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The target of rapamycin (TOR) kinase is a conserved regulatory hub that translates environmental and nutritional information into permissive or restrictive growth decisions. Despite the increased appreciation of the essential role of the TOR complex in plants, no large-scale phosphoproteomics or interactomics studies have been performed to map TOR signalling events in plants. To fill this gap, we combined a systematic phosphoproteomics screen with a targeted protein complex analysis in the model plant Arabidopsis thaliana . Integration of the phosphoproteome and protein complex data on the one hand shows that both methods reveal complementary subspaces of the plant TOR signalling network, enabling proteome-wide discovery of both upstream and downstream network components. On the other hand, the overlap between both data sets reveals a set of candidate direct TOR substrates. The integrated network embeds both evolutionarily-conserved and plant-specific TOR signalling components, uncovering an intriguing complex interplay with protein synthesis. Overall, the network provides a rich data set to start addressing fundamental questions about how TOR controls key processes in plants, such as autophagy, auxin signalling, chloroplast development, lipid metabolism, nucleotide biosynthesis, protein translation or senescence. The target of rapamycin (TOR) kinase, present in all eukaryotes, is a major regulator of growth and metabolism. Using quantitative phosphoproteomics and comprehensive interactome approaches, the authors reveal the TOR signalling network, including potential substrates.

A platform for isolating low-abundance protein complexes from Arabidopsis seedlings and cell cultures is described. Its power resides in an improved TAP tag combined with ultrasensitive MS and filtering against a list of nonspecific proteins. Tandem affinity purification coupled to mass spectrometry (TAP-MS) is one of the most advanced methods to characterize protein complexes in plants, giving a comprehensive view on the protein-protein interactions (PPIs) of a certain protein of interest (bait). The bait protein is fused to a double affinity tag, which consists of a protein G tag and a streptavidin-binding peptide separated by a very specific protease cleavage site, allowing highly specific protein complex isolation under near-physiological conditions. Implementation of this optimized TAP tag, combined with ultrasensitive MS, means that these experiments can be performed on small amounts (25 mg of total protein) of protein extracts from Arabidopsis cell suspension cultures. It is also possible to use this approach to isolate low abundant protein complexes from Arabidopsis seedlings, thus opening perspectives for the exploration of protein complexes in a plant developmental context. Next to protocols for efficient biomass generation of seedlings (∼7.5 months), we provide detailed protocols for TAP (1 d), and for sample preparation and liquid chromatography-tandem MS (LC-MS/MS; ∼5 d), either from Arabidopsis seedlings or from cell cultures. For the identification of specific co-purifying proteins, we use an extended protein database and filter against a list of nonspecific proteins on the basis of the occurrence of a co-purified protein among 543 TAP experiments. The value of the provided protocols is illustrated through numerous applications described in recent literature.

Hyperspectral imaging is a promising tool for non-destructive phenotyping of plant physiological traits, which has been transferred from remote to proximal sensing applications, and from manual laboratory setups to automated plant phenotyping platforms. Due to the higher resolution in proximal sensing, illumination variation and plant geometry result in increased non-biological variation in plant spectra that may mask subtle biological differences. Here, a better understanding of spectral measurements for proximal sensing and their application to study drought, developmental and diurnal responses was acquired in a drought case study of maize grown in a greenhouse phenotyping platform with a hyperspectral imaging setup. The use of brightness classification to reduce the illumination-induced non-biological variation is demonstrated, and allowed the detection of diurnal, developmental and early drought-induced changes in maize reflectance and physiology. Diurnal changes in transpiration rate and vapor pressure deficit were significantly correlated with red and red-edge reflectance. Drought-induced changes in effective quantum yield and water potential were accurately predicted using partial least squares regression and the newly developed Water Potential Index 2, respectively. The prediction accuracy of hyperspectral indices and partial least squares regression were similar, as long as a strong relationship between the physiological trait and reflectance was present. This demonstrates that current hyperspectral processing approaches can be used in automated plant phenotyping platforms to monitor physiological traits with a high temporal resolution.

Plant-parasitic nematodes are destructive plant pathogens that cause significant yield losses. They induce highly specialized feeding sites (NFS) in infected plant roots from which they withdraw nutrients. In order to establish these NFS, it is thought that the nematodes manipulate the molecular and physiological pathways of their hosts. Evidence is accumulating that the plant signalling molecule auxin is involved in the initiation and development of the feeding sites of sedentary plant-parasitic nematodes. Intercellular transport of auxin is essential for various aspects of plant growth and development. Here, we analysed the spatial and temporal expression of PIN auxin transporters during the early events of NFS establishment using promoter-GUS/GFP fusion lines. Additionally, single and double pin mutants were used in infection studies to analyse the role of the different PIN proteins during cyst nematode infection. Based on our results, we postulate a model in which PIN1-mediated auxin transport is needed to deliver auxin to the initial syncytial cell, whereas PIN3 and PIN4 distribute the accumulated auxin laterally and are involved in the radial expansion of the NFS. Our data demonstrate that cyst nematodes are able to hijack the auxin distribution network in order to facilitate the infection process.

Plant bZIP group I transcription factors have been reported mainly for their role during vascular development and osmosensory responses. Interestingly, bZIP29 has been identified in a cell cycle interactome, indicating additional functions of bZIP29 in plant development. Here, bZIP29 was functionally characterized to study its role during plant development. It is not present in vascular tissue but is specifically expressed in proliferative tissues. Genome-wide mapping of bZIP29 target genes confirmed its role in stress and osmosensory responses, but also identified specific binding to several core cell cycle genes and to genes involved in cell wall organization. bZIP29 protein complex analyses validated interaction with other bZIP group I members and provided insight into regulatory mechanisms acting on bZIP dimers. In agreement with bZIP29 expression in proliferative tissues and with its binding to promoters of cell cycle regulators, dominant-negative repression of bZIP29 altered the cell number in leaves and in the root meristem. A transcriptome analysis on the root meristem, however, indicated that bZIP29 might regulate cell number through control of cell wall organization. Finally, ectopic dominant-negative repression of bZIP29 and redundant factors led to a seedling-lethal phenotype, pointing to essential roles for bZIP group I factors early in plant development.

Background Thermography is a popular tool to assess plant water-use behavior, as plant temperature is influenced by transpiration rate, and is commonly used in field experiments to detect plant water deficit. Its application in indoor automated phenotyping platforms is still limited and mainly focuses on differences in plant temperature between genotypes or treatments, instead of estimating stomatal conductance or transpiration rate. In this study, the transferability of commonly used thermography analysis protocols from the field to greenhouse phenotyping platforms was evaluated. In addition, the added value of combining thermal infrared (TIR) with hyperspectral imaging to monitor drought effects on plant transpiration rate (E) was evaluated. Results The sensitivity of commonly used TIR indices to detect drought-induced and genotypic differences in water status was investigated in eight maize inbred lines in the automated phenotyping platform PHENOVISION. Indices that normalized plant temperature for vapor pressure deficit and/or air temperature at the time of imaging were most sensitive to drought and could detect genotypic differences in the plants’ water-use behavior. However, these indices were not strongly correlated to stomatal conductance and E. The canopy temperature depression index, the crop water stress index and the simplified stomatal conductance index were more suitable to monitor these traits, and were consequently used to develop empirical E prediction models by combining them with hyperspectral indices and/or environmental variables. Different modeling strategies were evaluated, including single index-based, machine learning and mechanistic models. Model comparison showed that combining multiple TIR indices in a random forest model can improve E prediction accuracy, and that the contribution of the hyperspectral data is limited when multiple indices are used. However, the empirical models trained on one genotype were not transferable to all eight inbred lines. Conclusion Overall, this study demonstrates that existing TIR indices can be used to monitor drought stress and develop E prediction models in an indoor setup, as long as the indices normalize plant temperature for ambient air temperature or relative humidity.

[This corrects the article DOI: 10.3389/fpls.2021.640914.].

Using synchronized tobacco Bright Yellow-2 cells and cDNA-amplified fragment length polymorphism-based genomewide expression analysis, we built a comprehensive collection of plant cell cycle-modulated genes. Approximately 1,340 periodically expressed genes were identified, including known cell cycle control genes as well as numerous unique candidate regulatory genes. A number of plant-specific genes were found to be cell cycle modulated. Other transcript tags were derived from unknown plant genes showing homology to cell cycle-regulatory genes of other organisms. Many of the genes encode novel or uncharacterized proteins, indicating that several processes underlying cell division are still largely unknown.

The ability to tag proteins has boosted the emergence of generic molecular methods for protein functional analysis. Fluorescent protein tags are used to visualize protein localization, and affinity tags enable the mapping of molecular interactions by, for example, tandem affinity purification or chromatin immunoprecipitation. To apply these widely used molecular techniques on a single transgenic plant line, we developed a multifunctional tandem affinity purification tag, named GS , which combines the streptavidin-binding peptide tag with citrine yellow fluorescent protein. We demonstrated the versatility of the GS tag in the dicot Arabidopsis ( ) using a set of benchmark proteins. For proof of concept in monocots, we assessed the localization and dynamic interaction profile of the leaf growth regulator ANGUSTIFOLIA3 (AN3), fused to the GS tag, along the growth zone of the maize ( ) leaf. To further explore the function of ZmAN3, we mapped its DNA-binding landscape in the growth zone of the maize leaf through chromatin immunoprecipitation sequencing. Comparison with AN3 target genes mapped in the developing maize tassel or in Arabidopsis cell cultures revealed strong conservation of AN3 target genes between different maize tissues and across monocots and dicots, respectively. In conclusion, the GS tag offers a powerful molecular tool for distinct types of protein functional analyses in dicots and monocots. As this approach involves transforming a single construct, it is likely to accelerate both basic and translational plant research.

The ability to tag proteins has boosted the emergence of generic molecular methods for protein functional analysis. Fluorescent protein tags are used to visualize protein localization, and affinity tags enable the mapping of molecular interactions by, for example, tandem affinity purification or chromatin immunoprecipitation. To apply these widely used molecular techniques on a single transgenic plant line, we developed a multifunctional tandem affinity purification tag, named GSyellow, which combines the streptavidin-binding peptide tag with citrine yellow fluorescent protein. We demonstrated the versatility of the GSyellow tag in the dicot Arabidopsis (Arabidopsis thaliana) using a set of benchmark proteins. For proof of concept in monocots, we assessed the localization and dynamic interaction profile of the leaf growth regulator ANGUSTIFOLIA3 (AN3), fused to the GSyellow tag, along the growth zone of the maize (Zea mays) leaf. To further explore the function of ZmAN3, we mapped its DNA-binding landscape in the growth zone of the maize leaf through chromatin immunoprecipitation sequencing. Comparison with AN3 target genes mapped in the developing maize tassel or in Arabidopsis cell cultures revealed strong conservation of AN3 target genes between different maize tissues and across monocots and dicots, respectively. In conclusion, the GSyellow tag offers a powerful molecular tool for distinct types of protein functional analyses in dicots and monocots. As this approach involves transforming a single construct, it is likely to accelerate both basic and translational plant research.