Split Intein-Mediated Protein Ligation for detecting protein-protein interactions and their inhibition

Yao, Zhong; Aboualizadeh, Farzaneh; Kroll, Jason; Akula, Indira; Snider, Jamie; Lyakisheva, Anna; Tang, Priscilla; Kotlyar, Max; Jurisica, Igor; Boxem, Mike; Stagljar, Igor

doi:10.1038/s41467-020-16299-1

Download PDF

Article
Open access
Published: 15 May 2020

Split Intein-Mediated Protein Ligation for detecting protein-protein interactions and their inhibition

Nature Communications volume 11, Article number: 2440 (2020) Cite this article

14k Accesses
24 Citations
26 Altmetric
Metrics details

Subjects

Abstract

Here, to overcome many limitations accompanying current available methods to detect protein-protein interactions (PPIs), we develop a live cell method called Split Intein-Mediated Protein Ligation (SIMPL). In this approach, bait and prey proteins are respectively fused to an intein N-terminal fragment (IN) and C-terminal fragment (IC) derived from a re-engineered split intein GP41-1. The bait/prey binding reconstitutes the intein, which splices the bait and prey peptides into a single intact protein that can be detected by regular protein detection methods such as Western blot analysis and ELISA, serving as readouts of PPIs. The method is robust and can be applied not only in mammalian cell lines but in animal models such as C. elegans. SIMPL demonstrates high sensitivity and specificity, and enables exploration of PPIs in different cellular compartments and tracking of kinetic interactions. Additionally, we establish a SIMPL ELISA platform that enables high-throughput screening of PPIs and their inhibitors.

Bioorthogonal masked acylating agents for proximity-dependent RNA labelling

Article 09 April 2024

Shubhashree Pani, Tian Qiu, … Bryan C. Dickinson

Bridging structural and cell biology with cryo-electron microscopy

Article 03 April 2024

Eva Nogales & Julia Mahamid

Proteome-scale discovery of protein degradation and stabilization effectors

Article 20 March 2024

Juline Poirson, Hanna Cho, … Mikko Taipale

Introduction

Protein–protein interactions (PPIs) compose many fundamental steps in most biological processes¹. Thus, PPI detection and analysis are essential for understanding molecular mechanisms of biological processes, elucidating mechanistic details of disease occurrence and progression, as well as for developing new treatments and diagnostics.

Numerous methods have been developed to detect PPIs^1,2. However, based on the underpinning principles of their design, these methods present bias for certain sets of PPIs and are accompanied by limitations³. For example, stable PPIs are often easily monitored by various methods, but transient and weak PPIs, which play essential regulatory roles, are far more difficult to detect. PPIs occurring in some special cellular locations can also only be examined with specific methods. Additionally, some approaches reconstitute PPIs in model organisms such as yeast⁴, which may not accurately represent native physiological environments, while methods based on affinity purification are usually biased by overrepresentation of abundant proteins and underrepresentation of weak PPIs that are easily lost during purification. Many methods also suffer from low quantifiability or throughput.

In this study, we develop a method for PPI detection called Split-Intein-Mediated Protein Ligation (SIMPL). In this approach, a split intein is used as a sensor for protein interactions. An intein is a protein fragment possessing enzymatic activity which allows it to excise itself from its parental peptide while ligating (via formation of a peptide bond) the flanking protein regions (referred to as the N-terminal extein (EN) and the C-terminal extein (EC)) into a new intact peptide through a process called protein splicing (Supplementary Fig. 1)^5,6. Inteins are usually small or can be reduced to a small domain close to 100 amino acids. Their function does not require any cofactors or energy source and they can typically work across relatively broad environmental conditions. Interestingly, an intein can be split into two parts, either naturally or artificially, without compromising its activity and thereby allowing protein trans-splicing⁷, making such split inteins attractive tools in biotechnological fields⁸. The same features also allowed us to set up the SIMPL system.

Here, we describe the design and implementation of SIMPL, a live cell split-intein-based method for PPI detection that enables in situ analysis of interactions occurring in various cellular compartments as well as their responses to pharmacological challenges such as enzymatic and PPI inhibitors.

Results

Design and facilitation of SIMPL

In our design (Fig. 1a), a bait protein is fused at its C-terminus to a V5 tag and an intein N-terminal fragment (IN). Correspondingly, a prey protein is fused at its N-terminus with a FLAG tag and an intein C-terminal fragment (IC). The bait and prey are co-expressed in selected mammalian cells to investigate their in vivo interaction. The association of bait and prey brings IN and IC into close proximity, allowing them to reconstitute a fully functional intein, which then catalyzes its own excision and the concurrent ligation of the bait and the prey peptides (as well as the V5 and FLAG tags). The resulting spliced protein can be resolved by regular western blot analysis due to its altered mobility, while the presence of the V5 and FLAG tags allows visualization or purification of protein using regular biochemical techniques.

**Fig. 1: Development of the SIMPL assay.**

The GP41-1 split intein, which was identified from environmental metagenomic sequence data⁹, was chosen for use in the SIMPL system due to its small size (88 amino acids long in IN and 37 amino acids long in IC) and because it possesses the most rapid reaction rate among all split inteins examined^7,10,11. Rapamycin-induced heterodimerization of FKBP1A (IC fused) and the FKBP rapamycin-binding (FRB) domain of mTOR¹² (IN fused) was used as a test case to evaluate SIMPL performance in a HEK 293 mammalian cell background. The major obstacle to implementing SIMPL is the intrinsic affinity between IN and IC, which introduces splicing unrelated to bait/prey interaction. We therefore re-engineered the GP41-1 split-intein. GP41-1 was re-split at eight different sites (Fig. 1b) and their behaviors were assessed (Fig. 1c). The intein split at position C25 (numbered from the last C-terminal amino acid of IC, Supplementary Fig. 2a) exhibited the best performance, with no apparent loss of enzyme activity and minimal self-association that is barely detected by western blot. The splicing reaction of C25 occurred with high fidelity, as only parental and spliced proteins are detected (Fig. 1c). This suggests that no N- or C-terminal cleavage occurred, which is a common side reaction of many split inteins^6,13. The identity of the spliced protein was further verified by immunoprecipitation, where the proteins were pulled down by α-FLAG antibody, stringently washed, and probed with α-V5 antibody (or vice versa). In both cases only the spliced protein was detected and no obvious signal was observed in the sample without rapamycin treatment (Supplementary Fig. 2b). The C25 GP41-1 split intein was therefore adopted for use in our SIMPL system. It should be noted that the expression of FRB fused to WT IN, FRB-IN (C37), was hardly detected by western blot analysis, possibly as a consequence of fast degradation due to its severely disordered conformation. Moreover, extra bands appeared in the WT (C37) sample, indicating side cleavage products. Both deleterious effects were significantly reduced or abolished with all re-split inteins, suggesting a performance improvement achieved through resplitting.

To characterize the SIMPL system, we treated HEK 293 cells transiently transfected with FRB/FKBP1A SIMPL constructs with different concentrations of rapamycin (Fig. 1d). The results showed a typical dose–response relationship with a dose range similar to those measured by BRET-based methods¹⁴. A time course rapamycin treatment experiment also demonstrated a fast response, with interaction observed in as little as 2 min (the smallest observation interval used) and persistently accumulating over time (Fig. 1e). Similar kinetics were also observed in HeLa cells (Supplementary Fig. 2c) and PC9 lung adenocarcinoma cells (Supplementary Fig. 2d), suggesting that SIMPL can be applied to different mammalian cell lines. It should be noted that this time series signal profile is distinct from that observed with other methods: experiments performed using NanoBRET observed a rapidly reached equilibrium between association and dissociation¹⁴. This is derived from the differences in what various methods measure. Methods such as NanoBRET usually detect PPI complexes themselves. In contrast, SIMPL solely measures the event of protein association but not its dissociation or the steady-state complex.

We further assessed SIMPL in isogenic stable cells to examine potential problems derived from transient transfection such as uneven expression in various cells and difficulty in manipulating expression level. The stable cell line was created by incorporating both FRB-IN and IC-FKBP1A into the genome of host Flp-In T-Rex HEK 293 cells through Flp recombinase-mediated integration. Cells with different expression levels of both FRB and FKBP1A, induced by incubation with varied doses of tetracycline, were treated with rapamycin (Fig. 1f). Interaction-induced splicing and dose–responsive expression of FRB and FKBP1A was observed in all samples, even at the lowest dose of tetracycline (30 ng/ml) employed. Importantly, increasing protein expression was not accompanied by a significant increase in background signal as judged in samples without rapamycin treatment. These observations demonstrate that the SIMPL reaction is efficient, specific, and highly sensitive, and can work properly across a wide range of bait and prey expression levels.

Alternative SIMPL formats to extend its detection capability

In the above prototypic SIMPL design, a bait molecule is fused at its C-terminus to the IN fragment (IN format, or bait-V5-IN) and a prey is fused at its N-terminus to the IC fragment (IC format, or IC-FLAG-prey). While functional in many cases, this arrangement limits the overall detection capability of SIMPL because in some instances the two tags in this format may be spatially inaccessible to each other. Additionally, the function of some proteins may be disrupted by the presence of tags on specific termini, necessitating a different strategy. We thus designed two alternative intein construct arrangements (Fig. 2a). In the C-terminal IC (CIC or prey-IC-FLAG) format IC is fused to the C-terminus of a prey while keeping the FLAG tag downstream. Its interaction with an IN bait leads to splicing between the bait (as well as V5 tag) and the FLAG tag, which produces a bait-V5-FLAG peptide. Similarly, the NIN (V5-IN-bait) format tags a bait N-terminally with the IN fragment and an upstream V5 peptide. Its interaction with an IC prey produces a V5-FLAG-prey peptide. Since both approaches lead to tag transfer, they still provide a readout of interaction that is compatible with western blot or IP-coupled western blot analysis. However, the interaction between an NIN bait and a CIC prey will produce a spliced small peptide V5-FLAG beyond the detection of western blot analysis. To address this, we created a CIC-GFP construct (prey-IC-FLAG-GFP) which can react with NIN bait to produce V5-FLAG-GFP peptide that allows detection by western blot or other analyses. Assessment of all four combinations of different SIMPL arrangements using the FRB/FKBP1A pair confirmed their feasibility, with rapamycin-induced bands corresponding to the molecular weight of appropriately spliced protein detected via western blot analysis in all cases (Fig. 2b, Supplementary Table 1). It should be noted that a basal splicing signal appeared in the sample of NIN/CIC-GFP combination without rapamycin treatment. This might be derived from an affinity change caused by different tagging or high-level expression of the proteins. However, the corresponding rapamycin-treated sample shows a dramatically increased signal (more than eight fold by density), making the states easily distinguishable from one other when proper controls and quantification are used. Thus, all four combinations are suitable for use in PPI detection in SIMPL.

**Fig. 2: Design of alternative formats of SIMPL to expand its capability.**

Enzyme-linked immunosorbent assay platform of SIMPL assay and its unbiased evaluation

While use of SIMPL with a western blot readout is applicable to detailed PPI analysis, it is limited to low-throughput analyses and is not strongly quantifiable. We therefore developed an alternative, enzyme-linked immunosorbent assay (ELISA)-coupled SIMPL platform for high-throughput, quantifiable measurement of PPIs. For this purpose, a hemagglutinin (HA) tag was introduced into the bait construct in tandem with V5. This allows for monitoring of protein splicing using an ELISA format, with protein capture performed using α-FLAG antibody and detection performed using α-HA antibody coupled to horseradish peroxidase (HRP) (Fig. 3a). The SIMPL signal can be normalized to bait expression, which can be similarly measured by ELISA using immobilization with α-V5 antibody followed by detection with HRP-conjugated α-HA antibody (Fig. 3b). Performance of the ELISA platform was tested by monitoring the dose–response of rapamycin-induced FRB/FKBP1A interaction in all four combinations: IN/IC, IN/CIC, NIN/IC, and NIN/CIC-GFP (Fig. 3c). The results of all four combinations showed an expected dose–response relationship consistent with the western analysis (Fig. 2b), demonstrating the feasibility of SIMPL ELISA. Specifically, the IN/IC profiles obtained from both ELISA analysis and quantified western analysis (Fig. 1d) presented notable similarity. Although two combinations, NIN/IC and NIN/CIC-GFP, showed relatively elevated basal splicing levels, these background signals were not high enough to interfere with interpretation of the spliced signal induced by rapamycin, with a robust 1.5- and 4-fold increase observed in the NIN/IC and NIN/CIC-GFP formats in ELISA analysis, respectively, after rapamycin treatment. In addition, expression of bait alone, either FRB (IN) or FRB (NIN), did not show any response to rapamycin treatment, further demonstrating the specificity of the assay.

**Fig. 3: Setting up the SIMPL ELISA platform and its evaluation with reference PPIs.**

We next evaluated the SIMPL system using a benchmarking approach with unbiased PPI reference sets, which has been widely accepted for assessing the overall performance of a PPI method. We employed a positive reference set (PRS) which contained 88 available positive PPIs derived from the previously well-established human PRS (hPRS)¹⁵, including different types of PPIs and covering those occurring in various subcellular locations (Supplementary Table 2). Our random reference set (RRS) contained 88 protein pairs with baits and preys selected from the PRS but used in combinations determined computationally to have low probability of interaction (Supplementary Table 2). The reference sets were evaluated with the ELISA platform in two formats, bait(IN)/prey(IC) and bait(IN)/prey(CIC) (Supplementary Table 3). The expression of baits in the same samples was also tested with ELISA (Supplementary Fig. 3a) and each SIMPL signal was thereby normalized to its corresponding bait expression (Supplementary Fig. 3b). Receiver operating characteristic (ROC) analyses of the assays demonstrated exceptional sensitivity with AUC values of 0.806 and 0.867 for IN/IC and IN/CIC formats, respectively (Fig. 3d). Accordingly, 41% (IN/IC) or 56% (IN/CIC) of PPIs can be detected by SIMPL without compromising assay specificity and maintaining a false-positive rate of ~5% (Fig. 3e), determined with threshold values obtained from ROC analyses. We further compared the ELISA readout with western blot analysis by selecting 10 PPIs with high ELISA signals (above threshold) and 10 with low ELISA signals (below threshold) either in IN/IC or in IN/CIC format and re-testing them by western (Supplementary Fig. 3c, d). The results were highly consistent between the two methods; nine PPIs in the high IC group and all PPIs in high CIC group presented clearly observable splicing bands. In contrast, only one PPI in each low signal group presented a strong splicing signal relative to the levels observed in the high group bands. Comparison with the results from other PPI methods in the literature^16,17,18 shows improvement of detection demonstrated with broader coverage (Fig. 3f). Interestingly, many PPIs can be detected by SIMPL using both the IN/IC and IN/CIC formats. Nevertheless, there are differences between the two orientations, presumably due to the spatial geometry of the interacting molecules or due to the disruption of the functionalities of the tagged termini. In general, the CIC format exhibits better performance in the tests described here (Fig. 3d, Supplementary Fig. 3e). For example, prey proteins containing signal peptides showed better detectability in CIC format (Supplementary Fig. 3e) since tagging on N termini blocks their recognition by signal recognition particle and thereby affects their correct sorting to the membrane.

Further characterization of SIMPL with physiological PPIs

We next used SIMPL to explore physiological PPIs and chose PPIs in the EGFR–RAS–ERK1/2 axis, an important signaling pathway¹⁹. Activated EGFR undergoes autophosphorylation and recruits scaffold proteins such as SHC1 to relay signal to downstream machinery²⁰. At the RAS level, activated RAS (KRAS in this study) binds and directly activates RAF kinases²¹ (RAF1 in this study). When EGFR-IN and IC-SHC1 were co-expressed in HEK 293 cells, their interaction was captured as a spliced band above EGFR recognizable by both α-FLAG and α-V5 antibodies (Fig. 4a). The interaction was also effectively detected using SHC1-CIC construct (Supplementary Fig. 4a). The interaction depends on EGFR activity as the constitutively active EGFR mutant (L858R) enhanced the signal while the kinase dead mutant (D855A)^22,23 abolished the interaction (Fig. 4a). To detect KRAS/RAF1 interaction, we chose the IC-KRAS construct to avoid the disturbance of its C-terminal lipidation. Assay with RAF1-IN detected the specific interaction (Fig. 4b) as wild-type KRAS and its constitutively active mutants (G12D and Q61H) displayed splicing signals, while no obvious signal was observed with the dominant negative KRAS mutant (S17N)²⁴. Assay with the NIN-RAF1 construct exhibited a more marked splicing signal than RAF1-IN (more than sixfold by density, Supplementary Fig. 4b). It should be noted that the domain responsible for RAS binding is located at the N-terminus of RAF1 and hence the N-terminus is physically closer to RAS. We therefore speculate that the signal enhancement is caused by RAF1 N-terminal tagging, which improved accessibility of reactive termini. Thus, these two classical PPIs involved in normal and oncogenic signaling were successfully recapitulated by SIMPL.

**Fig. 4: Detection of physiological PPIs and their inhibition with SIMPL.**

As the study of rapamycin-induced FRB/FKBP1A interaction demonstrated the potential of SIMPL to follow interaction kinetics (Fig. 1e, Supplementary Fig. 2c, d), we tested whether SIMPL can also track kinetics of physiological PPIs using the example of EGF-activated SHC1 recruitment to EGFR. We found that interaction (splicing) between EGFR (IN) and SHC1 (IC) had already occurred without EGF treatment when they were transiently overexpressed in cells (Fig. 4a), and the signal was only slightly enhanced after EGF stimulation (Supplementary Fig. 4c) as the density ratio of the spliced bands between non-treated and EGF-stimulated (5 min) samples is 1:1.7. It should be noted that overexpression of EGFR induces ligand-independent autoactivation and subsequent recruitment of SHC1 (ref. ²⁵). Unlike phosphorylation and PPI, splicing is irreversible and therefore led to accumulation of the spliced protein. This accumulated spliced protein likely masked the signal induced by EGF stimulation. The key to overcoming this is to reduce the level and duration of bait and prey expression. Thus, we created a stable cell line derived from Flp-In T-REx HEK 293 cells by incorporating both EGFR (IN) and SHC1 (IC) into the genome through Flp recombinase-mediated integration. This allowed control of the amplitude and temporal induction of their expression by tetracycline. Notably, in cells treated for 6 h with tetracycline in starvation medium (0.1% fetal calf serum) the splicing signal of EGFR/SHC1 interaction was markedly reduced, but restored upon EGF stimulation for 2 min (Fig. 4c), supporting the feasibility of using SIMPL to follow physiological PPIs. It should be noted that, due to the leakage of the tetracycline repressor system, low levels of EGFR (IN) and SHC1 (IC) were observed in cells without tetracycline treatment. EGF-stimulated splicing was also observed under this condition, consistent with the strong sensitivity of SIMPL assay.

As most PPI methods are not well suited for detection of weak or transient PPIs, we wanted to test whether SIMPL is capable of following these types of interactions. We selected protein kinases as our test case since their association with substrates, similar to common enzyme/substrate interactions, is usually characterized as transient and weak²⁶. Thus, IN-fused MAPK1 (ERK2), MAPK8 (JNK1), MAPK14 (p38α MAPK), MAPK7 (ERK5), AKT1, and PRKCA (PKCα) were examined with several well documented substrates in both IC and CIC formats. ELISA assay demonstrated that more than 50% of these PPIs could be detected by SIMPL, in one or both formats (Fig. 4d). MAPK members presented relatively strong interactions, which may be enhanced by docking interaction outside of their active sites²⁷. We examined whether SIMPL could capture the kinetic process of kinase/substrate interactions. Indeed, we observed an enhanced MAPK1/ELK1 interaction after MAPK1 activation induced by tetradecanoylphorbol acetate (TPA) stimulation (Supplementary Fig. 4d). However, no obvious increase was observed in many cases of kinase activation (Supplementary Fig. 4e–g). We speculate that in these instances the accumulation of the spliced proteins from the basal state may have masked the stimulation response due to the irreversibility of the splicing reaction and might be avoided by reducing basal bait/prey expression through the use of the stable cell line approach mentioned above for EGFR/SHC1, an area which deserves further investigation.

The evaluation with the reference PPI set suggests SIMPL is capable of detecting PPIs in various cellular compartments as the PRS covers PPIs occurring in different locations such as nucleus, cytoplasm, plasma membrane, and extracellular space (Supplementary Table 2). We further tested this by examining mitochondrial PPIs with SIMPL as mitochondria are special organelles with distinct features and their PPIs are often difficult to study. We selected several well-studied mitochondrial PPIs for this purpose (Supplementary Table 4), including proteins involved in oxidative phosphorylation²⁸, transport²⁹, cristea organization³⁰, and metabolism³¹. Baits were prepared using the IN format to avoid interference of transit peptides usually at N-termini of mitochondrial proteins. The corresponding preys were constructed in either the IC or CIC configuration (or both) to reduce the chance of steric interference preventing their association with IN or to prevent incorrect sorting of the prey proteins. Out of 10 PPIs examined, 8 (TIMM50/TIMM23, PDHA1/PDHB, CHCHD6/CHCHD3, NDUFV1/NDUFV3, SDHA/SDHB, UQCRC2/UQCRC2, ATP5MC1/ATP5MC1, and ETFA/ETFB) were successfully detected (Fig. 4e), including proteins localized to different sub-mitochondrial compartments (matrix, inner membrane and intermembrane space). We tested two additional controls for PDHA1/PDHB interaction to exclude the possibility that splicing occurred in cell lysates during sample processing (Fig. 4f). In the first control, the mitochondrial targeting sequence of PDHA1 was replaced with the nuclear localization signal of MYC. This modification prevents the resultant NLS-PDHA1 from being sorted to the mitochondria and, consistent with this, its interaction with PDHB was therefore not observed. In the second control, PDHA1 and PDHB were separately expressed in different cells and the two cell lysates were mixed and assayed by ELISA. Once again, no interaction between PDHA1 and PDHB was detected. Together, these results indicate that a significant amount of PDHA1/PDHB SIMPL splicing does not occur if both proteins are not properly targeted to the mitochondrion, supporting the broad applicability of SIMPL for monitoring interactions with diverse subcellular localizations.

Detecting PPIs in C. elegans with SIMPL

We next investigated the feasibility of using the SIMPL system in a multicellular animal using the nematode Caenorhabditis elegans as a model. We selected a C. elegans PRS of 27 PPI pairs from previously identified literature confirmed interactions³² and from interactions used previously to evaluate binary PPI mapping approaches³³ (Supplementary Table 5). We also assembled a C. elegans RRS by randomly combining protein pairs from the PRS, excluding known interactors. Full-length ORFs of the corresponding genes were PCR amplified and cloned into vectors containing split-intein tags optimized for expression in C. elegans, but otherwise identical to the ELISA compatible split-intein fragments used above.

Proteins were expressed under control of the general rps-0 ribosomal promoter. Transgenic animals were generated by microinjection, and both IC and CIC configurations were injected for each prey protein. To enable accurate quantification of splicing by ELISA, we injected a 4× higher concentration of prey plasmid than bait plasmid to ensure that splicing of the bait protein is not limited by the availability of the prey protein. All transgenic lines were first tested for expression of both bait and prey protein by western blotting. In all, we recovered 10 PRS pair-expressing lines and 13 RRS pair-expressing lines, representing 7 and 9 unique protein pairs, respectively (Fig. 5a). We first analyzed each line for splicing by western blot (Supplementary Fig. 5). We observed visible splicing for 7/10 PRS pairs and 5/13 RRS pairs; however, levels of splicing for the RRS pairs were lower than for the PRS pairs. We then quantified levels of splicing using ELISA as above, analyzing two independent protein lysates for each transgenic line. Using a sliding cutoff level of spliced bait/total bait signal to assign positive interactions, we observed clear separation between PRS and RRS protein pairs in both replicates (Fig. 5b). At a cutoff level that optimizes the fraction of true positives vs. false positives detected in both replicates, 8/10 PRS pairs tested positive in both replicates, while the remaining 2 pairs tested positive in one replicate (Fig. 5c). In contrast, none of the RRS pairs tested positive in both replicates, though six pairs tested positive in a single replicate. Collapsing IC/CIC orientations, 7/7 PRS protein pairs tested positive, and 1/9 RRS pairs tested positive. Overall, these results indicate that the SIMPL system is functional in C. elegans and suggests its universal nature could allow it to be exploited in many other systems.

**Fig. 5: Detecting PPIs in *C. elegans* with SIMPL.**

SIMPL as a drug screening platform

Finally, we investigated whether SIMPL can serve as a drug screening tool, in particular as an assay that could detect enzymatic- as well as PPI inhibitors. Since protein splicing is an irreversible process, inhibitors have to be administered before bait/prey expression (Fig. 6a). Using the EGFR/Shc1 interaction as an example, we observed a decrease of SIMPL signal upon the administration of AG1478 (ref. ³⁴), an EGFR tyrosine kinase inhibitor (TKI) which suppresses EGFR autophosphorylation and thereby reduces EGFR/Shc1 interaction (Fig. 6b). In this case, the interaction between Shc1 and EGFR occurs downstream to EGFR activation and serves as an indirect readout of EGFR activity. We then tested whether SIMPL can also monitor PPI inhibition caused by a direct PPI inhibitor using venetoclax, an FDA approved drug targeting the BAX/BCL2 interaction³⁵, as an example. We first examined the interactions of BAX/BCL2 (and BAX/BCL2L1 control) in three SIMPL formats, IN/IC, IN/CIC, and NIN/IC (Fig. 6c–f). Note that for the NIN-BAX/IC-BCL2 combination, immunoprecipitation was performed to resolve spliced protein product from the similarly-sized parental product (Fig. 6e). Based on these results the NIN-IC pairing displayed the highest signal (Fig. 6f). Using this combination in SIMPL with an ELISA readout we observed potent inhibition of the BAX/BCL2 interaction in the presence of venetoclax with an IC₅₀ of 9.1 nM (very similar to other cell-based assay results³⁶) but not the unrelated control TKI osimertinib (Fig. 6g, red and blue). The effect of venetoclax on BCL2L1 (BCL-XL) was much less potent as the inhibition of the BAX/BCL2L1 PPI was observed only at high venetoclax concentration (Fig. 6g, green), consistent with previous reports³⁶. Overall, these results clearly demonstrate the potential for using SIMPL as a highly sensitive small-molecule screening tool.

**Fig. 6: SIMPL for enzymatic/PPI inhibitor identification.**

Discussion

There is no universal method that works for every PPI and all interaction proteomics methods exhibit preferences, leading to low overlap of PPI coverage across many approaches^3,37. We developed SIMPL to expand detection coverage. PRS derived from hsPRS-v1 (ref. ¹⁵) is used to benchmark the suitability of SIMPL and to unbiasedly compare it to seven different PPI assays: LuTHy¹⁷, LUMIER³⁸, MAPPIT³⁹, KISS¹⁶, Yeast Two-Hybrid (YTH)⁴⁰, PCA⁴¹, and wNAPPA⁴². Our data demonstrate the improvement of PPI detection in terms of sensitivity, coverage, and the objective parameter AUC. We further tested SIMPL in C. elegans and obtained similar results. Therefore, SIMPL is a sensitive method for PPI detection with a low rate of false positives (≤5%) and suitability for use in different in vivo models.

Many features of the split-intein sensor make SIMPL a unique system. Since inteins do not exist in mammals it is unlikely that they would interfere with the function of mammalian cells. Indeed, we have not observed any cellular changes when inteins are orthogonally expressed in mammalian cells. The small size of GP41-1 split intein used in SIMPL also reduces its potential for involvement in nonspecific interactions. Additionally, since GP41-1 can work under relatively broad physiological conditions, it allows detection in different subcellular locations. Unlike many PPI methods, extra cofactors are also not needed in the SIMPL assay.

The kinetic features of split inteins should be considered. It has been shown that separated split intein is partly folded or completely disordered. The recognition between IN and IC initiates the association process, causes a disorder-to-order transition, and then triggers splicing^43,44. The C25 re-split GP41-1 developed in this study presumably proceeds through a similar kinetic route except that the association is mainly driven by bait/prey interaction, not by the recognition between IN and IC, due to the shortening of the IC fragment. Indeed, most PCA-based PPI sensor fragments are in unfolded conformations before complementation⁴⁵. In contrast to GP41-1, most of them, including BiFC, follow slow complementation kinetics which impairs their ability to detect fast interactions. The physical mechanism of this ultrafast kinetics of GP41-1 merits full investigation. It should be noted that luciferase-based PCA and some other PPI methods such as FRET, BRET³, and the recently developed SPARK (Specific Protein Association tool giving transcriptional Readout with rapid Kinetics)⁴⁶ are also capable of tracking fast PPIs, and, alongside SIMPL, provide a robust set of complementary tools for studying these PPIs and their kinetics in vivo.

The most striking feature of SIMPL is its irreversibility. Complementation of many PCA sensors is also irreversible but due to energetic trap. The covalent splicing in SIMPL makes it useful even with harsh experimental conditions, helping avoid the loss of specific interactions (and the gain of nonspecific interactions) during processing steps, which are common problems for many affinity-based methods. It should be noted that irreversible sensors actually record the association event of complex formation, not the complex itself. The accumulation of “unbreakable” signal may also substantially enhance the sensitivity. This feature, together with the ultrafast activity of GP41-1, makes SIMPL well suited to following PPI kinetics. However, kinetic studies with SIMPL need to be carefully designed since the accumulation of basal interaction signal can mask the signal of nascent complex formation if the basal PPI is relatively high. In this study, we used inducible expression of stably incorporated genes to help reduce basal interaction signal.

Our study also demonstrates the feasibility of SIMPL as a platform to characterize enzymatic and PPI inhibitors. Inhibitor efficiency measured with SIMPL was very close to results obtained with other methods, indicating that SIMPL can serve as an attractive, live cell-based assay for drug screening. Additionally, SIMPL may help overcome the challenges associated with identifying compounds that specifically disrupt or enhance PPIs which, though promising candidates for therapeutic intervention, have been difficult to target to date.

Notably, split inteins have previously been used for PPI detection, though in a more complex format, wherein the two intein moieties are respectively fused to components of split reporters such as fluorescent protein or luciferase⁸, and the readout is production of functional spliced reporter molecules. Importantly, the split inteins used in the aforementioned approach have a tendency to self-associate⁷, a process that is further aggravated by the affinity between the halves of the split reporter molecule, potentially resulting in a significant increase in nonspecific PPI signal. For these reasons, the method has not been widely used in research. In contrast, we have developed a straightforward split-intein strategy which allows protein splicing between bait and prey, or small tags, minimizing introduction of extra components. Importantly, we have also re-engineered our split-intein sensor to overcome the natural affinity between the intein components. Both factors dramatically decrease any nonspecific interaction derived from the detection system.

As with any other PPI method, SIMPL does have certain limitations. As heterologous expression of bait and prey proteins is required, SIMPL cannot measure endogenous PPIs unless the tags are integrated into the target genes by gene editing. Additionally, SIMPL is not able to follow protein dissociation due to its irreversibility. Despite these limitations, however, the data presented here demonstrate several attractive assets of SIMPL: improved high sensitivity without loss of specificity, broad applicability to PPIs in various cellular compartments or in different cell types, the ability to detect weak and transient PPIs, the potential to follow PPI kinetics, quantifiability, compatibility with high-throughput screening, and no requirement for special equipment or expertise. We therefore envision that SIMPL will have broad applications in biomedical research as well as the pharmaceutical industry.

Methods

Molecular cloning and library preparation

The plasmids containing GP41-1 split-intein cDNA, pCAG-Co-InCreN and pCAG-Co-InCreC, were obtained from Addgene. SIMPL bait and prey vectors are generated by integrating DNA pieces of GP41-1 split-intein fragments, linkers, and tags, as well as Gateway cloning cassette, into pCMV5 vector backbone by Gibson assembly (New England BioLabs). Plasmids for FlpIn stable cloning were created similarly into pCDNA5/FRT/TO vector with both bait and prey included by Gibson assembly. Most cDNAs were originally obtained from human ORFeome collection or from the Openfreezer collection at Lunenfeld-Tanenbaum Research Institute⁴⁷. Those not in entry clone vectors were cloned into pDONR223 by PCR and Gateway BP reactions (Life Technologies). Different cDNA fragments were then cloned into SIMPL vectors by Gateway LR reactions (Life Technologies). Site-directed mutagenesis was generated by PCR using KAPA HiFi DNA polymerase (KAPA Biosystems). The plasmids created in this study are available from the corresponding author upon reasonable request.

Cell culture and treatment

HEK 293, HEK 293 Flp-In T-Rex, and HeLa cells were grown in DMEM supplemented with 10% fetal calf serum (Life Technologies). PC9 cells were grown in RPMI 1640 medium supplemented with 10% fetal calf serum. For ELISA assay, cells were seeded in 96-well (Sarstedt AG & Co) or 384-well plates (Greiner Bio-One) with 15,000 (96 well) or 5000 (384 well) cells per well. Cells were transfected with various plasmids with polyethylenimine (PEI) Max (Polysciences)⁴⁸. Expression in HEK 293 Flp-In T-Rex cells was induced by treating the cells with tetracycline (1 µg/ml) for 6–16 h. For experiments to study signaling pathway activation, the cells were starved with 0.1% fetal calf serum as well as treated with tetracycline for 6 h before stimulation with EGF (Sigma-Aldrich), tetradecanoylphorbol acetate (TPA) (Sigma-Aldrich), or anisomycin (Sigma-Aldrich). Stable cell lines were created according to the manual of Flp-In T-REx (Invitrogen). Briefly, plasmid containing both bait and prey DNA and pOG44 plasmid (1:10 ratio) were cotransfected into HEK 293 Flp-In T-Rex cells. After 3 days, the cells underwent puromycin selection. Single colonies were selected and the expression of bait and prey were verified by western blot analysis.

Western blot analysis and immunoprecipitation

Cells were lysed in buffer H (Triton X-100 1%, β-glycerophosphate pH 7.3 50 mM, EGTA 1.5 mM, EDTA 1 mM, orthovanadate 0.1 mM, DTT 1 mM supplemented with protease inhibitors (Roche)). After centrifugation at 15,000 r.p.m. for 10 min, the supernatants were mixed with Laemmli sample buffer, boiled at 95 °C for 3–5 min, and subjected to western blot analysis. For immunoprecipitations, supernatants (0.3 ml) were incubated with antibodies at 4 °C with rotation for 1 h, followed by another hour of incubation with protein G sepharose beads (GE Healthcare). Beads were washed twice with LiCl (0.5 M in Tris pH 8.0 0.1 mM) and twice with lysis buffer, boiled with Laemmli sample buffer, and then were subjected to western blot analysis. Antibodies used for western blot analysis and immunoprecipitations were: α-FLAG antibody purchased from Sigma-Aldrich Co. (F1804) with 1:10,000 dilution and α-V5 antibody from Cell Signaling Technology (#13202) with 1:10,000 dilution. Each of the above antibodies was diluted according to provider’s protocol.

ELISA

HEK 293 cells were grown in 96- well or 384-well plates and were transfected with PEI as aforementioned. The cells in each well were lysed in 120 µl (96 well) or 80 µl (384 well) TNE buffer (Tris pH 7.5 20 mM, NaCl 150 mM, EDTA 2 mM and Triton X-100 0.5% supplemented with protease inhibitors). Aliquots of lysates (20 µl) were incubated for 3 h at 4 °C in a well of a 384 well Lumitrac plate (Greiner Bio-One) that was coated with α-FLAG antibody (20 µl/well with 1:100 dilution) and blocked with BSA. After three times thorough wash with phosphate buffer saline supplemented with 0.05% Tween 20 (PBST), the plate was incubated with HRP-conjugated α-HA antibody (GeneTex GTX115044, 1:5000 dilution) for 1 h at room temperature. The plate was washed three times with PBST followed by chemiluminescence reading using SuperSignal ELISA Pico substrate (ThermoFisher).

Selection of RRS pairs

All bait-prey pairs (75 baits × 78 preys) were considered for the RRS, and 88 were selected that had the lowest chances of interaction, using the following criteria: (1) absence from the PRS; (2) absence from the Integrated Interactions Database ver. 2018-11 (ref. ⁴⁹), thereby ensuring that the pairs had not been detected in experimental studies, predicted based on orthology, or predicted by five computational algorithms; (3) lowest probabilities of interaction according the FpClass PPI prediction algorithm⁵⁰; and (4) maximal coverage of candidate baits and preys.

C. elegans SIMPL vectors and cloning

To facilitate assembly of the expression plasmids, we used a SapI-based cloning strategy. We generated a series of donor vectors based on the kanamycin-resistant cloning vector pHSG298 (Takara Bio), in which the insert is flanked with SapI-sites. Digestion with SapI yields overhangs that enable assembly of promoter, ORF, split-intein, and UTR into a destination vector (pMLS257 Addgene #73716) in a single ligation reaction. The following plasmids were generated: (i) donor plasmids containing IN (pJRK244), IC (pJRK036), and CIC (pJRK152) split-intein donor sequences. Split-intein amino-acid sequences are identical to the mammalian ELISA compatible split-intein constructs, but are codon optimized for C. elegans and contain an artificial intron. (ii) Two rps-0 promoter donor plasmids, pJRK001 for assembly with IC and IN, and pJRK151 for assembly with CIC. (iii) Three unc-54 3′-UTR plasmids: pJRK150 for assembly with IC, pJRK153 for assembly with CIC, and pJRK002 for assembly with IN. ORFs were amplified by PCR from a mixed-stage cDNA library and cloned blunt-ended into vector pHSG298 digested with Eco53kI. Plasmid sequences available upon request. Plasmids used for injection were purified using the PureLink HQ Mini Plasmid DNA Purification Kit (ThermoFisher) using the extra wash step and buffer recommended for endA+ strains.

C. elegans strain and culture conditions

C. elegans strains were cultured under standard conditions⁵¹. Only hermaphrodites were used and all experiments were performed with animals grown at 20 °C on nematode growth medium agar plates seeded with E. coli OP50 bacteria.

Extrachromosomal strain generation

Young adult N2 animals were injected with 20 ng/µl of the prey IC/CIC SIMPL plasmid, 5 ng/µl of the bait IN SIMPL plasmid, 20 ng/µl of a plasmid conferring a dominant Rol phenotype and Hygromycin B resistance (pDD382 Addgene #91830), and 55 ng/µl lambda DNA (ThermoScientific SM0191). Four hermaphrodites were injected for each protein pair and placed on individual plates. After 2–3 days, Hygromycin B (250 µg/ml) was added to the plates to select for transgenic lines. From each plate a single F2 Rol animal was picked to establish up to four transgenic strains per protein pair, and each was tested for expression of the SIMPL constructs.

C. elegans lysis and ELISA

Mixed-stage animals grown under Hygromycin B (250 µg/ml) selection were washed off with M9 buffer (0.22 M KH₂PO₄, 0.42 M Na₂HPO₄, 0.85 M NaCl, 0.001 M MgSO₄), and washed two more times with M9 buffer. Samples were then pelleted and resuspended in 100–400 µl of Lysis Buffer (25 mM Tris HCl pH 7.5, 150 mM NaCl,1 mM EDTA, 0.5% Igepal 630, and 1 tablet/50 ml complete protease inhibitor cocktail (Sigma-Aldrich)). After flash freezing in liquid nitrogen and thawing, samples were sonicated with a Diagenode BioRupter Plus, 5 min high setting: 30 s on/30 s off in a 4 °C water bath. The lysates were then spun at max speed in a tabletop centrifuge at 4 °C for 15 min to clear cellular debris. ELISA was performed as above, but the SuperSignal ELISA pico chemiluminescent substrate was used undiluted (ThermoScientific).

Statistics

Two-tailed Student’s t-test with n = 3 was used to examine the significance of kinase/substrate and mitochondrial PPIs.

Reporting summary

Further information on research design is available in the Nature Research Reporting Summary linked to this article.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary Information files). Source data for the figures presented in the main manuscript and the Supplementary Information are available in the Source Data file. All other relevant data are available from the authors upon reasonable request.

References

Yao, Z., Petschnigg, J., Ketteler, R. & Stagljar, I. Application guide for omics approaches to cell signaling. Nat. Chem. Biol. 11, 387–397 (2015).
Article CAS PubMed Google Scholar
Petschnigg, J., Snider, J. & Stagljar, I. Interactive proteomics research technologies: recent applications and advances. Curr. Opin. Biotechnol. 22, 50–58 (2011).
Article CAS PubMed Google Scholar
Snider, J. et al. Fundamentals of protein interaction network mapping. Mol. Syst. Biol. 11, 848–848 (2015).
Article PubMed PubMed Central CAS Google Scholar
Suter, B., Kittanakom, S. & Stagljar, I. Two-hybrid technologies in proteomics research. Curr. Opin. Biotechnol. 19, 316–323 (2008).
Article CAS PubMed Google Scholar
Gogarten, J. P., Senejani, A. G., Zhaxybayeva, O., Olendzenski, L. & Hilario, E. Inteins: structure, function, and evolution. Annu. Rev. Microbiol. 56, 263–287 (2002).
Article CAS PubMed Google Scholar
Shah, N. H. & Muir, T. W. Inteins: nature’s gift to protein chemists. Chem. Sci. 5, 446–461 (2014).
Article CAS PubMed Google Scholar
Aranko, A. S., Wlodawer, A. & Iwaï, H. Nature’s recipe for splitting inteins. Protein Eng. Des. Sel. 27, 263–271 (2014).
Article CAS PubMed PubMed Central Google Scholar
Wood, D. W. & Camarero, J. A. Intein applications: from protein purification and labeling to metabolic control methods. J. Biol. Chem. 289, 14512–14519 (2014).
Article CAS PubMed PubMed Central Google Scholar
Dassa, B., London, N., Stoddard, B. L., Schueler-furman, O. & Pietrokovski, S. Fractured genes: a novel genomic arrangement involving new split inteins and a new homing endonuclease family. Nucleic Acids Res. 37, 2560–2573 (2009).
Article CAS PubMed PubMed Central Google Scholar
Carvajal-Vallejos, P., Pallisse, Roser, Mootz, H. D. & Schmidt, S. R. Unprecedented rates and efficiencies revealed for new natural split inteins from metagenomic sources. J. Biol. Chem. 287, 28686–28696 (2012).
Article CAS PubMed PubMed Central Google Scholar
Beyer, H. M., Mikula, K. M., Li, M., Wlodawer, A. & Iwai, H. The crystal structure of the naturally split gp41-1 intein guides the engineering of orthogonal split inteins from a cis-splicing intein. FEBS J (in press) https://doi.org/10.1111/febs.15113 (2019).
Choi, J., Chen, J., Schreiber, S. L. & Clardy, J. Structure of the FKBP12-Rapamycin complex interacting with the binding domain of human FRAP. Science 273, 239–242 (1996).
Article ADS CAS PubMed Google Scholar
Aranko, aS. et al. Structure-based engineering and comparison of novel split inteins for protein ligation. Mol. Biosyst. 10, 1023–1034 (2014).
Article CAS PubMed PubMed Central Google Scholar
Machleidt, T. et al. NanoBRET—a novel BRET platform for the analysis of protein-protein interactions. ACS Chem. Biol. 10, 1797–1804 (2015).
Article CAS PubMed Google Scholar
Venkatesan, K. et al. An empirical framework for binary interactome mapping. Nat. Methods 6, 83–90 (2009).
Article CAS PubMed Google Scholar
Lievens, S. et al. Kinase Substrate Sensor (KISS), a mammalian in situ protein interaction sensor. Mol. Cell. Proteomics 13, 3332–3342 (2014).
Article CAS PubMed PubMed Central Google Scholar
Trepte, P. et al. LuTHy: a double‐readout bioluminescence‐based two‐hybrid technology for quantitative mapping of protein–protein interactions in mammalian cells. Mol. Syst. Biol. 14, e8071 (2018).
Article PubMed PubMed Central CAS Google Scholar
Braun, P. et al. An experimentally derived confidence score for binary protein-protein interactions. Nat. Methods 6, 91–97 (2009).
Article CAS PubMed Google Scholar
Lemmon, M. A. & Schlessinger, J. Cell signaling by receptor tyrosine kinases. Cell 141, 1117–1134 (2010).
Article CAS PubMed PubMed Central Google Scholar
Zheng, Y. et al. Temporal regulation of EGF signalling networks by the scaffold protein Shc1. Nature 499, 166–171 (2013).
Article ADS CAS PubMed PubMed Central Google Scholar
Pylayeva-Gupta, Y., Grabocka, E. & Bar-Sagi, D. RAS oncogenes: weaving a tumorigenic web. Nat. Rev. Cancer 11, 761–774 (2011).
Article CAS PubMed PubMed Central Google Scholar
Petschnigg, J. et al. The mammalian-membrane two-hybrid assay (MaMTH) for probing membrane-protein interactions in human cells. Nat. Methods 11, 585–592 (2014).
Article CAS PubMed Google Scholar
Yao, Z. et al. A global analysis of the receptor tyrosine kinase-protein phosphatase interactome. Mol. Cell 65, 347–360 (2017).
Article CAS PubMed PubMed Central Google Scholar
Feig, L. A. & Cooper, G. M. Inhibition of NIH 3T3 cell proliferation by a mutant ras protein with preferential affinity for GDP. Mol. Cell. Biol. 8, 3235–3243 (1988).
Article CAS PubMed PubMed Central Google Scholar
Jura, N. et al. Mechanism for activation of the EGF receptor catalytic domain by the juxtamembrane segment. Cell 137, 1293–1307 (2009).
Article PubMed PubMed Central Google Scholar
Waas, W. F. & Dalby, K. N. Transient Protein-protein interactions and a random-ordered kinetic mechanism for the phosphorylation of a transcription factor by extracellular-regulated protein kinase 2. J. Biol. Chem. 277, 12532–12540 (2002).
Article CAS PubMed Google Scholar
Garai, Á. et al. Specificity of linear motifs that bind to a common mitogen-activated protein kinase docking groove. Sci. Signal. 5, ra74 (2012).
Article PubMed PubMed Central CAS Google Scholar
Floyd, B. J. et al. Mitochondrial protein interaction mapping identifies regulators of respiratory chain function article mitochondrial protein interaction mapping identifies regulators of respiratory chain function. Mol. Cell 63, 621–632 (2016).
Article CAS PubMed PubMed Central Google Scholar
Jackson, T. D., Palmer, C. S. & Stojanovski, D. Mitochondrial diseases caused by dysfunctional mitochondrial protein import. Biochem. Soc. Trans. 46, 1225–1238 (2018).
Article CAS PubMed Google Scholar
Kozjak-pavlovic, V. The MICOS complex of human mitochondria. Cell Tissue Res. 367, 83–93 (2017).
Article CAS PubMed Google Scholar
Ciszak, E. M., Korotchkina, L. G., Dominiak, P. M., Sidhu, S. & Patel, M. S. Structural basis for flip-flop action of thiamin pyrophosphate- dependent enzymes revealed by human pyruvate dehydrogenase. 278, 21240–21246 (2003).
Boxem, M. et al. A protein domain-based interactome network for C. elegans early embryogenesis. Cell 134, 534–545 (2008).
Article CAS PubMed PubMed Central Google Scholar
Simonis, N. et al. Empirically controlled mapping of the Caenorhabditis elegans protein-protein interactome network. Nat. Methods 6, 47–54 (2009).
Article CAS PubMed PubMed Central Google Scholar
Yaish, P., Gazit, A., Gilon, C. & Levitzki, A. Blocking of EGF-dependent cell proliferation by EGF receptor kinase inhibitors. Science 242, 933–935 (1988).
Article ADS CAS PubMed Google Scholar
Roberts, A. W., Stilgenbauer, S., Seymour, J. F. & Huang, D. C. S. Venetoclax in patients with previously treated chronic lymphocytic leukemia. Clin. Cancer Res. 23, 4527–4534 (2017).
Article CAS PubMed Google Scholar
Souers, A. J. et al. ABT-199, a potent and selective BCL-2 inhibitor, achieves antitumor activity while sparing platelets. Nat. Med. 19, 202–208 (2013).
Article CAS PubMed Google Scholar
Stagljar, I. The power of OMICs. Biochem. Biophys. Res. Commun. 479, 607–609 (2016).
Article CAS PubMed Google Scholar
Barrios-Rodiles, M. et al. High-throughput mapping of a dynamic signaling network in mammalian cells. Science 307, 1621–1625 (2005).
Article ADS CAS PubMed Google Scholar
Lemmens, I. et al. Heteromeric MAPPIT: a novel strategy to study modification-dependent protein-protein interactions in mammalian cells. Nucleic Acids Res. 31, e75 (2003).
Article PubMed PubMed Central CAS Google Scholar
Fields, S. & Song, O. A novel genetic system to detect protein-protein interactions. Nature 340, 245–246 (1989).
Article ADS CAS PubMed Google Scholar
Galarneau, A., Primeau, M., Trudeau, L. & Michnick, S. W. β-Lactamase protein fragment complementation assays as in vivo and in vitro sensors of protein–protein interactions. Nat. Biotechnol. 20, 619–622 (2002).
Article CAS PubMed Google Scholar
Ramachandra, N. et al. Self-assembling protein microarrays. Science 305, 86–91 (2004).
Article ADS CAS Google Scholar
Shah, N. H., Eryilmaz, E., Cowburn, D. & Muir, T. W. Naturally split inteins assemble through a ‘capture and collapse’ mechanism. J. Am. Chem. Soc. 135, 18673–18681 (2013).
Article CAS PubMed PubMed Central Google Scholar
Zheng, Y., Wu, Q., Wang, C., Xu, M. Q. & Liu, Y. Mutual synergistic protein folding in split intein. Biosci. Rep. 32, 433–442 (2012).
Article CAS PubMed Google Scholar
Michnick, S. W., Ear, P. H., Manderson, E. N., Remy, I. & Stefan, E. Universal strategies in research and drug discovery based on protein-fragment complementation assays. Nat. Rev. Drug Discov. 6, 569–582 (2007).
Article CAS PubMed Google Scholar
Kim, M. W. et al. Time-gated detection of protein-protein interactions with transcriptional readout. Elife 6, 1–24 (2017).
CAS Google Scholar
Olhovsky, M. et al. OpenFreezer: a reagent information management software system. Nat. Methods 8, 612–613 (2011).
Article CAS PubMed Google Scholar
Boussif, O. et al. A versatile vector for gene and oligonucleotide transfer into cells in culture and in vivo: polyethylenimine. Proc. Natl. Acad. Sci. USA 92, 7297–7301 (1995).
Article ADS CAS PubMed PubMed Central Google Scholar
Kotlyar, M., Pastrello, C., Malik, Z. & Jurisica, I. IID 2018 update: context-specific physical protein-protein interactions in human, model organisms and domesticated species. Nucleic Acids Res. 47, D581–D589 (2019).
Article CAS PubMed Google Scholar
Kotlyar, M. et al. In silico prediction of physical protein interactions and characterization of interactome orphans. Nat. Methods 12, 79–84 (2014).
Article PubMed CAS Google Scholar
Brenner, S. The genetics of Caenorhabditis elegans. Genetcis 77, 71–94 (1974).
CAS Google Scholar

Download references

Acknowledgements

We thank Punit Saraon for the help with the figure preparation, Jelena Tomic for editing, Mandy Lam and Mikko Taipale for providing access to equipment, and Mandy Lam, Mikko Taipale and Frederick Roth for providing cDNA clones, R. Schmidt for help with C. elegans strain generation. The work in the Stagljar lab is supported by the Cancer Research Society (#505486), Genome Canada via Ontario Genomics (#OGI-117, #OGI-159 & #OGI-120), Ontario Research fund (ORF/DIG-501411 & RE08-009), CIHR (#PJT-165862), FACIT Prospects Oncology Grant (#507942), and CQDM (Quantum Leap). This work was also supported by the Netherlands Organization for Scientific Research (NWO) VICI grant 016.VICI.170.165 to M.B. Jurisica lab was in part supported by Ontario Research Fund (#34876), Natural Sciences Research Council (NSERC #203475), and Canada Foundation for Innovation (CFI #225404, #30865).

Author information

Authors and Affiliations

Donnelly Centre, University of Toronto, Toronto, ON, Canada
Zhong Yao, Farzaneh Aboualizadeh, Indira Akula, Jamie Snider, Anna Lyakisheva, Priscilla Tang & Igor Stagljar
Division of Developmental Biology, Institute of Biodynamics and Biocomplexity, Faculty of Science, Utrecht University, Utrecht, Netherlands
Jason Kroll & Mike Boxem
Krembil Research Institute, University Health Network, Toronto, ON, Canada
Max Kotlyar & Igor Jurisica
Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
Igor Jurisica
Department of Computer Science, University of Toronto, Toronto, ON, Canada
Igor Jurisica
Institute of Neuroimmunology, Slovak Academy of Sciences, Bratislava, Slovak Republic
Igor Jurisica
Department of Biochemistry, University of Toronto, Toronto, ON, Canada
Igor Stagljar
Department of Molecular Genetics, University of Toronto, Toronto, ON, Canada
Igor Stagljar
Mediterranean Institute for Life Sciences, Meštrovićevo Šetalište 45, HR-21000, Split, Croatia
Igor Stagljar

Authors

Zhong Yao
View author publications
You can also search for this author in PubMed Google Scholar
Farzaneh Aboualizadeh
View author publications
You can also search for this author in PubMed Google Scholar
Jason Kroll
View author publications
You can also search for this author in PubMed Google Scholar
Indira Akula
View author publications
You can also search for this author in PubMed Google Scholar
Jamie Snider
View author publications
You can also search for this author in PubMed Google Scholar
Anna Lyakisheva
View author publications
You can also search for this author in PubMed Google Scholar
Priscilla Tang
View author publications
You can also search for this author in PubMed Google Scholar
Max Kotlyar
View author publications
You can also search for this author in PubMed Google Scholar
Igor Jurisica
View author publications
You can also search for this author in PubMed Google Scholar
Mike Boxem
View author publications
You can also search for this author in PubMed Google Scholar
Igor Stagljar
View author publications
You can also search for this author in PubMed Google Scholar

Contributions

Z.Y. conceptualized SIMPL, was actively involved in most experiments and data analysis, and wrote the bulk of the manuscript. F.A. performed some experiments. F.A., I.A., and P.T. were involved in DNA preparation. J.S. contributed to manuscript writing. J.S. and A.L. helped creating stable cell lines. J.K. and M.B. undertook the C. elegans work and wrote the related part in the manuscript. I.J. and M.K. performed computational analysis of RRS, helped data analysis, and contributed to manuscript writing. I.S. guided and supervised the work, contributed to manuscript writing and coordinated the preparation of the manuscript. All authors approved its content.

Corresponding author

Correspondence to Igor Stagljar.

Ethics declarations

Competing interests

I.S. and Z.Y. are named as co-inventors on a patent application concerning the described technology.

Additional information

Peer review information Nature Communications thanks the anonymous reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information

Peer Review File

Reporting Summary

Source data

Source Data

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

Reprints and permissions

About this article

Cite this article

Yao, Z., Aboualizadeh, F., Kroll, J. et al. Split Intein-Mediated Protein Ligation for detecting protein-protein interactions and their inhibition. Nat Commun 11, 2440 (2020). https://doi.org/10.1038/s41467-020-16299-1

Download citation

Received: 23 May 2019
Accepted: 21 April 2020
Published: 15 May 2020
DOI: https://doi.org/10.1038/s41467-020-16299-1

This article is cited by

AI-guided pipeline for protein–protein interaction drug discovery identifies a SARS-CoV-2 inhibitor
- Philipp Trepte
- Christopher Secker
- Erich E Wanker
Molecular Systems Biology (2024)
Met–HER3 crosstalk supports proliferation via MPZL3 in MET-amplified cancer cells
- Yaakov E. Stern
- Abdulhameed Al-Ghabkari
- Morag Park
Cellular and Molecular Life Sciences (2022)
Selection for constrained peptides that bind to a single target protein
- Andrew M. King
- Daniel A. Anderson
- Christopher A. Voigt
Nature Communications (2021)
A homogeneous split-luciferase assay for rapid and sensitive detection of anti-SARS CoV-2 antibodies
- Zhong Yao
- Luka Drecun
- Igor Stagljar
Nature Communications (2021)

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.