Celiac disease
Zorro Manrique, Maria Magdalena
DOI:
10.33612/diss.122712049
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Publication date:
2020
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Zorro Manrique, M. M. (2020). Celiac disease: From genetic variation to molecular culprits. University of
Groningen. https://doi.org/10.33612/diss.122712049
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CHAPTER 6
Knockdown of the long
non-coding RNA
RP11-291B21.2 interferes
with the activation of CD8
+
T cells
Maria Magdalena Zorro
1, Raul Aguirre-Gamboa
1, Toufic Mayassi
2,
Cezary Ciszewski
2, Sebo Withoff
1, Dylan de Vries
1, Lude Franke
1, Yang Li
1,
Cisca Wijmenga
1, Bana Jabri
2,3, Iris Jonkers
1Ch
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Abstract
CD8+ T cells, also called cytotoxic T cells (CTLs), are crucial effector cells in anti-viral and
anti-cancer immunity. However, it remains largely unknown how the CTL compartment is shaped towards subpopulations with distinct roles even though deregulation of particular CTL subtypes may contribute to autoimmune disorders such as celiac disease, type 1 diabetes and psoriasis. Because of their cell-type–specific function as regulators of gene expression, cell activation and differentiation, long non-coding RNAs (lncRNAs) are important regulatory transcripts in immune cell regulation. We selected the lncRNA, RP11-291B21.2, located in the vicinity of the natural killer receptor genes for further investigation because it is highly
expressed in naïve CD8+ T cells and downregulated in response to T cell receptor activation.
We characterized the pattern of RP11-291B21.2 expression across different T cell subsets in blood and investigated its role in intraepithelial CTL (IE-CTL) activation using single-cell RNA-seq data, co-expression network analysis and knockdown experiments. We find that
RP11-291B21.2 is specifically expressed in naïve CD8+ T cells and that its expression is reduced
upon physiological- or in vitro-induced activation. Knockdown of RP11-291B21.2 in IE-CTLs impaired the production of proinflammatory mediators such as tumor necrosis factor alpha and interferon gamma. Together these findings indicate that RP11-291B21.2 has a dual role:
it maintains the naïve/resting status of CD8+ T cells and modulates the activation of effector
memory T cells, antigen-experienced cells essential for mounting a rapid and strong immune defense.
Introduction
CD8+ T cells, also known as cytotoxic T cells (CTLs), are essential in the control of infections
and anti-tumor immunity. The CTL response includes a number of mechanisms, such as the release of perforins, granzymes, Fas/FasL and proinflammatory cytokines (e.g. IFNg, TFNa), that result in the lysis of infected or transformed cells and the enhancement of effector proper-ties of other immune cells such as monocytes, natural killer cells (NK), neutrophils and other
CTLs1,2. Abnormal CTL differentiation and function is known to contribute to an attenuated
immune response or to autoimmunity2.
Extensive work over recent years has shown that CTL differentiation depends on cytokines, transcription factors, DNA methylation status, histone modifications, microRNA expression
and transcriptional regulation2,3. Recently, long non-coding RNAs (lncRNAs) have garnered
attention due to their potential cell-type-specific and context-specific involvement in the
reg-ulation of gene expression4,5. LncRNAs have been identified as regulators of hematopoietic
cell differentiation and have been shown to be differentially expressed during the activation
of B cells, dendritic cells and T cells (amongst other cell types)4. Systematic assessment of
the transcriptional changes in the human or mouse CD8+ T cells activated upon infection or
vaccination has shown that particular lncRNAs are dynamically and specifically expressed
in different subpopulations of CD8+ T cells (naïve, effector and memory), a finding that both
corroborates previous findings supporting the cell-type-specificity of lncRNA expression and
shows they have a role in CTL fate decisions and activation6,7.
CTLs have been recognized as key drivers in the development of tissue-specific autoimmune diseases such as type 1 diabetes (T1D), psoriasis, and celiac disease (CeD). For instance, a hallmark of CeD is extensive infiltration of intraepithelial CTLs (IE-CTLs) into the intestinal mucosa, where these IE-CTLs become abnormally activated and kill intestinal epithelial cells independently of T cell receptor (TCR) specificity, which leads to the villous atrophy
character-istic of CeD8,9. An increase in the expression of the non-classical HLA-I molecules (e.g. MICA)
that are recognized by NK receptors expressed on the surface of IE-CTLs (e.g. NKG2D) is
specifically associated with CeD pathology10. Moreover, an upregulation of pro-inflammatory
cytokines such as IL-15 contributes to the expression of NK receptors in IE-CTLs and
pro-vides co-stimulatory signals that lead to epithelial cell destruction in CeD8,11. A more thorough
understanding of the mechanisms controlling CTL differentiation and activation could thus have significant therapeutic implications for CeD as well as other immune-mediated diseases.
Here we aimed to study the biological properties of a non-characterized lncRNA in CD8+
T cells. To do so we generated short-term CD8+ TCR ab cell lines derived from the
intesti-nal intraepithelial compartment and studied the effects of knocking down the lncRNA
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CD8+ T cell expression-specificity and on in silico predictions suggesting it is involved in cell
activation. Our results indicate a dual role for RP11-291B21.2 where it both maintains the
naïve status of CD8+ T cells and modulates the response to stimulation once the cells have
become functionally active.
Methods
Intraepithelial CTL (IE-CTL) cultures
Human biopsies were taken from CeD patients with their informed consent. All the protocols were approved by the University of Chicago Institutional Review Board. CeD individuals were defined on the basis of the presence of HLA-DQ8 or DQ2 and clinical (symptoms, response to a gluten free diet), histological (partial or total villous atrophy, crypt hyperplasia and in-creased IE-CTLs on duodenal biopsy) and serological (elevated anti-TG2 antibodies in blood)
criteria. CD8+ TCRab+ short-term IE-CTL cell lines derived from duodenal biopsies from CeD
individuals (n=3) were isolated and cultured as described previously12,13. In brief, cells from
the intraepithelial lymphocyte compartment were isolated by mechanical disruption in RPMI
(GIBCO) media supplemented with 1% dialyzed fetal bovine serum (Biowest), 1.5mM MgCl2
(Thermo Fisher Scientific) and 2mM EDTA (Corning). For IE-CTL cultures, a maximum of
10,000 cells expressing TCRab+ (IP26, BioLegend) and CD8a+ (RPAT-8, BioLegend) were
collected via fluorescence-activated cell sorting (FACS) on a FACSAria II cell sorter (BD
Bio-sciences). For ex vivo assessment of gene expression, a fraction of the cells (5x103) were
suspended in the lysis buffer included in the RNeasy plus micro kit (Qiagen), and these cells were subsequently analyzed by qPCR. The cells were expanded in vitro with a mix of feeder cells (irradiated heterologous peripheral blood mononuclear cells (PBMCs)) from two donors and Epstein Barr virus transformed B cells (EBV) in RPMI 1640 (GIBCO) medium with 1mg/ml PHA-L (Calbiochem), 10% human serum albumin (Atlanta Biologicals) and 100 units/ml IL-2 (NIH). The medium (RPMI supplemented with human albumin serum and IL-2) was refreshed every 2-3 days. After 12-14 days of expansion, aliquots of cells were frozen to establish a full set of cell lines for further use or re-expanded if required.
Blood-derived T cell isolation and culture
Heparinized blood samples were obtained from healthy donors. PBMCs were isolated by Ficoll density gradient centrifugation and subsequently stained with anti-CD45 (HI30, BD Bio-sciences), anti-CD3 (UCHT1, BD BioBio-sciences), anti-CD4 (SK3, BD BioBio-sciences), anti-CD8a (RPA-T8, BD Biosciences), anti-TCRαβ (IP26, BD Biosciences), anti-CD45RA (HI100,
Bioleg-end) and anti-CCR7 (G043H7, BiolegBioleg-end) antibodies. Isolation of CD4+ T cells or CD8+ T cells
was performed on a FACSAria II cell sorter (BD Biosciences). For all data, an initial gate for live cells based on forward and side scatter (FSC and SSC) parameters was used. In some
experiments CD8+ T cells were further separated, based on the expression pattern of CD45RA
and CCR7, into naïve (CD45RA+CCR7+), effector memory (TEM, CD45RA-CCR7-), central
population were suspended in the lysis buffer included in the RNeasy plus micro kit (Qiagen) for RNA isolation, and then qPCR was performed. For cell-line expansion, a fraction of each
sorted population (5x103 cells) was collected in culture medium and then cultured with feeder
cells as described above (see IE-CTL cultures).
Transfection of siRNA
IE-CTLs (CD8+ TCRab+) were thawed and re-expanded for 12 days as described above (see
IE-CTL cultures). To estimate cell viability (>80%), cells were analyzed with LIVE/DEAD fix-able Aqua Cell Stain Kit (Life Technologies) and cell activation (<10%) was determined by
FSC and SSC analysis using the LSR Fortessa™ (BD Biosciences) flow cytometer. Cells
were suspended at a density of 1x106 cells/ml in Accell siRNA delivery medium (Dharmacon),
supplemented with 100 units/ml IL-2 (NIH) and transfected with Accell siRNA duplexes de-signed for the non-targeting control (Dharmacon) or RP11-291B21.2 (Dharmacon) at a final
concentration of 1mM and plated in 96-well plates at a density of 2x105 cells/well. The
condi-tions for siRNA treatment were previously determined (data not shown). Untreated cells were included as negative control (wild type (WT)). After 24 hours, the medium was refreshed, the transfection was repeated and the cells were incubated for additional 48 hours.
IE-CTL stimulation
After siRNA treatment (72 hours), cells were washed and suspended at a density of 1x106
cells/ml in RPMI medium 1640 (GIBCO) containing 10% human serum albumin (Atlanta Bi-ologicals) and 100 units/ml IL-2 (NIH). Cells were either left unstimulated or stimulated with 1 mg/ml of plate-bound anti-CD3 antibody (eBioscience). This treatment emulates the
stimu-lation provided by the binding of antigen-presenting cells to the TCR14. A fraction of the cells
was treated with 1 ml/ml of Golgi stop and Golgi plug to inhibit protein release (both from BD Biosciences) and harvested for flow cytometry. After 3 hours, cells were centrifuged for 10
minutes at 400g, and the supernatants were collected and stored at -80oC until further protein
detection. The pellets were suspended in the lysis buffer included in the mirVanaTM miRNA
isolation kit (Invitrogen) for RNA isolation and downstream procedures including qPCR and RNA-seq.
Flow cytometry
After stimulation, cells were collected and washed with PBS and then stained with LIVE/DEAD fixable Aqua Cell Stain Kit (Life technologies), anti-CD3 APC-Cy7 (UCHT1, Biolegend) and anti-CD8a BV650 (RPA-T8BD, Biosciences). Subsequently, cells were washed and fixed in cytofix/cytoperm buffer (BD Biosciences), washed with 400 ml of Perm/wash buffer (BD Biosci-ences), and then incubated with conjugated antibodies to IFNg APC (4SB3, Biolegend), TNFa
PECy7 (Mab11, Biolegend) and CD107a BUV396 (H4A3, Biolegend) for 1 hour at 4oC. The
cells were washed and analyzed on the BD LSR Fortessa™ (BD Biosciences) flow cytometer. Data was analyzed with FlowJo (Treestarts). Results are expressed as the frequency of
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RNA sequencing (RNA-seq)
Total RNA from unstimulated or stimulated IE-CTLs cell lines was isolated with the mirVanaTM
miRNA isolation kit (Invitrogen). RNA concentration and quality were assessed on the Nan-odrop 1000 Spectrophotometer (Thermo Scientific) and the high-sensitivity RNA analysis kit (Experion, software version 3.0, Bio-Rad). RNA-seq libraries were prepared using the Quant seq 3’ kit (Lexogen) according to the manufacturer’s instructions. Sequencing was performed on the Nextseq500 (Illumina), yielding at least fifteen million sequence reads per sample. The fastQ files were trimmed for low quality reads, adaptors and poly-A tails. Trimmed fastQ files were aligned to build a human_g1k_v37 ensemble Release 75 reference genome using
hisat15 with default settings and sorted using SAMtools16. To perform gene-level quantification,
we used HTSeq-count17 using default mode=union. A modified Ensembl version 75 gtf file
mapping to the last 5’ 500 base pairs (bps) per gene was used to prevent counting of reads mapping to intra-genic A-repeats during gene annotation. Data normalization of raw counts (variance stabilizing transformation (VST)) and differential expression analysis between
con-ditions were performed using the DESeq218 package in R. Differentially expressed genes
(DEGs) were defined based on a False Discovery Rate (FDR) ≤0.05 among treatments. Prin-cipal component analysis (PCA) was performed using VST counts for all the samples. R Base functions (v3.4) including PCA, Venn diagrams and pheatmap were used to display overall
or specific transcriptional profiles. Gene-set enrichment analysis19 and Reactome pathways20
were used to identify biological processes and pathways enriched in different sets of DEGs.
For the RNA-seq dataset described in Fig. 1 (unpublished data, Mayassi T, et al), short-term
TCRgd (VD1) and CD8+TCRab CD8+ (CD8) blood- or intestinal-derived T cell lines were
ex-panded for 12 days, and then left untreated (unstimulated) or treated with 1.5 mg/ml of anti-CD3
or anti-TCRgd, respectively, for 4 hours. RNA was isolated with the mirVanaTM miRNA isolation
kit (Invitrogen) and used for bulk RNA-seq (Illumina TruSeq Ribo-Zero) and sequenced on a Hiseq 2500 instrument (Illumina) using default parameters (single end, 1x50bp). A standard pipeline was used to filter the sequencing reads. Reads were mapped to the build 37
hu-man reference genome using hisat15. Read counts were normalized to reads per kilobase of
transcript, per million mapped reads (RPKM). Differential expression analysis was performed
using the DESeq2 package18. Genes were considered differentially expressed based on an
FDR ≤ 0.05 among treatments. RT-qPCR
Total RNA from cell lysates was isolated using the mirVana™ miRNA isolation kit (AMBI-ON, catalog AM1561) for high numbers >5000 cells or the RNeasy plus micro kit (Qiagen) for low cell numbers <5000 cells. cDNA was prepared using either RevertAid H Minus First Strand cDNA Synthesis Kit (Thermo Scientific) for inputs >5000 cells, or SuperScript VILO cDNA synthesis kit (Invitrogen) for inputs <5000 cells. qPCR was performed using the Syber green mix (Bio-Rad) and run in a Quant studio 7 flex real time system (Applied Biosystems). The primers used were: RP11-219B21.2 5’ACCAGTAACAGGCATTGGGA, RP11-291B21.2
3’GCAAGTTGTCCACAGGTGAC, GAPDH 5’ ATGGGGAAGGTGAAGGTCG, GAPDH 3’ GGGGTCATTGATGGCAACAATA. Expression of GAPDH was included as internal control
to calculate the relative gene expression using the 2-ΔΔCT method21. The values of relative
ex-pression were converted to percentages by setting the WT cells or CD8+ naïve as reference
(100% expression). Olink
Levels of 92 pro- and anti-inflammatory proteins in supernatants were measured by the
Im-muno-Oncology panel 1 (Olink Bioscience) as described previously22,23. In brief, antibodies
coupled with specific oligonucleotide probes bind to their specific target proteins, and the se-quence is then quantified by RT-qPCR amplification. The results are given as the normalized protein expression (NPX) value on log-2 scale. The limit of detection (LOD) for each analyte was defined as three standard deviations above the background, and proteins with levels lower than LOD were excluded from the analysis. Net or total protein production in response to anti-CD3 stimulation was calculated by subtracting the level of protein production in unstim-ulated cells from that in the corresponding stimunstim-ulated sample. Supplementary Fig. 1 provides a summary of the methods and experimental approaches used to profile the expression of
RP11-291B21.2 in different immune cells and its potential function in CD8+ T cells.
Statistical analysis
The Shapiro-Wilk normality test was performed in R to assess the distributions of the flow cytometry, qPCR and Olink data. Differences within two groups were tested using unpaired one-tailed student’s t-test. Results were plotted using GraphPad Prism (GraphPad software) and presented as individual measurements (line plots) or mean ± standard error of the mean (SEM) (bar plots) from a representative experiment. Analysis of biological pathways and processes associated to individual genes or a group of genes were carried out using Gene
Network v2.0 (www.genenetwork.nl)24 and Reactome pathways20. To compare co-expression
patterns between RP11-291B21.2 and neighboring genes (cis genes in a 1 mega base (Mb) window centered on the location of the lncRNA) or distant genes (trans genes, outside the 1Mb window), we calculated Spearman correlation coefficients. Heatmaps were made using the R base function “pheatmap” to depict relevant patterns of gene expression or normalized protein secretion across the treatments. A brief description of the statistical tests and signifi-cance are described in each figure legend if applicable.
Results
LncRNA RP11-291B21.2 is co-expressed with NK receptor genes in T cells
To characterize the transcriptional signatures of intestinal lymphocytes (IELs) and their
coun-terparts in blood, RNA-seq was performed in short-term TCRgd (VD1) and CD8+TCRab (CD8)
blood- or intestinal-derived cell lines (unpublished data, Mayassi T, et al; for more details see
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cell subsets, we identified one lncRNA, RP11-291B21.2, with exceptionally high expression (~40 RPKM; Fig. 1A) compared to the mean expression of all other lncRNAs (0.33 RPKM on average; Fig. 1A). This level of expression is similar to the mean expression level of pro-tein coding genes (38 RPKM; Fig. 1A), which is surprising given that lncRNA expression is
generally lower than that of coding mRNAs25. Expression of RP11-291B21.2 was higher in
cells derived from intestinal tissues compared to blood-derived VD1 cells. Additionally, a re-duction in the expression of RP11-291B21.2 was noted after TCR stimulation, irrespective of the source (blood or intestine). Taken together, the high constitutive level of RP11-291B21.2, its tissue-specific expression profile and its modulation in response to stimulation suggest it has a role in the normal physiology of CTLs but also plays a role in the activation process of different T cell populations.
The biological role of the vast majority of lncRNAs, including RP11-291B21.2, is unexplored. However, examining their genomic co-localization with protein-coding genes and their tis-sue-specific expression profiles and performing co-expression analysis could provide some
clues about their function26. To assess whether RP11-291B21.2 is co-expressed with genes
in particular pathways, we performed Spearman correlation analysis on the transcriptomes
obtained from TCRgd (VD1) and CD8+TCRab (CD8) blood- or intestinal-derived cell lines and
plotted the correlation of all genes in a 1Mb window centered on RP11-291B21.2 (cis) and the top 20 correlated trans genes with RP11-291B21.2 (>5Mb away). Strikingly, genes in cis were more strongly correlated than trans genes, suggesting that RP11-291B21.2 potentially has a local cis-regulatory role. Among the genes strongly correlated with RP11-291B21.2 in cis are genes encoding for activating (e.g. KLRC2, KLRK1, KLRC3, KLRC4-KLRK1) and inhibitory (KLRC1) NK receptors; KLRD1, which encodes the NK receptor adapter molecule CD94; and STYK1, a recently described hallmark gene for NK cells that may act as a
reg-ulator of the PI3K/AKT/mTOR pathways27 (Fig. 1B). NK receptors are mainly expressed by
CTLs and NK cells and are known to recognize virus-infected cells, tumorigenic cells or cells expressing abnormal levels of MHC-I ligands. These receptors are also involved in
regula-tion of TCR stimularegula-tion and CTL effector funcregula-tions28. In trans, genes like MN1 and TEAD3
(encoding for transcriptional regulators) and several lncRNAs and microRNAs (e.g. miR-641,
RP11-543E8.2) with poorly characterized or unknown functions were correlated most strongly
(Fig. 1B). Although the overall correlation was similar in all conditions (unstimulated or stimu-lated cells, blood- or intestinal-derived cells), we found small differences in the correlation of certain genes in particular cell types. For instance, immune genes (CLEC7A) and taste recep-tor genes (e.g. TAS2R50, TAS2R13) were particularly highly correlated with RP11-291B21.2
expression in CD8+ IELs. In fact, the different cell types could be clustered based on the
pat-tern of correlation (e.g. a group of VD1 cell vs. CD8+ T cells; or a group of unstimulated VD1
vs. stimulated VD1). This suggests that the co-expression between RP11-291B21.2 and NK genes in CTLs is strong regardless of the cellular or stimulatory context, whereas the co-ex-pression with the ‘non-NK cell genes’ is more cell-type- and stimulation-specific.
To delineate the biological processes in which RP11-291B21.2 might operate, we
conduct-ed pathway analysis using Reactome (http://www.reactome.org)20 on the 36 most correlated
genes (correlation coefficient >0.4) in the TCRgd VD1 IEL cells where RP11-291B21.2 is most highly expressed. The correlated genes were significantly enriched in biological processes such as ‘DAP12 signaling’ and interaction between lymphoid and non-lymphoid tissues bi-ological processes (Fig. 1C). Interestingly, DAP12 is a key tyrosine kinase binding protein
(TYROBP) that acts as an activating signal transduction element in NK receptors28.
Co-expression of genes in cis may be a consequence of co-localization within a single
topo-logical domain, or be based on the shared function and/or regulation of genes, or both29,30.
To assess this, we plotted the 1Mb genomic region of RP11-291B21.2 and colored the cis genes according to their correlation coefficient (Fig. 2). Among the genes in close proximity to each other and linked to the same biological function (e.g. NK receptors versus taste receptor genes) we found similar degrees of correlation (e.g. KLRC2, KLRC3 and KLRC4 (high) vs.
TAS2R9 and TAS2R10 (low)). Furthermore, we also noted that some genes in close
proxim-ity to RP11-291B21.2 correlate less strongly (e.g. EIF2S3L) than cis genes located further away (e.g. KLRK1). Thus, we propose that co-expression of genes in cis with RP11-291B21.2 is mostly based on shared function and not just a consequence of proximity, which could mean that RP11-291B21.2 plays a regulatory role in NK receptor transcription or function. We also observed several lncRNAs within a distance of ~100kb (on the same chromosome) from
RP11-291B21.2 with significant/suggestive correlative strength. Co-expression analysis
per-formed in GeneNetwork24 predicted a function for two of the lncRNA genes (RP11-277P12.20
and RP11-277P12.9) most correlated with RP11-291B21.2 in NK cell cytotoxicity and antigen presentation (data not shown). This suggests that other lncRNAs may work together with
RP11-291B21.2 in cis to regulate genes with a shared role in NK cytotoxicity.
In addition, we interpreted DNase I hypersensitive data from publicly available data generated
from T cells31 as an indicator of gene regulatory regions such as promoters and enhancers.
In-terestingly, the genes with higher co-expression with the lncRNA (correlation coefficient >0.4) were found to co-localize within DNase I regions (mostly at genes located at positions chr12:
10,350,000-10,900,000) specific for CD8+ T cells and NK cells (Fig. 2). This overlap was most
notable in the loci containing the NK receptor genes. Furthermore, we found a dense region
of DNase I peaks overlapping with RP11-291B21.2 in CD8+ T cells (marked with a red star),
indicating the presence of a regulatory region or active transcription occurring at the transcrip-tion start site of the lncRNA, and this is specific for CTLs (Fig. 2).
Other data sources, including the human catalog of lncRNAs25 and GeneNetwork v2.024, also
suggest a role for RP11-291B21.2 in the regulation of the immune response, NK cytotoxicity and TCR signaling, amongst others (Supplementary Fig. 2). Taken together, our observations
point to a role for RP11-291B21.2 in CD8+ T cell activation either in cooperation with NK
Ch ap te r 6 Fig ur e 1 . R P1 1-2 91 B 21 .2 is c o-e xp re ss ed w ith N K re ce pto r g en es in T c ell s. S ho rt t erm p rim ary T ce ll li ne s C D 8+ T C R a b o r V D 1 ( TC R gd) g en era te d f ro m b lo od o r in te st in e w ere st im ula te d w ith 1 .5 m g/m l o f a nti-C D 3 o r a nti-TC R gd fo r 4 h ou rs, re sp ect ive ly. Th e t ra nscr ip to m e w as an alyze d b y R N A -se q ( un pu blish ed d ata , M aya ssi T, e t a l). (A ) B ar plo ts sh ow in g th e m ea n e xp re ssi on (R P K M ) a nd S E M o f R P 11 -2 91 B 21 .2 . D ash ed lin es in dica te a ve ra ge e xp re ssi on o f 1 00 ra nd om ly se le ct ed p ro te in -co din g g en es (lig ht gre y) a nd n on -co din g g en es (d ark gre y) . (B ) H ea tm ap d ep ict in g ci s ( all) o r tr an s ( to p 2 0) ge ne s co rre la te d w ith R P 11 -2 91 B 21 .2 . C olo r ch art s in dica te th e S pe arm an co rre la tio n co effici en t a nd ci s/ tra ns st atu s w ith re sp ect to R P 11 -2 91 B 21 .2 . T yp e o f T ce ll li ne a nd st im ula tio n ( U =u nst im ula te d, S =S tim ula te d) are sh ow n u nd er th e h ea tm ap . (C ) R ea ct om e a na lysi s w as pe rfo rm ed o n t he se t o f g en es w ith co rre la tio n co effici en t > 0.4 in th e V D 1-st im ula te d sa m ple s (n =7 ce ll li ne s) . S ize o f b ar de no te s th e si gn ifica nce (-l og 1 0 ( qva lu e)) o f e ach b io lo gica l p ath w ay . A B Fig ure 1 0.00 0.25 0.50 25 50 75 100 125 VD1-PBL CD8-IEL VD1-IEL Stim ula ted Un stim ula ted Exp ressi on va lue s (R PK M ) Expression values RP11-291B21.2 (RPKM) C unstim .iels.co r unstim .gam maDel ta.co r stim.ie ls.cor stim.g amma Delta. cor stim.a lphab eta.co r unstim .alph abeta .cor R P 1 1 − 2 9 1 B 2 1 .2 S T Y K 1 K L R C 4 − K L R K 1 K L R C 3 K L R C 4 R P 1 1 − 2 7 7 P 1 2 .2 0 K L R C 2 K L R K 1 Y B X 3 C L E C 7 A K L R A P 1 P R H 2 T A S 2 R 9 R P 1 1 − 2 7 7 P 1 2 .1 0 K L R C 1 T A S 2 R 1 0 R P 1 1 − 9 8 3 P 1 6 .4 A C 0 0 9 1 2 0 .6 R P 1 1 − 8 4 7 H 1 8 .3 P L S C R 2 T A S 2 R 6 3 P E IF 2 S 3 L R P 1 1 − 3 3 B 1 .4 T M E M 5 2 B M IR 6 2 6 T A S 2 R 1 2 T E A D 3 R P 3 − 3 5 5 L 5 .3 T A S 2 R 1 9 S N O R A 1 3 M N 1 S L C 2 5 A 3 9 P 2 M IR 6 4 1 T A S 2 R 1 5 T A S 2 R 2 0 R P 1 1 − 1 4 4 O 2 3 .8 L IN C 0 1 1 3 8 T A S 2 R 5 0 M IR 5 7 1 T A S 2 R 1 3 G A P D H P 5 5 R P 1 1 − 2 7 7 P 1 2 .9 K L R D 1 M A G O H B G A B A R A P L 1 A D P R M G K A P 1 S IA E T A X 1 B P 3 R P 1 1 − 5 4 3 E 8 .2 P R R 4 V E G F A T A S 2 R 1 4 H N R N P A B P 1 T A S 2 R 3 1 Type T y p e ci s tr a n s − 0 .5 0 0 .5 1 Type VD1-IEL_U VD1-PBL_U VD1-IEL_S VD1-PBL_S CD8-IEL_S CD8-IEL_U R P 11 −2 91 B 21 .2 S T Y K 1 K LR C 4− K LR K 1 K LR C 3 K LR C 4 R P 11 −2 77 P 12 .2 0 K LR C 2 K LR K 1 Y B X 3 C LE C 7A K LR A P 1 P R H 2 TA S 2R 9 R P 11 −2 77 P 12 .1 0 K LR C 1 TA S 2R 10 R P 11 −9 83 P 16 .4 A C 00 91 20 .6 R P 11 −8 47 H 18 .3 P LS C R 2 TA S 2R 63 P E IF 2S 3L R P 11 −3 3B 1.4 T M E M 52 B M IR 62 6 TA S 2R 12 T E A D 3 R P 3− 35 5L 5.3 TA S 2R 19 S N O R A 13 M N 1 S LC 25 A 39 P 2 M IR 64 1 TA S 2R 15 TA S 2R 20 R P 11 −1 44 O 23 .8 LIN C 01 13 8 TA S 2R 50 M IR 57 1 TA S 2R 13 G A P D H P 55 R P 11 −2 77 P 12 .9 K LR D 1 M A G O H B G A B A R A P L1 A D P R M G K A P 1 S IA E TA X 1B P 3 R P 11 −5 43 E 8.2 P R R 4 V E G FA TA S 2R 14 H N R N PA B P 1 TA S 2R 31 Typ e Ty p e ci s tra ns −0 .5 0 0.5 1 un stim .ie ls. cor un stim .g am ma De lta .co r stim .ie ls. cor stim .g am ma De lta .co r stim .a lp ha be ta .co r un stim .a lp ha be ta .co r RP 11− 291 B21 .2 STY K1 KLR C4− KLR K1 KLR C3 KLR C4 RP 11− 277 P12 .20 KLR C2 KLR K1 YB X3 CLE C7A KLR AP 1 PR H2 TAS 2R 9 RP 11− 277 P12 .10 KLR C1 TAS 2R 10 RP 11− 983 P16 .4 AC 009 120 .6 RP 11− 847 H18 .3 PLS CR 2 TAS 2R 63P EIF 2S3 L RP 11− 33B 1.4 TM EM 52B MIR 626 TAS 2R 12 TE AD 3 RP 3−3 55L 5.3 TAS 2R 19 SN OR A13 MN 1 SLC 25A 39P 2 MIR 641 TAS 2R 15 TAS 2R 20 RP 11− 144 O23 .8 LIN C01 138 TAS 2R 50 MIR 571 TAS 2R 13 GA PD HP 55 RP 11− 277 P12 .9 KLR D1 MA GO HB GA BA RA PL1 AD PR M GK AP 1 SIA E TAX 1BP 3 RP 11− 543 E8.2 PR R4 VE GFA TAS 2R 14 HN RN PAB P1 TAS 2R 31 Typ e Typ e cis tran s −0.5 0 0.5 1 Typ e unst im. iels .co r unst im. gam maD elta .co r stim .iel s.co r stim .ga mma Delt a.co r stim .alp hab eta. cor unst im. alph abe ta.co r R P 11 − 29 1B 21 .2 S T Y K 1 K LR C 4− K LR K 1 K LR C 3 K LR C 4 R P 11 − 27 7P 12 .2 0 K LR C 2 K LR K 1 Y B X 3 C LE C 7A K LR A P 1 P R H 2 TA S 2R 9 R P 11 − 27 7P 12 .1 0 K LR C 1 TA S 2R 10 R P 11 − 98 3P 16 .4 A C 00 91 20 .6 R P 11 − 84 7H 18 .3 P LS C R 2 TA S 2R 63 P E IF 2S 3L R P 11 − 33 B 1.4 T M E M 52 B M IR 62 6 TA S 2R 12 T E A D 3 R P 3− 35 5L 5.3 TA S 2R 19 S N O R A 13 M N 1 S LC 25 A 39 P 2 M IR 64 1 TA S 2R 15 TA S 2R 20 R P 11 − 14 4O 23 .8 LIN C 01 13 8 TA S 2R 50 M IR 57 1 TA S 2R 13 G A P D H P 55 R P 11 − 27 7P 12 .9 K LR D 1 M A G O H B G A B A R A P L1 A D P R M G K A P 1 S IA E TA X 1B P 3 R P 11 − 54 3E 8.2 P R R 4 V E G FA TA S 2R 14 H N R N PA B P 1 TA S 2R 31 Typ e Ty p e ci s tra ns − 0.5-0.5 00 0.50.5 11 ci s tra ns Inte rac tio n ly m p-no n-ly m p. t iss ue s D AP 12 inte rac tio ns D AP 12 sig na lin g 0 2 4 6 8 10 Im m un ore gLym p n on -Lym p ce ll DA P1 2 si gn alin g DA P1 2 in tera ctio ns -Lo g 1 0 (q va lue ) -Lo g 1 0 ( q v alu e) C or. co effi cie nt
Fi gu re 2 . R P1 1-29 1B 21 .2 lo cu s an d ci s ge ne s. S pe ar m an co rr el at io n an al ysi s w as pe rfo rm ed w ith re sp ect to R P 11 -2 91 B 21 .2 (d escr ib ed in F ig ur e 1) . U ni ve rsi ty of C al ifo rn ia S an ta C ru z (U C S C ) t ra cks w er e m od ifie d to sh ow g en es in a 1 M b-re gi on ce nt er ed o n R P 11 -2 91 B 21 .2 a nd th ei r r esp ect ive S pe ar m an co rr el at io ns. A rr ow s in di ca te lo ca tio n, d ire ct io n (se nse or a nt ise nse ) a nd g en e co rr el at io n (co lo r ch ar t, up pe r-rig ht co rn er ). G re y ar ro w s co rr esp on d to g en es excl ud ed fr om th e an al ysi s (u nd et ect ab le in o ur d at ase t). G en e na m es in b la ck or gr ey in di ca te co rr el at io n >0 .4 o r l ow er , r esp ect ive ly. R ed b ox sh ow s R P 11 -2 91 B 21 .2 g en om ic po si tio n. L ow er tr ack co rr esp on ds to D N ase I pr ofil e in p rim ar y bl oo d-de rive d C D 8 + T ce lls ta ke n fro m E pi ge no m ic ro ad m ap 31. R N 7S KP 16 1 R P1 1-65 6E 20 .5 R P1 1-27 7P 12 .2 0 R P1 1-27 7P 12 .9 R P1 1-27 7P 12 .1 0 TM EM 52 B G AB AR AP L1 10 ,3 00 ,0 00 10 ,4 00 ,0 00 1 0, 50 0, 00 0 1 0, 60 0, 00 0 1 0, 70 0, 00 0 1 0, 80 0, 00 0 1 0, 90 0, 00 0 1 1, 00 0, 00 0 1 1, 10 0, 00 0 11 ,2 00 ,0 00 50 0K b hg 19 KL R D 1 KL R K1 KL R C 2 KL R C 3 KL R C 1 EI F2 S3 L R P1 1-29 1B 21 .2 KL R AP 1 M AG O H B ST YK 1 YB X3 R P1 3-81 N 3. 2 TA S2 R 10 TA S2 R 9 TA S2 R 8 TA S2 R 7 TA S2 R 14 PR H 1 PR H 2 TA S2 R 13 TA S2 R 31 PR R 4 TA S2 R 20 TA S2 R 19 KL R C 4-KL R K1 C LE C 7A O LR 1 KL R C 4 AK 09 63 14 PR H 1-PR R 4 TA S2 R 50 PR B4 C LE C 9A C LE C 1A BC 05 50 55 SL C 25 A3 9P 2 TA S2 R 63 P TA S2 R 15 AC 01 86 30 H N R N PA BP 1 p1 3. 31 p1 2. 3 p1 2. 1 q1 1 12 q1 2 q1 4. 1 12 q1 5 q2 1. 1 q2 1. 2 12 q2 1. 31 q2 2 12 q2 3. 1 q2 3. 3 q2 4. 31 q2 4. 33 C hr 12 (P 13 .2 ) 10 ,2 00 ,0 00 CD 8 +T ce lls NK c el ls CD 4 +T ce lls DN as e I Fi gu re 2 unstim.iels.cor unstim.gammaDelta.cor stim.iels.cor stim.gammaDelta.cor stim.alphabeta.cor unstim.alphabeta.cor R P 11 −2 91 B 21 .2 S TY K 1 K LR C 4− K LR K 1 K LR C 3 K LR C 4 R P 11 −2 77 P 12 .2 0 K LR C 2 K LR K 1 Y B X 3 C LE C 7A K LR A P 1 P R H 2 TA S 2R 9 R P 11 −2 77 P 12 .1 0 K LR C 1 TA S 2R 10 R P 11 −9 83 P 16 .4 A C 00 91 20 .6 R P 11 −8 47 H 18 .3 P LS C R 2 TA S 2R 63 P E IF 2S 3L R P 11 −3 3B 1. 4 TM E M 52 B M IR 62 6 TA S 2R 12 TE A D 3 R P 3− 35 5L 5. 3 TA S 2R 19 S N O R A 13 M N 1 S LC 25 A 39 P 2 M IR 64 1 TA S 2R 15 TA S 2R 20 R P 11 −1 44 O 23 .8 LI N C 01 13 8 TA S 2R 50 M IR 57 1 TA S 2R 13 G A P D H P 55 R P 11 −2 77 P 12 .9 K LR D 1 M A G O H B G A B A R A P L1 A D P R M G K A P 1 S IA E TA X 1B P 3 R P 11 −5 43 E 8. 2 P R R 4 V E G FA TA S 2R 14 H N R N PA B P 1 TA S 2R 31 Type Ty pe ci s trans −0 .5 0 0. 5 1 Co r. co ef fici en t
Ch
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RP11-291B21.2 is expressed in CD8+ T cells with a naïve expression profile
To confirm that RP11-291B21.2 is truly specific to CD8+ T cells, we assessed its expression
profile in cells freshly isolated from blood. We used available RNA-seq data from seven
ma-jor immune cell types purified by cell sorting32 and single-cell RNA-seq (scRNA-seq) data33
as described in Supplementary Fig. 1. The level of RP11-291B21.2 was found to be highly
expressed in CD8+ T cells, lowly expressed in memory T cells and NK cells, and
non-detect-able in B cells, CD4+ T cells, granulocytes and monocytes (Fig. 3A). Moreover, T-distributed
stochastic neighborhood embedding (t-SNE) analysis of PBMC scRNAseq data identified 12 major clusters of cell types (Fig. 3B) based on the expression of canonical gene markers (Fig.
3C). RP11-291B21.2 is highly expressed within a subset of CD8+ T cells (Fig. 3D, orange
dots marked with a red oval). The cells that express the lncRNA at high levels (CD8+
RP11-291B21.2+) also express genes (e.g. CD3D, CD8A, CD8B) that define a CD8+ T cell cluster
along with genes typically associated with a naïve status such as CCR7 and SELL (gene
encoding for CD62L) (Fig. 3C, red boxes). Additionally, CD8+RP11-291B21.2+ cells do not
express NKG7 (a poorly characterized NK receptor), in contrast to cells that do not express
the lncRNA (CD8+RP11-291B21.2- cells).
Analysis of genes differential expressed between CD8+RP11-291B21.2+ and CD8+
RP11-291B21.2- cells revealed that the downregulated genes in CD8+RP11-291B21.2+ cells (e.g.
KLRB1L, CD69, GZMHB, GZMB; Fig. 3A in blue) are associated with processes including
cytotoxicity and immune activation (Fig. 4B, top 10 Reactome pathways in downregulated genes). Conversely, the upregulated genes (Fig. 4A in red) include well-established naïve
cell markers (e.g. CCR7, SELL3) and LEF-1 (encoding for TCF-1), a regulator of T cell
qui-escence34, amongst others. These results indicate that RP11-291B21.2 is specific to CD8+ T
cells that display a naïve or resting expression profile.
RP11-291B21.2 expression decreases upon functional activation of CD8+ T cells
To further characterize RP11-291B21.2+ cells, we evaluated the expression of this lncRNA in
different blood-derived CD8+ T cells sorted according to the surface markers CD45RA and
CCR7 into naïve, TCM, TEMRA and TEM cells (Fig. 5A shows the gating strategy), with each
having different functional properties3. We also included CD4+ T cells from blood as
nega-tive controls and IELs (TCRgd+ and CD8+TCRab+) to determine whether these cells express
RP11-291B21.2+ ex vivo. As predicted, based on the scRNA-seq profiles and the analyses
described above (Fig. 3-4), RP11-291B21.2 was expressed in all the sorted cell types except
CD4+ T cells (Fig. 5B). Here we observed that naïve CD8+ T cells exhibit the highest levels of
the lncRNA, followed by TCM, TEMRA and TEM, respectively (Fig. 4B, left), indicating that the level of RP11-291B21.2 decreases with rising functional activation status. Additionally, biopsy-derived T cells exhibited levels of RP11-291B21.2 comparable to those in TCM cells in
blood, which confirms that the expression of RP11-291B21.2 in intestinal CD8+ and VD1 cell
Fi gu re 3 . R P1 1-29 1B 21 .2 is e xp re ss ed in C D 8 + T c el ls w ith a n aï ve e xp re ss io n pr ofi le . ( A ) E xp re ssi on le ve l o f R P 11 -2 91 B 21 .2 (R P K M ) i n di ffe re nt im m un e ce lls (so rte d po pu la tio ns fo llo w ed b y bu lk R N A se q, r ep re se nt at ive o f t w o exp er im en ts) 32. ( B -D ) scR N A -se q da ta p re vi ou sl y ge ne ra te d fro m P B M C 33. ( B ) t-S N E p lo t d isp la yi ng th e m ai n im m un e-ce ll typ es in P B M C id en tifie d w ith ca no ni ca l m ar ke rs an d la be le d w ith d iff er en t co lo rs . ( C ) V io lin p lo ts sh ow in g th e exp re ssi on d ist rib ut io n of re pr ese nt at ive m ar ke r g en es acr oss th e ce ll cl ust er s. (D ) E xp re ssi on p at te rn o f R P 11 -2 91 B 21 .2 in th e di ffe re nt ce ll cl ust er s in fe rr ed in th e fu ll scR N A da ta se t. C ol or s ye llo w to re d in di ca te R P 11 -2 91 B 21 2. 2 exp re ssi on (l ow to h ig h) . R ed o va ls an d re ct an gl es m ar k th e po pu la tio n w he re th is ln cR N A is hi gh ly exp re sse d.
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Knockdown of the lncRNA RP11-291B21.2 interferes with the activation of CD8+ T cells.
Fig ur e 4 . D ow nr eg ula te d g en es in C D 8+ R P1 1-2 91 B 21 .2 + T ce lls ar e a ss oc ia te d w ith ce ll c yto to xic ity an d a cti va tio n. ( A ) T op 40 D E G s be tw ee n C D 8+ T ce lls exp re ssi ng (C D 8 + R P 11 -29 1B 21 .2+ ) o r n ot e xp re ssi ng (C D 8+ R P 11 -2 91 B 21 .2 -) R P 11 -2 91 B 21 .2 . D ow nre gu la te d ( blu e) or up re gu la te d ( re d) ge ne s in C D 8+ R P 11 -2 91 B 21 .2+ ce lls (co lo r ke y, l og 2 -F old ch an ge ). ( B ) B io lo gica l p ath w ays (R ea ct om e a na lysi s) o ve rre pre se nte d in th e se t o f d ow nre gu la te d g en es de scr ib ed in (A ). B ar le ng th in dica te s si gn ifica nce (-l og 1 0 ( q va lu e)) . Down-regulated pathways CD8+RP11-291B21.2+ A B Lo g2 FC CD 8+ RP 11 -29 1B 21 .2+ Fig ure 4 KL R B1 N KG 7 C C L5 G N LY C ST 7 C C L4 AP O BE C 3G C M C 1 D U SP 2 C D 69 G ZM H G ZM B JU N FO S LD H A TG FB 1 SR G N FG FB P2 R G S1 G AD D 45 B R PL 32 PR KC Q -A S1 R PL 22 N EL L2 R PS 8 R PS 5 R PS 13 PIK 3IP 1 TM EM 12 3 M YC EIF 3E N PM 1 LD H B C M SS 1 PA SK SE LL LT B R G S1 0 LE F1 C C R 7 0 5 10 15 FC g P ha go cyt osi s N FK b si gn alin g TL R ca sca de TC R si gn alin g A ntig en p re se nta tio n M H C I M A P ki na se a ct iva tio n A po pto si s In te rle uki n si gn alin g In te ra ct io ns lym p S ig na lin g b y In te rle uki ns -Lo g 1 0 ( q v alu e)
To determine if the level of RP11-291B21.2 is reduced with the activation of the CD8+ T cells
and remains low or undetectable in CD4+ T cells, we expanded the sorted populations by
co-culturing them with a mix of allogenic PBMCs and EBV cells (Fig. 5B center and right pan-els). The allogenic co-culture system is a well-known strategy to promote extensive prolifera-tion that drives the cells towards a more funcprolifera-tionally activated status, for example by inducing
cytokine production35. After co-culture, RP11-291B21.2 expression was downregulated in the
different populations of CD8+ T cells (Fig. 5B, central panel). Moreover, the lncRNA level was
reduced even more after a second co-culture in CD8+ T cells (Fig. 5B, right panel), but was
unaffected in CD4+ T cells. Overall, our observations indicate that RP11-291B21.2 is reduced
when CD8+ T cells become more activated or gain an “effector status”, suggesting that the
lncRNA actively maintains a naïve status when the lncRNA is expressed at high levels or represses the mechanism that allows cells to differentiate towards effector or memory T cell (Fig. 5C).
RP11-291B21.2 knockdown impairs the CD8+ T cell response upon TCR activation
To further explore the functional role of RP11-291B21.2 in CD8+ T cells, we knocked down the
lncRNA in CD8+ TCRab IEL (IE-CTLs) cell lines from intestinal tissue using siRNAs.
IE-CT-Ls cell lines were used because the optimization and execution of knockdown experiments requires a large number of cells and because IE-CTLs can be expanded to the required numbers while exhibiting considerable levels of the lncRNA (as shown in Fig. 1). IE-CTLs
have “activated, yet resting” properties, inherent to tissue-resident effector memory T cells36,
making them a suitable model to study RP11-291B21.2. After siRNA treatment, we measured
classical markers of activation and degranulation of CTLs (IFNg, TNFa and CD107a)37,38 using
intracellular FACS. Here we found that the expression of these markers was low under resting conditions, irrespective of the treatment (Fig. 6A and data not shown; <0.3% in WT, scrambled non-targeting siRNA (SCR) or knockdown (KD) unstimulated cells), but increased 8- to 15-fold after anti-CD3 treatment in all biological replicates compared to their respective unstimulated sample. Moreover, we found a reduced percentage of cells responding to anti-CD3 stimulation
(IFNg+, TNFa+ and CD107a+) in SCR and KD cells compared to WT cell lines (Fig. 6B). This
effect, while not statistically significant, was stronger in the KD cells, indicating that
RP11-291B21.2 may interfere with the response to TCR stimulation in IE-CTLs and supporting our
hypothesis that this lncRNA could contribute to the control of CD8+ T cell activation.
RP11-291B21.2 knockdown reduces the expression of pro-inflammatory genes re-sponding to TCR stimulation
To further characterize the effects of reduced RP11-291B21.2 expression on cell activation, we assessed the major transcriptional changes upon knockdown using RNA-seq. We con-firmed the knockdown of the lncRNA to ~40% of WT expression levels in RNA-seq data (Sup-plementary Fig. 3) and in qPCR data (data not shown). We also found that the non-targeting siRNA (SCR) affected the level of RP11-291B21.2. However, this effect was minor compared with the targeting siRNA (on average ~13% SCR vs. ~40% in KD cell lines).
Ch ap te r 6 Fig ur e 5 . E xp re ss io n o f R P1 1-2 91 B 21 .2 de cre as es w ith th e f un cti on al ac tiv ati on s ta tu s o f C D 8+ T c ell s. Fre sh ly iso la te d P B M C -d eri ve d o r in te st in al bio psy-de rive d ce lls w ere st ain ed w ith sp eci fic an tib od ie s an d so rte d ( A , B (le ft p an el) ). ( A ) b lo od -d eri ve d C D 8+ T ce lls w ere fu rth er se pa ra te d b ase d o n t he e xp re ssi on o f C D 45 R A o r C C R 7 ( do t p lo t, sh ow in g t he ga tin g st ra te gy (u pp er pa ne l)). (B ) q P C R e xp re ssi on p ro fil in g o f R P -11 29 1B 21 .2 in d iffe re nt ce ll typ es: b lo od -d eri ve d C D 8+ (n aïve , T C M , T E M , T E M R A ) a nd C D 4 + T ce lls or in te st in al-de -rive d T ce lls (C D 8 + T C R a b o r V D 1 ( TC R gd) ) (l eft ); sh ort -te rm C D 8+ a nd C D 4 + T ce ll li ne s aft er th e fir st (ce nte r) o r se co nd a llo ge nic st im ula tio n ( rig ht) . D ata is pre se nte d a s pe rce nta ge of R P 11 -2 91 B 21 .2 re la tive to n aïve C D 8+ ce lls pe r p an el. B ars sh ow m ea n ± S E M fro m o ne re pre se nta tive e xp eri m en t o f th e t w o in de pe nd en t e xp eri m en ts. S ta tist ica l d iffe re nce s w ere ca lcu la te d w ith o ne -si de d t -te st . P -va lu e ≤ 0 .0 00 1 ( *** *), ≤ 0 .0 1 ( **) . (C ) S ch em atic re pre se nta tio n o f R P 11 -2 91 B 21 .2 e xp re ssi on a cr oss fu nct io na l C D 8+ T ce ll p op ula tio ns. T he m ain su rfa ce m arke rs of ea ch ce ll p op ula tio n a re sh ow n ( C D 45 R A , C D 62 L, C C R 7, C D 45 R O , C D 69 , C D 10 3).
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CD8 N aive CD8 T CM CD8 T EM CD8 T EM RA CD4 0 1 2 3 4 5 50 100 150 *** * ** *** * ** CD 8 N aive CD 8 TCM CD 8 TEM CD 8 TEM RA CD4 0 1 2 3 4 5 50 100 150 *** * CD 8 Naive CD 8 TCM CD 8 TEM CD 8 TEM RA CD4 CD8 VD1 0 1 2 3 4 5 50 100 150 *** * Fig ure 5 %relative expressionRP11-291B21.2 A B C Ce ll lin es Ex -vi vo Ce ll lin es blo od bio ps y PH A Allo ge nic IL-2 PH A Allo ge nic IL-2 Ac tiv atio n s tat us RP 11 -29 1B 21 .2 CD 45 RO + CD 62 L-CC R7 -N aiv e C en tra l m em or y Tis su e r es id en t E ffe cto r m em or y E ffe cto r m em or y C D 45 R A + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L-C C R 7-Te m ra C D 69 + C D 10 3+ N aiv e C en tra l m em or y Tis su e r es id en t E ffe cto r m em or y E ffe cto r m em or y C D 45 R A + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L-C C R 7-Te m ra C D 69 + C D 10 3+ N aiv e C en tra l m em or y Tis su e r es id en t E ffe cto r m em or y E ffe cto r m em or y C D 45 R A + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L-C C R 7-Te m ra C D 69 + C D 10 3+ N aiv e C en tra l m em or y Tis su e r es id en t E ffe cto r m em or y E ffe cto r m em or y C D 45 R A + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L-C C R 7-Te m ra C D 69 + C D 10 3+ N aiv e C en tra l m em or y Tis su e r es id en t E ffe cto r m em or y E ffe cto r m em or y C D 45 R A + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L+ C C R 7+ C D 45 R O + C D 62 L-C C R 7-Te m ra C D 69 + C D 10 3+ CD 45 RA + CD 62 L+ CC R7 + CD 45 RO + CD 62 L+ CC R7 + Na ive T c en tra l M em ory (T CM ) T e ffe ct or m em ory RA (T EM RA ) Tissu e-r es ide nt effe cto r m em ory CD 45 RA + CC R7 -CD45RA CC R7 0 10 3 10 4 105 0 103 104 105 T e ffe cto r m em ory (T EM )Fi gu re 6 . R P1 1-29 1B 21 .2 k no ck do w n im pa irs C D 8 + T c el l r es po ns e to T C R a ct iv at io n. C D 8 + T C R a b + sh or t-t er m IE -C TL ce ll lin es de rive d fro m d uo de na l b io psi es (n =3 ) w er e le ft un tre at ed (W T) o r t ra nsf ect ed w ith n on -ta rg et in g si R N A (S C R ) o r R P 11 -2 91 B 21 .2 si R N A (K D ) f or 4 8 ho ur s, th en st im ul at ed w ith 1 m g/ m l o f a nt i-C D 3. U nst im ul at ed ce lls w er e in cl ud ed as co nt ro l. Th e exp re ssi on o f C D 10 7a , I FN g an d TN Fa w as qu an tifie d by in tra ce llu la r flo w cyt om et ry in th e ga te d C D 3 + C D 8a + p op ul at io n. (A ) d ot p lo ts (n =1 re pr ese nt at ive ce ll lin e) o r (B ) l in e pl ot s (n =3 ce ll lin es) a re sh ow n. N um be rs in di ca te th e pe rce nt ag e po si tive ce lls. O ne -si de d t-t est w as use d to a sse ss di ffe re nce s be tw ee n gr ou ps. N o st at ist ica l d iff er en ce s w er e fo un d.
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ap
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r 6
Knockdown of the lncRNA RP11-291B21.2 interferes with the activation of CD8+ T cells.
We performed PCA on the normalized read counts across all the samples and treatments to study the overall distribution of the transcriptome. The first two principal components explain
the majority of the variance (85%, Fig. 7). Two major clusters (grouped with circles)
corre-sponding to the unstimulated and anti-CD3 stimulated samples were found, thus we observed strong effects on gene expression as a consequence of anti-CD3 stimulation.
Next, we evaluated the transcriptomic response to anti-CD3 stimulation. In brief, we com-pared the gene expression between unstimulated WT, SCR or KD samples and their cor-responding anti-CD3 stimulated samples to determine DEGs (Fig. 8A), and then identified unique or shared DEGs in response to anti-CD3, which are illustrated in a Venn diagram (Fig. 8B). In total, 149 DEGs were identified, 88 of them responding uniquely in one condition (76 in WT, 7 in SCR and 5 in KD). Reactome analysis of DEGs found only in WT cells indicates en-richment in cell signaling and immune activation (e.g. RGS1, RSG12, S1PR4, GBP2, NFKB1,
PTPN7, IL2RA; data not shown), whereas the unique genes responding to SCR or KD were
Figure 7. PCA groups samples according to the response to TCR stimulation. CD8+ TCRab+ IE-CTL cell lines were
left untreated (WT) or transfected with siRNA (SCR, KD), and then stimulated with 1 mg/ml of anti-CD3. Unstimulated cells were included as control. The transcriptome was analyzed by RNA-seq. PCA based on the VST-normalized counts across all the samples and treatments. Circles indicate the separation between unstimulated or anti-CD3 stimulated cells.
197
regulatory mechanism of CD8
+T cell activation.
Figure 7. PCA groups samples according to the response to TCR stimulation. CD8+ TCRab+ IE-CTL cell lines were left untreated (WT) or transfected with siRNA (SCR, KD), and then stimulated with 1 µg/ml of anti-CD3. Unstimulated cells were included as control. The transcriptome was analyzed by RNA-seq. PCA based on the VST-normalized counts across all the samples and treatments. Circles indicate the separation between unstimulated or anti-CD3 stimulated cells.
PC 2 Ex pl ai ne d va ria nc e 5% PC1 Explained variance 80%
