arXiv subjects

Filippo Conforto

Publications and source records attributed to Filippo Conforto.

4 recordsLinked to original sources

arXiv2026

Yeast condensin acts as a transient intermolecular crosslinker in entangled DNA

Structural-Maintenance-of-Chromosome (SMC) complexes such as condensins organise the folding of chromosomes. However, their role in modulating the entanglement of DNA and chromatin is not fully understood. To address this question, we perform single molecule and bulk characterisation of yeast condensin in entangled DNA. First, we discover that yeast condensin can proficiently bind double-stranded DNA through its hinge domain, in addition to its heads. Through bulk microrheology assays we then discover that physiological concentrations of yeast condensin increase both the viscosity and elasticity of dense solutions of lambda-DNA suggesting that condensin acts as a crosslinker in entangled DNA, stabilising entanglements rather than resolving them and contrasting the popular theoretical picture where SMCs purely drive the formation of segregated, bottle-brush-like chromosome structures. We further discover that the presence of ATP fluidifies the solution -- likely by activating loop extrusion -- but does not recover the viscosity measured in the absence of protein. Finally, we show that the observed rheology can be understood by modelling SMCs as transient crosslinkers in bottle-brush-like entangled polymers. Our findings help us to understand how SMCs affect the dynamics and entanglement of genomes.

cond-mat.soft↗

arXiv2025

Binding Kinetics Oppositely Regulates type II Topoisomerase Relaxation and Decatenation Activities

Type II Topoisomerases (topo II) are critical to simplify genome topology during transcription and replication. They identify topological problems and resolve them by passing a double-stranded DNA segment through a transient break in another segment. The precise mechanisms underpinning topo IIs ability to maintain a topologically simple genome are not fully understood. Here, we investigate how binding kinetics affects the resolution of two distinct forms of topological entanglement: decatenation and torsional relaxation. First, by single-molecule measurements, we quantify how monovalent cation concentration affects the dissociation rate of topo II from DNA. Second, we discover that increasing dissociation rates accelerate decatenation while slowing down relaxation catalytic activities. Finally, by using molecular dynamics simulations, we uncover that this opposite behaviour is due to a trade-off between search of target through facilitated diffusion and processivity of the enzyme in catenated versus supercoiled DNA. Thus, our findings reveal that a modulation of topo II binding kinetics can oppositely regulate its topological simplification activity, and in turn can have a significant impact in vivo.

physics.bio-ph↗

arXiv2024

Fluidification of Entangled Polymers by Loop Extrusion

Loop extrusion is one of the main processes shaping chromosome organisation across the cell cycle, yet its role in regulating DNA entanglement and nucleoplasm viscoelasticity remains overlooked. We simulate entangled solutions of linear polymers under the action of generic Loop Extruding Factors (LEF) with a model that fully accounts for topological constraints and LEF-DNA uncrossability. We discover that extrusion drives the formation of bottle-brush-like structures which significantly lower the entanglement and effective viscosity of the system through an active fluidification mechanism. Interestingly, this fluidification displays an optimum at one LEF every 300-3000 basepairs. In marked contrast with entangled linear chains, the viscosity of extruded chains scales linearly with polymer length, yielding up to 1000-fold fluidification. Our results illuminate how loop extrusion contributes to actively modulate genome entanglement and viscoelasticity in vivo.

cond-mat.soft↗

arXiv2023

Geometric Learning of Knot Topology

Knots are deeply entangled with every branch of science. One of the biggest open challenges in knot theory is to formalise a knot invariant that can unambiguously and efficiently distinguish any two knotted curves. Additionally, the conjecture that the geometrical embedding of a curve encodes information on its underlying topology is, albeit physically intuitive, far from proven. Here we attempt to tackle both these outstanding challenges by proposing a neural network (NN) approach that takes as input a geometric representation of a knotted curve and tries to make predictions of the curve's topology. Intriguingly, we discover that NNs trained with a so-called geometrical "local writhe" representation of a knot can distinguish curves that share one or many topological invariants and knot polynomials, such as mutant and composite knots, and can thus classify knotted curves more precisely than some knot polynomials. Additionally, we also show that our approach can be scaled up to classify all prime knots up to 10-crossings with more than 95\% accuracy. Finally, we show that our NNs can also be trained to solve knot localisation problems on open and closed curves. Our main discovery is that the pattern of "local writhe" is a potentially unique geometric signature of the underlying topology of a curve. We hope that our results will suggest new methods for quantifying generic entanglements in soft matter and even inform new topological invariants.

cond-mat.soft↗