Thattai Mukund, van Oudenaarden Alexander
Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.
Genetics. 2004 May;167(1):523-30. doi: 10.1534/genetics.167.1.523.
Stochastic mechanisms can cause a group of isogenic bacteria, each subject to identical environmental conditions, to nevertheless exhibit diverse patterns of gene expression. The resulting phenotypic subpopulations will typically have distinct growth rates. This behavior has been observed in several contexts, including sugar metabolism and pili phase variation. Under fixed environmental conditions, the net growth rate of the population is maximized when all cells are of the fastest growing phenotype, so it is unclear what fitness advantage is conferred by population heterogeneity. However, unlike ideal laboratory conditions, natural environments tend to fluctuate, either periodically or randomly. Here we use a stochastic population model to show that, during growth in such fluctuating environments, a dynamically heterogenous bacterial population can sometimes achieve a higher net growth rate than a homogenous one. By using stochastic mechanisms to sample several distinct phenotypes, the bacteria are able to anticipate and take advantage of sudden changes in their environment. However, this heterogeneity is beneficial only if the bacterial response rate is sufficiently low. Our results could be useful in the design of artificial evolution experiments and in the optimization of fermentation processes.
随机机制可使一群同基因细菌，尽管每个细菌都处于相同的环境条件下，却表现出不同的基因表达模式。由此产生的表型亚群通常会有不同的生长速率。这种行为已在多种情况下被观察到，包括糖代谢和菌毛相变。在固定的环境条件下，当所有细胞都具有最快生长表型时，种群的净生长速率最大，因此尚不清楚种群异质性会带来何种适应性优势。然而，与理想的实验室条件不同，自然环境往往会周期性或随机地波动。在此，我们使用一个随机种群模型来表明，在这种波动环境中生长时，动态异质的细菌种群有时能比同质种群实现更高的净生长速率。通过利用随机机制来抽样几种不同的表型，细菌能够预测并利用其环境中的突然变化。然而，只有当细菌的反应速率足够低时，这种异质性才是有益的。我们的结果可能有助于人工进化实验的设计以及发酵过程的优化。
