Endogenous control genes in complex vascular tissue samples

<p>Abstract</p> <p>Background</p> <p>Gene expression microarrays and real-time PCR are common methods used to measure mRNA levels. Each method has a fundamentally different approach of normalization between samples. Relative quantification of gene expression using real-time PCR is often done using the 2^(-ΔΔCt) method, in which the normalization is performed using one or more endogenous control genes. The choice of endogenous control gene is often arbitrary or bound by tradition. We here present an analysis of the differences in expression results obtained with microarray and real-time PCR, dependent on different choices of endogenous control genes.</p> <p>Results</p> <p>In complex tissue, microarray data and real-time PCR data show the best correlation when endogenous control genes are omitted and the normalization is done relative to total RNA mass, as measured before reverse transcription.</p> <p>Conclusion</p> <p>We have found that for real-time PCR in heterogeneous tissue samples, it may be a better choice to normalize real-time PCR Ct values to the carefully measured mass of total RNA than to use endogenous control genes. We base this conclusion on the fact that total RNA mass normalization of real-time PCR data shows better correlation to microarray data. Because microarray data use a different normalization approach based on a larger part of the transcriptome, we conclude that omitting endogenous control genes will give measurements more in accordance with actual concentrations.</p

Directed Evolution of Glutathione Transferases Guided by Multivariate Data Analysis

Evolution of enzymes with novel functional properties has gained much attention in recent years. Naturally evolved enzymes are adapted to work in living cells under physiological conditions, circumstances that are not always available for industrial processes calling for novel and better catalysts. Furthermore, altering enzyme function also affords insight into how enzymes work and how natural evolution operates. Previous investigations have explored catalytic properties in the directed evolution of mutant libraries with high sequence variation. Before this study was initiated, functional analysis of mutant libraries was, to a large extent, restricted to uni- or bivariate methods. Consequently, there was a need to apply multivariate data analysis (MVA) techniques in this context. Directed evolution was approached by DNA shuffling of glutathione transferases (GSTs) in this thesis. GSTs are multifarious enzymes that have detoxication of both exo- and endogenous compounds as their primary function. They catalyze the nucleophilic attack by the tripeptide glutathione on many different electrophilic substrates. Several multivariate analysis tools, e.g. principal component (PC), hierarchical cluster, and K-means cluster analyses, were applied to large mutant libraries assayed with a battery of GST substrates. By this approach, evolvable units (quasi-species) fit for further evolution were identified. It was clear that different substrates undergoing different kinds of chemical transformation can group together in a multi-dimensional substrate-activity space, thus being responsible for a certain quasi-species cluster. Furthermore, the importance of the chemical environment, or substrate matrix, in enzyme evolution was recognized. Diverging substrate selectivity profiles among homologous enzymes acting on substrates performing the same kind of chemistry were identified by MVA. Important structure-function activity relationships with the prodrug azathioprine were elucidated by segment analysis of a shuffled GST mutant library. Together, these results illustrate important methods applied to molecular enzyme evolution

Diverging Alternative Splicing Fingerprints in the Transforming Growth Factor-β Signaling Pathway Identified in Thoracic Aortic Aneurysms

Impaired regulation of the transforming growth factor-β (TGFβ) signaling pathway has been linked to thoracic aortic aneurysm (TAA). Previous work has indicated that differential splicing is a common phenomenon, potentially influencing the function of proteins. In the present study we investigated the occurrence of differential splicing in the TGFβ pathway associated with TAA in patients with bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV). Affymetrix human exon arrays were applied to 81 intima/media tissue samples from dilated (n = 51) and nondilated (n = 30) aortas of TAV and BAV patients. To analyze the occurrence of alternative splicing in the TGFβ pathway, multivariate techniques, including principal component analysis and OPLS-DA (orthogonal partial least squares to latent structures discriminant analysis), were applied on all exons (n = 614) of the TGFβ pathway. The scores plot, based on the splice index of individual exons, showed separate clusters of patients with both dilated and nondilated aorta, thereby illustrating the potential importance of alternative splicing in TAA. In total, differential splicing was detected in 187 exons. Furthermore, the pattern of alternative splicing is clearly differs between TAV and BAV patients. Differential splicing was specific for BAV and TAV patients in 40 and 86 exons, respectively, and splicings of 61 exons were shared between the two phenotypes. The occurrence of differential splicing was demonstrated in selected genes by reverse transcription–polymerase chain reaction. In summary, alternative splicing is a common feature of TAA formation. Our results suggest that dilatation in TAV and BAV patients has different alternative splicing fingerprints in the TGFβ pathway