It is incompletely understood how biophysical properties like protein stability impact molecular evolution and epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. In contrast, nonspecific epistasis results when a mutation is influenced by a large number of nonlocal mutations. As most mutations are pleiotropic, the in vivo folding probability-governed by basal protein stability-is thought to determine activity-enhancing mutational tolerance, implying that nonspecific epistasis is dominant. However, evidence exists for both specific and nonspecific epistasis as the prevalent factor, with limited comprehensive data sets to support either claim. Here, we use deep mutational scanning to probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE with statistically indistinguishable catalytic efficiencies but lower probabilities of folding in vivo compared with wild-type. Local fitness landscapes show slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific epistasis was predominant for the subset of mutations exhibiting positive sign epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes and suggest that transcriptional-translational effects are as important as stability in determining evolutionary outcomes.

中文翻译：

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体内蛋白质折叠概率对局部健身环境的影响。

尚不完全了解蛋白质稳定性等生物物理特性如何影响分子进化和上位性。当突变仅影响另一个突变的表型效应时，通常在物理相互作用的残基上，上位性被定义为特异性。相反，当突变受大量的非局部突变影响时，会产生非特异性上位性。由于大多数突变是多效性的，被基础蛋白稳定性控制的体内折叠概率被认为可以确定增强活性的突变耐受性，这暗示着非特异性上位性是主要的。但是，已有证据表明特异性和非特异性上皮性是普遍因素，有限的综合数据集不能支持这两种说法。这里，我们使用深层突变扫描来探究体内酶折叠概率如何影响局部适应性景观。我们通过计算设计了酰胺酶AmiE的两个不同变体，其催化效率在统计学上无法区分，但与野生型相比，体内折叠的可能性更低。局部健身景观在变体之间显示出细微变化，健身效果的全球分布基本相同。但是，特异性上位是表现出阳性上位上位的突变的主要部分。这些突变映射到AmiE上接近初始突变或接近活性位点的空间上不同的位置。有趣的是，大多数特定的上位性突变是密码子依赖性的，具有不同的同义密码子会导致适应性标志反转。一起，