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Al-Thani, N. M.

Publications and source records attributed to Al-Thani, N. M..

3 recordsLinked to original sources

Identifying novel interactions of the colon-cancer related APC protein with Wnt-pathway nuclear transcription factors

BackgroundColon cancer is often driven by mutations of the adenomatous polyposis coli (APC) gene, an essential tumor suppressor gene of the Wnt {beta}-catenin signaling pathway. APC and its interactions in the cytoplasm have been well studied, however various groups have also observed its presence in the nucleus. Identifying novel interactions of APC in the Wnt pathway will provide an opportunity to better understand the nuclear role of APC and ultimately identify potential cancer treatment targets. MethodsWe used the all-vs-all sequencing (AVA-Seq) method to interrogate the interactome of protein fragments spanning most of the 60 Wnt {beta}-catenin pathway proteins. Using protein fragments identified the interacting regions between the proteins with more resolution than a full-length protein approach. Pull-down assays were used to validate a subset of these interactions. Results74 known and 703 novel Wnt {beta}-catenin pathway protein-protein interactions were recovered in this study. There were 8 known and 31 novel APC protein-protein interactions. Novel interactions of APC and nuclear transcription factors TCF7, JUN, FOSL1, and SOX17 were particularly interesting and confirmed in validation assays. ConclusionBased on our findings of novel interactions between APC and transcription factors and previous evidence of APC localizing to the nucleus, we suggest APC may compete and repress CTNNB1. This would occur through the binding of the transcription factors (JUN, FOSL1, TCF7) to regulate the Wnt signaling pathway including through enhanced marking of CTNNB1 for degradation in the nucleus by APC binding with SOX17. Additional novel Wnt {beta}-catenin pathway protein-protein interactions from this study could lead researchers to novel drug designs for cancer.

molecular biology↗

High-resolution protein fragment interactions using AVA-Seq on a human reference set

Protein-protein interactions (PPIs) are important in understanding numerous aspects of protein function. Here, the recently developed all-vs-all sequencing (AVA-Seq) approach to determine protein-protein interactions was tested on a gold-standard human protein interaction set (hsPRS-v2). Initially, these data were interpreted strictly from a binary PPI perspective to compare AVA-Seq to other binary PPI methods tested on the same hsPRS-v2. AVA-Seq recovered 20 of 47 (43%) binary PPIs from this reference set comparing favorably with other methods. The same experimental data allowed for the determination of >500 known and novel PPIs including interactions between wildtype fragments of tumor protein p53 and minichromosomal maintenance complex proteins 2, and 5 (MCM2 and MCM5) that could be of interest in human disease. Additional results gave a better understanding of why interactions might be missed using AVA-Seq and aide future PPI experimental design for maximum recovery of information.

genomics↗

High resolution protein-protein interaction mapping using all-versus-all sequencing (AVA-seq)

Two-hybrid systems test for protein-protein interactions and can provide important information for genes with unknown function. Despite their success, two-hybrid systems have remained mostly untouched by improvements from next-generation DNA sequencing. Here we present a method for all-versus-all protein interaction mapping (AVA-seq) that utilizes next-generation sequencing to remove multiple bottlenecks of the two-hybrid process. The method allows for high resolution protein-protein interaction mapping of a small set of proteins, or the potential for lower-resolution mapping of entire proteomes. Features of the system include open-reading frame selection to improve efficiency, high bacterial transformation efficiency, a convergent fusion vector to allow paired-end sequencing of interactors, and the use of protein fragments rather than full-length genes to better resolve specific protein contact points. We demonstrate the systems strengths and limitations on a set of proteins known to interact in humans and provide a framework for future large-scale projects.

genomics↗