These particles have something in common

Transcription

1 These particles have something in common Blood cells Chromosomes Algae Protozoa Certain parameters of these particles can be measured with a flow cytometer

2 Which parameters can be measured? the relative size (Forward Scatter - FSC) the granularity or complexity (Side Scatter - SSC) the fluorescence intensity (FL1, FL2, up to FL X)

3 Characteristics of FSC and SSC Coherent lightsource (488 nm) Forward scatter Cell size (488 nm) Side scatter Granularity (488 nm) Forward scatter (FSC) measured along the axis of the incoming light proportional the the cell size / cell surface (only true for perfect round cells) Side scatter (SSC) measured in 90 direction to the excitation light proportional to cell complexity or granularity

4 An example of light scatter: Granulocytes Side scatter Monocytes Debris Lymphocytes Forward scatter

5 Fluorescence λ=488 nm λ=530 nm Excitation light Emission light The fluorochrome molecule absorbes the energy of the incoming light It releases the absorbed energy by: vibration and dissipated heat emission of a photon with a higher wavelength ( = less energetic)

6 Fluorescence intensity FITC FITC FITC FITC FITC FITC FITC FITC FITC Relative fluorescence intensity Number of Events FITC

7 Parts of a flow cytometer Fluidics Provide a constant stream of sheath Transport the sample to the interrogation point Arrange and focus the cells to the laser intercept Optics Focus the excitation light Collect the emitted light Electronics Convert the optical signals into electronic signals Send the signals to the analysis computer Computer Display data graphically Control instrument settings

8 What a flowcytometer is Very basically, a flow cytometer is an automated fluorescence microscope (in fact, that is how the first prototype instruments looked like). Like a microscope, some adjustments have to be made to optimally illuminate and collect the light.

9 The basic microscope In a standard microscope, the operator uses the XYstage to screen the sample and detect cells of interest.

10 The automated Microscope Detector & Counter Waste Sample This primitive diagram shows the principle: Cells are passing the microscope objective, and an electronic circuit decides whether the cells is fluorescent or not. This is how a flow cytometer works!

11 Basic fluidics of the FACSAria Fluidics Cart Pressure Plenum Cuvette Sheath Waste Sample tube

12 Hydrodynamic focussing in the cuvette Sample Sheath Sample Sheath Sample pressure low, small core stream. Good for DNA analysis High sample pressure, broader core stream. Bad for DNA analysis 1

13 Summary Pressure (= Sheath Pressure) drives the sheath buffer through the cuvette, and the higher pressure in the sample tube (= Sample Differential) delivers the sample to the cuvette. In the cuvette the principle of hydrodynamic focussing arranges the cells like pearls on a string before they arrive at the laser interception point for analysis Hydrodynamic focussing cannot separate cell aggregates! Flow cytrometry is a technique that requires single cell suspensions

14 Basic optics Somehow the light from the laser(s) must be directed to the cuvette to illuminate the cells. At the same time, the emitted light must be collected to analyse the signals from the cells. The alignment of the system is performed during installation.

15 Basic optics A system of prisms and lenses directs the laser light to the interrogation point in the cuvette

16 Basic Optics The emitted light induced from each laser is focussed onto separate glass fibers.

17 Optical filters Longpass Bandpass Shortpass LP 500 SP 500 BP500/80

18 Octagon Detection System PerCP-Cy /40 FITC 655 LP SSC PE PE-Cy7

19 Summary Excitation light is steered with prisms and lenses to the interception point Emitted light is collected using lenses and is split up with dichroic mirrors and filters

20 Tasks for the electronical system Convert the optical signals into electonic signals (voltage pulses) Digitise the data Analyse Height (H), Width (W) and Area (A) of the pulse Send the data to the analysis computer

21 How a voltage pulse from the PMT is generated 1. Laser t Voltage 2. Laser t Voltage 3. Laser t Voltage

22 Height, Area, and Width Voltage Pulse Height (H) Pulse area(a) 0 40 Pulse Width (W) Time (µs)

23 Digitization The pulses go into a digitizing system that scans the pulses with a rate of 10 MHz, which corresponds to a sample each 0,1 µs. The pulse height of each slice is converted to a 14 bit number. 10 MHz scanning Digitization 14 bit

24 Parameter Calculation After the pulse has been digitized, the system can calculate the area and the width and apply the compensation to all signals. Basically, the system works vice versa like your CD player at home. It generates the

25 Threshold The threshold defines the minimal signal intensity which has to be surpassed on a certain channel. All signals with a lower intensity are not displayed and not recorded for later analysis.

26 Summary During passing the laser voltage pulses are generated at the PMT Amplifiers enhance the signals The electronics digitizes the pulse using 10MHz sampling Only signals passing the desired threshold(s) are analysed and recorded The data are finally passed to the analysis computer connected to the cytometer

27 Instrument settings the the exact values for for PMT voltages and and thresholds are are depending on on the the applications (type of of cells, staining methods) and and the the specific instrument. Displaying the the data data in in a linear fashion or or using the the logarithmic form form is is also also depending on on the the application.

28 Workstation The The connected workstation is is designed for for instrument control, data data acquisition, -storage and and -analysis. OS OS is is Windows2000 Professional running on on a IBM-compatible computer platform. Software DiVa application: Instrument connectivity, Data-acquisition and and analysis system DiVa Data Manager: Backup and and Restore the the database.

29 Data saving All All data data are are saved directly into into a special database. Every plot plot is is connected with with its its corresponding datafile. All All tubes carry a copy of of the the instrument setting that that was was active during acquisition. Due Due to to this, this, there are are no no special save commands in in the the software. Every action is is recorded in in the the database. When you you quit quit and and re-start the the software, it it will will open the the last last experiment exactly at at the the position you you left left it. it.

30 Visualization of data 1) Histograms - single parameter, intensity plotted as frequency distribution

31 Visualization of data 2) Dotplot - two parameter are plotted on X and Y Event 1 Event 2 Event Listmode file FSC SSC FL1 FL FL2-H FL1-H

32 Enough theory of flow! Let`s have a look at an example from real life

33 Example: Determine the percentage of CD3, CD4, and CD8 populations from whole blood Material Mouse splenocytes Method Three-colour immunofluorescence Preparation Staining of of freshly isolated splenocytes Stainings Isotype controls Single-colour stainings for for CD3-FITC, CD3-PE, CD3-PerCP und und CD3- APC APC to to determine suitable instrument settings

34 Prepare the instrument

35 Proper adjustment of FSC and SSC voltage FSC FSCund SSC SSCare optimally adjusted when the the population of of interest (i.e. (i.e. Lymphocytes) can can be be resolved from from all all other populations The The threshold on on FSC FSCis is adjusted so so that that most of of the the debris is is excluded from from the the data data acquisition.

36 Parameters (I) FSC FSCand andssc are are depending on on cell cell type type and and cell cell state (activated, resting) depend on on the the preparation method (Ficoll, LW, LW, LNW, fixation method etc.) etc.) are are normally used to to define the the population of of interest for for further analysis

37 Parameters Fluorescence channels (FL1, FL2, FL2, FL3, FL3, FLX) depending on on the the specific staining (conjugate) antibodies, propidium iodide for for DNA-labelling, etc.) etc.) most of of the the time time fluorescence serves as as marker for for the the statistical analysis

38 Defining the population of interest (often just named gating )

39 About Gating selectively analyse defined cell cell populations Gates can can be be set set manually or or automatically by by software multidimensional gating with with hierarchical gates too too narrow gates may may lead lead to to the the loss loss of of cell cell populations too too wide wide gates enhance the the number of of unwanted cells cells during analysis of of the the desired cell cell population the the cells cells in in the thegate are are considered to to be be the the 100%

40 Adjusting the fluorescence settings A) Adjusting PMT voltages Sample: Isotype control The observed fluorescence is considere to be unspecific background fluorescence, Setup is done gated on the lymphocyte population Try to put the background into the first decade (only a rule of thumb!) B) Defining quadrants Traditionally, a Quadrant is set to define the possible four populations in two-colour experiment. Later we will see that quadrants are not the appropriate way for multicolour analyses.

41 Theory of quadrant analysis FL2-H Q1 PE FITC + PE Q2 Q3 negative FITC Q4 FL1-H

42 Real life: FITC-fluorescence overspill FL1 530/30 FL2 585/42 Relative Intensität 500nm 550nm 600nm Wellenlänge (nm) 650nm 700nm

43 FITC Compensation Detektor - % Signal FL1 530/30 FL2 585/42 Relative Intensität 500nm 550nm 600nm Wellenlänge (nm) 650nm 700nm

44 FITC Compensation Lowering the FITCpopulation is achieved by Subtracting a percentage of FITCintensity from the affected PE-channel... FL1 530/30 FL2 585/42 Relative Intensity because 25% of the FITC-signal are actually detected in the PE channel nm 550nm 600nm Wavelength (nm) 650nm 700nm

45 PE-fluorescence overspill FL1 530/30 FL2 585/42 FL3 größer 650 Relative Intensity 500nm 550nm 600nm 650nm 700nm Wavelength (nm)

46 Automatic Multicolour Compensation Multicolour compensation with more than three colours can become very time-consuming because each channel has to be compensated against each other. Automatic compensation offers the possibility to run singlecolor controls and let the software calculate all overspills. Mathematical calculation results in the correct spillover values for all channels. However, to the user the visual data may look undercompensated. This will be discussed in detail during the training course.

47 Summary What we wehave seen: the theemission spectra of of common fluorochromes (FITC, PE) PE) the thespectral overlap of of fluorochromes into intoneighbouring channels depending on on the theemission spectra and and filtersets how howspectral overlap can canlead leadto to misinterpretation of of multicolour stainings How Howcompensation can cancorrect the thespectral overlap of of fluorochromes