Quantitative Analysis of Porcine Endogenous Retroviruses in Different Organs of Transgenic Pigs Generated for Xenotransplantation

The pig appears to be the most promising animal donor of organs for use in human recipients. Among several types of pathogens found in pigs, one of the greatest problems is presented by porcine endogenous retroviruses (PERVs). Screening of the source pig herd for PERVs should include analysis of both PERV DNA and RNA. Therefore, the present study focuses on quantitative analysis of PERVs in different organs such as the skin, heart, muscle, and liver and blood of transgenic pigs generated for xenotransplantation. Transgenic pigs were developed to express the human α-galactosidase, the human α-1,2-fucosyltransferase gene, or both genetic modifications of the genome (Lipinski et al., Medycyna Wet 66:316–322, 2010; Lipinski et al., Ann Anim Sci 12:349–356, 2012; Wieczorek et al., Medycyna Wet 67:462–466, 2011). The copy numbers of PERV DNA and RNA were evaluated using real-time Q-PCR and QRT-PCR, respectively. Comparative analysis of all PERV subtypes revealed the following relationships: PERV A > PERV B > PERV C. PERV A and B were found in all samples, whereas PERV C was detected in 47 % of the tested animals. The lowest level of PERV DNA was shown in the muscles for PERV A and B and in blood samples for PERV C. The lowest level of PERV A RNA was found in the skin, whereas those of PERV B and C RNA were found in liver specimens. Quantitative analysis revealed differences in the copy number of PERV subtypes between various organs of transgenic pigs generated for xenotransplantation. Our data support the idea that careful pig selection for organ donation with low PERV copy number may limit the risk of retrovirus transmission to the human recipients.     

La Simbiosi Cloromicetica

Summary

The A. takes in to consideration the nutrition of green plants when the soil is excessively poor of nutritive elements.

In these conditios it is worth the intervention of moulds capable of utilising the nutritive elements wich are found in the organic complex of the soil. A “chloromycetic symbiosis” is in this way formed which is extensive over the Earth and which concerns vegetation cowering almost a half of the vegetation growing area.

Besides the effects on nutrition the A. considers the effects on the physiology of developpement and of reproduction.     

Targeting of calsequestrin to sarcoplasmic reticulum after deletions of its acidic carboxy terminus

Calsequestrin (CS) is theCa²⁺ binding protein of thejunctional sarcoplasmic reticulum (jSR) lumen. Recently, a chimericCS-HA1, obtained by adding the nine-amino-acid viral epitopehemagglutinin (HA1) to the COOH terminus of CS, was shown to becorrectly segregated to the sarcoplasmic reticulum [A. Nori, K. A. Nadalini, A. Martini, R. Rizzuto, A. Villa, and P. Volpe.Am. J. Physiol. 272 (Cell Physiol. 41): C1420-C1428,1997]. A putative targeting mechanism of CS to jSR implieselectrostatic interactions between negative charges on CS and positivecharges on intraluminal domains of jSR integral proteins, such astriadin and junctin. To test this hypothesis, 2 deletion mutants ofchimeric CS were engineered: CS-HA1Glu-Asp, in which the 14 acidicresidues[-Glu-(Asp)₅-Glu-(Asp)₇-] of the COOH-terminal tail were removed, andCS-HA149_COOH, in which thelast, mostly acidic, 49 residues of the COOH terminus were removed.Both mutant cDNAs were transiently transfected in HeLa cells, myoblastsof rat skeletal muscle primary cultures, or regenerating soleus musclefibers of adult rats. The expression and intracellular localization ofCS-HA1 mutants were studied by epifluorescence microscopy with use ofantibodies against CS or HA1. CS-HA1 mutants were shown to beexpressed, sorted, and correctly segregated to jSR. Thus short or longdeletions of the COOH-terminal acidic tail do not influence thetargeting mechanism of CS.

     

Continuity of Procambium and Anomalous Cambium During Formation of Successive Cambia in Celosia argentea

The development of woody plants is related to the continuity of the procambium and cambium. Whether such a continuity is present in plants with successive cambia, especially in those, where the first cambium is formed outside the primary vascular bundles, has not been analyzed so far. Therefore, we studied the development of vascular meristem in Celosia argentea, in which the first and successive cambial cylinders arise outside the primary bundles and, intriguingly, in the literature are interpreted as developmentally independent structures. Our results showed that in C. argentea, the outermost procambial cells maintain their meristematic characteristics during differentiation of vascular bundles and divide periclinally, forming the zone of procambium-derived cells outside the primary bundles. This zone comprises parenchyma cells bordering the bundles, and a continuous ring of the incipient cambial cells neighboring the primary cortex. Later in the development, the ability to preserve the outermost cells in the cambium undifferentiated is repeated during the formation of successive cylinders of cambia. Together, our results clearly point to the developmental continuity of the procambium and successive cambia in C. argentea, despite their seemingly spatial distinctiveness. We postulate that the mechanism demonstrated in C. argentea is universal and orchestrates the development of successive cambia in other plant species.

     

Machine learning and data mining in complex genomic data—a review on the lessons learned in Genetic Analysis Workshop 19

In the analysis of current genomic data, application of machine learning and data mining techniques has become more attractive given the rising complexity of the projects. As part of the Genetic Analysis Workshop 19, approaches from this domain were explored, mostly motivated from two starting points. First, assuming an underlying structure in the genomic data, data mining might identify this and thus improve downstream association analyses. Second, computational methods for machine learning need to be developed further to efficiently deal with the current wealth of data.In the course of discussing results and experiences from the machine learning and data mining approaches, six common messages were extracted. These depict the current state of these approaches in the application to complex genomic data. Although some challenges remain for future studies, important forward steps were taken in the integration of different data types and the evaluation of the evidence. Mining the data for underlying genetic or phenotypic structure and using this information in subsequent analyses proved to be extremely helpful and is likely to become of even greater use with more complex data sets.