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Biology subjects

Wiggins, L.

Publications and source records attributed to Wiggins, L..

3 recordsLinked to original sources

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↗

Exploring the impact of variability in cell segmentation and tracking approaches

Segmentation and tracking are essential preliminary steps in the analysis of almost all live cell imaging applications. Although the number of open-source software systems that facilitate automated segmentation and tracking continue to evolve, many researchers continue to opt for manual alternatives for samples that are not easily auto-segmented, tracing cell boundaries by hand and re-identifying cells on consecutive frames by eye. Such methods are subject to inter-user variability, introducing idiosyncrasies into the results of downstream analysis that are a result of subjectivity and individual expertise. Such methods are also susceptible to intra-user variability, meaning findings are challenging to reproduce. Here we demonstrate and quantify the degree of intra- and inter-user variability in manual cell segmentation and tracking by comparing the phenotypic metrics extracted from cells segmented and tracked by different members of our research team. Furthermore, we compare the segmentation results for a ptychographic cell image obtained using different automated software and demonstrate the high dependence of performance on their imaging modality optimisation. Our results show that choice of segmentation and tracking methods should be considered carefully in order to enhance the quality and reproducibility of results.

cell biology↗

Sodium accumulation in breast cancer predicts malignancy and treatment response

Breast cancer is the leading cause of cancer-related death in women worldwide. Development of novel noninvasive diagnostic and predictive pathophysiological biomarkers would represent a significant clinical improvement. Here, we explored the utility of non-invasive 23Na MRI to profile tumour physiology using preclinical mouse models of breast cancer. We establish that tissue Na+ concentration ([Na+]) is elevated vs non-tumour regions across multiple different tumour models. Ex vivo SBFI fluorescence imaging corroborated that this elevation in tumour [Na+] is due to increased intracellular [Na+]. Effective treatment with cytotoxic chemotherapy reduced tumour tissue [Na+], but was not detected by 1H diffusion-weighted imaging (DWI). Moreover, combining 23Na MRI and DWI measurements enabled superior classification accuracy of tumour vs non-tumour regions compared to either parameter alone. Quantification of breast tumour tissue [Na+] using 23Na MRI thus represents a novel, accurate, non-invasive diagnostic and predictive imaging biomarker.

cancer biology↗