Transcription factor-based biosensors for screening and dynamic regulation

Front Bioeng Biotechnol. 2023 Feb 6:11:1118702. doi: 10.3389/fbioe.2023.1118702. eCollection 2023.

Abstract

Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.

Keywords: allosteric transcription factors; biosensors; dynamic regulation; metabolic engineering; screening.

Publication types

  • Review

Grants and funding

JT-L was supported by European Union Marie Skłodowska-Curie Action Individual Postdoctoral Fellowship (Grant agreement ID: 101062593). JT-L was supported by the Next-Generation EU (NGEU) fund through the Spanish Recovery, Transformation and Resilience Plan via a Margarita Salas personal grant from the Spanish Ministry of Universities (UNI/551/2021). MS was supported by the Next-Generation EU (NGEU) fund through the Spanish Recovery, Transformation and Resilience Plan via a María Zambrano personal grant from the Spanish Ministry of Universities (UNI/551/2021). PC acknowledges MCIN/AEI/10.13039/501100011033 funding through PID 2020-117271RB-C2 (BIODYNAMICS). PC was supported by the Spanish Ministry of Universities (UNI/551/2021), grant number UP 2021-036 funded by European Union - Next-generation EU. This research received financial support from Generalitat Valenciana through grant CIAICO/2021/159 (SmartBioFab). PC acknowledges MCIN/AEI/10.13039/501100011033 and NextGenerationEU/PRTR funding through grant TED 2021-131049 B-I00 (BioEcoDBTL). PC acknowledges MCIN/AEI/10.13039/501100011033 funding through grant PID 2021-127888NA-I00 (COMPSYNBIO).