Abstract
Chronic bacterial airway infections in people with cystic fibrosis (CF) are often caused by Pseudomonas aeruginosa, typically showing high phenotypic diversity amongst co-isolates from the same sputum sample. Whilst adaptive evolution during chronic infections has been reported, the genetic mechanisms underlying the observed rapid within-population diversification are not well understood. Two recent conflicting reports described very high and low rates of homologous recombination in two closely related P. aeruginosa populations from the lungs of different chronically infected CF patients. To investigate the underlying cause of these contrasting observations, we combined the short read datasets from both studies and applied a new comparative analysis. We inferred low rates of recombination in both populations. The discrepancy in the findings of the two previous studies can be explained by differences in the application of variant calling techniques. Two novel algorithms were developed that filter false-positive variants. The first algorithm filters variants on the basis of ambiguity within duplications in the reference genome. The second omits probable false-positive variants at regions of non-homology between reference and sample caused by structural rearrangements. As gains and losses of prophage or genomic islands are frequent causes of chromosomal rearrangements within microbial populations, this filter has broad appeal for mitigating false-positive variant calls. Both algorithms are available in a Python package.
Highlights
People with cystic fibrosis (CF) are susceptible to a range of bacterial airway infections, most commonly due to Pseudomonas aeruginosa, which once established are difficult to clear
All short read data from the Darch et al (2015) report were included, representing 22 of the P. aeruginosa isolates obtained from a single sputum sample from a chronically infected CF patient at a Nottingham clinic
Most were adjacent to prophage in the reference that were missing in the samples or at repetitive regions associated with paired reads mapping with unexpected separation distances (Fig. 3)
Summary
People with cystic fibrosis (CF) are susceptible to a range of bacterial airway infections, most commonly due to Pseudomonas aeruginosa, which once established are difficult to clear. Darch et al (2015) reported large trade-offs in virulence factors, quorum sensing signals and growth amongst CF lung P. aeruginosa. Recent studies have demonstrated that there is considerable phenotypic and genomic diversity within single populations of P. aeruginosa in the CF lung (Mowat et al, 2011; Workentine et al, 2013; Williams et al, 2015). They discovered that when multiple isolates were mixed together, resistance to antibiotics increased significantly. As this diversity impedes accurate diagnosis and treatment, there is an urgent need to understand the mechanisms by which these complex population structures have evolved
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