Supplementary material Gut
Supplementary Materials
Materials and Methods
Cell isolation and purification
Blood was collected in Ethylenediaminetetraacetic acid (EDTA) tubes and peripheral
blood mononuclear cells (PBMCs) were isolated by Ficoll density gradient centrifugation
using Ficoll-Paque PLUS (GE Healthcare Life Sciences, UK). CD14+ monocytes and NK
cells were purified from PBMCs by magnetic cell sorting using the CD14+ positive selection
kit and the NK cell negative selection kit, respectively, according to the manufacturer’s
instructions (Miltenyi Biotec, Bergisch-Gladbach, Germany). CD14+ monocyte purity was
>95% and NK cell purity >90%, assessed by flow cytometry.
CD3 and KLRG1+ cells were depleted from PBMCs using the CD3 MicroBead kit
(Miltenyi Biotec) and indirectly with KLRG1-biotin and anti-biotin Microbeads (Miltenyi
Biotec). CD3 and KLRG1+ cell depletion was >90%, as measured by flow cytometry.
Cell separation of PBMCs into KLRG1+ and KLRG1- CD56dim NK cells was
performed using fluorescence-activated cell sorting (FACS). PBMCs were stained with
PECy7 conjugated anti-CD56 (clone NCAM16.2, BD Biosciences), anti-CD3-AlexaFluor700
(clone UCHT1, Biolegend), BV421-conjugated anti-KLRG1 (clone 2F1, Biolegend), and
stained with live/dead Zombie Aqua dye (Biolegend). KLRG1+ and KLRG1- CD56dim NK
cells were sorted to a purity of ≥98% with the BD FACSAria III cell sorter (BD Biosciences).
ELISA
Supernatants from co-culture of purified NK cells with autologous HBsAg-pulsed
moDCs were harvested, spun free of cells, and frozen at -80°C for extracellular Granzyme B
and interleukin-2 (IL-2) measurements by sandwich ELISA kit (Abcam) according to the
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manufacturer’s instructions. HCMV IgG plasma titres was measured by using HCMV IgG
ELISA kit (K4150, BioVision) according to the manufacturer’s instruction.
Proliferation assays
NK cells (2 x 105 cells/mL) were labelled with carboxyfluorescein succinimidyl ester
(CFSE) (5 µM, Cayman) and incubated at room temperature for 10 minutes. Cells were
washed in complete medium and cultured in the presence or absence of HBsAg-pulsed
moDCs, HBsAg-pulsed moDCs+IL-15 (10ng/mL), HBsAg-pulsed moDCs+IL-7 (10ng/mL)
for 14 days using an NK/DCs ratio of 5:1. IL-15 (1 ng/mL) was added to support NK cell
survival, with 50% of the medium being replenished every 3 days. After culture for 14 days,
the fluorescence of CFSE-labelled CD3-CD56+ NK cells were analysed by flow cytometry.
NK cells were phenotyped using: PECy7 conjugated anti-CD56 (clone NCAM16.2, BD
Biosciences), BUV395-conjugated anti-CD16 (clone 3G8, BD Biosciences), BV421-
conjugated anti-KLRG1 (clone 2F1, Biolegend), and stained with fixable viability stain 700
(BD Biosciences). Anti-CD3-PE (clone UCHT1, Biolegend) was added to exclude T cells.
T-distributed stochastic nearest neighbour embedding (t-SNE)
For high-dimensional analysis of flow cytometry data, we used the Barnes-Hut
implementation of t-distributed stochastic nearest neighbour embedding (t-SNE), a non-linear
dimensionality reduction approach [55]. Cells that share similarity will be located closely
together in the 2D scatter plot of the t-SNE map. For t-SNE analysis, raw flow cytometry data
were imported and compensated in FlowJo. NK cells were defined as CD3-CD56+ after the
following gating strategy; a time and single cells gating to remove the aberrant event and
doublets, respectively; lymphocytes were gated on forward scatter versus side scatter; live
cells were identified by excluding Zombie Aqua positive dye cells. Then, NK cell
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populations were down-sampled to an equal number of cells per sample using the
‘DownSample’ plugin in FlowJo. These samples were concatenated into a single fcs file and
analysed using the ‘t-Sne’ plugin. The following parameters are used to generate the t-SNE
map; CD107a, CD56, CD57, CD69, KLRG1, under the following t-SNE settings; iteration
1000, perplexity 30, Eta 200, Theta 0.5. To create the coloured t-SNE plots, the samples were
exported from FlowJo as CSV-Channel values therefore the bi-exponential expression can be
reflected on a linear axis and linear colour gradient. The t-SNE plots were performed using R
as previously described [56]. R and the packages of ggplot2, colourRamps, ggthemes, and
scales were used to colour individual cells in the t-SNE plots by the expression intensity of
various markers.
RNA Sequencing Analysis
SeqGeq version 1.1 (Tree Star, Ashland, OR) [57] was used to analyse the data that
consist of flow cytometry parameters from cell sorting and the single RNA expression matrix
simultaneously. R software was used to merge these data before importing data to SeqGeq.
The quality control step was applied in order to remove dead cells, debris, and dimly
expressed genes, and to detect highly dispersed or variable genes across single cells for
downstream analysis (Figure S5B). The DrImpute package in R software (ver. 3.4.1) was
used to estimate the dropout zeros or events in scRNA-seq before further analysis and
visualization [58]. For all downstream analysis, most of which were assessed using Seurat
plugin in SeqGeq version 1.1 or in-house R scripts. The heatmap was generated by using
MORPHEUS (https://software.broadinstitute.org/morpheus). The significant differentially
expressed genes (DEGs) were defined as p-value <0.05 and absolute log2 fold change >1.5
and further were used for enrichment pathway and biological process analysis. Gene set
enrichment analysis was performed using GSEA version 2.0.14 [59]. Kyoto Encyclopedia of
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Genes and Genomes (KEGG) database was used to evaluate the relevant signalling pathways
of the DEGs [60]. Enrichment of the DEGs into biological process (BP) Selected Gene
Ontology (GO) terms was performed using MetaCoreTM (GeneGO, MI, USA). In KEGG and
GO enrichment analysis, the p-value <0.05 was considered statistically significant.
Flow Cytometry Panels
For flow cytometry analysis, the following fluorochrome-labelled antibodies were
used: PE-Cy7 conjugated anti MICA/MICB (clone 6D4), BV711 conjugated anti-CD14
(clone M5E2), BV605 conjugated anti-CD95 (clone DX2), APC conjugated anti-CD85j
(clone GHI/75), BV605 anti-Tim3 (clone F38-2E2), BV711 anti-PD1 (clone EH12.2H7) (all
purchased from Biolegend); BV421 conjugated anti-ULBP2/5/6 (clone 165903) were
purchased from BD Biosciences; APC conjugated anti-ULBP1 (clone 170818) and PE
conjugated anti-ULBP3 (clone 166510) from R&D Systems. Cell viability was determined
using live/dead Zombie Aqua dye from Biolegend. Samples were analysed using the BD
Biosciences LSRII cell analyser and FlowJo software version 10.6.0 (Tree Star, Ashland,
OR).
RNA extraction and quantitative real time PCR
RNA was extracted using the Favorgen total RNA mini kit (Favorgen Biotech). M-
MLV reverse transcriptase (Promega) was used to generate complementary DNA (cDNA)
from 200 ng total RNA (A260/280 ratio of 1.9-2.1) according to the manufacturer’s protocol.
cDNA was amplified with specific primers and EvaGreen Master Mix (Biotium) using the
Rotor-Gene 3000 thermocycler (Corbett Research). Relative mRNA levels were calculated
using GAPDH Ct values as a reference gene. Primer sequences are available in
supplementary table 1.
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Supplementary Table 1. Sequence of PCR primers used for qPCR
Primer Sequence CD2 F: AAT GCC TTG GAA ACC TGG GG R: TGA TCA TCG GTC TTC AGA TGC BECN1 F: GGA AGG GTC TAA GAC GTC CA R: AGT TCC TGG ATG GTG ACA CG ATF4 F: TTC TCC AGC GAC AAG GCT AAG G R: CTC CAA CAT CCA ATC TGT CCC G S100A6 F: AAG CTG CAG GAT GCT GAA AT R: CCC TTG AGG GCT TCA TTG TA ISG20 F: TAG CCG CTC ATG TCC TCT TT R: TGA GGG AGA GAT CAC CGA TT ARL6IP1 F: CAG AGA CTG CAA GTC TGG AAG A R: ATG ATG GCA GGT GGA AAC CA TIMP1 F: AAT TCC GAC CTC GTC ATC AGG R: ATC CCC TAA GGC TTG GAA CC CD40LG F: TGA GCA ACA ACT TGG TAA CCC TGG R: CTG GCT ATA AAT GGA GCT TGA CTC G BNIP3L F: ATG TCG TCC CAC CTA GTC GAG R: CTC CAC CCA GGA ACT GTT GAG CD7 F: GCA GCA GTC TCC CCA CTG R: CCG GAG CCG TAG ACA TTG A EAT-2 F: GGA GGT ACA GCT GCT TAC ACA R: CTC CTG GTA TCG ACT CGC TG GAPDH F: AAG GTG AAG GTC GGA GTC AAC R: GGG GTC ATT GAT GGC AAC AAT A
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Figure S1. The expression of NKG2D ligands on monocyte-derived dendritic cells (moDCs).
moDCs from eight HBV vaccinated subjects were left unstimulated or stimulated in the presence
HBsAg for 24 hours and analysed for the expression of NKG2D ligands by flow cytometry. (A)
Unbiased bulk analysis of eight non-pulsed and pulsed-moDCs with HBsAg using t-SNE algorithm.
moDCs were defined as CD14- cells following the gating of live, single cells. Density plots show the
clustering of cell phenotypes in all samples (left panel) and in moDCs donors stratified based on
absence (middle panel) or presence HBsAg stimulation (right panel). (B) Overlaid histogram plots
showing the expression of NKG2D ligands ULBP1, ULBP2/5/6, ULBP3, MICA/MICB from non-
pulsed moDCs (blue) and pulsed-moDCs with HBsAg (green). Fluorescence minus one (FMO)
controls were performed alongside samples, and values are indicated on histograms. Wilcoxon’s test
was performed for individual comparisons of paired groups, *p<0.05.
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Figure S2. Mature monocyte-derived dendritic cell (moDCs) phenotype after
stimulation with HBsAg, HBcAg, and TNF-α.
(A) After 6 days culture, monocyte-derived dendritic cells (moDCs) were stimulated to
become mature moDCs with antigen (HBsAg and HBcAg) or TNF-α for 24 hours. Flow
cytometry histogram and bar graph showing the maturation state of moDCs HBV vaccinated
individuals, evaluated by the expression of surface markers CD83, CD86, and HLA-DR. (B)
HBsAg-pulsed DCs maturation status in HBV vaccinated and unvaccinated individuals.
Wilcoxon’s test was performed for individual comparisons of paired groups, *p<0.05 for
comparison with unstimulated moDCs. Mann-Whitney test was performed for individual
comparison of two independent groups.
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Figure S3. Immune cells and quality control gating in SeqGeq. (A) Immune cell subsets gating based on flow cytometry parameter (CD56+CD8 T cells,
CD56+CD4 T cells, CD56bright and CD56dim NK cells) and gene expression level of KLRG1
(KLRG1+/- CD56+CD8 T cells and KLRG1+/- CD56dim NK cells). (B) Quality control
procedures in SeqGeq consists of (1) the assessment quality of cells by performing the “knee
calling” plot using “gene expressed per cell” parameter in y axis and “rank of genes
expressed” parameter in x axis, (2) the quality of genes evaluation using “cells expressing”
for each gene parameter in y axis and “total expression/read” for every gene in x axis, and (3)
the detection of highly dispersed genes across single cells.
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Figure S4. Gene set enrichment analysis (GSEA) of KLRG1+CD3+CD56+CD8 T cells.
Gene set transcriptional enrichment analysis of KLRG1+ versus KLRG1-CD3+CD56+CD8 T
cells. Significant gene set enrichment related to KLRG1+CD3+CD56+CD8 T cells included
genes that are upregulated on CD161int CD8 T cell (above) and CD8 stem cell memory
(below), both of which possess an effector memory phenotype in adult circulation.
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Figure S5. Validation of upregulated genes in KLRG1+CD56dim NK cells in single cell
RNA-sequencing data.
The upregulated genes in KLRG1+ compared to KLRG1-CD56dim NK cells from single cell
RNA-sequencing data were validated using qPCR of sorted KLRG1+ and KLRG1- CD56dim
NK cells from 10 subjects. Wilcoxon’s test was performed for individual comparisons of
paired groups, *p<0.05.
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Figure S6. NK cell degranulation stratified by human cytomegalovirus (HCMV)
serology.
The plasma titre of HCMV immunoglobulin G (IgG) was measured among all subjects within
study groups (vaccine (-), vaccine (+), and chronic HBV (CHB) patients). According to IgG
serological status for HCMV, CD107a degranulation after re-stimulation with (A) HBcAg-
pulsed moDCs and (B) HBsAg-pulsed moDCs was compared within individuals in study
groups. Mann-Whitney tests were performed for comparisons of two independent groups
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Figure S7. Cytotoxicity NK cells response of HBV vaccinated subjects in the presence or
absence monocytes (CD14+) during re-stimulation with HBsAg-pulsed moDCs.
NK cells within PBMCs and CD14 depleted PBMCs (∆CD14-PBMCs) from 6 HBV vaccinated
subjects were incubated with HBsAg-pulsed moDCs or K562 cells as a positive control for 18 hours.
(A) Representative flow cytometry contour plot showing the NK cell CD107a response in the
presence or absence monocytes (CD14+) during coculture with HBsAg-pulsed moDCs or K562 cells.
NK cells CD107a response was measured by the percentage of CD107a positive cells and CD107a
staining intensity (geometric mean fluorescence intensity/gMFI). The microarray analysis from two
public datasets (B) GSE2215 and (C) GSE15075 reveals a distinctive expression profile of monocytes
and in vitro generated mature moDCs. Volcano plot showing differentially expressed genes (DEGs)
of mature moDCs versus monocytes with absolute log2 fold change 1.2-fold difference and adjusted p
value <0.05. Blue and red indicate transcript down- and up-regulated, respectively. Heatmap
illustrating the differential expressed genes between monocytes and mature moDCs related to
phenotype and positive regulation of NK and T cells immune response and proliferation according to
biological process (BP) gene ontology (GO) analysis with the DAVID functional annotation tool.
Wilcoxon’s test was performed for individual comparisons of paired groups.
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Figure S8. NK cell receptors expression on CD56bright and CD56dim of HBV vaccinated
subjects and CHB patients.
Flow cytometry was performed on total PBMCs from vaccinated subjects and CHB patients.
NK cells were gated based on CD3-CD56+ expression. The CD56bright and CD56dim NK cell
subsets were gated for evaluating NK cell receptors expression. (A) vaccinated subjects. (B)
CHB patients. Wilcoxon’s tests were performed for comparisons of paired groups, **p<0.01,
***p<0.001.
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Figure S9. CD56dimKLRG1- and CD56dimKLRG1+ NK cell phenotyping.
(A) The expression of NK inhibitory receptors; CD85j/ILT2, TIM-3, PD-1 on
CD56dimKLRG1- and KLRG1+ NK cells were evaluated by flow cytometry. (B) The gene
expression of CD7 and EAT-2 between CD56dimKLRG1- and KLRG1+ NK cells were
measured by qPCR. Wilcoxon’s test was performed for individual comparisons of paired
groups, **p<0.01.
.
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Figure S10. Correlation of PD-1 and TIM-3 expression with CD56dimKLRG1+NK cells
of HBV vaccinated subjects Correlation of the frequency and gMFI of CD56dimPD-1+ NK
cells and CD56dimTIM-3+ NK cells with CD56dimKLRG1+ NK cells within HBV vaccinated
subjects. Spearman’s rank test was used to evaluate the correlations, *p<0.05.
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Supplementary table 1. Phenotypic comparison of KLRG1+ and KLRG1- NK cells Properties KLRG1+/- Methoda p-valueb (readout system) Adhesion receptors • CD2 ↑ RNA-seq/qPCR RNA-seq (*)/qPCR (*) • CD56 CD56dim FCM (%) FCM (****) • CD57 ↑ FCM (%/gMFI)/ qPCR FCM (*/**)/qPCR (*) • CD7 ↓ qPCR qPCR (**) Inhibitory receptors • panKIR (KIR2DL1/L2/L3) ↔ FCM (%/gMFI) - • KIR2DL1 ↑ RNA-seq RNA-seq (*) • KIR3DL2 ↑ RNA-seq RNA-seq (*) • LIRB1/ILT2/CD85j ↑ FCM (%/gMFI) FCM (**/**) • NKG2A ↓ FCM (%/gMFI)/ qPCR FCM (****/**)/qPCR (**) Activating receptors • CD16 ↑ FCM (%/gMFI)/ qPCR FCM (**/***)/ qPCR (**) • panKIR (KIR2DS1/S2/S4) ↔ FCM (%/gMFI) - • NKG2C ↔ FCM (%/gMFI) - • DNAM-1 ↑ FCM (%/gMFI) FCM (*/**)/ qPCR (**) • NKG2D ↔ FCM (%/gMFI) - • NKp46 ↓ FCM (%/gMFI)/ qPCR FCM (****/*)/qPCR (*) Adaptor molecules • FcεRIγ ↓ qPCR qPCR (**) • SYK ↓ qPCR qPCR (*) • DAB-2 ↓ qPCR qPCR (*) • EAT-2 ↓ qPCR qPCR (**) Cytokines receptors • IFN-α (IFNAR1 and IFNAR2) ↑ qPCR qPCR (*) • IL-18Rα (IL18R1) ↓ qPCR qPCR (*) Death receptors and ligands • CD95L/Fas ligand ↔ FCM (%) - • CD40L ↑ qPCR qPCR (*) • TRAIL ↑ FCM (%) FCM (**) Transcription factor • PLZF (ZBTB16) ↓ qPCR qPCR (*) • IKZF2 (Helios) ↓ qPCR qPCR (*)
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Biological activities
• Cytokine secretion (IFN-γ) ↓ FCM (%)/qPCR FCM (***)/qPCR (*) IL-12/18 stimulation
• Cytotoxicity (CD107a) ↓ FCM (%)/qPCR FCM (**)/qPCR (*) K562 stimulation
• ADCC ↑ FCM/qPCR FCM (*)/qPCR (*) Raji+anti-CD20 stimulation
a The method used to investigate the KLRG1+ and KLRG1- NK cell phenotype and functionality consists of FCM: flowcytometry, RNA-seq: RNA sequencing, qPCR: quantitative PCR. qPCR was carried out on sorted KLRG1+ and KLRG1- NK cells with purity ≥98%, BD FACSAria III cell sorter (BD Biosciences). The flow cytometry result was represented as percentage positive cells (%) or geometric mean fluorescence intensity (gMFI) b The p-value was calculated by Wilcoxon’s test for individual comparisons of paired groups, *p<0.05, **p<0.01, ***p<0.001, ****p<0.0001. The significant differentially expressed genes (DEGs) in RNA-seq data were defined as p-value <0.05 and absolute log2 fold change >1.5
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