Collective motion conceals fitness differences in crowded cellular populations

Abstract

Many cellular populations are tightly packed, such as microbial colonies and biofilms, or tissues and tumours in multicellular organisms. The movement of one cell in these crowded assemblages requires motion of others, so that cell displacements are correlated over many cell diameters. Whenever movement is important for survival or growth, these correlated rearrangements could couple the evolutionary fate of different lineages. However, little is known about the interplay between mechanical forces and evolution in dense cellular populations. Here, by tracking slower-growing clones at the expanding edge of yeast colonies, we show that the collective motion of cells prevents costly mutations from being weeded out rapidly. Joint pushing by neighbouring cells generates correlated movements that suppress the differential displacements required for selection to act. This mechanical screening of fitness differences allows slower-growing mutants to leave more descendants than expected under non-mechanical models, thereby increasing their chance for evolutionary rescue. Our work suggests that, in crowded populations, cells cooperate with surrounding neighbours through inevitable mechanical interactions. This effect has to be considered when predicting evolutionary outcomes, such as the emergence of drug resistance or cancer evolution.

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Fig. 1: Slower-growing clones persist at the front of expanding yeast colonies.
Fig. 2: Delayed extinction can be described via an effective surface tension.
Fig. 3: Effective surface tension emerges in mechanical simulations from purely physical cell–cell interactions.
Fig. 4: Slow purging of costly drug-resistant mutations can lead to resurgent growth on drug application.
Fig. 5: Fitness screening affects faster-growing mutants and is independent of cell morphology.

Data availability

Imaging data used in this study are available at https://figshare.com/projects/Kayser2018_NatEE/55727.

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Acknowledgements

Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award R01GM115851, a National Science Foundation CAREER Award (#1555330), a Simons Investigator award from the Simons Foundation (#327934), the National Energy Research Scientific Computing Center, a US Department of Energy Office of Science User Facility operated under contract number DE-AC02-05CH11231, and the Berkeley Research Computing programme at the University of California, Berkeley. J.K. acknowledges a research scholarship (KA 4486/1-1) awarded by the German Research Foundation. The authors thank B. Good, J. Paulose, M.-C. Duvernoy and S. Martis for vital discussions, and the group of J. Rine for invaluable insights on yeast genetics.

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Contributions

J.K., C.F.S. and O.H. conceived and designed the study. J.K. and M.G. carried out and analysed the experiments. C.F.S., M.G., D.F. and J.K. performed and evaluated the simulations. J.K., C.F.S., M.G., D.F. and O.H. discussed and interpreted the results. J.K., C.F.S. and O.H. wrote the manuscript.

Corresponding author

Correspondence to Oskar Hallatschek.

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Supplementary information

Supplementary Information

Supplementary Text, Video Legends and Fig. 1–21.

Reporting Summary

Supplementary Video 1

Time lapse series of a shrinking wide-mutant sector in a linear front.

Supplementary Video 2

Simulation of a shrinking mutant clone.

Supplementary Video 3

Single cell tracking at a moderately curved front.

Supplementary Video 4

Single cell tracking at a highly curved front.

Supplementary Video 5

Single cell tracking of front cells starting at birth.

Supplementary Video 6

Simulation of expanding, budding yeast cell population.

Supplementary Video 7

Fate of a slower growing clone after expulsion from the front.

Supplementary Video 8

Resurgent growth of a persisting mutant sector after drug application.

Supplementary Video 9

Single cell tracking at the mutant–wild-type boundary.

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Kayser, J., Schreck, C.F., Gralka, M. et al. Collective motion conceals fitness differences in crowded cellular populations. Nat Ecol Evol 3, 125–134 (2019). https://doi.org/10.1038/s41559-018-0734-9

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