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, 12 (8), e0182520

The Temporal Dynamics of the Tracheal Microbiome in Tracheostomised Patients With and Without Lower Respiratory Infections


The Temporal Dynamics of the Tracheal Microbiome in Tracheostomised Patients With and Without Lower Respiratory Infections

Marcos Pérez-Losada et al. PLoS One.


Background: Airway microbiota dynamics during lower respiratory infection (LRI) are still poorly understood due, in part, to insufficient longitudinal studies and lack of uncontaminated lower airways samples. Furthermore, the similarity between upper and lower airway microbiomes is still under debate. Here we compare the diversity and temporal dynamics of microbiotas directly sampled from the trachea via tracheostomy in patients with (YLRI) and without (NLRI) lower respiratory infections.

Methods: We prospectively collected 127 tracheal aspirates across four consecutive meteorological seasons (quarters) from 40 patients, of whom 20 developed LRIs and 20 remained healthy. All aspirates were collected when patients had no LRI. We generated 16S rRNA-based microbial profiles (~250 bp) in a MiSeq platform and analyzed them using Mothur and the SILVAv123 database. Differences in microbial diversity and taxon normalized (via negative binomial distribution) abundances were assessed using linear mixed effects models and multivariate analysis of variance.

Results and discussion: Alpha-diversity (ACE, Fisher and phylogenetic diversity) and beta-diversity (Bray-Curtis, Jaccard and Unifrac distances) indices varied significantly (P<0.05) between NLRI and YLRI microbiotas from tracheostomised patients. Additionally, Haemophilus was significantly (P = 0.009) more abundant in YLRI patients than in NLRI patients, while Acinetobacter, Corynebacterium and Pseudomonas (P<0.05) showed the inverse relationship. We did not detect significant differences in diversity and bacterial abundance among seasons. This result disagrees with previous evidence suggesting seasonal variation in airway microbiotas. Further study is needed to address the interaction between microbes and LRI during times of health and disease.

Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.


Fig 1
Fig 1. Box plots of phylogenetic alpha-diversity of microbiotas from patients with (YLRI) and without (NLRI) lower respiratory infections (LRI) (A) and of microbiotas from YLRI and NLRI patients across meteorological seasons (B).
Fig 2
Fig 2. Alluvial plots of mean relative proportions of most abundant (≥3%) phyla and genera in microbiomes from patients with (YLRI) and without (NLRI) lower respiratory infections (LRI) across meteorological seasons.

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    1. Bureau MCH. Prevalence of CSHCN. In: Services DoHaH, editor. Washington, DC: 2008.
    1. Berry JG, Graham DA, Graham RJ, Zhou J, Putney HL, O'Brien JE, et al. Predictors of clinical outcomes and hospital resource use of children after tracheotomy. Pediatrics. 2009;124(2):563–72. Epub 2009/07/15. doi: 10.1542/peds.2008-3491 ; - DOI - PMC - PubMed
    1. Dosa NP, Boeing NM, Ms N, Kanter RK. Excess risk of severe acute illness in children with chronic health conditions. Pediatrics. 2001;107(3):499–504. Epub 2001/03/07. . - PubMed
    1. Rusakow LS, Guarin M, Wegner CB, Rice TB, Mischler EH. Suspected respiratory tract infection in the tracheostomized child: the pediatric pulmonologist's approach. Chest. 1998;113(6):1549–54. Epub 1998/06/19. . - PubMed
    1. McCaleb R, Warren RH, Willis D, Maples HD, Bai S, O'Brien CE. Description of Respiratory Microbiology of Children With Long-Term Tracheostomies. Respir Care. 2016;61(4):447–52. doi: 10.4187/respcare.03518 . - DOI - PubMed

Grant support

This work was supported by a special recognition grant from the Office of Faculty Development at Boston Children’s Hospital to JMM. MP-L was funded in part by a K12 Career Development Program K12HL119994. This research was funded in part by a Margaret Q. Landenberger Research Foundation award to MP-L. MP-L was also partially supported by Award Numbers UL1TR001876 and KL2TR001877 from the NIH National Center for Advancing Translational Sciences. The contents of this publication are solely the responsibility of the authors and do not necessarily represent the official views of the National Center for Advancing Translational Sciences or the National Institutes of Health. ECN was funded by "CONICYT + PAI/ CONCURSO NACIONAL APOYO AL RETORNO DE INVESTIGADORES/AS DESDE EL EXTRANJERO, CONVOCATORIA 2014 + FOLIO 82140008”.