Genome-wide locus sequence typing (GLST) of eukaryotic pathogens
Schwabl, P.; Maiguashca Sanchez, J.; Costales, J. A.; Ocana, S.; Segovia, M.; Carrasco, H. J.; Hernandez, C.; Ramírez, J. D.; Lewis, M. D.; Grijalva, M. J.; Llewellyn, M. S.
Show abstract
Analysis of genetic polymorphism is a powerful tool for epidemiological surveillance and research. Powerful inference from pathogen genetic variation, however, is often restrained by limited access to representative target DNA, especially in the study of obligate parasitic species for which ex vivo culture is resource-intensive or bias-prone. Modern sequence capture methods enable pathogen genetic variation to be analyzed directly from vector/host material but are often too complex and expensive for resource-poor settings where infectious diseases prevail. This study proposes a simple, cost-effective genome-wide locus sequence typing (GLST) tool based on massive parallel amplification of information hotspots throughout the target pathogen genome. The multiplexed polymerase chain reaction amplifies hundreds of different, user-defined genetic targets in a single reaction tube, and subsequent agarose gel-based clean-up and barcoding completes library preparation at under 4 USD per sample. Approximately 100 libraries can be sequenced together in one Illumina MiSeq run. Our study generates a flexible GLST primer panel design workflow for Trypanosoma cruzi, the parasitic agent of Chagas disease. We successfully apply our 203-target GLST panel to direct, culture-free metagenomic extracts from triatomine vectors containing a minimum of 3.69 pg/l T. cruzi DNA and further elaborate on method performance by sequencing GLST libraries from T. cruzi reference clones representing discrete typing units (DTUs) TcI, TcIII, TcIV, and TcVI. The 780 SNP sites we identify in the sample set repeatably distinguish parasites infecting sympatric vectors and detect correlations between genetic and geographic distances at regional (< 150 km) as well as continental scales. The markers also clearly separate DTUs. We discuss the advantages, limitations and prospects of our method across a spectrum of epidemiological research.
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