Endothelin-1 and angiotensin II contribute to BNP but not c-fos gene expression response to elevated load in isolated mice hearts

The early events in the cardiac hypertrophic process induced by hemodynamic load include activation of B-type natriuretic peptide (BNP) and c-fos gene expression. However, it is unknown whether stretch acts directly or through local paracrine factors to trigger changes in cardiac gene expression. Herein we studied the involvement of endothelin-1 (ET-1) and angiotensin II (Ang II) in load-induced activation of left ventricular BNP and c-fos gene expression using an in vitro stretch model in isolated perfused adult mice hearts. Two-hour stretch induced by increasing coronary flow rate from 2 to 5 ml/min increased the expression of BNP and c-fos genes by 1.9- and 1.5-fold, respectively (P<0.001 and P<0.05). A mixed ET(A/B) receptor antagonist bosentan attenuated the BNP gene expression response to load by 58% (P<0.005). A similar 53% inhibition was observed with the selective ET(A) receptor blocker BQ-123 (P<0.05). Type 1 Ang II receptor antagonist CV-11974 decreased the activation of BNP gene expression by 50% (P<0.05). In contrast, the activation of c-fos gene expression was not inhibited by antagonists of ET(A/B) and AT(1) receptors. Our results show that ET-1 and Ang II play a key role in the induction of BNP, but not c-fos gene expression in response to load in intact adult murine hearts.     

Rhizavidin from Rhizobium etli: the first natural dimer in the avidin protein family

Rhizobium etli CFN42 is a symbiotic nitrogen-fixing bacterium of the common bean Phaseolus vulgaris. The symbiotic plasmid p42d of R. etli comprises a gene encoding a putative (strept)avidin-like protein, named rhizavidin. The amino acid sequence identity of rhizavidin in relation to other known avidin-like proteins is 20-30%. The amino acid residues involved in the (strept)avidin-biotin interaction are well conserved in rhizavidin. The structural and functional properties of rhizavidin were carefully studied, and we found that rhizavidin shares characteristics with bradavidin, streptavidin and avidin. However, we found that it is the first naturally occurring dimeric protein in the avidin protein family, in contrast with tetrameric (strept)avidin and bradavidin. Moreover, it possesses a proline residue after a flexible loop (GGSG) in a position close to Trp-110 in avidin, which is an important biotin-binding residue. [3H]Biotin dissociation and ITC (isothermal titration calorimetry) experiments showed dimeric rhizavidin to be a high-affinity biotin-binding protein. Its thermal stability was lower than that of avidin; although similar to streptavidin, it was insensitive to proteinase K. The immunological cross-reactivity of rhizavidin was tested with human serum samples obtained from cancer patients exposed to (strept)avidin. No significant cross-reactivity was observed. The biodistribution of the protein was studied by SPECT (single-photon emission computed tomography) imaging in rats. Similarly to avidin, rhizavidin was observed to accumulate rapidly, mainly in the liver. Evidently, rhizavidin could be used as a complement to (strept)avidin in (strept)avidin-biotin technology.     

Effects of a biocontrol agent Chondrostereum purpureum on sprouting of Sorbus aucuparia and Populus tremula after four growing seasons

The efficacy of a decay fungus Chondrostereum purpureum (Pers. ex Fr.) Pouzar to prevent sprouting of two tree species, rowan (Sorbus aucuparia L.) and European aspen (Populus tremula L.) was investigated in a four-growing season study. The efficacy of C. purpureum compared with the control (cutting only) increased during the whole study period indicating that long-term studies are needed to reveal the real effect of the biocontrol treatment. At the end of the study period the mortality of treated rowan stumps was 50 % and that of European aspen 77 %, i.e. clearly higher than in the control with mortality 14 and 52 % respectively. The height of living sprouts was considerably lower in the C. purpureum treatment than in the control. Furthermore, our results indicated that a high number of surrounding conspecific saplings decreased whereas a high number of red raspberry (Rubus idaeus L.) shoots increased mortality of C. purpureum treated stumps.     

Functional prediction of unidentified lipids using supervised classifiers

Mass spectrometry (MS)-based metabolomics studies often require handling of both identified and unidentified metabolite data. In order to avoid bias in data interpretation, it would be of advantage for the data analysis to include all available data. A practical challenge in exploratory metabolomics analysis is therefore how to interpret the changes related to unidentified peaks. In this paper, we address the challenge by predicting the class membership of unknown peaks by applying and comparing multiple supervised classifiers to selected lipidomics datasets. The employed classifiers include k-nearest neighbours (k-NN), support vector machines (SVM), partial least squares and discriminant analysis (PLS-DA) and Naive Bayes methods which are known to be effective and efficient in predicting the labels for unseen data. Here, the class label predictions are sought for unidentified lipid profiles coming from high throughput global screening in Ultra Performance Liquid Chromatography Mass Spectrometry (UPLC^TM/MS) experimental setup. Our investigation reveals that k-NN and SVM classifiers outperform both PLS-DA and Naive Bayes classifiers. Naive Bayes classifier perform poorly among all models and this observation seems logical as lipids are highly co-regulated and do not respect Naive Bayes assumptions of features being conditionally independent given the class. Common label predictions from k-NN and SVM can serve as a good starting point to explore full data and thereby facilitating exploratory studies where label information is critical for the data interpretation.