| Literature DB >> 29930949 |
Taylor E Woo1,2, Rachel Lim2, Michael G Surette3,4, Barbara Waddell3, Joel C Bowron1, Ranjani Somayaji2,3, Jessica Duong1, Christopher H Mody2,3, Harvey R Rabin2,3, Douglas G Storey1,3, Michael D Parkins2,3.
Abstract
The natural history and epidemiology of Pseudomonas aeruginosa infections in non-cystic fibrosis (non-CF) bronchiectasis is not well understood. As such it was our intention to determine the evolution of airway infection and the transmission potential of P. aeruginosa in patients with non-CF bronchiectasis. A longitudinal cohort study was conducted from 1986-2011 using a biobank of prospectively collected isolates from patients with non-CF bronchiectasis. Patients included were ≥18 years old and had ≥2 positive P. aeruginosa cultures over a minimum 6-month period. All isolates obtained at first and most recent clinical encounters, as well as during exacerbations, that were morphologically distinct on MacConkey agar were genotyped by pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). A total of 203 isolates from 39 patients were analysed. These were compared to a large collection of globally epidemic and local CF strains, as well as non-CF isolates. We identified four patterns of infection in non-CF bronchiectasis including: 1) persistence of a single strain (n=26; 67%); 2) strain displacement (n=8; 20%); 3) temporary disruption (n=3; 8%); and 4) chaotic airway infection (n=2; 5%). Patterns of infection were not significant predictors of rates of lung function decline or progression to end-stage disease and acquisition of new strains did not associate with the occurrence of exacerbations. Rarely, non-CF bronchiectasis strains with similar pulsotypes were observed in CF and non-CF controls, but no CF epidemic strains were observed. While rare shared strains were observed in non-CF bronchiectasis, whole-genome sequencing refuted patient-patient transmission. We observed a higher incidence of strain-displacement in our patient cohort compared to those observed in CF studies, although this did not impact on outcomes.Entities:
Year: 2018 PMID: 29930949 PMCID: PMC6004520 DOI: 10.1183/23120541.00162-2017
Source DB: PubMed Journal: ERJ Open Res ISSN: 2312-0541
Baseline patient demographics
| 66.7 (47.9, 72.7) | 61.46 (41, 71) | |
| 2.8 (1, 7) | 4.8 (1, 10.4) | |
| 51 (39, 65) | 58 (40.5, 78.5) | |
| Sinusitis | 11 (42) | 6 (46) |
| Reactive airway disease | 7 (27) | 3 (23) |
| COPD | 8 (31) | 1 (8) |
| Idiopathic | 13 (50) | 4 (31) |
| Post-infective | 13 (50) | 7 (54) |
| Immunodeficiency | 1 (8) | |
| Other | 1 (8) | |
| Inhaled tobramycin | 6 (23) | 3 (23) |
| Azithromycin | 6 (23) | 1 (8) |
| Ciprofloxacin | 3 (12) | 3 (23) |
| Inhaled β2-agonist | 23 (88) | 10 (77) |
| Inhaled CS | 16 (62) | 5 (38) |
| Ipratropium bromide | 2 (8) | 6 (46) |
| Systemic CS | 5 (19) | 2 (15) |
| Spiriva | 6 (23) | 2 (15) |
| 12 (46) | 5 (38) |
Data are presented as n (%) or median (interquartile range). FEV1: forced expiratory volume in 1 s; COPD: chronic obstructive pulmonary disease; CS: corticosteroid.
FIGURE 1Flow chart of study design including the total number of non-cystic fibrosis bronchiectasis patients enrolled. PEx: pulmonary exacerbation.
FIGURE 2Displaying the diversity in the natural history of infections of Pseudomonas aeruginosa in patients with non-cystic fibrosis bronchiectasis including: a) patients with stable infection by a single strain of P. aeruginosa (persistence of infection; n=26); b) strain displacement (n=8); c) temporary disruption (n=3); d) chaotic airways infection (n=2). The dendrograms were generated at 2.0% position tolerance and 1.5% optimisation using the unweighted pair-group method with arithmetic mean (UPGMA) and the Sørensen–Dice similarity coefficient. Isolates were named following the format “A(patient)-P(isolate)-(date isolated)”. ST: sequence typing; PEx: pulmonary exacerbation.
FIGURE 3Cluster diagram for four patient pairs with genotyped strains sharing the same sequence typing (ST). The dendrograms were generated at 2.0% position tolerance and 1.5% optimisation using the unweighted pair-group method with arithmetic mean (UPGMA) and the Sørensen–Dice similarity coefficient. Isolates were named following the format “A(patient)-P(isolate)-(date isolated)”.
FIGURE 4Clonal strains of Pseudomonas aeruginosa were identified from independent patient-pairs using multilocus sequence typing (MLST). Individual strains are coloured by patient. Strain relatedness was assessed using whole-genome sequencing and phylogeny generated from a matrix with the presence and absence of core and accessory genes using Roary [23].