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Final project – Final project – Computational Computational Biology Biology RNA RNA Quantificatio Quantificatio n n םםםםםם: לללל ללללל לללל לל ללללל םםםםםםם: ללללל ללללל ל"ללל- לללל לל

Final project – Computational Biology

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Final project – Computational Biology. RNA Quantification. מגישים: מיכל סימון חיים בן שימול בהנחיית: יהודה ברודי ד"ר ירון שב-טל. Introduction. Quantification of single molecules is a rather new method. Introduction. - PowerPoint PPT Presentation

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Page 1: Final project – Computational Biology

Final project – Final project – Computational Computational

BiologyBiologyRNA RNA

QuantificationQuantificationמיכל סימוןמגישים:

חיים בן שימול

יהודה ברודי בהנחיית:ד"ר ירון שב-טל

Page 2: Final project – Computational Biology

IntroductionIntroduction

Quantification of single molecules is a Quantification of single molecules is a rather new methodrather new method

Page 3: Final project – Computational Biology

IntroductionIntroduction It is now possible to fluorescently It is now possible to fluorescently

tag different molecules within the tag different molecules within the cell.cell.

Fluorescence microscopy makes it Fluorescence microscopy makes it possible track these molecules possible track these molecules (movement, interactions, kinetics (movement, interactions, kinetics etc.)etc.)

The data can be analyzed and The data can be analyzed and quantified using computational tools. quantified using computational tools.

Page 4: Final project – Computational Biology

Project goalProject goal

Providing an easy to use tool for Providing an easy to use tool for quantifying RNA molecules in cell, quantifying RNA molecules in cell,

determining their location and determining their location and distributiondistribution..

The tool will facilitate the tracing The tool will facilitate the tracing process of biological activities in process of biological activities in

cellscells..

Page 5: Final project – Computational Biology
Page 6: Final project – Computational Biology

RNA FISHRNA FISH

Synthesis of a complementary complementary oligonucleotide.oligonucleotide.

Covalently link the Covalently link the oligonucleotide to a oligonucleotide to a fluorescent molecule.fluorescent molecule.

Hybridization of the probe Hybridization of the probe with the RNA of interestwith the RNA of interest.

Detection of the labeled probe using fluorescent microscopy.

Page 7: Final project – Computational Biology

RNA FISHRNA FISH

Page 8: Final project – Computational Biology

Wide-Field microscopy Wide-Field microscopy techniquetechnique

Page 9: Final project – Computational Biology

Wide-Field microscopy Wide-Field microscopy techniquetechnique

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.

Page 10: Final project – Computational Biology

Wide-Field microscopy Wide-Field microscopy techniquetechnique

The final image is composed of pixels whose intensities are proportional to the florescence emitted by the cell at the represented area.

Page 11: Final project – Computational Biology

Image analysisImage analysis

Similar tool made in USA.Similar tool made in USA.

Page 12: Final project – Computational Biology

Image analysisImage analysis

Page 13: Final project – Computational Biology

At the beginning…...At the beginning…...

Page 14: Final project – Computational Biology

Image analysisImage analysis

IMARISIMARIS – – Tool for analyzing images Tool for analyzing images Wide graphical abilities.Wide graphical abilities. Embedded link to MATLAB programs.Embedded link to MATLAB programs.

Page 15: Final project – Computational Biology

Step I – defining spotsStep I – defining spots

Page 16: Final project – Computational Biology

Step II – Particles Step II – Particles boundingbounding

Each particle has a local maxima.Each particle has a local maxima. Each maxima is surrounded be local minima Each maxima is surrounded be local minima

points.points.

Page 17: Final project – Computational Biology

Step II – Particles Step II – Particles boundingbounding

Defining the right boundaries is essential Defining the right boundaries is essential for correct quantification!for correct quantification!

Boundaries too Boundaries too

wide:wide:

Page 18: Final project – Computational Biology

Step II – Particles Step II – Particles boundingbounding

Defining the right boundaries is essential Defining the right boundaries is essential for correct quantification!for correct quantification!

Boundaries too Boundaries too

narrow:narrow:

Page 19: Final project – Computational Biology

Step II – Particles Step II – Particles boundingbounding

Defining the right boundaries is essential Defining the right boundaries is essential for correct quantification!for correct quantification!

Reasonable Reasonable

boundaries:boundaries:

Page 20: Final project – Computational Biology

Step III – Calculating Step III – Calculating number of molecules in number of molecules in

each particleeach particle Summing the intensity of Summing the intensity of

each particle.each particle. Using calibration data for Using calibration data for

calculating the number of calculating the number of molecules in each molecules in each particle.particle.

Coloring each particle Coloring each particle with a color that will with a color that will indicate the number of indicate the number of molecules in it.molecules in it.

Page 21: Final project – Computational Biology

Calibration curveCalibration 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

Page 22: Final project – Computational Biology

Calibration curveCalibration curve

Page 23: Final project – Computational Biology

The final outputThe final output

Page 24: Final project – Computational Biology

AdvantagesAdvantages

Spots definition allows the user to determine Spots definition allows the user to determine which particles will be considered.which particles will be considered.

Displaying the boundaries upon the image allows Displaying the boundaries upon the image allows the user to verify the boundaries correctness.the user to verify the boundaries correctness.

The coloring of the particles is done upon the The coloring of the particles is done upon the image.image.

The final data may also be exported to an excel The final data may also be exported to an excel file.file.

Page 25: Final project – Computational Biology

Comparison to the existing Comparison to the existing tooltool

Overlapping spots gave the same Overlapping spots gave the same number of molecules in both tools.number of molecules in both tools.

Spots defined only by the old tool Spots defined only by the old tool were found to be noise rather than were found to be noise rather than real molecules.real molecules.

Page 26: Final project – Computational Biology

Comparison to the Comparison to the existing toolexisting tool

Page 27: Final project – Computational Biology

What’s next?What’s next?

Special treatment for the Special treatment for the transcription site.transcription site.

Improving the boundaries definition Improving the boundaries definition (currently, all particles are bounded (currently, all particles are bounded by squares).by squares).

Automatic de-convolution of the Automatic de-convolution of the image.image.

Page 28: Final project – Computational Biology

ThanksThanks

Dr. Yaron Shav-TalDr. Yaron Shav-Tal Mr. Yehuda BrodyMr. Yehuda Brody