Insights into centriole geometry revealed by cryotomography of doublet and triplet centrioles.

Centrioles are cylindrical assemblies comprised of 9 singlet, doublet, or triplet microtubules, essential for the formation of motile and sensory cilia. While the structure of the cilium is being defined at increasing resolution, centriolar structure remains poorly understood. Here, we used electron cryo-tomography to determine the structure of mammalian (triplet) and Drosophila (doublet) centrioles. Mammalian centrioles have two distinct domains: a 200 nm proximal core region connected by A-C linkers, and a distal domain where the C-tubule is incomplete and a pair of novel linkages stabilize the assembly producing a geometry more closely resembling the ciliary axoneme. Drosophila centrioles resemble the mammalian core, but with their doublet microtubules linked through the A tubules. The commonality of core-region length, and the abrupt transition in mammalian centrioles, suggests a conserved length-setting mechanism. The unexpected linker diversity suggests how unique centriolar architectures arise in different tissues and organisms.

The centrosomin CM2 domain is a multi-functional binding domain with distinct cell cycle roles.

The centrosome serves as the main microtubule-organizing center in metazoan cells, yet despite its functional importance, little is known mechanistically about the structure and organizational principles that dictate protein organization in the centrosome. In particular, the protein-protein interactions that allow for the massive structural transition between the tightly organized interphase centrosome and the highly expanded matrix-like arrangement of the mitotic centrosome have been largely uncharacterized. Among the proteins that undergo a major transition is the Drosophila melanogaster protein centrosomin that contains a conserved carboxyl terminus motif, CM2. Recent crystal structures have shown this motif to be dimeric and capable of forming an intramolecular interaction with a central region of centrosomin. Here we use a combination of in-cell microscopy and in vitro oligomer assessment to show that dimerization is not necessary for CM2 recruitment to the centrosome and that CM2 alone undergoes significant cell cycle dependent rearrangement. We use NMR binding assays to confirm this intramolecular interaction and show that residues involved in solution are consistent with the published crystal structure and identify L1137 as critical for binding. Additionally, we show for the first time an in vitro interaction of CM2 with the Drosophila pericentrin-like-protein that exploits the same set of residues as the intramolecular interaction. Furthermore, NMR experiments reveal a calcium sensitive interaction between CM2 and calmodulin. Although unexpected because of sequence divergence, this suggests that centrosomin-mediated assemblies, like the mammalian pericentrin, may be calcium regulated. From these results, we suggest an expanded model where during interphase CM2 interacts with pericentrin-like-protein to form a layer of centrosomin around the centriole wall and that at the onset of mitosis this population acts as a nucleation site of intramolecular centrosomin interactions that support the expansion into the metaphase matrix.

High-performance iterative electron tomography reconstruction with long-object compensation using graphics processing units (GPUs).

Iterative reconstruction algorithms pose tremendous computational challenges for 3D Electron Tomography (ET). Similar to X-ray Computed Tomography (CT), graphics processing units (GPUs) offer an affordable platform to meet these demands. In this paper, we outline a CT reconstruction approach for ET that is optimized for the special demands and application setting of ET. It exploits the fact that ET is typically cast as a parallel-beam configuration, which allows the design of an efficient data management scheme, using a holistic sinogram-based representation. Our method produces speedups of about an order of magnitude over a previously proposed GPU-based ET implementation, on similar hardware, and completes an iterative 3D reconstruction of practical problem size within minutes. We also describe a novel GPU-amenable approach that effectively compensates for reconstruction errors resulting from the TEM data acquisition on (long) samples which extend the width of the parallel TEM beam. We show that the vignetting artifacts typically arising at the periphery of non-compensated ET reconstructions are completely eliminated when our method is employed.

On the efficiency of iterative ordered subset reconstruction algorithms for acceleration on GPUs.

Expectation Maximization (EM) and the Simultaneous Iterative Reconstruction Technique (SIRT) are two iterative computed tomography reconstruction algorithms often used when the data contain a high amount of statistical noise, have been acquired from a limited angular range, or have a limited number of views. A popular mechanism to increase the rate of convergence of these types of algorithms has been to perform the correctional updates within subsets of the projection data. This has given rise to the method of Ordered Subsets EM (OS-EM) and the Simultaneous Algebraic Reconstruction Technique (SART). Commodity graphics hardware (GPUs) has shown great promise to combat the high computational demands incurred by iterative reconstruction algorithms. However, we find that the special architecture and programming model of GPUs add extra constraints on the real-time performance of ordered subsets algorithms, counteracting the speedup benefits of smaller subsets observed on CPUs. This gives rise to new relationships governing the optimal number of subsets as well as relaxation factor settings for obtaining the smallest wall-clock time for reconstruction-a factor that is likely application-dependent. In this paper we study the generalization of SIRT into Ordered Subsets SIRT and show that this allows one to optimize the computational performance of GPU-accelerated iterative algebraic reconstruction methods.

UCSF tomography: an integrated software suite for real-time electron microscopic tomographic data collection, alignment, and reconstruction.

A real-time alignment and reconstruction scheme for electron microscopic tomography (EMT) has been developed and integrated within our UCSF tomography data collection software. This newly integrated software suite provides full automation from data collection to real-time reconstruction by which the three-dimensional (3D) reconstructed volume is immediately made available at the end of each data collection. Real-time reconstruction is achieved by calculating a weighted back-projection on a small Linux cluster (five dual-processor compute nodes) concurrently with the UCSF tomography data collection running on the microscope's computer, and using the fiducial-marker free alignment data generated during the data collection process. The real-time reconstructed 3D volume provides users with immediate feedback to fully asses all aspects of the experiment ranging from sample choice, ice thickness, experimental parameters to the quality of specimen preparation. This information can be used to guide subsequent data collections. Access to the reconstruction is especially useful in low-dose cryo EMT where such information is very difficult to obtain due to extraordinary low signal to noise ratio in each 2D image. In our environment, we generally collect 2048 x 2048 pixel images which are subsequently computationally binned four-fold for the on-line reconstruction. Based upon experiments performed with thick and cryo specimens at various CCD magnifications (50000x-80000x), alignment accuracy is sufficient to support this reduced resolution but should be refined before calculating a full resolution reconstruction. The reduced resolution has proven to be quite adequate to assess sample quality, or to screen for the best data set for full-resolution reconstruction, significantly improving both productivity and efficiency of system resources. The total time from start of data collection to a final reconstructed volume (512 x 512 x 256 pixels) is about 50 min for a +/-70 degrees 2k x 2k pixel tilt series acquired at every 1 degrees.