Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Improved high-molecular-weight DNA extraction, nanopore sequencing and metagenomic assembly from the human gut microbiome

Abstract

Short-read metagenomic sequencing and de novo genome assembly of the human gut microbiome can yield draft bacterial genomes without isolation and culture. However, bacterial genomes assembled from short-read sequencing are often fragmented. Furthermore, these metagenome-assembled genomes often exclude repeated genomic elements, such as mobile genetic elements, compromising our understanding of the contribution of these elements to important bacterial phenotypes. Although long-read sequencing has been applied successfully to the assembly of contiguous bacterial isolate genomes, extraction of DNA of sufficient molecular weight, purity and quantity for metagenomic sequencing from stool samples can be challenging. Here, we present a protocol for the extraction of microgram quantities of high-molecular-weight DNA from human stool samples that are suitable for downstream long-read sequencing applications. We also present Lathe (www.github.com/bhattlab/lathe), a computational workflow for long-read basecalling, assembly, consensus refinement with long reads or Illumina short reads and genome circularization. Altogether, this protocol can yield high-quality contiguous or circular bacterial genomes from a complex human gut sample in approximately 10 d, with 2 d of hands-on bench and computational effort.

This is a preview of subscription content, access via your institution

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.

$32.00

All prices are NET prices.

Fig. 1: High-molecular-weight DNA extraction workflow.
Fig. 2: Post-sequencing bioinformatic workflow.

Data availability

No new data were generated or analyzed for this manuscript.

Code availability

Lathe is available at https://github.com/bhattlab/lathe. Post-assembly binning workflows can be found at https://github.com/bhattlab/metagenomics_workflows.

References

  1. Pasolli, E. et al. Extensive unexplored human microbiome diversity revealed by over 150,000 genomes from metagenomes spanning age, geography, and lifestyle. Cell 176, 649–662.e20 (2019).

    CAS  Article  Google Scholar 

  2. Almeida, A. et al. A new genomic blueprint of the human gut microbiota. Nature 568, 499–504 (2019).

    CAS  Article  Google Scholar 

  3. Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S. & Kyrpides, N. C. New insights from uncultivated genomes of the global human gut microbiome. Nature 568, 505–510 (2019).

    CAS  Article  Google Scholar 

  4. Almeida, A. et al. A unified sequence catalogue of over 280,000 genomes obtained from the human gut microbiome. Nat. Biotechnol. Forthcoming (2020).

  5. Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).

    CAS  Article  Google Scholar 

  6. Bowers, R. M. et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat. Biotechnol. 35, 725–731 (2017).

    CAS  Article  Google Scholar 

  7. Vandecraen, J., Chandler, M., Aertsen, A. & Van Houdt, R. The impact of insertion sequences on bacterial genome plasticity and adaptability. Crit. Rev. Microbiol. 43, 709–730 (2017).

    CAS  Article  Google Scholar 

  8. Darmon, E. & Leach, D. R. F. Bacterial genome instability. Microbiol. Mol. Biol. Rev. 78, 1–39 (2014).

    Article  Google Scholar 

  9. Yuan, S., Cohen, D. B., Ravel, J., Abdo, Z. & Forney, L. J. Evaluation of methods for the extraction and purification of DNA from the human microbiome. PLoS ONE 7, e33865 (2012).

    CAS  Article  Google Scholar 

  10. Moss, E. L., Maghini, D. G. & Bhatt, A. S. Complete, closed bacterial genomes from microbiomes using nanopore sequencing. Nat. Biotechnol. 38, 701–707 (2020).

    CAS  Article  Google Scholar 

  11. Ribado, J. V. The impact of environmental exposures on the human and mouse gut microbiome. Dissertation, Stanford University, 2019).

  12. Rang, F. J., Kloosterman, W. P. & de Ridder, J. From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy. Genome Biol. 19, 90 (2018).

    Article  Google Scholar 

  13. Rhoads, A. & Au, K. F. PacBio sequencing and its applications. Genomics Proteomics Bioinformatics 13, 278–289 (2015).

    Article  Google Scholar 

  14. Tamburini, F. B. et al. Short- and long-read metagenomics of South African gut microbiomes reveal a transitional composition and novel taxa. Preprint at https://www.biorxiv.org/content/10.1101/2020.05.18.099820v2.

  15. Wenger, A. M. et al. Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome. Nat. Biotechnol. 37, 1155–1162 (2019).

    CAS  Article  Google Scholar 

  16. Wick, R. R., Judd, L. M. & Holt, K. E. Performance of neural network basecalling tools for Oxford Nanopore sequencing. Genome Biol. 20, 129 (2019).

    Article  Google Scholar 

  17. Gorzelak, M. A. et al. Methods for improving human gut microbiome data by reducing variability through sample processing and storage of stool. PLoS One 10, e0134802 (2015).

    Article  Google Scholar 

  18. Flores, R. et al. Collection media and delayed freezing effects on microbial composition of human stool. Microbiome 3, 33 (2015).

    Article  Google Scholar 

  19. Koren, S. et al. Canu: scalable and accurate long-read assembly via adaptive k-mer weighting and repeat separation. Genome Res 27, 722–736 (2017).

    CAS  Article  Google Scholar 

  20. Lin, Y. et al. Assembly of long error-prone reads using de Bruijn graphs. Proc. Natl Acad. Sci. USA 113, E8396–E8405 (2016).

    CAS  Article  Google Scholar 

  21. Li, H. Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences. Bioinformatics 32, 2103–2110 (2016).

    CAS  Article  Google Scholar 

  22. Ruan, J. & Li, H. Fast and accurate long-read assembly with wtdbg2. Nat. Methods 17, 155–158 (2019).

    Article  Google Scholar 

  23. Antipov, D., Korobeynikov, A., McLean, J. S. & Pevzner, P. A. hybridSPAdes: an algorithm for hybrid assembly of short and long reads. Bioinformatics 32, 1009–1015 (2016).

    CAS  Article  Google Scholar 

  24. Bertrand, D. et al. Hybrid metagenomic assembly enables high-resolution analysis of resistance determinants and mobile elements in human microbiomes. Nat. Biotechnol. 37, 937–944 (2019).

    CAS  Article  Google Scholar 

  25. Vaser, R., Sović, I., Nagarajan, N. & Šikić, M. Fast and accurate de novo genome assembly from long uncorrected reads. Genome Res. 27, 737–746 (2017).

    CAS  Article  Google Scholar 

  26. Walker, B. J. et al. Pilon: an integrated tool for comprehensive microbial variant detection and genome assembly improvement. PLoS ONE 9, e112963 (2014).

    Article  Google Scholar 

  27. Delcher, A. L., Salzberg, S. L. & Phillippy, A. M. Using MUMmer to identify similar regions in large sequence sets. Curr. Protoc. Bioinformatics Chapter 10, Unit 10.3 (2003).

  28. Köster, J. & Rahmann, S. Snakemake—a scalable bioinformatics workflow engine. Bioinformatics 28, 2520–2522 (2012).

    Article  Google Scholar 

  29. Kurtzer, G. M., Sochat, V. & Bauer, M. W. Singularity: scientific containers for mobility of compute. PLoS ONE 12, e0177459 (2017).

    Article  Google Scholar 

  30. Kang, D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7, e7359 (2019).

    Article  Google Scholar 

  31. Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat. Microbiol. 3, 836–843 (2018).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank all members of the Bhatt laboratory for experimental advice and discussions. We thank Brayon Fremin for making suggestions for the abbreviated DNA extraction protocol, and Matthew Grieshop, Keenan Manpearl, David Sanchez Godinez and Alexandra I. Strom for helpful comments on the manuscript. D.G.M. was supported by the Stanford Graduate Fellowships in Science and Engineering program. E.L.M. was supported by the National Science Foundation Graduate Research Fellowship no. DGE-114747. This work was supported by the Damon Runyon Clinical Investigator Award, grant nos. NIH R01AI148623 and NIH R01AI143757 to the Bhatt laboratory and grant no. NIH P30 AG047366, which supports the Stanford ADRC. Computational work was supported by NIH S10 Shared Instrumentation grant no. 1S10OD02014101 and by NIH grant no. P30 CA124435, which supports the Genetics Bioinformatics Service Center, a Stanford Cancer Institute Shared Resource.

Author information

Authors and Affiliations

Authors

Contributions

E.L.M. and A.S.B. conceived the study. E.L.M., D.G.M., S.E.V. and A.S.B. performed all experiments and data analysis. D.G.M., S.E.V. and A.S.B. wrote the paper with input from all authors. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Ami S. Bhatt.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Nature Protocols thanks Stephen Nayfach and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Related links

Key reference using this protocol

Moss, E. L., Maghini, D. G. & Bhatt, A. S. Nat. Biotechnol. 38, 701–707 (2020): https://doi.org/10.1038/s41587-020-0422-6

Supplementary information

Supplementary Information

Supplementary Fig. 1 and Supplementary Notes 1 and 2.

Reporting Summary

Supplementary Table 1

Summary of HMW DNA extraction methods

Supplementary Table 2

Lytic enzyme activity

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Maghini, D.G., Moss, E.L., Vance, S.E. et al. Improved high-molecular-weight DNA extraction, nanopore sequencing and metagenomic assembly from the human gut microbiome. Nat Protoc 16, 458–471 (2021). https://doi.org/10.1038/s41596-020-00424-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41596-020-00424-x

Further reading

Comments

By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing