Molecular cloning,expression, and hormonal regulation of the chicken microsomal triglyceride transfer protein

During an egg-laying cycle, oviparous animals transfer massive amounts of triglycerides, the major lipid component of very low density lipoprotein (VLDL), from the liver to the developing oocytes. A major stimulus for this process is the rise in estrogen associated with the onset of an egg-laying cycle. In mammals, the microsomal triglyceride transfer protein (MTP) is required for VLDL assembly and secretion. To enable studies to determine if MTP plays a role in basal and estrogen-stimulated VLDL assembly and secretion in an oviparous vertebrate, we have cloned and sequenced the chicken MTP cDNA. This cDNA encodes a protein of 893 amino acids with an N-terminal signal sequence. The primary sequence of chicken MTP is, on average, 65% identical to that of mammalian homologs, and 23% identical to the Drosophila melanogaster protein. We have obtained a clone of chicken embryo fibroblast cells that stably express the avian MTP cDNA and show that these cells display MTP activity as measured by the transfer of a fluorescently labeled neutral lipid. As in mammals, chicken MTP is localized to the endoplasmic reticulum as revealed by indirect immunofluorescence and by the fact that its N-linked oligosaccharide moiety remains sensitive to endoglycosidase H. Endogenous, enzymatically active MTP is also expressed in an estrogen receptor-expressing chicken hepatoma cell line that secretes apolipoprotein B-containing lipoproteins. In this cell line and in vivo, the expression and activity of MTP are not influenced by estrogen. Therefore, up-regulation of MTP in the liver is not required for the increased VLDL assembly during egg production in the chicken. This indicates that MTP is not rate-limiting, even for the massive estrogen-induced secretion of VLDL accompanying an egg-laying cycle.     

Taxonomy of the ‘Synargis axenus complex’ belonging to the ‘Synargis regulus’ species group,with a phylogenetic reassessment of the genus Synargis Hübner, 1819 (Lepidoptera: Riodinidae: Nymphidiini)

Three new species of Synargis Hübner, 1819, from Paraguay and southern and central Brazil are described: Synargis fandanga sp. nov. from Paraguay (Amambay and Paraguari) and southern Brazil (Paraná and Santa Catarina), Synargis rasqueada sp. nov. from central Brazil (Mato Grosso), and Synargis gorpa sp. nov. from southern Brazil (Paraná, Santa Catarina, and Rio Grande do Sul). Lectotypes are designated for Lemonias axenus Hewitson, 1876, Ematurgina axenus ochrophlegma Sitchel, 1911, Ematurgina acervata Seitz, 1932, and Ematurgina perrupta Seitz, 1932. Ematurgina ochrophlegma f. dissimilis Hayward, 1949, is a new synonym of Synargis bifasciata (Mengel, 1902), and Ematurgina ochrophlegma f. distincta Hayward, 1949, is a new synonym of Synargis axenus (Hewitson, 1876). The revalidation of E. perrupta Seitz, 1932, and the new status Synargis ochrophlegma (Stichel, 1911) are proposed. Ematurgina perrupta ab. roeberi Seitz, 1932, and Ematurgina bifasciata ochrophlegma ab. leucomelaina Breyer, 1930, are considered unavailable names. Based on a previous phylogenetic hypothesis, the phylogeny of the genus Synargis is reassessed, adding these new and revalidated taxa, and nine additional characters. The ‘Synargis regulus’ species group and the ‘Synargis axenus complex’ are recovered as monophyletic, with S. gorpa sp. nov. sister to the remaining species of the ‘S. axenus complex’. Additionally, an up‐to‐date geographical distribution map and a dichotomous key are provided, and the taxonomy of the taxa involved is discussed. © 2013 The Linnean Society of London     

Both Genome Segments Contribute to the Pathogenicity of Very Virulent Infectious Bursal Disease Virus

Infectious bursal disease virus (IBDV) causes an economically significant disease of chickens worldwide. Very virulent IBDV (vvIBDV) strains have emerged and induce as much as 60% mortality. The molecular basis for vvIBDV pathogenicity is not understood, and the relative contributions of the two genome segments, A and B, to this phenomenon are not known. Isolate 94432 has been shown previously to be genetically related to vvIBDVs but exhibits atypical antigenicity and does not cause mortality. Here the full-length genome of 94432 was determined, and a reverse genetics system was established. The molecular clone was rescued and exhibited the same antigenicity and reduced pathogenicity as isolate 94432. Genetically modified viruses derived from 94432, whose vvIBDV consensus nucleotide sequence was restored in segment A and/or B, were produced, and their pathogenicity was assessed in specific-pathogen-free chickens. We found that a valine (position 321) that modifies the most exposed part of the capsid protein VP2 critically modified the antigenicity and partially reduced the pathogenicity of 94432. However, a threonine (position 276) located in the finger domain of the virus polymerase (VP1) contributed even more significantly to attenuation. This threonine is partially exposed in a hydrophobic groove on the VP1 surface, suggesting possible interactions between VP1 and another, as yet unidentified molecule at this amino acid position. The restored vvIBDV-like pathogenicity was associated with increased replication and lesions in the thymus and spleen. These results demonstrate that both genome segments influence vvIBDV pathogenicity and may provide new targets for the attenuation of vvIBDVs.     

Development of small-molecule P-gp inhibitors of the N-benzyl 1,4-dihydropyridine type: Novel aspects in SAR and bioanalytical evaluation of multidrug resistance (MDR) reversal properties

Novel series of N-benzyl 1,4-dihydropyridines have been prepared by facile syntheses. All relevant substituents of the molecular scaffold have been varied. The resulting compounds were biologically evaluated as P-glycoprotein (P-gp) inhibitors. Substitutions of the N-benzyl residue favour biological activity beside respective 3-ester functions. Most active compounds were further evaluated as multidrug resistance (MDR) modulators to restore the cytotoxic properties of varying daunorubicin applications.     

A Computational Model for Predicting Nanoparticle Accumulation in Tumor Vasculature

Vascular targeting of malignant tissues with systemically injected nanoparticles (NPs) holds promise in molecular imaging and anti-angiogenic therapies. Here, a computational model is presented to predict the development of tumor neovasculature over time and the specific, vascular accumulation of blood-borne NPs. A multidimensional tumor-growth model is integrated with a mesoscale formulation for the NP adhesion to blood vessel walls. The fraction of injected NPs depositing within the diseased vasculature and their spatial distribution is computed as a function of tumor stage, from 0 to day 24 post-tumor inception. As the malignant mass grows in size, average blood flow and shear rates increase within the tumor neovasculature, reaching values comparable with those measured in healthy, pre-existing vessels already at 10 days. The NP vascular affinity, interpreted as the likelihood for a blood-borne NP to firmly adhere to the vessel walls, is a fundamental parameter in this analysis and depends on NP size and ligand density, and vascular receptor expression. For high vascular affinities, NPs tend to accumulate mostly at the inlet tumor vessels leaving the inner and outer vasculature depleted of NPs. For low vascular affinities, NPs distribute quite uniformly intra-tumorally but exhibit low accumulation doses. It is shown that an optimal vascular affinity can be identified providing the proper balance between accumulation dose and uniform spatial distribution of the NPs. This balance depends on the stage of tumor development (vascularity and endothelial receptor expression) and the NP properties (size, ligand density and ligand-receptor molecular affinity). Also, it is demonstrated that for insufficiently developed vascular networks, NPs are transported preferentially through the healthy, pre-existing vessels, thus bypassing the tumor mass. The computational tool described here can effectively select an optimal NP formulation presenting high accumulation doses and uniform spatial intra-tumor distributions as a function of the development stage of the malignancy.     

5-Methoxyleoligin,a Lignan from Edelweiss,Stimulates CYP26B1-Dependent Angiogenesis In Vitro and Induces Arteriogenesis in Infarcted Rat Hearts In Vivo

Background

Insufficient angiogenesis and arteriogenesis in cardiac tissue after myocardial infarction (MI) is a significant factor hampering the functional recovery of the heart. To overcome this problem we screened for compounds capable of stimulating angiogenesis, and herein investigate the most active molecule, 5-Methoxyleoligin (5ML), in detail.

Methods and Results

5ML potently stimulated endothelial tube formation, angiogenic sprouting, and angiogenesis in a chicken chorioallantoic membrane assay. Further, microarray- and knock down- based analyses revealed that 5ML induces angiogenesis by upregulation of CYP26B1. In an in vivo rat MI model 5ML potently increased the number of arterioles in the peri-infarction and infarction area, reduced myocardial muscle loss, and led to a significant increase in LV function (plus 21% 28 days after MI).

Conclusion

The present study shows that 5ML induces CYP26B1-dependent angiogenesis in vitro, and arteriogenesis in vivo. Whether or not CYP26B1 is relevant for in vivo arteriogenesis is not clear at the moment. Importantly, 5ML-induced arteriogenesis in vivo makes the compound even more interesting for a post MI therapy. 5ML may constitute the first low molecular weight compound leading to an improvement of myocardial function after MI.     

Interactions of donor sources and media influence the histo‐morphological quality of full‐thickness skin models

Human artificial skin models are increasingly employed as non‐animal test platforms for research and medical purposes. However, the overall histopathological quality of such models may vary significantly. Therefore, the effects of manufacturing protocols and donor sources on the quality of skin models built‐up from fibroblasts and keratinocytes derived from juvenile foreskins is studied. Histo‐morphological parameters such as epidermal thickness, number of epidermal cell layers, dermal thickness, dermo‐epidermal adhesion and absence of cellular nuclei in the corneal layer are obtained and scored accordingly. In total, 144 full‐thickness skin models derived from 16 different donors, built‐up in triplicates using three different culture conditions were successfully generated. In univariate analysis both media and donor age affected the quality of skin models significantly. Both parameters remained statistically significant in multivariate analyses. Performing general linear model analyses we could show that individual medium‐donor‐interactions influence the quality. These observations suggest that the optimal choice of media may differ from donor to donor and coincides with findings where significant inter‐individual variations of growth rates in keratinocytes and fibroblasts have been described. Thus, the consideration of individual medium‐donor‐interactions may improve the overall quality of human organ models thereby forming a reproducible test platform for sophisticated clinical research.     

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes

The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the following step. Yet, this strategy does not consider potential interactions between a priori distant process steps and therefore cannot guarantee for optimal overall process performance. To overcome these limitations, we established a smart approach to develop and utilize integrated process models using machine learning techniques and genetic algorithms. We evaluated the application of the data-driven models to explore potential efficiency increases and compared them to a conventional development approach for one of our development products. First, we developed a data-driven integrated process model using gradient boosting machines and Gaussian processes as machine learning techniques and a genetic algorithm as recommendation engine for two downstream unit operations, namely solubilization and refolding. Through projection of the results into our large-scale facility, we predicted a twofold increase in productivity. Second, we extended the model to a three-step model by including the capture chromatography. Here, depending on the selected baseline-process chosen for comparison, we obtained between 50% and 100% increase in productivity. These data show the successful application of machine learning techniques and optimization algorithms for downstream process development. Finally, our results highlight the importance of considering integrated process models for the whole process chain, including all unit operations.