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1.
Parasit Vectors ; 11(1): 5, 2018 01 03.
Article in English | MEDLINE | ID: mdl-29298712

ABSTRACT

BACKGROUND: Only a few studies have examined the presence of Anaplasma marginale and Anaplasma centrale in South Africa, and no studies have comprehensively examined these species across the whole country. To undertake this country-wide study we adapted a duplex quantitative real-time PCR (qPCR) assay for use in South Africa but found that one of the genes on which the assay was based was variable. Therefore, we sequenced a variety of field samples and tested the assay on the variants detected. We used the assay to screen 517 cattle samples sourced from all nine provinces of South Africa, and subsequently examined A. marginale positive samples for msp1α genotype to gauge strain diversity. RESULTS: Although the A. marginale msp1ß gene is variable, the qPCR functions at an acceptable efficiency. The A. centrale groEL gene was not variable within the qPCR assay region. Of the cattle samples screened using the assay, 57% and 17% were found to be positive for A. marginale and A. centrale, respectively. Approximately 15% of the cattle were co-infected. Msp1α genotyping revealed 36 novel repeat sequences. Together with data from previous studies, we analysed the Msp1a repeats from South Africa where a total of 99 repeats have been described that can be attributed to 190 msp1α genotypes. While 22% of these repeats are also found in other countries, only two South African genotypes are also found in other countries; otherwise, the genotypes are unique to South Africa. CONCLUSIONS: Anaplasma marginale was prevalent in the Western Cape, KwaZulu-Natal and Mpumalanga and absent in the Northern Cape. Anaplasma centrale was prevalent in the Western Cape and KwaZulu-Natal and absent in the Northern Cape and Eastern Cape. None of the cattle in the study were known to be vaccinated with A. centrale, so finding positive cattle indicates that this organism appears to be naturally circulating in cattle. A diverse population of A. marginale strains are found in South Africa, with some msp1α genotypes widely distributed across the country, and others appearing only once in one province. This diversity should be taken into account in future vaccine development studies.


Subject(s)
Anaplasma centrale/classification , Anaplasma marginale/classification , Anaplasmosis/microbiology , Cattle Diseases/microbiology , Coinfection/veterinary , Genetic Variation , Genotype , Anaplasma centrale/genetics , Anaplasma centrale/isolation & purification , Anaplasma marginale/genetics , Anaplasma marginale/isolation & purification , Anaplasmosis/epidemiology , Animals , Bacterial Outer Membrane Proteins/genetics , Cattle , Cattle Diseases/epidemiology , Chaperonin 60/genetics , Coinfection/epidemiology , Coinfection/microbiology , Molecular Epidemiology , Multiplex Polymerase Chain Reaction , Prevalence , Real-Time Polymerase Chain Reaction , South Africa/epidemiology
2.
BMC Bioinformatics ; 9: 333, 2008 Aug 07.
Article in English | MEDLINE | ID: mdl-18687122

ABSTRACT

BACKGROUND: Data mining in large DNA sequences is a major challenge in microbial genomics and bioinformatics. Oligonucleotide usage (OU) patterns provide a wealth of information for large scale sequence analysis and visualization. The purpose of this research was to make OU statistical analysis available as a novel web-based tool for functional genomics and annotation. The tool is also available as a downloadable package. RESULTS: The SeqWord Genome Browser (SWGB) was developed to visualize the natural compositional variation of DNA sequences. The applet is also used for identification of divergent genomic regions both in annotated sequences of bacterial chromosomes, plasmids, phages and viruses, and in raw DNA sequences prior to annotation by comparing local and global OU patterns. The applet allows fast and reliable identification of clusters of horizontally transferred genomic islands, large multi-domain genes and genes for ribosomal RNA. Within the majority of genomic fragments (also termed genomic core sequence), regions enriched with housekeeping genes, ribosomal proteins and the regions rich in pseudogenes or genetic vestiges may be contrasted. CONCLUSION: The SWGB applet presents a range of comprehensive OU statistical parameters calculated for a range of bacterial species, plasmids and phages. It is available on the Internet at http://www.bi.up.ac.za/SeqWord/mhhapplet.php.


Subject(s)
Computational Biology/methods , Genome, Bacterial/genetics , Oligonucleotides/genetics , Software , Bacteriophages/genetics , Base Composition , Base Sequence , Internet , Oligonucleotides/analysis , Plasmids/genetics
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