Carbon source-dependent capsule thickness regulation in Streptococcus pneumoniae.

Background: The polysaccharide capsule of Streptococcus pneumoniae plays a major role in virulence, adherence to epithelial cells, and overall survival of the bacterium in the human host. Galactose, mannose, and N-acetylglucosamine (GlcNAc) are likely to be relevant for metabolization in the nasopharynx, while glucose is the primary carbon source in the blood. In this study, we aim to further the understanding of the influence of carbon sources on pneumococcal growth, capsule biosynthesis, and subsequent adherence potential. Methods: We tested the growth behavior of clinical wild-type and capsule knockout S. pneumoniae strains, using galactose, GlcNAc, mannose, and glucose as carbon source for growth. We measured capsule thickness and quantified capsule precursors by fluorescein isothiocyanate (FITC)-dextran exclusion assays and 31P-nuclear magnetic resonance measurements, respectively. We also performed epithelial adherence assays using Detroit 562 cells and performed a transcriptome analysis (RNA sequencing). Results: We observed a reduced growth in galactose, mannose, and GlcNAc compared to growth in glucose and found capsular size reductions in mannose and GlcNAc compared to galactose and glucose. Additionally, capsular precursor measurements of uridine diphosphate-(UDP)-glucose and UDP-galactose showed less accumulation of precursors in GlcNAc or mannose than in glucose and galactose, indicating a possible link with the received capsular thickness measurements. Epithelial adherence assays showed an increase in adherence potential for a pneumococcal strain, when grown in mannose compared to glucose. Finally, transcriptome analysis of four clinical isolates revealed not only strain specific but also common carbon source-specific gene expression. Conclusion: Our findings may indicate a careful adaption of the lifestyle of S. pneumoniae according to the monosaccharides encountered in the respective human niche.

Informed interpretation of metagenomic data by StrainPhlAn enables strain retention analyses of the upper airway microbiome.

IMPORTANCE: The usage of 16S rRNA gene sequencing has become the state-of-the-art method for the characterization of the microbiota in health and respiratory disease. The method is reliable for low biomass samples due to prior amplification of the 16S rRNA gene but has limitations as species and certainly strain identification is not possible. However, the usage of metagenomic tools for the analyses of microbiome data from low biomass samples is not straight forward, and careful optimization is needed. In this work, we show that by validating StrainPhlAn 3 results with the data from bacterial cultures, the strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA being present when parameters are carefully optimized to fit low biomass microbiomes. This work further proposes that strain retention analyses are feasible, at least for more abundant species. This will help to better understand the longitudinal dynamics of the upper respiratory microbiome during health and disease.

Antibiotics in pregnancy influence nasal microbiome and respiratory morbidity in infancy.

Background: The effects 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 at school age, and whether this association with respiratory morbidity is mediated by the nasal microbiome. Methods: We performed 16S ribosomal RNA 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 interviews. 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. Results: α-Diversity indices were lower in infants with antibiotic exposure compared to nonexposed 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 1.38, 95% CI 1.03-1.84; adjusted p-value (padj)=0.032 and risk ratio 1.75, 95% CI 1.02-2.97; padj=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. Conclusion: Prenatal 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.