Centre for Nuclear Magnetic Resonance, Ruđer Bošković Institute, Bijenička cesta 54, HR-10000 Zagreb, Croatia.
Center for Algorithmic and Mathematical Methods in Medicine, Biology, and Biotechnology, Mannheim University of Applied Sciences, Paul Wittsack Str. 10, 68163 Mannheim, Germany.
Biosystems. 2024 Dec;246:105355. doi: 10.1016/j.biosystems.2024.105355. Epub 2024 Oct 17.
Ancestral relationships among biological species are often represented and analyzed by means of phylogenetic trees. Substitution and distance matrices are two main types of matrices that are used in phylogeny analyses. Substitution matrices describe a frequency change of amino acids in nucleotide or protein sequence over time, while distance matrices estimate phylogeny using a matrix of pairwise distances based on a particular code or analytical concept. Recent investigation by Elena Fimmel and coworkers (Life 11:1338, 2021) showed that: 1. the robustness of a genetic code against point mutations can be described using the conductance measure, and 2. all possible point mutations of the genetic code can be represented as a weighted graph with weights that correspond to the probabilities of these mutations. In this article, we constructed and tested three novel distance matrices based on conductance measure, that take into account the point mutation robustness of the Standard Genetic Code (SGC). These distance matrices are based on maximum (CMAX), average (CAVG), and minimum (CMIN) conductance-optimized distances between codons coding for individual amino acids. The performance of those distance matrices was tested on a dataset of RecA proteins in Bacteria, Archaea (RadA homolog) and Eukarya (Rad51 homolog). RecA protein and its functional homologs were selected for this investigation since they are essential for the repair and maintenance of DNA, and consequently well conserved and present in all domains of life. PAM250 and BLOSUM62 matrices were usually used as a standard for distance matrix testing. PAM250 and BLOSUM62 substitution matrices specified accurately three biological domains of life according to Carl Woese and George Fox (Proc Natl Acad Sci U S A 74:5088, 1977). An identical result was obtained using three novel distance matrices (CMIN, CMAX, CAVG). This result supports the applicability of novel distance matrices based on the conductance method and suggests that further investigations based on this approach are justified.
生物种系之间的亲缘关系通常通过系统发生树来表示和分析。替代和距离矩阵是两种主要的矩阵类型，用于系统发生分析。替代矩阵描述了核苷酸或蛋白质序列中氨基酸随时间的频率变化，而距离矩阵则使用基于特定代码或分析概念的成对距离矩阵来估计系统发生。Elena Fimmel 及其同事最近的研究表明：1. 遗传密码对点突变的稳健性可以用电导率来描述，2. 遗传密码的所有可能点突变都可以表示为一个加权图，其中权重对应于这些突变的概率。在本文中，我们构建并测试了三种基于电导率的新距离矩阵，这些矩阵考虑了标准遗传密码（SGC）的点突变稳健性。这些距离矩阵基于编码单个氨基酸的密码子之间的最大（CMAX）、平均（CAVG）和最小（CMIN）电导率优化距离。这些距离矩阵在细菌、古菌（RadA 同源物）和真核生物（Rad51 同源物）的 RecA 蛋白数据集上进行了测试。选择 RecA 蛋白及其功能同源物进行这项研究，因为它们对 DNA 的修复和维持至关重要，因此在所有生命领域都得到很好的保守和存在。PAM250 和 BLOSUM62 矩阵通常被用作距离矩阵测试的标准。Carl Woese 和 George Fox（Proc Natl Acad Sci U S A 74:5088, 1977）的 PAM250 和 BLOSUM62 替换矩阵准确地指定了生命的三个生物领域。使用三种新的距离矩阵（CMIN、CMAX、CAVG）也得到了相同的结果。这一结果支持了基于电导法的新距离矩阵的适用性，并表明基于该方法的进一步研究是合理的。
