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Spatial biology of Ising-like synthetic genetic networks

BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial...

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Autores principales: Simpson, Kevin, L’Homme, Alfredo, Keymer, Juan, Federici, Fernán
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478219/
https://www.ncbi.nlm.nih.gov/pubmed/37667283
http://dx.doi.org/10.1186/s12915-023-01681-4
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author Simpson, Kevin
L’Homme, Alfredo
Keymer, Juan
Federici, Fernán
author_facet Simpson, Kevin
L’Homme, Alfredo
Keymer, Juan
Federici, Fernán
author_sort Simpson, Kevin
collection PubMed
description BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-023-01681-4.
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spelling pubmed-104782192023-09-06 Spatial biology of Ising-like synthetic genetic networks Simpson, Kevin L’Homme, Alfredo Keymer, Juan Federici, Fernán BMC Biol Research Article BACKGROUND: Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS: Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS: Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12915-023-01681-4. BioMed Central 2023-09-04 /pmc/articles/PMC10478219/ /pubmed/37667283 http://dx.doi.org/10.1186/s12915-023-01681-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Simpson, Kevin
L’Homme, Alfredo
Keymer, Juan
Federici, Fernán
Spatial biology of Ising-like synthetic genetic networks
title Spatial biology of Ising-like synthetic genetic networks
title_full Spatial biology of Ising-like synthetic genetic networks
title_fullStr Spatial biology of Ising-like synthetic genetic networks
title_full_unstemmed Spatial biology of Ising-like synthetic genetic networks
title_short Spatial biology of Ising-like synthetic genetic networks
title_sort spatial biology of ising-like synthetic genetic networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10478219/
https://www.ncbi.nlm.nih.gov/pubmed/37667283
http://dx.doi.org/10.1186/s12915-023-01681-4
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