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. 2018 Apr 20;13(4):e0194765.
doi: 10.1371/journal.pone.0194765. eCollection 2018.

IFN-λ and microRNAs are important modulators of the pulmonary innate immune response against influenza A (H1N2) infection in pigs

Affiliations

IFN-λ and microRNAs are important modulators of the pulmonary innate immune response against influenza A (H1N2) infection in pigs

Louise Brogaard et al. PLoS One. .

Abstract

The innate immune system is paramount in the response to and clearance of influenza A virus (IAV) infection in non-immune individuals. Known factors include type I and III interferons and antiviral pathogen recognition receptors, and the cascades of antiviral and pro- and anti-inflammatory gene expression they induce. MicroRNAs (miRNAs) are increasingly recognized to participate in post-transcriptional modulation of these responses, but the temporal dynamics of how these players of the antiviral innate immune response collaborate to combat infection remain poorly characterized. We quantified the expression of miRNAs and protein coding genes in the lungs of pigs 1, 3, and 14 days after challenge with swine IAV (H1N2). Through RT-qPCR we observed a 400-fold relative increase in IFN-λ3 gene expression on day 1 after challenge, and a strong interferon-mediated antiviral response was observed on days 1 and 3 accompanied by up-regulation of genes related to the pro-inflammatory response and apoptosis. Using small RNA sequencing and qPCR validation we found 27 miRNAs that were differentially expressed after challenge, with the highest number of regulated miRNAs observed on day 3. In contrast, the number of protein coding genes found to be regulated due to IAV infection peaked on day 1. Pulmonary miRNAs may thus be aimed at fine-tuning the initial rapid inflammatory response after IAV infection. Specifically, we found five miRNAs (ssc-miR-15a, ssc-miR-18a, ssc-miR-21, ssc-miR-29b, and hsa-miR-590-3p)-four known porcine miRNAs and one novel porcine miRNA candidate-to be potential modulators of viral pathogen recognition and apoptosis. A total of 11 miRNAs remained differentially expressed 14 days after challenge, at which point the infection had cleared. In conclusion, the results suggested a role for miRNAs both during acute infection as well as later, with the potential to influence lung homeostasis and susceptibility to secondary infections in the lungs of pigs after IAV infection.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Overview of experimental procedures.
RNA extraction and RT-qPCR procedures (boxed in red) were performed in-house, whereas small RNA sequencing (boxed in blue) was performed by an external service provider (Exiqon A/S).
Fig 2
Fig 2. Overview of RNAseq data analysis.
Workflow of the bioinformatics tools applied for RNAseq data analysis.
Fig 3
Fig 3. Volcano plots showing miRNA expression changes as obtained by RNAseq.
A) day 1 after challenge, B) day 3 after challenge, C) day 14 after challenge. x-axes show the log2FC values of post-challenge time points vs. unchallenged controls. 50% up- or down-regulation is denoted by vertical dotted lines (log2FC > 0.585, log2FC < -0.585). y-axes show the -log10 transformed p-values obtained from F-tests. p = 0.05 is denoted by a horizontal red line. A horizontal blue line denotes the p-value limit for significant differential expression when controlling for FDR; as shown, only on day 3 after challenge are there any miRNAs that are significantly differentially expressed after this correction. miRNAs that pass the criteria for differential expression are marked with a number denoting their identity; miRNAs that appear in more than one volcano plot are marked with the same number in all plots. 1 ssc-miR-205; 2 ssc-miR-34c; 3 ssc-miR-671-5p; 4 ssc-miR-146a-5p; 5 ssc-miR-2366; 6 ssc-miR-365-5p; 7 ssc-miR-146b; 8 ssc-miR-708-5p; 9 ssc-miR-92b-5p; 10 ssc-miR-708-3p; 11 mmu-miR-34b-3p; 12 mmu-miR-34b-5p; 13 ssc-miR-339-3p; 14 ssc-miR-196b-5p; 15 ssc-miR-193a-3p; 16 ssc-miR-4334-3p; 17 ssc-miR-133b; 18 ssc-miR-217; 19 ssc-miR-331-3p; 20 ssc-miR-216; 21 ssc-miR-187; 22 ssc-miR-144; 23 ssc-miR-296-3p; 24 ssc-miR-92b-3p; 25 ssc-miR-1343; 26 hsa-miR-375; 27 ssc-miR-744; 28 ssc-miR-7134-5p; 29 ssc-miR-190b; 30 ssc-miR-2320-3p; 31 ssc-miR-671-3p; 32 ssc-miR-128; 33 ssc-miR-328; 34 ssc-miR-30c-1-3p; 35 ssc-miR-1296-5p; 36 ssc-miR-149; 37 ssc-miR-183; 38 ssc-miR-129b; 39 ssc-miR-221-5p; 40 ssc-miR-29b; 41 ssc-miR-142-5p; 42 ssc-miR-504; 43 ssc-miR-20a; 44 ssc-miR-1249; 45 ssc-miR-7139-3p; 46 ssc-miR-486; 47 ssc-miR-451; 48 ssc-miR-335; 49 ssc-miR-215.
Fig 4
Fig 4. Venn diagram comparing differentially expressed miRNAs identified by and qPCR and RNAseq.
Overlap of miRNAs found to be differentially expressed at one or more post-challenge time points by RNAseq (yellow) and qPCR (blue). †miRNAs assayed by qPCR but not detected by sequencing; *miRNAs detected by sequencing, but not assayed by qPCR. When a known porcine (ssc) sequence for a given miRNA was not available in miRBase (v. 21), human (hsa) or mouse (mmu) names are applied in accordance with the homolog that best matched the novel porcine miRNA discovered in the RNAseq data, and these homolog sequences were likewise used for qPCR primer design.
Fig 5
Fig 5. Comparison of miRNA log2FC as measured by RNAseq and qPCR.
Log2FC (challenged group vs. control group) obtained by qPCR is plotted against the corresponding log2FC obtained by RNAseq. Each point represents log2FC of one miRNA on day 1 (black), day 3 (white), or day 14 (grey) after challenge.
Fig 6
Fig 6. Potential miRNA-mRNA interactions.
Expression of eight of the assayed miRNAs showed significant negative correlation with expression of protein coding genes that were identified (using RAIN v1.0 [50], TarBase v. 7.0 [52], and/or microT-CDS [53]) to be experimentally validated targets of the miRNA (solid lines), computationally predicted targets of the miRNA (dotted lines), or both (solid lines, underlined gene names).

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Grants and funding

LB, LEL, PMHH, and KS recieved no specific funding for this work. CA and JG were supported by the Independent Research Fund Denmark (4005-00443) (http://ufm.dk/forskning-og-innovation/rad-og-udvalg/dff) and Innovation Fund Denmark (0603-00320B) (https://innovationsfonden.dk/en). RD was supported by the Bundesministerium für Bildung und Forschung (01KI1006L) (https://www.bmbf.de/). Laboratory reagents and disposable labware were partially funded by Independent Research Fund Denmark (1337-00014) (http://ufm.dk/forskning-og-innovation/rad-og-udvalg/dff).

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