Biology subjects

Vanslembrouck, B.

Publications and source records attributed to Vanslembrouck, B..

4 recordsLinked to original sources

bioRxiv2024

Automated segmentation of soft X-ray tomography: native cellular structure with sub-micron resolution at high throughput for whole-cell quantitative imaging in yeast

Soft X-ray tomography (SXT) is an invaluable tool for quantitatively analyzing cellular structures at sub-optical isotropic resolution. However, it has traditionally depended on manual segmentation, limiting its scalability for large datasets. Here, we leverage a deep learning-based auto-segmentation pipeline to segment and label cellular structures in hundreds of cells across three Saccharomyces cerevisiae strains. This task-based pipeline employs manual iterative refinement to improve segmentation accuracy for key structures, including the cell body, nucleus, vacuole, and lipid droplets, enabling high-throughput and precise phenotypic analysis. Using this approach, we quantitatively compared the 3D whole-cell morphometric characteristics of wild-type, VPH1-GFP, and vac14 strains, uncovering detailed strain-specific cell and organelle size and shape variations. We show the utility of SXT data for precise 3D curvature analysis of entire organelles and cells and detection of fine morphological features using surface meshes. Our approach facilitates comparative analyses with high spatial precision and statistical throughput, uncovering subtle morphological features at the single cell and population level. This workflow significantly enhances our ability to characterize cell anatomy and supports scalable studies on the mesoscale, with applications in investigating cellular architecture, organelle biology, and genetic research across diverse biological contexts. Significance StatementO_LISoft X-ray tomography offers many powerful features for whole-cell multi-organelle imaging, but, like other high resolution volumetric imaging modalities, is typically limited by low throughput due to laborious segmentation. C_LIO_LIAuto-segmentation for soft X-ray tomography overcomes this limitation, enabling statistical 3D morphometric analysis of multiple organelles in whole cells across cell populations. C_LIO_LIThe combination of high 3D resolution of SXT data with statistically useful throughput represents an avenue for more thorough characterizations of cells in toto and opens new mesoscale biological questions and statistical whole-cell modeling of organelle and cell morphology, interactions, and responses to perturbations. C_LI

cell biology↗

bioRxiv2024

Soft X-ray tomography reveals variations in B.subtilis biofilm structure upon tasA deletion

Bacterial biofilms are complex communities of cells within a self-produced extracellular matrix. They play crucial roles in healthcare, nutrition, agriculture and environmental research, yet an analysis of their elaborate 3D architecture remains challenging. Understanding mechanisms of biofilm formation, particularly the effects of chemical, physical, and genetic influences or modifications, is crucial but requires structural information at subcellular resolution to enable a community-level analysis of biofilms. In this work, we developed a "biofilm-in-capillary" growth method compatible with full-rotation soft X-ray tomography, providing high-resolution 3D imaging of bacterial cells and their surrounding extracellular matrix during biofilm formation, without drying or fixation steps. This approach offers 50 nm isotropic spatial resolution, rapid imaging time, and quantitative native analysis of biofilm structure. We demonstrate the potential of our method using Bacillus subtilis biofilms, detecting coherent alignment and chaining of wild-type cells while they are travelling towards the oxygen-rich capillary tip region. In stark contrast, the genetic knock-out {Delta}tasA shows a loss of cellular orientation, including changes in the extracellular matrix in volume and chemical density. Notably, we show that the addition of TasA protein to a culture of a {Delta}tasA strain restores the extracellular matrix density and leads to a compaction of cell assemblies, yet no chaining is observed as for the wildtype. Our approach to imaging biofilms is scalable and transferable, opening new avenues for examining biofilm structure and function across various species, including mixed biofilms, and observing 3D reorganization in response to genetic and environmental factors.

microbiology↗

bioRxiv2023

Indirect Correlative Light and Electron Microscopy (iCLEM): A Novel Pipeline for Multiscale Quantification of Structure from Molecules to Organs

Correlative light and electron microscopy (CLEM) methods are powerful methods which combine molecular organization (from light microscopy) with ultrastructure (from electron microscopy). However, CLEM methods pose high cost/difficulty barriers to entry and have very low experimental throughput. Therefore, we have developed an indirect correlative light and electron microscopy (iCLEM) pipeline to sidestep the rate limiting steps of CLEM (i.e., preparing and imaging the same samples on multiple microscopes) and correlate multiscale structural data gleaned from separate samples imaged using different modalities by exploiting biological structures identifiable by both light and electron microscopy as intrinsic fiducials. We demonstrate here an application of iCLEM, where we utilized gap junctions and mechanical junctions between muscle cells in the heart as intrinsic fiducials to correlate ultrastructural measurements from transmission electron microscopy (TEM), and focused ion beam scanning electron microscopy (FIB-SEM) with molecular organization from confocal microscopy and single molecule localization microscopy (SMLM). We further demonstrate how iCLEM can be integrated with computational modeling to discover structure-function relationships. Thus, we present iCLEM as a novel approach that complements existing CLEM methods and provides a generalizable framework that can be applied to any set of imaging modalities, provided suitable intrinsic fiducials can be identified.

systems biology↗

bioRxiv2022

Extending of imaging volume in soft x-ray tomography

Soft x-ray tomography offers rapid whole single cell imaging with a few tens of nanometers spatial resolution without fixation or labelling. At the moment, this technique is limited to 10 {micro}m thick specimens, such that applications of soft x-ray tomography to large human cells or multicellular specimens are not possible. We have developed a theoretical and experimental framework for soft x-ray tomography to enable extension of imaging volume to 18 {micro}m thick specimens. This approach, based on long depth of field and half-acquisition tomography, is easily applicable to existing full-rotation based microscopes. This opens applications for imaging of large human cells, which are often observed in cancer research and cell to cell interactions.

cell biology↗