1
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Usyk M, Peters BA, Karthikeyan S, McDonald D, Sollecito CC, Vazquez-Baeza Y, Shaffer JP, Gellman MD, Talavera GA, Daviglus ML, Thyagarajan B, Knight R, Qi Q, Kaplan R, Burk RD. Comprehensive evaluation of shotgun metagenomics, amplicon sequencing, and harmonization of these platforms for epidemiological studies. Cell Rep Methods 2023; 3:100391. [PMID: 36814836 PMCID: PMC9939430 DOI: 10.1016/j.crmeth.2022.100391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 11/28/2022] [Accepted: 12/20/2022] [Indexed: 01/24/2023]
Abstract
In a large cohort of 1,772 participants from the Hispanic Community Health Study/Study of Latinos with overlapping 16SV4 rRNA gene (bacterial amplicon), ITS1 (fungal amplicon), and shotgun sequencing data, we demonstrate that 16SV4 amplicon sequencing and shotgun metagenomics offer the same level of taxonomic accuracy for bacteria at the genus level even at shallow sequencing depths. In contrast, for fungal taxa, we did not observe meaningful agreements between shotgun and ITS1 amplicon results. Finally, we show that amplicon and shotgun data can be harmonized and pooled to yield larger microbiome datasets with excellent agreement (<1% effect size variance across three independent outcomes) using pooled amplicon/shotgun data compared to pure shotgun metagenomic analysis. Thus, there are multiple approaches to study the microbiome in epidemiological studies, and we provide a demonstration of a powerful pooling approach that will allow researchers to leverage the massive amount of amplicon sequencing data generated over the last two decades.
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Affiliation(s)
- Mykhaylo Usyk
- Department of Pediatrics (Genetic Medicine), Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
- Department of Epidemiology and Population Health, NYU School of Medicine, New York, NY, USA
| | - Brandilyn A. Peters
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Smruthi Karthikeyan
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Daniel McDonald
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Christopher C. Sollecito
- Department of Pediatrics (Genetic Medicine), Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
| | - Yoshiki Vazquez-Baeza
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
| | - Justin P. Shaffer
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Marc D. Gellman
- Department of Psychology, University of Miami, Miami, FL, USA
| | - Gregory A. Talavera
- Division of Health Promotion and Behavioral Science, San Diego State University, San Diego, CA, USA
| | - Martha L. Daviglus
- Department of Medicine, University of Illinois-Chicago, Chicago, IL, USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical Center, Minneapolis, MN, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California San Diego, La Jolla, CA, USA
- Departments of Computer Science and Engineering, and Bioengineering, University of California San Diego, La Jolla, CA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, NYU School of Medicine, New York, NY, USA
| | - Robert Kaplan
- Department of Epidemiology and Population Health, NYU School of Medicine, New York, NY, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Robert D. Burk
- Department of Pediatrics (Genetic Medicine), Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Departments of Microbiology & Immunology, and Obstetrics, Gynecology & Women’s Health, Albert Einstein College of Medicine, Bronx, NY, USA
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2
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Zhou X, Baumann R, Gao X, Mendoza M, Singh S, Sand IK, Xia Z, Cox LM, Chitnis T, Yoon H, Moles L, Caillier SJ, Santaniello A, Ackermann G, Harroud A, Lincoln R, Gomez R, Peña AG, Digga E, Hakim DJ, Vazquez-Baeza Y, Soman K, Warto S, Humphrey G, Farez M, Gerdes LA, Oksenberg JR, Zamvil SS, Chandran S, Connick P, Otaegui D, Castillo-Triviño T, Hauser SL, Gelfand JM, Weiner HL, Hohlfeld R, Wekerle H, Graves J, Bar-Or A, Cree BA, Correale J, Knight R, Baranzini SE. Gut microbiome of multiple sclerosis patients and paired household healthy controls reveal associations with disease risk and course. Cell 2022; 185:3467-3486.e16. [PMID: 36113426 PMCID: PMC10143502 DOI: 10.1016/j.cell.2022.08.021] [Citation(s) in RCA: 64] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2021] [Revised: 04/21/2022] [Accepted: 08/18/2022] [Indexed: 02/07/2023]
Abstract
Changes in gut microbiota have been associated with several diseases. Here, the International Multiple Sclerosis Microbiome Study (iMSMS) studied the gut microbiome of 576 MS patients (36% untreated) and genetically unrelated household healthy controls (1,152 total subjects). We observed a significantly increased proportion of Akkermansia muciniphila, Ruthenibacterium lactatiformans, Hungatella hathewayi, and Eisenbergiella tayi and decreased Faecalibacterium prausnitzii and Blautia species. The phytate degradation pathway was over-represented in untreated MS, while pyruvate-producing carbohydrate metabolism pathways were significantly reduced. Microbiome composition, function, and derived metabolites also differed in response to disease-modifying treatments. The therapeutic activity of interferon-β may in part be associated with upregulation of short-chain fatty acid transporters. Distinct microbial networks were observed in untreated MS and healthy controls. These results strongly support specific gut microbiome associations with MS risk, course and progression, and functional changes in response to treatment.
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Affiliation(s)
- Xiaoyuan Zhou
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Ryan Baumann
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Xiaohui Gao
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Myra Mendoza
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Sneha Singh
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Ilana Katz Sand
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zongqi Xia
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Lau M. Cox
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Tanuja Chitnis
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Hongsup Yoon
- Institute of Clinical Neuroimmunology, Biomedical Center and University Hospitals, Ludwig-Maximilians-Universität München, and Munich Cluster of Systems Neurology (SyNergy), München, Germany
- Department Neuroimmunology, Max Planck Institute (MPI) of Neurobiology, Munich, Germany
| | - Laura Moles
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Stacy J. Caillier
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Adam Santaniello
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Gail Ackermann
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Adil Harroud
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Robin Lincoln
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | | | | | - Elise Digga
- Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Daniel Joseph Hakim
- Department of Bioinformatics and Systems Biology, University of California, San Diego, La Jolla, CA, USA
| | - Yoshiki Vazquez-Baeza
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Karthik Soman
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Shannon Warto
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Greg Humphrey
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Mauricio Farez
- Department of Neurology, Institute for Neurological Research Dr. Raul Carrea (FLENI), Buenos Aires, Argentina
| | - Lisa Ann Gerdes
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Jorge R. Oksenberg
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Scott S. Zamvil
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | | | - Peter Connick
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - David Otaegui
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Tamara Castillo-Triviño
- Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
- Department of Neurology, Hospital Universitario Donostia and Neurosciences Area, Biodonostia Health Research Institute, San Sebastián, Spain
| | - Stephen L. Hauser
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Jeffrey M. Gelfand
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Howard L. Weiner
- Department of Neurology, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Reinhard Hohlfeld
- Institute of Clinical Neuroimmunology, Biomedical Center and University Hospitals, Ludwig-Maximilians-Universität München, and Munich Cluster of Systems Neurology (SyNergy), München, Germany
| | - Hartmut Wekerle
- Department Neuroimmunology, Max Planck Institute (MPI) of Neurobiology, Munich, Germany
| | - Jennifer Graves
- Department of Neurosciences, University of California, San Diego, CA, USA
| | - Amit Bar-Or
- Department of Neurology, University of Pennsylvania, Pennsylvania, PA, USA
| | - Bruce A.C. Cree
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
| | - Jorge Correale
- Department of Neurology, Institute for Neurological Research Dr. Raul Carrea (FLENI), Buenos Aires, Argentina
| | - Rob Knight
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Sergio E. Baranzini
- Weill Institute for Neurosciences. Department of Neurology, University of California, San Francisco, CA, USA
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3
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Morton JT, Aksenov AA, Nothias LF, Foulds JR, Quinn RA, Badri MH, Swenson TL, Van Goethem MW, Northen TR, Vazquez-Baeza Y, Wang M, Bokulich NA, Watters A, Song SJ, Bonneau R, Dorrestein PC, Knight R. Learning representations of microbe-metabolite interactions. Nat Methods 2019; 16:1306-1314. [PMID: 31686038 PMCID: PMC6884698 DOI: 10.1038/s41592-019-0616-3] [Citation(s) in RCA: 124] [Impact Index Per Article: 24.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Accepted: 09/19/2019] [Indexed: 12/26/2022]
Abstract
Integrating multiomics datasets is critical for microbiome research; however, inferring interactions across omics datasets has multiple statistical challenges. We solve this problem by using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism. We show with known environmental (desert soil biocrust wetting) and clinical (cystic fibrosis lung) examples, our ability to recover microbe-metabolite relationships, and demonstrate how the method can discover relationships between microbially produced metabolites and inflammatory bowel disease.
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Affiliation(s)
- James T Morton
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Alexander A Aksenov
- Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Louis Felix Nothias
- Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - James R Foulds
- Department of Information Systems, University of Maryland Baltimore County, Baltimore, MD, USA
| | - Robert A Quinn
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI, USA
| | | | - Tami L Swenson
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Marc W Van Goethem
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Trent R Northen
- Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- DOE Joint Genome Institute, Walnut Creek, CA, USA
| | - Yoshiki Vazquez-Baeza
- Jacobs School of Engineering, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Mingxun Wang
- Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Nicholas A Bokulich
- The Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ, USA
- Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
| | - Aaron Watters
- Flatiron Institute, Simons Foundation, New York, NY, USA
| | - Se Jin Song
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA
| | - Richard Bonneau
- Department of Biology, New York University, New York, NY, USA
- Flatiron Institute, Simons Foundation, New York, NY, USA
- Computer Science Department, Courant Institute, New York, NY, USA
- Center For Data Science, New York University, New York, NY, USA
| | - Pieter C Dorrestein
- Collaborative Mass Spectrometry Innovaftion Center, University of California, San Diego, La Jolla, CA, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA.
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA.
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, USA.
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA.
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4
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Khanna S, Vazquez-Baeza Y, González A, Weiss S, Schmidt B, Muñiz-Pedrogo DA, Rainey JF, Kammer P, Nelson H, Sadowsky M, Khoruts A, Farrugia SL, Knight R, Pardi DS, Kashyap PC. Changes in microbial ecology after fecal microbiota transplantation for recurrent C. difficile infection affected by underlying inflammatory bowel disease. Microbiome 2017; 5:55. [PMID: 28506317 PMCID: PMC5433077 DOI: 10.1186/s40168-017-0269-3] [Citation(s) in RCA: 96] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2016] [Accepted: 04/23/2017] [Indexed: 05/05/2023]
Abstract
BACKGROUND Gut microbiota play a key role in maintaining homeostasis in the human gut. Alterations in the gut microbial ecosystem predispose to Clostridium difficile infection (CDI) and gut inflammatory disorders such as inflammatory bowel disease (IBD). Fecal microbiota transplantation (FMT) from a healthy donor can restore gut microbial diversity and pathogen colonization resistance; consequently, it is now being investigated for its ability to improve inflammatory gut conditions such as IBD. In this study, we investigated changes in gut microbiota following FMT in 38 patients with CDI with or without underlying IBD. RESULTS There was a significant change in gut microbial composition towards the donor microbiota and an overall increase in microbial diversity consistent with previous studies after FMT. FMT was successful in treating CDI using a diverse set of donors, and varying degrees of donor stool engraftment suggesting that donor type and degree of engraftment are not drivers of a successful FMT treatment of CDI. However, patients with underlying IBD experienced an increased number of CDI relapses (during a 24-month follow-up) and a decreased growth of new taxa, as compared to the subjects without IBD. Moreover, the need for IBD therapy did not change following FMT. These results underscore the importance of the existing gut microbial landscape as a decisive factor to successfully treat CDI and potentially for improvement of the underlying pathophysiology in IBD. CONCLUSIONS FMT leads to a significant change in microbial diversity in patients with recurrent CDI and complete resolution of symptoms. Stool donor type (related or unrelated) and degree of engraftment are not the key for successful treatment of CDI by FMT. However, CDI patients with IBD have higher proportion of the original community after FMT and lack of improvement of their IBD symptoms and increased episodes of CDI on long-term follow-up.
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Affiliation(s)
- Sahil Khanna
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Yoshiki Vazquez-Baeza
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
| | - Antonio González
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Sophie Weiss
- Department of Chemical and Biological Engineering, University of Colorado, Boulder, CO, USA
| | - Bradley Schmidt
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | | | - John F Rainey
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Patricia Kammer
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Heidi Nelson
- Division of Colorectal Surgery, Mayo Clinic, Rochester, MN, USA
| | - Michael Sadowsky
- BioTechnology Institute, University of Minnesota, Minneapolis, MN, USA
| | - Alexander Khoruts
- Division of Gastroenterology, University of Minnesota, Minneapolis, MN, USA
| | - Stefan L Farrugia
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA
| | - Rob Knight
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
- Department of Pediatrics, University of California, San Diego, La Jolla, CA, USA
| | - Darrell S Pardi
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA.
| | - Purna C Kashyap
- Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, MN, 55905, USA.
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5
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Abstract
Many factors affect the microbiomes of humans, mice, and other mammals, but substantial challenges remain in determining which of these factors are of practical importance. Considering the relative effect sizes of both biological and technical covariates can help improve study design and the quality of biological conclusions. Care must be taken to avoid technical bias that can lead to incorrect biological conclusions. The presentation of quantitative effect sizes in addition to P values will improve our ability to perform meta-analysis and to evaluate potentially relevant biological effects. A better consideration of effect size and statistical power will lead to more robust biological conclusions in microbiome studies.
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Affiliation(s)
- Justine Debelius
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Se Jin Song
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
- Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO, USA
| | - Yoshiki Vazquez-Baeza
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
| | - Zhenjiang Zech Xu
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Antonio Gonzalez
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, CA, USA.
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA.
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