Differential Expression of Three Members of the Multidomain Adhesion CCp Family in Babesia bigemina, Babesia bovis and Theileria equi

In the present study, we evaluated the inhibitory effect of trichostatin A on the asexual growth of bovine, equine, and canine Babesia parasites in vitro as well as on the in vivo growth of Babesia microti (B.microti) in mice. The growth of Babesia bovis (B.bovis), Babesia bigemina (B.bigemina), Babesia caballi (B.caballi), Theileria equi (T.equi), and Babesia gibsoni (B.gibsoni) species was significantly inhibited (P < 0.05) by very low concentrations of trichostatin A (IC50 values = 2.6, 2.4, 2.3, 2.4, and 2.3 nM, respectively). Furthermore, in B.microti-infected mice, trichostatin A caused significant higher (P < 0.05) inhibition of the growth of B.microti at the dose of 2 mg/kg body weight than that in the control group. These results indicated the trichostatin A might be a chemotherapeutic agent for treatment of babesiosis. DOI: http://dx.doi.org/10.5564/mjas.v11i2.210 Mongolian Journal of Agricultural Sciences Vol.11(2) 2013 pp.24-26

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Prevalence of parasites of wildlife in Yankari game reserve and Sumu wildlife park in Bauchi State, Nigeria

Sokoto Journal of Veterinary Sciences ◽

10.4314/sokjvs.v17i4.8 ◽

2020 ◽

Vol 17 (4) ◽

pp. 70-79

Author(s):

YJ Atuman ◽

C.A. Kudi ◽

P. Abdu ◽

A. Abubakar

Keyword(s):

Buffy Coat ◽

Gastrointestinal Parasites ◽

Control Measures ◽

Babesia Bovis ◽

Parasitic Infections ◽

Babesia Bigemina ◽

Theileria Equi ◽

Wildlife Species ◽

Eimeria Spp ◽

Game Reserve

The role of wildlife in the epidemiology of parasites in Yankari Game Reserve and Sumu Wildlife Park in Bauchi State, Nigeria was investigated by analysis of blood, faeces and ticks collected from 106 wildlife including 4 elephants (Loxodonta africana), 11 waterbucks (Kobus ellipsiprymus), 1 hartbeest (Alcelaphus baselaphus caama), 24 elands (Taurotragus oryx), 53 zebras (Equus quagga crawshayi), 1 kudu (Tragelaphus streptsiceros) and 12 wildebeest (Connochaetes taurinus). Blood samples were examined for haemoparasites by classical parasitological techniques i.e Geimsa's stained thin, thick and buffy coat blood smear. Whereas faecal samples were examined for gastrointestinal tract (GIT) parasites using floatation and sedimentation techniques while ticks were identified morphologically. Overall prevalence of haemoparasites was fifty six percent (56%). The identified haemoparasites were Anaplasma marginale, Babesia bigemina, Babesia bovis, Theileria equi, Babesia caballi, Trypanosoma spp and Ehrlichia ruminantium. Haemoparasites identified alone or in combination with others had a significant (P <0.05) effect on mean PCV of infected animals. Sixty percent (60%) of the wildlife species were infected with GIT parasites. Types of GIT parasites identified were two protozoans (Balantidium coli and Eimeria spp) and helminths from eighteen genera including ten nematodes (Strongyle type-egg, Dictyocaulus, Cooperia, Strongyloides, Haemonchus, Trichuris, Trichonema, Oesophagostomum, Bunostomum, and Ancylostoma), four Trematodes (Fasciola, Schistosoma, Paramphistomum and Gastrodiscus) and three Cestodes (Anoplocephala, Taenia and Moniezia. Four genera of ticks, Amblyomma, Boophilus, Hyalomma and Rhipicephalus were identified on the wildlife species. Our findings indicated the presence of infective parasites in wildlife and potential risks of transmitting these parasites to in contact domestic animals and humans in the study area. Control measures should be focused on reducing parasitic infections by proper management of wildlife in the Game Reserves in Bauchi State, Nigeria. Keywords: Gastrointestinal parasites, Haemoparasites, Prevalence, Ticks, Wildlife

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Applying Machine Learning to Predict the Exportome of Bovine and Canine Babesia Species That Cause Babesiosis

Pathogens ◽

10.3390/pathogens10060660 ◽

2021 ◽

Vol 10 (6) ◽

pp. 660

Author(s):

Stephen J. Goodswen ◽

Paul J. Kennedy ◽

John T. Ellis

Keyword(s):

Machine Learning ◽

Severe Disease ◽

Economic Loss ◽

Babesia Bovis ◽

Training Data ◽

Babesia Bigemina ◽

Bovine Babesiosis ◽

Canine Babesiosis ◽

Clinically Significant ◽

Significant Disease

Babesia infection of red blood cells can cause a severe disease called babesiosis in susceptible hosts. Bovine babesiosis causes global economic loss to the beef and dairy cattle industries, and canine babesiosis is considered a clinically significant disease. Potential therapeutic targets against bovine and canine babesiosis include members of the exportome, i.e., those proteins exported from the parasite into the host red blood cell. We developed three machine learning-derived methods (two novel and one adapted) to predict for every known Babesia bovis, Babesia bigemina, and Babesia canis protein the probability of being an exportome member. Two well-studied apicomplexan-related species, Plasmodium falciparum and Toxoplasma gondii, with extensive experimental evidence on their exportome or excreted/secreted proteins were used as important benchmarks for the three methods. Based on 10-fold cross validation and multiple train–validation–test splits of training data, we expect that over 90% of the predicted probabilities accurately provide a secretory or non-secretory indicator. Only laboratory testing can verify that predicted high exportome membership probabilities are creditable exportome indicators. However, the presented methods at least provide those proteins most worthy of laboratory validation and will ultimately save time and money.

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