Microbial-enrichment method enables high-throughput metagenomic characterization from host-rich samples

Copyright and License

© The Author(s), under exclusive licence to Springer Nature America, Inc. 2023.

Acknowledgement

We acknowledge assistance with animal experiments from Caltech Office of Laboratory Animal Research. We thank M. Ratanapanichkich (California Institute of Technology) for assistance on manual refinement of metagenomic bins and feedback on figure design. We thank A. Carter (California Institute of Technology) for assistance with Quant-seq library preparation, ddPCR measurements and feedback during manuscript preparation. We thank M. Cooper (California Institute of Technology) for identifying appropriate statistical tests, guidance during Quant-seq analysis and feedback on figure design. We thank S. R. Bogatyrev for preliminary investigations, discussions and advice. We thank O. Pradhan (California Institute of Technology) and R. Akana (California Institute of Technology) for advice and feedback during manuscript preparation. We thank B. McDonald (University of Chicago) for providing his expertise and advice on clinical sample collection and processing. We thank A. Wang (University of Chicago) for her assistance in the processing of the human tissue for Figs. 3–6. We thank N. Shelby (California Institute of Technology) for contributions to writing and editing this manuscript. This work was funded in part by a grant from the Kenneth Rainin Foundation (grant no. 2018-1207 to R.F.I.), the Army Research Office Multidisciplinary University Research Initiative (grant no. W911NF-17-1-0402 to R.F.I.), the Jacobs Institute for Molecular Engineering for Medicine, a NIH NIDDK grant (no. RC2 DK133947 to R.F.I. and B.J.), a National Science Foundation Graduate Research Fellowship (grant no. DGE‐1745301 to N.J.W.-W.), and a National Institutes of Health Biotechnology Leadership Pre-doctoral Training Program fellowship from Caltech's Donna and Benjamin M. Rosen Bioengineering Center (grant no. T32GM112592, to J.T.B.), a Helmsley Foundation grant (to F.T.), a NIH NIDDK grant (no. RC2 DK122394, to F.T.), a F30 (grant no. 5F30DK121470, to D.G.S.), a R01 (grant no. DK067180, to B.J.) and the Digestive Diseases Research Core Center grant no. P30 DK42086 at the University of Chicago (to B.J.). The funders had no role in the design of the study, the collection, analysis and interpretation of data, nor in writing the manuscript.

Contributions

These authors contributed equally: Natalie J. Wu-Woods, Jacob T. Barlow.

N.J.W.-W. and J.T.B. conceived and optimized MEM. J.T.B. designed sample collection and analyzed 16S sequencing. D.G.S. codesigned and performed human biopsy collection. N.J.W.-W. and F.T. analyzed shotgun sequencing. A.E.R. performed library preparation. R.F.I. contributed to the design and implementation of the study and to obtaining funding. A.M.E. oversaw the bioinformatic analysis, contributed to the design and implementation of the study and to obtaining funding. B.J. supervised the clinical work, contributed to the design and implementation of the study and to obtaining funding. All authors edited the manuscript. A detailed author contribution statement is available in the Supplementary Information.

Data Availability

The datasets generated and analyzed during the current study are available at CaltechDATA, https://doi.org/10.22002/gx69z-wec80. Microbial sequencing data are available at NCBI Accession no. PRJNA991155. Sequencing data from human samples have been host scrubbed using STAT78 sra-human-scrubber (https://github.com/ncbi/sra-human-scrubber) followed by alignment to CHM13 (ref. 79). Source data are provided with this paper.

Code Availability

The code used in data processing and analysis is available at CaltechDATA, https://doi.org/10.22002/gx69z-wec80.

Conflict of Interest

The work in this paper is the subject of a patent application filed by Caltech (R.F.I., N.J.W.-W., J.T.B. and A.E.R.). The other authors declare no competing interests.