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2 Janelia Publications

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    12/01/11 | Superresolution fluorescence imaging of mitochondrial nucleoids reveals their spatial range, limits, and membrane interaction.
    Brown TA, Tkachuk AN, Shtengel G, Kopek BG, Bogenhagen DF, Hess HF, Clayton DA
    Molecular and Cellular Biology. 2011 Dec;31:4994-5010. doi: 10.1128/MCB.05694-11

    A fundamental objective in molecular biology is to understand how DNA is organized in concert with various proteins, RNA, and biological membranes. Mitochondria maintain and express their own DNA (mtDNA), which is arranged within structures called nucleoids. Their functions, dimensions, composition, and precise locations relative to other mitochondrial structures are poorly defined. Superresolution fluorescence microscopy techniques that exceed the previous limits of imaging within the small and highly compartmentalized mitochondria have been recently developed. We have improved and employed both two- and three-dimensional applications of photoactivated localization microscopy (PALM and iPALM, respectively) to visualize the core dimensions and relative locations of mitochondrial nucleoids at an unprecedented resolution. PALM reveals that nucleoids differ greatly in size and shape. Three-dimensional volumetric analysis indicates that, on average, the mtDNA within ellipsoidal nucleoids is extraordinarily condensed. Two-color PALM shows that the freely diffusible mitochondrial matrix protein is largely excluded from the nucleoid. In contrast, nucleoids are closely associated with the inner membrane and often appear to be wrapped around cristae or crista-like inner membrane invaginations. Determinations revealing high packing density, separation from the matrix, and tight association with the inner membrane underscore the role of mechanisms that regulate access to mtDNA and that remain largely unknown.

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    01/01/11 | High resolution segmentation of neuronal tissues from low depth-resolution EM imagery.
    Glasner D, Hu T, Nunez-Iglesias J, Scheffer L, Xu C, Hess H, Fetter R, Chklovskii D, Basri R
    8th International Conference of Energy Minimization Methods in Computer Vision and Pattern Recognition Energy Minimization Methods in Computer Vision and Pattern Recognition. 2011;6819:261-72

    The challenge of recovering the topology of massive neuronal circuits can potentially be met by high throughput Electron Microscopy (EM) imagery. Segmenting a 3-dimensional stack of EM images into the individual neurons is difficult, due to the low depth-resolution in existing high-throughput EM technology, such as serial section Transmission EM (ssTEM). In this paper we propose methods for detecting the high resolution locations of membranes from low depth-resolution images. We approach this problem using both a method that learns a discriminative, over-complete dictionary and a kernel SVM. We test this approach on tomographic sections produced in simulations from high resolution Focused Ion Beam (FIB) images and on low depth-resolution images acquired with ssTEM and evaluate our results by comparing it to manual labeling of this data.

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