Human brucellosis in Baringo County, Kenya: Evaluating the diagnostic kits used and identifying infecting Brucella species.

Human brucellosis diagnosis has been a challenge in Brucella-endemic areas. In Kenya, diagnosis is usually carried out using Febrile Brucella Antigen agglutination test (FBAT) whose performance is not well documented. This paper reports on the sensitivity and specificity of the FBAT used for brucellosis diagnosis on blood samples/serum collected in three healthcare facilities in Baringo County, Kenya, and on Brucella species present in the study area. The FBAT test results at the hospitals were used to guide patient management. Patients who visited the hospital's laboratory with a clinician's request for brucellosis testing also filled a questionnaire to assess knowledge and attitudes associated with transmission of the disease in the study area. The remaining serum samples were tested again using FBAT and Rose Bengal Plate Test (RBPT) within a month of blood collection at the University Nairobi Laboratory. The two rapid tests were then compared, with respect to brucellosis diagnostic sensitivity and specificity. To identify infecting Brucella species, a proportion 43% (71/166) of the blood clots were analyzed by multiplex polymerase chain reaction (PCR) using specific primers for B. abortus, B. melitensis, B. ovis and B. suis. Out of 166 serum samples tested, 26.5% (44/166) were positive using FBAT and 10.2% (17/166) positive using RBPT. The sensitivity and specificity of FBAT compared to RBPT was 76.47% and 71.19%, respectively while the positive and negative predictive values were 29.55% and 96.72%, respectively. The FBAT showed higher positivity then RBPT. The difference in sensitivity and specificity of FBAT and RBPTs was relatively low. The high FBAT positivity rate would be indication of misdiagnosis; this would lead to incorrect treatment. Brucella abortus was detected from 9.9% (7/71) of the blood clots tested; no other Brucella species were detected. Thus human brucellosis, in Baringo was mainly caused by B. abortus.

Analyses of mitochondrial genes reveal two sympatric but genetically divergent lineages of Rhipicephalus appendiculatus in Kenya.

BACKGROUND: The ixodid tick Rhipicephalus appendiculatus transmits the apicomplexan protozoan parasite Theileria parva, which causes East coast fever (ECF), the most economically important cattle disease in eastern and southern Africa. Recent analysis of micro- and minisatellite markers showed an absence of geographical and host-associated genetic sub-structuring amongst field populations of R. appendiculatus in Kenya. To assess further the phylogenetic relationships between field and laboratory R. appendiculatus tick isolates, this study examined sequence variations at two mitochondrial genes, cytochrome c oxidase subunit I (COI) and 12S ribosomal RNA (rRNA), and the nuclear encoded ribosomal internal transcribed spacer 2 (ITS2) of the rRNA gene, respectively. RESULTS: The analysis of 332 COI sequences revealed 30 polymorphic sites, which defined 28 haplotypes that were separated into two distinct haplogroups (A and B). Inclusion of previously published haplotypes in our analysis revealed a high degree of phylogenetic complexity never reported before in haplogroup A. Neither haplogroup however, showed any clustering pattern related to either the geographical sampling location, the type of tick sampled (laboratory stocks vs field populations) or the mammalian host species. This finding was supported by the results obtained from the analysis of 12S rDNA sequences. Analysis of molecular variance (AMOVA) indicated that 90.8 % of the total genetic variation was explained by the two haplogroups, providing further support for their genetic divergence. These results were, however, not replicated by the nuclear transcribed ITS2 sequences likely because of recombination between the nuclear genomes maintaining a high level of genetic sequence conservation. CONCLUSIONS: COI and 12S rDNA are better markers than ITS2 for studying intraspecific diversity. Based on these genes, two major genetic groups of R. appendiculatus that have gone through a demographic expansion exist in Kenya. The two groups show no phylogeographic structure or correlation with the type of host species from which the ticks were collected, nor to the evolutionary and breeding history of the species. The two lineages may have a wide geographic distribution range in eastern and southern Africa. The findings of this study may have implications for the spread and control of R. appendiculatus, and indirectly, on the transmission dynamics of ECF.

Multi-locus genotyping reveals absence of genetic structure in field populations of the brown ear tick (Rhipicephalus appendiculatus) in Kenya.

Rhipicephalus appendiculatus is an important tick vector of several pathogens and parasitizes domestic and wild animals across eastern and southern Africa. However, its inherent genetic variation and population structure is poorly understood. To investigate whether mammalian host species, geographic separation and resulting reproductive isolation, or a combination of these, define the genetic structure of R. appendiculatus, we analyzed multi-locus genotype data from 392 individuals from 10 geographic locations in Kenya generated in an earlier study. These ticks were associated with three types of mammalian host situations; (1) cattle grazing systems, (2) cattle and wildlife co-grazing systems (3) wildlife grazing systems without livestock. We also analyzed data from 460 individuals from 10 populations maintained as closed laboratory stocks and 117 individuals from five other species in the genus Rhipicephalus. The pattern of genotypes observed indicated low levels of genetic differentiation between the ten field populations (FST=0.014±0.002) and a lack of genetic divergence corresponding to the degree of separation of the geographic sampling locations. There was also no clear association of particular tick genotypes with specific host species. This is consistent with tick dispersal over large geographic ranges and lack of host specificity. In contrast, the 10 laboratory populations (FST=0.248±0.015) and the five other species of Rhipicephalus (FST=0.368±0.032) were strongly differentiated into distinct genetic groups. Some laboratory bred populations diverged markedly from their field counterparts in spite of originally being sampled from the same geographic locations. Our results demonstrate a lack of defined population genetic differentiation in field populations of the generalist R. appendiculatus in Kenya, which may be a result of the frequent anthropogenic movement of livestock and mobility of its several wildlife hosts between different locations.

Micro- and minisatellite-expressed sequence tag (EST) markers discriminate between populations of Rhipicephalus appendiculatus.

Biological differences, including vector competence for the protozoan parasite Theileria parva have been reported among populations of Rhipicephalus appendiculatus (Acari: Ixodidae) from different geographic regions. However, the genetic diversity and population structure of this important tick vector remain unknown due to the absence of appropriate genetic markers. Here, we describe the development and evaluation of a panel of EST micro- and minisatellite markers to characterize the genetic diversity within and between populations of R. appendiculatus and other rhipicephaline species. Sixty-six micro- and minisatellite markers were identified through analysis of the R. appendiculatus Gene Index (RaGI) EST database and selected bacterial artificial chromosome (BAC) sequences. These were used to genotype 979 individual ticks from 10 field populations, 10 laboratory-bred stocks, and 5 additional Rhipicephalus species. Twenty-nine markers were polymorphic and therefore informative for genetic studies while 6 were monomorphic. Primers designed from the remaining 31 loci did not reliably generate amplicons. The 29 polymorphic markers discriminated populations of R. appendiculatus and also 4 other Rhipicephalus species, but not R. zambeziensis. The percentage Principal Component Analysis (PCA) implemented using Multiple Co-inertia Analysis (MCoA) clustered populations of R. appendiculatus into 2 groups. Individual markers however differed in their ability to generate the reference typology using the MCoA approach. This indicates that different panels of markers may be required for different applications. The 29 informative polymorphic micro- and minisatellite markers are the first available tools for the analysis of the phylogeography and population genetics of R. appendiculatus.