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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Bacterial signaling can occur within bacteria (intracellular) or between bacteria (intercellular). At times, a group of bacteria behaves like a community. To achieve this, they engage in quorum sensing, the perception of higher cell density that causes changes in gene expression. Quorum sensing involves both extracellular and intracellular signaling. The signaling cascade starts with a molecule called an autoinducer (AI). Individual bacteria produce AIs that move out of the bacterial cell...
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微生物群落中的生理转变驱动的动态共存.

Avaneesh V Narla1, Terence Hwa1, Arvind Murugan2

  • 1Department of Physics, University of California, San Diego.

bioRxiv : the preprint server for biology
|January 23, 2024
PubMed
概括

微生物群体可以通过在生长状态之间转移而动态共存,而不仅仅是固定的相互作用. 这种新模型揭示了生物质密度如何影响微生物生态系统中的物种多样性和稳定性.

科学领域:

  • 微生物生态学 微生物生态学
  • 理论生态学理论生态学
  • 系统生物学 系统生物学

背景情况:

  • 传统的微生物生态系统模型假定固定的物种相互作用和稳定的指数增长.
  • 微生物显著改变它们的环境,将它们从指数增长中推出到压力或非增长状态,这在生态继承和实验室培养中很常见.
  • 现有的模型往往忽视了这些动态生理状态变化对社区结构的影响.

研究的目的:

  • 引入一种新的现象学模型,即社区状态模型,用于理解由动态生理状态变化驱动的微生物共存.
  • 探索受总生物质密度影响的微生物群落动态如何影响物种共存和稳定.
  • 将焦点从详细的物种间相互作用转移到生态系统分析的宏观可观测值.

主要方法:

  • 开发了一个现象学模型 (社区国家模型),它绕过了特定的交互细节.
  • 基于物种的生长偏好,沿着全球生态坐标 (总社区生物质密度) 建模社区状态.
  • 使用简化模型分析了动态共存和整个社区的特征.

主要成果:

  • 确定了动态社区的三个关键特征:在高增长率下增加多样性耐受性,通过分阶级的物种占主导地位增强稳定性,并改变了纳入晚成长物种的要求.
  • 证明微生物群落可以保持多样性和稳定性,即使物种具有快速增长率,但主导着不同的社区状态.

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  • 展示了总生物质密度如何作为影响社区动态的关键生态坐标.

    • 结论:

    • 社区国家模型提供了超越稳定状态假设的微生物共存的见解.
    • 动态的社区状态和宏观的可观察因素,如生物质密度,对于理解微生物生态系统行为至关重要.
    • 这些发现表明了分析复杂微生物群落的新原则,强调了自上而下的方法.