A Mathematical Model for the Reciprocal Differentiation of T Helper 17 Cells and Induced Regulatory T Cells

dc.contributor.authorHong, Tianen
dc.contributor.authorXing, Jianhuaen
dc.contributor.authorLi, Liwuen
dc.contributor.authorTyson, John J.en
dc.contributor.departmentBiological Sciencesen
dc.date.accessioned2016-12-09T21:36:44Zen
dc.date.available2016-12-09T21:36:44Zen
dc.date.issued2011-07-01en
dc.description.abstractThe reciprocal differentiation of T helper 17 (T<sub<>H</sub>17) cells and induced regulatory T (iT<sub>reg</sub>) cells plays a critical role in both the pathogenesis and resolution of diverse human inflammatory diseases. Although initial studies suggested a stable commitment to either the T<sub>H</sub>17 or the iT<sub>reg</sub> lineage, recent results reveal remarkable plasticity and heterogeneity, reflected in the capacity of differentiated effectors cells to be reprogrammed among T<sub>H</sub>17 and iT<sub>reg</sub> lineages and the intriguing phenomenon that a group of naive precursor CD4<sup>+</sup> T cells can be programmed into phenotypically diverse populations by the same differentiation signal, transforming growth factor beta. To reconcile these observations, we have built a mathematical model of T<sub>H</sub>17/iT<sub>reg</sub> differentiation that exhibits four different stable steady states, governed by pitchfork bifurcations with certain degrees of broken symmetry. According to the model, a group of precursor cells with some small cell-to-cell variability can differentiate into phenotypically distinct subsets of cells, which exhibit distinct levels of the master transcription-factor regulators for the two T cell lineages. A dynamical control system with these properties is flexible enough to be steered down alternative pathways by polarizing signals, such as interleukin-6 and retinoic acid and it may be used by the immune system to generate functionally distinct effector cells in desired fractions in response to a range of differentiation signals. Additionally, the model suggests a quantitative explanation for the phenotype with high expression levels of both master regulators. This phenotype corresponds to a re-stabilized co-expressing state, appearing at a late stage of differentiation, rather than a bipotent precursor state observed under some other circumstances. Our simulations reconcile most published experimental observations and predict novel differentiation states as well as transitions among different phenotypes that have not yet been observed experimentally.en
dc.description.versionPublished versionen
dc.format.extent13 pagesen
dc.format.mimetypeapplication/pdfen
dc.identifier.doihttps://doi.org/10.1371/journal.pcbi.1002122en
dc.identifier.issn1553-734Xen
dc.identifier.issue7en
dc.identifier.urihttp://hdl.handle.net/10919/73636en
dc.identifier.volume7en
dc.language.isoenen
dc.publisherPLOSen
dc.relation.urihttp://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000293333200024&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=930d57c9ac61a043676db62af60056c1en
dc.rightsCreative Commons Attribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectBiochemical Research Methodsen
dc.subjectMathematical & Computational Biologyen
dc.subjectBiochemistry & Molecular Biologyen
dc.subjectROR-GAMMA-Ten
dc.subjectTRANSCRIPTION FACTORSen
dc.subjectLINEAGE-COMMITMENTen
dc.subjectTGF-BETAen
dc.subjectPROINFLAMMATORY IL-17(+)en
dc.subjectPROGENITOR CELLSen
dc.subjectDECISION-MAKINGen
dc.subjectRETINOIC ACIDen
dc.subjectT(H)17en
dc.subjectINFLAMMATIONen
dc.titleA Mathematical Model for the Reciprocal Differentiation of T Helper 17 Cells and Induced Regulatory T Cellsen
dc.title.serialPLOS Computational Biologyen
dc.typeArticle - Refereeden
dc.type.dcmitypeTexten
pubs.organisational-group/Virginia Techen
pubs.organisational-group/Virginia Tech/All T&R Facultyen
pubs.organisational-group/Virginia Tech/Faculty of Health Sciencesen
pubs.organisational-group/Virginia Tech/Scienceen
pubs.organisational-group/Virginia Tech/Science/Biological Sciencesen
pubs.organisational-group/Virginia Tech/Science/COS T&R Facultyen
pubs.organisational-group/Virginia Tech/University Distinguished Professorsen

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