Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses.

IF 10.1 1区 生物学
David Moi, Charles Bernard, Martin Steinegger, Yannis Nevers, Mauricio Langleib, Christophe Dessimoz
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引用次数: 0

Abstract

Recent advances in artificial-intelligence-based protein structure modeling have yielded remarkable progress in predicting protein structures. Because structures are constrained by their biological function, their geometry tends to evolve more slowly than the underlying amino acids sequences. This feature of structures could in principle be used to reconstruct phylogenetic trees over longer evolutionary timescales than sequence-based approaches; however, until now, a reliable structure-based tree-building method has been elusive. Here, we introduce a rigorous framework for empirical tree accuracy evaluation and tested multiple approaches using sequence and structure information. The best results were obtained by inferring trees from sequences aligned using a local structural alphabet-an approach robust to conformational changes that confound traditional structural distance measures. We illustrate the power of structure-informed phylogenetics by deciphering the evolutionary diversification of a particularly challenging family: the fast-evolving RRNPPA quorum-sensing receptors. We were able to propose a more parsimonious evolutionary history for this critical protein family that enables gram-positive bacteria, plasmids and bacteriophages to communicate and coordinate key behaviors. The advent of high-accuracy structural phylogenetics enables a myriad of applications across biology, such as uncovering deeper evolutionary relationships, elucidating unknown protein functions or refining the design of bioengineered molecules.

结构系统发育揭示了革兰氏阳性细菌及其病毒通信系统的进化多样化。
近年来,基于人工智能的蛋白质结构建模在预测蛋白质结构方面取得了显著进展。由于结构受其生物功能的限制,它们的几何结构往往比底层氨基酸序列进化得更慢。与基于序列的方法相比,这种结构特征原则上可用于在更长的进化时间尺度上重建系统发育树;然而,到目前为止,一种可靠的基于结构的树构建方法一直难以捉摸。在这里,我们引入了一个严格的经验树精度评估框架,并使用序列和结构信息测试了多种方法。通过使用局部结构字母表从序列中推断树获得了最好的结果,这是一种对构象变化具有鲁棒性的方法,这种方法混淆了传统的结构距离测量。我们通过破译一个特别具有挑战性的家族的进化多样化来说明结构信息系统发育的力量:快速进化的RRNPPA群体感应受体。我们能够为这个关键蛋白家族提出一个更简洁的进化史,使革兰氏阳性细菌、质粒和噬菌体能够交流和协调关键行为。高精度结构系统发育的出现使生物学领域的无数应用成为可能,例如揭示更深层次的进化关系,阐明未知的蛋白质功能或改进生物工程分子的设计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Nature Structural &Molecular Biology
Nature Structural &Molecular Biology 生物-生化与分子生物学
自引率
1.80%
发文量
160
期刊介绍: Nature Structural & Molecular Biology is a monthly journal that focuses on the functional and mechanistic understanding of how molecular components in a biological process work together. It serves as an integrated forum for structural and molecular studies. The journal places a strong emphasis on the functional and mechanistic understanding of how molecular components in a biological process work together. Some specific areas of interest include the structure and function of proteins, nucleic acids, and other macromolecules, DNA replication, repair and recombination, transcription, regulation of transcription and translation, protein folding, processing and degradation, signal transduction, and intracellular signaling.
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