Plant Methods

Tea, which is produced from new shoots of existing tea plants (Camellia sinensis), is one of the most popular, non-alcoholic, healthy beverages worldwide. Colletotrichum camelliae is one of the dominant fungal pathogens of tea. The interaction of C. camelliae with tea could be a useful pathosystem to elucidate various aspects of woody, medicinal plant-fungal interactions. Currently, many studies characterizing resistance or virulence and aggressiveness use lesion size at the infection sites on the leaves to quantify the growth of the pathogen. However, this method does not offer the sensitivity needed for the robust quantification of small changes in aggressiveness or the accurate quantification of pathogen growth at the early stages of infection. A quantitative real-time polymerase chain reaction (qRT-PCR) assay was developed for the quantification of C. camelliae growth on tea plant. This method was based on the comparison of fungal DNA in relation to plant biomass. This assay was used to investigate the phenotypes of tea plant cultivars in response to C. camelliae infection. Two cultivars, Zhongcha 108 (ZC108) and Longjing 43 (LJ43), were tested with this method. ZC108 was previously reported as an anthracnose-resistant cultivar against C. camelliae, while LJ43 was susceptible. The traditional lesion measurement method showed that both cultivars were susceptible to a virulent strain of C. camelliae, while the qRT-PCR approach indicated that very little fungal growth occurred in the anthracnose-resistant cultivar ZC108. The observed results in this study were consistent with previously published research. In addition, the DNA-based real-time PCR method was applied for analysis of pathogenic differences in general C. camelliae isolates and among several Colletotrichum spp that infect tea. This study showed that the DNA-based qRT-PCR technique is rapid, highly sensitive and easily applicable for routine experiments and could be used in screening for resistant tea plant cultivars or to identify differences in pathogen aggressiveness within and among Colletotrichum species.

The cultivar Micro-Tom (MT) is regarded as a model system for tomato genetics due to its short life cycle and miniature size. However, efforts to improve tomato genetic transformation have led to protocols dependent on the costly hormone zeatin, combined with an excessive number of steps. Here we report the development of a MT near-isogenic genotype harboring the allele Rg1 (MT-Rg1), which greatly improves tomato in vitro regeneration. Regeneration was further improved in MT by including a two-day incubation of cotyledonary explants onto medium containing 0.4 μM 1-naphthaleneacetic acid (NAA) before cytokinin treatment. Both strategies allowed the use of 5 μM 6-benzylaminopurine (BAP), a cytokinin 100 times less expensive than zeatin. The use of MT-Rg1 and NAA pre-incubation, followed by BAP regeneration, resulted in high transformation frequencies (near 40%), in a shorter protocol with fewer steps, spanning approximately 40 days from Agrobacterium infection to transgenic plant acclimatization. The genetic resource and the protocol presented here represent invaluable tools for routine gene expression manipulation and high throughput functional genomics by insertional mutagenesis in tomato.

Receptor-like protein kinases (RLKs) are a large and important group of plant proteins involved in numerous aspects of development and stress response. Within this family, homo-oligermization of receptors followed by autophosphorylation of the intracellular protein kinase domain appears to be a widespread mechanism to regulate protein kinase activity. In vitro studies of several RLKs have identified autophosphorylation sites involved in regulation of catalytic activity and signaling in vivo. Recent work has established that multiple RLKs are biochemically active when expressed in E. coli and readily autophosphorylate prior to purification or subsequent manipulation. This observation has led us to develop a simplified method for assaying RLK phosphorylation status as an indirect measure of intrinsic autophosphorylation activity. The method involves expressing a recombinant RLK protein kinase domain in E. coli, followed by SDS-PAGE of boiled cell lysate, and sequential staining with the phosphoprotein stain Pro-Q Diamond and a colloidal Coomassie total protein stain. We show this method can be used to measure and quantify in vitro autophosphorylation levels of recombinant wildtype and mutant versions of the Arabidopsis RLK HAESA, as well as to detect transphosphorylation activity of recombinant HAESA against a protein kinase inactive version of itself. Our method has several advantages over traditional protein kinase assays. It does not require protein purification, transfer, blotting, or radioactive reagents. It allows for rapid and quantitative assessment of autophosphorylation levels and should have general utility in the study of any autophosphorylating protein kinase expressed in E. coli.

Chemical genetics provides a powerful alternative to conventional genetics for understanding gene function. However, its application to plants has been limited by the lack of a technology that allows detailed phenotyping of whole-seedling development in the context of a high-throughput chemical screen. We have therefore sought to develop an automated micro-phenotyping platform that would allow both root and shoot development to be monitored under conditions where the phenotypic effects of large numbers of small molecules can be assessed. The ‘Microphenotron’ platform uses 96-well microtitre plates to deliver chemical treatments to seedlings of Arabidopsis thaliana L. and is based around four components: (a) the ‘Phytostrip’, a novel seedling growth device that enables chemical treatments to be combined with the automated capture of images of developing roots and shoots; (b) an illuminated robotic platform that uses a commercially available robotic manipulator to capture images of developing shoots and roots; (c) software to control the sequence of robotic movements and integrate these with the image capture process; (d) purpose-made image analysis software for automated extraction of quantitative phenotypic data. Imaging of each plate (representing 80 separate assays) takes 4 min and can easily be performed daily for time-course studies. As currently configured, the Microphenotron has a capacity of 54 microtitre plates in a growth room footprint of 2.1 m2, giving a potential throughput of up to 4320 chemical treatments in a typical 10 days experiment. The Microphenotron has been validated by using it to screen a collection of 800 natural compounds for qualitative effects on root development and to perform a quantitative analysis of the effects of a range of concentrations of nitrate and ammonium on seedling development. The Microphenotron is an automated screening platform that for the first time is able to combine large numbers of individual chemical treatments with a detailed analysis of whole-seedling development, and particularly root system development. The Microphenotron should provide a powerful new tool for chemical genetics and for wider chemical biology applications, including the development of natural and synthetic chemical products for improved agricultural sustainability.

The growing field of plant molecular farming relies on expression vectors that allow high yields of recombinant proteins to be produced through transient gene expression. While numerous expression vectors currently exist for this purpose, there are very few examples of systematic efforts to improve upon these. Moreover, the current generation of expression systems makes use of naturally-occurring regulatory elements, typically selected from plant viruses, to maximise yields. This study aims to use rational design to generate synthetic sequences that can rival existing ones. In this work, we present the rational design of novel synthetic 5′ and 3′ untranslated regions (UTRs) which can be used in various combinations to modulate accumulation levels of transiently-expressed recombinant proteins. Using the pEAQ-HT expression vector as a point of comparison, we show that pre-existing expression systems can be improved by the deployment of rationally designed synthetic UTRs. Notably, we show that a suite of short, synthetic 5′UTRs behave as expression enhancers that outperform the HT 5′UTR present in the CPMV-HT expression system. Furthermore, we confirm the critical role played by the 3′UTR of cowpea mosaic virus RNA-2 in the performance of the CPMV-HT system. Finally, we use the knowledge obtained from these results to develop novel expression vectors (named pHRE and pHREAC) that equal or outperform pEAQ-HT in terms of recombinant protein yield. These new vectors are also domesticated for the use of certain Type IIS restriction enzymes, which allows for quicker cloning and straightforward assessment of different combinations of UTRs. We have shown that it is possible to rationally design a suite of expression modulators in the form of synthetic UTRs. We have created novel expression vectors that allow very high levels of recombinant protein expression in a transient expression context. This will have important consequences for future efforts to develop ever-better plant transient overexpression vectors for research or industrial applications.

Metabolomics based on mass spectrometry analysis are increasingly applied in diverse scientific domains, notably agronomy and plant biology, in order to understand plants’ behaviors under different stress conditions. In fact, these stress conditions are able to disrupt many biosynthetic pathways that include mainly primary metabolites. Profiling and quantifying primary metabolites remain a challenging task because they are poorly retained in reverse phase columns, due to their high polarity and acid–base properties. The aim of this work is to develop a simultaneous untargeted/targeted profiling of amino acids, organic acids, sulfur metabolites, and other several metabolites. This method will be applied on sulfur depleted barley, in order to study this type of stress, which is difficult to detect at early stage. Also, this method aims to explore the impact of this stress on barley’s metabolome. Ultra-high performance liquid chromatography–high resolution mass spectrometry-based method was successfully applied to real samples allowing to discriminate, detect, and quantify primary metabolites in short-runs without any additional sampling step such as derivatization or ion pairing. The retention of polar metabolites was successfully achieved using modified C18 columns with high reproducibility (relative standard deviation below 10%). The quantification method showed a high sensitivity and robustness. Furthermore, high resolution mass spectrometry detection provided reliable quantification based on exact mass, eliminating potential interferences, and allowing the simultaneous untargeted metabolomics analysis. The untargeted data analysis was conducted using Progenesis QI software, performing alignment, peak picking, normalization and multivariate analysis. The simultaneous analysis provided cumulative information allowing to discriminate between two plant batches. Thus, discriminant biomarkers were identified and validated. Simultaneously, quantification confirmed coherently the relative abundance of these biomarkers. A fast and innovated simultaneous untargeted/targeted method has successfully been developed and applied to sulfur deficiency on barley. This work opens interesting perspectives in both fundamental and applied research. Biomarker discovery give precious indication to understand plant behavior during a nutritional deficiency. Thus, direct or indirect measurement of these compounds allows a real time fertilization management and encounter the challenges of sustainable agriculture.

In this study, a protocol is described for rapid preparation of an enriched, reasonably pure fraction of nuclear proteins from the leaves of tobacco (Nicotiana tabacum), potato (Solanum tuberosum) and apple (Malus domestica). The protocol gives reproducible results and can be carried out quickly in 2 hours. Tissue extracts clarified with filtration were treated with non-ionic detergent (Triton X-100) to lyse membranes of contaminating organelles. Nuclei were collected from a 60% Percoll layer of density gradient following low-speed centrifugation. Western blot analysis using antibodies to marker proteins of organelles indicated that the nuclear protein fractions were highly enriched and free or nearly free of proteins from the endoplasmic reticulum and chloroplasts.

Accurately segmenting vegetation from the background within digital images is both a fundamental and a challenging task in phenotyping. The performance of traditional methods is satisfactory in homogeneous environments, however, performance decreases when applied to images acquired in dynamic field environments. In this paper, a multi-feature learning method is proposed to quantify vegetation growth in outdoor field conditions. The introduced technique is compared with the state-of the-art and other learning methods on digital images. All methods are compared and evaluated with different environmental conditions and the following criteria: (1) comparison with ground-truth images, (2) variation along a day with changes in ambient illumination, (3) comparison with manual measurements and (4) an estimation of performance along the full life cycle of a wheat canopy. The method described is capable of coping with the environmental challenges faced in field conditions, with high levels of adaptiveness and without the need for adjusting a threshold for each digital image. The proposed method is also an ideal candidate to process a time series of phenotypic information throughout the crop growth acquired in the field. Moreover, the introduced method has an advantage that it is not limited to growth measurements only but can be applied on other applications such as identifying weeds, diseases, stress, etc.

The complexity of RNA regulation is one of the current frontiers in animal and plant molecular biology research. RNA-binding proteins (RBPs) are characteristically involved in post-transcriptional gene regulation through interaction with RNA. Recently, the mRNA-bound proteome of mammalian cell lines has been successfully cataloged using a new method called interactome capture. This method relies on UV crosslinking of proteins to RNA, purifying the mRNA using complementary oligo-dT beads and identifying the crosslinked proteins using mass spectrometry. We describe here an optimized system of mRNA interactome capture for Arabidopsis thaliana leaf mesophyll protoplasts, a cell type often used in functional cellular assays. We established the conditions for optimal protein yield, namely the amount of starting tissue, the duration of UV irradiation and the effect of UV intensity. We demonstrated high efficiency mRNA-protein pull-down by oligo-d(T)25 bead capture. Proteins annotated to have RNA-binding capacity were overrepresented in the obtained medium scale mRNA-bound proteome, indicating the specificity of the method and providing in vivo UV crosslinking experimental evidence for several candidate RBPs from leaf mesophyll protoplasts. The described method, applied to plant cells, allows identifying proteins as having the capacity to bind mRNA directly. The method can now be scaled and applied to other plant cell types and species to contribute to the comprehensive description of the RBP proteome of plants.