Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy DOI Creative Commons
B.H. Peter Duinkerken, Ahmad Alsahaf, Jacob P. Hoogenboom

et al.

npj Imaging, Journal Year: 2024, Volume and Issue: 2(1)

Published: Dec. 11, 2024

Abstract Microscopy is a key technique to visualize and understand biology. Electron microscopy (EM) facilitates the investigation of cellular ultrastructure at biomolecular resolution. Cellular EM was recently revolutionized by automation digitalisation allowing routine capture large areas volumes nanoscale Analysis, however, hampered greyscale nature electron images their data volume, often requiring laborious manual annotation. Here we demonstrate unsupervised automated extraction assemblies in conventionally processed tissues using large-scale hyperspectral energy-dispersive X-ray (EDX) imaging. First, discriminated biological features context tissue based on selected elemental maps. Next, designed data-driven workflow dimensionality reduction spectral mixture analysis, visualization isolation subcellular with minimal intervention. Broad implementations presented methodology will accelerate understanding ultrastructure.

Language: Английский

Segmentation in large-scale cellular electron microscopy with deep learning: A literature survey DOI Creative Commons
Anusha Aswath, Ahmad Alsahaf, Ben N. G. Giepmans

et al.

Medical Image Analysis, Journal Year: 2023, Volume and Issue: 89, P. 102920 - 102920

Published: Aug. 6, 2023

Electron microscopy (EM) enables high-resolution imaging of tissues and cells based on 2D 3D techniques. Due to the laborious time-consuming nature manual segmentation large-scale EM datasets, automated approaches are crucial. This review focuses progress deep learning-based techniques in cellular throughout last six years, during which significant has been made both semantic instance segmentation. A detailed account is given for key datasets that contributed proliferation learning The covers supervised, unsupervised, self-supervised methods examines how these algorithms were adapted task segmenting sub-cellular structures images. special challenges posed by such images, like heterogeneity spatial complexity, network architectures overcame some them described. Moreover, an overview evaluation measures used benchmark various tasks provided. Finally, outlook current trends future prospects given, especially with models unlabeled images learn generic features across datasets.

Language: Английский

Citations

30
Serial Block Face‐Scanning Electron Microscopy as a Burgeoning Technology DOI Creative Commons
Andrea G. Marshall, Kit Neikirk,

Dominique C. Stephens

et al.

Advanced Biology, Journal Year: 2023, Volume and Issue: 7(8)

Published: May 28, 2023

Abstract Serial block face scanning electron microscopy (SBF‐SEM), also referred to as serial block‐face microscopy, is an advanced ultrastructural imaging technique that enables three‐dimensional visualization provides larger x ‐ and y ‐axis ranges than other volumetric EM techniques. While SEM first introduced in the 1930s, SBF‐SEM developed a novel method resolve 3D architecture of neuronal networks across large volumes with nanometer resolution by Denk Horstmann 2004. Here, authors provide accessible overview advantages challenges associated SBF‐SEM. Beyond this, applications biochemical domains well potential future clinical are briefly reviewed. Finally, alternative forms artificial intelligence‐based segmentation which may contribute devising feasible workflow involving SBF‐SEM, considered.

Language: Английский

Citations

25
Modular segmentation, spatial analysis and visualization of volume electron microscopy datasets DOI
Andreas Müller, Deborah Schmidt, Jan Philipp Albrecht

et al.

Nature Protocols, Journal Year: 2024, Volume and Issue: 19(5), P. 1436 - 1466

Published: Feb. 29, 2024

Language: Английский

Citations

9
Zooming into lipid droplet biology through the lens of electron microscopy DOI Creative Commons
Wioleta Dudka, Veijo T. Salo, Julia Mahamid

et al.

FEBS Letters, Journal Year: 2024, Volume and Issue: 598(10), P. 1127 - 1142

Published: May 1, 2024

Electron microscopy (EM), in its various flavors, has significantly contributed to our understanding of lipid droplets (LD) as central organelles cellular metabolism. For example, EM illuminated that LDs, contrast all other organelles, are uniquely enclosed by a single phospholipid monolayer, revealed the architecture LD contact sites with different and provided near‐atomic resolution maps key enzymes regulate neutral biosynthesis biogenesis. In this review, we first provide brief history pivotal findings biology unveiled through lens an electron microscope. We describe main techniques used context research discuss their current capabilities limitations, thereby providing foundation for utilizing suitable methodology address LD‐related questions sufficient level structural preservation, detail, resolution. Finally, highlight examples where recently been is expected be instrumental expanding frontiers biology.

Language: Английский

Citations

9
Efficient cell-wide mapping of mitochondria in electron microscopic volumes using webKnossos DOI Creative Commons
Yi Jiang, H. Wang, Kevin M. Boergens

et al.

Cell Reports Methods, Journal Year: 2025, Volume and Issue: 5(2), P. 100989 - 100989

Published: Feb. 1, 2025

Language: Английский

Citations

1
How innovations in methodology offer new prospects for volume electron microscopy DOI Creative Commons
Arent J. Kievits, Ryan Lane, Elizabeth C. Carroll

et al.

Journal of Microscopy, Journal Year: 2022, Volume and Issue: 287(3), P. 114 - 137

Published: July 10, 2022

Detailed knowledge of biological structure has been key in understanding biology at several levels organisation, from organs to cells and proteins. Volume electron microscopy (volume EM) provides high resolution 3D structural information about tissues on the nanometre scale. However, throughput rate conventional microscopes limited volume size number samples that can be imaged. Recent improvements methodology are currently driving a revolution EM, making possible imaging whole small organisms. In turn, these recent developments image acquisition have created or stressed bottlenecks other parts pipeline, like sample preparation, analysis data management. While progress is stunning due advent automatic segmentation server-based annotation tools, challenges remain. Here we discuss trends emerging methods for increasing implications

Language: Английский

Citations

27
A century journey of organelles research in the plant endomembrane system DOI

Xiaohong Zhuang,

Ruixi Li, Liwen Jiang

et al.

The Plant Cell, Journal Year: 2024, Volume and Issue: 36(5), P. 1312 - 1333

Published: Jan. 16, 2024

Abstract We are entering an exciting century in the study of plant organelles endomembrane system. Over past century, especially within 50 years, tremendous advancements have been made complex cell to generate a much clearer and informative picture organelles, including molecular/morphological features, dynamic/spatial behavior, physiological functions. Importantly, all these discoveries achievements identification characterization system would not possible without: (1) innovations timely applications various state-of-art biology tools technologies for organelle research; (2) continuous efforts developing characterizing new markers by community; (3) landmark studies on elusive organelles. While molecular aspects results individual extensively reviewed, development techniques research is less appreciated. As one ASPB Centennial Reviews “organelle biology,” here we aim take journey across plants highlighting important (or technologies) key scientists that contributed visualize then highlight leading systems.

Language: Английский

Citations

4
Giant mitochondria in human liver disease DOI Creative Commons
Gerald J. Shami, Iryna Samarska,

Ger H. Koek

et al.

Liver International, Journal Year: 2023, Volume and Issue: 43(11), P. 2365 - 2378

Published: Aug. 24, 2023

Abstract This thematic review aims to provide an overview of the current state knowledge about occurrence giant mitochondria or megamitochondria in liver parenchymal cells. Their presence and accumulation are considered be a major pathological hallmark health fate cells that leads overall tissue deterioration eventually results organ failure. The first description on dates back 1960s, coinciding with availability generation electron microscopes clinical diagnostic laboratories. Detailed accounts their ultrastructure have mostly been described patients suffering from alcoholic disease, chronic hepatitis, hepatocellular carcinoma non‐alcoholic fatty disease. Interestingly, this extensive literature survey, it became apparent present themselves without highly organised crystal‐like intramitochondrial inclusions. origin, formation potential role remain to‐date largely unanswered. Likewise, biochemical composition well‐organised inclusions possible impact mitochondrial function is unclear. Herein, concepts mechanism three‐dimensional architecture will approached. We furthermore discuss importance diagnostics, including future research outlooks therapeutic interventions cure disease where implemented.

Language: Английский

Citations

10
OmniEM: Unifying the EM Multiverse through a Large-scale Foundation Model DOI
Liuyuan He, Ruohua Shi, Wenyao Wang

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: April 19, 2025

ABSTRACT Room-temperature electron microscopy (EM) analysis is rapidly evolving but faces growing challenges due to massive data heterogeneity and fragmented methodologies, forming a significant bottleneck in advancing EM-based discovery. To overcome this, we present OmniEM, the first unified extensible foundation model framework that consolidates wide spectrum of EM tasks under one platform. At its core EM-DINO, most powerful EM-specific vision trained via large-scale self-supervised learning (SSL) on EM-5M, largest comprehensive dataset date, containing 5 million standardized images spanning diverse species, tissues, preparation protocols, imaging modalities, resolutions ranging from 0.5 nm 70 nm. Notably, this was curated through novel model-driven filtering protocol. EM-DINO demonstrates strong image understanding ability semantic classification, OmniEM extends capacity lightweight yet U-shaped architecture, enabling impressive performance robust mitochondrial segmentation, multi class subcellular segmentation more. By unifying data, model, software into cohesive foundation, marks critical step toward general-purpose understanding. consolidating multiple single framework, streamlines analysis, representing more efficient reusable workflows accelerate scientific The code for paper will be released soon.

Language: Английский

Citations

0
Multiple sclerosis: what have we learned and can we still learn from electron microscopy DOI Creative Commons
Wendy Oost, Jan F. Meilof, Wia Baron

et al.

Cellular and Molecular Life Sciences, Journal Year: 2025, Volume and Issue: 82(1)

Published: April 23, 2025

Language: Английский

Citations

0