Protein compactness and interaction valency define the architecture of a biomolecular condensate across scales
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.
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.
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Further reading
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- Physics of Living Systems
Many proteins have been recently shown to undergo a process of phase separation that leads to the formation of biomolecular condensates. Intriguingly, it has been observed that some of these proteins form dense droplets of sizeable dimensions already below the critical concentration, which is the concentration at which phase separation occurs. To understand this phenomenon, which is not readily compatible with classical nucleation theory, we investigated the properties of the droplet size distributions as a function of protein concentration. We found that these distributions can be described by a scale-invariant log-normal function with an average that increases progressively as the concentration approaches the critical concentration from below. The results of this scaling analysis suggest the existence of a universal behaviour independent of the sequences and structures of the proteins undergoing phase separation. While we refrain from proposing a theoretical model here, we suggest that any model of protein phase separation should predict the scaling exponents that we reported here from the fitting of experimental measurements of droplet size distributions. Furthermore, based on these observations, we show that it is possible to use the scale invariance to estimate the critical concentration for protein phase separation.
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