Aurora User Training July 2019 Cytometry and Antibody Technology - PowerPoint PPT Presentation

Aurora User Training July 2019 Cytometry and Antibody Technology Facility University of Chicago

What is spectral cytometry and how is it different than conventional flow cytometry? Cytometry and Antibody Technology Facility Aurora Training Course

First, let’s review conventional cytometry • In conventional cytometry, one detector is assigned to one fluorophore Cytometry and Antibody Technology Facility Aurora Training Course

Is a fluorochrome only the section of spectra that we choose to view? 670/30 Filter Emission Intensity APC Emission Spectrum Wavelength Cytometry and Antibody Technology Facility Aurora Training Course

With spectral cytometery, all detectors are used for all fluorophores – Center Center Laser Channel Bandwith (nm) Start (nm) End (nm) Laser Channel Bandwith (nm) Start (nm) End (nm) Wavelenght (nm) Wavelenght (nm) V1 427.5 15 420 435 B1 508 20 498 518 V2 443 15 436 451 B2 524.5 17 516 533 V3 458 15 451 466 B3 541.5 17 533 550 V4 473 15 466 481 B4 580.5 19 571 590 V5 508 20 498 518 B5 598 20 588 608 V6 524.5 17 516 533 B6 615 20 605 625 V7 541.5 17 533 550 Blue B7 660 17 652 669 V8 580.5 19 571 590 Laser B8 678 18 669 687 Violet V9 598 20 588 608 B9 697 19 688 707 V10 615 20 605 625 B10 717 20 707 727 V11 664 27 651 678 B11 738 21 728 749 V12 691.5 28 678 706 B12 760 23 749 772 V13 720 29 706 735 B13 783 23 772 795 V14 749.5 30 735 765 B14 811.5 34 795 829 V15 779.5 30 765 795 V16 811.5 34 795 829 Center Center Laser Channel Bandwith (nm) Start (nm) End (nm) Laser Channel Bandwith (nm) Start (nm) End (nm) Wavelenght (nm) Wavelenght (nm) YG1 577 20 567 587 R1 660 17 652 669 YG2 598 20 588 608 R2 678 18 669 687 YG3 615 20 605 625 R3 697 19 688 707 YG4 660 17 652 669 Red R4 717 20 707 727 Yellow YG5 678 18 669 687 Laser R5 738 21 728 749 Green YG6 697 19 688 707 R6 760 23 749 772 YG7 720 29 706 735 R7 783 23 772 795 YG8 749.5 30 735 765 R8 811.5 34 795 829 YG9 779.5 30 765 795 YG10 811.5 34 795 829 Cytometry and Antibody Technology Facility Aurora Training Course

With spectral cytometry, each fluorophore is identified by their distinct signature Yellow Green Violet Blue Red The entire emission spectra of BV785 fluorescent dyes excited by the onboard lasers is measured Emission spectra excited by the Violet, Blue, and Red lasers are PE measured from the laser line to the infrared region . Full spectrum capture enables the use of novel unmixing algorithm APC for data analysis. Cytometry and Antibody Technology Facility Aurora Training Course

Spectral cytometry allows us to use more colors because we can separate highly overlapping fluorophores APC Alexa Fluor 647 Cytometry and Antibody Technology Facility Aurora Training Course

What is the workflow? • Conventional flow cytometry • Spectral flow cytometry 1. Run single stained controls 1. Run unstained cells 2. Set voltages 2. Run reference controls (single stains) 3. Compensate (optional at this step) 3. Spectral unmixing (recommended but optional at 4. Run full stained samples this step) 5. Analyze samples in FlowJo or 4. Run full stained samples FCS Express 5. Analyze samples in FlowJo or • Compensation can be done after FCS Express sample collection 6. (Spectral unmixing can be done again if needed) Cytometry and Antibody Technology Facility Aurora Training Course

The unmixing algorithm converts raw data to unmixed data Unmixed Worksheet Raw Worksheet Unmixi xing Al Algorithm Cytometry and Antibody Technology Facility Aurora Training Course

Raw vs. Unmixed Data Raw Data Unmixed Data • Parameters are the • Parameters are the instrument channels (V1, V2, fluorochromes included in the etc.) assay • Visualized in raw worksheet • Visualized in unmixed worksheet • Large fcs file size: at least 48 parameters + FSC and SSC • Smaller fcs file size: number of fluors + FSC and SSC • Can be unmixed as many times as desired • Can not be used to unmix Cytometry and Antibody Technology Facility Aurora Training Course

How does the unmixing work? Fluorophore 1 0.35 0.3 0.25 Fluorophore 1 & 2 0.2 0.15 700 0.1 600 0.05 500 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 400 Fluorophore 2 300 0.45 200 0.4 0.35 100 0.3 0 0.25 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 0.2 0.15 0.1 How do we determine how much of each 0.05 0 fluorophore is contributing to this signal? 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 Cytometry and Antibody Technology Facility Aurora Training Course

How does the unmixing work? Cytometry and Antibody Technology Facility Aurora Training Course

How does the unmixing work? Mixing Matrix 0.19 0 0.21 0 0.32 0.001 0.2 0.03 0.12 0.39 0.06 0.28 0.03 0.12 0.01 0.08 0.005 0.03 0 0.01 0 0.005 0 0 0 0 0 0 0 0 0 0 Cytometry and Antibody Technology Facility Aurora Training Course

How does the unmixing work? Mixing Matrix (M) Abundances ( ! ) Observed ( " ) (Unknowns) 39.83 0.19 0 420.89 0.21 0 643.28 0.32 0.001 446.61 0.2 0.03 601.32 0.12 0.39 387.94 [Fluorophore 1 and 0.06 0.28 175.17 Fluorophore 2] 0.03 0.12 109.03 0.01 0.08 44.05 0.005 0.03 9.71 0 0.01 5.36 0 0.005 0.83 0 0 0 0 0 0 0 0 0 0 0 0 0 0 #$ = & Solve for $. Cytometry and Antibody Technology Facility Aurora Training Course

Reference Controls Cytometry and Antibody Technology Facility Aurora Training Course

Reference Controls • In order to get successful unmixing, you need to have excellent reference controls • Garbage in = garbage out!! Cytometry and Antibody Technology Facility Aurora Training Course

Good Controls = Good Data Optimal controls are needed for accurate unmixing/compensation: X (+) � Positive and negative particles clearly separated Fluor B � Negative and positive particles with IDENTICAL autofluorescence X (-) characteristics Fluor A � Sufficient events for both data points A positive signal from cells cannot be matched with a negative signal from beads. � Fluorescence spectrum of positive control needs to be IDENTICAL to the one in the multicolor sample A minimum of 200 events for the positive and negative populations is required. More is better. v The positive signal intensity of the control must be as bright or brighter 37 Slides from Cytek than the multicolor sample Cytometry and Antibody Technology Facility Aurora Training Course

Fluorescence spectrum of positive control needs to be IDENTICAL to the one in the multicolor sample • For any tandem dye, you must use the exact same antibody – even the same lot • For a non tandem dye, you could potentially use a different antibody with the same fluorophore • You can’t use “equivalent” fluorophores for your controls • FITC is not the same as GFP • BV510 is not the same as live/dead aqua dye • Special considerations for lineage/dump channels if using tandem dyes • Fix/perm buffers can alter the spectra of a fluorophore, so all controls must be treated with the same buffers as your sample Cytometry and Antibody Technology Facility Aurora Training Course

Reference Control Multicolor Sample Will it unmix correctly? PD-L1 PE-Dazzle 594 on cells PD-L1 PE-Dazzle 594 Yes PD-L1 PE-Dazzle 594 on PD-L1 PE-Dazzle 594 Yes compensation beads No BV421, BV480 and BV510 are CD4 BV750 FoxP3 BV750 the only non-tandem BV Fluorophores CD4 PE Tetramer PE Yes No RC is probably dimmer than CD69 APC on unstimulated cells CD69 APC on activated cells multicolor sample Cytometry and Antibody Technology Facility Aurora Training Course

Spectrum Plots Allow to QC Controls (1) Expected Spectrum Clean Background If you are using compensation beads, 38 Slides from Cytek please wash them after staining Cytometry and Antibody Technology Facility Aurora Training Course

Spectrum Plots Allow to QC Controls When gated in the peak of the Spectrum Plots Allow to QC Controls distribution, spectrum looks normal When gated in the peak of the distribution, spectrum looks normal When gated on the brightest portion of the distribution, spectrum looks like Super Bright 436 When gated on the brightest portion 39 Slides from Cytek of the distribution, spectrum looks like Cytometry and Antibody Technology Facility Aurora Training Course Super Bright 436 39

What can we see in the spectra? • If your antibodies are too old and degrading – Ex: Cy7 is falling off of APC • If you accidentally contaminated your reference control or antibody stock with another fluorophore • If you accidentally mislabeled your reference control and it is actually for a different fluorophore • Of if you have two different reference controls that are actually stained with the same fluorophore If any of these things happen, the spectral unmixing will be incorrect and your data will look odd! Cytometry and Antibody Technology Facility Aurora Training Course