Zoeken
Zoeken kan via de modus 'eenvoudig zoeken' (één veld) of uitgebreid via 'geavanceerd zoeken' (meerdere velden). Zo kan je bv. zoeken op een combinatie van een auteursnaam (auteur), een jaartal (jaar) en een documenttype.
Boekenmand
Nuttige resultaten kan je aanvinken en toevoegen aan een mandje. De inhoud hiervan kan je exporteren of afdrukken (naar bv. PDF).
RSS
Op de hoogte blijven van nieuw toegevoegde publicaties binnen uw interessegebied? Dit kan door een RSS-feed (?) te maken van jouw zoekopdracht.
nieuwe zoekopdracht
one publication added to basket [345592] |
Characterizing algal microbiomes using long-read nanopore sequencing
In: Algal Research. Elsevier: Amsterdam. ISSN 2211-9264
| |
Trefwoorden |
Aquaculture Seaweed Ulva Linnaeus, 1753 [WoRMS]
|
Author keywords |
Marine seaweed; Microbiome; Oxford Nanopore Technologies |
Auteurs | | Top |
- van der Loos, L.M.
- D'hondt, S.
- Willems, A.
- De Clerck, O.
|
|
|
Abstract |
Microbes are vitally important for seaweed growth, functioning and reproduction, and are likely to have a big impact on aquaculture. Algae-associated bacteria, however, remain mostly unmonitored in aquaculture. Here, we studied the microbiomes of Ulva australis and Ulva lacinulata, three natural populations and an aquaculture set-up, based on full-length 16S rRNA gene sequences. The microbiome of cultivated Ulva was pronouncedly different from natural populations, and was specifically associated with higher relative abundances of known growth-promoting bacteria Sulfitobacter and Roseobacter. On a smaller scale, there were species-specific differences as well. In general, Ulva-associated communities were highly distinct from environmental seawater and sediment reference samples. We demonstrated a workflow generating full-length 16S rRNA sequences in real-time using Oxford Nanopore sequencing. We compared 3 different reference databases to assign taxonomy with Kraken2 (SILVA, Greengenes and NCBI). In addition, we used Nanopore's cloud-based EPI2ME workflow for comparison. All four methods yielded comparable results in terms of relative abundances on phylum and order level, but differed widely in alpha diversity indices at genus level. Using the NCBI 16S database, especially in combination with the EPI2ME workflow, resulted in a high proportion of false identifications of cyanobacteria due to chloroplast contamination. Based on our results, we recommend assigning taxonomy of Nanopore-derived long-reads with Kraken2 and the SILVA database in seaweed-microbiome studies. The protocols used in this study provide results within 24 h and may be applicable for rapid microbial surveys in aquaculture. |
IMIS is ontwikkeld en wordt gehost door het VLIZ.