Infection by soil transmitted helminths (geohelminths) currently affects over 1 billion people across the world. These parasites’ ability to persist in the environment as eggs and larvae results in high reinfection rates in exposed human populations, greatly reducing the long term efficiency of antihelminthic drug treatments. Effective containment measures call for the identification of geohelminth reservoirs.

Morphology based diagnostic methods are time intensive and their effectiveness depends on the operative’s expertise, which greatly reduces their applicability at large scale studies.

Metabarcoding analysis consists on PCR amplification of diagnostic sequences, known as molecular markers, from bulk DNA extractions of environmental samples. These markers are then matched against reference databases to determine the clades present sampled environment. This is a fast, accurate, and highly scalable method to characterize the species composition of a biological community.

My master’s thesis aims to develop an alternative method of geohelminth detection from soil samples, taking advantage of NGS technologies and meta barcoding analysis. We seek to develop a bioinformatic tool estimate the probability of occurrence of a set of helminth species of interest. We expect this tool will be a useful asset for the diagnostic of geohelminth reservoirs and the development of adequate preventive measures.