DOCSLIB.ORG

Quantitative Inferences from the Lung Microbiome by Laura Tipton BA, University of Virginia, 2007 MS, George Washington Universi

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Quantitative Inferences from the Lung Microbiome by Laura Tipton BA, University of Virginia, 2007 MS, George Washington Universi Quantitative Inferences from the Lung Microbiome by Laura Tipton BA, University of Virginia, 2007 MS, George Washington University, 2011 Submitted to the Graduate Faculty of School of Medicine in partial fulfillment of the requirements for the degree of Doctor of Philosophy University of Pittsburgh 2016 UNIVERSITY OF PITTSBURGH SCHOOL OF MEDICINE This dissertation was presented by Laura Tipton It was defended on December 14, 2016 and approved by Penayiotis Benos, PhD, Department of Computational & Systems Biology Alison Morris, MD, MS, Department of Immunology Kyle Bibby, PhD, PE, Swanson School of Engineering, Civil and Environmental Engineering Kathryn Roeder, PhD, CMU Department of Statistics Dissertation Advisor: Elodie Ghedin, PhD, NYU Department of Biology ii Copyright © by Laura Tipton 2016 iii QUANTITATIVE INFERENCE FROM THE LUNG MICROBIOME Laura Tipton, PhD University of Pittsburgh, 2016 Within the last decade, we have progressed from the belief that the healthy human lung is a sterile environment to attempts to study inter-kingdom interactions between microbial residents of the lungs. It has been repeatedly confirmed that the lungs contain both bacteria, predominantly from the Streptococcus, Veillonella, and Prevotella genera, and fungi, predominantly from the Cladosporium, Eurotium, Penicillium, and Aspergillus genera. The community composition as a whole undergoes shifts in every lung disease and condition that has been studied, including asthma, chronic obstructive pulmonary disorder, and cystic fibrosis. The studies that have observed these shifts have largely been descriptive, comparing the taxonomies present in healthy lungs to taxonomies in diseased lungs. Here we investigated the lung microbiome and relationships within the microbial community and between microbes and the host in a more quantitative and inferential manner. First, we introduced the lasso-penalized generalized linear mixed model (LassoGLMM) for microbiomes. LassoGLMM was applied to a short time-course study of the human oral bacterial microbiome with standard blood chemical measurements and to repeated measurements of the human lung bacterial microbiome and fungal mycobiome with local and systemic markers of inflammation. We sought to show that increased inflammation and other continuous clinical variables in human hosts are associated with distinct microbes present in the lung or oral microbiomes. Then, we examined cross-domain interactions between bacteria and fungi. Ecological interaction networks were inferred for the human lung and skin micro- and myco-biomes. Networks limited to a single domain of life were compared with those that iv include both bacteria and fungi to identify important components of the microbial community that would be overlooked in a single domain study. Finally, we explored the metabolism of the bacteria within the human lung using three different “-omics” datasets: taxonomic assignments from 16S rRNA gene sequences, gene families from metatranscriptomic sequences, and mass-to- charge ratio (m/z) features from metabolomics. Correlations were examined between pairs of datasets and all three datasets were integrated to identify bacteria contributing metabolic processes that may have otherwise gone unnoticed, resulting in the first complete characterization of the metabolism of the human lung bacterial microbiome. v TABLE OF CONTENTS preface ......................................................................................................................................... xiii 1.0 Introduction .................................................................................................................. 1 1.1 Bacteria in the Lungs........................................................................................... 2 1.1.1 Bacteria During Disease .................................................................................. 5 1.2 Fungi in the Lungs ............................................................................................... 8 1.2.1 Why is the lung mycobiome important?........................................................ 8 1.2.2 What do we know about the lung mycobiome? .......................................... 10 1.3 Other Microbes in the Lungs ............................................................................ 15 1.4 Challenges to Studying the Lung Microbiome ................................................ 16 1.5 Future of Lung Microbiome Research ............................................................ 21 1.6 Overview ............................................................................................................. 23 2.0 Measuring associations between the microbiota and repeated measures of continuous clinical variables using a lasso-penalized generalized linear mixed model ........ 25 2.1 Background ........................................................................................................ 25 2.2 Methods .............................................................................................................. 29 2.2.1 Sequence Data Processing ............................................................................. 30 2.2.2 Variable Screening Step ................................................................................ 31 2.2.3 Lasso-Penalized Generalized Linear Mixed Model .................................... 33 vi 2.2.4 Evaluating Models ......................................................................................... 35 2.2.5 Dichotomous Methods ................................................................................... 36 2.2.6 Ethics approval and consent to participate ................................................. 36 2.2.7 Availability of data ........................................................................................ 37 2.3 Results ................................................................................................................. 37 2.3.1 Associations between Oral Bacteria and Laboratory Measurements ...... 37 2.3.2 Associations of Lung Bacteria and Fungi with Cytokines ......................... 43 2.3.3 Model Evaluation ........................................................................................... 47 2.3.4 Comparison to Categorical Methods ........................................................... 50 2.4 Discussion ........................................................................................................... 54 2.5 Conclusions ......................................................................................................... 56 3.0 Inferred Cross-Domain Interactions in the Lung and Skin Microbiomes ........... 58 3.1 Introduction........................................................................................................ 58 3.2 Results ................................................................................................................. 63 3.2.1 Lung Microbiome .......................................................................................... 64 3.2.2 Skin Microbiome............................................................................................ 71 3.2.3 Co-culture Validation .................................................................................... 74 3.3 Discussion ........................................................................................................... 77 3.4 Methods .............................................................................................................. 81 3.4.1 Adapting SPIEC-EASI for Two Domains ................................................... 81 3.4.2 Datasets ........................................................................................................... 84 3.4.3 Sample and sequence processing .................................................................. 87 3.4.4 Constructing Networks ................................................................................. 89 vii 3.4.5 Evaluating and Comparing Networks ......................................................... 90 3.4.6 Microbial Co-cultures ................................................................................... 90 3.4.7 Accession Numbers ........................................................................................ 92 4.0 Multi-omics Investigation of the Lung Microbiome ............................................... 93 4.1 Background ........................................................................................................ 93 4.2 Results ................................................................................................................. 95 4.2.1 Single datasets ................................................................................................ 95 4.2.2 Two datasets ................................................................................................. 103 4.2.2.1 Correlations ....................................................................................... 103 4.2.2.2 Taxonomic Composition Comparison ............................................. 105 4.2.2.3 KEGG Ontology Comparison .......................................................... 109 4.2.3 Three Datasets.............................................................................................. 117 4.2.3.1 Block Identification ........................................................................... 117 4.3 Discussion ........................................................................................................
Load more

Recommended publications
  • Ecology and Evolution of Metabolic Cross-Feeding Interactions in Bacteria† Cite This: Nat
    Natural Product Reports View Article Online REVIEW View Journal | View Issue Ecology and evolution of metabolic cross-feeding interactions in bacteria† Cite this: Nat. Prod. Rep.,2018,35,455 Glen D'Souza, ab Shraddha Shitut, ce Daniel Preussger,c Ghada Yousif,cde Silvio Waschina f and Christian Kost *ce Literature covered: early 2000s to late 2017 Bacteria frequently exchange metabolites with other micro- and macro-organisms. In these often obligate cross-feeding interactions, primary metabolites such as vitamins, amino acids, nucleotides, or growth factors are exchanged. The widespread distribution of this type of metabolic interactions, however, is at odds with evolutionary theory: why should an organism invest costly resources to benefit other individuals rather than using these metabolites to maximize its own fitness? Recent empirical work has fi fi Creative Commons Attribution 3.0 Unported Licence. shown that bacterial genotypes can signi cantly bene t from trading metabolites with other bacteria relative to cells not engaging in such interactions. Here, we will provide a comprehensive overview over the ecological factors and evolutionary mechanisms that have been identified to explain the evolution Received 25th January 2018 and maintenance of metabolic mutualisms among microorganisms. Furthermore, we will highlight DOI: 10.1039/c8np00009c general principles that underlie the adaptive evolution of interconnected microbial metabolic networks rsc.li/npr as well as the evolutionary consequences that result for cells living in such communities. 1 Introduction 2.5 Mechanisms of metabolite transfer This article is licensed under a 2 Metabolic cross-feeding interactions 2.5.1 Contact-independent mechanisms 2.1 Historical account 2.5.1.1 Passive diffusion 2.2 Classication of cross-feeding interactions 2.5.1.2 Active transport 2.2.1 Unidirectional by-product cross-feeding 2.5.1.3 Vesicle-mediated transport Open Access Article.
    [Show full text]
  • Quorum Sensing Modulates the Epibiotic-Parasitic Relationship
    fmicb-09-02049 September 24, 2018 Time: 16:12 # 1 ORIGINAL RESEARCH published: 24 September 2018 doi: 10.3389/fmicb.2018.02049 Quorum Sensing Modulates the Epibiotic-Parasitic Relationship Between Actinomyces odontolyticus and Its Saccharibacteria epibiont, a Nanosynbacter lyticus Strain, TM7x Joseph K. Bedree1,2, Batbileg Bor2, Lujia Cen2, Anna Edlund3, Renate Lux4, Jeffrey S. McLean5, Wenyuan Shi2* and Xuesong He2* 1 Section of Oral Biology, Division of Oral Biology and Medicine, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States, 2 Department of Microbiology, The Forsyth Institute, Cambridge, MA, United States, 3 Department of Genomic Medicine, J. Craig Venter Institute, La Jolla, CA, United States, 4 Section of Periodontics, Division of Constitutive and Regenerative Sciences, School of Dentistry, University of California, Los Angeles, Los Angeles, CA, United States, 5 Department of Periodontics, School of Dentistry, University of Washington, Seattle, WA, United States Edited by: The ultra-small, obligate parasitic epibiont, TM7x, the first and only current member of Sebastian Fraune, Christian-Albrechts-Universität zu Kiel, the long-elusive Saccharibacteria (formerly the TM7 phylum) phylum to be cultivated, Germany was isolated in co-culture with its bacterial host, Actinomyces odontolyticus subspecies Reviewed by: actinosynbacter, XH001. Initial phenotypic characterization of the TM7x-associated Jürgen Tomasch, XH001 co-culture revealed enhanced biofilm formation in the presence of TM7x Helmholtz-Gemeinschaft Deutscher Forschungszentren (HZ), Germany compared to XH001 as monoculture. Genomic analysis and previously published Tim Miyashiro, transcriptomic profiling of XH001 also revealed the presence of a putative AI-2 quorum Pennsylvania State University, United States sensing (QS) operon, which was highly upregulated upon association of TM7x with *Correspondence: XH001.
    [Show full text]
  • Phenotypic and Physiological Characterization of the Epibiotic Interaction Between Tm7x and Its Basibiont Actinomyces
    HHS Public Access Author manuscript Author Manuscript Author ManuscriptMicrob Author ManuscriptEcol. Author manuscript; Author Manuscript available in PMC 2017 January 01. Published in final edited form as: Microb Ecol. 2016 January ; 71(1): 243–255. doi:10.1007/s00248-015-0711-7. Phenotypic and physiological characterization of the epibiotic interaction between TM7x and its basibiont Actinomyces Batbileg Bor1, Nicole Poweleit2, Justin S. Bois3, Lujia Cen1, Joseph K. Bedree1, Z. Hong Zhou2,4, Robert P. Gunsalus2, Renate Lux1, Jeffrey S. McLean5, Xuesong He1,*, and Wenyuan Shi1,* 1Section of Oral Biology, School of Dentistry, University of California, Los Angeles, CA 90095 2Department of Microbiology, Immunology, and Molecular Genetics, University of California, Los Angeles, CA 90095 3Division of Biology and Biological Engineering, California Institute of Technology, MC 114-96, Pasadena, CA 91125 4California Nanosystems Institute, University of California, Los Angeles, California 90095 5Department of Periodontics, University of Washington, Seattle, WA 98195 Abstract Despite many examples of obligate epibiotic symbiosis (one organism living on the surface of another) in nature, such an interaction has rarely been observed between two bacteria. Here, we further characterize a newly reported interaction between a human oral obligate parasitic bacterium TM7x (cultivated member of Candidatus Saccharimonas formerly Candidate Phylum TM7), and its basibiont Actinomyces odontolyticus species (XH001), providing a model system to study epiparasitic symbiosis in the domain Bacteria. Detailed microscopic studies indicate that both partners display extensive morphological changes during symbiotic growth. XH001 cells manifested as short rods in monoculture, but displayed elongated and hyphal morphology when physically associated with TM7x. Interestingly, these dramatic morphological changes in XH001 were also induced in oxygen-depleted conditions, even in the absence of TM7x.
    [Show full text]
  • Metabolic Network Percolation Quantifies Biosynthetic Capabilities
    RESEARCH ARTICLE Metabolic network percolation quantifies biosynthetic capabilities across the human oral microbiome David B Bernstein1,2, Floyd E Dewhirst3,4, Daniel Segre` 1,2,5,6,7* 1Department of Biomedical Engineering, Boston University, Boston, United States; 2Biological Design Center, Boston University, Boston, United States; 3The Forsyth Institute, Cambridge, United States; 4Harvard School of Dental Medicine, Boston, United States; 5Bioinformatics Program, Boston University, Boston, United States; 6Department of Biology, Boston University, Boston, United States; 7Department of Physics, Boston University, Boston, United States Abstract The biosynthetic capabilities of microbes underlie their growth and interactions, playing a prominent role in microbial community structure. For large, diverse microbial communities, prediction of these capabilities is limited by uncertainty about metabolic functions and environmental conditions. To address this challenge, we propose a probabilistic method, inspired by percolation theory, to computationally quantify how robustly a genome-derived metabolic network produces a given set of metabolites under an ensemble of variable environments. We used this method to compile an atlas of predicted biosynthetic capabilities for 97 metabolites across 456 human oral microbes. This atlas captures taxonomically-related trends in biomass composition, and makes it possible to estimate inter-microbial metabolic distances that correlate with microbial co-occurrences. We also found a distinct cluster of fastidious/uncultivated taxa, including several Saccharibacteria (TM7) species, characterized by their abundant metabolic deficiencies. By embracing uncertainty, our approach can be broadly applied to understanding metabolic interactions in complex microbial ecosystems. *For correspondence: DOI: https://doi.org/10.7554/eLife.39733.001 [email protected] Competing interests: The authors declare that no Introduction competing interests exist.
    [Show full text]
  • Deep Metagenomics Examines the Oral Microbiome During Dental Caries, Revealing Novel Taxa and Co-Occurrences with Host Molecules
    Downloaded from genome.cshlp.org on October 1, 2021 - Published by Cold Spring Harbor Laboratory Press Research Deep metagenomics examines the oral microbiome during dental caries, revealing novel taxa and co-occurrences with host molecules Jonathon L. Baker,1 James T. Morton,2 Márcia Dinis,3 Ruth Alvarez,3 Nini C. Tran,3 Rob Knight,4,5,6,7 and Anna Edlund1,5 1Genomic Medicine Group, J. Craig Venter Institute, La Jolla, California 92037, USA; 2Systems Biology Group, Flatiron Institute, New York, New York 10010, USA; 3Section of Pediatric Dentistry, UCLA School of Dentistry, Los Angeles, California 90095-1668, USA; 4Center for Microbiome Innovation, University of California at San Diego, La Jolla, California 92161, USA; 5Department of Pediatrics, University of California at San Diego, La Jolla, California 92161, USA; 6Department of Computer Science and Engineering, University of California at San Diego, La Jolla, California 92093, USA; 7Department of Bioengineering, University of California at San Diego, La Jolla, California 92093, USA Dental caries, the most common chronic infectious disease worldwide, has a complex etiology involving the interplay of microbial and host factors that are not completely understood. In this study, the oral microbiome and 38 host cytokines and chemokines were analyzed across 23 children with caries and 24 children with healthy dentition. De novo assembly of metagenomic sequencing obtained 527 metagenome-assembled genomes (MAGs), representing 150 bacterial species. Forty-two of these species had no genomes in public repositories, thereby representing novel taxa. These new genomes greatly expanded the known pangenomes of many oral clades, including the enigmatic Saccharibacteria clades G3 and G6, which had distinct functional repertoires compared to other oral Saccharibacteria.
    [Show full text]
  • Evidence of Independent Acquisition and Adaption of Ultra-Small Bacteria to Human Hosts Across the Highly Diverse Yet Reduced Genomes of the Phylum Saccharibacteria
    bioRxiv preprint doi: https://doi.org/10.1101/258137; this version posted February 2, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Evidence of independent acquisition and adaption of ultra-small bacteria to human hosts across the highly diverse yet reduced genomes of the phylum Saccharibacteria Jeffrey S. McLeana,b,1 , Batbileg Borc#, Thao T. Toa#, Quanhui Liua, Kristopher A. Kernsa, Lindsey Soldend, Kelly Wrightond, Xuesong Hec, Wenyuan Shic a Department of Periodontics, University of Washington, Seattle, WA, 98195, USA b Department of Microbiology, University of Washington, Seattle, WA, 98195, USA c Department of Microbiology, The Forsyth Institute, Cambridge, Massachusetts 02142 dDepartment of Microbiology, The Ohio State University, Columbus, OH, USA Short title: Host Adaptation of the Saccharibacteria Phylum Keywords: TM7, Saccharibacteria, Candidate Phyla Radiation, epibiont, oral microbiome, # These authors contributed equally to this work. 1To whom correspondence should be addressed. Email: [email protected] Author contribution: JSM, XH, BB and WS conceived the study and designed experiments. XH, JSM, BB, TT, KK, LS, KW, QL conducted experiments. All authors listed analyzed the data. JSM, XH, BB wrote the paper with input from all other authors. All authors have read and approved the manuscript. This research was funded by NIH NIGMS R01GM095373 (J.S.M.), NIH NIDCR Awards 1R01DE023810 (W.S., X.H., and J.M.), 1R01DE020102 (W.S., X.H., and J.S.M.), F32DE025548-01 (B.B.), T90DE021984 (T.T.) 1R01DE026186 (W.S., X.H., and J.S.M.).
    [Show full text]
  • Downloaded from the Integrated Microbial Genomes and Microbiomes Database (IMG/M) (Chen Et Al., 2019C) and Refined (See Methods) and a MAG from Marcy Et Al
    bioRxiv preprint doi: https://doi.org/10.1101/2020.04.29.069278; this version posted April 30, 2020. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY 4.0 International license. Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome Alon Shaiber1,2, Amy D. Willis3, Tom O. Delmont4, Simon Roux5, Lin-Xing Chen6, Abigail 5 C. Schmid7, Mahmoud Yousef8, Andrea R. Watson1,9, Karen Lolans1, Özcan C. Esen1, Sonny T. M. Lee10, Nora Downey11, Hilary G. Morrison11, Floyd E. Dewhirst12,13, Jessica L. Mark Welch11,*, A. Murat Eren1,2,9,11,* 1Department of Medicine, University of Chicago, Chicago, IL 60637, USA; 2Graduate Program in Biophysical Sciences, University of Chicago, Chicago, IL 60637, USA; 3Department of Biostatistics, 10 University of Washington, Seattle WA 98195, USA; 4Génomique Métabolique, Genoscope, Institut François Jacob, CEA, CNRS, Univ Evry, Université Paris-Saclay, 91057 Evry, France; 5Department of Energy Joint Genome Institute, Berkeley CA 94720, USA; 6Department of Earth and Planetary Sciences, University of California, Berkeley, CA 94720, USA; 7Undergraduate Student, Computational and Applied Mathematics, University of Chicago, Chicago, IL 60637, USA; 15 8Undergraduate Student, Computer Science, University of Chicago, Chicago, IL 60637, USA; 9Committee on Microbiology, University of Chicago, Chicago, IL 60637, USA; 10
    [Show full text]
  • Of the Human Oral Microbiome Using Cultivation-Dependent and –Independent Approaches
    University of Tennessee, Knoxville TRACE: Tennessee Research and Creative Exchange Doctoral Dissertations Graduate School 8-2019 Investigating the microbial “dark matter” of the human oral microbiome using cultivation-dependent and –independent approaches Karissa Cross University of Tennessee, [email protected] Follow this and additional works at: https://trace.tennessee.edu/utk_graddiss Recommended Citation Cross, Karissa, "Investigating the microbial “dark matter” of the human oral microbiome using cultivation- dependent and –independent approaches. " PhD diss., University of Tennessee, 2019. https://trace.tennessee.edu/utk_graddiss/5637 This Dissertation is brought to you for free and open access by the Graduate School at TRACE: Tennessee Research and Creative Exchange. It has been accepted for inclusion in Doctoral Dissertations by an authorized administrator of TRACE: Tennessee Research and Creative Exchange. For more information, please contact [email protected]. To the Graduate Council: I am submitting herewith a dissertation written by Karissa Cross entitled "Investigating the microbial “dark matter” of the human oral microbiome using cultivation-dependent and –independent approaches." I have examined the final electronic copy of this dissertation for form and content and recommend that it be accepted in partial fulfillment of the equirr ements for the degree of Doctor of Philosophy, with a major in Microbiology. Mircea Podar, Major Professor We have read this dissertation and recommend its acceptance: Heidi Goodrich-Blair, Erik Zinser, Frank Loeffler, Stephen Kania Accepted for the Council: Dixie L. Thompson Vice Provost and Dean of the Graduate School (Original signatures are on file with official studentecor r ds.) Investigating the microbial “dark matter” of the human oral microbiome using cultivation-dependent and –independent approaches A Dissertation Presented for the Doctor of Philosophy Degree The University of Tennessee, Knoxville Karissa Lynn Cross August 2019 Copyright © 2019 by Karissa Lynn Cross All rights reserved.
    [Show full text]
  • Deep Metagenomics Examines the Oral Microbiome During Dental Caries, Revealing Novel Taxa and Co-Occurrences with Host Molecules
    Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Deep metagenomics examines the oral microbiome during dental caries, revealing novel taxa and co-occurrences with host molecules Authors: Baker, J.L.1,*, Morton, J.T.2., Dinis, M.3, Alverez, R.3, Tran, N.C.3, Knight, R.4,5,6,7, Edlund, A.1,5,* 1 Genomic Medicine Group J. Craig Venter Institute 4120 Capricorn Lane La Jolla, CA 92037 2Systems Biology Group Flatiron Institute 162 5th Avenue New York, NY 10010 3Section of Pediatric Dentistry UCLA School of Dentistry 10833 Le Conte Ave. Los Angeles, CA 90095-1668 4Center for Microbiome Innovation University of California at San Diego La Jolla, CA 92023 5Department of Pediatrics University of California at San Diego La Jolla, CA 92023 6Department of Computer Science and Engineering University of California at San Diego 9500 Gilman Drive La Jolla, CA 92093 7Department of Bioengineering University of California at San Diego 9500 Gilman Drive La Jolla, CA 92093 *Corresponding Authors: JLB: [email protected], AE: [email protected] ORCIDs: JLB: 0000-0001-5378-322X, AE: 0000-0002-3394-4804 Downloaded from genome.cshlp.org on September 25, 2021 - Published by Cold Spring Harbor Laboratory Press Abstract Dental caries, the most common chronic infectious disease worldwide, has a complex etiology involving the interplay of microbial and host factors that are not completely understood. In this study, the oral microbiome, and 38 host cytokines and chemokines, were analyzed across 23 children with caries and 24 children with healthy dentition. De novo assembly of metagenomic sequencing obtained 527 metagenome-assembled genomes (MAGs), representing 150 bacterial species.
    [Show full text]
  • The Vaginal Microbiome and Preterm Birth Jennifer M
    The vaginal microbiome and preterm birth Jennifer M. Fettweis, Virginia Commonwealth University Myrna G. Serrano, Virginia Commonwealth University J. Paul Brooks, Virginia Commonwealth University David J. Edwards, Virginia Commonwealth University Philippe H. Girerd, Virginia Commonwealth University Hardik I. Parikh, Virginia Commonwealth University Bernice Huang, Virginia Commonwealth University Tom J. Arodz, Virginia Commonwealth University Laahirie Edupuganti, Virginia Commonwealth University Abigail L. Glascock, Virginia Commonwealth University Only first 10 authors above; see publication for full author list. Journal Title: Nature Medicine Volume: Volume 25, Number 6 Publisher: Nature Research (part of Springer Nature) | 2019-06-01, Pages 1012-+ Type of Work: Article | Final Publisher PDF Publisher DOI: 10.1038/s41591-019-0450-2 Permanent URL: https://pid.emory.edu/ark:/25593/v30zx Final published version: http://dx.doi.org/10.1038/s41591-019-0450-2 Copyright information: © 2019, The Author(s), under exclusive licence to Springer Nature America, Inc. This is an Open Access work distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Accessed October 5, 2021 11:23 AM EDT ARTICLES https://doi.org/10.1038/s41591-019-0450-2 The vaginal microbiome and preterm birth Jennifer M. Fettweis 1,2,3, Myrna G. Serrano1,3, J. Paul Brooks3,4, David J. Edwards3,5, Philippe H. Girerd2,3, Hardik I. Parikh1, Bernice Huang1, Tom J. Arodz3,6, Laahirie Edupuganti1,3, Abigail L. Glascock7, Jie Xu3,8,9, Nicole R. Jimenez1,3, Stephany C. Vivadelli1,3, Stephen S. Fong3,10, Nihar U. Sheth11, Sophonie Jean1, Vladimir Lee1,3, Yahya A.
    [Show full text]
  • Evidence of Independent Acquisition and Adaption of Ultra-Small Bacteria to Human Hosts Across the Highly Diverse Yet Reduced Genomes of the Phylum Saccharibacteria
    bioRxiv preprint doi: https://doi.org/10.1101/258137; this version posted February 2, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license. Evidence of independent acquisition and adaption of ultra-small bacteria to human hosts across the highly diverse yet reduced genomes of the phylum Saccharibacteria Jeffrey S. McLeana,b,1 , Batbileg Borc#, Thao T. Toa#, Quanhui Liua, Kristopher A. Kernsa, Lindsey Soldend, Kelly Wrightond, Xuesong Hec, Wenyuan Shic a Department of Periodontics, University of Washington, Seattle, WA, 98195, USA b Department of Microbiology, University of Washington, Seattle, WA, 98195, USA c Department of Microbiology, The Forsyth Institute, Cambridge, Massachusetts 02142 dDepartment of Microbiology, The Ohio State University, Columbus, OH, USA Short title: Host Adaptation of the Saccharibacteria Phylum Keywords: TM7, Saccharibacteria, Candidate Phyla Radiation, epibiont, oral microbiome, # These authors contributed equally to this work. 1To whom correspondence should be addressed. Email: [email protected] Author contribution: JSM, XH, BB and WS conceived the study and designed experiments. XH, JSM, BB, TT, KK, LS, KW, QL conducted experiments. All authors listed analyzed the data. JSM, XH, BB wrote the paper with input from all other authors. All authors have read and approved the manuscript. This research was funded by NIH NIGMS R01GM095373 (J.S.M.), NIH NIDCR Awards 1R01DE023810 (W.S., X.H., and J.M.), 1R01DE020102 (W.S., X.H., and J.S.M.), F32DE025548-01 (B.B.), T90DE021984 (T.T.) 1R01DE026186 (W.S., X.H., and J.S.M.).
    [Show full text]
  • Supplemental Material
    Supplemental Material: Deep metagenomics examines the oral microbiome during dental caries, revealing novel taxa and co-occurrences with host molecules Authors: Baker, J.L.1,*, Morton, J.T.2., Dinis, M.3, Alverez, R.3, Tran, N.C.3, Knight, R.4,5,6,7, Edlund, A.1,5,* 1 Genomic Medicine Group J. Craig Venter Institute 4120 Capricorn Lane La Jolla, CA 92037 2Systems Biology Group Flatiron Institute 162 5th Avenue New York, NY 10010 3Section of Pediatric Dentistry UCLA School of Dentistry 10833 Le Conte Ave. Los Angeles, CA 90095-1668 4Center for Microbiome Innovation University of California at San Diego La Jolla, CA 92023 5Department of Pediatrics University of California at San Diego La Jolla, CA 92023 6Department of Computer Science and Engineering University of California at San Diego 9500 Gilman Drive La Jolla, CA 92093 7Department of Bioengineering University of California at San Diego 9500 Gilman Drive La Jolla, CA 92093 *Corresponding AutHors: JLB: [email protected], AE: [email protected] ORCIDs: JLB: 0000-0001-5378-322X, AE: 0000-0002-3394-4804 SUPPLEMENTAL METHODS Study Design. Subjects were included in tHe study if tHe subject was 3 years old or older, in good general HealtH according to a medical History and clinical judgment of tHe clinical investigator, and Had at least 12 teetH. Subjects were excluded from tHe study if tHey Had generalized rampant dental caries, cHronic systemic disease, or medical conditions tHat would influence tHe ability to participate in tHe proposed study (i.e., cancer treatment, HIV, rHeumatic conditions, History of oral candidiasis). Subjects were also excluded it tHey Had open sores or ulceration in tHe moutH, radiation tHerapy to tHe Head and neck region of tHe body, significantly reduced saliva production or Had been treated by anti-inflammatory or antibiotic tHerapy in tHe past 6 montHs.
    [Show full text]