Assessing the Resolution of Methyltransferase-Mediated DNA Optical Mapping

评估甲基转移酶介导的 DNA 光学映射的分辨率

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作者:Laurens D'Huys, Raffaele Vitale, Elizabete Ruppeka-Rupeika, Vince Goyvaerts, Cyril Ruckebusch, Johan Hofkens

Abstract

Interest in the human microbiome is growing and has been, for the past decade, leading to new insights into disease etiology and general human biology. Stimulated by these advances and in a parallel trend, new DNA sequencing platforms have been developed, radically expanding the possibilities in microbiome research. While DNA sequencing plays a pivotal role in this field, there are some technological hurdles that are yet to be overcome. Targeting of the 16S rRNA gene with amplicon sequencing, for instance, is frequently used for sample composition profiling due to its short sample-to-result time and low cost, which counterbalance its low resolution (genus to species level). On the other hand, more comprehensive methods, namely, whole-genome sequencing (WGS) and shallow shotgun sequencing, are capable of yielding single-gene- and functional-level resolution at a higher cost and much higher sample processing time. It goes without saying that the existing gap between these two types of approaches still calls for the development of a fast, robust, and low-cost analytical platform. In search of the latter, we investigated the taxonomic resolution of methyltransferase-mediated DNA optical mapping and found that strain-level identification can be achieved with both global and whole-genome analyses as well as using a unique identifier (UI) database. In addition, we demonstrated that UI selection in DNA optical mapping, unlike variable region selection in 16S amplicon sequencing, is not limited to any genomic location, explaining the increase in resolution. This latter aspect was highlighted by SCCmec typing in methicillin-resistant Staphylococcus aureus (MRSA) using a simulated data set. In conclusion, we propose DNA optical mapping as a method that has the potential to be highly complementary to current sequencing platforms.

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