bioRxiv Science⌕ Search

Biology subjects

Lazarova, E.

Publications and source records attributed to Lazarova, E..

2 recordsLinked to original sources

Nuclear RNA forms an interconnected network of transcription-dependent and tunable microgels

Living cells are organised through active, non-equilibrium processes, yet the physical principles governing their material states remain unclear. The cell nucleus has been described as either fluid-like or solid-like, but these behaviours have not been reconciled within a single framework. Here we show that nascent RNA and the multivalent RNA-binding protein SAF-A assemble into a nucleus-spanning microgel network maintained near the sol-gel transition. This active network exhibits scale- and time-dependent viscoelasticity and naturally reconciles solid-like and fluid-like responses. By integrating super-resolution imaging with mechanistic polymer modelling, we identify RNA production and degradation as control parameters that tune network connectivity. The model predicts enhanced susceptibility to modest perturbations near criticality, which we confirm experimentally by shifting the system between sol-like and gel-like regimes. Measurements of molecular transport, combined with simulations, reveal size-dependent diffusion and transient trapping within gel pores, establishing direct physical consequences of the near-critical state. Our results identify RNA metabolism as an energy-driven regulator of nuclear material properties and position the nucleus as a living example of an active microgel poised near criticality.

molecular biology↗

SuperStructure: a Parameter-Free Super-Structure Identifier for SMLM Data

Single-Molecule Localisation Microscopy (SMLM) allows the quantitative mapping of molecules at high resolution. However, understanding the non-random interaction of proteins requires the identification of more complex patterns than those typified by standard clustering tools. Here we introduce SuperStructure, a parameter-free algorithm to quantify structures made of inter-connected clusters, such as protein gels. SuperStructure works without a priori assumptions and is thus an ideal methodology for standardised analysis of SMLM data.

bioinformatics↗