Please use this identifier to cite or link to this item: http://prr.hec.gov.pk/jspui/handle/123456789/15630
Title: Surveillance, Identification and Genotypes of Tick and Control Measures With Selected Herbal Plants Against Ticks In Cattle of Khyber Pakhtunkhwa, Pakistan
Authors: , Nasreen
Keywords: Biological & Medical Sciences
Zoology
Issue Date: 2020
Publisher: Abdul Wali Khan University, Mardan
Abstract: Dairy industry is the backbone of any livestock sector which not only the prime contributor of food resources but also an integral part of country economy in tropical regions like Pakistan. Large ruminants including cattle and buffaloes are the major food resources in terms of meat and milk particularly in Khyber Pakhtunkhwa (KP) Province, Pakistan. Currently, Pakistan has been facing huge economic burden and production losses in dairy industry owing to ticks and tick borne diseases. Moreover, the selection pressure pressed by commonly available commercial acaricide has led the ticks more resistant towards them, making it difficult to reduce the tick burden. Novel biological and synthetic compounds with management practices are the need of hour in order to curb tick population from dairy industry. Furthermore, molecular systematics and epidemiology are important to recognize the tick vector and their biology of disease spread in endemic areas. There is a lack of knowledge in genetic variations of tick species in KP. Thus the current project has aimed to conduct molecular identification of ticks, their resistance status and biological approaches towards tick managements from large ruminants. In current study, a total of ticks n= 649 were randomly collected from 277 animals (Cows n= 156 and Buffaloes n= 121) from various districts of KP province, Pakistan. Morphological identification followed by molecular analysis was carried out in order to determine tick species from the study area. Risk factors associated with tick burden were also calculated using Pearson chi square and multinomial regression for Odd ratio at significant value of P<0.05. Furthermore, for molecular taxonomy of collected hard ticks, n=25 DNA samples were extracted and amplified using three gene markers (COX 1, ITS2 and 16S rRNA) in PCR. Double distilled water was used as a negative which rum parallel with the positive control and samples of the current study. The yielded amplicon size for COX 1 was 700bp, 1000bp for ITS2 and 450bp for 16S rRNA which were then sent for sequencing for molecular identification. After careful analysis of tick sequences, five samples from each ITS2 and COX 1 genes and two tick DNA samples from 16S rRNA were used for phylogenetic analysis. Reference sequences were retrieved from Genbank database which revealed two distinct clades of Rhiphicepahlus and Hyalomma species. The sequences for each gene marker were enlisted and aligned separately with the sample using CLUSTAL W multiple alignment tool with the help of the same BioEdit software. Mega 7 software was used to construct phylogenetic tree using statistical tool of 1000 Bootstrap replication. Evaluation of plant based acaricidal efficacy and resistance against commercial acaricides were determined. FAO recommended procedures i.e. LPT (Larval packet test) and AIT (Adult immersion test) were adapted for the assessment of acaricidal efficacy of methanol extracts of medicinal plants and synthetic commercial acaricides against ticks of study area. Finally, computational method (in silico) with bioinformatics tools was used to predict potential inhibotors in order to block the function of nerotransmitters in insects. Three speices were identified as R. microplus (73.96%) followed by R. haemaphysaloides (23.27%) and Hy. scupense (2.77%) in different districts of KP. Various risk factors associated with tick burden in large ruminants were recorded. Chi-square analysis at P<0.05 was revealed that variables i.e. animal type (cow and buffaloes), age of animal and tick species are not the contributing factors and they were non-significant in association with Tick burden. However, variables i.e. location, months and sex of animals are significantly associated with high tick burden in current study. Multinomial regression analysis also confirmed the variable responsible for thigh tick burden. The variables i.e. month (April and March), sex (female) and geolocation (arid region) are the odds to promote tick burden in the region. Phylogenetic tree based on three mitochondrial genetic markers confirmed the speciation of hard ticks during morphological identification. As one tick sample which was given the ID Hy. anatolicum during morphological identification but it was successfully identified (using the gene marker COX 1) as Hy. detritum and it was more closely related to strain of Hy. detritum from China. Similarly, the sequences for R. microplus and R. haemaphysaloides were successfully identified and they are 99% similar to China and Indian isolates. Third parameter of the study was reported that both herbal medicinal plants A. sativum and C. sativa demonstrated anti-tick activity against hard ticks from field collection. The highest lethal activity of A. sativum and C. sativa plant on different biological parameter of adult tick i.e. egg laying index (0.2557± 0.003180 and 0.242± 0.00462), Egg laying inhibition (%) (33.54 and 37.08), % larval mortality (100±0.00 and 100.00±0.00) at 40mg/ml respectively. In silico analysis predicted the two most important compounds from these medicinal plants to inhibit neurotransmitter from insects. The most potent inhibitor Vitamin E is found, binds to acetyl cholinesterase at amino acid Glu255 with a docking score of -15.8534 Cannabidiol from C. sativa was found the another potent inhibitor that possibly binds to Val123 having binding score - 14.3793. The current study revealed the diversity of hard ticks infesting on large ruminants from various localities of KP province of Pakistan. Molecular taxonomy approach was successful in tick recognitions. The study also found the native medicinal plants to curb the field resistant tick population specially cattle ticks R. microplus. Moreover In silico computational method is another throughput approach to find the potent inhibitors from medicinal plants against ticks.
Gov't Doc #: 20763
URI: http://prr.hec.gov.pk/jspui/handle/123456789/15630
Appears in Collections:PhD Thesis of All Public / Private Sector Universities / DAIs.

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