Multi-Layer Autocatalytic Feedback Enables Integral Control Amidst Resource Competition and Across Scales

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Armin M. Zand, Stanislav Anastassov, Timothy Frei and Mustafa Khammash*, 
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引用次数: 0

Abstract

Integral feedback control strategies have proven effective in regulating protein expression in unpredictable cellular environments. These strategies, grounded in model-based designs and control theory, have advanced synthetic biology applications. Autocatalytic integral feedback controllers, utilizing positive autoregulation for integral action, are one class of simplest architectures to design integrators. This class of controllers offers unique features, such as robustness against dilution effects and cellular growth, as well as the potential for synthetic realizations across different biological scales, owing to their similarity to self-regenerative behaviors widely observed in nature. Despite this, their potential has not yet been fully exploited. One key reason, we discuss, is that their effectiveness is often hindered by resource competition and context-dependent couplings. This study addresses these challenges using a multilayer feedback strategy. Our designs enabled population-level integral feedback and multicellular integrators, where the control function emerges as a property of coordinated interactions distributed across different cell populations coexisting in a multicellular consortium. We provide a generalized mathematical framework for modeling resource competition in complex genetic networks, supporting the design of intracellular control circuits. The use of our proposed multilayer autocatalytic controllers is examined in two typical control tasks that pose significant relevance to synthetic biology applications: concentration regulation and ratiometric control. We define a ratiometric control task and solve it using a variant of our controller. The effectiveness of our controller motifs is demonstrated through a range of application examples, from precise regulation of gene expression and gene ratios in embedded designs to population growth and coculture composition control in multicellular designs within engineered microbial ecosystems. These findings offer a versatile approach to achieving robust adaptation and homeostasis from subcellular to multicellular scales.

多层自催化反馈使整体控制在资源竞争和跨尺度
积分反馈控制策略已被证明在不可预测的细胞环境中有效调节蛋白质表达。这些策略以模型设计和控制理论为基础,具有先进的合成生物学应用。自催化积分反馈控制器,利用积分动作的正自调节,是一类最简单的架构来设计积分器。这类控制器具有独特的特性,如抗稀释效应和细胞生长的鲁棒性,以及在不同生物尺度上合成实现的潜力,因为它们与自然界中广泛观察到的自我再生行为相似。尽管如此,它们的潜力尚未得到充分利用。我们讨论的一个关键原因是,它们的有效性经常受到资源竞争和上下文依赖耦合的阻碍。本研究使用多层反馈策略解决了这些挑战。我们的设计实现了群体水平的积分反馈和多细胞积分,其中控制功能作为分布在多细胞联盟中共存的不同细胞群体之间的协调相互作用的特性而出现。我们提供了一个广义的数学框架来模拟复杂遗传网络中的资源竞争,支持细胞内控制电路的设计。我们提出的多层自催化控制器的使用在两个典型的控制任务中进行了检查,这些任务与合成生物学应用具有重要的相关性:浓度调节和比率控制。我们定义了一个比率控制任务,并使用我们的控制器的一个变体来解决它。我们的控制器基序的有效性通过一系列应用实例得到了证明,从嵌入式设计中基因表达和基因比例的精确调控到工程微生物生态系统中多细胞设计中的种群增长和共培养成分控制。这些发现为实现从亚细胞到多细胞尺度的强大适应和稳态提供了一种通用的方法。
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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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