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BIO62004 Instrumentation in Medical Diagnostic, Laboratory and Blood Banking Topic 3: Research and Clinical Laboratory Instruments 3.1 (L6): Flow Cytometry Learning objectives Students should...

BIO62004 Instrumentation in Medical Diagnostic, Laboratory and Blood Banking Topic 3: Research and Clinical Laboratory Instruments 3.1 (L6): Flow Cytometry Learning objectives Students should be able to: 1. Discuss the application of flow cytometry, chromatography and mass spectroscopy in clinical diagnosis and basic research A. Flow Cytometry B. Chromatography C. Mass Spectroscopy Lecture Outline Introduction Instrumentation – Size comparison/ forward scatter, Complexity/side scatter, Fluorescence Data analysis – two parameter dot plot, gating, compensation, and three colour experiment Applications of flow cytometry Introduction Flow cytometry is a powerful technique for the analysis of multiple parameters of individual cells within heterogeneous populations The data gathered can be analyzed statistically by flow cytometry software to report cellular characteristics such as size, complexity, phenotype, and health The flow cytometer performs this analysis by passing thousands of cells per second through a laser beam and capturing the light that emerges from each cell as it passes through. https://flowcytometry.med.ualberta.ca/ (cell structure) (cell size) Instrumentation Fluidic system - presents samples to the interrogation Hydrodynamic focusing point and takes away the waste Lasers - the light source for scatter and fluorescence Optics - gather and direct the light Detectors - receive the light Electronics and the peripheral computer system - convert the signals from the detectors into digital data and perform the necessary analyses https://www.semrock.com/flow-cytometry.aspx Forward scatter histogram The scattered light received by the detector is translated into a voltage pulse Magnitude of the voltage pulse recorded for each cell is proportional to the cell size A histogram of forward-scatter data is a graphical representation of the size distribution within the population: one-dimensional data http://flowcytometry.weebly.com/forward-scatter-vs-side-scatter.html Side scatter histogram Side scatter is caused by granularity and structural complexity inside the cell The signals collected by the side-scatter detector can be plotted on one dimensional histograms Using two-dimensional dot or scatter plots, one can correlate size and the complexity of the cell populations Example: 2D scatter plot of blood Multiparametric analysis – Lymphocytes small cells possessing low internal complexity – Monocytes medium-sized cells with slightly more internal complexity – Neutrophils and other granulocytes large cells that have a lot of internal complexity Fluorescence Cellular characteristics can be analyzed using flow cytometry involves the use of fluorescent molecules such as fluorophore-labeled antibodies  cell markers When laser light of the right wavelength strikes the fluorophore, a fluorescent signal is emitted and detected by the flow cytometer. The fluorescent light is directed to the appropriate detector where it is translated into a voltage pulse proportional to the amount of fluorescence emitted Fluorescence How does the flow cytometer collect discrete fluorescence data for e.g. the Alexa Fluor® 488 and R-PE fluorophores? A 530 nanometer bandpass filter will collect most of the Alexa Fluor® 488 peak and a 585 nanometer bandpass filter will collect the bulk of the R-PE peak Forward scatter threshold If every single particle passing through the laser is collected as part of the data, the data pool would be dominated by information coming from a very large number of minute particles, like platelets and debris. Question: How to prevent this? A threshold (or discriminator or trigger) is set such that a certain forward scatter pulse size must be exceeded for the instrument to collect the data. Forward scatter threshold On the histogram, the blank area represents the small cells and debris that are excluded from analysis by the threshold Data analysis Linear or log scale histograms? Once the data has been collected, one can use histograms or dot plots to graphically represent the data Each of these plot types can be generated using linear scaling or using logarithmic scaling, also called log scaling Data analysis Example 1: Cells are stained with a fluorescently labeled antibody reacting to the CD4 cell-surface antigen, which generates events with fluorescence intensities that can vary 100-fold or more If we use linear scaling in histograms for this type of data, it is difficult to see both the CD4-positive and -negative populations at the same time. Switching fluorescence to a log scale allows both populations to be seen clearly on the same plot. Data analysis Example 2: For experiment used to measure DNA quantities in cells, the fluorescence values are in a very narrow range If we plot this data on a log scale, important subtle differences are obscured. When these same data are plotted on a linear scale, the specific distribution of DNA amounts is more apparent Data analysis Two parameter dot plot Biological samples usually contain multiple cell populations, each with different characteristics. These populations can be better distinguished by looking at two parameters at once. Data analysis Two parameter dot plot If a blood cell sample is probed with two fluorescently labeled antibodies reacting to CD4 and CD8 cell-surface antigens, the resulting histograms show two populations for each antigen, fluorescent or non- fluorescent. T-cells Data analysis The correlation between the CD4 and CD8 populations can only be seen using a dot plot. Data analysis In apoptotic cells, phosphatidyl serine (PS) is translocated from the inner to the outer leaflet of the plasma membrane, thus exposing PS to the external cellular environment. Annexin V labeled with a fluorophore or biotin can identify apoptotic cells by binding to PS exposed on the outer leaflet of the membrane. Data analysis Remember that each dot on the dot plot represents a cell, and each cell has associated with it ALL of the scatter and fluorescence data collected at the time it passed through the laser. Data analysis One can direct the analysis software to consider only the lymphocytes by drawing a region around this population - Gating Data analysis Once we have restricted the analysis to the lymphocyte cell population, one can produce additional histograms and dot plots that help us dissect subpopulations that we have labeled with fluorescent antibodies. Data analysis Data analysis How to correct for spectral overlap between fluorophores? – In a perfect world, the fluorescence emission profile for each individual fluorophore would be a very intense, narrow peak well separated from all other emission peaks. – In reality, organic dyes and fluorescent proteins have broad emission peaks, as can be seen from the profiles of Alexa Fluor® 488 dye and R-phycoerythrin, (R-PE). Data analysis To accurately record the fluorescence signal for a given fluorophore, we need to correct the emission signal, and this correction is often called compensation. * Compensation is the process of correcting the spillover from our primary signal in each secondary channel it is measured in. Data analysis The Alexa Fluor 488-labeled population is compensated so that the mean fluorescence values in both the positive and negative populations are equal in the R-PE channel. Practically, this is performed for each event by subtracting a percentage of the fluorescence in the Alexa Fluor® 488 channel from the fluorescence in the R-PE channel. Compensation Data analysis - Three colour experiment Stain a human peripheral blood cell sample with a combination of three fluorescent probes: Anti-CD3 – Alexa Fluor 488 Anti-CD4 – R-PE Anti-CD8 – R-PE Alexa Fluor 700 Data analysis - Three colour experiment Step 1: Gate on lymphocytes using forward and side scatter Data analysis - Three colour experiment Step 2: Set compensation using data from the three single-color tubes Anti-CD4 Anti-CD3 Anti-CD8 Data analysis - Three colour experiment Step 3: Locate the T cells using a histogram of CD3 staining and set a gate Define regions to capture both visible populations. – Region one, or R1, has been set on the CD3-negative peak, these are primarily B cells and natural killer cells. – Region two, or R2, has been set on the CD3-positive peak. These are the T cells of interest. To differentiate CD4 and CD8 cell surface antigens within the T cell population, a dot plot that is gated on the CD3-positive cells in the R2 region from the CD3 histogram needs to be created. Data analysis - Three colour experiment Step4: Use a CD4 versus CD8 dot plot to determine what percentage of the T cell population has the CD4 antigen and what percentage has the CD8 antigen. CD4+ T cells (or T helper cells (TH cells)) CD8+ T cells, also known as "Killer cells", indirectly killing cells identified as foreign & are cytotoxic - this means that they are assist other lymphocytes, including able to directly kill virus-infected cells as maturation of B cells into plasma cells and well as cancer cells memory B cells, and activation of cytotoxic T cells and macrophages. Applications of flow cytometry Cell signaling  Multiparametric flow cytometry provides researchers the power to monitor these key intracellular ‘checkpoints’ simultaneously, enabling analysis of complicated cell events. Researchers first used flow cytometry to measure simultaneously the levels of phospholipids and phosphoproteins in individual cells following several different perturbation conditions. Then, using this large dataset, they applied Bayesian network inference to recreate the structure of a signaling network Applications of flow cytometry Cell Health & Quality – Mitochondrial Analysis – Mitochondrial superoxide generation results in oxidative stress, damage and cell death by apoptosis or to cellular energetic decline. – Therefore, mitochondrial dysfunction caused by disease or compound treatment has dire consequences that can result in cell death. Cell permeant reagent 2’,7’ –dichlorofluorescein diacetate (DCFDA), a fluorogenic dye is used to measure hydroxyl, peroxyl and other reactive oxygen species (ROS) activity within the cell Applications of flow cytometry Cell health and quality – membrane integrity In apoptotic cells, phosphatidyl serine (PS) is translocated from the inner to the outer leaflet of the plasma membrane, thus exposing PS to the external cellular environment. Annexin V labeled with a fluorophore or biotin can identify apoptotic cells by binding to PS exposed on the outer leaflet of the membrane. Applications of flow cytometry Ploidy analysis – By measuring the DNA content of individual cells, one can obtain information about their ploidy, e.g. relevance in tumour cells characterization and analysis of cell cycle – Ploidy: the number of chromosomes in a germ cell (gamete) is called the haploid number, n, for that species and the number in a somatic cell, the diploid number, 2n – The most widely used dye for staining DNA is propidium iodide (PI), which has red fluorescence and can be excited at 488 nm. APPLICATION OF FLOW CYTOMETRY After studying this lecture, you should understand able to: 1. Discuss the application of flow cytometry, chromatography and mass spectroscopy in clinical diagnosis and basic research A. Flow Cytometry B. Chromatography C. Mass Spectroscopy

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