A behavioral model for mapping the genetic architecture of gut-microbiota networks.
Identifieur interne : 000049 ( Main/Exploration ); précédent : 000048; suivant : 000050A behavioral model for mapping the genetic architecture of gut-microbiota networks.
Auteurs : Libo Jiang [République populaire de Chine] ; Xinjuan Liu [République populaire de Chine] ; Xiaoqing He [République populaire de Chine] ; Yi Jin [République populaire de Chine] ; Yige Cao [République populaire de Chine] ; Xiang Zhan [États-Unis] ; Christopher H. Griffin [États-Unis] ; Claudia Gragnoli [États-Unis, Italie] ; Rongling Wu [République populaire de Chine, États-Unis]Source :
- Gut microbes [ 1949-0984 ] ; 2020.
Abstract
The gut microbiota may play an important role in affecting human health. To explore the genetic mechanisms underlying microbiota-host relationships, many genome-wide association studies have begun to identify host genes that shape the microbial composition of the gut. It is becoming increasingly clear that the gut microbiota impacts host processes not only through the action of individual microbes but also their interaction networks. However, a systematic characterization of microbial interactions that occur in densely packed aggregates of the gut bacteria has proven to be extremely difficult. We develop a computational rule of thumb for addressing this issue by integrating ecological behavioral theory and genetic mapping theory. We introduce behavioral ecology theory to derive mathematical descriptors of how each microbe interacts with every other microbe through a web of cooperation and competition. We estimate the emergent properties of gut-microbiota networks reconstructed from these descriptors and map host-driven mutualism, antagonism, aggression, and altruism QTLs. We further integrate path analysis and mapping theory to detect and visualize how host genetic variants affect human diseases by perturbing the internal workings of the gut microbiota. As the proof of concept, we apply our model to analyze a published dataset of the gut microbiota, showing its usefulness and potential to gain new insight into how microbes are organized in human guts. The new model provides an analytical tool for revealing the "endophenotype" role of microbial networks in linking genotype to end-point phenotypes.
DOI: 10.1080/19490976.2020.1820847
PubMed: 33131416
Affiliations:
- Italie, République populaire de Chine, États-Unis
- Latium, Pennsylvanie
- Pékin, Rome, University Park (Pennsylvanie)
- Université d'État de Pennsylvanie
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H. Griffin</name><affiliation wicri:level="4"><nlm:affiliation>Applied Research Laboratory, The Pennsylvania State University, University Park , PA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Applied Research Laboratory, The Pennsylvania State University, University Park , PA</wicri:regionArea><placeName><region type="state">Pennsylvanie</region><settlement type="city">University Park (Pennsylvanie)</settlement></placeName><orgName type="university">Université d'État de Pennsylvanie</orgName></affiliation></author><author><name sortKey="Gragnoli, Claudia" sort="Gragnoli, Claudia" uniqKey="Gragnoli C" first="Claudia" last="Gragnoli">Claudia Gragnoli</name><affiliation wicri:level="2"><nlm:affiliation>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA</wicri:regionArea><placeName><region type="state">Pennsylvanie</region></placeName></affiliation><affiliation wicri:level="2"><nlm:affiliation>Division of Endocrinology, Diabetes, and Metabolic Disease, Translational Medicine, Department of Medicine, Sidney Kimmel Medical College, Thomas Jefferson University , Philadelphia, PA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Division of Endocrinology, Diabetes, and Metabolic Disease, Translational Medicine, Department of Medicine, Sidney Kimmel Medical College, Thomas Jefferson University , Philadelphia, PA</wicri:regionArea><placeName><region type="state">Pennsylvanie</region></placeName></affiliation><affiliation wicri:level="3"><nlm:affiliation>Molecular Biology Laboratory, Bios Biotech Multi Diagnostic Health Center , Rome, Italy.</nlm:affiliation><country xml:lang="fr">Italie</country><wicri:regionArea>Molecular Biology Laboratory, Bios Biotech Multi Diagnostic Health Center , Rome</wicri:regionArea><placeName><settlement type="city">Rome</settlement><region nuts="2">Latium</region></placeName></affiliation></author><author><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name><affiliation wicri:level="3"><nlm:affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation><affiliation wicri:level="3"><nlm:affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</nlm:affiliation><country xml:lang="fr">République populaire de Chine</country><wicri:regionArea>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing</wicri:regionArea><placeName><settlement type="city">Pékin</settlement></placeName></affiliation><affiliation wicri:level="2"><nlm:affiliation>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA, USA.</nlm:affiliation><country xml:lang="fr">États-Unis</country><wicri:regionArea>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA</wicri:regionArea><placeName><region type="state">Pennsylvanie</region></placeName></affiliation></author></analytic><series><title level="j">Gut microbes</title><idno type="eISSN">1949-0984</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 gut microbiota may play an important role in affecting human health. To explore the genetic mechanisms underlying microbiota-host relationships, many genome-wide association studies have begun to identify host genes that shape the microbial composition of the gut. It is becoming increasingly clear that the gut microbiota impacts host processes not only through the action of individual microbes but also their interaction networks. However, a systematic characterization of microbial interactions that occur in densely packed aggregates of the gut bacteria has proven to be extremely difficult. We develop a computational rule of thumb for addressing this issue by integrating ecological behavioral theory and genetic mapping theory. We introduce behavioral ecology theory to derive mathematical descriptors of how each microbe interacts with every other microbe through a web of cooperation and competition. We estimate the emergent properties of gut-microbiota networks reconstructed from these descriptors and map host-driven mutualism, antagonism, aggression, and altruism QTLs. We further integrate path analysis and mapping theory to detect and visualize how host genetic variants affect human diseases by perturbing the internal workings of the gut microbiota. As the proof of concept, we apply our model to analyze a published dataset of the gut microbiota, showing its usefulness and potential to gain new insight into how microbes are organized in human guts. The new model provides an analytical tool for revealing the "endophenotype" role of microbial networks in linking genotype to end-point phenotypes.</div></front></TEI><pubmed><MedlineCitation Status="Publisher" Owner="NLM"><PMID Version="1">33131416</PMID><DateRevised><Year>2020</Year><Month>11</Month><Day>02</Day></DateRevised><Article PubModel="Print-Electronic"><Journal><ISSN IssnType="Electronic">1949-0984</ISSN><JournalIssue CitedMedium="Internet"><PubDate><Year>2020</Year><Month>Nov</Month><Day>01</Day></PubDate></JournalIssue><Title>Gut microbes</Title><ISOAbbreviation>Gut Microbes</ISOAbbreviation></Journal><ArticleTitle>A behavioral model for mapping the genetic architecture of gut-microbiota networks.</ArticleTitle><Pagination><MedlinePgn>1-15</MedlinePgn></Pagination><ELocationID EIdType="doi" ValidYN="Y">10.1080/19490976.2020.1820847</ELocationID><Abstract><AbstractText>The gut microbiota may play an important role in affecting human health. To explore the genetic mechanisms underlying microbiota-host relationships, many genome-wide association studies have begun to identify host genes that shape the microbial composition of the gut. It is becoming increasingly clear that the gut microbiota impacts host processes not only through the action of individual microbes but also their interaction networks. However, a systematic characterization of microbial interactions that occur in densely packed aggregates of the gut bacteria has proven to be extremely difficult. We develop a computational rule of thumb for addressing this issue by integrating ecological behavioral theory and genetic mapping theory. We introduce behavioral ecology theory to derive mathematical descriptors of how each microbe interacts with every other microbe through a web of cooperation and competition. We estimate the emergent properties of gut-microbiota networks reconstructed from these descriptors and map host-driven mutualism, antagonism, aggression, and altruism QTLs. We further integrate path analysis and mapping theory to detect and visualize how host genetic variants affect human diseases by perturbing the internal workings of the gut microbiota. As the proof of concept, we apply our model to analyze a published dataset of the gut microbiota, showing its usefulness and potential to gain new insight into how microbes are organized in human guts. The new model provides an analytical tool for revealing the "endophenotype" role of microbial networks in linking genotype to end-point phenotypes.</AbstractText></Abstract><AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Jiang</LastName><ForeName>Libo</ForeName><Initials>L</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Liu</LastName><ForeName>Xinjuan</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Gastroenterology, Beijing Chao-Yang Hospital, Capital Medical University , Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>He</LastName><ForeName>Xiaoqing</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Jin</LastName><ForeName>Yi</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Cao</LastName><ForeName>Yige</ForeName><Initials>Y</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Zhan</LastName><ForeName>Xiang</ForeName><Initials>X</Initials><AffiliationInfo><Affiliation>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Griffin</LastName><ForeName>Christopher H</ForeName><Initials>CH</Initials><AffiliationInfo><Affiliation>Applied Research Laboratory, The Pennsylvania State University, University Park , PA, USA.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Gragnoli</LastName><ForeName>Claudia</ForeName><Initials>C</Initials><AffiliationInfo><Affiliation>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Division of Endocrinology, Diabetes, and Metabolic Disease, Translational Medicine, Department of Medicine, Sidney Kimmel Medical College, Thomas Jefferson University , Philadelphia, PA, USA.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Molecular Biology Laboratory, Bios Biotech Multi Diagnostic Health Center , Rome, Italy.</Affiliation></AffiliationInfo></Author><Author ValidYN="Y"><LastName>Wu</LastName><ForeName>Rongling</ForeName><Initials>R</Initials><AffiliationInfo><Affiliation>Beijing Advanced Innovation Center for Tree Breeding by Molecular Design, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Center for Computational Biology, College of Biological Sciences and Technology, Beijing Forestry University , Beijing, China.</Affiliation></AffiliationInfo><AffiliationInfo><Affiliation>Department of Public Health Sciences, Penn State College of Medicine , Hershey, PA, USA.</Affiliation></AffiliationInfo></Author></AuthorList><Language>eng</Language><PublicationTypeList><PublicationType UI="D016428">Journal Article</PublicationType></PublicationTypeList><ArticleDate DateType="Electronic"><Year>2020</Year><Month>11</Month><Day>01</Day></ArticleDate></Article><MedlineJournalInfo><Country>United States</Country><MedlineTA>Gut Microbes</MedlineTA><NlmUniqueID>101495343</NlmUniqueID><ISSNLinking>1949-0976</ISSNLinking></MedlineJournalInfo><CitationSubset>IM</CitationSubset><KeywordList Owner="NOTNLM"><Keyword MajorTopicYN="N">The gut microbiota</Keyword><Keyword MajorTopicYN="N">competition</Keyword><Keyword MajorTopicYN="N">cooperation</Keyword><Keyword MajorTopicYN="N">network science</Keyword><Keyword MajorTopicYN="N">qtl</Keyword><Keyword MajorTopicYN="N">rule of thumb</Keyword></KeywordList></MedlineCitation><PubmedData><History><PubMedPubDate PubStatus="entrez"><Year>2020</Year><Month>11</Month><Day>2</Day><Hour>5</Hour><Minute>32</Minute></PubMedPubDate><PubMedPubDate PubStatus="pubmed"><Year>2020</Year><Month>11</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate><PubMedPubDate PubStatus="medline"><Year>2020</Year><Month>11</Month><Day>3</Day><Hour>6</Hour><Minute>0</Minute></PubMedPubDate></History><PublicationStatus>aheadofprint</PublicationStatus><ArticleIdList><ArticleId IdType="pubmed">33131416</ArticleId><ArticleId IdType="doi">10.1080/19490976.2020.1820847</ArticleId></ArticleIdList></PubmedData></pubmed><affiliations><list><country><li>Italie</li><li>République populaire de Chine</li><li>États-Unis</li></country><region><li>Latium</li><li>Pennsylvanie</li></region><settlement><li>Pékin</li><li>Rome</li><li>University Park (Pennsylvanie)</li></settlement><orgName><li>Université d'État de Pennsylvanie</li></orgName></list><tree><country name="République populaire de Chine"><noRegion><name sortKey="Jiang, Libo" sort="Jiang, Libo" uniqKey="Jiang L" first="Libo" last="Jiang">Libo Jiang</name></noRegion><name sortKey="Cao, Yige" sort="Cao, Yige" uniqKey="Cao Y" first="Yige" last="Cao">Yige Cao</name><name sortKey="Cao, Yige" sort="Cao, Yige" uniqKey="Cao Y" first="Yige" last="Cao">Yige Cao</name><name sortKey="He, Xiaoqing" sort="He, Xiaoqing" uniqKey="He X" first="Xiaoqing" last="He">Xiaoqing He</name><name sortKey="He, Xiaoqing" sort="He, Xiaoqing" uniqKey="He X" first="Xiaoqing" last="He">Xiaoqing He</name><name sortKey="Jiang, Libo" sort="Jiang, Libo" uniqKey="Jiang L" first="Libo" last="Jiang">Libo Jiang</name><name sortKey="Jin, Yi" sort="Jin, Yi" uniqKey="Jin Y" first="Yi" last="Jin">Yi Jin</name><name sortKey="Jin, Yi" sort="Jin, Yi" uniqKey="Jin Y" first="Yi" last="Jin">Yi Jin</name><name sortKey="Liu, Xinjuan" sort="Liu, Xinjuan" uniqKey="Liu X" first="Xinjuan" last="Liu">Xinjuan Liu</name><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name></country><country name="États-Unis"><region name="Pennsylvanie"><name sortKey="Zhan, Xiang" sort="Zhan, Xiang" uniqKey="Zhan X" first="Xiang" last="Zhan">Xiang Zhan</name></region><name sortKey="Gragnoli, Claudia" sort="Gragnoli, Claudia" uniqKey="Gragnoli C" first="Claudia" last="Gragnoli">Claudia Gragnoli</name><name sortKey="Gragnoli, Claudia" sort="Gragnoli, Claudia" uniqKey="Gragnoli C" first="Claudia" last="Gragnoli">Claudia Gragnoli</name><name sortKey="Griffin, Christopher H" sort="Griffin, Christopher H" uniqKey="Griffin C" first="Christopher H" last="Griffin">Christopher H. Griffin</name><name sortKey="Wu, Rongling" sort="Wu, Rongling" uniqKey="Wu R" first="Rongling" last="Wu">Rongling Wu</name></country><country name="Italie"><region name="Latium"><name sortKey="Gragnoli, Claudia" sort="Gragnoli, Claudia" uniqKey="Gragnoli C" first="Claudia" last="Gragnoli">Claudia Gragnoli</name></region></country></tree></affiliations></record>Pour manipuler ce document sous Unix (Dilib)
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