Regulatory Effects of Cooperativity and Signal Profile on Adaptive Dynamics in Incoherent Feedforward Loop Networks.

Q2 Medicine In Silico Biology Pub Date : 2025-01-01 DOI:10.1177/14343207241306092
Necmettin Yildirim, Thomas Brew, Ahmet Ay
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引用次数: 0

Abstract

Cellular adaptation to external signals is essential for biological functions, and it is an important field of interest in systems biology. This study examines the impact of cooperativity on the adaptation response of the Incoherent Feedforward Loop (IFFL) network motif to various signal profiles. Through comprehensive simulations, we studied how the IFFL motif responds to constant and pulse-type signals under varying levels of cooperativity. The results of our study demonstrate that positive cooperativity generally enhances the system's ability to adapt to different signal profiles. Nevertheless, given specific signal profiles, higher levels of cooperativity may decrease the system's adaptability. On the other hand, the adaptive response breaks down for negative cooperativity. For constant signals, increased positive cooperativity leads to a response with higher amplitude, and it accelerates the response time but delays the return time required to settle back down to the pre-stimulus state. Upon signal cessation, high positive cooperativity not only slows the system's response and return times but, in some cases, can lead to a complete temporary halt in response. For the pulse-like signal, cooperativity increases the maximum amplitude of the oscillatory response. These insights highlight the delicate balance between cooperativity and signal profile in cellular adaptation mechanisms involving the IFFL network motif.

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协同性和信号分布对非相干前馈环路网络自适应动力学的调节作用。
细胞对外部信号的适应是生物功能的必要条件,也是系统生物学的一个重要研究领域。本研究探讨了协同性对非相干前馈环路(IFFL)网络基序对各种信号谱的适应反应的影响。通过综合模拟,我们研究了IFFL基序在不同协同度下对恒定和脉冲型信号的响应。我们的研究结果表明,积极的合作通常增强了系统适应不同信号的能力。然而,给定特定的信号配置,更高水平的协同性可能会降低系统的适应性。另一方面,适应性反应被消极合作打破。对于恒定的信号,正向协同性的增加会导致更高幅度的反应,并且会加速反应时间,但会延迟回到刺激前状态所需的返回时间。在信号停止后,高正向协同性不仅减缓了系统的响应和返回时间,而且在某些情况下,可能导致响应完全暂时停止。对于类脉冲信号,协同性增加了振荡响应的最大幅度。这些见解强调了涉及IFFL网络基序的细胞适应机制中协同性和信号谱之间的微妙平衡。
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来源期刊
In Silico Biology
In Silico Biology Computer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍: The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.
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