The unpredictable, evolutionary nature of the influenza A virus (IAV) is the primary problem when generating a vaccine and when designing diagnostic strategies; thus, it is necessary to determine the constant regions in viral proteins. In this study, we completed an in silico analysis of the reported epitopes of the 4 IAV proteins that are antigenically most significant (HA, NA, NP, and M2) in the 3 strains with the greatest world circulation in the last century (H1N1, H2N2, and H3N2) and in one of the main aviary subtypes responsible for zoonosis (H5N1). For this purpose, the HMMER program was used to align 3,016 epitopes reported in the Immune Epitope Database and Analysis Resource (IEDB) and distributed in 34,294 stored sequences in the Pfam database.
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August 2015
Background: In recent years the emergence of multidrug resistant Klebsiella pneumoniae strains has been an increasingly common event. This opportunistic species is one of the five main bacterial pathogens that cause hospital infections worldwide and multidrug resistance has been associated with the presence of high molecular weight plasmids. Plasmids are generally acquired through horizontal transfer and therefore is possible that systems that prevent the entry of foreign genetic material are inactive or absent.
View Article and Find Full Text PDFHelicobacter pylori strains are the major risk factor for gastric cancer. Strains vary in their content of disease-associated genes, so genome-wide analysis of cancer-isolated strains will help elucidate their pathogenesis and genetic diversity. We present the draft genome sequence of H.
View Article and Find Full Text PDFAn Influenza Probe Set (IPS) consisting in 1,249 9-mer probes for genomic fingerprinting of closely and distantly related Influenza Virus strains was designed and tested in silico. The IPS was derived from alignments of Influenza genomes. The RNA segments of 5,133 influenza strains having diverse degree of relatedness were concatenated and aligned.
View Article and Find Full Text PDFUnlabelled: The Virtual Hybridization approach predicts the most probable hybridization sites across a target nucleic acid of known sequence, including both perfect and mismatched pairings. Potential hybridization sites, having a user-defined minimum number of bases that are paired with the oligonucleotide probe, are first identified. Then free energy values are evaluated for each potential hybridization site, and if it has a calculated free energy of equal or higher negative value than a user-defined free energy cut-off value, it is considered as a site of high probability of hybridization.
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