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Synthetic Lateral Inhibition in Periodic Pattern Forming Microbial Colonies
Author(s) -
Salva DuranNebreda,
Jordi Pla,
Blai Vidiella,
Jordi Piñero,
Núria Conde–Pueyo,
Ricard V. Solé
Publication year - 2021
Publication title -
acs synthetic biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.156
H-Index - 66
ISSN - 2161-5063
DOI - 10.1021/acssynbio.0c00318
Subject(s) - multicellular organism , pattern formation , synthetic biology , biological system , process (computing) , symmetry breaking , mechanism (biology) , computer science , biology , artificial intelligence , computational biology , physics , gene , genetics , quantum mechanics , operating system , biochemistry
Multicellular entities are characterized by intricate spatial patterns, intimately related to the functions they perform. These patterns are often created from isotropic embryonic structures, without external information cues guiding the symmetry breaking process. Mature biological structures also display characteristic scales with repeating distributions of signals or chemical species across space. Many candidate patterning modules have been used to explain processes during development and typically include a set of interacting and diffusing chemicals or agents known as morphogens . Great effort has been put forward to better understand the conditions in which pattern-forming processes can occur in the biological domain. However, evidence and practical knowledge allowing us to engineer symmetry-breaking is still lacking. Here we follow a different approach by designing a synthetic gene circuit in E. coli that implements a local activation long-range inhibition mechanism. The synthetic gene network implements an artificial differentiation process that changes the physicochemical properties of the agents. Using both experimental results and modeling, we show that the proposed system is capable of symmetry-breaking leading to regular spatial patterns during colony growth. Studying how these patterns emerge is fundamental to further our understanding of the evolution of biocomplexity and the role played by self-organization. The artificial system studied here and the engineering perspective on embryogenic processes can help validate developmental theories and identify universal properties underpinning biological pattern formation, with special interest for the area of synthetic developmental biology.

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