Applications of a new subspace clustering algorithm (COSA) in medical systems biology

A novel clustering approach named Clustering Objects on Subsets of Attributes (COSA) has been proposed (Friedman and Meulman, (2004). Clustering objects on subsets of attributes. J. R. Statist. Soc. B 66, 1–25.) for unsupervised analysis of complex data sets. We demonstrate its usefulness in medical systems biology studies. Examples of metabolomics analyses are described as well as the unsupervised clustering based on the study of disease pathology and intervention effects in rats and humans. In comparison to principal components analysis and hierarchical clustering based on Euclidean distance, COSA shows an enhanced capability to trace partial similarities in groups of objects enabling a new discovery approach in systems biology as well as offering a unique approach to reveal common denominators of complex multi-factorial diseases in animal and human studies. Doris Damian, Matej Orešič, and Elwin Verheij contributed equally to this work.     

TNFα activation of PKCδ, mediated by NFκB and ER stress,cross-talks with the insulin signaling cascade

TNFα plays key roles in the regulation of inflammation, cell death, and proliferation and its signaling cascade cross-talks with the insulin signaling cascade. PKCδ, a novel PKC isoform, is known to participate in proximal TNFα signaling events. However, it has remained unclear whether PKCδ plays a role in distal TNFα signaling events. Here we demonstrate that PKCδ is activated by TNFα in a delayed fashion that is temporally associated with JNK activation. To investigate the signaling pathways activating PKCδ and JNK, we used pharmacological and genetic inhibitors of NFκB. We found that inhibition of NFκB attenuated PKCδ and JNK activations. Further analysis revealed that ER stress contributes to TNFα-stimulated PKCδ and JNK activations. To investigate the role of PKCδ in TNFα action, we used 29-mer shRNAs to silence PKCδ expression. A reduction of ~90% in PKCδ protein levels reduced TNFα-stimulated stress kinase activation, including JNK. Further, PKCδ was necessary for thapsigargin-stimulated JNK activation. Because thapsigargin is a potent inducer of ER stress, we determined whether PKCδ was necessary for induction of the UPR. Indeed, a reduction in PKCδ protein levels reduced thapsigargin-stimulated CHOP induction, a hallmark of the UPR, but not BiP/GRP78 induction, suggesting that PKCδ does not globally regulate the UPR. Next, the role of PKCδ in TNFα mediated cross-talk with the insulin signaling pathway was investigated in cells expressing human IRS-1 and a 29-mer shRNA to silence PKCδ expression. We found that a reduction in PKCδ protein levels reversed the TNFα-mediated reduction in insulin-stimulated IRS-1 Tyr phosphorylation, Akt activation, and glycogen synthesis. In addition, TNFα-stimulated IRS protein Ser/Thr phosphorylation and degradation were blocked. Our results indicate that: 1) NFκB and ER stress contribute in part to PKCδ activation; 2) PKCδ plays a key role in the propagation of the TNFα signal; and 3) PKCδ contributes to TNFα-induced inhibition of insulin signaling events.     

Thiol-reactive clenbuterol analogues conjugated to bovine serum albumin

Several novel thiol-reactive clenbuterol analogues were coupled in high yield with bovine serum albumin (BSA). After labelling of unreacted cysteines with maleimide spin label (MiSL), the yield of the coupling reaction was determined by electron paramagnetic resonance (EPR) spectroscopy and spectral analysis. Two spin-probe populations with different mobility states were quantitatively determined. Molecular dynamics was used to model the structure of clenbuterol analogues and spin label conjugated to BSA and recognition of conjugates by anti-clenbuterol antibodies was demonstrated. The recognition of BSA-A, BSA-C and BSA-S conjugates with monoclonal and polyclonal anti-clenbuterol (mCLB-Ab and rCLB-Ab) antibodies was an indication, that chlorine substituents on the aromatic ring of clenbuterol derivatives are not necessary for the binding of antibodies to the conjugates. These results confirmed the importance of the tert-butylamino group as a part of the epitope and contribute to the understanding of the recognition process with anti-clenbuterol antibodies.     

Serum lipidomics meets cardiac magnetic resonance imaging: profiling of subjects at risk of dilated cardiomyopathy

Dilated cardiomyopathy (DCM), characterized by left ventricular dilatation and systolic dysfunction, constitutes a significant cause for heart failure, sudden cardiac death or need for heart transplantation. Lamin A/C gene (LMNA) on chromosome 1p12 is the most significant disease gene causing DCM and has been reported to cause 7-9% of DCM leading to cardiac transplantation. We have previously performed cardiac magnetic resonance imaging (MRI) to LMNA carriers to describe the early phenotype. Clinically, early recognition of subjects at risk of developing DCM would be important but is often difficult. Thus we have earlier used the MRI findings of these LMNA carriers for creating a model by which LMNA carriers could be identified from the controls at an asymptomatic stage. Some LMNA mutations may cause lipodystrophy. To characterize possible effects of LMNA mutations on lipid profile, we set out to apply global serum lipidomics using Ultra Performance Liquid Chromatography coupled to mass spectrometry in the same LMNA carriers, DCM patients without LMNA mutation and controls. All DCM patients, with or without LMNA mutation, differed from controls in regard to distinct serum lipidomic profile dominated by diminished odd-chain triglycerides and lipid ratios related to desaturation. Furthermore, we introduce a novel approach to identify associations between the molecular lipids from serum and the MR images from the LMNA carriers. The association analysis using dependency network and regression approaches also helped us to obtain novel insights into how the affected lipids might relate to cardiac shape and volume changes. Our study provides a framework for linking serum derived molecular markers not only with clinical endpoints, but also with the more subtle intermediate phenotypes, as derived from medical imaging, of potential pathophysiological relevance.     

Drug metabolome of the simvastatin formed by human intestinal microbiota in vitro

The human colon contains a diverse microbial population which contributes to degradation and metabolism of food components. Drug metabolism in the colon is generally poorly understood. Metabolomics techniques and in vitro colon models are now available which afford detailed characterization of drug metabolites in the context of colon metabolism. The aim of this work was to identify novel drug metabolites of Simvastatin (SV) by using an anaerobic human in vitro colon model at body temperature coupled with systems biology platform, excluding the metabolism of the host liver and intestinal epithelia. Comprehensive two-dimensional gas chromatography with a time-of-flight mass spectrometry (GC×GC-TOFMS) was used for the metabolomic analysis. Metabolites showing the most significant differences in the active faecal suspension were elucidated in reference with SV fragmentation and compared with controls: inactive suspension or buffer with SV, or with active suspension alone. Finally, time courses of selected metabolites were investigated. Our data suggest that SV is degraded by hydrolytic cleavage of methylbutanoic acid from the SV backbone. Metabolism involves demethylation of dimethylbutanoic acid, hydroxylation/dehydroxylation and β-oxidation resulting in the production of 2-hydroxyisovaleric acid (3-methyl-2-hydroxybutanoic acid), 3-hydroxybutanoic acid and lactic acid (2-hydroxypropanoic acid), and finally re-cyclisation of heptanoic acid (possibly de-esterified and cleaved methylpyranyl arm) to produce cyclohexanecarboxylic acid. Our study elucidates a pathway of colonic microbial metabolism of SV as well as demonstrates the applicability of the in vitro colon model and metabolomics to the discovery of novel drug metabolites from drug response profiles.     

Processing methods for differential analysis of LC/MS profile data

Background  

Liquid chromatography coupled to mass spectrometry (LC/MS) has been widely used in proteomics and metabolomics research. In this context, the technology has been increasingly used for differential profiling, i.e. broad screening of biomolecular components across multiple samples in order to elucidate the observed phenotypes and discover biomarkers. One of the major challenges in this domain remains development of better solutions for processing of LC/MS data.     

Cosecretion of protease inhibitor stabilizes antibodies produced by plant roots

A plant-based system for continuous production of monoclonal antibodies based on the secretion of immunoglobulin complexes from plant roots into a hydroponic medium (rhizosecretion) was engineered to produce high levels of single-chain and full-size immunoglobulins. Replacing the original signal peptides of monoclonal antibodies with a plant-derived calreticulin signal increased the levels of antibody yield 2-fold. Cosecretion of Bowman-Birk Ser protease inhibitor reduced degradation of the immunoglobulin complexes in the default secretion pathway and further increased antibody production to 36.4 microg/g root dry weight per day for single-chain IgG1 and 21.8 microg/g root dry weight per day for full-size IgG4 antibodies. These results suggest that constitutive cosecretion of a protease inhibitor combined with the use of the plant signal peptide and the antibiotic marker-free transformation system offers a novel strategy to achieve high yields of complex therapeutic proteins secreted from plant roots.