4.7 Article

Multiplexing Engineered Receptors for Multiparametric Evaluation of Environmental Ligands

Journal

ACS SYNTHETIC BIOLOGY
Volume 6, Issue 11, Pages 2042-2055

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.6b00279

Keywords

biosensor; receptor engineering; genetic circuit; mammalian; computational model; intercellular variation

Funding

  1. National Institutes of Health through Northwestern University's Biotechnology Training Program [GM 008449]
  2. Robert H. Lurie Comprehensive Cancer Center of Northwestern University
  3. Northwestern University Graduate School Cluster in Biotechnology, Systems, and Synthetic Biology
  4. Cornew Innovation Fund
  5. Northwestern University Flow Cytometry Facility and a Cancer Center Support Grant [NCI CA060553]
  6. Defense Advanced Research Projects Agency [W911NF-11-2-0066]

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Engineered cell-based therapies comprise a promising, emerging biomedical technology. Broad utilization of this strategy will require new approaches for implementing sophisticated functional programs, such as sensing and responding to the environment in a defined fashion. Toward this goal, we investigated whether our self-contained receptor and signal transduction system (MESA) could be multiplexed to evaluate extracellular cues, with a focus on elucidating principles governing the integration of such engineered components. We first developed a set of hybrid promoters that exhibited AND gate activation by two transcription factors. We then evaluated these promoters when paired with two MESA receptors and various ligand combinations. Unexpectedly, although the multiplexed system exhibited distinct responses to ligands applied individually and in combination, the same synergy was not observed as when promoters were characterized with soluble transcription factors. Therefore, we developed a mechanistic computational model leveraging these observations, to both improve our understanding of how the receptors and promoters interface and to guide the design and implementation of future systems. Notably, the model explicitly accounts for the impact of intercellular variation on system characterization and performance. Model analysis identified key factors that affect the current receptors and promoters, and enabled an in silico exploration of potential modifications that inform the design of improved logic gates and their robustness to intercellular variation. Ultimately, this quantitative design-driven approach may guide the use and multiplexing of synthetic receptors for diverse custom biological functions beyond the case study considered here.

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