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dc.contributor.authorCheng, Hao D.
dc.contributor.authorDowell, Karen G.
dc.contributor.authorBailey-Kellogg, Chris
dc.contributor.authorGoods, Brittany A.
dc.contributor.authorLove, J. C.
dc.contributor.authorFerrari, Guido
dc.contributor.authorAlter, Galit
dc.contributor.authorGach, Johannes
dc.contributor.authorForthal, Donald N.
dc.contributor.authorLewis, George K.
dc.contributor.authorGreene, Kelli
dc.contributor.authorGao, Hongmei
dc.contributor.authorMontefiori, David C.
dc.contributor.authorAckerman, Margaret E.
dc.date.accessioned2021-11-01T15:31:54Z
dc.date.available2021-11-01T15:31:54Z
dc.date.issued2021-10-30
dc.identifier.urihttps://hdl.handle.net/1721.1/136961
dc.description.abstractAbstract Background The critical role of antibody Fc-mediated effector functions in immune defense has been widely reported in various viral infections. These effector functions confer cellular responses through engagement with innate immune cells. The precise mechanism(s) by which immunoglobulin G (IgG) Fc domain and cognate receptors may afford protection are poorly understood, however, in the context of HIV/SHIV infections. Many different in vitro assays have been developed and utilized to measure effector functions, but the extent to which these assays capture distinct antibody activities has not been fully elucidated. Results In this study, six Fc-mediated effector function assays and two biophysical antibody profiling assays were performed on a common set of samples from HIV-1 infected and vaccinated subjects. Biophysical antibody profiles supported robust prediction of diverse IgG effector functions across distinct Fc-mediated effector function assays. While a number of assays showed correlated activities, supervised machine learning models indicated unique antibody features as primary contributing factors to the associated effector functions. Additional experiments established the mechanistic relevance of relationships discovered using this unbiased approach. Conclusions In sum, this study provides better resolution on the diversity and complexity of effector function assays, offering a clearer perspective into this family of antibody mechanisms of action to inform future HIV-1 treatment and vaccination strategies.en_US
dc.publisherBioMed Centralen_US
dc.relation.isversionofhttps://doi.org/10.1186/s12977-021-00579-9en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_US
dc.sourceBioMed Centralen_US
dc.titleDiverse antiviral IgG effector activities are predicted by unique biophysical antibody featuresen_US
dc.typeArticleen_US
dc.identifier.citationRetrovirology. 2021 Oct 30;18(1):35en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Chemistry
dc.contributor.departmentMassachusetts Institute of Technology. Department of Biological Engineering
dc.contributor.departmentKoch Institute for Integrative Cancer Research at MIT
dc.contributor.departmentRagon Institute of MGH, MIT and Harvard
dc.identifier.mitlicensePUBLISHER_CC
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2021-10-31T04:19:47Z
dc.language.rfc3066en
dc.rights.holderThe Author(s)
dspace.date.submission2021-10-31T04:19:47Z
mit.licensePUBLISHER_CC
mit.metadata.statusAuthority Work and Publication Information Neededen_US


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