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| 1 | Antigenic variation of the human influenza A(H3N2) virus during the 2014–2015 winter season显示文摘The human influenza A(H3N2) virus dominated the 2014–2015 winter season in many countries and caused massive morbidity and mortality because of its antigenic variation. So far, very little is known about the antigenic patterns of the recent H3N2 virus. By systematically mapping the antigenic relationships of H3N2 strains isolat ed since 2010, we discov ered that two groups with obvious antigenic divergence, named SW13(A/Switzerland/9715293/2013-like strains) and HK14(A/Hong Kong/5738/2014-like strains), co-circulated during the 2014–2015 winter season. HK14 group co-circulated with SW13 in Europe and the United States during this season, while there were few strains of HK14 in China's Mainland, where SW13 has dominated since 2012. Furthermore, we found that substitutions near the receptor-binding site on hemagglutinin played an important role in the antigenic variation of both the groups. These findings provide a comprehensive understanding of the recent antigenic evolution of H3N2 virus and will aid in the selection of vaccine strains. | HUA Sha LI XiYan LIU Mi CHENG YanHui PENG YouSong HUANG WeiJuan TAN MinJu WEI HeJiang GUO JunFeng WANG DaYan WU AiPing SHU YueLong JIANG TaiJiao | 2015 | Science China(Life Sciences)2015，58，9： | 17 |
| 2 | Nematode-Encoded RALF Peptide Mimics Facilitate Parasitism of Plants through the FERONIA Receptor Kinase显示文摘The molecular mechanism by which plants defend against plant root-knot nematodes(RKNs)is largely unknown.The plant receptor kinase FERONIA and its peptide ligands,rapid alkalinization factors(RALFs),regulate plant immune responses and cell expansion,which are two important factors for successful RKN parasitism.In this study,we found that mutation of FERONIA in Arabidopsis thaliana resulted in plants showing low susceptibility to the RKN Meloidogyne incognita.To identify the underlying mechanisms associated with this phenomenon,we identified 18 novel RALF-likes from multiple species of RKNs and showed that two RALF-likes(i.e.,MiRALF1 and MiRALF3)from M.incognita were expressed in the esophageal gland with high expression during the parasitic stages of nematode development.These nematode RALF-likes also possess the typical activities of plant RALFs and can directly bind to the extracellular domain of FERONIA to modulate specific steps of nematode parasitism-related immune responses and cell expansion.Genetically,both MiRALF1/3 and FERONIA are required for RKN parasitism in Arabidopsis and rice.Collectively,our study suggests that nematode-encoded RALFs facilitate parasitism via plant-encoded FERONIA and provides a novel paradigm for studying host-pathogen interactions. | Xin Zhang Huan Peng Sirui Zhu Junjie Xing Xin Li Zhaozhong Zhu Jingyuan Zheng Long Wang Bingqian Wang Jia Chen Zhenhua Ming Ke Yao Jinzhuo Jian Sheng Luan Devin Coleman-Derr Hongdong Liao Yousong Peng Deliang Peng Feng Yu | 2020 | Molecular Plant2020，13，10： | 3 |
| 3 | Increased plasma leptin as a novel predictor for psychopathological depressive symptoms in chronic schizophrenia显示文摘Background Depressive symptoms are often seen in schizophrenia. The overlap in presentation makes it difficult to distinguish depressive symptoms from the negative symptoms of schizophrenia. The adipokine leptin was found to be altered in both depression and schizophrenia. There are few studies focusing on the prediction of leptin in diagnosis and evaluation of depressive symptoms in schizophrenia.ObjectiveAims To assess the plasma leptin level in patients with schizophrenia and its relationships with depressive symptoms.Methods Cross-sectional studies were applied to(1) compare the levels of plasma leptin between schizophrenia(n=74) and healthy controls(n=50); and(2)investigate the relationship between plasma leptin levels and depressive subscores.Results(1) Plasma leptin levels were significantly higher in patients with schizophrenia than in healthy controls.(2) Correlation analysis revealed a significant negative association between leptin levels and the depressed factor scores on the Positive and Negative Syndrome Scale(PANSS).(3) Stepwise multiple regression analyses identified leptin as an influencing factor for depressed factor score on PANSS.Conclusion Leptin may serve as a predictor for the depressive symptoms of chronic schizophrenia. | Jinjie Xu Yumei Jiao Mengjuan Xing Yezhe Lin Yousong Su Wenhua Ding Cuizhen Zhu Yanmin Peng Dake Qi Donghong Cui | 2018 | General Psychiatry2018，31，6： | 1 |
| 4 | Network of co-mutations in Ebola virus genome predicts the disease lethality显示文摘 | Lizong Deng Mi Liu Sha Hua Yousong Peng Aiping Wu F Xiao-Feng Qin Genhong Cheng Taijiao Jiang | 2015 | Cell Research2015，25，6： | 1 |
| 5 | Prediction of coronavirus 3C-like protease cleavage sites using machine-learning algorithms显示文摘The coronavirus 3C-like(3CL)protease,a cysteine protease,plays an important role in viral infection and immune escape.However,there is still a lack of effective tools for determining the cleavage sites of the 3CL protease.This study systematically investigated the diversity of the cleavage sites of the coronavirus 3CL protease on the viral polyprotein,and found that the cleavage motif were highly conserved for viruses in the genera of Alphacoronavirus,Betacoronavirus and Gammacoronavirus.Strong residue preferences were observed at the neighboring positions of the cleavage sites.A random forest(RF)model was built to predict the cleavage sites of the coronavirus 3CL protease based on the representation of residues in cleavage motifs by amino acid indexes,and the model achieved an AUC of 0.96 in cross-validations.The RF model was further tested on an independent test dataset which were composed of cleavage sites on 99 proteins from multiple coronavirus hosts.It achieved an AUC of 0.95 and predicted correctly 80%of the cleavage sites.Then,1,352 human proteins were predicted to be cleaved by the 3CL protease by the RF model.These proteins were enriched in several GO terms related to the cytoskeleton,such as the microtubule,actin and tubulin.Finally,a webserver named 3CLP was built to predict the cleavage sites of the coronavirus 3CL protease based on the RF model.Overall,the study provides an effective tool for identifying cleavage sites of the 3CL protease and provides insights into the molecular mechanism underlying the pathogenicity of coronaviruses. | Huiting Chen Zhaozhong Zhu Ye Qiu Xingyi Ge Heping Zheng Yousong Peng | 2022 | Virologica Sinica2022，37，3： | 1 |
| 6 | Mechanism investigation of dioscin against CCl 4 -induced acute liver damage in mice显示文摘 | Binan Lu Yousong Xu Lina Xu Xiaonan Cong Lianhong Yin Hua Li Jinyong Peng | 2012 | Environmental Toxicology and Pharmacology2012，，2： | 1 |
| 7 | EVIHVR: A platform for analysis of expression, variation and identification of human virus receptors显示文摘Motivation:Virus receptors are presented on the cell surfaces of a host and are key for viral infection of host cells.However,no unified resource for the study of viral receptors is currently available.Results:To address this problem,we built EVIHVR,a platform for analyzing the expression and variation,and for the identification of human virus receptors.EVIHVR provides three functions:(1)Receptor expression function for browsing and analyzing the expression of human virus receptors in various human tissues/cells;(2)Receptor gene polymorphism function for analyzing the genetic polymorphism of human virus receptors in different human populations and human tissues;and(3)Predict receptor function for identifying potential virus receptors based on differential expression analysis.EVIHVR can become a useful tool for the analysis and identification of human virus receptors. | Zheng Zhang Zena Cai Longfei Mao Xing-Yi Ge Yousong Peng | 2022 | Infectious Medicine2022，1，1： | 1 |
| 8 | Large discrepancy between the two-way rNHT distances in hemagglutinin-inhibition assay显示文摘<正>Dear Editor,The influenza viruses cause continual epidemics in human society.As is reported by the World Health Organization(WHO),each year the seasonal influenza viruses,i.e.,human influenza A(H1N1),A(H3N2)and B viruses,infected 5%~15%of the world’s population,leading to about 3 to 5 million cases of severe illness | Yousong Peng Dayan Wang Yuelong Shu Taijiao Jiang | 2016 | Virologica Sinica2016，31，5： | 0 |
| 9 | Progress and Challenge in Computational Identification of Influenza Virus Reassortment显示文摘Genomic reassortment is an important evolutionary mechanism for influenza viruses.In this process,the novel viruses acquire new characteristics by the exchange of the intact gene segments among multiple influenza virus genomes,which may cause flu endemics and epidemics within or even across hosts.Due to the safety and ethical limitations of the experimental studies on influenza virus reassortment,numerous computational researches on the influenza virus reassortment have been done with the explosion of the influenza virus genomic data.A great amount of computational methods and bioinformatics databases were developed to facilitate the identification of influenza virus reassortments.In this review,we summarized the progress and challenge of the bioinformatics research on influenza virus reassortment,which can guide the researchers to investigate the influenza virus reassortment events reasonably and provide valuable insight to develop the related computational identification tools. | Xiao Ding Luyao Qin Jing Meng Yousong Peng Aiping Wu Taijiao Jiang | 2021 | Virologica Sinica2021，36，6： | 0 |
| 10 | Prediction of Cell Specific O-GalNAc Glycosylation in Human显示文摘Glycosylation is one of the most extensive post-translation modifications of proteins. Although lots of computational models have been developed to predict the glycosylation sites, none of them considered the tissue and cell specificity of glycosylation. Here, we built a two-step computational method GlycoCell to predict the cell-specific O-GalNAc glycosylation, the most complex type of O-glycosylation reported so far, in 12 human cell types. The first step predicted whether a site had the potential to be O-glycosylated. The model achieved an accuracy of 0.83. The second step predicted whether a potential glycosite would be O-glycosylated in the given cell type. For 12 cell types, a model was built for each cell type. The accuracies for these models ranged from 0.78 to 0.87. To facilitate the usage of GlycoCell for the public, a web server was built which is available at http://gffzzd3a3a31d642d43d8h6xqquqfcq5xb69wx.ffgz.tsg.suse.edu.cn/GlyoCell/main.htm. It could be useful for investigating the cell-specific O-glycosylation in human. | Yuanqiang Zou Kenli Li Taijiao Jiang Yousong Peng | 2017 | 国际计算机前沿大会会议论文集2017，，2： | 0 |
| 11 | Predicting the Antigenic Variant of Human Influenza A(H3N2) Virus with a Stacked Auto-Encoder Model显示文摘The influenza virus changes its antigenicity frequently due to rapid mutations, leading to immune escape and failure of vaccination. Rapid determination of the influenza antigenicity could help identify the antigenic variants in time. Here, we built a stacked auto-encoder (SAE) model for predicting the antigenic variant of human influenza A(H3N2) viruses based on the hemagglutinin (HA) protein sequences. The model achieved an accuracy of 0.95 in five-fold cross-validations, better than the logistic regression model did. Further analysis of the model shows that most of the active nodes in the hidden layer reflected the combined contribution of multiple residues to antigenic variation. Besides, some features (residues on HA protein) in the input layer were observed to take part in multiple active nodes, such as residue 189, 145 and 156, which were also reported to mostly determine the antigenic variation of influenza A(H3N2) viruses. Overall,this work is not only useful for rapidly identifying antigenic variants in influenza prevention, but also an interesting attempt in inferring the mechanisms of biological process through analysis of SAE model, which may give some insights into interpretation of the deep learning | Zhiying Tan Kenli Li Taijiao Jiang Yousong Peng | 2017 | 国际计算机前沿大会会议论文集2017，，2： | 0 |
| 12 | Computational Viromics: Applications of the Computational Biology in Viromics Studies显示文摘Viruses are a kind of biological entities which rely on host cells for survival.Depending on the genetic materials and replication mode,they can be grouped into double-stranded DNA(dsDNA),single-stranded DNA(ssDNA),doublestranded RNA(dsRNA),positive-sense single-stranded RNA(+ssRNA),negative-sense single-stranded RNA(-ssRNA),ssRNA reverse transcriptase viruses(ssRNART)and dsDNA reverse transcriptase viruses(dsDNA-RT)(Walker et al.2020).Viruses can infect most kinds of biological entities,including viruses,bacteria,archaea and eukaryote(La Scola et al.2008;Fermin,2018). | Congyu Lu Yousong Peng | 2021 | Virologica Sinica2021，36，5： | 0 |
| 13 | PREDAV-H1: a user-friendly web server for predicting antigenic variants of influenza H1N1 viruses显示文摘Dear Editor,The influenza H1N1 virus has caused three global pandemics since the beginning of the 20th century(Liu et al.,2015).The first is the notorious Spanish flu in 191&which killed 20-100 million people in the world.It circulated for nearly 40 years and was replaced by influenza H2N2 virus.In 1977,the virus reappeared in Russia and caused global pandemics.It continued to circulate until 2009 when it was replaced by the pandemic H1N1 virus.Influenza H1N1 viruses cause large morbidity and mortality to human society,and will continue to threaten humans.Vaccination is the most effective way to fight against the virus.However,due to rapid mutation of the virus,antigenic drift happens frequently,which leads to inefficiency of influenza vaccines.How to timely identify antigenic variants is an important question in influenza surveillance. | Congyu Lu Mi Liu Aiping Wu Yuelong Shu Yousong Peng Taijiao Jiang | 2019 | Science China(Life Sciences)2019，62，3： | 0 |
| 14 | Identification of genome-wide nucleotide sites associated with mammalian virulence in influenza A viruses显示文摘The virulence of influenza viruses is a complex multigenic trait.Previous studies about the virulence determinants of influenza viruses mainly focused on amino acid sites,ignoring the influence of nucleotide mutations.In this study,we collected>200 viral strains from 21 subtypes of influenza A viruses with virulence in mammals and obtained over 100 mammalian virulence-related nucleotide sites across the genome by computational analysis.Fifty of these nucleotide sites only experienced synonymous mutations.Experiments showed that synonymous mutations in three high-scoring nucleotide sites,i.e.,PB1–2031,PB1–633,and PB1–720,enhanced the pathogenicity of the influenza A(H1N1)viruses in mice.Besides,machine-learning models with accepted accuracy for predicting mammalian virulence of influenza A viruses were built.Overall,this study highlighted the importance of nucleotide mutations,especially synonymous mutations in viral virulence,and provided rapid methods for evaluating the virulence of influenza A viruses.It could be helpful for early warning of newly emerging influenza A viruses. | Peng Yousong Zhu Wenfei Feng Zhaomin Zhu Zhaozhong Zhang Zheng Chen Yongkun Liu Suli Wu Aiping Wang Dayan Shu Yuelong Jiang Taijiao | 2020 | Biosafety and Health2020，2，1： | 0 |
| 15 | Development of PREDAC-H1pdm to model the antigenic evolution of influenza A/(H1N1)pdm09 viruses显示文摘The Influenza A(H1N1)pdm09 virus caused a global pandemic in 2009 and has circulated seasonally ever since.As the continual genetic evolution of hemagglutinin in this virus leads to antigenic drift,rapid identification of antigenic variants and characterization of the antigenic evolution are needed.In this study,we developed PREDAC-H1pdm,a model to predict antigenic relationships between H1N1pdm viruses and identify antigenic clusters for post-2009 pandemic H1N1 strains.Our model performed well in predicting antigenic variants,which was helpful in influenza surveillance.By mapping the antigenic clusters for H1N1pdm,we found that substitutions on the Sa epitope were common for H1N1pdm,whereas for the former seasonal H1N1,substitutions on the Sb epitope were more common in antigenic evolution.Additionally,the localized epidemic pattern of H1N1pdm was more obvious than that of the former seasonal H1N1,which could make vaccine recommendation more sophisticated.Overall,the antigenic relationship prediction model we developed provides a rapid determination method for identifying antigenic variants,and the further analysis of evolutionary and epidemic characteristics can facilitate vaccine recommendations and influenza surveillance for H1N1pdm. | Mi Liu Jingze Liu Wenjun Song Yousong Peng Xiao Ding Lizong Deng Taijiao Jiang | 2023 | Virologica Sinica2023，38，4： | 0 |
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