Sandberg Troy E, Lloyd Colton J, Palsson Bernhard O, Feist Adam M
Department of Bioengineering, University of California, San Diego, California, USA.
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark.
Appl Environ Microbiol. 2017 Jun 16;83(13). doi: 10.1128/AEM.00410-17. Print 2017 Jul 1.
Adaptive laboratory evolution (ALE) experiments are often designed to maintain a static culturing environment to minimize confounding variables that could influence the adaptive process, but dynamic nutrient conditions occur frequently in natural and bioprocessing settings. To study the nature of carbon substrate fitness tradeoffs, we evolved batch cultures of via serial propagation into tubes alternating between glucose and either xylose, glycerol, or acetate. Genome sequencing of evolved cultures revealed several genetic changes preferentially selected for under dynamic conditions and different adaptation strategies depending on the substrates being switched between; in some environments, a persistent "generalist" strain developed, while in another, two "specialist" subpopulations arose that alternated dominance. Diauxic lag phenotype varied across the generalists and specialists, in one case being completely abolished, while gene expression data distinguished the transcriptional strategies implemented by strains in pursuit of growth optimality. Genome-scale metabolic modeling techniques were then used to help explain the inherent substrate differences giving rise to the observed distinct adaptive strategies. This study gives insight into the population dynamics of adaptation in an alternating environment and into the underlying metabolic and genetic mechanisms. Furthermore, ALE-generated optimized strains have phenotypes with potential industrial bioprocessing applications. Evolution and natural selection inexorably lead to an organism's improved fitness in a given environment, whether in a laboratory or natural setting. However, despite the frequent natural occurrence of complex and dynamic growth environments, laboratory evolution experiments typically maintain simple, static culturing environments so as to reduce selection pressure complexity. In this study, we investigated the adaptive strategies underlying evolution to fluctuating environments by evolving to conditions of frequently switching growth substrate. Characterization of evolved strains via a number of different data types revealed the various genetic and phenotypic changes implemented in pursuit of growth optimality and how these differed across the different growth substrates and switching protocols. This work not only helps to establish general principles of adaptation to complex environments but also suggests strategies for experimental design to achieve desired evolutionary outcomes.
适应性实验室进化（ALE）实验通常设计为维持静态培养环境，以尽量减少可能影响适应过程的混杂变量，但动态营养条件在自然和生物加工环境中经常出现。为了研究碳底物适应性权衡的本质，我们通过连续传代将分批培养物进化到在葡萄糖与木糖、甘油或乙酸盐之间交替的试管中。进化培养物的基因组测序揭示了在动态条件下优先选择的几种遗传变化，以及取决于所切换底物的不同适应策略；在某些环境中，出现了一种持久的“通才”菌株，而在另一种环境中，出现了两个交替占主导地位的“专才”亚群。双相生长延迟表型在通才和专才之间有所不同，在一种情况下完全消失，而基因表达数据区分了菌株为追求生长最优性而实施的转录策略。然后使用基因组规模的代谢建模技术来帮助解释导致观察到的不同适应策略的内在底物差异。这项研究深入了解了交替环境中适应的种群动态以及潜在的代谢和遗传机制。此外，ALE产生的优化菌株具有可用于工业生物加工的潜在表型。进化和自然选择必然会导致生物体在给定环境中提高适应性，无论是在实验室还是自然环境中。然而，尽管复杂和动态的生长环境在自然界中频繁出现，但实验室进化实验通常维持简单、静态的培养环境，以降低选择压力的复杂性。在本研究中，我们通过将进化到频繁切换生长底物的条件来研究对波动环境进化的潜在适应策略。通过多种不同数据类型对进化菌株进行表征，揭示了为追求生长最优性而实施的各种遗传和表型变化，以及这些变化在不同生长底物和切换方案之间的差异。这项工作不仅有助于确立适应复杂环境的一般原则，还为实现所需进化结果的实验设计提供了策略。
