A hospital qPCR-based survey of 10 gastrointestinal parasites in routine diagnostic screening, Marseille, France

Abstract

There is a scarcity of recent epidemiological data on intestinal parasitic infections in France. We conducted a prospective study aimed at estimating the prevalence of 10 enteric parasites in Marseille, France, using real-time polymerase chain reaction (PCR)-based diagnosis. A total of 643 faeces from 488 patients referred to the Parasitology-Mycology Laboratory of the University Hospital of Marseille over a 6 months period were included. DNA was extracted using a semi-automated method. Parasites of interest were detected using singleplex quantitative PCRs (qPCRs). For positive samples, the Blastocystis subtype was determined by sequence analysis. During the study, the overall prevalence of enteric parasites was 17%. Blastocystis sp. was the most frequent species (10.5%), followed by Dientamoeba fragilis (2.3%) and Giardia intestinalis (2.3%). The prevalence of other parasites was <1% each. The ST3 Blastocystis subtype was predominant (43.6%) and the other subtypes identified were ST1, ST2, ST4 and ST6. This is the first time that a qPCR-based diagnosis has been used to survey the prevalence of 10 enteric parasites in a French University Hospital. This study confirms that fast, specific, sensitive and simultaneous detection in a single stool sample by qPCR clearly outperforms conventional microscopy-based diagnosis. Furthermore, qPCR is particularly well suited to surveying gastroenteritis agents.

Keywords: Enteric parasites; France; microsporidia; protozoa; qPCR.

Fig. 1.

Results obtained after quantification by qPCR. The curve representing the number of gene copies, as a function of qPCR Ct values, in positive samples for each of the eight enteric parasites tested.

Fig. 2.

Phylogenetic relationship between the SSD rDNA sequence of Blastocystis. The molecular phylogenetic analysis was carried out using the Maximum Likelihood method based on the Tamura–Nei model. ST, subtype; (n): patient number in case of multiple samples.