these particles have something in common algae chromosomes blood cells protozoa certain parameters...
TRANSCRIPT
These particles have something in common
Algae
ChromosomesBlood cells
Protozoa
Certain parameters of these particles can be measured with a flow cytometer
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)
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
An example of light scatter:
Forward scatter
Sid
e sc
atte
rGranulocytes
Debris Lymphocytes
Monocytes
Fluorescence
=488 nm
Excitation light
=530 nm
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)
Fluorescence intensity
FITC
FIT
C
101 104103102
Relative fluorescence intensity
Nu
mb
er o
f E
ven
ts
FITC
FIT
CFITC
FITC
FITC
FITC
FIT
C
FITC
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
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.
The basic microscope
In a standard microscope, the operator uses the XY-stage to screen the sample and detect cells of interest.
The automated Microscope
Waste
Detector& Counter
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!
Basic fluidics of the FACSAria
PlenumCuvette
Waste
Sheath
Fluidics Cart
Pressure
Sampletube
1
Hydrodynamic focussing in the cuvette
SheathSample
SheathSample
Sample pressure low, small core stream. Good for DNA analysis
High sample pressure, broader core stream.Bad for DNA analysis
• 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
Summary
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.
Basic optics
A system of prisms and lenses directs the laser light to the interrogation point in the cuvette
Basic Optics
The emitted light induced from each laser is focussed onto separate glass fibers.
Optical filters
460 500 540460 500 540 460 500 540
SP 500SP 500LP 500LP 500 BP500/80BP500/80
Longpass Shortpass Bandpass
Octagon Detection System
SSC
PE PE-Cy7
FITC
PerCP-Cy5.5
695/40
655 LP
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
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
How a voltage pulse from the PMT is generated
Voltage
LaserLaser
LaserLaser
LaserLaser
t
t
t
Voltage
Voltage
1.
2.
3.
Height, Area, and Width
Time (µs)
Volt
age
Pulse area(A)
Puls
e H
eig
ht
(H)
Pulse Width (W)
400
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.
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
Instrument settings
the exact values for PMT voltages and thresholds are depending on the
applications (type of cells, staining methods) and the specific instrument.
Displaying the data in a linear fashion or using the logarithmic form is
also depending on the application.
the exact values for PMT voltages and thresholds are depending on the
applications (type of cells, staining methods) and the specific instrument.
Displaying the data in a linear fashion or using the logarithmic form is
also depending on the application.
Workstation
• The connected workstation is designed for instrument control, data
acquisition, -storage and -analysis.
• OS is Windows2000 Professional running on a IBM-compatible
computer platform.
•Software• DiVa application: Instrument connectivity, Data-acquisition and
analysis system• DiVa Data Manager: Backup and Restore the database.
• The connected workstation is designed for instrument control, data
acquisition, -storage and -analysis.
• OS is Windows2000 Professional running on a IBM-compatible
computer platform.
•Software• DiVa application: Instrument connectivity, Data-acquisition and
analysis system• DiVa Data Manager: Backup and Restore the database.
Data saving
All data are saved directly into a special database. Every plot
is connected with its corresponding datafile. All tubes carry
a copy of the instrument setting that was active during
acquisition.
Due to this, there are no special save commands in the
software. Every action is recorded in the database. When
you quit and re-start the software, it will open the last
experiment exactly at the position you left it.
All data are saved directly into a special database. Every plot
is connected with its corresponding datafile. All tubes carry
a copy of the instrument setting that was active during
acquisition.
Due to this, there are no special save commands in the
software. Every action is recorded in the database. When
you quit and re-start the software, it will open the last
experiment exactly at the position you left it.
Visualization of data
1) Histograms - single parameter, intensity plotted as frequency distribution
Event 1
Event 2
Event 3
FSC SSC FL1 FL2
30 60 638 840
100 160 245 85
300 650 160 720
Listmode file
400 800 10000
840
85
245 638FL1-H
FL2-H
0
200
400
600
800
1000
200 600
Visualization of data
2) Dotplot - two parameter are plotted on X and Y
Enough theory of flow!
Let`s have a look at an example from real life
Enough theory of flow!
Let`s have a look at an example from real life
Example: Determine the percentage of CD3, CD4, and CD8 populations from whole blood
Material• Mouse splenocytes
Method• Three-colour immunofluorescence
Preparation• Staining of freshly isolated splenocytes
Stainings• Isotype controls• Single-colour stainings for CD3-FITC, CD3-PE, CD3-PerCP und CD3-APC to determine suitable instrument settings
Material• Mouse splenocytes
Method• Three-colour immunofluorescence
Preparation• Staining of freshly isolated splenocytes
Stainings• Isotype controls• Single-colour stainings for CD3-FITC, CD3-PE, CD3-PerCP und CD3-APC to determine suitable instrument settings
Prepare the instrument
Proper adjustment of FSC and SSC voltage
• FSC und SSC are optimally
adjusted when the population of
interest (i.e. Lymphocytes) can be
resolved from all other
populations
• The threshold on FSC is
adjusted so that most of the
debris is excluded from the data
acquisition.
• FSC und SSC are optimally
adjusted when the population of
interest (i.e. Lymphocytes) can be
resolved from all other
populations
• The threshold on FSC is
adjusted so that most of the
debris is excluded from the data
acquisition.
Parameters (I)
• FSC and SSC
are depending on cell type and cell state (activated,
resting)
depend on the preparation method (Ficoll, LW,
LNW, fixation method etc.)
are normally used to define the population of interest for
further analysis
• FSC and SSC
are depending on cell type and cell state (activated,
resting)
depend on the preparation method (Ficoll, LW,
LNW, fixation method etc.)
are normally used to define the population of interest for
further analysis
Parameters
• Fluorescence channels (FL1, FL2, FL3, FLX)
depending on the specific staining (conjugate)
antibodies, propidium iodide for DNA-labelling, etc.)
most of the time fluorescence serves as marker for the
statistical analysis
• Fluorescence channels (FL1, FL2, FL3, FLX)
depending on the specific staining (conjugate)
antibodies, propidium iodide for DNA-labelling, etc.)
most of the time fluorescence serves as marker for the
statistical analysis
Defining the population of interest (often just named „gating“)
About „Gating“
• selectively analyse defined cell populations
• Gates can be set manually or automatically by software
• multidimensional gating with hierarchical gates
• too narrow gates may lead to the loss of cell populations
• too wide gates enhance the number of unwanted cells
• during analysis of the desired cell population the cells in the gate
are considered to be the 100%
• selectively analyse defined cell populations
• Gates can be set manually or automatically by software
• multidimensional gating with hierarchical gates
• too narrow gates may lead to the loss of cell populations
• too wide gates enhance the number of unwanted cells
• during analysis of the desired cell population the cells in the gate
are considered to be the 100%
Adjusting the fluorescence settings
A) Adjusting PMT voltagesSample: 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.
Theory of quadrant analysis
FL1-H
FL2-H
FITC+
PE
FITC
PE
negative
Q2
Q4Q3
Q1
Real life:FITC-fluorescence overspill
650nm 700nm500nm 550nm 600nm
Rel
ativ
e In
ten
sitä
t
Wellenlänge (nm)
FL1530/30
FL2585/42
FITC Compensation
Detektor - … % Signal
650nm 700nm500nm 550nm 600nm
Rel
ativ
e In
ten
sitä
t
Wellenlänge (nm)
FL1
530/30
FL2585/42
Lowering the FITC-population is achieved by...
... Subtracting a percentage of FITC-intensity from the affected PE-channel ...
650nm 700nm500nm 550nm 600nm
FL1530/30
FL2
585/42R
ela
tive I
nte
nsit
y
… because 25% of the FITC-signal are actually detected in the PE channel ...
Wavelength (nm)
FITC Compensation
PE-fluorescence overspill
650nm 700nm500nm 600nm
Wavelength (nm)
550nm
Rela
tive I
nte
nsit
y
FL3größer 650
FL1530/30
FL2585/42
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 single-color 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.
Summary
What we have seen:
• the emission spectra of common fluorochromes (FITC, PE)
• the spectral overlap of fluorochromes into neighbouring channels depending on the emission spectra and filtersets
• how spectral overlap can lead to misinterpretation of multicolour stainings
• How compensation can correct the spectral overlap of fluorochromes
What we have seen:
• the emission spectra of common fluorochromes (FITC, PE)
• the spectral overlap of fluorochromes into neighbouring channels depending on the emission spectra and filtersets
• how spectral overlap can lead to misinterpretation of multicolour stainings
• How compensation can correct the spectral overlap of fluorochromes