Computer simulations shed light on how immune cells identify foreign antigens

June 7, 2013

How do immune cells manage to sort through vast numbers of similar-looking proteins within the body to detect foreign invaders and fight infections? McGill researchers used computational tools to examine what kind of solutions immune systems may use to detect small concentrations of foreign antigens (characteristic of potentially harmful infections) in a sea of "self-antigens" normally present at the surface of cells.

"For , singling out foreign proteins is like looking for a needle in a haystack – where the needle may look very much like a straw, and where some straws may also look very much like a needle," notes McGill University physics professor Paul François.

Understanding how immune cells tackle this formidable challenge is important, because it could provide crucial insights into the understanding of , from AIDS to auto-immune disorders.

In a study published May 21 in the journal Physical Review Letters, François and McGill graduate student Jean-Benoît Lalanne used to examine what kind of solutions immune systems may use to detect small concentrations of foreign antigens (characteristic of potentially harmful infections) in a sea of "self-antigens" normally present at the surface of cells.

The researchers' yielded a surprisingly simple solution related to the well-known phenomenon of biochemical adaptation – a general that enable organisms to cope with varying environmental conditions.

To find solutions, the computer uses an algorithm inspired by . This algorithm, designed previously within the François research group, randomly generates mathematical models of . It then scores them by comparing properties of these networks to predefined properties of the immune system. Networks with best scores are duplicated in the next generation and mutated, and the process is iterated over many simulated "generations" until networks reach a perfect score.

In this case, almost all solutions found were very similar, sharing a common core structure or motif.

"Our approach provides a simpler theoretical framework and understanding of what happens" as immune cells sort through the "haystack" to detect foreign antigens and trigger the immune response, François says. "Our model shares many similarities with real immune networks. Strikingly, the simplest evolved solution we found has both similar characteristics and some of the blind spots of real immune cells we studied in a previous collaborative study with the groups of Grégoire Altan-Bonnet (Memorial Sloane Kettering, New York), Eric Siggia (Rockefeller University, New York) and Massimo Vergassola (Pasteur Institute, Paris)."

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1 / 5 (2) Jun 08, 2013
Is it not true that 80% of the immune system is in the gut? If the immune system relies heavily upon the action of this bacterial ecology, and if these bacterial populations widely vary from one person to the next (as research seems to suggest), then what does it mean to computationally model the immune system?

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