Preparation and characterization of polycaprolactone microspheres by electrospraying

This is the author accepted manuscript. Published online: 13 Sep 2016. The final version to be made available from the publisher via the DOI in this record.The ability to reproducibly produce and effectively collect electrosprayed polymeric microspheres with controlled morphology and size in bulk form is challenging. In this study, microparticles were produced by electrospraying polycaprolactone (PCL) of various molecular weights and solution concentrations in chloroform, and by collecting materials on different substrates. The resultant PCL microparticles were characterized by optical and electron microscopy to investigate the effect of molecular weight, solution concentration, applied voltage, working distance and flow rate on their morphology and size. The work demonstrates the key role of a moderate molecular weight and/or solution concentration in the formation of spherical PCL particles via an electrospraying process. Increasing the applied voltage was found to produce smaller and more uniform PCL microparticles. There was a relatively low increase in the particle average size with an increase in the working distance and flow rate. Four types of substrates were adopted to collect electrosprayed PCL particles: a glass slide, aluminium foil, liquid bath and copper wire. Unlike 2D bulk structures collected on the other substrates, a 3D tubular structure of microspheres was formed on the copper wire and could find application in the construction of 3D tumour mimics.The financial support received from the Cancer Research UK (CRUK) and Engineering and Physical Sciences Research Council (ESPRC) Cancer Imaging Centre in Cambridge and Manchester (C8742/A18097) is acknowledged

Loss of constitutive activity is correlated with increased thermostability of the human adenosine A2A receptor

BACKGROUND AND PURPOSE: Thermostabilization by mutagenesis is one method which has facilitated the determination of high-resolution structures of the adenosine A(2A) receptor (A(2A)R). Sets of mutations were identified, which both thermostabilized the receptor and resulted in preferential agonist (Rag23 mutant) or antagonist (Rant5 and Rant21) binding forms as assessed by radioligand binding analysis. While the ligand-binding profiles of these mutants are known, the effects these mutations have on receptor activation and downstream signalling are less well characterized. EXPERIMENTAL APPROACH: Here we have investigated the effects of the thermostabilizing mutations on receptor activation using a yeast cell growth assay. The assay employs an engineered Saccharomyces cerevisiae, MMY24, which couples receptor activation to cell growth. KEY RESULTS: Analysis of the receptor activation profile revealed that the wild-type (WT) A(2A)R had considerable constitutive activity. In contrast, the Rag23, Rant5 and Rant21 thermostabilized mutants all exhibited no constitutive activity. While the preferentially antagonist-binding mutants Rant5 and Rant21 showed a complete lack of agonist-induced activity, the Rag23 mutant showed high levels of agonist-induced receptor activity. Further analysis using a mutant intermediate between Rag23 and WT indicated that the loss of constitutive activity observed in the agonist responsive mutants was not due to reduced G-protein coupling. CONCLUSIONS AND IMPLICATIONS: The loss of constitutive activity may be an important feature of these thermostabilized GPCRs. In addition, the constitutively active and agonist-induced active conformations of the A(2A)R are distinct

Loss of constitutive activity is correlated with increased thermostability of the human adenosine A2A receptor

In this note we present an explicit realization of the affine vertex algebra V^cri(gl(1|1)) inside of the tensor product F ⊗ M where F is a fermionic verex algebra and M is a commutative vertex algebra. This immediately gives an alternative description of the center of V^cri(gl(1|1)) as a subalgebra M_0 of M. We reconstruct the Molev-Mukhin formula for the Hilbert-Poincare series of the center of V^cri(gl(1|1)). Moreover, we construct a family of irreducible Vcri(gl(1|1))-modules realized on F and parameterized by χ+, χ- ∈ C((z)). We propose a generalization of V^cri(gl(1|1)) as a critical level version of the super W_{1+∞} vertex algebra

The Interiors of Giant Planets: Models and Outstanding Questions

We know that giant planets played a crucial role in the making of our Solar System. The discovery of giant planets orbiting other stars is a formidable opportunity to learn more about these objects, what is their composition, how various processes influence their structure and evolution, and most importantly how they form. Jupiter, Saturn, Uranus and Neptune can be studied in detail, mostly from close spacecraft flybys. We can infer that they are all enriched in heavy elements compared to the Sun, with the relative global enrichments increasing with distance to the Sun. We can also infer that they possess dense cores of varied masses. The intercomparison of presently caracterised extrasolar giant planets show that they are also mainly made of hydrogen and helium, but that they either have significantly different amounts of heavy elements, or have had different orbital evolutions, or both. Hence, many questions remain and are to be answered for significant progresses on the origins of planets.Comment: 43 pages, 11 figures, 3 tables. To appear in Annual Review of Earth and Planetary Sciences, vol 33, (2005

A proteome-integrated, carbon source dependent genetic regulatory network in Saccharomyces cerevisiae

Integrated regulatory networks can be powerful tools to examine and test properties of cellular systems, such as modelling environmental effects on the molecular bioeconomy, where protein levels are altered in response to changes in growth conditions. Although extensive regulatory pathways and protein interaction data sets exist which represent such networks, few have formally considered quantitative proteomics data to validate and extend them. We generate and consider such data here using a label-free proteomics strategy to quantify alterations in protein abundance for S. cerevisiae when grown on minimal media using glucose, galactose, maltose and trehalose as sole carbon sources. Using a high quality-controlled subset of proteins observed to be differentially abundant, we constructed a proteome-informed network, comprising 1850 transcription factor interactions and 37 chaperone interactions, which defines the major changes in the cellular proteome when growing under different carbon sources. Analysis of the differentially abundant proteins involved in the regulatory network pointed to their significant roles in specific metabolic pathways and function, including glucose homeostasis, amino acid biosynthesis, and carbohydrate metabolic process. We noted strong statistical enrichment in the differentially abundant proteome of targets of known transcription factors associated with stress responses and altered carbon metabolism. This shows how such integrated analysis can lend further experimental support to annotated regulatory interactions, since the proteomic changes capture both magnitude and direction of gene expression change at the level of the affected proteins. Overall this study highlights the power of quantitative proteomics to help define regulatory systems pertinent to environmental conditions

Three dimensional structure directs T-cell epitope dominance associated with allergy

<p>Abstract</p> <p>Background</p> <p>CD4+ T-cell epitope immunodominance is not adequately explained by peptide selectivity in class II major histocompatibility proteins, but it has been correlated with adjacent segments of conformational flexibility in several antigens.</p> <p>Methods</p> <p>The published T-cell responses to two venom allergens and two aeroallergens were used to construct profiles of epitope dominance, which were correlated with the distribution of conformational flexibility, as measured by crystallographic B factors, solvent-accessible surface, COREX residue stability, and sequence entropy.</p> <p>Results</p> <p>Epitopes associated with allergy tended to be excluded from and lie adjacent to flexible segments of the allergen.</p> <p>Conclusion</p> <p>During the initiation of allergy, the N- and/or C-terminal ends of proteolytic processing intermediates were preferentially loaded into antigen presenting proteins for the priming of CD4+ T cells.</p

Loss of regulation of protein synthesis and turnover underpins an attenuated stress response in senescent human mesenchymal stem cells

Cells respond to stress by synthesizing chaperone proteins that seek to correct protein misfolding and maintain function. However, abrogation of protein homeostasis is a hallmark of aging, leading to loss of function and the formation of proteotoxic aggregates characteristic of pathology. Consequently, discovering the underlying molecular causes of this deterioration in proteostasis is key to designing effective interventions to disease or to maintaining cell health in regenerative medicine strategies. Here, we examined primary human mesenchymal stem cells, cultured to a point of replicative senescence and subjected to heat shock, as an in vitro model of the aging stress response. Multi -omics analysis showed how homeostasis components were reduced in senescent cells, caused by dysregulation of a functional network of chaperones, thereby limiting proteostatic competence. Time-resolved analysis of the primary response factors, including those regulating heat shock protein 70 kDa (HSPA1A), revealed that regulatory control is essentially translational. Senescent cells have a reduced capacity for chaperone protein translation and misfolded protein (MFP) turnover, driven by downregulation of ribosomal proteins and loss of the E3 ubiquitin ligase CHIP (C-terminus of HSP70 interacting protein) which marks MFPs for degradation. This limits the cell’s stress response and subsequent recovery. A kinetic model recapitulated these reduced capacities and predicted an accumulation of MFP, a hypothesis supported by evidence of systematic changes to the proteomic fold state. These results thus establish a specific loss of regulatory capacity at the protein, rather than transcript, level and uncover underlying systematic links between aging and loss of protein homeostasis.</jats:p

PEDRo: A database for storing, searching and disseminating experimental proteomics data

Abstract Background Proteomics is rapidly evolving into a high-throughput technology, in which substantial and systematic studies are conducted on samples from a wide range of physiological, developmental, or pathological conditions. Reference maps from 2D gels are widely circulated. However, there is, as yet, no formally accepted standard representation to support the sharing of proteomics data, and little systematic dissemination of comprehensive proteomic data sets. Results This paper describes the design, implementation and use of a Proteome Experimental Data Repository (PEDRo), which makes comprehensive proteomics data sets available for browsing, searching and downloading. It is also serves to extend the debate on the level of detail at which proteomics data should be captured, the sorts of facilities that should be provided by proteome data management systems, and the techniques by which such facilities can be made available. Conclusions The PEDRo database provides access to a collection of comprehensive descriptions of experimental data sets in proteomics. Not only are these data sets interesting in and of themselves, they also provide a useful early validation of the PEDRo data model, which has served as a starting point for the ongoing standardisation activity through the Proteome Standards Initiative of the Human Proteome Organisation

From Nonspecific DNA–Protein Encounter Complexes to the Prediction of DNA–Protein Interactions

©2009 Gao, Skolnick. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.doi:10.1371/journal.pcbi.1000341DNA–protein interactions are involved in many essential biological activities. Because there is no simple mapping code between DNA base pairs and protein amino acids, the prediction of DNA–protein interactions is a challenging problem. Here, we present a novel computational approach for predicting DNA-binding protein residues and DNA–protein interaction modes without knowing its specific DNA target sequence. Given the structure of a DNA-binding protein, the method first generates an ensemble of complex structures obtained by rigid-body docking with a nonspecific canonical B-DNA. Representative models are subsequently selected through clustering and ranking by their DNA–protein interfacial energy. Analysis of these encounter complex models suggests that the recognition sites for specific DNA binding are usually favorable interaction sites for the nonspecific DNA probe and that nonspecific DNA–protein interaction modes exhibit some similarity to specific DNA–protein binding modes. Although the method requires as input the knowledge that the protein binds DNA, in benchmark tests, it achieves better performance in identifying DNA-binding sites than three previously established methods, which are based on sophisticated machine-learning techniques. We further apply our method to protein structures predicted through modeling and demonstrate that our method performs satisfactorily on protein models whose root-mean-square Ca deviation from native is up to 5 Å from their native structures. This study provides valuable structural insights into how a specific DNA-binding protein interacts with a nonspecific DNA sequence. The similarity between the specific DNA–protein interaction mode and nonspecific interaction modes may reflect an important sampling step in search of its specific DNA targets by a DNA-binding protein

Development of a prototype lateral flow immunoassay (LFI) for the rapid diagnosis of melioidosis.

Burkholderia pseudomallei is a soil-dwelling bacterium and the causative agent of melioidosis. Isolation of B. pseudomallei from clinical samples is the "gold standard" for the diagnosis of melioidosis; results can take 3-7 days to produce. Alternatively, antibody-based tests have low specificity due to a high percentage of seropositive individuals in endemic areas. There is a clear need to develop a rapid point-of-care antigen detection assay for the diagnosis of melioidosis. Previously, we employed In vivo Microbial Antigen Discovery (InMAD) to identify potential B. pseudomallei diagnostic biomarkers. The B. pseudomallei capsular polysaccharide (CPS) and numerous protein antigens were identified as potential candidates. Here, we describe the development of a diagnostic immunoassay based on the detection of CPS. Following production of a CPS-specific monoclonal antibody (mAb), an antigen-capture immunoassay was developed to determine the concentration of CPS within a panel of melioidosis patient serum and urine samples. The same mAb was used to produce a prototype Active Melioidosis Detect Lateral Flow Immunoassay (AMD LFI); the limit of detection of the LFI for CPS is comparable to the antigen-capture immunoassay (∼0.2 ng/ml). The analytical reactivity (inclusivity) of the AMD LFI was 98.7% (76/77) when tested against a large panel of B. pseudomallei isolates. Analytical specificity (cross-reactivity) testing determined that 97.2% of B. pseudomallei near neighbor species (35/36) were not reactive. The non-reactive B. pseudomallei strain and the reactive near neighbor strain can be explained through genetic sequence analysis. Importantly, we show the AMD LFI is capable of detecting CPS in a variety of patient samples. The LFI is currently being evaluated in Thailand and Australia; the focus is to optimize and validate testing procedures on melioidosis patient samples prior to initiation of a large, multisite pre-clinical evaluation