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Publications - Cell and Metabolic Biology

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Publications

El Amerany, F.; Rhazi, M.; Balcke, G.; Wahbi, S.; Meddich, A.; Taourirte, M.; Hause, B.; The effect of chitosan on plant physiology, wound response, and fruit quality of tomato Polymers 14, 5006, (2022) DOI: 10.3390/polym14225006

In agriculture, chitosan has become popular as a metabolic enhancer; however, no deep information has been obtained yet regarding its mechanisms on vegetative tissues. This work was conducted to test the impact of chitosan applied at different plant growth stages on plant development, physiology, and response to wounding as well as fruit shape and composition. Five concentrations of chitosan were tested on tomato. The most effective chitosan doses that increased leaf number, leaf area, plant biomass, and stomatal conductance were 0.75 and 1 mg mL−1. Chitosan (1 mg mL−1) applied as foliar spray increased the levels of jasmonoyl–isoleucine and abscisic acid in wounded roots. The application of this dose at vegetative and flowering stages increased chlorophyll fluorescence (Fv/Fm) values, whereas application at the fruit maturation stage reduced the Fv/Fm values. This decline was positively correlated with fruit shape and negatively correlated with the pH and the content of soluble sugars, lycopene, total flavonoids, and nitrogen in fruits. Moreover, the levels of primary metabolites derived from glycolysis, such as inositol phosphate, lactic acid, and ascorbic acid, increased in response to treatment of plants with 1 mg mL−1- chitosan. Thus, chitosan application affects various plant processes by influencing stomata aperture, cell division and expansion, fruit maturation, mineral assimilation, and defense responses.
Publications

Peters, K.; Balcke, G.; Kleinenkuhnen, N.; Treutler, H.; Neumann, S.; Untargeted in silico compound classification—A novel metabolomics method to assess the chemodiversity in bryophytes Int. J. Mol. Sci. 22, 3251, (2021) DOI: 10.3390/ijms22063251

In plant ecology, biochemical analyses of bryophytes and vascular plants are often conducted on dried herbarium specimen as species typically grow in distant and inaccessible locations. Here, we present an automated in silico compound classification framework to annotate metabolites using an untargeted data independent acquisition (DIA)–LC/MS–QToF-sequential windowed acquisition of all theoretical fragment ion mass spectra (SWATH) ecometabolomics analytical method. We perform a comparative investigation of the chemical diversity at the global level and the composition of metabolite families in ten different species of bryophytes using fresh samples collected on-site and dried specimen stored in a herbarium for half a year. Shannon and Pielou’s diversity indices, hierarchical clustering analysis (HCA), sparse partial least squares discriminant analysis (sPLS-DA), distance-based redundancy analysis (dbRDA), ANOVA with post-hoc Tukey honestly significant difference (HSD) test, and the Fisher’s exact test were used to determine differences in the richness and composition of metabolite families, with regard to herbarium conditions, ecological characteristics, and species. We functionally annotated metabolite families to biochemical processes related to the structural integrity of membranes and cell walls (proto-lignin, glycerophospholipids, carbohydrates), chemical defense (polyphenols, steroids), reactive oxygen species (ROS) protection (alkaloids, amino acids, flavonoids), nutrition (nitrogen- and phosphate-containing glycerophospholipids), and photosynthesis. Changes in the composition of metabolite families also explained variance related to ecological functioning like physiological adaptations of bryophytes to dry environments (proteins, peptides, flavonoids, terpenes), light availability (flavonoids, terpenes, carbohydrates), temperature (flavonoids), and biotic interactions (steroids, terpenes). The results from this study allow to construct chemical traits that can be attributed to biogeochemistry, habitat conditions, environmental changes and biotic interactions. Our classification framework accelerates the complex annotation process in metabolomics and can be used to simplify biochemical patterns. We show that compound classification is a powerful tool that allows to explore relationships in both molecular biology by “zooming in” and in ecology by “zooming out”. The insights revealed by our framework allow to construct new research hypotheses and to enable detailed follow-up studies.
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