Active assembly and non-reciprocal dynamics of elastic membranes

Nature Physics (2026)Cite this article Equilibrium self-assembly and conventional materials processing techniques fall far short of mimicking dynamic self-actuating processes that are commonplace throughout biology. Here, to bridge the gap between living and synthetic matter, we study passive adhesive non-thermal actin fibres immersed in an active microtubule-based fluid. We show that autonomous chaotic flows power non-equilibrium fibre dynamics, thus inducing collisions, generating connections and weaving a membrane-like elastic network. The ensuing active assembly generates a hierarchy of shapes, structures and dynamical processes spanning nanometres to centimetres. Ultimately, it generates an active membrane that exhibits global limit cycles induced by a non-reciprocal coupling between deformations of the elastic membrane and the alignment axis of the nematic active fluid. Our work merges self-assembly with active matter to demonstrate self-processing materials wherein hierarchical life-like structures and dynamics emerge from an initially structureless suspension.This is a preview of subscription content, access via your institution Access Nature and 54 other Nature Portfolio journals Get Nature+, our best-value online-access subscription $32.99 / 30 days cancel any timeSubscribe to this journal Receive 12 print issues and online access $259.00 per yearonly $21.58 per issueBuy this articleUSD 39.95Prices may be subject to local taxes which are calculated during checkoutRepresentative data from this study are available via Zenodo at https://doi.org/10.5281/zenodo.17215226 (ref. 67). Source data are provided with this paper.The code used for data analysis is available via Zenodo at https://doi.org/10.5281/zenodo.17215226 (ref. 67).Cislo, D. J., Pavlopoulos, A. & Shraiman, B. I. ‘Morphogenetic action’ principle for 3D shape formation by the growth of thin sheets. Phys. Rev. X 15, 021068 (2025).

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The theoretical work was supported in part by the National Science Foundation through Grant No. PHY-2309135 to the Kavli Institute for Theoretical Physics (M.B.). V.V. and S.C. acknowledge partial support from the Army Research Office (Grant Nos. W911NF-22-2-0109 and W911NF-23-1-0212), the National Science Foundation through the Center for Living Systems (Grant No. 2317138), the National Institute for Theory and Mathematics in Biology, the Simons Foundation and the Chan Zuckerberg Foundation.These authors contributed equally: John Berezney, Sattvic Ray, Itamar Kolvin.Department of Physics, Brandeis University, Waltham, MA, USAJohn Berezney & Seth FradenDepartment of Physics, University of California at Santa Barbara, Santa Barbara, CA, USAJohn Berezney, Sattvic Ray, Fridtjof Brauns, Mark Bowick & Zvonimir DogicSchool of Physics, Georgia Institute of Technology, Atlanta, GA, USAItamar KolvinKavli Institute of Theoretical Physics, Santa Barbara, CA, USAFridtjof Brauns & Mark BowickLeinweber Institute for Theoretical Physics, University of Chicago, Chicago, IL, USASihan Chen & Vincenzo VitelliJames Frank Institute, University of Chicago, Chicago, IL, USASihan Chen & Vincenzo VitelliInterdisciplinary Program in Quantitative Biosciences, University of California, Santa Barbara, CA, USAZvonimir DogicSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarSearch author on:PubMed Google ScholarJ.B., S.R., I.K. and Z.D. conceptualized the work. J.B., S.R. and I.K. performed the experiments. J.B., S.R., I.K. and F.B. analysed the data. F.B., S.C., M.B. and V.V. developed the theoretical analysis. All authors contributed to the writing of the paper.Correspondence to Zvonimir Dogic.The authors declare no competing interests.Nature Physics thanks Jennifer Ross and Ishant Tiwari for their contribution to the peer review of this work. Peer reviewer reports are available.Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Theoretical model, experimental methods, Figs. 1–5, Videos 1–9 and video captions.Active MT fluid rearranges the passive actin network in the quasi-2D chamber. Preformed actin–fascin bundles (green) form anetwork and contract into a membrane under the influence of an active MT fluid (magenta). Rendering from a 3D imageacquired with a spinning-disc confocal microscope. Same conditions as in Fig 1a–e.Active assembly of actin–fascin bundles. Maximum intensity of the z-projection of actin–fascin bundles forming a networkunder the influence of active MT flows (1.5 μM actin, 0.5 μM fascin, active buffer 1). Same sample as in Fig. 2. The averagetranslation within the displayed region was removed to highlight network reconfiguration during periods of large in-planemotion.Actin assembly from very dilute preformed bundles. Active assembly generates a percolated actin network with a very largemesh size. Large deformations driven by the active fluid indicate that the percolated network lacks a finite elastic modulus andis floppy (1.0 μM actin, 0.33 μM fascin, active buffer 1).Active assembly of actin–fascin network from unbundled actin. The active fluid induces both bundling and network assembly. Inthe initial state, the sample consists of unbundled actin (1.5 μM actin, μM fascin, active buffer 2). Same sample as in Fig. 3.Height fluctuations of actin membrane. Top left: 3D rendering of segmented actin network. Colour indicates local height (samecolour bar as Supplementary Fig. 1a). Top right: reconstruction of the surface based on actin segmentation. Bottom: sideview of the actin membrane (x – z slice).Height fluctuations of actin membrane. Top left: 3D rendering of segmented actin network. Colour indicates local height (samecolour bar as Supplementary Fig. 1a). Top right: reconstruction of the surface based on actin segmentation. Bottom: sideview of the actin membrane (x – z slice).Macroscopic shear oscillations. System-sized shear oscillations emerge in the actin membrane (3.0 μM actin, 2.2 μM fascin,active buffer 2). Same sample as in Fig. 5a–c.Simulation of actin membrane oscillations. Velocity field (arrows) and vorticity (colour) showing self-excited waves in asimulation with w / ℓv−el = A = 1.6 and channel length L = 4w.Shear oscillations emerge in membranes above the critical width. Width dependence of system-sized shear oscillations (6.0 μMactin, 2.0 μM fascin, active buffer 1). Same sample as in Fig. 5e,f.Numerical source data for figure.Numerical source data for figure.Numerical source data for figure.Numerical source data for figure.Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.Reprints and permissionsBerezney, J., Ray, S., Kolvin, I. et al. Active assembly and non-reciprocal dynamics of elastic membranes. Nat. Phys. (2026). https://doi.org/10.1038/s41567-026-03215-5Download citationReceived: 10 October 2025Accepted: 09 February 2026Published: 02 April 2026Version of record: 02 April 2026DOI: https://doi.org/10.1038/s41567-026-03215-5Anyone you share the following link with will be able to read this content:Sorry, a shareable link is not currently available for this article. Provided by the Springer Nature SharedIt content-sharing initiative