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Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia
Cells are complex machines capable of processing information by means of an entangled network of molecular interactions. A crucial component of these decision-making systems is the presence of memory and this is also a specially relevant target of engineered synthetic systems. A classic example of m...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598587/ https://www.ncbi.nlm.nih.gov/pubmed/26500559 http://dx.doi.org/10.3389/fphys.2015.00281 |
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author | Sardanyés, Josep Bonforti, Adriano Conde, Nuria Solé, Ricard Macia, Javier |
author_facet | Sardanyés, Josep Bonforti, Adriano Conde, Nuria Solé, Ricard Macia, Javier |
author_sort | Sardanyés, Josep |
collection | PubMed |
description | Cells are complex machines capable of processing information by means of an entangled network of molecular interactions. A crucial component of these decision-making systems is the presence of memory and this is also a specially relevant target of engineered synthetic systems. A classic example of memory devices is a 1-bit memory element known as the flip-flop. Such system can be in principle designed using a single-cell implementation, but a direct mapping between standard circuit design and a living circuit can be cumbersome. Here we present a novel computational implementation of a 1-bit memory device using a reliable multicellular design able to behave as a set-reset flip-flop that could be implemented in yeast cells. The dynamics of the proposed synthetic circuit is investigated with a mathematical model using biologically-meaningful parameters. The circuit is shown to behave as a flip-flop in a wide range of parameter values. The repression strength for the NOT logics is shown to be crucial to obtain a good flip-flop signal. Our model also shows that the circuit can be externally tuned to achieve different memory states and dynamics, such as persistent and transient memory. We have characterized the parameter domains for robust memory storage and retrieval as well as the corresponding time response dynamics. |
format | Online Article Text |
id | pubmed-4598587 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-45985872015-10-23 Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia Sardanyés, Josep Bonforti, Adriano Conde, Nuria Solé, Ricard Macia, Javier Front Physiol Physiology Cells are complex machines capable of processing information by means of an entangled network of molecular interactions. A crucial component of these decision-making systems is the presence of memory and this is also a specially relevant target of engineered synthetic systems. A classic example of memory devices is a 1-bit memory element known as the flip-flop. Such system can be in principle designed using a single-cell implementation, but a direct mapping between standard circuit design and a living circuit can be cumbersome. Here we present a novel computational implementation of a 1-bit memory device using a reliable multicellular design able to behave as a set-reset flip-flop that could be implemented in yeast cells. The dynamics of the proposed synthetic circuit is investigated with a mathematical model using biologically-meaningful parameters. The circuit is shown to behave as a flip-flop in a wide range of parameter values. The repression strength for the NOT logics is shown to be crucial to obtain a good flip-flop signal. Our model also shows that the circuit can be externally tuned to achieve different memory states and dynamics, such as persistent and transient memory. We have characterized the parameter domains for robust memory storage and retrieval as well as the corresponding time response dynamics. Frontiers Media S.A. 2015-10-09 /pmc/articles/PMC4598587/ /pubmed/26500559 http://dx.doi.org/10.3389/fphys.2015.00281 Text en Copyright © 2015 Sardanyés, Bonforti, Conde, Solé and Macia. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Sardanyés, Josep Bonforti, Adriano Conde, Nuria Solé, Ricard Macia, Javier Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title | Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title_full | Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title_fullStr | Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title_full_unstemmed | Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title_short | Computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
title_sort | computational implementation of a tunable multicellular memory circuit for engineered eukaryotic consortia |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4598587/ https://www.ncbi.nlm.nih.gov/pubmed/26500559 http://dx.doi.org/10.3389/fphys.2015.00281 |
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