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      Screening for Protein-DNA Interactions by Automatable DNA-Protein Interaction ELISA

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          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.

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          Most cited references 95

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          WebLogo: a sequence logo generator.

          WebLogo generates sequence logos, graphical representations of the patterns within a multiple sequence alignment. Sequence logos provide a richer and more precise description of sequence similarity than consensus sequences and can rapidly reveal significant features of the alignment otherwise difficult to perceive. Each logo consists of stacks of letters, one stack for each position in the sequence. The overall height of each stack indicates the sequence conservation at that position (measured in bits), whereas the height of symbols within the stack reflects the relative frequency of the corresponding amino or nucleic acid at that position. WebLogo has been enhanced recently with additional features and options, to provide a convenient and highly configurable sequence logo generator. A command line interface and the complete, open WebLogo source code are available for local installation and customization. Copyright 2004 Cold Spring Harbor Laboratory Press
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            The pathogenicity of many bacteria depends on the injection of effector proteins via type III secretion into eukaryotic cells in order to manipulate cellular processes. TAL (transcription activator-like) effectors from plant pathogenic Xanthomonas are important virulence factors that act as transcriptional activators in the plant cell nucleus, where they directly bind to DNA via a central domain of tandem repeats. Here, we show how target DNA specificity of TAL effectors is encoded. Two hypervariable amino acid residues in each repeat recognize one base pair in the target DNA. Recognition sequences of TAL effectors were predicted and experimentally confirmed. The modular protein architecture enabled the construction of artificial effectors with new specificities. Our study describes the functionality of a distinct type of DNA binding domain and allows the design of DNA binding domains for biotechnology.
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              TRANSFAC: transcriptional regulation, from patterns to profiles.

              The TRANSFAC database on eukaryotic transcriptional regulation, comprising data on transcription factors, their target genes and regulatory binding sites, has been extended and further developed, both in number of entries and in the scope and structure of the collected data. Structured fields for expression patterns have been introduced for transcription factors from human and mouse, using the CYTOMER database on anatomical structures and developmental stages. The functionality of Match, a tool for matrix-based search of transcription factor binding sites, has been enhanced. For instance, the program now comes along with a number of tissue-(or state-)specific profiles and new profiles can be created and modified with Match Profiler. The GENE table was extended and gained in importance, containing amongst others links to LocusLink, RefSeq and OMIM now. Further, (direct) links between factor and target gene on one hand and between gene and encoded factor on the other hand were introduced. The TRANSFAC public release is available at For yeast an additional release including the latest data was made available separately as TRANSFAC Saccharomyces Module (TSM) at For CYTOMER free download versions are available at

                Author and article information

                Role: Editor
                PLoS One
                PLoS ONE
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                11 October 2013
                : 8
                : 10
                [1 ]Plant Physiology, Center for Plant Molecular Biology, University of Tuebingen, Tuebingen, Germany
                [2 ]Cognitive Systems, Center for Bioinformatics, University of Tuebingen, Tuebingen, Germany
                [3 ]Center for Life Science Automation, Rostock, Germany
                Florida International University, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: DW LHB HÜK GK CH AS AZ DW. Performed the experiments: LHB HÜK GK CH AS KT NW AH. Analyzed the data: LHB CH AS NW AH HÜK DW. Contributed reagents/materials/analysis tools: KH. Wrote the paper: LHB CH AS HÜK DW. Coordinated the experiments: LHB HÜK KH DW. Conceived the DPI-ELISA experiments: LHB HÜK GK. Conceived and designed the double-stranded DNA probe library algorithm: CH AS AZ DW. Conceived the protoplast one-hybrid assay: LHB HÜK DW. Performed the DPI-ELISA experiments: LHB HÜK GK. Programmed the double-stranded DNA probe library algorithm: CH AS. Performed the routines for automation and robotics: HÜK GK KT. Performed the protoplast one-hybrid assay: LHB NW AH. Contributed the biotinylated probe library: KH. Provided input to manuscript authors: LHB CH AS HÜK GK NW AH KT AZ KH DW.


                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Pages: 11
                This research was supported by a scholarship of the Landesgraduiertenförderung des Landes Baden-Württemberg to LHB. Funding for open access charge: German Science Foundation project grant HA2146/8-2. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Research Article



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