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Glanz-Idan, N. ; Tarkowski, P. ; Turečková, V. ; Wolf, S. Root-shoot communication in tomato plants: cytokinin as a signal molecule modulating leaf photosynthetic activity. Journal of experimental botany 2020, 71, 247-257. Publisher's VersionAbstract
Photosynthetic activity is affected by exogenous and endogenous inputs, including source-sink balance. Reducing the source to sink ratio by partial defoliation or heavy shading resulted in significant elevation of the photosynthetic rate in the remaining leaf of tomato plants within 3 d. The remaining leaf turned deep green, and its area increased by almost 3-fold within 7 d. Analyses of photosynthetic activity established up-regulation due to increased carbon fixation activity in the remaining leaf, rather than due to altered water balance. Moreover, senescence of the remaining leaf was significantly inhibited. As expected, carbohydrate concentration was lower in the remaining leaf than in the control leaves; however, expression of genes involved in sucrose export was significantly lower. These results suggest that the accumulated fixed carbohydrates were primarily devoted to increasing the size of the remaining leaf. Detailed analyses of the cytokinin content indicated that partial defoliation alters cytokinin biosynthesis in the roots, resulting in a higher concentration of trans-zeatin riboside, the major xylem-translocated molecule, and a higher concentration of total cytokinin in the remaining leaf. Together, our findings suggest that trans-zeatin riboside acts as a signal molecule that traffics from the root to the remaining leaf to alter gene expression and elevate photosynthetic activity. © The Author(s) 2019. Published by Oxford University Press on behalf of the Society for Experimental Biology.
Ohana-Levi, N. ; Munitz, S. ; Ben-Gal, A. ; Schwartz, A. ; Peeters, A. ; Netzer, Y. Multiseasonal grapevine water consumption – Drivers and forecasting. Agricultural and Forest Meteorology 2020, 280. Publisher's VersionAbstract
The interactions between temperature, relative humidity, radiation, wind speed and their effect on plant transpiration in the context of water consumption for irrigation purposes have been studied for over a century. Leaf area has also been established as an important factor affecting water consumption. We analyzed a multivariable time series composed of both meteorological and vegetative variables with a daily temporal resolution for the growing seasons of 2013–2016 for Vitis vinfera ‘Cabernet Sauvignon’ vineyards in the mountainous region in Israel. Time-series analysis of this data was used to characterize seasonal patterns affecting water consumption (ETc) of vines and to quantify interrelations between meteorological and vegetative factors affecting vine water consumption. Moreover, we applied a machine learning regression model to determine the relative influence of meteorological and vegetative factors on ETc during four growing seasons. Finally, we developed an ensemble model for temporally forecasting vine ETc for an additional season using a training dataset of multiple variables. Our findings show that decomposing the time-series dataset uncovered a wider variety of underlying temporal patterns, and enabled quantification of seasonal and daily relationships. Leaf area had a substantial impact on ETc and was found to have a relative influence ranging between 62 and 86% for the different growing seasons. Mean temperature was ranked second followed by minor effects of relative humidity, solar radiation and wind speed that were interchangeably ordered. The ensemble model produced reliable results, with cross validation coefficients   0.9. Incorporating leaf area measurements into the regression model improved both the performance of the model and the training data correlation. Using time-series statistics to explore meteorological and vegetative temporal characteristics, patterns, interrelations and relative effect on evapotranspiration may facilitate the understanding of water consumption processes and assist in generating more effective and skillful irrigation models. © 2019 Elsevier B.V.
Mugabe, D. ; Coyne, C. J. ; Piaskowski, J. ; Zheng, P. ; Ma, Y. ; Landry, E. ; McGee, R. ; Main, D. ; Vandemark, G. ; Zhang, H. ; et al. Quantitative trait loci for cold tolerance in Chickpea. Crop Science 2019, 59, 573-582. Publisher's VersionAbstract
Fall-sown chickpea (Cicer arietinum L.) yields are often double those of spring-sown chickpea in regions with Mediterranean climates that have mild winters. However, winter kill can limit the productivity of fall-sown chickpea. Developing cold-tolerant chickpea would allow the expansion of the current geographic range where chickpea is grown and also improve productivity. The objective of this study was to identify the quantitative trait loci (QTL) associated with cold tolerance in chickpea. An interspecific recombinant inbred line population of 129 lines derived from a cross between ICC 4958, a cold-sensitive desi type (C. arietinum), and PI 489777, a coldtolerant wild relative (C. reticulatum Ladiz), was used in this study. The population was phenotyped for cold tolerance in the field over four field seasons (September 2011-March 2015) and under controlled conditions two times. The population was genotyped using genotypingby- sequencing, and an interspecific genetic linkage map consisting of 747 single nucleotide polymorphism (SNP) markers, spanning a distance of 393.7 cM, was developed. Three significant QTL were found on linkage groups (LGs) 1B, 3, and 8. The QTL on LGs 3 and 8 were consistently detected in six environments with logarithm of odds score ranges of 5.16 to 15.11 and 5.68 to 23.96, respectively. The QTL CT Ca-3.1 explained 7.15 to 34.6% of the phenotypic variance in all environments, whereas QTL CT Ca-8.1 explained 11.5 to 48.4%. The QTLassociated SNP markers may become useful for breeding with further fine mapping for increasing cold tolerance in domestic chickpea. © Crop Science Society of America.
Mello, A. ; Efroni, I. ; Rahni, R. ; Birnbaum, K. D. The Selaginella rhizophore has a unique transcriptional identity compared with root and shoot meristems. New Phytologist 2019, 222, 882-894. Publisher's VersionAbstract
The genus Selaginella resides in an early branch of the land plant lineage that possesses a vasculature and roots. The majority of the Selaginella root system is shoot borne and emerges through a distinctive structure known as the rhizophore, the organ identity of which has been a long-debated question. The rhizophore of Selaginella moellendorffii – a model for the lycophytes – shows plasticity to develop into a root or shoot up until 8 d after angle meristem emergence, after which it is committed to root fate. We subsequently use morphology and plasticity to define the stage of rhizophore identity. Transcriptomic analysis of the rhizophore during its plastic stage reveals that, despite some resemblance to the root meristem, rhizophore gene expression patterns are largely distinct from both shoot and root meristems. Based on this transcriptomic analysis and on historical anatomical work, we conclude that the rhizophore is a distinct organ with unique features. © 2019, Blackwell Publishing Ltd. All rights reserved.
Nissan, H. ; Blum, S. ; Shimoni, E. ; Elbaum, R. Characterization of Silicon Accumulation in Maize Cell Suspension Cultures. Silicon 2019, 11, 2377-2383. Publisher's VersionAbstract
Purpose: Silicon (Si) is an abundant element in the earth’s crust and is available to plants as silicic acid. Silicon uptake by plants is correlated with increased tolerance to various biotic and abiotic stresses. However, cellular mechanisms responsible for its beneficial effects are still unknown. Even its cellular import mechanisms are not well understood. We thus aimed to characterize silicon localization within minimally differentiated Zea mays (Black Mexican Sweet) cells in suspension. Methods: Cells were grown in a medium containing silicon, and the mRNA levels of silicon transporters were measured by real-time PCR. Cells were separated into an insoluble (mainly walls and starch) and a cytoplasmic fraction. Soluble and total silicon was measured by inductively-coupled-plasma – atomic-emission-spectroscopy. Silicon distribution was assessed by transmission electron microscopy. The cell walls were analyzed chemically, and by Raman micro-spectroscopy and thermal gravimetric analysis. Results: Silicon treatment reduced the levels of silicon transporters transcripts, without affecting cell proliferation. About 70 % of the silicon was localized in the cytoplasm, mostly in vesicles. We found indications that silicon affected the secondary structure of proteins and thermally stabilized starch. Silicon was loosely bound, and diffused out of the cells within 24 hours. Conclusions: Our results show that silicon binds spontaneously to cell walls/starch and accumulates in cytoplasm vesicles. These processes allow the cells to accumulate silicon against its concentration gradient in solution. However, cellular intake acts against reversible diffusion processes, probably through the aquaporin silicon channels (Lsi1, Lsi6) that exchange the cellular silicon with the surrounding medium. © 2015, Springer Science+Business Media Dordrecht.
Gabay, G. ; Faigenboim, A. ; Dahan, Y. ; Izhaki, Y. ; Itkin, M. ; Malitsky, S. ; Elkind, Y. ; Flaishman, M. A. Transcriptome analysis and metabolic profiling reveal the key role of α-linolenic acid in dormancy regulation of European pear. Journal of Experimental Botany 2019, 70, 734-737. Publisher's VersionAbstract
Deciduous trees require sufficient chilling during winter dormancy to grow. To decipher the dormancy-regulating mechanism, we carried out RNA sequencing (RNA-Seq) analysis and metabolic profiling of European pear (Pyrus communis L.) vegetative buds during the dormancy phases. Samples were collected from two cultivars that differed greatly in their chilling requirements: Spadona' (SPD), a low chilling requirement cultivar; and Harrow Sweet (HS), a high chilling requirement cultivar. Comparative transcriptome analysis revealed >8500 differentially expressed transcripts; most were related to metabolic pathways. Out of 174 metabolites, 44 displayed differential levels in both cultivars, 38 were significantly changed only in SPD, and 15 only in HS. Phospholipids were mostly accumulated at the beginning of dormancy, sugars between before dormancy and mid-dormancy, and fatty acids, including α-linolenic acid, at dormancy break. Differentially expressed genes underlying previously identified major quantitative trait loci (QTLs) in linkage group 8 included genes related to the α-linolenic acid pathway, 12-oxophytodienoate reductase 2-like, and the DORMANCY-ASSOCIATED MADS-BOX (DAM) genes, PcDAM1 and PcDAM2, putative orthologs of PpDAM1 and PpDAM2, confirming their role for the first time in European pear. Additional new putative dormancy-related uncharacterized genes and genes related to metabolic pathways are suggested. These results suggest the crucial role of α-linolenic acid and DAM genes in pear bud dormancy phase transitions. © 2018 The Author(s).
Bahat, I. ; Netzer, Y. ; Ben-Gal, A. ; Grünzweig, J. ; Peeters, A. ; Cohen, Y. Comparison of water potential and yield parameters under uniform and variable rate drip irrigation in a cabernet sauvignon vineyard. In Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019; Precision Agriculture 2019 - Papers Presented at the 12th European Conference on Precision Agriculture, ECPA 2019; 2019; pp. 125-131. Publisher's VersionAbstract
An experiment in variable-rate drip irrigation (VRDI) was aimed at reducing variance of midday stem water potential (SWP) and in yield parameters by applying VRDI in a highly variable vineyard. During 2018, irrigation was separated into VRDI and uniform irrigation (UI) blocks. Each block was delineated to 10 management cells, and results of 2018 season were compared to 2017 season under UI. Standard error (SE) of SWP in the last 3 measurements before harvest decreased in the VRDI block in 2018 compared to 2017 by 14-44%. In contrast, in the UI block, SE in 2018 was higher by 11-42% compared to 2017. SE of fruit yield showed a similar trend. Applying principles of precision irrigation may lead to a more homogeneous vineyard in the parameters described above and to improved wine quality. © Wageningen Academic Publishers 2019
Qubaja, R. ; Grünzweig, J. ; Rotenberg, E. ; Yakir, D. Evidence for large carbon sink and long residence time in semiarid forests based on 15 year flux and inventory records. Global Change Biology 2019. Publisher's VersionAbstract
The rate of change in atmospheric CO2 is significantly affected by the terrestrial carbon sink, but the size and spatial distribution of this sink, and the extent to which it can be enhanced to mitigate climate change are highly uncertain. We combined carbon stock (CS) and eddy covariance (EC) flux measurements that were collected over a period of 15 years (2001–2016) in a 55 year old 30 km2 pine forest growing at the semiarid timberline (with no irrigating or fertilization). The objective was to constrain estimates of the carbon (C) storage potential in forest plantations in such semiarid lands, which cover  18% of the global land area. The forest accumulated 145–160 g C m−2 year−1 over the study period based on the EC and CS approaches, with a mean value of 152.5 ± 30.1 g C m−2 year−1 indicating 20% uncertainty in carbon uptake estimates. Current total stocks are estimated at 7,943 ± 323 g C/m2 and 372 g N/m2. Carbon accumulated mostly in the soil ( 71% and 29% for soil and standing biomass carbon, respectively) with long soil carbon turnover time (59 years). Regardless of unexpected disturbances beyond those already observed at the study site, the results support a considerable carbon sink potential in semiarid soils and forest plantations, and imply that afforestation of even 10% of semiarid land area under conditions similar to that of the study site, could sequester  0.4 Pg C/year over several decades. © 2019 John Wiley & Sons Ltd
Halbritter, A. H. ; De Boeck, H. J. ; Eycott, A. E. ; Reinsch, S. ; Robinson, D. A. ; Vicca, S. ; Berauer, B. ; Christiansen, C. T. ; Estiarte, M. ; Grünzweig, J. ; et al. The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx). Methods in Ecology and Evolution 2019. Publisher's VersionAbstract
Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world. © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
De Boeck, H. J. ; Bloor, J. M. G. ; Aerts, R. ; Bahn, M. ; Beier, C. ; Emmett, B. A. ; Estiarte, M. ; Grünzweig, J. ; Halbritter, A. H. ; Holub, P. ; et al. Understanding ecosystems of the future will require more than realistic climate change experiments – A response to Korell et al. Global Change Biology 2019. Publisher's Version
Herrmann, I. ; Bdolach, E. ; Montekyo, Y. ; Rachmilevitch, S. ; Townsend, P. A. ; Karnieli, A. Assessment of maize yield and phenology by drone-mounted superspectral camera. Precision Agriculture 2019. Publisher's VersionAbstract
The capability of unmanned aerial vehicle (UAV) spectral imagery to assess maize yield under full and deficit irrigation is demonstrated by a Tetracam MiniMCA12 11 bands camera. The MiniMCA12 was used to image an experimental field of 19 maize hybrids. Yield prediction models were explored for different maize development stages, with the best model found using maize plant development stage reproductive 2 (R2) for both maize grain yield and ear weight (respective R 2 values of 0.73 and 0.49, and root mean square error of validation (RMSEV) values of 2.07 and 3.41 metric tons per hectare using partial least squares regression (PLS-R) validation models). Models using vegetation indices for inputs rather than superspectral data showed similar R 2 but higher RMSEV values, and produced best results for the R4 development stage. In addition to being able to predict yield, spectral models were able to distinguish between different development stages and irrigation treatments. These abilities potentially allow for yield prediction of maize plants whose development stage and water status are unknown. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.
Arun, P. V. ; Herrmann, I. ; Budhiraju, K. M. ; Karnieli, A. Convolutional network architectures for super-resolution/sub-pixel mapping of drone-derived images. Pattern Recognition 2019, 88, 431-446. Publisher's VersionAbstract
Spatial resolution enhancement is a pre-requisite for integrating unmanned aerial vehicle (UAV) datasets with the data from other sources. However, the mobility of UAV platforms, along with radiometric and atmospheric distortions, makes the task difficult. In this paper, various convolutional neural network (CNN) architectures are explored for resolving the issues related to sub-pixel classification and super-resolution of drone-derived datasets. The main contributions of this work are: 1) network-inversion based architectures for super-resolution and sub-pixel mapping of drone-derived images taking into account their spectral-spatial characteristics and the distortions prevalent in them 2) a feature-guided transformation for regularizing the inversion problem 3) loss functions for improving the spectral fidelity and inter-label compatibility of coarser to finer-scale mapping 4) use of multi-size kernel units for avoiding over-fitting. The proposed approach is the first of its kind in using neural network inversion for super-resolution and sub-pixel mapping. Experiments indicate that the proposed super-resolution approach gives better results in comparison with the sparse-code based approaches which generally result in corrupted dictionaries and sparse codes for multispectral aerial images. Also, the proposed use of neural network inversion, for projecting spatial affinities to sub-pixel maps, facilitates the consideration of coarser-scale texture and color information in modeling the finer-scale spatial-correlation. The simultaneous consideration of spectral bands, as proposed in this study, gives better super-resolution results when compared to the individual band enhancements. The proposed use of different data-augmentation strategies, for emulating the distortions, improves the generalization capability of the framework. Sensitivity of the proposed super-resolution and sub-pixel mapping frameworks with regard to the network parameters is thoroughly analyzed. The experiments over various standard datasets as well as those collected from known locations indicate that the proposed frameworks perform better when compared to the prominent published approaches. © 2018 Elsevier Ltd
Gold, K. M. ; Townsend, P. A. ; Herrmann, I. ; Gevens, A. J. Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning. Plant Science 2019. Publisher's VersionAbstract
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual symptoms would improve management by greatly reducing disease potential and spread as well as improve both the financial and environmental sustainability of potato farms. In-vivo foliar spectroscopy offers the capacity to rapidly and non-destructively characterize plant physiological status, which can be used to detect the effects of necrotizing pathogens on plant condition prior to the appearance of visual symptoms. Here, we tested differences in spectral response of four potato cultivars, including two cultivars with a shared genotypic background except for a single copy of a resistance gene, to inoculation with Phytophthora infestans clonal lineage US-23 using three statistical approaches: random forest discrimination (RF), partial least squares discrimination analysis (PLS-DA), and normalized difference spectral index (NDSI). We find that cultivar, or plant genotype, has a significant impact on spectral reflectance of plants undergoing P. infestans infection. The spectral response of four potato cultivars to infection by Phytophthora infestans clonal lineage US-23 was highly variable, yet with important shared characteristics that facilitated discrimination. Early disease physiology was found to be variable across cultivars as well using non-destructively derived PLS-regression trait models. This work lays the foundation to better understand host-pathogen interactions across a variety of genotypic backgrounds, and establishes that host genotype has a significant impact on spectral reflectance, and hence on biochemical and physiological traits, of plants undergoing pathogen infection. © 2019 Elsevier B.V.
Herrmann, I. ; Vosberg, S. K. ; Townsend, P. A. ; Conley, S. P. Spectral data collection by dual field-of-view system under changing atmospheric conditions—a case study of estimating early season soybean populations. Sensors (Switzerland) 2019, 19. Publisher's VersionAbstract
There is an increasing interest in using hyperspectral data for phenotyping and crop management while overcoming the challenge of changing atmospheric conditions. The Piccolo dual field-of-view system collects up- and downwelling radiation nearly simultaneously with one spectrometer. Such systems offer great promise for crop monitoring under highly variable atmospheric conditions. Here, the system’s utility from a tractor-mounted boom was demonstrated for a case study of estimating soybean plant populations in early vegetative stages. The Piccolo system is described and its performance under changing sky conditions are assessed for two replicates of the same experiment. Plant population assessment was estimated by partial least squares regression (PLSR) resulting in stable estimations by models calibrated and validated under sunny and cloudy or cloudy and sunny conditions, respectively. We conclude that the Piccolo system is effective for data collection under variable atmospheric conditions, and we show its feasibility of operation for precision agriculture research and potential commercial applications. © 2019, MDPI AG. All rights reserved.
Shelef, O. ; Summerfield, L. ; Lev-Yadun, S. ; Villamarin-Cortez, S. ; Sadeh, R. ; Herrmann, I. ; Rachmilevitch, S. Thermal benefits from white variegation of silybum marianum leaves. Frontiers in Plant Science 2019, 10. Publisher's VersionAbstract
Leaves of the spiny winter annual Silybum marianum express white patches (variegation) that can cover significant surface areas, the outcome of air spaces formed between the epidermis and the green chlorenchyma. We asked: (1) what characterizes the white patches in S. marianum and what differs them from green patches? (2) Do white patches differ from green patches in photosynthetic efficiency under lower temperatures? We predicted that the air spaces in white patches have physiological benefits, elevating photosynthetic rates under low temperatures. To test our hypotheses we used both a variegated wild type and entirely green mutants. We grew the plants under moderate temperatures (20°C/10°C d/n) and compared them to plants grown under lower temperatures (15°C/5°C d/n). The developed plants were exposed to different temperatures for 1 h and their photosynthetic activity was measured. In addition, we compared in green vs. white patches, the reflectance spectra, patch structure, chlorophyll and dehydrin content, stomatal structure, plant growth, and leaf temperature. White patches were not significantly different from green patches in their biochemistry and photosynthesis. However, under lower temperatures, variegated wild-type leaves were significantly warmer than all-green mutants – possible explanations for that are discussed These findings support our hypothesis, that white variegation of S. marianum leaves has a physiological role, elevating leaf temperature during cold winter days. © 2019 Shelef, Summerfield, Lev-Yadun, Villamarin-Cortez, Sadeh, Herrmann and Rachmilevitch.
Kelly, G. ; Egbaria, A. ; Khamaisi, B. ; Lugassi, N. ; Attia, Z. ; Moshelion, M. ; Granot, D. Guard-Cell Hexokinase Increases Water-Use Efficiency Under Normal and Drought Conditions. Frontiers in Plant Science 2019, 10. Publisher's VersionAbstract
Water is a limiting resource for many land plants. Most of the water taken up by plants is lost to the atmosphere through the stomata, which are adjustable pores on the leaf surface that allow for gas exchange between the plant and the atmosphere. Modulating stomatal activity might be an effective way to reduce plants’ water consumption and enhance their productivity under normal, as well as water-limiting conditions. Our recent discovery of stomatal regulation by sugars that is mediated by guard-cell hexokinase (HXK), a sugar-sensing enzyme, has raised the possibility that HXK might be used to increase plant water-use efficiency (WUE; i.e., carbon gain per unit of water). We show here that transgenic tomato and Arabidopsis plants with increased expression of HXK in their guard cells (GCHXK plants) exhibit reduced transpiration and higher WUE without any negative effects on growth under normal conditions, as well as drought avoidance and improved photosynthesis and growth under limited-water conditions. Our results demonstrate that exclusive expression of HXK in guard cells is an effective tool for improving WUE, and plant performance under drought. © Copyright © 2019 Kelly, Egbaria, Khamaisi, Lugassi, Attia, Moshelion and Granot.
Attia, Z. ; Dalal, A. ; Moshelion, M. Vascular bundle sheath and mesophyll cells modulate leaf water balance in response to chitin. Plant Journal 2019. Publisher's VersionAbstract
Plants can detect pathogen invasion by sensing microbe-associated molecular patterns (MAMPs). This sensing process leads to the induction of defense responses. Numerous MAMP mechanisms of action have been described in and outside the guard cells. Here, we describe the effects of chitin, a MAMP found in fungal cell walls and insects, on the cellular osmotic water permeability (Pf) of the leaf vascular bundle-sheath (BS) and mesophyll cells (MCs), and its subsequent effect on leaf hydraulic conductance (Kleaf). BS is a parenchymatic tissue that tightly encases the vascular system. BS cells (BSCs) have been shown to influence Kleaf through changes in their Pf, for example, after sensing the abiotic stress response-regulating hormone abscisic acid. It was recently reported that, in Arabidopsis, the chitin receptors-like kinases, chitin elicitor receptor kinase 1 (CERK1) and LYSINE MOTIF RECEPTOR KINASE 5 (LYK5) are highly expressed in the BS as well as the neighboring mesophyll. Therefore, we studied the possible impact of chitin on these cells. Our results revealed that BSCs and MCs exhibit a sharp decrease in Pf in response to chitin treatment. In addition, xylem-fed chitin decreased Kleaf and led to stomatal closure. However, Atlyk5 mutant showed none of these responses. Complementing AtLYK5 in the BSCs (using the SCARECROW promoter) resulted in the response to chitin that was similar to that observed in the wild-type. These results suggest that BS play a role in the perception of apoplastic chitin and in initiating chitin-triggered immunity. © 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd
Elzinga, D. ; Sternburg, E. ; Sabbadin, D. ; Bartsch, M. ; Park, S. - Y. ; Vaidya, A. ; Mosquna, A. ; Kaundal, A. ; Wendeborn, S. ; Lachia, M. ; et al. Defining and Exploiting Hypersensitivity Hotspots to Facilitate Abscisic Acid Agonist Optimization. ACS Chemical Biology 2019, 14, 332-336. Publisher's VersionAbstract
Pyrabactin resistance 1 (PYR1) and related abscisic acid (ABA) receptors are new targets for manipulating plant drought tolerance. Here, we identify and use PYR1 hypersensitive mutants to define ligand binding hotspots and show that these can guide improvements in agonist potency. One hotspot residue defined, A160, is part of a pocket that is occupied by ABA's C6 methyl or by the toluyl methyl of the synthetic agonist quinabactin (QB). A series of QB analogues substituted at the toluyl position were synthesized and provide up to 10-fold gain in activity in vitro. Furthermore, we demonstrate that hypersensitive receptors can be used to improve the sensitivity of a previously described mammalian cell ABA-regulated transcriptional circuit by three orders of magnitude. Collectively, our data show that the systematic mapping of hypersensitivity sites in a ligand-binding pocket can help guide ligand optimization and tune the sensitivity of engineered receptors. © 2019 American Chemical Society.
Sun, Y. ; Harpazi, B. ; Wijerathna-Yapa, A. ; Merilo, E. ; de Vries, J. ; Michaeli, D. ; Gal, M. ; Cuming, A. C. ; Kollist, H. ; Mosquna, A. A ligand-independent origin of abscisic acid perception. Proceedings of the National Academy of Sciences of the United States of America 2019, 116, 24892-24899. Publisher's VersionAbstract
Land plants are considered monophyletic, descending from a single successful colonization of land by an aquatic algal ancestor. The ability to survive dehydration to the point of desiccation is a key adaptive trait enabling terrestrialization. In extant land plants, desiccation tolerance depends on the action of the hormone abscisic acid (ABA) that acts through a receptor-signal transduction pathway comprising a PYRABACTIN RESISTANCE 1-like (PYL)–PROTEIN PHOSPHATASE 2C (PP2C)–SNF1-RELATED PROTEIN KINASE 2 (SnRK2) module. Early-diverging aeroterrestrial algae mount a dehydration response that is similar to that of land plants, but that does not depend on ABA: Although ABA synthesis is widespread among algal species, ABA-dependent responses are not detected, and algae lack an ABA-binding PYL homolog. This raises the key question of how ABA signaling arose in the earliest land plants. Here, we systematically characterized ABA receptor-like proteins from major land plant lineages, including a protein found in the algal sister lineage of land plants. We found that the algal PYL-homolog encoded by Zygnema circumcarinatum has basal, ligand-independent activity of PP2C repression, suggesting this to be an ancestral function. Similarly, a liverwort receptor possesses basal activity, but it is further activated by ABA. We propose that co-option of ABA to control a preexisting PP2C-SnRK2-dependent desiccation-tolerance pathway enabled transition from an all-or-nothing survival strategy to a hormone-modulated, competitive strategy by enabling continued growth of anatomically diversifying vascular plants in dehydrative conditions, enabling them to exploit their new environment more efficiently. © 2019 National Academy of Sciences. All rights reserved.
Sterlin, Y. ; Pri-Tal, O. ; Zimran, G. ; Park, S. - Y. ; Ben-Ari, J. ; Kourelis, J. ; Verstraeten, I. ; Gal, M. ; Cutler, S. R. ; Mosquna, A. Optimized small-molecule pull-downs define MLBP1 as an acyl-lipid-binding protein. Plant Journal 2019, 98, 928-941. Publisher's VersionAbstract
Abscisic acid (ABA) receptors belong to the START domain superfamily, which encompasses ligand-binding proteins present in all kingdoms of life. START domain proteins contain a central binding pocket that, depending on the protein, can couple ligand binding to catalytic, transport or signaling functions. In Arabidopsis, the best characterized START domain proteins are the 14 PYR/PYL/RCAR ABA receptors, while the other members of the superfamily do not have assigned ligands. To address this, we used affinity purification of biotinylated proteins expressed transiently in Nicotiana benthamiana coupled to untargeted LC-MS to identify candidate binding ligands. We optimized this method using ABA–PYL interactions and show that ABA co-purifies with wild-type PYL5 but not a binding site mutant. The Kd of PYL5 for ABA is 1.1 μm, which suggests that the method has sufficient sensitivity for many ligand–protein interactions. Using this method, we surveyed a set of 37 START domain-related proteins, which resulted in the identification of ligands that co-purified with MLBP1 (At4G01883) or MLP165 (At1G35260). Metabolite identification and the use of authentic standards revealed that MLBP1 binds to monolinolenin, which we confirmed using recombinant MLBP1. Monolinolenin also co-purified with MLBP1 purified from transgenic Arabidopsis, demonstrating that the interaction occurs in a native context. Thus, deployment of this relatively simple method allowed us to define a protein–metabolite interaction and better understand protein–ligand interactions in plants. © 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd