AbstractParamphistomes are parasites of domestic and wild ruminants, the effects of which in animal health remain underestimated. Very few studies in Africa have been done using molecular techniques to resolve situations associated with taxonomical groupings and epidemiology of these parasites. In this study, the genetic variability of nine representative paramphistome isolates collected from southern African countries, namely Botswana, South Africa, Zambia and Zimbabwe, was assessed using both morphological and internal transcribed spacer 2 (ITS2) rDNA sequence data. Morphological characterization and identification were carried out using median sagittal sections of the paramphistomes. DNA of the individual paramphistomes was isolated, the ITS2 rDNA was amplified, purified and sequenced. The sequences were submitted to GenBank, which assigned them the following accession numbers: KP639631, KP639630, KP639632, KP639633, KP639634, KP639635, KP639636, KP639637 and KP639638. These sequences were used for phylogenetic analysis using MEGA 6. Morphological characterization revealed three species of paramphistomes belonging to three different sub-families: one Stephanopharynx compactus isolate, a member of the Stephanopharyngidae sub-family; one Carmyerius dollfusi isolate, a member of the Gastrothylacidae sub-family; and seven Calicophoron microbothrium isolates belonging to the Paramphistomidae sub-family. ITS2 sequence analysis using BlastN results indicated that this is the first report of S. compactus (KP639630) and C. dollfusi (KP639636). Phylogenetic reconstruction of the paramphistome isolates revealed three separate clades representing the three species. However, the clade with all the C. microbothrium isolates was the only one that was supported by a higher bootstrap value of 92%, although there was no differentiation of the isolates according to geographical locations. The low divergence values on the ITS2 sequences of the C. microbothrium isolates indicate that ITS rDNA sequences can be used as a molecular tool to infer knowledge for resolving taxonomic groupings.
PCR identification of Fusarium genus based on nuclear ribosomal-DNA sequence data
