The Role of Salicylic Acid in the Expression of RECEPTOR-LIKE PROTEIN 23 and Other Immunity-Related Genes.

The hormone salicylic acid (SA) plays a crucial role in plant immunity by activating responses that arrest pathogen ingress. SA accumulation also penalizes growth, a phenomenon visible in mutants that hyperaccumulate SA, resulting in strong growth inhibition. An important question, therefore, is why healthy plants produce basal levels of this hormone when defense responses are not activated. Here, we show that basal SA levels in unchallenged plants are needed for the expression of a number of immunity-related genes and receptors, such as RECEPTOR-LIKE PROTEIN 23 (RLP23). This was shown by depleting basal SA levels in transgenic Arabidopsis lines through the overexpression of the SA-inactivating hydroxylases DOWNY MILDEW-RESISTANT 6 (DMR6) or DMR6-LIKE OXYGENASE 1. RNAseq analysis revealed that the expression of a subset of immune receptor and signaling genes is strongly reduced in the absence of SA. The biological relevance of this was shown for RLP23: In SA-depleted and SA-insensitive plants, responses to the RLP23 ligand, the microbial pattern nlp24, were strongly reduced, whereas responses to flg22 remained unchanged. We hypothesize that low basal SA levels are needed for the expression of a subset of immune system components that enable early pathogen detection and activation of immunity.

Sensor-based phenotyping of above-ground plant-pathogen interactions.

Plant pathogens cause yield losses in crops worldwide. Breeding for improved disease resistance and management by precision agriculture are two approaches to limit such yield losses. Both rely on detecting and quantifying signs and symptoms of plant disease. To achieve this, the field of plant phenotyping makes use of non-invasive sensor technology. Compared to invasive methods, this can offer improved throughput and allow for repeated measurements on living plants. Abiotic stress responses and yield components have been successfully measured with phenotyping technologies, whereas phenotyping methods for biotic stresses are less developed, despite the relevance of plant disease in crop production. The interactions between plants and pathogens can lead to a variety of signs (when the pathogen itself can be detected) and diverse symptoms (detectable responses of the plant). Here, we review the strengths and weaknesses of a broad range of sensor technologies that are being used for sensing of signs and symptoms on plant shoots, including monochrome, RGB, hyperspectral, fluorescence, chlorophyll fluorescence and thermal sensors, as well as Raman spectroscopy, X-ray computed tomography, and optical coherence tomography. We argue that choosing and combining appropriate sensors for each plant-pathosystem and measuring with sufficient spatial resolution can enable specific and accurate measurements of above-ground signs and symptoms of plant disease.

Visualization of Three Sclerotiniaceae Species Pathogenic on Onion Reveals Distinct Biology and Infection Strategies.

Botrytis squamosa, Botrytis aclada, and Sclerotium cepivorum are three fungal species of the family Sclerotiniaceae that are pathogenic on onion. Despite their close relatedness, these fungi cause very distinct diseases, respectively called leaf blight, neck rot, and white rot, which pose serious threats to onion cultivation. The infection biology of neck rot and white rot in particular is poorly understood. In this study, we used GFP-expressing transformants of all three fungi to visualize the early phases of infection. B. squamosa entered onion leaves by growing either through stomata or into anticlinal walls of onion epidermal cells. B. aclada, known to cause post-harvest rot and spoilage of onion bulbs, did not penetrate the leaf surface but instead formed superficial colonies which produced new conidia. S. cepivorum entered onion roots via infection cushions and appressorium-like structures. In the non-host tomato, S. cepivorum also produced appressorium-like structures and infection cushions, but upon prolonged contact with the non-host the infection structures died. With this study, we have gained understanding in the infection biology and strategy of each of these onion pathogens. Moreover, by comparing the infection mechanisms we were able to increase insight into how these closely related fungi can cause such different diseases.

Quantification of plant morphology and leaf thickness with optical coherence tomography.

Optical coherence tomography (OCT) can be a valuable imaging tool for in vivo and label-free digital plant phenotyping. However, for imaging leaves, air-filled cavities limit the penetration depth and reduce the image quality. Moreover, up to now quantification of leaf morphology with OCT has been done in one-dimensional or two-dimensional images only, and has often been limited to relative measurements. In this paper, we demonstrate a significant increase in OCT imaging depth and image quality by infiltrating the leaf air spaces with water. In the obtained high-quality OCT images the top and bottom surface of the leaf are digitally segmented. Moreover, high-quality en face images of the leaf are obtained from numerically flattened leaves. Segmentation in three-dimensional OCT images is used to quantify the spatially resolved leaf thickness. Based on a segmented leaf image, the refractive index of an infiltrated leaf is measured to be 1.345±0.004, deviating only 1.2% from that of pure water. Using the refractive index and a correction for refraction effects at the air-leaf interface, we quantitatively mapped the leaf thickness. The results show that OCT is an efficient and promising technique for quantitative phenotyping on leaf and tissue level.