Open Access
Issue
Parasite
Volume 21, 2014
Article Number 50
Number of page(s) 8
DOI https://doi.org/10.1051/parasite/2014041
Published online 06 October 2014

© A. Titi et al., published by EDP Sciences, 2014

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Materials and methods

Area of study

Worms were collected weekly over a 24-month period (September 2010–August 2012) at the slaughterhouse of Jijel. Located on mainly siliceous subsoil, this department (wilaya) forms part of the coastal band and its altitude is often less than 300 m. Its Mediterranean climate is sufficiently humid, with the mean monthly temperature varying from 8.4 °C to 27.7 °C and mean annual rainfall varying from 1103 to 1252 mm during the study period (Table 1). All cattle slaughtered (local breed, Guelmoise or Brown Atlas) originated from farms located within a 50-km radius around the slaughterhouse. These animals were reared under extensive conditions throughout the year in family structures (a few cattle per farm). Benzimidazole-type anthelmintics against intestinal and lung strongylids were mainly administered twice a year to cattle. In contrast, paramphistomosis was not treated.

Table 1.

Monthly temperatures and rainfall in the department (wilaya) of Jijel during the two-year study (September 2010–August 2012).

Parasitological investigations

A total of 1523 rumens from 1402 bull calves (<18 months in age) and 121 older cows (>5 years) were emptied and washed. Adult parasites collected from each rumen were placed in a polyethylene bag containing a saline solution (0.9% NaCl, 0.45% glucose). The parasites were transported to the laboratory at 37 ± 2 °C and immediately counted by two people.

Prevalence of infection was calculated using the ratio: number of infected animals/total number of cattle × 100, and was separately expressed for each category of infected animals (bull calves or cows) and each season (Tables 2 and 3). A χ2 test was used to determine the influence of season on these values. The intensity of paramphistome infection was the second parameter and was also expressed for each category of infected animals and each season (Tables 2 and 3). Normality of parasite burdens was analysed using the Shapiro-Wilk normality test [37]. As their distribution was not normal, the Kruskal-Wallis test was used to establish levels of statistical significance. All analyses were performed using XLSTAT software (http://www.xlstat.com/fr).

Table 2.

Prevalence and intensity of bovine paramphistomosis in bull calves for each season during the two-year study.

Table 3.

Prevalence and intensity of bovine paramphistomosis in old cows for each season during the two-year study.

Table 2 gives the prevalence and intensity of infection noted in bull calves for each season: autumn (September–November), winter (December–February), spring (March–May) and summer (June–August). A similar presentation is used for old cows in Table 3. To compare the distribution of parasite burdens noted for bull calves and cows in relation to season, individual values were classified into one of the following categories: 1–50, 51–100, 101–150, 151–200, 201–250, 251–300, 301–350, 351–400 and >400 worms per infected ruminant. The values recorded for each category during the corresponding seasons of both years were pooled and the results are shown in Figure 1.

thumbnail Figure 1.

Numerical distribution of parasite burdens in relation to prevalence of bovine paramphistomosis for autumn (1a), winter (1b), spring (1c) and summer (1d). To build these graphs, the values obtained for corresponding seasons of both years were pooled.

Molecular identification of paramphistomids

Eleven adult paramphistomes were collected from the rumens of cattle slaughtered in Jijel (3 worms) and in three other neighbouring abattoirs: Constantine (1 worm), El Tarf (4 worms) and Setif (3 worms), with a single worm per infected ruminant. After collection, parasites were washed with physiological saline solution (0.9% NaCl) and fixed in 70% ethanol until their use for molecular identification.

Total DNA was extracted from each worm using the DNeasy® Tissue Kit (Qiagen) according to the manufacturer’s instructions. A Nanodrop ND-1000 spectrophotometer was used to quantify and check DNA purity. The internal transcribed spacer (ITS-2) fragment was amplified using the following primers: ITS2-F (5′-TGTGTCGATGAAGAGCGCAG-3′) and ITS2-R (5′-TGGTTAGTTTCTTTTCCTCCGC-3′) [16]. Amplification was performed in a 25-μL total reaction volume containing: 0.5 U Taq DNA polymerase (Qiagen), 5 μL 10× PCR buffer, 1 μL MgCl2 (1.5 mM), 0.8 μL dNTPs (0.2 mM) and 0.5 μL of each primer (20 ng/μL). A standard DNA concentration (500 ng/μL) was used for all PCR reactions. The PCR conditions were as follows: initial denaturation (10 min, 94 °C); 35 cycles, each comprising denaturation (60 s, 94 °C), annealing (90 s, 53 °C) and extension (60 s, 72 °C); final extension (10 min, 72 °C). PCR products were purified using MultiScreen® HTS-HV Filter Plates (Merck Millipore) and Sephadex® G-50 Superfine (Fisher Scientific), then sequenced using an ABI Prism BigDye® Terminator v1.1 Cycle Sequencing Ready Reaction Kit (Applied Biosystems), and run on an ABI 377 automated sequencer.

The sequences obtained were used to perform BLAST searches [2] via the National Center for Biotechnology Information’s GenBank database in order to ensure that parasite and other potential contaminating sequences had not been obtained in error. Sequences were then corrected and translated into amino acid sequences using the invertebrate mitochondrial genetic code and inspected for stop codons using SeqScape v2.5. Nucleotide sequences were multiply aligned using CLUSTAL X [42]. A unique sequence was obtained for each individual.

The new sequences have been deposited in GenBank as LN610457, LN610458 and LN610459.

Measurements of overall haplotypes and nucleotide diversity were calculated using DnaSP v5 [24]. Pairwise genetic diversity was calculated using Tamura and Nei’s three-parameter model [40] and Mega v5. Phylogenetic analyses were conducted by maximum likelihood (ML), maximum parsimony (MP) and neighbour-joining (NJ) using Mega v5 [23]. This analysis was subjected to 2000 bootstraps as a means of testing the reliability of individual branches within the generated tree. Paragonimus westermani (Kerbert, 1878) Braun, 1899 [5, 20] (AB354218.1) was nominated as the outgroup. The following GenBank data: AY790883.1, C. daubneyi; GU735640.1, Calicophoron microbothrium (Fischoeder, 1901) Eduardo, 1983 [9, 11]; and HM026462.1, Paramphistomum cervi (Zeder, 1790) Fischoeder, 1901 [11, 47] were included in the analysis in order to examine the topology of the tree.

The nomenclature used to identify paramphistome species was that adopted by Jones [17].

Results

Prevalence of bovine paramphistomosis

Annual prevalence of infection in bull calves (Table 2) was 14.6% and 14.5% during the first and second years, respectively. Seasonal variations were noted, with the lowest percentages in winter (8.2–9.0%) and the highest in summer 2011 (23.0%) and spring 2012 (23.1%). Prevalence values recorded in spring and summer during the first year were significantly greater (χ2 = 14.62, p < 0.01) than those noted in autumn and winter. A similar finding was also noted for the second year (χ2 = 12.86, p < 0.01). In contrast, the differences between values noted during the 2 years for a given season were not significant, whatever the type of season. In spite of the lower number of old cows slaughtered in Jijel (Table 3), high annual prevalences were recorded: 45.7% during the first and 41.9% during the second year. The differences among seasonal percentages during the 2 years were not significant. Similar results were also obtained when values noted during the 2 years for a given season were compared.

Cows were significantly more infected than bull calves during the first (χ2 = 31.17, p < 0.001) and second years (χ2 = 29.92, p < 0.001). This finding was also noted for each season considered separately (data not shown).

Parasite burdens

In bull calves (Table 2), the mean annual intensity recorded during the first and second years was 125.8 and 139.4 adult worms, respectively. Significant seasonal variations (first year: H = 16.68, p < 0.001; second year: H = 24.13, p < 0.001) were noted, with lower numbers of worms in spring and summer when the bull calves showed the highest prevalence values. In contrast, the differences between parasite burdens recorded for the corresponding seasons of both years were not significant, whatever the type of season. The mean annual intensity in old cows (Table 3) was clearly greater, with 313.8 and 272.9 adult worms counted during the first and second year, respectively. No significant differences among the four seasons for a given year or the corresponding seasons of both years were noted for this category of infected cattle.

When parasite burdens noted in old cows were compared with those from bull calves, the values were significantly greater in cows (first year: H = 33.42, p < 0.001; second year: H = 19.15, p < 0.001). Significant differences in relation to season were also noted for both springs, both summers and autumn 2010, while the other three differences were not significant (data not shown).

Figure 1 gives the numerical distribution of parasite burdens for both categories of infected ruminants in relation to season. In autumn (Fig. 1a) and winter (Fig. 1b), more than 200 paramphistomes were found in 31.8% (21/66) and 50% (15/30) of bull calves, respectively. Prevalences were lower in spring (Fig. 1c) and summer (Fig. 1d), as 9.2% (6/65) and 13.7% (8/58) of bull calves, respectively, contained more than 200 adult worms. In the case of old cows, the percentages were more variable. Burdens greater than 200 paramphistomes were noted in 44.4% (8/18) of cows in autumn, 100% (7/7) in winter, 44.4% (8/18) in spring and 58.8% (10/17) in summer.

Molecular identification of paramphistomid species

A data matrix of 428 bp was used in the analysis of the nuclear ribosomal ITS-2. The sequences were found to have strong similarity. The analysed region contained nine variable sites (seven parsimony informative sites), with an overall nucleotide diversity (π) of 0.009. Six different haplotypes were identified, with observed haplotype diversity (Hd) of 0.80 across all the studied taxa. In the sample from El Tarf, only one haplotype was observed. In contrast, in the samples from Setif and Jijel, different haplotypes were observed and were closely related, differing from each other by one or two base substitutions. The mean evolutionary diversity for the entire population was low (D = 0.009) and the coefficient of evolutionary differentiation (Cd) was 2.46.

Reconstruction of the evolutionary relationships between haplotypes using ITS-2 is presented in Figure 2. The three tree-building algorithms were largely congruent, with high bootstrap support values of 89% for ML, 86% for MP and 90% for NJ among the different taxa. The studied haplotypes split into two clades. The first clade regroups C. daubneyi and seven worms from the four departments (Constantine, El Tarf, Jijel and Setif); within this clade, C. daubneyi and the worms from El Tarf and Setif share the same haplotype. The second clade regroups P. cervi, C. microbothrium and four worms from Jijel and Setif; within this group, the worms from Jijel and Setif form a sister group with C. microbothrium.

thumbnail Figure 2.

ITS-2 tree based on neighbour-joining estimates with Paragonimus westermani as the outgroup. In blue, clade 1; in red: clade 2. Scale bar indicates the number of substitutions per sequence position.

Discussion

In bull calves slaughtered in Jijel, there was a significant effect of season on the prevalence and intensity of paramphistomosis. This seasonal effect is mainly due to the level of annual rainfall (1103–1252 mm, Table 1) and mild temperatures recorded in this coastal department, which creates a sufficiently humid and more temperate microclimate in spite of its Mediterranean type. This effect of season on the characteristics of cattle paramphistomoses in Jijel confirms the reports of different authors in temperate regions [3, 6, 7, 12, 39, 41] and subtropical or tropical countries [10, 15, 21, 34]. According to Hakalahti et al. [13], rainfall had a direct effect on the dynamics of parasite populations and, consequently, on disease transmission. As for fasciolosis [26, 31, 46], climatic conditions had a direct influence on the characteristics of C. daubneyi infection in the definitive and snail hosts of a given region. The significantly decreased prevalence noted for bull calves in autumn and winter might be due to the presence of numerous less than one-year-old individuals among the bull calves slaughtered during these periods. Owing to the death of numerous metacercariae encysted on vegetation during summer drying [27], most of these younger bull calves would not have enough time to become infected and/or harbour adult worms in their rumen before their slaughter. The progressive contamination of older bull calves (>12 months) during the next spring with metacercariae produced by the overwintering and/or spring snail generations [27, 28] and their progressive transformation into adults might explain the significantly lower parasite burdens noted in spring and summer, and the higher burdens during the next autumn and winter.

Contrary to bull calves, no significant seasonal effect on the characteristics of paramphistomosis was noted in old cows. This category of cattle was, however, more infected (41.9–45.7%) and contained high parasite burdens (a mean of 272–313 adult paramphistomes, Table 3). As the age of these slaughtered cows was more than 5 years, the most reliable explanation was an increasing accumulation of adult paramphistomes in their rumen during the past years in reason of repeated infections with metacercariae. However, another explanation, based on variability in the individual susceptibility of these cows to paramphistome infection, cannot be completely excluded. This last assumption is supported by the minimal and maximal individual burdens (84 and 1123 adult worms, respectively) found in the present study (data not shown). The high prevalence recorded for this category of cattle might be partly explained by the low number of these slaughtered cows (a total of 121 old cows instead of 1402 bull calves investigated during the two-year study).

The two paramphistome species, i.e. C. daubneyi and C. microbothrium, identified by molecular biology in the present study were already known in central Algeria [18, 19, 32]. As these two species were found in the coastal departments (El Tarf, Jijel) as well as on high plateaus of Atlas (Constantine, Setif; Fig. 2), their distribution is general in these four Algerian departments. The presence of both species in Jijel, for example, raises two fundamental questions. First, it is difficult to determine the importance of either paramphistomid in the definitive host because identification of all worms present in the rumen requires the use of PCR and, consequently, is expensive. Moreover, the possibility of cattle co-infections with both paramphistomids cannot be excluded. Secondly, the question of specific intermediate hosts (Galba truncatula Müller, 1774 [30] for C. daubneyi and Bulinus truncatus Audoin, 1827 [4] for C. microbothrium) merits close examination. Indeed, the presence of the bulinid in northeastern Algeria was not noted by Mekroud [27], Mekroud et al. [28] and Titi [45] during their field investigations. As the recruitment of slaughtered cattle was local (within a 50-km radius), it is necessary either to pursue investigations within these northeastern departments to find bulinid habitats, or to determine whether or not C. microbothrium uses another freshwater snail (another planorbid, for example) as a local intermediate host. Such examples of uncommon snail hosts have already been reported for F. hepatica, with Anisus leucostoma Millet, 1813 [29] and Omphiscola glabra Müller, 1774 [30] in central France [1] and B. truncatus in northern Tunisia [14].

In conclusion, bovine paramphistomosis existing in northeastern Algeria is dependent on seasons and is caused by at least two species: C. daubneyi and C. microbothrium. Further studies are still necessary (i) to determine the prevalence and intensity of infection caused by each paramphistome species in local cattle, and (ii) to specify the local intermediate host in the case of C. microbothrium.

Acknowledgments

The authors gratefully acknowledge Dr. J. Cook-Moreau for revising the English text.

References

  1. Abrous M, Rondelaud D, Dreyfuss G, Cabaret J. 1998. Unusual transmission of the liver fluke, Fasciola hepatica, by Lymnaea glabra or Planorbis leucostoma in France. Journal of Parasitology, 84, 1257–1259. [Google Scholar]
  2. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. 1990. Basic local alignment search tool. Journal of Molecular Biology, 215, 403–410. [CrossRef] [PubMed] [Google Scholar]
  3. Arias M, Lomba C, Dacal V, Vázquez L, Pedreira J, Francisco I, Piñeiro P, Cazapal-Monteiro C, Suárez JL, Díez-Baños P, Morrondo P, Sánchez-Andrade R, Paz-Silva A. 2011. Prevalence of mixed trematode infections in an abattoir receiving cattle from northern Portugal and north-west Spain. Veterinary Record, 168, 408–412. [CrossRef] [PubMed] [Google Scholar]
  4. Audouin V. 1827. Explication sommaire des planches de Mollusques de l’Égypte et de la Syrie, publiées par Jules-César Savigny, in Description de l’Égypte ou recueil des observations et des recherches qui ont été faites en Égypte pendant l’expédition de l’armée française, Panckoucke CLF, Editeur. 2nd édition, vol. 22: Histoire naturelle, Zoologie, Animaux invertébrés (suite). CLF Panckoucke: Paris, p 117–215. [Google Scholar]
  5. Braun M. 1899. Über Clinostomum Leidy. Zoologischer Anzeiger, 22, 489–493. [Google Scholar]
  6. Díaz P, Pedreira J, Sánchez-Andrade R, Suárez JL, Arias MS, Francisco I, Fernandez G, Díez-Baños P, Morrondo P, Paz-Silva A. 2007. Risk periods of infection by Calicophoron daubneyi (Digenea: Paramphistomata) in cattle from oceanic climate areas. Parasitology Research, 101, 339–342. [CrossRef] [PubMed] [Google Scholar]
  7. Díaz P, Paz-Silva A, Sánchez-Andrade R, Suárez JL, Pedreira J, Arias M, Díez-Baños P, Morrondo P. 2007. Assessment of climatic and orographic conditions on the infection by Calicophoron daubneyi and Dicrocoelium dendriticum in grazing beef cattle (NW Spain). Veterinary Parasitology, 149, 285–289. [CrossRef] [PubMed] [Google Scholar]
  8. Dinnik JA. 1962. Paramphistomum daubneyi sp.nov. from cattle and its snail host in the Kenya Highland. Parasitology, 52, 143–151. [CrossRef] [Google Scholar]
  9. Eduardo SL. 1983. The taxonomy of the family Paramphistomidae Fischoeder, 1901 with special reference to the morphology of species occurring in ruminants. III. Revision of the genus Calicophoron Näsmark, 1937. Systematic Parasitology, 5, 25–79. [CrossRef] [PubMed] [Google Scholar]
  10. Eslami A, Halajian A, Bokai S. 2011. A survey of the bovine amphistomiasis in Mazenderan Province, north of Iran. Iranian Journal of Veterinary Research, 12, 52–55. [Google Scholar]
  11. Fischoeder F. 1901. Die Paramphistomiden der Säugetiere. Zoologischer Anzeiger, 24, 367–375. [Google Scholar]
  12. Gonzalez-Warleta M, Lladosa S, Castro-Hermida JA, Martinez-Ibeas AM, Conesa D, Muñoz F, López-Quilez A, Manga-González M, Mezo M. 2013. Bovine paramphistomosis in Galicia (Spain): prevalence, intensity, etiology and geospatial distribution of the infection. Veterinary Parasitology, 191, 252–263. [CrossRef] [PubMed] [Google Scholar]
  13. Hakalahti T, Karvonen A, Valtonen ET. 2006. Climate warming and disease risks in temperate regions: Argulus coregoni and Diplostomum spathaceum as case studies. Journal of Helminthology, 80, 93–98. [CrossRef] [PubMed] [Google Scholar]
  14. Hamed N, Hammami H, Khaled S, Rondelaud D, Ayadi A. 2009. Natural infection of Fasciola hepatica (Trematoda: Fasciolidae) in Bulinus truncatus (Gastropoda: Planorbidae) in northern Tunisia. Journal of Helminthology, 83, 271–273. [CrossRef] [PubMed] [Google Scholar]
  15. Hassan SS, Kaur K, Joshi K, Juya PD. 2005. Epidemiology of paramphistomosis in domestic ruminants districts of Punjab and other adjoining areas. Journal of Veterinary Parasitology, 3, 43–46. [Google Scholar]
  16. Itagaki T, Tsumagari N, Tsutsumi N, Chinone S. 2003. Discrimination of three amphistome species by PCR-RFLP based on rDNA ITS2 markers. Journal of Veterinary Medicine and Science, 65, 931–933. [CrossRef] [Google Scholar]
  17. Jones A. 2005. Family Paramphistomidae Fischoeder, 1901, in Keys to the Trematoda, vol. 2, Jones A, Bray R, Gibson DI, Editors. CAB International and the Natural History Museum: London. p. 229–246. [Google Scholar]
  18. Kechemir N. 1988. Description and life cycle of Paramphistomum microbothrium Fischoeder, 1901 (Trematoda, Paramphistomidae). Archives de l’Institut Pasteur d’Algérie, 56, 147–159. [Google Scholar]
  19. Kechemir N. 1988. Trematodes of Bulinus truncatus (Mollusca, Planorbidae) in Algeria. Archives de l’Institut Pasteur d’Algérie, 56, 173–185. [Google Scholar]
  20. Kerbert C. 1878. Zur Trematoden-Kenntniss. Zoologischer Anzeiger, 1, 271–273. [Google Scholar]
  21. Khan UJ, Maqbool A. 2012. Prevalence of paramphistomosis in relation to meteorological factors. Pakistan Journal of Zoology, 44, 823–828. [Google Scholar]
  22. Kilani M, Chermette R, Guillot J, Polack B, Duncan JL, Cabaret J. 2010. Gastrointestinal helminthoses: amphistomosis, in Infectious and parasitic diseases of livestock, Lefèvre PC, Blancou J, Chermette R, Uilenberg G, Editors. Lavoisier: Paris. p. 1589–1601. [Google Scholar]
  23. Kumar S, Tamura K, Nei M. 2004. MEGA3: integrated software for molecular evolutionary genetics analysis and sequence alignment. Briefings in Bioinformatics, 5, 150–163. [Google Scholar]
  24. Librado P, Rozas J. 2009. DnaSP v5: a software for comprehensive analysis of DNA polymorphism data. Bioinformatics, 25, 1451–1452. [CrossRef] [PubMed] [Google Scholar]
  25. Mage C, Bourgne H, Toullieu JM, Rondelaud D, Dreyfuss G. 2002. Fasciola hepatica and Paramphistomum daubneyi: changes in prevalences of natural infections in cattle and in Lymnaea truncatula from central France over the past 12 years. Veterinary Research, 33, 439–447. [CrossRef] [EDP Sciences] [PubMed] [Google Scholar]
  26. Mas-Coma S, Valero MA, Bargues MD. 2009. Climate change effects on trematodiases, with emphasis on zoonotic fascioliasis and schistosomiasis. Veterinary Parasitology, 163, 264–280. [Google Scholar]
  27. Mekroud A. 2004. Contribution à l’étude de la distomatose à Fasciola hepatica Linnaeus 1758, dans le nord-est algérien Recherches sur les ruminants et le mollusque hôte. Constantine: Doctorate Thesis, University of Constantine. [Google Scholar]
  28. Mekroud A, Benakhla A, Benlatreche C, Rondelaud D, Dreyfuss G. 2002. First studies on the habitats of Galba truncatula (Mollusca, Gastropoda: Lymnaeidae), the snail host of Fasciola hepatica, and the dynamics of snail populations in northeastern Algeria. Revue de Médecine Vétérinaire de Toulouse, 153, 181–188. [Google Scholar]
  29. Millet de la Turtaudière PA. 1813. Mollusques terrestres et fluviatiles observés dans le département de Maine-et-Loire. Pavie: Angers. [Google Scholar]
  30. Müller OF. 1773–1774. Vermium terrestrium et fluviatilium, seu animalum infusoriorum, helminthicorum, et testaceorum, non marinorum, succincta historia. Heineck et Faber: Havniae et Lipsiae. [Google Scholar]
  31. Ollerenshaw CB, Smith LP. 1969. Meteorological factors and forecasts of helminthic diseases. Advances in Parasitology, 7, 283–323. [CrossRef] [PubMed] [Google Scholar]
  32. Păcenovsky J, Zahor Z, Krupicer I. 1987. The first finding of Paramphistomum daubneyi (Dinnik, 1962) in beef cattle in Algeria. Veterinary Medicine (Praha), 32, 379–384. [Google Scholar]
  33. Postal JM. 1984. Les paramphistomoses gastro-duodénales des ruminants. Contribution à l’étude de leur épidémiologie: cas du foyer vendéen. Alfort: Pharm. D. Thesis, University of Créteil. [Google Scholar]
  34. Rolfe PF, Boray JC, Nichols P, Collins GH. 1991. Epidemiology of paramphistomoses in cattle. International Journal for Parasitology, 21, 813–819. [CrossRef] [PubMed] [Google Scholar]
  35. Sey O. 1980. Revision of the amphistomes of European ruminants. Parasitologia Hungaricae, 13, 13–25. [Google Scholar]
  36. Sey O. 1989. A review of chemotherapy of paramphistomosis of domestic ruminants in Europe. Parasitologia Hungaricae, 22, 51–55. [Google Scholar]
  37. Shapiro SS, Wilk MB. 1965. An analysis of variance test for normality (complete samples). Biometrika, 52, 591–611. [Google Scholar]
  38. Šoštarić B, Beck R, Mihaljević Ž, Vicković I. 2011. Paramphistomosis, emerging or reemerging disease of ruminants in Croatia. Veterinarska Stanica, 42, 296–297. [Google Scholar]
  39. Szmidt-Adjidé V, Abrous M, Adjidé CC, Dreyfuss G, Lecompte A, Cabaret J, Rondelaud D. 2000. Prevalence of Paramphistomum daubneyi infection in cattle in central France. Veterinary Parasitology, 87, 133–138. [CrossRef] [PubMed] [Google Scholar]
  40. Tamura K, Nei M, Kumar S. 2004. Prospects for inferring very large phylogenies by using the neighbor-joining method. Proceedings of the National Academy of Sciences of the United States of America, 101, 11030–11035. [CrossRef] [PubMed] [Google Scholar]
  41. Tariq KA, Chishti MZ, Ahmad F, Shawi AS. 2008. Epidemiology of paramphistomosis of sheep (Ovis aries L.) in the north west temperate Himalayan region of India. Veterinary Research Communications, 32, 383–391. [CrossRef] [PubMed] [Google Scholar]
  42. Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG. 1997. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Research, 25, 4876–4882. [CrossRef] [PubMed] [Google Scholar]
  43. Titi A. 2008. Contribution à l’étude de la paramphistomose des ruminants dans quelques wilayas du nord-est algérien. El Tarf: Master Thesis, University of El Tarf. [Google Scholar]
  44. Titi A. 2013. La paramphistomose gastro-duodénale des ruminants dans le nord-est algérien. Investigations sur les bovins et le mollusque hôte. Constantine: Doctorate Thesis, University of Constantine. [Google Scholar]
  45. Titi A, Mekroud A, Sedraoui C, Vignoles P, Rondelaud D. 2010. Prevalence and intensity of Paramphistomum daubneyi infections in cattle from northeastern Algeria. Journal of Helminthology, 84, 177–181. [CrossRef] [PubMed] [Google Scholar]
  46. Torgerson P, Claxton J. 1999. Epidemiology and control, in Fasciolosis, Dalton JP, Editor. CABI Publishing: Oxon. p. 113–149. [Google Scholar]
  47. Zeder JG. 1790. Beschreibung des Hirschsplitterworms, Festucaria cervi. Schriften der Berlinische Gesellschaft Naturforschender Freunde, 10, 65–74. [Google Scholar]

Cite this article as: Titi A, Mekroud A, Chibat MH, Boucheikhchoukh M, Zein-Eddine R, Djuikwo-Teukeng FF, Vignoles P, Rondelaud D & Dreyfuss G: Ruminal paramphistomosis in cattle from northeastern Algeria: prevalence, parasite burdens and species identification. Parasite, 2014, 21, 50.

All Tables

Table 1.

Monthly temperatures and rainfall in the department (wilaya) of Jijel during the two-year study (September 2010–August 2012).

Table 2.

Prevalence and intensity of bovine paramphistomosis in bull calves for each season during the two-year study.

Table 3.

Prevalence and intensity of bovine paramphistomosis in old cows for each season during the two-year study.

All Figures

thumbnail Figure 1.

Numerical distribution of parasite burdens in relation to prevalence of bovine paramphistomosis for autumn (1a), winter (1b), spring (1c) and summer (1d). To build these graphs, the values obtained for corresponding seasons of both years were pooled.

In the text
thumbnail Figure 2.

ITS-2 tree based on neighbour-joining estimates with Paragonimus westermani as the outgroup. In blue, clade 1; in red: clade 2. Scale bar indicates the number of substitutions per sequence position.

In the text

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.