In silico prediction of host-pathogen protein interactions in melioidosis pathogen Burkholderia pseudomallei and human reveals novel virulence factors and their targets.
Identifieur interne : 000132 ( Main/Exploration ); précédent : 000131; suivant : 000133In silico prediction of host-pathogen protein interactions in melioidosis pathogen Burkholderia pseudomallei and human reveals novel virulence factors and their targets.
Auteurs : Cristian D. Loaiza [États-Unis] ; Naveen Duhan [États-Unis] ; Matthew Lister [États-Unis] ; Rakesh Kaundal [États-Unis]Source :
- Briefings in bioinformatics [ 1477-4054 ] ; 2020.
Abstract
The aerobic, Gram-negative motile bacillus, Burkholderia pseudomallei is a facultative intracellular bacterium causing melioidosis, a critical disease of public health importance, which is widely endemic in the tropics and subtropical regions of the world. Melioidosis is associated with high case fatality rates in animals and humans; even with treatment, its mortality is 20-50%. It also infects plants and is designated as a biothreat agent. B. pseudomallei is pathogenic due to its ability to invade, resist factors in serum and survive intracellularly. Despite its importance, to date only a few effector proteins have been functionally characterized, and there is not much information regarding the host-pathogen protein-protein interactions (PPI) of this system, which are important to studying infection mechanisms and thereby develop prevention measures. We explored two computational approaches, the homology-based interolog and the domain-based method, to predict genome-scale host-pathogen interactions (HPIs) between two different strains of B. pseudomallei (prototypical, and highly virulent) and human. In total, 76 335 common HPIs (between the two strains) were predicted involving 8264 human and 1753 B. pseudomallei proteins. Among the unique PPIs, 14 131 non-redundant HPIs were found to be unique between the prototypical strain and human, compared to 3043 non-redundant HPIs between the highly virulent strain and human. The protein hubs analysis showed that most B. pseudomallei proteins formed a hub with human dnaK complex proteins associated with tuberculosis, a disease similar in symptoms to melioidosis. In addition, drug-binding and carbohydrate-binding mechanisms were found overrepresented within the host-pathogen network, and metabolic pathways were frequently activated according to the pathway enrichment. Subcellular localization analysis showed that most of the pathogen proteins are targeting human proteins inside cytoplasm and nucleus. We also discovered the host targets of the drug-related pathogen proteins and proteins that form T3SS and T6SS in B. pseudomallei. Additionally, a comparison between the unique PPI patterns present in the prototypical and highly virulent strains was performed. The current study is the first report on developing a genome-scale host-pathogen protein interaction networks between the human and B. pseudomallei, a critical biothreat agent. We have identified novel virulence factors and their interacting partners in the human proteome. These PPIs can be further validated by high-throughput experiments and may give new insights on how B. pseudomallei interacts with its host, which will help medical researchers in developing better prevention measures.
DOI: 10.1093/bib/bbz162
PubMed: 32444871
Affiliations:
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Loaiza</name><affiliation wicri:level="1"><nlm:affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Duhan, Naveen" sort="Duhan, Naveen" uniqKey="Duhan N" first="Naveen" last="Duhan">Naveen Duhan</name><affiliation wicri:level="1"><nlm:affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Lister, Matthew" sort="Lister, Matthew" uniqKey="Lister M" first="Matthew" last="Lister">Matthew Lister</name><affiliation wicri:level="1"><nlm:affiliation>Bioinformatics Facility, Center for Integrated BioSystems, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics Facility, Center for Integrated BioSystems, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Kaundal, Rakesh" sort="Kaundal, Rakesh" uniqKey="Kaundal R" first="Rakesh" last="Kaundal">Rakesh Kaundal</name><affiliation wicri:level="2"><nlm:affiliation>Department of Plants, Soils, and Climate/Center for Integrated BioSystems, College of Agriculture and Applied Sciences, Utah State University, Logan, UT 84322 USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Utah</region></placeName><wicri:cityArea>Department of Plants, Soils, and Climate/Center for Integrated BioSystems, College of Agriculture and Applied Sciences, Utah State University, Logan</wicri:cityArea></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">PubMed</idno><date when="2020">2020</date><idno type="RBID">pubmed:32444871</idno><idno type="pmid">32444871</idno><idno type="doi">10.1093/bib/bbz162</idno><idno type="wicri:Area/Main/Corpus">000249</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Corpus" wicri:corpus="PubMed">000249</idno><idno type="wicri:Area/Main/Curation">000249</idno><idno type="wicri:explorRef" wicri:stream="Main" wicri:step="Curation">000249</idno><idno type="wicri:Area/Main/Exploration">000249</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">In silico prediction of host-pathogen protein interactions in melioidosis pathogen Burkholderia pseudomallei and human reveals novel virulence factors and their targets.</title><author><name sortKey="Loaiza, Cristian D" sort="Loaiza, Cristian D" uniqKey="Loaiza C" first="Cristian D" last="Loaiza">Cristian D. Loaiza</name><affiliation wicri:level="1"><nlm:affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Duhan, Naveen" sort="Duhan, Naveen" uniqKey="Duhan N" first="Naveen" last="Duhan">Naveen Duhan</name><affiliation wicri:level="1"><nlm:affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Lister, Matthew" sort="Lister, Matthew" uniqKey="Lister M" first="Matthew" last="Lister">Matthew Lister</name><affiliation wicri:level="1"><nlm:affiliation>Bioinformatics Facility, Center for Integrated BioSystems, Utah State University, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Bioinformatics Facility, Center for Integrated BioSystems, Utah State University</wicri:regionArea><wicri:noRegion>Utah State University</wicri:noRegion></affiliation></author><author><name sortKey="Kaundal, Rakesh" sort="Kaundal, Rakesh" uniqKey="Kaundal R" first="Rakesh" last="Kaundal">Rakesh Kaundal</name><affiliation wicri:level="2"><nlm:affiliation>Department of Plants, Soils, and Climate/Center for Integrated BioSystems, College of Agriculture and Applied Sciences, Utah State University, Logan, UT 84322 USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><placeName><region type="state">Utah</region></placeName><wicri:cityArea>Department of Plants, Soils, and Climate/Center for Integrated BioSystems, College of Agriculture and Applied Sciences, Utah State University, Logan</wicri:cityArea></affiliation></author></analytic><series><title level="j">Briefings in bioinformatics</title><idno type="eISSN">1477-4054</idno><imprint><date when="2020" type="published">2020</date></imprint></series></biblStruct></sourceDesc></fileDesc><profileDesc><textClass></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">The aerobic, Gram-negative motile bacillus, Burkholderia pseudomallei is a facultative intracellular bacterium causing melioidosis, a critical disease of public health importance, which is widely endemic in the tropics and subtropical regions of the world. Melioidosis is associated with high case fatality rates in animals and humans; even with treatment, its mortality is 20-50%. It also infects plants and is designated as a biothreat agent. B. pseudomallei is pathogenic due to its ability to invade, resist factors in serum and survive intracellularly. Despite its importance, to date only a few effector proteins have been functionally characterized, and there is not much information regarding the host-pathogen protein-protein interactions (PPI) of this system, which are important to studying infection mechanisms and thereby develop prevention measures. We explored two computational approaches, the homology-based interolog and the domain-based method, to predict genome-scale host-pathogen interactions (HPIs) between two different strains of B. pseudomallei (prototypical, and highly virulent) and human. In total, 76 335 common HPIs (between the two strains) were predicted involving 8264 human and 1753 B. pseudomallei proteins. Among the unique PPIs, 14 131 non-redundant HPIs were found to be unique between the prototypical strain and human, compared to 3043 non-redundant HPIs between the highly virulent strain and human. The protein hubs analysis showed that most B. pseudomallei proteins formed a hub with human dnaK complex proteins associated with tuberculosis, a disease similar in symptoms to melioidosis. In addition, drug-binding and carbohydrate-binding mechanisms were found overrepresented within the host-pathogen network, and metabolic pathways were frequently activated according to the pathway enrichment. Subcellular localization analysis showed that most of the pathogen proteins are targeting human proteins inside cytoplasm and nucleus. We also discovered the host targets of the drug-related pathogen proteins and proteins that form T3SS and T6SS in B. pseudomallei. Additionally, a comparison between the unique PPI patterns present in the prototypical and highly virulent strains was performed. The current study is the first report on developing a genome-scale host-pathogen protein interaction networks between the human and B. pseudomallei, a critical biothreat agent. We have identified novel virulence factors and their interacting partners in the human proteome. These PPIs can be further validated by high-throughput experiments and may give new insights on how B. pseudomallei interacts with its host, which will help medical researchers in developing better prevention measures.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">32444871</PMID><DateRevised><Year>2020</Year><Month>05</Month><Day>23</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1477-4054</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>May</Month><Day>23</Day></PubDate></JournalIssue><Title>Briefings in bioinformatics</Title><ISOAbbreviation>Brief Bioinform</ISOAbbreviation></Journal><ArticleTitle>In silico prediction of host-pathogen protein interactions in melioidosis pathogen Burkholderia pseudomallei and human reveals novel virulence factors and their targets.</ArticleTitle><ELocationID EIdType="pii" ValidYN="Y">bbz162</ELocationID><ELocationID EIdType="doi" ValidYN="Y">10.1093/bib/bbz162</ELocationID><Abstract><AbstractText>The aerobic, Gram-negative motile bacillus, Burkholderia pseudomallei is a facultative intracellular bacterium causing melioidosis, a critical disease of public health importance, which is widely endemic in the tropics and subtropical regions of the world. Melioidosis is associated with high case fatality rates in animals and humans; even with treatment, its mortality is 20-50%. It also infects plants and is designated as a biothreat agent. B. pseudomallei is pathogenic due to its ability to invade, resist factors in serum and survive intracellularly. Despite its importance, to date only a few effector proteins have been functionally characterized, and there is not much information regarding the host-pathogen protein-protein interactions (PPI) of this system, which are important to studying infection mechanisms and thereby develop prevention measures. We explored two computational approaches, the homology-based interolog and the domain-based method, to predict genome-scale host-pathogen interactions (HPIs) between two different strains of B. pseudomallei (prototypical, and highly virulent) and human. In total, 76 335 common HPIs (between the two strains) were predicted involving 8264 human and 1753 B. pseudomallei proteins. Among the unique PPIs, 14 131 non-redundant HPIs were found to be unique between the prototypical strain and human, compared to 3043 non-redundant HPIs between the highly virulent strain and human. The protein hubs analysis showed that most B. pseudomallei proteins formed a hub with human dnaK complex proteins associated with tuberculosis, a disease similar in symptoms to melioidosis. In addition, drug-binding and carbohydrate-binding mechanisms were found overrepresented within the host-pathogen network, and metabolic pathways were frequently activated according to the pathway enrichment. Subcellular localization analysis showed that most of the pathogen proteins are targeting human proteins inside cytoplasm and nucleus. We also discovered the host targets of the drug-related pathogen proteins and proteins that form T3SS and T6SS in B. pseudomallei. Additionally, a comparison between the unique PPI patterns present in the prototypical and highly virulent strains was performed. The current study is the first report on developing a genome-scale host-pathogen protein interaction networks between the human and B. pseudomallei, a critical biothreat agent. We have identified novel virulence factors and their interacting partners in the human proteome. These PPIs can be further validated by high-throughput experiments and may give new insights on how B. pseudomallei interacts with its host, which will help medical researchers in developing better prevention measures.</AbstractText><CopyrightInformation>© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.</CopyrightInformation></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Loaiza</LastName><ForeName>Cristian D</ForeName><Initials>CD</Initials><AffiliationInfo><Affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Duhan</LastName><ForeName>Naveen</ForeName><Initials>N</Initials><AffiliationInfo><Affiliation>Center for Integrated BioSystems/Department of Plants, Soils, and Climate, College of Agriculture and Applied Sciences, Utah State University, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Lister</LastName><ForeName>Matthew</ForeName><Initials>M</Initials><AffiliationInfo><Affiliation>Bioinformatics Facility, Center for Integrated BioSystems, Utah State University, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Kaundal</LastName><ForeName>Rakesh</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Department of Plants, Soils, and Climate/Center for Integrated BioSystems, College of Agriculture and Applied Sciences, Utah State University, Logan, UT 84322 USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>05</Month><Day>23</Day></ArticleDate></Article><MedlineJournalInfo><Country>England</Country><MedlineTA>Brief Bioinform</MedlineTA><NlmUniqueID>100912837</NlmUniqueID><ISSNLinking>1467-5463</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">Burkholderia pseudomallei
</Keyword><Keyword MajorTopicYN="N">Homo sapiens
</Keyword><Keyword MajorTopicYN="N">domain–domain interactions</Keyword><Keyword MajorTopicYN="N">host–pathogen interactions</Keyword><Keyword MajorTopicYN="N">interolog</Keyword><Keyword MajorTopicYN="N">melioidosis</Keyword><Keyword MajorTopicYN="N">networks</Keyword><Keyword MajorTopicYN="N">visualization</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="received"><Year>2019</Year><Month>06</Month><Day>12</Day></PubMedPubDate><PubMedPubDate PubStatus="revised"><Year>2019</Year><Month>11</Month><Day>13</Day></PubMedPubDate><PubMedPubDate PubStatus="accepted"><Year>2019</Year><Month>11</Month><Day>20</Day></PubMedPubDate><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>5</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>5</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>5</Month><Day>24</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">32444871</ArticleId><ArticleId IdType="pii">5842243</ArticleId><ArticleId IdType="doi">10.1093/bib/bbz162</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>États-Unis</li></country><region><li>Utah</li></region></list><tree><country name="États-Unis"><noRegion><name sortKey="Loaiza, Cristian D" sort="Loaiza, Cristian D" uniqKey="Loaiza C" first="Cristian D" last="Loaiza">Cristian D. Loaiza</name></noRegion><name sortKey="Duhan, Naveen" sort="Duhan, Naveen" uniqKey="Duhan N" first="Naveen" last="Duhan">Naveen Duhan</name><name sortKey="Kaundal, Rakesh" sort="Kaundal, Rakesh" uniqKey="Kaundal R" first="Rakesh" last="Kaundal">Rakesh Kaundal</name><name sortKey="Lister, Matthew" sort="Lister, Matthew" uniqKey="Lister M" first="Matthew" last="Lister">Matthew Lister</name></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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