Totally, 200 dung beetles were randomly collected in June 2017 from the highlands of Taleqan County, Alborz Province, Iran (36.1748° N, 50.7650° E), a common passage of jackals, foxes and other canids and felids (Fig. 5) . Wild boar, dog and livestock dung pitfall traps were used to capture dung beetles, previously described by Du Toit et al. . Trapped dung beetles were transferred to the Helminthology Lab of the Department of Medical Parasitology and Mycology, Tehran University of Medical Sciences, Tehran, Iran, using ventilated containers.
Species identification of the dung beetles
At the time of the assessment, most of the dung beetles were still alive. Therefore, dung beetles were stored in a refrigerator with autoclaved soil for 2 h to immobilize them. Then, species and sexes of the collected beetles were identified taxonomically, using entomology keys .
Morphological analysis of the recovered larvae
Beetles were dissected in normal saline solution and carefully studied for the presence of parasites with special focuses on larval stages using stereomicroscope. The beetles have been reported individually as positive or negative for larval stages of helminths. For positive beetles, larvae were removed and transferred into normal saline on ice for 1 h to relax and immobilize . Removed larvae were transferred into lactophenol and 70% ethanol for morphological and molecular studies. Morphological characteristics of the isolates were recorded carefully using camera lucida equipped microscope at 400× magnification. Identification was comparatively carried out based on taxonomic key references .
Molecular analysis of the recovered larvae
Ethanol preserved larvae were washed three times with sterile distilled water by centrifugation at 5000× g for 5 min to remove ethanol. Then, larvae were subjected to five cycles of freezing in liquid nitrogen and thawing in boiling water. Approximately 300 mg of glass beads (0.5 mm in diameter) were added to the larvae and shaken intensively for 5 min. Then, genomic DNA was extracted using genomic DNA extraction kit (GeneAll Exgene, South Korea) according to the manufacturer’s instructions and stored at -20 °C until use. The DNA concentration was assessed spectrometrically (NanoDrop ND-1000, Thermo Fischer Scientific, USA) at 260 nm. The 260/280 absorbance ratios of the DNA samples included 1.8–2.0, indicating no major protein contaminations.
Amplification of the cox1 gene and sequencing of the amplicons
Polymerase chain reaction (PCR) on cox1 gene was carried out using primer set of NTF (5’-TGATTGGTGGTTTTGGTAA-3’) and NTR (5’-ATAAGTACGAGTATCAATATC-3’) as previously described for Spirurida . The PCR amplification was carried out in a final reaction mixture of 50 µL, including 25 µL of 2x red PCR master mix (Ampliqon, Denmark), 2 µL of each primer (10 pmol), 5 μL of the extracted DNA and 16 μl of sterile distilled water. A negative control (distilled water) and positive control (extracted DNA from S. lupi provided by the Faculty of Veterinary Medicine, University of Tehran) were used in each set. Amplification was carried out using PeqSTAR Thermal Cycler (PeqLab, Germany) using the following cycling protocol of initial denaturation at 94 °C for 7 min, followed by 40 cycles of denaturation at 94 °C for 1 min, annealing at 58 °C for 1 min and extension at 72 °C for 1 min. Final extension was carried out at 72 °C for 10 min. Amplified products were electrophoresed on 1.5% agarose gels and visualized using UV transilluminator. The PCR products were sequenced using Sanger method in both directions (Bioneer, South Korea).
Sequences were edited and trimmed using Chromas software v.2.6.1 (Chromas, Australia). Analysis of the sequencing data was carried out using BLAST program and NCBI databases (http://www.ncbi.nlm.nih.gov/). Multiple sequence alignments were carried out using Clustal W method and BioEdit software v.7.1 (http://www.mbio.ncsu.edu/bioedit/bioedit.html) and results were compared to sequence results from GenBank database.
Sequences were edited and compared to entries from NCBI GenBank for further analysis. The best-fit model of nucleotide substitution was statistically selected by the MEGA software v.6.0 (Pennsylvania State University, USA) . The phylogenetic tree of Spirocerca spp. was constructed using the Maximum Likelihood (ML) method in agreement with Hasegawa-Kishino-Yano model with uniform rates for transitions and transversions. Bootstraps of 1,000 replicates were used for the assessment of topology reliability of the trees.