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Urinary tract infections (UTIs) are among the most common bacterial infections world wide, impacting 405 million people and resulting in significant morbidity and healthcare costs. The routine diagnostic test, urine culture, takes 2-4 days to identify the pathogen and determine an appropriate antibiotic. This approach can lead to suboptimal clinical management, high antibiotic prescription rates, and improper use, which in turn foster antimicrobial resistance (AMR).
Clinical metagenomics, which involves DNA sequencing of patient samples, offers a promising opportunity to revolutionize UTI diagnosis and treatment. Using Oxford Nanopore Technology (ONT), sequencing and data analysis can be performed in real-time. However, a crucial step for clinical application is the depletion of abundant human DNA, which dominates microbial DNA, as well as the removal of impurities and inhibitors present in the urine sample. Existing DNA extraction methods are not suitable for real-time sequencing because of their lengthy turnaround times, high costs, and challenges in managing clinical samples.
The thesis aimed to develop, evaluate, and optimize DNA extraction methods for rapid pathogen identification and antibiotic susceptibility profiling in UTI diagnostics. We developed a culture-independent DNA extraction method that selectively removes human DNA and enriches microbial DNA. This method is accurate, fast, and cost-effective for clinical samples.
In a proof-of-concept (PoC) study, urine samples from 78 patients with complicated UTI (cUTI) were evaluated using 11 different DNA extraction methods. The methods encompassed combinations of HL-SAN and M-SAN endonucleases, enzymatic and mechanical lysis strategies, and column and magnetic bead based DNA extraction techniques. Compared with routine culture-based diagnostic assays, the optimized method yielded the best pathogen identification performance (accuracy 99%, sensitivity 99%, specificity 100%) and antibiotic-susceptibility predictions (accuracy 90%, sensitivity 68%, specificity 95%). The method is also rapid, with a turnaround time of approximately 4 hours and a per sample cost of $36. Following modifications, a prospective validation study was carried out on an additional 296 cUTI samples, confirming pathogen identification performance consistent with the PoC study and slightly improved antibiotic susceptibility predictions. The limit of detection was 9.3 × 103 CFU/mL. The modifications also enabled the detection of Candida species, indicating the potential for comprehensive pathogen identification.
The developed method’s usefulness extends beyond cUTI samples, as shown by the PoC study on blood cultures for diagnosing bloodstream infections. In this study, key parameters like saponin, endonucleases, and salt concentrations were fine tuned for the blood cultures. The optimized approach successfully depleted host material in blood cultures.
In conclusion, the culture-independent sample preparation methods tackle the crucial challenge of DNA extraction from clinical samples. They provide a comprehensive and practical strategy to improve the diagnosis and management of UTIs and bloodstream infections, and to promote prudent antibiotic use and AMR stewardship. While additional validation is necessary, these findings show strong potential for broad clinical application and the potential to improve patient care.