Distributed Adaptive Search in T Cells: Lessons From Ants

Abstract

There are striking similarities between the strategies ant colonies use to forage for food and immune systems use to search for pathogens. Searchers (ants and cells) use the appropriate combination of random and directed motion, direct and indirect agent-agent interactions, and traversal of physical structures to solve search problems in a variety of environments. An effective immune response requires immune cells to search efficiently and effectively for diverse types of pathogens in different tissues and organs, just as different species of ants have evolved diverse search strategies to forage effectively for a variety of resources in a variety of habitats. Successful T cell search is required to initiate the adaptive immune response in lymph nodes and to eradicate pathogens at sites of infection in peripheral tissue. Ant search strategies suggest novel predictions about T cell search. In both systems, the distribution of targets in time and space determines the most effective search strategy. We hypothesize that the ability of searchers to sense and adapt to dynamic targets and environmental conditions enhances search effectiveness through adjustments to movement and communication patterns. We also suggest that random motion is a more important component of search strategies than is generally recognized. The behavior we observe in ants reveals general design principles and constraints that govern distributed adaptive search in a wide variety of complex systems, particularly the immune system.

Keywords: T cells; adaptive search; ant foraging; ant inspired algorithms; collective search.

Figure 1

Target distributions showing a range of clusteredness from a single pile of 1280 targets to 1280 targets distributed at uniform random. Each shows the number of piles and the number of targets per pile. The power law distribution has a mix of pile sizes with the number of piles inversely related to pile size.

Figure 2

The number of targets found in a 1 h simulation given different search strategies and target distributions (shown in Figure 1). For the most clustered distribution, pheromone recruitment to piles vastly outperforms random search (a CRW). The relative performance of pheromone recruitment compared to random search declines as targets are more dispersed. Site fidelity performs better than random search but not as well as pheromones in all of the clustered distributions. All strategies perform approximately equally for targets dispersed uniformly at random (1280 x 1). In the full CPFA, searchers choose whether to use random search, site fidelity or pheromone recruitment depending on the size of the piles they sense while searching. It is the most effective search strategy across all distributions, and it most clearly outperforms other strategies given intermediate pile numbers and sizes (e.g., 80 × 16) and the power law distribution which has mixed pile sizes.