Molecular detection of Toxoplasma gondii and Neospora caninum in rock pigeons (Columba livia) in Punjab, Pakistan.
Muhammad TayyubShahzad AliArshad JavidMuhammad ImranPublished in: Parasitology research (2022)
Rock pigeons are synanthropic birds and live in close association within human settlements. Synanthropic birds are considered potential carriers of diseases and pose a subsequent risk of their transmission to humans. Neospora caninum and Toxoplasma gondii are intracellular protozoans infecting a wide range of hosts, as well as birds. Data related to the incidence of these protozoans in rock pigeons in Pakistan are scant. The aims of the study were to detect T. gondii and N. caninum DNA in tissue samples from rock pigeons (Columba livia) and to identify possible risk factors associated with infection. To accomplish this, pectoral muscle and brain samples were carefully collected from rock pigeons (n = 120) belonging to three zones located in ten districts of Punjab during a 4-month sampling span (July 2018 to October 2018). Data related to sex, age, sampling site, districts, seasonality, and ecological zones were recorded. DNA from brain and pectoral muscle samples was screened for both T. gondii and N. caninum by PCR assays. Chi-square analysis was used to check the association between positive samples and risk factors. The level of significance was p ≤ 0.05. T. gondii was detected in 46 (38.3%) brain samples, while 24 pectoral muscle samples (20%) were positive for N. caninum. Agroecological zones were statistically associated with the detection of N. caninum DNA. The outcomes of this study provide an understanding of the epidemiological pattern of N. caninum and T. gondii infection in rock pigeons in different regions of Punjab, Pakistan.
Keyphrases
- toxoplasma gondii
- risk factors
- circulating tumor
- skeletal muscle
- white matter
- resting state
- single molecule
- cell free
- tertiary care
- endothelial cells
- electronic health record
- big data
- multiple sclerosis
- climate change
- data analysis
- human health
- high throughput
- quantum dots
- insulin resistance
- reactive oxygen species
- adipose tissue
- deep learning
- single cell