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Pair-wise multicomparison and OPLS analyses of cold-acclimation phases in Siberian spruce
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Umeå University, Faculty of Science and Technology, Department of Chemistry.
Department of Biology, Norwegian University of Science and Technology.
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2012 (English)In: Metabolomics, ISSN 1573-3882, Vol. 8, no Suppl 1, 123-130 p.Article in journal (Refereed) Published
Abstract [en]

Analysis of metabolomics data often goes beyond the task of discovering biomarkers and can be aimed at recovering other important characteristics of observed metabolomic changes. In this paper we explore different methods to detect the presence of distinctive phases in seasonal-responsive changes of metabolomic patterns of Siberian spruce (Picea obovata) during cold acclimation occurred in the period from mid-August to January. Multivariate analysis, specifically orthogonal projection to latent structures discriminant analysis (OPLSDA), identified time points where the metabolomic patterns underwent substantial modifications as a whole, revealing four distinctive phases during acclimation. This conclusion was re-examined by a univariate analysis consisting of multiple pair-wise comparisons to identify homogeneity intervals for each metabolite. These tests complemented OPLS-DA, clarifying biological interpretation of the classification: about 60% of metabolites found responsive to the cold stress indeed changed at one or more of the time points predicted by OPLS-DA. However, the univariate approach did not support the proposed division of the acclimation period into four phases: less than 10% of metabolites altered during the acclimation had homogeneous levels predicted by OPLS-DA. This demonstrates that coupling the classification found by OPLS-DA and the analysis of dynamics of individual metabolites obtained by pair-wise multicomparisons reveals a more correct characterization of biochemical processes in freezing tolerant trees and leads to interpretations that cannot be deduced by either method alone. The combined analysis can be used in other ‘omics’-studies, where response factors have a causal dependence (like the time in the present work) and pairwise multicomparisons are not conservative.

Place, publisher, year, edition, pages
Springer, 2012. Vol. 8, no Suppl 1, 123-130 p.
Keyword [en]
metabolomics, multiple hypothesis test, multivariate analysis, OPLS-DA, Siberian spruce, cold-acclimation
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:umu:diva-43509DOI: 10.1007/s11306-011-0304-5OAI: oai:DiVA.org:umu-43509DiVA: diva2:414376
Note
Published online 11 april 2011. Copywright, The Author(s) 2011. This article is published with open access at Springerlink.comAvailable from: 2011-05-03 Created: 2011-05-03 Last updated: 2012-08-09Bibliographically approved
In thesis
1. Proteomics and metabolomics in biological and medical applications
Open this publication in new window or tab >>Proteomics and metabolomics in biological and medical applications
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Biological processes in living organisms consist of a vast number of different molecular networks and interactions, which are complex and often hidden from our understanding. This work is focused on recovery of such details for two quite distant examples: acclimation to extreme freezing tolerance in Siberian spruce (Picea obovata) and detection of proteins associated with prostate cancer.

The first biological system in the study, upon P. obovata, is interesting by this species ability to adapt and sustain extremely low temperatures, such as -60⁰C or below. Despite decades of investigations, the essential features and mechanisms of the amazing ability of this species still remains unclear. To enhance knowledge about extreme freezing tolerance, the metabolome and proteome of P. obovata’s needles were collected during the tree’s acclimation period, ranging from mid August to January, and have been analyzed.

The second system within this study is the plasma proteome analysis of high risk prostate cancer (PCa) patients, with and without bone metastases. PCa is one of the most common cancers among Swedish men, which can abruptly develop into an aggressive, lethal disease. The diagnostic tools, including PSA-tests, are insufficient in predicting the disease’s aggressiveness and novel prognostic markers are urgently required.

Both biological systems have been analyzed following similar steps: by two-dimensional difference gel electrophoresis (2D-DIGE) techniques, followed by protein identification using mass spectrometry (MS) analysis and multivariate methods. Data processing has been utilized for searching for proteins that serve as unique indicators for characterizing the status of the systems. In addition, the gas chromatography-mass spectrometry (GC-MS) study of the metabolic content of P.obovata’s needles, from the extended observation period, has been performed. The studies of both systems, combined with thorough statistical analysis of experimental outcomes, have resulted in novel insights and features for both P. obovata and prostate cancer. In particular, it has been shown that dehydrins, Hsp70s, AAA+ ATPases, lipocalin and several proteins involved in cellular metabolism etc., can be uniquely associated with acclimation to extreme freezing in conifers. Metabolomic analysis of P. obovata needles has revealed systematic metabolic changes in carbohydrate and lipid metabolism. Substantial increase of raffinose, accumulation of desaturated fatty acids, sugar acids, sugar alcohols, amino acids and polyamines that may act as compatible solutes or cryoprotectants have all been observed during the acclimation process.

Relevant proteins for prostate cancer progression and aggressiveness have been identified in the plasma proteome study, for patients with and without bone metastasis. Proteins associated with lipid transport, coagulation, inflammation and immune response have been found among them. 

Place, publisher, year, edition, pages
Umeå: Kemiska institutionen, Umeå Universitet, 2011. 44 p.
Keyword
2D-DIGE, biomarkers, cold-acclimation, conifer, freezing tolerance, GC-MS, metabolomics, multiple hypothesis test, multivariate analysis, OPLS-DA, Picea obovata, plasma, prostate cancer, proteomics, ProteoMiner, Siberian spruce
National Category
Chemical Sciences
Identifiers
urn:nbn:se:umu:diva-43520 (URN)978-91-7459-204-7 (ISBN)
Public defence
2011-05-25, KBC-huset, KB3A9, Umeå Universitet, Umeå, 10:00 (English)
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Supervisors
Available from: 2011-05-04 Created: 2011-05-03 Last updated: 2014-12-10Bibliographically approved

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Shiryaeva, LiudmilaAntti, HenrikSchröder, Wolfgang P
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