论文标题
将谱系统计数据与微生物种群的适应性联系起来的大偏差原理
A large deviation principle linking lineage statistics to fitness in microbial populations
论文作者
论文摘要
在指数增殖的微生物种群中，由于单细胞水平的可变性，人口通常以低于单细胞的平均倍增时间的速度加倍。众所周知，从单个谱系获得的生成时间的分布通常不足以确定人口的增长率。从单个血统和人口增长率获得的可观察物之间是否存在明确的关系？我们表明，人口的增长率可以用孤立的血统的平均值来表示。这种谱系表示与大偏差原理有关，该原理是指数增殖种群的一般特征。由于种群不断增长的人群的偏差较大，因此获得生长速率的准确估计所需的谱系数量取决于谱系的持续时间，从而导致估计值的非单调收敛性，我们在合成和实验数据集中验证了估计值。
In exponentially proliferating populations of microbes, the population typically doubles at a rate less than the average doubling time of a single-cell due to variability at the single-cell level. It is known that the distribution of generation times obtained from a single lineage is, in general, insufficient to determine a population's growth rate. Is there an explicit relationship between observables obtained from a single lineage and the population growth rate? We show that a population's growth rate can be represented in terms of averages over isolated lineages. This lineage representation is related to a large deviation principle that is a generic feature of exponentially proliferating populations. Due to the large deviation structure of growing populations, the number of lineages needed to obtain an accurate estimate of the growth rate depends exponentially on the duration of the lineages, leading to a non-monotonic convergence of the estimate, which we verify in both synthetic and experimental data sets.
