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Spatial metagenomic characterization of microbial biogeography in the gut

Nature Biotechnology volume 37, pages 877–883 (2019)Cite this article

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Abstract

Spatial structuring is important for the maintenance of natural ecological systems1,2. Many microbial communities, including the gut microbiome, display intricate spatial organization3,4,5,6,7,8,9. Mapping the biogeography of bacteria can shed light on interactions that underlie community functions10,11,12, but existing methods cannot accommodate the hundreds of species that are found in natural microbiomes13,14,15,16,17. Here we describe metagenomic plot sampling by sequencing (MaPS-seq), a culture-independent method to characterize the spatial organization of a microbiome at micrometer-scale resolution. Intact microbiome samples are immobilized in a gel matrix and cryofractured into particles. Neighboring microbial taxa in the particles are then identified by droplet-based encapsulation, barcoded 16S rRNA amplification and deep sequencing. Analysis of three regions of the mouse intestine revealed heterogeneous microbial distributions with positive and negative co-associations between specific taxa. We identified robust associations between Bacteroidales taxa in all gut compartments and showed that phylogenetically clustered local regions of bacteria were associated with a dietary perturbation. Spatial metagenomics could be used to study microbial biogeography in complex habitats.

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Fig. 1: MaPS-seq and quality control.
Fig. 2: Spatial organization of the microbiota in the mouse distal colon.
Fig. 3: Survey of spatial organization in the mouse gastrointestinal tract.
Fig. 4: Spatial organization in the colon after dietary perturbation.

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Data availability

All sequencing data are available from the NCBI Sequence Read Archive under accession PRJNA541181.

Code availability

The code utilized in this study as well as microfluidic device designs and OTU tables can be accessed at http://github.com/ravisheth/mapsseq.

References

  1. Reichenbach, T., Mobilia, M. & Frey, E. Mobility promotes and jeopardizes biodiversity in rock–paper–scissors games. Nature 448, 1046–1049 (2007).

    Article  CAS  PubMed  Google Scholar 

  2. MacArthur, R. H. & Wilson, E. O. The Theory of Island Biogeography (Princeton University Press, 1967).

  3. Cordero, O. X. & Datta, M. S. Microbial interactions and community assembly at microscales. Curr. Opin. Microbiol. 31, 227–234 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Swidsinski, A., Loening Baucke, V., Verstraelen, H., Osowska, S. & Doerffel, Y. Biostructure of fecal microbiota in healthy subjects and patients with chronic idiopathic diarrhea. Gastroenterology 135, 568–579 (2008).

    Article  PubMed  Google Scholar 

  5. Yasuda, K. et al. Biogeography of the intestinal mucosal and lumenal microbiome in the Rhesus Macaque. Cell Host Microbe 17, 385–391 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Earle, K. A. et al. Quantitative imaging of gut microbiota spatial organization. Cell Host Microbe 18, 478–488 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Mark Welch, J. L., Rossetti, B. J., Rieken, C. W., Dewhirst, F. E. & Borisy, G. G. Biogeography of a human oral microbiome at the micron scale. Proc. Natl Acad. Sci. USA 113, E791–800 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Mark Welch, J. L., Hasegawa, Y., McNulty, N. P., Gordon, J. I. & Borisy, G. G. Spatial organization of a model 15-member human gut microbiota established in gnotobiotic mice. Proc. Natl Acad. Sci. USA 21, E9105–E9114 (2017).

    Article  Google Scholar 

  9. Donaldson, G. P., Lee, S. M. & Mazmanian, S. K. Gut biogeography of the bacterial microbiota. Nat. Rev. Microbiol. 14, 20–32 (2016).

    Article  CAS  PubMed  Google Scholar 

  10. Lee, S. M. et al. Bacterial colonization factors control specificity and stability of the gut microbiota. Nature 501, 426–429 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Nagara, Y., Takada, T., Nagata, Y., Kado, S. & Kushiro, A. Microscale spatial analysis provides evidence for adhesive monopolization of dietary nutrients by specific intestinal bacteria. PLoS ONE 12, e0175497 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  12. Tropini, C., Earle, K. A., Huang, K. C. & Sonnenburg, J. L. The gut microbiome: connecting spatial organization to function. Cell Host Microbe 21, 433–442 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Nava, G. M., Friedrichsen, H. J. & Stappenbeck, T. S. Spatial organization of intestinal microbiota in the mouse ascending colon. ISME J. 5, 627–638 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Pedron, T. et al. A crypt-specific core microbiota resides in the mouse colon. mBio 3, e00116-12 (2012).

    Article  PubMed  PubMed Central  Google Scholar 

  15. Valm, A. M., Welch, J. L. M. & Borisy, G. G. CLASI-FISH: principles of combinatorial labeling and spectral imaging. Syst. Appl. Microbiol. 35, 496–502 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Geva-Zatorsky, N. et al. In vivo imaging and tracking of host–microbiota interactions via metabolic labeling of gut anaerobic bacteria. Nat. Med. 21, 1091–1100 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Whitaker, W. R., Shepherd, E. S. & Sonnenburg, J. L. Tunable expression tools enable single-cell strain distinction in the gut microbiome. Cell 169, 538–546 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Pereira, F. C. & Berry, D. Microbial nutrient niches in the gut. Environ. Microbiol. 19, 1366–1378 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  19. Donaldson, G. P. et al. Gut microbiota utilize immunoglobulin A for mucosal colonization. Science 360, 795–800 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Wexler, A. G. et al. Human symbionts inject and neutralize antibacterial toxins to persist in the gut. Proc. Natl Acad. Sci. USA 113, 3639–3644 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kim, H. J., Boedicker, J. Q., Choi, J. W. & Ismagilov, R. F. Defined spatial structure stabilizes a synthetic multispecies bacterial community. Proc. Natl Acad. Sci. USA 105, 18188–18193 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Coyte, K. Z., Schluter, J. & Foster, K. R. The ecology of the microbiome: networks, competition, and stability. Science 350, 663–666 (2015).

    Article  CAS  PubMed  Google Scholar 

  23. Amann, R. & Fuchs, B. M. Single-cell identification in microbial communities by improved fluorescence in situ hybridization techniques. Nat. Rev. Microbiol. 6, 339–348 (2008).

    Article  CAS  PubMed  Google Scholar 

  24. Rakoff-Nahoum, S., Coyne, M. J. & Comstock, L. E. An ecological network of polysaccharide utilization among human intestinal symbionts. Curr. Biol. 24, 40–49 (2014).

    Article  CAS  PubMed  Google Scholar 

  25. Ji, B. W. et al. Quantifying spatiotemporal variability and noise in absolute microbiota abundances using replicate sampling. Nat. Methods https://doi.org/10.1038/s41592-019-0467-y (2019).

  26. Ormerod, K. L. et al. Genomic characterization of the uncultured Bacteroidales family S24-7 inhabiting the guts of homeothermic animals. Microbiome 4, 36 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  27. Rakoff-Nahoum, S., Foster, K. R. & Comstock, L. E. The evolution of cooperation within the gut microbiota. Nature 533, 255–259 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Carmody, R. N. et al. Diet dominates host genotype in shaping the murine gut microbiota. Cell Host Microbe 17, 72–84 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Sonnenburg, E. D. et al. Diet-induced extinctions in the gut microbiota compound over generations. Nature 529, 212–215 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. David, L. A. et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2014).

    Article  CAS  PubMed  Google Scholar 

  31. Webb, C. O., Ackerly, D. D., McPeek, M. A. & Donoghue, M. J. Phylogenies and community ecology. Annu. Rev. Ecol. Syst. 33, 475–505 (2002).

    Article  Google Scholar 

  32. Cavender-Bares, J., Kozak, K. H., Fine, P. V. A. & Kembel, S. W. The merging of community ecology and phylogenetic biology. Ecol. Lett. 12, 693–715 (2009).

    Article  PubMed  Google Scholar 

  33. Mazutis, L. et al. Single-cell analysis and sorting using droplet-based microfluidics. Nat. Protoc. 8, 870–891 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).

    Article  CAS  PubMed  Google Scholar 

  35. Walters, W. et al. Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1, e00009-15 (2016).

    Article  PubMed  Google Scholar 

  36. Klein, A. M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Bose, S. et al. Scalable microfluidics for single-cell RNA printing and sequencing. Genome Biol. 16, 120 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  38. Zilionis, R. et al. Single-cell barcoding and sequencing using droplet microfluidics. Nat. Protoc. 12, 44–73 (2017).

    Article  CAS  PubMed  Google Scholar 

  39. Johansson, M. E. V. & Hansson, G. C. Preservation of mucus in histological sections, immunostaining of mucins in fixed tissue, and localization of bacteria with FISH. Methods Mol. Biol. 842, 229–235 (2012).

    Article  CAS  PubMed  Google Scholar 

  40. Chung, K. et al. Structural and molecular interrogation of intact biological systems. Nature 497, 332–337 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Chen, F., Tillberg, P. W. & Boyden, E. S. Expansion microscopy. Science 347, 543–548 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Apprill, A., McNally, S., Parsons, R. & Weber, L. Minor revision to V4 region SSU rRNA 806R gene primer greatly increases detection of SAR11 bacterioplankton. Aquat. Microb. Ecol. 75, 129–137 (2015).

    Article  Google Scholar 

  43. Spencer, S. J. et al. Massively parallel sequencing of single cells by epicPCR links functional genes with phylogenetic markers. ISME J. 10, 427–436 (2016).

    Article  CAS  PubMed  Google Scholar 

  44. Abate, A. R., Chen, C.-H., Agresti, J. J. & Weitz, D. A. Beating Poisson encapsulation statistics using close-packed ordering. Lab Chip 9, 2628–2631 (2009).

    Article  CAS  PubMed  Google Scholar 

  45. Edgar, R. C. & Flyvbjerg, H. Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics 31, 3476–3482 (2015).

    Article  CAS  PubMed  Google Scholar 

  46. Edgar, R. C. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 10, 996–998 (2013).

    Article  CAS  PubMed  Google Scholar 

  47. Wang, Q., Garrity, G. M., Tiedje, J. M. & Cole, J. R. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Xiao, L. et al. A catalog of the mouse gut metagenome. Nat. Biotechnol. 33, 1103–1108 (2015).

    Article  CAS  PubMed  Google Scholar 

  49. Maaten, L. V. D. & Hinton, G. Visualizing data using t-SNE. J. Mach. Learn. Res. 9, 2579–2605 (2008).

    Google Scholar 

  50. Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Webb, C. O., Ackerly, D. D. & Kembel, S. W. Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 24, 2098–2100 (2008).

    Article  CAS  PubMed  Google Scholar 

  52. Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K. & Schloss, P. D. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl. Environ. Microbiol. 79, 5112–5120 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Franks, A. H. et al. Variations of bacterial populations in human feces measured by fluorescent in situ hybridization with group-specific 16S rRNA-targeted oligonucleotide probes. Appl. Environ. Microbiol. 64, 3336–3345 (1998).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. Harmsen, H., Elfferich, P. & Schut, F. A 16S rRNA-targeted probe for detection of lactobacilli and enterococci in faecal samples by fluorescent in situ hybridization. Microb. Ecol. Health Dis. 11, 3–12 (1999).

    Article  Google Scholar 

  56. Harmsen, H. et al. Development of 16S rRNA-based probes for the Coriobacterium group and the Atopobium cluster and their application for enumeration of Coriobacteriaceae in human feces from volunteers of different age groups. Appl. Environ. Microbiol. 66, 4523–4527 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Amann, R. I. et al. Combination of 16S rRNA-targeted oligonucleotide probes with flow cytometry for analyzing mixed microbial populations. Appl. Environ. Microbiol. 56, 1919–1925 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Wallner, G., Amann, R. & Beisker, W. Optimizing fluorescent in situ hybridization with rRNA-targeted oligonucleotide probes for flow cytometric identification of microorganisms. Cytometry 14, 136–143 (1993).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank A. Kaufman for technical assistance, R. Rabadan and D. Vitkup for technical advice and discussions, and D. Pe’er and the CUMC Pathology Department for access to sequencing instruments. H.H.W. acknowledges specific funding from the NIH (1R01AI132403, 1R01DK118044), ONR (N00014-15-1-2704) and Burroughs Welcome Fund PATH (1016691) for this work. K.W.L. is partially supported by NIH R01GM110494. P.A.S. acknowledges support from NIH/NIBIB K01EB016071. R.U.S. is supported by a Fannie and John Hertz Foundation Fellowship and an NSF Graduate Research Fellowship (DGE-1644869).

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Authors and Affiliations

  1. Department of Systems Biology, Columbia University Medical Center, New York, NY, USA

    Ravi U. Sheth, Peter A. Sims, Kam W. Leong & Harris H. Wang

  2. Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA

    Ravi U. Sheth

  3. Department of Biomedical Engineering, Columbia University, New York, NY, USA

    Mingqiang Li, Weiqian Jiang & Kam W. Leong

  4. Sulzberger Columbia Genome Center, Columbia University Medical Center, New York, NY, USA

    Peter A. Sims

  5. Department of Biochemistry and Molecular Biophysics, Columbia University Medical Center, New York, NY, USA

    Peter A. Sims

  6. Department of Pathology and Cell Biology, Columbia University Medical Center, New York, NY, USA

    Harris H. Wang

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Contributions

R.U.S. and H.H.W. developed the initial concept; R.U.S. developed the technique, performed experiments and analyzed data with input from P.A.S. and H.H.W.; and M.L., W.J. and K.W.L. assisted with prototypes of the microfluidic device. R.U.S. and H.H.W. wrote the manuscript. All authors discussed results and commented on and approved the manuscript.

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Correspondence to Harris H. Wang.

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H.H.W. and R.U.S. are inventors on a patent application filed by the Trustees of Columbia University in the City of New York regarding this work.

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Sheth, R.U., Li, M., Jiang, W. et al. Spatial metagenomic characterization of microbial biogeography in the gut. Nat Biotechnol 37, 877–883 (2019). https://doi.org/10.1038/s41587-019-0183-2

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