Protein-protein interactions (PPIs) are essential in understanding numerous aspects of protein function. Here, we significantly scaled and modified analyses of the recently developed all-vs-all sequencing (AVA-Seq) approach using a gold-standard human protein interaction set (hsPRS-v2) containing 98 proteins. Binary interaction analyses recovered 20 of 47 (43%) binary PPIs from this positive reference set (PRS), comparing favorably with other methods. However, the increase of 20Â in the interaction search space for AVA-Seq analysis in this manuscript resulted in numerous changes to the method required for future use in genome-wide interaction studies. We show that standard sequencing analysis methods must be modified to consider the possible recovery of thousands of positives among millions of tested interactions in a single sequencing run. The PRS data were used to optimize data scaling, autoactivator removal, rank interaction features (such as orientation and unique fragment pairs), and statistical cutoffs. Using these modifications to the method, AVA-Seq recovered >500 known and novel PPIs, including interactions between wild-type fragments of tumor protein p53 and minichromosome maintenance complex proteins 2 and 5 (MCM2 and MCM5) that could be of interest in human disease.

Objective Identify protein contact points between TP53 and minichromosome maintenance (MCM) complex proteins 2, 3, and 5 with high resolution allowing for potential novel Cancer drug design. Methods A next‐generation sequencing‐based protein–protein interaction method developed in our laboratory called AVA‐Seq was applied to a gold‐standard human protein interaction set. Proteins including TP53, MCM2, MCM3, MCM5, HSP90AA1, PCNA, NOD1, and others were sheared and ligated into the AVA‐Seq system. Protein–protein interactions were then identified in both mild and stringent selective conditions. Results Known interactions among MCM2, MCM3, and MCM5 were identified with the AVA‐Seq system. The interacting regions detected between these three proteins overlap with the structural data of the MCM complex, and novel domains were identified with high resolution determined by multiple overlapping fragments. Fragments of wild type TP53 were shown to interact with MCM2, MCM3, and MCM5, and details on the location of the interactions were provided. Finally, a mini‐network of known and novel cancer protein interactions was provided, which could have implications for fundamental changes in multiple cancers. Conclusion We provide a high‐resolution mini‐interactome that could direct novel drug targets and implicate possible effects of specific cancer mutations.

Background Colon cancer is often driven by mutations of the adenomatous polyposis coli (APC) gene, an essential tumor suppressor gene of the Wnt β-catenin signaling pathway. APC and its cytoplasmic interactions 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 understand APC’s nuclear role better and ultimately identify potential cancer treatment targets. Methods We used the all-vs-all sequencing (AVA-Seq) method to interrogate the interactome of protein fragments spanning most of the 60 Wnt β-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. Results 74 known and 703 novel Wnt β-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. Conclusion Based 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 APC binding to 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 β-catenin pathway protein-protein interactions from this study could lead researchers to novel drug designs for cancer.

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Here is an in‐depth characterization of a gold‐standard human protein interaction set (HsPRS‐v2) using AVA‐Seq's (all‐vs‐all sequencing) convergently fused fragment design. Selected protein pairs were sheared into ~500 bp fragments, selected for the open reading frame, assembled into the pAVA plasmid and integrated for protein interactions. Initially, these data were interpreted strictly from a binary perspective in order to compare this method to other binary protein‐protein interaction (PPI) methods which utilize the same HsPRS‐v2. AVA‐Seq was able to recapitulate 20 of 43 (46.5%) known binary PPIs from this positive reference set; 5 of these interactions were not captured by other methods previously reported. The use of this gold‐standard set allows for a better understanding of the limitations and advantages of AVA‐Seq. For example, there are PPIs which were not detected even though 95% of the amino acids between the two proteins were represented. Conversely, interactions were detected with as little as 16% protein coverage. The average protein coverage of all protein pairs used in this study was 60% while the average coverage for a detected interaction pair was 68%. By increasing the coverage of the proteins to >70%, the detection of expected PPIs in this data set is expected to increase to >50%. The same experimental data allowed for the determination of other interactions within this known interacting set. To that end, AVA‐Seq has detected >500 PPIs from the HsPRS‐v2 proteins tested; many of which are found with multiple unique fragment pairs, in multiple screening libraries, in multiple growth conditions and in both orientations. Ongoing work aims to make enhancements to this system for application of small, focused protein interaction sets (such as this study), as well as determining the entire interactomes, among others. The ease, swiftness, and reliability of AVA‐Seq allows the user to determine PPIs in a protein pool of their choosing and also interrogate the active site regions of proteins with high‐resolution by taking advantage of the convergent fragment feature of this method.