背景:已发现基因组组成是物种特异性的,并用于区分细菌物种。迄今为止,几乎没有公开的基于组成的方法能够区分最密切相关的生物,包括属内种和种内菌株。因此,有必要开发一种新的方法来解决这个问题。
结果:这里,我们初步确定"四核苷酸衍生的z值皮尔逊相关系数"(TETRA)方法代表了其他已发表的统计方法.然后,我们设计了一种称为“四核苷酸衍生的Z值曼哈顿距离”(TZMD)的新方法,并将其与TETRA方法进行了比较。我们的结果表明,TZMD反映了最大的基因组差异,虽然TETRA在大多数情况下不会,在理论上证明TZMD提供了改进的分辨率。此外,我们对真实数据的分析表明,TZMD改善了物种分化,并明显区分了相似的生物,包括属于同一物种的相似物种,亚种和种内菌株,其中大部分不能用TETRA来区分。此外,TZMD能够确定具有TZMD=0标准的克隆菌株,本质上包含相同的成分,高平均核苷酸同一性和高比例的共享基因组。
结论:我们的广泛评估表明TZMD具有较高的分辨率。这项研究首次提出了一种基于组合物的方法,用于在菌株水平上区分细菌,并证明了组合物也是菌株特异性的。TZMD是一种强大的工具,也是区分克隆和非克隆菌株的第一种易于使用的方法。因此,作为第一个基于组合的应变分型算法,TZMD将在未来促进细菌研究。
BACKGROUND: Genomic composition has been found to be species specific and is used to differentiate bacterial species. To date, almost no published composition-based approaches are able to distinguish between most closely related organisms, including intra-genus species and intra-species strains. Thus, it is necessary to develop a novel approach to address this problem.
RESULTS: Here, we initially determine that the \"tetranucleotide-derived z-value Pearson correlation coefficient\" (TETRA) approach is representative of other published statistical methods. Then, we devise a novel method called \"Tetranucleotide-derived Z-value Manhattan Distance\" (TZMD) and compare it with the TETRA approach. Our results show that TZMD reflects the maximal genome difference, while TETRA does not in most conditions, demonstrating in theory that TZMD provides improved resolution. Additionally, our analysis of real data shows that TZMD improves species differentiation and clearly differentiates similar organisms, including similar species belonging to the same genospecies, subspecies and intraspecific strains, most of which cannot be distinguished by TETRA. Furthermore, TZMD is able to determine clonal strains with the TZMD = 0 criterion, which intrinsically encompasses identical composition, high average nucleotide identity and high percentage of shared genomes.
CONCLUSIONS: Our extensive assessment demonstrates that TZMD has high resolution. This study is the first to propose a composition-based method for differentiating bacteria at the strain level and to demonstrate that composition is also strain specific. TZMD is a powerful tool and the first easy-to-use approach for differentiating clonal and non-clonal strains. Therefore, as the first composition-based algorithm for strain typing, TZMD will facilitate bacterial studies in the future.