4.8 Article

SensiPath: computer-aided design of sensing-enabling metabolic pathways

Journal

NUCLEIC ACIDS RESEARCH
Volume 44, Issue W1, Pages W226-W231

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkw305

Keywords

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Funding

  1. Structure et Dynamique des Systemes Vivants doctoral school, Universite Paris Saclay
  2. Direction Generale de l'Armement (DGA-MRIS Scholarship)
  3. Biotechnology and Biological Sciences Research Council, Centre for synthetic biology of fine and speciality chemicals [BB/M017702/1]
  4. GIP Genopole
  5. Toulouse White Biotech (TWB)
  6. French National Research Agency [ANR-15-CE1-0008]
  7. Biotechnology and Biological Sciences Research Council [BB/M017702/1]
  8. BBSRC [BB/M017702/1] Funding Source: UKRI
  9. Biotechnology and Biological Sciences Research Council [BB/M017702/1] Funding Source: researchfish

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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 formedical 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.

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