MinION Sequencing of colorectal cancer tumour microbiomes-A comparison with amplicon-based and RNA-Sequencing.
Journal
PloS one
ISSN: 1932-6203
Titre abrégé: PLoS One
Pays: United States
ID NLM: 101285081
Informations de publication
Date de publication:
2020
2020
Historique:
received:
20
11
2019
accepted:
29
04
2020
entrez:
21
5
2020
pubmed:
21
5
2020
medline:
4
8
2020
Statut:
epublish
Résumé
Recent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples. DNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation. The average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data. Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a cost-effective tool for rapid microbiome sequencing in a clinical setting.
Sections du résumé
BACKGROUND
Recent evidence suggests a role for the gut microbiome in the development and progression of many diseases and many studies have been carried out to analyse the microbiome using a variety of methods. In this study, we compare MinION sequencing with meta-transcriptomics and amplicon-based sequencing for microbiome analysis of colorectal tumour tissue samples.
METHODS
DNA and RNA were extracted from 11 colorectal tumour samples. 16S rRNA amplicon sequencing and MinION sequencing was carried out using genomic DNA, and RNA-Sequencing for meta-transcriptomic analysis. Non-human MinION and RNA-Sequencing reads, and 16S rRNA amplicon sequencing reads were taxonomically classified using a database built from available RefSeq bacterial and archaeal genomes and a k-mer based algorithm in Kraken2. Concordance between the three platforms at different taxonomic levels was tested on a per-sample basis using Spearman's rank correlation.
RESULTS
The average number of reads per sample using RNA-Sequencing was greater than 129 times that generated using MinION sequencing. However, the average read length of MinION sequences was more than 13 times that of RNA or 16S rRNA amplicon sequencing. Taxonomic assignment using 16S sequencing was less reliable beyond the genus level, and both RNA-Sequencing and MinION sequencing could detect greater numbers of phyla and genera in the same samples, compared to 16S sequencing. Bacterial species associated with colorectal cancer, Fusobacterium nucleatum, Parvimonas micra, Bacteroides fragilis and Porphyromonas gingivalis, were detectable using MinION, RNA-Sequencing and 16S rRNA amplicon sequencing data.
CONCLUSIONS
Long-read sequences generated using MinION sequencing can compensate for low numbers of reads for bacterial classification. MinION sequencing can discriminate between bacterial strains and plasmids and shows potential as a cost-effective tool for rapid microbiome sequencing in a clinical setting.
Identifiants
pubmed: 32433701
doi: 10.1371/journal.pone.0233170
pii: PONE-D-19-32321
pmc: PMC7239435
doi:
Substances chimiques
RNA, Bacterial
0
RNA, Ribosomal, 16S
0
Types de publication
Clinical Trial
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e0233170Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
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