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

该项目旨在回答这样一个问题：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主导原则是什么？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提供了一种复杂生物结构的自组织机制，但对于生物系统遵循的涌现特性（如果有的话）是不确定的。因此，通过生物系统的能量和质量的流动通常归因于社区在任何时刻的偶然组成，这是目前不可预测的。 该项目的观点是，生物系统的进化和组织方式，在某种意义上，独立于社区的组成。 在非平衡态热力学领域，最近提出了最大熵产生理论的一个临时证明，该证明假定具有足够自由度的稳态系统将组织以最大化熵产生率，即能量耗散率。虽然有组织的结构减少了系统的熵，但它们通过外部熵产生来维持，并且如果它们的存在增加了整体熵产生，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约束，结构必须从系统资源合成。因此，生物医药化学限制（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，自然选择的进化产生的生物系统往往遵循最大熵产生的路径，通过耗散高温辐射和化学势。 因此，一个由高速率产生熵的生物体组成的生态系统，比一个在相同约束条件下以较低速率产生熵的生态系统，具有更大的持久性和占用概率。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有一个关键的区别：生物系统在其宏基因组中存储信息。因此，有人提出，非生物系统瞬间最大化熵产生，而存储在宏基因组中的信息允许生物系统沿着沿着的路径产生熵，当随时间平均时，该路径可以增加熵产生。例如，通过储存内部能量，生物系统可以保持熵的产生，并在外部能量输入停止时持续存在。 基于MEP理论，假设具有更大信息含量的生物系统将比具有较低信息含量的生物系统具有更高的熵产生率。为了验证这些假设，该项目将使用流通微观世界（即，恒化器）作为用天然微生物群落接种的实验系统。 化学组成的变化将用于确定熵产生，而应用于rRNA基因高变区的大规模并行454焦磷酸测序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生最大化，2）由于生物多样性减少而导致的信息损失导致熵产生降低，3）群落组织起来使熵随时间平均时最大化。 除了实验测试外，该项目还将开发一个基于MEP理论的数学框架，以模拟生物系统使用分布式代谢网络表示编排的生物地球化学。该项目的计算模型和实验结果，包括教育推广活动，将张贴在该项目的网站上：http://ecosystems.mbl.edu/MEP

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