Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Research article

Meta-analysis of Chicken – Salmonella infection experiments

Marinus FW te Pas1*, Ina Hulsegge1, Dirkjan Schokker1, Mari A Smits12, Mark Fife3, Rima Zoorob4, Marie-Laure Endale5 and Johanna MJ Rebel2

Author Affiliations

1 Animal Breeding and Genetics Centre (ABGC), Wageningen UR Livestock Research, Animal Sciences Group, Wageningen University and Research Centre, P.O. Box 65, 8200 AB, Lelystad, The Netherlands

2 Central Veterinary Institute - Department of Infectious Biology, Animal Sciences Group, Wageningen University and Research Centre, P.O. Box 65, 8200 AB, Lelystad, The Netherlands

3 Institute for Animal Health, Genetics & Genomics group, Compton, Berkshire, UK

4 INSERM UMR-S 945, Institut Fédératif de Recherches (IFR) 113, department of Immunité-Cancer-Infection, Hôpital Pitié-Salpêtrière, 83 Bld de l'Hôpital, Bâtiment CERVI, 75651, Paris, Cédex 13, France

5 INRA, AgroParisTech, UMR1313 Animal Genetics and Integrative Biology, F-78350, Jouy-en-Josas, France

For all author emails, please log on.

BMC Genomics 2012, 13:146  doi:10.1186/1471-2164-13-146

Published: 24 April 2012

Abstract

Background

Chicken meat and eggs can be a source of human zoonotic pathogens, especially Salmonella species. These food items contain a potential hazard for humans. Chickens lines differ in susceptibility for Salmonella and can harbor Salmonella pathogens without showing clinical signs of illness. Many investigations including genomic studies have examined the mechanisms how chickens react to infection. Apart from the innate immune response, many physiological mechanisms and pathways are reported to be involved in the chicken host response to Salmonella infection. The objective of this study was to perform a meta-analysis of diverse experiments to identify general and host specific mechanisms to the Salmonella challenge.

Results

Diverse chicken lines differing in susceptibility to Salmonella infection were challenged with different Salmonella serovars at several time points. Various tissues were sampled at different time points post-infection, and resulting host transcriptional differences investigated using different microarray platforms. The meta-analysis was performed with the R-package metaMA to create lists of differentially regulated genes. These gene lists showed many similarities for different chicken breeds and tissues, and also for different Salmonella serovars measured at different times post infection. Functional biological analysis of these differentially expressed gene lists revealed several common mechanisms for the chicken host response to Salmonella infection. The meta-analysis-specific genes (i.e. genes found differentially expressed only in the meta-analysis) confirmed and expanded the biological functional mechanisms.

Conclusions

The meta-analysis combination of heterogeneous expression profiling data provided useful insights into the common metabolic pathways and functions of different chicken lines infected with different Salmonella serovars.