Publikationen - Molekulare Signalverarbeitung

In plants, the oxylipin pathway gives rise to several oxygenated fatty acid derivatives such as hydroxy- and keto fatty acids as well as volatile aldehydes and cyclic compounds, which are, in part, physiologically active [1]. Among these, jasmonic acid is discussed as signalling molecule during several stress responses, wounding, senescense and plant pathogen interactions [2].

The etiolated germination process of oilseed plants is characterized by the mobilization of storage lipids which serve as a major carbon source for the seedlings growth. During this stage the lipid storing organelles, the lipid bodies, are degraded and a new set of proteins, including a specific form of lipoxygenase (LOX), is detectable at their membranes in different plants [1,2]. LOXs are widely distributed in plants and animals and catalyze the regio- and stereo-specific oxygenation of polyunsaturated fatty acids [3]. The enzymatic transformations of the resulting fatty acid hydroperoxides have been extensively studied [4]. Three well characterized enzymes, a lyase, an allene oxide synthase, and a peroxygenase, were shown to degrade hydroperoxides into compounds of physiological importance, such as odors, oxylipins, and jasmonates. We have recently reported a new LOX reaction in plants where a specific LOX, the lipid body LOX, metabolizes esterified fatty acids. This reaction resulted in the formation of 13(S)-hydroxy-linoleic acid (13-HODE) and lead us to propose an additional branch of the LOX pathway: the reductase pathway. Besides a specific LOX form we suggest two additional enzyme activities, a lipid hydroperoxide reductase and a lipid hydroxide-specific lipase which lead to the formation of 13-HODE. 13-HODE might be the endogenous substrate for β-oxidation in the glyoxysomes during germination of oilseeds containing high amounts of polyunsaturated fatty acids.

Mutualistic symbioses between plant roots and microorganisms can reduce the demand for chemical fertilizers in agriculture. Most crops are able to establish arbuscular mycorrhiza (AM) symbiosis with fungi to take up phosphate more efficiently. A second symbiosis, nitrogen-fixing root nodule symbiosis, supersedes energy-intensive nitrogen fertilization: Legumes such as peas, clover and soybeans take up rhizobia – special bacteria that are capable of converting atmospheric nitrogen into ammonium – into their root cells. Plant root cells perceive rhizobia and AM fungi via very similar signaling molecules (N-acetylglucosamine tetra- or pentamers), even though the resultant developmental processes differ strongly. Interestingly, N-acetylglucosamine containing signals including fungal chitin- and bacterial peptidoglycan-fragments from their cell walls, also play a role in the recognition of pathogenic microorganisms.Despite the intrinsic sustainability potential of the nitrogen-fixing root nodule symbiosis, too much of a good thing, however, has led to global problems: The massive increase in global meat production is largely based on soybean. Large scale soybean monoculture destroyed ecosystems in South America. Large scale animal production results in excessive methane and nitrogen release into the environment, which causes climate change and death zones in marine ecosystems, respectively. This calls for a considerable reduction in meat consumption.

In receptor–ligand interactions, dissociation constants provide a key parameter for characterizing binding. Here, we describe filter-based radioligand binding assays at equilibrium, either varying ligand concentrations up to receptor saturation or outcompeting ligand from its receptor with increasing concentrations of ligand analogue. Using the auxin coreceptor system, we illustrate how to use a saturation binding assay to determine the apparent dissociation constant (K D ′ ) for the formation of a ternary TIR1–auxin–AUX/IAA complex. Also, we show how to determine the inhibitory constant (Ki) for auxin binding by the coreceptor complex via a competition binding assay. These assays can be applied broadly to characterize a one-site binding reaction of a hormone to its receptor.

Chrysanthemum chlorotic mottle viroid (CChMVd) (398–401 nt) belongs to genus Pelamoviroid, family Avsunviroidae and, like other members of this family, replicates in plastids through a rolling-circle mechanism involving hammerhead ribozymes. CChMVd RNA adopts a branched conformation stabilized by a kissing-loop interaction, resembling peach latent mosaic viroid in this respect. Chrysanthemum is the only natural and experimental host for CChMVd, which in the most sensitive varieties induces leaf mottling and chlorosis, delay in flowering, and dwarfing. The viroid has been found in major chrysanthemum growing areas including Europe and Asia. There are natural variants in which the change (UUUC→GAAA) mapping at a tetraloop in the CChMVd branched conformation is sufficient to change the symptomatic phenotype into a nonsymptomatic one without altering the viroid titer. Preinfection with nonsymptomatic variants prevents challenge inoculation with symptomatic ones. Moreover, experimental coinoculation with symptomatic and nonsymptomatic CChMVd variants results in symptomless phenotypes only when the latter is in vast excess, thus indicating its lower fitness.

A method for selective and sensitive quantification of amino acids is described. The combination of established derivatization procedures of secondary and primary amino groups with 9-fluorenylmethoxycarbonyl chloride (Fmoc-Cl) and subsequent detection of derivatized amino acids by LC-ESI-MS/MS using multiple reaction monitoring provides high selectivity. The attachment of an apolar moiety enables purification of derivatized amino acids from matrix by a single solid-phase extraction step, which increases sensitivity by reduced ion suppression during LC-ESI-MS/MS detection. Additionally, chromatography of all amino acids can be performed on reversed-phase HPLC columns using eluents without additives, which are known to cause significant decreases in signal to noise ratios. The method has been routinely applied for amino acid profiling of low amounts of liquids and tissues of various origins with a sample throughput of about 50–100 samples a day. In addition to a detailed description of the method, some representative examples are presented.

The structure of the microtubule cytoskeleton provides valuable information related to morphogenesis of cells. The cytoskeleton organizes into diverse patterns that vary in cells of different types and tissues, but also within a single tissue. To assess differences in cytoskeleton organization methods are needed that quantify cytoskeleton patterns within a complete cell and which are suitable for large data sets. A major bottleneck in most approaches, however, is a lack of techniques for automatic extraction of cell contours. Here, we present a semi-automatic pipeline for cell segmentation and quantification of microtubule organization. Automatic methods are applied to extract major parts of the contours and a handy image editor is provided to manually add missing information efficiently. Experimental results prove that our approach yields high-quality contour data with minimal user intervention and serves a suitable basis for subsequent quantitative studies.

The microtubule cytoskeleton plays important roles in cell morphogenesis. To investigate the mechanisms of cytoskeletal organization, for example, during growth or development, in genetic studies, or in response to environmental stimuli, image analysis tools for quantitative assessment are needed. Here, we present a method for texture measure-based quantification and comparative analysis of global microtubule cytoskeleton patterns and subsequent visualization of output data. In contrast to other approaches that focus on the extraction of individual cytoskeletal fibers and analysis of their orientation relative to the growth axis, CytoskeletonAnalyzer2D quantifies cytoskeletal organization based on the analysis of local binary patterns. CytoskeletonAnalyzer2D thus is particularly well suited to study cytoskeletal organization in cells where individual fibers are difficult to extract or which lack a clearly defined growth axis, such as leaf epidermal pavement cells. The tool is available as ImageJ plugin and can be combined with publicly available software and tools, such as R and Cytoscape, to visualize similarity networks of cytoskeletal patterns.

Morphological analysis of cell shapes requires segmentation of cell contours from input images and subsequent extraction of meaningful shape descriptors that provide the basis for qualitative and quantitative assessment of shape characteristics. Here, we describe the publicly available ImageJ plugin PaCeQuant and its associated R package PaCeQuantAna, which provides a pipeline for fully automatic segmentation, feature extraction, statistical analysis, and graphical visualization of cell shape properties. PaCeQuant is specifically well suited for analysis of jigsaw puzzle-like leaf epidermis pavement cells from 2D input images and supports the quantification of global, contour-based, skeleton-based, and pavement cell-specific shape descriptors.

Leaf epidermis pavement cells develop complex jigsaw puzzle-like shapes in many plant species, including the model plant Arabidopsis thaliana. Due to their complex morphology, pavement cells have become a popular model system to study shape formation and coordination of growth in the context of mechanically coupled cells at the tissue level. To facilitate robust assessment and analysis of pavement cell shape characteristics in a high-throughput fashion, we have developed PaCeQuant and a collection of supplemental tools. The ImageJ-based MiToBo plugin PaCeQuant supports fully automatic segmentation of cell contours from microscopy images and the extraction of 28 shape features for each detected cell. These features now also include the Largest Empty Circle criterion as a proxy for mechanical stress. In addition, PaCeQuant provides a set of eight features for individual lobes, including the categorization as type I and type II lobes at two- and three-cell junctions, respectively. The segmentation and feature extraction results of PaCeQuant depend on the quality of input images. To allow for corrections in case of local segmentation errors, the LabelImageEditor is provided for user-friendly manual postprocessing of segmentation results. For statistical analysis and visualization, PaCeQuant is supplemented with the R package PaCeQuantAna, which provides statistical analysis functions and supports the generation of publication-ready plots in ready-to-use R workflows. In addition, we recently released the FeatureColorMapper tool which overlays feature values over cell regions for user-friendly visual exploration of selected features in a set of analyzed cells.