These particles have something in common

(1)

These particles have something in common

Algae

Chromosomes Blood cells

Protozoa

Certain parameters of these particles can be measured with a flow

cytometer

(2)

Which parameters can be measured?

the relative size (Forward Scatter - FSC)

the granularity or complexity (Side Scatter

-SSC)

(3)

Characteristics of FSC and SSC

Coherent lightsource (488 nm) Forward scatter Cell size (488 nm) Side scatter Granularity (488 nm) Side scatter (SSC)

measured in 90° direction to the excitation light

proportional to cell „complexity“ or granularity

Forward scatter (FSC)

measured along the axis of the incoming light

proportional the the cell size / cell surface (only true for perfect round cells)

(4)

An example of light scatter:

Forward scatter Side scatter Granulocytes Debris Lymphocytes Monocytes

(5)

Fluorescence

λ=488 nm

Excitation light

λ=530 nm

Emission light

The fluorochrome molecule absorbes the energy of the incoming light It releases the absorbed energy by:

vibration and dissipated heat

(6)

Fluorescence intensity

FITC

101 ₁₀2 ₁₀3 ₁₀4

Relative fluorescence intensity

Number of Events FITC FITC FITC F IT C FITC FITC FITC FITC

(7)

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

(8)

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.

(9)

The basic microscope

In a standard

microscope, the

operator uses the

XY-stage to screen the

sample and detect

cells of interest.

(10)

The automated Microscope

Waste

Detector

& Counter

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!

(11)

Basic fluidics of the FACSAria

Plenum

Cuvette

Waste

Sheath

Fluidics Cart

Pressure

Sample tube

(12)

Hydrodynamic focussing in the cuvette

Sample Sample 1 Sheath Sheath Sample pressure low, small core stream. Good for DNA analysis High sample pressure, broader core stream. Bad for DNA analysis

(13)

Summary

• 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

(14)

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.

(15)

Basic optics

A system of prisms and

lenses directs the laser light

to the interrogation point in

the cuvette

(16)

Basic Optics

The emitted light induced from each laser is focussed onto

separate glass fibers.

(17)

Optical filters

460 500 540 460 500 540 460 500 540 SP 500 SP 500 LP 500 LP 500 BP500/80BP500/80 Longpass Shortpass Bandpass

(18)

Octagon Detection System

PerCP-Cy5.5

FITC

695/40 655 LP

SSC

PE

_PE-Cy7

(19)

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

(20)

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

(21)

How a voltage pulse from the PMT is generated

Voltage Laser Laser Laser Laser Laser Laser t t t Voltage Voltage 1. 2. 3.

(22)

Height, Area, and Width

Time (µs) Voltage Pulse area(A) Pulse H e ight (H) Pulse Width (W) 40 0

(23)

Digitization

The pulses go into a digitizing system that scans the pulses with a rate of 10 MHz, which corresponds to a sample each 0,1 µs.

The pulse height of each slice is converted to a 14 bit number.

10 MHz scanning

(24)

Parameter Calculation

After the pulse has been digitized, the system can calculate the area and the width and apply the compensation to all signals.

Basically, the system works vice versa like your CD player at home. It generates the

(25)

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.

(26)

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

(27)

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.

(28)

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

(29)

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

(30)

Visualization of data

(31)

Visualization of data

FSC SSC FL1 FL2 30 60 638 840 100 160 245 85 300 650 160 720 Listmode file 2) Dotplot - two parameter are plotted on

X and Y Event 1 Event 2 Event 3 400 800 1000 0 840 85 245 ₆₃₈ FL1-H FL2-H 0 200 400 600 800 1000 200 600

(32)

Enough theory of flow!

Let`s have a look at an example from real life

Enough theory of flow!

(33)

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 FITC, PE, 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 FITC, PE, PerCP und CD3-APC to determine suitable instrument settings

(34)

(35)

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.

(36)

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

(37)

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

(38)

Defining the population of interest

(39)

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%

(40)

Adjusting the fluorescence settings

A) Adjusting PMT voltages Sample: 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.

(41)

Theory of quadrant analysis

FL1-H FL2-H FITC + PE FITC PE negative Q2 Q4 Q3 Q1

(42)

Real life:

FITC-fluorescence overspill

650nm 700nm 500nm 550nm 600nm Relative Int ensität Wellenlänge (nm) FL1 530/30 FL2 585/42

(43)

FITC Compensation

Detektor - … % Signal FL1 530/30 FL2 585/42 650nm 700nm 500nm 550nm 600nm Relative Int ensität Wellenlänge (nm)

(44)

FITC Compensation

Lowering the FITC-population is achieved by...

... Subtracting a percentage of

FITC-intensity from the affected PE-channel ... 650nm 700nm 500nm 550nm 600nm FL1 530/30 _585/42FL2 R e la ti v e I n te ns

ity … because 25% of the

FITC-signal are actually detected in the PE

channel ...

(45)

PE-fluorescence overspill

650nm 700nm 500nm 600nm Wavelength (nm) 550nm Rel a tiv e Intensity FL3 größer 650 FL1 530/30 FL2 585/42

(46)

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.

(47)

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