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3 Janelia Publications

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    06/22/17 | 3D Bayesian cluster analysis of super-resolution data reveals LAT recruitment to the T cell synapse.
    Griffié J, Shlomovich L, Williamson DJ, Shannon M, Aaron J, Khuon S, L Burn G, Boelen L, Peters R, Cope AP, Cohen EA, Rubin-Delanchy P, Owen DM
    Scientific Reports. 2017 Jun 22;7(1):4077. doi: 10.1038/s41598-017-04450-w

    Single-molecule localisation microscopy (SMLM) allows the localisation of fluorophores with a precision of 10-30 nm, revealing the cell's nanoscale architecture at the molecular level. Recently, SMLM has been extended to 3D, providing a unique insight into cellular machinery. Although cluster analysis techniques have been developed for 2D SMLM data sets, few have been applied to 3D. This lack of quantification tools can be explained by the relative novelty of imaging techniques such as interferometric photo-activated localisation microscopy (iPALM). Also, existing methods that could be extended to 3D SMLM are usually subject to user defined analysis parameters, which remains a major drawback. Here, we present a new open source cluster analysis method for 3D SMLM data, free of user definable parameters, relying on a model-based Bayesian approach which takes full account of the individual localisation precisions in all three dimensions. The accuracy and reliability of the method is validated using simulated data sets. This tool is then deployed on novel experimental data as a proof of concept, illustrating the recruitment of LAT to the T-cell immunological synapse in data acquired by iPALM providing ~10 nm isotropic resolution.

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    Gonen Lab
    06/22/17 | Low-complexity domains adhere by reversible amyloid-like interactions between kinked β-sheets.
    Hughes MP, Sawaya MR, Goldschmidt L, Rodriguez JA, Cascio D, Gonen T, Eisenberg DS
    bioRxiv. 2017 Jun 22:. doi: 10.1101/153817

    Control of metabolism by compartmentation is a widespread feature of higher cells. Recent studies have focused on dynamic intracellular bodies such as stress granules, P-bodies, nucleoli, and metabolic puncta. These bodies appear as separate phases, some containing reversible, amyloid-like fibrils formed by interactions of low-complexity protein domains. Here we report five atomic structures of segments of low-complexity domains from granule-forming proteins, one determined to 1.1 Å resolution by micro-electron diffraction. Four of these interacting protein segments show common characteristics, all in contrast to pathogenic amyloid: kinked peptide backbones, small surface areas of interaction, and predominate attractions between aromatic side-chains. By computationally threading the human proteome on three of our kinked structures, we identified hundreds of low-complexity segments potentially capable of forming such reversible interactions. These segments are found in proteins as diverse as RNA binders, nuclear pore proteins, keratins, and cornified envelope proteins, consistent with the capacity of cells to form a wide variety of dynamic intracellular bodies.

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    Gonen Lab
    06/22/17 | Taking the measure of MicroED.
    Rodriguez JA, Eisenberg DS, Gonen T
    Current Opinion in Structural Biology. 2017 Jun 22;46:79-86. doi: 10.1016/j.sbi.2017.06.004

    It is now possible to routinely determine atomic resolution structures by electron cryo-microscopy (cryoEM), facilitated in part by the method known as micro electron-diffraction (MicroED). Since its initial demonstration in 2013, MicroED has helped determine a variety of protein structures ranging in molecular weight from a few hundred Daltons to several hundred thousand Daltons. Some of these structures were novel while others were previously known. The resolutions of structures obtained thus far by MicroED range from 3.2Å to 1.0Å, with most better than 2.5Å. Crystals of various sizes and shapes, with different space group symmetries, and with a range of solvent content have all been studied by MicroED. The wide range of crystals explored to date presents the community with a landscape of opportunity for structure determination from nano crystals. Here we summarize the lessons we have learned during the first few years of MicroED, and from our attempts at the first ab initio structure determined by the method. We re-evaluate theoretical considerations in choosing the appropriate crystals for MicroED and for extracting the most meaning out of measured data. With more laboratories worldwide adopting the technique, we speculate what the first decade might hold for MicroED.

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