The advent of rapid complete genome sequencing, and the potential to capture this information in genome-scale metabolic models, provide the possibility of comprehensively modeling microbial community interactions. For example, Rhodoferax and Geobacter species are acetate-oxidizing Fe(III)-reducers that compete in anoxic subsurface environments and this competition may have an influence on the in situ bioremediation of uranium-contaminated groundwater. Therefore, genomescale models of Geobacter sulfurreducens and Rhodoferax ferrireducens were used to evaluate how Geobacter and Rhodoferax species might compete under diverse conditions found in a uraniumcontaminated aquifer in Rifle, CO. The model predicted that at the low rates of acetate flux expected under natural conditions at the site, Rhodoferax will outcompete Geobacter as long as sufficient ammonium is available. The model also predicted that when high concentrations of acetate are added during in situ bioremediation, Geobacter species would predominate, consistent with fieldscale observations. This can be attributed to the higher expected growth yields of Rhodoferax and the ability of Geobacter to fix nitrogen. The modeling predicted relative proportions of Geobacter and Rhodoferax in geochemically distinct zones of the Rifle site that were comparable to those that were previously documented with molecular techniques. The model also predicted that under nitrogen fixation, higher carbon and electron fluxes would be diverted toward respiration rather than biomass formation in Geobacter, providing a potential explanation for enhanced in situ U(VI) reduction in low-ammonium zones. These results show that genome-scale modeling can be a useful tool for predicting microbial interactions in subsurface environments and shows promise for designing bioremediation strategies. The ISME Journal (2011) 5, 305-316; doi:10.1038/ismej.2010; published online 29 July 2010 Subject Category: integrated genomics and post-genomics approaches in microbial ecology Keywords: Geobacter; Rhodoferax; community modeling; bioremediation; systems microbiology Introduction A wide phylogenetic diversity of microorganisms that are capable of dissimilatory metal reduction has been recovered from subsurface environments Lovley, 2006). The factors controlling which species predominate in a given subsurface environment are poorly understood, but may have important environmental consequences. For example, some dissimilatory metal-reducing microorganisms, such as those from the Geobacteraceae family, are capable of reducing U(VI) to U(IV), which can impact the mobility of uranium in the subsurface (Lovley, 1991(Lovley, , 2001(Lovley, , 2006Lovley et al., 1993Lovley et al., , 2004Wall and Krumholz, 2006), whereas others do not reduce U(VI) Lovley, 2006). Stimulating dissimilatory metal reduction to promote the reductive precipitation of uranium shows promise as a bioremediation strategy for uranium-contaminated groundwater (Anderson et al., 2003;Vrionis et al., 2005), but relies on stimulating the ...

The authors propose that prokaryotic metabolism is fundamentally constrained by the cytoplasmic membrane surface area available for protein expression, and show that this constraint can explain previously puzzling physiological phenomena, including respiro-fermentation.

Astrocyte dysfunction and inflammation are associated with the pathogenesis of major depressive disorder (MDD). However, the mechanisms underlying these effects remain largely unknown. Here, we found that multiple endocrine neoplasia type 1 (Men1; protein: menin) expression is attenuated in the brain of mice exposed to CUMS (chronic unpredictable mild stress) or lipopolysaccharide. Astrocyte-specific reduction of Men1 (GcKO) led to depressive-like behaviors in mice. We observed enhanced NF-κB activation and IL-1β production with menin deficiency in astrocytes, where depressive-like behaviors in GcKO mice were restored by NF-κB inhibitor or IL-1β receptor antagonist. Importantly, we identified a SNP, rs375804228, in human MEN1, where G503D substitution is associated with a higher risk of MDD onset. G503D substitution abolished menin-p65 interactions, thereby enhancing NF-κB activation and IL-1β production. Our results reveal a distinct astroglial role for menin in regulating neuroinflammation in depression, indicating that menin may be an attractive therapeutic target in MDD.

An alternative consolidated bioprocessing approach is the use of a co-culture containing cellulolytic and solventogenic clostridia. It has been demonstrated that the rate of cellulose utilization in the co-culture of Clostridium acetobutylicum and Clostridium cellulolyticum is improved compared to the mono-culture of C. cellulolyticum, suggesting the presence of syntrophy between these two species. However, the metabolic interactions in the co-culture are not well understood. To understand the metabolic interactions in the co-culture, we developed a genome-scale metabolic model of C. cellulolyticum comprising of 431 genes, 621 reactions, and 603 metabolites. The C. cellulolyticum model can successfully predict the chemostat growth and byproduct secretion with cellulose as the substrate. However, a growth arrest phenomenon, which occurs in batch cultures of C. cellulolyticum at cellulose concentrations higher than 6.7 g/L, cannot be predicted by dynamic flux balance analysis due to the lack of understanding of the underlying mechanism. These genome-scale metabolic models of the pure cultures have also been integrated using a community modeling framework to develop a dynamic model of metabolic interactions in the co-culture. Co-culture simulations suggest that cellobiose inhibition cannot be the main factor that is responsible for improved cellulose utilization relative to mono-culture of C. cellulolyticum.

BackgroundRhodoferax ferrireducens is a metabolically versatile, Fe(III)-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies.ResultsThe iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress.ConclusionThis study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.

Acetate amendment at uranium contaminated sites in Rifle, CO. leads to an initial bloom of Geobacter accompanied by the removal of U(VI) from the groundwater, followed by an increase of sulfate-reducing bacteria (SRBs) which are poor reducers of U(VI). One of the challenges associated with bioremediation is the decay in Geobacter abundance, which has been attributed to the depletion of bio-accessible Fe(III), motivating the investigation of simultaneous amendments of acetate and Fe(III) as an alternative bioremediation strategy. In order to understand the community metabolism of Geobacter and SRBs during artificial substrate amendment, we have created a genome-scale dynamic community model of Geobacter and SRBs using the previously described Dynamic Multi-species Metabolic Modeling framework. Optimization techniques are used to determine the optimal acetate and Fe(III) addition profile. Field-scale simulation of acetate addition accurately predicted the in situ data. The simulations suggest that batch amendment of Fe(III) along with continuous acetate addition is insufficient to promote long-term bioremediation, while continuous amendment of Fe(III) along with continuous acetate addition is sufficient to promote long-term bioremediation. By computationally minimizing the acetate and Fe(III) addition rates as well as the difference between the predicted and target uranium concentration, we showed that it is possible to maintain the uranium concentration below the environmental safety standard while minimizing the cost of chemical additions. These simulations show that simultaneous addition of acetate and Fe(III) has the potential to be an effective uranium bioremediation strategy. They also show that computational modeling of microbial community is an important tool to design effective strategies for practical applications in environmental biotechnology.

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BackgroundIn recent years, constraint-based metabolic models have emerged as an important tool for metabolic engineering; a number of computational algorithms have been developed for identifying metabolic engineering strategies where the production of the desired chemical is coupled with the growth of the organism. A caveat of the existing algorithms is that they do not take the bioprocess into consideration; as a result, while the product yield can be optimized using these algorithms, the product titer and productivity cannot be optimized. In order to address this issue, we developed the Dynamic Strain Scanning Optimization (DySScO) strategy, which integrates the Dynamic Flux Balance Analysis (dFBA) method with existing strain algorithms.ResultsIn order to demonstrate the effective of the DySScO strategy, we applied this strategy to the design of Escherichia coli strains targeted for succinate and 1,4-butanediol production respectively. We evaluated consequences of the tradeoff between growth yield and product yield with respect to titer and productivity, and showed that the DySScO strategy is capable of producing strains that balance the product yield, titer, and productivity. In addition, we evaluated the economic viability of the designed strain, and showed that the economic performance of a strain can be strongly affected by the price difference between the product and the feedstock.ConclusionOur study demonstrated that the DySScO strategy is a useful computational tool for designing microbial strains with balanced yield, titer, and productivity, and has potential applications in evaluating the economic performance of the design strains.