Seeing around corners: cells solve mazes and respond at a distance using attractant breakdown

Tweedy, L., Thomason, P. A., Paschke, P. I., Martin, K., Machesky, L. M. , Zagnoni, M. and Insall, R. H. (2020) Seeing around corners: cells solve mazes and respond at a distance using attractant breakdown. Science, 369(6507), eaay9792. (doi: 10.1126/science.aay9792) (PMID:32855311)

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Introduction: Cells migrate over long distances during normal embryonic development and in disease, and they navigate through complex, branched paths. Chemotaxis, cell migration steered by gradients of attractive chemicals, is a central regulator of this behavior. Its sensitivity is limited by the responsiveness of attractant receptors. Simple chemotaxis is unable to guide cells over long distances and cannot resolve complexities and branches. Self-generated chemotaxis, a process in which cells create their own local, dynamic gradients by breaking down an attractant in their environment, is different. Gradients can be steeper because they are only made in the vicinity of the cells. They also work over long distances because they are remade locally as the cells migrate. Furthermore, self-generated gradients can follow complex paths because they are constantly generated by interactions between the cells and their environment. Rationale: The migration of cells through complex structures such as developing embryos or vascularized tumors involves both long distances and numerous decisions about which path to follow. Therefore, we examined chemotaxis in artificial complex environments, which are represented here by mazes. We predicted the pathfinding of cells in mazes using computational and mathematical modeling of self-generated gradients and tested the outcomes with real cells in microfluidic mazes. Results: We modeled cells as they navigated through various junctions between a connection to an attractant well and a dead end. We then tested the model’s predictions with cells that typically use long-range navigation: Dictyostelium discoideum cells (which find each other over large distances in the environment) and metastatic cancer cells (which spread around the human body). Both successfully solved a range of mazes, even remarkably complex ones (see figure), and could identify optimum paths. The results confirm that a model of self-generated chemotaxis captures all essential decision-making in these mazes: Cells broke down attractants locally, which were replenished at different, predictable rates by each possible path. The resulting local attractant gradients allowed cells to sense upcoming maze junctions before reaching them, even around corners, and to make correct decisions about paths they had not yet encountered. Attractant breakdown thus allowed cells to create a detailed picture of their surroundings. Real cell behavior closely agreed with the models for both rapidly moving D. discoideum and slower-moving pancreatic cancer cells, implying that the underlying conceptual model is an effective explanation of general cell behavior. In particular, the diffusivity of attractant, which is ignored by simple models, is crucial to cells’ responses. We simulated and then constructed “easy” and “hard” mazes, which appear similar but caused radically different pathfinding by cells. Finally, we designed maze geometries that passively created a temporary peak of attractant flux, deliberately misdirecting cells into a dead end and creating a chemotactic “mirage.” Conclusion: Self-generated chemoattractant gradients allow cells to navigate complex paths with great efficiency. Diffusion and attractant breakdown allow cells to obtain detailed information about their surroundings that could not be provided by simple attractant gradients. Cell migration in vivo cannot be understood without considering the interplay among cells, attractants, and the structure of the local environment. Microfluidic mazes are an excellent experimental system for studying these interactions.

Item Type:Articles
Glasgow Author(s) Enlighten ID:Insall, Professor Robert and Thomason, Dr Peter and Machesky, Professor Laura and Paschke, Dr Peggy
Authors: Tweedy, L., Thomason, P. A., Paschke, P. I., Martin, K., Machesky, L. M., Zagnoni, M., and Insall, R. H.
College/School:College of Medical Veterinary and Life Sciences > Institute of Cancer Sciences
Journal Name:Science
Publisher:American Association for the Advancement of Science
ISSN (Online):1095-9203
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Science 369(6507): eaay9792
Publisher Policy:Reproduced in accordance with the publisher copyright policy
Data DOI:10.5525/gla.researchdata.1029

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