The Role of Suboptimal Concentrations of Nebulized Tobramycin in Driving Antimicrobial Resistance in Pseudomonas aeruginosa Isolates in Cystic Fibrosis

Changes in factors associated with inhaled antibiotic prescriptions for people with cystic fibrosis over time in the U.S

RATIONALE

CF care guidelines recommend chronic inhaled antibiotics for chronic Pseudomonas aeruginosa (Pa) lung infection. These medications are costly, time consuming and prescription needs may change with improved outcomes.

OBJECTIVES

We determined the proportion of pwCF with chronic, intermittent or negative Pa infection categories, their clinical and demographic characteristics, factors associated with inhaled antibiotic prescription and changes between 2011 and 2019.

METHODS

This cohort study using the U.S. CF Foundation patient registry for pwCF >2 years, no prior lung transplant, and with ≥3 respiratory cultures/year determined chronic inhaled antibiotics (≥3 months per calendar year) and Pa infection status from encounter level data. Outcomes and odds of prescription for relevant clinical factors were evaluated using generalized estimating equation models with additional interaction between the predictor and the calendar year to examine changes of predictors over time.

RESULTS

Proportion of pwCF with chronic and intermittent Pa decreased and antibiotic prescription rates increased for these groups and decreased for Pa negative pwCF. Hispanic ethnicity, female sex, pancreatic insufficiency, CF diabetes, and ivacaftor/lumacaftor were associated with higher antibiotic prescriptions for each Pa status. Among Pa-negative pwCF prescriptions were higher with Burkholderia spp. (1.17, (CI95 1.03,1.34)) or MRSA (OR 1.45, (1.26,1.68)) but decreased between 2011 and 2019. For Aspergillus OR increased to 1.6,(1.3,1.8) in 2019. Prescriptions for pwCF on ivacaftor decreased, becoming lower in 2019 for chronic (OR 0.7, (0.5,0.8)) and Pa-negative pwCF (OR 0.7, (0.5,0.8)).

CONCLUSIONS

Factors predicting inhaled antibiotic prescription differed between 2011 and 2019 indicating changes in health and care for pwCF even prior to triple-modulators.

Impact of Growth Conditions on High-Throughput Identification of Repurposing Drugs for Pseudomonas aeruginosa Cystic Fibrosis Lung Infections

Pseudomonas aeruginosa lung infections in cystic fibrosis (CF) patients represent a therapeutic challenge due to antibiotic resistance. Repurposing existing drugs is a promising approach for identifying new antimicrobials. A crucial factor in successful drug repurposing is using assay conditions that mirror the site of infection. Here, the impact of growth conditions on the anti-P. aeruginosa activity of a library of 3386 compounds was evaluated. To this, after 24 h exposure, the survival rate of CF P. aeruginosa RP73 planktonic cells was assessed spectrophotometrically under "CF-like" (artificial CF sputum, pH 6.8, 5% CO2) and enriched (Tryptone Soya Broth, pH 7.2, and aerobiosis) conditions. Among non-antibiotic compounds (n = 3127), 13.4% were active regardless of growth conditions, although only 3.2% had comparable activity; 4% and 6.2% were more active under CF-like or enriched conditions, respectively. Interestingly, 22.1% and 26.6% were active exclusively under CF-like and enriched conditions, respectively. Notably, 7 and 12 hits caused 100% killing under CF-like and enriched conditions, respectively. Among antibiotics (n = 234), 42.3% were active under both conditions, although only 18.4% showed comparable activity; 9.4% and 14.5% were more active under CF-like and enriched conditions, respectively. Interestingly, 23% and 16.6% were active exclusively under CF-like and enriched conditions, respectively. Sulphonamides showed higher activity under CF-like conditions, whereas tetracyclines, fluoroquinolones, and macrolides were more effective under enriched settings. Our findings indicated that growth conditions significantly affect the anti-P. aeruginosa activity of antibiotics and non-antibiotic drugs. Consequently, repurposing studies and susceptibility tests should be performed under physicochemical conditions that the pathogen tackles at the site of infection.

Selection of antibiotic resistance in pigs after exposure to feed cross-contaminated with oxytetracycline

Due to possible cross-contamination of animal feedstuff with antibiotics, food-producing animals may be exposed to undesirable low concentrations of antimicrobials. These sub-therapeutic levels of antibiotics can lead to the selection of resistant bacteria in the animal gut. The goal of this study was to assess, through analysis of the faeces of treated and control pigs, the risk of resistant E. coli being selected after daily exposure for three weeks to feed contaminated with oxytetracycline at 1% of the therapeutic dose. Liquid Chromatography coupled to tandem Mass Spectrometry was used to determine the oxytetracycline concentrations in faecal samples. In the treated group, concentrations were in the range of 4481.9 - 8671.2 µg/kg. In the control group, these concentrations were either below the method's limit of quantification or up to 60.5 µg/kg. After a transient increase in resistance in both groups, microbiological analysis showed that the treated group had a significantly higher oxytetracycline resistance rate by the end of the study than the control group (p < 0.001). Furthermore, the treated animals were found to select co-resistances to nalidixic acid and ampicillin. Finally, at tolerated antibiotic contamination levels of feed, the treated group had a higher proportion of multidrug-resistant isolates at the end of the study than the control one (p < 0.05). The present study demonstrates that, at the tolerated contamination rates, both antimicrobial resistance and multidrug-resistant bacteria can be selected and evidenced in the gut microbiota.

Improving health literacy of antibiotic use in people with cystic fibrosis (CF)-comparison of the readability of patient information leaflets (PILs) from the EU, USA and UK of 23 CF-related antibiotics used in the treatment of CF respiratory infections

Background

Antibiotic adherence is poor amongst people with cystic fibrosis (CF). Low-quality patient information leaflets (PILs), which accompany prescription antibiotics, with poor readability may contribute to poor antibiotic adherence, with the potential for antimicrobial resistance (AMR) development. The aim of this study was to examine the readability of antibiotic PILs used to treat CF lung infections.

Methods

CF-related antibiotics (n = 23; seven classes: aminoglycosides, β-lactams, fluoroquinolones, macrolides/lincosamides, oxazolidinones, tetracyclines, trimethoprim/sulfamethoxazole) were investigated. Readability of PILs (n = 141; 23 antibiotics) from the EU (n = 40), USA (n = 42) and UK (n = 59) was calculated.

Results

Mean [± standard error of mean (SEM)] values for the Flesch Reading Ease (FRE) for EU, USA and UK were 50.0 ± 1.1, 56.2 ± 1.3 and 51.7 ± 1.1, respectively (FRE target ≥60). Mean (± SEM) values for the Flesch Kinkaid Grade Level (FKGL) for the EU, USA and UK were 9.0 ± 0.2, 7.5 ± 0.2 and 9.6 ± 0.2, respectively (FKGL target ≤8). US PILs were significantly shorter (P < 0.0001) in words (mean ± SEM = 1365 ± 52), than either UK or EU PILs, with fewer sentences (P < 0.0001), fewer words per sentence (P < 0.0001) and fewer syllables per word. The mean ( ± SEM) reading time of UK PILs (n = 59) was 12.7 ± 0.55 mins .

Conclusions

Readability of antibiotic PILs is poor. Improving PIL readability may lead to improved health literacy, which may translate to increased antibiotic adherence and AMR avoidance. Authors preparing written materials for the lay/patient CF community are encouraged to employ readability calculators, so that final materials are within recommended readability reference parameters, to support the health (antibiotic) literacy of their readers.

Repurposing High-Throughput Screening Identifies Unconventional Drugs with Antibacterial and Antibiofilm Activities against Pseudomonas aeruginosa under Experimental Conditions Relevant to Cystic Fibrosis

Pseudomonas aeruginosa is the most common pathogen infecting cystic fibrosis (CF) lungs, causing acute and chronic infections. Intrinsic and acquired antibiotic resistance allow P. aeruginosa to colonize and persist despite antibiotic treatment, making new therapeutic approaches necessary. Combining high-throughput screening and drug repurposing is an effective way to develop new therapeutic uses for drugs. This study screened a drug library of 3,386 drugs, mostly FDA approved, to identify antimicrobials against P. aeruginosa under physicochemical conditions relevant to CF-infected lungs. Based on the antibacterial activity, assessed spectrophotometrically against the prototype RP73 strain and 10 other CF virulent strains, and the toxic potential evaluated toward CF IB3-1 bronchial epithelial cells, five potential hits were selected for further analysis: the anti-inflammatory and antioxidant ebselen, the anticancer drugs tirapazamine, carmofur, and 5-fluorouracil, and the antifungal tavaborole. A time-kill assay showed that ebselen has the potential to cause rapid and dose-dependent bactericidal activity. The antibiofilm activity was evaluated by viable cell count and crystal violet assays, revealing carmofur and 5-fluorouracil as the most active drugs in preventing biofilm formation regardless of the concentration. In contrast, tirapazamine and tavaborole were the only drugs actively dispersing preformed biofilms. Tavaborole was the most active drug against CF pathogens other than P. aeruginosa, especially against Burkholderia cepacia and Acinetobacter baumannii, while carmofur, ebselen, and tirapazamine were particularly active against Staphylococcus aureus and B. cepacia. Electron microscopy and propidium iodide uptake assay revealed that ebselen, carmofur, and tirapazamine significantly damage cell membranes, with leakage and cytoplasm loss, by increasing membrane permeability. IMPORTANCE Antibiotic resistance makes it urgent to design new strategies for treating pulmonary infections in CF patients. The repurposing approach accelerates drug discovery and development, as the drugs' general pharmacological, pharmacokinetic, and toxicological properties are already well known. In the present study, for the first time, a high-throughput compound library screening was performed under experimental conditions relevant to CF-infected lungs. Among 3,386 drugs screened, the clinically used drugs from outside infection treatment ebselen, tirapazamine, carmofur, 5-fluorouracil, and tavaborole showed, although to different extents, anti-P. aeruginosa activity against planktonic and biofilm cells and broad-spectrum activity against other CF pathogens at concentrations not toxic to bronchial epithelial cells. The mode-of-action studies revealed ebselen, carmofur, and tirapazamine targeted the cell membrane, increasing its permeability with subsequent cell lysis. These drugs are strong candidates for repurposing for treating CF lung P. aeruginosa infections.

In Vitro Activity of Finafloxacin against Panels of Respiratory Pathogens

This study determined the in vitro activity of finafloxacin against panels of bacterial strains, representative of those associated with infection in cystic fibrosis patients and predominately isolated from clinical cases of respiratory disease. Many of these isolates were resistant to various antimicrobials evaluated including the aminoglycosides, cephalosporins, carbapenems and fluoroquinolones. Broth microdilution assays were performed at neutral and acidic pH, to determine antimicrobial activity. Finafloxacin demonstrated superior activity at reduced pH for all of the bacterial species investigated, highlighting the requirement to determine the activity of antimicrobials in host-relevant conditions.

Machine Learning Techniques for Antimicrobial Resistance Prediction of Pseudomonas Aeruginosa from Whole Genome Sequence Data

AIM

Due to the growing availability of genomic datasets, machine learning models have shown impressive diagnostic potential in identifying emerging and reemerging pathogens. This study aims to use machine learning techniques to develop and compare a model for predicting bacterial resistance to a panel of 12 classes of antibiotics using whole genome sequence (WGS) data of Pseudomonas aeruginosa.

METHOD

A machine learning technique called Random Forest (RF) and BioWeka was used for classification accuracy assessment and logistic regression (LR) for statistical analysis.

RESULTS

Our results show 44.66% of isolates were resistant to twelve antimicrobial agents and 55.33% were sensitive. The mean classification accuracy was obtained ≥98% for BioWeka and ≥96 for RF on these families of antimicrobials. Where ampicillin was 99.31% and 94.00%, amoxicillin was 99.02% and 95.21%, meropenem was 98.27% and 96.63%, cefepime was 99.73% and 98.34%, fosfomycin was 96.44% and 99.23%, ceftazidime was 98.63% and 94.31%, chloramphenicol was 98.71% and 96.00%, erythromycin was 95.76% and 97.63%, tetracycline was 99.27% and 98.25%, gentamycin was 98.00% and 97.30%, butirosin was 99.57% and 98.03%, and ciprofloxacin was 96.17% and 98.97% with 10-fold-cross validation. In addition, out of twelve, eight drugs have found no false-positive and false-negative bacterial strains.

CONCLUSION

The ability to accurately detect antibiotic resistance could help clinicians make educated decisions about empiric therapy based on the local antibiotic resistance pattern. Moreover, infection prevention may have major consequences if such prescribing practices become widespread for human health.

The Effects of Sub-inhibitory Antibiotic Concentrations on Pseudomonas aeruginosa: Reduced Susceptibility Due to Mutations

Pseudomonas aeruginosa chronically infects in the lungs of people with cystic fibrosis and other forms of lung disease. Infections are treated with antibiotics, but over time, the bacteria acquire mutations that reduce their antibiotic susceptibility. The effects of inhibitory amounts of antibiotics in selecting for antibiotic-resistant mutants have been well studied. However, the concentrations of antibiotics that reach infecting bacteria can be sub-inhibitory and but may nonetheless promote emergence of antibiotic-resistant bacteria. Therefore, the aim of this research was to investigate the effects of sub-inhibitory concentrations of antibiotics on the antibiotic susceptibility of P. aeruginosa. Two P. aeruginosa reference strains, PAO1 and PA14, and six isolates from individuals with cystic fibrosis were studied. The bacteria were passaged in the presence of antibiotics (ceftazidime, ciprofloxacin, meropenem or tobramycin) at sub-inhibitory amounts. Fifteen populations of bacteria (up to five per strain) were exposed to each of the four antibiotics. Antibiotic susceptibility was determined following 10 passages on agar supplemented with antibiotic and compared with susceptibility prior to antibiotic exposure. Antibiotic exposure resulted in susceptibility being significantly (>2-fold) reduced for 13 of the 60 populations. Seven samples had reduced susceptibility to ciprofloxacin, three to tobramycin, two to ceftazidime and one to meropenem. Whole-genome sequencing revealed the mutations arising following antibiotic exposure. Mutants with reduced antibiotic susceptibility had mutations in genes known to affect antibiotic resistance, including regulators of efflux pumps (mexR, mexS, mexZ and nalC) and the fusA1 gene that is associated with aminoglycoside resistance. Genes not previously associated with resistance, including gacS, sigX and crfX and two genes with no known function, were also mutated in some isolates with reduced antibiotic susceptibility. Our results show that exposure to sub-inhibitory amounts of antibiotics can select for mutations that reduce the susceptibility of P. aeruginosa to antibiotics and that the profile of mutations is different from that arising during selection with inhibitory antibiotic concentrations. It is likely that exposure to sub-inhibitory amounts of antibiotics during infection contributes to P. aeruginosa becoming antibiotic-resistant.