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Nanodelivery of a functional membrane receptor to manipulate cellular phenotype.

ABSTRACT: Modification of membrane receptor makeup is one of the most efficient ways to control input-output signals but is usually achieved by expressing DNA or RNA-encoded proteins or by using other genome-editing methods, which can be technically challenging and produce unwanted side effects. Here we develop and validate a nanodelivery approach to transfer in vitro synthesized, functional membrane receptors into the plasma membrane of living cells. Using ?2-adrenergic receptor (?2AR), a prototypical G-protein coupled receptor, as an example, we demonstrated efficient incorporation of a full-length ?2AR into a variety of mammalian cells, which imparts pharmacologic control over cellular signaling and affects cellular phenotype in an ex-vivo wound-healing model. Our approach for nanodelivery of functional membrane receptors expands the current toolkit for DNA and RNA-free manipulation of cellular function. We expect this approach to be readily applicable to the synthesis and nanodelivery of other types of GPCRs and membrane receptors, opening new doors for therapeutic development at the intersection between synthetic biology and nanomedicine.

SUBMITTER: Patriarchi T

PROVIDER: S-EPMC5824837 | biostudies-other | 2018 Feb

REPOSITORIES: biostudies-other

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Nanodelivery of a functional membrane receptor to manipulate cellular phenotype.

Patriarchi Tommaso T Shen Ao A He Wei W Baikoghli Mo M Cheng R Holland RH Xiang Yang K YK Coleman Matthew A MA Tian Lin L

Scientific reports 20180223 1

Modification of membrane receptor makeup is one of the most efficient ways to control input-output signals but is usually achieved by expressing DNA or RNA-encoded proteins or by using other genome-editing methods, which can be technically challenging and produce unwanted side effects. Here we develop and validate a nanodelivery approach to transfer in vitro synthesized, functional membrane receptors into the plasma membrane of living cells. Using β<sub>2</sub>-adrenergic receptor (β<sub>2</sub> ...[more]

PMID: 29476125

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Project description:Cell population heterogeneity can affect cellular response and is a major factor in drug resistance. However, there are few techniques available to represent and explore how heterogeneity is linked to population response. Recent high-throughput genomic, proteomic, and cellomic approaches offer opportunities for profiling heterogeneity on several scales. We have recently examined heterogeneity in vascular endothelial growth factor receptor (VEGFR) membrane localization in endothelial cells. We and others processed the heterogeneous data through ensemble averaging and integrated the data into computational models of anti-angiogenic drug effects in breast cancer. Here we show that additional modeling insight can be gained when cellular heterogeneity is considered. We present comprehensive statistical and computational methods for analyzing cellomic data sets and integrating them into deterministic models. We present a novel method for optimizing the fit of statistical distributions to heterogeneous data sets to preserve important data and exclude outliers. We compare methods of representing heterogeneous data and show methodology can affect model predictions up to 3.9-fold. We find that VEGF levels, a target for tuning angiogenesis, are more sensitive to VEGFR1 cell surface levels than VEGFR2; updating VEGFR1 levels in the tumor model gave a 64% change in free VEGF levels in the blood compartment, whereas updating VEGFR2 levels gave a 17% change. Furthermore, we find that subpopulations of tumor cells and tumor endothelial cells (tEC) expressing high levels of VEGFR (>35,000 VEGFR/cell) negate anti-VEGF treatments. We show that lowering the VEGFR membrane insertion rate for these subpopulations recovers the anti-angiogenic effect of anti-VEGF treatment, revealing new treatment targets for specific tumor cell subpopulations. This novel method of characterizing heterogeneous distributions shows for the first time how different representations of the same data set lead to different predictions of drug efficacy.

Dataset Information

Nanodelivery of a functional membrane receptor to manipulate cellular phenotype.

Publications

Nanodelivery of a functional membrane receptor to manipulate cellular phenotype.

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