Vibrational Spectroscopy-Based Chemometrics to Map Host Resistance to Sudden Oak Death

Transcription

1 6 th SOD Symposium, San Francisco Vibrational Spectroscopy-Based Chemometrics to Map Host Resistance to Sudden Oak Death Pierluigi (Enrico) Bonello Department of Plant Pathology

2 Coauthors Anna Conrad Ohio State Univ. (Currently U. Kentucky) Brice McPherson UC Berkeley Dave Wood UC Berkeley Luis Rodriguez-Saona Ohio State Univ. 163

3 Coauthors on Paper Presented at the North American Forest Insect Work Conference, DC, June 3, 2016 David Showalter Ohio State Univ. Jason Smith Univ. Florida Kenneth Raffa Univ. Wisconsin Richard Sniezko USDA-FS DGRC Daniel Herms Ohio State Univ. Sandy Liebhold USDA-FS NRS 164

4 Main points Identification and utilization of host resistance is essential for effective, feasible, long-term management of select tree-killing pests for which top-down control cannot work Non destructive, quick tools for screening are necessary Early and sustained support is required 165

5 Tree-Killing PIPs Tree-killing Phytophagous Insects and Phytopathogens (PIPs) intimately and cryptically associated with hosts damage high fitness value host tissue kill a large proportion of naïve host trees e.g. canker, wilt and rust fungi, bark and wood borers Laurel wilt Emerald ash borer White pine blister rust 166

6 Geography Survival and Reproduction Dispersal Host Tree Defenses PIP Natural Enemies Abiotic Environment Invasion Progression Our focus is on established PIPs Mitigation Prevention Eradication Containment A B C D PIP Source 1 Introduction to Naïve Ecosystem 2 Establishment 3 Spread 4 Outbreak Stages Barriers Management Adapted from Blackburn et al Trends in Ecol and Evol. 167

7 Disease/Pest Triangle Host Amount of Disease /Pest Damage Pathogen/P est Environment 168

8 169

9 Available approaches I. Short-term ecosystem maintenance II. Long-term ecosystem transition Millar and Stephenson Science. 349:

10 Host resistance is effective... with tree-killing PIPs, those that: are cryptically associated with their hosts (extremely difficult to detect and eradicate) are intimately associated with their hosts (facilitates exchange of molecular signals) damage high fitness value host tissue (low damage tolerance, short acceptable lag for PIP control) kill a large proportion of naïve host trees (or coevolved trees with compromised defenses) 171

11 172

12 Modern Host Resistance Programs Trait Discovery Selection and screening of available germplasm Trait Development Breeding or genetic engineering to combine traits Screening/ verification of continued selections Mechanistic basis, interactions Trait Deployment Incorporating heterogeneity for durability/ resilience 173

13 Feasibility of Modern Trait Discovery and Development Marker-assisted selection/ molecular breeding reduce time and labor cost of phenotyping continued selections genetic, genomic, transcriptomic, chemical markers enables non-destructive screening of naïve populations, informing management Harper et al Sci. Rep. 6:

14 Feasibility of Modern Trait Discovery and Development Mechanistic understanding of resistance traits though manipulative studies facilitates development and deployment Cisgenesis rapid and controlled trait incorporation potentially more widely acceptable than transgenesis Transgenesis rapid and controlled trait incorporation dramatically expands germplasm from which resistance traits can be drawn See chestnut blight resistance example provided by Bill Powell s group at SUNY ESF 175

15 (Emerging) Effectiveness of Modern Resistance Deployment Understanding of resistance durability Combining diverse quantitative and qualitative mechanisms across time and/or space Guided by assessments of PIP evolutionary potential Associational/ landscape resistance concepts May allow for deployment of genetically diverse resilient populations vs. only resistant individuals Includes other forms of heterogeneity Stand structure/age, species composition 176

16 Conclusion Deployment of host resistance is feasible and essential for: effective long-term management (forest transitions) of select tree-killing pests, such as Phytophthora ramorum 177

17 The Sudden Oak Death Case COAST LIVE OAK SUSCEPTIBILITY VARIES Google Resistant External canker length measured 10 months following coast live oak inoculation with P. ramorum (N = 154). Susceptible 178

18 Meanwhile, in Marin County CANKER LENGTH PREDICTS SURVIVAL External canker length measured 9 months following inoculation can be used to predict coast live oak survival 7 years following inoculation (McPherson et al., 2014). 179

19 PHYTOCHEMICALS AND DEFENSE Ellagic acid and a tyrosol derivative are associated with resistant CLO (Nagle et al., 2011). Concentrations of 4 putative phenolic biomarkers of resistance were identified from asymptomatic tissue of already infected CLO (McPherson et al., 2014). Ellagic acid and crude methanol extract from CLO phloem tissue both inhibit the growth of P. ramorum in vitro (McPherson et al., 2014). 180

20 PHLOEM PHENOLICS PREDICT RESISTANCE Relationship between resistance and selected putative phenolic biomarkers of resistance. The plot shows the estimated probability of resistance and logit values. The probability of resistance is greater than 80% when logit values are greater than 1.39 (dashed line). From: McPherson et al.,

21 OBJECTIVE Test the feasibility and efficacy of Fourier Transform- Infrared (FT-IR) spectroscopy for discriminating between resistant and susceptible coast live oaks. 182

22 WHY FT-IR IS USEFUL Measures light absorbance for a range of wavelengths. Functional groups, like those found in phytochemicals, have characteristic FT-IR spectra shape and position. Variation in intensity and presence or absence of certain spectral bands can be used to distinguish between samples. Rapid, reproducible, and non-destructive. Predictive models are easily developed using commercially available chemometric software. 183

23 Back to Briones DISEASE PHENOTYPES REVISITED Resistant Susceptible Resistant CLO (n = 22) have significantly smaller canker lengths than susceptible CLO (n = 24) (independent t-test, P < 0.001). Only trees classified as resistant or susceptible in 2012 were used to build the FT-IR model 184

24 Fourier-Transform IR spectroscopy Vibrational spectroscopy-based technique exploits asymmetric molecular stretching, vibration, and rotation of chemical bonds as they are exposed to IR radiation 185

25 Fourier-Transform IR spectroscopy Chemical fingerprint data can be analyzed using various chemometric methods, such as PCA, SIMCA or PLSR 186

26 IMPORTANT SPECTRAL REGIONS IDENTIFED Soft independent modeling of class analogy (SIMCA) was used to identify regions of spectrum that differed between resistant and susceptible CLO and for developing a model for predicting tree resistance. Only extracts from trees classified as resistant or susceptible in 2012 (N = 46) were used for this analysis. 187

27 SIMCA DISCRIMINATES BETWEEN RESISTANT AND SUSCEPTIBLE CLO Interclass distance = 2.4 Resistant Susceptible LEFT SIMCA 3-D class projection plot. Dashed lines indicate 95% CI for each group. RIGHT Coomans plot from 4 factor SIMCA analysis. Dashed lines indicate critical sample residual threshold. 188

28 FT-IR, PHYTOCHEMICALS, AND ESTIMATES OF RESISTANCE FT-IR identified two regions, corresponding primarily to carbonyl group vibrations, that were important for identifying resistant trees. Spectral differences may be associated with phenolic compounds, e.g. quercetin and ellagic acid. 100% of extracts from resistant trees (n = 24) and 100% of extracts from susceptible trees (n = 36) were correctly classified, with an interclass distance of 2.4 (the larger the interclass distance, the less likely samples will be classified as both resistant and susceptible by the SIMCA model) The SIMCA model can be used in the future to predict resistance of naïve trees. 189

29 FT-IR, PHYTOCHEMICALS, AND ESTIMATES OF RESISTANCE Resistant CLOs constituted 16% of the naïve Briones population (14% based on disease expression after inoculation, i.e. canker lengths) In a prior study in Marin County (McPherson et al. 2014), and based on phenolic biomarkers, we estimated that 25-30% of RESIDUAL trees (i.e. after much of the epidemic in the 90s/early 2000s) were resistant 190

30 Percentage Killed 100 Coast Live Oak Mortality for 18 Marin County Plots

31 NEW APPROACHES TO ASSESS RESISTANCE FT-IR spectroscopy coupled with chemometric analysis can identify resistant CLO. Implementation of handheld FT-IR or Raman devices may make infield identification of resistant CLO a reality in the future. 192

32 Next Steps 193

33 NEW APPROACHES TO ASSESS RESISTANCE Using these approaches, naïve CLO could be screened for resistance to P. ramorum relatively quickly and without a need for inoculation. Resistance could then be mapped on the landscape to improve epidemiological understanding and lead to the formulation of rational management plans 194

34 Redwood Park, bleeding + killed coast live oaks, 2011 Peak height and red color represent disease intensity Joshua O Neill, MS Thesis, UC Berkeley 195

35 Funding supporting our work USDA FS FHP - Conducting Activities Related to Monitoring, Extension, Management and Mitigation of the Sudden Oak Death Disease Caused by Phytophthora ramorum OARDC SEEDS Program A new tool for the rapid identification of pest-resistant trees 196

36 THANK YOU! 197