Nasal microbiota clusters associate with inflammatory response, viral load, and symptom severity in experimental rhinovirus challenge

Abstract

The role of nasal and fecal microbiota in viral respiratory infections has not been established. We collected nasal swabs and washes, and fecal samples in a clinical study assessing the effect of probiotic Bifidobacterium animalis subsp. lactis Bl-04 on experimental rhinovirus infection. The nasal and fecal microbiota were characterized by 16S rRNA gene sequencing. The resulting data were compared with nasal inflammatory marker concentrations, viral load, and clinical symptoms. By using unsupervised clustering, the nasal microbiota divided into six clusters. The clusters predominant of Staphylococcus, Corynebacterium/Alloiococcus, Moraxella, and Pseudomonadaceae/Mixed had characteristic inflammatory marker and viral load profiles in nasal washes. The nasal microbiota clusters of subjects before the infection associated with the severity of clinical cold symptoms during rhinovirus infection. Rhinovirus infection and probiotic intervention did not significantly alter the composition of nasal or fecal microbiota. Our results suggest that nasal microbiota may influence the virus load, host innate immune response, and clinical symptoms during rhinovirus infection, however, further studies are needed.

Figure 1

Study outline and sampling set-up. Subjects were enrolled from three separate cohorts to receive either Bl-04 (2 × 10⁹ CFU/day) or placebo for 28 days prior to being challenged with an experimental rhinovirus. The participants continued investigational product intake for 4 days post-challenge. On study day (D) 0, subjects were inoculated with rhinovirus type A39 (FDA-BB-IND #12934) (100 TCID₅₀, split between both nostrils). On D1–D5, participants returned to the study site for assessment of infection symptoms assessed by WURSS-21, collection of nasal lavage for inflammatory marker analyses, and quantitative rhinovirus culture. Volunteers returned a final time at D28 for collection of convalescent serum for antibody to rhinovirus type A39.

Figure 2

Clustering of nasal microbiota samples. (a) Principal coordinates plot showing clustering independent of time point and treatment. (b) Unweighted pair-group method (UPGMA) clustering of samples (c) Principal coordinates plot of sample distribution in different time points and treatment groups.

Figure 3

Relative abundance (%) of bacterial genera in the nasal microbiotas of six clusters in the two study groups over study time. The number of samples for each time and treatment point is shown in Supplementary Table 1.

Figure 4

Mean alpha diversities of the clusters over time. Staph vs. Ps/Mix estimated mean difference (EMD) [log] = −0.35, Cor/All vs. Ps/Mix EMD [log] = −0.35, Mor vs. Ps/Mix EMD [log] = −0.54, Hae vs. Ps/Mix EMD [log] = −0.37, Staph vs. Mor EMD [log] = 0.19, and Cor/All vs. Mor EMD [log] = 0.19. RM ANCOVA, all p-values are unadjusted. Over time total N: Mixed N = 11, Ps/Mix N = 110, Staph N = 288, Cor/All N = 429, Hae N = 25, and Mor N = 66.

Figure 5

Inflammatory marker response and viral titer during rhinovirus infection. Inflammatory marker concentrations (a–g) were determined from nasal washes D0–D5 by ELISA. Geometric mean values from D0 to D5 are shown for Staph, Cor/All, Mor, and Ps/Mix clusters. Viral titer (h) was analyzed from nasal washes D1–D5. Statistical testing for the change in inflammatory markers (a–g) from D0 and for viral titer (h) by cluster was assessed with RM ANCOVA.

Figure 6

Nasal microbiota cluster and clinical symptoms during rhinovirus infection. The symptom scores for clusters Staph, Cor/All, Mor, and Ps/Mix were evaluated over D1–D5 by using (a) WURSS-21 questionnaire. Scores for sub-category (b) Total Cold Symptoms, and for individual symptoms (c) Runny Nose, (d) Plugged Nose, (e) Sneezing, and (f) Cough in WURSS-21 are shown separately. The statistical testing was performed with negative binomial (GEE) model.