Automatic design of gene regulatory mechanisms for spatial pattern formation

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Reza Mousavi, Daniel Lobo
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引用次数: 0

Abstract

Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms—including the number of genes necessary for the formation of the target spatial pattern—we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.

自动设计空间模式形成的基因调控机制
基因调控机制(GRMs)控制着空间和时间表达模式的形成,这些模式可以作为复杂形状发育的调控信号。合成发育生物学旨在设计这种基因回路,以了解和产生所需的多细胞空间模式。然而,由于遗传回路中的非线性相互作用和反馈回路,为复杂的多维空间模式设计合成 GRM 是目前的一项挑战。在这里,我们提出了一种自动设计 GRM 的方法,这种 GRM 可以产生任何给定的二维空间模式。所提出的方法使用两个正交的形态发生梯度作为多细胞组织区域或培养物中的位置信息信号,这构成了一个连续的工程细胞场,实现了同一设计的基因组管理。为了有效设计电路网络和相互作用机制,包括形成目标空间模式所需的基因数量,我们开发了一种基于高性能进化计算的自动算法。该算法的容差可进行配置,以设计出既简单又能产生近似模式或既复杂又能产生精确模式的 GRM。我们通过自动设计 GRM 演示了这一方法,GRM 只需解释两个正交形态发生梯度,就能生成多种合成空间表达模式。所提出的框架为系统设计和发现产生空间模式的复杂基因回路提供了一种通用方法。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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