Emergence of temporal noise hierarchy in co-regulated genes of multi-output feed-forward loop.

IF 2 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY Physical biology Pub Date : 2024-12-05 DOI:10.1088/1478-3975/ad9792
Mintu Nandi
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引用次数: 0

Abstract

Natural variations in gene expression, called noise, are fundamental to biological systems. The expression noise can be beneficial or detrimental to cellular functions. While the impact of noise on individual genes is well-established, our understanding of how noise behaves when multiple genes are co-expressed by shared regulatory elements within transcription networks remains elusive. This lack of understanding extends to how the architecture and regulatory features of these networks influence noise. To address this gap, we study the multi-output feed-forward loop motif. The motif is prevalent in bacteria and yeast and influences co-expression of multiple genes by shared transcription factors (TFs). Focusing on a two-output variant of the motif, the present study explores the interplay between its architecture, co-expression (symmetric and asymmetric) patterns of the two genes, and the associated noise dynamics. We employ a stochastic modeling approach to investigate how the binding affinities of the TFs influence symmetric and asymmetric expression patterns and the resulting noise dynamics in the co-expressed genes. This knowledge could guide the development of strategies for manipulating gene expression patterns through targeted modulation of TF binding affinities.

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多输出前馈回路共调基因中出现的时间噪声层次结构
基因表达的自然变化被称为噪声,是生物系统的基本要素。表达噪音可能对细胞功能有利,也可能有害。虽然噪音对单个基因的影响已经得到证实,但我们对多个基因在转录网络中通过共享调控元件共同表达时噪音的表现仍然缺乏了解。这种认识的缺乏还延伸到了这些网络的结构和调控特征如何影响噪声。为了填补这一空白,我们研究了多输出前馈环图案。该模式普遍存在于细菌和酵母中,通过共享转录因子影响多个基因的共同表达。本研究以该图案的双输出变体为重点,探讨了其结构、两个基因的共同表达模式(包括对称和非对称表达)以及相关噪声动态之间的相互作用。我们采用随机建模的方法来研究转录因子的结合亲和力如何影响对称和非对称表达模式以及由此产生的共表达基因的噪声动态。这些知识可以指导我们制定策略,通过有针对性地调节转录因子的结合亲和力来操纵基因表达模式。
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来源期刊
Physical biology
Physical biology 生物-生物物理
CiteScore
4.20
自引率
0.00%
发文量
50
审稿时长
3 months
期刊介绍: Physical Biology publishes articles in the broad interdisciplinary field bridging biology with the physical sciences and engineering. This journal focuses on research in which quantitative approaches – experimental, theoretical and modeling – lead to new insights into biological systems at all scales of space and time, and all levels of organizational complexity. Physical Biology accepts contributions from a wide range of biological sub-fields, including topics such as: molecular biophysics, including single molecule studies, protein-protein and protein-DNA interactions subcellular structures, organelle dynamics, membranes, protein assemblies, chromosome structure intracellular processes, e.g. cytoskeleton dynamics, cellular transport, cell division systems biology, e.g. signaling, gene regulation and metabolic networks cells and their microenvironment, e.g. cell mechanics and motility, chemotaxis, extracellular matrix, biofilms cell-material interactions, e.g. biointerfaces, electrical stimulation and sensing, endocytosis cell-cell interactions, cell aggregates, organoids, tissues and organs developmental dynamics, including pattern formation and morphogenesis physical and evolutionary aspects of disease, e.g. cancer progression, amyloid formation neuronal systems, including information processing by networks, memory and learning population dynamics, ecology, and evolution collective action and emergence of collective phenomena.
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