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Modern molecular diagnostic approaches in the diagnostic microbiological laboratory like real-time quantitative polymerase chain reaction (qPCR) have led to a considerable increase of diagnostic sensitivity. They usually outperform the diagnostic sensitivity of culture-based approaches. Culture-based diagnostics were found to be insufficiently sensitive for the assessment of the composition of biofilms in chronic wounds and poorly standardized for screenings for enteric colonization with multi-drug resistant bacteria. However, the increased sensitivity of qPCR causes interpretative challenges regarding the attribution of etiological relevance to individual pathogen species in case of multiple detections of facultative pathogenic microorganisms in primarily non-sterile sample materials. This is particularly the case in high-endemicity settings, where continuous exposition to respective microorganisms leads to immunological adaptation and semi-resistance while considerable disease would result in case of exposition of a non-adapted population. While biofilms in chronic wounds show higher pathogenic potential in case of multi-species composition, detection of multiple pathogens in respiratory samples is much more difficult to interpret and asymptomatic enteric colonization with facultative pathogenic microorganisms is frequently observed in high endemicity settings. For respiratory samples and stool samples, cycle-threshold-value-based semi-quantitative interpretation of qPCR results has been suggested. Etiological relevance is assumed if cycle-threshold values are low, suggesting high pathogen loads. Although the procedure is challenged by lacking standardization and methodical issues, first evaluations have led to promising results. Future studies should aim at generally acceptable quantitative cut-off values to allow discrimination of asymptomatic colonization from clinically relevant infection.

More Pathogenicity or Just More Pathogens?—On the Interpretation Problem of Multiple Pathogen Detections with Diagnostic Multiplex Assays