Biozentrum and Swiss Institute of Bioinformatics, University of Basel, Basel 4056, Switzerland.
Systems Biology Lab, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit, Amsterdam 1081HZ, The Netherlands.
Proc Natl Acad Sci U S A. 2023 Feb 21;120(8):e2211091120. doi: 10.1073/pnas.2211091120. Epub 2023 Feb 13.
Microbes in the wild face highly variable and unpredictable environments and are naturally selected for their average growth rate across environments. Apart from using sensory regulatory systems to adapt in a targeted manner to changing environments, microbes employ bet-hedging strategies where cells in an isogenic population switch stochastically between alternative phenotypes. Yet, bet-hedging suffers from a fundamental trade-off: Increasing the phenotype-switching rate increases the rate at which maladapted cells explore alternative phenotypes but also increases the rate at which cells switch out of a well-adapted state. Consequently, it is currently believed that bet-hedging strategies are effective only when the number of possible phenotypes is limited and when environments last for sufficiently many generations. However, recent experimental results show that gene expression noise generally decreases with growth rate, suggesting that phenotype-switching rates may systematically decrease with growth rate. Such growth rate dependent stability (GRDS) causes cells to be more explorative when maladapted and more phenotypically stable when well-adapted, and we show that GRDS can almost completely overcome the trade-off that limits bet-hedging, allowing for effective adaptation even when environments are diverse and change rapidly. We further show that even a small decrease in switching rates of faster-growing phenotypes can substantially increase long-term fitness of bet-hedging strategies. Together, our results suggest that stochastic strategies may play an even bigger role for microbial adaptation than hitherto appreciated.
野生微生物面临着高度变化和不可预测的环境，并且是根据其在各种环境中的平均生长速度自然选择的。除了使用感官调节系统有针对性地适应不断变化的环境外，微生物还采用了风险分散策略，即在同一种群的细胞中，细胞会随机在不同的表型之间切换。然而，风险分散策略存在一个基本的权衡：增加表型切换率会增加适应不良细胞探索替代表型的速度，但也会增加细胞脱离适应良好状态的速度。因此，目前人们认为，风险分散策略只有在可能的表型数量有限且环境持续足够多的代时才有效。然而，最近的实验结果表明，基因表达噪声通常随生长速率降低，这表明表型切换速率可能随生长速率系统地降低。这种生长速率相关的稳定性（GRDS）导致细胞在适应不良时更具探索性，在适应良好时更具表型稳定性，我们表明，GRDS 几乎可以完全克服限制风险分散的权衡，即使环境多样化且变化迅速，也能实现有效的适应。我们进一步表明，即使是更快生长的表型的切换率略有降低，也可以大大提高风险分散策略的长期适应性。总之，我们的研究结果表明，随机策略在微生物适应中可能发挥的作用比以前想象的更大。
