Ray J Christian J
Center for Computational Biology Department of Molecular Biosciences, University of Kansas , 2030 Becker Drive, Lawrence, Kansas 66047, United States.
ACS Synth Biol. 2016 Aug 19;5(8):810-6. doi: 10.1021/acssynbio.5b00229. Epub 2016 Mar 7.
Phenotypic memory can predispose cells to physiological outcomes, contribute to heterogeneity in cellular populations, and allow computation of environmental features, such as nutrient gradients. In bacteria and synthetic circuits in general, memory can often be set by protein concentrations: because of the relative stability of proteins, the degradation rate is often dominated by the growth rate, and inheritance is a significant factor. Cells can then be primed to respond to events that recur with frequencies faster than the time to eliminate proteins. Protein memory can be extended if cells reach extremely low growth rates or no growth. Here we characterize the necessary time scales for different quantities of protein memory, measured as relative entropy (Kullback-Leibler divergence), for a variety of cellular growth arrest transition dynamics. We identify a critical manifold in relative protein degradation/growth arrest time scales where information is, in principle, preserved indefinitely because proteins are trapped at a concentration determined by the competing time scales as long as nongrowth-mediated protein degradation is negligible. We next asked what characteristics of growth arrest dynamics and initial protein distributions best preserve or eliminate information about previous environments. We identified that sharp growth arrest transitions with skewed initial protein distributions optimize flexibility, with information preservation and minimal cost of residual protein. As a result, a nearly memoryless regime, corresponding to a form of bet-hedging, may be an optimal strategy for storage of information by protein concentrations in growth-arrested cells.
表型记忆可使细胞易于出现生理结果,导致细胞群体的异质性,并能对环境特征(如营养梯度)进行计算。一般来说,在细菌和合成回路中,记忆通常可由蛋白质浓度设定:由于蛋白质相对稳定,降解速率往往受生长速率主导,且遗传是一个重要因素。这样,细胞就能为应对比蛋白质消除时间频率更快的重复事件做好准备。如果细胞达到极低生长速率或停止生长,蛋白质记忆就能得到延长。在此,我们针对各种细胞生长停滞转变动力学,以相对熵(库尔贝克 - 莱布勒散度)衡量不同数量蛋白质记忆所需的时间尺度。我们在相对蛋白质降解/生长停滞时间尺度中识别出一个临界流形,在该流形中,只要非生长介导的蛋白质降解可忽略不计,信息原则上就能无限期保存,因为蛋白质被困在由竞争时间尺度决定的浓度下。接下来,我们探究生长停滞动力学和初始蛋白质分布的哪些特征能最佳地保留或消除关于先前环境的信息。我们发现,具有倾斜初始蛋白质分布的急剧生长停滞转变能优化灵活性,实现信息保存且残余蛋白质成本最小。因此,一种近乎无记忆的状态,对应于一种押注策略,可能是生长停滞细胞中通过蛋白质浓度存储信息的最优策略。