Rauter, Thomas*
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Plants as non-mobile organisms constantly integrate varying environmental signals to flexibly adapt their growth and development. Local fluctuations in water and nutrient availability, sudden changes in temperature or other abiotic and biotic stresses can trigger changes in the growth of plant organs. Multiple mutually interconnected hormonal signaling cascades act as essential endogenous translators of these exogenous signals in the adaptive responses of plants. Although the molecular backbones of hormone transduction pathways have been identified, the mechanisms underlying their interactions are largely unknown. Here, using genome wide transcriptome profiling we identify an auxin and cytokinin cross-talk component; SYNERGISTIC ON AUXIN AND CYTOKININ 1 (SYAC1), whose expression in roots is strictly dependent on both of these hormonal pathways. We show that SYAC1 is a regulator of secretory pathway, whose enhanced activity interferes with deposition of cell wall components and can fine-tune organ growth and sensitivity to soil pathogens.
- MeSH
- Arabidopsis genetika růst a vývoj metabolismus MeSH
- buněčná stěna chemie metabolismus MeSH
- cytokininy metabolismus MeSH
- endozomy metabolismus MeSH
- geneticky modifikované rostliny metabolismus MeSH
- Golgiho aparát metabolismus MeSH
- kořeny rostlin metabolismus mikrobiologie MeSH
- kyseliny indoloctové metabolismus MeSH
- membránové proteiny genetika metabolismus MeSH
- odolnost vůči nemocem genetika MeSH
- Plasmodiophorida patogenita MeSH
- proteiny huseníčku genetika metabolismus MeSH
- půda MeSH
- regulace genové exprese u rostlin genetika MeSH
- regulátory růstu rostlin metabolismus MeSH
- sekreční dráha genetika MeSH
- stanovení celkové genové exprese MeSH
- transkriptom genetika MeSH
- vezikulární transportní proteiny metabolismus MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Extracellular vesicle (EV) research increasingly demands for quantitative characterisation at the single vesicle level to address heterogeneity and complexity of EV subpopulations. Emerging, commercialised technologies for single EV analysis based on, for example, imaging flow cytometry or imaging after capture on chips generally require dedicated instrumentation and proprietary software not readily accessible to every lab. This limits their implementation for routine EV characterisation in the rapidly growing EV field. We and others have shown that single vesicles can be detected as light diffraction limited fluorescent spots using standard confocal and widefield fluorescence microscopes. Advancing this simple strategy into a process for routine EV quantitation, we developed 'EVAnalyzer', an ImageJ/Fiji (Fiji is just ImageJ) plugin for automated, quantitative single vesicle analysis from imaging data. Using EVAnalyzer, we established a robust protocol for capture, (immuno-)labelling and fluorescent imaging of EVs. To exemplify the application scope, the process was optimised and systematically tested for (i) quantification of EV subpopulations, (ii) validation of EV labelling reagents, (iii) in situ determination of antibody specificity, sensitivity and species cross-reactivity for EV markers and (iv) optimisation of genetic EV engineering. Additionally, we show that the process can be applied to synthetic nanoparticles, allowing to determine siRNA encapsulation efficiencies of lipid-based nanoparticles (LNPs) and protein loading of SiO2 nanoparticles. EVAnalyzer further provides a pipeline for automated quantification of cell uptake at the single cell-single vesicle level, thereby enabling high content EV cell uptake assays and plate-based screens. Notably, the entire procedure from sample preparation to the final data output is entirely based on standard reagents, materials, laboratory equipment and open access software. In summary, we show that EVAnalyzer enables rigorous characterisation of EVs with generally accessible tools. Since we further provide the plugin as open-source code, we expect EVAnalyzer to not only be a resource of immediate impact, but an open innovation platform for the EV and nanoparticle research communities.
