Integrating all the pieces for a big-picture view of infection
What makes an infectious disease like tuberculosis so difficult to eradicate? Ask a scientist, and the answer you get may depend on that person’s particular area of expertise. A microbiologist will tell you about a rod-shaped bacterium called Mycobacterium tuberculosis that infects the lungs and resists the efforts of immune system guardians that usually make short work of invaders. An epidemiologist will explain that the rise in HIV infections (which increase susceptibility to TB), along with the emergence of drug-resistant tuberculosis strains and inattention to control measures, has led to a worldwide resurgence of TB. Focusing down from that global view, a geneticist may talk about genetic differences that make certain people more susceptible than others, as well as Mycobacterium tuberculosis genes that affect its virulence.
In truth, all of these elements, as well as scores of other factors operating at different levels, over different time scales, all contribute and interact with one another. It’s is a big-picture problem—so big, in fact, that it’s nearly impossible to fully understand and explore through conventional means of observation and experimentation.
What’s needed is a multi-scale, system-wide approach, and that’s just what Denise Kirschner has been working to develop. Kirschner uses mathematical models and simulations, based on real-life observations and experiments, to probe complex interactions between disease-causing microbes and their hosts. This theoretical approach, which Kirschner and coworkers pioneered and which is now the focus of a National Institutes of Health initiative, generates predictions that can be tested with experiments. The results of those experiments then feed back to help refine the models and simulations.
In some cases, simulation makes it possible to do “experiments” that can't be done in the real world.
“We can run a simulation in five seconds that represents 200 years,” Kirschner says. This makes it possible to witness in a flash the effects of, say, administering a vaccine for 100 years.
“We’re not trying to replace experimental biologists,” Kirschner emphasizes. “We’re working together with them to combine and integrate information from different scales and reveal relationships that otherwise might not be detected.”
Although the goal of getting a fully fleshed out picture of any host-pathogen system from the genetic level to the global is still a distant prospect, Kirschner’s lab, partnering with experimental scientists, is making progress on many subsystems—integrating events at the molecular, cellular and tissue levels, for example.
“It's this kind of hand-in-hand cooperation between wet lab scientists and theoretical scientists,” says Kirschner, “that will really push science forward.”
