Modeling transcriptional factor cross-talk to understand parabolic kinetics, bimodal gene expression and retroactivity in biosensor design

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dc.contributor.authorAris, Hannah
dc.contributor.authorBorhani, Shayan
dc.contributor.authorCahn, Devorah
dc.contributor.authorO'Donnell, Colleen
dc.contributor.authorTan, Elizabeth
dc.contributor.authorXu, Peng
dc.date.accessioned2019-02-25T15:42:18Z
dc.date.available2019-02-25T15:42:18Z
dc.date.issued2019-02-05
dc.description.abstractTranscriptional factor-based biosensor has been widely used to reprogram and adjust cellular activity to the changing environment. These biosensors translate an internal cellular signal to a transcriptional reporter output. Previous examples have demonstrated transcriptional factor (TF) cross-talk could lead to complex gene ex- pression dynamics. In this report, we formulated a mechanism-based kinetic model to simulate and predict how TF cross-talk reshape the transcriptional dynamics of an engineered biosensor. Our model comprises TF cross- talk and Hill-type equation to quantify the degree of gene repression and de-repression; it also accounts for protein degradation, cell growth (dilution) e ff ect and the carrying capacity of the system. Our simulation fi ts well with the biphasic parabolic gene expression pattern of an experimentally validated malonyl-CoA sensor. We discovered that exponential growth could lead to hysteresis in the TF cross-talk model. With Logistic growth to limit the carrying capacity, we fi nd that bimodal gene expression pattern could arise, and this phenomenon is rooted in the hysteresis characteristics of the TF cross-talk model. The computational insights obtained in this study will guide us to design accurate, sensitive TF-based biosensors and may serve as a diagnostic platform to troubleshoot the complex transcriptional dynamics in biosensor design. The computational framework devel- oped here will also provide an educational toolbox for synthetic biologist and biochemical/biomolecular en- gineering students to understand biosystem design and transcriptional regulationen_US
dc.description.sponsorshipThis work was supported by the Cellular & Biochem Engineering Program of the National Science Foundation under grant no.1805139. The authors would also like to acknowledge the Department of Chemical, Biochemical and Environmental Engineering at University of Maryland Baltimore County for funding support.en_US
dc.description.urihttps://www.sciencedirect.com/science/article/pii/S1369703X19300452en_US
dc.format.extent8 pagesen_US
dc.genrejournal articles postprintsen_US
dc.identifierdoi:10.13016/m2ao4o-hf1u
dc.identifier.citationHannah Aris , Shayan Borhani , Devorah Cahn , Colleen O'Donnell , Elizabeth Tan , Peng Xu, Modeling transcriptional factor cross-talk to understand parabolic kinetics, bimodal gene expression and retroactivity in biosensor design, Biochemical Engineering Journal Volume 144, 15 April 2019, Pages 209-216, https://doi.org/10.1016/j.bej.2019.02.005en_US
dc.identifier.urihttps://doi.org/10.1016/j.bej.2019.02.005
dc.identifier.urihttp://hdl.handle.net/11603/12856
dc.language.isoen_USen_US
dc.publisherElsevier B.V.en_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Chemical, Biochemical & Environmental Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/3.0/us/
dc.rights.uriAccess to this item will begin on April 30, 2021*
dc.subjectMalonyl-CoA sensoren_US
dc.subjecttranscriptional factor cross-talken_US
dc.subjectFapRen_US
dc.subjectkinetic modelen_US
dc.subjecthysteresisen_US
dc.subjectbimodal gene expressionen_US
dc.titleModeling transcriptional factor cross-talk to understand parabolic kinetics, bimodal gene expression and retroactivity in biosensor designen_US
dc.typeTexten_US

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