Particulate matter (PM10) enhances RNA virus infection through modulation of innate immune responses

Abstract

Sensing of pathogens by specialized receptors is the hallmark of the innate immunity. Innate immune response also mounts a defense response against various allergens and pollutants including particulate matter present in the atmosphere. Air pollution has been included as the top threat to global health declared by WHO which aims to cover more than three billion people against health emergencies from 2019 to 2023. Particulate matter (PM), one of the major components of air pollution, is a significant risk factor for many human diseases and its adverse effects include morbidity and premature deaths throughout the world. Several clinical and epidemiological studies have identified a key link between the PM existence and the prevalence of respiratory and inflammatory disorders. However, the underlying molecular mechanism is not well understood. Here, we investigated the influence of air pollutant, PM₁₀ (particles with aerodynamic diameter less than 10 μm) during RNA virus infections using Highly Pathogenic Avian Influenza (HPAI) - H5N1 virus. We thus characterized the transcriptomic profile of lung epithelial cell line, A549 treated with PM₁₀ prior to H5N1infection, which is known to cause severe lung damage and respiratory disease. We found that PM₁₀ enhances vulnerability (by cellular damage) and regulates virus infectivity to enhance overall pathogenic burden in the lung cells. Additionally, the transcriptomic profile highlights the connection of host factors related to various metabolic pathways and immune responses which were dysregulated during virus infection. Collectively, our findings suggest a strong link between the prevalence of respiratory illness and its association with the air quality.

Keywords: Air pollution; Anti-viral innate immunity; Metabolic pathways genes; PM(10); Viral infection.

Graphical abstract

Fig. 1

PM₁₀regulates the innate immune response upon RNA virus infection – (A) Scanning electron images of coarse airborne particulate matter PM₁₀. (a) Image of blank (control) solution with no PM₁₀ dissolved in it. (b–l) Images of different shapes with varied structures representing the different characteristic morphological features of PM₁₀ in the samples. Quantification of innate immune response. A549 cells were treated with PM₁₀ (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section) and control mentioned as blank for (B) 24 h then harvested in Trizol to quantify the mRNA expression of IFNβ and IL6 by qRT-PCR. (C) 36 h then cell supernatant was collected to measure the protein level of IL6 by ELISA. (D) Schematic representation of workflow for quantification of IFNβ and ISRE promoter activities by luciferase assay as indicated in A549 cells. NDV represents New-Castle Disease Virus infection at MOI = 2. (E) Schematic work flow of PM₁₀ exposure (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section) and NDV infection. (F–G) Quantification of IFNβ and IL6 mRNA transcripts in uninfected (control), mock infected, blank treated and PM₁₀ exposed cells by qRT-PCR. (H) Schematic work flow of PM₁₀ (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section) exposure and H5N1 Influenza infection. (I–J) Quantification of IFNβ and IL6 mRNA transcripts in uninfected (control), mock infected, blank treated and PM₁₀ exposed cells by qRT-PCR. Data are mean ± SEM of triplicate samples from single experiment and are representative of three independent experiments. ∗∗∗p < 0.001, ∗∗p < 0.01 and ∗p < 0.05 by one-way ANOVA Tukey test and unpaired t-test.

Fig. 2

PM₁₀elevates the RNA virus infection – (A–F) Estimation of viral replication in A549 cells exposed with PM₁₀ for 24 h before virus infection at MOI = 2. (A) Schematic work flow of the experiment, PM₁₀ exposure (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section; PM₁₀ dose standardization) enhances the NDV abundance (viral transcripts) in the cells compared to the control groups (uninfected control, mock infected, and blank treated cells respectively). (B–C) Schematic work flow of the experiment, PM₁₀ exposure (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section; PM₁₀ dose standardization) enhances the H5N1 and H1N1 abundance (viral transcripts) in the cells compared to the control groups (uninfected control, mock infected, and blank treated cells respectively). (D) Schematic work flow for microscopy: A549 cells were exposed with PM₁₀ (labelled as PM; corresponds to PM(I) dosage form - details are mentioned in the methods section; PM₁₀ dose standardization) then after infected with GFP – labelled NDV for 24 h, cells on the cover slips were then fixed (as per the protocol described in methods section) and estimated for the GFP positive signals, quantified as (E) total number of NDV-GFP infected cells and (F) intensity of GFP signals in the infected cells. (G) Schematic work flow to estimate the cell death in cell supernatant after PM₁₀ exposure (at different dosage: PM(I), PM(II), and PM(III) – details are mentioned in the methods section; PM₁₀ dose standardization) and NDV infection in A549 cells. Cells (dead) were counted by the trypan blue counting assay. Data are mean ± SEM of triplicate samples from single experiment and are representative of three independent experiments. ∗∗∗p < 0.001 by one-way ANOVA Tukey test and unpaired t-test. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3

Transcriptomic analysis shows PM₁₀enhances abundance of metabolic pathways-related transcripts (genes) during H5N1 infection – (A) Schematic outline of PM₁₀ exposure and H5N1 infection (MOI 2) in A549 cells at indicated time. Cells were subjected to whole transcriptome sequencing and differential gene expression analysis. (B) Volcano plot represents differential expression of genes between two groups of samples (mock H5N1 infected and PM₁₀ exposed plus H5N1 infected) during H5N1 infection in A549 cells. For each gene: p-value is plotted against fold change (mock vs PM₁₀). Significantly differentially expressed genes are marked in red colour while genes which are altered (>1.5-fold) are marked in blue colour. (C) Gene Ontology analysis performed as per the protocol mentioned in methods section represents the top differentially expressed genes in ontology terms: BP (biological processes), CC (cellular components) and MF (molecular functions) respectively depicted by bubble plot and circle plot generated through R package GOPlot. (D) Pathway enrichment analysis performed as per the protocol mentioned in methods section. Chord plot represents the differentially expressed genes and their connection with the top enriched pathways. Circle plot represents the top enriched pathways and status of the genes contributing to the pathways by their log FC and Z-score. (E–H) Quantification (measured by qRT-PCR) and validation of the fold changes in the abundances of significantly expressed metabolic pathways related transcripts: VIPR1, CYP1A1, ALDH1A3 and PPP1R14A in the samples of A549 cells; untreated (control), mock H5N1 infected (H5N1) and PM₁₀ exposed (labelled as PM; corresponds to PM(I) dosage form - details are mentioned in the methods section) plus H5N1 infected (H5N1+PM), analysed by RNA- Sequencing. For figure (E–H): Data are mean ± SEM of triplicate samples from single experiment and are representative of two independent experiments. ∗∗∗p < 0.001 and ∗∗p < 0.01 by one-way ANOVA Tukey test and unpaired t-test. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4

Knockdown of validated genes reduces RNA virus infection by enhancing innate immune response – A549 cells were transiently transfected with 1.5 μg of two of the respective sh-clones of each indicated genes or scrambled control for 72 h then infected with NDV (MOI 2) for 24 h and subjected to the quantification of the respective indicated transcripts or genes; (A) CYP1A1, (B) VIPR1 and (C) PPP1R14A; NDV viral RNA transcripts and antiviral cytokines; IL6 and IFIT1 transcripts. (D) Schematic representation of the overall conclusion of the study. Data are mean ± SEM of triplicate samples from single experiment and are representative of three independent experiments. ∗∗∗p < 0.001 and ∗∗p < 0.01 by one-way ANOVA Tukey test and unpaired t-test.