Quantitative 3D-imaging for cell biology and ecology of environmental microbial eukaryotes

• Published in: eLife Vol. 6
• Main Authors: Colin, Sebastien, Coelho, Luis Pedro, Sunagawa, Shinichi, Bowler, Chris, Karsenti, Eric, Bork, Peer, Pepperkok, Rainer, de Vargas, Colomban
• Format: Journal Article
• Language: English
• Published: England eLife Science Publications, Ltd 31.10.2017; eLife Sciences Publications Ltd; eLife Sciences Publication; eLife Sciences Publications, Ltd
• Subjects: Automated microscopy; Automation; Biodiversity; Cell Biology; Cells (Biology); Computational biology; Criminal investigation; DNA; Ecology; Ecosystem; Ecosystems; Environmental cell biology; Environmental Microbiology; Eukaryota - classification; Eukaryota - cytology; Eukaryota - physiology; Eukaryotes; Fluorescence; Fluorescence microscopy; Forests; Fungi; Imaging, Three-Dimensional - methods; Laboratories; Life Sciences; Machine learning; Marine plankton biodiversity; Microbial eukaryotes; Microorganisms; Microscopy; Molecular biology; Oceans; Optical Imaging - methods; Organisms; Plankton; Reason; Scientific equipment industry; Scientists; Software; Symbioses; Taxonomy; Tools and Resources; Venezuela; United States; ecology; cell biology; Automated microscopy; Machine learning; Microbial eukaryotes; Symbioses; Marine plankton biodiversity; Environmental cell biology
• ISSN: 2050-084X; 2050-084X
• DOI: 10.7554/eLife.26066

We present a 3D-fluorescence imaging and classification tool for high throughput analysis of microbial eukaryotes in environmental samples. It entails high-content feature extraction that permits accurate automated taxonomic classification and quantitative data about organism ultrastructures and interactions. Using plankton samples from the Oceans expeditions, we validate its applicability to taxonomic profiling and ecosystem analyses, and discuss its potential for future integration of eukaryotic cell biology into evolutionary and ecological studies.