1. Final project – Computational Biology RNA Quantification מגישים: מיכל סימון חיים בן שימול בהנחיית: יהודה ברודי ד"ר ירון שב-טל

2. Introduction Quantification of single molecules is a rather new method

3. Introduction It is now possible to fluorescently tag different molecules within the cell. It is now possible to fluorescently tag different molecules within the cell. Fluorescence microscopy makes it possible track these molecules (movement, interactions, kinetics etc.) Fluorescence microscopy makes it possible track these molecules (movement, interactions, kinetics etc.) The data can be analyzed and quantified using computational tools. The data can be analyzed and quantified using computational tools.

4. Project goal Providing an easy to use tool for quantifying RNA molecules in cell, determining their location and distribution. The tool will facilitate the tracing process of biological activities in cells.

6. RNA FISH complementary oligonucleotide. Synthesis of a complementary oligonucleotide. Covalently link the oligonucleotide to a fluorescent molecule. Covalently link the oligonucleotide to a fluorescent molecule. Hybridization of the probe with the RNA of interest Hybridization of the probe with the RNA of interest. Detection of the labeled probe using fluorescent microscopy.

7. RNA FISH

8. Wide-Field microscopy technique

9. Fluorescent sample is illuminated with light of the proper wave length. The sample will emit light of a different wave length. The light will be detected by a CCD camera. The camera will acquire a two dimensional image of the emitted light intensity. Acquiring several 2d planes will build a 3d representation of the object.

10. Wide-Field microscopy technique The final image is composed of pixels whose intensities are proportional to the florescence emitted by the cell at the represented area.

11. Image analysis Similar tool made in USA. Similar tool made in USA.

12. Image analysis

13. At the beginning…...

14. Image analysis IMARIS – Tool for analyzing images IMARIS – Tool for analyzing images Wide graphical abilities. Wide graphical abilities. Embedded link to MATLAB programs. Embedded link to MATLAB programs.

15. Step I – defining spots

16. Step II – Particles bounding Each particle has a local maxima. Each particle has a local maxima. Each maxima is surrounded be local minima points. Each maxima is surrounded be local minima points.

17. Step II – Particles bounding Defining the right boundaries is essential for correct quantification! Boundaries too wide:

18. Step II – Particles bounding Defining the right boundaries is essential for correct quantification! Boundaries too narrow:

19. Step II – Particles bounding Defining the right boundaries is essential for correct quantification! Reasonableboundaries:

20. Step III – Calculating number of molecules in each particle Summing the intensity of each particle. Summing the intensity of each particle. Using calibration data for calculating the number of molecules in each particle. Using calibration data for calculating the number of molecules in each particle. Coloring each particle with a color that will indicate the number of molecules in it. Coloring each particle with a color that will indicate the number of molecules in it.

21. Calibration curve The light output of a single probe is determined by measuring the TFI (total fluorescent intensity) of different dilutions of the probe in a fixed volume. The TFI is plotted against the number of fluorochrome molecules to generate the calibration curve. The slope is equal to the TFI per fluorochrome

22. Calibration curve

23. The final output

24. Advantages Spots definition allows the user to determine which particles will be considered. Spots definition allows the user to determine which particles will be considered. Displaying the boundaries upon the image allows the user to verify the boundaries correctness. Displaying the boundaries upon the image allows the user to verify the boundaries correctness. The coloring of the particles is done upon the image. The coloring of the particles is done upon the image. The final data may also be exported to an excel file. The final data may also be exported to an excel file.

25. Comparison to the existing tool Overlapping spots gave the same number of molecules in both tools. Overlapping spots gave the same number of molecules in both tools. Spots defined only by the old tool were found to be noise rather than real molecules. Spots defined only by the old tool were found to be noise rather than real molecules.

26. Comparison to the existing tool

27. What’s next? Special treatment for the transcription site. Special treatment for the transcription site. Improving the boundaries definition (currently, all particles are bounded by squares). Improving the boundaries definition (currently, all particles are bounded by squares). Automatic de-convolution of the image. Automatic de-convolution of the image.

28. Thanks Dr. Yaron Shav-Tal Dr. Yaron Shav-Tal Mr. Yehuda Brody Mr. Yehuda Brody