Dataset for comparative analysis of precision metagenomics and traditional methods in urinary tract infection diagnosticsNCBI
This study presents a comprehensive dataset comparing three diagnostic methodologies—microbial culture, polymerase chain reaction (PCR), and precision metagenomics (precision metagenomics)—for the detection and classification of uropathogens in urine samples from patients with suspected urinary trac...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-04-01
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| Series: | Data in Brief |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235234092500071X |
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| Summary: | This study presents a comprehensive dataset comparing three diagnostic methodologies—microbial culture, polymerase chain reaction (PCR), and precision metagenomics (precision metagenomics)—for the detection and classification of uropathogens in urine samples from patients with suspected urinary tract infections (UTIs). While microbial culture remains the gold standard for UTI diagnosis, it has limitations in sensitivity, particularly for fastidious or non-culturable microorganisms. PCR offers higher sensitivity but is restricted to pre-targeted organisms, limiting its diagnostic range. Precision Metagenomics, a target-agnostic sequencing method, provides a more inclusive approach by enabling the identification of a broad spectrum of pathogens, including bacteria, viruses, fungi, and parasites, without prior knowledge of the organisms. The dataset includes 47 urine samples, each analyzed by microbial culture, PCR, and precision metagenomics, followed by bioinformatic classification using the Explify® platform. precision metagenomics identified significantly more uropathogens (62 distinct organisms) compared to PCR (19 organisms) and microbial culture (13 organisms), with 98 % of samples testing positive for polymicrobial infections via precision metagenomics. The precision metagenomics method demonstrated superior diagnostic yield by detecting pathogens that were missed by both microbial culture and PCR, particularly in culture-negative and PCR-negative cases. This dataset holds substantial reuse potential for further research into the microbiome of urinary tract infections, pathogen discovery, antimicrobial resistance studies, and the development of more accurate diagnostic models for UTI management. By offering insights into both polymicrobial infections and rare pathogens, this dataset supports the advancement of diagnostic strategies for complex and chronic UTIs. |
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| ISSN: | 2352-3409 |