Simpler STED setups

This work discusses rugged technical simplifications for STED nanoscopy and methods related to it (RESOLFT). STED is a type of laser scanning microscopy that uses stimulated emission in order to inhibit spontaneous fluorescence from outer parts of the focal spot. This deliberate transient off-switching of fluorophores permits even densely packed fluorescent molecules to be spatially isolated from the rest; and because isolated molecules can be registered sequentially — no matter how close they are — the resolution is increased beyond the diffraction limit. For switching, STED asks for a separate inhibition beam modified in a way that it suppresses fluorescence, but only in the peripheral regions of the focal spot. The requirements of a second beam path and additional means for beam shaping have kept STED from gaining the currency it deserves, although high resolution is in huge demand, generally. Here, it is discussed how contemporary STED setups can be simplified radically; in fact up to a point where it is possible to upgrade existing laser scanning systems with a co-aligned STED-beam, simply by adding an element about the size of an optical thin-film filter. As the apparent need for a separate beam path ceases to exist, STED becomes simpler and more reliable. At the same time, the performance is the same as for a traditional STED-setup

Agent-based simulation of reactions in the crowded and structured intracellular environment: Influence of mobility and location of the reactants

<p>Abstract</p> <p>Background</p> <p>In this paper we apply a novel agent-based simulation method in order to model intracellular reactions in detail. The simulations are performed within a virtual cytoskeleton enriched with further crowding elements, which allows the analysis of molecular crowding effects on intracellular diffusion and reaction rates. The cytoskeleton network leads to a reduction in the mobility of molecules. Molecules can also unspecifically bind to membranes or the cytoskeleton affecting (i) the fraction of unbound molecules in the cytosol and (ii) furthermore reducing the mobility. Binding of molecules to intracellular structures or scaffolds can in turn lead to a microcompartmentalization of the cell. Especially the formation of enzyme complexes promoting metabolic channeling, e.g. in glycolysis, depends on the co-localization of the proteins.</p> <p>Results</p> <p>While the co-localization of enzymes leads to faster reaction rates, the reduced mobility decreases the collision rate of reactants, hence reducing the reaction rate, as expected. This effect is most prominent in diffusion limited reactions. Furthermore, anomalous diffusion can occur due to molecular crowding in the cell. In the context of diffusion controlled reactions, anomalous diffusion leads to fractal reaction kinetics. The simulation framework is used to quantify and separate the effects originating from molecular crowding or the reduced mobility of the reactants. We were able to define three factors which describe the effective reaction rate, namely <it>f ^diff</it>for the diffusion effect, <it>f ^volume</it>for the crowding, and <it>f ^access</it>for the reduced accessibility of the molecules.</p> <p>Conclusions</p> <p>Molecule distributions, reaction rate constants and structural parameters can be adjusted separately in the simulation allowing a comprehensive study of individual effects in the context of a realistic cell environment. As such, the present simulation can help to bridge the gap between <it>in vivo </it>and <it>in vitro </it>kinetics.</p

‘Domino’ systems biology and the ‘A’ of ATP

AbstractWe develop a strategic ‘domino’ approach that starts with one key feature of cell function and the main process providing for it, and then adds additional processes and components only as necessary to explain provoked experimental observations. The approach is here applied to the energy metabolism of yeast in a glucose limited chemostat, subjected to a sudden increase in glucose. The puzzles addressed include (i) the lack of increase in Adenosine triphosphate (ATP) upon glucose addition, (ii) the lack of increase in Adenosine diphosphate (ADP) when ATP is hydrolyzed, and (iii) the rapid disappearance of the ‘A’ (adenine) moiety of ATP. Neither the incorporation of nucleotides into new biomass, nor steady de novo synthesis of Adenosine monophosphate (AMP) explains. Cycling of the ‘A’ moiety accelerates when the cell's energy state is endangered, another essential domino among the seven required for understanding of the experimental observations. This new domino analysis shows how strategic experimental design and observations in tandem with theory and modeling may identify and resolve important paradoxes. It also highlights the hitherto unexpected role of the ‘A’ component of ATP

MicroRNAs in Tumor Endothelial Cells: Regulation, Function and Therapeutic Applications

Tumor endothelial cells (TECs) are key stromal components of the tumor microenvironment, and are essential for tumor angiogenesis, growth and metastasis. Accumulating evidence has shown that small single-stranded non-coding microRNAs (miRNAs) act as powerful endogenous regulators of TEC function and blood vessel formation. This systematic review provides an upto-date overview of these endothelial miRNAs. Their expression is mainly regulated by hypoxia, pro-angiogenic factors, gap junctions and extracellular vesicles, as well as long non-coding RNAs and circular RNAs. In preclinical studies, they have been shown to modulate diverse fundamental angiogenesis-related signaling pathways and proteins, including the vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) pathway; the rat sarcoma virus (Ras)/rapidly accelerated fibrosarcoma (Raf)/mitogen-activated protein kinase kinase (MEK)/extracellular signal-regulated kinase (ERK) pathway; the phosphoinositide 3-kinase (PI3K)/AKT pathway; and the transforming growth factor (TGF)-β/TGF-β receptor (TGFBR) pathway, as well as krüppel-like factors (KLFs), suppressor of cytokine signaling (SOCS) and metalloproteinases (MMPs). Accordingly, endothelial miRNAs represent promising targets for future anti-angiogenic cancer therapy. To achieve this, it will be necessary to further unravel the regulatory and functional networks of endothelial miRNAs and to develop safe and efficient TEC-specific miRNA delivery technologies

A systems biology approach to dynamic modeling and inter-subject variability of statin pharmacokinetics in human hepatocytes

A dynamic model for the biotransformation of atorvastatin has been developed using quantitative metabolite measurements in primary human hepatocytes. The model comprises kinetics for transport processes and metabolic enzymes as well as population liver expression data allowing us to assess the impact of inter-individual variability of concentrations of key proteins. Application of computational tools for parameter sensitivity analysis enabled us to considerably improve the validity of the model and to create a consistent framework for precise computer-aided simulations in toxicology

Sunitinib Inhibits Cell Proliferation and Alters Steroidogenesis by Down-Regulation of HSD3B2 in Adrenocortical Carcinoma Cells

The multi-tyrosine kinase inhibitor sunitinib is used in the treatment of several solid tumors. Animal experiments pointed to an adrenotoxic effect of sunitinib. Therefore, we evaluated the expression of key targets of sunitinib in human adrenocortical carcinoma (ACC) tumor samples and investigated its in vitro effects in ACC cell lines. We carried out immunohistochemistry for vascular endothelial growth factor (VEGF) and its receptor (VEGF-R2) in 157 ACC samples and nine normal adrenal glands. VEGF and VEGF-R2 protein were expressed in 72 and 99% of ACC samples, respectively. Using NCI-H295 and SW13 ACC cell lines, we investigated the effects of sunitinib on cell proliferation. Sunitinib reduced dose-dependently cell viability of both NCI-H295 and SW13 cells (SW13: 0.1 μM 96 ± 7%, 1 μM 90 ± 9%*, 5 μM 62 ± 6%*, controls 100 ± 9%; *p < 0.05). To determine sunitinib effects on steroidogenesis, we measured steroid hormones in cell culture supernatant by gas chromatography–mass spectrometry. We observed a pronounced decrease of cortisol secretion (1 μM 90.1 ± 1.5%*, 5 μM 57.2 ± 0.3%*, controls 100 ± 2.4%) and a concomitant increase in the DHEA/4-androstenedione and 17-hydroxypregnenolone/17-hydroxyprogesterone ratios, indicating specific inhibition of 3β-hydroxysteroid dehydrogenase (HSD3B2). In yeast microsomes transformed with HSD3B2, no direct inhibition of HSD3B2 by sunitinib was detected. Sunitinib induced down-regulation of HSD3B2 mRNA and protein in ACC cell lines (mRNA: 1 μM 44 ± 16%*; 5 μM 22 ± 2%*; 10 μM 19 ± 4%*; protein: 1 μM 82 ± 8%; 5 μM 63 ± 8%*; 10 μM 55 ± 9%*). CYP11B1 was down-regulated at mRNA but not at protein level and CYP11A1 remained unchanged. In conclusion, target molecules of sunitinib are expressed in the vast majority of ACC samples. Sunitinib exhibits anti-proliferative effects in vitro, and appears to specifically block adrenal steroidogenesis by down-regulation of HSD3B2, rendering it a promising option for treatment of ACC

Indirect protein quantification of drug-transforming enzymes using peptide group-specific immunoaffinity enrichment and mass spectrometry

Immunoaffinity enrichment of proteotypic peptides, coupled with selected reaction monitoring, enables indirect protein quantification. However the lack of suitable antibodies limits its widespread application. We developed a method in which multi-specific antibodies are used to enrich groups of peptides, thus facilitating multiplexed quantitative protein assays. We tested this strategy in a pharmacokinetic experiment by targeting a group of homologous drug transforming proteins in human hepatocytes. Our results indicate the generic applicability of this method to any biological system

Indirect protein quantification of drug-transforming enzymes using peptide group-specific immunoaffinity enrichment and mass spectrometry

Immunoaffinity enrichment of proteotypic peptides, coupled with selected reaction monitoring, enables indirect protein quantification. However the lack of suitable antibodies limits its widespread application. We developed a method in which multi-specific antibodies are used to enrich groups of peptides, thus facilitating multiplexed quantitative protein assays. We tested this strategy in a pharmacokinetic experiment by targeting a group of homologous drug transforming proteins in human hepatocytes. Our results indicate the generic applicability of this method to any biological system

Multiscale modelling of vascular tumour growth in 3D: the roles of domain size & boundary condition

We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour