Im Rahmen des K plus Programms gefördert durch:

Analysis of Cell Arrays: A Tool for Evaluation of High Density

Micro Colony Chips in Fluorescence Assays

Martina Uray & Horst Bischof Institute for Computer Graphics and Vision

Jochen Gerlach & Ingo Klimant Institute of Analytical Chemistry and Radiochemistry

Brigitte PohnResearch Centre Applied Biocatalysis

Helmut Schwab Institute for Molecular Biotechnology

2PPGT 2005 Martina Uray

Overview

• Motivation

• System Setup

• Enzymatic Reaction

• Automatic Analysis

• Results

• Conclusion and Future Work

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Motivation

• Need– Generation of highly active, specific and enantioselective

biocatalysts High throughput screening methods, suitable for desired enzyme reaction

• New development– Screening of whole cell arrays without decomposition of cells

and further cleaning steps – High throughput due to a semi-automatic software tool

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• Two strains with significant difference in esterase activity• Spotting of the array (~5000 colonies) with Microgrid II robot

(Biorobotics) – Regular sub-blocks, strains are randomly distributed– Reference spots for activity comparison– Cells grow at 30° over night and form micro colonies

• Replication of arrays

– Studies on different substrates or reaction conditions

• Preparation of the sensor– 100 µm thick– Includes the indicator, substrate and reaction buffer

System Setup I

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System Setup II

• Start of the reaction by putting the array onto the sensor– Substrate diffuses into the micro colonies– Reaction leads to a flux of protons into the sensor– Usage of fluorescent pH indicator which fluorescence

intensity is dependent on proton concentration– Excitation with a blue LED – Signal detection with a CCD camera– Measurement in constant time intervals

Image stack which shows the sensory response over time

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Enzymatic Reaction I

120 s 220 s

320 s

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Enzymatic Reaction II

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Automatic Analysis I

• Given– Composition of the array

(number of blocks, number of spots per block, fix spot-diameter)• Automatically …

– …find the position of the spots Corresponding block Situation inside the block

– …find the centre of the colonies Spot-content from centre and diameter

– …calculate the kinetic properties of every spot in the array Intensity development over time (intensity curve) Gradient (regression line) reflects the turnover rate

– …rate colonies Mapping to high and low activity

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Automatic Analysis I

• Software tool with graphical user interface• Automatically find the centre and the position of the spots

(fixed diameter)• Manually select an image and delineate the array with a

rectangle

• Normalize image for comparison

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Automatic Analysis II

1. Gaussian filter Noise reduction

2. Cross correlation Binary image

3. Summation over stack Grey scale image

4. Radon Transformation Estimation of rotation and starting point of grid Rough grid alignment

5. Fast Mean Shift (adaptive gradient ascent method) points towards the direction of maximum increase in density Exact spot centres

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Results I

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Results II

Spot positions are …• … clearly identified as long as there is a

signal• … approximated when there is no signal• … missed if the real centre is too far from

the first grid approximation

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Results III

• Comparison between standard and unknown spots Distinction of high (NJ70) and low (N27) activity esterase mutants spotted randomly over the array

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• Developed a semi-automatic system for fast screening of a huge amount of datasets

• Demonstrated robust performance

• Next Steps:– Calculate grid from reflected light image

Evaluate the exact size of the spots (Fast Mean Shift Algorithm) Calculation of spot intensity in comparison to its size

– Handle bright spots on dark background– Evaluate spot intensities in different parts of the array over

different time intervals

Conclusion & Future Work

15PPGT 2005 Martina Uray

Thank you for your attention!