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挖掘光感受器构象异构体之间的转换速率。

Unearthing the transition rates between photoreceptor conformers.

作者信息

Smith Robert W, Helwig Britta, Westphal Adrie H, Pel Eran, Hörner Maximilian, Beyer Hannes M, Samodelov Sophia L, Weber Wilfried, Zurbriggen Matias D, Borst Jan Willem, Fleck Christian

机构信息

Laboratory of Systems & Synthetic Biology, Wageningen UR, PO Box 8033, Wageningen, 6700EJ, The Netherlands.

LifeGlimmer GmbH, Markelstrasse 38, Berlin, 12163, Germany.

出版信息

BMC Syst Biol. 2016 Nov 25;10(1):110. doi: 10.1186/s12918-016-0368-y.

DOI:10.1186/s12918-016-0368-y
PMID:27884151
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5123409/
Abstract

BACKGROUND

Obtaining accurate estimates of biological or enzymatic reaction rates is critical in understanding the design principles of a network and how biological processes can be experimentally manipulated on demand. In many cases experimental limitations mean that some enzymatic rates cannot be measured directly, requiring mathematical algorithms to estimate them. Here, we describe a methodology that calculates rates at which light-regulated proteins switch between conformational states. We focus our analysis on the phytochrome family of photoreceptors found in cyanobacteria, plants and many optogenetic tools. Phytochrome proteins change between active (P ) and inactive (P ) states at rates that are proportional to photoconversion cross-sections and influenced by light quality, light intensity, thermal reactions and dimerisation. This work presents a method that can accurately calculate these photoconversion cross-sections in the presence of multiple non-light regulated reactions.

RESULTS

Our approach to calculating the photoconversion cross-sections comprises three steps: i) calculate the thermal reversion reaction rate(s); ii) develop search spaces from which all possible sets of photoconversion cross-sections exist, and; iii) estimate extinction coefficients that describe our absorption spectra. We confirm that the presented approach yields accurate results through the use of simulated test cases. Our test cases were further expanded to more realistic scenarios where noise, multiple thermal reactions and dimerisation are considered. Finally, we present the photoconversion cross-sections of an Arabidopsis phyB N-terminal fragment commonly used in optogenetic tools.

CONCLUSIONS

The calculation of photoconversion cross-sections has implications for both photoreceptor and synthetic biologists. Our method allows, for the first time, direct comparisons of photoconversion cross-sections and response speeds of photoreceptors in different cellular environments and synthetic tools. Due to the generality of our procedure, as shown by the application to multiple test cases, the photoconversion cross-sections and quantum yields of any photoreceptor might now, in principle, be obtained.

摘要

背景

准确估计生物或酶促反应速率对于理解网络的设计原理以及如何根据需要对生物过程进行实验操作至关重要。在许多情况下,实验限制意味着某些酶促反应速率无法直接测量,需要数学算法来估计它们。在这里,我们描述了一种计算光调节蛋白在构象状态之间转换速率的方法。我们将分析重点放在蓝细菌、植物和许多光遗传学工具中发现的光受体的光敏色素家族上。光敏色素蛋白在活性(P )和非活性(P )状态之间的转换速率与光转换截面成正比,并受光质、光强度、热反应和二聚化的影响。这项工作提出了一种在存在多个非光调节反应的情况下能够准确计算这些光转换截面的方法。

结果

我们计算光转换截面的方法包括三个步骤:i)计算热逆转反应速率;ii)开发所有可能的光转换截面集存在的搜索空间;iii)估计描述我们吸收光谱的消光系数。我们通过使用模拟测试案例证实了所提出的方法产生了准确的结果。我们的测试案例进一步扩展到考虑噪声、多个热反应和二聚化的更现实场景。最后,我们展示了光遗传学工具中常用的拟南芥phyB N端片段的光转换截面。

结论

光转换截面的计算对光感受器和合成生物学家都有影响。我们的方法首次允许直接比较不同细胞环境和合成工具中光感受器的光转换截面和响应速度。由于我们程序的通用性,如在多个测试案例中的应用所示,原则上现在可以获得任何光感受器的光转换截面和量子产率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/c4a92c381330/12918_2016_368_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/9cb5c458214e/12918_2016_368_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/536cc715d9a9/12918_2016_368_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/253393402315/12918_2016_368_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/28c41ef046fb/12918_2016_368_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/065cebca021e/12918_2016_368_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/c4a92c381330/12918_2016_368_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/9cb5c458214e/12918_2016_368_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/536cc715d9a9/12918_2016_368_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/253393402315/12918_2016_368_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/28c41ef046fb/12918_2016_368_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/065cebca021e/12918_2016_368_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f195/5123409/c4a92c381330/12918_2016_368_Fig6_HTML.jpg

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