Controlling stomatal aperture, a potential strategy for managing plant bacterial disease

Metabolomics reveal root differential metabolites of different root-type alfalfa under drought stress

Introduction

Alfalfa (Medicago sativa L.) is the favored premium feed ingredient in animal husbandry production which is in serious jeopardy due to soil moisture shortages. It is largely unknown how different root types of alfalfa respond to arid-induced stress in terms of metabolites and phytohormones.

Methods

Therefore, rhizomatous rooted M. sativa 'Qingshui' (or QS), tap-rooted M. sativa 'Longdong' (or LD), and creeping rooted M. varia 'Gannong No. 4' (or GN) were investigated to identify metabolites and phytohormones responses to drought conditions.

Results

We found 164, 270, and 68 significantly upregulated differential metabolites were categorized into 35, 38, and 34 metabolic pathways in QS, LD, and GN within aridity stress, respectively. Amino acids, organic acids, sugars, and alkaloids were the four categories of primary differential metabolites detected, which include 6-gingerol, salicylic acid (SA), indole-3-acetic acid (IAA), gibberellin A4 (GA4), abscisic acid (ABA), trans-cinnamic acid, sucrose, L-phenylalanine, L-tyrosine, succinic acid, and nicotinic acid and so on, turns out these metabolites are essential for the resistance of three root-type alfalfa to aridity coercing.

Discussion

The plant hormone signal transduction (PST) pathway was dramatically enriched after drought stress. IAA and ABA were significantly accumulated in the metabolites, indicating that they play vital roles in the response of three root types of alfalfa to water stress, and QS and LD exhibit stronger tolerance than GN under drought stress.

Small holes, big impact: Stomata in plant-pathogen-climate epic trifecta

The regulation of stomatal aperture opening and closure represents an evolutionary battle between plants and pathogens, characterized by adaptive strategies that influence both plant resistance and pathogen virulence. The ongoing climate change introduces further complexity, affecting pathogen invasion and host immunity. This review delves into recent advances on our understanding of the mechanisms governing immunity-related stomatal movement and patterning with an emphasis on the regulation of stomatal opening and closure dynamics by pathogen patterns and host phytocytokines. In addition, the review explores how climate changes impact plant-pathogen interactions by modulating stomatal behavior. In light of the pressing challenges associated with food security and the unpredictable nature of climate changes, future research in this field, which includes the investigation of spatiotemporal regulation and engineering of stomatal immunity, emerges as a promising avenue for enhancing crop resilience and contributing to climate control strategies.

Automated estimation of stomatal number and aperture in haskap (Lonicera caerulea L.)

MAIN CONCLUSION

This study developed the reliable Mask R-CNN model to detect stomata in Lonicera caerulea. The obtained data could be utilized for evaluating some characters such as stomatal number and aperture area. The native distribution of haskap (Lonicera caerulea L.), a small-shrub species, extends through Northern Eurasia, Japan, and North America. Stomatal observation is important for plant research to evaluate the physiological status and to investigate the effect of ploidy levels on phenotypes. However, manual annotation of stomata using microscope software or ImageJ is time consuming. Therefore, an efficient method to phenotype stomata is needed. In this study, we used the Mask Regional Convolutional Neural Network (Mask R-CNN), a deep learning model, to analyze the stomata of haskap efficiently and accurately. We analyzed haskap plants (dwarf and giant phenotypes) with the same ploidy but different phenotypes, including leaf area, stomatal aperture area, stomatal density, and total number of stomata. The R-square value of the estimated stomatal aperture area was 0.92 and 0.93 for the dwarf and giant plants, respectively. The R-square value of the estimated stomatal number was 0.99 and 0.98 for the two phenotypes. The results showed that the measurements obtained using the models were as accurate as the manual measurements. Statistical analysis revealed that the stomatal density of the dwarf plants was higher than that of the giant plants, but the maximum stomatal aperture area, average stomatal aperture area, total number of stomata, and average leaf area were lower than those of the giant plants. A high-precision, rapid, and large-scale detection method was developed by training the Mask R-CNN model. This model can help save time and increase the volume of data.

Prevention of Stomatal Entry as a Strategy for Plant Disease Control against Foliar Pathogenic Pseudomonas Species

The genus Pseudomonas includes some of the most problematic and studied foliar bacterial pathogens. Generally, in a successful disease cycle there is an initial epiphytic lifestyle on the leaf surface and a subsequent aggressive endophytic stage inside the leaf apoplast. Leaf-associated bacterial pathogens enter intercellular spaces and internal leaf tissues by natural surface opening sites, such as stomata. The stomatal crossing is complex and dynamic, and functional genomic studies have revealed several virulence factors required for plant entry. Currently, treatments with copper-containing compounds, where authorized and admitted, and antibiotics are commonly used against bacterial plant pathogens. However, strains resistant to these chemicals occur in the fields. Therefore, the demand for alternative control strategies has been increasing. This review summarizes efficient strategies to prevent bacterial entry. Virulence factors required for entering the leaf in plant-pathogenic Pseudomonas species are also discussed.