Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data

Bylesjö, Max; Eriksson, Daniel; Kusano, Miyako; Moritz, Thomas; Trygg, Johan

doi:10.1111/j.1365-313x.2007.03293.x

Cited by 209 publications

(168 citation statements)

References 42 publications

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“…Normalized data were exported to sIMCA-p+ (version 11.5, umetrics, umeå, sweden) to perform orthogonal partial least squares discriminant analysis (OpLs-DA) where grouping trends and outliers in the data were observed and a model was constructed to identify marker metabolites that differentiated GC and non-GC cohorts (33,34). From the normalized data, an indication of statistical significance was based on a non-parametric two-tailed paired Wilcoxon analysis performed with spss 13.0 for Windows (spss, Chicago, IL).…”

Section: Data Processing For Gc/ms and Statistical Analysismentioning

confidence: 99%

Tissue metabolomic fingerprinting reveals metabolic disorders associated with human gastric cancer morbidity

Wang²,

Liu³

et al. 2011

Oncol Rep

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Abstract. the principal way to improve the outcome of gastric cancer (GC) is to predict carcinogenesis and metastasis at an early stage. the aims of the present study were to test the hypothesis that distinct metabolic profiles are reflected in GC tissues and to further explore potential biomarkers for GC diagnosis. Gas chromatography/mass spectrometry (GC/Ms) was utilized to analyze tissue metabolites from 30 GC patients. A diagnostic model for GC was constructed using orthogonal partial least squares discriminant analysis (OpLs-DA), and the metabolomic data were analyzed using the non-parametric Wilcoxon rank sum test to identify the metabolic tissue biomarkers for GC. Over 100 signals were routinely detected in one single total ion current (tIC) chromatogram, and the OPLS-DA model generated from the metabolic profile of the tissues adequately discriminated the GC tissues from the normal mucosae. Among the low-molecular-weight endogenous metabolites, a total of 41 compounds, such as amino acids, organic acids, carbohydrates, fatty acids and steroids, were detected, and 15 differential metabolites were identified with significant difference (p<0.05). A total of 20 variables were noted which contributed to a great extent in the discriminating OpLs-DA model (VIp value >1.0), among which 12 metabolites were identified using both VIP values (VIP >1) and the Wilcoxon test (p<0.05). In conclusion, the identification of the metabolites associated with GC morbidity potentially revealed perturbations of glycolysis, fatty acid β-oxidation, cholesterol and amino acid metabolism. these results suggest that tissue metabolic profiles have great potential in detecting GC and may aid in understanding its underlying mechanisms.

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Section: Data Processing For Gc/ms and Statistical Analysismentioning

confidence: 99%

Tissue metabolomic fingerprinting reveals metabolic disorders associated with human gastric cancer morbidity

Wang²,

Liu³

et al. 2011

Oncol Rep

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“…In the context of feature selection from both data sets, one closely related work proved to bring biologically meaningful results is the O2PLS model (Trygg and Wold, 2003), associated to variable selection in Bylesjö et al (2007) for combining and selecting transcript and metabolite data in Arabidopsis Thaliana in a regression framework. O2PLS decomposes each data set in three structures (predictive, unique and residual).…”

Section: Introductionmentioning

confidence: 99%

A Sparse PLS for Variable Selection when Integrating Omics Data

Cao¹,

Rossouw²,

Robert-Granié³

et al. 2008

Statistical Applications in Genetics and Molecular Biology

433

321

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“…Techniques for deconvoluting multivariate data are common analytic tools in microarray data analyses, systems biology studies, and chemometric detection (41)(42)(43)(44)(45), but their implementation for discovering atomic-level informa-FIGURE 3. FTIR spectra illustrate quantifiable changes in secondary structure resulting from challenges to L5, either by drug inhibition or residue substitution.…”

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confidence: 99%

Allosteric Drug Discrimination Is Coupled to Mechanochemical Changes in the Kinesin-5 Motor Core

Kim

Buckley

Learman

et al. 2010

Journal of Biological Chemistry

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Essential in mitosis, the human Kinesin-5 protein is a target for >80 classes of allosteric compounds that bind to a surfaceexposed site formed by the L5 loop. Not established is why there are differing efficacies in drug inhibition. Here we compare the ligand-bound states of two L5-directed inhibitors against 15 Kinesin-5 mutants by ATPase assays and IR spectroscopy. Biochemical kinetics uncovers functional differences between individual residues at the N or C termini of the L5 loop. Infrared evaluation of solution structures and multivariate analysis of the vibrational spectra reveal that mutation and/or ligand binding not only can remodel the allosteric binding surface but also can transmit long range effects. Changes in L5-localized 3 10 helix and disordered content, regardless of substitution or drug potency, are experimentally detected. Principal component analysis couples these local structural events to two types of rearrangements in ␤-sheet hydrogen bonding. These transformations in ␤-sheet contacts are correlated with inhibitory drug response and are corroborated by wild type Kinesin-5 crystal structures. Despite considerable evolutionary divergence, our data directly support a theorized conserved element for long distance mechanochemical coupling in kinesin, myosin, and F 1 -ATPase. These findings also suggest that these relatively rapid IR approaches can provide structural biomarkers for clinical determination of drug sensitivity and drug efficacy in nucleotide triphosphatases.Allostery is important in controlled catalysis, signal transduction, and apoptosis (1). The classic view of proteins demonstrating this property (2) asserts that binding of a ligand at one site provokes conformational changes at a remote, second site. Recent studies (3) evaluating underlying mechanisms of allostery alternatively suggest that ligand binding results in selection of preexisting conformational substates. Implicit in the latter model is the principle that interactions between the orthosteric and allosteric sites are tightly linked through structure and thermodynamics (4). Active challenges in structural biology, which are central to this work, are deciphering the chemical nature of the ligand-protein interactions as well as how energy is transduced through protein structures to transmit allosteric events.Our experimental model, the human Kinesin-5 motor protein (Eg5 or KSP), plays key roles in bipolar mitotic spindle formation and is a protein target for allosteric compounds (5-7) that alter catalytic ATPase activity of the protein (8, 9). Biochemical studies demonstrate a wide concentration range of inhibition by these compounds (10 -12); there may be differences in the kinetic mechanism of allostery (13-15), and even allosteric activation (16) is possible. The best characterized inhibitors, monastrol (10) and S-trityl-L-cysteine (STC)2 (11), were uncovered from independent chemical screens.Interest in these allosteric compounds has been acute because they are potential anticancer agents. Additionally, these compo...

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Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data

Cited by 209 publications

References 42 publications

Tissue metabolomic fingerprinting reveals metabolic disorders associated with human gastric cancer morbidity

Tissue metabolomic fingerprinting reveals metabolic disorders associated with human gastric cancer morbidity

A Sparse PLS for Variable Selection when Integrating Omics Data

Allosteric Drug Discrimination Is Coupled to Mechanochemical Changes in the Kinesin-5 Motor Core

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