Rhipicephalus microplus, known as the hard tick, is a vector for the parasites Babesia spp. and Anaplasma marginale, both of which can cause significant financial losses to the livestock industry. There is currently no effective vaccine for R. microplus tick infestations, despite the identification of numerous prospective tick vaccine candidates. As a result, the current research set out to develop an immunoinformatics-based strategy using existing methods for designing a multi-epitope based vaccination that is not only effective but also safe and capable of eliciting cellular and humoral immune responses. First, R. microplus proteins Bm86, Subolesin, and Bm95 were used to anticipate and link B and T-cell epitopes (HTL and CTL) to one another. Antigenicity testing, allergenicity assessment, and toxicity screening were just a few of the many immunoinformatics techniques used to identify potent epitopes. Multi-epitope vaccine design was chosen based on the antigenic score 0.935 that is promising vaccine candidate. Molecular docking was used to determine the nature of the interaction between TLR2 and the vaccine construct. Finally, molecular dynamic simulation was used to assess the stability and compactness of the resulting vaccination based on docking scores. The developed vaccine was shown to be stable, have immunogenic qualities, be soluble, and to have high expression by in silico cloning. These findings suggest that experimental investigation of the multi-epitope based vaccine designed in the current study will produce achievable vaccine candidates against R. microplus ticks, enabling more effective control of infestations.

Canine Enteric Coronavirus (CCoV) is one of the major enteric pathogen affecting dogs. This study aims to investigate the molecular prevalence, phylogenetic analysis, associated risk factors, and haemato-biochemical alterations in Canine Coronavirus in dogs in district Lahore, Pakistan. 450 fecal samples were collected from symptomatic dogs originating from various pet-clinics and kennels during 2018-2019. Samples were initially analyzed by sandwich lateral flow immunochromatographic assay and then further processed by RT-PCR (reverse transcriptase polymerase chain reaction) targeting the M gene followed by sequencing. RT-PCR based positive (n=20) and negative (n=20) dogs were samples for their blood for the haemato-biochemical analysis. A questionnaire was used to collect data from pet owners, in order to analyze the data for risk factors analysis by chi square test on SPSS. The prevalence of CCoV was 35.1%, and 23.8 % through Sandwich lateral flow immunochromatographic and RT-PCR respectively. Various risk factors like breed, age, sex, vomiting, diarrhea, sample source, body size, cohabitation with other animals, living environment, food, deworming history, contact with other animals or birds feces, and season were significantly associated with CCoV. The CCoV identified in Pakistan were 98% similar with the isolates from China (KT 192675, 1), South Korea (HM 130573, 1), Brazil (GU 300134, 1), Colombia (MH 717721, 1), United Kingdom (JX 082356, 1) and Tunisia (KX156806). Haematobiochemical alterations in CCoV affected dogs revealed anaemia, leucopenia, lymphopenia, neutrophilia, and decreased packed cell volume, and a significant increase in alkaline phosphate and alanine transaminase. It is concluded that infection with canine coronavirus appears widespread among dog populations in district Lahore, Pakistan. This study is the first report regarding the molecular detection and sequence analysis of CCoV in Pakistan.