M Liem1, T Regensburg-Tuïnk2, C Henkel3, H Jansen4, H Spaink2. 1. Institute Biology, Leiden University, Sylviusweg 72, 2333 BE, Leiden, The Netherlands. m.liem@biology.leidenuniv.nl. 2. Institute Biology, Leiden University, Sylviusweg 72, 2333 BE, Leiden, The Netherlands. 3. Norwegian University of Life Sciences (NMBU), Ås, Norway. 4. Future Genomics Technologies, Leiden, The Netherlands.
Abstract
OBJECTIVE: Currently the majority of non-culturable microbes in sea water are yet to be discovered, Nanopore offers a solution to overcome the challenging tasks to identify the genomes and complex composition of oceanic microbiomes. In this study we evaluate the utility of Oxford Nanopore Technologies (ONT) sequencing to characterize microbial diversity in seawater from multiple locations. We compared the microbial species diversity of retrieved environmental samples from two different locations and time points. RESULTS: With only three ONT flow cells we were able to identify thousands of organisms, including bacteriophages, from which a large part at species level. It was possible to assemble genomes from environmental samples with Flye. In several cases this resulted in > 1 Mbp contigs and in the particular case of a Thioglobus singularis species it even produced a near complete genome. k-mer analysis reveals that a large part of the data represents species of which close relatives have not yet been deposited to the database. These results show that our approach is suitable for scalable genomic investigations such as monitoring oceanic biodiversity and provides a new platform for education in biodiversity.
OBJECTIVE: Currently the majority of non-culturable microbes in sea water are yet to be discovered, Nanopore offers a solution to overcome the challenging tasks to identify the genomes and complex composition of oceanic microbiomes. In this study we evaluate the utility of Oxford Nanopore Technologies (ONT) sequencing to characterize microbial diversity in seawater from multiple locations. We compared the microbial species diversity of retrieved environmental samples from two different locations and time points. RESULTS: With only three ONT flow cells we were able to identify thousands of organisms, including bacteriophages, from which a large part at species level. It was possible to assemble genomes from environmental samples with Flye. In several cases this resulted in > 1 Mbp contigs and in the particular case of a Thioglobus singularis species it even produced a near complete genome. k-mer analysis reveals that a large part of the data represents species of which close relatives have not yet been deposited to the database. These results show that our approach is suitable for scalable genomic investigations such as monitoring oceanic biodiversity and provides a new platform for education in biodiversity.