A Stomatal Model of Anatomical Tradeoffs Between Gas Exchange and Pathogen Colonization

Response of stomatal density and size in Betula ermanii to contrasting climate conditions: The contributions of genetic and environmental factors

As plant distribution and performance are determined by both environmental and genetic factors, clarifying the contribution of these two factors is a key for understanding plant adaptation and predicting their distribution under ongoing global warming. Betula ermanii is an ideal species for such research because of its wide distribution across diverse environments. Stomatal density and size are crucial traits that plants undergo changes in to adapt to different environments as these traits directly influence plant photosynthesis and transpiration. In this study, we conducted a multi-location common garden experiment using B. ermanii to (1) clarify the contribution of both environmental and genetic factors to the variation in stomatal density and size of B. ermanii, (2) demonstrate the differences in the plasticity of stomatal density and size among B. ermanii populations, and (3) understand how stomatal density and size of B. ermanii would respond to increased temperature and changing precipitation patterns. Genetic factors played a more significant role in stomatal size than environmental factors, suggesting that B. ermanii struggles to adjust its stomatal size in response to a changing environment. Our results also revealed a positive correlation between stomatal size plasticity and original habitat suitability, indicating that in B. ermanii populations in harsh environments exhibit lower adaptability to environmental shifts. Although stomatal density and size of B. ermanii showed the significant responses to increased temperature and shifting precipitation patterns, the response ranges of stomatal density and size to the environmental factors varied among populations. Our findings highlighted the interplay between genetic and environmental factors in determining the intraspecific variation in stomatal density and size in B. ermanii. This indicated that certain populations of B. ermanii exhibit limited stomatal plasticity and adaptability, which could directly affect photosynthesis and transpiration, suggesting potential population-specific fitness implications for B. ermanii under future climate change.

Endophytic Fungi Inoculation Reduces Ramulosis Severity in Gossypium hirsutum Plants

Biotic stress in cotton plants caused by the phytopathogenic fungus Colletotrichum gossypii var. cephalosporioides triggers symptoms of ramulosis, a disease characterized by necrotic spots on young leaves, followed by death of the affected branch's apical meristem, plant growth paralysis, and stimulation of lateral bud production. Severe cases of ramulosis can cause up to 85% yield losses in cotton plantations. Currently, this disease is controlled exclusively by using fungicides. However, few studies have focused on biological alternatives for mitigating the effects of contamination by C. gossypii var. cephalosporioides on cotton plants. Thus, the hypothesis raised is that endophytic fungi isolated from an Arecaceae species (Butia purpurascens), endemic to the Cerrado biome, have the potential to reduce physiological damage caused by ramulosis, decreasing its severity in these plants. This hypothesis was tested using plants grown from seeds contaminated with the pathogen and inoculated with strains of Gibberella moniliformis (BP10EF), Hamigera insecticola (BP33EF), Codinaeopsis sp. (BP328EF), G. moniliformis (BP335EF), and Aspergillus sp. (BP340EF). C. gossypii var. cephalosporioides is a leaf pathogen; thus, the evaluations were focused on leaf parameters: gas exchange, chlorophyll a fluorescence, and oxidative metabolism. The hypothesis that inoculation with endophytic strains can mitigate physiological and photochemical damage caused by ramulosis in cotton was confirmed, as the fungi improved plant growth and stomatal index and density, increased net photosynthetic rate (A) and carboxylation efficiency (A/Ci), and decreased photochemical stress (ABS/RC and DI0/RC) and oxidative stress by reducing enzyme activity (CAT, SOD, and APX) and the synthesis of malondialdehyde (MDA). Control plants developed leaves with a low adaxial stomatal index and density to reduce colonization of leaf tissues by C. gossypii var. cephalosporioides due to the absence of fungal antagonism. The Codinaeopsis sp. strain BP328EF can efficiently inhibit C. gossypii var. cephalosporioides in vitro (81.11% relative inhibition), improve gas exchange parameters, reduce photochemical stress of chlorophyll-a, and decrease lipid peroxidation in attacked leaves. Thus, BP328EF should be further evaluated for its potential effect as a biological alternative for enhancing the resistance of G. hirsutum plants and minimizing yield losses caused by C. gossypii var. cephalosporioides.

Admixture mapping and selection scans identify genomic regions associated with stomatal patterning and disease resistance in hybrid poplars

Variation in fitness components can be linked in some cases to variation in key traits. Metric traits that lie at the intersection of development, defense, and ecological interactions may be expected to experience environmental selection, informing our understanding of evolutionary and ecological processes. Here, we use quantitative genetic and population genomic methods to investigate disease dynamics in hybrid and non-hybrid populations. We focus our investigation on morphological and ecophysiological traits which inform our understanding of physiology, growth, and defense against a pathogen. In particular, we investigate stomata, microscopic pores on the surface of a leaf that regulate gas exchange during photosynthesis and are sites of entry for various plant pathogens. Stomatal patterning traits were highly predictive of disease risk. Admixture mapping identified a polygenic basis of disease resistance. Candidate genes for stomatal and disease resistance map to the same genomic regions and experienced positive selection. Genes with functions to guard cell homeostasis, the plant immune system, components of constitutive defenses, and growth-related transcription factors were identified. Our results indicate positive selection acted on candidate genes for stomatal patterning and disease resistance, potentially acting in concert to structure their variation in naturally formed backcrossing hybrid populations.

Investigating Biochemical and Histopathological Responses between Raspberries and Aculeastrum americanum

Late leaf rust is a fungal disease in raspberries caused by Aculeastrum americanum (Farl.) M. Scholler U. Braun (syn. Thekopsora americana (Farl.) Aime McTaggart) leading to early defoliation and yield losses. Red raspberries (Rubus idaeus L.) are susceptible to this pathogen, although this susceptibility varies among cultivars. In contrast, black raspberries were previously reported to be more resistant (Rubus occidentalis L.) and immune (Rubus niveus Thunb.) to this pathogen, raising their importance in plant breeding programs. However, what features make them respond differently to the same pathogen? In this study, we characterize for the first time the pre- and post-formed structural and biochemical defense mechanisms of R. idaeus cv. Autumn Bliss, R. occidentalis and R. niveus. Ultrastructural and histopathological analyses were used to uncover the interactions between these raspberries and A. americanum. The ultrastructural results indicate that the pathogen germinates on both leaf surfaces but can only form appressoria on the stomata. Although the three raspberry species were infected and colonized by A. americanum, a clear difference in susceptibility was observed between them. A compact mesophyll, pre- and post-formed phenolic compounds, and post-formed pectic compounds were the main plant defense mechanisms against fungal colonization. These findings provide new information about raspberries’ defense mechanisms in response to A. americanum and elucidate the interactions occurring in these pathosystems.

Early Detection of Fusarium oxysporum Infection in Processing Tomatoes (Solanum lycopersicum) and Pathogen-Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling

The early detection of pathogen infections in plants has become an important aspect of integrated disease management. Although previous research demonstrated the idea of applying digital technologies to monitor and predict plant health status, there is no effective system for detecting pathogen infection before symptomatology appears. This paper presents the use of a low-cost and portable electronic nose coupled with machine learning (ML) models for early disease detection. Several artificial neural network models were developed to predict plant physiological data and classify processing tomato plants and soil samples according to different levels of pathogen inoculum by using e-nose outputs as inputs, plant physiological data, and the level of infection as targets. Results showed that the pattern recognition models based on different infection levels had an overall accuracy of 94.4-96.8% for tomato plants and between 94.81% and 96.22% for soil samples. For the prediction of plant physiological parameters (photosynthesis, stomatal conductance, and transpiration) using regression models or tomato plants, the overall correlation coefficient was 0.97-0.99, with very significant slope values in the range 0.97-1. The performance of all models shows no signs of under or overfitting. It is hence proven accurate and valid to use the electronic nose coupled with ML modeling for effective early disease detection of processing tomatoes and could also be further implemented to monitor other abiotic and biotic stressors.

Stomatal opening ratio mediates trait coordinating network adaptation to environmental gradients

A trait coordination network is constructed through intercorrelations of functional traits, which reflect trait-based adaptive strategies. However, little is known about how these networks change across spatial scales, and what drivers and mechanisms mediate this change. This study bridges that gap by integrating functional traits related to plant carbon gain and water economy into the coordination network of Siberian elm (Ulmus pumila), a eurybiont that survives along a 3800 km environmental gradient from humid forest to arid desert. Our results demonstrated that both stomatal density and stomatal size reached a physiological threshold at which adjustments in these traits were not sufficient to cope with the increased environmental stress. Network analysis further revealed that the mechanism for overcoming this threshold, the stomatal opening ratio, g_ratio , was represented by the highest values for centrality across different spatial scales, and therefore mediated the changes in the trait coordination network along environmental gradients. The mediating roles manifested as creating the highest maximum theoretical stomatal conductance (g_smax ) but lowest possible g_ratio for pathogen defense in humid regions, while maintaining the g_ratio 'sweet spot' (c. 20% in this region) for highest water use efficiency in semihumid regions, and having the lowest g_smax and highest g_ratio for gas exchange and leaf cooling in arid regions. These results suggested that the stomatal traits related to control of stomatal movement play fundamental roles in balancing gas exchange, leaf cooling, embolism resistance and pathogen defense. These insights will allow more accurate model parameterization for different regions, and therefore better predictions of species' responses to global change.