Ultrafast and accurate 16S microbial community analysis using Kraken 2

Abstract

For decades, 16S ribosomal RNA sequencing has been the primary means for identifying the bacterial species present in a sample with unknown composition. One of the most widely-used tools for this purpose today is the QIIME (Quantitative Insights Into Microbial Ecology) package. Recent results have shown that the newest release, QIIME 2, has higher accuracy than QIIME, MAPseq, and mothur when classifying bacterial genera from simulated human gut, ocean, and soil metagenomes, although QIIME 2 also proved to be the most computationally expensive method. Kraken, first released in 2014, has been shown to provide exceptionally fast and accurate classification for shotgun metagenomics sequencing projects. Bracken, released in 2016, then provided users with the ability to accurately estimate species or genus abundances using Kraken classification results. Kraken 2, which matches the accuracy and speed of Kraken 1, now supports 16S rRNA databases, allowing for direct comparisons to QIIME and similar systems. Here we show that, using the same simulated 16S rRNA metagenomic data as previous studies, Kraken 2 and Bracken are up to 300 times faster and also more accurate at 16S profiling than QIIME 2.

A microbial signature following bariatric surgery is robustly consistent across multiple cohorts

“…In order to compare changes in the abundance of opportunistic pathogens at the species level after surgery across cohorts, 16S rRNA gene datasets were taxonomically classified using the Kraken2 pipeline in addition to the metagenomic datasets. Recent work by Lu et al 45 showed that classification of 16S rRNA gene microbial communities using Kraken2 is fast and accurate.…”

Interpretations of Environmental Microbial Community Studies Are Biased by the Selected 16S rRNA (Gene) Amplicon Sequencing Pipeline

“…Yet another group of tools directly classifies sequencing reads into taxonomic bins without OTU/ASV generation. These tools are typically used for shotgun metagenomics but sometimes also for amplicon analysis, e.g., MEGAN (Mitra et al, 2011), Kraken2 (Lu and Salzberg, 2020) or Centrifuge (Cuscó et al, 2018;Khachatryan et al, 2020). Recovering representative sequences such as OTUs or ASVs allows for further analysis like constructing phylogenetic trees or performing targeted analyses, such as searching for the same sequence or related sequences in other data sets, that is not possible when using direct read classification.…”

A Microbial Signature Following Bariatric Surgery is Robustly Consistent Across Multiple Cohorts

“…In order to compare changes in the abundance of opportunistic pathogens at the species level after surgery across cohorts, 16S rRNA gene datasets were taxonomically classified using the Kraken2 pipeline in addition to the metagenomic datasets. Recent work by Lu et al 2020 [28] showed that classification of 16S rRNA gene microbial communities using Kraken2 is fast and accurate.…”