Abstract
Over the last two decades coast live oak (CLO) dominance in many California coastal ecosystems has been threatened by the alien invasive pathogen Phytophthora ramorum, the causal agent of sudden oak death. In spite of high infection and mortality rates in some areas, the presence of apparently resistant trees has been observed, including trees that become infected but recover over time. However, identifying resistant trees based on recovery alone can take many years. The objective of this study was to determine if Fourier-transform infrared (FT-IR) spectroscopy, a chemical fingerprinting technique, can be used to identify CLO resistant to P. ramorum prior to infection. Soft independent modeling of class analogy identified spectral regions that differed between resistant and susceptible trees. Regions most useful for discrimination were associated with carbonyl group vibrations. Additionally, concentrations of two putative phenolic biomarkers of resistance were predicted using partial least squares regression; >99% of the variation was explained by this analysis. This study demonstrates that chemical fingerprinting can be used to identify resistance in a natural population of forest trees prior to infection with a pathogen. FT-IR spectroscopy may be a useful approach for managing forests impacted by sudden oak death, as well as in other situations where emerging or existing forest pests and diseases are of concern.
Highlights
Based on the evidence that quantitative differences in the constitutive chemical composition of coast live oak (CLO) phloem tissue are associated with resistance to P. ramorum, the objectives of this study were to determine if Fourier-transform infrared (FT-IR) spectroscopy could be used to (1) discriminate between resistant and susceptible trees, and (2) predict the concentration of putative phenolic biomarkers of resistance, by analyzing phloem tissue collected prior to infection
FT-IR SPECTRA AND Soft independent modeling of class analogy (SIMCA) ANALYSIS Spectral data were collected from the mid-IR region (4000â700 cmâ1), and overlapping peaks were resolved by using standard normal variate (SNV) and second derivative functions (Figure 2, Table 1)
Loadings plots for factor 4 and factor 3 (FLV1) overlaid with preprocessed spectral data indicate areas of DISCUSSION For the first time, we demonstrate that chemical fingerprinting, based on FT-IR spectroscopy of phloem extracts combined with chemometric analysis, can be used to predict resistance in a natural population of CLOs prior to infection by an important invasive pathogen, P. ramorum
Summary
Sudden oak death is a highly destructive disease that has caused extensive mortality of oaks and tanoaks in coastal central and northern California and southwest Oregon over the last two decades (Rizzo et al, 2002; reviewed in Rizzo and Garbelotto, 2003; McPherson et al, 2005, 2010; Meentemeyer et al, 2008; Brown and Allen-Diaz, 2009; Davis et al, 2010; Cobb et al, 2012). Even with high infection and mortality rates, variation in CLO susceptibility to the pathogen has been observed in laboratory assays (Dodd et al, 2005) and within natural populations in field studies (McPherson et al, 2005; Ockels et al, 2007; Nagle et al, 2011). When trees are artificially inoculated with a pathogen, resistance can be defined based on canker length, where resistant trees are those with canker lengths www.frontiersin.org
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