Literature DB >> 28463802

A three-step framework for programming pattern formation.

Natalie S Scholes1, Mark Isalan2.   

Abstract

The spatial organisation of gene expression is essential to create structure and function in multicellular organisms during developmental processes. Such organisation occurs by the execution of algorithmic functions, leading to patterns within a given domain, such as a tissue. Engineering these processes has become increasingly important because bioengineers are seeking to develop tissues ex vivo. Moreover, although there are several theories on how pattern formation can occur in vivo, the biological relevance and biotechnological potential of each of these remains unclear. In this review, we will briefly explain four of the major theories of pattern formation in the light of recent work. We will explore why programming of such patterns is necessary, while discussing a three-step framework for artificial engineering approaches.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Mesh:

Year:  2017        PMID: 28463802     DOI: 10.1016/j.cbpa.2017.04.008

Source DB:  PubMed          Journal:  Curr Opin Chem Biol        ISSN: 1367-5931            Impact factor:   8.822


  7 in total

1.  Stochastic Turing patterns in a synthetic bacterial population.

Authors:  David Karig; K Michael Martini; Ting Lu; Nicholas A DeLateur; Nigel Goldenfeld; Ron Weiss
Journal:  Proc Natl Acad Sci U S A       Date:  2018-06-11       Impact factor: 11.205

Review 2.  Synthetic spatial patterning in bacteria: advances based on novel diffusible signals.

Authors:  Martina Oliver Huidobro; Jure Tica; Georg K A Wachter; Mark Isalan
Journal:  Microb Biotechnol       Date:  2021-11-29       Impact factor: 6.575

3.  Engineered cell-to-cell signalling within growing bacterial cellulose pellicles.

Authors:  Kenneth T Walker; Vivianne J Goosens; Akashaditya Das; Alicia E Graham; Tom Ellis
Journal:  Microb Biotechnol       Date:  2018-11-21       Impact factor: 5.813

Review 4.  Spatial Stochastic Intracellular Kinetics: A Review of Modelling Approaches.

Authors:  Stephen Smith; Ramon Grima
Journal:  Bull Math Biol       Date:  2018-05-21       Impact factor: 1.758

5.  Model-guided design of mammalian genetic programs.

Authors:  J J Muldoon; V Kandula; M Hong; P S Donahue; J D Boucher; N Bagheri; J N Leonard
Journal:  Sci Adv       Date:  2021-02-19       Impact factor: 14.136

Review 6.  Turing pattern design principles and their robustness.

Authors:  Sean T Vittadello; Thomas Leyshon; David Schnoerr; Michael P H Stumpf
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2021-11-08       Impact factor: 4.226

7.  Model reduction enables Turing instability analysis of large reaction-diffusion models.

Authors:  Stephen Smith; Neil Dalchau
Journal:  J R Soc Interface       Date:  2018-03       Impact factor: 4.118

  7 in total

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