bioRxiv · 10.1101/2023.06.21.545968
Optimisation of a DNA extraction protocol for improving the bacterial and fungal classification based on Nanopore sequencing
Abstract
Ribosomal RNA gene amplicon sequencing is commonly used to evaluate microbiome profiles in health and disease and document the impact of interventional treatments. Long-read nanopore sequencing is attractive since it can provide greater classification at the species level. However, optimised protocols to target marker genes for bacterial and fungal profiling are needed. To achieve an increased taxonomic resolution, we developed extraction and long-amplicon PCR-based approaches using Nanopore sequencing. Three sample lysis conditions were applied to a mock microbial community, including known bacterial and fungal species; the 96 MagBead DNA lysis buffer (ML) alone, incorporating bead-beating (MLB) or bead-beating plus MetaPolyzyme enzymatic treatment (MLBE). Profiling of bacterial comparison, MLB had more statistically different bacterial phyla and genera than the others. For fungal profiling, MLB had a significant increase of Ascomycota and a decline of Basidiomycota, subsequently failing to detect Malassezia and Cryptococcus. Also, the principal coordinates analysis (PCoA) plot by the Bray-Curtis index showed a significant difference among groups for bacterial (p = 0.033) and fungal (p = 0.012) profiles. Overall, the microbial profiling and diversity analysis revealed that ML and MLBE have more similarity than MLB for both bacteria and fungi, therefore, bead-beating is not recommended for long-read amplicon sequencing. However, ML alone was suggested as an optimal approach considering DNA yield, classification, reagent cost and hands-on time. This could be an initial proof-of-concept study for simultaneous human microbiome and mycobiome studies.
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Thu, M. S., Sawaswong, V., Chanchaem, P., Klomkliew, P., Campbell, B. J., Hirankarn, N., Fothergill, J. L., Payungporn, S.. 2023-06-21. Optimisation of a DNA extraction protocol for improving the bacterial and fungal classification based on Nanopore sequencing. https://doi.org/10.1101/2023.06.21.545968
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