- Whole Genome Microarray Analyses of a Marine Cyanobacterium
B. Palenik et al (download full text)
Summary - Our unique approach to microarray experiments and analysis has allowed us to use whole genome microarrays in a number of experiments with high confidence in our results. For example, in initial experiments cells grown with nitrate were compared with cells grown with ammonia. The question of whether or when cells are using ammonia or nitrate for growth is an ecologically important one and is unresolved in many marine environments. We found that 247 genes were down-regulated during growth under ammonia compared to nitrate. We have also characterized phosphate limitation in WH8102 and made knockout mutants in a number of the two-component Regulatory systems of the cell including those that are involved in phosphate sensing and regulation. We are also examining phosphate limitation experiments with the wild type and mutant cells using whole genome microarray analyses. Because of its relatively small number of regulatory systems compared to many microbes, Synechococcus sp. WH8102 is an ideal model system for preparing a complete picture of the regulatory networks of an environmentally significant microbe.
- Improving Microarray Analysis with Hyperspectral Imaging and Multivariate Data Analysis
D. M. Haaland et al (download One page overview or full text)
Summary - We have designed, constructed, and characterized a new hyperspectral microarray scanning system that collects a full fluorescence emission spectrum at each pixel. When combined with our improved multivariate curve resolution (MCR) algorithms that can discover and quantitate emissions from spectral data with little a priori information, the new system can identify, model, and correct gene expressions for unknown emissions, increase throughput by accommodating many spectrally overlapped labels in a single scan, and improve sensitivity, accuracy, precision, dynamic range, and reliability.
- New 3-D Hyperspectral Confocal Microscope for in vivo Imaging of Cells
D. M. Haaland et al (download full text)
Summary - Fluorescence imaging has become a critical tool for biologists in the examination of in vivo processes and structures in whole cells. We have designed and built a new state-of-the-art 3-D hyperspectral confocal fluorescence microscope. The new system operates with diffraction-limited spatial resolution in three dimensions (~250 nm in the x and y dimensions and ~600 nm in the z direction). It collects >8,300 full-emission spectra per second (512 wavelengths in the visible spectral region, 490 to 800 nm) with the use of a Sandia-designed imaging prism spectrometer. A state-of-the-art 2-D charge-coupled device (CCD) detector with electron multiplier gain gives the system high sensitivity for low-light applications. The potential applications of this unique instrument are many. With the use of multiple donor-acceptor fluorescence dyes and the fluorescence resonance energy transfer (FRET) method, our new microscope will allow us to simultaneously monitor the formation of multiple protein-protein complexes in living cells.
- Particle-Based Model of Protein Chemistry and Diffusion in Microbial Cells
S. Plimpton and A. Slepoy (download One page overview or full text)
Summary - We have developed a simple simulation model of a prokaryotic cell that treats proteins, protein complexes, and other organic molecules as particles which diffuse via Browniam motion and react with nearby particles in accord with chemical rate equations. In this report we discuss the motivation for the model, highlight its underlying equations, and describe simulations of a 3-stage kinase cascade and a portion of the carbon fixation pathway in the Synechococcus microbe.
- Carboxysome Simulation (download 5.6 MB mpeg movie) -
A discrete particle model of diffusion and chemical reactions within an idealized model of a Synechococcus microbe. The visualization is a 2d projection of a 3d simulation where the outer circle is the cell and the inner circle is a carboxysome. HCO3 (yellow) diffuses into the cell and carboxysome where it is converted to CO2 (small yellow) by carbonic anhydrase (pink). RuBisCO proteins (orange) that have been activated by ribulose (blue) then convert CO2 into 3-carbon sugars which further combine into glucose (green). This is a simplified view of a complex network of reactions that occur in the Calvin cycle as Synechococcus converts inorganic carbon to organic sugars.
- Targeted Molecular Dynamics Simulations of RuBisCO
Paul Crozier et al (download One page overview)
RuBisCO is the primary carbon fixation enzyme in Synechococcus, as well as in other bacteria and all plants. Its poor specificity and inefficiency represent a bottleneck for carbon sequestration and the photosynthetic process. In the Sandia National Laboratories-Oak Ridge National Laboratory Genomics:GTL project, "Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling," we are studying RuBisCO using the targeted molecular dynamics (TMD) method to show how structural changes in its binding niche gating mechanism alter the overall enzyme specificity and performance.
- New Data Entry and Browsing Tool (DEB) simplifies work of experimentalist across multiple sites
Arie Shoshani et al (download full text)
The Scientific Data Management Group at LBNL has developed a web-based Data Entry and Browsing (DEB) tool that facilitates capturing the metadata from experiments in a computer searchable form. The interface design mimics the familiar laboratory notebook format. The DEB system can generate pages that can be used to populate a physical notebook. One of the strong features of the design is the ability to browse through previous experiments and describe the next experiments with minimal effort based on existing entries in the database.
The process of generating and analyzing microarray data for Synechococcus sp. WH8102 whole genome in the Sandia GTL project involves three experimental facilities spread across the nation. Each generates metadata about their operation as well as data files. The Synechococcus sp. microbes are cultured in the Scripps Institution of Oceanography (SIO) in San Diego, then the sample pool is sent to The Institute for Genomics Research (TIGR) in Rockville, Maryland for microarray hybridization, 2-color scanning, and analysis. The scanned files and slides are then sent to Sandia National Laboratories (SNL) in Albuquerque, New Mexico for analysis and additional scanning with a hyperspectral imaging instrument. Each of the institutes has an independent system for keeping track of metadata about their part of the operation. Deb is now in production use to provide easy sharing of metadata between all the sites.
- BiLab - A new Tool that Combines the Ease-of-Use of MatLab and the Power of Multiple Computational Biology Libraries.
Al Geist et al (download One page overview)
We are developing a new tool called BiLab that could revolutionize computational biology the way MATLABŪ revolutionized numerical linear algebra. BiLab is similar to MatLab in look and feel, except instead of only understanding matrices and doing linear algebra, BiLab understands biological objects, such as DNA, proteins, and molecules and is able to manipulate them through any of the functions in a half-dozen standard computational biology libraries. BiLab displays results in biologically relevant form, for example, a protein may be displayed as a molecule, a sequence alignment as stacked sequences. Like MATLAB, data can be typed in manually or read in from files. BiLab understands the concept of remote biological databases and the prototype is able to dynamically load data from SwissProt, GenBank, FASTA, Protein Data Bank, EMBL, and other databases for analysis and study.
- Developed first parallel-R Analysis Package
Nagiza Samatova et al (visit Parallel-R web site)
R is the most popular language and environment for statistical computing and graphics available as open source on uniprocessors today. Researchers at ORNL have developed the first parallel version of R for doing large scale statistical analysis on multiprocessors. Parallel-R augments R (http://www.r-project.org), with process and communication abstractions to enable task, pipeline, and data parallelism. As the only package that provides a parallel framework to statistical data analysis in R, the new Parallel-R package has quickly grown in popularity. It is now being distributed by 27 mirror sites from more than 16 countries.
- More highlights to come...
This work sponsored by the US Department of Energy's Office of Science Genomes to Life Program
Last Modified May 3, 2005 by Al Geist