Biology subjects

Catley, T. E.

Publications and source records attributed to Catley, T. E..

6 recordsLinked to original sources

bioRxiv2026

TRF2 mediates force-resistant bridging of distal telomeric DNA repeats

Shelterin binds telomeres, regulates telomere length, and protects chromosome ends from mis-repair, which is essential for genome stability. Telomere end-protection uniquely depends on the TRF2 subunit, which assembles telomeric DNA into a protective T-loop structure in vivo, yet the biochemical mechanism underlying this process remains unresolved. Using single-molecule optical tweezers and atomic force microscopy, we show that the human shelterin complex tethers distal telomeric DNA repeats, looping the intervening DNA. These bridges withstand tens of piconewtons of applied load, rupture at a force that scales with telomeric repeat number and re-form on relaxation. Structure-function analysis demonstrates that this force-resistant tethering is TRF2-dependent under our conditions and depends on multiple interfaces, with the TRFH domain making a major but non-exclusive contribution: introducing the TRF2 TRFH domain into TRF1 is sufficient to confer tethering, whereas its deletion from TRF2 reduces but does not abolish activity. We propose telomeric dsDNA tethering by TRF2 as a candidate first step in T-loop formation, preceding invasion of the telomeric 3' ssDNA overhang.

biophysics↗

bioRxiv2026

Deep Learning-Enhanced TopoStats for the Automated Quantification of DNA and Complex Biomolecular Structures

Atomic force microscopy (AFM) enables nanometre-scale, label-free imaging of biomolecules and surfaces under near-native conditions, yet quantitative analysis of AFM data remains limited compared to other bioimaging modalities. This limitation largely arises from the absence of open, automated tools capable of addressing AFM-specific artefacts, data formats, and topographical outputs. Here, we present the latest version of TopoStats, an open-source Python package for automated and quantitative AFM image analysis, developed as a deep-learning enabled advancement of our original TopoStats software to support more complex samples and richer molecular characterisation. The pipeline integrates all key processing stages, including image flattening and noise correction, object detection and segmentation, morphometric feature extraction, and strand tracing with topological classification. Designed for accessibility and reproducibility, TopoStats adheres to the FAIR for Research Software (FAIR4RS) principles and provides configurable workflows adaptable to diverse biological samples. Combining high-resolution AFM and our analysis pipeline allows the quantification of subtle structural changes within a heterogeneous sample set, revealing properties not accessible with other structural biology techniques. We demonstrate the effectiveness of our pipeline to differentiate between plasmids with both different topology and sequence, by extracting meaningful quantitative descriptors that distinguish the samples with statistical significance. Collectively, these developments establish TopoStats as a versatile framework for high-throughput, quantitative AFM analysis, advancing AFM from a fundamentally qualitative visualisation technique toward a quantitative analytical tool.

biophysics↗

bioRxiv2025

Imaging and mechanism of DNA-DNA recognition mediated by divalent ions

In the cell, DNA must be tightly packed to facilitate its organisation into the nucleus, where recognition of homologous sequences underpins key processes such as recombination. Yet the structural basis of DNA-DNA pairing remains unknown. Here we combine high-resolution AFM and atomistic MD simulations to provide the first direct visualisation of DNA pairing in the presence of divalent ions. We show that strongly paired DNAs often achieve groove-to-groove alignment, driven by ionic bridges connecting the minor grooves of the two duplexes. These contacts are further stabilized by sequence-specific interactions, whose strength and specificity vary with the ion type. This mechanism of ion-mediated groove alignment provides a molecular framework for the long-hypothesized "helical alignment" model, in which homologous recognition is facilitated by preserving structural register between the two helices. Together, our findings reveal a fundamental principle by which divalent ions promote DNA-DNA pairing, with broad implications for chromosomal condensation and genome organization.

biophysics↗

bioRxiv2025

Cytosolic DNA structures produced by mismatch-repair deficiency coordinate anti-tumor immunity in colorectal cancer

Patients with the microsatellite instable (MSI) subtype of colorectal cancer (CRC) have better prognosis and immunotherapy response than patients with the chromosomally instable (CIN) subtype due to improved cytotoxic T cell responses from high neoantigen levels and production of the chemokines CXCL10 and CCL5 that recruit cytotoxic T cells. This high chemokine production in MSI CRCs is due to constitutive activation of the cytosolic DNA (cyDNA) sensor STING by specific features of MSI cyDNA that lead to more effective STING pathway activation. Here, we investigate the features of MSI and CIN cyDNA to identify structures that more effectively activate STING. We find that MSI cyDNA is enriched in G-quadruplexes which improve STING and CD8+ T cell activation. Additionally, MSI micronuclei are also more efficient at inducing chemokine expression than CIN micronuclei. However, micronuclei are less effective than free cyDNA at inducing anti-tumor immunity and instead lead to increased Treg activation and IL10 production. Overall, these data highlight the role of specific cyDNA structures in anti-tumor immunity and provide essential knowledge for improved design of therapeutic DNA-based STING agonists that could be combined with immune checkpoint therapies to improve the prognosis of poorly immunogenic tumors like CIN CRCs.

cancer biology↗

bioRxiv2024

Multiscale topological analysis of kinetoplast DNA via high-resolution AFM

Kinetoplast DNA is a complex nanoscale network, naturally assembled from thousands of interconnected DNA circles within the mitochondrion of certain parasites. Despite the relevance of this molecule to parasitology and the recent discovery of tuneable mechanics, its topology remains highly contested. Here we present a multiscale analysis into the structure of kDNA using a combination of high-resolution atomic force microscopy and custom-designed image analysis protocols. By capturing a notably large set of high-resolution images, we are able to look beyond individual kDNA variations and quantify population properties throughout several length scales. Within the sample, geometric fluctuations of area and mean curvature are observed, corresponding with previous in-vitro measurements. These translate to localised variations in density, with a sample-wide decrease in DNA density from the outer rim of the molecule to the centre and an increase in pore size. Nodes were investigated in a single molecule study, and their estimated connectivity significantly exceeded mean valence, with a high dependence on their position in the network. While node separation was approximately half the minicircle circumference, it followed a strong bimodal distribution, suggesting more complex underlying behaviour. Finally, upon selective digestion of the network, breakdown of the fibril-cap heterogeneity was observed, with molecules expanding less upon immobilisation on the mica surface. Additionally, selective digestion was seen in localised areas of the network, increasing pore size disproportionately. Overall, the combination of high-resolution AFM and single molecule image analysis provides a promising method to the continued investigation of complex nanoscale structures. These findings support the ongoing characterisation of kDNA topology to aid understanding of its biological and mechanical phenomena.

biophysics↗

bioRxiv2024

Under or Over? Tracing Complex DNA Topologies with High-Resolution Atomic Force Microscopy

The topology of DNA plays a crucial role in the regulation of cellular processes and genome stability. Despite its significance, DNA topology remains challenging to determine due to the length and conformational complexity of individual topologically constrained DNA molecules. We demonstrate unparalleled resolution of complex DNA topologies using Atomic Force Microscopy (AFM) in aqueous conditions. We present a new high-throughput automated pipeline to determine DNA topology from raw AFM images, using deep-learning methods to trace the backbone of individual DNA molecules and identify crossing points. Our pipeline efficiently determines which segment passes over which, including the handling of challenging crossings, where the path of each molecule may be harder to resolve. We demonstrate the wider applicability of our tracing method by determining the structure of stalled replication intermediates from Xenopus egg extracts, including theta structures and late replication products. By developing new methodologies to accurately trace the DNA path through every crossing, we determine the topology of plasmids, knots and catenanes from the E. coli Xer recombination system. In doing so we uncover a recurrent depositional effect and reveal its origins using coarse-grained simulations. Our approach is broadly applicable to a range of nucleic acid structures, including those which interact with proteins, and opens avenues for understanding fundamental biological processes which are regulated by or affect DNA topology.

biophysics↗