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. Author manuscript; available in PMC: 2012 Nov 1.
Published in final edited form as: Arterioscler Thromb Vasc Biol. 2011 Nov;31(11):2624–2633. doi: 10.1161/ATVBAHA.111.232827

Paraoxonase-2 modulates stress response of endothelial cells to oxidized phospholipids and a bacterial quorum-sensing molecule

Juyong Brian Kim 1,*, Yu-Rong Xia 2,*, Casey E Romanoski 3, Sangderk Lee 4, YongHong Meng 5, Yi-Shou Shi 6, Noam Bourquard 7, Ke Wei Gong 8, Zachary Port 9, Victor Grijalva 10, Srinivasa T Reddy 11, Judith A Berliner 12, Aldons J Lusis 13, Diana M Shih 14
PMCID: PMC3244174  NIHMSID: NIHMS322652  PMID: 21836061

Abstract

Objective

Chronic infection has long been postulated as a stimulus for atherogenesis. Pseudomonas aeruginosa infection has been associated with increased atherosclerosis in rats, and the bacteria produce a quorum-sensing molecule 3-oxo-dodecynoyl-homoserine lactone (3OC12-HSL) that is critical for colonization and virulence. Paraoxonase 2 (PON2) hydrolyzes 3OC12-HSL and also protects against the effects of oxidized phospholipids thought to contribute to atherosclerosis. We now report the response of human aortic endothelial cells (HAEC) to 3OC12-HSL and oxidized 1-palmitoyl-2-arachidonoyl-sn-glycero-3-phosphocholine (Ox-PAPC) in relation to PON2 expression.

Methods and Results

Using expression profiling and network modeling, we identified the unfolded protein response (UPR), cell cycle genes, and the MAPK signaling pathway to be heavily involved in the HAEC response to 3OC12-HSL. The network also showed striking similarities to a network created based on HAEC response to Ox-PAPC, a major component of minimally-modified LDL. HAEC in which PON2 was silenced by siRNA showed increased pro-inflammatory and UPR responses when treated with 3OC12-HSL or Ox-PAPC.

Conclusion

3OC12-HSL and Ox-PAPC influence similar inflammatory and UPR pathways. Quorum sensing molecules such as 3OC12-HSL contribute to the pro-atherogenic effects of chronic infection. The anti-atherogenic effects of PON2 include destruction of quorum sensing molecules.

Keywords: Atherosclerosis, Chronic Infection, Inflammation, Oxidative Stress, Unfolded Protein Response

It is now established that chronic inflammation plays a major role in the initiation and progression of atherosclerosis, although the detailed mechanisms remain poorly understood. Chronic infection has long been suspected as one of the etiologies of atherogenesis given its association with increased level of systemic inflammation, and several pathogens including CMV, Chlamydia pneumonia, Porphyromonas gingivalis (a periodontal pathogen), and Helicobacter pylori have been associated with increased risk of atherosclerosis 1-4.

Pseudomonas aeruginosa is an opportunistic Gram-negative pathogen that is often associated with chronic airway infection in cystic fibrosis patients as well as with nosocomial infections associated with high morbidity and mortality. It is the most common pathogen isolated from patients who have been hospitalized longer than one week. These pathogens are widespread in nature, inhabiting soil, water, plants, and animals including humans. It rarely causes overt disease in healthy individuals, however, it has minimal nutritional requirements and can tolerate a wide variety of physical conditions leading to resistant colonization through formation of biofilms. Chronic respiratory infection of P. aeruginosa in rats has been shown to increase atherosclerosis 5.

The homoserine lactone, 3OC12-HSL, is a product of P. aeruginosa and is a quorum-sensing signaling molecule that modulates its own growth in order to maintain optimal nutrition, acting as the key signaling molecule that effectively maintains biofilm and colonization. In addition, 3OC12-HSL has been shown to modulate host cell functions, such as immune responses, inflammatory gene The auto-inducer 3OC12-HSL, in contrast to the bacterial induction, endotoxin and LPS, apoptosis is known to 6-9. activate mammalian cells via a toll like receptor 4 (TLR4)-independent pathway 9.

Ox-PAPC is a mixture of oxidized phospholipids whose biologically active components are also present in minimally oxidized LDL (MM-LDL). Ox-PAPC mimics the proinflammatory effects of MM-LDL, including enhancement of monocyte-endothelial cell interaction and induction of tissue factor, IL-8, CCL2, G-CSF and other mediators of atherothrombosis10, 11. The biologically active lipid components of Ox-PAPC have been shown to be enriched in human12 and rabbit10,13 atherosclerotic arteries, apoptotic cells and cells exposed to oxidative stress as compared to the normal vessels or cells11, 14. These lipids are thought to be mediators of inflammation leading to lesion development 11, 14. However, the abundance of oxidized phosphatidylcholine (PC) in atherosclerotic lesions remains controversial. For instance, in an analysis of arterial PC molecular species, oxidized PC species in the mass range m/z 594-666, were shown to be a minor component (less than 0.5%) of total arterial PC in both swine atherosclerotic and normal arteries15.

The paraoxonase (PON) gene family in humans has three members, PON1, PON2, and PON3. All three PONs have been found to have anti-inflammatory effects and protect against atherosclerosis in murine models 16-18. Recent studies show that PON2 is present in mitochondria and plays a role in protection against superoxide leakage from the electron transport chain 19, 20. These findings strengthen the notion that PON2 has anti-oxidative functions. All three PONs exhibit lactonase activity against acyl homoserine lactones 21, with PON2 being the most active in hydrolyzing 3OC12-HSL 21-23. Thus PON2 may play a role in host defense responses to pathogenic bacteria 24.

Given the key role of endothelial cells in atherosclerosis, we sought to obtain a systems-level view of the effects of 3OC12-HSL on HAEC inflammatory responses and to compare this with the effects of oxidized phospholipids that are formed during the oxidation of LDL. We also investigated the role of PON2 in protecting against the effects of 3OC12- HSL and oxidized phospholipids.

Methods

Detailed methods can be found in the online data supplement at http://atvb.ahajournals.org.

Statistics

Data are shown as the mean ± standard deviation in Figures 2-5, and S1-S3. Means were compared using the two-tailed Student’s t-test for data presented in Figures 2-5, and S1-S3. With the exception of the microarray study, a minimum of three biological replicates and two technical replicates are used in each experiment.

Figure 2.

Figure 2

Figure 2

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PON2 knockdown resulted in more severe response of the HAEC to 3OC12-HSL treatment. (A) Determination of the ability of membrane protein isolated from control and PON2 siRNA transfected HAEC to hydrolyze 3OC12-HSL. Five μg of membrane protein from HAEC transfected with control or PON2 siRNAs was incubated with 10 μM of 3OC12-HSL for various periods of time (0 to 90 min). Afterwards, the remaining 3OC12-HSL in the reaction mixture was assayed using a bioassay. (B) and (C) Determination of the ability of intact HAEC transfected with control or PON2 siRNAs to hydrolyze 3OC12-HSL. PON2 or control siRNA transfected HAEC were incubated with 25 μM (B) or 50 μM (C) of 3OC12-HSL for 0, 2, or 4 hr before 6 μl of the media was removed and assayed for remaining 3OC12-HSL level using the bioassay. (D) Cell metabolism of PON2 or control siRNA transfected HAEC after 3OC12-HSL treatment. One day after siRNA transfection, cells were treated with various concentrations of 3OC12-HSL for 17 hrs before cell metabolism was measured. For A-D: *: p < 0.05, **: p < 0.01, ***: p < 0.0001, PON2 siRNA transfected cells vs. control siRNA transfected cells. (E) Expression of UPR genes in PON2 or control siRNA transfected HAEC with or without 3OC12-HSL treatment. Two days after siRNA transfection, cells were treated with 0 or 50 μM of 3OC12-HSL (C12) for 4 hrs before total RNA was isolated for quantitative PCR analysis. **: p < 0.01, vehicle treated-PON2 siRNA transfected cells vs. vehicle treated-control siRNA transfected cells. #: p < 0.05, ##: p < 0.01, C12 treated-PON2 siRNA transfected cells vs. C12 treated-control siRNA transfected cell. (F) Western blot analysis of UPR and apoptosis markers in PON2 or control siRNA transfected HAEC treated with 50 μM of 3OC12-HSL for various time periods (0 to 60 min, upper panel). Quantification of western blot data is shown in lower panel of (F). β actin was used as the loading control. Values for phospho-eIF2α or cleaved caspase 7 protein were normalized to β-actin. Relative protein level was calculated as (protein of interest/β-actin) of the PON2 siRNA treated sample at time X / (protein of interest/β-actin) of the control siRNA treated sample at the same time X. (G) and (I) Increased expression of calcium pathway genes (G) and inflammatory genes (I) in PON2 siRNA transfected HAEC with 3OC12-HSL treatment. For G, and I: *: p < 0.05, **: p < 0.01, ***: p < 0.0001, vehicle treated-PON2 siRNA transfected cells vs. vehicle treated-control siRNA transfected cells. #: p < 0.05, ##: p < 0.01, ###: p < 0.0001, C12 treated-PON2 siRNA transfected cells vs. C12 treated-control siRNA transfected cell. (H) Determination of NF-κB activation by Western blot analysis of phospho-p65. Cells were treated with 50 μM of 3OC12-HSL (C12) for various time periods (0 to 240 min) before total cell lysate was harvested for western blot analysis.

Figure 5. PON2 protects against Ox-PAPC induced oxidative stress and UPR response in HAEC.

Figure 5

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(A) Inverse correlation between PON2 mRNA levels and intracellular superoxide levels (as determined by the NBT reduction assay) among 96 primary cultures of HAEC. (B) Increased intracellular superoxide levels in PON2 siRNA transfected HAEC with or without Ox-PAPC treatment. Control or PON2 siRNAs transfected HAEC were treated with 0, or 50 μg /ml of Ox-PAPC for 1 hr before intracellular superoxide levels were measured. *: p < 0.05, PON2 siRNA transfected cells vs. control siRNA transfected cells. (C) Western blot analysis of UPR markers of HAEC transfected with PON2 or control siRNA and treated with 50 μg /ml of Ox-PAPC for 0 to 4 hrs. (D) Induction of UPR genes in HAEC transfected with PON2 or control siRNA and treated with 0 or 50 μg /ml of Ox-PAPC for 4 hrs. (E) Induction of expression of IL-8, CCL2, and HO-1 genes in HAEC transfected with PON2 or control siRNA and treated with 0 or 50 μg /ml of Ox-PAPC for 4 hrs. #: p < 0.05, ##: p < 0.01, Ox-PAPC treated-PON2 siRNA transfected cells vs. Ox-PAPC treated-control siRNA transfected cell. (F) Correlation between basal PON2 mRNA level and fold change of UPR genes upon Ox-PAPC treatment among 96 primary cultures of HAEC. Expression data were obtained from our previous publication33. Briefly, HAEC from each donor were treated in duplicate with media (basal level) or media + 40 μg/ml Ox-PAPC (Ox-PAPC) for 4 hr before RNA isolation. RNA expression level was determined by Affymetrix HT-HU133A Microarrays. The fold change of Ox-PAPC over basal level of UPR gene of interest, which was calculated as the (log2(Ox-PAPC) − log2(basal)), was correlated with basal level of PON2 mRNA.

Results

The effects of 3OC12-HSL on global gene expression in HAEC

We utilized expression microarrays to examine the effects of 3OC12-HSL on gene expression in HAEC. We initially analyzed the differentially expressed genes between 3OC12-HSL treated and untreated HAEC isolated from the donors based on selection criteria described in Methods. This screen yielded 601 differentially expressed probes corresponding to 585 genes (Supplemental Table I). The corresponding q-value on FDR calculation was 0.133. Approximately 67% of the differentially expressed genes were up-regulated after 3OC12-HSL treatment.

Since some previous reports have linked the effect of 3OC12-HSL with the NF-κB pathway, we searched for known NF-κB target genes. We observed significant induction of interleukin 8 (IL-8, 2.7 fold), heme oxygenase 1 (HO-1, 1.7 fold), E-selectin (4.1 fold), chemokine (C-C motif) ligand 2 (CCL2, 1.8 fold) and cyclooxygenase-2 (COX2, 1.4 fold). These results were further validated using quantitative PCR (data not shown).

Next, we performed a Gene Ontology (GO) and KEGG pathway analysis of the differentially expressed genes using DAVID (http://david.abcc.ncifcrf.gov/)25, 26 and WebGestalt (http://bioinfo.vanderbilt.edu/webgestalt/)27 respectively. GO analysis showed a significant enrichment for unfolded protein response and heat shock proteins. The gene list also showed significant enrichment for KEGG pathways including metabolic pathways, MAPK signaling pathway, cell cycle, and calcium signaling pathway. The list of the top GO terms and KEGG pathways are shown in Table 1, and the remaining enriched GO terms and KEGG pathways can be found in Supplemental tables III and IV respectively.

Table 1.

Representative GO terms and KEGG pathways enriched from 585 differentially expressed genes.

Gene Ontology (# of genes) (Enrichment
P-value)		 KEGG pathway (# of genes) (Enrichment P-
value)
Response to Unfolded Protein (20) (2.7e-
12)
Response to protein stimulus (21) (9.7e-
10)
Regulation of cell death (57) (1.86e-06)
Heat shock protein binding (2.04e-06)
(14)
Regulation of apoptosis (2.66e-06) (56)
Mitosis (4.13e-06) (24)
Response to organic substance (5.29e-
06) (51)
Response to ER stress (1.5e-04) (8)
Blood vessel morphogenesis (1.9e-04)
(22)
Negative regulation of DNA binding
(2.55e-04) (10)		 Metabolic pathways (37) (2.9e-06)
p53 signaling pathway (8) (8.0e-05)
Pathways in cancer (16) (8.2e-05)
Cell cycle (10) (8.2e-05)
Antigen processing and presentation (8) (2e-
04)
MAPK signaling pathway (13) (4e-04)
NOD-like receptor signaling pathway (6)
(1.2e-03)
Neurotrophin signaling pathway (8) (1.7e-
03)
Complement and coagulation cascades (6)
(1.7e-03)
Pyrimidine metabolism (7) (1.7e-03)
Phosphatidylinositol signaling system (6)
(2.2e-03)
Calcium signaling pathyway (9) (2.2e-03)
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*: EASE p-value (modified fisher’s exact test) was used for GO terms and hypergeometric test with Benjamini-Hochberg adjusted P-value from Webgestalt online tool was used for KEGG pathway enrichment. Illumina Humanref-8 v.2 probe set was used as background.

Weighted Gene Co-expression Network Construction and Analysis (WGCNA) of 3OC12-HSL regulated genes

The WGCNA network was constructed with a list of 1264 probes, corresponding to 1231 genes, obtained from a relaxed criteria (see Methods) compared to the differential expression analysis in order to capture variations in donor-specific responses. The resulting gene co-expression network was composed of 3OC12-HSL regulated genes separated into 14 modules of highly correlated genes, and assigned a unique color identifier, with the remaining poorly connected genes assigned to the gray module (Figure 1A). The full list of genes and module membership information can be found in Supplemental table II. Genes with the greatest intramodular connectivity index (Kin) represent network “hubs” 28. Hence, the “hub genes” within a module indicates genes that is likely functionally important. For each module, we searched for enrichment of GO terms and KEGG pathways, and these results are shown in Supplemental tables V and VI.

Figure 1. Weighted Gene Co-expression Network of HAEC transcriptome.

Figure 1

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(A) Edge-weighted spring embedded layout via Cytoscape 41 of network created from HAEC treated with 3OC12-HSL (Left) and Ox-PAPC (Right). Nodes were colored to match the module identified from average linkage hierarchical clustering with topological overlap dissimilarity measure as described in methods. (Left) Pearson correlation with Beta=14 was used to create an adjacency matrix (ADJ) for all genes within the network and 1-ADJ was used as measure of dissimilarity. The dissimilarity index was used as the interaction strength between nodes to create a network. 925 nodes were included in total following the screen to create 12714 edges. (Right) Pearson correlation with Beta=5 was used to create ADJ within the network and dissimilarity index was used as interaction strength to create network with 827 nodes and 12000 edges; (B) Close-up view of the yellow modules from HAEC treated with 3OC12-HSL (Left) and Ox-PAPC (Right). The UPR genes within the module are highlighted in green.

Initially, we investigated the modules where the NF-κB pathway derived pro-inflammatory genes were located. IL-8, E-selectin, ICAM-1 were found to be within the yellow module. Upon GO term analysis, the yellow module was also found to highly enrich for UPR related genes (Supplemental tables II and V), including molecular chaperones and transcription factors known to be involved in the UPR pathway. These UPR related genes included ATF3, XBP1, TRIB3, CEBPB, SLC7A5, and also DDIT3 which encodes the CHOP protein (Supplemental tables II and VII). Hub genes with high intramodular connectivity within the yellow module included SLC7A5, TRIB3, CEBPB, E-Selectin, ICAM1, and ATF3.

UPR genes were also identified within the black module, but mostly limited to chaperones and ERO1-alpha. ERO1-alpha has been reported to be involved in the regulation of ER-stress induced apoptosis via stimulation of the Inositol 1,4,5-triphosphate receptor (IP3R) activity 29. The IP3R activity is important in regulating calcium release from ER, which is postulated to be the molecular trigger for the UPR pathway to initiate apoptosis.

Overlapping pathways between the differentially expressed gene sets of 3OC12-HSL- and Ox-PAPC-treated HAEC

We compared the differentially expressed gene set (601 probes/585 genes) generated from the 3OC12-HSL treated HAEC against a differentially expressed gene set (1043 probes/675 genes) previously generated using HAEC collected from 12 healthy individuals treated with Ox-PAPC 30. We observed that 99 genes out of the 585 differentially expressed genes from 3OC12-HSL treated HAEC were present in the 675 genes from the Ox-PAPC treated HAEC. (Supplemental table VIII) This overlap was highly significant when tested for hypergeometric distribution (p<5×10−9). Notably present were genes related to cell cycle, UPR, amino acid transporters, and regulation of gene transcription/transcription factors. Furthermore, the similarity in direction of regulation was evident (85 of 99 genes responded in same direction), suggesting that Ox-PAPC and 3OC12-HSL influence similar pathways in the HAEC to produce their UPR-inducing effects and others. The network analysis also showed that the modules identified from the Ox-PAPC-treated HAEC were similar to those identified from 3OC12-HSL-treated HAEC. Among the most significant modules from the Ox-PAPC-treated HAEC network, enrichments were found for GO terms including UPR and cell cycle 30. The yellow modules enriched for UPR genes in both networks (Supplemental table V and X), and were both central in the network (Figure 1), suggesting the pivotal role of UPR genes in response to 3OC12-HSL and Ox-PAPC.

To confirm the microarray data, HAEC from 2 independent donors were examined for Ox-PAPC- and 3OC12-HSL-induced gene expression by qPCR. In agreement with the microarray findings, we found similar patterns of induction of inflammatory and UPR genes between Ox-PAPC- and 3OC12-HSL- treated cells in both HAEC cultures (Supplemental figure IA). However, we found that only Ox-PAPC increased intracellular superoxide level in HAEC whereas 3OC12-HSL did not after one hour of treatment (Supplemental figure IB).

PON2 is important in protection against UPR, apoptosis, and inflammation induced by 3OC12-HSL in cells

Among the PON family members, PON2 is known to exhibit the highest hydrolytic activity against 3OC12-HSL and is the only PON member that is expressed in HAEC 21, 31. We performed siRNA transfection study to examine the role of PON2 in modulating HAEC’s response to 3OC12-HSL treatment. Two days after transfection, we observed that PON2 mRNA and protein levels in the PON2 siRNA transfected HAEC were 90% and 75% lower than those received the control siRNA (Supplemental figure II). Cell lysates prepared from the PON2 siRNA transfected cells exhibited significantly decreased hydrolytic activity against 3OC12-HSL (Figure 2A). Furthermore, PON2 siRNA transfected cells were less capable of hydrolyzing 3OC12-HSL as evidenced by significantly higher levels of 3OC12-HSL levels remained in the conditioned media at both 2 hr and 4 hr after addition of 25 μM (Figure 2B) or 50 μM (Figure 2C) 3OC12-HSL, as compared to the control. PON2 siRNA transfected HAEC also showed significantly decreased cell metabolism as compared to those transfected with control siRNA when treated with 15, 30, or 50 μM of 3OC12-HSL for 20 hr (Figure 2D).

We observed that PON2 knockdown rendered the cells more susceptible to 3OC12-HSL (50 μM)-induced UPR as evidenced by significantly increased expression of UPR genes including HSPH1, HSPA4L, DNAJB2, spliced form of XBP-1, DDIT3, ATF3, and TRIB3 as compared to control siRNA transfected cells (Figure 2E). Phosphorylation of eIF2a, an early event in UPR, was also significantly increased with PON2 knockdown (Figure 2F). In addition, increased level of cleaved caspase 7, an apoptosis marker, was observed in PON2 siRNA transfected cells after 3OC12-HSL treatment as compared to the control (Figure 2F). We examined genes involved in calcium signaling pathway and found increased expression of ITPKB, PLCD1, PLCD4, ERO1L and TRPM4 in PON2 siRNA transfected cells after 50 μM 3OC12-HSL treatment (Figure 2G).

Because of the increase in a number of NF-κB regulated genes, we examined the effect of 3OC12-HSL (50 μM) on NF-κB activation. As compared to the control siRNA transfected cells, we observed earlier and stronger NF-κB activation in the PON2 siRNA transfected cells, as shown by increased phosphorylation of P65 (Figure 2H). Expression of NF-κB target genes including IL-8, COX2, IL-1β, and ICAM-1 were significantly increased after PON2 knockdown as compared to the control siRNA transfected cells (Figure 2I).

When the HAEC transfected with control or PON2 siRNA were treated with a lower dose of 3OC12-HSL (25 μM) for 4 hr, induction of ICAM-1 and XBP-1s were similar between the two groups of cells (Supplemental figure III). However, the induction of COX2, IL-8, and ATF3 were significantly higher in the PON2 siRNA transfected cells as compared to the control siRNA transfected cells (Supplemental figure III), demonstrating PON2 was still protective even when HAEC were exposed to a lower dose of 3OC12-HSL.

To examine whether increased expression of PON2 will protect cells against 3OC12-HSL, HeLa cells were transfected with human PON2 or GFP expression vectors. Two days after transfection, we observed a 6-fold increase in PON2 mRNA levels in the PON2-transfected cells as compared to the GFP-transfected cells (data not shown). PON2-overexpressing cells were more capable of hydrolyzing 3OC12-HSL as evidenced by significantly lower levels of 3OC12-HSL levels remained in the conditioned media at both 0.5 hr and 1 hr after addition of 50 μM 3OC12-HSL, as compared to the GFP-expressing cells (Figure 3A). We found basal mRNA levels of COX2, IL-8, DDIT3, and ATF3 were significantly lower in PON2 overexpressing cells as compared to those of the GFP expressing cells (Figure 3B, 3C). These data suggest a role for PON2 in protection against inflammation and ER stress even at basal state. After 3OC12-HSL treatment, induction of inflammatory genes including COX2, IL-8, and ICAM-1 (Figure 3B), as well as UPR genes including XBP-1s, DDIT3, and ATF3 (Figure 3C) were significantly decreased in the PON2-overexpressing cells as compared to the GFP-expressing cells, suggesting that PON2 protects against 3OC12-HSL-induced inflammation and UPR.

Figure 3. PON2 overexpression decreased 3OC12-HSL induced inflammatory and UPR response in HeLa cells.

Figure 3

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(A) HeLa cells transfected with a GFP or a human PON2 expression vector were incubated with 50 μM of 3OC12-HSL for 0 to 2 hr before 6 μl of the media was removed and assayed for remaining 3OC12-HSL level using the bioassay. **: p < 0.01, ***: p < 0.0001, GFP vs. PON2 transfected cells. (B), (C) Decreased expression of inflammatory genes (B) and UPR genes (C) in 3OC12-HSL treated HeLa cells transfected with a human PON2 expression vector. Two concentrations of 3OC12-HSL (C12) were used: 25 μM and 50 μM. Treatment time was 4 hr. *: p < 0.05, GFP- vs. PON2-transfected cells receiving the same treatment.

Prostaglandin E2 receptor EP2 and 3OC12-HSL signaling

As described above (Supplemental table S8), we observed overlapping pathways between the differentially expressed gene sets of 3OC12-HSL- and Ox-PAPC-treated HAEC, suggesting 3OC12-HSL and Ox-PAPC may share some upstream signaling pathway(s). The prostaglandin E2 (PGE2) receptor EP2 was demonstrated as a receptor activated by Ox-PAPC32. To answer the question whether EP2 is a receptor for 3OC12-HSL, we utilized the PGE2 (EP2) antagonist, AH6809. We observed that AH6809 co-treatment did not block 3OC12-HSL-induced phosphorylation of eIF2α (Figure 4A), a marker for UPR. However, AH6809 co-treatment partially blocked 3OC12-HSL-induced NF-κB activation as shown by decreased phosphorylation of p65, especially at 240 min (Figure 4A). In addition, AH6809 significantly decreased 3OC12-HSL induced expression of E-selectin, COX2, and IL-1β, whereas, expression of ICAM-1, IL-8, DDIT3, and XBP-1s was not affected by AH6809 (Figure 4B and 4C). Therefore, our data suggest EP2 plays a role in NF-κB activation induced by 3OC12-HSL. However, EP2 is unlikely to be the receptor for 3OC12-HSL since only NF-κB activation but not UPR response are affected by an EP2 antagonist, AH6809.

Figure 4. EP2 is involved in 3OC12-HSL induced NF-kB activation.

Figure 4

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(A) Western blot analysis of HAEC treated with vehicle control, DMSO (D), 10 μM of AH6809 (AH), 50 μM of 3OC12-HSL (C12), or 10 μM of AH6809 and 50 μM of 3OC12-HSL (C12 + AH). (B) and (C) gene expression analysis of HAEC after 4 hr treatment of the same agents as described in (A). *: p < 0.05, **: p < 0.01, C12 treated vs. C12 + AH6809 treated.

Natural variation in PON2 is associated with inflammatory response to Ox-PAPC in endothelial cells

Recent studies have shown that PON2 is present in mitochondria and plays a role in protection against superoxide leakage from the electron transport chain 19, 20. These findings strengthen the notion that PON2 has anti-oxidative functions. In the present study, we observed a significant inverse correlation between PON2 mRNA levels and intracellular superoxide levels among 96 independent primary cultures of HAEC (Figure 5A), demonstrating that natural variation in PON2 levels influences intracellular oxidative stress. Furthermore, PON2 knockdown in HAEC by siRNA transfection also increased intracellular superoxide levels at basal state and with 50 μg /ml Ox-PAPC treatment for 1 hr (Figure 5B).

Ox-PAPC treatment has been shown to induce UPR and inflammatory response in HAEC 30. We observed that PON2 knockdown in HAEC significantly increased phosphorylation of eIF2α and phosphorylation of JNK upon Ox-PAPC treatment (Figure 5C), suggesting an increased UPR in the PON2 deficient cells as compared to the control. In addition, we found significantly higher expression of UPR genes in PON2 deficient HAEC after 4 hrs of Ox-PAPC treatment as compared to those of the control (Figure 5D). These UPR genes include spliced form of XBP-1, ATF4, DDIT3, CEBPB, CHAC1, and ATF3. In addition, expression of inflammatory genes, IL-8, and CCL2 was significantly increased whereas expression of the anti-oxidative gene HO-1 was not changed with PON2 knockdown (Figure 5E). Interestingly, analyzing a previously published microarray dataset33 we also observed a significant inverse correlation between basal PON2 mRNA levels and fold induction of UPR genes upon Ox-PAPC treatment among the 96 independent primary cultures of HAEC (Figure 5F), demonstrating natural variation in PON2 level in HAEC influences Ox-PAPC-induced UPR response as well. With the exception of XBP-1 (R = −0.18, p = 0.02), there is no significant correlation between basal mRNA levels of PON2 and basal level of UPR genes listed in Figure 5F (data not shown). In summary, our results further demonstrated the importance of PON2 in protection against oxidative stress, UPR, and inflammatory response in endothelial cells and support an athero-protective role for PON2.

Discussion

Our study is the first to examine global gene expression changes in HAEC after 3OC12-HSL treatment. Our data showed that there is upregulation of pro-inflammatory genes that are downstream of NF-κB pathway and activation of UPR pathway, which likely leads to regulation of cell cycle and apoptotis-related genes. Previously, the Pseudomonas aeruginosa autoinducer 3OC12-HSL has been shown to modulate immune response and induce apoptosis in host cells 6, 7, 9. Using global expression profiling, we were able to recapitulate many of the known cellular responses induced by the auto-inducer 3OC12-HSL and discover novel pathway such as UPR. Using expression profiling data, we created a weighted gene co-expression network of 3OC12-HSL regulated genes and identified 14 modules of highly correlated genes. We found UPR, cell cycle genes, and MAPK signaling pathway to be heavily involved in the HAEC response to 3OC12-HSL.The co-existence of NF-κB target genes and UPR genes as hub genes in the yellow module strongly suggests a functional connection between these two pathways. A previous study has shown that ER stress activates NF-κB via the activation of IRE1 and tumor necrosis factor receptor-associated factor 2 (TRAF2) 34. Activation of IRE1 also leads to splicing of XBP-1 and subsequent increased transcription of DDIT3, which also belongs to the yellow module. In addition, the yellow module was enriched for the MAPK KEGG pathway. For example, c-Jun was upregulated and highly connected within the yellow module (Supplemental table II). It has been previously shown that activation of JNK protein kinases is also mediated by IRE1 and TRAF2 35. Upon further inspection of the connections, strong correlations were seen between UPR and NF-κB target genes, including XBP1, DDIT3, CEBPB, TNFAIP3, and IL-8. Therefore, activation of IRE1 is likely to be responsible for the induction of UPR and NF-κB target genes of the yellow module.

Our data demonstrated activation of NF-κB by 3OC12-HSL in HAEC. There are conflicting reports regarding the effects of 3OC12-HSL on NF-κB activation. Activation of NF-κB by 3OC12-HSL has been demonstrated in human lung fibroblasts and epithelial cells 7, 36 and mouse keratinocytes 6. However, a recent report showed that 3OC12-HSL disrupted NF-κB signaling induced by LPS and TNFα in mouse macrophages, fibroblast and in vivo 37. One possible explanation for these conflicting reports is that 3OC12-HSL may activate or disrupt NF-κB signaling depending on the cell type, concentration of 3OC12-HSL, and duration of treatment. ER stress is known to induce NF-κB activation via IRE1 and TRAF2 34. This may be the initial event leading to 3OC12-HSL induced NF-κB activation. We found that a PGE2 (EP2) antagonist, AH6809, partially blocked 3OC12-HSL induced NF-κB activation and the effect is most prominent at 240 min (Figure 4A). A previous study 38 showed that peptidoglycan (PGN), a cell wall component of the Gram-positive bacterium, Staphylococcus aureus, activates NF-kB in RAW 264.7 macrophages in 2 phases. In the first phase, PGN causes NF-kB activation through Toll like receptor 2 and ERK. NF-kB activation then leads to COX2 expression and PGE2 release. In the second phase, PGN-induced PGE2 release results in activation of the EP2 and EP4 receptors and the cAMP/PKA pathway, which in turn increase IKKab activity, p65 phosphorylation at Ser276, leading to further NF-kB activation38. In the present study, we postulate that the initial activation of NF-kB by 3OC12-HSL is mediated by UPR. Subsequently, NF-kB activation leads to COX2 expression and PGE2 release. PGE2 release, in turn, leads to activation of the EP2 receptor and further activation of NF-κB. The fact that phosphorylation of p65 is most affected at 240 min in the presence of AH6809 suggests EP2 is involved in the second phase of NF-κB activation. We found that AH6809 significantly decreased 3OC12-HSL-induced expression of E-selectin, COX2, and IL-1β, all of which are NF-κB target genes (Figure 4B). However, expression of another two NF-κB target genes, ICAM-1 and IL-8, was not affected by AH6809 (Figure 4C). One possible explanation is that induction of ICAM-1 and IL-8 expression by NF-κB occurs in the early phase but not in the second phase of NF-κB activation. Another possible explanation for IL-8 comes from a previous study that showed Ox-PAPC induced expression of IL-8 is mediated by UPR transcription factors ATF4 and XBP-112. It is likely that 3OC12-HSL-induced IL-8 expression depends more on UPR than NF-kB pathway as well. In agreement, neither phosphorylation of eIF2α, a UPR marker, nor induction of UPR transcription factors, DDIT3 and XBP-1s, were altered by the presence of AH6809 in 3OC12-HSL treatment (Figure 4A, 4C).

We found that 3OC12-HSL induces UPR in HAEC. The mechanism(s) leading to 3OC12-HSL induced UPR remain(s) unknown. There have been previous reports that 3OC12-HSL modulated host cell responses via regulation of calcium release. Shiner et al 8 reported that within minutes of 3OC12-HSL treatment to endothelial cells, there appears a large increase in cytosolic calcium level mobilized from intracellular stores of calcium in the ER. This release as well as apoptosis was blocked when phospholipase C activity was inhibited suggesting that this early release of Ca2+ occurred via IP3R. Despite the connection of ER stress to IP3R-induced Ca release (IICR), it is unlikely that such an early event is due to UPR regulated signaling. Rather, the evidence suggests that 3OC12-HSL acts by an independent mechanism directly affecting the IICR, such as by directly activating G-protein coupled receptors (GPCR). We postulate that 3OC12-HSL triggers an immediate ER calcium release, leading to ER stress and apoptosis.

A similar expression pattern of UPR gene activation was seen in HAEC treated with 3OC12-HSL and Ox-PAPC. Gargalovic et al. 30 showed that Ox-PAPC treatment of HAEC resulted in induction of genes with strong enrichment for UPR pathway as well as the MAPK pathway and inflammatory genes. In the current study, we observed substantial overlapping pathways, such as UPR, MAPK pathway and cell cycle, between the differentially expressed gene sets of 3OC12-HSL- and Ox-PAPC-treated HAEC. This pattern suggests that the UPR and disturbance of cell cycle are part of a common cellular response to stress. We also observed some overlap in inflammatory gene induction between the 3OC12-HSL- and Ox-PAPC-treated HAEC. However, increased expression of E-selectin, ICAM-1, and COX2, three known NF-κB target genes, were only observed in 3OC12-HSL- but not Ox-PAPC- treated cells (Supplemental tables I and II and data not shown). This finding corroborates the finding that NF-κB is not activated by Ox-PAPC 39. Our previous study identified EP2 as a receptor for Ox-PAPC32. In this study, we tested the hypothesis that EP2 is also a receptor for 3OC12-HSL. However, our data demonstrated that the EP2 antagonist AH6809 did not inhibit 3OC12-HSL induced UPR (Figure 4), making this hypothesis unlikely. Further studies are needed to determine the shared and unique pathways that lead to UPR and cell cycle disturbance upon 3OC12-HSL and Ox-PAPC treatment. Of particular interest, our findings that 3OC12-HSL, similar to Ox-PAPC, promotes inflammatory gene expression and UPR in HAEC suggest that chronic infection with P. auruginosa may in fact act as a potent stimulus for atherogenesis.

Our data show PON2 deficiency in HAEC renders the cells more susceptible whereas PON2 overexpression in HeLa cells makes cells more resistant to the detrimental effects of 3OC12-HSL. One important question is whether PON2’s protective effect results solely from its lactonase activity on 3OC12- HSL. Recent studies show that PON2 plays a role in protection against superoxide leakage from the electron transport chain of the mitochondria19, 20 and in protection against UPR induced by tunicamycin40. These findings suggest that PON2’s protective effect against 3OC12-HSL is likely due to a combination of its lactonase activity and UPR-preventing functions.

We observed that PON2 mRNA expression levels inversely correlated with intracellular superoxide levels and Ox-PAPC induced fold induction of UPR genes among primary cultures of HAEC isolated from 96 human heart donors. These findings suggest that natural variation in PON2 level in HAEC isolated from healthy subjects influences the oxidative stress and the Ox-PAPC induced UPR stress response of the endothelial cells. Our PON2 knockdown studies in HAEC also showed detrimental effects of PON2 deficiency in protection against Ox-PAPC-induced oxidative stress and UPR. In summary, this study demonstrated that PON2 protects against the pro-inflammatory, UPR-inducing effects of 3OC12-HSL and Ox-PAPC, two types of molecules that may be important in infection, inflammation, and atherosclerosis. Whereas animal studies have shown protective effects of PON2 against atherosclerosis 18, 20, further studies are needed to determine the effects of PON2 on host defense.

Supplementary Material

1

Acknowledgments

Sources of Funding This study was supported in part by NIH grants 2RO1 HL071776-05A1 and 2 P01 HL030568-26A1.

Footnotes

Disclosures None.

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Contributor Information

Juyong Brian Kim, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Yu-Rong Xia, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Casey E. Romanoski, Department of Human Genetics, University of California, Los Angeles

Sangderk Lee, Department of Pathology and Laboratory Medicine, University of California, Los Angeles.

YongHong Meng, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Yi-Shou Shi, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Noam Bourquard, Molecular and Medical Pharmacology, University of California, Los Angeles.

Ke Wei Gong, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Zachary Port, Department of Medicine, Division of Cardiology, University of California, Los Angeles.

Victor Grijalva, Molecular and Medical Pharmacology, University of California, Los Angeles.

Srinivasa T. Reddy, Department of Medicine, Division of Cardiology, University of California, Los Angeles; Molecular and Medical Pharmacology, University of California, Los Angeles

Judith A. Berliner, Department of Medicine, Division of Cardiology, University of California, Los Angeles; Department of Pathology and Laboratory Medicine, University of California, Los Angeles

Aldons J. Lusis, Department of Medicine, Division of Cardiology, University of California, Los Angeles; Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles; Department of Human Genetics, University of California, Los Angeles

Diana M. Shih, Department of Medicine, Division of Cardiology, University of California, Los Angeles

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