Metagenomics reveals novel microbial signatures of farm exposures in house dust

Ziyue Wang; Kathryn R Dalton; Mikyeong Lee; Christine G Parks; Laura E Beane Freeman; Qiyun Zhu; Antonio González; Rob Knight; Shanshan Zhao; Alison A Motsinger-Reif; Stephanie J London

doi:10.1101/2023.04.07.23288301

Metagenomics reveals novel microbial signatures of farm exposures in house dust

medRxiv [Preprint]. 2023 Apr 12:2023.04.07.23288301. doi: 10.1101/2023.04.07.23288301.

Authors

Affiliations

¹ Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
² Genomics and the Environment in Respiratory and Allergic Health Group, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Durham, NC, USA.
³ Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
⁴ School of Life Sciences, Biodesign Center for Fundamental and Applied Microbiomics, Arizona State University, Tempe, AZ, USA.
⁵ Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
⁶ Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA.
⁷ Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
⁸ Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.

Abstract

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.

Publication types

Preprint

Abstract

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