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VMP1-deficient Chlamydomonas exhibits severely aberrant cell morphology and disrupted cytokinesies
(2014)
Background: The versatile Vacuole Membrane Protein 1 (VMP1) has been previously investigated in six species. It has been shown to be essential in macroautophagy, where it takes part in autophagy initiation. In addition, VMP1 has been implicated in organellar biogenesis; endo-, exo- and phagocytosis, and protein secretion; apoptosis; and cell adhesion. These roles underly its proven involvement in pancreatitis, diabetes and cancer in humans.
Results: In this study we analyzed a VMP1 homologue from the green alga Chlamydomonas reinhardtii. CrVMP1 knockdown lines showed severe phenotypes, mainly affecting cell division as well as the morphology of cells and organelles. We also provide several pieces of evidence for its involvement in macroautophagy.
Biomarkers are used to predict phenotypical properties before these features become apparent and, therefore, are valuable tools for both fundamental and applied research. Diagnostic biomarkers have been discovered in medicine many decades ago and are now commonly applied. While this is routine in the field of medicine, it is of surprise that in agriculture this approach has never been investigated. Up to now, the prediction of phenotypes in plants was based on growing plants and assaying the organs of interest in a time intensive process. For the first time, we demonstrate in this study the application of metabolomics to predict agronomic important phenotypes of a crop plant that was grown in different environments. Our procedure consists of established techniques to screen untargeted for a large amount of metabolites in parallel, in combination with machine learning methods. By using this combination of metabolomics and biomathematical tools metabolites were identified that can be used as biomarkers to improve the prediction of traits. The predictive metabolites can be selected and used subsequently to develop fast, targeted and low-cost diagnostic biomarker assays that can be implemented in breeding programs or quality assessment analysis. The identified metabolic biomarkers allow for the prediction of crop product quality. Furthermore, marker-assisted selection can benefit from the discovery of metabolic biomarkers when other molecular markers come to its limitation. The described marker selection method was developed for potato tubers, but is generally applicable to any crop and trait as it functions independently of genomic information.
Maltose frequently occurs as intermediate of the central carbon metabolism of prokaryotic and eukaryotic cells. Various mutants possess elevated maltose levels. Maltose exists as two anomers, (alpha- and beta-form) which are rapidly interconverted without requiring enzyme-mediated catalysis. As maltose is often abundant together with other oligoglucans, selective quantification is essential. In this communication, we present a photometric maltose assay using 4-alpha-glucanotransferase (AtDPE2) from Arabidopsis thaliana. Under in vitro conditions, AtDPE2 utilizes maltose as glucosyl donor and glycogen as acceptor releasing the other hexosyl unit as free glucose which is photometrically quantified following enzymatic phosphorylation and oxidation. Under the conditions used, DPE2 does not noticeably react with other di- or oligosaccharides. Selectivity compares favorably with that of maltase frequently used in maltose assays. Reducing end interconversion of the two maltose anomers is in rapid equilibrium and, therefore, the novel assay measures total maltose contents. Furthermore, an AtDPE2-based continuous photometric assay is presented which allows to quantify beta-amylase activity and was found to be superior to a conventional test. Finally, the AtDPE2-based maltose assay was used to quantify leaf maltose contents of both Arabidopsis wild type and AtDPE2-deficient plants throughout the light-dark cycle. These data are presented together with assimilatory starch levels. (C) 2017 Published by Elsevier Inc.