sort - mitweb.mit.edu/flowcytometry/www/bd-horizon-tour-2016-sort.pdfcell sorting cell sorting:...
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SortBest practices in panel design to optimize the isolation of cells of interest
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For Research Use Only. Not for use in diagnostic or therapeutic procedures.
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23-18846-00
Cell sorting
Cell sorting: isolation of a population of interest for downstream analysis
• Cell enrichment
• Cell transplantation
• Downstream functional and genomic analysis
Goal: to obtain a pure population with maximum yield
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Increasing resolution for cell sorting
• Clear resolution of a population of interest is critical for an optimal sort.
• How to increase resolution in a sorting setting?
– Eliminate the impact of unwanted cells
– Increase the ability to visualize from population of interests.
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Increasing resolution for cell sorting
• Clear resolution of a population of interest is critical for an optimal sort.
• How to increase resolution in a sorting setting?– Eliminate the impact of unwanted cells.
– Increase the ability to visualize population of interests.
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CD
3
BV421
V450 FITCPerCP-Cy™5.5
PE PE-CF594 Alexa Fluor®
647
Alexa Fluor®
700
CD197 (CCR7)
Considerations for cell sorting
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Cell analysis
• Fluorochromes
• Biology
• Instrument setup
Cell sorting
• Fluorochromes
• Biology
• Instrument setup
• Sample preparation
• Gating strategy
Considerations for cell sorting: overview
• Experiment setup
– Sample preparation
– Instrument settings
• Gating strategy
– Histogram vs plots
– Biexponential scale
– Doublet discrimination
– Data display
• Panel design
– Dead cell exclusion
– Lineage exclusion/depletion
– Antibody titration
– Fluorochrome choice
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Considerations for cell sortingSample preparation, instrument setup
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Sample preparation
• Cell dissociation/detachment
• Cell resuspension buffer
• Staining volume and antibody concentration
• Cell sorting buffer and cell density
• Optional use of DNAse
• Temperature, pH
• Sample collection:
– Cell collection buffer (cell culture, transplantation, genomic analysis)
– Temperature, pH
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Instrument settings
• Nozzle size/sheath pressure
– 70 µm/70 psi for lymphocytes
– 100 µm/20 psi for larger and/or fragile cells
• Event rate (number of events/second)
– Low speed for higher sorting efficiency
• Sort setup
– Bulk sorting
– Purity vs yield
– Single cells
• Laser alignment
• Drop delay
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Instrument settings: speed vs yield vs purity
• Influenced by:
– Drops per second, events per second, sort “mask” and target population frequency
• Good rule of thumb:
– Maximum recommended event rate = drops per second / 5
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0
10
20
30
40
50
60
70
80
90
100
0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80
Events/second (x 1000)
Percen
t Y
ield
Speed
Purity Yield
Considerations for cell sortingGating strategy
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Histogram vs plots, biexponential scale, doublet discrimination, data display
Different options for data display
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Histogram Dot plot Contour plot
CD-X
Co
un
t
CD-X
CD
-Y
CD-X
CD
-Y
Histograms vs plots: How many populations do you see?
13
CD-X BUV395
CD-X BUV395
SS
C-A
CD4 BUV395
CD-X BUV395
CD-X BUV395
Cou
nt
Cou
nt
SS
C-A
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Dot plots vs contour plots:How many population do you see?
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CD
45
RA
AP
C
CD197 BV421
CD
45
RA
AP
C
CD197 BV421
Histograms vs bivariate plots:where to draw the gate?
• Transfected cells express different levels of GFP.
• Bivariate plots better reveal the separation from negative/dim to positive cells.
• What if GFP is expressed at low levels?
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Co
un
t
SS
C-A
GFPGFP
Gating low GFP expressing cells:what is real and what is not?
• High background in the GFP channel is usually due to autofluorescence.
• Negative controls are instrumental for proper gating.
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GFPS
SC
-A
SS
C-A
GFP
Parental cells Transfected reporter cells
Gating low GFP expressing cells:what is real and what is not?
• High background in the GFP channel is usually due to autofluorescence.
• Negative controls are instrumental for proper gating.
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GFPS
SC
-A
SS
C-A
GFP
3.8%2%
Parental cells Transfected reporter cells
Gating low GFP expressing cells:leveraging autofluorescence
• Autofluorescence is detected in multiple channels.
• Plot GFP against another channel with autofluorescence.
• Autofluorescent cells will be “double positive” (diagonal), revealing true GFP single positives.
Parental cells
PerC
P-C
y5
.5 0%
GFP
3.1%
Transfected cells
PerC
P-C
y5
.5
GFP
PerCP-Cy5.5
SS
C-A
SS
C-A
GFP
Parental cells Transfected cells
2.5% 4.8%
This example showing different displays of the same data shows the value of the biexponentialscale, a mostly logarithmic scale on the upper end, linear at the low end and symmetrical about the negatives.
• Compensated single positives are continuous.
• All populations are visible.
0 100 1000 10000 1x105
<FITC-A>
0
100
1000
10000
1x105
<P
E-A
>
Biexponential scale
Standard log scale
These look like two separate populations.
This population “looks” under compensated. Visualization of
compensated data is greatly improved using the biexponential scale.
The biexponential scale: the best way to look at compensated data
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Gating strategy: biexponential scaleC
D3
BU
V3
95
CD4 PerCP-Cy5.5
CD
3 B
UV
39
5
CD4 PerCP-Cy5.5
CD
3 B
UV
39
5
CD4 PerCP-Cy5.5
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Doublet discrimination
Sort check
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Electronic pulse
Height
Area
Width
Sig
na
l
Time
Sig
na
l
Time
Sig
na
lTime
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Doublet discrimination
Sig
na
l
Time
1x Width
2x Width
Sig
nal
Time
FS
C-H
FSC-W
SS
C-H
SSC-W
SS
C-A
FSC-A
Cells
Doublet discrimination
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DAPI
2n
4nDoublets
>4n
Gate on cells Gate on doublets Gate on singlets
Doublets
Singlets
Doublet discrimination
Singlets DoubletsTotal cells
Bulk sort
Single-cell sort
SingletsTotal cells
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Gating strategy:low antigen density populations
CD11b FITC
Unstained
CD
14
AP
C
Post-sort
CD11b FITC
CD
14
AP
C
Pre-sort
CD11b FITC
CD
14
AP
C
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Gating strategy:low antigen density populations
CD11b FITC
Unstained
CD
14
AP
C
Post-sort
CD11b FITC
CD
14
AP
C
Pre-sort
CD11b FITC
CD
14
AP
C
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Gating strategy:low antigen density populations
CD11b BV421
Unstained
CD
14
AP
C
Post-sort
CD11b BV421
CD
14
AP
C
Pre-sort
CD11b BV421
CD
14
AP
C
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Gating strategy: summary
• Use bivariate plots rather than histograms.
• Use contour plots for a clearer identification of populations of interest.
• Manually adjust the biexponential scale to gate all the cells of interest.
• Use proper controls to identify and eliminate background (autofluorescence).
• Use a doublet discrimination strategy for proper isolation of a single-cell suspension.
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Considerations for cell sortingPanel design
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Fluorochrome choice, dead cell exclusion, lineage exclusion/depletion
Why is it relevant to design an optimized panel for cell sorting?
• Best practices to build an optimized panel for analysis apply to the cell sort as well.
• Additional considerations may be taken in account when designing a panel for cell sorting to obtain:
– Highest purity and yield
– Clear resolution from unwanted cell populations
CD11b FITC
CD
14
AP
C
18%
CD11b BV421
CD
14
AP
C
22%
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How to build a panel for cell sorting?
• A good panel for sorting relies on the use of negative as well as positive markers.
• Properly choose fluorochromes.
– Antigen density
– Spillover
– Co-expression
• Know the biology.
– Minimize spillover into the most critical markers to maximize the resolution of your population of interest.
• Exclude unwanted cells to increase the resolution of the target cells.
– Dead cells
– Lineage
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Choosing fluorochromes for a cell sorting panel: exclude unwanted cells
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Dead cells
Lineage cells
Cells of interest
Choices for dead-cell exclusion
Choices for lineage exclusion
Dead-cell exclusion
The presence of dead cells impacts cell sorting.
• Inaccurate quantification of the population of interest
• Reduced purity
• Dead cells can be excluded using:
– Light scatter properties
– Viability dyes
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SS
C-A
FSC-A
Dead-cell exclusion by light scatter
• Scatter alone can be used to identify heat-killed HeLa cells.
• A viability dye is required to detect and gate out dead cells.
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Live and heat-killedHeLa cells S
SC
-A
FSC-A
SS
C-A
FSC-A
Mousebone marrow S
SC
-A
FSC-A
SS
C-A
FSC-A
SS
C-A
Viability dye
SS
C-A
Viability dye
Dead-cell exclusion using viability dyesDye Unfixed
cellsFixed cells
Detector Laser
DAPI X BV421 UV/Violet
Via-ProbeGreen X FITC
Blue
PI X PE Blue/YG
7-AAD X
PerCP-Cy™5.5
Blue/YG
DRAQ7™ X APC Red
Via-Probe Red X APC
Red
FVS450 BV421 Violet
FVS510 BV510 Violet
FVS575V BV605 Violet
FVS520 FITC Blue
FVS570 PE Blue/YG
FVS620 PE-CF594 Blue/YG
FVS660 APC Red
FVS700 AF700 Red
FVS780 APC-H7 Red
• Nucleic acid dyes bind nucleic acids non-covalently
• No-wash stain procedure
• Recommended for sort of unfixed samples
• Fixable Viability Stains bind amine moieties covalently
• Wash is required after stain
• Recommended for sort of fixed samples
Choosing fluorochromes for a cell sorting panel: exclude unwanted cells
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Dead cells
Lineage cells
Cells of interest
Choices for dead-cell exclusion
Choices for lineage exclusion
Lineage-cell exclusion
The presence of lineage cells impacts cell sorting.
• Inaccurate quantification of the population of interest
• Reduced purity
• Increased time necessary to sort a rare population
• Lineage cells can be excluded using:
– Light scatter properties
– Lineage cocktails
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SS
C-A
FSC-A
Lineage exclusion by light scatter
• In peripheral blood, different cell lineages can be easily discriminated based on light scatter.
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CD4 FITCA
PC
SS
C-A
FSC-A CD4 FITC
AP
C
Sca-1
c-k
it
Lineage exclusion by light scatter is not sufficient for rare population detection
• In samples such as mouse bone marrow, detection of rare stem cells is confounded by the overwhelming presence of lineage cells.
• The use of lineage markers is needed to clearly detect rare populations of interest.
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FSC-A
SS
C-A
FSC-A
SS
C-A
Examples of lineage marker cocktails
• Take into consideration instrument configuration and available detectors.
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Lineage cocktail Marker Fluorochrome
T cells CD3 FITC
B cells CD19 APC
NK cells CD56 PerCP-Cy5.5
Monocytes/macrophages CD14 BV421
Erythrocytes CD235a BV786
Examples of lineage marker cocktails
• Take into consideration instrument configuration and available detectors.
• Combine all lineage markers in the same format to overcome configuration limitations and to increase panel design flexibility.
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Lineage cocktail Marker Fluorochrome
T cells CD3 PerCP-Cy5.5
B cells CD19 PerCP-Cy5.5
NK cells CD56 PerCP-Cy5.5
Monocytes/macrophages CD14 PerCP-Cy5.5
Erythrocytes CD235a PerCP-Cy5.5
Choosing a fluorochrome for a lineage cocktail
• Match the fluorochrome for the lineage cocktail with a viability dye detected in the same channel.
• In a single channel (dump channel), lineage and dead cells can now be excluded.
• Choose moderate dyes with high spillover into other detectors for the dump channel.
• Reserve dyes with bright signal and low spillover for the population of interest.
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Fluorochrome Viability dye
FITCBD Via-Probe Green, FVS520
PerCP-Cy5.5 7-AAD, FVS620
APCBD Via-Probe Red, FVS660
Alexa Fluor®
700DRAQ7, FVS700
BV421 DAPI, FVS450
Building a lineage dump channel
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Lineage 1PerCP-Cy5.5
SS
C-A
Lineage 2PerCP-Cy5.5
SS
C-A
Lineage 3PerCP-Cy5.5
SS
C-A
All lineagesPerCP-Cy5.5
+7-AAD
SS
C-A
SS
C-A
PerCP-Cy5.5
SS
C-A
7-AAD CD-X BV421
CD
-Y A
lexa F
luo
r®
64
7
2.4%
CD-X BV421
CD
-Y A
lexa F
luo
r®
64
7
15.4%
No lineage exclusion Lineage exclusion
Advantages of depleting lineage cellsprior to cell sort
• Lineage cells can be removed from the sample prior to sort using multiple rounds of magnetic selection or cell sorting
– Cell enrichment
– Cell depletion
• Lineage depletion can improve cell sorts of rare population of cells
– Increased sort efficiency
– Increased purity
– Reduced sort time
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Magnetic depletion of lineage cellsreduces sorting time…
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Theoretical time to sort 105 pDCs
2.5 minutes
pDCs 0.075%
pDCs 10.7%
No lineage depletion
1st round of lineage depletion
HLA
-DR
V4
50
CD11c APC
CD
12
3 P
E
HLA
-DR
V4
50
CD
12
3 P
E
0.28%
21.6%
Lineage FITC
Lineage FITC CD11c APC
Theoretical time to sort 105 pDCs
6.5 hours
46
…and increases purity
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No lineage depletion 1st round magnetic lineage depletion
CD11c APC
SS
C-A
HLA
-DR
V4
50
CD
12
3 P
E
FSC-A
SS
C-A
HLA
-DR
V4
50
CD11c APC
FSC-A
CD
12
3 P
E
lin FITC lin FITC
Choosing fluorochromes for a cell sorting panel: resolve the population of interest
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Dead cells
Lineage cells
Cells of interest
Choices for dead-cell exclusion
Choices for lineage exclusion
Choices for populations of interest
Detection of murine hematopoietic stem and progenitor cells
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Bone marrow
c-K
it
Sca-1
Myeloid
pro-B B cell
CLP2
CD127+
CLP
GMLP HSC
• Hematopoietic stem cells (HSCs) and common lymphoid progenitors (CLPs) are rare cell populations (<1%) in mouse bone marrow.
• HSCs: bright expression of c-kit and Sca-1
• CLPs: dim expression of c-kit and Sca-1
• Clear resolution of dim and bright c-kit and Sca-1 populations is critical for the isolation of HSCs and CLPs.
Adapted from Iwasaki H, Akashi K. Hematopoietic developmental pathways: on cellular basis. Oncogene. 2007; 26:6687-6696.
BV421
APC/Alexa Fluor® 647
FITC/Alexa Fluor® 488
PerCP-Cy5.5
BV510
V450
V500
Alexa Fluor® 700
APC-H7
BV605
BV650
PE
BV786
PE-CF594
BB515
CD127
c-kit
Sca-1
Lineage/7-AAD
Impact of fluorochrome choice on HSC and CLP resolution
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Antigen Assignment
FluorochromeSpecificity Laser
Fluorochrome choice: panel 1
Antigen density: APC-H7 is not bright enough to clearly separate dim CLPs.
Adjacent spillover: Co-expression of c-kit and CD127 was not taken into consideration.
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c-k
it A
PC
-H7
Sca-1 PE
HSCs
CD127 APC
Co
un
t
CLPs
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BV421
APC/Alexa Fluor® 647
FITC/Alexa Fluor® 488
PerCP-Cy5.5
BV510
V450
V500
Alexa Fluor® 700
APC-H7
BV605
BV650
PE
BV786
PE-CF594
BB515
CD127
c-kit
Sca-1
Lineage/ 7-AAD
FluorochromeSpecificity Laser
Antigen Assignment
Impact of fluorochrome choice on HSC and CLP resolution
Fluorochrome choice: panel 2
Antigen density: BV421 clearly separates dim and bright c-kit positive cells.
Adjacent spillover: Fluorochromes were spread across different lasers, for minimal spectral overlap, maximum resolution.
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c-K
it B
V4
21
Sca-1 PE
HSCs
CLPs
CD127 APC
Co
un
t
Fluorochrome choice: panel comparison
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c-K
it A
PC
-H7
Sca-1 PE Sca-1 PE
c-k
it B
V4
21
Recipe for best panel for sorting
• Use a dump channel to exclude dead and lineage cells.
• Magnetic depletion of lineage cells further improves the cell sort of rare populations.
• Take into consideration co-expression and spillover.
• Match the brightest fluorochromes with the antigens with lower antigen density.
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Conclusion
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Dead cells
Lineage cells
Cells of interest
Choices for dead-cell exclusion
Choices for lineage exclusion
Choices for populations of interest