Introduction Methods Results Conclusions

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Lincoln University. Christchurch, New Zealand. Acknowledgements. Ministry of Business, Innovation and Employment (MBIE). Bio-Protection Research Centre ...
Andreas Makiola

Ian A Dickie1, Travis Glare1, Robert J Holdaway2, Charles K Lee3, Kate Orwin2, Jamie Wood2

[email protected]

1

Bio-Protection Research Centre Lincoln University Christchurch, New Zealand

Bio-Protection Research Centre, Lincoln 2 Landcare Research, Lincoln 3 Waikato DNA Sequencing Facility, School of Science, University of Waikato

How good is eDNA metabarcoding at detecting fungal pathogens? Introduction

Results

• Rust fungi (Pucciniales) are a major group of plant pathogens of global economic and ecological importance. In New Zealand, rust fungi play a key role in normal ecosystem function; some are used as biocontrol agents, while others pose a major biosecurity risk for agriculture and native plants. • As such, large-scale, reliable and cost-effective detection, identification and monitoring of rust fungi is important to industry, government and research institutions. • We investigate biases in the detection and the abundances of rust fungi between metabarcoding and a traditional DNA cloning approach.

• Strong correlation of shared operational taxonomic unit (OTU) abundances between all methods (see Table 1).

• Seven OTUs shared across all three methods, which is much less than expected (18.12±0.51) (see Figure 2). • Neighbour net phylogeny reveals a phylogenetic bias in detection between methods (see Figure 3). Unique cloning OTUs have 1bp mismatch to metabarcoding primer. Table 1. Correlations between proportional abundance of shared OTUs between methods overall and on plot level. Plots and OTUs as random effect variances. Number of shared OTUs / total

unique OTUs (Illumina) observed: 2 expected: 0.46±0.17

Methods

Overall1

Plot level1

Illumina / Ion Torrent

10 / 16 ***

64 / 416 **

Illumina / Cloning

7 / 24 ***

48 / 624 **

Ion Torrent / Cloning

9 /24 ***

55 / 624 ***

1significance

of correlated shared OTU abundances unique OTUs (Cloning) observed: 10 expected: 0.52±0.19

shared OTUs (Illumina/Ion Torrent/Cloning) observed: 7 expected: 18.12±0.51

Figure 1. Myrtle rust (Puccinia psidii), recently discovered on Raoul Island, is one example of the many rusts that are threatening New Zealand. Image: M Daughtrey, Cornell University.

Methods shared OTUs (Ion Torrent/Cloning) observed: 2 expected: 2.88±0.37

• Environmental DNA (eDNA) extraction from pooled leaf samples • 30 (20x20m) grassland plots across all of New Zealand • ITS2 region as fungal barcode • Two fundamentally different next-generation sequencing technologies

shared OTUs (Illumina/Ion Torrent) observed: 3 expected: 2.22±0.42 unique OTUs (Ion Torrent) observed: 2 expected: 0.78±0.18

Cloning

Metabarcoding (Illumina)

Metabarcoding (Ion Torrent)

PCR amplification with rust fungal specific primers

PCR amplification with universal fungal primers

PCR amplification with universal fungal primers

Cloning and low cycle PCR with plasmid primers

Size selection

Size selection

Sanger sequencing

Illumina MiSeq sequencing

Ion Torrent sequencing

Figure 2. Network representing shared (yellow) and unique (white) rust fungal operational taxonomic units (OTUs) between methods (Illumina, Ion Torrent, Cloning). Edge width represents proportional abundance of an OTU within method. Species identities are the best BLAST match. OTUs are considered to be identical >98.5 % BLAST match. Expected numbers of OTUs and 95% confidence interval are based on Monte Carlo random sampling (50 iterations).

Comparison of methods

Acknowledgements Ministry of Business, Innovation and Employment (MBIE) Bio-Protection Research Centre (BPRC)

Figure 3. Neighbour net phylogeny of rust fungal OTUs detected by methods. Illumina (green, squares), Ion Torrent (blue, circles), cloning (orange, triangles). Cluster 1 (equally picked up by all methods), cluster 2 (uniquely detected by cloning) and cluster 3 (uniquely detected by Illumina). Chi-squared test for independence is not significant.

Conclusions • Any biases in quantification are not method dependent. • Metabarcoding primers may discriminate against certain taxa. • We support the use of eDNA metabarcoding for large scale presence (detection) of rust fungal species, and oppose its use for confirming absence of species.