STM8: A Pathway Logic Model of Intracellular Signal Transduction

Table of Contents


STM8 is a formal knowledge base containing information about the changes that occur in the proteins inside a cell in response to exposure to receptor ligands, chemicals, or various stresses. STM8 is represented in Pathway Logic (PL) and can be explored using the Pathway Logic Assistant (PLA). The key features of STM8 (and PLA) that distinguish it in various ways from other signal transduction pathway knowledge bases and viewers (such as Reactome, KEGG, Cytoscape, CellDesigner) are:

The STM8 Network Collection

Cell biologists spend a lot of time throwing things (stimuli) at cells in culture and studying the results. The STM8 Response Networks are formal representations of conclusions that can be made from such experiments. These representations constitute executable models that have natural graphical visualizations. The STM8 collection also includes a phenotype (story) network (the Death network). Phenotype networks focus on a particular endpoint or goal and may have multiple stimuli, in contrast to the response networks that have a single stimulus and may have many different endpoints. In either case, the size (number of rules and datums) of each network depends on the available literature and the interests of our clients.

Response networks

Story networks

Projects often require for networks that have a particular outcome (such as apoptosis) but not a specific stimuli. Story (phenotype) networks are built by collecting statements made in review articles, translating them into rules, and using PLA to display them. An example of a story is the Death Network assembled for the Iarpa FunGCat project:

The review articles used for Death Network are:

Once the network is assembled, we try to verify it by collecting the experimental evidence from the supporting references. If experimental evidence is found that supports the statement then the rule is considered valid. If the experimental evidence does not support the statement or if the reference is another review article, then the rule is considered to be unsupported and colored yellow in the PLA display. In either case, the rules will have links to evidence pages containing the statements from the review article, the PMIDs of the supporting references, and any datums that are relevant.

In many cases, the supporting reference (the numbers represent PMIDs) will be marked "done" but there will not be any datums in the evidence page. That is because we could not find any connection between the statement and the experimental results. You can check for yourself by going to and entering the PMID into the search box. This will bring up all the datums curated from the reference.

Why tell a story? Consider Pyropotosis from the evidence. Most of the experiments from the review articles are done in mouse bone marrow derived macrophages and are about mouse proteins involved in inflammasome formation. The end goal of pyroptosis is the secretion of mature IL1b. Why are there so few experiments using human cells and proteins? One of the excuses is that obtaining bone marrow macrophages from human is not practical. But immunology text books tell us that IL1b is also secreted by epithelial cells (Janeway), fibroblasts, and hepatocytes (Abbas). Now that we have our story, we know where the gaps in the evidence are (see the yellow rules) and we have descriptions of the experiments that were done to put the story together. Given the existing preliminary data, it would be simple to design experiments using a human cell line and see how the story plays out in humans.

Demo: How to use PLA to examine the Death Network

This demo assumes that the user is already familiar with the use of PLA as described in the SmallKB guide and the PLA reference manual . In the following guided tour, double click on a figure to see an enlarged version. Single click to restore the figure to its original size.

Getting started

Download the PLA STM8 Launcher from PLA Online. Follow instructions on the page to get around security barriers and start the launcher. A launcher window will open showing the collection of STM8 networks. Clicking on a network name will display information about the network.


Screen shot of the STM8 launcher with the Death network selected

Select the Death network and click on the launch button.

When PLA starts up, a knowledge base manager (KBManager) window (title: Death Manager) appears in the upper left corner of your screen. The KBManager displays a list of available knowledge bases (rule sets). "RKB" is selected by default and will be highlighted in blue.

Start by selecting a predefined dish: press the "Select Dish" button on the right side of the KBManager window. This produces a menu with two options: "Edit" and "PreDefined". Select (click on) "PreDefined". This produces a (sub)menu. Select "DeathDish" (by clicking on the corresponding menu item).

Shortly a PLA viewer window with tab titled graph2:DeathDish will appear on your screen displaying the Death Network. [Note that the graph numbers in titles may differ if you have created graphs or nets in addition to those discussed in the demo or restarted with a fresh PLA. This is fine.]

The PLA display


Screen shot of the Death Network displayed in the PLA tab window

The PLA window is organized in sections: Menu Bar, Tool Bar, Navigation Panel, Graph Panel, and Information Panel.

About the Petri Net Representation

A network of reactions is displayed as a graph with two kinds of nodes. Ovals represent occurrences—proteins or chemicals in a specific state and location. For example the oval labeled Casp7-act@CLc represents the protein Casp7 in its active state located on the cytoplasm (CLc). We use the following notation:

CLm --- Plasma membrane
CLo --- Stuck to the outside of the plasma membrane
CVc --- Stuck to the cytoplasmic side of the membrane of acytoplasmic vesicle
ERl --- Endoplasmic reticulum lumen
ERm --- Endoplasmic Reticulum membrane
ESm --- Endosome membrane
GOm --- Golgi Apparatus membrane
MIS --- Mitochondrion intermembrane space
MIX --- Mitochondrion matrix
MOM --- Mitochondrion outer membrane
NUc --- Nuclear membrane
Sig --- A pseudo location for phenotypes
Receptor Complexes
Cd40C --- forms in response to Cd40Lg binding to Cd40
Csf1RC --- forms in response to Csf1 binding to Csf1R
EgfRC --- forms in response to Egf binding to EgfR
FasRC --- forms in response to FasL binding to FasR
GP130C --- forms in response to IL6 binding to Gp130 and IL6R
HgfRC --- forms in response to Hgf binding to HgfR
IfnaRC --- forms in response to members of the Ifna family or Ifnb1 binding to IfnaR2 and IfnaR1
IfngRC --- forms in response to Ifng binding to IfngR1, Jak1, IfngR2, and Jak2
Igf1RC --- forms in response to Igf1 binding to Igf1R
IL1R1C --- forms in response to IL1 binding to IL1R1 and IL2Rap
IL2RC --- forms in response to IL2 binding to IL2Rb, IL2Ra, and IL2Rg
IL4RC --- forms in response to IL4 binding to IL4R IL2Rg
IL12Rb1C --- A preassembled complex consisting of IL12Rb1 and Tyk2
IL12Rb2C --- A preassembled complex consisting of IL12Rb2 and Jak2
IL12RC --- forms in response to IL12 binding to IL12Rb1, Tyk2, IL12Rb2, and Jak2
IL17RC --- forms in response to IL17a binding to IL17Ra and IL17Rc
IL22RC --- forms in response to IL22 binding to IL22Ra1 and IL10Rb
InsRC --- forms in response to Ins binding to InsR
NgfRC --- forms in response to Ngf binding to NgfR
PdgfRC --- forms in response to Pdgf binding to PdgfR
RageC --- forms in response to AGE binding to Rage
Tgfb1RC --- forms in response to Tgfb1 binding to TgfbR1 and TgfbR2
TLR2C --- forms in response to TLR2 ligands binding to TLR2
TLR3C --- forms in response to TLR3 ligands binding to TLR3
TLR4C --- forms in response to TLR4 ligands binding to TLR4
TLR9C --- forms in response to TLR9 ligands binding to TLR9
TnfR1C --- forms in response to Tnf binding to TnfR1
TrkaC --- forms in response to Ngf binding to Trka
VegfR2C --- forms in response to Vegfa binding to VegfR2
Non Receptor Complexes
CHR --- forms around Chromatin
RNAC --- forms around the capped mRNA complex
aaBound --- tRNA bound to any amino acid
aaFree --- tRNA not bound to any amino acid
absent --- not present
acetyl --- acetylated
acetyl-site --- acetylated at a specific site
act --- activated (for kinases only)
broken --- for DNA with strand breaks
cleaved --- cleaved
cleaved-site --- cleaved at a specific site
clustered --- for aggregated proteins
degraded --- degraded
dimer --- auto-dimerized
DNAbound --- bound to DNA
GDP --- bound to GDP
GTP --- bound to GTP
K48ubiq --- covalently bound to ubiquitin polymerized via K48 linkages
K63ubiq --- covalently bound to ubiquitin polymerized via K63 linkages
off --- gene transcription is off
oligomer --- auto-oligomerized
on --- gene transcription is on
ox --- oxidized
p17 --- 17 kD fragment
p50 --- 50 kD fragment
pore --- forming a membrane pore
red --- reduced
spliced --- mRNA has been spliced
STphos --- phosphorylated on Serine and/or Threonine
Tphos --- phosphorylated on Serine
Tphos --- phosphorylated on Threonine
ubiq --- ubiquitinated
unk --- unknown
unspliced --- mRNA has not been spliced
Yphos --- phosphorylated on Tyrosine

If the occurrences are in a complex, they are displayed with components stacked in a rounded rectangle. Darker colored ovals represent occurrences in the initial state (the state of all occurrences before a stimulus is added. Lighter colored ovals represent potential states/locations of these components.

Rectangles represent rules. The label in a rectangle is its (abbreviated) identifier in the knowledge base. Solid arrows from an occurrence to a rule indicate that the occurrence is a reactant (rule input). Solid arrows from a rule to an occurrence indicate that the occurrence is a product (rule output). Dashed arrows from an occurrence to a rule indicate that the occurrence is a modifier/enzyme/catalyst—it is necessary for the reaction to take place but is not changed by the reaction.

Browsing the Death Network

Here are some ways to explore the Death network.

Find the node representing Cell-Death

There are three ways that cells can die in this network: Pyroptosis, Necroptosis, and Apoptosis. Lets look at Apoptosis.

Shortly a new tab will appear displaying a graph representing a subnet containing all the paths leading to Apoptosis. Simplify the graph by hiding redundant edges.


Screen shot of the DeathDish Apoptosis subnetwork

Now ask how many paths are in the network that can lead to apoptosis.

The answer will appear in the information panel. (There are 20 paths.)

To look at each of the paths in context of the graph:

All the paths will be listed in the info panel (since they all must turn ALIVE into DEAD). These are shown as lists of rule numbers but each can be highlighted in the graph by clicking on the box in the highlight column.

Suppose you are only looking for paths originating from the needle protein from Chromobacterium violaceum (CprI!C.violaceum).

There are two paths using CprI!C.violaceum@CLc. You can compare the two paths by clicking back and forth or you can compare them directly. For each path launch a new network by pressing the Launch button at the bottom of the panel. You will now have a graph for each path (graph6 and graph8). From graph6 (the first path launched) click on Compare in the menu bar. Choose graph8 (the second path launched) from the list of graphs. A compare graph will appear.


Comparison of paths from CprI!C.violaceum@CLc to Apoptosis

The nodes in pink are common to both graph6 and 8. The nodes in purple are unique to graph16 and the nodes in cyan are unique to graph18. It is now obvious that apoptosis can be caused by activation of either Caspase-3 or Caspase-7.

Entity Identification

We have supplied a table of modifications and locations above but what about the proteins and chemicals. If you are unfamiliar with the name we use for a protein or just want to learn more about it, you can click on the occurrence node. The Context Menu Tab in the information panel (lower right) will display some buttons which include "About Occurrence". Clicking on this button will display relevant information. For proteins, there is a link to the UniProt record. For chemicals, there is a link to the PubChem CID.


All of the rules in the response networks are derived from experimental data so if you are doubtful or curious about a rule, you can ask for the evidence page and see the data that was used to create the rule. You can see an example by looking at the evidence page for rule 1546 which was imported from the Lps Response network.

A page containing all the datums used to create the rule will display.

Not sure how to read a datum? You can find details in the Datum KB documentation .

In the Death Story, rules were created from assertions made in review articles. Evidence pages for these rules contain the assertions, their sources, and references provided. If the assertions had references containing experiemntal results, they were collected as datums. If the datums supported the assertions, they were added to the evidence pages. Rules without significant experimental evidence are colored yellow.

A page containing the assertions that were used to make the rule will display.


That should get you started. Please look at some of the response networks. (Go back to the STM8 launcher, select a response network and press the launch button.) In the case of the very large nets, when you select the dish the PLA window displays the list of occurrences rather than the graph. This is because the graph is complex, looking rather like a dish of spaghetti and may just confuse (or frighten). If you really want to see the graph, press the Render button. It may take a couple minutes, so have patience. If you know the goal you are interested in, you can skip rendering the full graph and use the selections tab to set the goal and compute the relevant subnet. If you are interested in the rules that change or use a particular occurrence, you can use the PLA Explore mechanism to display the surrounding network, restrict exploration to upstream or downstream events.

The curation of STM8 was partially supported by funding from NIH, NSF, DARPA, and IARPA.