There's a widely accepted view that the genome is the computer program of life, and genes the software subroutines that code from DNA via RNA to proteins; and that like computers, when the software goes wrong bad things happen.
But biologists building computer models for testing drugs or pinning down the causes of disease say these metaphors are past their sell-by date. Instead, they're using computer models to try to see what effect different genes really have on our bodies.
A pioneer in this field, Denis Noble, codirector of computational physiology at Oxford University, has spent 47 years developing biological models. As a medical student in 1960 he developed the first viable mathematical model of a working heart cell, showing how it was possible to reproduce the heart's rhythm by modeling the changing electrical potential within it. Today, his heart cell models are so accurate that pharmaceutical companies use them to test for the effects of drugs on cardiac arrhythmia.
And the model shows effects you might not expect. For example, in Noble's heart cell model, if you remove the pacemaker gene protein -- first discovered in 1997 -- which generates 80 percent of the heart's electrical current, you might expect that the heart would stop or go haywire. In fact there is almost no change.
"The system is so robust that other mechanisms -- 40 or 50 other proteins -- ensure that if one fails the others can take over. It is beautifully failsafe," Noble says. "Nor can you conclude that if knocking out a gene has no observable effect it's not involved in a particular body function."
It takes all night on a computer with 18 processors to simulate one second of a complete beating heart, reconstructing the function down to the cellular level, so Noble is looking forward to having access to a 10-petaflop supercomputer -- the equivalent to about 5,000 consumer PCs -- being developed by Fujitsu. The machine is being designed to run simulations of complete human organ models in real time, including a whole organ heart model to be provided by Noble and his collaborators. Other teams are building multi-level computer models of all the other human organs as part of the Human Physiome Project.
Roche is one of the many pharmaceutical companies working with computer models from university groups such as Noble's, as well as using commercial mathematical modeling tools from companies such as MathWorks and Entelos.
Cristiano Migliorini, a modeling expert at Roche, suggests that biologists proposing new theories will soon submit computer models with their papers so that other scientists can re-use this knowledge.
"If someone publishes a good paper on a low-level mechanism in the liver, for instance, it would be great to be able to slot that software into a larger scale, higher-level liver model," he said.
Noble, meanwhile, has distilled his findings into "10 Commandments of Systems Biology." This list, in his paper in last October's issue of the Journal of Experimental Physiology, challenges popular perceptions about genes. Genes, Noble says, cannot be assigned specific functions; DNA is not the sole transmitter of inheritance; and there is no "genetic program." In fact there is no "program" at any level, including the brain.
Noble questions the "dogma of genetic determinism." The idea that it's rarely correct to attribute a function solely to one gene seems at odds with the headlines about discoveries of cancer genes, pacemaker genes, depression genes and so forth.
multifunctional
But as he explains: "The first function a gene is found to be involved in is rarely, if ever, the only one and may not be the most important one. The only unambiguous labeling of genes is in terms of the protein they code for."
The body's information doesn't only come from our genes, he argues: "There is also feedback to the genome from the cells, the tissues, the body as a whole and even from the environment. Genetic coding only tells us which protein a gene will make, it doesn't define how much of it."
The discovery of higher-level mechanisms that adjust how much protein a gene makes is a persuasive argument for a more integrated understanding of biology.
In the heart, for example, Noble says, "the ionic currents are so finely balanced during the slow phases of pacemaker activity that it is inconceivable that nature arrives at the correct expression and activity level without some kind of feedback control."
However "at present, we do not know the mechanism for this."
His money is on some form of gene marking (known as epigenetics) that controls gene expression and function during development.
DNA isn't the sole transmitter of inheritance because we also inherit the rest of the contents of our mother's egg cell.
"The information in the egg cell is vast," he says. "It's not just a messy soup, but highly structured with lipids, mitochondria, microtubules and lots of small molecules arranged in cellular compartments, much of which isn't coded for by genes."
Noble's views on inheritance are not mainstream. Marc Kirschner, chair of systems biology at Harvard Medical School and an admirer of Noble's work, says that while he can see Noble's point, it's likely to cause confusion.
"I think there is a danger in stating that in such strong terms," Kirschner says.
But he agrees that rather than describe the genome as a software program, we should think of it more like a database or library of information inside each cell that the cell can access.
The idea of a program doesn't fit with how the body works, Noble says.
cellular level
"If there is some program that, for instance, determines cardiac rhythm, it is not a separate [controlling] thing, it is the interaction between the cell proteins and the cell's electrical potential. It's not simply a genetic program -- the rhythm is created at the level of the cell as a whole. If you break the cell, you no longer have cardiac rhythm," he says.
One could argue that Noble's 10 Commandments are changing our perceptions rather than the facts, and yet the furore created by the geneticist James Watson's comments last year about the relationship between genes, intelligence and race shows that perception matters.
Noble says that Watson's remarks were an example of the "tendency of some biologists to imagine that phenomena at a higher level are simply correlated with the molecular structure of the genome and the proteins."
"It is a deeply flawed understanding because of the two-way interaction between organisms and the environment. It's not dealing with all the facts and deals with those we do have in a very partial way," he says.
Kirschner, although agreeing with the general thrust of Noble's views that this is the century of "putting it together again," sounds a note of caution.
"While many biologists recognize a need to take environment and systems thinking into account, they find it easy to follow the DNA paradigm because it has been, and continues to be, so productive," he says. "It would be a mistake to pit these two against each other. They are different ways to a common goal and of course we systems biologists make continuous use of reductionist methods and analysis."
So if you think you're just like a computer, it's time for a metaphor upgrade. And no, you can't blame absolutely everything on your genes.
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