Affinity purification-mass spectrometry network analysis

This protocol describes how to use data from an affinity purification-mass spectrometry experiment to to generate relevant interaction networks, enriching the networks with information from public resources, analyzing the networks and creating effective visualizations.

Background

The data used for this protocol represents interactions between human and HIV proteins by Jäger et al. In this quantitative AP-MS experiment, a relatively small number of bait proteins are used to pull down a larger set of prey proteins.

Note that this tutorial does not describe how to pre-process the raw AP-MS data, the data used here is already scored and filtered.

Setup

This protocol uses two apps, that can be installed from the Cytoscape App Store, or using the Cytoscape App Store in Cytoscape: stringApp and enhancedGraphics.

Import Network and Data

  • Load the network via File → Import → Network from File...., and select the Example data.
  • In the Import Network from Table dialog, select the Bait column as Source Node and Prey column as Target Node.
  • Designate the AP-MS Score as an Edge Attribute.
  • For all other data values, designate them as Target Node Attribute, by clicking in the column header and selecting the red spreadsheet icon.
  • Click OK to import the network.

Note: In cases where a Prey node interacts with more than one Bait node, it will have multiple rows of values for the same attribute (for example HEKScore). During import, the last value imported will overwrite prior values and visualizations using this attribute thus only shows the last value.

Import Network and Data

The imported network consists of multiple smaller subnetworks, each representing a bait node and its associated prey nodes:

Augmenting Network with Existing Protein-protein Interaction Data

We are going to use existing protein-protein interaction data to enrich the network, using the STRING database with the human protein nodes as input.

  • In the Node Table, sort the table for your network by the Uniprot column by clicking on the header twice. This will sort for the human protein nodes, which are the ones with entries for Uniprot.
  • Select all the relevant entries in the Uniprot column by selecting the top item, then scroll down and hold down Shift and then selecting the last entry. Click Ctrl+C to copy.
  • Paste the list of gene symbols into the Network Search at the top of the Control Panel. Select String Protein from the drop-down.
  • Click the options icon and set the Confidence (score) cutoff to 0.999. Keep the default, 0, for Maximum additional interactors.
  • Click the search icon to search. The resulting network may load automatically or you will see an intermediate dialog to confirm anbiguous query matches (confirm the cutoff and maximum values, then click Import).

Augmenting network with existing protein-protein interaction data

The resulting network contains known interactions between the human proteins, with an evidence score of 0.999 or greater.

Merge Networks

To incorprate the new information into our AP-MS network, we need merge the STRING and AP-MS networks. We can use the Uniprot IDs available in both networks as the mathcing attribute.

  • Go to Tools → Merge → Networks...
  • In the Available Networks list, select both networks and click the right arrow to add then to the Networks to Merge list.
  • Expand the Advanced Options interface.
  • In the Matching Columns field, select Uniprot for the AP-MS network and query term for the string network.
  • In the How to merge columns section, find the entry for display name for the string network. Click on the column for the ap-ms network for that same row and select name from the drop-down.

Merge Networks

When the network first loads, it will have the STRING style applied. However, because the HIV nodes are not from STRING, they will be white and difficult to see. The layout also makes the network hard to interpret.

  • Switch the style to default to make all nodes visible.
  • Under Layout → Settings..., select the Prefuse Force Directed Layout and change the settings as follows:
    • Set Default Spring Coefficient to 5E-5
    • Set Default Spring Length to 100
    • Set Default Node Mass to 3.
  • Click Apply to apply the layout.

Network Visualization

The default style is not so informative in this case, so let's change the style of the network a bit.

  • In the Style tab of the Control Panel, click the Options menu and select Create New Style.... Name the style AP-MS.
  • Change the default node shape to ellipse and check Lock node width and height.
  • Set the node Size to 50.
  • Set the default node Fill Color to light grey.
  • Create a passthrough mapping for the node Label using the display name.

Network Visualization

The network should now look like this:

Enrichment Analysis

Now that we have a merged network, we can do enrichment analysis on it, using the STRING enrichment tool.

  • Select Apps → STRING → Retrieve functional enrichment. Use the default value (0.05) for Enrichment FDR value cutoff.
  • When the enrichment analysis is complete, a new tab titled STRING Enrichment will open in the Table Panel.

Enrichment Analysis

The STRING app includes several options for filtering and displaying the enrichment results. The features are all available at the top of the STRING Enrichment tab.

  • We are going to filter the table to only show GO Process. At the top left of the STRING enrichment tab, click the filter icon . Select GO Process and check the Remove redundant terms check-box. Then click OK.
  • Next, we will add a split donut chart to the nodes representing the top terms by clicking on .
  • Explore custom setting via in the top right of the STRING enrichment tab.

Visualizing Results

We can create a visualization based on the Jurkat Score, and the different interaction types:

  • In the Style tab of the Control Panel, copy the current style to create a new style named AP-MS Jurkat Score.
  • Remove the STRING enrichment chart by clicking the Reset charts icon at the top of the STRING Enrichment tab.
  • Create a continuous mapping for the node Fill Color using the JurkatScore column. Select a purple gradient from the ColorBrewer palettes.
  • Switch the deafult node Fill Color to yellow to highlight the HIV proteins.
  • In the Edge tab, create a continuous mapping for edge Width using the AP-MS Score column.
  • Set the width values to a range from 1 to 5.
  • Create a Discrete mapping for edge Stroke Color using the interaction column. Choose a green color for all interactions of type interacts with. This will color all the interactions in the original AP-MS dataset.

Visualizing Results

We now have a visualization of the network highlighting the ap-ms experimental data (green edges), as well as additional known interactions (grey edges), with node color indicating the Jurkat Score from the data:

Visualizing Results

We could create a similar kind of style for the HEK score, but that only allows for viewing each style seperately. Instead, we can create a combined style, using the enhancedGraphics app.

For this, we will need a new column defining a new attribute that will be used for mapping to the Custom Graphics property via the enhancedGraphics app. This new attribute has to be in the form of mappings recognized by the enhancedGraphics app.

  • In the Table Panel, click the button for Create New Column, then select New Single Column → String and name it CombinedScore.
  • In the first cell of the CombinedScore column, enter the mapping below and click enter.

    • piechart: showlabels="false" range="0,1" arcstart="90" valuelist=".5,.5" colorlist="up:blue,zero:white,down:white;up:purple,zero:white,down:white" attributelist="HEKScore,JurkatScore" labellist="HEKScore,JurkatScore"

  • Your new entry may disappear to the bottom of the column; just click on the column header once or twice to re-sort. Right-click on the new entry and select Apply to entire column. This will fill the column with the same mapping.

Visualizing Results

  • In the Style panel, select Copy Style... and name your new style AP-MS CombinedScore.
  • Create a passthrough mapping for Image/Chart 1 using the new CombinedScore attribute.


The network is now showing the Jurkat score (purple gradient on the right-hand side of the nodes) and HEK scores (blue gradient on the left). AP-MS experiment interactions are shown as green lines in which the thickness of the line reflects the average score, and interactions from STRING are shown as gray lines.

Visualizing Results

Zooming in on the network, specifically the POL and PR HIV nodes, we can see a set of interactions found in the original paper, which represent binding of POL and PR with the translational initiation complex EIF3.

Note: Remember that when we imported multiple values for a single node attribute, such as the HEKScore for human Prey nodes interacting with more than one HIV Bait node, the last value imported overwrote prior values and the visualization thus only shows the last value. For EIF3A, which interacts with both PR and POL, only the data relevant to the PR interaction is maintained in the Node Table because our source data was sorted alphabetically by Bait.

Exporting Networks

Cytoscape provides a number of ways to save results and visualizations:

  • As a session: File → Save Session, File → Save Session As...
  • As an image: File → Export → Network to Image...
  • To the web: File → Export → Network to Web Page... (Example)
  • To a public repository: File → Export → Network to NDEx
  • As a graph format file: File → Export → Network to File.
    Formats:
    • CX JSON / CX2 JSON
    • Cytoscape.js JSON
    • GraphML
    • PSI-MI
    • XGMML
    • SIF