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. 2020 Sep 25;192:110244. doi: 10.1016/j.envres.2020.110244

Urban air PM modifies differently immune defense responses against bacterial and viral infections in vitro

Muhammad Ali Shahbaz a,∗, Maria-Viola Martikainen a, Teemu J Rönkkö a, Mika Komppula b, Pasi I Jalava a, Marjut Roponen a
PMCID: PMC7516585  PMID: 32980306

Abstract

Epidemiological evidence has shown the association between exposure to ambient fine particulate matter (PM) and increased susceptibility to bacterial and viral respiratory infections. However, to date, the underlying mechanisms of immunomodulatory effects of PM remain unclear. Our objective was to explore how exposure to relatively low doses of urban air PM alters innate responses to bacterial and viral stimuli in vitro. We used secondary alveolar epithelial cell line along with monocyte-derived macrophages to replicate innate lung barrier in vitro. Co-cultured cells were first exposed for 24 h to PM2.5-1 (particle aerodynamic diameter between 1 and 2.5 μm) and subsequently for an additional 24 h to lipopolysaccharide (TLR4), polyinosinic-polycytidylic acid (TLR3), and synthetic single-stranded RNA oligoribonucleotides (TLR7/8) to mimic bacterial or viral stimulation. Toxicological endpoints included pro-inflammatory cytokines (IL-8, IL-6, and TNF-α), cellular metabolic activity, and cell cycle phase distribution. We show that cells exposed to PM2.5-1 produced higher levels of pro-inflammatory cytokines following stimulation with bacterial TLR4 ligand than cells exposed to PM2.5-1 or bacterial ligand alone. On the contrary, PM2.5-1 exposure reduced pro-inflammatory responses to viral ligands TLR3 and TLR7/8. Cell cycle analysis indicated that viral ligands induced cell cycle arrest at the G2-M phase. In PM-primed co-cultures, however, they failed to induce the G2-M phase arrest. Contrarily, bacterial stimulation caused a slight increase in cells in the sub-G1 phase but in PM2.5-1 primed co-cultures the effect of bacterial stimulation was masked by PM2.5-1. These findings indicate that PM2.5-1 may alter responses of immune defense differently against bacterial and viral infections. Further studies are required to explain the mechanism of immune modulation caused by PM in altering the susceptibility to respiratory infections.

Keywords: Ambient particulate matter, Toll-like receptor, Lipopolysaccharides, Poly: IC, ORN R-0006, Respiratory infections

1. Introduction

Exposure to ambient air pollution causes up to 4.2 million annual premature deaths worldwide (Cohen et al., 2017). One major component of air pollution is particulate matter (PM). PM is a mixture of solid and liquid particles (organic and inorganic-derived particles) dispersed in ambient air. Its size, shape, and composition vary depending on the source of origin. Generally, PM originates from natural (e.g. airborne dust, volcanic activity, and pollen) or anthropogenic sources (e.g. industry and traffic primarily by different combustion processes). It has been classified according to aerodynamic diameter into coarse (≤10 μm), Fine (≤2.5 μm), and ultra-fine (≤0.1 μm) PM (US EPA, 2016). The size of the particles directly links with the potential of PM for causing detrimental health outcomes. PM with an aerodynamic diameter less than 2.5 μm (PM2.5) are among the most studied air pollutants of health concern since smaller particles are more likely to penetrate deeper in the lungs and encounter lung surface (Xing et al., 2016). PM2.5 is not a self-contained pollutant; it contains a heterogeneous combination of solid and liquid particles, which not only includes chemicals but also biological fractions (Kelly and Fussell, 2012). Epidemiological evidence suggests that there is an increasing risk of developing bacterial and viral respiratory infection with exposure to ambient air pollution, in particular, fine particulate matter (Ciencewicki and Jaspers, 2007; Croft et al., 2019; Horne et al., 2018; Zhang et al., 2019). Furthermore, the recent coronavirus epidemic emphasizes the need for a detailed understanding of the link between air pollution and respiratory infection. Nationwide U.S cross-sectional study has highlighted the association between a small increase in long term exposure to PM2.5 and an increased risk of mortality due to COVID-19 infection (Wu et al., 2020). In experimental models, fine PM exposure has increased the risk of pneumonia due to the deleterious effect on alveolar macrophages and alveolar epithelium (Migliaccio et al., 2013; Mushtaq et al., 2011). As reviewed in Wei and Tang (2018) few studies have focused on the immune-modulatory effect of fine PM and its effects on the immune response to respiratory infections. Therefore, it is crucial to explore links between fine PM exposure and alteration in the immune response to bacterial and viral respiratory infections since large populations are exposed to air pollutants and respiratory infections may spread more rapidly in the densely populated areas.

Alveolar epithelium and alveolar macrophages serve as pillars in the innate immune system of the respiratory tract. Inhaled pathogens must evade the innate immune system to establish infections (Bhattacharya and Westphalen, 2016). In vitro co-culture of secondary epithelial cells (A549 cells) and THP1 monocytes, differentiated into macrophage-like cells have been used in immunological and toxicological studies on the respiratory health to better understand the effect of cell-cell interaction and to better mimic the first line of defense i.e., alveolar epithelium and macrophages (Dehai et al., 2014; Holownia et al., 2015).

Family of Toll-like receptors (TLRs) expressed by epithelial and dedicated immune cells are an important component in pathogen recognition and innate immune response (Medzhitov, 2001). Activation of TLRs on airway epithelial cells has been shown to induce the production of several cytokines, chemokines, and antimicrobial peptides (Guillot et al., 2005; Hertz et al., 2003; Sha et al., 2004). The importance of TLRs for the host defense in the lung has been demonstrated by the increased susceptibility of TLR knockout mice towards viral or bacterial infections (Takeuchi et al., 2000; Wetzler, 2003). This is because each member of TLR family recognizes specific pathogen-associated molecular patterns (PAMPs), e.g., TLR3 is activated by virus-derived double-stranded RNA (Alexopoulou et al., 2001) and TLR4 by bacterial lipopolysaccharides (Beutler, 2002), whereas TLR7 and TLR8 recognize single-stranded viral RNA (Diebold et al., 2004; Heil et al., 2004). In our study, TLR ligands were used to mimic bacterial and viral stimuli, i.e., polyinosinic-polycytidylic acid (Poly I:C), which represents virus-derived double-stranded RNA and activates TLR3, lipopolysaccharide (LPS) (Gram-positive bacteria, TLR4), and synthetic single-stranded RNA oligoribonucleotide (ORN R-0006) (single-stranded viral RNA, TLR7/8). Previously, ligands have been also used for mimicking bacterial and viral stimuli (Diebold et al., 2004; Kumar et al., 2006; Park and Lee, 2013).

In the present study, we aimed to unravel how acute exposure to relatively low doses of fine PM alters the immune response to bacterial and viral stimuli. We used urban air PM2.5-1 (fraction of PM that have an aerodynamic diameter of 2.5–1.0 μm) to expose the co-cultured cells in a two-step submerged exposure model. First, cells were primed with a dose range of PM2.5-1 for 24 h, and in the second step, they were exposed to bacterial TLR4 ligand (LPS), viral ligand TLR3 (Poly I:C), and TLR7/8 ligand (ORN R 006).

2. Methods

2.1. Particulate matter samples

We used PM samples obtained from a sampling campaign conducted in China during 2014. PM samples were collected at Nanjing University (NJU) Xianlin campus. Details of the collection method, the origin of the sample, PM composition, and method of size-segregation have been described earlier by Jalava et al. (2015) and Rönkkö et al. (2018). In brief, we used PM2.5-1 samples collected with high volume cascade impactor during night time. The sampler collects four different size ranges, from which the fine particle size was chosen for this study. PM2.5-1 samples were stored at −20 °C until the day of the exposure. On the day of exposure PM2.5-1 samples were suspended in 10% dimethyl sulfoxide (DMSO) (Sigma Aldrich, USA) in endotoxin tested water (Sigma, W1503) and sonicated for 30 min before utilization for exposure. After administrating the samples to cell culture medium, the final DMSO concentration was <0.3%.

2.2. Co-culture model

We utilized the A549-THP1 co-culture, which has been previously described by Kasurinen et al. (2018). Briefly, type II human alveolar epithelial cell line (A549) and human monocytic cell line THP-1 were purchased from ATCC (ATCCRCCL-185™) and German Collection of Microorganisms and Cell Cultures (DSMZ, Germany) respectively. A549 cells were routinely maintained in Dulbecco's Modified Eagle Medium (DMEM), supplemented with 10% fetal bovine serum (FBS), 2 mM L-glutamine (L-glut), and 100 U/ml penicillin/streptomycin. THP-1 cells were maintained in Roswell Park Memorial Institute (RPMI) 1640 culture medium (Life Sciences, Gibco) supplemented with 10% FBS, 2 mM L-glut, and 100 U/ml pen/strep. THP-1 monocytic cells were differentiated to active macrophage-like cells before co-culture experiments with phorbol 12-myristate 13-acetate (PMA) (Kasurinen et al., 2018). After establishing co-culture, both cell lines were cultured in DMEM. All reagents were purchased from Sigma-Aldrich (USA) unless noted otherwise.

For the co-culture experiments, A549 cells were seeded in 12-well plates at a seeding density of 120,000 cells per well in FBS supplemented media and allowed them to attach for 4 h. Once the A549 cells were attached to the bottom of the well, media in the wells was aspirated and activated macrophage-like THP-1 cells were seeded at a seeding density of 24,000 cells per well on top of attached A549 cells. The co-cultured cells were incubated at 37 °C and 5% CO2 for 40 h before exposing the cells to the first exposure. The seeded co-culture yields approximately 400,000–600,000 cells per well after the end of the exposure. One hour before the exposure the co-culture medium was replaced with fresh medium supplemented with 5% FBS, 2 mM L-Glut, and 100 U/ml (pen/strep).

2.3. Cell exposure

The study was designed as a two-step submerged exposure. Co-cultured cells were exposed to three concentrations of PM2.5-1 (25 μg/ml, 50 μg/ml, and 100 μg/ml corresponding to 6.6, 13.2, and 26.3 μg/cm2) in duplicate wells for 24 h at 37 °C and 5% CO2.

The PM2.5-1-exposed cells were then co-exposed for next 24 h to fixed doses of three different ligands: 1 μM of ORN R-0006 (TLR7/8 ligand, Miltenyi Biotech), 25 μg/ml of Poly IC (TLR3 ligand, Miltenyi Biotech), and 50 ng/ml of lipopolysaccharide (LPS) (TLR4 ligand). All the ligands were reconstituted and used according to the manufacturers’ instructions. Various controls were included in the experimental setup, i.e. unexposed control, PM2.5-1 control (for each concentration), ORN R-0006 control, Poly IC control, and LPS control.

At the end of co-exposure, cell culture media was retrieved and stored at −80 °C for the cytokine analysis. The cells were then detached using 1 ml trypsin-EDTA and 5 min incubation at 37 °C, followed by adding 100 μl of FBS to inactivate trypsin. 300 μl of the cell suspension was then separated for MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide) assay and viability assay. The remaining 700 μl of cell suspension was centrifuged at 4000 RCF for 5 min at 4 °C. The supernatant was carefully removed, and the cell pellet was then suspended in PBS. FBS-free cell suspension was used for 2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA) assay, propidium iodide (PI) exclusion assay, and thiol assay.

2.4. Inflammatory cytokine analysis

We performed the sandwich enzyme-linked immunosorbent assay (ELISA) for quantitative cytokine analysis from the co-culture cell supernatant samples stored at −80 °C. Measured pro-inflammatory markers included interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α) (all ELISA Ready-SET-Go kit, Invitrogen), interleukin 8 (IL-8) (ELISA, R&D-Systems, USA). All the ELISA's were performed according to the manufacturer's instruction for each kit.

2.5. Cellular metabolic activity

Cellular metabolic activity (CMA) was analyzed by treating 100 μl aliquots of cell suspension from each sample in duplicates with 25 μl of MTT solution (5 mg/ml in PBS) in 96 well plate for 2 h at 37 °C and 5% CO2. During incubation, live cells uptake yellow MTT and metabolize it to purple formazan. After incubation, 100 μl of sodium dodecyl sulfate (SDS) lysis buffer was added to each well. Cells were then lysed for 2 h at 37 °C and 5% CO2 followed by 30 min at room temperature on a plate shaker to release formazan from the cells. After incubation, absorbance was measured at 570 nm using a Synergy H1, Microplate reader (BioTek, USA). The absorbance values of the exposed cells were then normalized against the untreated controls and the percentage of cellular metabolic activity was calculated by the following formula: ((absorbance exposed/absorbance control) *100%).

2.6. Oxidative stress

2′,7′-dichlorodihydrofluorescein diacetate (H2DCF-DA) was used to measure the cellular oxidative stress. Cells suspended in PBS (100 μl aliquots) were pipetted to 96 well plate wells in duplicates. 8 μl of H2DCF-DA (0.5 μM in DMSO) was added to each well and 2′, 7’ –dichlorofluorescein (DCF) fluorescence was measured at 3-time points (0, 30, and 60 min) using 485 nm excitation and 530 nm emission with Synergy H1 Microplate reader (BioTek, USA). Area under the curve (AUC) for the increasing fluorescence values against time was calculated using ((15*T60) + (30*T30) - (45*T0)) for all treated and control samples. The values for exposed samples were then normalized against unexposed control.

2.7. Membrane permeability

After the cellular oxidative stress measurement, the same 96-well plated cells were used for the PI exclusion test. We added 7.2 μl of PI solution (0.5 mg/ml in PBS) to each well and mixed the plate for 2 min on a plate shaker. The cells were incubated for 20 min at 37 °C and 5% CO2 in a humidified incubator before measuring baseline PI fluorescence (540 nm excitation and 610 nm emission using Synergy H1 Microplate reader (BioTek, USA). Then 20 μl of lysis solution (10% Triton X-100 in double-distilled water) was added and the cells were incubated room temperature. After 20 min of incubation, maximum PI fluorescence was measured at the same settings as for baseline. The percentage of live cells was calculated by using formula (100-((PIbaseline/PImax)*100%)).

2.8. Viability with DAPI staining

Cell viability and proliferation were analyzed using DAPI staining. Every cell sample was stained with solution 13 (Acridine Orange (AO) and 4′6-diamidino-2-phenylidinole (DAPI) (Chemometec, Denmark) in a ratio of 19:1. Stained samples were analyzed with Nucleocounter NC-3000 (Chemometec, Denmark) using protocol provided by the manufacturer.

2.9. Cell cycle analysis

Duplicate experiments on separate culture plates were performed to obtain cells for cell cycle analysis. Briefly, cells were harvested after exposures and fixed using 70% ethanol. Fixed cells were then stored at −20 °C until analysis was performed. For analysis, cells were centrifuged at 400–500 RCF at 4 °C, and ethanol was discarded without disturbing the cell pellets. Cell pellets were washed with PBS, centrifuged, and suspended again in PBS before treating them with 15 μg/ml of RNAse-A dissolved in DNAse/RNAse-free water (Sigma-Aldrich, Italy) for 1 h at 50 °C on heat block in a darkroom. After incubation cells were then stained with propidium iodide (final concentration in sample tube 0.01 mg/ml) and incubated at 37 °C for 30 min. Samples were kept at 4 °C and in the dark until analyzed using a BD FACSCanto™ II (BD Biosciences, San Jose, CA, USA). Results were analyzed further using FLOWJO. Results were presented as percentages of cells in Sub-G1, G1-GO, and G2-M phase.

2.10. Apoptosis marker analysis

We analyzed the redox status of cellular thiols as a marker for apoptosis. 19 μl of the cell suspended in PBS was mixed with 1 μl of Solution 5 (VitaBright-48 (VB-48), Acridine Orange (AO), and Propidium Iodide (PI), ChemoMetec, Denmark). Samples were loaded on NC-Slide A8 and analyzed on Nucleocounter NC-3000 (ChemoMetec, Denmark) using a premade protocol provided by the manufacturer. The scatter plots obtained from Nucleocounter were analyzed using FlowJo software version 10 (FlowJo LLC, USA). Live and dead cells were gated, and then live cell populations were further marked to separate the low intensity and high intensity VB-48 stained cells. Cells that are apoptotic or with low levels of reduced thiols have low VB-48 stains. The percentage of cell with low-intensity VB-48 stains were considered as apoptotic cell population.

2.11. Statistical analyses

All experiments were performed three times and all analysis were run in duplicates. The data have been presented as means and standard error of means (SEM). The data of all studied variables were normally distributed and thus fulfilled assumptions of parametric testing. Levene's test was used to test the homogeneity of variances. Since they were unequal, comparisons between exposed samples and control samples as well as comparisons between different exposures were made using Welch's analysis of variance, followed by Dunnett's T3 post hoc test. Values of P < 0.05 were considered statistically significant. IBM SPSS statistics software, version 25 was used for all statistical analyses.

3. Results

PM stimulation increased the production of IL-6 in a dose-dependent manner in the co-cultured cells. Of the studied viral ligands, TLR7/8 induced the highest production of IL-6 whereas TLR3 induced a marginal increase in IL-6 production compared to unexposed control cells. TLR4 also significantly increased the IL-6 production relative to the unexposed control. In co-exposure to PM and TLR7/8, the IL-6 release of the cells increased significantly at the lowest PM dose when compared to responses of the cells after PM exposure only. However, PM and TLR7/8 co-exposure resulted in much lower IL-6 concentrations than for TLR 7/8 ligand alone. With the highest PM dose, IL-6 levels were not only lower than after exposure to TLR-7/8 ligand alone but they were also decreased when compared to IL-6 release after the cells were exposed to same PM mass without the ligand. Co-exposure to PM and TLR3 induced lower cytokine secretion than PM alone. In contrast, co-exposure to PM and TLR4 caused IL-6 production that was higher than that of cells exposed to either PM or TLR4 alone (Fig. 1 ).

Fig. 1.

Fig. 1

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IL-6 pro-inflammatory cytokine production was assessed after two-step submerged exposure. Co-cultured cells were first exposed to three doses (25, 50, 100 μg/ml) of PM2.5-1 and after 24 h, to three different Toll-like receptor ligands (TLR7/8, TLR3, TLR4) for another 24 h. Figure shows mean ± SEM, n = 3. Significance was assumed at p < 0.05. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50. ¤ indicates significance from ligand-PM100.

PM increased the production of TNF-α dose-dependently. TLR7/8 induced the highest production of TNF-α, whereas TLR3 was not able to induce TNF-α production in our cell model. TLR4 induced slight but non-significant increase in TNF-α production. Ιn PM and TLR7/8 co-exposures, production of TNF-α was approximately the same for all PM doses and comparable to the response after exposure to highest PM dose alone, but significantly lower than after exposure to TLR7/8 alone. Interestingly, when the cell model was co-exposed to PM and TLR3, cytokine secretion was lower than in stimulation with PM alone, but the difference was not statistically significant. In contrast to other two ligands, cells primed PM responded to TLR4 exposure by significantly enhanced TNF-α production (Fig. 2 ).

Fig. 2.

Fig. 2

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TNF-α pro-inflammatory cytokine production was accessed after two-step submerged exposures described in Fig. 1. Figure shows mean ± SEM, n = 3. Significance was assumed at p < 0.05. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50. ¤ indicates significance from ligand-PM100.

In co-exposure to PM and TLR7/8, the production of IL-8 increased slightly for the lowest two doses when compared to respective PM dose alone. However, no significant indication of additive effects of PM and TLR7/8 was observed at any of the dose levels. Similar to TLR7/8, co-exposure to PM and TLR3 induced roughly the same level of cytokine secretion than PM. In contrast, co-exposure to PM and TLR4 caused IL-8 production that was higher than that of cells exposed to PM or TLR4 alone (Fig. 3 ).

Fig. 3.

Fig. 3

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IL-8 pro-inflammatory cytokine production was accessed after two-step submerged exposures described in Fig. 1. Figure shows mean ± SEM, n = 3. Significance was assumed at p < 0.05. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50. ¤ indicates significance from ligand-PM100. PM alone increased the production of IL-8 dose-dependently. Of the studied ligands, TLR7/8 induced the highest, and TLR3 the lowest IL-8 production.

PM alone induced a dose-dependent decrease in CMA. Studied TLR ligands alone did not affect the CMA when compared to the unexposed control. CMA following co-exposure to PM and TLR ligands did not differ from that observed after exposure to PM alone (Fig. 4 ).

Fig. 4.

Fig. 4

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Cellular metabolic activity (CMA) was assessed using the MTT after two-step submerged exposures described in Fig. 1. Figure shows mean ± SEM, n = 4. Significance was assumed at p < 0.05. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50. ¤ indicates significance from ligand-PM100.

PM alone, TLR ligands alone or co-exposure of PM and TLR did not induce any changes in intracellular ROS production compared to unexposed control cells (Fig. 5 ).

Fig. 5.

Fig. 5

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Oxidative stress was assessed by using DCF-test after two-step submerged exposures described in Fig. 1. Figure shows mean ± SEM, n = 4.

PM alone caused a slight dose-dependent decrease in cell membrane integrity. The studied ligands (TLR7/8, TLR3, and TLR4) did not affect the integrity of cell membranes as compared to unexposed control. The results of combined exposures were not different from PM alone exposures (Fig. 6 A). Co-exposure to PM and TLR ligands slightly decreased cell viability compared to unexposed control and the respective PM dose alone, however, none of the changes were statistically significant (Fig. 6B).

Fig. 6.

Fig. 6

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A. Cell membrane integrity was assessed by using PI exclusion B. Viability was assessed by using DAPI staining after two-step submerged exposures described in Fig. 1. Figure shows mean ± SEM, n = 4.

PM alone increased dose-dependently the percentage of cells in the Sub-G1 phase. Of the studied TLR ligands, only TLR4 ligand caused a slight increase in the percentage of cells in the Sub-G1 phase. PM-TLR7/8 co-exposure increased the percentage of cells in the Sub-G1 phase and they induced slightly higher responses than the respective PM doses alone. (Fig. 7 A).

Fig. 7.

Fig. 7

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Cell cycle analysis was performed using PI staining after two-step submerged exposure described in Fig. 1. A. Sub-G1 phase, Fig B. G1-G0 phase, and Fig C. G2-M phase. Figure shows mean ± SEM, n = 3. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50.

Interestingly, PM alone, TLR7/8, TLR4 alone, or any of the PM-TLR co-exposures did not affect the percentages of cells in the G1-G0 phase. TLR3 alone significantly decreased the number of cells in the G1-G0 phase (Fig. 7B).

PM exposure induced a slight dose-dependent decrease in cells in G2-M phase, which was however statistically non-significant. Of the studied TLRs, only TLR3 caused a significant increase in cells in the G2-M phase when compared to control. Pre-exposure to PM reduced cellular responses to TLRs; the percentage of cells in the G2-M phase was significantly lower following co-exposure of PM-TLR7/8 and PM-TLR3 when compared to the respective exposures to ligands alone. (Fig. 7C).

PM alone induced a dose-dependent increase in the live cells with low levels of reduced thiols. Viral ligands TLR7/8 and TLR3 alone did not significantly affect the percentage of cells with reduced thiols when compared to unexposed control. However, when PM-treated cultures were treated with TLR ligands, there was a slight trend towards an increase in cells with depleted thiol levels as compared to the respective PM dose, but differences were not significant. Bacterial ligand (TLR4) alone induced a significant increase in cells with reduced thiol levels. However, when cell cultures were co-exposed to PM and TLR4, the percentage of cells with reduced thiol levels did not differ from those induced by respective doses of PM (Fig. 8 ).

Fig. 8.

Fig. 8

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Cells with depleted free thiols were determined from VB-48™ stain intensity after two-step submerged exposure described in Fig. 1. Figure shows mean ± SEM, n = 3. Significance was assumed at p < 0.05. * indicates significance from unexposed control. a indicates significance from PM-25. b indicates significance from PM-50. c indicates significance from PM-100. d indicates significance from TLR7/8. e indicates significance from TLR3. f indicates significance from TLR4. # indicates significance from ligand-PM-25. $ indicates significance from ligand-PM-50.

4. Discussion

PM2.5 exposure has been considered to impair the normal immune responses of the lung, rendering it susceptible to infections (Feng et al., 2016). In this study, we evaluated how exposure to PM2.5-1 affects innate immune responses of A549-THP1 co-cultures against viral and bacterial stimuli. Alveolar epithelial cells serve as a physical barrier, which alongside the presence of immune cells constitutes an innate immune response. A comparative study on mono and co-culture of A549 epithelial cells and THP1 activated macrophages has concluded that the use of only one cell line can underestimate or overestimate the magnitude of adverse effects caused by PM (Kasurinen et al., 2018). Therefore, to better understand cell-cell communication, co-cultures were used as an in vitro model to mimic the lung barrier. Furthermore, previous studies have shown that PM2.5 can induce pro-inflammatory cytokine expression in the lung epithelium and human macrophage cells by stimulating overexpression of genes for transcription factors and cytokines (Zhou et al., 2015; Zhu et al., 2019). In an in vivo study conducted by Zhao et al. (2016), PM2.5 exposure disrupted the balance between M1 and M2 polarized macrophages, which caused an increase in the pro-inflammatory cytokines. Our results confirmed that relatively low doses of PM2.5-1 can cause a modest increase in pro-inflammatory responses, measured as the production of IL-8, IL-6, and TNF-α, in A549 and THP1 co-culture.

We characterized the cytokine response of A549-THP1 co-culture to viral TLR ligands (TLR3, TLR7/8) and bacterial TLR ligand (TLR4). Results showed that both viral ligands caused an increase in IL-6 and IL-8 levels compared to control. However, response to TLR7/8 ligand was very high compared TLR3 ligand response. Our results are partially consistent with the study on primary airway epithelial cells, showing that exposure to TLR3 ligand increased IL-6, IL-8, and TNF-α production of the cells (Lever et al., 2015). Interestingly, in our study TLR3 ligand did not induce TNF-α production. TNF-α serves an important physiological role of activation of nuclear factor kappa-light-chain-enhancer of activated B cells (NF-Κβ) and influx of neutrophils to the site of inflammation (Schütze et al., 1995). A study on the A549-THP1 co-culture has concluded that TNF-α was secreted by activated macrophages and A549-THP1 co-culture when exposed to PM but not by PM-exposed A549 cells (Kasurinen et al., 2018). Furthermore, TNF-α has been detected in neither control A549 cells nor the cells exposed to cigarette smoke (Holownia et al., 2016). To our knowledge synthetic TLR7/8 ligand ORN R 006 has not been previously used in any other study on respiratory epithelial cells, however, TLR7 ligation with loxoribine or TLR8 ligation with Poly U has led to atypical activation of nuclear factor kappa-B (NFkB) pathway (Cherfils-Vicini et al., 2010). In our study, we assume that TLR7/8 activated NFkB has led to the induction of downstream inflammatory cytokines including IL-6 and IL-8, and TNF-α. On the other hand, TLR4 ligand (LPS) alone induced IL-6, IL-8, and TNF-α in the A549-THP1 co-culture, which is consistent with the results of the study that has been conducted on human lung mucoepidermoid carcinoma (H292) and THP-1 cells. LPS stimulation induced significant pro-inflammatory cytokines in both cell lines (Liu et al., 2018).

Co-cultures primed with PM2.5-1 on subsequent exposure with viral ligand TLR7/8 showed no additive effect on the response of pro-inflammatory cytokines as the response remained roughly the same as for PM2.5-1 alone. This indicates that in PM2.5-1 primed co-cultures the pro-inflammatory response was altered against TLR7/8 ligand. Another viral ligand TLR3 behaved differently as it alone induced very low levels of IL-8 and IL-6 but not induce the production of TNF-α in co-culture. In addition, when PM primed co-cultures were exposed to TLR3 ligand, the production of IL-8 and IL-6 was not further increased. This indicates that in addition to low inflammatory potential of TLR3 ligand, it may also suppress responses induced by PM.

Several studies have indicated that urban particulate matter decreases the ability of the macrophage to phagocytize and weakens the capacity of alveolar macrophages as well as alveolar epithelium to mount an effective immune response against viral stimuli (Migliaccio et al., 2013; Xu et al., 2008; Zhou and Kobzik, 2007). Results from an in vivo study on mice also that ultrafine carbon particle exposure suppresses the early immune response in the lung. However, at day 7 inflammation and viral exacerbation increased drastically (Lambert et al., 2003). Therefore, in our study, it could be assumed that prior exposure to PM2.5-1 decreased the ability of A549-THP1 co-culture to mount an effective immune response which may potentially lead to more exaggerated viral infection. Further studies using real viral exposures are needed to estimate the virulence of the viral infection and to understand the exact mechanisms.

In contrast to viral ligands, bacterial TLR4 ligand added to PM2.5-1 pre-treated co-culture caused a dramatic increase in the IL-8, TNF-α, and IL-6 levels indicating a possible sensitization of the immune cells. Our results are consistent with the study performed on secondary lung epithelial BEAS-2B cells in a co-culture with purified monocytes (Chaudhuri et al., 2010). The study showed that diesel exhaust particles override the nature of the inflammatory response to LPS and produced an exaggerated pro-inflammatory response. In a more recent study, exposure to PM at low concentrations to murine macrophages has caused priming of the respective immune cells resulting in hyperinflammatory response to subsequent LPS exposure (Gawda et al., 2018). The hyperinflammatory response may be attributed to the fact that PM2.5-1 can also contain bacterial endotoxin in its biological fraction; if present, it can cause the activation of TLR-MYD 88 by activation of TLR4 receptor leading to downstream activation of NF-κB mediated inflammatory response. Once activated it can increase the expression of pro-inflammatory markers and induce expression of more TLR4 receptors (Bauer et al., 2012; Peden, 2011). Therefore, subsequent exposure to bacterial stimuli may lead to a more abrupt pro-inflammatory response in the form of a cytokine storm, rendering individuals susceptible to acquire the worse form of respiratory bacterial exacerbations.

In this study, any of the stimulations did not induce significant changes to ROS stress. Moreover, no drastic changes in viability were seen. Activation of pro-inflammatory pathways are often associated with ROS stress generated by the exposure to PM on lung epithelial cells. However, some studies have previously shown that in co-culture model the presence of immune cells caused a mitigating effect on the oxidative stress in the alveolar epithelial cells (Kasurinen et al., 2018; Persson et al., 2013). Persson et al. (2013) showed that the presence of activated macrophages in A549 culture causes effective sequestering of Fe-ions from the media and thus minimizing Fe driven oxidative reaction. Alternatively, it is possible that the oxidative stress has occurred much earlier than was our measuring time-point. In this study, we used non-cytotoxic doses of PM2.5-1, TLR4, TLR3, and TLR7/8 to eliminate the hindering effect of cytotoxic responses to other measured endpoints. The aim was to investigate the role of PM2.5-1 in modulating the subsequent innate immunity responses i.e., the release of different pro-inflammatory cytokines, which may play a role in the susceptibility to bacterial and viral infection in PM 2.5-1 exposed co-culture.

Cellular metabolic activity of A549-THP1 co-cultured cells reduced significantly with the PM2.5-1 exposure at middle and higher doses, whereas TLR ligands alone did not affect CMA negatively. In subsequent exposures, reduction in CMA was associated with doses of PM with slight or no improvement in CMA after the addition of viral ligands TLR3 and TLR7/8 or bacterial ligand TLR4. Previous studies on a similar cell model exposed to PM originating from different sources concluded that reduction in CMA is caused by activation of macrophages in the co-culture, which produces a mitigation effect on the majority of A549 cells (Kasurinen et al., 2018).

Cellular glutathione (GSH) depletion is used as an indicator of early apoptotic cells (Coppola and Ghibelli, 2000). In this study, we determined the level of free thiols such as GSH. Our results suggested, that PM2.5-1 is associated with an increased number of cells with low levels of free thiols, especially at higher doses, whereas viral ligands TLR3 and TLR7/8 alone did not affect the status of reduced thiols in cells. Adjacent to the individual exposures, cells that were first treated with PM2.5-1 and later with TLR3 or TLR7/8 viral ligands showed slight or no changes in free thiol levels when compared to PM2.5-1 alone. On the other hand, bacterial TLR4 ligand-induced a significant increase in the number of cells with depleted free thiols when compared to control. However, the effect of TLR4 diminished in cells, which were pre-exposed to PM2.5-1. This indicated that early apoptosis would be solely due to the activation of macrophages by PM2.5-1, which caused a reduction in CMA leading to a higher number of cells undergoing apoptosis. Furthermore, it could also be assumed that the reduction in cellular thiol levels works independently of ROS stress, since, in our exposure, no significant ROS stress was indicated. This assumption is in line with previous results concluding a necessary and critical role for GSH loss in apoptosis and uncoupling GSH depletion from ROS formation (Rodrigo Franco et al., 2007).

Lastly, we also studied the cell cycle phase distribution of exposed cells. Exposure to PM2.5-1 increased the percentage of cells in the Sub-G1 phase and reduced the percentage of cells in the G2-M phase, indicating an increase in the number of cells undergoing cell cycle arrest at the G1 phase as well as apoptosis. As discussed above, reduction in CMA caused by the presence of activated macrophages in the co-culture may have resulted in an increased number of cells in the Sub-G1 phase. Kaplon et al. (2015) reviewed the interconnection of cellular metabolism and cell cycle arrest and concluded that decreased CMA may lead to cell cycle arrest and eventually apoptosis. Contrary to PM2.5-1 alone, individual exposure to viral ligands TLR3 and TLR7/8 increased the percentage of cells in the G2-M phase. Davy and Doorbar (2007) reviewed various mechanisms by which RNA, DNA, and retroviruses are known to induce cell cycle arrest at the G2-M phase and how this alteration helps viruses in survival and replication within the host cells during infection. For example, avian coronavirus infectious bronchitis virus has induced G2-M phase arrest to promote favorable conditions for viral replication (Dove et al., 2006). Therefore, we assumed that the increase in the number of cells in the G2-M phase is associated with viral ligand-induced cell cycle arrest to progeny viral production. However, viral ligands failed to induce modifications in the G2-M phase in PM2.5-1 primed co-cultures. From our results, it can be speculated that prior exposure to PM may alter the viral virulence. On the other hand, bacterial ligand TLR4 increased the number of cells in the Sub-G1 phase, with no effect on G1-G0 and G2-M phases. In correlation to the results from thiol assay, which accounts for the early apoptotic cells; pretreatment of cells with PM2.5-1 slightly increased the number of cells in the Sub-G1 phase, especially at higher doses of PM2.5-1. The response was, however, not statistically significant when compared to PM2.5-1 alone but it shows that co-exposure with TLR4 ligand has some effect on the number of cells in the Sub-G1 phase. Therefore, our results indicate that PM2.5-1 priming modifies immune responses against bacterial and viral stimulation in the studied cell model.

5. Conclusion

PM2.5-1 exposure altered the pro-inflammatory cytokine response to both bacterial and viral stimuli in the alveolar lung cell model. PM2.5-1 increased the sensitivity of the A549-THP1 co-culture to produce pro-inflammatory cytokines, which potentially leads to hyperinflammatory response against bacterial infection. Instead, virus-mediated pro-inflammatory effects were suppressed if the co-culture model of the alveolar barrier was primed with PM2.5-1. These findings provide insight into the underlying immunomodulatory effects of fine particulate matter, which potentially leads to susceptibility to respiratory infections.

Funding

The work was supported by Päivikki and Sakari Sohlberg Foundation, Juho Vainio Foundation, and the Academy of Finland grants (319245, 294081, 287982).

Author contribution

Muhammad Ali Shahbaz: Formal analysis, Investigation, Methodology, Data curation, Visualization, Writing-original draft, Writing-review, and editing. Maria-Viola Martikainen: Investigation, Writing-review, and editing. Teemu J. Rönkkö: Investigation, Writing-editing, and reviewing. Mika Komppula: Resources, Writing-review, and editing. Pasi I. Jalava: Funding acquisition, Methodology, Resources, Supervision, Validation, Writing-review, and editing. Marjut Roponen: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing-review, and editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

The authors wish to thank Ms Hanne Vainikainen, MSc Tuukka Ihantola and MSc Henri Hakkarainen for their technical support.

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