Biology subjects

Dunsby, C.

Publications and source records attributed to Dunsby, C..

17 recordsLinked to original sources

bioRxiv2026

Multi-Site Reproducibility Study of 3D High-Content Analysis with Dual-View Oblique Plane Microscopy

High content imaging is being applied to achieve quantitative fluorescence readouts in increasingly complex 3-dimensional (3D) cell culture models such as spheroids and organoids. Compared to conventional 2D assays, 3D assays better represent biological heterogeneity but require more complex sample preparation, 3D imaging and 3D image analysis that can affect the accuracy and precision of such assays. We used spheroids formed from the NRAS-activated melanoma cell line 19161 modified to express an ERK kinase translocation reporter (KTR) as an exemplar 3D phenotypic assay carried out in 96-well plates. The spheroids were treated with the ERK activator TPA and a range of concentrations of the MEK inhibitor Binimetinib. 3D live-cell imaging with sub-cellular spatial resolution was performed using a dual-view oblique plane microscope (dOPM) - a form of single-objective light-sheet microscope - and the experiment was performed separately at 4 different institutes. The results were analysed using an identical 3D analysis pipeline and parameters. We assessed the variation in assay readout using a linear mixed effects model. Random variance at the well level was negligible (SD = 0.0048 relative to range of KTR biosensor readout at reference site of 0.17), indicating low technical noise. Treatment effects were dose-dependent and highly statistically significant compared to DMSO control across all sites (Dunnett-corrected p < 0.001). The range in KTR readout between the minimum (3.5 M Binimetinib) and maximum (100 nM TPA) treatments varied between 59 to 96% relative to the reference site. Measured bias in KTR readout between sites was between 6 and 12% of the range of the reference site. This study quantifies the reproducibility of a 3D live spheroid-based assay employing a fluorescence biosensor requiring readout out at the per-cell level using the dOPM platform and discusses areas where experimental protocol could be improved in the future to further improve reproducibility.

bioengineering↗

bioRxiv2025

Multimodal profiling unveils a reversible basal-like breast cancer cell state resistant to AKT inhibition

The PI3K/AKT/mTOR pathway is central to cell metabolism and growth. However, pharmacological inhibition of the pathway is not uniformly effective across cancer types, or even within a single cancer model. In this study, we leverage oblique plane microscopy of triple negative breast cancer organoids, as well as lineage tracing to uncover a source of heterogeneity. Non-genetic resistance to AKT inhibition is associated with basal cell features of normal breast epithelium and the master transcription factor of basal cell state, {Delta}Np63, is sufficient to confer resistance. Cells can transition between states within four weeks and therefore, AKT inhibition only delays tumour growth, with tumours rich in KRT14+ cells resulting. Thus, under selection, triple negative breast cancer exploits a repertoire of cell states inherent to the breast.

cancer biology↗

bioRxiv2025

Cleared tissue dual-view oblique plane microscopy

We present a dual-view oblique plane microscope (dOPM) for imaging thick optically cleared tissue samples using a silicone immersion primary objective. The custom-designed remote refocusing relay utilizes stock optics to achieve remote refocusing in refractive index-matched samples. The spatial resolution of the system was characterized using a series of fluorescent bead phantoms with refractive indices ranging from 1.4-1.5, with the point spread function full width at half maximum measuring [~]0.5 {micro}m laterally and [~]1 {micro}m axially for a refractive index-matched bead sample, with minimal degradation over a >250 {micro}m axial range. We characterize how the remote refocusing performance at sample refractive indices up to n = 1.5 can be partially compensated for using adjustment of the correction collar on the primary objective. We apply the system to imaging a range of biological samples with varied refractive indices. Combined with tiled acquisition, image stitching and multi-view image fusion, the microscope enables multicolour imaging of mm-wide and [~]250 {micro}m thick optically cleared mouse ovarian cancer and colon tissue samples with subcellular resolution. We also image a whole Drosophila melanogaster fruit fly brain. The system offers a platform for fast and high-resolution, multicolour volumetric imaging across spatial scales, integrated on a commercially available microscope frame.

biophysics↗

bioRxiv2025

Assessing PARP trapping dynamics in ovarian cancer using a CRISPR-engineered FRET biosensor

Poly(ADP-ribose) polymerase inhibitors (PARPi) have revolutionised the treatment of ovarian high grade serous carcinoma (HGSC), especially those with defective homologous recombination. However, the emergence of resistance poses a critical challenge, as over 50% of patients relapse within three years. The mechanisms underlying changes in PARP trapping, a central aspect of PARPi efficacy, are not well understood due to limitations in current experimental methodologies. Existing techniques lack resolution and throughput, impeding efforts to study PARP trapping dynamics over time with single-cell resolution. Effective tools to study PARP trapping in live cells are urgently needed to elucidate resistance mechanisms and inform therapeutic strategies. To address this, we used CRISPR-Cas9 gene editing to dual-label endogenous PARP1 with EGFP and mCherryFP in OVCAR4 cells to develop a novel intramolecular FRET-based biosensor that enables real-time, single-cell visualization of PARP trapping dynamics in live cells. High-content fluorescence lifetime imaging microscopy (FLIM) revealed dose dependent PARP trapping upon exposure to PARP inhibitor and distinguished between the trapping efficiencies of four different PARPi (veliparib, olaparib, rucaparib, talazoparib). Moreover, we found reduced PARP trapping in PARPi-resistant models, both in vitro and in vivo, providing critical evidence for altered PARP trapping as a resistance mechanism and illustrating the potential of this FRET biosensor to interrogate resistance mechanisms quantitatively. This PARP trapping biosensor represents a transformative advance, enabling dynamic, high-resolution analysis of mechanisms underlying cancer drug resistance. It provides critical insights into the heterogeneity of PARPi resistance, with implications for developing more effective therapies and improving personalised treatment strategies for ovarian cancer patients. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=58 SRC="FIGDIR/small/642798v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@1c5ee67org.highwire.dtl.DTLVardef@1a6d101org.highwire.dtl.DTLVardef@e3a2bborg.highwire.dtl.DTLVardef@d0ba03_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2024

Model-free machine learning-based 3D single molecule localisation microscopy

Single molecule localisation microscopy (SMLM) can provide two-dimensional super-resolved image data from conventional fluorescence microscopes, while three dimensional (3D) SMLM usually involves a modification of the microscope, e.g. to engineer a predictable axial variation in the point spread function. Here we demonstrate a 3D SMLM approach (we call "easyZloc") utilising a lightweight Convolutional Neural Network that is generally applicable, including with "standard" (unmodified) fluorescence microscopes, and which we consider may be practically useful in a high throughput SMLM workflow. We demonstrate the reconstruction of nuclear pore complexes with comparable performance to previously reported methods but with a significant reduction in computational power and execution time. 3D reconstructions of the nuclear envelope and a tubulin sample over a larger axial range are also shown.

biophysics↗

bioRxiv2024

Imaging of MAP kinase dynamics reveals endocytic regulation of pulsatile signalling and network re-wiring in response to targeted therapy in EGFR-mutant non-small cell lung cancer

A better understanding of the signalling mechanisms underlying transitions from drug-sensitive to drug-tolerant states is required to overcome therapy failure. We combined single-cell biosensor imaging with functional perturbations to investigate the regulation of oncogenic signalling in EGFR-mutant lung adenocarcinoma. We find that despite the constant presence of the mutant oncogene, ERK signalling exhibits pulsatile dynamics, with pulse characteristics determined by the endocytic machinery. Analysis of drug-tolerant persisters (DTPs) revealed that, after an initial phase of complete pathway shut-down, signalling was rewired leading to renewed ERK pulses that drive cell cycle progression. FAK- and SRC-regulated adhesion complexes replace mutant EGFR as the driver of reactivated ERK pulses in DTPs, yet they remain controlled by the membrane trafficking machinery. We show that DTPs rely on additional survival pathways including YAP signalling, and that the phosphatase PTPRS represents a key node in therapy resistant cells, coordinating regulation of ERK, the cytoskeleton, and YAP.

cancer biology↗

bioRxiv2023

Active mesh and neural network pipeline for cell aggregate segmentation

Segmenting cells within cellular aggregates in 3D is a growing challenge in cell biology, due to improvements in capacity and accuracy of microscopy techniques. Here we describe a pipeline to segment images of cell aggregates in 3D. The pipeline combines neural network segmentations with active meshes. We apply our segmentation method to cultured mouse mammary duct organoids imaged over 24 hours with oblique plane microscopy, a high-throughput light-sheet fluorescence microscopy technique. We show that our method can also be applied to images of mouse embryonic stem cells imaged with a spinning disc microscope. We segment individual cells based on nuclei and cell membrane fluorescent markers, and track cells over time. We describe metrics to quantify the quality of the automated segmentation. Our segmentation pipeline involves a Fiji plugin which implement active meshes deformation and allows a user to create training data, automatically obtain segmentation meshes from original image data or neural network prediction, and manually curate segmentation data to identify and correct mistakes. Our active meshes-based approach facilitates segmentation postprocessing, correction, and integration with neural network prediction. Statement of significanceIn vitro culture of organ-like structures derived from stem cells, so-called organoids, allows to image tissue morphogenetic processes with high temporal and spatial resolution. Three-dimensional segmentation of cell shape in timelapse movies of these developing organoids is however a significant challenge. In this work, we propose an image analysis pipeline for cell aggregates that combines deep learning with active contour segmentations. This combination offers a flexible and efficient way to segment three-dimensional cell images, which we illustrate with by segmenting datasets of growing mammary gland organoids and mouse embryonic stem cells.

bioinformatics↗

bioRxiv2023

Remote-refocusing light-sheet fluorescence microscopy enables 3D imaging of electromechanical coupling of hiPSC-derived and adult cardiomyocytes in co-culture

Improving cardiac function through stem-cell regenerative therapy requires functional and structural integration of the transplanted cells with the host tissue. Visualizing the electromechanical interaction between native and graft cells necessitates 3D imaging with high spatio-temporal resolution and low phototoxicity. A custom light-sheet fluorescence microscope was used for volumetric imaging of calcium dynamics in co-cultures of adult rat left ventricle cardiomyocytes and human induced pluripotent stem cell-derived cardiomyocytes. Aberration-free remote refocus of the detection plane synchronously to the scanning of the light sheet along the detection axis enabled fast dual-channel 3D imaging at subcellular resolution without mechanical sample disturbance at up to 8 Hz over a [~]300 {micro}m x 40 {micro}m x 50 {micro}m volume. The two cell types were found to undergo electrically stimulated and spontaneous synchronized calcium transients and contraction. Electromechanical coupling was found to improve with co-culture duration, with 50% of adult-CM coupled after 24 hours of co-culture, compared to 19% after 4 hours (p = 0.0305). Immobilization with para-nitroblebbistatin did not prevent calcium transient synchronization, with 35% and 36% adult-CM coupled in control and treated samples respectively (p = 0.91), indicating that electrical coupling can be maintained independently of mechanotransduction.

cell biology↗

bioRxiv2022

Robust, single-shot, optical autofocus system utilizing cylindrical lenses to provide high precision and long range of operation

We present a robust, "real-time" optical autofocus system for microscopy that provides high accuracy (<230 nm) and long range ([~]130 {micro}m) with a 1.4 numerical aperture oil immersion objective lens. This autofocus can operate in a closed loop, single-shot functionality over a range of {+/-}37.5 {micro}m and can also operate as a 2-step process up to {+/-}68 {micro}m. A real-time autofocus capability is useful for experiments with long image data acquisition times, including single molecule localization microscopy, that may be impacted by defocusing resulting from drift of components, e.g., due to changes in temperature or mechanical drift. It is also vital for automated slide scanning or multiwell plate imaging where the sample may not be in the same horizontal plane for every field of view during the image data acquisition. To realise high precision and long range, we implement orthogonal optical readouts using cylindrical lenses. We demonstrate the performance of this new optical autofocus system with automated multiwell plate imaging and single molecule localisation microscopy and illustrate the benefit of using a superluminescent diode as the autofocus light source.

bioengineering↗

bioRxiv2022

3D single-cell shape analysis of cancer cells using geometric deep learning

AO_SCPLOWBSTRACTC_SCPLOWAberrations in 3D cell morphogenesis are linked to diseases such as cancer. Yet there is little systems-level understanding of cell shape determination in 3D, largely because there is a paucity of data-driven methods to quantify and describe 3D cell shapes. We have addressed this need using unsupervised geometric deep learning to learn shape representations of over 95,000 melanoma cells imaged by 3D high-throughput light-sheet microscopy. We used a dynamic graph convolutional foldingnet autoencoder with improved deep embedded clustering to simultaneously learn lower-dimensional representations and classes of 3D cell shapes. We describe a landscape of 3D cell morphology using deep learning-derived 3D quantitative morphological signatures (3DQMS) across different substrate geometries, following treatment by different clinically relevant small molecules and systematic gene depletion in high-throughput. By data integration, we predict modes of action for different small molecules providing mechanistic insights and blueprints for biological re-engineering. Finally, we provide explainability and interpretability for deep learning models.

bioinformatics↗

bioRxiv2021

Environmentally dependent and independent control of cell shape determination by Rho GTPase regulators in melanoma

In order to invade 3D tissues, cancer cells dynamically change cell morphology in response to geometric and mechanical cues in the environment. But how cells determine their shape in 3D versus 2D environments is poorly understood. Studying 2D versus 3D single cell shape determination has historically been technically difficult due to the lack of methodologies to directly compare the two environments. We developed an approach to study cell shape in 2D versus 3D by measuring cell shape at different depths in collagen using stage-scanning oblique plane microscopy (ssOPM). We find characteristic shape changes occur in melanoma cells depending on whether a cell is attached to a 2D surface or 3D environment, and that these changes can be modulated by Rho GTPase regulatory proteins. Our data suggest that regulation of cell protrusivity undergoes a switch of control between different Rho GTPase regulators depending on the physical microenvironment.

cell biology↗

bioRxiv2021

Video-rate remote refocusing through continuous oscillation of a membrane deformable mirror.

This paper presents the use of a deformable mirror (DM) configured to rapidly refocus a microscope employing a high numerical aperture objective lens. An Alpao DM97-15 membrane DM was used to refocus a 40x/0.80 NA water-immersion objective through a defocus range of -50 to 50 m at 26.3 sweeps per second. We achieved imaging with a mean Strehl metric of > 0.6 over a field of view in the sample of 200x200 m2 over a defocus range of 77 m. We describe an optimisation procedure where the mirror is swept continuously in order to avoid known problems of hysteresis associated with the membrane DM employed. This work demonstrates that a DM-based refocusing system could in the future be used in light-sheet fluorescence microscopes to achieve video-rate volumetric imaging.

bioengineering↗

bioRxiv2021

Single-shot phase contrast microscopy using polarisation-resolved differential phase contrast

We present a robust, low-cost single-shot implementation of differential phase microscopy utilising a polarisation-sensitive camera to simultaneously acquire 4 images from which the phase gradients and quantitative phase image can be calculated. This polarisation-resolved differential phase contrast (pDPC) microscopy technique can be interleaved with single-shot imaging polarimetry.

biophysics↗

bioRxiv2021

Robust optical autofocus system utilizing neural networks trained for extended range and time-course and automated multiwell plate imaging including single molecule localization microscopy

We present a robust, long-range optical autofocus system for microscopy utilizing machine learning. This can be useful for experiments with long image data acquisition times that may be impacted by defocusing resulting from drift of components, e.g. due to changes in temperature or mechanical drift. It is also useful for automated slide scanning or multiwell plate imaging where the sample(s) to be imaged may not be in the same horizontal plane throughout the image data acquisition. To address the impact of (thermal or mechanical) fluctuations over time in the optical autofocus system itself, we utilise a convolutional neural network (CNN) that is trained over multiple days to account for such fluctuations. To address the trade-off between axial precision and range of the autofocus, we implement orthogonal optical readouts with separate CNN training data, thereby achieving an accuracy well within the 600 nm depth of field of our 1.3 numerical aperture objective lens over a defocus range of up to approximately +/- 100 m. We characterise the performance of this autofocus system and demonstrate its application to automated multiwell plate single molecule localisation microscopy.

bioengineering↗

bioRxiv2020

Dual-view oblique plane microscopy (dOPM)

We present a new folded dual-view oblique plane microscopy (OPM) technique termed dOPM that enables two orthogonal views of the sample to be obtained by translating a pair of tilted mirrors in refocussing space. Using a water immersion 40x 1.15 NA primary objective, deconvolved image volumes of 200 nm beads were measured to have full width at half maxima (FWHM) of 0.35{+/-}0.04 m and 0.39{+/-}0.02 m laterally and 0.81{+/-}0.07 m axially. The laterally integrated z-sectioning value was 1.33{+/-}0.45 m using light-sheet FWHM in the frames of the two views of 4.99{+/-}0.58 m and 4.89{+/-}0.63 m. To qualitatively demonstrate that the system can reduce shadow artefacts while providing a more isotropic resolution, a multi-cellular spheroid approximately 100 m in diameter was imaged.

bioengineering↗

bioRxiv2020

Impact of N-terminally substituted glucagon family receptor agonists on signal bias, trafficking and downstream responses

Receptors for the peptide hormones glucagon-like peptide-1 (GLP-1), glucose-dependent insulinotropic polypeptide (GIP) and glucagon (GCG) are important regulators of insulin secretion and energy metabolism. Recently described GLP-1 receptor agonists showing signal bias in favour of cyclic AMP over {beta}-arrestin-2 recruitment have delivered promising results in preclinical studies. Here we first sought to establish the role of {beta}-arrestins in the control of intracellular signalling and trafficking responses at the closely related GLP-1, GIP and GCG receptors, through studies performed in cells depleted of both {beta}-arrestin isoforms. We also generated analogues of GLP-1, GCG and GIP which in some cases showed selective reduction in {beta}-arrestin-2 recruitment versus cAMP signalling compared to the parent peptide. Despite reduced acute signalling potency and/or efficacy, some biased GLP-1 and GIP analogues increased maximal sustained insulin secretion from INS-1 832/3 clonal beta cells, although only at high agonist concentrations. Biased GCG analogues did not affect maximal insulin release, or glucose output in hepatocytes.

pharmacology and toxicology↗

bioRxiv2020

The influence of peptide context on signalling and trafficking of glucagon-like peptide-1 receptor biased agonists

Signal bias and membrane trafficking have recently emerged as important considerations in the therapeutic targeting of the glucagon-like peptide-1 receptor (GLP-1R) in type 2 diabetes and obesity. In the present study, we have evaluated a peptide series with varying sequence homology between native GLP-1 and exendin-4, the archetypal ligands on which approved GLP-1R agonists are based. We find notable differences in agonist-mediated signalling, endocytosis and recycling, dependent both on the introduction of a His [->] Phe switch at position 1 and the specific mid-peptide helical regions and C-termini of the two agonists. These observations were linked to insulin secretion in a beta cell model and provide insights into how ligand factors influence GLP-1R function at the cellular level. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/961524v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@cb425borg.highwire.dtl.DTLVardef@719e37org.highwire.dtl.DTLVardef@14a45b9org.highwire.dtl.DTLVardef@127afd1_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗