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Flow Cytometry Training: Introduction day 1 session 2

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Flow Cytometry Training talks - part 1
This forms the first session of the Garvan Flow , Flow Cytometry Training course. this is a 1 1/2 day training course aimed at giving new and experienced researchers a better understanding of cytometry in medical and biological research.

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Flow Cytometry Training: Introduction day 1 session 2

  1. 1. Day 1 Introduction 10:30 To 1:00 pm Session 2 FLOW CYTOMETRY TRAINING Robert Salomon (Flow Manager and Senior Flow Cytomerty Scientist)
  2. 2. Theory Session – 0900 till 1300  Introductions to the Lab and Staff  Self Introductions  Basics of flow cytometry  Applications for Flow Cytometry Morning tea - Provided  Getting Started  Panel Design  Controls and compensation  Data Analysis and Interpretation  Data Acquisition Overview  Instrumentation Lunch – provided Practical Session SESSION 2 Outline – 5 mins Day 1
  3. 3.  To design good Flow Cytometry Experiments you’ll need to  Start with a good panel  Use appropriate controls  Compensation controls  Fluorescence minus one (FMO)controls  Positive and negative controls  Monitor your instrument GETTING STARTED
  4. 4.  What is a “PANEL” ?  A Panel is a combination of fluorochromes that allows us to characterise our sample using flow cytometry.  It requires balancing technical and biological factors so that we can accurately interpret the biological state of our cells PANEL DESIGN
  5. 5.  Understanding Fluorochromes PANEL DESIGN Input Light Energy Output Light Energy Fluorochrome
  6. 6.  Getting started on your panel  Know your Sample and Desired outcome  What is the goal of the experiment ?  Which markers are critical ?  Refer to literature for abundance & co-expression of antigen  Know your Fluorochormes and Instruments  Fluorochrome brightness  Spectral overlap  What excites the fluor and what is the emmision  Theoretically design an “optimal Panel”  Optimise the individual Elements in the Panel  Antibody titration  Put it all together : Test the “optimised Panel”  Use all relevant controls  Refine the panel PANEL DESIGN
  7. 7.  What are the important epitopes ?  How abundant are they ?  Which of my characteristics of interest are co-expressed ?  Which characteristics are negative for my cells of interest ? (dead cell exclusion dyes) PANEL DESIGN: KNOW YOUR SAMPLE
  8. 8.  Choice of Fluorchorome is critical , especially in more complex panels >4 fluors  What restrictions do I have ?  Is there anything intrinsic in my sample that I will restrict my choices?  What fluorochromes can I see on the instrument?  What antibody/ reagents are available to me ?  What is the best combination available?  Can I match my least abundant epitope to the brightest fluorochrome?  Who do my fluorochromes interact ? PANEL DESIGN: KNOW YOUR FLUOROCHROMES
  9. 9.  Is there anything intrinsic in my sample that I will restrict my choices?  Fluorescent Proteins  Auto Fluorescence PANEL DESIGN: FLUOROCHROME RESTICTIONS
  10. 10.  What fluorochromes can I see on the instrument? PANEL DESIGN: FLUOROCHROME RESTICTIONS http://flow.garvan.org.au/flow- cytometers-instrument-details
  11. 11.  What fluorochromes antibody combinations are available? PANEL DESIGN: FLUOROCHROME RESTICTIONS
  12. 12.  Fluorochrome Brightness 1. Quantum Efficiency = How well the fluor is excited. 1. Quantum Yield = How well the fluor converts excitation into emission. PANEL DESIGN: OPTIMISING FLUOROCHROME COMBINATIONS
  13. 13.  Stain Index gives a measure of how well the positive population separares from the negative population SI =(MFI pos – MFI neg )/2 x SD MFI neg pop  Is a combination of: 1. Epitope expression level 2. Fluorochrome 3. Cell type 4. The pressence of other fluors in the sample PANEL DESIGN: OPTIMISING FLUOROCHROME COMBINATIONS
  14. 14. PANEL DESIGN: OPTIMISING FLUOROCHROME COMBINATIONS Epitope Expression Level Fluorochrome Brightness
  15. 15. PANEL DESIGN: THEORETICAL PANELS Name Rob Salomon Panel Name 2015 B/T Sep Desired Outcome Separation of B cells from CD4 and CD8 Tcells Instrument Canto II PANEL 1 parameters target Expression level Fluor Fluor Brightness channel 1 Cd3 high GFP ++ B530 2 cd4 high PE ++++ B585 3 cd8 high APC ++++ R660 4 cd19 very low APC Cy7 + R780 5 Ter119 very high PE CY7 +++ B780 6 Death DAPI +++++ V450 7 8 PANEL 2 parameters target Expression level Fluor Fluor Brightness channel 1 Cd3 high GFP ++ B530 2 cd4 high APC CY7 ++++ R780 3 cd8 high APC ++++ R660 4 cd19 very low PE ++++ B585 5 Ter119 very high Percp cy5.5 +++ B695 6 Death DAPI +++++ V450 7 8
  16. 16. PANEL DESIGN: THEORETICAL PANELS Name Rob Salomon Panel Name 2015 B/T Sep Desired Outcome Separation of B cells from CD4 and CD8 Tcells Instrument Canto II PANEL 1 parameters target Expression level Fluor Fluor Brightness channel 1 Cd3 high GFP ++ B530 2 cd4 high PE ++++ B585 3 cd8 high APC ++++ R660 4 cd19 very low APC Cy7 + R780 5 Ter119 very high PE CY7 +++ B780 6 Death DAPI +++++ V450 7 8 PANEL 2 parameters target Expression level Fluor Fluor Brightness channel 1 Cd3 high GFP ++ B530 2 cd4 high APC CY7 ++++ R780 3 cd8 high APC ++++ R660 4 cd19 very low PE ++++ B585 5 Ter119 very high Percp cy5.5 +++ B695 6 Death DAPI +++++ V450 7 8
  17. 17.  Antibody titration  To establish the optimum antibody dilution, highest signal/noise ratio  Done for each antibody in the correct experimental condition PANEL DESIGN: OPTIMISE INDIVIDUAL ELEMENTS http://regmed.musc.edu/flowcytometry/images/AntibodyTitration.jpg Note: tandem dyes may require lot-specific titration
  18. 18.  Depending on type of assay.  Determining changes in level of expression  Absolutely requires saturating levels  Differentiating between cell types.  Can be achieved through non-saturating however care should be taken PANEL DESIGN: OPTIMISE INDIVIDUAL ELEMENTS Saturating 4 7 4 5/7 Non Saturating 01
  19. 19.  FMO (fluorescence minus one)  Contains all markers except one  To discriminate positive vs negative populations PANEL DESIGN: OPTIMISE INDIVIDUAL ELEMENTS http://www.dartmouth.edu/~dartlab/?page=flow-cytometry
  20. 20. Name Rob Salomon Panel Name 2015 B/T Sep Desired Outcome Separation of B cells from CD4 and CD8 Tcells Instrument Canto II PANEL 2 parameters target Expression level Fluor Fluor Brightness channel 1 cd3 high GFP ++ B530 2 cd4 high APC CY7 ++++ R780 3 cd8 high APC ++++ R660 4 cd19 very low PE ++++ B585 5 Ter119 very high Percp cy5.5 +++ B695 6 Death DAPI +++++ V450 7 8 PUTTING IT ALL TOGETHER: TEST YOUR COMPLETE PANEL Panel Plus Controls and Analyse
  21. 21. Unstained control As negative controls – no antibody present To assess any autofluorescence Compensation controls Single colour controls – stain with one fluorophore with the EXACT conditions as experimental samples Compensate for fluorophore emission overlaps CONTROLS: INSTRUMENT & SETUP CONTROLS http://www.abdserotec.com/flow-cytometry-fluorescence-compensation.html
  22. 22. Unstained controls  Allow relative Determination of positivity PUTTING IT ALL TOGETHER: CONTROLS Question : Which Populations is the Positive ?
  23. 23. Unstained controls  Allow relative Determination of positivity PUTTING IT ALL TOGETHER: CONTROLS Question : Which Populations is the Positive ? Answer : Both – Because I spiked in a negative control
  24. 24.  Compensation Controls  Set of samples/beads consisting of  One tube of unstained sample/beads +  Tubes of single fluorochrome labelled samples OR  Tubes of single fluorochrome labelled beads spiked with unstained beads. PUTTING IT ALL TOGETHER: CONTROLS
  25. 25. EFFECT OF COMPENSATION Digital compensation doesn’t change the underlying data it just allows us to interpret it
  26. 26. EFFECT OF COMPENSATION Digital compensation doesn’t change the underlying data it just allows us to interpret it
  27. 27. DIGRESSION: WHY DO WE NEED TO COMPENSATE ? spectral viewers http://www.bdbiosci ences.com/research /multicolor/spectru m_viewer/index.jsp http://www.invitroge n.com/site/us/en/h ome/support/Resear ch- Tools/Fluorescence- SpectraViewer.html
  28. 28. DIGRESSION: WHY DO WE NEED TO COMPENSATE ? spectral viewers http://www.bdbiosci ences.com/research /multicolor/spectru m_viewer/index.jsp http://www.invitroge n.com/site/us/en/h ome/support/Resear ch- Tools/Fluorescence- SpectraViewer.htmlU se the
  29. 29. DIGRESSION: WHY DO WE NEED TO COMPENSATE ? spectral viewers http://www.bdbiosci ences.com/research /multicolor/spectru m_viewer/index.jsp http://www.invitroge n.com/site/us/en/h ome/support/Resear ch- Tools/Fluorescence- SpectraViewer.htmlU se the
  30. 30. DIGRESSION: WHY DO WE NEED TO COMPENSATE ? spectral viewers http://www.bdbiosci ences.com/research /multicolor/spectru m_viewer/index.jsp http://www.invitroge n.com/site/us/en/h ome/support/Resear ch- Tools/Fluorescence- SpectraViewer.htmlU se the
  31. 31. DIGRESSION: WHY DO WE NEED TO COMPENSATE ? Spectral overlap occurs when fluorochromes excited by the same lasers emit in similar ranges. B 530 B 585 PE 5% 87% FITC 95% 13% 0% 20% 40% 60% 80% 100% 120% PercentageofSignal inDetector Effect of spectral overlap - Instrument View
  32. 32. COMPENSATION THEORY Compensation is applied at the single event level B 530 B 585 FITC 100% 13% PE 5% 100% 0% 20% 40% 60% 80% 100% 120% AxisTitle Signal from Compensation Controls overlap overlap B 530 B 585 FITC bright 100 13 0 20 40 60 80 100 120 SignalStrength FITC bright B 530 B 585 FITC dull 50 6 0 20 40 60 80 100 120 SignalStrength FITC dull
  33. 33.  Compensation removes the signal spillover from one fluorochrome into any other parameter. COMPENSATION THEORY MFI pos population NTC 1 = MFI neg population NTC 1 MFI pos population NTC 2 = MFI neg population NTC 2 ……………………………….. MFI pos population NTC n = MFI neg population NTC n MFI = Media Fluorescent Intensity NTC = Non Target channel MFI FITC channel MFI Pe channel MFI APC channel Fitc 25818 193 222 Pe 421 23940 228 APC 431 181 27271 unstained 905 377 235
  34. 34.  Compensation removes the signal spillover from one fluorochrome into any other parameter. COMPENSATION THEORY MFI pos population NTC 1 = MFI neg population NTC 1 MFI pos population NTC 2 = MFI neg population NTC 2 ……………………………….. MFI pos population NTC n = MFI neg population NTC n MFI = Media Fluorescent Intensity NTC = Non Target channel Where D= Fluorescence in detector F= Fluorescence signal N = FL from detector # N = FL in Detector #
  35. 35. EFFECT OF COMPENSATION Digital compensation doesn’t change the underlying data it just allows us to interpret it
  36. 36. EFFECT OF COMPENSATION Digital compensation doesn’t change the underlying data it just allows us to interpret it
  37. 37. DATA ANALYSIS AND INTERPRETATION
  38. 38. PLOT TYPES Dot Plot Histogram Histogram Contour Plot
  39. 39.  Rectangular Gates  Elliptical Gates  Polygon Gates  Quadrant Gates  Histogram regions GATES & GATING Rough gates – generally suitable for initial gating Generally better suited to biological populations Gives the most control – generally recommended Flow data generally doesn’t conform to 900 angles Only applicable for histograms
  40. 40.  Gating Hierarchy HIERARCHY
  41. 41.  Gating Hierarchy HIERARCHY 1 2 3 4 5a 5b
  42. 42.  Numbers  Percentages – parent and total  MFI - Median/Mean Fluorescent intensity  CV’s STATISTICS
  43. 43.  As we increase our number of observations we also increase the ability to resolve smaller and smaller changes STATISTICAL RELEVANCE IN FLOW CYTOMETRY The smallest flow file will generally contain at least 5000 events. It is not unusual to obtain >10^6 events.  http://www.dako.com/08065_15dec05_guide_to_flow_cytometry. pdf
  44. 44.  Data must be on scale  There must be controls to show the relationship between populations  Instrument settings must be constant  Be careful viewing uncompensated data  Do not over interpret results (especially without the correct controls) HOW TO INTERPRET PLOTS
  45. 45.  Out of scale data cannot be read efficiently. DATA MUST BE ON SCALE Right most population off scale
  46. 46. 1. Decide what your looking for 2. Decide on the logic used to identify the population of interest 3. Label Everything 4. Draw your plots 5. Open you gate hierarchy 6. Draw the Gates 7. Chose your statistics of interest CREATING AN ANALYSIS TEMPLATE
  47. 47. INSTRUMENTATION Analysers  FACSCalibur  CantoI  CantoII  AMR Fortessa  LSRII SORP Sorters and Cell Separation  FACSAriaIIu  FACSAriaIII (x 2)  AutoMacs Pro
  48. 48. FACS CALIBUR* 2 laser 488nm (blue) 633nm (red) 8 parameters SSc & FSc blue laser - 3x red laser - 1x Event rate < 3, 000
  49. 49. CANTO I 2 laser 488nm (blue) 633nm (red) 8 parameters SSc & FSc blue laser - 4x red laser - 2x Event rate < 15, 000
  50. 50. CANTO II 3 laser 405nm (violet) 488nm (blue) 633nm (red) 10 parameters SSc & FSc violet - 2x blue laser - 4x red laser - 2x Event rate < 10, 000
  51. 51. AMR FORTESSA 4 laser 405nm (violet) 488nm (blue) 533nm (YG) 633nm (red) 15 parameters SSC & FSC violet - 4x blue laser - 2x yellowgreen - 4x red laser - 3x Event rate < 20, 000
  52. 52. LSRII SORP ** 5 laser 355nm (UV) 405nm (violet) 488nm (blue) 561nm (YG) 633nm (red) 20 parameters SSc & FSc & FSc PMT UV - 2x violet - 6x blue - 2x YG -4x red - 3x Event rate < 20, 000
  53. 53. ARIA IIU CELL SORTER 3 laser 405nm (violet) 488nm (blue) 633nm (red) 12 parameters SSc & FSc violet - 2x blue - 6x red - 2x Event rate < 20, 000
  54. 54. ARIA III CELL SORTER 4 laser 405nm (violet) 488nm (blue) 561nm (YG) 633nm (red) 18 parameters SSc & FSc violet - 6x blue - 2x YG - 5x red - 3x Event rate < 20, 000
  55. 55. AUTOMACS PRO Magnetic Cell Separation Technique. Speed ~4ml in 15mins
  56. 56. WHAT’S INSIDE A FLOW CYTOMETER ?  Flow cytometers have 3 key systems  Fluidics  Optics  Electronics
  57. 57. FLUIDICS SYSTEM Wet cart Sheath filter Flow Cell Waste 1. Top up at start of run
  58. 58. FLUIDICS SYSTEM Wet cart Sheath filter Flow Cell Waste 1. Top up at start of run 2. Check and remove air bubbles
  59. 59. FLUIDICS SYSTEM Wet cart Sheath filter Flow Cell Waste 1. Top up at start of run 2. Check and remove air bubbles 3. Ensure flow cell is free from air and blockages
  60. 60. FLUIDICS SYSTEM Wet cart Sheath filter Flow Cell Waste 1. Top up at start of run 2. Check and remove air bubbles 3. Ensure flow cell is free from air and blockages 4. Ensure no air bubbles in line and waste height doesn’t change
  61. 61. INSTRUMENT POWER
  62. 62. INSTRUMENT STARTUP
  63. 63. SHEATH FILTER
  64. 64. FLUIDICS PRIME 1. Turn system on 2. Remove air From Sheath Filter 3. Perform software fluidics startup Canto I, and Canto II
  65. 65. FLUIDICS PRIME 1. Turn system on 2. Remove air From Sheath Filter 3. Turn laser off (if possible) 4. Prime 2 x ( no Tube) 5. Run TDW for 1 min – or until no air in waste lines 6. Turn laser on. Calibur LSRII / LSRII SORP
  66. 66. FLOW CELL Low Medium High Hydrodynamic focusing of sample to laser intercept - (interrogation point) Legend Laser intercept Core Stream
  67. 67. FLOW CELL Hydrodynamic focusing of sample to laser intercept - (interrogation point) Low Medium High Legend Laser intercept Core Stream Laser focal plane Signal spread
  68. 68. SAMPLE FLOW RATE CONTROL
  69. 69. OPTICS Laser emission Laser delivery Sample laser interaction at flow cell Emission collection Spectral separation Ensure lasers are on - software LSRII SORP OR Hardware
  70. 70. OPTICS Laser emission Laser delivery Sample laser interaction at flow cell Emission collection Spectral separation Ensure lasers are on - software LSRII SORP OR Hardware Ensure Clean Flow cell
  71. 71. OPTICS Laser emission Laser delivery Sample laser interaction at flow cell Emission collection Spectral separation Ensure lasers are on - software LSRII SORP OR Hardware Ensure Clean Flow Cell Achieved by filter selection
  72. 72. OPTICS: LASERS
  73. 73. OPTICS: FLOW CELL
  74. 74. OPTICS  Allows the excitation and the collection of the emitted light LASER Steering mirrors Steering mirrors Flow Cell - interrogation point emission
  75. 75. OPTICS CONT.. Signal Detection is achieved by collecting emitted or scattered light Forward Scatter (FSc) detector Fluorescent and Side Scatter (SSc) Detectors
  76. 76.  Dichroic mirrors bounce light  Bandpass filter clean up the signal HOW DO WE COLLECT MULTIPLE SIGNALS FROM THE ONE EXCITATION SOURCE ? Dichroic Mirror
  77. 77. SPECTRAL SEPARATION  Dichroic mirrors  LP (Long Pass) – allows light longer than nominated wavelength to pass  SP (Short Pass) – allows light shorter than nominated wavelength to pass  Band Pass filters  Restrict the wavelength of light that is allowed to pass
  78. 78. SPECTRAL SEPARATION  Band Pass filters  Restrict the wavelength of light that is allowed to pass Centre of bandpass Width of bandpass
  79. 79. UNDERSTANDING PMT ARRAYS Dichroic ring Band Pass ring PMT ring
  80. 80. USING PMT ARRAYS Channel Common fluorochrome B 780 PE CY7 B 670 PE CY5 PerCP B 610 Dichroic only B 575 PE B 530 FITC/ GFP 488/10 SSC
  81. 81. UNDERSTANDING PMT ARRAYS Position Wave length A B C D E F A
  82. 82. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B C D E F A
  83. 83. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B C D E F A B
  84. 84. UNDERSTANDING PMT ARRAYS position Wave length A >488nm B >735nm C D E F A B
  85. 85. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C D E F A B C
  86. 86. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D E F A B C
  87. 87. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D E F A B C D
  88. 88. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D 488-735nm E F A B C D
  89. 89. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D 488-735nm E F A B C D E
  90. 90. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D 488-735nm E 655-735nm F A B C D E
  91. 91. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D 488-735nm E 655-735nm F A B C D E F
  92. 92. UNDERSTANDING PMT ARRAYS Position Wave length A >488nm B >735nm C 750-810nm D 488-735nm E 655-735nm F 670-735nm A B C D E F
  93. 93. CONFIGURATION DOCUMENTS
  94. 94. UNDERSTANDING THE PMT Detector or PMT Amplification Voltage Electron Cascade Digitisatio n and processing http://sales.hamamatsu.com/assets/applicati ons/ETD/pmt_handbook_complete.pdf Light signal electronic signal
  95. 95. AFFECT OF PMT VOLTAGE Low voltage Negative population
  96. 96. AFFECT OF PMT VOLTAGE Mid Voltage Negative population Negative population Low voltage
  97. 97. AFFECT OF PMT VOLTAGE High Voltage Negative population ??? Negative population ??? Negative population ??? Mid VoltageLow voltage

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