1. CellMonitor Cell Incubator With Automated Imaging & Monitoring
photons at work
photons at work
CellMonitor
Cell Incubator With Automated Imaging & Monitoring

2. CellMonitor - System Overview

3. CellMonitor – Automated* Microscope in Incubator
System Overview
Automation of all functions
Fast screening
High resolution fluorescence and brightfield microscopy
Image recognition software
Integrated in cell culture incubator
Enviromental conditions control
Multiphoton microscopy and laser based cell manipulation** (on demand)
Incubation rack
Microscope-
table
Microscope
Lock
Robot
Transfer-
position
*developed by Fraunhofer IPM & FIT, ** developed by ROWIAK GmbH

4. Features of CellMonitor
High resolution microscopic imaging in brightfield and fluorescence mode
Image analysis of fluorescence signals
Monitoring of confluency and cell counting
Continuous documentation of cell growth parameters
Selection of transfected cell cultures and single cell colonies
Condition dependent system control
Constant quality control

5. CellMonitor – Microscope Configuration
Fully automated inverse microscope
Bright field and fluorescence modes
Hardware and software autofocus
Automated phase contrast
LED illumination at 530 nm and 464nm
Standard filter set: GFP (525nm), other filters on request
Integration of multiphoton microscopy possible

6. CellMonitor – Microscope Specifications
Transmitted light: LED
Fluorescence: reflected light illumination with LED's at a variety of wavelengths possible (e.g. 464nm, 488nm, 530nm)
Up to threee different filter sets
Objectives (standard outfit): 125x/0.04, 5x/0.12 with phase contrast, 40x/0.6 with phase contrast
Resolution down to 0.8µm
Sample carrier for microtiter plates
Autofocus: Fast hardware autofocus by optical triangulation for scanning, software autofocus for high resolution
Imaging speed: Complete scan of a 6 well MTP at 1.25x magnification ca. 200 images in ca. 4 min

7. MTP Handling
Loading of a MTP into the system

8. CellMonitor – Software Features

9. Standard Software Features
Analysis of cell confluency
Assessment of number of cells or confluent colonies
Reporting on position, roundness, and diameter of cells or cell colonies in the field of view
User adjustable cell recognition parameters
Standard software has been programmed to automatically recognize cells with certain optical performance i.e. transfected HeLa cells or mouse embryonic stem cells
Implementation of automatic recognition of cell types with other optical performance possible

10. Imaging Capabilities – Bright field
Sample images: Hela-Kyoto wild type
Brightfield 5x, phase contrast
Brightfield 40x, phase contrast
Cell cultures originate from the Max-Planck-Institut für Zellkultur und Genetik MPI-CBG

11. Imaging Capabilities – Bright field & Fluorescence
Sample images
Brightfield 40x
Brightfield 40x, phase contrast
Fluo 40x, Autofluorescence
Transgenic ES-cells
Transgenic ES-cells
Transgenic ES-cells
Cell cultures orginiate from Max-Planck-Institut für Zellkultur und Genetik MPI-CBG

12. Imaging Capabilities – Multiphoton Mode
Sample images
DAPI
DAPI
Connexin46-GFP
Connexin46-GFP
Multiphoton image of HeLa cells
3D reconstruction of 25µm Z-stack of HeLa cells

13. Imaging Capabilities – Multiphoton Mode
Sample images
Autofluorescence/SHG
Mosaic image of mouse vertebra (1x1mm)

14. Image Recognition Software
Confluency measurement
Self learning algorithms
User defines sample patterns for
1. Foreground
2. Background
Automated confluency measurement in high-throughput
Bright field mode
Recognized patterns

15. Image recognition software
Recognized number of cells 
Cell counting
Sample definition
Automatic identification of the remaining cells
Calculation of total cell number

16. TRAINED Foreground/Background analysis
Image Recognition – Colony Counting
Illumination filters
TRAINED Foreground/Background analysis
Extraction of individual regions
Selection of patterns based upon characteristics like diameter and morphology

17. TRAINED Foreground/Background analysis
Image recognition – Fluorescence I
Illumination filters
TRAINED Foreground/Background analysis
Extraction of individual regions
Selection of specific colonies

18. Image recognition – Fluorescence II
Selection of a background ring around the monitored region
Usage of masks (outer and inner part) on flourescent image
Measurement of the flourescence intensity without background

19. CellMonitor – Modular System Design

20. CellMonitor – Modularity
CellMonitor – Key Components
Fully automated microscope
Microscope incubator
Image recognition software
Multiphoton microscopy for imaging and manipulation (on request)
Additional modules can be added
Colony Picker

21. From CellMonitor to CellCultivator
Additional modules can be added to the Cell Monitor
Air recirculation Laminar-Flow
Microscope incubator
Liquid-handling unit
refrigerator
Pickermodule
Storage incubator
Workbench
2D-Planar table as handling system driven by linear motors incl. runner

22. Complete System - CellCultivator

23. Storage Incubator Grappler for MTP supply to the microscope table
Automated positing system
Conditions: 37°C, > 95% rel., 5% CO2; incubator sterilizable
Outer dimensions (WxDxH): 110x80x186 cm
Inner dimensions (WxDxH): 76,8 cm x 67,8 cm x 74,6 cm
Weight: approx. 550 kg
Power consumption: ca. 2 kW
Capacity of Storage Incubator: 500 plates
Gate
Plate
Feeder

24. CellMonitor - USPs Optimized for sensitive cell cultures
Continuous maintenance of optimal conditions
Integration of multiphoton microscopy
Optimized monitoring of tissue culture for tissue engineering
Laser cell manipulation possible
Modular setup of complete system
Individual customized solutions possible

25. CellMonitor – Key Applications
Cultivation of stem cells
Cultivation of primary cells
Long term monitoring
Transfection by optoporation
Tissue engineering
3D culture
3D live cell imaging and manipulation
Imaging of tissue up to a high depth
© BD Biosciences
Suitable plate format
Connexin46-GFP expressing HeLa cells

26. Why 3D culture?
Mimicking biological and physiological conditions more realistic than monolayer cell cultures
“In vivo like Morphology”
Needed for tissue engineering and stem cell cultivation and differentiation
Might help to fill the gap between monolayer culture and animal trial in pharma
more predictive lead generation
more relevant ADMET/Tox results

27. Examples of three dimensional tissue models
Francesco Pampaloni, Ernst H. K. Stelzer and Andrea Masotti: Three-Dimensional Tissue Models for Drug Discovery and Toxicology; Recent Patents on Biotechnology 2009, 3,

28. CellMonitor – Marketing

29. CellMonitor – Target Markets
Pharmaceutical and Biotech Industry
Tissue Engineering
Pharmacology
Toxicology
Cytology
Academia
Research institutes which work on generation of cell cultures (primary cells, embryonic stem cells, etc.) with high throughput
Key Words
Molecular Pathology, ADME Tox, Cell Culture, Target Identification, Regenerative Studies, Plant Science, Embryology/IVF, Cell Culture and Maintenance

30. CellMonitor – Summary
Automated functions : Microscope control, autofocus, objective changer, phase rings, condenser, light source control, etc.
Integration into automated cell culture processes: Automated transfer of MTPs from and to robot systems
Climatization: Temperature, humidity and CO2 controlled
Image analysis: Confluency, cell counting, fluorescence signal analysis
Low maintenance: High power LED light sources
Customized solutions possible: Integration of laser manipulation for laser cell transfection or organelle ablation, multiphoton microscopy 30