Biology subjects

Duncan, L. H.

Publications and source records attributed to Duncan, L. H..

5 recordsLinked to original sources

bioRxiv2022

Comparative analysis of single-cell and single-nucleus RNA-sequencing in a rabbit model of retinal detachment-related proliferative vitreoretinopathy.

Structured AbstractO_ST_ABSPurposeC_ST_ABSProliferative vitreoretinopathy (PVR) is the most common cause of failure of retinal reattachment surgery and the molecular changes leading to this aberrant wound healing process is currently unknown. We aimed to study PVR pathogenesis using single-cell transcriptomics to dissect cellular heterogeneity in a rabbit PVR model. MethodsPVR was induced unilaterally in Dutch Belted rabbits. At different timepoints following PVR induction, retinas were dissociated into either cells or nuclei suspension and processed for single-cell or single-nucleus RNA sequencing (scRNA-seq or snRNA-seq). ResultsscRNA-Seq and snRNA-Seq were conducted on retinas at 4 hours and 14 days after disease induction. While the capture rate of unique molecular identifiers (UMI) and genes were greater in scRNA-seq samples, overall gene expression profiles of individual cell types were highly correlated between scRNA-seq and snRNA-seq. A major disparity between the two sequencing modalities is the cell type capture rate, however, with glial cell types over-represented in scRNA-seq, and inner retinal neurons were enriched by snRNA-seq. Furthermore, fibrotic Muller glia were over-represented in snRNA-seq samples, while reactive Muller glia were in scRNA-seq samples. Trajectory analyses were similar between the two methods, allowing for the combined analysis of the scRNA-seq and snRNA-seq datasets. ConclusionsThese findings highlight limitations of both scRNA-seq and snRNA-seq analysis and imply that use of both techniques can more accurately identify transcriptional networks critical for aberrant fibrogenesis in PVR.

neuroscience↗

bioRxiv2021

Multiview super-resolution microscopy

We enhance the performance of confocal microscopy over imaging scales spanning tens of nanometers to millimeters in space and milliseconds to hours in time, improving volumetric resolution more than 10-fold while simultaneously reducing phototoxicity. We achieve these gains via an integrated, four-pronged approach: 1) developing compact line-scanners that enable sensitive, rapid, diffraction-limited imaging over large areas; 2) combining line-scanning with multiview imaging, developing reconstruction algorithms that improve resolution isotropy and recover signal otherwise lost to scattering; 3) adapting techniques from structured illumination microscopy, achieving super-resolution imaging in densely labeled, thick samples; 4) synergizing deep learning with these advances, further improving imaging speed, resolution and duration. We demonstrate these capabilities on more than twenty distinct fixed and live samples, including protein distributions in single cells; nuclei and developing neurons in Caenorhabditis elegans embryos, larvae, and adults; myoblasts in Drosophila wing imaginal disks; and mouse renal, esophageal, cardiac, and brain tissues.

bioengineering↗

bioRxiv2020

A neurite-zippering mechanism, mediated by layer-specific expression of IgCAMs, regulates synaptic laminar specificity in the C. elegans nerve ring neuropil

During development, neurites and synapses segregate into specific neighborhoods or layers within nerve bundles. The developmental programs guiding placement of neurites in specific layers, and hence their incorporation into specific circuits, are not well understood. We implement novel imaging methods and quantitative models to document the embryonic development of the C. elegans brain neuropil, and discover that differential adhesion mechanisms control precise placement of single neurites onto specific layers. Differential adhesion is orchestrated via developmentally-regulated expression of the IgCAM SYG-1, and its partner ligand SYG-2. Changes in SYG-1 expression across neuropil layers result in changes in adhesive forces, which sort SYG-2-expressing neurons. Sorting to layers occurs, not via outgrowth from the neurite tip, but via an alternate mechanism of retrograde zippering, involving interactions between neurite shafts. Our study indicates that biophysical principles from differential adhesion govern neurite placement and synaptic specificity in vivo in developing neuropil bundles.

neuroscience↗

bioRxiv2020

Structural and developmental principles of neuropil assembly in C. elegans

Neuropil is a fundamental form of tissue organization within brains1. In neuropils, densely packed neurons synaptically interconnect into precise circuit architecture2,3, yet the structural and developmental principles governing nanoscale precision in bundled neuropil assembly remain largely unknown4-6. Here we use diffusion condensation, a coarse-graining clustering algorithm7, to identify nested circuit structures within the C. elegans cerebral neuropil (called the nerve ring). We determine that the nerve ring neuropil is organized into four tightly bundled strata composed of related behavioral circuits. We demonstrate that the stratified architecture of the neuropil is a geometrical representation of the functional segregation of sensory information and motor outputs, with specific sensory organs and muscle quadrants mapping onto particular neuropil strata. We identify groups of neurons with unique morphologies that integrate information across strata and that create a sophisticated honeycomb-shaped scaffold that encases the strata within the nerve ring. We resolve the developmental sequence leading to stratified neuropil organization through the integration of lineaging and cell tracking algorithms with high resolution light-sheet microscopy, and reveal principles of cell position, migration and hierarchical outgrowth that guide neuropil organization. Our results uncover conserved design principles underlying nerve ring neuropil architecture and function, and a pioneer neuron-based, temporal progression of outgrowth that guides the hierarchical development of the layered neuropil. Our findings provide a blueprint for using structural and developmental approaches to systematically understand neuropil organization within brains.

neuroscience↗

bioRxiv2019

Accelerating iterative deconvolution and multiview fusion by orders of magnitude

We describe theoretical and practical advances in algorithm and software design, resulting in ten to several thousand-fold faster deconvolution and multiview fusion than previous methods. First, we adapt methods from medical imaging, showing that an unmatched back projector accelerates Richardson-Lucy deconvolution by at least 10-fold, in most cases requiring only a single iteration. Second, we show that improvements in 3D image-based registration with GPU processing result in speedups of 10-100-fold over CPU processing. Third, we show that deep learning can provide further accelerations, particularly for deconvolution with a spatially varying point spread function. We illustrate the power of our methods from the subcellular to millimeter spatial scale, on diverse samples including single cells, nematode and zebrafish embryos, and cleared mouse tissue. Finally, we show that our methods facilitate the use of new microscopes that improve spatial resolution, including dual-view cleared tissue light-sheet microscopy and reflective lattice light-sheet microscopy.

bioengineering↗