Breaking the Standard: Can Oxford Nanopore Technologies Sequencing Compete With Illumina in Protistan Amplicon Studies?

Advancements in sequencing technologies have revolutionized environmental research, leading to a superior understanding of ecosystem functions. In recent years, high-throughput sequencing techniques evolved from short-read Illumina sequencing to long-read Oxford Nanopore Technologies (ONT) sequencing. While Illumina still dominates the sequencing market and offers high accuracy with low error rates, it is limited by shorter read lengths. ONT provides much longer reads, allowing for greater taxonomic resolution but at the cost of higher error rates. Since existing comparative amplicon analyses deal almost exclusively with prokaryotes, it is uncertain if ONT can serve as a reliable alternative to Illumina regarding protistic metabarcoding approaches. Therefore, this study focuses on comparing error rates, taxonomic classification accuracy, and the community composition of sequences obtained from Illumina and ONT sequencing of the 18S V9 rRNA gene region as well as the full-length 18S rRNA gene from sediment samples. In addition, the applicability of the recently updated Natrix2 amplicon processing pipeline for both sequencing approaches was evaluated. While higher error rates were observed for ONT reads, especially for short reads, the full-length ONT 18S sequences achieved greater taxonomic classification accuracy down to the species level. Illumina V9 sequencing, by contrast, provided reliable classification only down to the phylum level. An analysis of community compositions revealed significant taxonomic differences between the sequencing approaches, with ONT identifying more subtle responses of species to external influences. Nevertheless, the basic community patterns were detectable with all sequencing approaches. To conclude, this study showed for the first time that particularly full-length 18S ONT sequencing can serve as a reliable alternative to Illumina V9 sequencing for protist analysis and may even outperform Illumina depending on the specific research objectives.