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Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples

View ORCID ProfileSamuel Martin, View ORCID ProfileDarren Heavens, Yuxuan Lan, Samuel Horsfield, View ORCID ProfileMatthew D Clark, View ORCID ProfileRichard M Leggett
doi: https://doi.org/10.1101/2021.05.07.443191
Samuel Martin
1Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
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Darren Heavens
1Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
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  • ORCID record for Darren Heavens
Yuxuan Lan
1Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
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Samuel Horsfield
1Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
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Matthew D Clark
2Natural History Museum, London, SW7 5BD, UK
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Richard M Leggett
1Earlham Institute, Norwich Research Park, Norwich, NR4 7UZ, UK
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  • ORCID record for Richard M Leggett
  • For correspondence: richard.leggett@earlham.ac.uk
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Abstract

Background Adaptive sampling is a method of software-controlled enrichment unique to nanopore sequencing platforms recently implemented in Oxford Nanopore’s own control software. By examining the first few hundred bases of a DNA molecule as it passes through a pore, software can determine if the molecule is sufficiently interesting to sequence in its entirety. If not, the molecule is ejected from the pore by reversing the voltage across it, freeing the pore for a new molecule. User supplied sequences define the targets to be sequenced or ejected. Here we explore the potential of using adaptive sampling for enrichment of rarer species within metagenomic samples.

Results We created a synthetic mock community consisting of seven bacterial species at different proportions ranging from 1.2% to 47% and used this as the basis for a series of enrichment and depletion experiments. To investigate the effect of DNA length on adaptive sampling efficiency, we created sequencing libraries with mean read lengths of 1.7 kbp, 4.7 kbp, 10.6 kbp, and 12.8 kbp and enriched or depleted for individual and multiple species over a series of sequencing runs. Across all experiments enrichment ranged from 1.67-fold for the most abundant species with the shortest read length to 13.87-fold for the least abundant species with the longest read length. Factoring in the reduction to sequence output associated with repeatedly rejecting molecules reduces the calculated efficiency of this enrichment to between 0.96-fold and 4.93-fold. We note that reducing ejections due to false negatives (approximately 36%) would significantly increase efficiency. We used the relationship between abundance, molecule length and enrichment factor to produce a mathematical model of enrichment based on molecule length and relative abundance, whose predictions correlated strongly with experimental data. A web application is provided to allow researchers to explore model predictions in advance of performing their own experiments.

Conclusions Our data clearly demonstrates the benefit for enriching low abundant species in adaptive sampling metagenomic experiments, especially with longer molecules, and our mathematical model can be used to determine whether a given experimental DNA sample is suitable for adaptive sampling. Notably, repeated voltage reversals have no effect on pore stability.

Competing Interest Statement

The authors have not received direct financial contributions from ONT; however, RML and MDC have received a small number of free flow cells as part of the MAP and MARC programmes. RML has also received travel and accommodation expenses to speak at ONT-organized conferences.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted May 08, 2021.
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Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples
Samuel Martin, Darren Heavens, Yuxuan Lan, Samuel Horsfield, Matthew D Clark, Richard M Leggett
bioRxiv 2021.05.07.443191; doi: https://doi.org/10.1101/2021.05.07.443191
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Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples
Samuel Martin, Darren Heavens, Yuxuan Lan, Samuel Horsfield, Matthew D Clark, Richard M Leggett
bioRxiv 2021.05.07.443191; doi: https://doi.org/10.1101/2021.05.07.443191

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