Abstract
Pasteuria spp. are endospore forming bacteria which act as natural antagonists to many of the most economically significant plant parasitic nematodes (PPNs). Highly species-specific nematode suppression may be observed in soils containing a sufficiently high density of Pasteuria spp. spores. This suppression is enacted by the bacteria via inhibition of root invasion and sterilization of the nematode host. Molecular methods for the detection of Pasteuria spp. from environmental DNA (eDNA) have been described; however, these methods are limited in both scale and in depth. We report the use of small subunit rRNA gene metabarcoding to profile Pasteuria spp. and nematode communities in parallel. We have investigated Pasteuria spp. population structure in Scottish soils using eDNA from two sources: soil extracted DNA from the second National Soil Inventory of Scotland (NSIS2); and nematode extracted DNA collected from farms in the East Scotland Farm Network (ESFN). We compared the Pasteuria spp. community culture to both nematode community structure and the physiochemical properties of soils. Our results indicate that Pasteuria spp. populations in Scottish soils are broadly dominated by two sequence variants. The first of these aligns with high identity to Pasteuria hartismeri, a species first described parasitizing Meloidogyne ardenensis, a nematode parasite of woody and perennial plants in northern Europe. The second aligns with a Pasteuria-like sequence which was first recovered from a farm near Edinburgh which was found to contain bacterial feeding nematodes and Pratylenchus spp. encumbered by Pasteuria spp. endospores. Further, soil carbon, moisture, bulk density, and pH showed a strong correlation with the Pasteuria spp. community composition. These results indicate that metabarcoding is appropriate for the sensitive, specific, and semi-quantitative profiling of Pasteuria species from eDNA.
Highlights
Plant parasitic nematodes (PPNs) pose a major threat to global food security, with estimated combined crop losses due to plant parasitic nematodes (PPNs) equating to $80 billion USD each year (Nicol et al, 2011; Jones et al, 2013)
These samples were selected based on the following criteria: only upper soil horizons were included; satellite samples, 4–16 m from the main sample pit, were selected where available allowing assessment of variation at a site; and 11 National Soil Inventory Survey 2 (NSIS2) sample sites, indicated to contain Pasteuria-like sequences based on shallow non-specific 16S rRNA gene sequence analysis of the NSIS2 dataset (Freitag, unpublished data), were included in order to characterize populations at these sites
Considering East Scotland Farm Network (ESFN) samples which did not amplify as failed DNA extractions or PCR reactions, 45.9% of successful ESFN samples returned Pasteuria spp
Summary
Plant parasitic nematodes (PPNs) pose a major threat to global food security, with estimated combined crop losses due to PPNs equating to $80 billion USD each year (Nicol et al, 2011; Jones et al, 2013). Specificity of Pasteuria spp. presents an advantage over broad spectrum chemical control and less targeted management practices such as soil solarization which may remove ecosystem services that are mediated by beneficial organisms, including BCAs (Wang et al, 2006) This host specificity presents a challenge to the use of Pasteuria spp. as inundative or inoculative BCAs, as the interaction of a strain with a native PPN population cannot be predicted without prior testing. One hundred thirty archived NSIS2 DNA samples were removed from storage at −80°C for inclusion in our analysis These samples were selected based on the following criteria: only upper soil horizons were included; satellite samples, 4–16 m from the main sample pit, were selected where available allowing assessment of variation at a site; and 11 NSIS2 sample sites, indicated to contain Pasteuria-like sequences based on shallow non-specific 16S rRNA gene sequence analysis of the NSIS2 dataset (Freitag, unpublished data), were included in order to characterize populations at these sites.
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