The Omics Dashboard for interactive exploration of gene-expression data.

The Omics Dashboard is a software tool for interactive exploration and analysis of gene-expression datasets. The Omics Dashboard is organized as a hierarchy of cellular systems. At the highest level of the hierarchy the Dashboard contains graphical panels depicting systems such as biosynthesis, energy metabolism, regulation and central dogma. Each of those panels contains a series of X-Y plots depicting expression levels of subsystems of that panel, e.g. subsystems within the central dogma panel include transcription, translation and protein maturation and folding. The Dashboard presents a visual read-out of the expression status of cellular systems to facilitate a rapid top-down user survey of how all cellular systems are responding to a given stimulus, and to enable the user to quickly view the responses of genes within specific systems of interest. Although the Dashboard is complementary to traditional statistical methods for analysis of gene-expression data, we show how it can detect changes in gene expression that statistical techniques may overlook. We present the capabilities of the Dashboard using two case studies: the analysis of lipid production for the marine alga Thalassiosira pseudonana, and an investigation of a shift from anaerobic to aerobic growth for the bacterium Escherichia coli.

Electron transport in acetate-grown Methanosarcina acetivorans.

BACKGROUND: Acetate is the major source of methane in nature. The majority of investigations have focused on acetotrophic methanogens for which energy-conserving electron transport is dependent on the production and consumption of H2 as an intermediate, although the great majority of acetotrophs are unable to metabolize H2. The presence of cytochrome c and a complex (Ma-Rnf) homologous to the Rnf (Rhodobacter nitrogen fixation) complexes distributed in the domain Bacteria distinguishes non-H2-utilizing Methanosarcina acetivorans from H2-utilizing species suggesting fundamentally different electron transport pathways. Thus, the membrane-bound electron transport chain of acetate-grown M. acetivorans was investigated to advance a more complete understanding of acetotrophic methanogens. RESULTS: A component of the CO dehydrogenase/acetyl-CoA synthase (CdhAE) was partially purified and shown to reduce a ferredoxin purified using an assay coupling reduction of the ferredoxin to oxidation of CdhAE. Mass spectrometry analysis of the ferredoxin identified the encoding gene among annotations for nine ferredoxins encoded in the genome. Reduction of purified membranes from acetate-grown cells with ferredoxin lead to reduction of membrane-associated multi-heme cytochrome c that was re-oxidized by the addition of either the heterodisulfide of coenzyme M and coenzyme B (CoM-S-S-CoB) or 2-hydoxyphenazine, the soluble analog of methanophenazine (MP). Reduced 2-hydoxyphenazine was re-oxidized by membranes that was dependent on addition of CoM-S-S-CoB. A genomic analysis of Methanosarcina thermophila, a non-H2-utilizing acetotrophic methanogen, identified genes homologous to cytochrome c and the Ma-Rnf complex of M. acetivorans. CONCLUSIONS: The results support roles for ferredoxin, cytochrome c and MP in the energy-conserving electron transport pathway of non-H2-utilizing acetotrophic methanogens. This is the first report of involvement of a cytochrome c in acetotrophic methanogenesis. The results suggest that diverse acetotrophic Methanosarcina species have evolved diverse membrane-bound electron transport pathways leading from ferredoxin and culminating with MP donating electrons to the heterodisulfide reductase (HdrDE) for reduction of CoM-S-S-CoB.

Characterization of CamH from Methanosarcina thermophila, founding member of a subclass of the {gamma} class of carbonic anhydrases.

The homotrimeric enzyme Mt-Cam from Methanosarcina thermophila is the archetype of the gamma class of carbonic anhydrases. A search of databases queried with Mt-Cam revealed that a majority of the homologs comprise a putative subclass (CamH) in which there is major conservation of all of the residues essential for the archetype Mt-Cam except Glu62 and an acidic loop containing the essential proton shuttle residue Glu84. The CamH homolog from M. thermophila (Mt-CamH) was overproduced in Escherichia coli and characterized to validate its activity and initiate an investigation of the CamH subclass. The Mt-CamH homotrimer purified from E. coli cultured with supplemental zinc (Zn-Mt-CamH) contained 0.71 zinc and 0.15 iron per monomer and had k(cat) and k(cat)/K(m) values that were substantially lower than those for the zinc form of Mt-Cam (Zn-Mt-Cam). Mt-CamH purified from E. coli cultured with supplemental iron (Fe-Mt-CamH) was also a trimer containing 0.15 iron per monomer and only a trace amount of zinc and had an effective k(cat) (k(cat)(eff)) value normalized for iron that was 6-fold less than that for the iron form of Mt-Cam, whereas the k(cat)/K(m)(eff) was similar to that for Fe-Mt-Cam. Addition of 50 mM imidazole to the assay buffer increased the k(cat)(eff) of Fe-Mt-CamH more than 4-fold. Fe-Mt-CamH lost activity when it was exposed to air or 3% H(2)O(2), which supports the hypothesis that Fe(2+) has a role in the active site. The k(cat) for Fe-Mt-CamH was dependent on the concentration of buffer in a way that indicates that it acts as a second substrate in a "ping-pong" mechanism accepting a proton. The k(cat)/K(m) was not dependent on the buffer, consistent with the mechanism for all carbonic anhydrases in which the interconversion of CO(2) and HCO(3)(-) is separate from intermolecular proton transfer.

Characterizing microbial diversity in production water from an Alaskan mesothermic petroleum reservoir with two independent molecular methods.

The phylogenetic diversity of Bacteria and Archaea within a biodegraded, mesothermic petroleum reservoir in the Schrader Bluff Formation of Alaska was examined by two culture-independent methods based on fosmid and small-subunit rRNA gene PCR clone libraries. Despite the exclusion of certain groups by each method, there was overall no significant qualitative difference in the diversity of phylotypes recovered by the two methods. The resident Bacteria belonged to at least 14 phylum-level lineages, including the polyphyletic Firmicutes, which accounted for 36.2% of all small-subunit rRNA gene-containing (SSU(+)) fosmid clones identified. Members of uncultured divisions were also numerous and made up 35.2% of the SSU(+) fosmid clones. Clones from domain Archaea accounted for about half of all SSU(+) fosmids, suggesting that their cell numbers were comparable to those of the Bacteria in this microbial community. In contrast to the Bacteria, however, nearly all archaeal clones recovered by both methods were related to methanogens, especially acetoclastic methanogens, while the plurality of bacterial fosmid clones was affiliated with Synergistes-like acetogenic Firmicutes that possibly degrade longer-chain carboxylic acid components in the crude oil to acetate. These data suggest that acetate may be a key intermediary metabolite in this subsurface anaerobic food chain, which leads to methane production as the primary terminal electron sink.

Microbiome and Blood Analyte Differences Point to Community and Metabolic Signatures in Lean and Obese Horses.

Due to modern management practices and the availability of energy dense feeds, obesity is a serious and increasingly common health problem for horses. Equine obesity is linked to insulin resistance and exacerbation of inflammatory issues such as osteoarthritis and laminitis. While the gut microbiome is thought to play a part in metabolic status in horses, bacterial communities associated with obesity have yet to be described. Here we report differences in metabolic factors in the blood of obese, normal and lean horses correlated with differences in gut microbiome composition. We report that obese horses had higher levels of leptin, triglycerides, glucose, and cortisol in their blood, and more diverse gut microbiome communities with higher relative abundance of Firmicutes, and lower numbers of Bacteroidetes and Actinobacteria. Network analyses of correlations between body condition, blood analytes, and microbial composition at the genus level revealed a more nuanced picture of microbe-host interactions, pointing to specific bacterial species and assemblages that may be signatures of obesity and leanness in the horse gut. In particular, bacteria groups positively associated with two blood analytes and obesity included Butyrivibrio spp., Prevotellaceae, Blautia spp., two members of Erysipelotrichaceae, and a Lachnospiraceae taxa. These results are an important first step in unraveling the metabolic differences between obese and lean horse gut communities, and designing targeted strategies for microbial intervention.

Genomic and proteomic analyses reveal multiple homologs of genes encoding enzymes of the methanol:coenzyme M methyltransferase system that are differentially expressed in methanol- and acetate-grown Methanosarcina thermophila.

Each of the genomic sequences of Methanosarcina acetivorans, Methanosarcina mazei, and Methanosarcina thermophila revealed two homologs of mtaA, three homologs of mtaB, and three homologs of mtaC encoding enzymes specific for methanogenesis from methanol. Two-dimensional gel electrophoretic analyses of polypeptides from M. thermophila established that methanol induces the expression of mtaA-1, mtaB-1, mtaB-2, mtaB-3, mtaC-1, mtaC-2, and mtaC-3 whereas mtaB-3 and mtaC-3 are constitutively expressed in acetate-grown cells. The gene product of one of three mttC homologs, encoding trimethylamine-specific methyltransferase I, was detected in methanol- but not acetate-grown M. thermophila. A postulated role for the multiple homologs is discussed.

CBFA: phenotype prediction integrating metabolic models with constraints derived from experimental data.

BACKGROUND: Flux analysis methods lie at the core of Metabolic Engineering (ME), providing methods for phenotype simulation that allow the determination of flux distributions under different conditions. Although many constraint-based modeling software tools have been developed and published, none provides a free user-friendly application that makes available the full portfolio of flux analysis methods. RESULTS: This work presents Constraint-based Flux Analysis (CBFA), an open-source software application for flux analysis in metabolic models that implements several methods for phenotype prediction, allowing users to define constraints associated with measured fluxes and/or flux ratios, together with environmental conditions (e.g. media) and reaction/gene knockouts. CBFA identifies the set of applicable methods based on the constraints defined from user inputs, encompassing algebraic and constraint-based simulation methods. The integration of CBFA within the OptFlux framework for ME enables the utilization of different model formats and standards and the integration with complementary methods for phenotype simulation and visualization of results. CONCLUSIONS: A general-purpose and flexible application is proposed that is independent of the origin of the constraints defined for a given simulation. The aim is to provide a simple to use software tool focused on the application of several flux prediction methods.

An integrated computational environment for elementary modes analysis of biochemical networks.

Elementary flux modes (EFMs) have been claimed as one of the most promising approaches for pathway analysis. These are a set of vectors that emerge from the stoichiometric matrix of a biochemical network through the use of convex analysis. The computation of all EFMs of a given network is an NP-hard problem and existing algorithms do not scale well. Moreover, the analysis of results is difficult given the thousands or millions of possible modes generated. In this work, we propose a new plug-in, running on top of the OptFlux Metabolic Engineering workbench (Rocha et al., 2010), whose aims are to ease the analysis of these results and explore synergies among EFM analysis, phenotype simulation and strain optimisation. Two case studies are shown to illustrate the capabilities of the proposed tool.

TraA is required for megaplasmid conjugation in Rhodococcus erythropolis AN12.

Pulsed-field gel electrophoresis (PFGE) revealed three previously uncharacterized megaplasmids in the genome of Rhodococcus erythropolis AN12. These megaplasmids, pREA400, pREA250, and pREA100, are approximately 400, 250, and 100kb, respectively, based on their migration in pulsed-field gels. Genetic screening of an AN12 transposon insertion library showed that two megaplasmids, pREA400, and pREA250, are conjugative. Mobilization frequencies of these AN12 megaplasmids to recipient R. erythropolis SQ1 were determined to be approximately 7x10(-4) and 5x10(-4) events per recipient cell, respectively. It is known for other bacterial systems that a relaxase encoded by the traA gene is required to initiate DNA transfer during plasmid conjugation. Sequences adjacent to the transposon insertion in megaplasmid pREA400 revealed a putative traA-like open reading frame. A targeted gene disruption method was developed to generate a traA mutation in AN12, which allowed us to address the role of the traA gene product for Rhodococcus megaplasmid conjugation. We found that the AN12 traA mutant is no longer capable of transferring the pREA400 megaplasmid to SQ1. Furthermore, we confirmed that the conjugation defect was specifically due to the disruption of the traA gene, as pREA400 megaplasmid conjugation defect is restored with a complementing copy of the traA gene.

Identification of bifunctional delta12/omega3 fatty acid desaturases for improving the ratio of omega3 to omega6 fatty acids in microbes and plants.

We report the identification of bifunctional Delta12/omega3 desaturases from Fusarium moniliforme, Fusarium graminearum, and Magnaporthe grisea. The bifunctional activity of these desaturases distinguishes them from all known Delta12 or omega3 fatty acid desaturases. The omega3 desaturase activity of these enzymes also shows a broad omega6 fatty acid substrate specificity by their ability to convert linoleic acid (LA), gamma-linolenic acid, di-homo-gamma-linolenic acid, and arachidonic acid to the omega3 fatty acids, alpha-linolenic acid (ALA), stearidonic acid, eicosatetraenoic acid, and eicosapentaenoic acid (EPA), respectively. Phylogenetic analysis suggests that omega3 desaturases arose by independent gene duplication events from a Delta12 desaturase ancestor. Expression of F. moniliforme Delta12/omega3 desaturase resulted in high ALA content in both Yarrowia lipolytica, an oleaginous yeast naturally deficient in omega3 desaturation, and soybean. In soybean, seed-specific expression resulted in 70.9 weight percent of total fatty acid (%TFA) ALA in a transformed seed compared with 10.9%TFA in a null segregant seed and 53.2%TFA in the current best source of ALA, linseed oil. The ALA/LA ratio in transformed seed was 22.3, a 110- and 7-fold improvement over the null segregant seed and linseed oil, respectively. Thus, these desaturases have potential for producing nutritionally desirable omega3 long-chain polyunsaturated fatty acids, such as EPA, with a significantly improved ratio of omega3/omega6 long-chain polyunsaturated fatty acids in both oilseeds and oleaginous microbes.