IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v11y2020i1d10.1038_s41467-020-18224-y.html
   My bibliography  Save this article

Tunable multiphase dynamics of arginine and lysine liquid condensates

Author

Listed:
  • Rachel S. Fisher

    (CUNY Advanced Science Research Center)

  • Shana Elbaum-Garfinkle

    (CUNY Advanced Science Research Center
    City University of New York)

Abstract

Liquid phase separation into two or more coexisting phases has emerged as a new paradigm for understanding subcellular organization, prebiotic life, and the origins of disease. The design principles underlying biomolecular phase separation have the potential to drive the development of novel liquid-based organelles and therapeutics, however, an understanding of how individual molecules contribute to emergent material properties, and approaches to directly manipulate phase dynamics are lacking. Here, using microrheology, we demonstrate that droplets of poly-arginine coassembled with mono/polynucleotides have approximately 100 fold greater viscosity than comparable lysine droplets, both of which can be finer tuned by polymer length. We find that these amino acid-level differences can drive the formation of coexisting immiscible phases with tunable formation kinetics and can be further exploited to trigger the controlled release of droplet components. Together, this work provides a novel mechanism for leveraging sequence-level components in order to regulate droplet dynamics and multiphase coexistence.

Suggested Citation

  • Rachel S. Fisher & Shana Elbaum-Garfinkle, 2020. "Tunable multiphase dynamics of arginine and lysine liquid condensates," Nature Communications, Nature, vol. 11(1), pages 1-10, December.
  • Handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18224-y
    DOI: 10.1038/s41467-020-18224-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-020-18224-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-020-18224-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yuri Hong & Saeed Najafi & Thomas Casey & Joan-Emma Shea & Song-I Han & Dong Soo Hwang, 2022. "Hydrophobicity of arginine leads to reentrant liquid-liquid phase separation behaviors of arginine-rich proteins," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    2. Agustín Mangiarotti & Nannan Chen & Ziliang Zhao & Reinhard Lipowsky & Rumiana Dimova, 2023. "Wetting and complex remodeling of membranes by biomolecular condensates," Nature Communications, Nature, vol. 14(1), pages 1-15, December.
    3. Manisha Poudyal & Komal Patel & Laxmikant Gadhe & Ajay Singh Sawner & Pradeep Kadu & Debalina Datta & Semanti Mukherjee & Soumik Ray & Ambuja Navalkar & Siddhartha Maiti & Debdeep Chatterjee & Jyoti D, 2023. "Intermolecular interactions underlie protein/peptide phase separation irrespective of sequence and structure at crowded milieu," Nature Communications, Nature, vol. 14(1), pages 1-21, December.
    4. Ibraheem Alshareedah & Mahdi Muhammad Moosa & Matthew Pham & Davit A. Potoyan & Priya R. Banerjee, 2021. "Programmable viscoelasticity in protein-RNA condensates with disordered sticker-spacer polypeptides," Nature Communications, Nature, vol. 12(1), pages 1-14, December.
    5. Archishman Ghosh & Divya Kota & Huan-Xiang Zhou, 2021. "Shear relaxation governs fusion dynamics of biomolecular condensates," Nature Communications, Nature, vol. 12(1), pages 1-10, December.
    6. Dinesh Sundaravadivelu Devarajan & Jiahui Wang & Beata Szała-Mendyk & Shiv Rekhi & Arash Nikoubashman & Young C. Kim & Jeetain Mittal, 2024. "Sequence-dependent material properties of biomolecular condensates and their relation to dilute phase conformations," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
    7. Mofan Feng & Xiaoxi Wei & Xi Zheng & Liangjie Liu & Lin Lin & Manying Xia & Guang He & Yi Shi & Qing Lu, 2024. "Decoding Missense Variants by Incorporating Phase Separation via Machine Learning," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    8. Avigail Baruch Leshem & Sian Sloan-Dennison & Tlalit Massarano & Shavit Ben-David & Duncan Graham & Karen Faulds & Hugo E. Gottlieb & Jordan H. Chill & Ayala Lampel, 2023. "Biomolecular condensates formed by designer minimalistic peptides," Nature Communications, Nature, vol. 14(1), pages 1-11, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:11:y:2020:i:1:d:10.1038_s41467-020-18224-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.