Moana Mika1, Ines Mack2, Insa Korten3, Weihong Qi4, Suzanne Aebi5, Urs Frey6, Philipp Latzin2, Markus Hilty7. 1. Institute for Infectious Diseases, University of Bern, Bern, Switzerland; Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland. 2. Division of Respiratory Medicine, Department of Pediatrics, Inselspital and University of Bern, Bern, Switzerland; University Children's Hospital (UKBB), Basel, Switzerland. 3. Graduate School for Cellular and Biomedical Sciences, University of Bern, Bern, Switzerland; Division of Respiratory Medicine, Department of Pediatrics, Inselspital and University of Bern, Bern, Switzerland. 4. Functional Genomics Center, Swiss Federal Institute of Technology Zurich/University of Zurich, Zurich, Switzerland. 5. Institute for Infectious Diseases, University of Bern, Bern, Switzerland. 6. University Children's Hospital (UKBB), Basel, Switzerland. 7. Institute for Infectious Diseases, University of Bern, Bern, Switzerland; Department of Infectious Diseases, University Hospital, Bern, Switzerland. Electronic address: markus.hilty@ifik.unibe.ch.
Abstract
BACKGROUND: Understanding the composition and dynamics of the upper respiratory tract microbiota in healthy infants is a prerequisite to investigate the role of the microbiota in patients with respiratory diseases. This is especially true in early life, when the immune system is in development. OBJECTIVE: We sought to describe the dynamics of the upper respiratory tract microbiota in healthy infants within the first year of life. METHODS: After exclusion of low-quality samples, microbiota characterization was performed by using 16S rDNA pyrosequencing of 872 nasal swabs collected biweekly from 47 unselected infants. RESULTS: Bacterial density increased and diversity decreased within the first year of life (R(2) = 0.95 and 0.73, respectively). A distinct profile for the first 3 months of life was found with increased relative abundances of Staphlyococcaceae and Corynebacteriaceae (exponential decay: R(2) = 0.94 and 0.96, respectively). In addition, relative bacterial abundance and composition differed significantly from summer to winter months. The individual composition of the microbiota changed with increasing time intervals between samples and was best modeled by an exponential function (R(2) = 0.97). Within-subject dissimilarity in a 2-week time interval was consistently lower than that between subjects, indicating a personalized microbiota. CONCLUSION: This study reveals age and seasonality as major factors driving the composition of the nasal microbiota within the first year of life. A subject's microbiota is personalized but dynamic throughout the first year. These data are indispensable to interpretation of cross-sectional studies and investigation of the role of the microbiota in both healthy subjects and patients with respiratory diseases. They might also serve as a baseline for future intervention studies.
BACKGROUND: Understanding the composition and dynamics of the upper respiratory tract microbiota in healthy infants is a prerequisite to investigate the role of the microbiota in patients with respiratory diseases. This is especially true in early life, when the immune system is in development. OBJECTIVE: We sought to describe the dynamics of the upper respiratory tract microbiota in healthy infants within the first year of life. METHODS: After exclusion of low-quality samples, microbiota characterization was performed by using 16S rDNA pyrosequencing of 872 nasal swabs collected biweekly from 47 unselected infants. RESULTS: Bacterial density increased and diversity decreased within the first year of life (R(2) = 0.95 and 0.73, respectively). A distinct profile for the first 3 months of life was found with increased relative abundances of Staphlyococcaceae and Corynebacteriaceae (exponential decay: R(2) = 0.94 and 0.96, respectively). In addition, relative bacterial abundance and composition differed significantly from summer to winter months. The individual composition of the microbiota changed with increasing time intervals between samples and was best modeled by an exponential function (R(2) = 0.97). Within-subject dissimilarity in a 2-week time interval was consistently lower than that between subjects, indicating a personalized microbiota. CONCLUSION: This study reveals age and seasonality as major factors driving the composition of the nasal microbiota within the first year of life. A subject's microbiota is personalized but dynamic throughout the first year. These data are indispensable to interpretation of cross-sectional studies and investigation of the role of the microbiota in both healthy subjects and patients with respiratory diseases. They might also serve as a baseline for future intervention studies.
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