Discrimination of Mixed Infections of Echinococcus Species Based on in Silico Sequence Analysis: A New Way of Reflecting Overlapped Strains in Indigenous Areas

Abstract

Objectives: Hydatidosis, as a cyclo-zoonotic indigenous disease, is marked by various strains and multiple infections around the world where different overlapping cycles of Echinococcus spp. are explicitly circulating among intermediate and definitive hosts. One of the current challenges in Echinococcus taxonomy is associated with the imprecise identification of dual infections in endemic regions. The aim of this study was to genotype Echinococcus strains, particularly those ignored during mixed infections, by employing phylogenetic analysis in order to determine the accurate status of the parasite in endemic areas. Methods: 60 isolates were collected from the liver and lungs of twenty humans, fifteen sheep, fifteen goat, and ten cattle during 2012 -14 in Markazi province, Iran. Subsequently, the extraction of DNA was performed, followed by amplification and identification of the DNA through both PCRfor internal transcribed spacer 1(ITS1-rDNA) of ribosomal DNA and restriction fragment length polymorphism (RFLP) using two endonuclease enzymes: Rsa1 and Hpall. Then, the isolates were directly sequenced in order to accomplish the definite identification of strains/haplotypes. In addition, the mixed infections were analyzed by mixed sequences reader (MSR). Results: The RFLP, phylogenetic analyses of ITSl-rDNA sequences and MSA finding based on analyzed chromatograms strongly revealed the sheep strain (n = 58) and two mixed infection Gl and G6 genotypes (n = 2). The five specific haplotypes that represent moderate diversity indices were identified. The haplotype diversity was estimated to be 0.522, with a nucleotide diversity of 0.02. Conclusions: The G1 was reported to be the dominant strain in the central regions of Iran; however, the first dual discrimination of Gl and G6 genotypes in these regions showed that a sheep-camel/dog life cycle is circulating in central Iran. The current findings can facilitate the parasite taxonomic classification based on in silico analysis particularly about those that are neglected in dual infections. Additional studies are highly needed with a greater sample size and in various regions of Iran.