细菌群落的模拟

D. Ashlock, Andrew McEachern
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引用次数: 6

摘要

本研究构建并测试了一个基于agent的细菌群落模型,目的是模拟自然界中大多数细菌无法培养的观察结果。元基因组学的新领域,即从环境中提取DNA的直接、大规模测序,是这一观察结果的来源。经过测试的假设是,细菌形成了相互依赖的群落,因此,当细菌在单一培养基中生长时,它们很少能产生可行的能量。介绍了一种新的游戏——新陈代谢游戏。代理们通过彼此玩这个游戏来产生能量。研究在模拟中使用了不同数量的细菌种类。生存能力的能量水平是通过对单一细菌物种进行模拟来设定的,然后在对多种细菌物种的模拟中对该假设进行测试。多种细菌物种在一种新型的多种群进化算法中进化,称为多世界算法。从模拟中回收的可培养细菌制剂的比例比自然界中发现的要大,但仍然很低,这支持了细菌可能无法培养的假设,因为它们需要伴侣物种的存在。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A simulation of bacterial communities
This study constructs and tests an agent-based model of bacterial communities with the goal of modeling the observation that the majority of bacteria in nature cannot be cultured. The new field of metagenomics, the direct, mass sequencing of DNA recovered from the environment, is the source of this observation. The hypothesis tested is that bacteria form interdependent communities so that viable levels of energy production are rare in bacteria when they are grown in monoculture. A new game, the metabolism game is introduced. Agents produce energy by playing this game with one another. Studies are run with different number of bacterial species in the simulation. The energy level for viability is set by running simulations with a single bacterial species and then the hypothesis is tested in simulations with multiple bacterial species. Multiple bacterial species are evolved in a novel type of multi-population evolutionary algorithm called a multiple worlds algorithm. The fraction of culturable bacterial agents recovered from the simulation is larger than that found in nature but still quite low, supporting the hypothesis that bacteria may not be culturable because they require the presence of partner species.
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