Jean-Francois Tomb

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.

Electron transport in acetate-grown Methanosarcina acetivorans

BackgroundAcetate 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.ResultsA 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.ConclusionsThe 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.

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

BackgroundFlux 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.ResultsThis 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.ConclusionsA 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.

Enhancing Elementary Flux Modes Analysis Using Filtering Techniques in an Integrated Environment

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 plugin, running on top of the OptFlux Metabolic Engineering workbench, whose aims are to ease the analysis of these results and explore synergies among EFM analysis, phenotype simulation and strain optimization.