Fundamentals of Light Microscopy II: Fluorescence, Deconvolution, Confocal, Multiphoton, Spectral microscopy. Integrated Microscopy Course

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1 Fundamentals of Light Microscopy II: Fluorescence, Deconvolution, Confocal, Multiphoton, Spectral microscopy Integrated Microscopy Course

2 Review Lecture 1: Microscopy Basics Light train Kohler illumination* Getting an image Diffraction and refraction Objectives Special techniques Dark field Phase Contrast Differential Interference Contrast

3 Lecture Objectives 1. Understand the Principles of Florescence Microscopy 2. Understand how Deconvolution Improves Resolution 3. Understand How Laser Scanning Confocals work 4. Understand the Principles of Spectral Unmixing

4 Light Spectrum Visible Spectrum = 400nm to 750nm Planck s Law: E=hc/l where h is Planck s constant, c is the speed of light, and l is the wavelength of a photon Shorter Wavelength 1. Higher energy 2. More Harmful to cells 3. More easily scattered Longer Wavelength Lower energy Less harmful to cells Less easily scattered

5 Fluorescence First described in the 1800 s by Sir George Stokes (fluorspar) Light emission that continues only during the absorption of the excitation light Stokes Shift: the phenomenon in which the emitted light has longer wavelength than the excitation light

6 Jablonski Diagram 3 S Vibrational relaxation 0 3 Internal conversion Excited Singlet States S Vibrational relaxation 0 Emission light Heat Quenching 3 Excitation light S Ground state energy levels 2

7 Characteristics of Fluorescence 1. Because of the differing rotational, vibrational and even electronic states a molecule can have, peaks are BROAD. 2. Each spectrum is characteristic of a given molecule. 3. Before returning to its normal state, the electron remain at the excited level for approximately seconds. 4. Because the excited state is HIGHLY REACTIVE it can bleach (react with other molecules). 5. Everything is a point of light. Light goes in all directions.

8 Fluorescent Microscope (Epi-fluorescence) Excitation Wavelength Emission Filter Emission Wavelength Dichroic Beam splitter Excitation Filter 3 Major Parts 1. Excitation Filter (Ex) 2. Dichroic Beam splitter 3. Emission Filter (Em) Objective = Condenser Sample

9 Filter Spectrum FITC TxRed FITC Filter Set Texas Red Filter Set Ex Filter Dichroic Em Filter Ex Filter Dichroic Em Filter

10 Problem: Fluorophore Spectral Overlap With broad fluorescent peaks and broad collection parameters, fluorescence from one fluorophore can appear in a second channel Alexa Dye Excitations with FITC Filter Alexa Dye Emissions with FITC Filter You can mistake yellow or orange for green fluorophore! How to correct for this? One way is to do image subtraction Label with 1 fluorophore and see how bad the bleed through is in second channel. Get intensity ratio then subtract out contribution from other fluorophore Example: Corrected Intensity Green = Measured Intensity Green X% Intensity Orange Confocal allows better ways!

11 Resolution of Fluorescence Microscopy Bright field Max NA of a Oil Objective n (oil) = NA (oil) = (1.515) (1.00) = 1.5 Epi-Fluorescence Max NA of a Oil Objective n (oil) = NA (oil) = (1.515) (1.00) = 1.5 Max resolution for a oil objective under Bright Field d = 1.22λ / (NA ob + NA cond) λ = 546nm (green) d = 1.22 (546nm) / ( ) d = 266nm Max resolution for a oil objective under Epi-Florescence d = 1.22λ / (2 * NA obj) λ = 546nm (green) d = 1.22 (546nm) / (2* 1.5) d = 222nm * It is possible to detect fluorescence from smaller structures but it will be impossible to resolve them*

12 More pixels equals larger field of view Field of View (CCD)

13 What affects resolution? Size of pixel System Magnification & NA Camera Coupler Size of pixel determines the resolution Smaller pixels provide for better resolution Size of pixel also relates to sensitivity of the camera Larger pixels provide higher sensitivity Higher Magnification and Higher NA allows for use of larger pixels. Low magnification requires smaller pixels

14 Why does pixels size matter? Our ability to distinguish fine detail is determined by pixel size Resolution! Nyquist theory states that we must sample at 2.3 times the highest spatial frequency we wan to resolve. We can satisfy this requirement by varying pixel size.

15 Resolution and Pixel Size Small pixels Large pixels

16 Sampling and Pixels

17 When should I be concerned about Bit Depth? -When there are very bright and very dim areas in the sample you need to image -When you are making intensity measurements

18 Bit Depth Bit depth describes the range of intensity that the CCD can capture Cameras that have high bit depth usually are more sensitive to light Our eyes and computer monitors can only process ~ 8 bits or 256 shades of gray. Why do we have 12bit, 14bit and 16bit cameras?

19 Bit Depth What is Bit Depth? The number of different intensities that the camera can capture Usually we think of it as number of shades of gray Shades of gray is like a length ruler, but for intensity

20 Bit Depth Bit Depth is usually a number of 2 n 8 bit = 2 8, or 256 gray tones 12 bit = 2 12, or 4096 gray tones 16 bit = 2 16, or 65,536 grays tones More bits equals more contrast More bits equals better measurement of brightness = MORE DATA!

21

22 Fluorescence Microscopy Pros and Cons of Fluorescence Microscopy Pros Allows for multiple labels Techniques: Immunofluorescence, FISH Sensitive Relatively inexpensive Cons Out of focus light blurs image. Must have fluorescent reporter Fluorescent bleed through Difficult with thick sections

23 Challenges Spectral Overlap: Broad peaks cross over into one another. One fluorophore comes off in 2 channels Blur: Out of focus light decreases resolution Bleaching: Excited fluorophores react to become non-fluorescent Phototoxicity: Light can harm cells Background/Autofluorescence: Cells have fluorophores too. May look like the ones you want to examine.

24 Deconvolution Microscopy Computationally Increases Image Resolution

25 Deconvolution Microscopy and 3D Reconstruction X-Y X-Z Definitions 1. PSF (Point spread function) how a point of light reacts when it is in focus and out of focus, determined experimentally or back calculated from the collected images. 2. Voxel (volume element) 3- dimensional pixel Key points All fluorescent molecules emit light, both in focus and out of focus an image always blurred by the contribution of light from structures which are out of focus phenomenon can be relatively well defined by the optical properties of the image formation in the microscope imaging system Z X Y voxel

26 What does Deconvolution Do? Deconvolution looks at each voxel (3D pixel) and determines its relationship with the voxels around it. Then it either subtracts out what it calculates is blur from nearby bright voxels (easy way) or it moves out of focus light back to its voxel of origin (hard way). Raw Data Deconvolved Data

27 Methods for Deconvolution 1. Non-Restorative Algorithms (unsharp mask, nearest neighbors, no neighbors, multiple neighbors) Subtract a given amount of light from nearby voxels to account for blur effect. A. Relatively cheap, very simple to do, quick, computationally undemanding. Doable with Metamorph. B. Subtractive Trade higher contrast for decreased signal. UNUSABLE for quantitation.

28 2. Restorative Algorithms (inverse filter, constrained iterative deconvolution, maximum likelihood estimation, blind deconvolution and many others) A mathematical method for applying the point-spread function (PSF) to remove and/or reassign the "out-of-focus" blur in an image specimen. - NOT subtractive Premises a. Since the image has been acted on by the PSF, a set of weighted sines and cosines will represent this. Use Fourier Transformation to calculate these. c. Divide fourier transformation of measured image by fourier transformation of the PSF (the OTF) and you should get closer to true image. Perfect if all values were right. d. Reblur with original PSF and you should get back to observed image.

29 Types of Restorative Algorithm Inverse Filter does this once and stops. Can intensify noise and produce artifacts. Quicker. Constrained iterative deconvolution keeps trying to improve image by decreasing difference between reblurred and original. Certain constraints applied to solution. Slower and computationally intense. Maximum likelihood estimation further applies statistical calculations to noise and is still more computationally intense. May be better for noisy data Blind deconvolution can refer to either using an empirically determined PSF or determining the exact PSF as you go.

30 Typical Constrained Iterative Deconvolution Output Standard Avg Counts Iteration Residual (R) Residual Normalized R The Normalized R is the best way to see if the image is still improving

31 Differences Between Methods: There is a reason to go through iterative solutions CID Original Nearest Neighbor

32 Deconvolution Microscopy Raw Deconvolved Pros and Cons of Deconvolution Microscopy Pros Allows for higher Resolution Allows collection of image plane stacks Hg Bulb allows for variety of filter combinations Can get superior sensitivity Cheaper than confocal Cons Computationally intense if iterative Minimal penetration of thick sections Sensitive to spherical aberrations Can amplify noise, produce artifacts Requires 3D data set

33 Confocal Microscopy Physically Increases Image Resolution

34 Laser Confocal Scanning Microscopy Laser 1980 s Dichroic Beam Splitter Photo- Multiplier Tube (PMT) Detector Objective Confocal Pin Hole Out of Focus Sample In Focus Out Of Focus

35 Laser Light Sources Lasers Bulb

36 Laser Confocal Scanning Microscopy The laser beam excites a point on the specimen. It also inadvertently excites other points on the specimen. Only the In-Focus emission light is allowed to be detected by the PMT. The Light detected by the PMT is associated to a pixel (picture element) on the monitor. The laser beam then moves to the the next point and another pixel is collected. Size Confocal Pinhole Result on the Intensity of the Image Result on the Resolution of the Image Increase opening Increase Intensity decrease resolution Decrease opening Decrease intensity increase resolution

37 Laser Confocal Scanning Microscopy No Pin Hole 50um Pin Hole Pros and Cons of Confocal Microscopy Pros Allows for higher resolution Allow collection of stacks of image planes and 3D reconstruction Laser penetrates somewhat thick sections Better control of bleed through/autofluorescence Faster than deconvolution Cons Limited EX peaks on lasers Phototoxicity (up to a 40º C temp jump at focal point) Loss of image intensity Fairly expensive Prone to Photobleaching Precise Laser Positioning (FRAP)

38 Multiphoton Microscopy Optically increases resolution

39 Multiphoton Microscopy ( nm) Based on phenomena described by Maria Goppert- Mayer (1931) Two photons of low energy (long wavelength) can excite a fluorophore resulting in emission of a photon of higher energy (short wavelength) Requires nearsimultaneous absorption of the two photons ( nm)

40 Multi-Photon Confocal Microscopy Characteristics 1. Attosecond pulses only properly strike at the In-Focus plane of the specimen. 2. Multiple short pulses of longer wavelength light have the same amount of energy as one long pulse of shorter wavelength. Pros and Cons of Multi-Photon Microscopy Pros More penetrating up to hundreds of micron No out of focus light Laser is tunable. Can get range of wavelengths including UV dyes. Better for Living cells if you re careful. Cons Best excitation wavelength is not always obvious Cost (Very Expensive) Laser is POWERFUL. Can damage cells, slides and even walls. Difficult to align and use (Less so now) Can also kill off specific cells/organelles.

41 Multi-Photon Images Mouse Liver Tissue Mouse Cardiac Tissue Grey = hepatocytes Green = collagen Green = collagen Red = myocytes

42 Spectral Unmixing Computationally Resolves Spectral Overlap

43 Spectral Unmixing Allows one to use and resolve multiple fluorophores with highly overlapping emission spectra Specific Cases: You need to use fluorophores with highly overlapping signal (GFP and YFP; Mitotracker red and dsred)

44 Emission Fingerprinting - the Method 1. *contains spectral information for each pixel 2. Instead of using an emission filter, spectral unmixing relies on obtaining intensity values for each pixel at a number of wavelengths, and then creating a spectrum. Next, the user compares this spectrum to defined spectra for different fluorophores. After mathematic comparison, you can determine the true value of each fluorophore present. 3.

45 Linear Unmixing How it works! Unmixing separates the total emission signal into weighted contributions of each dye based on the knowledge of their emission fingerprints pixel by pixel! Combined spectra = a x GFP + b x YFP

46 A final problem data management (Or: Where is my file?!! ) Answer save files with a fixed filename such as: Initial for scope 1ss1022ad Slide number Field of view Your initials The date Second answer Save in a fixed place on server

47 Imaging Ethics Don t believe anything you read and only half of what you see Assume accurate representation of reality Images = data Spatially arranged in xy matrix Each pixel represents image intensity Numerical sampling of the specimen as presented by the data acquisition system to the sensor

48 Imaging Ethics Always do manipulations on copy Original on CD/DVD/checksum Protects you from allegations of fraud Simple adjustments are OK Darkroom techniques contrast, gamma Cropping OK avoid acquisition bias Honesty best policy document in methods

49 Imaging Ethics Digital images that will be compared to one another should be acquired under identical conditions, and any post- acquisition image processing should also be identical. Use of software filters to improve image quality is usually not recommended for biological images. Collage/cloning image is very questionable Don t use lossy file types Resolution and magnification are important

50 References: 1. Molecular Probes 2. Chroma Filters 3. Omega Optical 4. Zeiss Microscopes 5. Applied Precision Deconvolution 6. Fluorescent Protein Spectra 7. Free Image Processing Program ` 8. Confocal List serve listserv.acsu.buffalo.edu/cgi-bin/wa?s1=confocal 9. Microscopy List serve Olympus Nikon

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