540 Chemie und zugeordnete Wissenschaften
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Current metabolomics approaches utilize cellular metabolite extracts, are destructive, and require high cell numbers. We introduce here an approach that enables the monitoring of cellular metabolism at lower cell numbers by observing the consumption/production of different metabolites over several kinetic data points of up to 48 hours. Our approach does not influence cellular viability, as we optimized the cellular matrix in comparison to other materials used in a variety of in‐cell NMR spectroscopy experiments. We are able to monitor real‐time metabolism of primary patient cells, which are extremely sensitive to external stress. Measurements are set up in an interleaved manner with short acquisition times (approximately 7 minutes per sample), which allows the monitoring of up to 15 patient samples simultaneously. Further, we implemented our approach for performing tracer‐based assays. Our approach will be important not only in the metabolomics fields, but also in individualized diagnostics.
Current metabolomics approaches utilize cellular metabolite extracts, are destructive, and require high cell numbers. We introduce here an approach that enables the monitoring of cellular metabolism at lower cell numbers by observing the consumption/production of different metabolites over several kinetic data points of up to 48 hours. Our approach does not influence cellular viability, as we optimized the cellular matrix in comparison to other materials used in a variety of in‐cell NMR spectroscopy experiments. We are able to monitor real‐time metabolism of primary patient cells, which are extremely sensitive to external stress. Measurements are set up in an interleaved manner with short acquisition times (approximately 7 minutes per sample), which allows the monitoring of up to 15 patient samples simultaneously. Further, we implemented our approach for performing tracer‐based assays. Our approach will be important not only in the metabolomics fields, but also in individualized diagnostics.
NMR and chromatography methods combined with mass spectrometry are the most important analytical techniques employed for plant metabolomics screening. Metabolomic analysis integrated to transcriptome screening add an important extra dimension to the information flow from DNA to RNA to protein. The most useful NMR experiment in metabolomics analysis is the proton spectra due the high receptivity of 1H and important structural information, through proton–proton scalar coupling. Routinely, databases have been used in identification of primary metabolites, however, there is currently no comparable data for identification of secondary metabolites, mainly, due to signal overlap in normal 1H NMR spectra and natural variation of plant. Related to spectra overlap, alternatively, better resolution can be find using 1H pure shift and 2D NMR pulse sequence in complex samples due to spreading the resonances in a second dimension. Thus, in data brief we provide a catalogue of metabolites and expression levels of genes identified in soy leaves and roots under flooding stress.
Plant-released flavonoids induce the transcription of symbiotic genes in rhizobia and one of the first bacterial responses is the synthesis of so called Nod factors. They are responsible for the initial root hair curling during onset of root nodule development. This signal exchange is believed to be essential for initiating the plant symbiosis with rhizobia affiliated with the Alphaproteobacteria. Here, we provide evidence that in the broad host range strain Sinorhizobium fredii NGR234 the complete lack of quorum sensing molecules results in an elevated copy number of its symbiotic plasmid (pNGR234a). This in turn triggers the expression of symbiotic genes and the production of Nod factors in the absence of plant signals. Therefore, increasing the copy number of specific plasmids could be a widespread mechanism of specialized bacterial populations to bridge gaps in signaling cascades.