Dataset Information

Exploring Rain as Source of Biological Control Agents for Fire Blight on Apple.

ABSTRACT: Poor survival on plants can limit the efficacy of Biological Control Agents (BCAs) in the field. Yet bacteria survive in the atmosphere, despite their exposure to high solar radiation and extreme temperatures. If conditions in the atmosphere are similar to, or more extreme than, the environmental conditions on the plant surface, then precipitation may serve as a reservoir of robust BCAs. To test this hypothesis, two hundred and fifty-four rain-borne isolates were screened for in vitro inhibition of Erwinia amylovora, the causal agent of fire blight, as well as of other plant pathogenic bacteria, fungi and oomycetes. Two isolates showed strong activity against E. amylovora and other plant pathogenic bacteria, while other isolates showed activity against fungal and oomycete pathogens. Survival assays suggested that the two isolates that inhibited E. amylovora were able to survive on apple blossoms and branches similarly to E. amylovora. Pathogen population size and associated fire blight symptoms were significantly reduced when detached apple blossoms were treated with the two isolates before pathogen inoculation, however, disease reduction on attached blossoms within an orchard was inconsistent. Using whole genome sequencing, the isolates were identified as Pantoea agglomerans and P. ananatis, respectively. A UV-mutagenesis screen pointed to a phenazine antibiotic D-alanylgriseoluteic acid synthesis gene cluster as being at the base of the antimicrobial activity of the P. agglomerans isolate. Our work reveals the potential of precipitation as an under-explored source of BCAs, whole genome sequencing as an effective approach to precisely identify BCAs, and UV-mutagenesis as a technically simple screen to investigate the genetic basis of BCAs. More field trials are needed to determine the efficacy of the identified BCAs in fire blight control.

SUBMITTER: Mechan Llontop ME

PROVIDER: S-EPMC7033628 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Exploring Rain as Source of Biological Control Agents for Fire Blight on Apple.

Mechan Llontop Marco E ME Hurley Kelly K Tian Long L Bernal Galeano Vivian A VA Wildschutte Hans K HK Marine Sasha C SC Yoder Keith S KS Vinatzer Boris A BA

Frontiers in microbiology 20200214

Poor survival on plants can limit the efficacy of Biological Control Agents (BCAs) in the field. Yet bacteria survive in the atmosphere, despite their exposure to high solar radiation and extreme temperatures. If conditions in the atmosphere are similar to, or more extreme than, the environmental conditions on the plant surface, then precipitation may serve as a reservoir of robust BCAs. To test this hypothesis, two hundred and fifty-four rain-borne isolates were screened for <i>in vitro</i> inh ...[more]

PMID: 32117187

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Project description:BACKGROUND: Desirable apple varieties are clonally propagated by grafting vegetative scions onto rootstocks. Rootstocks influence many phenotypic traits of the scion, including resistance to pathogens such as Erwinia amylovora, which causes fire blight, the most serious bacterial disease of apple. The purpose of the present study was to quantify rootstock-mediated differences in scion fire blight susceptibility and to identify transcripts in the scion whose expression levels correlated with this response. RESULTS: Rootstock influence on scion fire blight resistance was quantified by inoculating three-year old, orchard-grown apple trees, consisting of 'Gala' scions grafted to a range of rootstocks, with E. amylovora. Disease severity was measured by the extent of shoot necrosis over time. 'Gala' scions grafted to G.30 or MM.111 rootstocks showed the lowest rates of necrosis, while 'Gala' on M.27 and B.9 showed the highest rates of necrosis. 'Gala' scions on M.7, S.4 or M.9F56 had intermediate necrosis rates. Using an apple DNA microarray representing 55,230 unique transcripts, gene expression patterns were compared in healthy, un-inoculated, greenhouse-grown 'Gala' scions on the same series of rootstocks. We identified 690 transcripts whose steady-state expression levels correlated with the degree of fire blight susceptibility of the scion/rootstock combinations. Transcripts known to be differentially expressed during E. amylovora infection were disproportionately represented among these transcripts. A second-generation apple microarray representing 26,000 transcripts was developed and was used to test these correlations in an orchard-grown population of trees segregating for fire blight resistance. Of the 690 transcripts originally identified using the first-generation array, 39 had expression levels that correlated with fire blight resistance in the breeding population. CONCLUSIONS: Rootstocks had significant effects on the fire blight susceptibility of 'Gala' scions, and rootstock-regulated gene expression patterns could be correlated with differences in susceptibility. The results suggest a relationship between rootstock-regulated fire blight susceptibility and sorbitol dehydrogenase, phenylpropanoid metabolism, protein processing in the endoplasmic reticulum, and endocytosis, among others. This study illustrates the utility of our rootstock-regulated gene expression data sets for candidate trait-associated gene data mining.

Project description:Washington State produces about 70% of total fresh market apples in the United States. One of the primary goals of apple breeding programs is the development of new cultivars resistant to devastating diseases such as fire blight. The overall objective of this study was to investigate high-throughput phenotyping techniques to evaluate fire blight disease symptoms in apple trees. In this regard, normalized stomatal conductance data acquired using a portable photosynthetic system, image data collected using RGB and multispectral cameras, and visible-near infrared spectral reflectance acquired using a hyperspectral sensing system, were independently evaluated to estimate the progression of fire blight infection in young apple trees. Sensors with ranging complexity - from simple RGB to multispectral imaging to hyperspectral system - were evaluated to select the most accurate technique for the assessment of fire blight disease symptoms. The proximal multispectral images and visible-near infrared spectral reflectance data were collected in two field seasons (2016, 2017); while, proximal side-view RGB images and multispectral images using unmanned aerial systems were collected in 2017. The normalized stomatal conductance data was correlated with disease severity rating (r = 0.51, P < 0.05). The features extracted from RGB images (e.g., maximum length of senesced leaves, area of senesced leaves, ratio between senesced and healthy leaf area) and multispectral images (e.g., vegetation indices) also demonstrated potential in evaluation of disease rating (|r| > 0.35, P < 0.05). The average classification accuracy achieved using visible-near infrared spectral reflectance data during the classification of susceptible from symptomless groups ranged between 71 and 93% using partial least square regression and quadratic support vector machine. In addition, fire blight disease ratings were compared with normalized difference spectral indices (NDSIs) that were generated from visible-near infrared reflectance spectra. The selected spectral bands in the range 710-2,340 nm used for computing NDSIs showed consistently higher correlation with disease severity rating than data acquired from RGB and multispectral imaging sensors across multiple seasons. In summary, these specific spectral bands can be used for evaluating fire blight disease severity in apple breeding programs and potentially as early fire blight disease detection tool to assist in production systems.

Dataset Information

Exploring Rain as Source of Biological Control Agents for Fire Blight on Apple.

Publications

Exploring Rain as Source of Biological Control Agents for Fire Blight on Apple.

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