Respiratory Disease following Viral Lung Infection Alters the Murine Gut Microbiota

Abstract

Alterations in the composition of the gut microbiota have profound effects on human health. Consequently, there is great interest in identifying, characterizing, and understanding factors that initiate these changes. Despite their high prevalence, studies have only recently begun to investigate how viral lung infections have an impact on the gut microbiota. There is also considerable interest in whether the gut microbiota could be manipulated during vaccination to improve efficacy. In this highly controlled study, we aimed to establish the effect of viral lung infection on gut microbiota composition and the gut environment using mouse models of common respiratory pathogens respiratory syncytial virus (RSV) and influenza virus. This was then compared to the effect of live attenuated influenza virus (LAIV) vaccination. Both RSV and influenza virus infection resulted in significantly altered gut microbiota diversity, with an increase in Bacteroidetes and a concomitant decrease in Firmicutes phyla abundance. Although the increase in the Bacteroidetes phylum was consistent across several experiments, differences were observed at the family and operational taxonomic unit level. This suggests a change in gut conditions after viral lung infection that favors Bacteroidetes outgrowth but not individual families. No change in gut microbiota composition was observed after LAIV vaccination, suggesting that the driver of gut microbiota change is specific to live viral infection. Viral lung infections also resulted in an increase in fecal lipocalin-2, suggesting low-grade gut inflammation, and colonic Muc5ac levels. Owing to the important role that mucus plays in the gut environment, this may explain the changes in microbiota composition observed. This study demonstrates that the gut microbiota and the gut environment are altered following viral lung infections and that these changes are not observed during vaccination. Whether increased mucin levels and gut inflammation drive, or are a result of, these changes is still to be determined.

Respiratory viral infection alters the gut microbiota by inducing inappetence

“…At the family level, the major change seen was an increase in the abundance of the S24_7 family (also known as Muribaculaceae (Lagkouvardos et al, 2019): Fig.1G). This pattern was very similar to that previously observed after RSV infection (Groves et al, 2018).…”

“…While we have previously observed RSV specific CD8 + T cells tracking to different tissues, such as the spleen, after infection (Kinnear et al, 2018), we did not look in the intestines in the current or previous study. It should be noted we observed no increase in lymphoid infiltration in the gut after RSV or influenza infection (Groves et al, 2018). This leads us to think that the effect of CD8 + T cells on inappetence is via a secreted factor.…”

“…However, several studies have demonstrated that respiratory infections are associated with a change in the composition of the gut microbiota (Wang et al, 2014;Deriu et al, 2016;Bartley et al, 2017;Groves et al, 2018;Hanada et al, 2018;Yildiz et al, 2018). We have previously observed that viral lung infections alter the gut microbiota, leading to an increase in the relative abundance of Bacteroidetes and a decrease in the relative abundance of Firmicutes (Groves et al, 2018).…”

“…The V4 variable region of the 16S rRNA gene was amplified using universal bacterial primers (Klindworth et al, 2013) which were uniquely barcoded for each sample (Illumina Nextera Indexes Version 2). The amplicons were purified, quantified and equimolar pooled to produce a 16S rRNA gene library as described previously (Groves et al, 2018). Paired-end sequencing of the 8 pM denatured library, spiked with 8 pM of PhiX, was performed using the Illumina MiSeq platform (Kozich et al, 2013).…”

“…16S rRNA gene sequencing data was processed using the QIIME 1.9.0 software suite (Caporaso et al, 2010) as outlined fully in Groves et al, (2018). For microbiota composition analysis, operational taxonomic units (OTUs) were clustered at 97% sequence identify using UCLUST (Edgar, 2010) and open reference clustering.…”