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Leung MHY, Tong X, Bøifot KO, Bezdan D, Butler DJ, Danko DC, Gohli J, Green DC, Hernandez MT, Kelly FJ, Levy S, Mason-Buck G, Nieto-Caballero M, Syndercombe-Court D, Udekwu K, Young BG, Mason CE, Dybwad M, Lee PKH. Characterization of the public transit air microbiome and resistome reveals geographical specificity. Microbiome 2021; 9:112. [PMID: 34039416 PMCID: PMC8157753 DOI: 10.1186/s40168-021-01044-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Accepted: 03/09/2021] [Indexed: 05/21/2023]
Abstract
BACKGROUND The public transit is a built environment with high occupant density across the globe, and identifying factors shaping public transit air microbiomes will help design strategies to minimize the transmission of pathogens. However, the majority of microbiome works dedicated to the public transit air are limited to amplicon sequencing, and our knowledge regarding the functional potentials and the repertoire of resistance genes (i.e. resistome) is limited. Furthermore, current air microbiome investigations on public transit systems are focused on single cities, and a multi-city assessment of the public transit air microbiome will allow a greater understanding of whether and how broad environmental, building, and anthropogenic factors shape the public transit air microbiome in an international scale. Therefore, in this study, the public transit air microbiomes and resistomes of six cities across three continents (Denver, Hong Kong, London, New York City, Oslo, Stockholm) were characterized. RESULTS City was the sole factor associated with public transit air microbiome differences, with diverse taxa identified as drivers for geography-associated functional potentials, concomitant with geographical differences in species- and strain-level inferred growth profiles. Related bacterial strains differed among cities in genes encoding resistance, transposase, and other functions. Sourcetracking estimated that human skin, soil, and wastewater were major presumptive resistome sources of public transit air, and adjacent public transit surfaces may also be considered presumptive sources. Large proportions of detected resistance genes were co-located with mobile genetic elements including plasmids. Biosynthetic gene clusters and city-unique coding sequences were found in the metagenome-assembled genomes. CONCLUSIONS Overall, geographical specificity transcends multiple aspects of the public transit air microbiome, and future efforts on a global scale are warranted to increase our understanding of factors shaping the microbiome of this unique built environment.
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Affiliation(s)
- M H Y Leung
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
| | - X Tong
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China
| | - K O Bøifot
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - D Bezdan
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - D J Butler
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - D C Danko
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - J Gohli
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway
| | - D C Green
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - M T Hernandez
- Environmental Engineering Program, College of Engineering and Applied Science, University of Colorado, Boulder, CO, USA
| | - F J Kelly
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - S Levy
- HudsonAlpha Institute of Biotechnology, Huntsville, AL, USA
| | - G Mason-Buck
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - M Nieto-Caballero
- Environmental Engineering Program, College of Engineering and Applied Science, University of Colorado, Boulder, CO, USA
| | - D Syndercombe-Court
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK
| | - K Udekwu
- Department of Aquatic Sciences & Assessment, Swedish University of Agriculture, Uppsala, Sweden
| | - B G Young
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - C E Mason
- Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA.
- The HRH Prince Alwaleed Bin Talal Bin Abdulaziz Alsaud Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, USA.
- The WorldQuant Initiative for Quantitative Prediction, Weill Cornell Medicine, New York, NY, USA.
- The Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
| | - M Dybwad
- Comprehensive Defence Division, Norwegian Defence Research Establishment FFI, Kjeller, Norway.
- Department of Analytical, Environmental & Forensic Sciences, King's College London, London, UK.
| | - P K H Lee
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR, China.
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