揭示蓝绿光合作用:Synechocystis sp. PCC 6803光合作用的波长依赖性数学模型

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Tobias Pfennig, Elena Kullmann, Tomáš Zavřel, Andreas Nakielski, Oliver Ebenhöh, Jan Červený, Gábor Bernát, Anna Barbara Matuszyńska
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引用次数: 0

摘要

蓝藻以其光驱动的化学生产方式,具有彻底改变传统工业和农业生产方式的巨大潜力。要充分利用其光合能力并提高产品产量,研究其与环境(包括光照强度和光谱)之间错综复杂的相互作用至关重要。数学模型为优化这一过程中的策略提供了宝贵的见解。在本研究中,我们为蓝藻 Synechocystis sp. PCC 6803 提出了一个基于常微分方程的模型,以评估其在各种光源(包括单色光)下的表现。我们的模型可以再现各种生理测量量,如实验报告的电子通过四种主要途径的分配、氧气进化以及环境和饱和 CO2 下的碳固定速率。通过捕捉光合作用系统不同组成部分之间的相互作用,我们的模型有助于理解驱动系统行为的潜在机制。我们的模型定性地再现了各种光照条件下发出的荧光,复制了饱和脉冲的脉冲幅度调制(PAM)荧光测定实验。利用我们的模型,我们测试了四种假定的蓝藻状态转换机制,并发现假定藻体脱离的模型在生理上没有任何益处。此外,我们还评估了不同光色和辐照条件下生物技术生产的代谢控制。我们提出了在不同光照条件下过度表达以提高产量的基因目标。通过提供蓝藻光合作用的综合计算模型,我们的工作增强了人们对蓝藻依赖光的行为的基本认识,并首次建立了依赖波长的框架,以系统地测试蓝藻的生物催化生产能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Shedding light on blue-green photosynthesis: A wavelength-dependent mathematical model of photosynthesis in Synechocystis sp. PCC 6803
Cyanobacteria hold great potential to revolutionize conventional industries and farming practices with their light-driven chemical production. To fully exploit their photosynthetic capacity and enhance product yield, it is crucial to investigate their intricate interplay with the environment including the light intensity and spectrum. Mathematical models provide valuable insights for optimizing strategies in this pursuit. In this study, we present an ordinary differential equation-based model for the cyanobacterium Synechocystis sp. PCC 6803 to assess its performance under various light sources, including monochromatic light. Our model can reproduce a variety of physiologically measured quantities, e.g. experimentally reported partitioning of electrons through four main pathways, O2 evolution, and the rate of carbon fixation for ambient and saturated CO2. By capturing the interactions between different components of a photosynthetic system, our model helps in understanding the underlying mechanisms driving system behavior. Our model qualitatively reproduces fluorescence emitted under various light regimes, replicating Pulse-amplitude modulation (PAM) fluorometry experiments with saturating pulses. Using our model, we test four hypothesized mechanisms of cyanobacterial state transitions for ensemble of parameter sets and found no physiological benefit of a model assuming phycobilisome detachment. Moreover, we evaluate metabolic control for biotechnological production under diverse light colors and irradiances. We suggest gene targets for overexpression under different illuminations to increase the yield. By offering a comprehensive computational model of cyanobacterial photosynthesis, our work enhances the basic understanding of light-dependent cyanobacterial behavior and sets the first wavelength-dependent framework to systematically test their producing capacity for biocatalysis.
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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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