Distributed Adaptive Search in T Cells: Lessons From Ants.


FULLTEXT
Published:
07.03.2019
|
Last Revised:
07.05.2019
PMID:
31263465
Frontiers in immunology
Journal Article,Review

Moses Biological Computation Laboratory, Department of Computer Science, University of New Mexico, Albuquerque, NM, United States.,Biology Department, University of New Mexico, Albuquerque, NM, United States.,Santa Fe Institute, Santa Fe, NM, United States.
The Cannon Laboratory, Department of Molecular Genetics & Microbiology, University of New Mexico School of Medicine, Albuquerque, NM, United States.,Department of Pathology, University of New Mexico School of Medicine, Albuquerque, NM, United States.,Autophagy, Inflammation, and Metabolism Center of Biomedical Research Excellence, University of New Mexico School of Medicine, Albuquerque, NM, United States.
Santa Fe Institute, Santa Fe, NM, United States.,Department of Biology, Stanford University, Stanford, CA, United States.
Santa Fe Institute, Santa Fe, NM, United States.,Biodesign Institute and School for Computing, Informatics, and Decision Sciences Engineering, Arizona State University, Tempe, AZ, United States.

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.

GrantID: P20 GM103452, Acronym: GM, Agency: NIGMS NIH HHS, Country: United States | GrantID: P20 GM121176, Acronym: GM, Agency: NIGMS NIH HHS, Country: United States | GrantID: P50 GM085273, Acronym: GM, Agency: NIGMS NIH HHS, Country: United States | GrantID: R01 AI097202, Acronym: AI, Agency: NIAID NIH HHS, Country: United States