on the whole genome sequences was 2012.42, 2014.81, 2011.74, and 2015.53, respectively. The recombination sites of GI.6[P11] strains in Beijing were located near the ORF1/2 junction. The histo-blood group antigens (HBGA) binding sites of GI.6[P11] strains in Beijing were conserved and there were some unique amino acid mutations in non-structural proteins in the ORF1 region.

Polyclonal Spread of Fosfomycin Resistance among Carbapenemase-Producing Members of the Enterobacterales in the Czech Republic.

Fosfomycin (FOS) has been recently reintroduced into clinical practice, but its effectiveness against multidrug-resistant (MDR) Enterobacterales is reduced due to the emergence of FOS resistance. The copresence of carbapenemases and FOS resistance could drastically limit antibiotic treatment. The aims of this study were (i) to investigate fosfomycin susceptibility profiles among carbapenem-resistant Enterobacterales (CRE) in the Czech Republic, (ii) to characterize the genetic environment of fosA genes among the collection, and (iii) to evaluate the presence of amino acid mutations in proteins involved in FOS resistance mechanisms. During the period from December 2018 to February 2022, 293 CRE isolates were collected from different hospitals in the Czech Republic. FOS MICs were assessed by the agar dilution method (ADM), FosA and FosC2 production was detected by the sodium phosphonoformate (PPF) test, and the presence of fosA-like genes was confirmed by PCR. Whole-genome sequencing was conducted with an Illumina NovaSeq 6000 system on selected strains, and the effect of point mutations in the FOS pathway was predicted using PROVEAN. Of these strains, 29% showed low susceptibility to fosfomycin (MIC, ≥16 μg/mL) by ADM. An NDM-producing Escherichia coli sequence type 648 (ST648) strain harbored a fosA10 gene on an IncK plasmid, while a VIM-producing Citrobacter freundii ST673 strain harbored a new fosA7 variant, designated fosA7.9. Analysis of mutations in the FOS pathway revealed several deleterious mutations occurring in GlpT, UhpT, UhpC, CyaA, and GlpR. Results regarding single substitutions in amino acid sequences highlighted a relationship between ST and specific mutations and an enhanced predisposition for certain STs to develop resistance. This study highlights the occurrence of several FOS resistance mechanisms in different clones spreading in the Czech Republic. IMPORTANCE Antimicrobial resistance (AMR) currently represents a concern for human health, and the reintroduction of antibiotics such as fosfomycin into clinical practice can provide further option in treatment of multidrug-resistant (MDR) bacterial infections. However, there is a global increase of fosfomycin-resistant bacteria, reducing its effectiveness. Considering this increase, it is crucial to monitor the spread of fosfomycin resistance in MDR bacteria in clinical settings and to investigate the resistance mechanism at the molecular level. Our study reports a large variety of fosfomycin resistance mechanisms among carbapenemase-producing Enterobacterales (CRE) in the Czech Republic. Our study summarizes the main achievements of our research on the use of molecular technologies, such as next-generation sequencing (NGS), to describe the heterogeneous mechanisms that reduce fosfomycin effectiveness in CRE. The results suggest that a program for widespread monitoring of fosfomycin resistance and epidemiology fosfomycin-resistant organisms can aide timely implementation of countermeasures to maintain the effectiveness of fosfomycin.

Identification, genome sequencing, and virulence variation analysis of MCRV-NH, an epidemic reovirus strain in cultured mud crab, Scylla paramamosain

Mud Crab Reovirus (MCRV) is a major pathogen of cultured mud crab Scylla paramamosain. Early studies showed that the mortality rate caused by MCRV was high. However, current studies show that MCRV has been widely present in cultured mud crab ponds, and the mortality rate has dramatically decreased, suggesting that it has become more infectious but less virulent. In this study, an epidemic MCRV strain named MCRV-NH was isolated from a representative farming areas of mud crabs to reveal the intrinsic molecular mechanism of the virulence variation of MCRV. Electron microscopy results showed that MCRV-NH was similar to the early reported MCRV or Scylla serrata reovirus (SsRV) in terms of morphology and structure. Viral infection experiments showed that no mud crab was dead during the infection period of 11 days even though MCRV-NH could rapidly proliferate in mud crabs at 21–23 °C, demonstrating that the mortality rate caused by MCRV-NH significantly decreased. Sequencing results of the MCRV-NH genome showed that eleven nucleotides were deleted in the sequencing region, and its nucleotide sequence identities with those of MCRV and SsRV were 99.43% and 99.33%, and the numbers of corresponding nucleotide mutations were 150 and 126, respectively. Evolutionary analysis showed that MCRV-NH belonged to the same species as MCRV and SsRV, and MCRV-NH should be a variant. In comparison with the open reading frames (ORFs) of MCRV and SsRV, the ORFs of MCRV-NH had no nucleotide deletions, but the numbers of nucleotide mutations were 100 and 123, and the numbers of amino acid mutations were 32 and 35, respectively. Eight mutated amino acids compared with the two reoviruses were located at the predicted active sites of the viral proteins. Among them, three mutations resulted in the generation of new phosphorylation sites, and two mutations led to the loss of the original phosphorylation sites. Meanwhile, a heptapeptide repeat sequence in VP9 disappeared, and a streptococcal histidine triad protein in VP6 and a Big-1 (bacterial Ig-like domain 1) domain in VP11 were generated due to key amino acid mutations in these viral proteins, which are involved in the infection and replication of MCRV. These changes in the active sites of the viral proteins may be responsible for the MCRV virulence variation. This study provided essential evidence to support the conclusion that MCRV-NH was a variant of MCRV with weaker pathogenicity and revealed the underlying possible molecular mechanism of the virulence variation of MCRV-NH.

Evolution of monkeypox virus from 2017 to 2022: In the light of point mutations.

Monkeypox virus (MPXV) causing multi-country outbreak-2022 is related to viruses caused outbreak-2017-2018 in West Africa. Still not fully understood which proteins of the MPXV discovered in Nigeria in 2017 have mutated through different lineages to the extent that it could cause a multi-country outbreak in 2022; similarly, codon usage bias, host adaptation indices, and the role of selection or mutation pressure in the mutated genes are also not fully studied. Here we report that according to the available sequence data this monkeypox virus acquires point mutations in multiple proteins in each period, and these point mutations accumulate and become a virus that can root outbreak-2022. Viruses exported from Nigeria to Singapore, Israel, and the United Kingdom in 2018-2019 were developed as evolutionary ancestors to B.1 viruses (MPXVs causing multi-country outbreak-2022) through MPXV/United States/2021/MD virus. Although these exported viruses have different amino acid mutations in different proteins, amino acid mutations in 10 proteins are common among them. The MPXV-United Kingdom-P2 virus evolved with only mutations in these 10 proteins and further evolved into MPXV/United States/2021/MD with amino acid mutations in 26 (including amino acid mutations in 10 proteins of the MPXV-United States-P2) proteins. It is noteworthy that specific amino acid mutations in these 22/26 (presence in MPXV/United States/2021/MD) proteins are present in B.1 viruses. Further, analysis of Relative Synonymous Codon Usage (RSCU), Synonymous Codon Usage Fraction (SCUF), and Effective Number of Codons (ENc) revealed codon usage bias in genes that exhibited nucleotide mutations in lineage B.1. Also, host adaptation indices analyzes such as Codon Adaptation Index (CAI), Expected-CAI (eCAI), Relative Codon Deoptimization Index (RCDI) and Expected value for the RCDI (eRCDI) analyzes reveal that the genes that demonstrated nucleotide mutations in lineage B.1 are favorable for human adaptation. Similarly, ENc-GC3s plot, Neutrality plot, and Parity Rule 2 (PR2)-bias plot analyzes suggest a major role of selection pressure than mutation pressure in the evolution of genes displaying nucleotide mutations in lineage B.1. Overall, from 2017 to 2022, MPXV's mutation and spread suggests that this virus continues to evolve through point mutation in the genes according to the available sequence data.

Molecular Evolution of Attachment Glycoprotein (G) and Fusion Protein (F) Genes of Respiratory Syncytial Virus ON1 and BA9 Strains in Xiamen, China.

ABSTRACTMonitoring viral transmission and analyzing the genetic diversity of a virus are imperative to better understand its evolutionary history and the mechanism driving its evolution and spread. Especially, effective monitoring of key antigenic mutations and immune escape variants caused by these mutations has great scientific importance. Thus, to further understand the molecular evolutionary dynamics of respiratory syncytial virus (RSV) circulating in China, we analyzed nasopharyngeal swab specimens derived from hospitalized children ≤5 years old with acute respiratory tract infections (ARIs) in Xiamen during 2016 to 2019. We found that infants under 6 months of age (52.0%) were the main population with RSV infection. The prevalent pattern “BBAA” of RSV was observed during the epidemic seasons. RSV ON1 and BA9 genotypes were the dominant circulating strains in Xiamen. Interestingly, we observed four Xiamen-specific amino acid substitution combinations in the G protein and several amino acid mutations primarily occurring at antigenic sites Ø and V in the F protein. Our analyses suggest that introduction of new viruses and local evolution are shaping the diversification of RSV strains in Xiamen. This study provides new insights on the evolution and spread of the ON1 and BA9 genotypes at local and global scales.IMPORTANCE Monitoring the amino acid diversity of the RSV G and F genes helps us to find the novel genotypes, key antigenic mutations affecting antigenicity, or neutralizing antibody-resistant variants produced by natural evolution. In this study, we analyzed the molecular evolution of G and F genes from RSV strains circulating in Xiamen, China. These data provide new insights on local and global transmission and could inform the development of control measures for RSV infections.

Long-term, infection-acquired immunity against the SARS-CoV-2 Delta variant in a hamster model.

The emergence of the SARS-CoV-2 Delta variant (B.1.617.2) raises concerns about potential reduced sensitivity of the virus to antibody neutralization and subsequent vaccine breakthrough infections. Here, we use a live virus neutralization assay with sera from Pfizer- and Moderna-vaccinated individuals to examine neutralizing antibody titers against SARS-CoV-2 and observe a 3.9- and 2.7-fold reduction, respectively, in neutralizing antibody titers against the Delta variant compared with an early isolate bearing only a D614G substitution in its spike protein. We observe similar reduced sensitivity with sera from hamsters that were previously infected with an early isolate of SARS-CoV-2. Despite this reduction in neutralizing antibody titers against the Delta variant, hamsters previously infected (up to 15 months earlier) with an early isolate are protected from infection with the Delta variant, suggesting that the immune response to the first infection is sufficient to provide protection against subsequent infection with the Delta variant.

Evolution and genetic diversity of SARS-CoV-2 in Africa using whole genome sequences

BackgroundThe ongoing SARS-CoV-2 pandemic was introduced into Africa on 14th February 2020 and has rapidly spread across the continent causing a severe public health crisis and mortality. We investigated the genetic diversity and evolution of this virus during the early outbreak months, between 14th February to 24th April 2020, using whole genome sequences. MethodsWe performed recombination analysis against closely related CoV strains, Bayesian time scaled phylogeny, and investigation of spike protein amino acid mutations. ResultsRecombination signals were observed between the Afr-SARS-CoV-2 sequences and reference sequences within the RdRPs and S genes. The evolutionary rate of the Afr-SARS-CoV-2 was 4.133 × 10−4 Highest Posterior Density (HPD 4.132 × 10−4 to 4.134 × 10−4) substitutions/site/year. The time to most recent common ancestor (TMRCA) of the African strains was December 7th 2019, (95% HPD November 12th 2019-December 29th 2019). The Afr-SARCoV-2 sequences diversified into two lineages A and B, with B being more diverse with multiple sub-lineages confirmed by both maximum clade credibility (MCC) tree and PANGOLIN software. There was a high prevalence of the D614G spike protein amino acid mutation 59/69 (82.61%) among the African strains. ConclusionThis study has revealed a rapidly diversifying viral population with the G614G spike protein variant dominatinge advocate for up scaling NGS sequencing platforms across Africa to enhance surveillance and aid control effort of SARS-CoV-2 in Africa.

Intra-host non-synonymous diversity at a neutralizing antibody epitope of SARS-CoV-2 spike protein N-terminal domain

ObjectivesSARS-CoV-2 has evolved rapidly into several genetic clusters. However, data on mutations during the course of infection are scarce. This study aims to determine viral genome diversity in serial samples of COVID-19 patients. MethodsTargeted deep sequencing of the spike gene was performed on serial respiratory specimens from COVID-19 patients using nanopore and Illumina sequencing. Sanger sequencing was then performed to confirm the single nucleotide polymorphisms. ResultsA total of 28 serial respiratory specimens from 12 patients were successfully sequenced using nanopore and Illumina sequencing. A 75-year-old patient with severe disease had a mutation, G22017T, identified in the second specimen. The frequency of G22017T increased from ≤5% (nanopore: 3.8%; Illumina: 5%) from the first respiratory tract specimen (sputum) to ≥60% (nanopore: 67.7%; Illumina: 60.4%) in the second specimen (saliva; collected 2 days after the first specimen). The difference in G22017T frequency was also confirmed by Sanger sequencing. G22017T corresponds to W152L amino acid mutation in the spike protein which was only found in <0.03% of the sequences deposited into a public database. Spike amino acid residue 152 is located within the N-terminal domain, which mediates the binding of a neutralizing antibody. DiscussionA spike protein amino acid mutation W152L located within a neutralizing epitope has appeared naturally in a patient. Our study demonstrated that monitoring of serial specimens is important in identifying hotspots of mutations, especially those occurring at neutralizing epitopes which may affect the therapeutic efficacy of monoclonal antibodies.

Complete genome analysis of hepatitis B virus in Qinghai-Tibet plateau: the geographical distribution, genetic diversity, and co-existence of HBsAg and anti-HBs antibodies

BackgroundThe genetic variation and origin of Hepatitis B Virus (HBV) in Qinghai-Tibet Plateau were poorly studied. The coexistence of HBsAg and anti-HBs has been described as a puzzle and has never been reported in the indigenous population or in recombinant HBV sequences. This study aimed to report geographical distribution, genetic variability and seroepidemiology of HBV in southwest China.MethodsDuring 2014–2017, 1263 HBsAg positive serum were identified and 183 complete genome sequences were obtained. Serum samples were collected from community-based populations by a multistage random sampling method. Polymerase chain reaction (PCR) was used to amplify the HBV complete genome sequences. Then recombination, genetic variability, and serological analysis were performed.Results(1) Of the 1263 HBsAg positive serum samples, there were significant differences between the distribution of seromarkers in Tibet and Qinghai. (2) Of 183 complete genome sequences, there were 130 HBV/CD1 (71.0%), 49 HBV/CD2 (26.8%) and four HBV/C2 isolates (2.2%). Serotype ayw2 (96.1%) was the main serological subtype. (3) Several nucleotide mutations were dramatically different in CD1 and CD2 sequences. Clinical prognosis-related genetic variations such as nucleotide mutation T1762/A1764 (27.93%), A2189C (12.85%), G1613A (8.94%), T1753C (8.38%), T53C (4.47%) T3098C (1.68%) and PreS deletion (2.23%) were detected in CD recombinants. (4) From the inner land of China to the northeast boundary of India, different geographical distributions between CD1 and CD2 were identified. (5) Twenty-seven (2.14%) HBsAg/HBsAb coexistence serum samples were identified. S protein amino acid mutation and PreS deletion were with significant differences between HBsAg/HBsAb coexistence group and control group.ConclusionsHBV/CD may have a mixed China and South Asia origin. Based on genetic variations, the clinical prognosis of CD recombinant seems more temperate than genotype C strains in China. The HBsAg/HBsAb coexistence is a result of both PreS deletion and aa variation in S protein. Several unique mutations were frequently detected in HBV/CD isolates, which could potentially influence the clinical prognosis.

Investigating the genomic landscape of novel coronavirus (2019-nCoV) to identify non-synonymous mutations for use in diagnosis and drug design.

Novel coronavirus has wrecked medical and health care facilities claiming ∼5% death tollsglobally. All efforts to contain the pathogenesis either using inhibitory drugs or vaccines largelyremained futile due to a lack of better understanding of the genomic feature of this virus. In thepresent study, we compared the 2019-nCoV with other coronaviruses, which indicated that batSARS like coronavirus could be a probable ancestor of the novel coronavirus. The proteinsequence similarity of pangolin-hCoV and bat-hCoV with human coronavirus was higher ascompared to their nucleotide similarity denoting the occurrence of more synonymous mutationsin the genome. Phylogenetic and alignment analysis of 591 novel coronaviruses of differentclades from Group I to Group V revealed several mutations and concomitant amino acidchanges. Detailed investigation on nucleotide substitution unfolded 100 substitutions in thecoding region of which 43 were synonymous and 57 were of non-synonymous type. The nonsynonymous substitutions resulting into 57 amino acid changes were found to be distributed overdifferent hCoV proteins with maximum on spike protein. An important di-amino acid change RGto KR was observed in ORF9 protein. Additionally, several interesting features of the novelcoronavirus genome have been highlighted in respect to various other human infecting viruseswhich may explain extreme pathogenicity, infectivity and simultaneously the reason behindfailure of the antiviral therapies.SummaryThis study presents a comprehensive phylogenetic analysis of SARS-CoV2 isolates to understand discrete mutations that are occurring between patient samples. The analysis unravel various amino acid mutations in the viral proteins which may provide an explanation for varying treatment efficacies of different inhibitory drugs and a future direction towards a combinatorial treatment therapies based on the kind of mutation in the viral genome.

Amino acid impact factor.

Amino acid mutations in proteins are random and those mutations which are beneficial or neutral survive during the course of evolution. Conservation or co-evolution analyses are performed on the multiple sequence alignment of homologous proteins to understand how important different amino acids or groups of them are. However, these traditional analyses do not explore the directed influence of amino acid mutations, such as compensatory effects. In this work we develop a method to capture the directed evolutionary impact of one amino acid on all other amino acids, and provide a visual network representation for it. The method developed for these directed networks of inter- and intra-protein evolutionary interactions can also be used for noting the differences in amino acid evolution between the control and experimental groups. The analysis is illustrated with a few examples, where the method identifies several directed interactions of functionally critical amino acids. The impact of an amino acid is quantified as the number of amino acids that are influenced as a consequence of its mutation, and it is intended to summarize the compensatory mutations in large evolutionary sequence data sets as well as to rationally identify targets for mutagenesis when their functional significance can not be assessed using structure or conservation.

Protein-Protein Interactions Prediction via Multimodal Deep Polynomial Network and Regularized Extreme Learning Machine.

Predicting the protein-protein interactions (PPIs) has played an important role in many applications. Hence, a novel computational method for PPIs prediction is highly desirable. PPIs endow with protein amino acid mutation rate and two physicochemical properties of protein (e.g., hydrophobicity and hydrophilicity). Deep polynomial network (DPN) is well-suited to integrate these modalities since it can represent any function on a finite sample dataset via the supervised deep learning algorithm. We propose a multimodal DPN (MDPN) algorithm to effectively integrate these modalities to enhance prediction performance. MDPN consists of a two-stage DPN, the first stage feeds multiple protein features into DPN encoding to obtain high-level feature representation while the second stage fuses and learns features by cascading three types of high-level features in the DPN encoding. We employ a regularized extreme learning machine to predict PPIs. The proposed method is tested on the public dataset of H. pylori, Human, and Yeast and achieves average accuracies of 97.87%, 99.90%, and 98.11%, respectively. The proposed method also achieves good accuracies on other datasets. Furthermore, we test our method on three kinds of PPI networks and obtain superior prediction results.

Adaptive evolution during the establishment of European avian-like H1N1 influenza A virus in swine.

An H1N1 subtype influenza A virus with all eight gene segments derived from wild birds (including mallards), ducks and chickens, caused severe disease outbreaks in swine populations in Europe beginning in 1979 and successfully adapted to form the European avian‐like swine (EA‐swine) influenza lineage. Genes of the EA‐swine lineage that are clearly segregated from its closest avian relatives continue to circulate in swine populations globally and represent a unique opportunity to study the adaptive process of an avian‐to‐mammalian cross‐species transmission. Here, we used a relaxed molecular clock model to test whether the EA‐swine virus originated through the introduction of a single avian ancestor as an entire genome, followed by an analysis of host‐specific selection pressures among different gene segments. Our data indicated independent introduction of gene segments via transmission of avian viruses into swine followed by reassortment events that occurred at least 1–4 years prior to the EA‐swine outbreak. All EA‐swine gene segments exhibit greater selection pressure than avian viruses, reflecting both adaptive pressures and relaxed selective constraints that are associated with host switching. Notably, we identified key amino acid mutations in the viral surface proteins (H1 and N1) that play a role in adaptation to new hosts. Following the establishment of EA‐swine lineage, we observed an increased frequency of intrasubtype reassortment of segments compared to the earlier strains that has been associated with adaptive amino acid replacements, disease severity and vaccine escape. Taken together, our study provides key insights into the adaptive changes in viral genomes following the transmission of avian influenza viruses to swine and the early establishment of the EA‐swine lineage.

Prediction of protein-protein interactions by label propagation with protein evolutionary and chemical information derived from heterogeneous network

Prediction of protein-protein interactions (PPIs) is of great significance. To achieve this, we propose a novel computational method for PPIs prediction based on a similarity network fusion (SNF) model for integrating the physical and chemical properties of proteins. Specifically, the physical and chemical properties of protein are the protein amino acid mutation rate and its hydrophobicity, respectively. The amino acid mutation rate is extracted using a BLOSUM62 matrix, which puts the protein sequence into block substitution matrix. The SNF model is exploited to fuse protein physical and chemical features of multiple data by iteratively updating each original network. Finally, the complementary features from the fused network are fed into a label propagation algorithm (LPA) for PPIs prediction. The experimental results show that the proposed method achieves promising performance and outperforms the traditional methods for the public dataset of H. pylori, Human, and Yeast. In addition, our proposed method achieves average accuracy of 76.65%, 81.98%, 84.56%, 84.01% and 84.38% on E. coli, C. elegans, H. sapien, H. pylori and M. musculus datasets, respectively. Comparison results demonstrate that the proposed method is very promising and provides a cost-effective alternative for predicting PPIs. The source code and all datasets are available at http://pan.baidu.com/s/1dF7rp7N.