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通过共进化统计建模和深度突变扫描来理解 B1 内酰胺酶中的上位网络。

Understanding epistatic networks in the B1 β-lactamases through coevolutionary statistical modeling and deep mutational scanning.

机构信息

Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada.

Laboratoire de Physique de l'Ecole Normale Supérieure, ENS, Université PSL, CNRS, Sorbonne Université, Université de Paris, F-75005, Paris, France.

出版信息

Nat Commun. 2024 Sep 30;15(1):8441. doi: 10.1038/s41467-024-52614-w.

DOI:10.1038/s41467-024-52614-w
PMID:39349467
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11442494/
Abstract

Throughout evolution, protein families undergo substantial sequence divergence while preserving structure and function. Although most mutations are deleterious, evolution can explore sequence space via epistatic networks of intramolecular interactions that alleviate the harmful mutations. However, comprehensive analysis of such epistatic networks across protein families remains limited. Thus, we conduct a family wide analysis of the B1 metallo-β-lactamases, combining experiments (deep mutational scanning, DMS) on two distant homologs (NDM-1 and VIM-2) and computational analyses (in silico DMS based on Direct Coupling Analysis, DCA) of 100 homologs. The methods jointly reveal and quantify prevalent epistasis, as ~1/3rd of equivalent mutations are epistatic in DMS. From DCA, half of the positions have a >6.5 fold difference in effective number of tolerated mutations across the entire family. Notably, both methods locate residues with the strongest epistasis in regions of intermediate residue burial, suggesting a balance of residue packing and mutational freedom in forming epistatic networks. We identify entrenched WT residues between NDM-1 and VIM-2 in DMS, which display statistically distinct behaviors in DCA from non-entrenched residues. Entrenched residues are not easily compensated by changes in single nearby interactions, reinforcing existing findings where a complex epistatic network compounds smaller effects from many interacting residues.

摘要

在进化过程中,蛋白质家族在保持结构和功能的同时经历了大量的序列分歧。虽然大多数突变是有害的,但进化可以通过分子内相互作用的上位网络来探索序列空间,从而减轻有害突变的影响。然而,对蛋白质家族中这种上位网络的综合分析仍然有限。因此,我们对 B1 金属β-内酰胺酶进行了全家族范围的分析,结合了对两个远亲(NDM-1 和 VIM-2)的实验(深度突变扫描,DMS)和对 100 个同源物的计算分析(基于直接耦合分析的计算 DMS,DCA)。这两种方法共同揭示并量化了普遍的上位作用,因为在 DMS 中,约有 1/3 的等效突变是上位作用的。从 DCA 来看,在整个家族中,有一半的位置在有效耐受突变数量上存在超过 6.5 倍的差异。值得注意的是,这两种方法都在中等残基埋置区域定位到了具有最强上位作用的残基,这表明在形成上位网络时,残基包装和突变自由度之间存在平衡。我们在 DMS 中确定了 NDM-1 和 VIM-2 之间的根深蒂固的 WT 残基,它们在 DCA 中的行为与非根深蒂固的残基有明显的区别。根深蒂固的残基不容易被附近单个相互作用的变化所补偿,这加强了现有发现,即复杂的上位网络会加剧许多相互作用残基的较小影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/b01b939f82ed/41467_2024_52614_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/d07d5d70d422/41467_2024_52614_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/5c6211f25939/41467_2024_52614_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/1f266ece2c4e/41467_2024_52614_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/394a48a3d19a/41467_2024_52614_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/b01b939f82ed/41467_2024_52614_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/d07d5d70d422/41467_2024_52614_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/5c6211f25939/41467_2024_52614_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/1f266ece2c4e/41467_2024_52614_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/394a48a3d19a/41467_2024_52614_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9afe/11442494/b01b939f82ed/41467_2024_52614_Fig5_HTML.jpg

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