Mechanisms of ligand transfer by the hepatic tocopherol transfer protein

alpha-Tocopherol is a member of the vitamin E family that functions as the principal fat-soluble antioxidant in vertebrates. Body-wide distribution of tocopherol is regulated by the hepatic alpha-tocopherol transfer protein (alphaTTP), which stimulates secretion of the vitamin from hepatocytes to circulating lipoproteins. This biological activity of alphaTTP is thought to stem from its ability to facilitate the transfer of vitamin E between membranes, but the mechanism by which the protein exerts this activity remains poorly understood. Using a fluorescence energy transfer methodology, we found that the rate of tocopherol transfer from lipid vesicles to alphaTTP increases with increasing alphaTTP concentration. This concentration dependence indicates that ligand transfer by alphaTTP involves direct protein-membrane interaction. In support of this notion, equilibrium analyses employing filtration, dual polarization interferometry, and tryptophan fluorescence demonstrated the presence of a stable alphaTTP-bilayer complex. The physical association of alphaTTP with membranes is markedly sensitive to the presence of vitamin E in the bilayer. Some naturally occurring mutations in alphaTTP that cause the hereditary disorder ataxia with vitamin E deficiency diminish the effect of tocopherol on the protein-membrane association, suggesting a possible mechanism for the accompanying pathology.     

Genetic mutation analysis at early stages of cell line development using next generation sequencing

A central goal for most biopharmaceutical companies is to reduce the development timeline to reach clinical proof of concept. This objective requires the development of tools that ensure the quality of biotherapeutic material destined for the clinic. Recent advances in high throughput protein analytics provide confidence in our ability to assess productivity and product quality attributes at early stages of cell line development. However, one quality attribute has, until recently, been absent from the standard battery of analytical tests facilitating informed choices early in cell line selection: genetic sequence confirmation. Techniques historically used for mutation analysis, such as detailed mass spectrometry, have limitations on the sample number and turnaround times making it less attractive at early stages. Thus, we explored the utility of Next‐Generation Sequencing (NGS) as a solution to address these limitations. Amplicon sequencing is one such NGS technique that is robust, rapid, sensitive, and amenable to multiplexing, all of which are essential attributes for our purposes. Here we report a NGS method based upon amplicon sequencing that has been successfully incorporated into our cell line development workflow alongside other high‐throughput protein analytical assays. The NGS method has demonstrated its value by identifying at least one Chinese hamster ovary (CHO) clone expressing a variant form of the biotherapeutic in each of the four clinical programs in which it has been utilized. We believe this sequence confirmation method is essential to safely accelerating the time to clinical proof of concept of biotherapeutics, and guard against delays related to sequence mutations. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:813–817, 2016     

Disease swamps molecular signatures of genetic-environmental associations to abiotic factors in Tasmanian devil (Sarcophilus harrisii) populations

Landscape genomics studies focus on identifying candidate genes under selection via spatial variation in abiotic environmental variables, but rarely by biotic factors (i.e., disease). The Tasmanian devil (Sarcophilus harrisii) is found only on the environmentally heterogeneous island of Tasmania and is threatened with extinction by a transmissible cancer, devil facial tumor disease (DFTD). Devils persist in regions of long-term infection despite epidemiological model predictions of species’ extinction, suggesting possible adaptation to DFTD. Here, we test the extent to which spatial variation and genetic diversity are associated with the abiotic environment (i.e., climatic variables, elevation, vegetation cover) and/or DFTD. We employ genetic-environment association analyses using 6886 SNPs from 3287 individuals sampled pre- and post-disease arrival across the devil's geographic range. Pre-disease, we find significant correlations of allele frequencies with environmental variables, including 365 unique loci linked to 71 genes, suggesting local adaptation to abiotic environment. The majority of candidate loci detected pre-DFTD are not detected post-DFTD arrival. Several post-DFTD candidate loci are associated with disease prevalence and were in linkage disequilibrium with genes involved in tumor suppression and immune response. Loss of apparent signal of abiotic local adaptation post-disease suggests swamping by strong selection resulting from the rapid onset of DFTD.     

Large-scale identification of polymorphic microsatellites using an <Emphasis Type="Italic">in silico</Emphasis> approach

Background  

Simple Sequence Repeat (SSR) or microsatellite markers are valuable for genetic research. Experimental methods to develop SSR markers are laborious, time consuming and expensive. In silico approaches have become a practicable and relatively inexpensive alternative during the last decade, although testing putative SSR markers still is time consuming and expensive. In many species only a relatively small percentage of SSR markers turn out to be polymorphic. This is particularly true for markers derived from expressed sequence tags (ESTs). In EST databases a large redundancy of sequences is present, which may contain information on length-polymorphisms in the SSR they contain, and whether they have been derived from heterozygotes or from different genotypes. Up to now, although a number of programs have been developed to identify SSRs in EST sequences, no software can detect putatively polymorphic SSRs.     

Changes in cardiac Na<Superscript>+</Superscript>/K<Superscript>+</Superscript>-ATPase expression and activity in female rats fed a high-fat diet

The aim of this study was to investigate whether the presence of endogenous estradiol alters the effects of a high-fat (HF) diet on activity/expression of the cardiac Na⁺/K⁺-ATPase, via PI3K/IRS and RhoA/ROCK signalling cascades in female rats. For this study, female Wistar rats (8 weeks old, 150–200 g) were fed a standard diet or a HF diet (balanced diet for laboratory rats enriched with 42% fat) for 10 weeks. The results show that rats fed a HF diet exhibited a decrease in phosphorylation of the α₁ subunit of Na⁺/K⁺-ATPase by 30% (p < 0.05), expression of total α₁ subunit of Na⁺/K⁺-ATPase by 31% (p < 0.05), and association of IRS1 with p85 subunit of PI3K by 42% (p < 0.05), while the levels of cardiac RhoA and ROCK2 were significantly increased by 84% (p < 0.01) and 62% (p < 0.05), respectively. Our results suggest that a HF diet alters cardiac Na⁺/K⁺-ATPase expression via molecular mechanisms involving RhoA/ROCK and IRS-1/PI3K signalling in female rats.     

Diagnosing idiopathic learning disability: a cost-effectiveness analysis of microarray technology in the National Health Service of the United Kingdom

Array based comparative genomic hybridisation (aCGH) is a powerful technique for detecting clinically relevant genome imbalance and can offer 40 to > 1000 times the resolution of karyotyping. Indeed, idiopathic learning disability (ILD) studies suggest that a genome-wide aCGH approach makes 10–15% more diagnoses involving genome imbalance than karyotyping. Despite this, aCGH has yet to be implemented as a routine NHS service. One significant obstacle is the perception that the technology is prohibitively expensive for most standard NHS clinical cytogenetics laboratories. To address this, we investigated the cost-effectiveness of aCGH versus standard cytogenetic analysis for diagnosing idiopathic learning disability (ILD) in the NHS. Cost data from four participating genetics centres were collected and analysed. In a single test comparison, the average cost of aCGH was ￡442 and the average cost of karyotyping was ￡117 with array costs contributing most to the cost difference. This difference was not a key barrier when the context of follow up diagnostic tests was considered. Indeed, in a hypothetical cohort of 100 ILD children, aCGH was found to cost less per diagnosis (￡3,118) than a karyotyping and multi-telomere FISH approach (￡4,957). We conclude that testing for genomic imbalances in ILD using microarray technology is likely to be cost-effective because long-term savings can be made regardless of a positive (diagnosis) or negative result. Earlier diagnoses save costs of additional diagnostic tests. Negative results are cost-effective in minimising follow-up test choice. The use of aCGH in routine clinical practice warrants serious consideration by healthcare providers. Copyright statement The Corresponding Author has the right to grant on behalf of all authors and does grant on behalf of all authors, an exclusive licence (or non exclusive for government employees) on a worldwide basis to the BMJ Publishing Group Ltd, and its Licensees to permit this article (if accepted) to be published in BMJ editions and any other BMJPGL products and to exploit all subsidiary rights, as set out in our licence (bmj.com/advice/copyright.shtml). Authorship The authors included on this paper fulfil the criteria of authorship and no one who fulfils the criteria has been excluded from authorship. The authors made a substantial contribution to the conception, design, analysis and interpretation of data. They were involved in drafting the article or revising it critically for important intellectual content and approving the version to be published. Contributorship Sarah Wordsworth (Guarantor): Planning, conducting and reporting work, interpretation of data, drafting and revising article. James Buchanan: Conducting and reporting work, interpretation of data, revising article. Regina Regan: Completing costing questionnaire, providing protocol details, other costing information, interpretation of data, information about learning disability and genome imbalance and revising article. Val Davison: Completing costing questionnaire, providing protocol details, sharing overall laboratory experience and drafting article. Kim Smith: Completing costing questionnaire, providing protocol details, drafting article. Sara Dyer: Completing costing questionnaire and providing protocol details. Carolyn Campbell: Completing costing questionnaire and providing protocol details. Edward Blair: Critical appraisal of article for clinical content and revising article. Eddy Maher: Completing costing questionnaire, providing protocol details, sharing overall laboratory experience and drafting article. Jenny Taylor: Planning and facilitating work between centres. Drafting and revising article. Samantha JL Knight: Completing costing questionnaire, providing protocol details, other costing information, interpretation of data, providing information about learning disability and genome imbalance, drafting and revising article. Jenny Taylor and Samantha JL Knight contributed equally to the work presented.