Decoding personal biotic and abiotic airborne exposome

Chao Jiang, Xinyue Zhang, Peng Gao, Qiong Chen, Michael Snyder

Published: 2021-01-12 DOI: 10.1038/s41596-020-00451-8

airborne exposome

biotic and abiotic

high-throughput profiling

personal environmental exposome

omics technology

AI 解读

Fabrication of angstrom-scale two-dimensional channels for mass transport

Efficient and strand-specific profiling of replicating chromatin with enrichment and sequencing of protein-associated nascent DNA in mammalian cells

The eINTACT method for studying nuclear changes in host plant cells targeted by bacterial effectors in native infection contexts

Rapid reaction optimization by robust and economical quantitative benchtop19F NMR spectroscopy

Profiling native pulmonary basement membrane stiffness using atomic force microscopy

Photoimmunotechnology as a powerful biological tool for molecular-based elimination of target cells and microbes, including bacteria, fungi and viruses

Measuring key human carbohydrate digestive enzyme activities using high-performance anion-exchange chromatography with pulsed amperometric detection

Neural cell isolation from adult macaques for high-throughput analyses and neurosphere cultures

Preparation, validation and use of a vasoactive tryptophan-derived hydroperoxide and relevant control compounds

Neuronal subtype-specific growth cone and soma purification from mammalian CNS via fractionation and fluorescent sorting for subcellular analyses and spatial mapping of local transcriptomes and proteomes

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The complexity and dynamics of human diseases are driven by the interactions between internal molecular activities and external environmental exposures. Although advances in omics technology have dramatically broadened the understanding of internal molecu
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ACKNOWLEDGMENTS
ACKNOWLEDGMENTS

Franzosa, E. A. et al. Species-level functional profiling of metagenomes and metatranscriptomes. Nat. Methods 15, 962–968 (2018).
Contrepois, K. et al. Cross-platform comparison of untargeted and targeted lipidomics approaches on aging mouse plasma. Sci. Rep. 8, 17747 (2018).
Gao, P. et al. Human exposure to polycyclic aromatic hydrocarbons: metabolomics perspective. Environ. Int. 119, 466–477 (2018).
Wishart, D. S. et al. HMDB 4.0: the human metabolome database for 2018. Nucleic Acids Res. 46, D608–D617 (2018).
Gao, P. et al. Emerging and legacy PAHs in urban soils of four small cities: concentrations, distribution, and sources. Sci. Total Environ. 685, 463–470 (2019).
Wood, D. E., Lu, J. & Langmead, B. Improved metagenomic analysis with Kraken 2. Genome Biol. 20, 257 (2019).
Jiang, C. et al. Dynamic human environmental exposome revealed by longitudinal personal monitoring. Cell 175, 277–291 (2018).
Huang, R. J. et al. High secondary aerosol contribution to particulate pollution during haze events in China. Nature 514, 218–222 (2015).
Cohen, S., Janicki-Deverts, D. & Miller, G. E. Psychological stress and disease. JAMA 298,1685–1687 (2007).
Vermeulen, R., Schymanski, E. L., Barabási, A. L. & Miller, G. W. The exposome and health: where chemistry meets biology. Science 367, 392–396 (2020).
Pfeifer, G. P. Environmental exposures and mutational patterns of cancer genomes. Genome Med. 2, 54 (2010).
Heederik, D. & Von Mutius, E. Does diversity of environmental microbial exposure matter for the occurrence of allergy and asthma? J. Allergy Clin. Immunol. 130, 44–50 (2012).
Miller, F. W. et al. Epidemiology of environmental exposures and human autoimmune diseases: findings from a National Institute of Environmental Health Sciences Expert Panel Workshop. J. Autoimmun. 39, 259–271 (2012).
Fujimura, K. E. et al. House dust exposure mediates gut microbiome Lactobacillus enrichment and airway immune defense against allergens and virus infection. Proc. Natl Acad. Sci. USA 111, 805–810 (2014).
Wild, C. P. Complementing the genome with an ‘exposome’: the outstanding challenge of environmental exposure measurement in molecular epidemiology. Cancer Epidemiol. Biomarkers Prev. 14, 1847–1850 (2005).
Wild, C. P. The exposome: from concept to utility. Int. J. Epidemiol. 41, 24–32 (2012).
Lindholm, M. E. et al. An integrative analysis reveals coordinated reprogramming of the epigenome and the transcriptome in human skeletal muscle after training. Epigenetics 9, 1557–1569 (2014).
Laker, R. C. et al. Transcriptomic and epigenetic responses to short-term nutrient-exercise stress in humans. Sci. Rep. 7, 15134 (2017).
Cao, C. et al. Inhalable microorganisms in Beijing’s PM2.5 and PM10 pollutants during a severe smog event. Environ. Sci. Technol. 48, 1499–1507 (2014).
Lax, S. et al. Longitudinal analysis of microbial interaction between humans and the indoor environment. Science 345, 1048–1052 (2014).
Dannemiller, K. C. et al. Next-generation DNA sequencing reveals that low fungal diversity in house dust is associated with childhood asthma development. Indoor Air 24, 236–247 (2014).
Barberán, A. et al. Continental-scale distributions of dust-associated bacteria and fungi. Proc. Natl Acad. Sci. USA 112, 5756–5761 (2015).
Abbatt, J. P. D. & Wang, C. The atmospheric chemistry of indoor environments. Environ. Sci. Process. Impacts 22, 25–48 (2020).
Oliveira, M., Slezakova, K., Delerue-Matos, C., Pereira, M. C. & Morais, S. Children environmental exposure to particulate matter and polycyclic aromatic hydrocarbons and biomonitoring in school environments: a review on indoor and outdoor exposure levels, major sources and health impacts. Environ Int. 124, 180–204 (2019).
Cissé, O. H., Ma, L., Jiang, C., Snyder, M. & Kovacs, J. A. Humans are selectively exposed to Pneumocystis jirovecii. mBio 11, e03138-19 (2020).
Hänninen, O. O. et al. The EXPOLIS study: implications for exposure research and environmental policy in Europe. J. Expo. Anal. Environ. Epidemiol. 14, 440–456 (2004).
Lelieveld, J., Evans, J. S., Fnais, M., Giannadaki, D. & Pozzer, A. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature 525, 367–371 (2015).
Behzad, H., Gojobori, T. & Mineta, K. Challenges and opportunities of airborne metagenomics. Genome Biol. Evol. 7, 1216–1226 (2015).
Jiang, W. et al. Optimized DNA extraction and metagenomic sequencing of airborne microbial communities. Nat. Protoc. 10, 768–779 (2015).
Gao, P., da Silva, E. B., Townsend, T., Liu, X. & Ma, L. Q. Emerging PAHs in urban soils: concentrations, bioaccessibility, and spatial distribution. Sci. Total Environ. 670, 800–805 (2019).
Xiang, P. et al. Cellular responses of normal (HL-7702) and cancerous (HepG2) hepatic cells to dust extract exposure. Chemosphere 193, 1189–1197 (2018).
Leung, M. H. Y., Wilkins, D., Li, E. K. T., Kong, F. K. F. & Lee, P. K. H. Indoor-air microbiome in an urban subway network: diversity and dynamics. Appl. Environ. Microbiol. 80, 6760–6770 (2014).
Hospodsky, D. et al. Characterizing airborne fungal and bacterial concentrations and emission rates in six occupied children’s classrooms. Indoor Air 25, 641–652 (2015).
Salter, S. J. et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol. 12, 87 (2014).
Weiss, S. et al. Tracking down the sources of experimental contamination in microbiome studies. Genome Biol. 15, 564 (2014).
Cui, Y. et al. The exposome: embracing the complexity for discovery in environmental health. Environ. Health Perspect. 124, A137–A140 (2016).
Gao, P. et al. Spatial and temporal changes of P and Ca distribution and fractionation in soil and sediment in a karst farmland-wetland system. Chemosphere 220, 844–650 (2019).
da Silva, E. B. et al. Background concentrations of trace metals As, Ba, Cd, Co, Cu, Ni, Pb, Se, and Zn in 214 Florida urban soils: different cities and land uses. Environ. Pollut. 264, 114737 (2020).
Volckens, J. et al. Development and evaluation of an ultrasonic personal aerosol sampler. Indoor Air 27, 409–416 (2017).
Truong, D. T. et al. MetaPhlAn2 for enhanced metagenomic taxonomic profiling. Nat. Methods 12, 902–903 (2015).
Barupal, D. K. & Fiehn, O. Generating the blood exposome database using a comprehensive text mining and database fusion approach. Environ. Health Perspect. 127, 97008 (2019).
Wishart, D. et al. T3DB: the toxic exposome database. Nucleic Acids Res. 43, D928–D934 (2015).
García-Alcalde, F. et al. Qualimap: evaluating next-generation sequencing alignment data. Bioinformatics 28, 2678–2679 (2012).

Decoding personal biotic and abiotic airborne exposome

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