Cells Executing Sophisticated Search Strategies (and How Our Physicist Friends Helped Us Learn About It)

In studying and analyzing the computational feats of living organisms, we will learn how networks that are far more sophisticated than our own operate to solve problems.
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In my ongoing effort to emphasize the cognitive capabilities of cells, this blog describes two examples of highly sophisticated searching behavior by very different kinds of cells. At the same time, I want to discuss the bewildering resistance of at least one conventional evolutionist to additional researchers coming in from other fields to help unravel biological phenomena. The two subjects are connected because cooperation with scientists trained in other disciplines was critical to revealing sophisticated cell search capacities in both examples.

In his "Sandwalk" blog last year, Larry Moran attempted to make fun of my enthusiasm for physicists bringing their skills and insights into biology:

"Meanwhile, I welcome all those physicists who know nothing about evolution, protein structure, genetics, physiology, metabolism and ecology. That's just what we need in the biological sciences to go along with all the contributions made by equally ignorant creationists."

Moran's dated sarcasm equating physicists with creationists was pointed out to me by a friend who also sent a link to a recent news story about how T cells hunt down Toxoplasma gondii parasites in infected mice.

The ScienceDaily story referred to a Nature paper published this week by a group that involved "... a unique collaboration between the laboratories of senior authors Christopher Hunter, professor and chair of the Pathobiology Department in Penn's School of Veterinary Medicine, and Andrea Liu, the Hepburn Professor of Physics in the Department of Physics and Astronomy. Penn Vet postdoctoral researcher Tajie Harris and physics graduate student Edward Banigan also played leading roles in the research."

The physicists used their analytical skills to identify the T cell search strategy as a "generalized Lévy walk" partially guided by chemokine signals. This was not something the biologists could have learned on their own.

The T-cell results are especially important because they show that single cells display a search ability that parallels one used by multicellular organisms with nervous systems. The authors write in their summary: "... CD8+ T-cell behaviour is similar to Lévy strategies reported in organisms ranging from mussels to marine predators and monkeys, and CXCL10 aids T cells in shortening the average time taken to find rare targets."

The T cell case is not isolated. An increasingly famous example of sophistication in cell migration and search behavior is the study of slime mold Physarum polycephalum amoebae migrating through mazes.

The slime mold work was done not in a biological institution but by Toshiyuki Nakagaki and his colleagues at the Research Institute for Electronic Science, Hokkaido University, Sapporo, Japan.

Condensed matter physics statistical analysis has been central to this research, and
the slime mold solutions have proved superior to mathematically-derived search patterns. As the researchers wrote in a 2004 article:

"Statistical analysis showed that the network geometry met the multiple requirements of a smart network: short total length of tubes, close connections among all the branches (a small number of transit food-sites between any two food-sites) and tolerance of accidental disconnection of the tubes. These findings indicate that the plasmodium can achieve a better solution to the problem of network configuration than is provided by the shortest connection of Steiner's minimum."

Among the behaviours documented by Nakagki and colleagues are maze-solving to find the minimum path for access to nutrients and anticipation of periodic depletion of nutrients.

The Physarum solutions have even been applied recently to optimizing railroad traffic (reported in 2011). The use of biomimetic methods to find superior algorithms for traffic control illustrates how biology can contribute to mathematics, the physical and computational sciences.

In studying and analyzing the computational feats of living organisms, we will learn how networks that are far more sophisticated than our own operate to solve problems. We need the help of physicists and mathematicians to do that. Why would anyone serious about understanding how life really operates want to exclude them?

As I said in my book, we can expect new information science to arise from studying cells and evolution. I'm surprised that Larry Moran did not choose that prediction to ridicule. Maybe he found it too fantastical for his highly critical attention. Or perhaps he saw that goal as incompatible with his vision of evolution science, which seems to be to keep things just as they are.

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