Theory: Biological systems organize to maximize entropy production subject to information and biophysicochemical constraints

理论：生物系统在信息和生物物理化学约束下组织起来最大化熵产生

• 批准号: 0928742
• 负责人: Joseph Vallino
• 金额: $ 75万
• 依托单位: Marine Biological Laboratory
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0928742&HistoricalAwards=false
• 关键词: Theory; Biological; systems; organize; maximize

This project seeks to answer the question: What is the governing principle that determines how energy and matter flow through biological systems composed of independent but interacting individual organisms, such as occurs in ecosystems? Surprisingly, no predictive theory exists for such a fundamental question. The theory of evolution by natural selection provides a mechanism for self-organization of complex biological structures, but is indeterminate in regards to the emergent properties biological systems follow, if any. As a consequence, the flow of energy and mass through biological systems is often attributed to the chance composition of the community at any instance in time, which is currently unpredictable. This project takes the perspective that biological systems evolve and organize in a manner that is, in a sense, independent of community composition. In the field of nonequilibrium thermodynamics a provisional proof on the theory of maximum entropy production (MEP) has recently been proposed, which posits that steady state systems with sufficient degrees of freedom will organize to maximize the rate of entropy production; that is, the rate of energy dissipation. While organized structures decrease the entropy of a system, they are maintained by external entropy production and have a higher probability of persistence if their presence increases overall entropy production. However, the configuration of structures that generate entropy, and dissipate energy, are constrained by system resources from which the structures must be synthesized from. Hence, biophysicochemical constraints (i.e., elemental resources, organic chemistry, etc.) limit the complexity of dissipative structures. Hurricanes that dissipate thermal energy between the atmosphere and ocean are examples of such dissipative structures. This project proposes that evolution by natural selection produces biological systems that tend to follow a pathway of maximum entropy production by dissipating high temperature radiation and chemical potential. Consequently, an ecosystem composed of organisms that produce entropy at a high rate has a greater probability of persistence and occupation than an ecosystem under the same constraints that produces entropy at a lower rate. While MEP theory does not distinguish between abiotic and biotic systems, biological systems differ from abiotic ones in one key way: biological systems store information within their metagenome. Therefore, it is proposed that abiotic systems maximize entropy production instantaneously, while information stored within the metagenome allows biological systems to produce entropy along pathways that can increase entropy production when averaged over time. For instance, by storing internal energy, biological systems can maintain entropy production and persist during periods when external energy inputs cease. Based on MEP theory, it is hypothesized that biological systems with greater information content will have higher entropy production rates than biological systems with lower information content.To test these hypotheses, the project will use flow through microcosms (i.e., chemostats) as experimental systems inoculated with natural microbial communities. Changes in chemical composition will be used to determine entropy production and massively parallel 454 pyrosequencing applied to hypervariable regions in rRNA genes will provide a direct measure of the information content of complex microbial communities. The project will demonstrate that 1) community composition changes to maximize entropy production, 2) loss of information due to decreases in biodiversity results in lower entropy production and 3) communities organize to maximize entropy when averaged over time. In addition to experimental tests, the project will develop a mathematical framework based on MEP theory to model biogeochemistry orchestrated by biological systems using a distributed metabolic network representation. Computational models and experimental results from this project, including educational outreach activities, will be posted on the project's web site: http://ecosystems.mbl.edu/MEP

这个项目试图回答这样一个问题：决定能量和物质如何在由独立但相互作用的个体有机体组成的生物系统中流动的支配原则是什么，比如在生态系统中？令人惊讶的是，对于这样一个基本问题，没有预测理论存在。自然选择的进化理论为复杂生物结构的自组织提供了一种机制，但在生物系统遵循的涌现特性方面是不确定的，如果有的话。因此，通过生物系统的能量和质量的流动通常归因于群落在任何时刻的偶然组成，这在目前是不可预测的。该项目采用的观点是，生物系统以一种独立于社区组成的方式进化和组织。在非平衡态热力学领域，最近提出了关于最大熵产生理论（MEP）的一个临时证明，该理论假定具有足够自由度的稳态系统会组织起来使熵产生率最大化；也就是能量耗散的速率。虽然有组织的结构降低了系统的熵，但它们是由外部熵产生维持的，如果它们的存在增加了总体熵产生，则具有更高的持久性概率。然而，产生熵和耗散能量的结构的配置受到系统资源的限制，而这些系统资源必须用来合成结构。因此，生物物理化学约束（即元素资源、有机化学等）限制了耗散结构的复杂性。在大气和海洋之间耗散热能的飓风就是这种耗散结构的例子。该项目提出，通过自然选择的进化产生的生物系统倾向于遵循通过消散高温辐射和化学势产生最大熵的途径。因此，由产生高熵率的生物体组成的生态系统比在相同约束条件下产生低熵率的生态系统具有更大的持续和占领的可能性。虽然MEP理论没有区分非生物系统和生物系统，但生物系统与非生物系统在一个关键方面有所不同：生物系统在其宏基因组中存储信息。因此，有人提出，非生物系统瞬时最大化熵产，而存储在宏基因组中的信息允许生物系统沿着可以随着时间平均增加熵产的途径产生熵。例如，通过储存内部能量，生物系统可以维持熵的产生，并在外部能量输入停止时持续存在。基于MEP理论，假设信息含量较高的生物系统比信息含量较低的生物系统具有更高的熵产率。为了验证这些假设，该项目将使用流动通过微观世界（即，化学调节剂）作为接种天然微生物群落的实验系统。化学成分的变化将用于确定熵产，大规模平行454焦磷酸测序应用于rRNA基因的高变区，将提供复杂微生物群落信息含量的直接测量。该项目将证明：1)群落组成的变化使熵产最大化；2)生物多样性减少导致的信息损失导致熵产降低；3)当平均时间时，群落组织使熵产最大化。除了实验测试之外，该项目还将开发一个基于MEP理论的数学框架，以使用分布式代谢网络表示的生物系统来模拟生物地球化学。该项目的计算模型和实验结果，包括教育外展活动，将发布在该项目的网站：http://ecosystems.mbl.edu/MEP上