A rapid MALDI-TOF mass spectrometry-based method for colistin susceptibility testing in Escherichia coli

Antimicrobial Susceptibility Testing for Colistin: Extended Application of Novel Quantitative and Morphologic Assay Using Scanning Electron Microscopy

Background

Colistin (Polymyxin E) has reemerged in the treatment of MDR Gram-negative infections. Traditional Colistin AST methods have long turnaround times and are cumbersome for routine use. We present a SEM-AST technique enabling rapid detection of Colistin resistance through direct observation of morphological and quantitative changes in bacteria exposed to Colistin.

Methods

Forty-four Gram-negative reference organisms were chosen based on their Colistin susceptibility profiles. Bacterial suspensions of ∼107 CFU/mL were exposed to Colistin at EUCAST-ECOFF, with controls not exposed, incubated at 37°C, and then sampled at 0, 15, 30, 60, and 120 minutes. Phosphotungstic Acid (PTA) staining was applied, followed by SEM imaging using Hitachi TM4000PlusII-Tabletop-SEM at ×2000, ×5000 and ×7000 magnifications. Bacterial viability analysis was performed for all conditions by quantifying viable and dead organisms based on PTA-staining and morphologic changes.

Results

We identified a significant drop in the percentage of viable organisms starting 30 minutes after exposure in susceptible strains, as compared to nonsignificant changes in resistant strains across all tested organisms. The killing effect of Colistin was best observed after 120 minutes of incubation with the antibiotic, with significant changes in morphologic features, including bacterial inflation, fusion, and lysis, observed as early as 30 minutes. Our observation matched the results of the gold standard-based broth microdilution method.

Conclusions

We provide an extended application of the proof of concept for the utilization of the SEM-AST assay for Colistin for a number of clinically relevant bacterial species, providing a rapid and reliable susceptibility profile for a critical antibiotic.

Metabolism-Triggered Plasmonic Nanosensor for Bacterial Detection and Antimicrobial Susceptibility Testing of Clinical Isolates

Antimicrobial resistance (AMR) is predicted to become the leading cause of death worldwide in the coming decades. Rapid and on-site antibiotic susceptibility testing (AST) is crucial for guiding appropriate antibiotic choices to combat AMR. With this in mind, we have designed a simple and efficient plasmonic nanosensor consisting of Cu2+ and cysteine-modified AuNP (Au/Cys) that utilizes the metabolic activity of bacteria toward Cu2+ for bacterial detection and AST. When Cu2+ is present, it induces the aggregation of Au/Cys. However, in the presence of bacteria, Cu2+ is metabolized to varying extents, resulting in distinct levels of aggregation. Moreover, the metabolic activity of bacteria can be influenced by their antibiotic susceptibility, allowing us to differentiate between susceptible and resistant strains through direct color changes from the Cu2+-Au/Cys platform over approximately 3 h. These color changes can be easily detected using naked-eye observation, smartphone analysis, or absorption readout. We have validated the platform using four clinical isolates and six types of antibiotics, demonstrating a clinical sensitivity and specificity of 95.8%. Given its simplicity, low cost, high speed, and high accuracy, the plasmonic nanosensor holds great potential for point-of-care detection of antibiotic susceptibility across various settings.

Rapid determination of colistin resistance in Klebsiella pneumoniae by MALDI-TOF peak based machine learning algorithm with MATLAB

INTRODUCTION

To date, limited data exist on demonstrating the usefulness of machine learning (ML) algorithms applied to MALDI-TOF in determining colistin resistance among Klebsiella pneumoniae. We aimed to detect colistin resistance in K. pneumoniae using MATLAB on MALDI-TOF database.

MATERIALS AND METHODS

A total of 260 K. pneumoniae isolates were collected. Three ML models, namely, linear discriminant analysis (LDA), support vector machine, and Ensemble were used as ML algorithms and applied to training data set.

RESULTS

The accuracies for the training phase with 200 isolates were found to be 99.3%, 93.1%, and 88.3% for LDA, support vector machine, and Ensemble models, respectively. Accuracy, sensitivity, specificity, and precision values for LDA in the application test set with 60 K. pneumoniae isolates were 81.6%, 66.7%, 91.7%, and 84.2%, respectively.

CONCLUSION

This study provides a rapid and accurate MALDI-TOF MS screening assay for clinical practice in identifying colistin resistance in K. pneumoniae.

First-in-human application of double-stranded RNA bacteriophage in the treatment of pulmonary Pseudomonas aeruginosa infection

A double-stranded RNA (dsRNA) phage phiYY is able to kill a pyomelanin-producing Pseudomonas aeruginosa strain, which was isolated from a 40-year-old man with interstitial lung disease (ILD) and chronic lung infection. Phage therapy was used as a last resort for this patient. The three-course nebulized phiYY treatment was used to reduce the bacterial burden and clinical symptoms of the patient. Recurrences of P. aeruginosa infections were observed 1-3 days post phage therapy. The recurrent isolates exhibited distinct antibiotic-susceptibility profiles compared with the original strain yet were still susceptible to phiYY. This assay represents the application of dsRNA phage in the treatment of chronic lung infection, albeit the safety and efficacy of the dsRNA phage require further assessment.