Open Access Research article

Strengthening insights into host responses to mastitis infection in ruminants by combining heterogeneous microarray data sources

Sem Genini115*, Bouabid Badaoui1, Gert Sclep1, Stephen C Bishop2, Dave Waddington2, Marie-Hélène Pinard van der Laan3, Christophe Klopp4, Cédric Cabau5, Hans-Martin Seyfert6, Wolfram Petzl7, Kirsty Jensen2, Elizabeth J Glass2, Astrid de Greeff8, Hilde E Smith8, Mari A Smits9, Ingrid Olsaker10, Guro M Boman10, Giuliano Pisoni11, Paolo Moroni1116, Bianca Castiglioni12, Paola Cremonesi12, Marcello Del Corvo112, Eliane Foulon13, Gilles Foucras13, Rachel Rupp14 and Elisabetta Giuffra117

Author Affiliations

1 Parco Tecnologico Padano - CERSA, Via Einstein, 26900 Lodi, Italy

2 The Roslin Institute and R(D)SVS, Division of Genetics and Genomics, Roslin, Midlothian, University of Edinburgh, EH25 9RG, UK

3 INRA/AgroParisTech, UMR1236 Génétique et Diversité Animales, F-78352 Jouy en Josas, France

4 INRA, Sigenae UR875 Biométrie et Intelligence Artificielle, BP 52627, F-31326 Castanet-Tolosan Cedex, France

5 INRA, Sigenae UR83 Recherches Avicoles, F-37380 Nouzilly, France

6 Leibniz Institute for Farm Animal Biology (FBN), Molecular Biology Research Unit, Wilhelm-Stahl-Allee 2, D-18196 Dummerstorf, Germany

7 Clinic for Ruminants, Ludwig-Maximilians University, Munich, Germany

8 Central Veterinary Institute of Wageningen UR, P.O. Box 65, 8200 AB, Lelystad, The Netherlands

9 Wageningen UR Livestock Research, Animal Breeding and Genomics Centre, P.O. Box 65, 8200 AB, Lelystad, The Netherlands

10 Department of Basic Sciences and Aquatic Medicine, Norwegian School of Veterinary Science, P.O. Box 8146 Dep, NO-0033 Oslo, Norway

11 Università degli Studi di Milano, Department of Veterinary Pathology, Hygiene and Public Health, via Celoria 10, 20133 Milan, Italy

12 Istituto di Biologia e Biotecnologia Agraria, Consiglio Nazionale delle Ricerche, Milan, Italy

13 INRA-ENVT, UMR1225, Interactions Hôtes Agents Pathogènes, F-31300 Toulouse, France

14 INRA, UR631, Station d'Amélioration Génétique des Animaux, F-31326 Castanet-Tolosan, France

15 Department of Clinical Studies, School of Veterinary Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA

16 Quality Milk Production Services, Cornell University, Ithaca, New York, USA

17 INRA, UMR 1313 de Génétique Animale et Biologie Intégrative, Jouy-en-Josas, France

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BMC Genomics 2011, 12:225  doi:10.1186/1471-2164-12-225

Published: 11 May 2011

Abstract

Background

Gene expression profiling studies of mastitis in ruminants have provided key but fragmented knowledge for the understanding of the disease. A systematic combination of different expression profiling studies via meta-analysis techniques has the potential to test the extensibility of conclusions based on single studies. Using the program Pointillist, we performed meta-analysis of transcription-profiling data from six independent studies of infections with mammary gland pathogens, including samples from cattle challenged in vivo with S. aureus, E. coli, and S. uberis, samples from goats challenged in vivo with S. aureus, as well as cattle macrophages and ovine dendritic cells infected in vitro with S. aureus. We combined different time points from those studies, testing different responses to mastitis infection: overall (common signature), early stage, late stage, and cattle-specific.

Results

Ingenuity Pathway Analysis of affected genes showed that the four meta-analysis combinations share biological functions and pathways (e.g. protein ubiquitination and polyamine regulation) which are intrinsic to the general disease response. In the overall response, pathways related to immune response and inflammation, as well as biological functions related to lipid metabolism were altered. This latter observation is consistent with the milk fat content depression commonly observed during mastitis infection. Complementarities between early and late stage responses were found, with a prominence of metabolic and stress signals in the early stage and of the immune response related to the lipid metabolism in the late stage; both mechanisms apparently modulated by few genes, including XBP1 and SREBF1.

The cattle-specific response was characterized by alteration of the immune response and by modification of lipid metabolism. Comparison of E. coli and S. aureus infections in cattle in vivo revealed that affected genes showing opposite regulation had the same altered biological functions and provided evidence that E. coli caused a stronger host response.

Conclusions

This meta-analysis approach reinforces previous findings but also reveals several novel themes, including the involvement of genes, biological functions, and pathways that were not identified in individual studies. As such, it provides an interesting proof of principle for future studies combining information from diverse heterogeneous sources.

Keywords:
Meta-analysis; microarray analysis; mastitis infection; lipid metabolism; immune response