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This document presents supplemental information related to a study on the single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination. It includes detailed subject and vaccine information, EpiTOF panel and gating details, and analyses of vaccine-induced epigenomic changes through various sequencing methods. The document also outlines the immune response to different vaccines using single-cell ATAC-seq and RNA-seq data.

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0% found this document useful (0 votes)
12 views10 pages

MMC 1

This document presents supplemental information related to a study on the single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination. It includes detailed subject and vaccine information, EpiTOF panel and gating details, and analyses of vaccine-induced epigenomic changes through various sequencing methods. The document also outlines the immune response to different vaccines using single-cell ATAC-seq and RNA-seq data.

Uploaded by

terence0404
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
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Cell, Volume 184

Supplemental information

The single-cell epigenomic and transcriptional


landscape of immunity to influenza vaccination
Florian Wimmers, Michele Donato, Alex Kuo, Tal Ashuach, Shakti Gupta, Chunfeng
Li, Mai Dvorak, Mariko Hinton Foecke, Sarah E. Chang, Thomas Hagan, Sanne E. De
Jong, Holden T. Maecker, Robbert van der Most, Peggie Cheung, Mario Cortese, Steven
E. Bosinger, Mark Davis, Nadine Rouphael, Shankar Subramaniam, Nir Yosef, Paul J.
Utz, Purvesh Khatri, and Bali Pulendran
Table of Contents
DataS1 Subject and vaccine information, related to STAR Methods page 3
DataS2 EpiTOF panel and gating, related to STAR Methods page 4
DataS3 Vaccine-induced epigenomic changes by bulk ATAC-seq and RNA-seq, related to page 6
Figure 3
DataS4 ScATAC-seq and scRNA-seq analysis of immune response to TIV, related to Figure 4 page 7
DataS5 ScATAC-seq and scRNA-seq analysis of immune response to H5N1/H5N1+AS03, page 9
related to Figure 5

2
DataS1 – Subject and vaccine information, related to STAR
Methods

Subject information

TIV
Treatment Participants Median Age Gender (%) Race (%)
(no.) (range)
Antibiotics 10 29 Male (70%) White (50%)
(24 - 38) Female (30%) Black or African American (30%)
Other (20%)
Control 11 27 Male (64%) White (63%)
(24-35) Female (36%) Black or African American (27%)
Other (10%)

H5N1/H5N1+AS03
Vaccine Participants Median Age Gender (%) Race (%)
(no.) (range)
H5N1 16 26 Male (44%) White (44%)
(22-40) Female (56%) Black (25%)
Asian (19%)
Other (12%)
H5N1+AS03 34 28 Male (38%) White (77%)
(21-44) Female (62%) Black (18%)
Asian (3%)
Other (2%)

Vaccine information

TIV
Vaccine Vaccine H1N1 strain H3N2 strain B strain
Brand/Season
TIV Fluzone A/California/07/2009 A/Texas/50/2012 B/Masschusetts/02/2012
2014-2015

3
DataS2 – EpiTOF panel and gating, related to STAR Methods
EpiTOF antibody panel
Panel 1 Panel 2

Metal Marker Manufacturer Type Clone Metal Marker Manufacturer Type Clone

Mouse Mouse
89Y CD45 Fluidigm HI30 89Y CD45 Fluidigm HI30
IgG1 IgG1
141Pr H3 CST Rabbit mAb D1H2 141Pr H3 CST Rabbit mAb D1H2
Mouse
142Nd γ-H2AX CST Rabbit mAb 20E3 142Nd Arg-me1 Abcam 5D1
IgG1
Arg-me2
143Nd H2BK5ac CST Rabbit mAb D5H1S 143Nd CST Rabbit mAb 13222
(sym)
Mouse Mouse
144Nd H3S10ph Active Motif MABI 0312 144Nd H3K4me2 Active Motif MABI 0303
IgG1 IgG1
Mouse Mouse
145Nd CD4 BioLegend RPA-T4 145Nd CD4 BioLegend RPA-T4
IgG1 IgG1
Mouse Mouse
146Nd CD8 BioLegend SK1 146Nd CD8 BioLegend SK1
IgG1 IgG1
Mouse Mouse
147Sm H4K5ac Active Motif MABI 0405 147Sm H3K9me2 Biolegend 5E5-G5
IgG1 IgG1
Mouse Mouse
148Nd CD34 BD 8G12 148Nd CD34 BD 8G12
IgG1 IgG1
Cleaved H3 Mouse
149Sm CST Rabbit mAb D7J2K 149Sm H3K9me1 Biolegend 7E7.H12
(Thr22) IgG1
Mouse
150Nd H3.3S31ph Active Motif 1A8G10 150Nd H3K36me3 RevMab Rabbit mAb RM155
IgG2b
Mouse
151Eu H3K23ac RevMab Rabbit mAb RM169 151Eu H3K27me1 Active Motif MABI 0321
IgG2a
Mouse Arg-me2
152Sm H3K9ac Active Motif 2G1F9 152Sm CST Rabbit mAb 13522
IgG2a (asy)
Mouse
153Eu H2BS14ph CST Rabbit mAb D67H2 153Eu H3K36me2 Active Motif MABI 0332
IgG1
Mouse
154Sm H2AK119ub CST Rabbit mAb D27C4 154Sm H3K27me3 Active Motif MABI 0323
IgG1
Mouse Mouse Bu15
155Gd CD11c BioLegend Bu15 155Gd CD11c BioLegend
IgG1 IgG1
Mouse
156Gd H3K18ac RevMAb Rabbit mAb RM166 156Gd H4K20me2 Active Motif MABI 0422
IgG1
Mouse
158Gd H3K56ac Active Motif 12.1 158Gd H3.3 Abcam Rabbit mAb EPR17899
IgG1
Mouse Biolegend Mouse
159Tb CD197 Biolegend G043H7 159Tb CD197 G043H7
IgG2a IgG2a
Mouse
160Gd PADI4 OriGene IgG2a OTI4H5 160Gd H4K20me3 BioLegend 6F8-D9
IgG1
Mouse
161Dy H2BK120ub CST Rabbit mAb D11 161Dy Macro-H2A Millipore 14G7
IgG2b
162Dy Crotonyl-Lys PTM Biolabs Mouse IgG 4D5 162Dy H3K4me3 Life Rabbit IgG G.532.8

163Dy H3R2cit Abcam Rabbit mAb EPR17703 163Dy H2A.Z Abcam Rabbit mAb [EPR6171(2)(B)]

164Dy H3K14ac CST Rabbit mAb D4B9 164Dy H3K36me1 Abcam Rabbit mAb EPR16993
Mouse Mouse
165Ho FOXP3 BD 259D/C7 165Ho FOXP3 BD 259D/C7
IgG1 IgG1
Mouse BD Mouse
166Er CD123 BD 9F5 166Er CD123 9F5
IgG1 IgG1
Mouse Mouse
167Er CD45RO BioLegend UCHL1 167Er CD45RO BioLegend UCHL1
IgG2a IgG2a
168Er H4K16ac CST Rabbit mAb E2B8W 168Er H4K20me1 Active Motif Mouse IgG 5E10-D8
Mouse Mouse
169Tm CD25 Fluidigm 2A3 169Tm CD25 Fluidigm 2A3
IgG1 IgG1
Mouse Mouse UCHT1
170Er CD3 BioLegend UCHT1 170Er CD3 BioLegend
IgG1 IgG1
Mouse Mouse
171Yb CD14 Biolegend M5E2 171Yb CD14 Biolegend M5E2
IgG2a IgG2a
Mouse Mouse
172Yb CD56 BD NCAM16.2 172Yb CD56 BD NCAM16.2
IgG2b IgG2b
Mouse Mouse
173Yb H4 Abcam ab31830 173Yb H4 Abcam ab31830
IgG1 IgG1
Mouse Mouse
174Yb H3K27ac Active Motif MABI 0309 174Yb CENP-A MBL 3-19
IgG1 IgG1
Mouse Mouse
175Lu CD19 BioLegend HIB19 175Lu CD19 BioLegend HIB19
IgG1 IgG1
Mouse Mouse
176Yb HLA-DR BioLegend L243 176Yb HLA-DR BioLegend L243
IgG2a IgG2a
209Bi CD16 Fluidigm Mouse IgG 3G8 209Bi CD16 Fluidigm Mouse IgG 3G8

4
DataS2 – EpiTOF panel and gating, related to STAR Methods
(Continued)
EpiTOF gating scheme

5
DataS3 - Vaccine-induced epigenomic changes by bulk ATAC-seq
and RNA-seq, related to Figure 3
(A) Boxplot showing the fraction of reads in peaks (FRIP) for each sample.

(B) Boxplot showing the number of tags used for peak calling for each sample.

(C) Boxplots showing the number of identified peaks for each samples. Samples in grey were excluded
from analysis based on FRIP threshold shown in the left panel.

(D) Fragment size distribution plots and TSS enrichment plots from a representative ATAC-seq sample.

6
DataS4 - ScATAC-seq and scRNA-seq analysis of immune
response to TIV, related to Figure 4
(A) UMAP representation of single immune cells using scATAC-seq after pre-processing. Color indicates
clusters with manually annotated cell type identity.

(B) Boxplot showing the number of unique fragments per cell in each cluster.

(C) Heatmap showing chromVAR TF accessibility values per cluster for the top 60 most variable TFs.
Accessibility was normalized by row.

(D) Shown is the cell fraction by cluster for each vaccine time point (left) and subject (right) using scATAC-
seq data.

(E) UMAP representation of single immune cells using scRNA-seq after pre-processing. Color indicates
clusters with manually annotated cell type identity.

(F) Per-cell QC metrics. After preprocessing, qc metrics were calculated for each cell in each cluster. Shown
are the RNA counts (top), unique genes (middle), and mitochondrial RNA fraction (bottom) per cell.

(G) Top7 distinctive genes per cluster. After QC filtering, we calculated the differentially expressed genes
(DEGs) in each cluster compared to all other cells. Heatmap shows the expression levels of the top 7 DEGs
in up to 500 randomly sampled cells from each cluster.

(H) Shown is the cell fraction by cluster for each vaccine time point (left) and subject (right) using scRNA-
seq data.

7
DataS4 - ScATAC-seq and scRNA-seq analysis of immune
response to TIV, related to Figure 4 (Continued)
A B C
10 cluster
MA0102.3_CEB A
MA0833.1_ATF4

MA0099.2_FOS::JUN
MA0478.1_FOSL2
MA0477.1_FOSL1
MA0841.1_NFE2
MA0491.1_JUND
MA0490.1_JUNB
MA0476.1_FOS
MA0462.1_BATF::JUN
Umap2

0 MA0743.1_SCRT1
MA0684.1_RUNX3
RUNX2
MA0748.1_YY2
MA0763.1_ETV3

MA0028.2_ELK1
MA0764.1_ETV4
MA0761.1_ETV1
MA0098.3_ETS1
MA0667.1_MYF6
MA0091.1_TAL1::TCF3

0 MA0830.1_TCF4

Umap1 MA0048.2_NHLH1
OX2

MA0691.1_TF
OX1
MA0766.1_GAT
MA0140.2_GATA1::TAL1

Cell Type MA0037.2_GATA3


MA0036.2_GATA2

9
1
4
10
3

8
6
2
7
11
D E 0 1 2

d0
time d1 donor 10
d30

11 11
10 10

Umap2
9 9
8 8 0
7 7
6 6

4 4
3 3
2 2
0
1 1
Umap1
0.00 1.00 0.00 1.00
rac by vaccine condition rac by subject ran_2
Cell Type

ran_1

F G
6 11 12 18

cluster
TCF4

UGCG
MALAT1

SELL

CD74
2
A1

CST3
1
SNX3

0
CLEC9A

WDFY4
CDK6
AC084033.3

LDHB
FCER1A
CLEC10A
RACK1
EEF1A1
EEF1B2

FAU

NACA

TCF7L2

H MS4A7
RHOC
LST1
FCGR3A
CDKN1C
d0
time d1 donor B2M

d30 TMSB4X

1 ACTB
TMSB10

1 2 COTL1
2 3
3 4 FTH1
FTL

4
6
6 7
7 8 CYBB
8 9 FGL2

9 10 SLC2A3
10 11
11 12
CSF3R
A
12 13
13
VCAN

14
MNDA

14 CD14
S100A8
S100A9

16 16 S100A12

17
A
17 L

18 18 FCN1
S100A6

19 19 CTSS
FOS
20 20 SRGN
NCF1
CD36

0.00 1.00 0.00 1.00 MS4A6A

ALDH2

rac by vaccine condition rac by vaccine condition G0S2

8
Data S5 - ScATAC-seq and scRNA-seq analysis of immune
response to H5N1/H5N1+AS03, related to Figure 5
(A) UMAP representation of single immune cells using scATAC-seq after pre-processing. Color indicates
clusters with manually annotated cell type identity.

(B) Boxplot showing the number of unique fragments per cell in each sample before downsampling (top) and
after downsampling (middle), as well as per cluster after downsampling (bottom).

(C) Heatmap showing chromVAR TF accessibility values per cluster for the top 60 most variable TFs.
Accessibility was normalized by row.

(D) Shown is the cell fraction by cluster for each vaccine condition (left) and subject (right) using scATAC-
seq data.

(E) UMAP representation of single immune cells using scRNA-seq after pre-processing. Color indicates
clusters with manually annotated cell type identity.

(F) Per-cell QC metrics. After preprocessing, qc metrics were calculated for each cell in each cluster. Shown
are the RNA counts (top), unique genes (middle), and mitochondrial RNA fraction (bottom) per cell.

(G) Top7 distinctive genes per cluster. After QC filtering, we calculated the differentially expressed genes
(DEGs) in each cluster compared to all other cells. Heatmap shows the expression levels of the top 7 DEGs
in up to 500 randomly sampled cells from each cluster.

(H) Shown is the cell fraction by cluster for each vaccine condition (left) and subject (right) using scRNA-seq
data.

9
Data S5 - ScATAC-seq and scRNA-seq analysis of immune
response to H5N1/H5N1+AS03, related to Figure 5
A B C
8
cluster

6 ATF4

PA
ATF::JUN
4

OX2
FAP4

Umap1 T
R
R
RUNX3
RUNX2
ATA3
ATA2
ATA5

Cell Type AT T

8
5
7
9
4
6
3
2
D E 0 2

v v
condition donor v v

2 5

Umap2
2
3
3
4
4 0
5 5
6 6
7 7
8 8
9 9
0

Cell frac by vaccine condition Cell frac b


Cell Type ran

ran

F G 2 3
5
4 6 7 8 9
cluster
IRF8
APP
TCF4
CCDC50
PLD4
ITM2C
SYNE2
JCHAIN

IFITM2
MS4A7

RHOC

SON

2
RBM39
DDX5
SRRM2

P
H3F3B
NACA

UBA52
FAU
0
A
SERF2
TMSB4X
ACTB
B2M

TYROBP
FTL

H TYMP
TXNIP
SMAP2
KLF2
PSAP
v v CTSS

condition donor v v
CYBB
NEA
PTPRC
NAMPT
ZEB2
CD93
CSF3R

2
2 3 VCAN
APLP2
3 4 METTL9
A

4 5
5 6 TSPO

6
LYZ

7 NFKBIA
7 8
ZFP36
FOS

8 9 KLF4
9 FOSB
JUN
KLF6
A
TNFAIP3

CST3
CD74
WDFY4
CPNE3
SNX3
CLNK

MALA
LUC7L3
HNRNP
LDHB
PNN

Cell frac by vaccine condition Cell frac by PNISR


SOX4
CDK6
MSI2

10

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