Abstract
Genetically-encoded biosensors offer a wide range of opportunities to develop advanced synthetic biology applications. Circuits with the ability of detecting and quantifying intracellular amounts of a compound of interest are central to whole-cell biosensors design for medical and environmental applications, and they also constitute essential parts for the selection and regulation of high-producer strains in metabolic engineering. However, the number of compounds that can be detected through natural mechanisms, like allosteric transcription factors, is limited; expanding the set of detectable compounds is therefore highly desirable. Here, we present the SensiPath web server, accessible at http://sensipath.micalis.fr. SensiPath implements a strategy to enlarge the set of detectable compounds by screening for multi-step enzymatic transformations converting non-detectable compounds into detectable ones. The SensiPath approach is based on the encoding of reactions through signature descriptors to explore sensing-enabling metabolic pathways, which are putative biochemical transformations of the target compound leading to known effectors of transcription factors. In that way, SensiPath enlarges the design space by broadening the potential use of biosensors in synthetic biology applications.
Highlights
Synthetic biology and metabolic engineering applications often require as part of their design a way to assess the presence or to quantify the amount of a compound of interest
We describe here the design steps required to build a strain of E. coli able to detect the drug cocaine, and a strain able to detect the pollutant parathion with the help of SensiPath
The development of novel biosensors is presently needed in order to enlarge the set of detectable and observable metabolites that are available for synthetic biology applications such as in health, environment or fine chemical production
Summary
Synthetic biology and metabolic engineering applications often require as part of their design a way to assess the presence or to quantify the amount of a compound of interest. Genetically-encoded biosensors such as riboswitches and allosteric transcription factors offer the possibility to control the expression of a gene of choice This feature makes them valuable for many applications [1,2] such as pollutant monitoring or high-throughput screening of optimized strains and enzymes [3,4,5], as expression of reporter genes like fluorescent proteins can be linked to the concentration of the compound of interest. We recently demonstrated that this approach could be attempted in a systematic fashion by combining information on the available biosensors and automatic design of enzymatic networks This led to the development of five new whole-cell biosensors for pollutants (parathion, 2C4NP), biomarker (hippuric acid) and drugs (cocain, nitroglycerin) [17]. We collected a large dataset of more than 500 detectable compounds for which intracellular biosensors exist from several gene expression regulation databases, focusing our search on allosteric transcription factors
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