Document of bibliographic reference 345592

BibliographicReference record

Type
Bibliographic resource
Type of document
Journal article
BibLvlCode
AS
Title
Characterizing algal microbiomes using long-read nanopore sequencing
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.
WebOfScience code
https://www.webofscience.com/wos/woscc/full-record/WOS:000694713000016
Bibliographic citation
van der Loos, L.M.; D'hondt, S.; Willems, A.; De Clerck, O. (2021). Characterizing algal microbiomes using long-read nanopore sequencing. Algal Research 59: 102456. https://dx.doi.org/10.1016/j.algal.2021.102456
Is peer reviewed
true

Authors

author
Name
Luna van der Loos
Identifier
https://orcid.org/0000-0003-3686-2844
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Fycologie
author
Name
Sofie D'hondt
Identifier
https://orcid.org/0000-0002-2128-0553
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Fycologie
author
Name
Anne Willems
Identifier
https://orcid.org/0000-0002-8421-2881
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biochemie en Microbiologie; Laboratorium voor Microbiologie
author
Name
Olivier De Clerck
Identifier
https://orcid.org/0000-0002-3699-8402
Affiliation
Universiteit Gent; Faculteit Wetenschappen; Vakgroep Biologie; Onderzoeksgroep Fycologie

Links

referenced creativework
type
DOI
accessURL
https://dx.doi.org/10.1016/j.algal.2021.102456

thesaurus terms

term
Aquaculture (term code: 473 - defined in term set: ASFA Thesaurus List)
Seaweed (term code: 9676 - defined in term set: ASFA Thesaurus List)

taxonomic terms

taxonomic terms associated with this publication
Ulva [Green laver]

Document metadata

date created
2021-10-04
date modified
2021-10-05