A fundamental goal of the Environmental Stress Pathway Project (ESPP) of the Virtual Institute of Stress and survival (VIMSS) is a rigorous understanding of Desulfovibrio vulgaris Hildenborough physiology and its ability to survive in its environment. Such knowledge will be critical in discerning the biogeochemistry at metal contaminated sites, for bioremediation and natural attenuation for toxic metals. The Functional Genomics and Imaging Core (FGIC) focuses on the measurement of these responses at a cell wide level using systems biology approaches. Progress in the last one year built upon our optimized pipeline for generating biomass for various functional genomics studies and utilized improved genetic methods. Numerous additional transcriptomics data sets were added to our compendium of stress response studies. These included peroxide stress, low oxygen stress, high and low pH stress and alteration of growth conditions (e.g presence of methionine, alternate electron donors etc). To understand how genotype and environment interact to determine the phenotype and fitness of an organism, a long-term evolution experiment was also conducted to examine the dynamics and adaptation of D. vulgaris under extended salt exposure. For many of these stresses iTRAQ based quantitative proteomics and CE-MS based metabolite studies were also conducted. Improved genetic methods were employed to create several critical knock out mutants (e.g. echA, qmoABC and tatA) and several were characterized via growth and transcriptomics studies. Progress was also made in extending transcriptomics analysis to examine alternate D. vulgaris physiological states such as in biofilms and growth in syntrophic co-culture with Methanococcus maripaludis. Methods to conduct iTRAQ proteomics and stable isotopomer (13C) based metabolic flux analysis were also developed for studying co-cultures. A novel FTICR-MS based method for a comparative 12C/13C based metabolite analysis is being developed and will enable a direct comparison of control cultures to experimental samples. Additionally we continued to collect cell wide data in Shewanella oneidensis and Geobacter metallireducens for comparative studies. Great progress was made in improving extraction and high throughput of metabolite studies. Metabolite extraction and CE-MS detection for several hundred metabolites can now be conducted for these non-model organisms using high resolution separation and high resolution mass spectrometric methods. Continued studies to map cell wide responses have also emphasized the importance of changes that require orthologous measurements. With this in mind a novel protocol to monitor protein-protein interactions and redox state of the proteins has been developed. In an effort to supplement model development and elucidate intricacies of stress response cascades, comprehensive methods for identifying alternative regulatory mechanisms such as small non-coding RNAs are also underway. To optimize the use of the large amounts of data being collected, several data mining efforts were initiated. For example, iTRAQ data sets from the multiple stress response studies were mined for potential post translational modifications and confirmation of hypothetical proteins while 13C flux data were used to confirm gene annotation and assess missing steps in metabolic pathways. Work in underway in collaboration with the computational core to set up searchable databases of our proteomics and metabolite data also.