Systemic distribution of different low pathogenic avian influenza (LPAI) viruses in chicken

<p>Abstract</p> <p>Background</p> <p>Since we were able to isolate viable virus from brain and lung of H7N1 low pathogenic avian influenza virus (LPAIV) infected chickens, we here examined the distribution of different LPAIV strains in chickens by measuring the viral AI RNA load in multiple organs. Subtypes of H5 (H5N1, H5N2), H7 (H7N1, H7N7) and H9 (H9N2), of chicken (H5N2, H7N1, H7N7, H9N2), or mallard (H5N1) origin were tested. The actual presence of viable virus was evaluated with virus isolation in organs of H7N7 inoculated chickens.</p> <p>Findings</p> <p>Viral RNA was found by PCR in lung, brain, intestine, peripheral blood mononuclear cells, heart, liver, kidney and spleen from chickens infected with chicken isolated LPAIV H5N2, H7N1, H7N7 or H9N2. H7N7 virus could be isolated from lung, ileum, heart, liver, kidney and spleen, but not from brain, which was in agreement with the data from the PCR. Infection with mallard isolated H5N1 LPAIV resulted in viral RNA detection in lung and peripheral blood mononuclear cells only.</p> <p>Conclusion</p> <p>We speculate that chicken isolated LPAI viruses are spreading systemically in chicken, independently of the strain.</p

A Pathway Analysis Tool for Analyzing Microarray Data of Species with Low Physiological Information

Pathway information provides insight into the biological processes underlying microarray data. Pathway information is widely available for humans and laboratory animals in databases through the internet, but less for other species, for example, livestock. Many software packages use species-specific gene IDs that cannot handle genomics data from other species. We developed a species-independent method to search pathways databases to analyse microarray data. Three PERL scripts were developed that use the names of the genes on the microarray. (1) Add synonyms of gene names by searching the Gene Ontology (GO) database. (2) Search the Kyoto Encyclopaedia of Genes and Genomes (KEGG) database for pathway information using this GO-enriched gene list. (3) Combine the pathway data with the microarray data and visualize the results using color codes indicating regulation. To demonstrate the power of the method, we used a previously reported chicken microarray experiment investigating line-specific reactions to Salmonella infection as an example