Characterising drinking water microbiome using Oxford Nanopore MinION^TM sequencer

Characterising drinking water microbiome using Oxford Nanopore MinION^TM sequencer

Xiong, Xinyue (TU Delft Civil Engineering and Geosciences; TU Delft Sanitary Engineering; Oasen)

Medema, G.J. (mentor)
Liu, G. (graduation committee)
Bogaard, T.A. (graduation committee)
Chen, L. (graduation committee)

Delft University of Technology

Civil Engineering

2019-10-10

Biological safety of drinking water is vital for safeguarding public health. Many efforts have been made to explore the microbial universe in drinking water. Nanopore sequencing developed by Oxford Nanopore Technologies is expected to enable PCR-free and rapid identification of species with high accuracy, thus overcoming the impediments of next-generation sequencing. However, the capability of Nanopore sequencing for characterizing the microbiome in drinking water with extremely low biomass content has not been explicitly evaluated. Therefore, this research was carried out to explore the potential of Nanopore sequencing for microbial community characterization and species identification in drinking water. In this study, NanoAmpli-Seq full-length 16S rRNA sequencing and 1D² genomic DNA (gDNA) sequencing were performed on an Oxford Nanopore MinION^TM sequencer. DNA samples of artificial microbial communities were sequenced in order to assess the performance of both sequencing strategies. Subsequently, DNA extracted from tap water was subjected to Nanopore sequencing with the two methods. Results showed that NanoAmpli-Seq 16S rRNA sequencing precisely identified abundant species in artificial microbial communities with high level of reproducibility but biased community profiles due to variation in PCR efficiencies of different species, whereas only 10 species were identified in tap water samples. In addition, raw results from 1D² gDNA sequencing provided an unbiased microbial community profile of an artificial community DNA, while polished data improved the species identification accuracy at the expense of the ability to profile the community structure. Furthermore, 45 hours’ sequencing generated more reliable results than 5 hours’ sequencing with higher profiling accuracy of community structure. Nevertheless, 1D² gDNA sequencing still did not exhibit desirable species identification performance on tap water DNA samples. Notably, despite two enteropathogenic species (Enterobacter cloacae and Laribacter hongkongensis) were identified, the detection of Homo sapiens in the same sample indicated the potential existence of post sample contamination. To conclude, Nanopore sequencing possesses great potential to serve as an efficient tool for study of drinking water microbiology. Specifically, notwithstanding the dissatisfactory performance of NanoAmpli-Seq, its high reproducibility across sequencing runs, adaptability to low DNA quality and quantity, and short turnaround time indicated its potential usefulness to promptly monitor microbial community changes subjected to environmental changes in extremely low-biomass samples (i.e. drinking water). Despite that 1D² gDNA sequencing exhibited superior performance on species identification and microbial community profiling to NanoAmpli-Seq, more endeavors should be made to overcome the hurdles (e.g. demand for high molecular weight gDNA, standard methods for analyzing sequencing data), thereby improving the species identification coverage and microbial community profiling accuracy in drinking water. Understanding the presence and dynamics of the microbial community in DWDS is important for water utilities to gain a better understanding of various microbial processes in drinking water from source to customers’ taps, based on which water treatment strategies could be improved and better management of drinking water quality could be performed.

Drinking water microbiome
Nanopore sequencing
16S rRNA amplicon sequencing
Whole genome sequencing

http://resolver.tudelft.nl/uuid:b4615c5e-5648-4672-8506-c5ae0834e4e6

2020-10-01

Student theses

master thesis

© 2019 Xinyue Xiong