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Collective migration reveals mechanical flexibility of malaria parasites


Plasmodium sporozoites are the crescent-shaped forms of malaria parasites injected from the salivary glands of mosquitoes into the skins of their vertebrate hosts. To proceed towards the liver of the host, sporozoites individually migrate at very high speeds and with relatively few adhesive interactions. By contrast, in the mosquito sporozoites often exist as collectives. Here we study their motion in collectives extracted from salivary glands, a situation in which dozens of sporozoites form rotating vortices. Complementing our experiments with quantitative image analysis and agent-based computer simulations, we find that, owing to their mechanical flexibility, single sporozoites are sorted according to their curvatures and speeds, and that these effects increase with vortex size. We also find that the vortices undergo oscillatory breathing because the thrust from the motility force of the single sporozoites can be stored in their elastic energy. Our findings suggest that the malaria parasite has evolved flexibility as an essential means to adapt to its mechanical environment and to ensure efficient transmission. In general, our work demonstrates how single-particle shape and mechanics can determine the dynamics of large, active collectives.

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Fig. 1: Collectives of malaria parasites form rotating vortices.
Fig. 2: Quantitative image analysis reveals unexpected speed distributions.
Fig. 3: Agent-based computer simulations explain experimentally observed features by self-sorting.
Fig. 4: Simulations predict sporozoite self-sorting in rotating vortices.
Fig. 5: Mechanism of vortex size fluctuations.

Data availability

All data necessary to reproduce Figs. 2–5 are available via Zenodo at Source data are provided with this paper.

Code availability

Custom codes that were used to analyse experimental data within this manuscript are available from the corresponding authors upon reasonable request. Python scripts to generate the plots in the figures are available via Zenodo at Our code for the agent-based computer simulations is available via GitHub at


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We thank J. Ripp, M. Singer, S. Rossberger, H. Böhm, J. Spatz, C. Haubold and F. Hamprecht for stimulating discussions. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) through SFB 1129 (Projektnummer 240245660). P.P. acknowledges funding through an interdisciplinary postdoctoral fellowship of the cluster of excellence CellNetworks. U.S.S. is a member of the Interdisciplinary Center for Scientific Computing (IWR) at Heidelberg. F.F. and U.S.S. were supported by the Marsilius-Kolleg of Heidelberg University.

Author information

Authors and Affiliations



P.P. and A.B. wrote the simulation code. P.P. performed the simulations and analysed the experimental data. K.B. performed the experiments. A.J. and K.R. performed the image analysis. F.F. and U.S.S. designed and supervised the project. P.P., F.F. and U.S.S. wrote the manuscript. All authors approved the manuscript.

Corresponding authors

Correspondence to Friedrich Frischknecht or Ulrich S. Schwarz.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics statement

All animal experiments were performed according to European guidelines and regulations and the German Animal Welfare Act (Tierschutzgesetz) and executed following the guidelines of the Society of Laboratory Animal Science (GV-SOLAS) and of the Federation of European Laboratory Animal Science Associations (FELASA). All experiments were approved by the responsible German authorities (Regierungspräsidium Karlsruhe).

Peer review

Peer review information

Nature Physics thanks Isabelle Tardieux, Daria Bonazzi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–6 and Sections A–E.

Supplementary Video 1

Video for data presented in Fig. 1b.

Supplementary Video 2

Video for data presented in Fig. 1d,e.

Supplementary Video 3

Video for data presented in Fig. 1f–i.

Supplementary Video 4

Videos of vortex formation from isolated sporozoites and the merging of two small vortices.

Supplementary Video 5

Videos of experimental vortices.

Supplementary Video 6

Video of simulation with identical sporozoites.

Supplementary Video 7

ad, Videos of simulations showing vortex formation from isolated sporozoites (a), a merger of two vortices (b), vortex re-organization in the presence of a repulsion zone (c) and splitting of a large vortex (d).

Supplementary Video 8

Video for data presented in Fig. 3.

Supplementary Video 9

Video for data presented in Fig. 4a,b.

Supplementary Video 10

Video for data presented in Fig. 4c.

Supplementary Video 11

Video for data presented in Fig. 5b,c.

Supplementary Video 12

Video of simulation of an isolated vortex with a rigid obstacle at the core.

Source data

Source Data Fig. 2

Zip file with all relevant data files for Fig. 2, together with the python script to plot it.

Source Data Fig. 3

Zip file with all relevant data files for Fig. 3, together with the python script to plot it.

Source Data Fig. 4

Zip file with all relevant data files for Fig. 4, together with the python script to plot it.

Source Data Fig. 5

Zip file with all relevant data files for Fig. 5, together with the python script to plot it.

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Patra, P., Beyer, K., Jaiswal, A. et al. Collective migration reveals mechanical flexibility of malaria parasites. Nat. Phys. 18, 586–594 (2022).

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