Post on 20-Jul-2020
Erzeugung und Klassifizierung größerer
Datenmengen im High-Content ScreeningOlympus scanR
Product Unit Life Science Research | Olympus Soft Imaging Solutions | Dr. Mike Wördemann
Linz, 28th Nov. 2017
High-Content Screening
▪ Automated, image-based cytometry
▪ Screening at cellular level
▪ Simultaneous multi-parameter readout
▪ Demands
• Robustness
• Reliability
• Automation
• Quantification
▪ For biological research and drug discovery
Olympus Soft Imaging SolutionsPage 2
https://www.olympus-lifescience.com
Statistics Volume Comparison
Olympus Soft Imaging SolutionsPage 3
Imaging
System
10
9
Flow Cytometer
Plate Reader
Sample throughput
Cells
/ s
am
ple
10
61
03
100.0001000
Image-based
Cytometry
Workflow
Olympus Soft Imaging SolutionsPage 4
Processing & Analysis
(image level)Data Analysis Result OutputAcquisition
Automated
High Throughput
Multi well micro plates, for example 96W, 384W
Automatic well plate loader
Full automation, integration into sample preparation pipelines
Olympus Soft Imaging SolutionsPage 5
Source: Olympus marketing video
Cytometric data exploration
Page 6
Example: Multi colour beads
– Image acquisition
– Image processing
– Object segmentation
– Parameter extraction
Olympus Soft Imaging Solutions
Cytometric data exploration
Page 7
Example: Multi colour beads
Exploring data to find the relevant parameters
Olympus Soft Imaging Solutions
Cytometric classification
Page 8
Example: Multi colour beads
Classification in
parameter space
Olympus Soft Imaging Solutions
Cytometric classification
Page 9
Example: Multi colour beads
Cascaded „Gating“ enables even
complex classification tasks
Olympus Soft Imaging Solutions
Cytometric classification
Page 10
Example: Mitotic analysis of fixed cells (ensemble-based)
2x DNA content
1x DNA content
Olympus Soft Imaging Solutions
Cytometric classification
Page 11
Example: Mitotic analysis of fixed cells (ensemble-based)
2x DNA content
1x DNA content
Mitotic phase (~1%)
micro well plate distribution
Olympus Soft Imaging Solutions
Life cell cytometry
Page 12
Example: Mitotic analysis of life cells (time-based)
Cytometric concept can be transfered to time-varying data
Extract kinetic parameters from curves of static parameters, for example:
– GFP mitosis marker over time peaks during mitosis
– Static parameter: GFP content
– Kinetic parameter
1. maximum peak value of GFP over time
2. average GFP value over time
– classification on kinetic parameters
Olympus Soft Imaging Solutions
Life cell cytometry
Page 13
Example: Mitotic analysis of life cells (time-based)
Cytometric concept can be transfered to time-varying data
Extract kinetic parameters from curves of static parameters, for example:
– GFP mitosis marker over time peaks during mitosis
– Static parameter: GFP content
– Kinetic parameter
1. maximum peak value of GFP over time
2. average GFP value over time
– classification on kinetic parameters
micro well plate distribution
Olympus Soft Imaging Solutions
Conclusions
Page 14
Cytometric classification concept allows intuitive classification based on biological
properties (phenotype and labels)
“Rare events” can easily be identified
Can be extened to time-varying data
Scales well up to many 10 million data points
Challenges and potential future Requirements include label-free assays, faster data
generation (more statistics), and ML-based image segmentation
Olympus Soft Imaging Solutions