Biology subjects

Owen, D. M.

Publications and source records attributed to Owen, D. M..

13 recordsLinked to original sources

bioRxiv2026

SynthMLM: A framework for interpretable analysis and synthetic localisation data generation for SMLM

Quantitative analysis of single-molecule localisation microscopy (SMLM) data remains challenging because biologically diverse, well-annotated datasets are limited, whilst nanoscale protein organisation is heterogeneous and difficult to describe with hand-tuned metrics. We present SynthMLM, a framework that infers interpretable structural descriptors from experimental SMLM data and uses these descriptors to generate synthetic localisation datasets. We demonstrate SynthMLM by generating descriptor-matched synthetic datasets corresponding to diverse experimental SMLM datasets and evaluating their agreement with real data using descriptor-level and embedding-based measures. By enabling controlled generation of synthetic localisation data, SynthMLM provides a practical resource for benchmarking SMLM analysis methods, testing algorithm failure modes, and developing machine-learning workflows where large, labelled datasets are required.

biophysics↗

bioRxiv2026

VLab4Mic: prediction of structural resolvability in super-resolution microscopy

Determining whether a microscopy experiment can resolve a specific feature of a protein assembly remains difficult because researchers must balance imaging modality, labelling strategy, and probe choice. We present VLab4Mic, a simulation platform that predicts structural resolvability before experiments. Starting from atomic models from the PDB or AlphaFold predictions, VLab4Mic places antibodies, nanobodies, chemical linkers, or fluorescent proteins on epitopes, applies stochastic labelling and steric constraints, and generates virtual samples for widefield, confocal, AiryScan, Stimulated Emission Depletion (STED), and Single-Molecule Localisation Microscopy (SMLM). Simulations of nuclear pore complexes agree with experimental data across all five modalities. In case studies, HIV capsid appearance depended strongly on orientation, and STED and SMLM separated domed from flat clathrin lattices where confocal and AiryScan did not. VLab4Mic therefore lets researchers judge which biological questions a given imaging configuration can answer before spending time tuning parameters at the microscope.

bioinformatics↗

bioRxiv2025

Integrated metabolomic and genomic insights into amino acid incorporation within the hybrid polyketide-alkaloid antibiotic TLN-05220

Actinobacteria are a rich source of bioactive compounds and unique biosynthetic chemistry. Micromonospora echinospora subsp. challisensis NRRL 12255 produces the aromatic polyketide TLN-05220, which exhibits nanomolar activity against antibiotic-resistant human pathogens including vancomycin-resistant Enterococcus faecalis and methicillin-resistant Staphylococcus aureus. The pentangular polyphenol core of TLN-05220 is decorated with a piperazinone moiety, yet the enzymes responsible for the construction of this uncommon modification from amino acid precursors are unknown. Synthetic piperazinone-containing molecules have diverse antimicrobial, antiviral, anticancer, and anti-inflammatory bioactivity profiles, and determining biosynthetic routes for the assembly of this heterocycle may enhance drug discovery and medicinal chemistry efforts. We identified a putative TLN-05220 biosynthetic gene cluster (BGC) in the commercially available strain M. echinospora ATCC 15837 containing both type-I and type-II polyketide synthases, two predicted asparagine synthetase-like enzymes, and two genes (tln1 and tln5) that putatively encode pyridoxal 5-phosphate (PLP)-dependent amino acid synthases. Stable isotopic feeding studies coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS), identified L-alanine, L-serine, and glycine as metabolic precursors of TLN-05220. Subsequent in vitro enzymology established that Tln1 is a PLP-dependent alanine racemase, while Tln5 performs a stereoselective {beta}-substitution reaction of O-phospho-L-serine with a preferential D-alanine nucleophile. Alanine racemization and Tln5 pseudodipeptide L-serine-C{beta}-N-D-alanine (D,L-PDP) incorporation into TLN-05220 were further supported using deuterated intermediates and mass spectrometry techniques. Establishing the enzymes that catalyze amino acid installation within TLN-05220 inspires further biosynthetic discovery and engineering while enabling the biocatalytic syntheses of novel amino acid-containing polyketide antibiotics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/685158v1_ufig1.gif" ALT="Figure 1"> View larger version (20K): org.highwire.dtl.DTLVardef@4402e8org.highwire.dtl.DTLVardef@11af789org.highwire.dtl.DTLVardef@1717c5borg.highwire.dtl.DTLVardef@19b6529_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2025

Nanoscale spatial-omics via contrastive embedding of single-molecule localisation data

Omics approaches have revolutionised biology, and cells can now be routinely characterised on the genomic, transcriptomic and proteomic levels. However, there is an additional pillar; the (nanoscale) spatial organisation of molecules in the cell - information now accessible through super-resolution microscopy. We present a contrastive learning framework for nanoscale spatial-omics that embeds single-molecule localisation microscopy data into a latent space representing protein architecture directly to enabling comparative analysis. Using simulated and experimental data, we demonstrate its ability to enable new bioanalysis capabilities including assessing changes to cellular nanoscale architecture arising from pharmacological treatments, cell type, fluorophore selection or data-processing workflows. The approach supports downstream tasks such as clustering proteins by nanoscale organisation, mapping dose-response trajectories and identifying batch effects in replicate datasets, establishing contrastive learning as a scalable foundation for nanoscale spatial-omics and providing a platform for comparative phenotyping, quality control, and hypothesis generation.

bioinformatics↗

bioRxiv2024

Nano-org, a functional resource for single-molecule localisation microscopy data

We present a publicly accessible, curated, and functional resource, termed "nano-org", containing single-molecule localisation microscopy (SMLM) data representing the nanoscale distributions of proteins in cells. Nano-org is searchable by comparing the statistical similarity of the datasets it contains. This unique functionality allows the resource to be used to understand the relationships of nanoscale architectures between proteins, cell types or conditions, enabling a new field of spatial nano-omics.

biophysics↗

bioRxiv2022

Single-molecule analysis of receptor-beta-arrestin interactions in living cells

{beta}-arrestin plays a key role in G protein-coupled receptor (GPCR) signaling and desensitization. Despite recent structural advances, the mechanisms that govern receptor-{beta}-arrestin interactions at the plasma membrane of living cells remain elusive. Here, we combine single-molecule microscopy with molecular dynamics simulations to dissect the complex sequence of events involved in {beta}-arrestin interactions with both receptors and the lipid bilayer. In contrast to the currently widely accepted model, we show that {beta}-arrestin spontaneously inserts into the lipid bilayer and transiently interacts with receptors via lateral diffusion on the plasma membrane. Moreover, we show that following receptor interaction, the plasma membrane stabilizes {beta}-arrestin in a membrane-bound, active-like conformation, allowing it to diffuse to clathrin coated pits separately from the activating receptor. These results challenge our current understanding of {beta}-arrestin function at the plasma membrane, revealing a new critical role for {beta}-arrestin pre-association with the lipid bilayer in facilitating its interactions with receptors and subsequent activation.

cell biology↗

bioRxiv2021

A framework for evaluating the performance of SMLM cluster analysis algorithms

Single molecule localisation microscopy (SMLM) generates data in the form of Cartesian coordinates of localised fluorophores. Cluster analysis is an attractive route for extracting biologically meaningful information from such data and has been widely applied. Despite the range of developed cluster analysis algorithms, there exists no consensus framework for the evaluation of their performance. Here, we use a systematic approach based on two metrics, the Adjusted Rand Index (ARI) and Intersection over Union (IoU), to score the success of clustering algorithms in diverse simulated clustering scenarios mimicking experimental data. We demonstrate the framework using three analysis algorithms: DBSCAN, ToMATo and KDE, show how to deduce optimal analysis parameters and how they are affected by fluorophore multiple blinking. We propose that these standard conditions and metrics become the basis for future analysis algorithm development and evaluation.

biophysics↗

bioRxiv2021

Correction of multiple-blinking artefacts in photoactivated localisation microscopy

Photoactivated localisation microscopy (PALM) produces an array of localisation coordinates by means of photoactivatable fluorescent proteins. However, observations are subject to fluorophore multiple-blinking and each protein is included in the dataset an unknown number of times at different positions, due to localisation error. This causes artificial clustering to be observed in the data. We present a workflow using calibration-free estimation of blinking dynamics and model-based clustering, to produce a corrected set of localisation coordinates now representing the true underlying fluorophore locations with enhanced localisation precision. These can be reliably tested for spatial randomness or analysed by other clustering approaches, and previously inestimable descriptors such as the absolute number of fluorophores per cluster are now quantifiable, which we validate with simulated data. Using experimental data, we confirm that the adaptor protein, LAT, is clustered at the T cell immunological synapse, with its nanoscale clustering properties depending on location and intracellular phosphorylatable tyrosine residues.

biophysics↗

bioRxiv2020

Quantitative mapping of membrane nanoenvironments through single-molecule imaging of solvatochromic probes

Environmentally-sensitive fluorophores report on their local biochemical or biophysical environments through changes in their emission. We combine the solvatochromic probe di-4-ANEPPDHQ with multi-channel SMLM and quantitative analysis of the resulting marked point patterns to map biophysical environments in the mammalian cell membrane. We show that plasma membrane properties can be mapped with nanoscale resolution, and that partitioning between ordered and disordered regions is observed on length scales below 300 nm.

biophysics↗

bioRxiv2020

Asymmetric phospholipids impart novel biophysical properties to lipid bilayers allowing environmental adaptation

Phospholipids are a diverse group of biomolecules consisting of a hydrophilic head group and two hydrophobic acyl tails. The nature of the head and length and saturation of the acyl tails are important for defining the biophysical properties of lipid bilayers. It has recently been shown that the membranes of certain yeast species contain high levels of unusual asymmetric phospholipids, consisting of one long and one medium chain acyl moiety - a configuration not common in mammalian cells or other well studied model yeast species. This raises the possibility that structurally asymmetric phospholipids impart novel biophysical properties to the yeast membranes. Here, we use atomistic molecular dynamics simulations (MD) and environmentally-sensitive fluorescent membrane probes to characterize key biophysical parameters of membranes formed from asymmetric lipids for the first time. Interestingly, we show that saturated, but asymmetric phospholipids maintain membrane lipid order across a wider range of temperatures and do not require acyl tail unsaturation or sterols to maintain their properties. This may allow cells to maintain membrane fluidity even in environments which lack the oxygen required for the synthesis of unsaturated lipids and sterols.

biophysics↗

bioRxiv2019

Blinking Statistics and Molecular Counting in direct Stochastic Reconstruction Microscopy (dSTORM)

MotivationMany recent advancements in single molecule localisation microscopy exploit the stochastic photo-switching of fluorophores to reveal complex cellular structures beyond the classical diffraction limit. However, this same stochasticity makes counting the number of molecules to high precision extremely challenging, preventing key insight into the cellular structures and processes under observation. ResultsModelling the photo-switching behaviour of a fluorophore as an unobserved continuous time Markov process transitioning between a single fluorescent and multiple dark states, and fully mitigating for missed blinks and false positives, we present a method for computing the exact probability distribution for the number of observed localisations from a single photo-switching fluorophore. This is then extended to provide the probability distribution for the number of localisations in a dSTORM experiment involving an arbitrary number of molecules. We demonstrate that when training data is available to estimate photo-switching rates, the unknown number of molecules can be accurately recovered from the posterior mode of the number of molecules given the number of localisations. Finally, we demonstrate the method on experimental data by quantifying the number of adapter protein Linker for Activation of T cells (LAT) on the cell surface of the T cell immunological synapse. AvailabilitySoftware available at https://github.com/lp1611/mol_count_dstorm.

biophysics↗

bioRxiv2019

Three-dimensional total internal reflection fluorescence nanoscopy with sub-10 nm resolution

Single-molecule localization microscopy (SMLM) enables far-field imaging with lateral resolution in the range of 10 to 20 nanometres, exploiting the fact that the centre position of a single molecules image can be determined with much higher accuracy than the size of that image itself. However, attaining the same level of resolution in the axial (third) dimension remains challenging. Here, we present SIMPLER, a photometric method to decode the axial position of single molecules in a total internal reflection fluorescence (TIRF) microscope. SIMPLER requires no hardware modification whatsoever to a conventional TIRF microscope, and complements any 2D SMLM method to deliver 3D images with nearly isotropic nanometric resolution. Examples of the performance of SIMPLER include the visualization of the nuclear pore complex through dSTORM with sub-20 nm resolution and of microtubule cross-sections resolved with sub-10 nm through DNA-PAINT.

biophysics↗

bioRxiv2018

Machine-learning for cluster analysis of localization microscopy data.

Quantifying the clustering of points within single-molecule localization microscopy data is useful to understanding the spatial relationships of the molecules in the underlying sample. The conversion of point pattern data into a meaningful description of clustering is difficult, especially for biologically derived data, as the definitions of clustering are often subjective or simplistic. Many existing computational approaches are also limited in their ability to process large-scale data-sets or to deal effectively with inhomogeneities in clustering. Here we have developed a supervised machine-learning approach to cluster analysis which is fast and accurate. Trained on a variety of simulated clustered data, the network can then classify all points from a typical localization microscopy data-set (several million points from the entire field of view) as being either clustered or not-clustered, with the potential to include additional classifiers to describe different types of clusters. Clustered points can then be further refined into like-clusters for the measurement of cluster area, shape, and point-density. We demonstrate the performance on simulated data and experimental data of the kinase Csk and the adaptor PAG in both naive and pre-stimulated primary human T cell synapses.

cell biology↗