We describe a protocol based on the DHFR-PCA assay enabling the systematic identification of physical interactors for any given bait protein at high-throughput. This protocol can be adapted by screening for more baits, and this at any desired level of replication. We demonstrate the reliability of this protocol by the identification of physical interaction partners for a bait protein involved in the Nuclear Pore Complex: Nup82. Our analysis enabled to find five previously reported interactors and one previously unreported interactor (Figures 3F & 3G), highlighting the ability of the method to study the yeast protein interactome.
The protocol described here includes several critical steps to which the experimenter should pay attention. We recommend to 1) Make sure that the bait DHFR F[1,2] fusion is correct (Figure 1B); this can be achieved by sequencing the construction and measuring proper protein expression using an anti-DHFR F[1,2] or anti-DHFR F[3] antibody; 2) Prior to beginning the screen, it is recommended to verify if any bait of interest exhibits promiscuous interactions in PCA screens. This can be done by performing control screens with baits crossed with the appropriate L-DHFR control or by manually mating the bait with the appropriate L-DHFR control and performing a growth assay in MTX medium. 3) Plates should be poured the day before they are used so that moisture is optimal for cell adherence on the agar surface during the printing process; 4) Source plates should not be used more than four times to transfer enough cells on the destination plate. Increasing the number of copies of the destination plate can be done by successive steps of expansion (e.g. 4 copies -> 16 copies -> 64 copies). Alternatively, cells can be picked at different positions on the lawns or in the colony between different rounds of replication; 5) If several positions are missing after the diploid selection(s), make sure that the source plates were not used too many times in the mating step (steps 4.5 to 4.7); 6) Ensure that the MTX medium contains all essential ingredients at the right concentrations. Indeed, if no growth at all is observed on the MTX medium, it can be either because no interaction is detectable by PCA for the proteins of interest or because the MTX medium was not prepared properly. To ensure that the medium allows growth of strains showing DHFR fragments complementation, a constitutive interaction can be added at empty positions of the collection and used as a positive control such as DHFR-fragments fused to leucine zipper moieties33 (Figure 1C). Parallel tests using the linker-DHFR fragments or the zipper-linker-DHFR fragments will allow to discriminate between conditions that allow all cells to grow (low MTX concentration or bait protein that tend to make false positive interactions, as described below) and conditions that prevent growth of all strains (MTX concentration too high or essential ingredient missing in the medium); 7) Given that PCA is performed through successive rounds of replications from one medium to another, cross-contamination among strains between different plates may occur if, for instance, the pin-tool is not sterilized properly between replication rounds and/or the last water bath (i.e. wet station) in the sterilization procedure is contaminated by colonies of previous replication rounds. Several positions on the arrays are empty and can thus be used as control positions where no growth should be observed to detect cross-contaminations.
Image analysis can be performed using several published softwares (see section 5 of the protocol) or any custom script. In this study, the custom script executes the following steps: 1) The script subtracts pixel values of an empty plate to pixel values of each plate in order to correct for illumination biases. 2) The script converts each background-corrected picture to binary using a pixel value threshold of 10. 3) For each 1,536 positions of each plate, determined by overlaying a rectangle on the edge colonies, the script runs ImageJ “Analyze particles ...” function in a circular selection. The circular selection is set with a radius equal to the interval between two positions minus 10 pixels. 4) The script selects the closest particle from the center of the selection and confirms it as a colony if its location is not more than half the interval between two colonies away from the center of the selection. 5) The script measures pixel values of the selected particle on the background-corrected picture. 6) To further correct any remaining background illumination biases, the script subtracts the mean value of all the pixels from the circular selection that were not part of a particle to pixel values of the colony. The sum of these corrected pixel values, stored in the column “IntDenBackSub” of Supplementary Table 1, are used as a measure of colony size.
A critical step within the analysis part is the choice of the significance threshold. Here, we chose a threshold based on the distribution of the negative L-DHFR F[3] controls, but depending on the objective of the screen, such threshold may be too stringent. Indeed, L-DHFR F[3] controls are overexpressed (strong TEF promoter) such that the complementary fragments may spontaneously complement each other and these are thus not representative of the expression of most proteins. This is highlighted by the fact that the distribution of the L-DHFR F[3] controls is higher than the average of the background growth (Figure 3D). Thus, some interactions having scores below this stringent threshold but that are clearly outside of the background growth distribution can be considered as putative hits that may represent, for instance, transient or weak interactions. These can be further studied and cross-validated if, for instance, the two proteins are not expressed at levels that can allow the spontaneous complementation of the DHFR fragments like the L-DHFR controls. As an alternative, one could set a significance threshold based on the proportion of overlap with reported physical interactors in databases like BioGRID35 in order to maximize the proportion of true positives over false positives. However, unlike the use of the L-DHFR distribution, this alternative may not always be feasible if, for instance, the number of known physical interactors is not sufficiently high. Moreover, the choice of the significance threshold has an impact on the proportion of false positives and false negatives in the final data set. Indeed, like any other PPI detection assay, false positives can result from unspecific interaction of a protein with the DHFR-fusion protein if, for example, the protein is highly abundant as mentioned earlier. This is exemplified by the fact that some preys systematically interact with all bait proteins in PCA screens and, thus, need to be removed from the analysis11 (e.g. Tef2 and Ade17 and Supplementary Table 2). To circumvent this problem, a control PCA screen of the two collections against the appropriate L-DHFR control (F[1,2] or F[3]) to identify baits and preys exhibiting spontaneous DHFR fragments complementation can be performed in the specific conditions of each screen. Moreover, performing a Gene Ontology enrichment analysis can increase the confidence in the data if the function of a given bait is known. On the other hand, DHFR-PCA can give rise to false negatives for several reasons: 1) not all proteins can be fused to the DHFR fragments as these may destabilize the proteins or modify their localization if, for instance, the DHFR fusion to the C-terminus interferes with a localization signal; 2) DHFR reconstitution in some cellular compartments may not produce folate if, for instance, an essential precursor for folate synthesis is not available; 3) C-termini need to be within a distance of 8 nm for DHFR complementation to occur11. Thus, a well-known interaction may not be detected if their C-termini are not close enough in space. This is exemplified here by the fact that a large fraction of Nup82 physical interactions reported in databases, most of which are indirect, were not detected in our assay. Similarly, interactions between membrane proteins for which the C-termini are in trans relative to the membrane will not lead to DHFR fragments complementation and will not be detected11. Limitations 1) and 3) can be circumvented relatively simply by fusing the DHFR fragment to the N-termini of the protein. Doing so may prevent to interfere with a localization signal near the C-termini and may allow to detect an interaction between membrane proteins whose N and C-terminus are in cis relative to the membrane.
Several challenges remain in the study of PINs (reviewed in2,3). The maps of PINs produced so far have largely been described in a single experimental condition for each species and thus offer a single snapshot of how protein networks might be organized. There is therefore a need for the exploration of other experimental conditions to see how PINs may be reorganized in response to environmental changes, specific stimuli, across development or following mutations. These challenges will be overcome by the development of new technologies for interrogating PPIs in real-time, in living cells and by adapting current techniques so that they can be used by a larger community of laboratories. As a quantitative technique that can detect changes in the amount of DHFR complementation complexes27, DHFR-PCA can be adapted to overcome these challenges and has been used to study how PPIs are affected by a DNA damaging agent22, chemical agents25, gene deletions23,26 or in other yeast species and their hybrids33. Exploring these new dimensions will become more and more important to reveal the dynamic of the PIN.