Development and evaluation of a diagnostic cytokine-release assay for Mycobacterium suricattae infection in meerkats (Suricata suricatta)

CITATION: Clarke, C., et al. 2017. Development and evaluation of a diagnostic cytokine-release assay for mycobacterium suricattae infection in meerkats (Suricata suricatta). BMC Veterinary Research, 13:2, doi:10.1186/s12917-016-0927-x.The original publication is available at http://bmcvetres.biomedcentral.comBackground: Sensitive diagnostic tools are necessary for the detection of Mycobacterium suricattae infection in meerkats (Suricata suricatta) in order to more clearly understand the epidemiology of tuberculosis and the ecological consequences of the disease in this species. We therefore aimed to develop a cytokine release assay to measure antigen-specific cell-mediated immune responses of meerkats. Results: Enzyme-linked immunosorbent assays (ELISAs) were evaluated for the detection of interferon-gamma (IFN-γ) and IFN-γ inducible protein 10 (IP-10) in meerkat plasma. An IP-10 ELISA was selected to measure the release of this cytokine in whole blood in response to Bovigam® PC-HP Stimulating Antigen, a commercial peptide pool of M. bovis antigens. Using this protocol, captive meerkats with no known M. suricattae exposure (n = 10) were tested and results were used to define a diagnostic cut off value (mean plus 2 standard deviations). This IP-10 release assay (IPRA) was then evaluated in free-living meerkats with known M. suricattae exposure, categorized as having either a low, moderate or high risk of infection with this pathogen. In each category, respectively, 24.7%, 27.3% and 82.4% of animals tested IPRA-positive. The odds of an animal testing positive was 14.0 times greater for animals with a high risk of M. suricattae infection compared to animals with a low risk. Conclusion: These results support the use of this assay as a measure of M. suricattae exposure in meerkat populations. Ongoing longitudinal studies aim to evaluate the value of the IPRA as a diagnostic test of M. suricattae infection in individual animals.http://bmcvetres.biomedcentral.com/articles/10.1186/s12917-016-0927-xPublisher's versio

Quantification and identification of sperm subpopulations using computer-aided sperm analysis and species-specific cut-off values for swimming speed

Motility is an essential characteristic of all fl agellated spermatozoa and assessment of this parameter is one criterion for most semen or sperm evaluations. Computer-aided sperm analysis (CASA) can be used to measure sperm motility more objectively and accurately than manual methods, provided that analysis techniques are standardized. Previous studies have shown that evaluation of sperm subpopulations is more important than analyzing the total motile sperm population alone. We developed a quantitative method to determine cut-off values for swimming speed to identify three sperm subpopulations. We used the Sperm Class Analyzer ® (SCA) CASA system to assess the total percentage of motile spermatozoa in a sperm preparation as well as the percentages of rapid, medium and slow swimming spermatozoa for six mammalian species. Curvilinear velocity (VCL) cut-off values were adjusted manually for each species to include 80% rapid, 15% medium and 5% slow swimming spermatozoa. Our results indicate that the same VCL intervals cannot be used for all species to classify spermatozoa according to swimming speed. After VCL intervals were adjusted for each species, three unique sperm subpopulations could be identifi ed. The effects of medical treatments on sperm motility become apparent in changes in the distribution of spermatozoa among the three swimming speed classes.Web of Scienc

Biological and epidemiological consequences of MTBC diversity

Tuberculosis is caused by different groups of bacteria belonging to the Mycobacterium tuberculosis complex (MTBC). The combined action of human factors, environmental conditions and bacterial virulence determine the extent and form of human disease. MTBC virulence is a composite of different clinical phenotypes such as transmission rate and disease severity among others. Clinical phenotypes are also influenced by cellular and immunological phenotypes. MTBC phenotypes are determined by the genotype, therefore finding genotypes responsible for clinical phenotypes would allow discovering MTBC virulence factors. Different MTBC strains display different cellular and clinical phenotypes. Strains from Lineage 5 and Lineage 6 are metabolically different, grow slower, and are less virulent. Also, at least certain groups of Lineage 2 and Lineage 4 strains are more virulent in terms of disease severity and human-to-human transmission. Because phenotypic differences are ultimately caused by genotypic differences, different genomic loci have been related to various cellular and clinical phenotypes. However, defining the impact of specific bacterial genomic loci on virulence when other bacterial determinants, human and environmental factors are also impacting the phenotype would contribute to a better knowledge of tuberculosis virulence and ultimately benefit tuberculosis control