A complete understanding of cell biological processes relies on finding the protein interaction networks that underlie their molecular mechanisms. One approach to identify protein interactions is the yeast 2-hybrid (Y2H) assay, which works by assembling a functioning chimeric transcription factor once two protein domains of interest bind to one another1. A typical Y2H screen is performed by creating a population of yeast that houses both a library of plasmids encoding interacting proteins fused to a transcriptional activator (e.g., 'prey' fusion protein) and a given 'bait' plasmid comprised of the protein of interest fused to a DNA binding domain (e.g., the Gal4 DNA-binding domain that binds to the Gal4-upstream activating sequence). One of the main advantages of the Y2H approach is that it is relatively easy and inexpensive to conduct in a typical laboratory equipped for routine molecular biological work2. However, when traditionally performed, a user samples individual colonies that arise upon selection for a positive Y2H interaction. This severely limits the number of library 'prey' clones that can be surveyed. This problem is compounded when the abundance of a particular interacting prey is very high relative to the others, diminishing the chance of detecting interaction from low abundance prey plasmids.
One solution for using the Y2H principle in comprehensive coverage of the proteome is the use of a matrix-formatted approach wherein an array containing known individual prey plasmids can be digitally interrogated. However, such an approach requires an infrastructure that is not readily accessible or cost-effective to individual investigators who are interested in defining the interactome of a small number of proteins or domains3. In addition, very complex prey libraries that may encode multiple fragments of interacting proteins would expand the size of such matrix arrays to impractical sizes. An alternative is to perform assays with complex libraries in batches and assess the presence of interacting clones using massive parallel high-throughput sequencing4. This can be applied to assay the presence of prey plasmids that arise in multiple colonies using a typical Y2H formatted approach in which yeast cells housing an interacting pair of fusion proteins are allowed to grow on a plate5,6. This general idea can be accentuated to increase query of both multiple bait and prey components at the same time7,8.
Still, many investigations require an easier yet more focused effort on just a few protein 'baits' and can benefit more by an exhaustive and semi-quantitative query of a single complex prey library. We have developed and validated an approach to perform wide-scale protein interaction studies using a Y2H principle in batch format4. This uses the rate of expansion of a particular prey plasmid as a proxy for the relative strength of Y2H interaction9. Deep sequencing of all plasmids within a population subjected to normal growth or selective growth conditions produces a complete map of clones that yield strong and weak Y2H interactions. The repertoire of interactors can be obtained and directly compared across multiple bait plasmids. The resulting workflow termed DEEPN (Dynamic Enrichment for Evaluation of Protein Networks) can thus be used to identify differential interactomes from the same prey libraries to identify proteins, allowing comparison between one protein vs. another.
Here, we demonstrate DEEPN and introduce improvements in the laboratory methods that facilitate its use, which are outlined in Figure 1. Significant improvements include:
Generation of prey yeast populations. One of the key requirements of DEEPN is generating populations of yeast with different bait plasmids that have the same distribution of the plasmid prey libraries. Equivalent baseline populations of the prey plasmid library are essential for making accurate comparisons between the interactomes of different baits. This is best achieved when a library plasmid is already housed in a haploid yeast population and moving a given bait plasmid into that population is achieved by mating to produce a diploid. Here, we provide a clear guide in how to make such populations using commercial libraries housed in haploid yeast. Although we found methods that generate a high number of diploids, the overall mating efficiency of these commercial library-containing yeast strains was low. Therefore, we constructed a new strain that can house prey libraries that yields far more diploids per mating reaction.
New set of bait plasmids. Many current plasmids that express 'bait' fusion proteins comprised of the protein of interest and a DNA-binding domain are 2µ-based, allowing them to amplify their copy number. This copy number can be quite variable in the population and lead to variability in the Y2H transcriptional response. This in turn could skew the ability to gauge the strength of a given protein interaction based on the growth response of cells under selection. This can be partly address by using a low copy plasmid, some of which have been previously described such as the commercially available pDEST3210. We constructed a new bait plasmid (pTEF-GBD) that produces Gal4-DNA-binding domain fusion proteins within a TRP1 centromere-based low copy plasmid carrying the Kanr resistance gene that also allows cloning of bait fragments both upstream and downstream of the Gal4 DNA-binding domain.
New High-Density Y2H fragment library. We constructed a new plasmid to house Y2H prey libraries and used it to build a highly complex Y2H library made of randomly sheared fragments of genomic DNA from Saccharomyces cerevisiae. Sequence analysis showed that this library had over 1 million different elements, far more complex than previously described yeast genomic Y2H plasmid libraries11. With this new library, we were able to show that the DEEPN workflow is robust enough to accommodate complex libraries with many different plasmids in a manner that is reliable and reproducible.