Biology subjects

Culley, S.

Publications and source records attributed to Culley, S..

13 recordsLinked to original sources

bioRxiv2026

Multiphoton tomographic fluorescence lifetime imaging microscopy -TomoFLIM

Fluorescence lifetime imaging microscopy provides quantitative, concentration-independent contrast for probing molecular interactions, biochemical environments and cellular physiology. However, the requirement to acquire sufficient time-resolved photon statistics makes FLIM inherently slow, limiting its application to dynamic biological processes. In live-cell applications, including calcium signalling and vesicular trafficking, acquisition times can exceed the timescale of the underlying biology, causing temporal averaging, motion artefacts and loss of transient information. Methods that increase FLIM acquisition speed while preserving quantitative lifetime accuracy are therefore required. We report on a high-speed, compressive, multiphoton fluorescence lifetime imaging technique (TomoFLIM). Two-photon fluorescence is excited using a line focus projected tomographically across the sample, while time-tagged fluorescence is acquired using time-correlated single-photon counting. Time-resolved fluorescence data are reconstructed using Lucy-Richardson deconvolution followed by a computationally efficient centre-of-mass method lifetime estimator. In addition, TomoFLIM Net, a physics-informed neural-network, directly reconstructs fluorescence intensity and lifetime from compressed time-resolved tomographic data. TomoFLIM was benchmarked against raster-scanned fluorescence lifetime measurements using calibrated fluorescence lifetime beads and biological specimens. We demonstrate imaging at compression ratios exceeding 90%, with Pearson correlation coefficients above 80% relative to reference images. A raster-scanned FLIM dataset acquired in 60 s was reproduced using TomoFLIM in 3.75 s, representing a 16-fold increase in frame rate and equivalent reduction in accumulated dark counts. TomoFLIM Net recovered distinct experimental bead lifetime populations, demonstrating a direct route from compressed measurements to quantitative lifetime maps. TomoFLIM therefore offers significant potential for rapid live-cell imaging of dynamic biological processes, including deep within turbid biological specimens.

biophysics↗

bioRxiv2025

Image quality metrics fail to accurately represent biological information in fluorescence microscopy

Image processing methods offer the potential to improve the quality of fluorescence microscopy data, allowing for image acquisition at lower, less phototoxic illumination doses. The training and evaluation of such methods is informed and driven by full-reference image quality metrics (IQMs); however, these metrics derive from applications to natural scene images, not fluorescence microscopy images. Here we investigate the response of IQMs to common properties of fluorescence microscopy data and whether IQMs are capable of reporting the biological information content of images. We find that IQM scores are biased by image content for both raw and processed microscopy data, and that improvements in IQM values reported after processing are not reliably correlated with performance in downstream analysis tasks. As common IQMs are unreliable proxies for guiding image processing developments in biological fluorescence microscopy, image processing performance should be benchmarked according to downstream analysis success.

bioinformatics↗

bioRxiv2025

Extracting biological structure and heterogeneity from the nano to the macro scale

Fluorescence microscopy is an essential tool in biology. It has revealed great variability at multiple scales, in macromolecular complexes, cells, and organisms. Understanding this variability will reveal the mechanisms by which genetically or biochemically identical systems adopt different biological states. Achieving this requires the ability to extract both the underlying biological structure and how it varies across the population. Currently the field lacks general techniques to deal with arbitrary structures and different types of variability. Here we present SQUASSH, a new convolutional neural network-based approach to freely fit structural models to fluorescence microscopy data that simultaneously quantifies variability to reveal correlations, dynamics, and systematic distortions. SQUASSH is highly versatile: it accommodates diverse imaging modalities at length scales from nm to mm. This approach opens up applications such as imaging nanoscale macromolecular structures, revealing patterns in shape changes from organelle to tissue scale, and characterizing systems biology of dynamical processes.

cell biology↗

bioRxiv2023

Characterisation and correction of polarisation effects in fluorescently labelled fibres

Many biological structures take the form of fibres and filaments, and quantitative analysis of fibre organisation is important for understanding their functions in both normal physiological conditions and disease. In order to visualise these structures, fibres can be fluorescently labelled and imaged, with specialised image analysis methods available for quantifying the degree and strength of fibre alignment. Here we show that fluorescently labelled fibres can display polarised emission, with the strength of this effect varying depending on structure and fluorophore identity. This can bias automated analysis of fibre alignment and mask the true underlying structural organisation. We present a method for quantifying and correcting these polarisation effects without requiring polarisation resolved microscopy, and demonstrate its efficacy when applied to images of fluorescently labelled collagen gels, allowing for more reliable characterisation of fibre microarchitecture.

cell biology↗

bioRxiv2022

High-fidelity 3D live-cell nanoscopy through data-driven enhanced super-resolution radial fluctuation

In recent years, the development of new image analysis approaches has highlighted the possibility of recovering superresolution information from short sequences of wide-field images. Our recently developed method, SRRF (Super-Resolution Radial Fluctuations), enables long-term live-cell imaging beyond the resolution limit without specialized hardware. Here, we present eSRRF (enhanced-SRRF), a significant improvement over our initial method, enhancing image fidelity to the underlying structure and resolution. Especially, eSRRF uses automated data-driven parameter optimization, including an estimation of the number of frames necessary for optimal reconstruction. We demonstrate the improved fidelity of the images reconstructed with eSRRF and highlight its versatility and ease of use over a wide range of microscopy techniques and biological systems. We also extend eSRRF to 3D super-resolution microscopy by combining it with multi-focus microscopy (MFM), obtaining volumetric super-resolution imaging of live cells with acquisition speed of ~1 volume/second.

biophysics↗

bioRxiv2021

Physical mechanisms of ESCRT-III-driven cell division in archaea

Living systems propagate by undergoing rounds of cell growth and division. Cell division is at heart a physical process that requires mechanical forces, usually exerted by protein assemblies. Here we developed the first physical model for the division of archaeal cells, which despite their structural simplicity share machinery and evolutionary origins with eukaryotes. We show how active geometry changes of elastic ESCRT-III filaments, coupled to filament disassembly, are sufficient to efficiently split the cell. We explore how the non-equilibrium processes that govern the filament behaviour impact the resulting cell division. We show how a quantitative comparison between our simulations and dynamic data for ESCRTIII-mediated division in Sulfolobus acidocaldarius, the closest archaeal relative to eukaryotic cells that can currently be cultured in the lab, and reveal the most likely physical mechanism behind its division.

biophysics↗

bioRxiv2020

Live cell imaging of the hyperthermophilic archaeon Sulfolobus acidocaldarius identifies complementary roles for two ESCRTIII homologues in ensuring a robust and symmetric cell division

Live-cell imaging has revolutionized our understanding of dynamic cellular processes in bacteria and eukaryotes. While similar techniques have recently been applied to the study of halophilic archaea, our ability to explore the cell biology of thermophilic archaea is limited, due to the technical challenges of imaging at high temperatures. Here, we report the construction of the Sulfoscope, a heated chamber that enables live-cell imaging on an inverted fluorescent microscope. Using this system combined with thermostable fluorescent probes, we were able to image Sulfolobus cells as they divide, revealing a tight coupling between changes in DNA compaction, segregation and cytokinesis. By imaging deletion mutants, we observe important differences in the function of the two ESCRTIII proteins recently implicated in cytokinesis. The loss of CdvB1 compromises cell division, causing occasional division failures and fusion of the two daughter cells, whereas the deletion of cdvB2 leads to a profound loss of division symmetry, generating daughter cells that vary widely in size and eventually generating ghost cells. These data indicate that DNA separation and cytokinesis are coordinated in Sulfolobus, as is the case in eukaryotes, and that two contractile ESCRTIII polymers perform distinct roles to ensure that Sulfolobus cells undergo a robust and symmetrical division. Taken together, the Sulfoscope has shown to provide a controlled high temperature environment, in which cell biology of Sulfolobus can be studied in unprecedent details.

microbiology↗

bioRxiv2019

Closed mitosis requires local disassembly of the nuclear envelope

At the end of mitosis, eukaryotic cells must segregate both copies of their replicated genome into two new nuclear compartments (1). They do this either by first dismantling and later reassembling the nuclear envelope in a so called \"open mitosis\", or by reshaping an intact nucleus and then dividing into two in a \"closed mitosis\" (2, 3). However, while mitosis has been studied in a wide variety of eukaryotes for over a century (4), it is not known how the double membrane of the nuclear envelope is split into two at the end of a closed mitosis without compromising the impermeability of the nuclear compartment (5). In studying this problem in the fission yeast Schizosaccharomyces pombe, a classical model for closed mitosis (5), we use genetics, live cell imaging and electron tomography to show that nuclear fission is achieved via local disassembly of the nuclear envelope (NE) within the narrow bridge that links segregating daughter nuclei. In doing so, we identify a novel inner NE-localised protein Les1 that restricts the process of local NE breakdown (local NEB) to the bridge midzone and prevents the leakage of material from daughter nuclei. The mechanics of local NEB in a closed mitosis closely mirror those of NEB in open mitosis (3), revealing an unexpectedly deep conservation of nuclear remodelling mechanisms across diverse eukaryotes.

cell biology↗

bioRxiv2019

Proteasome-mediated protein degradation resets the cell division cycle and triggers ESCRT-III-mediated cytokinesis in an archaeon

The archaeon Sulfolobus acidocaldarius is a relative of eukaryotes known to progress orderly through its cell division cycle despite lacking obvious CDK/cyclin homologues. Here, in exploring the mechanisms underpinning archaeal cell division cycle control, we show that the proteasome of S. acidocaldarius, like its eukaryotic counterpart, regulates the transition from the end of one cell division cycle to the beginning of the next. Further, we identify the archaeal ESCRT-III homologue CdvB as a key target of the proteasome, and show that state-dependent degradation of CdvB triggers archaeal cell division by allowing constriction of a CdvB1:CdvB2 ESCRT-III division ring. These findings suggest an ancient role for proteasome-mediated degradation in resetting the cell division cycle in both archaea and eukaryotes.

cell biology↗

bioRxiv2018

NanoJ: a high-performance open-source super-resolution microscopy toolbox

Super-resolution microscopy has become essential for the study of nanoscale biological processes. This type of imaging often requires the use of specialised image analysis tools to process a large volume of recorded data and extract quantitative information. In recent years, our team has built an open-source image analysis framework for super-resolution microscopy designed to combine high performance and ease of use. We named it NanoJ - a reference to the popular ImageJ software it was de-veloped for. In this paper, we highlight the current capabilities of NanoJ for several essential processing steps: spatio-temporal alignment of raw data (NanoJ-Core), super-resolution image re-construction (NanoJ-SRRF), image quality assessment (NanoJ-SQUIRREL), structural modelling (NanoJ-VirusMapper) and control of the sample environment (NanoJ-Fluidics). We expect to expand NanoJ in the future through the development of new tools designed to improve quantitative data analysis and measure the reliability of fluorescent microscopy studies.

bioinformatics↗

bioRxiv2018

Automating multimodal microscopy with NanoJ-Fluidics

Fluorescence microscopy can reveal all aspects of cellular mechanisms, from molecular details to dynamics, thanks to approaches such as super-resolution and live-cell imaging. Each of its modalities requires specific sample preparation and imaging conditions to obtain high-quality, artefact-free images, ultimately providing complementary information. Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows involving multiple sample preparation steps. We present a robust fluidics approach to automate complex sequences of treatment, labelling and imaging of live and fixed cells. Our open-source NanoJ-Fluidics system is based on low-cost LEGO hardware controlled by ImageJ-based software and can be directly adapted to any microscope, providing easy-to-implement high-content, multimodal imaging with high reproducibility. We demonstrate its capacity to carry out complex sequences of experiments such as super-resolved live-to-fixed imaging to study actin dynamics; highly-multiplexed STORM and DNA-PAINT acquisitions of multiple targets; and event-driven fixation microscopy to study the role of adhesion contacts in mitosis.

cell biology↗

bioRxiv2017

Content-Aware Image Restoration: Pushing the Limits of Fluorescence Microscopy

Fluorescence microscopy is a key driver of discoveries in the life-sciences, with observable phenomena being limited by the optics of the microscope, the chemistry of the fluorophores, and the maximum photon exposure tolerated by the sample. These limits necessitate trade-offs between imaging speed, spatial resolution, light exposure, and imaging depth. In this work we show how image restoration based on deep learning extends the range of biological phenomena observable by microscopy. On seven concrete examples we demonstrate how microscopy images can be restored even if 60-fold fewer photons are used during acquisition, how near isotropic resolution can be achieved with up to 10-fold under-sampling along the axial direction, and how tubular and granular structures smaller than the diffraction limit can be resolved at 20-times higher frame-rates compared to state-of-the-art methods. All developed image restoration methods are freely available as open source software in Python, FO_SCPLOWIJIC_SCPLOW, and KO_SCPLOWNIMEC_SCPLOW.

bioinformatics↗

bioRxiv2017

NanoJ-SQUIRREL: quantitative mapping and minimisation of super-resolution optical imaging artefacts

Most super-resolution microscopy methods depend on steps that contribute to the formation of image artefacts. Here we present NanoJ-SQUIRREL, an ImageJ-based analytical approach providing a quantitative assessment of super-resolution image quality. By comparing diffraction-limited images and super-resolution equivalents of the same focal volume, this approach generates a quantitative map of super-resolution defects, as well as methods for their correction. To illustrate its broad applicability to super-resolution approaches we apply our method to Localization Microscopy, STED and SIM images of a variety of in-cell structures including microtubules, poxviruses, neuronal actin rings and clathrin coated pits. We particularly focus on single-molecule localisation microscopy, where super-resolution reconstructions often feature imperfections not present in the original data. By showing the quantitative evolution of data quality over these varied sample preparation, acquisition and super-resolution methods we display the potential of NanoJ-SQUIRREL to guide optimization of superresolution imaging parameters.

biophysics↗