Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales
- University of Vienna, Austria
- Medical University of Vienna, Austria
- Russian Academy of Sciences, Russian Federation
Abstract
Non-membrane-bound biomolecular condensates have been proposed to represent an important mode of subcellular organization in diverse biological settings. However, the fundamental principles governing the spatial organization and dynamics of condensates at the atomistic level remain unclear. The S. cerevisiae Lge1 protein is required for histone H2B ubiquitination and its N-terminal intrinsically disordered fragment (Lge11-80) undergoes robust phase separation. This study connects single- and multi-chain all-atom molecular dynamics simulations of Lge11-80 with the in vitro behavior of Lge11-80 condensates. Analysis of modelled protein-protein interactions elucidates the key determinants of Lge11-80 condensate formation and links configurational entropy, valency and compactness of proteins inside the condensates. A newly derived analytical formalism, related to colloid fractal cluster formation, describes condensate architecture across length scales as a function of protein valency and compactness. In particular, the formalism provides an atomistically resolved model of Lge11-80 condensates on the scale of hundreds of nanometers starting from individual protein conformers captured in simulations. The simulation-derived fractal dimensions of condensates of Lge11-80 and its mutants agree with their in vitro morphologies. The presented framework enables a multiscale description of biomolecular condensates and embeds their study in a wider context of colloid self-organization.
Data availability
All data generated or analysed during this study are included in the manuscript and supporting files (Supplementary Files 1 and 2); source data files have been provided for Figure 2 (Figure 2 -source data 1), Figure 1-figure supplement 1 (Figure 1-figure supplement 1-source data 2), Figure 1-figure supplement 2 (Figure 1-figure supplement 2-source data 1), Figure 5-figure supplement 2 (Figure 5-figure supplement 2-source data 1); compressed folders containing source data files have been provided for Figure 1 (Figure 1 -source data 1), Figure 2 (Figure 2 -source data 2), Figure 3 (Figure 3 -source data 1), Figure 4 (Figure 4 -source data 1), Figure 5 (Figure 5 -source data 1), Figure 6 (Figure 6 -source data 1), Figure 1-figure supplement 1 (Figure 1-figure supplement 1-source data 1), Figure 2-figure supplement 1 (Figure 2-figure supplement 1-source data 1), Figure 3-figure supplement 1 (Figure 3-figure supplement 1-source data 1), Figure 4-figure supplement 1 (Figure 4-figure supplement 1-source data 1), Figure 6-figure supplement 1 (Figure 6-figure supplement 1-source data 1). These source files contain the numerical data used to generate the figures.
Article and author information
Author details
Funding
Austrian Science Fund (P 30550)
- Bojan Zagrovic
Austrian Science Fund (P 30680-B21)
- Bojan Zagrovic
NOMIS Stiftung (Pioneering Research Grant)
- Alwin Köhler
Austrian Science Fund (F79)
- Alwin Köhler
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Rohit V Pappu, Washington University in St Louis, United States
Version history
- Preprint posted: February 19, 2022 (view preprint)
- Received: May 6, 2022
- Accepted: July 18, 2023
- Accepted Manuscript published: July 20, 2023 (version 1)
- Version of Record published: August 7, 2023 (version 2)
- Version of Record updated: August 16, 2023 (version 3)
Copyright
© 2023, Polyansky et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 606
- Page views
-
- 126
- Downloads
-
- 1
- Citations
Article citation count generated by polling the highest count across the following sources: PubMed Central, Crossref, Scopus.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales
eLife 12:e80038.
https://doi.org/10.7554/eLife.80038
Further reading
-
- Neuroscience
- Physics of Living Systems
Olfactory navigation is observed across species and plays a crucial role in locating resources for survival. In the laboratory, understanding the behavioral strategies and neural circuits underlying odor-taxis requires a detailed understanding of the animal’s sensory environment. For small model organisms like Caenorhabditis elegans and larval Drosophila melanogaster, controlling and measuring the odor environment experienced by the animal can be challenging, especially for airborne odors, which are subject to subtle effects from airflow, temperature variation, and from the odor’s adhesion, adsorption, or reemission. Here, we present a method to control and measure airborne odor concentration in an arena compatible with an agar substrate. Our method allows continuous controlling and monitoring of the odor profile while imaging animal behavior. We construct stationary chemical landscapes in an odor flow chamber through spatially patterned odorized air. The odor concentration is measured with a spatially distributed array of digital gas sensors. Careful placement of the sensors allows the odor concentration across the arena to be continuously inferred in space and monitored through time. We use this approach to measure the odor concentration that each animal experiences as it undergoes chemotaxis behavior and report chemotaxis strategies for C. elegans and D. melanogaster larvae populations as they navigate spatial odor landscapes.
-
- Neuroscience
- Physics of Living Systems
Detailed descriptions of behavior provide critical insight into the structure and function of nervous systems. In Drosophila larvae and many other systems, short behavioral experiments have been successful in characterizing rapid responses to a range of stimuli at the population level. However, the lack of long-term continuous observation makes it difficult to dissect comprehensive behavioral dynamics of individual animals and how behavior (and therefore the nervous system) develops over time. To allow for long-term continuous observations in individual fly larvae, we have engineered a robotic instrument that automatically tracks and transports larvae throughout an arena. The flexibility and reliability of its design enables controlled stimulus delivery and continuous measurement over developmental time scales, yielding an unprecedented level of detailed locomotion data. We utilize the new system’s capabilities to perform continuous observation of exploratory search behavior over a duration of 6 hr with and without a thermal gradient present, and in a single larva for over 30 hr. Long-term free-roaming behavior and analogous short-term experiments show similar dynamics that take place at the beginning of each experiment. Finally, characterization of larval thermotaxis in individuals reveals a bimodal distribution in navigation efficiency, identifying distinct phenotypes that are obfuscated when only analyzing population averages.
