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