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Spatiotemporal control of liquid crystal structure and dynamics through activity patterning

Nature Materials volume 20, pages 875–882 (2021)Cite this article

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Abstract

Active materials are capable of converting free energy into mechanical work to produce autonomous motion, and exhibit striking collective dynamics that biology relies on for essential functions. Controlling those dynamics and transport in synthetic systems has been particularly challenging. Here, we introduce the concept of spatially structured activity as a means of controlling and manipulating transport in active nematic liquid crystals consisting of actin filaments and light-sensitive myosin motors. Simulations and experiments are used to demonstrate that topological defects can be generated at will and then constrained to move along specified trajectories by inducing local stresses in an otherwise passive material. These results provide a foundation for the design of autonomous and reconfigurable microfluidic systems where transport is controlled by modulating activity with light.

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Fig. 1: Patterning activity in an actin liquid crystal leads to spatially confined flows and topological defects.
Fig. 2: Simulations of defect behaviour in a patterned active nematic.
Fig. 3: Simulations of defect-pair creation using activity pattern.
Fig. 4: Simulations of defect deflection by a rectangular activity pattern.
Fig. 5: Targeted activation can be used to direct defect trajectories in experiment and simulation.
Fig. 6: Simulations of defect pathway control in a channel system.

Data availability

All experimental image data are available on the Dryad server (https://doi.org/10.5061/dryad.7wm37pvr6). Additional data are available upon request.

Code availability

The custom analysis script used to make the histograms in Fig. 5 and Supplementary Fig. 9 is available at github.com/Gardel-lab.

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Acknowledgements

R.Z. and A.M. are grateful to The University of Chicago Research Computing Center for assistance with the calculations carried out in this work. This work is primarily supported by The University of Chicago Materials Research Science and Engineering Center, which is funded by the National Science Foundation (NSF) under award DMR-2011854. J.J.d.P. acknowledges support from NSF grant DMR-1710318. The calculations presented here were performed on the GPU cluster supported by the NSF under grant DMR-1828629. N.K. acknowledges the Yen Fellowship of the Institute for Biophysical Dynamics, The University of Chicago. Z.B. acknowledges support from NIH R01 GM114627 and a W. M. Keck Foundation grant to Z.B. and M. Prakash. M.L.G. acknowledges support from NSF Grant DMR-1905675 and NIH GM104032.

Author information

Author notes

  1. Rui Zhang

    Present address: Department of Physics, The Hong Kong University of Science and Technology, Hong Kong SAR, China

  2. These authors contributed equally: Rui Zhang, Steven A. Redford.

Authors and Affiliations

  1. Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, USA

    Rui Zhang, Ali Mozaffari, Margaret L. Gardel & Juan J. de Pablo

  2. The Graduate Program in Biophysical Sciences, The University of Chicago, Chicago, IL, USA

    Steven A. Redford

  3. James Franck Institute, The University of Chicago, Chicago, IL, USA

    Steven A. Redford, Nitin Kumar, Aaron R. Dinner, Vincenzo Vitelli & Margaret L. Gardel

  4. Department of Bioengineering, Stanford University, Stanford, CA, USA

    Paul V. Ruijgrok & Zev Bryant

  5. Department of Physics, Indian Institute of Technology Bombay, Mumbai, India

    Nitin Kumar

  6. Program in Biophysics, Stanford University, Stanford, CA, USA

    Sasha Zemsky

  7. Department of Chemistry, The University of Chicago, Chicago, IL, USA

    Aaron R. Dinner

  8. Department of Physics, The University of Chicago, Chicago, IL, USA

    Vincenzo Vitelli & Margaret L. Gardel

  9. Department of Structural Biology, Stanford University Medical Center, Stanford, CA, USA

    Zev Bryant

  10. Center for Molecular Engineering, Argonne National Laboratory, Lemont, IL, USA

    Juan J. de Pablo

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Contributions

R.Z., S.A.R., N.K., M.L.G. and J.J.d.P. conceived the research. R.Z. performed simulations with help from A.M.; S.A.R. performed experiments. P.V.R., S.Z. and Z.B. contributed novel reagents and expertise. R.Z. and S.A.R. performed data analysis. N.K., A.M., V.V. and A.R.D. contributed to analysis and interpretation. M.L.G. and J.J.d.P. supervised the research. R.Z., S.A.R., M.L.G. and J.J.d.P. wrote the manuscript. Everyone contributed to the discussion and manuscript revision.

Corresponding authors

Correspondence to Margaret L. Gardel or Juan J. de Pablo.

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Supplementary information

Supplementary Information

Supplementary Video legends 1–9, Figs. 1–10, Table 1 and discussion.

Supplementary Video 1

Active nematic with time varying activity. Time-lapse fluorescence images of liquid crystal with conditions detailed in Supplementary Table 1. To stimulate motor gear shifting, the sample was illuminated with a 491 nm laser across the entire field of view in addition to imaging wavelengths. Stimulated frames are indicated with ‘Light on' in the upper left-hand corner.

Supplementary Video 2

Active nematic with spatially varying activity. Time-lapse fluorescence images of liquid crystal with conditions detailed in Supplementary Table 1. To stimulate motor gear shifting in only one portion of the sample, a 470 nm LED was targeted to only the region outlined by the red box using a digital micromirror array for the duration of the video (see Methods).

Supplementary Video 3

Simulations of flat interface showing that a +½ defect (highlighted in a red circle) originally nucleated in an active region (red shadowed) and straying into a passive region is eventually attracted back to the active region.

Supplementary Video 4

Simulations of defect generation using a rectangular pattern. Two pairs of defects are generated, followed by complex motion, annihilation and regeneration of defects.

Supplementary Video 5

Simulations of defect generation using a triangular pattern. A single pair of defects arises from the asymmetric activity pattern.

Supplementary Video 6

Simulations of a pair of ±½ defects. Annihilation for uniform activity α/α0 = 0.2 showing that the +½ defect moves along its symmetry axis and eventually annihilates the −½ defect.

Supplementary Video 7

Active nematic with spatially directed defect motion. Time-lapse fluorescence images of liquid crystal with conditions detailed in Supplementary Table 1. To stimulate motor gear shifting a 470 nm LED was targeted to only the quarter-annulus region outlined in red using a digital micromirror array (see Methods). The defect centre is indicated with a blue dot while the tail indicates the defect path since the start of the experiment. Replicate 1.

Supplementary Video 8

Simulations show that the annulus pattern can constrain and guide the +½ defect, supporting the experimental observation that activity patterns can guide the defect.

Supplementary Video 9

Simulations of defect pathways in a ‘H' channel using two different activity patterns, showing that the activity pattern is able to guide defect pathways through a microfluidic device.

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Zhang, R., Redford, S.A., Ruijgrok, P.V. et al. Spatiotemporal control of liquid crystal structure and dynamics through activity patterning. Nat. Mater. 20, 875–882 (2021). https://doi.org/10.1038/s41563-020-00901-4

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