Real-time PCR as a Diagnostic Tool for Bacterial Diseases

Max Maurin


Expert Rev Mol Diagn. 2012;12(7):731-754. 

In This Article

Abstract and Introduction


In recent years, quantitative real-time PCR tests have been extensively developed in clinical microbiology laboratories for routine diagnosis of infectious diseases, particularly bacterial diseases. This molecular tool is well-suited for the rapid detection of bacteria directly in clinical specimens, allowing early, sensitive and specific laboratory confirmation of related diseases. It is particularly suitable for the diagnosis of infections caused by fastidious growth species, and the number of these pathogens has increased recently. This method also allows a rapid assessment of the presence of antibiotic resistance genes or gene mutations. Although this genetic approach is not always predictive of phenotypic resistances, in specific situations it may help to optimize the therapeutic management of patients. Finally, an approach combining the detection of pathogens, their mechanisms of antibiotic resistance, their virulence factors and bacterial load in clinical samples could lead to profound changes in the care of these infected patients.


This review will focus on recent advances in the development of quantitative real-time PCR (qPCR)-based diagnostic tools allowing detection and optional quantification of bacterial DNA in clinical specimens. The authors will describe the existing and potential contributions of qPCR tests for diagnosis, prognosis and treatment of diseases caused by specific bacterial species, including assessment of the antibiotic susceptibilities of these pathogens. Previous reviews have already addressed these issues.[1–3] The author's goal is to describe the latest advances in this area, citing the most recent and relevant publications, without attempting to be exhaustive. Only qPCR tests applied to human specimens will be studied. The article aims to highlight the many possibilities offered by these new techniques, and also the low number of solutions marketed as compared with potential applications, as evidenced by the large number of in-house tests developed in this area (Table 1).