Background: Shotgun metagenomic sequencing has the potential to provide bacterial strain-level resolution which is of key importance to tackle a host of clinical questions. While bioinformatics tools that achieve strain-level resolution are available, thorough benchmarking is needed to validate their use for less investigated and low biomass microbiomes like those from the upper respiratory tract. Methods: We analyzed a previously published dataset of longitudinally collected nasopharyngeal samples from Bangladeshi infants (Microbiota & Health study) and a novel dataset of oropharyngeal samples from Swiss children with cystic fibrosis. Data from bacterial cultures were used for benchmarking the parameters of StrainPhlAn 3, a bioinformatic tool designed for strain-level resolution. In addition, StrainPhlAn 3 results were compared to metagenomic assemblies and whole-genome sequencing data of S. aureus strains. Finally, strain retention analyses were performed. Results: After optimizing the analytical parameters, we compared our results to culture gold standard methods and achieved sensitivity values of 87% (S. pneumoniae), 80% (M. catarrhalis), 75% (H. influenzae) and 57% (S. aureus) for 420 nasopharyngeal and 75% (H. influenzae) and 46% (S. aureus) for 260 oropharyngeal samples. Comparing the phylogenetic tree of the core genome of 50 S. aureus isolates with a corresponding marker gene tree generated by StrainPhlAn 3 revealed a striking similarity in tree topology for all but three samples indicating adequate strain resolution. Quantitative analyses of longitudinally collected samples revealed clear signatures of strain retention for the four analyzed species. Conclusions: Comparison of StrainPhlAn 3 results to data from bacterial cultures revealed that strain-level tracking of the respiratory microbiome is feasible despite high content of host DNA when parameters are carefully optimized to fit low biomass microbiomes. This allowed to perform strain retention analyses applied to relevant pathobionts which will help to better understand the longitudinal dynamics of the upper respiratory microbiome during health and disease.
BackgroundThe effect of prenatal antibiotic exposure on respiratory morbidity in infancy and the involved mechanisms are still poorly understood. We aimed to examine whether prenatal antibiotic exposure in the third trimester is associated with nasal microbiome and respiratory morbidity in infancy and school age, and whether this association with respiratory morbidity is mediated by the nasal microbiome.MethodsWe performed 16S rRNA gene sequencing (regions V3-V4) on nasal swabs obtained from 296 healthy term infants from the prospective Basel-Bern birth cohort (BILD) at age 4–6 weeks. Information about antibiotic exposure was derived from birth records and standardised interview. Respiratory symptoms were assessed by weekly telephone interviews in the first year of life and a clinical visit at age 6 years. Structural equation modelling was used to test direct and indirect associations accounting for known risk factors.Resultsα-diversity indices were lower in infants with antibiotic exposure compared to non-exposed infants (e.g., Shannon index p-value=0.006). Prenatal antibiotic exposure was also associated with a higher risk of any as well as severe respiratory symptoms in the first year of life (risk ratio (RR) 1.38, 95% confidence interval (CI) 1.03;1.84, padj-value=0.032 and RR 1.75, 95% CI 1.02;2.97, padj-value=0.041, respectively), but not with wheeze or atopy in childhood. However, we found no indirect mediating effect of nasal microbiome explaining these clinical symptoms.ConclusionPrenatal antibiotic exposure was associated with lower diversity of nasal microbiome in infancy and, independently of microbiome, with respiratory morbidity in infancy, but not with symptoms later in life.
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