LEGIOLOUP: Design of a rapid diagnostic system for the simultaneous detection of viable cells of Legionella spp., L. pneumophila and other pathogenic Legionella species using qPCR combined with PMA.
Project Description
Legionellosis is a disease with significant media impact because it is often associated with community outbreaks linked to domestic hot water systems, cooling towers, jacuzzis, ornamental fountains and similar installations. Although the standard method for detecting the pathogen is culture (UNE-EN ISO 11731), it presents several limitations, such as the long waiting time to obtain results, the precautions required to ensure the viability of microorganisms in the sample, the inability to dectect viable but non-culturable bacteria and the difficulty of isolating the bacterium in samples with a high load of accompanying microbiota.
Distinguishing between live and dead cells is essential when detecting Legionella spp., since identifying DNA from this microorganism does not necessarily indicate the presence of a viable population capable of causing infection. The main objective of the project is therefore to develop, optimize and validate a protocol for the simultaneous detection and quantification of viable —an thus infective— cells from three pathogenic Legionella species (L. pneumophila, l. micdaeii and L. longbeachae) using multiplex qPCR combined with a PMA pretreatment.
This approach aims to overcome current technical limtiations by creating a new method —currently unavailable on the markt— for rapid, sensitive and specific detection of viable but non-culturable cells from the three pathogenic Legionella species mentioned. The method combines multiplex PCR with PMA pretreatment using DNA-intercalating agents (such as propidium monoazide, PMA). In this way, it would enable the simultaneous diagnosis of multiple viable pathogenic Legionella species in under 8 hours, using either water samples or clinical samples.
This protocol would also allow us to efficiently evaluate disinfection treatments, since it enables us to distinguish potentially inefective VBNC forms that may appear afterwards —forms that cannot be detected using other methods—.
2016-2017
TOTAL: 128.375 €
Co-funded by the Valencian Institute of Business Competitiveness (IVACE) and by Funds under the 2016 Business I+D+I Plan.