Summary. -Marek's disease virus (MDV) isolated from poultry flocks in three states of India was monitored for the virus occurrence in the field. The MDV genome was isolated from feather follicles, spleen, and liver of the chicken (173 samples). Twenty two samples were positive for MDV genome in PCR and belonged to the serotype 1. The sequencing of MEQ gene of 11 samples revealed that nucleotide sequences of the isolate Ind-KA-01-06 was similar to the very virulent MDV, strain RB-1B. In situ hybridization studies also confirmed a presence of MDV serotype 1 in the infected liver tissues. Furthermore, the ability of the virus to induce apoptosis detected by flow cytometry showed that the virulent MDV induced apoptosis more efficiently than Turkey herpesvirus (HVT) vaccine virus. The present study showed the presence of virulent/very virulent MDV strains in the Indian poultry flocks.
Abstract:Accurate sex identification of pure line chickens in their early age has significant economic impact in breeding industry. In the recent years, range of Polymerase Chain Reaction (PCR) based sex determination techniques are routinely used to identify the sex of parent lines in breeding industries, however purified DNA is a prerequisite. Hence this study was aimed to develop a rapid and inexpensive PCR based gender identification method for chicken using whole blood samples and dried blood spots as template for PCR without DNA extraction. In addition, practicability of two W-chromosome specific gene targets in chicken for sex determination also characterised. Successful amplification of sex specific fragments and an internal control was achieved with the range of 0.125μl and 0.250μl volume of whole blood on filter paper (~1 mm) prepared from chicken and dried blood spot. This technique does not require DNA extraction, freeze/thawing of blood samples, pre-treatment with any reagents, dilution of whole blood or dried blood spots on filter paper. It can be carried out with commercially available Taq polymerase enzymes with increased concentration of MgCl 2 (3 mM) and 0.5% of DMSO without optimisation of PCR buffers. In conclusion, as compared to the existing PCR based sex identification techniques, the present approach is relatively economic, time saving, requires minimal steps and eliminates the need for DNA extraction.
Introduction:
Animal derived raw materials such as trypsin and Fetal Bovine Serum are used in vaccine manufacturing and pose the threat of introducing animal pathogens as contaminants into the final products. Thus screening for adventitious virus/ genome is part of quality control in manufacturing of biologicals. Various in-vitro and in-vivo detection assays have been developed for the detection of potential viral contaminants in vaccines. However, these assays are expensive, time consuming, labor intensive and incomplete limiting their ability to meet the increasing demands of the biological industry. Polymerase chain reaction technology scores over the in-vitro and in-vivo assays in speed, specificity, sensitivity and robustness of detection and can replace them in regular use. In the present study, a set of multiplex and individual PCRs were developed for the detection of porcine (n=6) and bovine viral genomes (n=5). Veterinary vaccines (10), human vaccines (9), porcine typsin lots (9), and fetal bovine serum (8) were screened for adventitious viral genomes using multiplex PCRs. It was observed that 60% of veterinary vaccines, 77.7% of trypsin, and 62.5% of fetal bovine serum were contaminated with adventitious viral genomes.
A total of 200 samples from Porcine circovirus 2 suspected (n = 112) and healthy (n = 88) swine populations collected from different districts of Tamil Nadu, south India were used in this study. The samples comprising of serum (n = 124), swabs from natural orifices (n = 52), and postmortem tissues (n = 24). All the samples were processed and subjected to the screening and detection of the PCV2 genome by a specific PCR assay.PCV2 genomes from positive samples were further subjected to genotyping with specifically designed primers for the full-length amplification of the ORF2 gene which codes for capsid protein (Cp) and serves as an epidemiological marker. Randomly, 13 amplified ORF2 genes were sequenced and the aligned sequences were subjected to signature motif analysis and phylogeny in MEGA X. The molecular prevalence of PCV2 infection in Tamil Nadu is 10.5% (n = 21). Signature motif and phylogenetic studies of 13 samples revealed 38.5% (n = 5) presence of each PCV2b intermediate 1(IM1) and PCV2b genotypes, followed by 15.4% (n = 2) PCV2d-2 and 7.7% (n = 1) PCV2d genotypes. The PCV2b-IM1 genotype has a 99.43% sequence homology with Vietnam isolate (JX506730). PCV2b genotypes showed 99.72% sequence identity with Chinese isolate (KX068219). PCV2d-2 genotypes reported in this study have 100% sequence identity with Taiwan isolate (MF169721). PCV2d genotype showed 97.87% sequence identity with Thailand isolate (MF314293). Amino acid analysis of all the 13 full-length ORF2 gene sequences revealed specific mutations in the immune reactive domains of A, B, C, and D. Capsid protein of three PCV2b and five PCV2b IM1 isolates had extra amino acid residue lysine (K) at 234 position of ORF2 similar to PCV2d. For the first time in South India, PCV2b IM1 and PCV2d-2 genotypes are reported. This study evidences the genetic shifts of PCV2 isolates in India and it is analogous to that of global genotypic shift.
False negative outcome of a diagnosis is one the major reasons for the dissemination of the diseases with high risk of propagation. Diagnostic sensitivity and the margin of error determine the false negative outcome of the diagnosis. A mathematical model had been developed to estimate the mean % secondary infections based on the margin of error of diagnostic sensitivity, % prevalence and R0 value. This model recommends a diagnostic test with diagnostic sensitivity ≥ 96% and at least 92% lower bound limit of the 95% CI or ≤ 4% margin of error for a highly infectious diseases like COVID-19 to curb the secondary transmission of the infection due to false negative cases. Positive relationship was found between mean % secondary infection and margin of error of sensitivity suggesting greater the margin of error of a diagnostic test sensitivity, higher the number of secondary infections in a population due to false negative cases. Negative correlation was found between number of COVID-19 test kits (>90% sensitivity) with regulatory approval and margin of error (R= −0.92, p=0.023) suggesting lesser the margin of error of a diagnostic test, higher the chances of getting approved by the regulatory agencies. However, there are no specific regulatory standards available for margin of error of the diagnostic sensitivity of COVID-19 diagnostic tests. Highly infectious disease such as COVID-19, certainly need specific regulatory standards on margin of error or 95% CI of the diagnostic sensitivity to curb the dissemination of the disease due to false negative cases and our model can be used to set the standards such as sensitivity, margin of error or lower bound limit of 95% CI.
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