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Title: Microbiotyping the Sinonasal Microbiome
Authors: Ahmed Bassiouni
Sathish Paramasivan
Arron Shiffer
Matthew R. Dillon
Emily K. Cope
Clare Cooksley
Mahnaz Ramezanpour
Sophia Moraitis
Mohammad Javed Ali
Benjamin S. Bleier
Claudio Callejas
Marjolein E. Cornet
Richard G. Douglas
Daniel Dutra
Christos Georgalas
Richard J. Harvey
Peter H. Hwang
Amber U. Luong
Rodney J. Schlosser
Pongsakorn Tantilipikorn
Marc A. Tewfik
Sarah Vreugde
Peter John Wormald
J. Gregory Caporaso
Alkis J. Psaltis
University of Nicosia
Pontificia Universidad Católica de Chile
University of New South Wales (UNSW) Australia
University of Texas Health Science Center at Houston
Northern Arizona University
Medical University of South Carolina
Macquarie University
Stanford University
Faculty of Medicine, Siriraj Hospital, Mahidol University
The University of Adelaide
Universidade de Sao Paulo - USP
University of Auckland
Harvard Medical School
McGill University
Amsterdam UMC
LV Prasad Institute
Keywords: Immunology and Microbiology;Medicine
Issue Date: 8-Apr-2020
Citation: Frontiers in Cellular and Infection Microbiology. Vol.10, (2020)
Abstract: © Copyright © 2020 Bassiouni, Paramasivan, Shiffer, Dillon, Cope, Cooksley, Ramezanpour, Moraitis, Ali, Bleier, Callejas, Cornet, Douglas, Dutra, Georgalas, Harvey, Hwang, Luong, Schlosser, Tantilipikorn, Tewfik, Vreugde, Wormald, Caporaso and Psaltis. This study offers a novel description of the sinonasal microbiome, through an unsupervised machine learning approach combining dimensionality reduction and clustering. We apply our method to the International Sinonasal Microbiome Study (ISMS) dataset of 410 sinus swab samples. We propose three main sinonasal “microbiotypes” or “states”: the first is Corynebacterium-dominated, the second is Staphylococcus-dominated, and the third dominated by the other core genera of the sinonasal microbiome (Streptococcus, Haemophilus, Moraxella, and Pseudomonas). The prevalence of the three microbiotypes studied did not differ between healthy and diseased sinuses, but differences in their distribution were evident based on geography. We also describe a potential reciprocal relationship between Corynebacterium species and Staphylococcus aureus, suggesting that a certain microbial equilibrium between various players is reached in the sinuses. We validate our approach by applying it to a separate 16S rRNA gene sequence dataset of 97 sinus swabs from a different patient cohort. Sinonasal microbiotyping may prove useful in reducing the complexity of describing sinonasal microbiota. It may drive future studies aimed at modeling microbial interactions in the sinuses and in doing so may facilitate the development of a tailored patient-specific approach to the treatment of sinus disease in the future.
ISSN: 22352988
Appears in Collections:Scopus 2020

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