In a recent study posted to the bioRxiv* preprint server, researchers investigated the effect of influenza A virus (FLUAV) pre-exposure and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in the elderly population using a 14-month-aged golden Syrian hamsters (GSH) model.
Seasonal influenza viruses are among the most prevalent causes of morbidity and mortality among the elderly. Since SARS-CoV-2 also causes respiratory infection, it makes the elderly susceptible to developing acute respiratory distress syndrome (ARDS), which in some cases leads to prolonged hospitalization and death. Studies have also pointed at changes in residential microbiota within the respiratory tract following SARS-CoV-2 infections. Animal models have proven beneficial in studying varied aspects of SARS-CoV-2 pathogenesis.
While experimental studies used five to-eight weeks old GSHs, 8-10-month-old GSHs, equivalent to ~40-50 human years, emulate severe disease and could help examine age-related changes in a host and the relationship between the immune response and host residential microbes. The higher risk of enhanced illness in the elderly encompasses hyperimmune response and immunosenescence. However, studies have barely investigated the mechanisms governing these changes.
In healthy individuals, lung microbiota is dominated by commensal bacteria of the phyla Firmicutes. Studies have shown that following coronavirus disease 2019 (COVID-19), opportunistic pathogens and commensal bacteria, including Pseudomonas, Enterobacteriaceae, and Acinetobacter, replace them. Other cohort studies have also described SARS-CoV-2-induced changes in the gut microbiota. Most likely due to the gut-lung axis, dysbiosis of the gut microbiota is characterized by depletion of commensal bacteria and enrichment of pathogenic bacteria, including Streptococcus, Rothia, Veillonella, Erysipelatoclostridium, Actinomyces, Collinsella, and Morganella, is not fully understood.
About the study
In the present study, researchers assessed dysbiosis of the lung, intestine, and fecal microbiota composition, following SARS-CoV-2 infection with and without FLUAV pre-exposure. They divided GSHs into three groups, as follows:
i) mock group, challenged only by 1X phosphate-buffer saline (PBS),
ii) GSH-group challenged only by SARS-CoV-2,
iii) FLUAV-SARS-CoV-2 GSHs challenged by SARS-CoV-2 13 days after exposure to FLUAV.
The team analyzed the weight loss, viral shedding, and histopathological changes in different animal tissues three and six days post-challenge (dpc). Further, the researchers collected lung homogenates to sequence and amplified the V4 region of 16S ribosomal ribonucleic acid (rRNA) genes and investigated the lung microbiome of all test animals. Furthermore, they computed the Spearman correlation between infection factors and the relative abundance of bacterial taxa within the small intestine, cecum, and feces and illustrated them using a heatmap.
Regardless of pre-FLUAV exposure, all the test animals suffered significant weight loss following SARS-CoV-2 infection. They also had high viral loads in the nasal turbinates (NT), lungs, and trachea. However, at six dpc, NT viral load was higher only in the SARS-CoV-2 group. Prior FLUAV exposure delayed SARS-CoV-2 replication in aged GSHs. The authors observed more pronounced lesions in FLUAV pre-exposed GSHs, with more prominent NT lesions at three dpc than at six dpc. Additionally, their NT lumen was filled with abundant catarrhal to fibrinosuppurative exudate.
Consistent with previous studies, the authors observed beta diversity separations among SARS-CoV-2 challenged GSH groups and the mock corresponding to COVID-19 severity. Conversely, alpha diversity did not vary significantly in the lower respiratory tract among both groups. The lung microbiota of aged GSH was dominated by Firmicutes and Bacteroidetes phyla and Prevotella, Veillona, and Streptococcus species. At three and six dpc, SARS-CoV-2 challenged GSHs had an increased relative abundance of Proteobacteria. Previous studies have also associated the expansion of Proteobacteria members with alveolar and systemic inflammation in patients with ARDS and FLUAV H1N1 infection.
SARS-CoV-2 infection increased the relative abundance of opportunistic bacteria, such as Streptococcus, Rothia, Veillonella, Erysipelatoclostridium, and Actinomyces, within fecal samples. However, pre-FLUAV exposure enriched species, such as Enterococcus, Prevotella, Finegoldia, and Peptoniphilus. The relative abundance of short-chain fatty acid (SCFA)-producing Firmicutes, such as Lachnospiraceae NK4A136 in the small intestine and cecum, modulated intestinal barrier integrity and pro-inflammatory factors.
SARS-CoV-2 challenge enriched multiple genera in fecal samples compared to their pre-challenged counterparts; however, the FLUAV exposed GSHs had no significantly enriched taxa. The findings suggested that initial stimulation of the innate immune response causes more changes in the intestinal microbiota than subsequent immune activations. Intriguingly, there was a bidirectional interplay between the gut microbiome and respiratory viral infections. Accordingly, the authors observed that FLUAV infection favored type I interferon immune response, which promoted the outgrowth of Proteobacteria.
The current study identified several specific microbial markers in co-infections from opportunistic pathogens during COVID-19. Future studies should continue to investigate microbiota changes within the different anatomical sections of the intestine. Since human samples from the elderly are difficult to collect and highly variable among individuals due to environmental factors; therefore, future studies should use animal models as an alternative. As more and more studies continue to improve the understanding of the disease pathology and the effect of SARS-CoV-2 and FLUAV infections on the microbiota, it could potentially lead to the identification of disease severity-based differential host markers for geriatric patients.
bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.