Biology subjects

Ward, E. N.

Publications and source records attributed to Ward, E. N..

6 recordsLinked to original sources

bioRxiv2025

SIMple: A fibre-based platform for accessible structured illumination microscopy

Structured illumination microscopy can be used to achieve optical sectioning and super resolution in fluorescence images, reducing out-of-focus light and increasing the resolution beyond the diffraction limit, without the need for specialised detection optics. However, the complex illumination path is difficult to build and align. We present an illumination path based on fibre-optic components for both splitting and phase-shifting the illumination light. This enables a SIMple and compact "Plug&Play" modality which substantially reduces the time and alignment required when adding the optics to an existing widefield instrument. The system is capable of optical sectioning imaging at camera-limited frame-rates using multiple excitation wavelengths simultaneously, as demonstrated by imaging fixed and live biological samples at 561 and 491 nm. Super-resolution imaging of fixed samples on a very compact, self-contained microscope is also demonstrated: illumination is coupled in by fibre to a lightweight frame with dimensions of just 300 x 450 x 300 mm3, enabling easy transportation and use in laboratories with limited space. Characterisation of the system using bead analysis shows a resolution of 168 and 172 nm at 491 and 561 nm, respectively, an improvement by a factor of 1.91 and 1.92 compared to widefield, with a field of view of 100 x 100 {micro}m2.

bioengineering↗

bioRxiv2025

Brain cholesterol metabolites cause significant neurodegeneration in human iPSC-derived neurons

Disrupted cholesterol metabolism is increasingly recognised as a contributing factor in neurodegeneration; however, the specific effects of key brain-derived cholesterol metabolites, 24S-hydroxycholesterol (24S-HC) and 27-hydroxycholesterol (27-HC), remain poorly understood. Using human iPSC-derived i3 cortical neurons, we demonstrate that both 24S-HC and 27-HC significantly impair neuronal calcium signalling by elevating resting calcium levels, reducing spike amplitude, and disrupting network synchrony. These functional deficits are accompanied by widespread organelle dysfunction. Both oxysterols induce mitochondrial fragmentation, decrease spare respiratory capacity, and impair lysosomal degradation. Notably, 27-HC uniquely triggers lysosomal swelling and membrane permeabilisation. Additional signs of cellular stress, including axonal swellings and elevated endoplasmic reticulum calcium levels, were also observed. Furthermore, both 24S-HC and 27-HC were found to directly interact with alpha-synuclein (aSyn), promoting its accumulation in cellular models. In contrast, cholesterol itself had minimal impact, highlighting the distinct toxicity of its hydroxylated metabolites. Together, these findings reveal a mechanistic link between oxysterol accumulation and neuronal dysfunction, supporting the hypothesis that elevated levels of 24S-HC and 27-HC, commonly observed in Parkinsons and Alzheimers disease, may actively drive neurodegenerative processes. Targeting oxysterol metabolism may therefore represent a promising therapeutic avenue for intervention in neurodegenerative disorders.

neuroscience↗

bioRxiv2025

Deep learning for fluorescence lifetime predictions enables high-throughput in vivo imaging

Fluorescence lifetime imaging microscopy (FLIM) is a powerful optical tool widely used in biomedical research to study changes in a samples microenvironment. However, data collection and interpretation are often challenging, and traditional methods such as exponential fitting and phasor plot analysis require a high number of photons per pixel for reliably measuring the fluorescence lifetime of a fluorophore. To satisfy this requirement, prolonged data acquisition times are needed, which makes FLIM a low-throughput technique with limited capability for in vivo applications. Here, we introduce FLIMngo, a deep learning model capable of quantifying FLIM data obtained from photon-starved environments. FLIMngo outperforms other deep learning approaches and phasor plot analyses, yielding accurate fluorescence lifetime predictions from decay curves obtained with fewer than 50 photons per pixel by leveraging both time and spatial information present in raw FLIM data. Thus, FLIMngo reduces FLIM data acquisition times to a few seconds, thereby, lowering phototoxicity related to prolonged light exposure and turning FLIM into a higher throughput tool suitable for analysis of live specimens. Following the characterisation and benchmarking of FLIMngo on simulated data, we highlight its capabilities through applications in live, dynamic samples. Examples include the quantification of disease-related protein aggregates in non-anaesthetised Caenorhabditis (C.) elegans, which significantly improves the applicability of FLIM by opening avenues to continuously assess C. elegans throughout their lifespan. Finally, FLIMngo is open-sourced and can be easily implemented across systems without the need for model retraining.

biophysics↗

bioRxiv2024

A high-resolution microscopy system for biological studies of cold-adapted species under physiological conditions

The fundamental processes governing life are sensitively dependent on temperature. Whilst much is known about the constraints on how proteins operate at 37{degrees}C, little knowledge exists about how biological function is maintained sub-zero temperature conditions, where proteins are less stable and oxidative damage is high. However, almost 90% of habitable environments on Earth are permanently below 5{degrees}C (i.e. the deep sea and polar regions). This means that we do not understand how a large and diverse proportion of the global biome functions. To address this question at the cellular level, tools are required for imaging biological systems at high resolution under physiological conditions. This poses severe technical challenges that cannot be addressed with traditional optical microscopy techniques. High-resolution imaging objectives require short working distances and the use of immersion media, which lead to rapid heat transfer from the microscope to the sample. This affects the viability of live specimens and the interpretability of the results when the sample function optimally at low temperatures. Condensation and temperature-induced shrinking of components pose further challenges, reducing image resolution and contrast. Here, we address these issues and provide a method for high-fidelity imaging of live biological samples at temperatures of around, or below, 0{degrees}C. Our method is compatible with different microscopy modalities, including super-resolution imaging. It relies on hardware additions to traditional microscopy systems that can be straightforwardly implemented, namely, a cooling collar, 10% ethanol as an immersion medium, and nitrogen flow to mitigate condensation. We demonstrate the method in live cell cultures derived from Antarctic fish species and highlight the need to maintain physiological conditions for these fragile biological samples. Future applications are diverse and include evolutionary biology and the study of cold-adapted organisms, as well as cellular biophysics and several applications in biotechnology.

biophysics↗

bioRxiv2024

FLIMPA: A versatile software for Fluorescence Lifetime Imaging Microscopy Phasor Analysis

Fluorescence lifetime imaging microscopy (FLIM) is an advanced microscopy technique capable of providing a deeper understanding of the molecular environment of a fluorophore. While FLIM data were traditionally analysed through the exponential fitting of the fluorophores emission decays, the use of phasor plots is increasingly becoming the preferred standard. This is due to their ability to visualise the distribution of fluorescent lifetimes within a sample, offering insights into molecular interactions in the sample without the need for model assumptions regarding the exponential decay behaviour of the fluorophores. However, so far most researchers have had to rely on commercial phasor plot software packages, which are closed-source and rely on proprietary data formats. In this paper, we introduce FLIMPA, an opensource, stand-alone software for phasor plot analysis that provides many of the features found in commercial software, and more. FLIMPA is fully developed in Python and offers advanced tools for data analysis and visualisation. It enhances FLIM data comparison by integrating phasor points from multiple trials and experimental conditions into a single plot, while also providing the possibility to explore detailed, localised insights within individual samples. We apply FLIMPA to introduce a cell-based assay for the quantification of microtubule depolymerisation, measured through fluorescence lifetime changes of SiR-tubulin, in response to various concentrations of Nocodazole, a microtubule depolymerising drug relevant to anti-cancer treatment.

biophysics↗

bioRxiv2022

α-synuclein fibril and synaptic vesicle interactions lead to vesicle destruction and increased uptake into neurons

Monomeric alpha-synuclein (aSyn) is a well characterised as a lipid binding protein. aSyn is known to form amyloid fibrils which are also localised with lipids and organelles in so called Lewy bodies, insoluble structures found in Parkinsons disease patients brains. It is still unclear under which conditions the aSyn-lipid interaction can start to become pathological. Previous work to address pathological interactions has focused on using synthetic lipid membranes, which lack the complexity of physiological lipid membranes which not only have a more complex lipid composition, but also contain lipid interacting proteins. Here, we investigate how either monomeric or fibrillar aSyn interact with physiological synaptic vesicles (SV) isolated from rodent brain. Using small angle neutron scattering and high-resolution imaging we observe that aSyn fibrils disintegrate SV, whereas aSyn monomers cause clustering of SV. Furthermore, SV enhance the aggregation rate of aSyn, however increasing the SV:aSyn ratio causes a reduction in aggregation propensity. SV lipids appear as an integrated part of aSyn fibrils and while the fibril morphology differs to aSyn fibrils alone, the core fibril structure remains the same. We finally demonstrate that lipid-associated aSyn fibrils are more easily taken up into cortical i3Neurons derived from induced pluripotent stem cells. Our study sheds light on differences between interactions of aSyn with synthetic lipid vesicles and physiological SV. We show how aSyn fibrils may enhance pathology by disintegrating SV, which in turn may have fatal consequences for neurons. Furthermore, disease burden may additionally be impacted by an increased uptake of lipid-associated aSyn by neurons, leading to more SV damage and enhancing aSyn aggregation.

neuroscience↗