Cultivation-independent approach for the direct detection of bacteria in human clinical specimens as a tool for analysing culture-negative samples: a prospective study

Abstract

Administration of empirical antibiotic therapy prior to microbiological diagnosis is thought to be associated the failure of subsequent bacterial growth in culture. The aim of this study was to detect bacterial pathogens via direct amplification and sequencing of the 16S rDNA gene in samples showing negative culture results as alternative diagnostic tools to troubleshoot difficult samples. Twenty-three (7.66 %) positive samples were detected, most of which were monomicrobial infections; 15 of the cases were identified as HAIs, 6 had catheter colonisation, and 2 had sample colonisation. The pathogens identified included Escherichia, Salmonella, Pseudomonas spp., Enterococcus spp. and coagulase-negative staphylococci (CoNS). The most frequent infections were bacteraemia and urinary tract infection, but meningitis, warm infection and soft tissue infection were also documented. These findings emphasise the efficacy and usefulness of molecular diagnosis, thus 16S rDNA gene analysis is strongly indicated by HAIs diagnostics.

Keywords: 16S rDNA; Broad-range PCR; Culture-negative; Direct sequencing; Hospital-acquired infections.

Fig. 1

Bacteria identification to the species level by broad-range 16S rDNA PCR and sequencing from 19 samples with negative culture. This general tree was generated using the neighbour-joining (NJ) with the Tamura–Nei model. The numbers shown at the branch point indicate bootstrap values. The dataset was subjected to 1000 bootstrap replications. The sequences were selected from the GenBank database, and their accession numbers are listed in brackets. Sequences with an asterisk correspond with the clinical samples from this study, and the sequence accession numbers are GenBank KJ437454 to KJ437472. All the sequences could be an assign unambiguously to a genus. The species designation was determining with the closest genetic identification based on GenBank sequence analysis