Dataset Information

Automated protein-DNA interaction screening of Drosophila regulatory elements.

ABSTRACT: Drosophila melanogaster has one of the best characterized metazoan genomes in terms of functionally annotated regulatory elements. To explore how these elements contribute to gene regulation, we need convenient tools to identify the proteins that bind to them. Here we describe the development and validation of a high-throughput yeast one-hybrid platform, which enables screening of DNA elements versus an array of full-length, sequence-verified clones containing over 85% of predicted Drosophila transcription factors. Using six well-characterized regulatory elements, we identified 33 transcription factor-DNA interactions of which 27 were previously unidentified. To simultaneously validate these interactions and locate the binding sites of involved transcription factors, we implemented a powerful microfluidics-based approach that enabled us to retrieve DNA-occupancy data for each transcription factor throughout the respective target DNA elements. Finally, we biologically validated several interactions and identified two new regulators of sine oculis gene expression and hence eye development.

SUBMITTER: Hens K

PROVIDER: S-EPMC3929264 | biostudies-literature | 2011 Oct

REPOSITORIES: biostudies-literature

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Automated protein-DNA interaction screening of Drosophila regulatory elements.

Hens Korneel K Feuz Jean-Daniel JD Isakova Alina A Iagovitina Antonina A Massouras Andreas A Bryois Julien J Callaerts Patrick P Celniker Susan E SE Deplancke Bart B

Nature methods 20111030 12

Drosophila melanogaster has one of the best characterized metazoan genomes in terms of functionally annotated regulatory elements. To explore how these elements contribute to gene regulation, we need convenient tools to identify the proteins that bind to them. Here we describe the development and validation of a high-throughput yeast one-hybrid platform, which enables screening of DNA elements versus an array of full-length, sequence-verified clones containing over 85% of predicted Drosophila tr ...[more]

PMID: 22037703

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Project description: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.

Dataset Information

Automated protein-DNA interaction screening of Drosophila regulatory elements.

Publications

Automated protein-DNA interaction screening of Drosophila regulatory elements.

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