Determining the Reliability of Measuring Mercury Cycling Gene Abundance with Correlations with Mercury and Methylmercury Concentrations.

Methylmercury (MeHg) is a bioaccumulative toxic contaminant in many ecosystems, but factors governing its production are poorly understood. Recent work has shown that the anaerobic microbial conversion of mercury (Hg) to MeHg requires the Hg-methylation genes hgcAB and that these genes can be used as biomarkers in PCR-based estimators of Hg-methylator abundance. In an effort to determine reliable methods for assessing hgcA abundance and diversity and linking them to MeHg concentrations, multiple approaches were compared including metagenomic shotgun sequencing, 16S rRNA gene pyrosequencing and cloning/sequencing hgcAB gene products. Hg-methylator abundance was also determined by quantitative hgcA qPCR amplification and metaproteomics for comparison to the above measurements. Samples from eight sites were examined covering a range of total Hg (HgT; 0.03-14 mg kg-1 dry wt. soil) and MeHg (0.05-27 µg kg-1 dry wt. soil) concentrations. In the metagenome and amplicon sequencing of hgcAB diversity, the Deltaproteobacteria were the dominant Hg-methylators while Firmicutes and methanogenic Archaea were typically ∼50% less abundant. This was consistent with metaproteomics estimates where the Deltaproteobacteria were steadily higher. The 16S rRNA gene pyrosequencing did not have sufficient resolution to identify hgcAB+ species. Metagenomic and hgcAB results were similar for Hg-methylator diversity and clade-specific qPCR-based approaches for hgcA are only appropriate when comparing the abundance of a particular clade across various samples. Weak correlations between Hg-methylating bacteria and soil Hg concentrations were observed for similar environmental samples, but overall total Hg and MeHg concentrations poorly correlated with Hg-cycling genes.

Evidence-based green algal genomics reveals marine diversity and ancestral characteristics of land plants.

BACKGROUND: Prasinophytes are widespread marine green algae that are related to plants. Cellular abundance of the prasinophyte Micromonas has reportedly increased in the Arctic due to climate-induced changes. Thus, studies of these unicellular eukaryotes are important for marine ecology and for understanding Viridiplantae evolution and diversification. RESULTS: We generated evidence-based Micromonas gene models using proteomics and RNA-Seq to improve prasinophyte genomic resources. First, sequences of four chromosomes in the 22 Mb Micromonas pusilla (CCMP1545) genome were finished. Comparison with the finished 21 Mb genome of Micromonas commoda (RCC299; named herein) shows they share ≤8,141 of ~10,000 protein-encoding genes, depending on the analysis method. Unlike RCC299 and other sequenced eukaryotes, CCMP1545 has two abundant repetitive intron types and a high percent (26 %) GC splice donors. Micromonas has more genus-specific protein families (19 %) than other genome sequenced prasinophytes (11 %). Comparative analyses using predicted proteomes from other prasinophytes reveal proteins likely related to scale formation and ancestral photosynthesis. Our studies also indicate that peptidoglycan (PG) biosynthesis enzymes have been lost in multiple independent events in select prasinophytes and plants. However, CCMP1545, polar Micromonas CCMP2099 and prasinophytes from other classes retain the entire PG pathway, like moss and glaucophyte algae. Surprisingly, multiple vascular plants also have the PG pathway, except the Penicillin-Binding Protein, and share a unique bi-domain protein potentially associated with the pathway. Alongside Micromonas experiments using antibiotics that halt bacterial PG biosynthesis, the findings highlight unrecognized phylogenetic complexity in PG-pathway retention and implicate a role in chloroplast structure or division in several extant Viridiplantae lineages. CONCLUSIONS: Extensive differences in gene loss and architecture between related prasinophytes underscore their divergence. PG biosynthesis genes from the cyanobacterial endosymbiont that became the plastid, have been selectively retained in multiple plants and algae, implying a biological function. Our studies provide robust genomic resources for emerging model algae, advancing knowledge of marine phytoplankton and plant evolution.

Identification of proteins capable of metal reduction from the proteome of the Gram-positive bacterium Desulfotomaculum reducens†MI-1 using an NADH-based activity assay.

Understanding of microbial metal reduction is based almost solely on studies of Gram-negative organisms. In this study, we focus on Desulfotomaculum reducens MI-1, a Gram-positive metal reducer whose genome lacks genes with similarity to any characterized metal reductase. Using non-denaturing separations and mass spectrometry identification, in combination with a colorimetric screen for chelated Fe(III)-NTA reduction with NADH as electron donor, we have identified proteins from the D. reducens proteome not previously characterized as iron reductases. Their function was confirmed by heterologous expression in Escherichia coli. Furthermore, we show that these proteins have the capability to reduce soluble Cr(VI) and U(VI) with NADH as electron donor. The proteins identified are NADH : flavin oxidoreductase (Dred_2421) and a protein complex composed of oxidoreductase flavin adenine dinucleotide/NAD(P)-binding subunit (Dred_1685) and dihydroorotate dehydrogenase 1B (Dred_1686). Dred_2421 was identified in the soluble proteome and is predicted to be a cytoplasmic protein. Dred_1685 and Dred_1686 were identified in both the soluble as well as the insoluble protein fraction, suggesting a type of membrane association, although PSORTb predicts both proteins are cytoplasmic. This study is the first functional proteomic analysis of D. reducens and one of the first analyses of metal and radionuclide reduction in an environmentally relevant Gram-positive bacterium.

Molecular dissection of a putative iron reductase from Desulfotomaculum reducens MI-1.

Desulfotomaculum reducens MI-1 is a Firmicute strain capable of reducing a variety of heavy metal ions and has a great potential in heavy metal bioremediation. We recently identified Dred_2421 as a potential iron reductase through proteomic study of D. reducens. The current study examines its iron-reduction mechanism. Dred_2421, like its close homolog from Escherichia coli (2, 4-dienoyl-CoA reductase), has an FMN-binding N-terminal domain (NTD), an FAD-binding C-terminal domain (CTD), and a 4Fe-4S cluster between the two domains. To understand the mechanism of the iron-reduction activity and the role of each domain, we generated a series of variants for each domain and investigated their iron-reduction activity. Our results suggest that CTD is the main contributor of the iron-reduction activity, and that NTD and the 4Fe-4S cluster are not directly involved in such activity. This study provides a mechanistic understanding of the iron-reductase activity of Dred_2421 and may also help to elucidate other physiological activities this enzyme may have.

Proteomic profiles of five strains of oxygenic photosynthetic cyanobacteria of the genus Cyanothece.

Members of the cyanobacterial genus Cyanothece exhibit considerable variation in physiological and biochemical characteristics. The comparative assessment of the genomes and the proteomes has the potential to provide insights on differences among Cyanothece strains. By applying Sequedex, an annotation-independent method for ascribing gene functions, we confirmed significant species-specific differences of functional genes in different Cyanothece strains, particularly in Cyanothece PCC7425. Using a shotgun proteomics approach based on prefractionation and tandem mass spectrometry, we detected ∼28-48% of the theoretical Cyanothece proteome, depending on the strain. The expression of a total of 642 orthologous proteins was observed in all five Cyanothece strains. These shared orthologous proteins showed considerable correlations in their abundances across different Cyanothece strains. Functional classification indicated that the majority of proteins involved in central metabolic functions such as amino acid, carbohydrate, protein, and RNA metabolism, photosynthesis, respiration, and stress responses were observed to a greater extent in the core proteome, whereas proteins involved in membrane transport, iron acquisition, regulatory functions, flagellar motility, and chemotaxis were observed to a greater extent in the unique proteome. Considerable differences were evident across different Cyanothece strains. Notably, the analysis of Cyanothece PCC7425, which showed the highest number of unique proteins (682), provided direct evidence of evolutionary differences in this strain. We conclude that Cyanothece PCC7425 diverged significantly from the other Cyanothece strains or evolved from a different lineage.

Gene co-expression network analysis in Rhodobacter capsulatus and application to comparative expression analysis of Rhodobacter sphaeroides.

BACKGROUND: The genus Rhodobacter contains purple nonsulfur bacteria found mostly in freshwater environments. Representative strains of two Rhodobacter species, R. capsulatus and R. sphaeroides, have had their genomes fully sequenced and both have been the subject of transcriptional profiling studies. Gene co-expression networks can be used to identify modules of genes with similar expression profiles. Functional analysis of gene modules can then associate co-expressed genes with biological pathways, and network statistics can determine the degree of module preservation in related networks. In this paper, we constructed an R. capsulatus gene co-expression network, performed functional analysis of identified gene modules, and investigated preservation of these modules in R. capsulatus proteomics data and in R. sphaeroides transcriptomics data. RESULTS: The analysis identified 40 gene co-expression modules in R. capsulatus. Investigation of the module gene contents and expression profiles revealed patterns that were validated based on previous studies supporting the biological relevance of these modules. We identified two R. capsulatus gene modules preserved in the protein abundance data. We also identified several gene modules preserved between both Rhodobacter species, which indicate that these cellular processes are conserved between the species and are candidates for functional information transfer between species. Many gene modules were non-preserved, providing insight into processes that differentiate the two species. In addition, using Local Network Similarity (LNS), a recently proposed metric for expression divergence, we assessed the expression conservation of between-species pairs of orthologs, and within-species gene-protein expression profiles. CONCLUSIONS: Our analyses provide new sources of information for functional annotation in R. capsulatus because uncharacterized genes in modules are now connected with groups of genes that constitute a joint functional annotation. We identified R. capsulatus modules enriched with genes for ribosomal proteins, porphyrin and bacteriochlorophyll anabolism, and biosynthesis of secondary metabolites to be preserved in R. sphaeroides whereas modules related to RcGTA production and signalling showed lack of preservation in R. sphaeroides. In addition, we demonstrated that network statistics may also be applied within-species to identify congruence between mRNA expression and protein abundance data for which simple correlation measurements have previously had mixed results.

SPOCS: software for predicting and visualizing orthology/paralogy relationships among genomes.

SUMMARY: At the rate that prokaryotic genomes can now be generated, comparative genomics studies require a flexible method for quickly and accurately predicting orthologs among the rapidly changing set of genomes available. SPOCS implements a graph-based ortholog prediction method to generate a simple tab-delimited table of orthologs and in addition, html files that provide a visualization of the predicted ortholog/paralog relationships to which gene/protein expression metadata may be overlaid. AVAILABILITY AND IMPLEMENTATION: A SPOCS web application is freely available at http://cbb.pnnl.gov/portal/tools/spocs.html. Source code for Linux systems is also freely available under an open source license at http://cbb.pnnl.gov/portal/software/spocs.html; the Boost C++ libraries and BLAST are required.

A multi-omic survey of black cottonwood tissues highlights coordinated transcriptomic and metabolomic mechanisms for plant adaptation to phosphorus deficiency.

Introduction: Phosphorus (P) deficiency in plants creates a variety of metabolic perturbations that decrease photosynthesis and growth. Phosphorus deficiency is especially challenging for the production of bioenergy feedstock plantation species, such as poplars (Populus spp.), where fertilization may not be practically or economically feasible. While the phenotypic effects of P deficiency are well known, the molecular mechanisms underlying whole-plant and tissue-specific responses to P deficiency, and in particular the responses of commercially valuable hardwoods, are less studied. Methods: We used a multi-tissue and multi-omics approach using transcriptomic, proteomic, and metabolomic analyses of the leaves and roots of black cottonwood (Populus trichocarpa) seedlings grown under P-deficient (5 µM P) and replete (100 µM P) conditions to assess this knowledge gap and to identify potential gene targets for selection for P efficiency. Results: In comparison to seedlings grown at 100 µM P, P-deficient seedlings exhibited reduced dry biomass, altered chlorophyll fluorescence, and reduced tissue P concentrations. In line with these observations, growth, C metabolism, and photosynthesis pathways were downregulated in the transcriptome of the P-deficient plants. Additionally, we found evidence of strong lipid remodeling in the leaves. Metabolomic data showed that the roots of P-deficient plants had a greater relative abundance of phosphate ion, which may reflect extensive degradation of P-rich metabolites in plants exposed to long-term P-deficiency. With the notable exception of the KEGG pathway for Starch and Sucrose Metabolism (map00500), the responses of the transcriptome and the metabolome to P deficiency were consistent with one another. No significant changes in the proteome were detected in response to P deficiency. Discussion and conclusion: Collectively, our multi-omic and multi-tissue approach enabled the identification of important metabolic and regulatory pathways regulated across tissues at the molecular level that will be important avenues to further evaluate for P efficiency. These included stress-mediating systems associated with reactive oxygen species maintenance, lipid remodeling within tissues, and systems involved in P scavenging from the rhizosphere.

Amino acid treatment enhances protein recovery from sediment and soils for metaproteomic studies.

Characterization of microbial protein expression provides information necessary to better understand the unique biological pathways that occur within soil microbial communities that contribute to atmospheric CO2 levels and the earth's changing climate. A significant challenge in studying the soil microbial community proteome is the initial dissociation of bacterial proteins from the complex mixture of particles found in natural soil. The differential extraction of intact bacterial cells limits the characterization of the complete representation of a microbial community. However, in situ lysis of bacterial cells in soil can lead to potentially high levels of protein adsorption to soil particles. Here, we investigated various amino acids for their ability to block soil protein adsorption sites prior to in situ lysis of bacterial cells, as well as their compatibility with both tryptic digestion and mass spectrometric analysis. The treatments were tested by adding proteins from lysed Escherichia coli cells to representative treated and untreated soil samples. The results show that it is possible to significantly increase protein identifications through blockage of binding sites on a variety of soil and sediment textures; use of an optimized desorption buffer further increases the number of identifications.

MultiAlign: a multiple LC-MS analysis tool for targeted omics analysis.

BACKGROUND: MultiAlign is a free software tool that aligns multiple liquid chromatography-mass spectrometry datasets to one another by clustering mass and chromatographic elution features across datasets. Applicable to both label-free proteomics and metabolomics comparative analyses, the software can be operated in several modes. For example, clustered features can be matched to a reference database to identify analytes, used to generate abundance profiles, linked to tandem mass spectra based on parent precursor masses, and culled for targeted liquid chromatography-tandem mass spectrometric analysis. MultiAlign is also capable of tandem mass spectral clustering to describe proteome structure and find similarity in subsequent sample runs. RESULTS: MultiAlign was applied to two large proteomics datasets obtained from liquid chromatography-mass spectrometry analyses of environmental samples. Peptides in the datasets for a microbial community that had a known metagenome were identified by matching mass and elution time features to those in an established reference peptide database. Results compared favorably with those obtained using existing tools such as VIPER, but with the added benefit of being able to trace clusters of peptides across conditions to existing tandem mass spectra. MultiAlign was further applied to detect clusters across experimental samples derived from a reactor biomass community for which no metagenome was available. Several clusters were culled for further analysis to explore changes in the community structure. Lastly, MultiAlign was applied to liquid chromatography-mass spectrometry-based datasets obtained from a previously published study of wild type and mitochondrial fatty acid oxidation enzyme knockdown mutants of human hepatocarcinoma to demonstrate its utility for analyzing metabolomics datasets. CONCLUSION: MultiAlign is an efficient software package for finding similar analytes across multiple liquid chromatography-mass spectrometry feature maps, as demonstrated here for both proteomics and metabolomics experiments. The software is particularly useful for proteomic studies where little or no genomic context is known, such as with environmental proteomics.

Proteome analyses of strains ATCC 51142 and PCC 7822 of the diazotrophic cyanobacterium Cyanothece sp. under culture conditions resulting in enhanced H2 production.

Cultures of the cyanobacterial genus Cyanothece have been shown to produce high levels of biohydrogen. These strains are diazotrophic and undergo pronounced diurnal cycles when grown under N(2)-fixing conditions in light-dark cycles. We seek to better understand the way in which proteins respond to these diurnal changes, and we performed quantitative proteome analysis of Cyanothece sp. strains ATCC 51142 and PCC 7822 grown under 8 different nutritional conditions. Nitrogenase expression was limited to N(2)-fixing conditions, and in the absence of glycerol, nitrogenase gene expression was linked to the dark period. However, glycerol induced expression of nitrogenase during part of the light period, together with cytochrome c oxidase (Cox), glycogen phosphorylase (Glp), and glycolytic and pentose phosphate pathway (PPP) enzymes. This indicated that nitrogenase expression in the light was facilitated via higher levels of respiration and glycogen breakdown. Key enzymes of the Calvin cycle were inhibited in Cyanothece ATCC 51142 in the presence of glycerol under H(2)-producing conditions, suggesting a competition between these sources of carbon. However, in Cyanothece PCC 7822, the Calvin cycle still played a role in cofactor recycling during H(2) production. Our data comprise the first comprehensive profiling of proteome changes in Cyanothece PCC 7822 and allow an in-depth comparative analysis of major physiological and biochemical processes that influence H(2) production in both strains. Our results revealed many previously uncharacterized proteins that may play a role in nitrogenase activity and in other metabolic pathways and may provide suitable targets for genetic manipulation that would lead to improvement of large-scale H(2) production.

Characterizing microbial community and geochemical dynamics at hydrothermal vents using osmotically driven continuous fluid samplers.

Microbes play a key role in mediating aquatic biogeochemical cycles. However, our understanding of the relationships between microbial phylogenetic/physiological diversity and habitat physicochemical characteristics is restrained by our limited capacity to concurrently collect microbial and geochemical samples at appropriate spatial and temporal scales. Accordingly, we have developed a low-cost, continuous fluid sampling system (the Biological OsmoSampling System, or BOSS) to address this limitation. The BOSS does not use electricity, can be deployed in harsh/remote environments, and collects/preserves samples with daily resolution for >1 year. Here, we present data on the efficacy of DNA and protein preservation during a 1.5 year laboratory study as well as the results of two field deployments at deep-sea hydrothermal vents, wherein we examined changes in microbial diversity, protein expression, and geochemistry over time. Our data reveal marked changes in microbial composition co-occurring with changes in hydrothermal fluid composition as well as the temporal dynamics of an enigmatic sulfide-oxidizing symbiont in its free-living state. We also present the first data on in situ protein preservation and expression dynamics highlighting the BOSS's potential utility in meta-proteomic studies. These data illustrate the value of using BOSS to study relationships among microbial and geochemical phenomena and environmental conditions.

Suite of activity-based probes for cellulose-degrading enzymes.

Microbial glycoside hydrolases play a dominant role in the biochemical conversion of cellulosic biomass to high-value biofuels. Anaerobic cellulolytic bacteria are capable of producing multicomplex catalytic subunits containing cell-adherent cellulases, hemicellulases, xylanases, and other glycoside hydrolases to facilitate the degradation of highly recalcitrant cellulose and other related plant cell wall polysaccharides. Clostridium thermocellum is a cellulosome-producing bacterium that couples rapid reproduction rates to highly efficient degradation of crystalline cellulose. Herein, we have developed and applied a suite of difluoromethylphenyl aglycone, N-halogenated glycosylamine, and 2-deoxy-2-fluoroglycoside activity-based protein profiling (ABPP) probes to the direct labeling of the C. thermocellum cellulosomal secretome. These activity-based probes (ABPs) were synthesized with alkynes to harness the utility and multimodal possibilities of click chemistry and to increase enzyme active site inclusion for liquid chromatography-mass spectrometry (LC-MS) analysis. We directly analyzed ABP-labeled and unlabeled global MS data, revealing ABP selectivity for glycoside hydrolase (GH) enzymes, in addition to a large collection of integral cellulosome-containing proteins. By identifying reactivity and selectivity profiles for each ABP, we demonstrate our ability to widely profile the functional cellulose-degrading machinery of the bacterium. Derivatization of the ABPs, including reactive groups, acetylation of the glycoside binding groups, and mono- and disaccharide binding groups, resulted in considerable variability in protein labeling. Our probe suite is applicable to aerobic and anaerobic microbial cellulose-degrading systems and facilitates a greater understanding of the organismal role associated with biofuel development.

Comparison of Chloroflexus aurantiacus strain J-10-fl proteomes of cells grown chemoheterotrophically and photoheterotrophically.

Chloroflexus aurantiacus J-10-fl is a thermophilic green bacterium, a filamentous anoxygenic phototroph, and the model organism of the phylum Chloroflexi. We applied high-throughput, liquid chromatography-mass spectrometry in a global quantitative proteomics investigation of C. aurantiacus cells grown under oxic (chemoorganoheterotrophically) and anoxic (photoorganoheterotrophically) redox states. Our global analysis identified 13,524 high-confidence peptides that matched to 1,286 annotated proteins, 242 of which were either uniquely identified or significantly increased in abundance under photoheterotrophic culture condition. Fifty-four of the 242 proteins are previously characterized photosynthesis-related proteins, including chlorosome proteins, proteins involved in the bacteriochlorophyll biosynthesis, 3-hydroxypropionate (3-OHP) CO(2) fixation pathway, and components of electron transport chains. The remaining 188 proteins have not previously been reported. Of these, five proteins were found to be encoded by genes from a novel operon and observed only in photoheterotrophically grown cells. These proteins candidates may prove useful in further deciphering the phototrophic physiology of C. aurantiacus and other filamentous anoxygenic phototrophs.

Dynamics of organic matter molecular composition under aerobic decomposition and their response to the nitrogen addition in grassland soils.

Grassland soils store a substantial proportion of the global soil carbon (C) stock. The transformation of C in grassland soils with respect to chemical composition and persistence strongly regulate the predicted terrestrial-atmosphere C flux in global C biogeochemical cycling models. In addition, increasing atmospheric nitrogen (N) deposition alters C chemistry in grassland soils. However, there remains controversy about the importance of mineralogical versus biochemical preservation of soil C, as well as uncertainty regarding how grassland soil C chemistry responds to elevated N. This study used grassland soils with diverse soil organic matter (SOM) chemistries in an 8-month aerobic incubation experiment to evaluate whether the chemical composition of SOM converged across sites over time, and how SOM persistence responded to the N addition. This study demonstrates that over the course of incubation, the richness of labile compounds decreased in soils with less ferrihydrite content, whereas labile compounds were more persistent in ferrihydrite rich soils. In contrast, we found that the richness of more complex compounds increased over the incubation in most sites, independent of soil mineralogy. Moreover, we demonstrate the extent to which the diverse chemical composition of SOM converged among sites in response to microbial decomposition. N fertilization decreased soil respiration and inhibited the convergence of molecular composition across ecosystems by altering N demand for microbial metabolism and chemical interactions between minerals and organic molecules. This study provides original evidence that the decomposition and metabolism of labile organic molecules were largely regulated by soil mineralogy (physicochemical preservation), while the metabolism of more complex organic molecules was controlled by substrate complexity (biochemical preservation) independent to mineral-organic interactions. This study advanced our understanding of the dynamic biogeochemical cycling of C by unveiling that N addition dampened C respiration and diminished the convergence of SOM chemistry across diverse grassland ecosystems.

Large improvements in MS/MS-based peptide identification rates using a hybrid analysis.

We report a hybrid search method combining database and spectral library searches that allows for a straightforward approach to characterizing the error rates from the combined data. Using these methods, we demonstrate significantly increased sensitivity and specificity in matching peptides to tandem mass spectra. The hybrid search method increased the number of spectra that can be assigned to a peptide in a global proteomics study by 57-147% at an estimated false discovery rate of 5%, with clear room for even greater improvements. The approach combines the general utility of using consensus model spectra typical of database search methods with the accuracy of the intensity information contained in spectral libraries. A common scoring metric based on recent developments linking data analysis and statistical thermodynamics is used, which allows the use of a conservative estimate of error rates for the combined data. We applied this approach to proteomics analysis of Synechococcus sp. PCC 7002, a cyanobacterium that is a model organism for studies of photosynthetic carbon fixation and biofuels development. The increased specificity and sensitivity of this approach allowed us to identify many more peptides involved in the processes important for photoautotrophic growth.

Deciphering the microbial and molecular responses of geographically diverse Setaria accessions grown in a nutrient-poor soil.

The microbial and molecular characterization of the ectorhizosphere is an important step towards developing a more complete understanding of how the cultivation of biofuel crops can be undertaken in nutrient poor environments. The ectorhizosphere of Setaria is of particular interest because the plant component of this plant-microbe system is an important agricultural grain crop and a model for biofuel grasses. Importantly, Setaria lends itself to high throughput molecular studies. As such, we have identified important intra- and interspecific microbial and molecular differences in the ectorhizospheres of three geographically distant Setaria italica accessions and their wild ancestor S. viridis. All were grown in a nutrient-poor soil with and without nutrient addition. To assess the contrasting impact of nutrient deficiency observed for two S. italica accessions, we quantitatively evaluated differences in soil organic matter, microbial community, and metabolite profiles. Together, these measurements suggest that rhizosphere priming differs with Setaria accession, which comes from alterations in microbial community abundances, specifically Actinobacteria and Proteobacteria populations. When globally comparing the metabolomic response of Setaria to nutrient addition, plants produced distinctly different metabolic profiles in the leaves and roots. With nutrient addition, increases of nitrogen containing metabolites were significantly higher in plant leaves and roots along with significant increases in tyrosine derived alkaloids, serotonin, and synephrine. Glycerol was also found to be significantly increased in the leaves as well as the ectorhizosphere. These differences provide insight into how C4 grasses adapt to changing nutrient availability in soils or with contrasting fertilization schemas. Gained knowledge could then be utilized in plant enhancement and bioengineering efforts to produce plants with superior traits when grown in nutrient poor soils.

Loss of the response regulator CtrA causes pleiotropic effects on gene expression but does not affect growth phase regulation in Rhodobacter capsulatus.

The purple nonsulfur photosynthetic bacterium Rhodobacter capsulatus has been extensively studied for its metabolic versatility as well as for production of a gene transfer agent called RcGTA. Production of RcGTA is highest in the stationary phase of growth and requires the response regulator protein CtrA. The CtrA protein in Caulobacter crescentus has been thoroughly studied for its role as an essential, master regulator of the cell cycle. Although the CtrA protein in R. capsulatus shares a high degree of sequence similarity with the C. crescentus protein, it is nonessential and clearly plays a different role in this bacterium. We have used transcriptomic and proteomic analyses of wild-type and ctrA mutant cultures to identify the genes dysregulated by the loss of CtrA in R. capsulatus. We have also characterized gene expression differences between the logarithmic and stationary phases of growth. Loss of CtrA has pleiotropic effects, with dysregulation of expression of approximately 6% of genes in the R. capsulatus genome. This includes all flagellar motility genes and a number of other putative regulatory proteins but does not appear to include any genes involved in the cell cycle. Quantitative proteomic data supported 88% of the CtrA transcriptome results. Phylogenetic analysis of CtrA sequences supports the hypothesis of an ancestral ctrA gene within the alphaproteobacteria, with subsequent diversification of function in the major alphaproteobacterial lineages.

Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition.

MOTIVATION: LC-MS allows for the identification and quantification of proteins from biological samples. As with any high-throughput technology, systematic biases are often observed in LC-MS data, making normalization an important preprocessing step. Normalization models need to be flexible enough to capture biases of arbitrary complexity, while avoiding overfitting that would invalidate downstream statistical inference. Careful normalization of MS peak intensities would enable greater accuracy and precision in quantitative comparisons of protein abundance levels. RESULTS: We propose an algorithm, called EigenMS, that uses singular value decomposition to capture and remove biases from LC-MS peak intensity measurements. EigenMS is an adaptation of the surrogate variable analysis (SVA) algorithm of Leek and Storey, with the adaptations including (i) the handling of the widespread missing measurements that are typical in LC-MS, and (ii) a novel approach to preventing overfitting that facilitates the incorporation of EigenMS into an existing proteomics analysis pipeline. EigenMS is demonstrated using both large-scale calibration measurements and simulations to perform well relative to existing alternatives. AVAILABILITY: The software has been made available in the open source proteomics platform DAnTE (Polpitiya et al., 2008)) (http://omics.pnl.gov/software/), as well as in standalone software available at SourceForge (http://sourceforge.net).

Analysis of biostimulated microbial communities from two field experiments reveals temporal and spatial differences in proteome profiles.

Stimulated by an acetate-amendment field experiment conducted in 2007, anaerobic microbial populations in the aquifer at the Rifle Integrated Field Research Challenge site in Colorado reduced mobile U(VI) to insoluble U(IV). During this experiment, planktonic biomass was sampled at various time points to quantitatively evaluate proteomes. In 2008, an acetate-amended field experiment was again conducted in a similar manner to the 2007 experiment. As there was no comprehensive metagenome sequence available for use in proteomics analysis, we systematically evaluated 12 different organism genome sequences to generate sets of aggregate genomes, or "pseudo-metagenomes", for supplying relative quantitative peptide and protein identifications. Proteomics results support previous observations of the dominance of Geobacteraceae during biostimulation using acetate as sole electron donor, and revealed a shift from an early stage of iron reduction to a late stage of iron reduction. Additionally, a shift from iron reduction to sulfate reduction was indicated by changes in the contribution of proteome information contributed by different organism genome sequences within the aggregate set. In addition, the comparison of proteome measurements made between the 2007 field experiment and 2008 field experiment revealed differences in proteome profiles. These differences may be the result of alterations in abundance and population structure within the planktonic biomass samples collected for analysis.