Articles|Signalling and Signal Transduction

Networks in Nature

By Brona McVittie

Networks are everywhere in nature. We all exist within hierarchical systems. Whether a company director, middle manager or staff on the factory floor, we each play a functional role within a network. While all roles are important, they are not equal. Corruption within the system will have different effects depending on where it arises. The greatest potential threat is top-down corruption. While workers on the ground can be easily replaced by the director, a corrupt leader cannot be so easily overthrown by the workers. To fully understand a company we need to appreciate the relationships between its members.

The situation within a cell is comparable. We could view the cell as a collection of interrelated companies, each with their own hierarchies, sometimes overlapping. Company directors are like upstream nodes in a signalling network, a network that governs processes fundamental to cell function. Such genes when mutated cause complete breakdown of the system. Downstream from these key players, at the next level in the hierarchy, middle-managers relay instructions to the factory staff. Genes of this nature, when mutated, disturb only those workers in their charge. Mutations further downstream will have correspondingly smaller effects.

Understanding genes is much easier with an appreciation of their context within gene networks. Drugs are often designed to target the products of specific network nodes (genes), blocking their action. So to understand the effects of the drug on the whole system, it's helpful to know where the respective gene sits within the hierarchy. Targeting genes that dominate a signalling pathway will obviously have the greatest impact, however this may not be desirable and could manifest in unwanted side-effects. Thus downstream drug targets may offer greater medical potential.

Biologists are teaming up with mathematicians and computer scientists to help them understand complex signalling networks and reveal potential drug targets within cells. Rainer Spang (University of Regensburg, Germany) devises computer models to model signal flow in cells. “If we stimulate a cell, for example by knocking down a certain gene, a lot of stuff happens downstream. If you take a certain signalling gene out of a cell, it might affect the expression of thousands of other genes. Using these data, we can reconstruct how the signal is flowing in the cell, from one molecule to the next.”

The ERASysBio+ funded project, ApoNET, seeks to identify drug targets within two signalling pathways implicated in liver cancer; “namely so-called TRAIL and TNF signalling pathways,” Michael Boutros (University of Heidelberg and German Cancer Research Center, Germany) explains. The TNF pathway is involved in the body's inflammatory response, whereas TRAIL primarily triggers apoptosis (see On the TRAIL of Suicidal Cells). TRAIL is not unique in its ability to trigger cell suicide, although because cancer cells refuse to be retired, it could come in useful.

A number of molecules, like TRAIL, can initiate apoptosis by binding to receptors on the surface of cells. Binding activates genes downstream in the network to produce a whole host of enzymes that effectively help to safely dispose of unwanted cells, although cancer cells often fail to respond to such triggers. “We have tools to assimilate these signalling pathways and we plan to identify signalling nodes by perturbing them,” Michael says. His team uses a technique to disable specific network nodes, by blocking the RNA made by the respective gene. Then they look at how this affects all the other genes within the cell using transcriptome sequencing (see Sequences within Cells).

“The physiological response when you treat cells with TRAIL or TNF is largely different,” explains Michael. “Nevertheless certain signalling cascades downstream, for example NFkappaB, are activated by both molecules.” Michael and ApoNET partners, Henning Walczak (Imperial College London, UK) and Rainer Spang (University of Regensburg, Germany) need to establish the extent to which these signalling networks overlap. “We'd like to understand whether triggering the same downstream factors is a time-dependent effect,” adds Michael. “For example, could one of the ligands maybe activate downstream pathways earlier than the other or with a higher strength?”

“The way we look at it, “ says Michael, “'we won't only discover whether the cells die or not, but we will have a very fine-tuned description of what 's happening in the cells.” Modern sequencing methods allow researchers to assess the effects of knocking down specific genes on the entire genome of the cell. “Using next-generation sequencing (see Sequences within Cells) we measure the response of every gene within the cell after perturbation. Then we have to put the puzzle together using data modelling (see The Dominion of Data).”

Read other articles: