Transcriptomic network to support HLA-DR expression in LNSC. Abstract
Rheumatoid arthritis (RA) is an autoimmune disease that occurs when the body’s tissues are
mistakenly attacked by their own immune system. Lymph nodes are important in the linkage between antigen presenting cells and lymphocytes, a process which appears to be highly regulated by lymph node stromal cells (LNSCs). HLA-DR is one of the molecules that represents the major determinants in the induction of the adaptive immune system. The aim of the study is whether DR+ and HLA-DR- cells have differentially expressed genes that can be modulated on LNSCs. In order to investigate the HLA-DR, confocal images have been made to look at the localization in the cell where the HLA-DR is being expressed and a scRNA seq has been applied to find the differentially expressed genes (DEG). After IFN-y stimulation of LNSCs, confocal images have shown that HLA-DR is expressed in the whole cell. Differential expression analysis of scRNA seq data reveals PLVAP, CLEC14A, PECAM1 as potential membrane markers to isolate cells expressing these markers on HLA-DR+ cells. The reconstruction of transcriptional regulatory networks pinpoints RFXAP, RFXANK and RFX5 as transcription factors to maintain the HLA-DR upregulated differentially expressed genes. This study proposes potential candidates to be targeted to modulate the HLA-DR expression in LNSCs.
Introduction
Rheumatoid arthritis (RA) is an autoimmune disease that is associated with progressive disability and other complications such as joint damage, decreased quality of live and cardiovascular problems. The cause of RA is partly unknown. (McInnes & Schett, 2011) In industrialized countries RA nowadays affects 0.5- 1% of the adults and the frequency of RA is detected three times more often in women than in men. (Scott et al., 2010) An autoimmune disease is characterized by when the body's tissues are mistakenly attacked by their own immune system, this is happens through an autoreactive response of T or B cells. (Rojas et al., 2018)
50% Of the risk of getting RA can increase with genetic factors, and environmental factors such as smoking (Scott et al., 2010). People susceptible for RA will develop it within three to four years (Hähnlein et al., 2018) Within these people the generation of anti-citrullinated protein antibodies (ACPA) is a sign of developing RA. (Kurowska et al., 2017) In the lymph nodes of these patients subsets of B cells, T cells and innate lymphoid cells had different frequencies compared to healthy patients, showing in these patients higher ACPA levels in pre-clinical phase. (Van Baarsen et al., 2013) Lymph nodes are important in the linkage between the antigen presenting cells and lymphocytes and doing so, they initiate the adaptive immune response. (Koning & Mebius, 2020) Stromal cells are able to help in the migration to the lymphoid cells that are critical for the immune response. (Rodda et al., 2018) Lymph node stromal cells (LNSC’s) are a mixture of endothelial and mesenchymal cells
(Krishnamurty & Turley, 2020). Mesenchymal cells are represented by CD31-PDNP+ fibroblastic reticular cells (FRC) and double negative cells (DN). (Hirosue & Dubrot, 2015). FRCs and antigen presenting cells (APC) bind to a specific receptor-ligand pairs on the T-cells, a good example of one of these markers is PD-1/PD-L1 (Hirosue & Dubrot, 2015) FRCs are specialized immune interacting fibroblasts that coordinate the migration and positioning of lymphocytes. (Perez-Shibayama et al., 2019)
Earlier research has shown that LNSC’s play an important role in shaping the immune response, this is done by the expression and engagement of adaptation of receptor-ligand pairs on T cells and the
LNSC involved (for example PD-1/PD-L1). (Hirosue & Dubrot, 2015) It has been shown that LNSCs regulate the proliferation of activated T-cells and restrain the entry of the cell into the cell cycle. (Lukacs-Kornek et al., 2011; Siegert et al., 2011 cited in Baptista et al., 2014). In addition, Hirosue & Dubrot (2015) have shown that LNSC’s not only guide the antigens to the APC but also present antigen themselves to the T cells. This way they activate the naïve T-cells in the lymph nodes. (Brown & Turley, 2015) The activation of the CD4+ T cells through the antigens goes via MHC-II molecules on mouse LNSCs. (Nadafi et al., 2020) LNSCs seem to be obtaining an epigenetic imprint during
systematic autoimmunity, this might play a role in the development of RA. (Karouzakis et al., 2019) It has been reported that there are differences in LNSC behaviour between healthy individuals,
individuals more susceptible for RA , and RA patients (Hähnlein et al., 2018).
Figure 1. Lymph node with all involved cells.
Lymph node stromal cells shown in this figure (FRC) are able to take the APC cells to the naïve T-cells in the lymph node shown at location C. In addition, FRCs are able to activate the naïve T-cells as well shown at location D. Image taken from Hirosue & Dubrot (2015)
In humans, HLA-DR is one of the molecules that represents the major determinants in the induction of the adaptive immune system. They are expressed by APC and there is nowadays a whole list of HLA alleles that are in association with RA such as HLA-DR4 and HLA-DR1. (Kampstra & Toes, 2017) The aim of the study is to investigate if HLA-DR+ and HLA-DR- cells have differentially expressed genes to modulate on LNSCs. Through this information, the differentially expressed genes can be used to
modulate the LNSC phenotype. More specifically a gene downregulated in HLA-DR- might be upregulated with synthetic molecules drug to switch LNSCs into HLA-DR+. Also, from the
differentially expressed genes pool, the genes are selected on encoding for proteins located in the plasma membrane. Such surface protein might be used to sort specifically antigen presenting LNSC for further analysis.
Methods
Due to the corona virus the experimental wet lab protocols have been executed by Cristoforo Grasso MSc.
Figure 2. Workflow of the experiments.
A biopsy of a lymph node has been digested and stained for FACS sorting. The cells were then sorted in DR+ and HLA-DR- cells, after the sorting a 10x genomics scRNA seq has been conducted to analyze the transcriptomics of single cells. Confocal imaging has been conducted as well to make multiple 2D images of the cells that can been analyzed.
Analysis and statistics of the differential gene expression
R language packages will be used to analyse the scRNA transcriptomics data genes expressed in these cells and compare the differences with each other performing an RNA sequencing. A p-value of 0.05 and a fold change cut-off of 1.5 were set.
The analysis uses the function “FindMarkers” from the package SeuratV3.1, to compute the
differentially expressed genes analysis. The Enhancedvulcano package to generate the volcano plot. The violin plots were generate using the function “Vlnplot” from SeuratV3.1.
R version 4.0.0 (2020-04-24)
Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 18362) Matrix products: default
locale: [1] LC_COLLATE=Dutch_Netherlands.1252 [2] LC_CTYPE=Dutch_Netherlands.1252 [3] LC_MONETARY=Dutch_Netherlands.1252 [4] LC_NUMERIC=C [5] LC_TIME=Dutch_Netherlands.1252 attached base packages:
[1] stats graphics grDevices utils datasets [6] methods base
loaded via a namespace (and not attached): [1] BiocManager_1.30.10 compiler_4.0.0
[3] tools_4.0.0
Gene ontology of enrichment pathway
In order to find the function and localization of genes, genecards.org´s option for the localization and function was consulted. In addition metascape.org was used for the gene ontology of the upregulated genes. Here the GO bio (Joslyn et al., 2004) and TRRUST (Han et al., 2018) software was used.
IFN-y stimulation and immunofluorescence staining of LNSCs by confocal microscopy
Glass cover slips were placed into a 24 well plate. Per condition 10000 cells were seeded, and the cells were let to attach onto the coverslip overnight. The experiment had 2 conditions, unstimulated and stimulated with 50ng/ml of INF-y in DMEM complete culture medium for 72h. During the 72h the cells were kept in the incubator at 5% CO2 and 37 °C
Immunofluorescence staining for confocal microscopy
For the Immunofluorescence staining , medium was removed using the aspirator. The cover slip is then washed with 500ul PBS for 3min and then removed by the aspirator. For the fixation, 200 ul 4% PFA in PBS has been added for 15 minutes at room temperature (RT). And is then washed two times in PBS for 5 minutes again. For the blocking and permeabilization 200 ul PBS + 3% BSA + 0.3% Triton has been added for 30 minutes at RT. After washing for 3x of 5 min with 500ul PBS per time, the incubation with the first antibody with 200 ul (anti-human HLA-DR 1:100, Biolegend) has been done overnight. PBS + 1% BSA + 0.3% Triton + antibody has been added. After washing for 3x of 5 min with 500ul PBS per time, 150ul of the secondary antibody (1:400) in a mixture of PBS/BSA(1%)/Triton (0.3%)/NHS(10%) is added and incubated for 30 min at RT. After washing and drying, the slides are covered with 10 ul mounting medium Vectashield hardset and are then dried overnight and then put in a cold room ready for the confocal analysis. Images were taken with the White Light Laser Confocal Microscope Leica TCS SP8 X. The 3D images were generated with stack images of 0.15 nm. Leica microsystem LAS X software is used for the analysis of the images.
Lymph node digestion
The stromal tissue is put in a sterile tube and 3 ml out of the total 9 ml of pre-warmed digestion medium has been added. Then the tube is placed in a 37 °C water bath and shaken every 5 minutes. The tissue is then disrupted after 15 minutes by aspirating and expirating 5 times using a 1ml pipet. After the disruption and when the large fragments have settled, the supernatant is poured in a 100um strainer and collected in 20 ml ice-cold PBS, 2% FCS, 5mM EDTA and being centrifuged at 1138 rpm. Another 3 ml digestion-mix has been added to the remaining fragments and incubated in a warm water bath. The steps described above are repeated for 2 more times for a total of 45 minutes. The supernatant is then re-suspended and 1 ml DNEM 10% is added to perform a cell count at the Burker-turk chamber.
To make the right amount of Dispase II, the complete volume is dissolved in 100 ml Hepes-buffered saline containing 50mM Hepes and 150mM NaCl to get a 10mg/ml concentration. This is filtered through a 0.22 µM filter. When using 10 mg/ml 240 ul/ml of digestion medium is needed.
The Dnase is dissolved into water, for both Dnase grade I and II a solution of 100 mg/ml is made. For grade I the solution is further diluted to 10 mg/ml, when using 10 mg/ml, 30 µl/ml of digestion medium is needed. For grade II (100 mg/ml) a digestion medium of 10µl/ml is needed. It is dissolved in RPMI 1640 and when using a 100 mg/ml solution a 6 µl/ml digestion medium is needed.
For the LN stop buffer a mixture with concentration of 2% FCS and 5mM EDTA is needed. Finally, RPMI 1640 without L-glutamine is added.
Flowcytometry sorting
After the digestion of the biopsy according to the protocol “Digestion of adult human lymph nodes adapted for needle biopsy”, the volume required for flowcytometry analyses is calculated. Then the cells were washed with 2 ml PBS + 5% FCS and centrifuged 1500 rpm for 3 minutes, the PBS + 5% FCS is divided over the different 5ml FACS tubes. After that, 100 ul single-colour of the unlabelled CD31-PDPN+ (1:100, Angiobio, with as clone NC-08, B235057) and isotype antibody were incubated for 1 hour at 4 °C in the dark. The cells were then washed again in 2 ml PBS + 5% FCS and centrifuged at 1500 rpm for 3 minutes long. 500 ul of colour mix is added in the mix tube, including the secondary of the CD31-PDPN+ (1:200). The cells are resuspended in 350 ul of PBS + 5% FCS cell suspension and the measured at FACS ARIA. The cells are then collected in PBS + 50% FCS. After sorting the cells are spun for 5 min at 1500rpm, the supernatant is carefully removed on a tissue and the tube in gently tapped on the tissue. Finally, the cells are resuspended in 350 ul of RTL buffer.
The other antibodies used were; CD31, (Biolegend, AlexaFluor488, clone; WM-59, B245699) HLA-DR (eBiosciences, PE, clone; L243, 1995352) and CD45 (eBiosciences, eFluor450, clone; HIR2, 1987940)
Glossary
Collagenase P is a mixtures of enzymes used for disaggregation of tissues. Dispase II is a protease, splitting the fibronectin and collagen.
Dnase I is an endonuclease that splits the phosphodiester bonds, and therefore hydrolyzing the DNA
strands.
DMEM: is a medium used for cell growth. RPMI 1640 is a medium used for cell growth.
Confocal Microscopy: A technique for increasing optical resolution and contrast of the micrograph. It makes multiple two-dimensional images at different depth so a three-dimensional structure can be made.
ScRNA seq is a way to reveal the presence and quantity of RNA of a biological sample. FACS sorter sorts cell populations by the presence or absence of a specific characteristic. R language is a programming language used for data analysis.
Results
The confocal images were used to investigate where in the cells the HLA-DR was located. The experiment has 3 conditions: stimulated with IFN-y, unstimulated and isotype. Several stimulated cells showed that they contain HLA-DR (Figure 3) These 2D images show that stimulated LNSCs express HLA-DR throughout the whole cell.
Whereas the unstimulated cells are negative for HLA-DR, on the image only the nuclei can be detected. (Figure 4) Similarly in the isotype control cells only their nuclei is shown in the confocal images (Figure 5). But, there are differences in the density of the HLA-DR throughout the cell. To explore the intracellular compartment, a stack of images were taken to generate 3D images and a video. The top (0 um) and bottom (2um) of the cells are comparable to each other and revealed high HLA-DR intensity (Figures 6 & 7). This indicates that the HLA-DR is expressed throughout the cells compartments of the cell but the amount expressed is variable.
Figure 3. Confocal images stimulated cells.
Figure 4. Confocal images of Isotype control cells.
The images (60x) show that no HLA-DR is being expressed in the cells and only the nuclei are visible (shown in blue)
Figure 5. Confocal images of the unstimulated cells.
The images (60x) show that no HLA-DR is being expressed in these cells. Only the nuclei of the cells are visible (shown in blue)
Figure 6. Confocal image of stimulated cells.
In the image (60x) HLA-DR is colored accordingly to the legend in the right top corner. The scale indicates that the depth of the cell in a cross section. The depth of the cell from the top 0um to the bottom 2um.
Figure 7. Confocal image of stimulated cells.
In the image (60x) HLA-DR is colored accordingly to the legend in the right top corner. The scale indicates that the depth of the cell in a cross section. The depth of the cell from the top 0um to the bottom 2um.
HLA-DR- have different genes expressed compared to HLA-DR+
Using single cell RNAseq, the genes expressed in HLA-DR- and HLA-DR+ LNSCs are investigated. In this research the genes upregulated and genes downregulated were compared between sorted HLA-DR- cells and the HLA-DR+ cells.
A volcano plot is utilized to observe the genes that are significantly differentially expressed (p<0.05) with a fold difference cutoff of 1.5 (figure 8). The fold change cutoff is for the genes being more expressed in one sample compared to the median expression of all the genes. Besides just creating a volcano plot for the expressed genes, using scRNA seq and Genecrd.org lists of genes with their function and localization in the cell were created (tables 1 &2). These tables either represent 20
upregulated genes or 20 downregulated genes. In addition, the violin plot for genes PLVAP, CLEC14A and PECAM1 indicate upregulated expression in HLA-DR+ cells while CALD1, FXYD1 and S100A4 are downregulated (Figure 9). Moreover, the upregulated genes were depicted in a heatmap showing their exclusive expression in HLA-DR+ cells. (Figure 10)
The Volcano plot shows that the genes expressed on the left side in red are the genes downregulated in HLA-DR- compared to the HLA-DR+. The genes expressed on the right side of the volcano plot are the genes that are upregulated in the HLA-DR+.
A couple of the downregulated genes are; TAGLN, IGFBP5, ACTA2,CCL19 and CC21. (Table 1) All these genes have different functions. As shown in table 1, ACTA2 has a function in vascular contractility and blood pressure homeostasis and is located in the actin filaments (Rockey et al., 2013). Another gene that is downregulated in HLA-DR- and represented in table 1 is IGFBP5, this gene inhibits or
stimulates growth promoting effects of the cell and can be found in the Golgi apparatus (Dong et al., 2020). In addition, CALD1, FXYD1 and S100A4 are all 3 located in the cell membrane. CALD1 is involved in actin binding and myosin binding (Huber et al., 1993), FXYD1, inhibits the activity of NKA when unphosphorylated and activates its activity when in a phosphorylated state. (Mishra et al., 2015)
The HLA-DR+ cells have other genes upregulated compared to HLA-DR-, some of these genes are; HLA-DPA, HLA-DPA1 PECAM1, CLEC14A, PLVAP and IFI27. HLA-DPA, HLA-DPA1 (Table 2) both have the function to be expressed on APCs and present the antigens on the CD4-postive T cells and these 2 genes are located in the cell membrane (Mardian et al., 2017). IFI27 is involved in cell apoptosis and is induced by type I-interferon (Hsieh et al., 2015). In addition, IFI27 is characterized by a quick release of cytochrome C and therefore can be located in the cell membrane of the mitochondria (Wang et al., 2018). PLVAP is involved in the formation of diaphragms that bridge endothelial
fenestrae and is localized in the cell membrane (Auvinen et al., 2019). PECAM1 is associated with the adhesion function needed for TEM and is also important for the lateral border recycling compartment (Etich et al., 2013). This gene can be found in the cell membrane. As well as PECAM1 the CLEC14A can be found in the cell membrane, but encodes a member of the C-type lectin/ C-type lectin like domain superfamily (Lee et al., 2017).
These results show that HLA-DR+ cells have other genes upregulated compared to HLA-DR- cells and that both cell types have different genes expressed.
Figure 8. Differentially expressed genes in HLA-DR+ vs
to the HLA-DR+ (genes shown at the right). The genes found significant and being more expressed than the other genes are represented with the color red. The genes found significant enough but not having a FC cutoff of 1.5 are shown in blue.
Figure 9. Violin plot of 3 downregulated and 3 upregulated genes in HLA-DR+ cells.
Using a violin plot, the genes PLVAP, CLEC14A and PECAM1 are shown to have a positive expression compared to the CALD1, FXYD1 and the S100A4 gene that are negatively expressed in HLA-DR+ cells.
Figure 10. Heatmap of the upregulated genes in HLA-DR+ cells
The expression of the represented genes is shown in HLA-DR- cells and HLA-DR+. The genes are known to be upregulated in HLA-DR+ cells and are shown to have an upregulated expression in HLA-DR+ cells.
Table 1. 20 downregulated genes in HLA-DR- cells.
The genes are represented together with their function and the compartment they are located in. these genes are significantly expressed (P<0.05) together shown with the average logFC and adjusted p-value based on _ogether_i correction using all features in the dataset. The percentage of cells where the feature is detected in the first group shown in the pct.1 and The percentage of cells where the feature is detected in the second group represented with pct.2
gene function compartment p_val avg_logFC pct.1 pct.2 p_val_adj
IGKC Protein coding gene and included inantigen binding membranecell 0,00E+00 12.647.1 -07 0,97 0,99 9 0,00 E+0 0 LGALS
1 plays a role in regulating apoptosis, cellproliferation and cell differentiation cytoplasm 0,00
E+0 0 -14.666.4 19 0,38 8 0,877 0,00 E+0 0
CALD1 actin binding and myosin binding membranecell 0,00E+00 15.031.9 -29
0,56
8 0,935 0,00
E+0
0
IGFBP5 inhibits or stimulates growth promotingeffects of the cell apparatusgolgi 0,00E+00 16.854.9 -12
0,16
4 0,825 0,00
E+0
0
MYL9 cell locomotion, receptor capping andcytokinesis nucleoplasm 0,00E+00 22.065.0 -23
0,28
5 0,81 0,00
E+0
0
TAGLN early marker in smooth muscle cells
microtubul es, mitochond ria 0,00E+0 0 -22.130.5 70 0,24 4 0,867 0,00 E+0 0
TPM2 important role in calcium dependentregulation of muscle contraction cytoplasm 4,22292E- 20.844.9 -09
0,22
7 0,771 1,42
E
-287
FTH1 stores iron, ready for imediate use,important for iron hemeostasis microtubules 1,36276E- 0,83680 -38
0,94
1 0,982 4,55
E
-272
MT2A MT2A has a high content of cysteineresidues that bind heavy metals cytoplasm 2,35249E- 14.199.1 -84
0,31
3 0,773 7,88
E
-245
ACTA2 vascular contractility and blood pressurehomeostasis filamentsactin 5,14234E- 21.872.4 -24
0,14
9 0,663 1,72
E
-229
PLAC9 is a transcriptional respressor, it repressesIL-2 gene expression nucleus 6,68216E- 13.807.1 -35
0,27
9 0,708 2,24
E
-211
CPE it removes the dibasic residues from the c-terminal side after endoprotease cleavage nucleoplasm 1,20214E- 12.861.2 -40 0,12 8 0,654 4,02 E -210 IGLC2
when an antigen binds it will trigger the clonal expansion and maken B-lymfocytes differentiate into immunoglobins-secreting plasma cells cell membrane 1,03 E -210 -0,82530 33 0,85 2 0,94 3,45 E -206 C11orf 96 - nucleoplasm 2,32 E -209 -16.745.6 54 0,22 6 0,684 7,80 E -205 IGLC3
when an antigen binds it will trigger the clonal expansion and make B-lymfocytes differentiate into immunoglobins-secreting plasma cells cell membrane 8,82 E -200 -10.658.8 19 0,50 5 0,804 2,96 E -195
FXYD1 when NKA are in an unphosforylated state,it inhibits its activity and when in a phosforylated state it activates its activity
cell membrane 7,25 E -196 -12.939.9 48 0,07 7 0,565 2,43 E -191 NR2F2
Ligand-activated transcription factor that binds to the DNA a site and may be required for angionesis and heart development nucleus 1,63193E- 10.090.3 -39 0,54 2 0,835 5,48 E -189
PRRX1 acts as transcriptional regulator of musclecreatine kinase nucleus 1,52188E- 12.072.2 -89
0,10
3 0,598 5,09
E
-184
-properties of cancer cells, cell cycle
progression and intercellular adhesion membrane 188 14.421.822 9 2 183
TPM1 important role in calcium dependentregulation of muscle contraction cytoplasm 3,35184E- 16.614.7 -63
0,41
1 0,722 1,12
E
-179
Table 2. 20 upregulated genes in HLA-DR+ cells.
The genes are represented together with their function and the compartment they are located in. these genes are significantly expressed (P<0.05) together shown with the average logFC and adjusted p-value based on _ogether_i correction using all features in the dataset. The percentage of cells where the feature is detected in the first group shown in the pct.1 and The percentage of cells where the feature is detected in the second group represented with pct.2
gene function compartment p_val avg_logFC pct.1 pct.2 p_val_adj
HLA-DRB1
Presents MHCII together with HLA-DRA, it displays antigenic peptides on APCs for recognition for the HLA-DRB1-restricted CD4-positive T cells. This causes specific T helper effector function and anti-body mediated immune response together with macrophage activation
cell membrane 0 30.629.75
8 0,919 0,022 0
CD74 Serves as a cell surface receptor in MHC II antigenprocessing and it transports the complex from the
endoplasmatic reticulum to the lysomal system cell membrane 0
28.955.45
5 0,938 0,078 0
IFI27 Involved in cell apoptosis, by type I-interferoninduced. Characterized by a quick release of cytochrome C
mitochondrion
membrane 0 26.303.136 0,826 0,054 0
HLA-DRA the endocytic route of APC and present them on theBinds peptides that derive from antigens that acces
surface of CD4-positive T cells cell membrane 0
25.569.29
2 1.000 0 0
ACKR1
A chemokine receptor that is uncoupled from the classic ligand-driven signal transduction cascade, resulting in chemokine sequestration, degradation or trancytosis
endosome 0 22.420.493 0,511 0,012 0
AQP1 Forms water-specific channels that allow water to
move into the osmotic gradient cell membrane 0 21.672.405 0,732 0,025 0
VWF important in the homeostasis; promotes adhesion ofblood platelets extracellularmatrix 0 20.626.284 0,779 0,029 0
SOX18 Transcriptional activator that plays an important rolein embryonic cardiovascular development and
lymphangiogenesis nucleus 0
20.227.29
9 0,786 0,036 0
HLA-DPA1
Binds peptides that derive from antigens that acces the endocytic route of APC and present them on the
surface of CD4-positive T cells cell membrane 0 20.089.764 0,807
0,05
2 0
PLVAP involved in the formation of diaphragms that bridgeendothelial fenestrae cell membrane 0 19.803.429 0,707 0,007 0
CLEC14A Encodes a member of the C-type lectin/ C-type lectinlike domain superfamily cell membrane 0 19.628.466 0,752 0,018 0
GIMAP7 GTPase activity cytoplasm 0 17.752.001 0,765 0,032 0
EGFL7 Promotes endothelial cell adhesion to extracellularmatrix and regulates vascular tubulogenesis extracellularmatrix 0 17.670.326 0,846 0,063 0
RBP7 Intracellular transport of retinol cytoplasm 0 17.612.05
6 0,612 0,006 0
PECAM1 Adhesion function need for TEM is also important forthe lateral border recycling compartment cell membrane 0 17.346.571 0,8 0,049 0
CLDN5 Obliterates the tight-junctions of the intracellularspace junction/cellcell
membrane 0
16.701.49
9 0,738 0,06 0
2 2
GNG11 Modulator or transducer in various transmembranesignaling systems cell membrane 0 16.116.586 0,857 0,275 0
LIFR Signal transduction molecule cell membrane 0 15.940.766 0,757 0,124 0
EMCN Interferes with the assembly of focal adhesion andinhibits interaction between cells and the
extracellular matrix cell membrane 0 15.772.280 0,664
0,01
8 0
Gene ontology of enrichment pathway showing cytokine-mediated signaling pathway the most involved
In order to investigate what pathways are involved in observed upregulated genes, a gene ontology of enrichment pathways was used. The most common pathway the genes are involved is the cytokine-mediated signaling pathway followed by the angiogenesis pathway, cytokine binding and platelet activation, signaling and aggregation pathway (Figure 11). 8 of the 20 genes are involved in the cytokine-mediated signaling pathway, 6 in the angiogenesis pathway, the cytokine binding and platelet activation, signaling and aggregation each have 3 genes involved. (Table 3)
In addition, the transcription factors RFXAP,RFXANK and RFX5 are involved with these genes as well (Figure 12). This means that the cytokine-mediated signaling pathway is the most involved pathway in the upregulated genes with RFXAP, RFXANK and RFX5 as transcription factors.
Figure 11. Bar graph of enriched terms across input gene lists, colored by p-values
The functions of the 20 upregulated genes in what pathway they are involved.
Table 3. Top 4 clusters with their representative enriched terms (one per cluster).
“Count” is the number of genes in the user-provided lists with membership in the given ontology term. “%” is the
percentage of all of the user-provided genes that are found in the given ontology term “Log10(P)” is the p-value in log base 10. “Log10(q)” is the multi-test adjusted p-value in log base 10.
Figure 12. Summary of enrichment analysis in TRRUST.
The transcription factors that are shown that are involved in the different upregulated genes.
Discussion
The results have shown that LNSCs express HLA-DR all over in the cell but the amount in which it is expressed is variable throughout the cell. In addition, HLA-DR+ cells have genes downregulated, some of these genes are TAGLN, IGFBP5, ACTA2, CALD1, FXYD1 and S100A4 compared to DPA, HLA-DPA1, HLA-DPB1, PLVAP, CLEC14A, PECAM1, SOX18 and IFI27 which are upregulated in HLA-DR+ cells. Therefore, there can be concluded that HLA-DR+ and HLA-DR- cells have differentially expressed genes. In addition, the upregulated genes show that most of them are involved in cytokine-mediated signaling pathway and they are regulated by the transcription factors RFXAP, RFXANK and RFX5. These findings indicate that HLA-DR+ cells have differentially expressed genes compared to HLA-DR- cells. This upregulation of HLA-DR only happened in the stimulated cells and not the unstimulated. The unstimulated cells therefore showed the same phenotype as the isotype control cells. The genes upregulated and downregulated that were significant enough and having a fold change of 1.5 were shown in the volcano plot (figure 8). However, not all of these genes shown there were represented in tables 1 and 2. This can be explained due to the number of genes that were upregulated and downregulated, tables 1 and 2 only show 20 genes each. The gene CALD1 is downregulated compared to the HLA-DR+ cells but is shows an expression in HLA-DR+ cells as well (Figure 9). However, in the table of the upregulated genes (Table 2) it is not significant at all whereas it is significantly downregulated compared to the HLA-DR+ cells. One of the limitations of this study is that only the transcription factors are of upregulated genes are shown. So the transcription factors that regulate the downregulated genes still need to be investigated. However, using the same analysis as done for the upregulated genes, these transcription factors can be found as well.
Earlier research has proven that PD-1/PD-L1 is a marker for HLA-DR+ cells in a mouse model (Hirosue & Dubrot 2015). In addition, Hirosue & Dubrot 2015 also have shown that PLVAP is important for size-based filtration of antigens in the lymph node. And that this size-exclusion important is during an inflammation. The current results have shown that PLVAP is upregulated in the HLA-DR+ cells and is therefore important to the immune response of the body. Moreover, the activation of the CD4+ T cells by antigens goes through MHC-II expression. (Nadafi et al., 2020) This is in agreement with the function of the upregulated genes; HLA-DPA, HLA-DPA1 and HLA-DPB1. These genes are seen to be upregulated in HLA-DR+ cells (Figure 8 & Table 2). Finally, Kampstra & Toes 2017 have found that alleles such as HLA-DR4 and HLA-DR1 can be associated with RA. However, it can be that it is not the cause of RA but just a reaction of the body to upregulate these genes. It seems that HLA-DR is located
in a spherical-shaped structure. Based on previous studies of Münz 2010 it is speculated that this structure reflects lysosomal-like structure.
The current results show what transcription factors might be involved, and what genes are upregulated and downregulated in HLA-DR+ LNSCs. Hence, a follow up research could focus on finding a gene that is downregulated that can be upregulated to make the cells HLA-DR+ and
investigate further and what transcription factor regulate these genes. Furthermore, the genes found in the cell membrane can be used for sorting them to further analysis. In addition, the speculation that the spherical-shaped structure reflects lysosomal-like structure is not confirmed yet and it is suggested to intracellularly quantify HLA-DR expression to gain insights in its function in LNSCs. Concluding, the gene expression of HLA-DR+ and HLA-DR- is clear. Although, more research needs to be done to investigate whether the genes can regulate HLA-DR expression and if antigen presentation via LNSCs can be modulated.
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