Freshwater monitoring by nanopore sequencing

Lara Urban; Andre Holzer; J Jotautas Baronas; Michael Hall; Philipp Braeuninger-Weimer; Michael J Scherm; Daniel J Kunz; Surangi N Perera; Daniel E Martin-Herranz; Edward T Tipper; Susannah J Salter; Maximilian R Stammnitz

To obtain valid taxonomic assignments from freshwater sequencing profiles using nanopore sequencing, twelve different classification tools were compared through several performance metrics (Extended Data Figure 1 ; Methods). Root mean square errors (RMSE) between observed and expected bacteria of the mock community differed slightly across all classifiers. An Enterobacteriaceae overrepresentation was observed across all replicates and classification methods, pointing towards a consistent Escherichia coli amplification bias potentially caused by skewed taxonomic specificities of the selected 16S primer pair (27f and 1492r) 14 . Robust quantifications were obtained by Minimap2 15 alignments against the SILVA v.132 database 16 , for which 99.68 % of classified reads aligned to the expected mock community taxa (mean sequencing accuracy 92.08 %). Minimap2 classifications reached the second lowest RMSE (excluding Enterobacteriaceae), and relative quantifications were highly consistent between mock community replicates. Benchmarking of the classification tools on one aquatic sample further confirmed Minimap2's reliable performance in a more complex bacterial community, although other tools such as SPINGO 17 , MAPseq 18 , or IDTAXA 19 also produced highly concordant results despite variations in processing speed and memory usage (data not shown).