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Transmission of human-associated microbiota along family and social networks

Nature Microbiology volume 4, pages 964–971 (2019)Cite this article

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Abstract

The human microbiome, described as an accessory organ because of the crucial functions it provides, is composed of species that are uniquely found in humans1,2. Yet, surprisingly little is known about the impact of routine interpersonal contacts in shaping microbiome composition. In a relatively ‘closed’ cohort of 287 people from the Fiji Islands, where common barriers to bacterial transmission are absent, we examine putative bacterial transmission in individuals’ gut and oral microbiomes using strain-level data from both core single-nucleotide polymorphisms and flexible genomic regions. We find a weak signal of transmission, defined by the inferred sharing of genotypes, across many organisms that, in aggregate, reveals strong transmission patterns, most notably within households and between spouses. We were unable to determine the directionality of transmission nor whether it was direct. We further find that women harbour strains more closely related to those harboured by their familial and social contacts than men, and that transmission patterns of oral-associated and gut-associated microbiota need not be the same. Using strain-level data alone, we are able to confidently predict a subset of spouses, highlighting the role of shared susceptibilities, behaviours or social interactions that distinguish specific links in the social network.

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Fig. 1: Household membership results in shared bacterial lineages.
Fig. 2: Organisms vary in their transmissibility across the social network.
Fig. 3: Some individuals are ‘supersharers’.
Fig. 4: Machine learning predicts a subset of spouses with high confidence.

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Code availability

The code for the analyses in this paper start with an alignment table in the form of a Python dictionary containing individual core genes as its highest-level keys, where for each core gene there is a M × N × 4 numpy array, for M subjects, N loci and four different alleles (A, G, C and T). The code for filtering these alignment tables into SNP tables and Manhattan distance calculations, and scripts for identifying non-shared mobile genetic elements from 1-kb regions are posted on GitHub at https://github.com/thomasgurry/fijiComp_transmission.

Data availability

Additional information on the samples can be obtained from www.fijicomp.org. All samples may be downloaded from the NCBI Short Read Archive under Bioproject PRJNA217052. Note that the name for sample SRS475548 in the Short Read Archive was incorrectly entered; it should be the oral microbiome sample from M2.33, not W2.33. All accession numbers are listed in Supplementary Table 1. Sample collection was voluntary; thus, not all of the individuals have oral and gut microbiome samples associated with the surveys.

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Acknowledgements

This work was supported by funding from the Center for Microbiome Informatics and Therapeutics at the Massachusetts Institute for Technology (MIT). This work was supported by grants from the National Human Genome Research Institute (U54HG003067) to the Broad Institute, the Center for Environmental Health Sciences at MIT, the Center for Microbiome Informatics and Therapeutics at MIT, and the Fijian Ministry of Health. I.L.B. is a Sloan Foundation Research Fellow, a Packard Fellowship in Science and Engineering, and a Pew Foundation Biomedical Scholar.

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Author notes

  1. These author contributed equally: Ilana L. Brito, Thomas Gurry.

Authors and Affiliations

  1. Meinig School of Biomedical Engineering, Cornell University, Ithaca, NY, USA

    Ilana L. Brito

  2. Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Thomas Gurry, Shijie Zhao & Eric J. Alm

  3. Center for Microbiome, Informatics and Therapeutics, Massachusetts Institute of Technology, Cambridge, MA, USA

    Thomas Gurry, Shijie Zhao & Eric J. Alm

  4. Broad Institute, Cambridge, MA, USA

    Katherine Huang, Sarah K. Young, Terrence P. Shea & Eric J. Alm

  5. Wildlife Conservation Society, Suva, Fiji

    Waisea Naisilisili & Stacy D. Jupiter

  6. Edith Cowan University, Joondalup, Western Australia, Australia

    Aaron P. Jenkins

  7. School of Public Health, University of Sydney, Sydney, New South Wales, Australia

    Aaron P. Jenkins

  8. Janssen Human Microbiome Institute, Cambridge, MA, USA

    Dirk Gevers

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Contributions

This study was conceived by I.L.B. and E.J.A. The study was designed by I.L.B., A.P.J., S.P.J. and E.J.A. Raw data were collected by I.L.B. and W.N. Metagenomic assemblies and metrics were developed and assessed by I.L.B., T.G., S.Z., K.H., S.K.Y., T.P.S., D.G. and E.J.A. Final analyses were performed by I.L.B. and T.G. The paper was written by I.L.B., T.G. and E.J.A.

Corresponding authors

Correspondence to Ilana L. Brito or Eric J. Alm.

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The authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Figures 1–27 and Supplementary Table Legends.

Reporting Summary

Supplementary Tables 1–5

Supplementary Table 1: information on the FijiCOMP study participants; Supplementary Table 2: social network relationships; Supplementary Tables 3 and 4: information about the gut and saliva microbiome metagenomic assemblies, respectively; Supplementary Table 5: core genes used for SNP analyses.

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Brito, I.L., Gurry, T., Zhao, S. et al. Transmission of human-associated microbiota along family and social networks. Nat Microbiol 4, 964–971 (2019). https://doi.org/10.1038/s41564-019-0409-6

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