Steven T. Peltier

Community cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource

The Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis (CAMERA, http://camera.calit2.net/) is a database and associated computational infrastructure that provides a single system for depositing, locating, analyzing, visualizing and sharing data about microbial biology through an advanced web-based analysis portal. CAMERA collects and links metadata relevant to environmental metagenome data sets with annotation in a semantically-aware environment allowing users to write expressive semantic queries against the database. To meet the needs of the research community, users are able to query metadata categories such as habitat, sample type, time, location and other environmental physicochemical parameters. CAMERA is compliant with the standards promulgated by the Genomic Standards Consortium (GSC), and sustains a role within the GSC in extending standards for content and format of the metagenomic data and metadata and its submission to the CAMERA repository. To ensure wide, ready access to data and annotation, CAMERA also provides data submission tools to allow researchers to share and forward data to other metagenomics sites and community data archives such as GenBank. It has multiple interfaces for easy submission of large or complex data sets, and supports pre-registration of samples for sequencing. CAMERA integrates a growing list of tools and viewers for querying, analyzing, annotating and comparing metagenome and genome data.

Automated microscopy system for mosaic acquisition and processing.

An automatic mosaic acquisition and processing system for a multiphoton microscope is described for imaging large expanses of biological specimens at or near the resolution limit of light microscopy. In a mosaic, a larger image is created from a series of smaller images individually acquired systematically across a specimen. Mosaics allow wide‐field views of biological specimens to be acquired without sacrificing resolution, providing detailed views of biological specimens within context. The system is composed of a fast‐scanning, multiphoton, confocal microscope fitted with a motorized, high‐precision stage and custom‐developed software programs for automatic image acquisition, image normalization, image alignment and stitching. Our current capabilities allow us to acquire data sets comprised of thousands to tens of thousands of individual images per mosaic. The large number of individual images involved in creating a single mosaic necessitated software development to automate both the mosaic acquisition and processing steps. In this report, we describe the methods and challenges involved in the routine creation of very large scale mosaics from brain tissue labelled with multiple fluorescent probes.

Characterization of a direct detection device imaging camera for transmission electron microscopy.

The complete characterization of a novel direct detection device (DDD) camera for transmission electron microscopy is reported, for the first time at primary electron energies of 120 and 200 keV. Unlike a standard charge coupled device (CCD) camera, this device does not require a scintillator. The DDD transfers signal up to 65 lines/mm providing the basis for a high-performance platform for a new generation of wide field-of-view high-resolution cameras. An image of a thin section of virus particles is presented to illustrate the substantially improved performance of this sensor over current indirectly coupled CCD cameras.

X-ray Microscopy as an Approach to Increasing Accuracy and Efficiency of Serial Block-face Imaging for Correlated Light and Electron Microscopy of Biological Specimens

The recently developed three-dimensional electron microscopic (EM) method of serial block-face scanning electron microscopy (SBEM) has rapidly established itself as a powerful imaging approach. Volume EM imaging with this scanning electron microscopy (SEM) method requires intense staining of biological specimens with heavy metals to allow sufficient back-scatter electron signal and also to render specimens sufficiently conductive to control charging artifacts. These more extreme heavy metal staining protocols render specimens light opaque and make it much more difficult to track and identify regions of interest (ROIs) for the SBEM imaging process than for a typical thin section transmission electron microscopy correlative light and electron microscopy study. We present a strategy employing X-ray microscopy (XRM) both for tracking ROIs and for increasing the efficiency of the workflow used for typical projects undertaken with SBEM. XRM was found to reveal an impressive level of detail in tissue heavily stained for SBEM imaging, allowing for the identification of tissue landmarks that can be subsequently used to guide data collection in the SEM. Furthermore, specific labeling of individual cells using diaminobenzidine is detectable in XRM volumes. We demonstrate that tungsten carbide particles or upconverting nanophosphor particles can be used as fiducial markers to further increase the precision and efficiency of SBEM imaging.

High-resolution large-scale mosaic imaging using multiphoton microscopy to characterize transgenic mouse models of human neurological disorders

The thorough characterization of transgenic mouse models of human central nervous system diseases is a necessary step in realizing the full benefit of using animal models to investigate disease processes and potential therapeutics. Because of the labor- and resource-intensive nature of high-resolution imaging, detailed investigation of possible structural or biochemical alterations in brain sections has typically focused on specific regions of interest as determined by the researcher a priori. For example, Parkinsons disease researchers often focus imaging on regions of the brain expected to exhibit pathology such as the substantia nigra and striatum. Because of limitations in acquiring and storing high-resolution imaging data, additional data contained in the specimen is not usually acquired or disseminated/reported to the research community. Here we present a method of imaging large regions of brain at close to the resolution limit of light microscopy using a mosaic imaging technique in conjunction with multiphoton microscopy. These maps are being used to characterize several genetically modified animal models of neurological disease by filling the information “gap” among techniques such as magnetic resonance imaging and electron microscopic analysis.

Enabling parallel scientific applications with workflow tools

Electron tomography is a powerful tool for deriving three-dimensional (3D) structural information about biological systems within the spatial scale spanning 1 nm3 and 10 mm3. With this technique, it is possible to derive detailed models of sub-cellular components such as organelles and synaptic complexes and to resolve the 3D distribution of their protein constituents in situ. Due in part to exponentially growing raw data-sizes, there continues to be a need for the increased integration of high-performance computing (HPC) and grid technologies with traditional electron tomography processes to provide faster data processing throughput. This is increasingly relevant because emerging mathematical algorithms that provide better data fidelity are more computationally intensive for larger raw data sizes. Progress has been made towards the transparent use of HPC and grid tools for launching scientific applications without passing on the necessary administrative overhead and complexity (resource administration, authentication, scheduling, data delivery) to the non-computer scientist end-user. There is still a need, however, to simplify the use of these tools for applications developers who are developing novel algorithms for computation. Here we describe the architecture of the Telescience project (http://telescience.ucsd.edu), specifically the use of layered workflow technologies to parallelize and execute scientific codes across a distributed and heterogeneous computational resource pool (including resources from the TeraGrid and OptlPuter projects) without the need for the application developer to understand the intricacies of the grid

Multiport-readout frame-transfer 5 megapixel CCD imaging system for TEM applications

A multiport-readout, frame-transfer charge-coupled device (CCD) digital imaging system has been successfully developed and tested for intermediate-high-voltage electron microscopy (IVEM) applications up to 400 keV. The system employs a back-thinned CCD with 2560 x 1960 pixels and a pixel size of 24 microm x 24 microm. In the current implementation, four of the eight on-chip readout ports are used in parallel each operating at a pixel rate of 1- or 2-MHz so that the entire CCD array can be read out in as short as 0.6 s. The frame-transfer readout functions as an electronic shutter which permits the rapid transfer of charges in the active pixels to four masked buffers where the charges are readout and digitized while the active area of the CCD is integrating the next frame. With a thin film-based phosphor screen and a high-performance lens relay, the system has a conversion factor of 2.1 digital units per incident electron at 400 keV, and a modulation transfer function value of 14% at the Nyquist frequency.

Future directions for camera systems in electron microscopy.

Publisher Summary Charge-coupled device (CCD) invented in 1970, soon became the sensor of choice in many imaging applications, particularly for video cameras and camcorders. This chapter reviews current efforts to scale up lens-coupled CCD camera and make a system capable of exceeding the spatial resolution of film, while maintaining single-electron sensitivity. This lens-coupled CCD system represents the current state-of-the-art in CCD-based systems, and it also demonstrates the great engineering effort required to achieve these key performance benchmarks when the detector is based on a resolution-limiting scintillation screen. The chapter discusses the development of a parallel effort to produce a radiation-tolerant system that can withstand direct electron bombardment. It also describes efforts required to adapt the pixel array detector (PAD) that is commonly used in X-ray diffraction, and discusses the development of a groundbreaking prototype system based on an active pixel sensor (APS). This early implementation of an APS-based direct detection detector (DDD) has already delivered unprecedented performance in many areas exceeding the fundamental capabilities of CCD-based systems.

Global telescience featuring IPv6 at iGrid2002

Electron tomography is a powerful technique for deriving 3D structural information from biological specimens. As advanced instrumentation, networking, and grid computing are applied to electron tomography and biological sciences in general, much work is needed to integrate and coordinate these advanced technologies in a transparent way to deliver them to the end user. The Telescience Portal (http://gridport.npaci.edu/Telescience) is a web-based solution for end-to-end electron tomography that centralizes applications and seamlessly interfaces with the grid to accelerate the throughput of data results. In this paper we will describe the architecture and design of the Telescience Portal in the context of our experiences leading up to and including the iGrid2002 workshop. We will examine the lessons learned in developing the production Telescience environment, leveraging a successful international collaboration with groups in Japan and Taiwan, building end-to-end native IPv6 networks across continents, and examining IPv6 enabled mechanisms for transferring large data from two unique, remotely accessible high performance scientific instruments. Traditional computer science communities develop next generation technologies. Applications like Telescience drive these next generation technologies into production quality applications for everyday research needs.

Real-time multi-scale brain data acquisition, assembly, and analysis using an end-to-end OptIPuter

At iGrid 2005 we demonstrated the transparent operation of a biology experiment on a test-bed of globally distributed visualization, storage, computational, and network resources. These resources were bundled into a unified platform by utilizing dynamic lambda allocation, high bandwidth protocols for optical networks, a Distributed Virtual Computer (DVC) [N. Taesombut, A. Chien, Distributed Virtual Computer (DVC): Simplifying the development of high performance grid applications, in: Proceedings of the Workshop on Grids and Advanced Networks, GAN 04, Chicago, IL, April 2004 (held in conjunction with the IEEE Cluster Computing and the Grid (CCGrid2004) Conference)], and applications running over the Scalable Adaptive Graphics Environment (SAGE) [L. Renambot, A. Rao, R. Singh, B. Jeong, N. Krishnaprasad, V. Vishwanath, V. Chandrasekhar, N. Schwarz, A. Spale, C. Zhang, G. Goldman, J. Leigh, A. Johnson, SAGE: The Scalable Adaptive Graphics Environment, in: Proceedings of WACE 2004, 23-24 September 2004, Nice, France, 2004]. Using these layered technologies we ran a multi-scale correlated microscopy experiment [M.E. Maryann, T.J. Deerinck, N. Yamada, E. Bushong, H. Ellisman Mark, Correlated 3D light and electron microscopy: Use of high voltage electron microscopy and electron tomography for imaging large biological structures, Journal of Histotechnology 23 (3) (2000) 261-270], where biologists imaged samples with scales ranging from 20X to 5000X in progressively increasing magnification. This allows the scientists to zoom in from entire complex systems such as a rat cerebellum to individual spiny dendrites. The images used spanned multiple modalities of imaging and specimen preparation, thus providing context at every level and allowing the scientists to better understand the biological structures. This demonstration attempts to define an infrastructure based on OptIPuter components which would aid the development and design of collaborative scientific experiments, applications and test-beds and allow the biologists to effectively use the high resolution real estate of tiled displays.