Synthetic mixed-signal computation in living cells

Detalhes bibliográficos
Autor(a) principal: Rubens, Jacob R.
Data de Publicação: 2016
Outros Autores: Selvaggio, Gianluca, Lu, Timothy K.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10316/108722
https://doi.org/10.1038/ncomms11658
Resumo: Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.
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spelling Synthetic mixed-signal computation in living cellsCell EngineeringEscherichia coliGenetic EngineeringSignal Processing, Computer-AssistedComputers, MolecularGene Regulatory NetworksGenes, SyntheticSynthetic BiologyLiving cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.Springer Nature2016-06-03info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10316/108722http://hdl.handle.net/10316/108722https://doi.org/10.1038/ncomms11658eng2041-1723Rubens, Jacob R.Selvaggio, GianlucaLu, Timothy K.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-09-11T08:34:42Zoai:estudogeral.uc.pt:10316/108722Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T21:24:59.638943Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Synthetic mixed-signal computation in living cells
title Synthetic mixed-signal computation in living cells
spellingShingle Synthetic mixed-signal computation in living cells
Rubens, Jacob R.
Cell Engineering
Escherichia coli
Genetic Engineering
Signal Processing, Computer-Assisted
Computers, Molecular
Gene Regulatory Networks
Genes, Synthetic
Synthetic Biology
title_short Synthetic mixed-signal computation in living cells
title_full Synthetic mixed-signal computation in living cells
title_fullStr Synthetic mixed-signal computation in living cells
title_full_unstemmed Synthetic mixed-signal computation in living cells
title_sort Synthetic mixed-signal computation in living cells
author Rubens, Jacob R.
author_facet Rubens, Jacob R.
Selvaggio, Gianluca
Lu, Timothy K.
author_role author
author2 Selvaggio, Gianluca
Lu, Timothy K.
author2_role author
author
dc.contributor.author.fl_str_mv Rubens, Jacob R.
Selvaggio, Gianluca
Lu, Timothy K.
dc.subject.por.fl_str_mv Cell Engineering
Escherichia coli
Genetic Engineering
Signal Processing, Computer-Assisted
Computers, Molecular
Gene Regulatory Networks
Genes, Synthetic
Synthetic Biology
topic Cell Engineering
Escherichia coli
Genetic Engineering
Signal Processing, Computer-Assisted
Computers, Molecular
Gene Regulatory Networks
Genes, Synthetic
Synthetic Biology
description Living cells implement complex computations on the continuous environmental signals that they encounter. These computations involve both analogue- and digital-like processing of signals to give rise to complex developmental programs, context-dependent behaviours and homeostatic activities. In contrast to natural biological systems, synthetic biological systems have largely focused on either digital or analogue computation separately. Here we integrate analogue and digital computation to implement complex hybrid synthetic genetic programs in living cells. We present a framework for building comparator gene circuits to digitize analogue inputs based on different thresholds. We then demonstrate that comparators can be predictably composed together to build band-pass filters, ternary logic systems and multi-level analogue-to-digital converters. In addition, we interface these analogue-to-digital circuits with other digital gene circuits to enable concentration-dependent logic. We expect that this hybrid computational paradigm will enable new industrial, diagnostic and therapeutic applications with engineered cells.
publishDate 2016
dc.date.none.fl_str_mv 2016-06-03
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10316/108722
http://hdl.handle.net/10316/108722
https://doi.org/10.1038/ncomms11658
url http://hdl.handle.net/10316/108722
https://doi.org/10.1038/ncomms11658
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2041-1723
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
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dc.publisher.none.fl_str_mv Springer Nature
publisher.none.fl_str_mv Springer Nature
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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