RESUMO
For a long time D-enantiomers of proteinogenic L-amino acids were assumed to be physiologically irrelevant for plants. But there is growing evidence that D-amino acids (D-AAs) also fulfil important physiological functions in these organisms. However, the knowledge about the metabolic fate of D-AAs in plants is still scarce and more information about it is needed. To close this gap we established an optimized protocol for the processing and analysis of D- and L-AAs from large numbers of Arabidopsis lines. This included the application of 18 different D-AAs to seedlings, the extraction of free amino acids from the samples and the determination of 16 L-AAs and their corresponding D-enantiomers. To validate our approach we searched for genetic accessions with aberrant amino acid metabolism. Therefore we applied D-AAs on 17 ecotypes of Arabidopsis thaliana and analysed their free amino acid contents. These analyses confirmed the suitability of the system for the analysis of large sets of plant samples with enhanced velocity and improved accuracy. Furthermore, the resulting data led to the definition of standard amino acid profiles in response to D-AAs of Arabidopsis seedlings. Within these analyses the ecotype Landsberg erecta was found with aberrant metabolic patterns like drastically reduced capabilities to convert different D-AAs to D-alanine and D-glutamate. The presented experimental setup and results of this study offer starting points to dissect the metabolic pathway of D-AAs in plants.
RESUMO
DNA-binding proteins (DBPs), such as transcription factors, constitute about 10% of the protein-coding genes in eukaryotic genomes and play pivotal roles in the regulation of chromatin structure and gene expression by binding to short stretches of DNA. Despite their number and importance, only for a minor portion of DBPs the binding sequence had been disclosed. Methods that allow the de novo identification of DNA-binding motifs of known DBPs, such as protein binding microarray technology or SELEX, are not yet suited for high-throughput and automation. To close this gap, we report an automatable DNA-protein-interaction (DPI)-ELISA screen of an optimized double-stranded DNA (dsDNA) probe library that allows the high-throughput identification of hexanucleotide DNA-binding motifs. In contrast to other methods, this DPI-ELISA screen can be performed manually or with standard laboratory automation. Furthermore, output evaluation does not require extensive computational analysis to derive a binding consensus. We could show that the DPI-ELISA screen disclosed the full spectrum of binding preferences for a given DBP. As an example, AtWRKY11 was used to demonstrate that the automated DPI-ELISA screen revealed the entire range of in vitro binding preferences. In addition, protein extracts of AtbZIP63 and the DNA-binding domain of AtWRKY33 were analyzed, which led to a refinement of their known DNA-binding consensi. Finally, we performed a DPI-ELISA screen to disclose the DNA-binding consensus of a yet uncharacterized putative DBP, AtTIFY1. A palindromic TGATCA-consensus was uncovered and we could show that the GATC-core is compulsory for AtTIFY1 binding. This specific interaction between AtTIFY1 and its DNA-binding motif was confirmed by in vivo plant one-hybrid assays in protoplasts. Thus, the value and applicability of the DPI-ELISA screen for de novo binding site identification of DBPs, also under automatized conditions, is a promising approach for a deeper understanding of gene regulation in any organism of choice.