Markus Hilty

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 bioinformatic 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. We analyzed a previously published data set of longitudinally collected nasopharyngeal samples from Bangladeshi infants (Microbiota and Health study) and a novel data set 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 with metagenomic assemblies derived from StrainGE and newly derived whole-genome sequencing data. After optimizing the analytical parameters, we compared StrainPhlAn 3 results to culture gold standard methods and achieved sensitivity values of 87% ( Streptococcus pneumoniae ), 80% ( Moraxella catarrhalis ), 75% ( Haemophilus influenzae ), and 57% ( Staphylococcus 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. In conclusion, a comparison of StrainPhlAn 3 results to data from bacterial cultures revealed that strain-level tracking of the respiratory microbiome is feasible despite the high content of host DNA when parameters are carefully optimized to fit low biomass microbiomes. 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.

Airborne concentrations of organic dust on animal farms are known to be very high. This dust is partly composed of microorganisms such as bacteria, fungi and their components [endotoxins, (1→3)-β-d-glucans, mould allergens, mycotoxins], recognised as being responsible for numerous health effects. Several cross-sectional studies have measured levels of airborne bacteria, fungi and endotoxins on pig farms. However, the temporal dynamics of organic dust’s components throughout the year have rarely been assessed, and airborne concentrations of (1→3)-β-d-glucans and mould allergens remain poorly understood in these work environments. This longitudinal, four-season study measured cultivable fungi, endotoxins, (1→3)-β-d-glucans, Aspergillus versicolor (AveX), Aspergillus fumigatus (Asp f1) and Alternaria sp (Alt a1) allergens on 31 pig farms in Switzerland. Results showed that exposure to AveX occurred in all four seasons. Total mean airborne concentration of endotoxins were between 3 and 4 times higher than the Swiss recommended limit value of 1000 EU m-3 and mean airborne concentrations of fungi were between 30 and 50 times higher than the Swiss recommended limit value of 1000 cfu m-3. Finally, accumulations of faecal matter on floors, humidity and dusty pathways were associated with increased concentrations of (1→3)-β-d-glucans. In conclusion, pig farmers require better information about biological occupational risks, and measures to improve air quality should be implemented, especially in winter.