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Poeschl, Y.; Möller, B.; Müller, L.; Bürstenbinder, K.; User-friendly assessment of pavement cell shape features with PaCeQuant: Novel functions and tools (Charles T. Anderson, Elizabeth S. Haswell, Ram Dixit). Methods Cell Biol. 160, 349-363, (2020) DOI: 10.1016/bs.mcb.2020.04.010
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.
Mielke, S.; Gasperini, D.; Plant–Insect Bioassay for Testing Arabidopsis Resistance to the Generalist Herbivore Spodoptera littoralis (Champion, A. & Laplaze, L., eds.). Methods Mol. Biol. 2085, 69-78, (2020) ISBN: 978-1-0716-0142-6 DOI: 10.1007/978-1-0716-0142-6_5
Jasmonates are essential engineers of plant defense responses against many pests, including herbivorous insects. Herbivory induces the production of jasmonic acid (JA) and its bioactive conjugate jasmonoyl-l-isoleucine (JA-Ile), which then triggers a large transcriptional reprogramming to promote plant acclimation. The contribution of the JA pathway, including its components and regulators, to defense responses against insect herbivory can be evaluated by conducting bioassays with a wide range of host plants and insect pests. Here, we describe a detailed and reproducible protocol for testing feeding behavior of the generalist herbivore Spodoptera littoralis on the model plant Arabidopsis thaliana and hence infer the contribution of JA-mediated plant defense responses to a chewing insect.
Ziegler, J.; Hussain, H.; Neubert, R. H. H.; Abel, S.; Sensitive and Selective Amino Acid Profiling of Minute Tissue Amounts by HPLC/Electrospray Negative Tandem Mass Spectrometry Using 9-Fluorenylmethoxycarbonyl (Fmoc-Cl) Derivatization (Alterman, M. A., ed.). Methods Mol. Biol. 2030, 365-379, (2019) ISBN: 978-1-4939-9639-1 DOI: 10.1007/978-1-4939-9639-1_27
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.
Möller, B.; Bürstenbinder, K.; Semi-Automatic Cell Segmentation from Noisy Image Data for Quantification of Microtubule Organization on Single Cell Level 199-203, (2019) ISBN: 978-1-5386-3641-1 DOI: 10.1109/ISBI.2019.8759145
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.
Möller, B.; Zergiebel, L.; Bürstenbinder, K.; Quantitative and Comparative Analysis of Global Patterns of (Microtubule) Cytoskeleton Organization with CytoskeletonAnalyzer2D (Cvrčková, F. & Žárský, V., eds.). Methods Mol. Biol. 1992, 151-171, (2019) ISBN: 978-1-4939-9469-4 DOI: 10.1007/978-1-4939-9469-4_10
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.
Möller, B.; Poeschl, Y.; Klemm, S.; Bürstenbinder, K.; Morphological Analysis of Leaf Epidermis Pavement Cells with PaCeQuant (Cvrčková, F. & Žárský, V., eds.). Methods Mol. Biol. 1992, 329-349, (2019) ISBN: 978-1-4939-9469-4 DOI: 10.1007/978-1-4939-9469-4_22
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.
Wasternack, C.; Jasmonates in Plant Growth and Stress Responses (Tran, L.-S. P. & Pal, S., eds.). 221-263, (2014) ISBN: 978-1-4939-0491-4 DOI: 10.1007/978-1-4939-0491-4_8
Jasmonates are lipid-derived compounds which are signals in plant stress responses and development. They are synthesized in chloroplasts and peroxisomes. An endogenous rise occurs upon environmental stimuli or in distinct stages of development such as that of anthers and trichomes or in root growth. Hydroxylation, carboxylation, glucosylation, sulfation, methylation, or conjugation of jasmonic acid (JA) leads to numerous metabolites. Many of them are at least partially biologically inactive. The most bioactive JA is the (+)-7-iso-JA–isoleucine conjugate. Its perception takes place by the SCFCOI1-JAZ-co-receptor complex. At elevated levels of JAs, negative regulators such as JAZ, or JAV are subjected to proteasomal degradation, thereby allowing positively acting transcription factors of the MYC or MYB family to switch on JA-induced gene expression. In case of JAM negative regulation takes place by anatagonism to MYC2. JA and COI1 are dominant signals in gene expression after wounding or in response to necrotrophic pathogens. Cross-talk to salicylic acid, ethylene, auxin, and other hormones occurs. Growth is inhibited by JA, thereby counteracting the growth stimulation by gibberellic acid. Senescence, trichome formation, arbuscular mycorrhiza, and formation of many secondary metabolites are induced by jasmonates. Effects in cold acclimation; in intercropping; during response to herbivores, nematodes, or necrotrophic pathogens; in pre- and post-harvest; in crop quality control; and in biosynthesis of secondary compounds led to biotechnological and agricultural applications.
Wasternack, C.; Hause, B.; Benno Parthier und die Jasmonatforschung in Halle (Hacker, J., ed.). Nova Acta Leopoldina Supplementum Nr. 28, 29-38, (2013)
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