Optimality in Self-Organized Molecular Sorting

Marco Zamparo, Donatella Valdembri, Guido Serini, Igor V. Kolokolov, Vladimir V. Lebedev, Luca Dall’Asta, and Andrea Gamba
Phys. Rev. Lett. 126, 088101 – Published 23 February 2021
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Abstract

We introduce a simple physical picture to explain the process of molecular sorting, whereby specific proteins are concentrated and distilled into submicrometric lipid vesicles in eukaryotic cells. To this purpose, we formulate a model based on the coupling of spontaneous molecular aggregation with vesicle nucleation. Its implications are studied by means of a phenomenological theory describing the diffusion of molecules toward multiple sorting centers that grow due to molecule absorption and are extracted when they reach a sufficiently large size. The predictions of the theory are compared with numerical simulations of a lattice-gas realization of the model and with experimental observations. The efficiency of the distillation process is found to be optimal for intermediate aggregation rates, where the density of sorted molecules is minimal and the process obeys simple scaling laws. Quantitative measures of endocytic sorting performed in primary endothelial cells are compatible with the hypothesis that these optimal conditions are realized in living cells.

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  • Received 22 November 2018
  • Accepted 25 January 2021

DOI:https://doi.org/10.1103/PhysRevLett.126.088101

© 2021 American Physical Society

Physics Subject Headings (PhySH)

Condensed Matter, Materials & Applied PhysicsInterdisciplinary PhysicsStatistical Physics & ThermodynamicsNonlinear DynamicsPhysics of Living SystemsPolymers & Soft Matter

Authors & Affiliations

Marco Zamparo1,2,*, Donatella Valdembri3,4,*, Guido Serini3,4,†, Igor V. Kolokolov5,6,‡, Vladimir V. Lebedev5,6,§, Luca Dall’Asta1,7,8,2,∥, and Andrea Gamba1,2,8,¶

  • 1Institute of Condensed Matter Physics and Complex Systems, Department of Applied Science and Technology, Politecnico di Torino, Corso Duca degli Abruzzi 24, 10129 Torino, Italy
  • 2Italian Institute for Genomic Medicine c/o Candiolo Cancer Institute, Fondazione del Piemonte per l’Oncologia (FPO), Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Candiolo, 10060 Torino, Italy
  • 3Department of Oncology, University of Torino School of Medicine, Candiolo, 10060 Torino, Italy
  • 4Candiolo Cancer Institute, Fondazione del Piemonte per l’Oncologia (FPO), Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS), Candiolo, 10060 Torino, Italy
  • 5L.D. Landau Institute for Theoretical Physics, 142432, Moscow Region, Chernogolovka, Ak. Semenova, 1-A, Russia
  • 6National Research University Higher School of Economics, 101000, Myasnitskaya 20, Moscow, Russia
  • 7Collegio Carlo Alberto, Piazza Arbarello 8, 10122 Torino, Italy
  • 8Istituto Nazionale di Fisica Nucleare (INFN), Italy

  • *These authors contributed equally to this work.
  • guido.serini@ircc.it
  • kolokol@itp.ac.ru
  • §lebede@itp.ac.ru
  • luca.dallasta@polito.it
  • andrea.gamba@polito.it

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Issue

Vol. 126, Iss. 8 — 26 February 2021

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