<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Raf Winand</style></author><author><style face="normal" font="default" size="100%">Bert Bogaerts</style></author><author><style face="normal" font="default" size="100%">Stefan Hoffman</style></author><author><style face="normal" font="default" size="100%">Lefèvre, Loic</style></author><author><style face="normal" font="default" size="100%">Delvoye, Maud</style></author><author><style face="normal" font="default" size="100%">Julien Van Braekel</style></author><author><style face="normal" font="default" size="100%">Fu, Qiang</style></author><author><style face="normal" font="default" size="100%">Nancy Roosens</style></author><author><style face="normal" font="default" size="100%">Sigrid C.J. De Keersmaecker</style></author><author><style face="normal" font="default" size="100%">Kevin Vanneste</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Targeting the 16S rRNA gene for bacterial identification in complex mixed samples: comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies) generation sequencing technologies.</style></title><secondary-title><style face="normal" font="default" size="100%">Int J Mol Sci</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">bacteria</style></keyword><keyword><style  face="normal" font="default" size="100%">DNA, Bacterial</style></keyword><keyword><style  face="normal" font="default" size="100%">High-Throughput Nucleotide Sequencing</style></keyword><keyword><style  face="normal" font="default" size="100%">Nanopores</style></keyword><keyword><style  face="normal" font="default" size="100%">RNA, Ribosomal, 16S</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2019 Dec 31</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">21</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Rapid, accurate bacterial identification in biological samples is an important task for microbiology laboratories, for which 16S~rRNA gene Sanger sequencing of cultured isolates is frequently used. In contrast, next-generation sequencing does not require intermediate culturing steps and can be directly applied on communities, but its performance has not been extensively evaluated. We present a comparative evaluation of second (Illumina) and third (Oxford Nanopore Technologies (ONT)) generation sequencing technologies for 16S targeted genomics using a well-characterized reference sample. Different 16S gene regions were amplified and sequenced using the Illumina MiSeq, and analyzed with Mothur. Correct classification was variable, depending on the region amplified. Using a majority vote over all regions, most false positives could be eliminated at the genus level but not the species level. Alternatively, the entire 16S gene was amplified and sequenced using the ONT MinION, and analyzed with Mothur, EPI2ME, and GraphMap. Although &amp;gt;99\% of reads were correctly classified at the genus level, up to $\approx$40\% were misclassified at the species level. Both~technologies, therefore, allow reliable identification of bacterial genera, but can potentially misguide identification of bacterial species, and constitute viable alternatives to Sanger sequencing for rapid analysis of mixed samples without requiring any culturing steps.&lt;/p&gt;
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