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Dynamic Human Environmental Exposome Revealed by Longitudinal Personal Monitoring

Overview
Journal Cell
Publisher Cell Press
Specialty Cell Biology
Date 2018 Sep 23
PMID 30241608
Citations 72
Authors
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Abstract

Human health is dependent upon environmental exposures, yet the diversity and variation in exposures are poorly understood. We developed a sensitive method to monitor personal airborne biological and chemical exposures and followed the personal exposomes of 15 individuals for up to 890 days and over 66 distinct geographical locations. We found that individuals are potentially exposed to thousands of pan-domain species and chemical compounds, including insecticides and carcinogens. Personal biological and chemical exposomes are highly dynamic and vary spatiotemporally, even for individuals located in the same general geographical region. Integrated analysis of biological and chemical exposomes revealed strong location-dependent relationships. Finally, construction of an exposome interaction network demonstrated the presence of distinct yet interconnected human- and environment-centric clouds, comprised of interacting ecosystems such as human, flora, pets, and arthropods. Overall, we demonstrate that human exposomes are diverse, dynamic, spatiotemporally-driven interaction networks with the potential to impact human health.

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References
1.
Barberan A, Ladau J, Leff J, Pollard K, Menninger H, Dunn R . Continental-scale distributions of dust-associated bacteria and fungi. Proc Natl Acad Sci U S A. 2015; 112(18):5756-61. PMC: 4426398. DOI: 10.1073/pnas.1420815112. View

2.
Kuleshov V, Jiang C, Zhou W, Jahanbani F, Batzoglou S, Snyder M . Synthetic long-read sequencing reveals intraspecies diversity in the human microbiome. Nat Biotechnol. 2015; 34(1):64-9. PMC: 4884093. DOI: 10.1038/nbt.3416. View

3.
McMurdie P, Holmes S . phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One. 2013; 8(4):e61217. PMC: 3632530. DOI: 10.1371/journal.pone.0061217. View

4.
Smith C, OMaille G, Want E, Qin C, Trauger S, Brandon T . METLIN: a metabolite mass spectral database. Ther Drug Monit. 2006; 27(6):747-51. DOI: 10.1097/01.ftd.0000179845.53213.39. View

5.
Rinke C, Schwientek P, Sczyrba A, Ivanova N, Anderson I, Cheng J . Insights into the phylogeny and coding potential of microbial dark matter. Nature. 2013; 499(7459):431-7. DOI: 10.1038/nature12352. View