Partner 10: AcureOmics AB, Umeå, Sweden (AO)
AcureOmics AB (AO) the leading SME in metabolomics offers metabolic profiling in the pharmaceutical-, biotechnological- and food industries. AO opens up new unique opportunities for diagnostic approaches and personalized medicine. Metabolomics will be performed by AO at the Swedish Metabolomics platform in Umeå (UPSC) under the responsibility of Drs. Bennett, Moritz and Trygg. The national academic metabolomics platform at UPSC was launched in 2002. AO provides a well-established cutting-edge metabolomics platform and long and have extensive experience in identifying biochemical pathways especially when regarding autoimmune diseases. Since then, more than 45000 samples ranging from plasma, urine, muscle and cerebrospinal fluid to extracts from plants have been analyzed and standardised and optimised analytical procedures have been developed.
Partner 10 team leader:
Associate professor Katrin Lundstedt-Enkel
katrin.lundsted-enkelt@acureomics.com
Analysis and validation of humanised mouse models and iPSC in WP7; Numerous sample extracts from humanised mice will be analysed for metabolic profiles by gas chromatography mass spectrometry (GC-MS; GCTOFMS) and liquid chromatography mass spectrometry (LC-MS; QTOF, LTQ-Orbitrap). Targeted metabolomics of lipid mediators present at concentrations too low to be detected via global metabolomics methods will also be applied. This includes analysis of eicosanoids, endocannabinoids, sphingolipids and neuroprostanes. In addition, the competence and expertise of the two most advanced NMR laboratories in Sweden (Swedish NMR centre in Gothenburg and that in Umeå) are included in the national metabolomics infrastructure. All the magnets are adapted for high-resolution studies of biological macromolecules in solution. To evaluate the huge amount of data obtained by the omics technologies multivariate statistics are needed. We will model and interpret data in a systems biology approach to enable correlation of metabolite profiles with other molecular profiles. Statistical data integration of multiple omics data will be used to identify biochemical pathways as well as novel therapeutic targets and characterise the system interactions dynamics in biological processes.
AcureOmics AB is currently (2009-2013) a partner in a Marie Curie Initial Training Network, in the BOLD project (Biology of Liver and Pancreatic Development and Disease). In BOLD metabolomic approaches have been demonstrated to be useful in identifying biochemical pathways for drug action in animals and cell lines. After exposure to chemicals or chemical mixtures, dynamic processes involving interactions between the exogenous chemicals and molecular targets implicated in cellular signaling pathways such as cell proliferation and differentiation, apoptosis, angiogenesis, cell cycle regulation, oxidative stress, inflammation, immune responses and metabolic homeostasis can be affected and lead to alterations in the endogenous metabolite patterns. Metabolomics was also able to depict pathways involved in different organ systems when analyzing body fluids, tissue samples or indeed, the whole homogenized animal. In bioinformatics and biostatistics, Drs. Trygg and Lundstedt have for more than 25 years developed state of the art statistical methods for analysis and visualization of large amount of data. For instance, the method orthogonal partial least-squares (OPLS) were developed by Dr. Trygg. AO have long experience in systems biology approaches to integrate biological information across multiple ‘omics platforms to elucidate biochemical mechanisms and pathways and link these to clinical phenotypes.
Relevant publications:
1, Trygg J, et al. (2007) Chemometrics in Metabonomics J Proteome Res. 6,469 -479.
2, Eriksson L, et al. (2004) Using chemometrics for navigating in the large data sets of genomics, proteomics, and metabonomics (gpm). Analytical and Bioanalytical Chemistry 380, (3), 419-429.
3, Trygg J, et al. (2002) Orthogonal projections to latent structures (O-PLS). Journal of Chemometrics 16, (3), 119-128.