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A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations.

Wei X, Das J, Fragoza R, Liang J, Bastos de Oliveira FM, Lee HR, Wang X, Mort M, Stenson PD, Cooper DN, Lipkin SM, Smolka MB, Yu H - PLoS Genet. (2014)

Bottom Line: We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles.We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions.The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Weill Cornell College of Medicine, New York, New York, United States of America; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

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Schematic of our comparative interactome-scanning pipeline.Our pipeline begins with Clone-seq (a), a massively-parallel low-cost site-directed mutagenesis pipeline leveraging next-generation sequencing. This is followed by a high-throughput GFP assay (b) to determine protein stability, and a high-throughput Y2H assay (c), along with SILAC-based mass spectrometry (d) to determine the impact of DNA coding variants on protein interactions.
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pgen-1004819-g001: Schematic of our comparative interactome-scanning pipeline.Our pipeline begins with Clone-seq (a), a massively-parallel low-cost site-directed mutagenesis pipeline leveraging next-generation sequencing. This is followed by a high-throughput GFP assay (b) to determine protein stability, and a high-throughput Y2H assay (c), along with SILAC-based mass spectrometry (d) to determine the impact of DNA coding variants on protein interactions.

Mentions: To address these questions, we decided to focus on proteins with known disease mutations that participate in interactions with available co-crystal structures in the Protein Data Bank (PDB) [8]. To detect the alteration of the interactions by disease mutations, it is necessary to first detect the interactions of the wild-type proteins using an assay of choice. This turns out to be a major bottleneck because all high-throughput interaction-detection assays have very limited sensitivity [9], [10]. Our assay of choice is Y2H because there are over 16,000 human protein interactions detected by our version of Y2H that can serve as the reference interactome for comparison [11], [12], [13], [14], the largest for any assay performed to date (Figure S1). In total, there are 217 interactions detected by our version of Y2H with available co-crystal structures; 51 of these also have known missense disease mutations on corresponding proteins in the Human Gene Mutation Database (HGMD) [1] and the corresponding interactions for the wild-type proteins can be detected in our experiments with strong Y2H-positive phenotypes (Figure S2; Materials and Methods). Here, we focused on missense mutations because they are intrinsically more likely to generate interaction-specific disruptions [6]. We established a high-throughput comparative interactome-scanning pipeline to clone disease mutations and examine their molecular phenotypes (Fig. 1). The methodologies established here can be readily applied to any non-synonymous variant in the coding region, including nonsense mutations.


A massively parallel pipeline to clone DNA variants and examine molecular phenotypes of human disease mutations.

Wei X, Das J, Fragoza R, Liang J, Bastos de Oliveira FM, Lee HR, Wang X, Mort M, Stenson PD, Cooper DN, Lipkin SM, Smolka MB, Yu H - PLoS Genet. (2014)

Schematic of our comparative interactome-scanning pipeline.Our pipeline begins with Clone-seq (a), a massively-parallel low-cost site-directed mutagenesis pipeline leveraging next-generation sequencing. This is followed by a high-throughput GFP assay (b) to determine protein stability, and a high-throughput Y2H assay (c), along with SILAC-based mass spectrometry (d) to determine the impact of DNA coding variants on protein interactions.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4263371&req=5

pgen-1004819-g001: Schematic of our comparative interactome-scanning pipeline.Our pipeline begins with Clone-seq (a), a massively-parallel low-cost site-directed mutagenesis pipeline leveraging next-generation sequencing. This is followed by a high-throughput GFP assay (b) to determine protein stability, and a high-throughput Y2H assay (c), along with SILAC-based mass spectrometry (d) to determine the impact of DNA coding variants on protein interactions.
Mentions: To address these questions, we decided to focus on proteins with known disease mutations that participate in interactions with available co-crystal structures in the Protein Data Bank (PDB) [8]. To detect the alteration of the interactions by disease mutations, it is necessary to first detect the interactions of the wild-type proteins using an assay of choice. This turns out to be a major bottleneck because all high-throughput interaction-detection assays have very limited sensitivity [9], [10]. Our assay of choice is Y2H because there are over 16,000 human protein interactions detected by our version of Y2H that can serve as the reference interactome for comparison [11], [12], [13], [14], the largest for any assay performed to date (Figure S1). In total, there are 217 interactions detected by our version of Y2H with available co-crystal structures; 51 of these also have known missense disease mutations on corresponding proteins in the Human Gene Mutation Database (HGMD) [1] and the corresponding interactions for the wild-type proteins can be detected in our experiments with strong Y2H-positive phenotypes (Figure S2; Materials and Methods). Here, we focused on missense mutations because they are intrinsically more likely to generate interaction-specific disruptions [6]. We established a high-throughput comparative interactome-scanning pipeline to clone disease mutations and examine their molecular phenotypes (Fig. 1). The methodologies established here can be readily applied to any non-synonymous variant in the coding region, including nonsense mutations.

Bottom Line: We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles.We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions.The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

View Article: PubMed Central - PubMed

Affiliation: Department of Medicine, Weill Cornell College of Medicine, New York, New York, United States of America; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, United States of America.

ABSTRACT
Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, "Clone-seq", leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

Show MeSH