Expression of Pseudomonas aeruginosa Antibiotic Resistance Genes Varies Greatly during Infections in Cystic Fibrosis Patients

Abstract

The lungs of individuals with cystic fibrosis (CF) become chronically infected with that is difficult to eradicate by antibiotic treatment. Two key antibiotic resistance mechanisms are the AmpC β-lactamase that degrades β-lactam antibiotics and MexXYOprM, a three-protein efflux pump that expels aminoglycoside antibiotics from the bacterial cells. Levels of antibiotic resistance gene expression are likely to be a key factor in antibiotic resistance but have not been determined during infection. The aims of this research were to investigate the expression of the and genes during infection in patients with CF and in bacteria isolated from the same patients and grown under laboratory conditions. isolates from 36 CF patients were grown in laboratory culture and gene expression measured by reverse transcription-quantitative PCR (RT-qPCR). The expression of varied over 20,000-fold and that of over 2,000-fold between isolates. The median expression levels of both genes were increased by the presence of subinhibitory concentrations of antibiotics. To measure gene expression during infection, we carried out RT-qPCR using RNA extracted from fresh sputum samples obtained from 31 patients. The expression of varied over 4,000-fold, while expression varied over 100-fold, between patients. Despite these wide variations, median levels of expression of in bacteria in sputum were similar to those in laboratory-grown bacteria. The expression of was higher in sputum than in laboratory-grown bacteria. Overall, our data demonstrate that genes that contribute to antibiotic resistance can be highly expressed in patients, but there is extensive isolate-to-isolate and patient-to-patient variation.

Lean, mean, learning machines

“…In Pseudomonas aeruginosa, differences in the expression of resistance genes account for some resistance phenotypes that currently cannot be explained by genetic variation alone 3 . Using 414 P. aeruginosa clinical isolates, Khaledi et al 4 examined the ability of machine learning methods to predict resistance to four common anti-pseudomonal antimicrobials using data on gene presence or absence (GPA), genetic variation and gene expression under standard culture conditions.…”

Diallyl sulfide from garlic suppresses quorum‐sensing systems of Pseudomonas aeruginosa and enhances biosynthesis of three B vitamins through its thioether group

“…Pseudomonas aeruginosa is a ubiquitous gram‐negative opportunistic pathogen that causes a variety of infections in human, including chronic infection of the airway in patients with cystic fibrosis (Stover et al ., 2000; Martin et al ., 2018; Kostylev et al ., 2019). P. aeruginosa produces a large number of virulence factors that cause persistent infections (Lee and Zhang, 2015).…”

A Fundamental Change in Antibiotic Susceptibility Testing Would Better Prevent Therapeutic Failure: From Individual to Population-Based Analysis

“…the majority of the bacterial population may be present at lower frequencies in clinical samples, but remain unanalyzed (Martin et al, 2018;Qin et al, 2018;Maciel et al, 2020;Montealegre et al, 2020). Unfortunately, diversity in susceptibility remains undetected due to the current standard operating procedures of AST.…”

“…However, misguiding AST results can lead to poor and even fatal outcomes (Zilberberg et al, 2017 ; Jiang et al, 2018 ; Karve et al, 2018 ; Band and Weiss, 2019 ; Eliakim-Raz et al, 2019 ; Peeters et al, 2019 ; Rodriguez-Gomez et al, 2019 ; Uppsala University, 2019 ). There is a consensus among some medical researchers that these tests need improvement (Valsesia et al, 2015 ; Karve et al, 2018 ; Martin et al, 2018 ; Band and Weiss, 2019 ; Kahlmeter et al, 2019 ; Lerminiaux and Cameron, 2019 ; Nicoloff et al, 2019 ; Peeters et al, 2019 ). To improve the clinical value of AST, we challenge and propose a change of the two most dogmatic steps of the clinical tests: standardization of bacterial inoculation size (McFaland, 1907 ; Smith and Kirby, 2018 ) and the use of a limited number of bacterial colonies (Kao et al, 2014 ; Qin et al, 2018 ; Maciel et al, 2020 ; Montealegre et al, 2020 ).…”

“…Present formats of AST are designed to detect the susceptibility of the most prevalent bacteria, but not necessarily the most resistant. Other bacterial subtypes with higher resistance than the majority of the bacterial population may be present at lower frequencies in clinical samples, but remain unanalyzed (Martin et al, 2018 ; Qin et al, 2018 ; Maciel et al, 2020 ; Montealegre et al, 2020 ). Unfortunately, diversity in susceptibility remains undetected due to the current standard operating procedures of AST.…”