July 21, 2009 | David F. Coppedge

Systems Biology Oddly Silent About Darwin

Two papers on the rise of “systems biology” appeared in Nature last week.  Both are astounded by the complexity of the cell, but neither had anything to say about evolution, Darwin, or phylogeny – mildly surprising when the proponents of evolution keep saying that “nothing in biology makes sense except in the light of evolution.”
    Systems biology tries to take a holistic view of the cell as a system.  It considers the networks of interactions between genes and proteins.  Nathan Blow, in his article about emerging technologies for the study of cell interactions,1 showed diagrams that are stunning in their complexity.  The known protein interactions look something like a galaxy.  Even the pathway maps that simplify the interactions look like detailed flowcharts for a city.  The caption says, “Pathway maps illustrate the complexity of cellular interactions.”  One technology company, Plectix, has come up with a computer model called Cellucidate that carries the analogy further:

“The system is represented at a very granular level where the participants are allowed to do in silico what they would do in real life,” says Paul Edwards, chief executive at Plectix.  Imagine the city-building computer game SimCity reworked for complex cellular networks, but here the agents of the cell – proteins and other molecules – are the automata instead of colourful animated people.  “In that way the model mirrors the behaviour of the living system it represents: the biology that emerges from our models is the combinatorial expression of all these automata doing their own little thing – just the way it is in the cell,” says Gordon Webster, vice-president of biology at Plectix.

Even that model, however, is not the whole story.  What are the dynamics behind those interactions?  Why are the little people going where they go, and interacting the way they do?  Blow writes, “To understand the dynamics of the information flow in cells, researchers not only need more knowledge of protein�protein interaction networks, but they also need to understand protein�DNA interactions, the effects of microRNAs and epigenetic changes on gene expression, and how other macromolecules such as metabolites affect the output of signalling networks.”  The system as a whole determines the output.  It sounds like systems biology has a long way to go.
    A notable phrase in the articles is information flow.  Protein interaction (proteomics) involves complex feedback loops and regulatory processes.  It becomes quite a trick to follow the information.  Blow writes, “it’s clear that scientists might be on the cusp of changing the way they look at signalling and information flow in cells.”  The genetic information in DNA is just a static blueprint, “whereas proteomics is much closer to what is going on in the cell, a molecular manifestation of a phenotype,” Mike Snyder [Yale] said.  How much information is there to keep track of?  “At the moment, GeneGo employs 50 scientists to manually mine and curate published literature for studies on protein interaction, gene expression, metabolism and drugs to expand and update its internal database, which now contains more than 120,000 multi-step interaction pathways, each averaging 11 steps, with information on direction, mechanism and feedback along the pathways, along with direct links to literature evidence.”
    It will take a lot of brain and computer processing power to capture the information flow going on inside a single cell.  Maybe that’s why Nathan Blow ended with these comments:

But when it comes to figuring out the best way to explore information flow in cells, [Mike] Tyers [U of Edinburgh] jokes that it is like comparing different degrees of infinity.  “The interesting point coming out of all these studies is how complex these systems are – the different feedback loops and how they cross-regulate each other and adapt to perturbations are only just becoming apparent,” he says.  “The simple pathway models are a gross oversimplification of what is actually happening.
    Paul Nurse of Rockefeller University in New York wrote about understanding the cell’s information flow last year.  He noted that “our past successes have led us to underestimate the complexity of living organisms”, an oversight that is rapidly disappearing within the world of systems biology and will probably never happen again.

In the second article,2 Nathan Blow described one attempt to elucidate (using Cellucidate) just one protein pathway:

When researchers at Plectix BioSystems in Somerville, Massachusetts, began to use their new Cellucidate software to model the epidermal growth factor receptor pathway, they calculated that there were 1033 potential states – including all protein complexes and phosphorylation states – for the system.  “This is the kind of complexity that scientists have to grapple with when it comes to cell-signalling networks,” says Gordon Webster, vice-president of biology at Plectix.

Those are the potential interactions, of course, not all the ones actually encountered in life.  The challenge is to figure out the interactions that cells use, and what rules they follow.  Researchers in systems biology are looking for the “gold standard” measure of protein interactions.  These efforts are “providing a gold mine for people to dig into.”


1.  Nathan Blow, “Systems biology: Untangling the protein web,” Nature 460, 415-418 (16 July 2009) | doi:10.1038/460415a.
2.  Nathan Blow, “Systems biology: Playing by the rules,” Nature 460, 417 (16 July 2009) | doi:10.1038/460417a.

There are people in the gold mine already, and they don’t take kindly to claim jumpers.  They’re the intelligent design people.  No Darwinist freeloaders allowed.
    Signaling networks, pathways, feedback loops, combinatorial expression, multi-step interaction pathways, robustness to perturbations, cross-regulation, exceptional complexity, information flow – this is the new language of biology.  Nothing in biology will hereafter make sense except in the light of information and design.  Poor Charlie is like the has-been performer nobody goes to see any more, except for his loyal honor guard who demand that we buy tickets and watch his moonwalk whether we like it or not (07/04/2009 commentary). 

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