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Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples

Author

Listed:
  • Maria Rita Perrone

    (Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy)

  • Salvatore Romano

    (Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy)

  • Giuseppe De Maria

    (Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy)

  • Paolo Tundo

    (Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy)

  • Anna Rita Bruno

    (Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy)

  • Luigi Tagliaferro

    (Presidio Ospedaliero Santa Caterina Novella, Azienda Sanitaria Locale Lecce, 73013 Galatina, Italy)

  • Michele Maffia

    (Department of Biological and Environmental Sciences and Technologies, University of Salento, 73100 Lecce, Italy)

  • Mattia Fragola

    (Department of Mathematics and Physics, University of Salento, 73100 Lecce, Italy)

Abstract

The compositional analysis of 16S rRNA gene sequencing datasets is applied to characterize the bacterial structure of airborne samples collected in different locations of a hospital infection disease department hosting COVID-19 patients, as well as to investigate the relationships among bacterial taxa at the genus and species level. The exploration of the centered log-ratio transformed data by the principal component analysis via the singular value decomposition has shown that the collected samples segregated with an observable separation depending on the monitoring location. More specifically, two main sample clusters were identified with regards to bacterial genera (species), consisting of samples mostly collected in rooms with and without COVID-19 patients, respectively. Human pathogenic genera (species) associated with nosocomial infections were mostly found in samples from areas hosting patients, while non-pathogenic genera (species) mainly isolated from soil were detected in the other samples. Propionibacterium acnes , Staphylococcus pettenkoferi , Corynebacterium tuberculostearicum , and jeikeium were the main pathogenic species detected in COVID-19 patients’ rooms. Samples from these locations were on average characterized by smaller richness/evenness and diversity than the other ones, both at the genus and species level. Finally, the ρ metrics revealed that pairwise positive associations occurred either between pathogenic or non-pathogenic taxa.

Suggested Citation

  • Maria Rita Perrone & Salvatore Romano & Giuseppe De Maria & Paolo Tundo & Anna Rita Bruno & Luigi Tagliaferro & Michele Maffia & Mattia Fragola, 2022. "Compositional Data Analysis of 16S rRNA Gene Sequencing Results from Hospital Airborne Microbiome Samples," IJERPH, MDPI, vol. 19(16), pages 1-21, August.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:16:p:10107-:d:889164
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    References listed on IDEAS

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