Early warning indicators of tipping points in biological systems

描述（由申请人提供） 翻译后摘要：生物系统往往显示在其状态的突然，根本性的转变，以应对环境中的微小变化。这些“临界点”包括疾病爆发、种群崩溃和细胞分化。考虑到这些临界点中的许多都有 巨大的健康影响-无论是积极的还是消极的-我们必须对这些转变有更多的了解。虽然要完全了解这一系统需要有详细的知识，但非线性动力学理论的最新进展表明，在这种临界点之前存在通用的预警指标。特别是，理论预测，当接近临界点时，系统的波动应该变得更大更慢，这可能预示着生物系统的巨大变化。在这里，我们建议通过实验来测量这些早期预警指标，首先是在突然崩溃之前的群体水平上，然后是在细胞状态改变之前的单个细胞内。我们将首先使用实验室微生物种群，这些微生物种群在恶化过程中表现出灾难性的崩溃， 环境.主要的模型系统将是芽殖酵母，它们合作分解蔗糖。这种增长的合作性质意味着，在每一种环境中，种群生存都需要一个临界的种群规模;因此，为了应对环境的恶化，种群会突然崩溃。然而，通过测量人口规模的日常波动，我们观察到随着临界点的临近，波动的规模和时间尺度都在增加。据我们所知，这项初步工作是对显示灾难性崩溃的人口中这些早期预警指标的首次实验性测量。现在我们已经证明了这种方法的可行性，我们将在不同的恶化环境中测量这些早期预警指标，在存在“作弊”细胞（不有助于分解糖）的情况下，以及在包含多个物种的实验室生态系统中。我们还将研究在空间扩展的人口崩溃之前的人口波动;相邻地区之间的这种耦合预计会掩盖一些早期预警指标，但也可能导致空间模式在临界点之前出现。最后，我们将转移到细胞水平，并探索是否有可能在表型转换之前通过实验观察这些早期预警指标，最初是在糖利用方面。理论预测基因表达将成为 在重要的细胞转变如分化之前更易变。此外，参与遗传电路的关键蛋白质的波动时间尺度应该在转换之前增加。本提案中描述的实验代表了一个独特的机会，可以在突然转变之前探索生物系统的普遍特征。 公共卫生相关性：生物系统可能会经历突然的“临界点”，如疾病爆发、种群崩溃、细胞分化或癌症转移。由于这些转变中有许多对人类健康有着深远的影响，因此能够提前确定这些转变何时发生将具有极大的价值。在这里，我们建议研究可能的预警指标即将临界点的基础上的波动的生物系统。

DESCRIPTION (Provided by the applicant) Abstract: Biological systems often display sudden, radical shifts in their state in response to small changes in the environment. Such ""tipping points"" include disease outbreaks, the collapse of populations, and cellular differentiation. Given that many of these tipping points have huge health implications-either positive or negative-it is essential that we develop an increased understanding of these transitions. Although a complete understanding requires detailed knowledge of the system, recent progress in the theory of nonlinear dynamics argues that there are generic early warning indicators preceding such tipping points. In particular, theory predicts that fluctuations of the system should become larger and slower as the tipping point is approached, potentially signaling dramatic changes in the biological system. Here we propose to measure these early warning indicators experimentally, first at the level of the population before sudden collapse and next within individual cells before a change in cell state. We will start by using laboratory microbial populations that display catastrophic collapse in deteriorating environments. The primary model system will be budding yeast, which cooperatively breakdown the sugar sucrose. The cooperative nature of this growth means that in each environment there is a critical population size required for population survival; in response to a deteriorating environment the population therefore collapses suddenly. However, by measuring the day-to-day fluctuations in the population size we have observed both an increase in the size and timescale of the fluctuations as the tipping point approaches. To our knowledge, this preliminary work is the first experimental measurement of these early warning indicators in a population that displays catastrophic collapse. Now that we have demonstrated the feasibility of the approach, we will measure these early warning indicators in different deteriorating environments, in the presence of ""cheater"" cells (that don't contribute to breaking down the sugar), and in laboratory ecosystems containing more than one species. We will also study population fluctuations before collapse in spatially extended populations; this coupling between neighboring regions is expected to obscure some early warning indicators, but may also cause spatial patterns to emerge before the tipping point. Finally, we will move to the level of the cell and explore whether it is possible to experimentally observe these early warning indicators before a phenotypic switch, initially in sugar utilization. Theory predicts that gene expression will become more variable before important cellular transitions such as differentiation. In addition, the timescale of fluctuations of the key proteins involved in the genetic circuit should increase before the switch. The experiments described in this proposal represent a unique opportunity to explore the universal signatures of biological systems before sudden transitions. Public Health Relevance: Biological systems can experience sudden "tipping points" such as a disease outbreak, population collapse, cellular differentiation, or cancer metastasis. As many of these transitions have profound implications for human health, there would be extreme value in being able to determine in advance when such transitions are about to take place. Here we propose to study possible early warning indicators of impending tipping points that are based upon the fluctuations of the biological system.