Carbon sequestration in Synechococcus Sp.: from molecular machines to hierarchical modeling.

The U.S. Department of Energy recently announced the first five grants for the Genomes to Life (GTL) Program. The goal of this program is to "achieve the most far-reaching of all biological goals: a fundamental, comprehensive, and systematic understanding of life." While more information about the program can be found at the GTL website (www.doegenomestolife.org), this paper provides an overview of one of the five GTL projects funded, "Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling." This project is a combined experimental and computational effort emphasizing developing, prototyping, and applying new computational tools and methods to elucidate the biochemical mechanisms of the carbon sequestration of Synechococcus Sp., an abundant marine cyanobacteria known to play an important role in the global carbon cycle. Understanding, predicting, and perhaps manipulating carbon fixation in the oceans has long been a major focus of biological oceanography and has more recently been of interest to a broader audience of scientists and policy makers. It is clear that the oceanic sinks and sources of CO(2) are important terms in the global environmental response to anthropogenic atmospheric inputs of CO(2) and that oceanic microorganisms play a key role in this response. However, the relationship between this global phenomenon and the biochemical mechanisms of carbon fixation in these microorganisms is poorly understood. The project includes five subprojects: an experimental investigation, three computational biology efforts, and a fifth which deals with addressing computational infrastructure challenges of relevance to this project and the Genomes to Life program as a whole. Our experimental effort is designed to provide biology and data to drive the computational efforts and includes significant investment in developing new experimental methods for uncovering protein partners, characterizing protein complexes, identifying new binding domains. We will also develop and apply new data measurement and statistical methods for analyzing microarray experiments. Our computational efforts include coupling molecular simulation methods with knowledge discovery from diverse biological data sets for high-throughput discovery and characterization of protein-protein complexes and developing a set of novel capabilities for inference of regulatory pathways in microbial genomes across multiple sources of information through the integration of computational and experimental technologies. These capabilities will be applied to Synechococcus regulatory pathways to characterize their interaction map and identify component proteins in these pathways. We will also investigate methods for combining experimental and computational results with visualization and natural language tools to accelerate discovery of regulatory pathways. Furthermore, given that the ultimate goal of this effort is to develop a systems-level of understanding of how the Synechococcus genome affects carbon fixation at the global scale, we will develop and apply a set of tools for capturing the carbon fixation behavior of complex of Synechococcus at different levels of resolution. Finally, because the explosion of data being produced by high-throughput experiments requires data analysis and models which are more computationally complex, more heterogeneous, and require coupling to ever increasing amounts of experimentally obtained data in varying formats, we have also established a companion computational infrastructure to support this effort as well as the Genomes to Life program as a whole.

Release of extraction-resistant mRNA in stationary phase Saccharomyces cerevisiae produces a massive increase in transcript abundance in response to stress.

BACKGROUND: As carbon sources are exhausted, Saccharomyces cerevisiae cells exhibit reduced metabolic activity and cultures enter the stationary phase. We asked whether cells in stationary phase cultures respond to additional stress at the level of transcript abundance. RESULTS: Microarrays were used to quantify changes in transcript abundance in cells from stationary phase cultures in response to stress. More than 800 mRNAs increased in abundance by one minute after oxidative stress. A significant number of these mRNAs encode proteins involved in stress responses. We tested whether mRNA increases were due to new transcription, rapid poly-adenylation of message (which would not be detected by microarrays), or potential release of mature mRNA present in the cell but resistant to extraction during RNA isolation. Examination of the response to oxidative stress in an RNA polymerase II mutant, rpb1-1, suggested that new transcription was not required. Quantitative RT-PCR analysis of a subset of these transcripts further suggested that the transcripts present in isolated total RNA from stationary phase cultures were polyadenylated. In contrast, over 2,000 transcripts increased after protease treatment of cell-free lysates from stationary phase but not exponentially growing cultures. Different subsets of transcripts were released by oxidative stress and temperature upshift, suggesting that mRNA release is stress-specific. CONCLUSIONS: Cells in stationary phase cultures contain a large number of extraction-resistant mRNAs in a protease-labile, rapidly releasable form. The transcript release appears to be stress-specific. We hypothesize that these transcripts are associated with P-bodies.