Biology subjects

Gamill, M. C.

Publications and source records attributed to Gamill, M. C..

3 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↗

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↗