Metabolic Profiling as Well as Stable Isotope Assisted Metabolic and Proteomic Analysis of RAW 264.7 Macrophages Exposed to Ship Engine Aerosol Emissions: Different Effects of Heavy Fuel Oil and Refined Diesel Fuel

Exposure to air pollution resulting from fossil fuel combustion has been linked to multiple short-term and long term health effects. In a previous study, exposure of lung epithelial cells to engine exhaust from heavy fuel oil (HFO) and diesel fuel (DF), two of the main fuels used in marine engines, led to an increased regulation of several pathways associated with adverse cellular effects, including pro-inflammatory pathways. In addition, DF exhaust exposure was shown to have a wider response on multiple cellular regulatory levels compared to HFO emissions, suggesting a potentially higher toxicity of DF emissions over HFO. In order to further understand these effects, as well as to validate these findings in another cell line, we investigated macrophages under the same conditions as a more inflammationrelevant model. An air-liquid interface aerosol exposure system was used to provide a more biologically relevant exposure system compared to submerged experiments, with cells exposed to either the complete aerosol (particle and gas phase), or the gas phase only (with particles filtered out). Data from cytotoxicity assays were integrated with metabolomics and proteomics analyses, including stable isotope-assisted metabolomics, in order to uncover pathways affected by combustion aerosol exposure in macrophages. Through this approach, we determined differing phenotypic effects associated with the different components of aerosol. The particle phase of diluted combustion aerosols was found to induce increased cell death in macrophages, while the gas phase was found more to affect the metabolic profile. In particular, a higher cytotoxicity of DF aerosol emission was observed in relation to the HFO aerosol. Furthermore, macrophage exposure to the gas phase of HFO leads to an induction of a pro-inflammatory metabolic and proteomic phenotype. These results validate the effects found in lung epithelial cells, confirming the role of inflammation and cellular stress in the response to combustion aerosols

Emissions from a modern log wood masonry heater and wood pellet boiler : Composition and biological impact on air-liquid interface exposed human lung cancer cells

The consumption of wood fuel is markedly increasing in developing and industrialized countries. Known side effects of wood smoke inhalation manifest in proinflammatory signaling, oxidative stress, DNA damage and hence increased cancer risk. In this study, the composition and acute biological impact of emissions of state-of-the-art wood combustion compliances: masonry heater (MH) and pellet boiler (PB) were investigated. Therefore A549 cells were exposed to emission aerosols in an automated air-liquid interface exposure station followed by cytotoxicity, transcriptome and proteome analyses. In parallel, aerosols were subjected to a chemical and physical haracterization. Compared to PB, the MH combustion at the same dilution ratio resulted in a 3-fold higher particle mass concentration (PM2.5) and deposited dose (PB: 27 $\pm$ 2 ng/cm2, MH; 73 $\pm$ 12 ng/cm2). Additionally, the MH aerosol displayed a substantially larger concentration of aldehydes, polycyclic aromatic hydrocarbons (PAH) or oxidized PAH. Gene ontology analysis of transcriptome of A549 cells exposed to MH emissions revealed the activation of proinflammatory response and key signaling cascades MAP kinase and JAK-STAT. Furthermore, CYP1A1, an essential enzyme in PAH metabolism, was induced. PB combustion aerosol activated the proinflammatory marker IL6 and different transport processes. The proteomics data uncovered induction of DNA damage-associated proteins in response to PB and DNA doublestrand break processing proteins in response to MH emissions. Taking together, the MH produces emissions with a higher particle dose and more toxic compounds while causing only mild biological responses. This finding points to a significant mitigating effect of antioxidative compounds in MH wood smoke

Levels of intracellular metabolite pools in aerosol-exposed macrophages.

<p>Pools of (a) lactic acid, (b) succinic acid, and itaconic acid were measured. Levels represent the mean of 9 biological replicates. *** = p < 0.001. Error bars represent s.e.m.</p

HFO particles induce activation of immune response in RAW 264.7 macrophages.

<p>(a) The Gene Ontology term GO:0006955, corresponding to activation of immune response, was found to be significantly up-regulated in HFO-treated samples (p = 0.059) and not regulated in the DF-treated samples. (b) Model of how the regulated proteins found in this study affect the NF-kB immune response pathway in the cell. Stimulation of the toll-like receptor (TLR2) leads to activation of NF-kB. Tumor necrosis factor alpha-induced protein 8-like protein 2 (TNFAIP8L2) acts as a negative regulator of TLR2, preventing hyperresponsiveness of the immune system, and inhibiting NF-kappa-B activation. Peroxiredoxin 2 (Pdrx2) reduces hydrogen peroxide, inhibiting NF-kappa-B activation.</p

Summary of the main HFO- and DF-particle exposure effects.

<p>The arrows indicate the direction of regulation for cellular functions derived from the most statistically significant enriched Gene Ontology terms from the transcriptome, proteome, and metabolome (details in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126536#pone.0126536.s012" target="_blank">S2 Table</a>).</p><p>^x BEAS-2B up, A549 down</p><p>* BEAS-2B down, A549 up</p><p>Summary of the main HFO- and DF-particle exposure effects.</p

Effects of shipping particles on lung cells.

<p>The net effects from the particles were referenced against the gaseous phase of the emissions. (A) Number of the regulated components in the transcriptome shows more genes regulated by the DF than the HFO particles (in BEAS-2B cells). Similar results were observed for the proteome (B) and metabolome (C) (in A549 cells). (D) Meta-analyses for the transcriptome and proteome using the combined Gene Ontology (GO) term analysis of the 10% most regulated transcripts and proteins. Individual GO terms are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0126536#pone.0126536.s012" target="_blank">S2 Table</a>; the hierarchical pathways are indicated on the right. (E) Gene regulation of Wiki-pathway bioactivation; (F) gene regulation of Wiki-pathway inflammation; g, secreted metabolites; and h, metabolic flux measurements using ¹³C-labelled glucose. For all experiments, n = 3.</p