Ron Germain: Towards a grand unified theory

At 15, Ron Germain cared for white mice kept on a ping-pong table in his basement. " You couldn't just buy inbred mice at the pet store, " he recalls, " but I had a connection. " With his C57BL/6 and A/J strains, he attempted to cure graft-versus-host disease with thymic transplants. His mother would supplement these experiments by driving him to Rockefeller University, where the young Germain snuck into seminars on immunology. And so it is little surprise that he's since risen through the ranks of T cell immunology, first at Harvard Medical School and later at the National Institutes of Health (NIH). He's helped elucidate the expression, structure, and function of MHC class II molecules, the cell biology of antigen processing, and the molecular basis of T cell recognition (1). Currently, he and his team peer into the dynamics of immune cell movement using two-photon microscopy, and construct mathematical models of T cell signaling and activation (2–4). In 2006, Germain spearheaded a systems immunology program at the National Institute of Allergy and Infectious Diseases (NIAID), which included the development of software to build and test complex models. More recently he's helped establish the Center for Human Immunology (CHI) at the NIH, an interdisciplinary effort with the goal of translating analyses of the human immune system into therapies for immune-mediated diseases. What strikes me about your papers, particularly one called " The Art of the Probable " (5), is your attention to overriding concepts and emergent properties in the immune system. It's true, I'm a conceptual person. I'm not so interested in ferreting out every little detail. I want to understand how things work in the larger sense. In my papers, I don't tend to report fi ve new trans-genics, three knockouts, and 82,000 blots. That's just not how I do science because getting data doesn't necessarily give you important answers. Sometimes I'm afraid we've failed to pay attention to how the immune system actually works. Too many things are described in these very black-and-white, linear ways—you do this and you get that. But that's not biological reality. And that was the point of " The Art of the Probable " —that there's more to things, like fl uctuating cells states and bi-stable conditions. How will immunologists handle the fl ood of raw data spewing forth from technological advances? Part of the trick will be to fi gure out …