astana – september 21th, 2018flm.kz/files/15083426245bfe116456723.pdf · flow cytometry facs...
TRANSCRIPT
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Astana – September 21th, 2018Kazakhstan
Flow Cytometry Workshop
Customized cellular products
Matthias Schiemann
Technische Universität München, Germany
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Flow Cytometry units of the Technischen UniversitätMünchen (CyTUM)
Steering Committee
Chair: M. Schiemann
Members: D. Busch, D. Zehn, C. Traidl-Hoffmann
Lehrstuhl für Tierphysiologie und Immunologie
Wissenschaftszentrum Weihenstephan für Ernährung, Landnutzung und Umwelt
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Flow Cytometry FACS Unit`s – located at MIH, LTI and UNIKA-T
à First University overarching facility in Germany
680 user• 300 (Analysis)• 380 (Cell Sorting)
Instruments:
• 28 Analyzer• 7 Cell Sorter
• 10 employees
CyTUM
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Instrumentation of the CyTUM MIH
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>200 different cell typesAdherence
Density
Microfluidics
Antibody
Plasma
PBMCs
Erythrocytesc tes
cs
Adherence
Density
Plasma
PBMCs
Erythrocytesc tes
Microfluidicscs
Antibody
Cell separation – an overview
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MACS FACS
LaserPOI
Droplet generation
Deflection
Nozzle
Sca ttered light
Fluorescence
Waste
Antibody based cell separation methods
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Introduction FACS
LaserPOI
Droplet generation
Deflection
Nozzle
Sca ttered light
Fluorescence
Waste
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Scientific Question and considerations
- Sample processing- Cell isolation/preparation- Staining/biological
durability/activation- Temperature
- Sorting parameters- Pressure- Shearing
effects/Acceleration- Decompression/expansion- Laser light- Electrostatic charge- Impact- Energy Dissipation Rate
Varma, S. et al., Analytical chemistry (2017)Richardson, G. M. et al., Cytometry A (2015)Mollet, M. et al., Biotechnology and Bioengineering (2007)
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A closer look at some FACS forces
Ge, J. et al., Cytometry A (2013)Catt, S. L. et al., Molecular human reproduction (1997)
Olesen, S. P. et al., Nature (1988)Seidl, J. et al., Cytometry (1999).
Eisinger, J. et al., Biophysical chemistry (1987)
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Characterization of cell alterations caused by FACS
In versatile applications FACS is unrivaled to otherpurification methods, thus limited to applications forresearch use only.
In the work of our group we evaluate assays to determinecell fitness, in order to validate current research data.These results might also be useful for other clinical cellprocessing's.
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Method – “optimized” cell sorter
We built a modified MoFlo XDPTM cell sorter, for controlling temperature sort
conditions of the whole system, enabling us to evaluate the influence of
temperature. In this approach we used different technologies to evaluate every
single parameter during sorting, like in an equation, with only one variable.
37�C4�C
LLO91-99–specific T cell lineH2-Kd/LLO91-99/mb2m SA-Alexa54645 min staining
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FACS Optimizing - Temperature
0
5
10
15
20
25
30 60 90 120 150 180 210 240 270 300 330 360
time [min]
tem
pera
ture
[°C]
roomtemperature
conventionellice cooling
coolingoption
Ice cooling
Centralized cooling solution for all conventionalinstruments
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Temperature control on the MoFlo XDPTM fluidic system
Sorting with temperature control:Stable from 7�C up to 30�C
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Cell death after temperature storage by propidium iodide (PI) staining
Flow cytometric analysis of cell death after temperature storage by propidium iodide (PI) staining. Graphs show percentages of living cells in a time course for human PBMCs, murine splenocytes and K562 cells.
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Phosphorylation of the MAPK p38 signaling pathway
Immunoblot (top left graph) for phosphorylated p38 in ficoled PBMCs from BuffyCoatDonors, with exclusion of Buffer related phosphorylation effects (lower graph). p38 signal strength was determined via ImageJ Software shown as a bar chart (top right graph).
phospho-p38
endogenous-p38
PB
MC
´s u
nsor
ted
PB
MC
´s im
med
iate
afte
r sor
t
0.18 0.54 0.59 0.58 0.45 0.25
PBMC´s incubated after sort time in min
0 5 15 30
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Functional Analysis of sorted cells
Two graphs (both left) show the proliferation based thymidine uptake of sorted CD8 positive cells in a mixed lymphocyte reaction (MLR).
Lower graph displays the survival of sorted CD8 cells from whole blood in a time course over two days.
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mRNA levels via MicroArray
sorted – 0h
unsorted - 0h
unsorted
4h
resting
unsorted - 0h
sorted – 4h
over time
sorted – 4hsorted – 4h
unsorted - 4h
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Conclusion and Discussion
- We were able to observe sorting induced cell alterations in different cell lines, as well as altered cell physiology.
- Primary cells, specially PBMCs and T-cells seemed very robust und unaffected by the use of FACS.
- The parameters evaluated in this project could also be applied to other clinical cell processing methods.
- mRNA levels via MicroArray
- no activation – more down regulation
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General problem: remaining sort-marker
• changes of the cell populationcross linking, activation, cell death, receptor blockade
• clinical issuestoxicity, immunogenicity, allergic reactions
• regulatory/economical aspectsdifficult process for reagent approval
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MHC Multimers
MHC dimers
(Schneck)
1 10 100 1000 10000FL2-H: SIIN-dimer 1:20
1
10
100
1000
10000
FL1-
H: C
D8a
20.5 0.47
21.4 57.6
H2-Kb/SIINFEKL dimer
CD
8a
MHC monomer MHC tetramers
(Altman/Davis)
1 10 100 1000 10000FL2-H: SIIN-tet 1:20
1
10
100
1000
10000
FL1-
H: C
D8a
20.7 0.85
1.13 77.3
H2-Kb/SIINFEKL tetramerC
D8a
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LLO91-99-specific T cells
MHC Multimers - adoptive Transfer
bact
eria
per s
plee
n
2 x 107 + Multimerno T cells
2 x 107 + T cell line
104
N = 12
105
106
107
T cells
day -1 0 3
Listeria i.v. CFUBacteria spleen / liver
infection after 1 dayBalb/c
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2 x 107 + MHC Tetramers
no T cells
2 x 107 + T cell line
LLO91-99-specific T cells
104
MHC Multimers - adoptive Transfer
N = 12
bact
eria
per
spl
een
105
106
107
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Reversible MHC Multimers - Streptamers
d-Biotin/Streptactin
KD 10-12 M
d-Biotin
StreptagIII/Streptactin
KD 10-6 M
1 10 100 1000 10000FL2-H: MHC-pily aHSV staining no bio 0
0
20
40
60
80
100
% o
f Max
w/o d-biotincontrol
0
20
40
60
80
100
% o
f Max
+d-biotin
LLO91-99/Kd - Streptamertime 0 min30
% o
f Max
epitope tag staining
Knabel, Franz, Schiemann et al.
Nature Medicine 2002
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PE
Alexa 488
*
*
*
*
MHC Streptamers
time[sec]0 200 400 600 800 1000 1200
fluor
esce
nce
inte
nsity
0
10000
20000
30000
40000
50000
60000
koff = -0,0038; t1/2 = 182,41 sec
Regression : y = a * e –koff * t
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2 x 107 + MHC Tetramers
no T cells
2 x 107 + T cell line
2 x 107 + MHC Streptamers + d-Biotin
MHC Streptamers and effective adoptive Immunotherapy
** p < 0.001 N = 12
104
Bact
eria
per
spl
een
105
106
107
LLO91-99-specific T cells
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CD3
MH
C M
ult
imer
100 101 102 103 104100
101
102
103
104
10
6.22
2.18 81.6
positive fraction
magnetic beads / reversible Multimers
10000
100000
1000000
1x107 1 x 1051x105
PBS
10 mice/group
T cell line ex vivo
prim
ary
T ce
lls
viab
le L
iste
ria
/ sp
leen
Directly ex vivo sorted T cells
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• remaining marker (MHC multimers) can alter stained cells
• fully reversible staining with MHC Streptamers
• low numbers of primary T cells for effective adoptive transfer
• identification of highly effective memory subsets for adoptive transfer
Preclinical research summary
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• hematopoetic / mesenchymal stem cells
• T cells (antigen-specific T cells, regulatory T cells)
• endothelia, chondrocytes, NK cells …....
Increasing targets and applications
Cell therapy
donor recipient
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T cell therapy
donor recipient
4-5 weeks
CD8
B8/IE
1 m
ultim
er
1-2 days
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Clinical cell sorting
before sort positive fraction
A2/pp65 -Streptamer-Beads
CliniMACS, MiltenyiCD8
MH
C m
ult
imer
(H
LA-A
2/pp
6549
5-50
3)
100 101 102 103 104100
101
102
103
104
100 101 102 103 104100
101
102
103
104
93.8 %0.45 %
magnetic particle
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• MHC Multimer-purification: pp65495-503-specific T cells
• adoptive transfer of 100.000 specific cells
• 14 years, ALL, CMV positive
• stem cell transplantation (father)
• after 2 weeks, CMV reactivation, Ganciclovir resistant Þ Foscarnet
Example: Patient (Utrecht)
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Immune-Monitoring upon T cell transfer
0.65%
8. weeks after transfer
1.09%
5. week
0.38%
3. week
0.08%
1. weekCM
V pp
65 T
etra
mer
APC
CD8 Pacific Blue
before
0.0 %
0.78%
4. week
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T cells, virus load
-10 0 10 20 30 40 50 60 70
0.20
0.40
0.60
0.80
1.00
1.20
1.40
virus load
0.0
0.3
0.5
0.8
1.0
1.3
1.5
CD3+CD8+ Multimer+ T cells
days after adoptive transfer
viru
s lo
ad [#
cop
ies
x 10
.000
] Multim
er+ CD3+ lymphocytes [%
]
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Identification ofdonor derivedT cells by CDR3specific primers
Bulk sorting of at least5/105 Donor T cell for PCRscreening with V-betaspecific primers
DonorPatient
CD
R-1
CD
R-2
CD
R-3
CD
R-1
CD
R-2
CD
R-3
Donor
Single cell sort on 48 spot slides for CDR3-T cell Tracking in CMV patients
Donor Recipient
Sorting of 1 antigen specific donor T cells per PCR sample
Sorting of 1 antigen specific patient T cells per PCR sample
Patient
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Patient (SCID, Tunesia)
• Streptamer-purification: pp65495-503 specific T cells
• adoptive transfer of 30.000 specific cells
• 8 Mo, severe combined immunodeficiency
• stem cell transplantation (father)
• CMV in urine, blood, ascites, trachea, liquor, skin biopsy
• Ganciclovir resistant
A. Borkhardt (Düsseldorf)
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CD8 APC-A750
MHC
Mul
timer
PE
7.94
3 weeks after AT
31
4 weeks after AT
0.54
7 weeks after AT
3.89
6 weeks after AT
18.6
5 weeks after AT
0
1 week after AT
0
before AT
0.21
8 weeks after AT
Immunmonitoring upon T cell transfer
Sequence (Patient) V�13N …TGTGCCAGCTTTTTTGGGGGTGGGGATCAAC…
Sequence (Donor) V�13N …TGTGCCAGCTTTTTTGGGGGTGGGGATCAAC…TCRVb13.6 BD2.1 BJ1.2
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TUMCells
Core Team: Martin Hildebrandt
Alex SlobodianskiMichael Neuenhahn Nicole Frisch
Julia Albrecht Tanja Rossmann-Bloeck
Products - designed for the production of:
§ Blood cell products
§ Investigational drugs§ Advanced Therapy Medicinal Products (ATMPs), which include:
§ Somatic cell therapy; Gene transfer drugs; Tissue-engineered products (combination products).
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Clinical cell processing
Interaction of TCR – MHC Streptamers è only T cells are accessible
• is this principle transferable to other surface molecules / cells ?
è virtually any cell can be addressed (access to cell therapy)
è multiple marker stainings
� recombinant Fab-streptag monomers
� if necessary, affinity modification
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unstained8x washing2x washing
CD30 Fab multimer
% o
f Max
Stable binding of aCD30 multimers even after excessive washing
Fab Streptamers
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Fully reversible staining with Fab-Streptamers
FL1 - FITC
CD
3 Fa
b-m
ultim
er /
Fab-
mon
omer
64.5
Fab-multimer
0.005
Fab-multimerê
D-biotin
0.018
Fab-multimerê
D-biotin
ê
ST-PE
62.8
Fab-multimerê
D-biotin
ê
Fab-multimer
64.1
FL1 - FITCC
D3
mAb
mAb
Stemberger, Dreher, Tschulik, Schiemann et al.
PloS One 2012
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Multiplex Streptamer staning and sorting
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Method – “untouched” cells
www.iba-lifesciences.com
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Fully reversible staining with Fab-Streptamere
www.iba-lifesciences.com
www.fabian-online.com
Cell selection and expansion:
• FABian® for automated cell selection - with reversible reagents
• PBMCs, T and B cell isolation directly from whole blood withoutmagnetic beads and density gradient centrifugation.
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• MHC Streptamers
• Tool for basic research and clinical applications
• Fab Streptamers – transfer of Streptamers to virtually any cell surface
marker
• Reversibility as a standard for clinical cell purification
Summary
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From bench to beside - collaboration groups
Schiemann Lab Immunmonitoring
Immanuel Andrä Michael Neuenhahn
Susi Dürr
Lynette Henkel
Busch Lab
Veit Buchholz
Anna HochholzerLothar Germeroth Herbert Stadler
Christian Stemberger
Interdisziplinäres Zentrum für Zelltherapie am Klinikum der Universität München (IZZTKUM)
Martin Hildebrand
Dirk Busch