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首页> 外文期刊>Proceedings of the National Academy of Sciences of the United States of America >Separating intrinsic from extrinsic fluctuations in dynamic biological systems
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Separating intrinsic from extrinsic fluctuations in dynamic biological systems

机译：在动态生物系统中将内在波动与外在波动分开

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摘要

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.
机译：从细胞中的分子到生态系统中的生物，生物种群由于个体事件的固有随机性以及不断变化的环境的外部影响而发生波动。组合效应通常太复杂而无法进行有效分析，因此许多研究都简化了假设，例如忽略了内在或外在效应以减少模型假设的数量。在这里，我们以数学方式演示了如何使用嵌入在共享波动环境中的两个相同且独立的报告程序来识别内在和外在噪声项，而且还说明这些贡献在质量和数量上与以前所报告的不同。此外，我们显示了通过双重报告者方法确定的噪声贡献对于哪类生物系统与通过内在或外在机制的正确随机模型预测的噪声贡献相对应。我们发现，对于广泛的系统类别，可以使用忽略内在随机性的模型来严格分析来自双重报告者方法的外在噪声。相反，只有在生物学中很少存在的非常特殊的条件下，才可以使用忽略外部随机性的模型来严格分析固有噪声。测试条件是否满足几乎是不可能的，因此双重报告者方法可能会得出有关系统特性（尤其是固有噪声）的错误结论。我们的结果有助于建立一个严格的框架来分析动态波动的生物系统。

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