Phylogenetic analysis of Schistosoma mansoni in an infected population from two governorates in Egypt

Document Type : Original Article

Authors

1 Parasitology department, Medical research institute, Alexandria University

2 Department of Parasitology, Medical Research Institute, University of Alexandria, Egypt.

3 medical laboratory science college, Upper Nile University, South Sudan ,Juba

4 Colleague of molecular Biology, Applied Medical Chemistry, Medical Technology Center, Medical Research Institute.

5 Department of Parasitology, Medical Research Institute, University of Alexandria, Egypt

Abstract

Background: Data scarcity significantly hinders comprehensive phylogenetic analyses of of S.mansoni. This limitation impedes our understanding of its evolutionary history, population structure, and the emergence of drug resistance. Addressing this gap through increased genomic sampling is crucial for robust evolutionary inferences and effective control strategies
Objectives: The present work aimed to appraise the genetic diversity of S. mansoni in two Egyptian governorates.
Subjects and Methods: Schistosoma eggs were detected using the Kato–Katz method in a total of 238 faecal samples from the two areas. From 33 positive samples, cytochrome c oxidase (cox-1) gene of 9 random cases were detected using conventional PCR, and sequenced from the mitochondrial DNA of S. mansoni. The alignment results were subsequently used to construct a phylogenetic tree via the neighbour-joining method in the MEGA6 program.
Results: The overall detection rate of S. mansoni in the study population was 13.9% representing 14.1%, and 13.6% in Kafr El Sheikh and El-Behira governorates, respectively. Alignment analysis of S. mansoni in the two governorates revealed three closely related clusters. One of the sequences was submitted to GenBank under accession number MW784615 (https://blast.ncbi.nlm.nih.gov/Blast.cgi#alnHdr_532139118).
Conclusions: Phylogenetic analysis revealed minimal genetic diversity of S. mansoni isolates from the two examined populations in Kafr Elsheikh and Behira Governorates.

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