216 research outputs found

    Ultra-rapid laser protein micropatterning: screening for directed polarization of single neurons

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    Protein micropatterning is a powerful tool for studying the effects of extracellular signals on cell development and regeneration. Laser micropatterning of proteins is the most flexible method for patterning many different geometries, protein densities, and concentration gradients. Despite these advantages, laser micropatterning remains prohibitively slow for most applications. Here, we take advantage of the rapid multi-photon induced photobleaching of fluorophores to generate sub-micron resolution patterns of full-length proteins on polymer monolayers, with sub-microsecond exposure times, i.e. one to five orders of magnitude faster than all previous laser micropatterning methods. We screened a range of different PEG monolayer coupling chemistries, chain-lengths and functional caps, and found that long-chain acrylated PEG monolayers are effective at resisting non-specific protein adhesion, while permitting efficient cross-linking of biotin-4-fluorescein to the PEG monolayers upon exposure to femtosecond laser pulses. We find evidence that the dominant photopatterning chemistry switches from a two-photon process to three- and four-photon absorption processes as the laser intensity increases, generating increasingly volatile excited triplet-state fluorophores, leading to faster patterning. Using this technology, we were able to generate over a hundred thousand protein patterns with varying geometries and protein densities to direct the polarization of hippocampal neurons with single-cell precision. We found that certain arrays of patterned triangles as small as neurite growth cones can direct polarization by impeding the elongation of reverse-projecting neurites, while permitting elongation of forward-projecting neurites. The ability to rapidly generate and screen such protein micropatterns can enable discovery of conditions necessary to create in vitro neural networks with single-neuron precision for basic discovery, drug screening, as well as for tissue scaffolding in therapeutics.Hertz Foundation (Fellowship)National Institutes of Health (U.S.) (R01 EUREKA Award 1-R01-NS066352)David & Lucile Packard Foundation (Award in Science and Engineering

    Synchronous Symmetry Breaking in Neurons with Different Neurite Counts

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    As neurons develop, several immature processes (i.e., neurites) grow out of the cell body. Over time, each neuron breaks symmetry when only one of its neurites grows much longer than the rest, becoming an axon. This symmetry breaking is an important step in neurodevelopment, and aberrant symmetry breaking is associated with several neuropsychiatric diseases, including schizophrenia and autism. However, the effects of neurite count in neuronal symmetry breaking have never been studied. Existing models for neuronal polarization disagree: some predict that neurons with more neurites polarize up to several days later than neurons with fewer neurites, while others predict that neurons with different neurite counts polarize synchronously. We experimentally find that neurons with different neurite counts polarize synchronously. We also show that despite the significant differences among the previously proposed models, they all agree with our experimental findings when the expression levels of the proteins responsible for symmetry breaking increase with neurite count. Consistent with these results, we observe that the expression levels of two of these proteins, HRas and shootin1, significantly correlate with neurite count. This coordinated symmetry breaking we observed among neurons with different neurite counts may be important for synchronized polarization of neurons in developing organisms

    Irreversible inhibitors of the EGF receptor may circumvent acquired resistance to gefitinib

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    Non-small cell lung cancers (NSCLCs) with activating mutations in the kinase domain of the epidermal growth factor receptor (EGFR) demonstrate dramatic, but transient, responses to the reversible tyrosine kinase inhibitors gefitinib (Iressa) and erlotinib (Tarceva). Some recurrent tumors have a common secondary mutation in the EGFR kinase domain, T790M, conferring drug resistance, but in other cases the mechanism underlying acquired resistance is unknown. In studying multiple sites of recurrent NSCLCs, we detected T790M in only a small percentage of tumor cells. To identify additional mechanisms of acquired resistance to gefitinib, we used NSCLC cells harboring an activating EGFR mutation to generate multiple resistant clones in vitro. These drug-resistant cells demonstrate continued dependence on EGFR and ERBB2 signaling for their viability and have not acquired secondary EGFR mutations. However, they display increased internalization of ligand-activated EGFR, consistent with altered receptor trafficking. Although gefitinib-resistant clones are cross-resistant to related anilinoquinazolines, they demonstrate sensitivity to a class of irreversible inhibitors of EGFR. These inhibitors also show effective inhibition of signaling by T790M-mutant EGFR and killing of NSCLC cells with the T790M mutation. Both mechanisms of gefitinib resistance are therefore circumvented by irreversible tyrosine kinase inhibitors. Our findings suggest that one of these, HKI-272, may prove highly effective in the treatment of EGFR-mutant NSCLCs, including tumors that have become resistant to gefitinib or erlotinib

    Labeling Strategies Matter for Super-Resolution Microscopy: A Comparison between HaloTags and SNAP-tags

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    Super-resolution microscopy requires that subcellular structures are labeled with bright and photostable fluorophores, especially for live-cell imaging. Organic fluorophores may help here as they can yield more photons—by orders of magnitude—than fluorescent proteins. To achieve molecular specificity with organic fluorophores in live cells, self-labeling proteins are often used, with HaloTags and SNAP-tags being the most common. However, how these two different tagging systems compare with each other is unclear, especially for stimulated emission depletion (STED) microscopy, which is limited to a small repertoire of fluorophores in living cells. Herein, we compare the two labeling approaches in confocal and STED imaging using various proteins and two model systems. Strikingly, we find that the fluorescent signal can be up to 9-fold higher with HaloTags than with SNAP-tags when using far-red rhodamine derivatives. This result demonstrates that the labeling strategy matters and can greatly influence the duration of super-resolution imaging

    Conductive-probe atomic force microscopy characterization of silicon nanowire

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    The electrical conduction properties of lateral and vertical silicon nanowires (SiNWs) were investigated using a conductive-probe atomic force microscopy (AFM). Horizontal SiNWs, which were synthesized by the in-plane solid-liquid-solid technique, are randomly deployed into an undoped hydrogenated amorphous silicon layer. Local current mapping shows that the wires have internal microstructures. The local current-voltage measurements on these horizontal wires reveal a power law behavior indicating several transport regimes based on space-charge limited conduction which can be assisted by traps in the high-bias regime (> 1 V). Vertical phosphorus-doped SiNWs were grown by chemical vapor deposition using a gold catalyst-driving vapor-liquid-solid process on higly n-type silicon substrates. The effect of phosphorus doping on the local contact resistance between the AFM tip and the SiNW was put in evidence, and the SiNWs resistivity was estimated

    Ensemble Analysis of Angiogenic Growth in Three-Dimensional Microfluidic Cell Cultures

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    We demonstrate ensemble three-dimensional cell cultures and quantitative analysis of angiogenic growth from uniform endothelial monolayers. Our approach combines two key elements: a micro-fluidic assay that enables parallelized angiogenic growth instances subject to common extracellular conditions, and an automated image acquisition and processing scheme enabling high-throughput, unbiased quantification of angiogenic growth. Because of the increased throughput of the assay in comparison to existing three-dimensional morphogenic assays, statistical properties of angiogenic growth can be reliably estimated. We used the assay to evaluate the combined effects of vascular endothelial growth factor (VEGF) and the signaling lipid sphingoshine-1-phosphate (S1P). Our results show the importance of S1P in amplifying the angiogenic response in the presence of VEGF gradients. Furthermore, the application of S1P with VEGF gradients resulted in angiogenic sprouts with higher aspect ratio than S1P with background levels of VEGF, despite reduced total migratory activity. This implies a synergistic effect between the growth factors in promoting angiogenic activity. Finally, the variance in the computed angiogenic metrics (as measured by ensemble standard deviation) was found to increase linearly with the ensemble mean. This finding is consistent with stochastic agent-based mathematical models of angiogenesis that represent angiogenic growth as a series of independent stochastic cell-level decisions

    Rapid and Accurate Prediction and Scoring of Water Molecules in Protein Binding Sites

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    Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity
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