Pig transgenesis by Sleeping Beauty DNA transposition

Modelling of human disease in genetically engineered pigs provides unique possibilities in biomedical research and in studies of disease intervention. Establishment of methodologies that allow efficient gene insertion by non-viral gene carriers is an important step towards development of new disease models. In this report, we present transgenic pigs created by Sleeping Beauty DNA transposition in primary porcine fibroblasts in combination with somatic cell nuclear transfer by handmade cloning. Göttingen minipigs expressing green fluorescent protein are produced by transgenesis with DNA transposon vectors carrying the transgene driven by the human ubiquitin C promoter. These animals carry multiple copies (from 8 to 13) of the transgene and show systemic transgene expression. Transgene-expressing pigs carry both transposase-catalyzed insertions and at least one copy of randomly inserted plasmid DNA. Our findings illustrate critical issues related to DNA transposon-directed transgenesis, including coincidental plasmid insertion and relatively low Sleeping Beauty transposition activity in porcine fibroblasts, but also provide a platform for future development of porcine disease models using the Sleeping Beauty gene insertion technology.     

The effect of intravital chelation with dimercaprol,calcium disodium edetate, 1-10-phenantroline and 2,2′-dipyridyl on the sulfide silver stainability of the rat brain

Summary Dimercaprol, calcium disodium edetate, 1-10-phenantroline and 2,2-dipyridyl were injected intraperitoneally in adult albino rats in doses ranging from 10 to 1500 mg per kg body weight. Ten animals were injected intracerebrally. At various survival times (2 minutes to several hours) their effects on the staining pattern of heavy metals as revealed by the sulfide silver method of Timm were determined. EDTA was virtually ineffective while dimercaprol, phenantroline and dipyridyl reduced the staining in many regions of the brain. A noteworthy effect of phenantroline was that it reduced the staining of a cortical area, corresponding remarkably well in extent, shape and location to the neocortical somatosensory area.     

Testing aluminum addition as a tool for lake restoration in shallow,eutrophic Lake Sønderby,Denmark

Hydrobiologia - Internal phosphorus (P) loading in shallow lakes may delay recovery from previous high external loading for decades. In Lake Sønderby (8 ha, mean depth 2.8 m), Fyn...     

Diversity of sulfate-reducing bacteria from an extreme hypersaline sediment, Great Salt Lake (Utah)

The diversity of sulfate-reducing bacteria (SRB) inhabiting the extreme hypersaline sediment (270 g L(-1) NaCl) of the northern arm of Great Salt Lake was studied by integrating cultivation and genotypic identification approaches involving PCR-based retrieval of 16S rRNA and dsrAB genes, the latter encoding major subunits of dissimilatory (bi) sulfite reductase. The majority (85%) of dsrAB sequences retrieved directly from the sediment formed a lineage of high (micro) diversity affiliated with the genus Desulfohalobium, while others represented novel lineages within the families Desulfohalobiaceae and Desulfobacteraceae or among Gram-positive SRB. Using the same sediment, SRB enrichment cultures were established in parallel at 100 and at 190 g L(-1) NaCl using different electron donors. After 5-6 transfers, dsrAB and 16S rRNA gene-based profiling of these enrichment cultures recovered a SRB community composition congruent with the cultivation-independent profiling of the sediment. Pure culture representatives of the predominant Desulfohalobium-related lineage and of one of the Desulfobacteraceae-affilated lineages were successfully obtained. The growth performance of these isolates and of the enrichment cultures suggests that the sediment SRB community of the northern arm of Great Salt Lake consists of moderate halophiles, which are salt-stressed at the in situ salinity of 27%.     

Sensitivity analysis of periprosthetic healing to cell migration, growth factor and post-operative gap using a mechanobiological model

A theoretical rationale, which could help in the investigation of mechanobiological factors affecting periprosthetic tissue healing, is still an open problem. We used a parametric sensitivity analysis to extend a theoretical model based on reactive transport and computational cell biology. The numerical experimentation involved the drill hole, the haptotactic and chemotactic migrations, and the initial concentration of an anabolic growth factor. Output measure was the mineral fraction in tissue surrounding a polymethymethacrylate (PMMA) canine implant (stable loaded implant, non-critical gap). Increasing growth factor concentration increased structural matrix synthesis. A cell adhesion gradient resulted in heterogeneous bone distribution and a growth factor gradient resulted in homogeneous bone distribution in the gap. This could explain the radial variation of bone density from the implant surface to the drill hole, indicating less secure fixation. This study helps to understand the relative importance of various host and clinical factors influencing bone distribution and resulting implant fixation.     

Three distinct epitopes on the extracellular face of the glucagon receptor determine specificity for the glucagon amino terminus

The glucagon and glucagon-like peptide-1 (GLP-1) receptors are homologous family B seven-transmembrane (7TM) G protein-coupled receptors, and they selectively recognize the homologous peptide hormones glucagon (29 amino acids) and GLP-1 (30-31 amino acids), respectively. The amino-terminal extracellular domain of the glucagon and GLP-1 receptors (140-150 amino acids) determines specificity for the carboxyl terminus of glucagon and GLP-1, respectively. In addition, the glucagon receptor core domain (7TM helices and connecting loops) strongly determines specificity for the glucagon amino terminus. Only 4 of 15 residues are divergent in the glucagon and GLP-1 amino termini; Ser2, Gln3, Tyr10, and Lys12 in glucagon and the corresponding Ala8, Glu9, Val16, and Ser18 in GLP-1. In this study, individual substitution of these four residues of glucagon with the corresponding residues of GLP-1 decreased the affinity and potency at the glucagon receptor relative to glucagon. Substitution of distinct segments of the glucagon receptor core domain with the corresponding segments of the GLP-1 receptor rescued the affinity and potency of specific glucagon analogs. Site-directed mutagenesis identified the Asp385 --> Glu glucagon receptor mutant that specifically rescued Ala2-glucagon. The results show that three distinct epitopes of the glucagon receptor core domain determine specificity for the N terminus of glucagon. We suggest a glucagon receptor binding model in which the extracellular ends of TM2 and TM7 are close to and determine specificity for Gln3 and Ser2 of glucagon, respectively. Furthermore, the second extracellular loop and/or proximal segments of TM4 and/or TM5 are close to and determine specificity for Lys12 of glucagon.     

RosettaDDGPrediction for high-throughput mutational scans: From stability to binding

Reliable prediction of free energy changes upon amino acid substitutions (ΔΔGs) is crucial to investigate their impact on protein stability and protein–protein interaction. Advances in experimental mutational scans allow high-throughput studies thanks to multiplex techniques. On the other hand, genomics initiatives provide a large amount of data on disease-related variants that can benefit from analyses with structure-based methods. Therefore, the computational field should keep the same pace and provide new tools for fast and accurate high-throughput ΔΔG calculations. In this context, the Rosetta modeling suite implements effective approaches to predict folding/unfolding ΔΔGs in a protein monomer upon amino acid substitutions and calculate the changes in binding free energy in protein complexes. However, their application can be challenging to users without extensive experience with Rosetta. Furthermore, Rosetta protocols for ΔΔG prediction are designed considering one variant at a time, making the setup of high-throughput screenings cumbersome. For these reasons, we devised RosettaDDGPrediction, a customizable Python wrapper designed to run free energy calculations on a set of amino acid substitutions using Rosetta protocols with little intervention from the user. Moreover, RosettaDDGPrediction assists with checking completed runs and aggregates raw data for multiple variants, as well as generates publication-ready graphics. We showed the potential of the tool in four case studies, including variants of uncertain significance in childhood cancer, proteins with known experimental unfolding ΔΔGs values, interactions between target proteins and disordered motifs, and phosphomimetics. RosettaDDGPrediction is available, free of charge and under GNU General Public License v3.0, at https://github.com/ELELAB/RosettaDDGPrediction .