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

CellMonitor - System Overview

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

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

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

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

MTP Handling Loading of a MTP into the system

CellMonitor – Software Features

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

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

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

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

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

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

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

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

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

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

CellMonitor – Modular System Design

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

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

Complete System - CellCultivator

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

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

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

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

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, 103-117

CellMonitor – Marketing

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

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