Biology subjects

Barentine, A. E. S.

Publications and source records attributed to Barentine, A. E. S..

9 recordsLinked to original sources

bioRxiv2026

Organization of Myosin H in the Apical Complex of Toxoplasma Gondii Revealed by 3D Single-Molecule Super-Resolution Microscopy

Toxoplasma gondii is a single-celled eukaryotic parasite with prolific invasion capability. The parasite uses an apical complex comprised of proteinaceous structures and secretory organelles to efficiently enter host cells. As a result, the apical complex remains a vital structure of interest, with many studies dedicated to understanding its protein organization. One such protein is the motor Myosin H (MyoH), which is indispensable for parasite motility and host cell invasion. Given the small size of the complex, roughly a diffraction-limited volume in the visible, high-resolution techniques are required to make precise determinations of protein organization. In this work, we use 3D single-molecule localization microscopy in both traditionally fixed and gel-expanded parasites to localize the indispensable motor Myosin H within the apical complex. Labeling of the N- and C-terminus of MyoH in fixed parasites resolved the orientation of the motor protein in the apical complex, showing the motor head radially exterior to the tail. Two-color imaging of MyoH with tubulin in fixed parasites allowed for localization of the MyoH termini relative to the conoid, a barrel of tubulin-based fibers in the apical complex and showed the MyoH tail toward the interior face of the conoid and the head at the conoid exterior. Gel expansion showed improved labeling density for both tubulin and MyoH but altered MyoH localization, highlighting the nuanced effects of gel expansion on protein organization. Statement of SignificanceThis work employs 3D single-molecule super-resolution microscopy to provide quantitative physical analysis of the spatial organization of a vital myosin motor, MyoH, in the model apicomplexan parasite Toxoplasma gondii. While previous studies have provided high-resolution views of the parasites invasion machinery, MyoH has remained elusive at the nanoscale. We resolved differences in radial organization between the N- and C-termini of the motor, thus determining the orientation of the protein in the apical space. Two-color imaging revealed the organization of the motor in the greater context of the parasites invasion complex. 3D single-molecule imaging in gel-expanded samples revealed an increase in labeling efficiency but perturbed localization of only the MyoH C-terminus, highlighting the nuanced effects of gel expansion on protein organization.

biophysics↗

bioRxiv2025

Efficient Double Helix Detection with Steerable Filters

We present an efficient detection scheme for localization of Double Helix point-spread functions for 3D single-molecule localization microscopy or tracking. Using steerable filters, we extract both 2D position and lobe orientation (axial position) estimates using just 7 convolutions, orders of magnitude less than used in deep-learning-based approaches. We pair this detection with a fitter and implement both as a plug-in for the open source PYthon Microscopy Environment (PYME), which features percentile-based background subtraction, signal-to-noise-based detection thresholding, and performant parallel analysis. Our complete localization analysis pipeline achieves state-of-the-art performance with minimal user input.

biophysics↗

bioRxiv2023

Nanoscale cellular organization of viral RNA and proteins in SARS-CoV-2 replication organelles

The SARS-CoV-2 viral infection transforms host cells and produces special organelles in many ways, and we focus on the replication organelle where the replication of viral genomic RNA (vgRNA) occurs. To date, the precise cellular localization of key RNA molecules and replication intermediates has been elusive in electron microscopy studies. We use super-resolution fluorescence microscopy and specific labeling to reveal the nanoscopic organization of replication organelles that contain vgRNA clusters along with viral double-stranded RNA (dsRNA) clusters and the replication enzyme, encapsulated by membranes derived from the host endoplasmic reticulum (ER). We show that the replication organelles are organized differently at early and late stages of infection. Surprisingly, vgRNA accumulates into distinct globular clusters in the cytoplasmic perinuclear region, which grow and accommodate more vgRNA molecules as infection time increases. The localization of ER labels and nsp3 (a component of the double-membrane vesicle, DMV) at the periphery of the vgRNA clusters suggests that replication organelles are enclosed by DMVs at early infection stages which then merge into vesicle packets as infection progresses. Precise co-imaging of the nanoscale cellular organization of vgRNA, dsRNA, and viral proteins in replication organelles of SARS-CoV-2 may inform therapeutic approaches that target viral replication and associated processes.

microbiology↗

bioRxiv2020

PYMEVisualize: an open-source tool for exploring 3D super-resolution data

Localization-based super-resolution microscopy techniques such as PALM, STORM, and PAINT are increasingly critical tools for biological discovery. These methods generate lists of single fluorophore positions that capture nanoscale structural details of subcellular organisation, but to develop biological insight, we must post-process and visualize this data in a meaningful way. A large number of algorithms have been developed for localization post-processing, transforming point data into representations which approximate traditional microscopy images, and performing specific quantitative analysis directly on points. Implementations of these algorithms typically stand in isolation, necessitating complex workflows involving multiple different software packages. Here we present PYMEVisualize, an open-source tool for the interactive exploration and analysis of 3D, multicolor, single-molecule localization data. PYMEVisualize brings together a broad range of the most commonly used post-processing, density mapping, and direct quantification tools in an easy-to-use and extensible package. This software is one component of the PYthon Microscopy Environment (python-microscopy.org), an integrated application suite for light microscopy acquisition, data storage, visualization, and analysis built on top of the scientific Python environment.

biophysics↗

bioRxiv2020

DMA-tudor interaction modules control the specificity of in vivo condensates

Biomolecular condensation is a widespread mechanism of cellular compartmentalization. Because the survival of motor neuron protein (SMN) is required for the formation of three different membraneless organelles (MLOs), we hypothesized that at least one region of SMN employs a unifying mechanism of condensation. Unexpectedly, we show here that SMNs globular tudor domain was sufficient for dimerization-induced condensation in vivo, while its two intrinsically disordered regions (IDRs) were not. The condensate-forming property of the SMN tudor domain required binding to its ligand, dimethylarginine (DMA), and was shared by at least seven additional tudor domains in six different proteins. Remarkably, asymmetric versus symmetric DMA determined whether two distinct nuclear MLOs - gems and Cajal bodies - were separate or overlapping. These findings show that the combination of a tudor domain bound to its DMA ligand - DMA-tudor - represents a versatile yet specific interaction module that regulates MLO assembly and defines their composition.

biochemistry↗

bioRxiv2019

3D super-resolution deep-tissue imaging in living mice

Stimulated emission depletion (STED) microscopy enables the three-dimensional (3D) visualization of dynamic nanoscale structures in living cells, offering unique insights into their organization. However, 3D-STED imaging deep inside biological tissue is obstructed by optical aberrations and light scattering. We present a STED system that overcomes these challenges. Through the combination of 2-photon excitation, adaptive optics, far-red emitting organic dyes, and a long-working distance water-immersion objective lens, our system achieves aberration-corrected 3D super-resolution imaging, which we demonstrate 164 {micro}m deep in fixed mouse brain tissue and 76 {micro}m deep in the brain of a living mouse.

biophysics↗

bioRxiv2019

3D Multicolor Nanoscopy at 10,000 Cells a Day

Diffraction-unlimited single-molecule techniques like STORM and (F)PALM enable three-dimensional (3D) fluorescence imaging at tens of nanometer resolution and are invaluable to investigate sub-cellular organization. The multitude of camera frames required to reconstruct a super-resolved image limits the typical throughput of these techniques to tens of cells per day, rendering these methods incompatible with large-scale cell biological or clinical application. STORM acquisition rates can be increased by over an order of magnitude, however the data volumes of about 40 TB a day and concomitant analysis burdens exceed the capacity of existing workflows. Here we present an integrated platform which transforms SMLM from a trick-pony technique into a work horse for cell biology. We leverage our developments in microscopy-specific data compression, distributed storage, and distributed analysis to automatically perform real-time localization analysis, which enable SMLM at throughputs of 10,000 cells a day. We implemented these advances in a fully-integrated environment that supports a highly-flexible architecture for distributed analysis, enabling quickly- and graphically-reconfigurable analyses to be automatically initiated from the microscope during acquisition, remotely executed, and even feedback and queue new acquisition tasks on the microscope. We demonstrate the utility of this framework by imaging hundreds of cells per well in multi-well sample formats. Our platform, the PYthon-Microscopy Environment (PYME), is easily configurable for hardware control on custom microscopes, and includes a plugin framework so users can readily extend all components of their imaging, visualization, and analysis pipeline. PYME is cross-platform, open source, and efficiently puts high-caliber visualization and analysis tools into the hands of both microscope developers and users.

biophysics↗

bioRxiv2017

Nano-scale size holes in ER sheets provide an alternative to tubules for highly-curved membranes

The endoplasmic reticulum (ER) is composed of interconnected membrane sheets and tubules. Super-resolution microscopy recently revealed densely packed, rapidly moving ER tubules, highlighting the importance of revisiting classical views of ER structure with high spatial resolution in living cells. Using live-cell Stimulated Emission Depletion (STED) microscopy, we show highly dynamic, subdiffraction-sized holes in ER sheets. Holes coexist with uniform sheet regions and are distinct from tubular ER structures. The curvature-stabilizing reticulon protein Rtn4 localizes to these holes and the ER luminal tether Climp63 controls their diameter and mobility. Analytical modeling demonstrates that holes in ER sheets can serve as reservoirs for curvature-stabilizing proteins to support ER tubule extension and retraction, thus providing an explanation for how the ER locally alters its morphology on fast time-scales.\n\nOne Sentence SummaryDynamic nano-scale sized holes are prominent features of ER sheets that serve as reservoirs for curvature-stabilizing proteins to support ER tubule extension and retraction.

cell biology↗

bioRxiv2017

Simultaneously measuring image features and resolution in live-cell STED images

Reliable interpretation and quantification of cellular features in fluorescence microscopy requires an accurate estimate of microscope resolution. This is typically obtained by measuring the image of a non-biological proxy for a point-like object, such as a fluorescent bead. While appropriate for confocal microscopy, bead-based measurements are problematic for Stimulated Emission Depletion (STED) and similar techniques where the resolution depends critically on the choice of fluorophore and acquisition parameters. We demonstrate that for a known geometry, e.g. tubules, the resolution can be accurately measured by fitting a model that accounts for both the Point Spread Function (PSF) and the fluorophore distribution. To address the problem of coupling between tubule diameter and PSF width, we developed a technique, Nested-loop Ensemble PSF (NEP) fitting. NEP fitting enables extraction of the size of cellular features and the PSF in fixed-cell and live-cell images without relying on beads or pre-calibration. We validate our technique using fixed microtubules and apply it to measure the diameter of endoplasmic reticulum tubules in live COS-7 cells. NEP fitting has been implemented as a plugin for the PYthon Microscopy Environment (PYME), a freely available and open source software.

cell biology↗