Dear Editor,Influenza viruses cause significant mortality and morbidity in humans.Vaccination is currently the most effective way to combat the virus(Perofsky and Nelson,2020).Unfortunately,the influenza virus frequen...Dear Editor,Influenza viruses cause significant mortality and morbidity in humans.Vaccination is currently the most effective way to combat the virus(Perofsky and Nelson,2020).Unfortunately,the influenza virus frequently changes its antigenicity through rapid mutations,leading to decreased vaccine efficacy or even failure.To improve vaccine effectiveness,it is necessary to monitor antigenic variation and update vaccine strains when significant antigenic variation occurs(Perofsky and Nelson,2020;Malik et al.,2024).展开更多
During the final proofing stage of the paper,the wrong version of Fig.2 was accidently used when replacing it with a high-resolution version.The star and circle marks were missing in the published version.
The virus receptors are key for the viral infection of host cells.Identification of the virus receptors is still challenging at present.Our previous study has shown that human virus receptor proteins have some unique ...The virus receptors are key for the viral infection of host cells.Identification of the virus receptors is still challenging at present.Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level,high number of interaction partners and high expression level.Here,a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences.A total of 1424 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome.In addition,the combination of the random-forest model with protein–protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses,such as the enterovirus,norovirus and West Nile virus.Finally,the candidate alternative receptors of the SARS-Co V-2 were also predicted in this study.As far as we know,this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.展开更多
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 viru...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.展开更多
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 prot...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.展开更多
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 identificatio...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.展开更多
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 （H...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 and about 250000 to 500000 deaths worldwide （WHO, 2014）. Vaccination is currently the most effective way to fight against it. Due to the frequent mutations on the HA protein, the virus often changes its antigen, which may lead to the ineffectiveness of the influenza vaccines （Carrat and Flahault, 2007; Taubenberger and Kash, 2010）.展开更多
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),do...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).展开更多
In recent years,substantial advancements have been achieved in understanding the diversity of the human virome and its intricate roles in human health and diseases.Despite this progress,the field of human virome resea...In recent years,substantial advancements have been achieved in understanding the diversity of the human virome and its intricate roles in human health and diseases.Despite this progress,the field of human virome research remains nascent,primarily hindered by the lack of effective methods,particularly in the domain of computational tools.This perspective systematically outlines ten computational challenges spanning various types of virome studies.These challenges arise due to the vast diversity of viromes,the absence of a universal marker gene in viral genomes,the low abundance of virus populations,the remote or minimal homology of viral proteins to known proteins,and the highly dynamic and heterogeneous nature of viromes.For each computational challenge,we discuss the underlying reasons,current research progress,and potential solutions.The resolution of these challenges necessitates ongoing collaboration among computational scientists,virologists,and multidisciplinary experts.In essence,this perspective serves as a comprehensive guide for directing computational efforts in human virome studies.展开更多
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 ...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展开更多
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 a...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://www.biomedcloud.com.cn/GlyoCell/main.htm. It could be useful for investigating the cell-specific O-glycosylation in human.展开更多
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 imm...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.展开更多
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 addr...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.展开更多
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 t...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.展开更多
Integrin genes are widely involved in tumorigenesis.Yet,a comprehensive characterization of integrin family members and their interactome at the pan-cancer level is lacking.Here,we systematically analyzed integrin fam...Integrin genes are widely involved in tumorigenesis.Yet,a comprehensive characterization of integrin family members and their interactome at the pan-cancer level is lacking.Here,we systematically analyzed integrin family in approximately 10,000 tumors across 32 cancer types.Globally,integrins represent a frequently altered and misexpressed pathway,with alteration and dysregulation overall being protumorigenic.Expression dysregulation,better than mutational landscape,of integrin family successfully identifies a subgroup of aggressive tumors with a high level of proliferation and stemness.The results reveal that several molecular mechanisms collectively regulate integrin expression in a context-dependent manner.For potential clinical usage,we constructed a weighted scoring system,integrinScore,to measure integrin signaling patterns in individual tumors.Remarkably,integrinScore was consistently correlated with predefined molecular subtypes in multiple cancers,with integrinScore-high tumors being more aggressive.Importantly,integrinScore was cancer-dependent and closely associated with proliferation,stemness,tumor microenvironment,metastasis,and immune signatures.IntegrinScore also predicted patients’response to immunotherapy.By mining drug databases,we unraveled an array of compounds that may modulate integrin signaling.Finally,we built a userfriendly database,Pan-cancer Integrin Explorer(PIExplorer;http://computationalbiology.cn/PIExplorer),to facilitate researchers to explore integrin-related knowledge.Collectively,we provide a comprehensive characterization of integrins across cancers and offer gene-specific and cancer-specific rationales for developing integrin-targeted therapy.展开更多
Vaccination is currently the most effective way to protect against influenza viruses.This study presents PREDAC(PRE-Dict Antigenic Cluster),a sequence-based computational method to model antigenic clusters of influenz...Vaccination is currently the most effective way to protect against influenza viruses.This study presents PREDAC(PRE-Dict Antigenic Cluster),a sequence-based computational method to model antigenic clusters of influenza viruses.PREDAC could improve vaccine recommendations for influenza viruses and has been used to support the influenza vaccine strain recommendations at the Chinese National Influenza Center.Moreover,a PREDAC server which includes tools for the prediction of antigenic variants and antigenic clusters of both influenza A and B viruses was built and made publicly available at http://www.computationalbiology.cn/home/.PREDAC could not only facilitate systematic studies of the antigenic evolution of influenza viruses but also provide user-friendly tools for vaccine strain recommendations for influenza viruses.展开更多
基金upported by the Major Project of Guangzhou National Laboratory(GZNL2024A01002)National Key Plan for Scientific Research and Development of China(2022YFC2303802)+1 种基金National Natural Science Foundation of China(32170651&32370700)Hunan Provincial Natural Science Foundation of China(2024JJ2015).
文摘Dear Editor,Influenza viruses cause significant mortality and morbidity in humans.Vaccination is currently the most effective way to combat the virus(Perofsky and Nelson,2020).Unfortunately,the influenza virus frequently changes its antigenicity through rapid mutations,leading to decreased vaccine efficacy or even failure.To improve vaccine effectiveness,it is necessary to monitor antigenic variation and update vaccine strains when significant antigenic variation occurs(Perofsky and Nelson,2020;Malik et al.,2024).
文摘During the final proofing stage of the paper,the wrong version of Fig.2 was accidently used when replacing it with a high-resolution version.The star and circle marks were missing in the published version.
基金supported by the National Key Plan for Scientific Research and Development of China(2016YFD0500300)Hunan Provincial Natural Science Foundation of China(2018JJ3039)+1 种基金the Chinese Academy of Medical Sciences(2016-I2M-1-005)the special project for COVID-19 of Guangzhou Regenerative Medicine and Health Guangdong Laboratory(2020GZR110406001)
文摘The virus receptors are key for the viral infection of host cells.Identification of the virus receptors is still challenging at present.Our previous study has shown that human virus receptor proteins have some unique features including high N-glycosylation level,high number of interaction partners and high expression level.Here,a random-forest model was built to identify human virus receptorome from human cell membrane proteins with an accepted accuracy based on the combination of the unique features of human virus receptors and protein sequences.A total of 1424 human cell membrane proteins were predicted to constitute the receptorome of the human-infecting virome.In addition,the combination of the random-forest model with protein–protein interactions between human and viruses predicted in previous studies enabled further prediction of the receptors for 693 human-infecting viruses,such as the enterovirus,norovirus and West Nile virus.Finally,the candidate alternative receptors of the SARS-Co V-2 were also predicted in this study.As far as we know,this study is the first attempt to predict the receptorome for the human-infecting virome and would greatly facilitate the identification of the receptors for viruses.
基金This work was supported by the National Natural Science Foundation of China(31801101 to X.D.,31671371,32070678 to T.J.)the CAMS Initiative for Innovative Medicine(CAMS-I2M,2016-I2M-1-005,2020-I2M-2-003 to T.J.)。
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.
基金supported by the National Key Plan for Scientific Research and Development of China(2016YFD0500300)National Natural Science Foundation of China(32170651)Hunan Provincial Natural Science Foundation of China(2020JJ3006)。
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.
基金funded by the National Natural Science Foundation of China (32070678)the National Key Research and Development Program of China (2021YFC2302001).
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.
基金supported by the National Natural Science Foundation(31500126 and 31371338)National Key Plan for Scientific Research and Development of China(2016YFD0500300 and 2016YFC1200200)the Young Teacher’s Development Plan of Hunan University to YS(531107040720)
文摘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 and about 250000 to 500000 deaths worldwide （WHO, 2014）. Vaccination is currently the most effective way to fight against it. Due to the frequent mutations on the HA protein, the virus often changes its antigen, which may lead to the ineffectiveness of the influenza vaccines （Carrat and Flahault, 2007; Taubenberger and Kash, 2010）.
基金supported by the National Key Plan for Scientific Research and Development of China(2016YFD0500300)Hunan Provincial Natural Science Foundation of China(2020JJ3006)。
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).
基金supported by National Natural Science Foundation of China(32170651&32370700).
文摘In recent years,substantial advancements have been achieved in understanding the diversity of the human virome and its intricate roles in human health and diseases.Despite this progress,the field of human virome research remains nascent,primarily hindered by the lack of effective methods,particularly in the domain of computational tools.This perspective systematically outlines ten computational challenges spanning various types of virome studies.These challenges arise due to the vast diversity of viromes,the absence of a universal marker gene in viral genomes,the low abundance of virus populations,the remote or minimal homology of viral proteins to known proteins,and the highly dynamic and heterogeneous nature of viromes.For each computational challenge,we discuss the underlying reasons,current research progress,and potential solutions.The resolution of these challenges necessitates ongoing collaboration among computational scientists,virologists,and multidisciplinary experts.In essence,this perspective serves as a comprehensive guide for directing computational efforts in human virome studies.
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
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://www.biomedcloud.com.cn/GlyoCell/main.htm. It could be useful for investigating the cell-specific O-glycosylation in human.
基金the National Natural Science Foundation of China(NSFC-31871396,31571444,31400232,and 31672012)the Young Elite Scientist Sponsorship Program from CAST(YESS20160001)the Science and Technology Inn ovation Project of Chinese Academy of Agricultural Sciences(2060302-51).
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.
基金This work was supported by the Hunan Provin-cial Natural Science Foundation of China(2020JJ3006,2019JJ20004)the National Natural Science Founda-tion of China(32170651)。
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.
基金supported by the National Key Plan for Scientific Research and Development of China (2016YFC1200200 and 2016YFD0500300)the National Natural Science Foundation of China (31500126 and 31671371)+1 种基金the Chinese Academy of Medical Sciences (2016-I2M-1-005the Fundamental Research Funds for the Central Universities of China
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.
基金supported by grants from the National Natural Science Foundation of China(Grant No.81972418 to Dingxiao Zhang)the Hunan Provincial Science Fund for Distinguished Young Scholars(Grant No.2021JJ10028 to Dingxiao Zhang)+5 种基金the Shenzhen Natural Science Foundation(Grant No.JCYJ20220530160410024 to Dingxiao Zhang)and the Fundamental Research Funds for the Central Universities(Dingxiao Zhang)the Natural Science Foundation of Hunan Province(Grant No.2022JJ40111 to Cheng Zou)the Changsha Municipal Natural Science Foundation(Grant No.KQ2202182 to Cheng ZouGrant No.KQ2202154 to Jiangling Xiong)the China Postdoctoral Science Foundation(Grant No.2022M721100 to Jiangling Xiong).
文摘Integrin genes are widely involved in tumorigenesis.Yet,a comprehensive characterization of integrin family members and their interactome at the pan-cancer level is lacking.Here,we systematically analyzed integrin family in approximately 10,000 tumors across 32 cancer types.Globally,integrins represent a frequently altered and misexpressed pathway,with alteration and dysregulation overall being protumorigenic.Expression dysregulation,better than mutational landscape,of integrin family successfully identifies a subgroup of aggressive tumors with a high level of proliferation and stemness.The results reveal that several molecular mechanisms collectively regulate integrin expression in a context-dependent manner.For potential clinical usage,we constructed a weighted scoring system,integrinScore,to measure integrin signaling patterns in individual tumors.Remarkably,integrinScore was consistently correlated with predefined molecular subtypes in multiple cancers,with integrinScore-high tumors being more aggressive.Importantly,integrinScore was cancer-dependent and closely associated with proliferation,stemness,tumor microenvironment,metastasis,and immune signatures.IntegrinScore also predicted patients’response to immunotherapy.By mining drug databases,we unraveled an array of compounds that may modulate integrin signaling.Finally,we built a userfriendly database,Pan-cancer Integrin Explorer(PIExplorer;http://computationalbiology.cn/PIExplorer),to facilitate researchers to explore integrin-related knowledge.Collectively,we provide a comprehensive characterization of integrins across cancers and offer gene-specific and cancer-specific rationales for developing integrin-targeted therapy.
基金supported by the Chinese Academy of Medical Sciences(2016-I2M-1-005)the National Key Research and Development of China(2016YFD0500300 and 2016YFC1200200)the National Natural Science Foundation of China(31671371).
文摘Vaccination is currently the most effective way to protect against influenza viruses.This study presents PREDAC(PRE-Dict Antigenic Cluster),a sequence-based computational method to model antigenic clusters of influenza viruses.PREDAC could improve vaccine recommendations for influenza viruses and has been used to support the influenza vaccine strain recommendations at the Chinese National Influenza Center.Moreover,a PREDAC server which includes tools for the prediction of antigenic variants and antigenic clusters of both influenza A and B viruses was built and made publicly available at http://www.computationalbiology.cn/home/.PREDAC could not only facilitate systematic studies of the antigenic evolution of influenza viruses but also provide user-friendly tools for vaccine strain recommendations for influenza viruses.
