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. 2023 Oct 17;11(10):2582.
doi: 10.3390/microorganisms11102582.

The Effect of Bifidobacterium animalis subsp. lactis Bl-04 on Influenza A Virus Infection in Mice

Affiliations

The Effect of Bifidobacterium animalis subsp. lactis Bl-04 on Influenza A Virus Infection in Mice

Bryan Zabel et al. Microorganisms. .

Abstract

Influenza A virus infection is a major global disease requiring annual vaccination. Clinical studies indicate that certain probiotics may support immune function against influenza and other respiratory viruses, but direct molecular evidence is scarce. Here, mice were treated with a placebo or Bifidobacterium animalis subsp. lactis Bl-04 (Bl-04) orally via food (cereal) and also by gavage and exposed to Influenza A virus H1N1 (H1N1). The symptoms of the infection were observed, and tissues and digesta were collected for viral load RT-qPCR, transcriptomics, and microbiomics. The treatment decreased the viral load by 48% at day 3 post-infection in lungs and symptoms of infection at day 4 compared to placebo. Tissue transcriptomics showed differences between the Bl-04 and placebo groups in the genes in the Influenza A pathway in the intestine, blood, and lungs prior to and post-infection, but the results were inconclusive. Moreover, 16S rRNA gene profiling and qPCR showed the presence of Bl-04 in the intestine, but without major shifts in the microbiome. In conclusion, Bl-04 treatment may influence the host response against H1N1 in a murine challenge model; however, further studies are required to elucidate the mechanism of action.

Keywords: Bifidobacterium; animal study; immune response; influenza; probiotic; transcriptomics.

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Conflict of interest statement

S.M.M., D.N., A.H., N.Y., S.L. and M.J.L. are employees of IFF Health & Biosciences that manufactures Bl-04 for dietary supplements. B.Z., L.L. and W.M. are former employees of IFF Health & Biosciences. IFF outsourced the statistical analysis to J.J. and the animal experiments to Southern Research Institute. K.B.W. was an employee of Southern Research Institute at the time of the study.

Figures

Figure 1
Figure 1
Viral load and health scores in IAV-infected mice. (A) Mean +/− SD IAV H1N1 log10 genome copies per mg of mouse lung tissue measured by RT-qPCR at days 3, 5, and 7 post-infection in Bl-04 (n = 8) and placebo (n = 8) groups. * Estimated difference for linear mixed-effects model for log10-viral load significant at day 3 (p = 0.0004). (B) Percentage of mice with rough coat at different study days in Bl-04 and placebo groups. * Odds ratio for the treatment difference between groups significant at day 4 (p = 0.046). (C) Percentage of mice with hunched posture at different study days in Bl-04 and placebo groups. * Odds ratio for the treatment difference between groups significant at day 4 (p = 0.039). (D) Percentage of mice with abnormal breathing at different study days. For health scores, the number of animals per group was 29 for days 0–3, 21 for days 4–5, 13 for days 6–8, and 5 for days 9–14.
Figure 2
Figure 2
Global transcriptomics analyses of Bl-04 and placebo groups in all tissues tested over the course of the study. The data points of the same analysis are divided into pre- and post-infection timepoint panels. Principal component analysis (PCA) of transcriptomes of all samples tested in Bl-04 (red) and placebo control (blue) group. Tissues are separated into individual panels (AH). Each point is an individual sample transcriptome containing all genes expressed. Ellipses represent a 95% confidence level for a multivariate t-distribution.
Figure 3
Figure 3
Pathway analysis results of Bl-04 treatment group compared to the placebo group. ROntoTools pathway analysis using differential expression comparing Bl-04 to placebo group within each timepoint and tissue at (A) pre-infection and (B) post-infection. All points shown are significant (combined FDR < 0.05), with the color denoting the total level of pathway perturbation and the size denoting the significance. Pathways from selected categories are shown. All pathways can be found in Table S2. Any timepoint or tissue not shown is due to no significant pathway perturbation.
Figure 4
Figure 4
Influenza A pathway gene expression prior to and during H1N1 infection in mouse tissues. Balloon plot of Influenza A (mmu05164) KEGG pathway genes found differentially expressed in the Bl-04 group compared to placebo group at (A) pre-infection and (B) post-infection timepoints. All genes shown have significant expression (padj < 0.05). Size of the balloon denotes significance (−log10-adjusted p-value). Color denotes expression level (log2 fold change) with blue having lower expression and red having increased expression relative to the placebo group. LungL: left lung, LungR: right lung.
Figure 5
Figure 5
Differentially abundant amplicon sequence variants (ASVs) in the intestinal microbiota. The ASV corresponding to the subspecies B. animalis subsp. lactis, including Bl-04, was increased overall in the jejunum, ileum, and caecum (all weeks combined for each intestinal section; FDR < 0.05) and at Week 4 for each intestinal section (* FDR < 0.05) compared to placebo (A). An ASV corresponding to Adlercreutzia sp. was increased at Week 1 in the ileum and caecum of placebo mice compared to Bl-04 (* FDR < 0.05) (B) and three ASVs corresponding to Clostridiales sp. (novel species) were differentially abundant in the caecum at Week 4 (* FDR < 0.05) (C). Baseline (day −21; n = 8 per day), Week 1 (days −20, −18, −14; n = 8 per day), Week 3 (days −7, 0; n = 8 per day) pre-infection, and Week 4 post-infection (days 3, 5, and 7; n = 16 per day).

References

    1. Lozano R., Naghavi M., Foreman K., Lim S., Shibuya K., Aboyans V., Abraham J., Adair T., Aggarwal R., Ahn S.Y., et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet. 2012;380:2095–2128. doi: 10.1016/S0140-6736(12)61728-0. - DOI - PMC - PubMed
    1. Iuliano A.D., Roguski K.M., Chang H.H., Muscatello D.J., Palekar R., Tempia S., Cohen C., Gran J.M., Schanzer D., Cowling B.J., et al. Estimates of global seasonal influenza-associated respiratory mortality: A modelling study. Lancet. 2018;391:1285–1300. doi: 10.1016/S0140-6736(17)33293-2. - DOI - PMC - PubMed
    1. Lee K.H., Gordon A., Shedden K., Kuan G., Ng S., Balmaseda A., Foxman B. The respiratory microbiome and susceptibility to influenza virus infection. PLoS ONE. 2019;14:e0207898. doi: 10.1371/journal.pone.0207898. - DOI - PMC - PubMed
    1. Tsang T.K., Lee K.H., Foxman B., Balmaseda A., Gresh L., Sanchez N., Ojeda S., Lopez R., Yang Y., Kuan G., et al. Association Between the Respiratory Microbiome and Susceptibility to Influenza Virus Infection. Clin. Infect. Dis. 2020;71:1195–1203. doi: 10.1093/cid/ciz968. - DOI - PMC - PubMed
    1. Van Kerkhove M.D., Vandemaele K.A.H., Shinde V., Jaramillo-Gutierrez G., Koukounari A., Donnelly C.A., Carlino L.O., Owen R., Paterson B., Pelletier L., et al. Risk Factors for Severe Outcomes following 2009 Influenza A (H1N1) Infection: A Global Pooled Analysis. PLoS Med. 2011;8:e1001053. doi: 10.1371/journal.pmed.1001053. - DOI - PMC - PubMed

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