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A Framework for the Systematic Selection of Biosensor Chassis for Environmental Synthetic Biology

Swetha Sridhar, Caroline M. Ajo‐Franklin, Caroline A. Masiello

2022ACS Synthetic Biology23 citationsDOIOpen Access PDF

Abstract

Microbial biosensors sense and report exposures to stimuli, thereby facilitating our understanding of environmental processes. Successful design and deployment of biosensors hinge on the persistence of the microbial host of the genetic circuit, termed the chassis. However, model chassis organisms may persist poorly in environmental conditions. In contrast, non-model organisms persist better in environmental conditions but are limited by other challenges, such as genetic intractability and part unavailability. Here we identify ecological, metabolic, and genetic constraints for chassis development and propose a conceptual framework for the systematic selection of environmental biosensor chassis. We identify key challenges with using current model chassis and delineate major points of conflict in choosing the most suitable organisms as chassis for environmental biosensing. This framework provides a way forward in the selection of biosensor chassis for environmental synthetic biology.

Topics & Concepts

ChassisSynthetic biologySelection (genetic algorithm)Biochemical engineeringComputer scienceBiosensorBiologyEcologyComputational biologyEngineeringArtificial intelligenceBiochemistryStructural engineeringGene Regulatory Network AnalysisMicrobial Metabolic Engineering and Bioproductionbioluminescence and chemiluminescence research
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