Abstract
Air pollution is an environmental risk factor linked to multiple human diseases including cardiovascular diseases (CVDs). While particulate matter (PM) emitted by diesel exhaust damages multiple organ systems, heart disease is one of the most severe pathologies affected by PM. However, the in vivo effects of diesel exhaust particles (DEP) on the heart and the molecular mechanisms of DEP-induced heart dysfunction have not been investigated. In the current study, we attempted to identify the proteomic signatures of heart fibrosis caused by diesel exhaust particles (DEP) in CVDs-prone apolipoprotein E knockout (ApoE−/−) mice model using tandem mass tag (TMT)-based quantitative proteomic analysis. DEP exposure induced mild heart fibrosis in ApoE−/− mice compared with severe heart fibrosis in ApoE−/− mice that were treated with CVDs-inducing peptide, angiotensin II. TMT-based quantitative proteomic analysis of heart tissues between PBS- and DEP-treated ApoE−/− mice revealed significant upregulation of proteins associated with platelet activation and TGFβ-dependent pathways. Our data suggest that DEP exposure could induce heart fibrosis, potentially via platelet-related pathways and TGFβ induction, causing cardiac fibrosis and dysfunction.
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Introduction
Air pollution is a heterogeneous mixture of particles and gases1. It is an important environmental risk factor linked to human diseases such as ischemic heart disease, cerebrovascular disease, lung cancer, acute lower respiratory disease, and chronic obstructive pulmonary disease2. The adverse effects of air pollution are primarily attributed to particulate matter with diameter < 2.5 μm (PM2.5). Global PM2.5-related mortality was estimated to be 3.16 million in 2010 and is predicted to cause 5.17 million deaths in 20503. Interestingly, the majority of mortality in 2050 is predicted to be related to ischemic heart disease (2.17 million) and cerebrovascular disease (2.60 million)3, underscoring the importance of investigating the effects of PM2.5-induced cardiovascular diseases (CVDs) and developing therapeutic interventions.
Diesel exhaust particles (DEP), produced from combustion of diesel fuel, enter the human body via inhalation4. Although coarse DEP are trapped in airways and lungs, small particles (diameter < 2.5 μm) penetrate the respiratory system, circulate in blood vessels, and cause dysfunction of multiple organs, including the heart5,6,7. Previous studies have identified that thrombosis contributes to DEP-induced CVDs8,9,10,11, but the regulatory mechanisms for these pathologies remain incompletely understood.
Because PM is heterogenous, its components differ depending on the location of collection4. It is therefore not feasible to obtain environmental PM of reliable consistency to investigate its adverse effects on human disease. To compensate for the heterogenous makeup of PM, we combusted gasoline fuel or diesel fuel in the laboratory and produced consistent gasoline exhaust particles (GEP) and DEP with consistent makeup12,13. We previously analyzed GEP components and identified altered gene expression patterns in human umbilical vein endothelial cells (HUVECs) exposed to GEP12. Furthermore, after analyzing the components of DEP, we investigated their adverse effects on HUVECs, identifying that accumulation of autophagosomes induces HUVECs apoptosis by impairing autophagic flux and activating the caspase-8-caspase-3 cascade13. However, the in vivo effects of DEP on the heart and their related molecular mechanisms of potential DEP-induced heart dysfunction have not been investigated.
To determine how DEP affected cardiac fibrosis and protein levels, we exposed apolipoprotein E knockout (ApoE−/−) mice to DEP with intratracheal instillation and investigated changes of heart tissue protein expression patterns using tandem mass tag (TMT) labeling followed by liquid chromatography-tandem mass spectrometry (LC–MS/MS), allowing simultaneous comparison of protein abundances in all heart tissues. We chose ApoE−/− mouse model because ApoE is an essential component of lipoprotein which plays a role in uptake of chylomicrons and very low-density lipoprotein (VLDL) and serves as a ligand to hepatic receptors such as LDL receptor (LDLR) for the cholesterol clearance14,15. ApoE and LDLR interplay was important in the regulation of cholesterol metabolism16, thus the absence of ApoE delayed lipoprotein clearance and developed hyperlipoproteinemia17, leading to CVDs evidenced by previous studies with ApoE−/− mouse model14,18,19. DEP exposure induced mild heart fibrosis in ApoE−/− mice compared with severe heart fibrosis in AngII-infused ApoE−/− mice, and the most highly upregulated protein by DEP exposure was platelet factor 4 (PF4). Subsequently, we performed gene ontology (GO) analysis of proteins upregulated by DEP exposure, identifying that platelet activation is the primary process induced by DEP. Ingenuity pathways analysis (IPA) revealed that pathways related to CVDs and cardiac dysfunction were the significantly affected disease and toxicity phenotypes. Further, network analysis identified transforming growth factor β (TGFβ) as a major hub for signaling pathways regulated by DEP. These data suggested that DEP exposure induced heart fibrosis, potentially via platelet-related pathways and TGFβ induction, causing cardiac fibrosis and dysfunction.
Results
DEP exposure induced heart fibrosis in ApoE −/− mice
We established a mouse model of intratracheal DEP instillation to study potential heart damage. Originally, heart fibrosis was compared in WT mice subjected to intratracheal administration of PBS or DEP (Figure S1A). However, DEP did not induce heart fibrosis in WT mice, as demonstrated by Masson’s trichrome staining (Figure S1B-C). Thus, we used CVDs-prone ApoE−/− mice to evaluate the potential adverse effect of DEP on animals with a predisposition for heart disease (Fig. 1A). When we performed this study, we used the angiotensin II (AngII)-induced heart damage model in ApoE−/− mice as a positive control (Fig. 1A) to compare the severity of heart fibrosis in the positive control with that induced by DEP exposure. After implantation of an osmotic pump containing saline or AngII, intratracheal administration of DEP or PBS was performed eight times (every 3 day over 25 days). Three days following the final intratracheal administration, mice were sacrificed. Subsequently, hearts were harvested, and fibrosis and expression of proteins related to the fibrosis were examined. Masson’s trichrome staining of ApoE−/− mice hearts revealed that DEP exposure induced mild fibrosis compared with severe fibrosis induced by AngII infusion (Fig. 1B, C). The finding of fibrosis in DEP-exposed ApoE−/− mice hearts was supported by increased expression of ⍺-smooth muscle actin (⍺SMA), a key protein upregulated in heart fibrosis (Fig. 1D, E)20,21.
TMT-based quantitative proteomic analysis
We prepared heart tissue lysates from five groups consisting of PBS- or DEP-treated WT mice, PBS- or DEP-treated ApoE−/− mice, and AngII-infused ApoE−/− mice for proteomic analysis (n = 3 mice/group). From TMT labeling followed by LC–MS/MS analysis, 6,518 total proteins were identified from the five groups of mouse samples, and 6,461 proteins were commonly identified in the five groups (Table S1 and Figure S2). Spectra with an average reporter signal-to-noise ratio threshold ≥ 10 across 16 TMTpro 16plex channels were considered for quantification, with 5,038 proteins subjected to quantitative analysis (Table S2). To identify proteins that were significantly changed by DEP exposure in WT and ApoE−/− mice, a Student’s t test comparison of the log2(normalized signal-to-noise ratio) values was conducted. Statistical analysis identified that 73 proteins were significantly different (P-value < 0.05) between PBS- and DEP-treated WT mice, and 235 proteins were significantly different (P-value < 0.05) between PBS- and DEP-treated ApoE−/− mice (Tables S3 and S4). Using the criteria of |fold change|> 1.3 and P-value < 0.05, 17 proteins were differentially expressed between PBS- and DEP-treated WT mice (Table S5), and 52 proteins showed statistically significant changes between PBS- and DEP-treated ApoE−/− mice (Fig. 2). More proteins were significantly changed by DEP exposure in ApoE−/− mice than in WT mice, suggesting that the ApoE−/− mouse model was potentially more susceptible to DEP exposure. In hearts of DEP-exposed ApoE−/− mice, 39 proteins were upregulated, and 13 proteins were downregulated (Fig. 2A). A hierarchical clustering analysis of the 52 proteins revealed that the expression patterns between PBS- and DEP-treated ApoE−/− mice were distinct (Fig. 2B). The 39 upregulated proteins in hearts of DEP-treated ApoE−/− mice are listed in Table 1. The most highly upregulated protein was platelet factor 4 (PF4, Q9Z126) followed by cGMP-specific 3',5'-cyclic phosphodiesterase (Q8CG03), serglycin (SRGN, P13609), and ras-related protein Rab-27B (Q99P58). We also analyzed protein expression pattern in hearts of AngII-infused ApoE−/− mice versus those of PBS-treated ApoE−/− mice, and the abundance of 438 proteins was significantly different (P-value < 0.05) (Table S6). Using the criteria of |fold change|> 1.3 and P-value < 0.05 between groups, 143 proteins were differentially expressed following AngII infusion in ApoE−/− mice, with 118 upregulated proteins (Table 2). Among upregulated proteins, five proteins ((inositol 1,4,5-triphosphate receptor associated 1 (Q9WUX5), zyxin (Q62523), protein IWS1 homolog (Q8C1D8), latent-transforming growth factor beta-binding protein 1 (Q8CG19), and carboxylesterase 1C (P23953)) were upregulated by both DEP exposure and AngII infusion in ApoE−/− mice.
Pathway analysis of differentially expressed proteins in hearts of DEP-exposed ApoE −/− mice
GO enrichment analysis of the 39 proteins upregulated (> 1.3-fold, P-value < 0.05) in DEP-treated ApoE−/− mice in comparison to PBS-treated ApoE−/− mice revealed that positive regulation of platelet activation and platelet activation terms were enriched in the top five biological process terms, while calcium ion binding and actin binding were enriched in the top five molecular function terms (Fig. 3A). The 39 proteins significantly increased in DEP-treated ApoE−/− mice were subjected to IPA analysis (Table 3), revealing that the top five molecular and cellular functions in order of significance were ‘cell-to-cell signaling and interaction,’ ‘cellular function and maintenance,’ ‘cellular development,’ ‘cellular growth and proliferation,’ and ‘cell morphology.’ The two diseases and disorders most related were ‘inflammatory response’ and ‘cardiovascular disease,’ indicating that DEP exposure could cause CVDs in ApoE−/− mice. Further, ‘cardiac arteriopathy,’ ‘cardiac dilation,’ ‘cardiac enlargement,’ ‘congenital heart anomaly,’ and ‘cardiac inflammation’ were categorized in the cardiotoxicity functions analyzed in the IPA program (Table 3). The top three networks from IPA analysis results were TGFβ (12 proteins), extracellular signal-regulated kinase (ERK)1/2 (12 proteins), and transforming growth factor beta 1 (TGFB1)/NFκB (10 proteins), identifying these signaling pathways as the major hubs of DEP-induced heart damage (Fig. 3B).
Validation of proteomics findings by western blotting
To validate the proteomic data, we performed western blotting for two mechanistically relevant upregulated proteins, PF4 (Q9Z126) and SRGN (P13609). These proteins were selected due to their known regulatory roles in CVDs-related platelet activation22,23,24,25,26. Upregulation of PF4 (Q9Z126) and SRGN (P13609) protein levels was confirmed by western blotting, with comparable relative expression patterns to those of proteomic analysis (Fig. 4A and B). These data validated important mechanistic findings initially identified by proteomics analysis, and also supported the reliability of the proteomics data set.
Discussion
Previous epidemiological studies identified that environmental PM levels positively correlate with the severity and mortality rates of CVDs27,28. Specifically, several recent studies have demonstrated that PM exposure causes heart dysfunction by inducing cardiomyocyte apoptosis and production of inflammatory cytokines29,30,31 but the regulatory mechanisms for these pathologies remain incompletely understood. To delineate the regulatory mechanisms of PM-induced heart dysfunction, it is necessary to identify candidate proteins potentially responsible for development and progression of heart diseases. However, most studies investigating PM-related human disease have focused on differentially expressed proteins in lung, skin, and brain tissues32,33,34 and heart metabolite levels35. To further evaluate these pathologies, we established mouse models by exposing WT mice and ApoE−/− mice to DEP, with AngII-infused ApoE−/− mice as a positive control for robust heart fibrosis. While 100 μg of DEP was administered intratracheally into mice every 3 days for 25 days for induction of heart fibrosis, we had to select a specific dose of DEP because there were no established standard protocols to study the adverse effects of DEP in vivo. Previous studies used different protocols to investigate the adverse effects of DEP in vivo. Lee et al. exposed 50 µg of DEP to C57BL/6 mice by intratracheal instillation twice a week for 4 weeks and found that this experimental protocol caused the DNA damage in lung36. Another study showed that intratracheal instillation of 100 µg DEP on day 1 and day 4 and DEP + lipopolysaccharide (20 µg) on day 7 induced lung inflammation in a mouse model37. We were interested in investigating effects on mouse heart under the exposure of DEP. Thus, we hypothesized that more DEP had to be used because some portions of DEP injected into tracheal route would be trapped in airway or lung and the remaining portions of DEP would penetrate the respiratory system, circulate in blood vessels, and cause dysfunctions in heart. Although there was a previous study in which 200 µg of DEP was intratracheally instilled into C57BL/6 mice38, we selected 100 µg of extracted DEP in a single injection and repeated eight total times to induce potential heart damage. Heart protein expression analysis using LC–MS/MS was used to identify candidate proteins related to heart dysfunction in these models. Specifically, to identify differentially expressed proteins affected by DEP exposure in the ApoE−/− mouse model of CVDs, we used TMT as an isobaric labeling mass tags that allowed simultaneous quantification of multiple samples and is more precise than label-free quantification39,40. This approach was used for quantitative analysis in combination with high-resolution mass spectrometry.
Multiple delivery approaches have been used to expose animal models to PM, including inhalation, intratracheal instillation, and nasal inoculation. Inhalation is the most physiologically relevant method that can assess the real effects of human exposure to ambient PM but requires significant quantities of PM and a costly exposure chamber41. Contrastingly, the cost of intratracheal instillation is relatively low, and the components of intratracheally administered PM translocate to extrapulmonary tissue from the bloodstream and cause DNA damage in tissue42,43. Thus, many studies use intratracheal instillation to investigate the effect of PM on tissue damage, including the effects of PM on the cardiovascular system8,9,31,44. Furthermore, the intratracheal delivery approach also delivers particles to the lung more efficiently than the intranasal delivery approach45,46. Based on these studies, we utilized intratracheal DEP instillation even if the intratracheal instillation is not the most appropriate delivery of PM to study the effects of human exposure to ambient PM. Originally, we investigated differentially expressed proteins in hearts of WT mice exposed to DEP. However, we identified only 17 differentially expressed proteins meeting the criteria of |fold change|> 1.3 and P-value < 0.05 (Table S5). Myosin-3 (P13541, MYH3, > 1.43-fold) was increased in WT mice exposed to DEP. When mutated in the tail domain, MYH3 contributes to atrial septal defects47, but as a whole, the 17 differentially expressed proteins were insufficient for bioinformatic pathway analysis. Therefore, we performed bioinformatic analysis by exposing ApoE−/− mice, which are more susceptible to CVDs14,44, to DEP and conducting bioinformatic pathway analysis. Bioinformatic analysis of heart tissue from PBS- and DEP-treated ApoE−/− mice identified 52 differentially expressed proteins, with 39 proteins upregulated and 13 proteins downregulated by DEP treatment (Fig. 2). Among the upregulated proteins, five proteins, including latent-transforming growth factor beta-binding protein 1 (Q8CG19), were also upregulated in the well-known heart fibrosis mouse model of AngII infusion into ApoE−/− mice.
Among the 39 proteins upregulated in DEP-treated ApoE−/− mice (Table 1), platelet factor 4 (PF4, Q9Z126) was most highly upregulated (> 2.94-fold increase). PF4, also known as chemokine (C-X-C motif) ligand 4 (CXCL4), is an abundant platelet alpha-granule CXC chemokine released during platelet activation22. PF4 binds and neutralizes the glycosaminoglycan heparan sulfate, promoting platelet aggregation and thrombus formation22. Platelet activation at vessel injury sites prevents excessive bleeding and regulates hemostasis48. However, platelet hyperactivation has pathological roles in multiple human diseases, including CVDs such as myocardial infarction and atherosclerosis. For example, platelet function is elevated in patients with ST-segment elevation acute myocardial infarction (STEMI)49. PF4 released from platelets binds the LDLR, preventing LDL endocytosis and increasing vessel LDL retention time, which potentially increases LDL oxidation (ox-LDL)23. Monocyte uptake of ox-LDL transforms monocytes into foam cells and contributes to early atherosclerosis onset50. Furthermore, PF4 increases expression of E-selectin, which regulates endothelial inflammation and atherosclerosis24,51. This suggests that increased PF4 expression reflects platelet activation and ultimately leads to heart and blood vessel disease. While PDE5A (Q8CG03) was found to be highly upregulated by DEP exposure in ApoE−/− mice (> 2.41-fold increase), inhibition of PDE5A was previously found to prevent cardiac fibrosis by regulating the Smad signaling cascade52. It was also shown that PDE5A is involved in bleomycin-induced pulmonary fibrosis53, suggesting that upregulation of PDE5A by DEP exposure in ApoE−/− mice could be associated with tissue fibrosis. In addition, PDE5A−/− mice showed reduced cardiac rupture and inflammatory response after myocardial infarction54, and showed prolonged tail bleeding time and delayed thrombus formation, indicating that PDE5A regulates the function of platelet55. We identified that serglycin (SRGN, P13609) was highly upregulated by DEP exposure in ApoE−/− mice (> 2.30-fold increase). SRGN is an intracellular proteoglycan that colocalizes with PF4 in platelet ⍺-granules25,56. PF4 levels are profoundly decreased in platelets from Srgn−/− mice, and platelet aggregation potential is inhibited26, suggesting that SRGN upregulation could contribute to platelet activation. DEP exposure upregulated bridging integrator 2 (BIN2, D3Z6Q9) (> 2.10-fold increase). BIN2 interacts with stromal interaction molecule 1 and inositol trisphosphate receptor on platelets and regulates Ca2+ signaling57. Deletion of platelet BIN2 impairs thrombus formation, suggesting that BIN2 contributes to platelet activation57. We further identified that DEP exposure upregulated multimerin-1 (MMRN1, B2RPV6) and platelet glycoprotein V (GP5, O08742) (MMRN1 > 2.02-fold increase, GP5 > 1.87-fold increase). MMRN1 is a member of the EMILIN/multimerin family and is present in ⍺-granules of resting platelets and secretary granules of endothelial cells58,59. Following platelet activation, MMRN1 is secreted and binds fibrillar collagen to support platelet adhesion and thrombus formation60,61,62. GP5 is an abundant glycoprotein at the platelet surface, and is reported to bind collagen and mediate platelet adhesion and aggregation63. Further, soluble GP5 is a potential marker of thrombosis in ischemic stroke64. These prior studies suggest that DEP upregulation of MMRN1 and GP5 could activate platelets in ApoE−/− mice. Taken together, the prior and present findings suggest potential platelet activation in hearts of DEP-exposed ApoE−/− mice, which is consistent with GO enrichment analysis findings (Fig. 3A).
Mild fibrosis was present in hearts of ApoE−/− mice exposed to DEP (Fig. 1B, C). Consistent with this observation, transforming growth factor beta-1 proprotein (TGFB1 or TGFβ1, P04202) and latent-transforming growth factor beta-binding protein 1 (LTBP1, Q8CG19) were also upregulated in hearts of ApoE−/− mice exposed to DEP (TGFB1 > 1.88-fold increase, LTBP1 > 1.36-fold increase). IPA findings identified that TGFβ and TGFB1 were major hubs for DEP-induced heart fibrosis, and were in the first and third interaction networks (Fig. 3B). Cardiac fibrosis is characterized by transformation of cardiac fibroblasts into ⍺SMA-expressing myofibroblasts and subsequent dysregulation of extracellular matrix (ECM) protein expression, promoting cardiac dysfunction65. TGFβ, which is synthesized as a proprotein and processed into a mature form66, plays a critical role in progression of cardiac disease67. TGFβ induces transformation of fibroblasts to myofibroblasts and increases ECM protein expression68. TGFβ causes cardiac dysfunction by inducing cardiomyocyte hypertrophy and the endothelial-to-mesenchymal transition (EndMT)69,70,71. Further, age-associated myocardial fibrosis is decreased in TGFβ1-deficient mice, and ventricular fibrosis is exacerbated in TGFβ1-overexpressing mice72,73. Heart levels of LTBP1 were upregulated by both DEP exposure and AngII infusion (DEP exposure > 1.36-fold and AngII infusion > 1.48-fold increases of LTBP1 expression). LTBP1 forms a complex with TGFβ and targets extracellular fibrillin and fibronectin, where TGFβ is sequestered in a latent state74,75,76. When this complex is degraded by proteases or other stimuli, latent TGFβ is released and activates neighboring cells by binding its receptor, inducing multiple TGFβ-activated cellular phenotypes, including fibrosis76. The findings of the present study support potential involvement of TGFβ in DEP-induced heart fibrosis of ApoE−/− mice.
While the proteins including PF4, PDE5A, MMRN1, and GP5 that showed statistically significant increases in hearts of DEP-exposed ApoE−/− mice were known to be associated with thrombosis, thrombosis is a blood clot within blood vessel that disrupts the blood flow77. Although the roles of platelet in thrombosis, fibrosis, and blood vessel remodeling were reported9,78,79, the direct evidence for the relationship between thrombosis and fibrosis seems to be limited. Disturbed blood flow pattern induces vascular inflammation and EndMT80,81. Zeisberg et al. reported that cardiac fibrosis is associated with the appearance of fibroblast originated from endothelial cells82. It was shown that inhibition of EndMT by administration of bone morphogenic protein 7 attenuated the progression of cardiac fibrosis82. This result implies that EndMT induced by thrombosis-mediated blood flow disruption may be able to contribute to the cardiac fibrosis. However, more studies are required to elucidate the relationship between thrombosis and cardiac fibrosis.
We previously characterized the chemical components of DEP13. DEP consist of organic carbon, ions, elemental carbon, and elements. Because we extracted filter-collected particles with PBS in the present study, intratracheally instilled DEP would be likely to contain water soluble fractions such as ions and some elements. However, the adverse effects of individual ions and elements on the heart are not clear. Although phosphorus is a candidate element for cardiac fibrosis83, further studies are required to examine the effects of each component on heart fibrosis and platelet activation.
Since previous studies showed that PM exposure to heart in mouse model induced cardiac fibrosis through TGFβ and Smad3 signaling cascade84,85 and that PM exposure could induce platelet activation and thrombosis9,11, our findings in the current study may have some similarity to the previous reports. However, we think that our proteomics-based approach allows for discovery of new protein targets such as PF4 and PED5A using proteomic analysis because most of the previous studies focused on exploring some known targets that were related to cardiac fibrosis and platelet activation/thrombosis.
In conclusion, we identified that candidate proteins and biomechanical pathways which could contribute to heart damage were induced by DEP exposure in the ApoE−/− mouse model. Specifically, we focused on platelet-dependent pathways in heart dysfunction because prior studies have suggested that air pollution has prothrombotic effects that contribute to human diseases10,86. Thus, future studies will be aimed at determining the precise roles of proteins that regulate platelet activation and thrombosis such as PF4, SRGN, BIN2, MMRN1, and GP5 in DEP-induced heart damage.
Methods
PM preparation
Engine exhaust particles were produced with a diesel engine (498 cc, DG8500SE, Hi-Earns Mechanical and Electrical Co., Ltd., Changzhou, China) and collected on filters using a low-volume PM2.5 sampler (URG-2000-30EH, URG, Chapel Hill, NC, USA) at a flow rate of 16.7 L/min for 30 min as described previously13. The mass of the collected PM2.5 was determined based on the weight of the filter, which was equilibrated at 21 ± 2 °C and relative humidity 35 ± 5% for 24 h before and after collection. The weights of the filter that were measured before and after DEP collection were 85.1200 mg and 194. 3967 mg, respectively. DEP with diameter < 2.5 μm were collected on a glass fiber filter (Pall Corporation, Port Washington, NY, USA) and extracted with phosphate-buffered saline (PBS, Sigma-Aldrich, St. Louis, MO, USA). Extracted DEP were filtered through a 0.2 μm PTFE syringe filter (Sartorius AG, Germany) prior to treating mice.
Animal experiments
Animal experiments were performed by Knotus (Incheon, Republic of Korea) and approved by the Institutional Animal Care and Use Committee (KNOTUS 20-KE-017). All methods for the animal experiments were performed in accordance with the relevant guidelines and regulations. Animals were euthanized by isoflurane and all efforts were taken to minimize their suffering. These experimental procedures are consistent with those outlined in the ARRIVE guidelines. Seven-week-old male apolipoprotein E knockout (ApoE−/−) mice or C57BL/6 wild-type (WT) mice were purchased from Jackson Laboratory (Bar Harbor, ME, USA) and adapted to the facility for 1 week. Mice were divided into five groups (n = 3 mice/group): (1) intratracheal administration of PBS in WT mice (PBS-treated WT mice), (2) intratracheal administration of DEP in WT mice (DEP-treated WT mice), (3) intratracheal administration of PBS and saline infusion in ApoE−/− mice (PBS-treated ApoE−/− mice), (4) intratracheal administration of DEP and saline infusion in ApoE−/− mice (DEP-treated ApoE−/− mice), and (5) intratracheal administration of PBS and angiotensin II infusion (AngII, Sigma-Aldrich) in ApoE−/− mice (AngII-infused ApoE−/− mice). For infusion, mice were anesthetized, and an osmotic pump (Alzet, Cupertino, CA, USA) filled with AngII (1000 ng/kg/min) or saline was subcutaneously administered on Day 0 such that AngII or saline was perfused throughout the experiment. From the following day (Day 1), mice were anesthetized and treated with extracted DEP (100 µg) that included soluble components in PBS and particles smaller than 0.2 µm or PBS via intratracheal administration. Mice were treated with DEP or PBS every 3 day for 25 days (eight total exposures); 3 days following the final treatment, they were euthanized. Hearts were removed, fixed in 10% neutral buffered formalin, and embedded in paraffin. Tissue sections (5 μm) were cut, deparaffinized, and subjected to Masson’s trichrome staining. The fibrotic area was observed using an EVOS M5000 Imaging system (Invitrogen, Carlsbad, CA, USA), and the fibrotic area was quantified using Image J software. Briefly, the blue positive area was divided by the total area for each field, and the average value, which means the fibrotic area, was calculated for each group84. Analysis was performed by blinded persons to the groups. When hearts were removed, some part of hearts were frozen and used for the proteomic analysis or western blotting.
In-solution digestion for proteomic analysis
Heart tissues were first lysed in lysis buffer (7 M Urea, 2 M Thiourea, 1 mM EDTA, 150 mM NaCl, 50 mM Tris–HCl pH 7.5, and protease inhibitor cocktail (Roche Diagnostics, Mannheim, Germany)) using a probe-type sonicator (Sonics & Materials, Newtown, CT, USA). Protein concentrations were determined using a Bradford protein assay (Bio-Rad Laboratories, Inc. Hercules, CA, USA). Prior to in-solution digestion, all samples were diluted using 25 mM ammonium bicarbonate (ABC) to equalize concentrations. Urea was added to samples to a final concentration of 8 M. Samples were then reduced with 5 mM tris(2-carboxyethyl) phosphine hydrochloride and alkylated with 10 mM iodoacetamide. After samples were treated with 25 mM ABC to decrease the urea concentration to < 1 M, samples were digested with lysyl endopeptidaseR (Lys-C, Fujifilm Wako Pure Chemical Corporation, Osaka, Japan) at an enzyme/substrate ratio of 1 mAU Lys-C per 50 μg total protein at 30 °C for 2 h87. Trypsin was then added to the samples (Promega, Madison, WI, USA) at a protease to substrate ratio of 1:50 (wt/wt) and incubated at 37 °C overnight. Digested peptide samples were desalted using a Sep-Pak tC18 cartridge (Waters Corporation, Milford, MA, USA) and subsequently dried in a miVAC vacuum concentrator (Genevac Ltd., Ipswich, UK). After samples were resuspended in 100 mM triethyl ammonium bicarbonate (TEAB), peptide concentrations were determined using a quantitative colorimetric peptide assay kit (Thermo Fisher Scientific, Rockford, IL, USA).
Tandem mass tag (TMT) labeling and basic pH reversed‑phase liquid chromatography
After TMTpro 16plex label reagents (0.5 mg per vial, Thermo Fisher Scientific, Rockford, IL, USA, VF304377 (lot number)) were resuspended in 42 μL of anhydrous acetonitrile (ACN), 20 μL of each label reagent was added to 30 μg of each peptide samples for labeling and the labeling reactions were made for 60 min at room temperature. Then, 5 μL of 5% hydroxylamine in 100 mM TEAB was added to each peptide sample and incubated for 15 min to quench the labeling reactions. Equal amounts of TMT-labeled samples were then combined, desalted using a Sep-Pak tC18 cartridge, and dried in a miVAC vacuum concentrator. TMT-labeled peptide samples were resuspended in 10 mM ammonium formate (AF), and peptide concentrations were determined using a quantitative colorimetric peptide assay kit. Then, 410 μg peptide sample was loaded onto an X-Bridge peptide BEH C18 column (4.6 mm i.d. × 250 mm length; pore size 130 Å; particle size 3.5 μm, Waters Corporation) and fractionated by basic pH reversed-phase liquid chromatography using an Agilent 1290 Infinity liquid chromatography (LC) system (Agilent Technology, Santa Clara, CA). Peptides were separated at a flow rate of 0.5 mL/min with the following gradient conditions: 0 min 100% buffer A (10 mM AF, pH 10) and 0% buffer B (10 mM AF, pH 10 in 90% acetonitrile), 0–10 min 0–5% B, 10–48.5 min 5–40% B, 48.5–62.5 min 40–70% B, 62.5–72.5 min 70% B, 72.5–82.5 min 70–5% B, and 82.5–92.5 min 5% B. Fractionation was conducted by collecting 96 wells (1 well/0.8 min, Restek corporation, Bellefonte, PA, USA) during the chromatographic run (10–82.5 min). The resultant 96 fractions were pooled to 24 concatenated fractions, dried, and subsequently resuspended in 17.08 μL 0.4% acetic acid.
Liquid chromatography and tandem mass spectrometry (LC–MS/MS) analysis
Three µg fractionated peptide samples were injected into a trap column (2 cm × 75 µm i.d., 100 Å, 3 µm) and separated on a reversed-phase Acclaim PepMap RSLC C18 column (50 cm × 75 µm i.d., 100 Å, 2 µm) using an UltiMate 3000 RSLCnano System (Thermo Fisher Scientific). Column temperature was constantly set to 50℃ with a column heater The operating flow rate was 300 nL/min with the following gradient conditions: 0 min 95% buffer A (100% water with 0.1% formic acid) and 5% buffer B (100% acetonitrile with 0.1% formic acid), 0–4 min 5% B, 4-13 min 5–10% B, 13–150 min 10–25% B, 150–155 min 25–28% B, 155–160 min 28–40% B, 160–165 min 40–80% B, 165–170 min 80%B, 170–170.1 min 80–5% B, and 170.1–180 min 5–0%B. The nano UHPLC system was coupled to an Orbitrap Eclipse Tribrid Mass Spectrometer (Thermo Fisher Scientific). MS1 data were collected using an Orbitrap (120,000 resolution; scan range 350–2000 m/z; maximum injection time 50 ms; automatic gain control (AGC) 4 × 105). Determined charge states between 2 and 6 were required for sequencing, and a 30 s dynamic exclusion window was used. Data-dependent ‘top 20’ MS2 scans were performed in an 0.5 Da ion trap isolation window with collision-induced dissociation (CID) fragmentation (NCE 35%; maximum injection time 35 ms; AGC 1 × 104). MS3 quantification scans were performed using the multinotch MS3-based TMT method88 (ten synchronous precursor selection (SPS) ions; 50,000 resolution; NCE 55% for higher-energy collisional dissociation (HCD); maximum injection time of 130 ms; AGC 1.5 × 105).
Data processing for protein identification and quantification
MS raw files were searched against the SwissProt mouse database (November 2020) with 17,196 entries using Proteome Discoverer software (version 2.4, Thermo Fisher Scientific). The search criteria were set to a mass tolerance of 10 ppm for MS data and 0.6 Da for MS/MS data with fixed modifications for cysteine carbamidomethylation (+ 57.021 Da), TMT on lysine residues and peptide N termini (+ 304.207 Da), and variable modification of methionine oxidation (+ 15.995 Da). The false discovery rate (FDR) was set to 0.01 for identification of peptides and proteins. All proteins were identified by one or more unique peptides. Reporter ion quantification was performed with a 20 ppm mass tolerance, and signal-to-noise ratio values of reporter ions were used for peptide quantification. Only spectra with an average reporter signal-to-noise ratio threshold ≥ 10 across 16 TMTpro 16-plex channels were considered for quantification. The signal-to-noise ratio values of each reporter ion channel were summed across all quantified proteins and normalized to make the summed signal-to-noise ratio values of each channel equal across all 16 channels. The normalized signal-to-noise ratio values were first log-transformed, and missing values were then replaced using values computed from the normal distribution with a width of 0.3 and a downshift of 1.8. Proteins exhibiting statistical significances between two types of mouse groups (Student’s t test comparison of the log2(normalized signal-to-noise ratio) values P < 0.05) were identified. Statistical significance was calculated using Perseus software (1.6.14.0)89.
Bioinformatics analysis
A volcano plot of peptides with quantitative information was constructed using Perseus (1.6.14.0) according to statistical P-value (-log10P-value as y-axis) and relative abundance ratios (log2fold change as x-axis) between PBS- and DEP-treated ApoE−/− mice. For hierarchical clustering of proteins with statistically significant changes (P-value < 0.05, > 1.3-fold) between PBS- and DEP-treated ApoE−/− mice, log2(normalized signal-to-noise ratio) values were first normalized using the z-score, and subsequent clustering of both columns and rows was conducted based on Euclidean distance with the average linkage method using Perseus (1.6.14.0). GO functional classifications of proteins with statistically significant upregulation (P-value < 0.05, > 1.3-fold) between PBS- and DEP-treated ApoE−/− mice were analyzed using DAVID software (http://david.abcc.ncifcrf.gov) to identify GO terms that were significantly enriched in the proteins. Additionally, IPA software (data version 81348237; QIAGEN, Redwood City, CA) was used to analyze molecular and cellular functions and the associated network functions of proteins exhibiting statistically significant increases in DEP-treated ApoE−/− mice relative to PBS-treated ApoE−/− mice.
Western blotting
Frozen heart tissue was lysed in cell lysis buffer (Cell Signaling Technology, Beverly, MA, USA) supplemented with protease inhibitor cocktail (Sigma-Aldrich). Equal amounts of cell lysates were separated by sodium dodecyl sulfate–polyacrylamide gel electrophoresis. Proteins were transferred onto Immuno-Blot polyvinylidene difluoride membranes (Bio-Rad Laboratories) and subsequently blocked in 5% nonfat milk (Santa Cruz Biotechnology, Santa Cruz, CA, USA) in 0.1% Tween 20-containing tris-buffered saline (TBS) for 1 h. Membranes were cut to include the corresponding protein molecular weight sizes and incubated overnight at 4 °C with the appropriate primary antibodies. After washing three times with 0.1% Tween 20-containing TBS, membranes were incubated with horseradish peroxidase-conjugated secondary antibody (1:5,000 dilution, Santa Cruz Biotechnology) for 1 h. After washing with 0.1% Tween 20-containing TBS, signals were visualized using an ImageQuant LAS4000 mini system (GE Healthcare, Chicago, IL, USA) using Western Blotting Luminol Reagent (Santa Cruz Biotechnology). Densitometric analysis was performed using Image J software. ⍺-smooth muscle actin (SMA) antibody was purchased from Abcam (Cambridge, UK). PF4 antibody was purchased from R&D systems (Minneapolis, MN, USA). Serglycin (SRGN) antibody was purchased from Santa Cruz Biotechnology. ⍺-tubulin antibody was purchased from Sigma-Aldrich.
Statistics
Western blotting results are presented as means ± SD. Statistical significance between two groups was evaluated using a two-tailed Student’s t test. Statistical significance between more than two groups was evaluated using one-way ANOVA. P-value < 0.05 was considered significant.
Data availability
The data analyzed in the current study are available from the corresponding author on reasonable request. The mass spectrometry data have been deposited to the ProteomeXchange Consortium via the PRIDE90 partner repository with the dataset identifier PXD045029.
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Acknowledgements
This work was supported by both intramural research grants from the Korea National Institute of Health to Dr. Geun-Young Kim (2019-NI-101-01 and 2021-NI-024-01) and by the International Research & Development Program of the National Research Foundation of Korea (NRF) funded by the Ministry of Science and ICT (2019K1A4A7A02102530) to Dr. Ji Eun Lee.
Funding
Korean Ministry of Science and ICT, 2019K1A4A7A02102530, Korea National Institute of Health, 2019-NI-101-01 and 2021-NI-024-01.
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I.J. and Y.J.C. performed experiments and equally contributed to this study. M.P. and K.P. generated DEP. S.H.L., W–H.K. and H.J. analyzed and interpreted data. J.E.L. and G-Y.K. equally designed the study, wrote the manuscript, and supervised the project. All of the authors have read and approved the paper.
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Jung, I., Cho, Y.J., Park, M. et al. Proteomic analysis reveals activation of platelet- and fibrosis-related pathways in hearts of ApoE−/− mice exposed to diesel exhaust particles. Sci Rep 13, 22636 (2023). https://doi.org/10.1038/s41598-023-49790-y
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DOI: https://doi.org/10.1038/s41598-023-49790-y
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