Next-generation sequencing (NGS) and advances in microbiota knowledge are opening new perspectives for environmental microbiology and public health. Massive parallel sequencing of bacterial DNA is providing new insights to unravel microbial dissemination in different matrices, including air. Here, we have assessed the air biodiversity in several indoor environments by NGS-based metagenomics and compared results with respect to classical approaches. Environmental sampling was achieved in three exemplificative indoor locations: offices, recreational facilities and public restrooms. Sampling was performed by active (surface air system and high-volume aerosol collection system) and passive (index of microbial air contamination and novel tissue-based passive sampling) techniques. Collected samples were tested by traditional microbiology and DNA-based methods. Biodiversity indices were computed using EstimateS software. Statistical analysis by SPSS and R was applied to determine the variability of bacteria groups after comparing sampling and analysis protocols. In each point (n = 6), air was sampled in duplicate by four methods and tested in parallel by culture-based and DNA-based approaches. A total of over 30 +/- 10 isolates for each point were identified at species level. A total of 3,207,415 sequence reads were generated by NGS analysis, leading to the identification of over 170 OTUs. NGS analyses of air biodiversity were more informative when using active sampling methods (0.729, p < 0.05) and less by passive methods (- 0.897, p < 0.05). NGS allowed a comprehensive and reproducible evaluation of air microbiota and the definition of microbial signatures. Air can be assayed by NGS using different strategies, representing a promising tool for evaluating microbial load and biodiversity. Although NGS requires sophisticated equipment, bioinformatics tools and trained personnel, we propose a model for the evaluation of indoor air quality in occupational and public health settings.
Next-generation sequencing (NGS) and advances in microbiota knowledge are opening new perspectives for environmental microbiology and public health. Massive parallel sequencing of bacterial DNA is providing new insights to unravel microbial dissemination in different matrices, including air. Here, we have assessed the air biodiversity in several indoor environments by NGS-based metagenomics and compared results with respect to classical approaches. Environmental sampling was achieved in three exemplificative indoor locations: offices, recreational facilities and public restrooms. Sampling was performed by active (surface air system and high-volume aerosol collection system) and passive (index of microbial air contamination and novel tissue-based passive sampling) techniques. Collected samples were tested by traditional microbiology and DNA-based methods. Biodiversity indices were computed using EstimateS software. Statistical analysis by SPSS and R was applied to determine the variability of bacteria groups after comparing sampling and analysis protocols. In each point (n = 6), air was sampled in duplicate by four methods and tested in parallel by culture-based and DNA-based approaches. A total of over 30 +/- 10 isolates for each point were identified at species level. A total of 3,207,415 sequence reads were generated by NGS analysis, leading to the identification of over 170 OTUs. NGS analyses of air biodiversity were more informative when using active sampling methods (0.729, p < 0.05) and less by passive methods (- 0.897, p < 0.05). NGS allowed a comprehensive and reproducible evaluation of air microbiota and the definition of microbial signatures. Air can be assayed by NGS using different strategies, representing a promising tool for evaluating microbial load and biodiversity. Although NGS requires sophisticated equipment, bioinformatics tools and trained personnel, we propose a model for the evaluation of indoor air quality in occupational and public health settings.
Can air microbiota be a novel marker for public health? A sampling model and preliminary data from different environments
Gianfranceschi G;Romano Spica V;Valeriani F
2020-01-01
Abstract
Next-generation sequencing (NGS) and advances in microbiota knowledge are opening new perspectives for environmental microbiology and public health. Massive parallel sequencing of bacterial DNA is providing new insights to unravel microbial dissemination in different matrices, including air. Here, we have assessed the air biodiversity in several indoor environments by NGS-based metagenomics and compared results with respect to classical approaches. Environmental sampling was achieved in three exemplificative indoor locations: offices, recreational facilities and public restrooms. Sampling was performed by active (surface air system and high-volume aerosol collection system) and passive (index of microbial air contamination and novel tissue-based passive sampling) techniques. Collected samples were tested by traditional microbiology and DNA-based methods. Biodiversity indices were computed using EstimateS software. Statistical analysis by SPSS and R was applied to determine the variability of bacteria groups after comparing sampling and analysis protocols. In each point (n = 6), air was sampled in duplicate by four methods and tested in parallel by culture-based and DNA-based approaches. A total of over 30 +/- 10 isolates for each point were identified at species level. A total of 3,207,415 sequence reads were generated by NGS analysis, leading to the identification of over 170 OTUs. NGS analyses of air biodiversity were more informative when using active sampling methods (0.729, p < 0.05) and less by passive methods (- 0.897, p < 0.05). NGS allowed a comprehensive and reproducible evaluation of air microbiota and the definition of microbial signatures. Air can be assayed by NGS using different strategies, representing a promising tool for evaluating microbial load and biodiversity. Although NGS requires sophisticated equipment, bioinformatics tools and trained personnel, we propose a model for the evaluation of indoor air quality in occupational and public health settings.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
