Influence of DNA extraction kits on freshwater fungal DNA metabarcoding.
Environmental DNA
Freshwater
Fungi
Metabarcoding
Method
Journal
PeerJ
ISSN: 2167-8359
Titre abrégé: PeerJ
Pays: United States
ID NLM: 101603425
Informations de publication
Date de publication:
2022
2022
Historique:
received:
02
11
2021
accepted:
01
05
2022
entrez:
2
6
2022
pubmed:
3
6
2022
medline:
3
6
2022
Statut:
epublish
Résumé
Environmental DNA (eDNA) metabarcoding is a common technique for efficient biodiversity monitoring, especially of microbes. Recently, the usefulness of aquatic eDNA in monitoring the diversity of both terrestrial and aquatic fungi has been suggested. In eDNA studies, different experimental factors, such as DNA extraction kits or methods, can affect the subsequent analyses and the results of DNA metabarcoding. However, few methodological studies have been carried out on eDNA of fungi, and little is known about how experimental procedures can affect the results of biodiversity analysis. In this study, we focused on the effect of DNA extraction method on fungal DNA metabarcoding using freshwater samples obtained from rivers and lakes. DNA was extracted from freshwater samples using the DNeasy PowerSoil kit, which is mainly used to extractmicrobial DNA from soil, and the DNeasy Blood & Tissue kit, which is commonly used for eDNA studies on animals. We then compared PCR inhibition and fungal DNA metabarcoding results; No PCR inhibition was detected in any of the samples, and no significant differences in the number of OTUs and OTU compositions were detected between the samples processed using different kits. These results indicate that both DNA extraction kits may provide similar diversity results for the river and lake samples evaluated in this study. Therefore, it may be possible to evaluate the diversity of fungi using a unified experimental method, even with samples obtained for diversity studies on other taxa such as those of animals.
Sections du résumé
Background
Environmental DNA (eDNA) metabarcoding is a common technique for efficient biodiversity monitoring, especially of microbes. Recently, the usefulness of aquatic eDNA in monitoring the diversity of both terrestrial and aquatic fungi has been suggested. In eDNA studies, different experimental factors, such as DNA extraction kits or methods, can affect the subsequent analyses and the results of DNA metabarcoding. However, few methodological studies have been carried out on eDNA of fungi, and little is known about how experimental procedures can affect the results of biodiversity analysis. In this study, we focused on the effect of DNA extraction method on fungal DNA metabarcoding using freshwater samples obtained from rivers and lakes.
Methods
DNA was extracted from freshwater samples using the DNeasy PowerSoil kit, which is mainly used to extractmicrobial DNA from soil, and the DNeasy Blood & Tissue kit, which is commonly used for eDNA studies on animals. We then compared PCR inhibition and fungal DNA metabarcoding results;
Results
No PCR inhibition was detected in any of the samples, and no significant differences in the number of OTUs and OTU compositions were detected between the samples processed using different kits. These results indicate that both DNA extraction kits may provide similar diversity results for the river and lake samples evaluated in this study. Therefore, it may be possible to evaluate the diversity of fungi using a unified experimental method, even with samples obtained for diversity studies on other taxa such as those of animals.
Identifiants
pubmed: 35651749
doi: 10.7717/peerj.13477
pii: 13477
pmc: PMC9150701
doi:
Substances chimiques
DNA, Fungal
0
DNA, Environmental
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Pagination
e13477Informations de copyright
©2022 Matsuoka et al.
Déclaration de conflit d'intérêts
The authors declare there are no competing interests.
Références
Sci Rep. 2019 Mar 5;9(1):3581
pubmed: 30837589
Nat Rev Microbiol. 2019 Jun;17(6):339-354
pubmed: 30872817
PLoS One. 2021 May 7;16(5):e0250162
pubmed: 33961651
PLoS One. 2019 Jan 31;14(1):e0210357
pubmed: 30703107
Mol Cell Probes. 2005 Feb;19(1):51-9
pubmed: 15652220
New Phytol. 2013 Jul;199(1):288-299
pubmed: 23534863
PLoS One. 2013 Oct 18;8(10):e76910
pubmed: 24204702
Genome Res. 2007 Mar;17(3):377-86
pubmed: 17255551
Mol Ecol. 2012 Apr;21(8):2045-50
pubmed: 22486824
Sci Rep. 2017 Jan 12;7:40368
pubmed: 28079122
J Appl Microbiol. 2012 Nov;113(5):1014-26
pubmed: 22747964
Bioinformatics. 2011 Aug 15;27(16):2194-200
pubmed: 21700674
Mol Ecol Resour. 2018 May;18(3):557-569
pubmed: 29394525
Brief Bioinform. 2012 Nov;13(6):656-68
pubmed: 22772836
PLoS One. 2015 May 14;10(5):e0127234
pubmed: 25974078
Mol Ecol. 2021 Jul;30(13):3175-3188
pubmed: 32974967
Mol Ecol Resour. 2021 Oct;21(7):2565-2579
pubmed: 34002951
Environ Microbiol. 2021 Aug;23(8):4797-4806
pubmed: 34258854
PLoS One. 2012;7(7):e40863
pubmed: 22808280
Mol Ecol Resour. 2016 Mar;16(2):415-22
pubmed: 26307935
New Phytol. 2010 Oct;188(1):291-301
pubmed: 20636324
Nat Commun. 2016 Aug 30;7:12544
pubmed: 27572523
Ecology. 2009 Dec;90(12):3566-74
pubmed: 20120823
Nat Rev Microbiol. 2016 Jul;14(7):434-47
pubmed: 27296482