The overall aims of the project were achieved by addressing the following six main objectives:
Firstly, the identification of the end phenotypes was achieved contributing in the analysis and construction of datasets of a large population of performance tested pigs from different breeds from which biological specimens were also collected to link external and internal phenotypes.
Secondly, the ER applied mass spectrometry (MS) based proteomics technologies, for the identification, detection and high throughput quantification of new protein/peptide markers in different biological substrates collected from the performance tested pigs. The ER settled the facilities and the protocols for the protein extraction and digestion. Following optimisation of the protocol the ER applied label-free LC-MS to investigate the difference in the liver proteome between two pig breeds, Italian Duroc (ID) and Italian Large White (ILW). Twenty-five proteins were identified to be differentially expressed between these breeds. Moreover, Western blotting was used to identify the presence of kynurenine 3-monooxygenasn (KMO) in liver samples from eight pigs from two different KMO genotypes. Kidney samples were also tested and used as positive control. No difference was observed between the two different phenotypes. These data were compared with genotyping results that the group reported for this gene. The results confirmed that there is no association between mutations that changes the 3D inferred protein structure and the protein level. Changes in the effect on the metabolomic pathway of the encoded enzyme might be due to different enzyme activities due to the identified mutations.
Thirdly, metabolomics analysis was performed using nuclear magnetic resonance (NMR) and MS to characterise and compare the metabolites of ID and ILW. About 250 samples between urine, plasma, serum and liver from the two breeds were processed using the facilities of Teagasc. Data analysis of the metabolomic dataset using Partial Least Squared Discriminant Analysis (PLS-DA) showed some patterns in the samples related to the two breeds.
Fourthly, the dataset developed over the project from the proteomics and metabolomics studies were processed using different approaches. For example, ANOVA analysis, PCA, PLS-DA were applied for the proteomics and metabolomics analysis. Different proteins and metabolites were identified to change significantly between breeds (see above). A new statistical pipeline to statistically validate the results was applied.
Cytoscape was used to obtain a functional interpretation of the 25 proteins differentially abundant between breeds. STRING database was used to investigate the protein-protein interaction of the proteins differentially abundant.
Moreover, the Pig Quantitative Trait Locus Database was used to explore possible links between up or down-regulated proteins and genomic QTLs for economically relevant traits and parameters that could be affected by genes encoding these proteins.
The multilayer data produced using these multi “omics” approaches were stored in the database with the genotype information already collected by Fontanesi’s group and will be an important aid in further studies.
Fifthly, several activities were undertaken, by the ER to communicate the output of the research to a wider public, nine between conferences and workshops, about ten between seminar and classes, one article is currently under review in PLoS One journal. This article is already available in a repository as preprints papers. At least other three papers will be published from the work done and will be freely accessible. Many other activities were undertaken to introduce among students and general public the research work performed in the MSCA and its implications for citizens. Moreover, the ER to better integrate his activities with the daily life in Bologna, involved in these initiatives several small local enterprises and two associations that are dealing with pig products.
Lastly, during the project the ER had the chance to work in a multidisciplinary environment, working in different departments and organisations, dealing with local entrepreneurs and associations, to follow many courses about informatics, found hunting, etc. The ER had also experience in teaching in different classes, all which contributed to strength the knowledge and skills of the ER in the field of animal science.
