Coexistence and Within-Host Evolution of Diversified Lineages of Hypermutable Pseudomonas aeruginosa in Long-term Cystic Fibrosis Infections

Abstract

The advent of high-throughput sequencing techniques has made it possible to follow the genomic evolution of pathogenic bacteria by comparing longitudinally collected bacteria sampled from human hosts. Such studies in the context of chronic airway infections by Pseudomonas aeruginosa in cystic fibrosis (CF) patients have indicated high bacterial population diversity. Such diversity may be driven by hypermutability resulting from DNA mismatch repair system (MRS) deficiency, a common trait evolved by P. aeruginosa strains in CF infections. No studies to date have utilized whole-genome sequencing to investigate within-host population diversity or long-term evolution of mutators in CF airways. We sequenced the genomes of 13 and 14 isolates of P. aeruginosa mutator populations from an Argentinian and a Danish CF patient, respectively. Our collection of isolates spanned 6 and 20 years of patient infection history, respectively. We sequenced 11 isolates from a single sample from each patient to allow in-depth analysis of population diversity. Each patient was infected by clonal populations of bacteria that were dominated by mutators. The in vivo mutation rate of the populations was ∼100 SNPs/year–∼40-fold higher than rates in normo-mutable populations. Comparison of the genomes of 11 isolates from the same sample showed extensive within-patient genomic diversification; the populations were composed of different sub-lineages that had coexisted for many years since the initial colonization of the patient. Analysis of the mutations identified genes that underwent convergent evolution across lineages and sub-lineages, suggesting that the genes were targeted by mutation to optimize pathogenic fitness. Parallel evolution was observed in reduction of overall catabolic capacity of the populations. These findings are useful for understanding the evolution of pathogen populations and identifying new targets for control of chronic infections.

Diversity of metabolic profiles of cystic fibrosis Pseudomonas aeruginosa during the early stages of lung infection

“…The time between the early and late isolates covers a period of up to six years which, according to our previous estimates of in vivo growth rates of P. aeruginosa in CF patients, is up to about 38 000 generations (Yang et al, 2008). Our hypothesis was that major adaptive PMs have previously been used to determine the evolutionary dynamics of P. aeruginosa isolates from CF patients (Feliziani et al, 2014;Markussen et al, 2014;Yang et al, 2011) and to determine growth and virulence traits (Oberhardt et al, 2008), but we are, to the best of our knowledge, the first to use this method to assign specific metabolic pathways to selected substrates in order to investigate the metabolic adaptation patterns of P. aeruginosa isolates from CF patients.…”

High-Resolution Analysis by Whole-Genome Sequencing of an International Lineage (Sequence Type 111) of Pseudomonas aeruginosa Associated with Metallo-Carbapenemases in the United Kingdom

“…A study among multiple isolates from patients with cystic fibrosis focusing on hypermutators (which have a mutation rate approximately 40-fold higher than those in normal populations) found a mutation rate of approximately 100 SNPs per year (35) and extensive within-patient diversification of populations, which were composed of a number of different sublineages. Without diversification, we would therefore have expected approximately 10 SNPs between isolates from the same patient separated by 4 years.…”

“…BEAST analysis (http://beast.bio.ed.ac.uk/), which has previously been successfully used for the investigation of the evolution of isolates of P. aeruginosa from patients with cystic fibrosis (35), produces time-measured phylogenies, allowing estimation of the time of divergence of different clades and is therefore a useful additional tool for analyzing sequences from isolates obtained over an extended period. The FASTA file describing SNPs in multiple samples was imported into BEAUti 1.8 and used to generate a BEAST 1.8 compatible xml file using the following parameters: Hasegawa-Kishino-Yano (HKY) substitution model, gamma site heterogeneity model, lognormal relaxed clock, coalescent constant size tree prior, UPGMA starting tree model, and 5 million Markov Chain Monte Carlo (MCMC) chain length (36).…”

A Low-Molecular-Weight Alginate Oligosaccharide Disrupts Pseudomonal Microcolony Formation and Enhances Antibiotic Effectiveness

“…ATP production levels by PAO1 and NH57388A were compared in MH and AS media with or without 2% OligoG CF-5/10. Cultures were prepared as for the growth curve experiments and analyzed using the BacTiter-Glo microbial cell viability assay (Promega) at 0, 2,4,6,8,12,24, and 48 h, with luminescence read on a Fluostar Omega plate reader.…”