Analysis of an antioxidative defence system of hydrogen peroxide-treated pancreatic islet-derived 1.1B4 cells and siRNA targeting NR4A3-treated cells by microarray

ABSTRACT

Pancreatic islet β-cells weaken under oxidative stress. In this study, human pancreatic islet-derived 1.1B4 cells were exposed to H₂O₂ and analysed using a human microarray, which revealed that heme oxygenase 1 (HMOX1), glutamate-cysteine ligase, early growth response 1, nuclear receptor subfamily 4 group A member 3 (NR4A3) and jun B proto-oncogene were upregulated, whereas superoxide dismutase 1 and catalase were not. Expression of NR4A3 rapidly increased after H₂O₂ addition, and the 1.1B4 cells treated with siRNA targeting NR4A3 became sensitive to H₂O₂; further, HMOX1 expression was strongly inhibited, suggesting that NR4A3 is an oxidative stress-responsive transcription factor that functions through HMOX1 expression in pancreatic islet β-cells. Expression of cyclin E1 and cyclin-dependent kinase 1 was also inhibited by siRNAs targeting NR4A3.

GRAPHICAL ABSTRACT

KEYWORDS:

• Pancreatic β-cells
• oxidative stress
• microarray
• HMOX1
• NR4A3
• siNR4A3
• transcription factor
• CDK2

Introduction

Methods for restoring the decline in β-cells frequently observed in type 2 diabetes are needed [1]. Elevated glucose concentrations have been suggested to increase the levels of reactive oxygen species (ROS) in β-cells [2]. Chronically high ROS levels can decrease insulin gene expression and accelerate apoptosis [2, 3]. Pancreatic β-cells are more sensitive to oxidative stress than other cells because these express antioxidant enzymes at a lower level than other cells [2]. However, the effect of oxidative stress on β-cells is not well understood [4].

High oxidative stress induces cell damage in several cell types. The regulatory mechanisms by which H₂O₂ modulates transcription factors are summarised in a review [5], which reported that many sensing proteins and oxidants regulate transcription factors to induce apoptosis. Oxidative stress also induces the expression of heme oxygenase-1 (HMOX1) that acts as an antioxidant defence system [6].

We previously found that oxidative stress induced by H₂O₂ increased the expression of the nuclear receptor subfamily 4, Group A member 1 (NR4A1) and NR4A3 genes in HUC-F2 fibroblasts, and that inhibition of NR4A1 with specific siRNA triggered an increase in apoptosis following the addition of H₂O₂ [7]. The NR4A orphan nuclear receptor family of transcription factors is rapidly and strongly upregulated following exposure to stressful stimuli [8]. Lee et al. [9] and Volakakis et al. [10] reported that expression of NR4A genes is modulated by oxidative stress.

In this study, we aimed to analyse gene expression in β-cells in response to ROS using H₂O₂ and human pancreatic β-cell-derived hybrid cells (1.1B4 cells). We analysed the effect of H₂O₂ on the expression of genes in 1.1B4 cells using a human microarray. We also analysed the expression of genes in NR4A3 siRNA-treated cells to determine the effect of decreased NR4A3 mRNA on the expression of genes in 1.1B4 cells.

Materials and methods

Microarray and software

Whole Human Genome Oligo Microarray Kit 4 × 44 K ver. 2.0, Feature Extraction Software 9.5.1.1 (Agilent Technologies, Palo Alto, CA, USA), GeneSpring GX10 v 7.3.1 (Agilent Technologies), and Spotfire software (TIBCO, NTTCom, Tokyo, Japan) were used.

Biological Resources: human pancreatic islet-derived cells (1.1B4 cells)

Cells of 1.1B4 (ECACC No. 10012801) [11], a hybrid of normal human islet cells and transformed PANC-1 cells, were obtained from DS Pharma Biomedical Co. Ltd., Osaka, Japan.

Cell culture of 1.1B4 cells and RT–qPCR

The 1.1B4 cells were cultured in RPMI-1640 medium. Cell viability was analysed using an MTT assay [12]. Total RNA was extracted using Isogen [13] or RNeasy Mini Kit. The expression was measured using RT-qPCR. The procedures are described in detail in the Supplemental Material and Supplemental Table S1.

RNA interference of NR4A3

NR4A3 Silencer Select siRNA was used according to the ABI protocol, with Silencer Select Negative Control #1 siRNA and nuclease-free water (NFW) (ABI) as negative controls. The efficiency was measured by RT-qPCR. The procedures are described in detail in the Supplemental Material.

Analysis of gene expression in 1.1B4 cells by microarray

Experiment A: H₂O₂ treatment

B4 cells (n = 12) were seeded at 1.5 × 10⁵ cells/ml in the microplate (Agilent Technologies), and 24 h later, six wells were incubated with 100 µM H₂O₂ for 4 h (H₂O₂ treated group). Total RNA was extracted from the 12 wells using the RNeasy Mini Kit according to the manufacturer’s instructions. The quality of the 12 RNA samples was assessed, and an aliquot of three RNA samples from the same group was combined into one microarray sample, resulting in a total of two microarray samples for the H₂O₂ treated group and two for the control group. The four samples were analysed using a human microarray according to the manufacturer’s protocol. After reading, one control microarray was scratched; the expression was compared to the average of two treated array samples and one control. The 12 RNA samples were also used individually for RT-qPCR. (See supplemental Fig. S7)

Experiment B: siNR4A3 treatment

The 1.1B4 cells (n = 22) were incubated for 24 h. Half (n = 11) were treated with siNR4A3, and the other half (n = 11) were treated with NFW. Forty-eight hours later, cells in two wells from each group were treated with 100 µM H₂O₂ for 2 h. After 24 h, mRNA was purified. Aliquots of three RNA samples without H₂O₂ were combined into one microarray sample (three siRNA-treated and three control) and subjected to microarray analysis, as described for experiment A. Aliquots of two RNA samples from the H₂O₂-treated group were also combined and analysed (n = 2, siRNA-treated H₂O₂-treated sample and siRNA-treated without H₂O₂ treatment). For RT-qPCR, 22 RNA samples were used individually. (See supplemental Fig. S7)

Statistical analysis

Student’s t-test, ANOVA with Tukey’s HSD post hoc test, and pairwise t-test (R Core Team; R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria; 2017 URL https://www.R-project.org/) were used.

Results

Effect of H₂O₂ on 1.1B4 cell growth and gene expression analysed by DNA microarray

Human 1.1B4 cells were exposed to 0, 10, 20, 30, 40, 50, 100 or 200 µM H₂O₂, and cell viability was measured using the MTT assay (Supplemental Fig. S1). We observed no toxicity in response to H₂O₂ up to 50 µM; growth was limited at 100 µM H₂O₂ and was completely suppressed at 200 µM. Therefore, to investigate the antioxidant system, 1.1B4 cells were treated with 100 µM H₂O₂ and analysed using a human microarray. The results were submitted to the Gene Expression Omnibus (GEO) database of NCBI (accession number GSE83369). (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE83369). A total of 2903 genes were upregulated by more than two-fold in untreated cells, and 2283 genes were downregulated by less than half. Most genes were classified as unknown or others, and genes classified as nucleotide metabolism-related comprised the major group (Table 1, Supplemental Fig. S2, S3). The expression of several genes was confirmed using RT-qPCR (Table 1, Figure 1). The expression ratio of the antioxidant enzyme HMOX1 (Figure 1(b)) was high and upregulated; however, those of SOD1 and CAT (Figure 1(a)) remained unchanged, and their relative expression was considerably lower than that of HMOX1. In contrast, the levels of peroxide-reducing GPX1 and the antioxidant enzyme GCLC were increased, but their expression ratio was low. Among the antioxidant pathways [5,6], the levels of KEAP1 (Figure 1(d)), CREB, HSF, HIF1, TP53, NF-κB and SP1 were unchanged. Among the transcription factors upregulated by H₂O₂ (Marinho et al. [5]), FOSB (Figure 1(c)), and JUNB were strongly upregulated, suggesting that the AP-1 pathway was upregulated. Insulin was downregulated, and the apoptosis marker caspases were upregulated. Many genes whose functions are unknown were upregulated or downregulated. Among these, NR4A3, an orphan receptor, was significantly upregulated (Figure 1(e)). Considering this result, we measured the effect of H₂O₂ concentration on NR4A3 expression (Figure 2(a)). The NR4A3 gene was significantly upregulated by H₂O₂ (used at a concentration of 100 µM for 4 h) (Figure 2(b)). Interestingly, this expression rapidly increased and then decreased to its original levels by 24 h, suggesting that NR4A3 is an early responder to H₂O₂ stress. To further investigate the role of NR4A3, we treated 1.1B4 cells with siRNA targeting NR4A3 followed by H₂O₂ treatment, and then measured cell viability. The treatment of 1.1B4 cells with siRNA decreased cell viability, which was strongly inhibited by the addition of H₂O₂ after siRNA treatment (Figure 3).

Figure 1. Effect of H₂O₂ addition on expression of various genes. A. Human 1.1B4 cells were treated with H₂O₂ as described in Table 1 and Supplemental Material. For RT-qPCR analysis of CAT under Condition A described in the Supplemental Material, 12 RNA samples from the two groups obtained for microarray were used, and the value obtained was the expression ratio to GAPDH expression. (* indicates a significant difference of p < 0.05 by t-test). B-F. Levels of HMOX1, FOSB, KEAP1, NR4A3, and EGR1, respectively, were measured.

Figure 2. Effect of H₂O₂ concentration on NR4A3 gene expression and time course of expression. A. Human 1.1B4 cells (1.0 × 10⁵ cells/ml) were incubated in 2 ml of culture medium, and 24 h later, the medium was changed to individual concentrations of H₂O₂-containing medium. After 4 as well as 24 h, total RNA was extracted using Isogen reagent. The expression of NR4A3 was measured by RT-qPCR under Condition B (n = 3) described in the Supplemental Material. B. After addition of 100 µM H₂O₂, the cells were incubated for various time periods and RNA was extracted (n = 3). ß-Actin was used as a control. (* p < 0.05, ** p < 0.01).

Figure 3. Effect of siRNA targeting NR4A3 on cell viability. A. After addition of siNR4A3 to 1.1B4 cells, total RNA was extracted and expression of NR4A3 was measured by RT-qPCR using the Cyber green method under Condition B described in the Supplemental Material (n = 3; * p < 0.05). B. After addition of siNR4A3, the 1.1B4 cells were incubated with 100 mM of H₂O₂, and cell viability was measured by MTT assay (n = 5). NFW: nuclease free water-added cell; siNR4A3: siRNA of NR4A3-treated cell.

Table 1. Comparison of the expression between H₂O₂-treated 1.1B4 cells and control cells using microarray and RT-qPCR.

Gene Symbol	Gene Name	Expression ratio by Microarray (H2O2/Controll)	Relative Expression ratio to GAPDH by RT-qPCR(H2O2/Controll)	Fold changes by H2O2 measured by RT-qPCR(H2O2/Controll)
Antioxidant Responsible Enzyme
HMOX1	heme oxygenase (decycling) 1	4.73	0.379/0.204	1.86*
SOD1	superoxide dismutase 1, soluble	1.23	0.0026/0.0028	0.93
SOD2	superoxide dismutase 2, mitochondrial	1.17	0.029/0.023	1.23
SOD3	superoxide dismutase 3, extracellular		0.00007/0.00004	1.72*
CAT	Catalase	0.84	0.022/0.023	0.97
GPX1	glutathione peroxidase 1	1.87	0.024/0.022	1.09
GCLC	glutamate-cysteine ligase, catalytic subunit	2.27	0.043/0.019	2.18*
Antioxidant responsibleTranscription Factor
FOSB	FBJ murine osteosarcoma viral oncogene homolog B	853.8	0.0543/0.0009	63.93*
JUNB	jun B proto-oncogene	6.97	0.280/0.087	3.23*
NFE2L2	nuclear factor (erythroid-derived 2)-like 2 (NRF2)	1.65	0.131/0.078	1.67*
KEAP1	kelch-like ECH-associated protein 1	0.98	0.0089/0.074	1.21
CREB1	cAMP responsive element binding protein 1	1.18
HSF1	heat shock transcription factor 1	0.92
HSPA1A	heat shock 70kDa protein 1A	13.47
HIF1A	hypoxia inducible factor 1, alpha subunit	1.00
TP53	tumor protein p53	0.74
NFKB1(NF-κB)	nuclear factor of kappa light polypeptide gene enhancer in B-cells 1	0.87
NOTCH1	Notch homolog 1, translocation-associated	0.54
SP1	Sp1 transcription factor	1.06
SREBF1	sterol regulatory element binding transcription factor 1 (A_24_390784,SREB-1)	1.02
MAFF	v-maf musculoaponeurotic fibrosarcoma oncogene homolog F	15.25	0.028/0.003	8.27*
Othres
CYCS	cytochrome c, somatic	2.60	0.0038/0.0031	1.23
CIDEA	cell death-inducing DFFA-like effector a	9.54	0.00014/0.00011	1.25
OSGIN1	oxidative stress induced growth inhibitor 1	12.04	0.0331/0.0055	6.05*
RELA	v-rel reticuloendotheliosis viral oncogene homolog	1.36	0.0038/0.0025	1.50*
NR4A3	nuclear receptor subfamily 4, group A members 3	130.94	0.00176/0.00008	23.1*
MAOA	monoamine oxidase A	2.58	0.00002/0.00001	1.96*
NR4A1	nuclear receptor subfamily 4, group A, member 1	7.65	0.00061/0.00011	5.48*
CXCL3	chemokine (C-X-C motif) ligand 3	14.2	0.0062/0.0007	9.32*
GPR68	G protein-coupled receptor 68	6.34	0.00077/0.00042	1.84*
NFKBIA	nuclear factor of kappa light polypeptide gene enhancer in B-cells inhibitor, alpha	4.35	0.126/0.045	2.79*
TP63	tumor protein p63	39.02	0.00063/0.00037	1.72*
SEPP1	selenoprotein P, plasma, 1	10.17	0.00023/0.00010	2.22*
PMAIP1	phorbol-12-myristate-13-acetate-induced protein 1	9.93	0.0378/0.0077	4.88*
BTK	Bruton agammaglobulinemia tyrosine kinase	10.71	0.00080/0.00020	4.00*
IL8	interleukin 8	7.35	0.075/0.023	3.28*
EGR1	early growth response 1	77.6	0.254/0.011	22.97*
EGR2	early growth response 2	714
EGR3	early growth response 3	89.16
EGR4	early growth response 4	853.9
NQO1	NAD(P)H dehydrogenase, quinone 1	0.86	0.0553/0.0442	1.25
DUOX2	dual oxidase 2	37.37
BAX	BCL2-associated X protein	2.16
RAB5B	RAB5B, member RAS oncogene family	2.47
FIGF	c-fos induced growth factor (vascular endothelial growth factor D)	46.66
INS	Insulin	0.023
CASP10	Homo sapiens caspase 10	11.13
CASP3	caspase 3	1.63
CASP6	caspase 6	1.35
CASP9	caspase 9	1.87
CASP8	caspase 8	1.46

The average of two microarray datasets for H₂O₂-treated cells was compared to one microarray dataset for control cells after normalisation (Experiment A). For RT-qPCR analysis under Condition A described in the Supplemental Material, 12 RNA samples from two groups obtained for microarray were used, and the value was the expression ratio to GAPDH expression. * p < 0.05.

Comprehensive gene expression analysis of 1.1B4 cells treated with siRNA targeting NR4A3 by DNA microarray

Next, we performed a comprehensive gene expression analysis of 1.1B4 cells using a human microarray after treatment with siRNA targeting NR4A3. The data were submitted to the GEO database of NCBI under the accession number GSE86924 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc = GSE86924). We found that 1,044 genes were significantly upregulated by more than 1.5-fold, and 859 genes were significantly downregulated by less than 0.67-fold (Supplemental Fig. S4A, B, Supplemental Table S2). Changes in the expression of antioxidant enzymes, transcription factors related to H₂O₂ addition [6], and several well-known genes are listed in Table 2. Some of these results were confirmed by RT-qPCR (Table 2, Figure 4, Supplemental Fig. S5). NR4A3 expression was downregulated (Figure 4(a)), that of the orphan receptor NR4A1 was unchanged, whereas that of NR4A2 was upregulated. Among the genes encoding antioxidant enzymes, the expression of HMOX1 was decreased (Figure 4(b)). However, the expression of GCLC was only 0.88 times that of the control, and the expression of SOD1 was not significantly changed. We observed interesting gene expression responses of the antioxidant enzyme GLRX (Figure 4(c)); its expression increased in contrast to that of HMOX1. The expression of most of the redox-sensitive transcription factors was unchanged, except for that of FOSB and JUNB, which was unchanged after siRNA addition but increased after H₂O₂ addition, suggesting that the AP-1 pathway operates independently. The expression of these genes in siNR4A3-treated cells was very low after H₂O₂ addition (Figure 3). Among the cell cycle regulatory genes, the expression of CCNE1 (cyclin E) and CDK2 (Figure 4(d)) was markedly decreased, as was that of several cyclin-dependent kinases. Therefore, it can be suggested that NR4A3 has a negative effect on the mRNA levels of cell cycle genes, especially cyclin E1 and cyclin-dependent kinase 2, directly or indirectly, and may cause growth inhibition.

Figure 4. Changes in gene expression in response to NR4A3 siRNA treatment and H₂O₂ treatment measured by RT-qPCR. RT-qPCR conditions are described in Table 2 and Supplemental Material. A. NR4A3. B. HMOX1. C. GLRX. D. CDK2. E. EGR1. Pairwise t tests were used for the statistical analysis of post-hoc tests between NFW and siNR4A3 (* p < 0.05).

Table 2. Changes in gene expression in 1.1B4 cells in response to NR4A3 siRNA treatment and H₂O₂ treatment, measured by microarray and RT-qPCR.

Gene symbol	Gene name	Fold changes by Array (SiRNA vs Cont)	Fold changes by Array (H2O2 vs Cont)	Fold changes by Array (SiRNAH2O2 vs Cont)	Fold changes by RT-qPCR (*1)	Gene symbol	Gene name	Fold changes by Array (SiRNA vs Cont)	Fold changes by Array (H2O2 vs Cont)	Fold changes by Array (SiRNAH2O2 vs Cont)	Fold changes by RT-qPCR (*1)
Orphan receptor						Cell cycle
NR4A3	nuclear receptor subfamily 4, group A members 3	0.85	1.6591	0.74095	0.37/0.06/1.71/0.19	E2F1	E2F transcription factor 1	0.97958319	1.12980985	1.141726194	0.87/1.02/0.87/0.77
NR4A2	nuclear receptor subfamily 4, group A, member 2	1.06	0.876	1.08297	0.73/1.58/1.52/2.3	CDK1	cyclin-dependent kinase 1	0.7342	0.9287101	0.646039766
NR4A1	nuclear receptor subfamily 4, group A, member 1	*2	*2	*2	0.77/0.84/1.14/0.94	CDK2	cyclin-dependent kinase 2	0.34304	1.03735497	0.436884078	0.75/0.23/0.78/0.3
Antioxidant responsibleTranscription Factor						CDK4	cyclin-dependent kinase 4	0.87803	1.0117838	0.920232147
MAFA	v-maf musculoaponeurotic fibrosarcoma oncogene homolog A (avian)	0.75	0.6755	0.75858	1.08/1.2/1.29/1.08	CCNA1	cyclin A1	0.84123	0.83744297	0.707146026
FOSB	FBJ murine osteosarcoma viral oncogene homolog B	0.96	2.9993	2.5011	0.97/0.88/3.01/2.44	CCNB1	cyclin B1	0.72389	0.88577962	0.582131683
FOS	FBJ murine osteosarcoma viral oncogene homolog	2.5	0.9779	1.80732		CCND1	cyclin D1	0.99547	0.88648918	1.05860612
JUNB	jun B proto-oncogene	1.02	1.4355	1.51787		CCNE1	cyclin E1	0.44222	1.2919713	0.581768758	0.91/0.39/1.39/0.67
JUN	jun proto-oncogene	0.76	1.2467	0.81371		CCNE2	cyclin E2	0.637101422	1.24577989	0.791307492	0.79/0.68/1.05/0.81
KEAP1	kelch-like ECH-associated protein 1	0.93	1.1269	1.09478		CCNY	cyclin Y	0.62658	1.02418749	0.644597739
NFE2L2	nuclear factor (erythroid-derived 2)-like 2, NRF2	*2	*2	*2	0.58/0.65/0.55/0.74	CDKN1B	cyclin-dependent kinase inhibitor 1B (p27, Kip1)	1.66505	0.70956622	1.405834718	1.04/1.64/0.93/1.32
CREB5	cAMP responsive element binding protein 5	2	1.5404	2.92969		CDKN1B	cyclin-dependent kinase inhibitor 1B (p27, Kip1)	1.66505	0.70956622	1.405834718
TP53	tumor protein p53	0.83	0.9956	0.97902		E2F2	E2F transcription factor 2	0.666884557	1.37643782	0.824505781
NOTCH4	notch 4	1.36	1.0769	1.55379		Others
NFKB1	nuclear factor of kappa light polypeptide gene enhancer in B-cells 1	0.95	1.0955	1.01665	1.00/0.85/0.97/0.84	RAB5B	member RAS oncogene family (RAB5B)	0.54527	0.87891288	0.612490652	1.14/0.83/1.04/0.68
NFKB2	nuclear factor of kappa light polypeptide gene enhancer in B-cells 2 (p49/p100)	0.77	1.0345	1.03637		RAP1B	RAP1B, member of RAS oncogene family	0.58507	1.02444091	0.55639909
SP1	Sp1 transcription factor	0.8	1.1195	0.83924		TGFB3	transforming growth factor, beta 3	0.50684	0.99540181	0.550678484
HIF1A	hypoxia inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor)	1.02	1.0418	0.98372	1.03/0.89/0.80/0.80	PIK3CA	phosphoinositide-3-kinase, catalytic, alpha polypeptide	1.24095	0.9316925	1.152505273
SREBF1	sterol regulatory element binding transcription factor 1	0.76	0.8055	0.57008		MRAS	muscle RAS oncogene homolog	0.4872	0.96272673	0.443562902
HSF1	heat shock transcription factor 1	0.84	0.9991	0.81956		RAP1B	RAP1B, member of RAS oncogene family	0.59426	0.99096539	0.55447865
SREBF1	sterol regulatory element binding transcription factor 1 (A_33_P3222139,SREB-1)	0.8589	0.8814	0.90419		HIF1A	hypoxia inducible factor 1, alpha subunit (basic helix-loop-helix transcription factor)	0.91634	1.5215472	0.83361862
NFE2L2(NRF2)	NFE2 like bZIP transcription factor 2	*2	*2	*2		BAD	BCL2-associated agonist of cell death	0.65799	0.9593163	0.6394185	1.02/0.79/1.03/0.70
Antioxidant Responsible Enzyme
HMOX1	heme oxygenase (decycling) 1	0.4859	1.711	1.21016	0.88/0.6/1.25/0.98	BAD	BCL2-associated agonist of cell death	2.09416	0.92632348	2.145621727
GCLC	glutamate-cysteine ligase, catalytic subunit	0.8815	1.2798	1.16517	1.22/1.2/1.41/1.33	AKT1	v-akt murine thymoma viral oncogene homolog 1	0.85096	0.95129097	0.892481819
GPX1	glutathione peroxidase 1(A_33_P3239849)	0.8187	0.9689	0.8332	0.96/0.97/1.04/0.98	FOXO1	Homo sapiens forkhead box O1 (FOXO1), mRNA [NM_002015]	1.0298	1.057155	1.115007236	0.78/0.94/0.82/0.79
GPX1	glutathione peroxidase 1(A_33_P3354322)	0.8125	1.0124	0.79735		FOXO3	Homo sapiens forkhead box O3 (FOXO3), transcript variant 1, mRNA	1.08933	1.16739087	1.251716596	0.85/0.99/0.80/1.09
CAT	catalase	1.5963	1.0156	1.54531		SKP2	S-phase kinase-associated protein 2	0.618629347	0.97661	0.60886	0.88/0.94/0.49/0.4
SOD1	superoxide dismutase 1, soluble	0.8711	1.0016	0.85098		CDKN1B(p27Kip1)	cyclin dependent kinase inhibitor 1B	1.66505498	0.70957	1.40583
SOD2	superoxide dismutase 2, mitochondrial	0.6454	1.0415	0.69816		INS	insulin	1.471976371	0.93484693	1.279772162
SOD3	superoxide dismutase 3, extracellular	0.6597	0.6322	0.53692		EGR1	early growth response 1	0.648413266	2.68479454	2.108890351	0.61/0.44/2.00/1.02
GLRX	glutaredoxin (thioltransferase)	1.972	0.9262	1.86416	0.92/1.75/0.91/1.24	ACTB	actin, beta	0.89854	0.87100011	1.018403839	0.27/0.15/0.26/0.06
GLRX2	glutaredoxin 2	0.8301	1.0373	0.80569		GAPDH	glyceraldehyde-3-phosphate dehydrogenase	0.73695	0.91758519	0.764738012	0.43/0.29/0.41/0.14
TXN	thioredoxin	0.8237	1.0354	0.82975		TBP	TATA box binding protein	0.93576	1.06439203	1.071294139
PMEL	premelanosome protein	1.6221	0.9695	1.64028	1.01/1.78/0.84/1.08

*1:Cont/siNR4A3/H2O2/siNR4A3_H202.

*2 discareded during data process because of low value.

The average of three microarray datasets for NR4A3 siRNA-treated cells after normalisation was compared with the average of three microarray datasets for control cells without H₂O₂ treatment (Experiment B). A microarray dataset for NR4A3 siRNA- and H₂O₂-treated cells, and that for NFW- and H₂O₂-treated cells were also compared. For RT-qPCR analysis under Condition C described in the Supplemental material, 22 RNA samples from four groups obtained for microarray were used, and the value was the expression ratio to TBP expression. * p < 0.05.

Discussion

Recently, Chaffey et al. [14] reported that 1.1B4 cells may not retain the phenotype expected from normal human β-cells. Therefore, we searched for the homology of the NR4A3 probe sequence used in this study (A_23_P398566) using MegaBlast at NCBI, and found that the probe sequence only matched the human NR4A3 mRNA and Macaca fascicularis brain cDNA clone, but did not match the corresponding rodent sequence. Therefore, the data presented in this study can be considered to correspond to human data (Supplemental Fig. S8). Chaffey et al. [14] reported that the extremely limited availability of human pancreatic β-cell lines amenable to in vitro manipulation presents a clear barrier to progress in diabetes research. Primary human islets represent the gold standard for the study of β-cell function, but are available only intermittently. Therefore, the advent of a hybrid cell line obtained by the fusion of PANC-1 with a primary human β-cell, and which retains certain critical features of both offers a unique opportunity to study the development of persistent β-cell and diabetes research.

Because of the weak expression of antioxidant enzymes in islet β-cells [2], these cells develop diabetes mellitus in response to oxidative stress. However, in other cells, H₂O₂ induced SOD1, SOD2, and CAT expression [15]. In this study, HMOX and GCLC were strongly upregulated in H₂O₂-treated 1.1B4 cells (Table 1), whereas other major antioxidant enzymes were not upregulated. Therefore, HMOX1, GCLC, and the transcription factor NR4A3 are suggested to be responsible for the antioxidant defence system in pancreatic cells, and for defending against oxidative stress in diabetes, whereas CAT and GPX1 do not seem to be effective in these cells.

Alam and Cook [6] have described four pathways involved in HMOX1 regulation. However, we demonstrated that the downregulation of HMOX1 by NR4A3 siRNA causes a loss of antioxidative resistance. It is suggested that NR4A3 is a fifth oxidative stress-responsive transcription factor for HMOX1 and may be a major one in β-cells (Graphical Abstract). The FOSB, JUNB, AP-1, and EGR1 genes were also upregulated (Tables 1 and 2, Figure 1(c,f)), suggesting that these factors might also play an important role; however, this requires further investigation.

The NR4A protein binds to NBRE (taggtca), or forms heterodimers and then binds to NuRE (aat(g/a)(c/t)ca) [16]. The antisense sequences tgaccta and tgacatt were observed to be located upstream of HMOX1 (Supplemental Fig. S6A). CDK2 and CCNE1 also contained these sequences (Supplementary Fig. S6B and C), suggesting that these transcription factors are regulated by NR4A3 following H₂O₂ addition.

Robertson [17] reported that the unrelenting deterioration of β-cells is related to chronic oxidative stress. In this study, insulin expression in 1.1B4 cells decreased by 0.02-fold after H₂O₂ addition as compared to that in control cells (Table 1), and diabetes led to increased oxidative stress, suggesting that β-cells decreased insulin production in diabetes. This suggests that drug discovery trials should include antioxidant protection of β-cells. However, antioxidant drugs are not currently clinically used for the treatment of human diabetes. We recently identified a strong antioxidant zeylaniin A [18] in food products, which may be useful for the treatment of human diabetes in future. The limit of this study is the cells used is hybrid of normal human cells and transformed cells, but it is concluded that the results of this study show that HMOX1, GCLC, and the transcription factor NR4A3 are suggested to be responsible for the antioxidant defence system in pancreatic cells, and for defending against oxidative stress in human diabetes.

Geolocation information

Department of Life Science, Graduate School, Ochanomizu University, Bunkyo-ku, Tokyo, 112-8610, Japan.

Disclosure of interest

The authors report there are no competing interests to declare.

Preprints

https://www.biorxiv.org/content/10.1101/2021.08.20.457070v1

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The datasets are available from the corresponding author upon reasonable request.

Additional information

Funding

This work was supported by the Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Scientific Research (A, B, and C)] under Grant numbers 17500533, 20300243, 24240096, and 25282020; and Grant-in-Aid for Challenging Exploratory Research under Grant number 21650196.