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      Bacterial community analysis of floor dust and HEPA filters in air purifiers used in office rooms in ILAS, Beijing

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          Abstract

          Air purifiers with high-efficiency particulate air (HEPA) filters remove not only particulate matter but also airborne microorganisms in indoor environments. We investigated the bacterial community in HEPA filters (used for 1 year) and that in the floor dust of 12 office rooms in Beijing. We found that the viable bacteria proportion in the filter was significantly higher than that in the floor dust ( p < 0.001). The Non-Metric Multi-Dimensional Scaling analysis showed that the bacterial communities in the filters and dust were significantly different ( p = 0.001). The Chao1, Shannon–Wiener and phylogenetic diversity values in the filter were significantly higher than those in the dust ( p < 0.001). The predominant bacterial classes in the filter were Alphaproteobacteria and Actinobacteria, whereas those in the dust were Bacteroidia, Clostridia and Bacilli. Human occupancy contributed more to the bacterial community in the filter than that in the dust. Klebsiella and Alloprevotella in the dust and filters positively correlated with the occupancy density. Soil bacteria contributed to a significantly higher proportion of the bacteria in the HEPA filter ( p < 0.001). In contrast, human oral, indoor air and outdoor haze contributed to a higher proportion of the bacteria in the dust samples ( p < 0.001, p < 0.01 and p < 0.05, respectively). As HEPA filters serve as an ecological niche for indoor bacteria, they should be carefully investigated during the assessment of indoor environmental health.

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          Trimmomatic: a flexible trimmer for Illumina sequence data

          Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact: usadel@bio1.rwth-aachen.de Supplementary information: Supplementary data are available at Bioinformatics online.
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            QIIME allows analysis of high-throughput community sequencing data.

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              UPARSE: highly accurate OTU sequences from microbial amplicon reads.

              Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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                Author and article information

                Contributors
                qinchuan@pumc.edu.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                14 April 2020
                14 April 2020
                2020
                : 10
                : 6417
                Affiliations
                [1 ]ISNI 0000 0001 0662 3178, GRID grid.12527.33, Institute of Laboratory Animal Science, , Chinese Academy of Medical Sciences & Peking Union Medical College, ; Beijing, 100021 China
                [2 ]NHC Key Laboratory of Human Disease Comparative Medicine, Beijing, 100021 China
                [3 ]ISNI 0000 0001 0193 3564, GRID grid.19373.3f, Department of Food Science and Engineering, School of Chemistry and Chemical Engineering, , Harbin Institute of Technology, ; Harbin, 150001 China
                Article
                63543
                10.1038/s41598-020-63543-1
                7156680
                32286482
                ce736a39-4236-4ecf-8c88-6fb6151b3a29
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 November 2019
                : 1 April 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100005149, CAMS | Cancer Institute and Hospital, Chinese Academy of Medical Sciences (Cancer Institute and Hospital);
                Award ID: 2018-12M-1-001
                Award ID: 2017-12M-2-005
                Award Recipient :
                Categories
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                © The Author(s) 2020

                Uncategorized
                microbial ecology,risk factors
                Uncategorized
                microbial ecology, risk factors

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