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Metagenomics reveals novel microbial signatures of farm exposures in house dust

Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole...

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Autores principales: Wang, Ziyue, Dalton, Kathryn R., Lee, Mikyeong, Parks, Christine G., Beane Freeman, Laura E., Zhu, Qiyun, González, Antonio, Knight, Rob, Zhao, Shanshan, Motsinger-Reif, Alison A, London, Stephanie J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120797/
https://www.ncbi.nlm.nih.gov/pubmed/37090637
http://dx.doi.org/10.1101/2023.04.07.23288301
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author Wang, Ziyue
Dalton, Kathryn R.
Lee, Mikyeong
Parks, Christine G.
Beane Freeman, Laura E.
Zhu, Qiyun
González, Antonio
Knight, Rob
Zhao, Shanshan
Motsinger-Reif, Alison A
London, Stephanie J.
author_facet Wang, Ziyue
Dalton, Kathryn R.
Lee, Mikyeong
Parks, Christine G.
Beane Freeman, Laura E.
Zhu, Qiyun
González, Antonio
Knight, Rob
Zhao, Shanshan
Motsinger-Reif, Alison A
London, Stephanie J.
author_sort Wang, Ziyue
collection PubMed
description Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.
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spelling pubmed-101207972023-04-22 Metagenomics reveals novel microbial signatures of farm exposures in house dust Wang, Ziyue Dalton, Kathryn R. Lee, Mikyeong Parks, Christine G. Beane Freeman, Laura E. Zhu, Qiyun González, Antonio Knight, Rob Zhao, Shanshan Motsinger-Reif, Alison A London, Stephanie J. medRxiv Article Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health. Cold Spring Harbor Laboratory 2023-04-12 /pmc/articles/PMC10120797/ /pubmed/37090637 http://dx.doi.org/10.1101/2023.04.07.23288301 Text en https://creativecommons.org/publicdomain/zero/1.0/This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license (https://creativecommons.org/publicdomain/zero/1.0/) .
spellingShingle Article
Wang, Ziyue
Dalton, Kathryn R.
Lee, Mikyeong
Parks, Christine G.
Beane Freeman, Laura E.
Zhu, Qiyun
González, Antonio
Knight, Rob
Zhao, Shanshan
Motsinger-Reif, Alison A
London, Stephanie J.
Metagenomics reveals novel microbial signatures of farm exposures in house dust
title Metagenomics reveals novel microbial signatures of farm exposures in house dust
title_full Metagenomics reveals novel microbial signatures of farm exposures in house dust
title_fullStr Metagenomics reveals novel microbial signatures of farm exposures in house dust
title_full_unstemmed Metagenomics reveals novel microbial signatures of farm exposures in house dust
title_short Metagenomics reveals novel microbial signatures of farm exposures in house dust
title_sort metagenomics reveals novel microbial signatures of farm exposures in house dust
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10120797/
https://www.ncbi.nlm.nih.gov/pubmed/37090637
http://dx.doi.org/10.1101/2023.04.07.23288301
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