Institute of Biophysics and Physical Biochemistry, University of Regensburg, Universitätsstraße 31, D-93040 Regensburg, Germany.
University of Rennes, Inria, CNRS, IRISA, F-35000 Rennes, France.
Biol Chem. 2019 Feb 25;400(3):367-381. doi: 10.1515/hsz-2018-0344.
For evolutionary studies, but also for protein engineering, ancestral sequence reconstruction (ASR) has become an indispensable tool. The first step of every ASR protocol is the preparation of a representative sequence set containing at most a few hundred recent homologs whose composition determines decisively the outcome of a reconstruction. A common approach for sequence selection consists of several rounds of manual recompilation that is driven by embedded phylogenetic analyses of the varied sequence sets. For ASR of a geranylgeranylglyceryl phosphate synthase, we additionally utilized FitSS4ASR, which replaces this time-consuming protocol with an efficient and more rational approach. FitSS4ASR applies orthogonal filters to a set of homologs to eliminate outlier sequences and those bearing only a weak phylogenetic signal. To demonstrate the usefulness of FitSS4ASR, we determined experimentally the oligomerization state of eight predecessors, which is a delicate and taxon-specific property. Corresponding ancestors deduced in a manual approach and by means of FitSS4ASR had the same dimeric or hexameric conformation; this concordance testifies to the efficiency of FitSS4ASR for sequence selection. FitSS4ASR-based results of two other ASR experiments were added to the Supporting Information. Program and documentation are available at https://gitlab.bioinf.ur.de/hek61586/FitSS4ASR.
对于进化研究,以及蛋白质工程来说,祖先序列重建(ASR)已经成为一种不可或缺的工具。每个 ASR 方案的第一步都是准备一个包含最多几百个最近同源物的代表性序列集,其组成决定了重建的结果。序列选择的一种常见方法包括几轮手动重新编译,这是由各种序列集的嵌入式系统发育分析驱动的。对于香叶基香叶基甘油磷酸合酶的 ASR,我们还额外使用了 FitSS4ASR,它用一种高效且更合理的方法替代了这个耗时的方案。FitSS4ASR 对同源物集应用正交滤波器,以消除异常值序列和那些只具有弱系统发育信号的序列。为了证明 FitSS4ASR 的有用性,我们通过实验确定了八个前身的寡聚状态,这是一个微妙且分类特异性的特性。通过手动方法和 FitSS4ASR 推断的相应祖先具有相同的二聚体或六聚体构象;这种一致性证明了 FitSS4ASR 用于序列选择的效率。另外两个 ASR 实验的基于 FitSS4ASR 的结果已添加到支持信息中。程序和文档可在 https://gitlab.bioinf.ur.de/hek61586/FitSS4ASR 获得。