DeepMIB : User-friendly and open-source software for training of deep learning network for biological image segmentation

We present DeepMIB, a new software package that is capable of training convolutional neural networks for segmentation of multidimensional microscopy datasets on any workstation. We demonstrate its successful application for segmentation of 2D and 3D electron and multicolor light microscopy datasets with isotropic and anisotropic voxels. We distribute DeepMIB as both an open-source multi-platform Matlab code and as compiled standalone application for Windows, MacOS and Linux. It comes in a single package that is simple to install and use as it does not require knowledge of programming. DeepMIB is suitable for everyone interested of bringing a power of deep learning into own image segmentation workflows. Author summary Deep learning approaches are highly sought after solutions for coping with large amounts of collected datasets and are expected to become an essential part of imaging workflows. However, in most cases, deep learning is still considered as a complex task that only image analysis experts can master. With DeepMIB we address this problem and provide the community with a user-friendly and open-source tool to train convolutional neural networks and apply them to segment 2D and 3D grayscale or multi-color datasets.Peer reviewe

Endoplasmic reticulum remains continuous and undergoes sheet-to-tubule transformation during cell division in mammalian cells

The endoplasmic reticulum (ER) is a multifaceted cellular organelle both structurally and functionally, and its cell cycle–dependent morphological changes are poorly understood. Our quantitative confocal and EM analyses show that the ER undergoes dramatic reorganization during cell division in cultured mammalian cells as mitotic ER profiles become shorter and more branched. 3D modeling by electron tomography reveals that the abundant interphase structures, sheets, are lost and subsequently transform into a branched tubular network that remains continuous. This is confirmed by observing the most prominent ER subdomain, the nuclear envelope (NE). A NE marker protein spreads to the mitotic ER tubules, although it does not show a homogenous distribution within the network. We mimicked the mitotic ER reorganization using puromycin to strip the membrane-bound ribosomes from the interphase ER corresponding to the observed loss of ribosomes normally occurring during mitosis. We propose that the structural changes in mitotic ER are linked to ribosomal action on the ER membranes

Morphological Heterogeneity of the Endoplasmic Reticulum within Neurons and Its Implications in Neurodegeneration

The endoplasmic reticulum (ER) is a multipurpose organelle comprising dynamic structural subdomains, such as ER sheets and tubules, serving to maintain protein, calcium, and lipid homeostasis. In neurons, the single ER is compartmentalized with a careful segregation of the structural subdomains in somatic and neurite (axodendritic) regions. The distribution and arrangement of these ER subdomains varies between different neuronal types. Mutations in ER membrane shaping proteins and morphological changes in the ER are associated with various neurodegenerative diseases implying significance of ER morphology in maintaining neuronal integrity. Specific neurons, such as the highly arborized dopaminergic neurons, are prone to stress and neurodegeneration. Differences in morphology and functionality of ER between the neurons may account for their varied sensitivity to stress and neurodegenerative changes. In this review, we explore the neuronal ER and discuss its distinct morphological attributes and specific functions. We hypothesize that morphological heterogeneity of the ER in neurons is an important factor that accounts for their selective susceptibility to neurodegeneration.Peer reviewe

Golgi clusters and vesicles mediate mitotic inheritance independently of the endoplasmic reticulum

We have examined the fate of Golgi membranes during mitotic inheritance in animal cells using four-dimensional fluorescence microscopy, serial section reconstruction of electron micrographs, and peroxidase cytochemistry to track the fate of a Golgi enzyme fused to horseradish peroxidase. All three approaches show that partitioning of Golgi membranes is mediated by Golgi clusters that persist throughout mitosis, together with shed vesicles that are often found associated with spindle microtubules. We have been unable to find evidence that Golgi membranes fuse during the later phases of mitosis with the endoplasmic reticulum (ER) as a strategy for Golgi partitioning (Zaal, K.J., C.L. Smith, R.S. Polishchuk, N. Altan, N.B. Cole, J. Ellenberg, K. Hirschberg, J.F. Presley, T.H. Roberts, E. Siggia, et al. 1999. Cell. 99:589–601) and suggest that these results, in part, are the consequence of slow or abortive folding of GFP–Golgi chimeras in the ER. Furthermore, we show that accurate partitioning is accomplished early in mitosis, by a process of cytoplasmic redistribution of Golgi fragments and vesicles yielding a balance of Golgi membranes on either side of the metaphase plate before cell division

DeepACSON automated segmentation of white matter in 3D electron microscopy

Tracing the entirety of ultrastructures in large three-dimensional electron microscopy (3D-EM) images of the brain tissue requires automated segmentation techniques. Current segmentation techniques use deep convolutional neural networks (DCNNs) and rely on high-contrast cellular membranes and high-resolution EM volumes. On the other hand, segmenting low-resolution, large EM volumes requires methods to account for severe membrane discontinuities inescapable. Therefore, we developed DeepACSON, which performs DCNN-based semantic segmentation and shape-decomposition-based instance segmentation. DeepACSON instance segmentation uses the tubularity of myelinated axons and decomposes under-segmented myelinated axons into their constituent axons. We applied DeepACSON to ten EM volumes of rats after sham-operation or traumatic brain injury, segmenting hundreds of thousands of long-span myelinated axons, thousands of cell nuclei, and millions of mitochondria with excellent evaluation scores. DeepACSON quantified the morphology and spatial aspects of white matter ultrastructures, capturing nanoscopic morphological alterations five months after the injury. With DeepACSON, Abdollahzadeh et al. combines existing deep learning-based methods for semantic segmentation and a novel shape decomposition technique for the instance segmentation. The pipeline is used to segment low-resolution 3D-EM datasets allowing quantification of white matter morphology in large fields-of-view.Peer reviewe

Automated 3D Axonal Morphometry of White Matter

Peer reviewe

REEP3 and REEP4 determine the tubular morphology of the endoplasmic reticulum during mitosis

The endoplasmic reticulum (ER) is extensively remodeled during metazoan open mitosis. However, whether the ER becomes more tubular or more cisternal during mitosis is controversial, and dedicated factors governing the morphology of the mitotic ER have remained elusive. Here, we describe the ER membrane proteins REEP3 and REEP4 as major determinants of ER morphology in metaphase cells. REEP3/4 are specifically required for generating the high-curvature morphology of mitotic ER and promote ER tubulation through their reticulon homology domains (RHDs). This ER-shaping activity of REEP3/4 is distinct from their previously described function to clear ER from metaphase chromatin. We further show that related REEP proteins do not contribute to mitotic ER shaping and provide evidence that the REEP3/4 carboxyterminus mediates regulation of the proteins. These findings confirm that ER converts to higher curvature during mitosis, identify REEP3/4 as specific and crucial morphogenic factors mediating ER tubulation during mitosis, and define the first cell cycle-specific role for RHD proteins.Peer reviewe

Microscopic characterization reveals the diversity of EVs secreted by GFP-HAS3 expressing MCF7 cells

We have shown the connection of hyaluronan synthesis activity with the enhanced shedding of extracellular vesicles, but detailed morphological analysis of those hyaluronan-induced EVs is still missing. In this study we utilized a comprehensive set of high-resolution imaging techniques to characterize in high detail the size and morphology of EVs originating from stable MCF7 breast cancer cell line and transiently transfected cells expressing GFP-HAS3. To avoid possible artefacts or loss of EVs resulting from the isolation process, special attention was paid to analysis of EVs in situ in monolayer and in 3D cultures. The results of this study show that GFP-HAS3 expressing MCF7 cells produce morphologically diverse EVs but also demonstrates the variation in results obtained with different experimental setup, which emphasizes the importance of comparison between different methods when interpreting the observations.Peer reviewe

gACSON software for automated segmentation and morphology analyses of myelinated axons in 3D electron microscopy

Background and Objective: Advances in electron microscopy (EM) now allow three-dimensional (3D) imaging of hundreds of micrometers of tissue with nanometer-scale resolution, providing new opportunities to study the ultrastructure of the brain. In this work, we introduce a freely available Matlab-based gACSON software for visualization, segmentation, assessment, and morphology analysis of myelinated axons in 3D-EM volumes of brain tissue samples. Methods: The software is equipped with a graphical user interface (GUI). It automatically segments the intra-axonal space of myelinated axons and their corresponding myelin sheaths and allows manual segmentation, proofreading, and interactive correction of the segmented components. gACSON analyzes the morphology of myelinated axons, such as axonal diameter, axonal eccentricity, myelin thickness, or gratio. Results: We illustrate the use of the software by segmenting and analyzing myelinated axons in six 3DEM volumes of rat somatosensory cortex after sham surgery or traumatic brain injury (TBI). Our results suggest that the equivalent diameter of myelinated axons in somatosensory cortex was decreased in TBI animals five months after the injury. Conclusion: Our results indicate that gACSON is a valuable tool for visualization, segmentation, assessment, and morphology analysis of myelinated axons in 3D-EM volumes. It is freely available at https://github.com/AndreaBehan/g-ACSON under the MIT license. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )Peer reviewe

Quantification of anisotropy and orientation in 3D electron microscopy and diffusion tensor imaging in injured rat brain

Diffusion tensor imaging (DTI) reveals microstructural features of grey and white matter non-invasively. The contrast produced by DTI, however, is not fully understood and requires further validation. We used serial block-face scanning electron microscopy (SBEM) to acquire tissue metrics, i.e., anisotropy and orientation, using three-dimensional Fourier transform-based (3D-FT) analysis, to correlate with fractional anisotropy and orientation in DTI. SBEM produces high-resolution 3D data at the mesoscopic scale with good contrast of cellular membranes. We analysed selected samples from cingulum, corpus callosum, and perilesional cortex of sham-operated and traumatic brain injury (TBI) rats. Principal orientations produced by DTI and 3D-FT in all samples were in good agreement. Anisotropy values showed similar patterns of change in corresponding DTI and 3D-FT parameters in sham-operated and TBI rats. While DTI and 3D-FT anisotropy values were similar in grey matter, 3D-FT anisotropy values were consistently lower than fractional anisotropy values from DTI in white matter. We also evaluated the effect of resolution in 3D-FT analysis. Despite small angular differences in grey matter samples, lower resolution datasets provided reliable results, allowing for analysis of larger fields of view. Overall, 3D SBEM allows for more sophisticated validation studies of diffusion imaging contrast from a tissue microstructural perspective.Peer reviewe