Literature DB >> 34985753

Cell-Free Biosensors and AI Integration.

Paul Soudier1, Léon Faure1, Manish Kushwaha1, Jean-Loup Faulon2,3,4.   

Abstract

Cell-free biosensors hold a great potential as alternatives for traditional analytical chemistry methods providing low-cost low-resource measurement of specific chemicals. However, their large-scale use is limited by the complexity of their development.In this chapter, we present a standard methodology based on computer-aided design (CAD ) tools that enables fast development of new cell-free biosensors based on target molecule information transduction and reporting through metabolic and genetic layers, respectively. Such systems can then be repurposed to represent complex computational problems, allowing defined multiplex sensing of various inputs and integration of artificial intelligence in synthetic biological systems.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Artificial neural networks; CAD; Machine learning; Metabolite biosensors; Perceptron; Transcription factors

Mesh:

Year:  2022        PMID: 34985753     DOI: 10.1007/978-1-0716-1998-8_19

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  15 in total

Review 1.  Where microbiology meets microengineering: design and applications of reporter bacteria.

Authors:  Jan Roelof van der Meer; Shimshon Belkin
Journal:  Nat Rev Microbiol       Date:  2010-07       Impact factor: 60.633

2.  Biosensors for environmental monitoring A global perspective.

Authors:  Sara Rodriguez-Mozaz; Maria J López de Alda; Maria-Pilar Marco; Damià Barceló
Journal:  Talanta       Date:  2005-01-30       Impact factor: 6.057

3.  Linear DNA for rapid prototyping of synthetic biological circuits in an Escherichia coli based TX-TL cell-free system.

Authors:  Zachary Z Sun; Enoch Yeung; Clarmyra A Hayes; Vincent Noireaux; Richard M Murray
Journal:  ACS Synth Biol       Date:  2013-12-04       Impact factor: 5.110

4.  RegulonDB: a database on transcriptional regulation in Escherichia coli.

Authors:  A M Huerta; H Salgado; D Thieffry; J Collado-Vides
Journal:  Nucleic Acids Res       Date:  1998-01-01       Impact factor: 16.971

Review 5.  Custom-made transcriptional biosensors for metabolic engineering.

Authors:  Mathilde Koch; Amir Pandi; Olivier Borkowski; A C Batista; Jean-Loup Faulon
Journal:  Curr Opin Biotechnol       Date:  2019-03-25       Impact factor: 9.740

6.  RegTransBase--a database of regulatory sequences and interactions based on literature: a resource for investigating transcriptional regulation in prokaryotes.

Authors:  Michael J Cipriano; Pavel N Novichkov; Alexey E Kazakov; Dmitry A Rodionov; Adam P Arkin; Mikhail S Gelfand; Inna Dubchak
Journal:  BMC Genomics       Date:  2013-04-02       Impact factor: 3.969

Review 7.  Microbially derived biosensors for diagnosis, monitoring and epidemiology.

Authors:  Hung-Ju Chang; Peter L Voyvodic; Ana Zúñiga; Jérôme Bonnet
Journal:  Microb Biotechnol       Date:  2017-08-03       Impact factor: 5.813

8.  A dataset of small molecules triggering transcriptional and translational cellular responses.

Authors:  Mathilde Koch; Amir Pandi; Baudoin Delépine; Jean-Loup Faulon
Journal:  Data Brief       Date:  2018-02-27

9.  Perspective: Solidifying the impact of cell-free synthetic biology through lyophilization.

Authors:  Keith Pardee
Journal:  Biochem Eng J       Date:  2018-10-15       Impact factor: 3.978

10.  Plug-and-play metabolic transducers expand the chemical detection space of cell-free biosensors.

Authors:  Peter L Voyvodic; Amir Pandi; Mathilde Koch; Ismael Conejero; Emmanuel Valjent; Philippe Courtet; Eric Renard; Jean-Loup Faulon; Jerome Bonnet
Journal:  Nat Commun       Date:  2019-04-12       Impact factor: 14.919

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