Supplementary data Supplementary Table e-1. Flow cytometry ...

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Supplementary data Supplementary Table e-1. Flow cytometry reagents and staining combinations Reagents Antibody Fluorochrome conjugation Clone Source CD3 FITC UCHT1 BD Biosciences CD3 PerCP-Cy5.5 SK7 Biolegend CD3 BUV395 SK7 BD Biosciences CD3 APC-R700 UCHT1 BD Biosciences CD4 BV786 SK3 BD Biosciences CD4 BUV661 SK3 BD Biosciences CD8 AlexaFluor700 RPA-T8 BD Biosciences CD8 BV786 RPA-T8 BD Biosciences CD45RA FITC HI100 BD Biosciences CD45RO PE UCHL1 BD Biosciences CD45RO APC-H7 UCHL1 BD Biosciences CCR7 APC 3D12 BD Biosciences CD31 PE WM59 BD Biosciences CD25 BV421 2A3 BD Biosciences CD127 PC7 R34.34 Beckman Coulter FoxP3 PE-CF594 236A/E7 BD Biosciences IFNγ BV650 4S.B3 BD Biosciences GM-CSF PE BVD2-21C11 BD Biosciences IL-10 APC JES3-19F1 BD Biosciences IL-17 BV421 N49-653 BD Biosciences IL-4 PE-CF594 MP4-25D2 BD Biosciences IL-22 PerCP- eFluor710 22URTI eBioscience

Transcript of Supplementary data Supplementary Table e-1. Flow cytometry ...

Page 1: Supplementary data Supplementary Table e-1. Flow cytometry ...

Supplementary data Supplementary Table e-1. Flow cytometry reagents and staining combinations

Reagents

Antibody Fluorochrome

conjugation

Clone Source

CD3 FITC UCHT1 BD Biosciences

CD3 PerCP-Cy5.5 SK7 Biolegend

CD3 BUV395 SK7 BD Biosciences

CD3 APC-R700 UCHT1 BD Biosciences

CD4 BV786 SK3 BD Biosciences

CD4 BUV661 SK3 BD Biosciences

CD8 AlexaFluor700 RPA-T8 BD Biosciences

CD8 BV786 RPA-T8 BD Biosciences

CD45RA FITC HI100 BD Biosciences

CD45RO PE UCHL1 BD Biosciences

CD45RO APC-H7 UCHL1 BD Biosciences

CCR7 APC 3D12 BD Biosciences

CD31 PE WM59 BD Biosciences

CD25 BV421 2A3 BD Biosciences

CD127 PC7 R34.34 Beckman Coulter

FoxP3 PE-CF594 236A/E7 BD Biosciences

IFNγ BV650 4S.B3 BD Biosciences

GM-CSF PE BVD2-21C11 BD Biosciences

IL-10 APC JES3-19F1 BD Biosciences

IL-17 BV421 N49-653 BD Biosciences

IL-4 PE-CF594 MP4-25D2 BD Biosciences

IL-22 PerCP-

eFluor710

22URTI eBioscience

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Annexin V BUV395 N/A BD Biosciences

Propidium iodide N/A N/A BD Biosciences

Integrin β7 FITC FIB504 Biolegend

CCR9 PE-Cy7 L053E8 Biolegend

CCR5 BV421 J418F1 Biolegend

CCR2 PerCP-Cy5.5 K036C2 Biolegend

CLA PE HECA-452 BD Biosciences

CCR4 PE-CF594 1G1 BD Biosciences

BIM AF488 C34C5 Cell Signaling technology

PUMA PE EP512Y Abcam

BAX AF488 2D2 Biolegend

BAK PE D4E4 Cell Signaling technology

BCL-XL AF488 54H6 Cell Signaling technology

BCL-2 BV421 100 Biolegend

LIVE/DEAD Fixable

Aqua Dead Cell Stain

N/A N/A Invitrogen

Staining combinations

CD3-PerCP; CD4-BV786; CD8-AlexaFluor700; CD45RA-FITC; CCR7-APC;

Live/Dead

CD3-APC-R700; CD4-BV786; CD45RO-APC-H7; CD31-PE; CD25-BV421; CD127-

PC7; FoxP3-PE-CF594

CD3-FITC; CD4-BV786; CD8-AlexaFluor700; CD45RO-PE; CCR7-APC; CD25-

BV421; CD127-PC7; Annexin V-BUV395; Propidium iodide

CD3-BUV395; CD4-BV786; CD8-AlexaFluor700; IFNγ-BV650; GM-CSF-PE; IL-10-

APC; IL-17-BV421; IL-4-PE-CF594; IL-22-PerCP

CD3-BUV395; CD4-BUV661; CD8-BV786; Integrin β7-FITC; CCR9-PE-Cy7; CCR5-

BV421; CCR2-PerCP-Cy5.5; CLA-PE; CCR4-PE-CF594

CD3-BUV395; CD4-BUV661; CD8-BV786; BIM-AF4888; PUMA-PE

CD3-BUV395; CD4-BUV661; CD8-BV786; BCL-XL-AF488; BCL-2-BV421

CD3-BUV395; CD4-BUV661; CD8-BV786; BAX-AF488; BAK-PE

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Supplementary Figure e-1. T-cell subset staining and gating strategy

Supplementary Figure e-1. T-cell subset staining and gating strategy.

Representative example of T-cell subset staining by flow cytometry and gating

strategy used from a MS patient sample.

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Supplementary Figure e-2. Annexin V/propidium iodide staining

Supplementary Figure e-2. Annexin V/propidium iodide staining.

Representative example of Annexin/PI staining of CD8+ (top) and CD4+

(bottoom) T-cell subsets from a healthy control subject under each exposure.

UNTX = medium alone, VEH = vehicle (DMSO), DMF = dimethyl fumarate, MMF

= monomethyl fumarate, PI = propidium iodide.

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Supplementary Figure e-3. DMF treatment in vivo alters the regulatory to effector cell balance

Supplementary Figure e-3. DMF treatment in vivo alters the regulatory to

effector cell balance.

Greater losses in putatively pro-inflammatory effector T-cell populations versus

putatively regulatory T-cell subsets were seen with DMF treatment of MS

patients, leading to changes in regulatory to effector cell ratios. Increases were

seen in the ratios of regulatory T-cells (Treg) to Th1 (A), Tc1 (B) and GM-CSF-

expressing CD4+ T-cells (C), as well as in the ratios of IL-10-expressing CD4+ T-

cells to Th1 (D) and GM-CSF-expressing CD4+ T cells (E). Data shown is from

multiple sclerosis patients (n=13) pre-treatment (Month 0) and up to 12 months

following DMF treatment initiation. The p values displayed represent the

statistical significance of the exponential decay trajectory (shown in red) in a

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random coefficient mixed effects model. Individual patient trajectories are shown

in grey.

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Supplementary Figure e-4. Susceptibility of circulating T-cells to dexamethasone-induced apoptosis pre- and post-DMF treatment

Supplementary Figure e-4. Susceptibility of circulating T-cells to

dexamethasone-induced apoptosis pre- and post-DMF treatment.

Annexin V/PI staining to capture T-cell apoptosis following exposure to different

concentrations of dexamethasone. Representative example of dose-dependent

increase in dexamethasone-induced T-cell apoptosis (top row) compared to

vehicle control (bottom row) using purified T-cells from a DMF-treated patient and

gating on all CD3+ T-cells (A). Summary graphs showing frequencies of Annexin

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V+/PI+ apoptotic cells (corrected for degree of apoptosis with vehicle control: Δ%

An+/PI+ = % An+/PI+ with dexamethasone minus % An+PI+ with corresponding

vehicle concentration) do not change significantly pre- versus on-treatment (n=3

patients; highest 3 concentrations of dexamethasone shown) (B). An = Annexin

V, PI = propidium iodide, PRE = pre-treatment, ON = on-treatment.

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Supplementary Table e-2. T-cell expression of pro- and anti-apoptotic molecules pre- and post-DMF treatment

Molecules ΔMFI Pre-treatment

(95% CI)

ΔMFI Post-treatment

(95% CI)

p value (pre- vs. post-

treatment)

Pro-apoptotic

BIM 191 (148-234) 188 (130-247) ns

PUMA 2227 (501-3954) 2326 (1016-3635) ns

BAX 152 (-54-357) 168 (-14-351) ns

BAK 138 (115-161) 154 (121-187) ns

Anti-apoptotic

BCL-XL 311 (245-377) 315 (200-429) ns

BCL-2 2204 (704-3704) 2588 (971-4205) 0.0425

Supplementary Table e-2. T-cell expression of pro- and anti-apoptotic

molecules pre- and post-DMF treatment.

CD3+ T-cell expression of pro- and anti-apoptotic molecules pre- and post-in vivo

treatment with DMF. Results are shown as mean ΔMFI (MFI of molecule minus

MFI of isotype control) and 95% confidence intervals (n=3 matched pre-/post-

treatment samples; p values compare pre- and post-treatment mean MFIs using

paired t-tests). ns = not significant, MFI = mean fluorescence intensity.

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Supplementary Figure e-5. Relative changes in tissue-homing T-cell populations with DMF treatment

Supplementary Figure e-5. Relative changes in tissue-homing T-cell

populations with DMF treatment.

Representative example of staining for gut (CCR9+beta7integrin+), skin

(CLA+CCR4+) and brain (CCR2+CCR5+) homing T-cell populations, gating on

CD4+ cells (A). Summary graphs showing the change in relative frequency

between matched pre- and 3 month post-treatment samples of each tissue

homing population amongst CD4+ (B) and CD8+ (C) T-cells (n=3 patients; p

values shown represent adjusted p values from repeated measures one-way

ANOVA with Tukey’s post test). DMF = dimethyl fumarate, ns = not significant.