A general strategy to engineer high-performance mammalian Whole-Cell Biosensors

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Abstract

Transcription-based whole-cell biosensors (WCBs) are cells engineered with an analyte-responsive promoter driving the transcription of a reporter gene. WCBs can sense and report on bioactive molecules (analytes) relevant to human health. Designing an analyte-sensitive promoter requires a cumbersome trial-and-error approach and usually results in biosensors with poor performance. Here, we integrated Synthetic Biology with Control Engineering to design, computationally model, and experimentally implement high-performance biosensors in mammalian cells. Our approach, unlike traditional methods, does not rely on optimizing individual components such as promoters and transcription factors. Instead, it uses biomolecular circuits to enhance the biosensor’s performance despite inherent component flaws. We experimentally implemented eight different biosensors by employing CRISPR-Cas systems, then quantitatively compared their performance and identified one configuration, which we named CASense, that overcomes the limitations of current biosensors. Our approach is generalisable and can be adapted to sense any analyte of interest for which there is an analyte-sensitive promoter, making it a versatile tool for multiple applications. As a proof of concept, we engineered a high-performance biosensor of intracellular copper due to the critical role that copper plays in human health and disease, and to the lack of techniques able to measure intracellular copper levels in living cells. The significance of our work lies in its potential to impact the monitoring of bioactive molecules and chemicals both in vitro and in vivo, which is crucial in areas such as toxicology, drug discovery, disease diagnosis and therapy.

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