<span style="font-size:11.0pt;font-family: "Times New Roman","serif";mso-fareast-font-family:"Times New Roman";mso-bidi-font-family: Mangal;mso-ansi-language:EN-GB;mso-fareast-language:EN-US;mso-bidi-language: HI" lang="EN-GB">Evaluation and use of <i style="mso-bidi-font-style:normal">in silico</i> structure based epitope prediction for listeriolysin O of <i style="mso-bidi-font-style:normal">Listeria monocytogenes</i></span>

160-166Listeria<span style="font-size: 11.0pt;font-family:" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;letter-spacing:.2pt;mso-ansi-language:en-gb;="" mso-fareast-language:en-us;mso-bidi-language:hi"="" lang="EN-GB"> infection is major health problem causing listeriosis that <span style="font-size:11.0pt; font-family:" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;letter-spacing:.2pt;mso-ansi-language:en-gb;="" mso-fareast-language:en-in;mso-bidi-language:hi"="" lang="EN-GB">manifests as abortion, stillbirth, septicemia, meningitis and meningoencephalitis. Listeriolysin O is the <span style="font-size:11.0pt; font-family:" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;letter-spacing:.2pt;mso-ansi-language:en-us;="" mso-fareast-language:en-us;mso-bidi-language:hi"="">cholesterol-dependent cytolysin toxin involved in the escape of L. monocytogenes from primary and secondary intracellular vacuoles and, therefore, can serve as the vital target for vaccine development. Consequently, the present study was aimed to design epitope-based vaccine against Listeria.<b style="mso-bidi-font-weight: normal"> <span style="font-size:11.0pt; font-family:" times="" new="" roman","serif";mso-fareast-font-family:"times="" roman";="" mso-bidi-font-family:mangal;letter-spacing:.2pt;mso-ansi-language:en-gb;="" mso-fareast-language:en-us;mso-bidi-language:hi"="" lang="EN-GB">LLO, ILO, and SLO proteins from L. monocytogenes, L. ivanovii and L. seeligeri, respectively were analyzed using various bioinformatics and immuonoinformatics tools, including sequence and structure-based ones. A total of 11 antigenic B-cell epitopes, and 4 and 3 allelic classes for MHC class I and MHC class II binding peptides, respectively were predicted for LLO protein. The<span style="mso-bidi-font-weight: bold"> unique peptide 363LGDLRD368 was identified in the LLO protein. Further, we also observed that IgG class of B-cells were predominant in these proteins. The study revealed potential B-cell and T-cell epitope that can raise the desired immune response against these proteins. The present study would, therefore, be helpful in designing and predicting novel vaccine candidates, which in near future might offer the source for eradicating listeriosis.</span

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Not AvailablePH20 hyaluronidase proteins are members of Zona Pellucida Binding Protein family. PH20 hyaluronidase is bifunctional i.e. have hyaluronidase as well as sperm-zona binding activity reportedly. In this study, we performed in silico characterization of novel PH20 protein using partial nucleotide sequences obtained from SNP genotyping of Bubalus bubalis bulls by Sanger dideoxy sequencing method. Possible glycosylation and mannosylation patterns were also predicted in both the PH20 hyaluronidase sequences which may be responsible for its hyaluronidase activity. Further, the potential tertiary structure of PH20 was deduced using Swiss-Model server. The tertiary structure models of PH20 were validated by ProSA server and ramachandran plots. These structural models were assigned PMDB identifiers PM0080458 and PM0080459. Physicochemical characterization revealed that B. bubalis PH20 hyaluronidase are more thermostable and more hydrophobic than that of the cattle PH20 hyaluronidase. The functional annotations were further inferred using gene oOntology based predictions. Present work on structural elucidation of PH20 predicts a reference model for functional genomics studies related to multifunctionality of PH20 hyaluronidase proteins in other species.Not Availabl

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Not AvailableMachine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.Not Availabl

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Not AvailableMachine learning algorithms were employed for predicting the feed conversion efficiency (FCE), using the blood parameters and average daily gain (ADG) as predictor variables in buffalo heifers. It was observed that isotonic regression outperformed other machine learning algorithms used in study. Further, we also achieved the best performance evaluation metrics model with additive regression as the meta learner and isotonic regression as the base learner on 10-fold cross-validation and leaving-one-out cross-validation tests. Further, we created three separate partial least square regression (PLSR) models using all 14 parameters of blood and ADG as independent (explanatory) variables and FCE as the dependent variable, to understand the interactions of blood parameters, ADG with FCE each by inclusion of all FCE values (i), only higher FCE values (negative RFI) (ii), and inclusion of only lower FCE (positive RFI) values (iii). The PLSR model including only the higher FCE values was concluded the best, based on performance evaluation metrics as compared to PLSR models developed by inclusion of the lower FCE values and all types of FCE values. IGF1 and its interactions with the other blood parameters were found highly influential for higher FCE measures. The strength of the estimated interaction effects of the blood parameter in relation to FCE may facilitate understanding of intricate dynamics of blood parameters for growth.Not Availabl

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Not AvailableSingle Nucleotide Polymorphism (SNP) is one of the important molecular markers widely used in animal breeding program for improvement of any desirable genetic traits. Considering this, the present study was carried out to identify, annotate and analyze the SNPs related to four important traits of buffalo viz. milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency. We identified 246,495, 168,202, 74,136 and 194,747 genome-wide SNPs related to mentioned traits, respectively using ddRAD sequencing technique based on 85 samples of Murrah Buffaloes. Distribution of these SNPs were highest (61.69%) and lowest (1.78%) in intron and exon regions, respectively. Under coding regions, the SNPs for the four traits were further classified as synonymous (4697) and non-synonymous (3827). Moreover, Gene Ontology (GO) terms of identified genes assigned to various traits. These characterized SNPs will enhance the knowledge of cellular mechanism for enhancing the productivity of water buffalo through molecular breeding.Not Availabl

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Not AvailableSingle Nucleotide Polymorphism (SNP) is one of the important molecular markers widely used in animal breeding program for improvement of any desirable genetic traits. Considering this, the present study was carried out to identify, annotate and analyze the SNPs related to four important traits of buffalo viz. milk volume, age at first calving, post-partum cyclicity and feed conversion efficiency. We identified 246,495, 168,202, 74,136 and 194,747 genome-wide SNPs related to mentioned traits, respectively using ddRAD sequencing technique based on 85 samples of Murrah Buffaloes. Distribution of these SNPs were highest (61.69%) and lowest (1.78%) in intron and exon regions, respectively. Under coding regions, the SNPs for the four traits were further classified as synonymous (4697) and non-synonymous (3827). Moreover, Gene Ontology (GO) terms of identified genes assigned to various traits. These characterized SNPs will enhance the knowledge of cellular mechanism for enhancing productivity of water buffalo through molecular breeding.Not Availabl