Frontiers in Microbiology (Mar 2019)
Molecular Techniques Complement Culture-Based Assessment of Bacteria Composition in Mixed Biofilms of Urinary Tract Catheter-Related Samples
Abstract
Urinary or ureteral catheter insertion remains one of the most common urological procedures, yet is considered a predisposing factor for urinary tract infection. Diverse bacterial consortia adhere to foreign body surfaces and create various difficult to treat biofilm structures. We analyzed 347 urinary catheter- and stent-related samples, treated with sonication, using both routine culture and broad-range 16S rDNA PCR followed by Denaturing Gradient Gel Electrophoresis and Sanger sequencing (PCR-DGGE-S). In 29 selected samples, 16S rRNA amplicon Illumina sequencing was performed. The results of all methods were compared. In 338 positive samples, from which 86.1% were polybacterial, 1,295 representatives of 153 unique OTUs were detected. Gram-positive microbes were found in 46.5 and 59.1% of catheter- and stent-related samples, respectively. PCR-DGGE-S was shown as a feasible method with higher overall specificity (95 vs. 85%, p < 0.01) though lower sensitivity (50 vs. 69%, p < 0.01) in comparison to standard culture. Molecular methods considerably widened a spectrum of microbes detected in biofilms, including the very prevalent emerging opportunistic pathogen Actinotignum schaalii. Using massive parallel sequencing as a reference method in selected specimens, culture combined with PCR-DGGE was shown to be an efficient and reliable tool for determining the composition of urinary catheter-related biofilms. This might be applicable particularly to immunocompromised patients, in whom catheter-colonizing bacteria may lead to severe infectious complications. For the first time, broad-range molecular detection sensitivity and specificity were evaluated in this setting. This study extends the knowledge of biofilm consortia composition by analyzing large urinary catheter and stent sample sets using both molecular and culture techniques, including the widest dataset of catheter-related samples characterized by 16S rRNA amplicon Illumina sequencing.
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