SLiMScape 3.x: a Cytoscape 3 app for discovery of Short Linear Motifs in protein interaction networks

Introduction

Many protein-protein interactions (PPIs) are mediated by a short linear motif (SLiM) in one protein interacting with globular domains in another¹. The past decade has seen the development of many computational methods and tools for predicting SLiMs from protein sequences and/or PPI data^2,3. SLiMs are short (2–15 amino acids in length) and degenerate (with few residues determining specificity)⁴, which makes them hard to identify against a backdrop of highly conserved structural domains. These features also impart remarkable evolutionary plasticity, and convergent (i.e. independent) evolution of new SLiM occurrences is common^5,6. Some of the best examples of this come from viruses, which often hijack host cellular processes via molecular mimicry of host SLiMs⁷. An effective approach for de novo SLiM discovery is to explicitly model this convergent evolution and look for enriched sequence patterns in non-homologous proteins^5,8,9. SLiMFinder combines this approach with a robust statistical model, which enables a good estimation of the probability that an observed enrichment is by chance^6,9–11. “Query” SLiMFinder (QSLiMFinder) extends this approach to define the motif search space on a specific protein, such as a viral interactor, and look for enrichment in the remaining non-homologous proteins in the dataset¹¹.

Combining motif discovery tools with biological knowledge has recently identified a new motif (“ABBA”) that binds the anaphase-promoting complex or cyclosome (APC/C) ubiquitin ligase¹². Nevertheless, despite the improved performance and potential of these methods, they are yet to deliver the promised windfall of new motifs⁴. In large part, this is due to the difficulty in constructing appropriate datasets for SLiM discovery^2,6. SLiM discovery relies on a careful balance of maximising the SLiM-containing signal in the data whilst removing noise by reducing the search space, either in terms of PPI or protein regions¹¹. Cytoscape is a well developed platform for the interactive generation and exploration of PPI datasets¹³. Cytoscape is a useful resource for SLiM discovery, enabling visual groupings of proteins that share a common interaction partner and may also share a SLiM-mediated mechanism of binding. Such proteins can either be used as input for de novo SLiM discovery approaches^5,6 or explored for enrichment of known motifs¹⁴.

SLiMScape brings these tools together in a friendly environment that allows the user to browse, define and explore protein nodes whose interactors are enriched for over-represented motifs. The previously developed SLiMScape plugin for Cytoscape 2.x enabled the user to interactively run SLiMFinder⁹ for de novo SLiM discovery, or SLiMSearch¹⁵ for predicting novel occurrences of known SLiMs¹⁶. To take advantage of the recent developments and features of Cytoscape, we have developed SLiMScape 3.x, a redesigned and updated app for Cytoscape 3.x. The SLiM discovery functions of SLiMScape have also been extended through the incorporation of QSLiMFinder¹¹ and enrichment statistics for known SLiMs using SLiMProb (formerly called SLiMSearch 1.x)¹⁴. SLiMScape 3.x is built on a new set of SLiMSuite servers that permit any of the commandline options of the standalone programs to be called via the Cytoscape app. Alternatively, SLiMSuite server jobs can be executed online (http://www.slimsuite.unsw.edu.au/servers.php) and the results imported and visualised using SLiMScape.

Methods

Loading input data

SLiMScape is designed to be run directly from within Cytoscape, or to visualise the results of a previous SLiMSuite server job. As such, all three SLiMSuite programs will accept three different inputs to identify the primary dataset of proteins for analysis (Figure 1):

• 1. A selection of nodes from an existing Cytoscape network view. Node ‘name’ attributes must be Uniprot identifiers or accession numbers.

• 2. A list of Uniprot identifiers or accession numbers, separated by commas, whitespace and/or new lines.

• 3. The Job ID of a previous SLiMSuite server job. This may have been submitted via SLiMScape or run directly on the server.

Figure 1. SLiMScape Cytoscape panels.

A. SLiMFinder run panel. B. SLiMFinder options panel. C. Results panel containing sequence and motif information. D. Results graph. Nodes containing SLiMs are indicated as red diamonds, where dark red indicates 2+ SLiMs. Nodes without SLiMs are displayed with default settings (blue circles in this case).

SLiMFinder. A set of proteins is the only required input for SLiMFinder.

QSLiMFinder. QSLiMFinder needs an additional query protein input, which is used to build the motif space¹¹. This should be the Uniprot accession number of one of the input proteins. If no accession number is given, the first protein returned by Uniprot will be used. This is not necessarily the same as the first accession number provided and should therefore be avoided. The query protein(s) used will be reported in the job’s log output at the server.

SLiMProb. SLiMProb needs one or more SLiMs to search within the protein dataset. These should be provided as SLiM regular expressions, e.g. DSG.{2,3}[ST] (where .{2,3} indicates two or three “wildcards” are permitted and [ST] is a serine or threonine). (See the Eukaryotic Linear Motif (ELM) database¹⁸ or SLiMScape documentation for more examples.) Multiple motifs can be provided, separated by commas. Whitespace is not permitted.

Data aliases. The SLiMSuite REST servers also feature a number of input aliases (http://rest.slimsuite.unsw.edu.au/alias). These include Uniprot ID lists and motif definitions for ELM and their occurrences from the ELM database¹⁸.

Running the program

Once all required inputs are provided and parameters are set, the desired program can be executed by clicking on the “Run X” button (where X is the name of the program being run). A popup window indicating processing will appear if a new server run is commencing (Figure 2). Jobs typically take a few minutes to run, although larger jobs (>100 proteins) may take several hours to complete depending on server load and the program settings. The server Job ID for this run will be displayed and also populate the Job ID box in the input panel (Figure 1A). This popup gives three progress options:

• Stop and return to Cytoscape. The job will continue running on the server but Cytoscape can be used as usual in the meantime. Additional jobs may be sent to the server whilst waiting for one to complete.

• Monitor job progress at the SLiMSuite server. This will open the job’s status page at the SLiMSuite server in the user’s default web browser.

• Check for job completion. If complete, this will load the results for visualisation. Otherwise, the popup will reload.

Figure 2. SLiMScape progress popup.

Running jobs will report the server job ID for future recall and provide options to: Stop and return to Cytoscape; Monitor job progress at the SLiMSuite server; or Check for job completion.

Alternatively, a previous server Job ID can be entered in the Job ID box and loaded by clicking the “Retrieve” button. If complete, this will load the data into Cytoscape for visualisation. Otherwise, the running popup will appear. If an inappropriate Job ID is provided, or a job has crashed, an appropriate message should appear. If in doubt, the Monitor button in the progress popup (Figure 2) can be used to check that a job has executed correctly.

Use cases

Cytoscape can be used to import PPI data from a number of databases. The IntAct database at the European Bioinformatics Institute (EBI)²⁵ is particularly suitable for SLiMScape analyses because the majority of nodes are mapped to Uniprot accession numbers. Other databases can be used but some additional mapping on to Uniprot identifiers might be required.

The proteins ‘F-box and WD repeat domain containing 11’ (Gene Symbol: FBXW11; Uniprot: Q9UKB1) and ‘beta-transducin repeat containing E3 ubiquitin protein ligase’ (Gene Symbol: BTRC; Uniprot: Q9Y297) are two proteins of the SCF(beta-TRCP)-ubiquitin ligase complex, which recognise phosphodegron motifs (ELM DEG_SCF_TRCP1_1¹⁸) via their WD40 domains. We used the File » Import » Network » Public Databases function of Cytoscape to search for records matching FBXW11 and BTRC and imported the 184 records (184 edges; 86 nodes) from IntAct (Figure 3A). This network was then reduced to direct human and viral PPI of BTRC and FBXW11 and duplicate edges compressed.

Figure 3. SLiMFinder results for shared FBXW11/BTRC interactors.

A. PPI network imported from IntAct. B. Human and viral proteins that interact with both FBXW11 and BTRC. C. SLiMFinder results for de novo SLiM prediction in the shared interactors (Job ID 15061100050). D. QSLiMFinder server results for de novo SLiM prediction using HIV Vpu as a query (Job ID 15061200029).

Working on the principle that WD40-interaction motifs are most likely to be found in proteins that interact with both WD40 proteins, Cytoscape was used to reduce the network further to nodes interacting with both proteins (Figure 3B). These interactors were then input to SLiMFinder for de novo SLiM prediction, using disorder and Uniprot feature masking. SLiMFinder returned a variant of the phosphodegron motif, DSG (P < 0.05), which was found in 14 of the 21 proteins (Figure 3C).

The HIV Vpu protein interacts with both proteins and is therefore of particular interest as a potential molecular mimic. We repeated the analysis using QSLiMFinder with Vpu as the query. As previously observed¹¹, restricting the motif search space with QSLiMFinder increases the sensitivity of the search and returns the DSG motif with greater significance (P < 10⁻⁵) in addition to a number of different variants of the same motif (Figure 3D).

These data were clearly enriched for a DSG motif, which is a more degenerate variant of the annotated ELM DEG_SCF_TRCP1_1 motif, DSG.{2,3}[ST]. To investigate this further, the full set of BTRC and/or FBXW11 interactors were subject to a SLiMProb search of both the DSG and ELM (DSG.{2,3}[ST]) motifs with the same disorder and Uniprot feature masking (Job ID 15061200035). Using Cytoscape, proteins were arranged into three PPI sets of BTRC-only, FBXW11-only and shared interactors, arranged with DSG-containing proteins at one end and DSG-free proteins at the other (Figure 4). The SLiMProb run was opened up as new network to identify homology between the proteins (Figure 4A) and the two networks merged (Figure 4B). The SLiMProb search was repeated with additional conservation masking (Job ID 15061200036). Proteins with conserved motif occurrences were manually changed to circles (conserved DSG) or hexagons (conserved DSG.{2,3}[ST]) in the merged network (Figure 4B).

Figure 4. SLiMProb results for DSG and DSG.{2,3}[ST] motifs in FBXW11/BTRC interactors.

A. Protein network generated from SLiMProb results labelled using Gene names extracted from Uniprot IDs. Edges in this network represent sequence homology. Red nodes indicate proteins with motif occurrences. Proteins with both motifs are in dark red. Proteins without either motif are blue circles. B. Merged PPI and homology network. Blue dotted lines represent sequence homology. Nodes are coloured and shaped according to motif occurrences: DSG, orange; DSG.{2,3}[ST], dark red; conserved DSG, circles; conserved DSG.{2,3}[ST], hexagons; no motifs, blue rectangles. The dark red circles (WWTR1 and TRIM9) have conserved DSG occurrences and unconserved DSG.{2,3}[ST] occurrences.

Visual inspection of the motif distribution suggested that the DSG motif is actually more specific for the interaction than the defined ELM, showing a greater enrichment in the proportion of joint interactors versus interaction partners of only BTRC or FBXW11. This observation was confirmed by subsequent SLiMProb analysis of six different groups of proteins (Figure 5). However, when the sequence composition of the proteins was taken into consideration, it became clear that the defined ELM was considerably more enriched across all BTRC/FBXW11 interactors than the simpler DSG motif. This was particularly pronounced when looking at evolutionarily conserved instances (i.e. results from SLiMProb analyses with conservation masking) (Figure 5C). This demonstrates the power of combining Cytoscape and SLiMSuite to get insights that are not obvious from either tool in isolation.

Figure 5. SLiMProb enrichment for DSG and DSG.{2,3}[ST] (“ELM”) motifs in FBXW11/BTRC interactors.

A. Schematic of the different protein subsets analysed. B. Proportions of unrelated proteins with motif occurrences. ELM indicates DSG.2,3[ST]. DSGcons and ELMcons are conserved occurrences. C. Observed/expected number of unrelated proteins with motif occurrences (N_UPC/E_UPC, see Table 1).

Also of interest is the other viral protein in the dataset, the NSP1 protein of ribovirus A (Uniprot: Q84940), which is reported to interact with FBXW11 but not BTRC. It has a DSG.SD sequence, which is intriguingly similar to the DEG_SCF_TRCP1_1 motif. Indeed, this motif was recently reported to be another case of molecular mimicry, targeting the beta-TrCP subunit²⁶. The evolutionary dynamics of SLiMs are complex; further work will need to be done to establish whether any of the other DSG instances that fail to match the more specific ELM definition represent hitherto undescribed variants of the motif or non-functional background sequence patterns.

Summary

SLiM discovery is a challenging task that requires high quality data in addition to appropriate bioinformatics tools. There is often a disconnect between users with the biological knowledge to construct the former and those with the computational experience to run the latter. Embedding the SLiM discovery tools of SLiMSuite within the interactive environment of Cytoscape will help to bridge that gap, enable new patterns to be identified and new questions to be formulated.

Data availability

SLiMSuite results for the figures in this manuscript can be retrieved by entering the Job ID indicated in the text through the SLiMScape app, or at: http://www.slimsuite.unsw.edu.au/servers.php. Job IDs for Figure 5 are given in Table 2.

Software availability