Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
Seit Februar 2021 bietet Wolfgang Brandt, ehemaliger Leiter der Arbeitsgruppe Computerchemie am IPB, sein Citizen Science-Projekt zur Pilzbestimmung an. Dafür hat er in regelmäßigen Abständen öffentliche Vorträge zur Vielfalt…
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.
Publikation
Chutia, R.; Scharfenberg, S.; Neumann, S.; Abel, S.; Ziegler, J.;Modulation of phosphate deficiency-induced metabolic changes by iron availability in Arabidopsis thalianaInt. J. Mol. Sci.227609(2021)DOI: 10.3390/ijms22147609
Concurrent suboptimal supply of several nutrients requires the coordination of nutrient-specific transcriptional, phenotypic, and metabolic changes in plants in order to optimize growth and development in most agricultural and natural ecosystems. Phosphate (Pi) and iron (Fe) deficiency induce overlapping but mostly opposing transcriptional and root growth responses in Arabidopsis thaliana. On the metabolite level, Pi deficiency negatively modulates Fe deficiency-induced coumarin accumulation, which is controlled by Fe as well as Pi deficiency response regulators. Here, we report the impact of Fe availability on seedling growth under Pi limiting conditions and on Pi deficiency-induced accumulation of amino acids and organic acids, which play important roles in Pi use efficiency. Fe deficiency in Pi replete conditions hardly changed growth and metabolite profiles in roots and shoots of Arabidopsis thaliana, but partially rescued growth under conditions of Pi starvation and severely modulated Pi deficiency-induced metabolic adjustments. Analysis of T-DNA insertion lines revealed the concerted coordination of metabolic profiles by regulators of Fe (FIT, bHLH104, BRUTUS, PYE) as well as of Pi (SPX1, PHR1, PHL1, bHLH32) starvation responses. The results show the interdependency of Pi and Fe availability and the interplay between Pi and Fe starvation signaling on the generation of plant metabolite profiles.
Publikation
Peters, K.; Worrich, A.; Weinhold, A.; Alka, O.; Balcke, G.; Birkemeyer, C.; Bruelheide, H.; Calf, O. W.; Dietz, S.; Dührkop, K.; Gaquerel, E.; Heinig, U.; Kücklich, M.; Macel, M.; Müller, C.; Poeschl, Y.; Pohnert, G.; Ristok, C.; Rodríguez, V. M.; Ruttkies, C.; Schuman, M.; Schweiger, R.; Shahaf, N.; Steinbeck, C.; Tortosa, M.; Treutler, H.; Ueberschaar, N.; Velasco, P.; Weiß, B. M.; Widdig, A.; Neumann, S.; van Dam, N. M.;Current Challenges in Plant Eco-MetabolomicsInt. J. Mol. Sci.191385(2018)DOI: 10.3390/ijms19051385
The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these challenges will advance connecting the distinct spatiotemporal scales and bridging biochemistry and ecology
Publikation
Mönchgesang, S.; Strehmel, N.; Trutschel, D.; Westphal, L.; Neumann, S.; Scheel, D.;Plant-to-Plant Variability in Root Metabolite Profiles of 19 Arabidopsis thaliana Accessions Is Substance-Class-DependentInt. J. Mol. Sci.171565(2016)DOI: 10.3390/ijms17091565
Natural variation of secondary metabolism between different accessions of Arabidopsis thaliana (A. thaliana) has been studied extensively. In this study, we extended the natural variation approach by including biological variability (plant-to-plant variability) and analysed root metabolic patterns as well as their variability between plants and naturally occurring accessions. To screen 19 accessions of A. thaliana, comprehensive non-targeted metabolite profiling of single plant root extracts was performed using ultra performance liquid chromatography/electrospray ionization quadrupole time-of-flight mass spectrometry (UPLC/ESI-QTOF-MS) and gas chromatography/electron ionization quadrupole mass spectrometry (GC/EI-QMS). Linear mixed models were applied to dissect the total observed variance. All metabolic profiles pointed towards a larger plant-to-plant variability than natural variation between accessions and variance of experimental batches. Ratios of plant-to-plant to total variability were high and distinct for certain secondary metabolites. None of the investigated accessions displayed a specifically high or low biological variability for these substance classes. This study provides recommendations for future natural variation analyses of glucosinolates, flavonoids, and phenylpropanoids and also reference data for additional substance classes.