Genome-Wide Identification of Susceptibility Alleles for Viral Infections through a Population Genetics Approach

Viruses have exerted a constant and potent selective pressure on human genes throughout evolution. We utilized the marks left by selection on allele frequency to identify viral infection-associated allelic variants. Virus diversity (the number of different viruses in a geographic region) was used to measure virus-driven selective pressure. Results showed an excess of variants correlated with virus diversity in genes involved in immune response and in the biosynthesis of glycan structures functioning as viral receptors; a significantly higher than expected number of variants was also seen in genes encoding proteins that directly interact with viral components. Genome-wide analyses identified 441 variants significantly associated with virus-diversity; these are more frequently located within gene regions than expected, and they map to 139 human genes. Analysis of functional relationships among genes subjected to virus-driven selective pressure identified a complex network enriched in viral products-interacting proteins. The novel approach to the study of infectious disease epidemiology presented herein may represent an alternative to classic genome-wide association studies and provides a large set of candidate susceptibility variants for viral infections

Immunogenicity and Safety of Defective Vaccinia Virus Lister: Comparison with Modified Vaccinia Virus Ankara

Potent and safe vaccinia virus vectors inducing cell-mediated immunity are needed for clinical use. Replicating vaccinia viruses generally induce strong cell-mediated immunity; however, they may have severe adverse effects. As a vector for clinical use, we assessed the defective vaccinia virus system, in which deletion of an essential gene blocks viral replication, resulting in an infectious virus that does not multiply in the host. The vaccinia virus Lister/Elstree strain, used during worldwide smallpox eradication, was chosen as the parental virus. The immunogenicity and safety of the defective vaccinia virus Lister were evaluated without and with the inserted human p53 gene as a model and compared to parallel constructs based on modified vaccinia virus Ankara (MVA), the present “gold standard” of recombinant vaccinia viruses in clinical development. The defective viruses induced an efficient Th1-type immune response. Antibody and cytotoxic-T-cell responses were comparable to those induced by MVA. Safety of the defective Lister constructs could be demonstrated in vitro in cell culture as well as in vivo in immunodeficient SCID mice. Similar to MVA, the defective viruses were tolerated at doses four orders of magnitude higher than those of the wild-type Lister strain. While current nonreplicating vectors are produced mainly in primary chicken cells, defective vaccinia virus is produced in a permanent safety-tested cell line. Vaccines based on this system have the additional advantage of enhanced product safety. Therefore, a vector system was made which promises to be a valuable tool not only for immunotherapy for diseases such as cancer, human immunodeficiency virus infection, or malaria but also as a basis for a safer smallpox vaccine

Utilizing maximal frequent itemsets and social network analysis for HIV data analysis

Acquired immune deficiency syndrome is a deadly disease which is caused by human immunodeficiency virus (HIV). This virus attacks patients immune system and effects its ability to fight against diseases. Developing effective medicine requires understanding the life cycle and replication ability of the virus. HIV-1 protease enzyme is used to cleave an octamer peptide into peptides which are used to create proteins by the virus. In this paper, a novel feature extraction method is proposed for understanding important patterns in octamer's cleavability. This feature extraction method is based on data mining techniques which are used to find important relations inside a dataset by comprehensively analyzing the given data. As demonstrated in this paper, using the extracted information in the classification process yields important results which may be taken into consideration when developing a new medicine. We have used 746 and 1625, Impens and schilling data instances from the 746-dataset. Besides, we have performed social network analysis as a complementary alternative method