用户自定义基因以100万倍的基因组突变率不断进化

Gordon Rix, Rory L. Williams, Hansen Spinner, Vincent J. Hu, Debora S. Marks, Chang C. Liu
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引用次数: 0

摘要

当大自然在数百万年的时间里维持或进化一个基因的功能时,它会产生多种同源序列,这些序列的保存和变化模式包含了有关该基因的丰富的结构、功能和历史信息。然而,自然基因多样性可能排除了功能序列空间的广大区域,包括系统发育和进化的偏心,限制了我们可以提取的信息。我们介绍了一种可访问的实验方法,将长期基因进化压缩到实验室时间尺度,允许直接观察广泛的适应和分化,然后推断任何可选择基因的结构,功能和环境约束。为了实现这种方法,我们开发了一种新的正交DNA复制(OrthoRep)系统,该系统在体内以每个碱基10^-4个替换的速率持久地对选定的基因进行超突变。当使用OrthoRep进化一个条件必需的不适应酶时,我们获得了数千个独特的多突变序列,许多对相隔60个氨基酸(偏离率为15%),揭示了影响酶适应的已知和新的因素。进化序列的适应度无法通过训练自然变异的先进机器学习模型来预测。我们认为,OrthoRep支持前瞻性和系统性地发现影响基因进化的制约因素,发现适应度景观中的新区域,以及在生物分子工程中的一般应用。
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Continuous evolution of user-defined genes at 1-million-times the genomic mutation rate
When nature maintains or evolves a gene's function over millions of years at scale, it produces a diversity of homologous sequences whose patterns of conservation and change contain rich structural, functional, and historical information about the gene. However, natural gene diversity likely excludes vast regions of functional sequence space and includes phylogenetic and evolutionary eccentricities, limiting what information we can extract. We introduce an accessible experimental approach for compressing long-term gene evolution to laboratory timescales, allowing for the direct observation of extensive adaptation and divergence followed by inference of structural, functional, and environmental constraints for any selectable gene. To enable this approach, we developed a new orthogonal DNA replication (OrthoRep) system that durably hypermutates chosen genes at a rate of >10^-4 substitutions per base in vivo. When OrthoRep was used to evolve a conditionally essential maladapted enzyme, we obtained thousands of unique multi-mutation sequences with many pairs >60 amino acids apart (>15% divergence), revealing known and new factors influencing enzyme adaptation. The fitness of evolved sequences was not predictable by advanced machine learning models trained on natural variation. We suggest that OrthoRep supports the prospective and systematic discovery of constraints shaping gene evolution, uncovering of new regions in fitness landscapes, and general applications in biomolecular engineering.
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