Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy
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 and digitalisation allowing routine capture of large areas a...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-12-01
|
| Series: | npj Imaging |
| Online Access: | https://doi.org/10.1038/s44303-024-00059-7 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850119279964323840 |
|---|---|
| author | B. H. Peter Duinkerken Ahmad M. J. Alsahaf Jacob P. Hoogenboom Ben N. G. Giepmans |
| author_facet | B. H. Peter Duinkerken Ahmad M. J. Alsahaf Jacob P. Hoogenboom Ben N. G. Giepmans |
| author_sort | B. H. Peter Duinkerken |
| collection | DOAJ |
| description | 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 and digitalisation allowing routine capture of large areas and volumes at nanoscale resolution. Analysis, however, is hampered by the greyscale nature of electron images and their large data volume, often requiring laborious manual annotation. Here we demonstrate unsupervised and automated extraction of biomolecular assemblies in conventionally processed tissues using large-scale hyperspectral energy-dispersive X-ray (EDX) imaging. First, we discriminated biological features in the context of tissue based on selected elemental maps. Next, we designed a data-driven workflow based on dimensionality reduction and spectral mixture analysis, allowing the visualization and isolation of subcellular features with minimal manual intervention. Broad implementations of the presented methodology will accelerate the understanding of biological ultrastructure. |
| format | Article |
| id | doaj-art-c9b8f4dd120d4cc38148bdfb0f3913db |
| institution | OA Journals |
| issn | 2948-197X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | npj Imaging |
| spelling | doaj-art-c9b8f4dd120d4cc38148bdfb0f3913db2025-08-20T02:35:40ZengNature Portfolionpj Imaging2948-197X2024-12-01211910.1038/s44303-024-00059-7Automated analysis of ultrastructure through large-scale hyperspectral electron microscopyB. H. Peter Duinkerken0Ahmad M. J. Alsahaf1Jacob P. Hoogenboom2Ben N. G. Giepmans3Department of Biomedical Sciences, University Groningen, University Medical Centre GroningenDepartment of Biomedical Sciences, University Groningen, University Medical Centre GroningenDepartment of Imaging Physics, Delft University of TechnologyDepartment of Biomedical Sciences, University Groningen, University Medical Centre GroningenAbstract 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 and digitalisation allowing routine capture of large areas and volumes at nanoscale resolution. Analysis, however, is hampered by the greyscale nature of electron images and their large data volume, often requiring laborious manual annotation. Here we demonstrate unsupervised and automated extraction of biomolecular assemblies in conventionally processed tissues using large-scale hyperspectral energy-dispersive X-ray (EDX) imaging. First, we discriminated biological features in the context of tissue based on selected elemental maps. Next, we designed a data-driven workflow based on dimensionality reduction and spectral mixture analysis, allowing the visualization and isolation of subcellular features with minimal manual intervention. Broad implementations of the presented methodology will accelerate the understanding of biological ultrastructure.https://doi.org/10.1038/s44303-024-00059-7 |
| spellingShingle | B. H. Peter Duinkerken Ahmad M. J. Alsahaf Jacob P. Hoogenboom Ben N. G. Giepmans Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy npj Imaging |
| title | Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy |
| title_full | Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy |
| title_fullStr | Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy |
| title_full_unstemmed | Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy |
| title_short | Automated analysis of ultrastructure through large-scale hyperspectral electron microscopy |
| title_sort | automated analysis of ultrastructure through large scale hyperspectral electron microscopy |
| url | https://doi.org/10.1038/s44303-024-00059-7 |
| work_keys_str_mv | AT bhpeterduinkerken automatedanalysisofultrastructurethroughlargescalehyperspectralelectronmicroscopy AT ahmadmjalsahaf automatedanalysisofultrastructurethroughlargescalehyperspectralelectronmicroscopy AT jacobphoogenboom automatedanalysisofultrastructurethroughlargescalehyperspectralelectronmicroscopy AT bennggiepmans automatedanalysisofultrastructurethroughlargescalehyperspectralelectronmicroscopy |