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Home chemical and microbial transitions across urbanization

Nature Microbiology volume 5, pages 108–115 (2020)Cite this article

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Abstract

Urbanization represents a profound shift in human behaviour, and has considerable cultural and health-associated consequences1,2. Here, we investigate chemical and microbial characteristics of houses and their human occupants across an urbanization gradient in the Amazon rainforest, from a remote Peruvian Amerindian village to the Brazilian city of Manaus. Urbanization was found to be associated with reduced microbial outdoor exposure, increased contact with housing materials, antimicrobials and cleaning products, and increased exposure to chemical diversity. The degree of urbanization correlated with changes in the composition of house bacterial and microeukaryotic communities, increased house and skin fungal diversity, and an increase in the relative abundance of human skin-associated fungi and bacteria in houses. Overall, our results indicate that urbanization has large-scale effects on chemical and microbial exposures and on the human microbiota.

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Fig. 1: Study design.
Fig. 2: House chemical and microbial diversity is altered by urbanization.
Fig. 3: House fungal diversity is correlated with abundance of cleaning and personal care products and overall chemical diversity.

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Data availability

Mass spectrometry data have been deposited in MassIVE (accession number MSV000082924). Molecular networking jobs are available at https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=549cfafcdaef4a7496768f45bb90771c (full housing dataset). GNPS molecular networking jobs for dataset matching are available at https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=f1bc8144b7f648dc94215a34b94537df (Checherta), https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=044f5c1437e4453eb9d47afafadb7cfb (Puerto Almendra), https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=c3736e2379d1470f8b9e990a1afeb682 (Iquitos), https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=8799f335311540bdb5af75da896bd87c (Manaus low income) and https://gnps.ucsd.edu/ProteoSAFe/status.jsp?task=1070c36112c940a186fcf4454f845f08 (Manaus middle class; searches performed 19 August 2018). In silico structure annotation using NAP is provided at https://proteomics2.ucsd.edu/ProteoSAFe/status.jsp?task=af425ada55d54adca9c7b28a823af54c. The raw sequencing data and processed BIOM tables are available at Qiita (https://qiita.ucsd.edu/) under study ID 10333, and also at EMBL-EBI under submission number ERP107551.

Code availability

Instructions and source codes for replicating the bioinformatic analyses are provided at https://github.com/knightlab-analyses/amazon-urbanization.

Change history

  • 24 January 2020

    In the version of this Letter originally published, Maria G. Dominguez-Bello’s e-mail address was missing a hyphen; it has now been corrected to mg.dominguez-bello@rutgers.edu.

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Acknowledgements

We thank the collaborators in Peru, the late L. Bocca and the interpreter J. J. Semu for their support and information sources; in Manaus, A. Vasconcelos and J. Machado for help with the fieldwork, and the support of the community leader M. Aparecida Lisboa, Director of Association Fazendo Amigos (AFA), Manaus; the nurses that accompanied the researchers in the jungle; I. Fajardo Neddermann for helping us with the architectural work; D. Vargas and M. Magris, who helped to prepare the urbanization score survey; D. McDonald, J. Morton, R. da Silva and L. Jiang, who helped with DNA and MS data analysis. A. Cai helped to determine the sources of microorganisms correlated with cleaning products; in Peru, staff and community members participating within the Malaria Immunology and Genetics in the Amazon Project with the Ministry of Health of Peru for support. This study was supported by the Sloan Foundation (to M.G.D.-B., R.K. and P.C.D.), C&D Fund, and Emch Fund for Microbial Diversity (to M.G.D.-B.). Partial support was also provided by the NIH Research Initiative for Scientific Enhancement Program 2R25GM061151-13 (to J.F.R.-C.). L.-I.M. was partially supported by a fellowship from the Canadian Institutes of Health Research (grant no. 338511; http://www.cihr-irsc.gc.ca/). C.C. was supported by the Belgian American Educational Foundation and the Research Foundation Flanders. We acknowledge the NIH for providing the MS and MS data analysis infrastructure P41-GM103484 and GMS10RR029121 (to P.C.D.).

Author information

Author notes

  1. These authors contributed equally: Laura-Isobel McCall, Chris Callewaert, Qiyun Zhu.

Authors and Affiliations

  1. Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA

    Laura-Isobel McCall

  2. Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA

    Laura-Isobel McCall

  3. Department of Pediatrics, University of California San Diego, La Jolla, CA, USA

    Chris Callewaert, Qiyun Zhu, Se Jin Song, Pieter C. Dorrestein & Rob Knight

  4. Center for Microbial Ecology and Technology, Ghent University, Gent, Belgium

    Chris Callewaert

  5. Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA

    Se Jin Song, Pieter C. Dorrestein & Rob Knight

  6. Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA

    Amina Bouslimani, Madeleine Ernst & Pieter C. Dorrestein

  7. Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, USA

    Amina Bouslimani, Madeleine Ernst & Pieter C. Dorrestein

  8. Marine Biology Research Division, Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, USA

    Jeremiah J. Minich

  9. Biochemistry Department, University of Puerto Rico, San Juan, Puerto Rico, USA

    Jean F. Ruiz-Calderon

  10. School of Architecture, University of Puerto Rico, San Juan, Puerto Rico, USA

    Humberto Cavallin

  11. Center for Environmental Sciences, Federal University of Amazonas, Manaus, Brazil

    Henrique S. Pereira

  12. Department of Civil, Architectural and Environmental Engineering, University of Texas at Austin, Austin, TX, USA

    Atila Novoselac

  13. Department of Biology, University of Puerto Rico, San Juan, Puerto Rico, USA

    Jean Hernandez

  14. Department of Environmental Sciences, University of Puerto Rico, San Juan, Puerto Rico, USA

    Rafael Rios

  15. College of Health and Human Services, Office of Research Integrity, Concordia University, Portland, OR, USA

    OraLee H. Branch

  16. Universidad Nacional de la Amazonia Peruana, Iquitos, Peru

    OraLee H. Branch

  17. Center for Advanced Biotechnology and Medicine, Rutgers University, Piskataway, NJ, USA

    Martin J. Blaser

  18. Center for Natural Sciences and Humanities, Federal University of ABC, Santo André, Brazil

    Luciana C. Paulino

  19. Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA

    Rob Knight

  20. Department of Bioengineering, University of California San Diego, La Jolla, CA, USA

    Rob Knight

  21. Department of Biochemistry and Microbiology, Rutgers University, New Brunswick, NJ, USA

    Maria G. Dominguez-Bello

  22. Department of Anthropology, Rutgers University, New Brunswick, NJ, USA

    Maria G. Dominguez-Bello

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Contributions

M.G.D.-B., P.C.D. and R.K. conceived and designed the study. M.G.D.-B., J.F.R.-C., H.S.P., J.H., R.R., O.H.B., M.J.B., L.C.P., A.N. and H.C. collected the samples and metadata. A.B. acquired LC–MS data. L.-I.M. led the LC–MS data analysis. C.C. led the taxonomy and metadata analysis. Q.Z. led the DNA data and multi-omics analysis. J.J.M. performed qPCR. S.J.S., M.E., H.C., A.N., A.B. and J.J.M. provided additional contributions to data analysis. L.-I.M., C.C., Q.Z. and M.G.D.-B. wrote the manuscript with contributions from R.K. and P.C.D. All of the authors reviewed the final manuscript.

Corresponding authors

Correspondence to Pieter C. Dorrestein, Rob Knight or Maria G. Dominguez-Bello.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Notes, Supplementary Tables 1–6, Supplementary Figs. 1–22, Supplementary References and legends for Supplementary Data 1–5.

Reporting Summary

Supplementary Data 1

Cleaning product metabolite feature table.

Supplementary Data 2

Pearson correlation analysis between relative abundances of cleaning products and bacteria (n = 256).

Supplementary Data 3

Pearson correlation analysis between relative abundances of cleaning products and fungi (n = 140).

Supplementary Data 4

Pearson correlation analysis between relative abundances of cleaning products and microeukaryotes (n = 82).

Supplementary Data 5

Urbanization score calculation tool.

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McCall, LI., Callewaert, C., Zhu, Q. et al. Home chemical and microbial transitions across urbanization. Nat Microbiol 5, 108–115 (2020). https://doi.org/10.1038/s41564-019-0593-4

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