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.

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. 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.  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.  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.  Understanding Fluorochromes
PANEL DESIGN
Input Light
Energy
Output Light
Energy
Fluorochrome

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.  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.  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.  Is there anything intrinsic in my sample that I will restrict my
choices?
 Fluorescent Proteins
 Auto Fluorescence
PANEL DESIGN:
FLUOROCHROME RESTICTIONS

10.  What fluorochromes can I see on the instrument?
PANEL DESIGN:
FLUOROCHROME RESTICTIONS
http://flow.garvan.org.au/flow-
cytometers-instrument-details

11.  What fluorochromes antibody combinations are available?
PANEL DESIGN:
FLUOROCHROME RESTICTIONS

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.  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. PANEL DESIGN:
OPTIMISING FLUOROCHROME COMBINATIONS
Epitope Expression Level
Fluorochrome Brightness

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. 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.  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.  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.  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. 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. 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. Unstained controls
 Allow relative Determination of positivity
PUTTING IT ALL TOGETHER:
CONTROLS
Question : Which Populations is the Positive ?

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.  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. EFFECT OF COMPENSATION
Digital
compensation
doesn’t change the
underlying data it
just allows us to
interpret it

26. EFFECT OF COMPENSATION
Digital
compensation
doesn’t change the
underlying data it
just allows us to
interpret it

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. 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. 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. 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. 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. 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.  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.  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. EFFECT OF COMPENSATION
Digital
compensation
doesn’t change the
underlying data it
just allows us to
interpret it

36. EFFECT OF COMPENSATION
Digital
compensation
doesn’t change the
underlying data it
just allows us to
interpret it

37. DATA ANALYSIS AND INTERPRETATION

38. PLOT TYPES
Dot Plot
Histogram Histogram
Contour Plot

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.  Gating Hierarchy
HIERARCHY

41.  Gating Hierarchy
HIERARCHY
1
2
3
4
5a
5b

42.  Numbers
 Percentages – parent and total
 MFI - Median/Mean Fluorescent intensity
 CV’s
STATISTICS

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.  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.  Out of scale data cannot be read efficiently.
DATA MUST BE ON SCALE
Right most population off scale

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. INSTRUMENTATION
Analysers
 FACSCalibur
 CantoI
 CantoII
 AMR Fortessa
 LSRII SORP
Sorters and
Cell Separation
 FACSAriaIIu
 FACSAriaIII (x 2)
 AutoMacs Pro

48. FACS CALIBUR*
2 laser
488nm (blue)
633nm (red)
8 parameters
SSc & FSc
blue laser - 3x
red laser - 1x
Event rate
< 3, 000

49. CANTO I
2 laser
488nm (blue)
633nm (red)
8 parameters
SSc & FSc
blue laser - 4x
red laser - 2x
Event rate
< 15, 000

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. 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. 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. 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. 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. AUTOMACS PRO
Magnetic Cell
Separation
Technique.
Speed ~4ml in
15mins

56. WHAT’S INSIDE A FLOW CYTOMETER ?
 Flow cytometers have 3 key systems
 Fluidics
 Optics
 Electronics

57. FLUIDICS SYSTEM
Wet
cart
Sheath
filter
Flow
Cell
Waste
1. Top up at start of
run

58. FLUIDICS SYSTEM
Wet
cart
Sheath
filter
Flow
Cell
Waste
1. Top up at start
of run
2. Check and
remove air
bubbles

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. 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. INSTRUMENT POWER

62. INSTRUMENT STARTUP

63. SHEATH FILTER

64. FLUIDICS PRIME
1. Turn system on
2. Remove air From Sheath Filter
3. Perform software fluidics startup
Canto I, and Canto II

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. FLOW CELL
Low
Medium
High
Hydrodynamic
focusing of
sample to laser
intercept -
(interrogation point)
Legend
Laser intercept
Core Stream

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. SAMPLE FLOW RATE CONTROL

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. 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. 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. OPTICS: LASERS

73. OPTICS: FLOW CELL

74. OPTICS
 Allows the excitation and the collection of the emitted light
LASER
Steering
mirrors
Steering
mirrors
Flow Cell -
interrogation
point
emission

75. OPTICS CONT..
Signal Detection
is achieved by
collecting
emitted or
scattered light
Forward Scatter (FSc)
detector
Fluorescent and Side
Scatter (SSc) Detectors

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. 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. SPECTRAL SEPARATION
 Band Pass filters
 Restrict the wavelength of
light that is allowed to pass
Centre of
bandpass
Width of
bandpass

79. UNDERSTANDING PMT ARRAYS
Dichroic ring
Band Pass ring
PMT ring

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. UNDERSTANDING PMT ARRAYS
Position Wave length
A
B
C
D
E
F
A

82. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B
C
D
E
F
A

83. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B
C
D
E
F
A
B

84. UNDERSTANDING PMT ARRAYS
position Wave length
A >488nm
B >735nm
C
D
E
F
A
B

85. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B >735nm
C
D
E
F
A
B
C

86. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B >735nm
C 750-810nm
D
E
F
A
B
C

87. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B >735nm
C 750-810nm
D
E
F
A
B
C
D

88. UNDERSTANDING PMT ARRAYS
Position Wave length
A >488nm
B >735nm
C 750-810nm
D 488-735nm
E
F
A
B
C
D

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. 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. 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. 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. CONFIGURATION DOCUMENTS

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. AFFECT OF PMT VOLTAGE
Low voltage
Negative
population

96. AFFECT OF PMT VOLTAGE
Mid Voltage
Negative
population
Negative
population
Low voltage

97. AFFECT OF PMT VOLTAGE
High Voltage
Negative
population ???
Negative
population ???
Negative
population ???
Mid VoltageLow voltage