Metabolic modeling of Halomonas campaniensis improves polyhydroxybutyrate production under nitrogen limitation.

Poly-hydroxybutyrate (PHB) is an environmentally friendly alternative for conventional fossil fuel-based plastics that is produced by various microorganisms. Large-scale PHB production is challenging due to the comparatively higher biomanufacturing costs. A PHB overproducer is the haloalkaliphilic bacterium Halomonas campaniensis, which has low nutritional requirements and can grow in cultures with high salt concentrations, rendering it resistant to contamination. Despite its virtues, the metabolic capabilities of H. campaniensis as well as the limitations hindering higher PHB production remain poorly studied. To address this limitation, we present HaloGEM, the first high-quality genome-scale metabolic network reconstruction, which encompasses 888 genes, 1528 reactions (1257 gene-associated), and 1274 metabolites. HaloGEM not only displays excellent agreement with previous growth data and experiments from this study, but it also revealed nitrogen as a limiting nutrient when growing aerobically under high salt concentrations using glucose as carbon source. Among different nitrogen source mixtures for optimal growth, HaloGEM predicted glutamate and arginine as a promising mixture producing increases of 54.2% and 153.4% in the biomass yield and PHB titer, respectively. Furthermore, the model was used to predict genetic interventions for increasing PHB yield, which were consistent with the rationale of previously reported strategies. Overall, the presented reconstruction advances our understanding of the metabolic capabilities of H. campaniensis for rationally engineering this next-generation industrial biotechnology platform. KEY POINTS: A comprehensive genome-scale metabolic reconstruction of H. campaniensis was developed. Experiments and simulations predict N limitation in minimal media under aerobiosis. In silico media design increased experimental biomass yield and PHB titer.

Metabolic behavior for a mutant Oenococcus oeni strain with high resistance to ethanol to survive under oenological multi-stress conditions.

Malolactic fermentation (MLF) positively influences the quality of the wine, and it occurs as a result of a lactic acid bacteria's metabolism, mainly of the Oenococcus oeni species. However, delays and halting of MLF are frequent problems in the wine industry. This is mainly because O. oeni's development is inhibited by different kinds of stress. Even though the sequencing of the genome of the PSU-1 strain of O. oeni, as well as other strains, has made it possible to identify genes involved in the resistance to some types of stress, all of the factors that could be involved are still unknown. With the aim of contributing to this knowledge, the random mutagenesis technique was used in this study as a strategy for genetic improvement of strains of the O. oeni species. The technique proved to be capable of generating a different and improved strain when compared to the PSU-1 strain (the parent from which it descends). Then, we evaluated the metabolic behavior of both strains in three different wines. We used synthetic MaxOeno wine (pH 3.5; 15% v/v ethanol), red wine (Cabernet Sauvignon), and white wine (Chardonnay). Furthermore, we compared the transcriptome of both strains, grown in MaxOeno synthetic wine. The specific growth rate of the E1 strain was on average 39% higher in comparison to the PSU-1 strain. Interestingly, E1 strain showed an overexpression of the OEOE_1794 gene, which encodes a UspA-like protein, which has been described as promoting growth. We observed that the E1 strain was able to convert, on average, 34% more malic acid into lactate than the PSU-1 strain, regardless of the wine being used. On the other hand, the E1 strain showed a flux rate of fructose-6-phosphate production that was 86% higher than the mannitol production rate, and the internal flux rates increase in the direction of pyruvate production. This coincides with the higher number of OEOE_1708 gene transcripts observed in the E1 strain grown in MaxOeno. This gene encodes for an enzyme fructokinase (EC 2.7.1.4) involved in the transformation of fructose to fructose-6-phosphate.

Genome-scale metabolic models of Microbacterium species isolated from a high altitude desert environment.

The Atacama Desert is the most arid desert on Earth, focus of important research activities related to microbial biodiversity studies. In this context, metabolic characterization of arid soil bacteria is crucial to understand their survival strategies under extreme environmental stress. We investigated whether strain-specific features of two Microbacterium species were involved in the metabolic ability to tolerate/adapt to local variations within an extreme desert environment. Using an integrative systems biology approach we have carried out construction and comparison of genome-scale metabolic models (GEMs) of two Microbacterium sp., CGR1 and CGR2, previously isolated from physicochemically contrasting soil sites in the Atacama Desert. Despite CGR1 and CGR2 belong to different phylogenetic clades, metabolic pathways and attributes are highly conserved in both strains. However, comparison of the GEMs showed significant differences in the connectivity of specific metabolites related to pH tolerance and CO2 production. The latter is most likely required to handle acidic stress through decarboxylation reactions. We observed greater GEM connectivity within Microbacterium sp. CGR1 compared to CGR2, which is correlated with the capacity of CGR1 to tolerate a wider pH tolerance range. Both metabolic models predict the synthesis of pigment metabolites (ß-carotene), observation validated by HPLC experiments. Our study provides a valuable resource to further investigate global metabolic adaptations of bacterial species to grow in soils with different abiotic factors within an extreme environment.

Mapping the Physiological Response of Oenococcus oeni to Ethanol Stress Using an Extended Genome-Scale Metabolic Model.

The effect of ethanol on the metabolism of Oenococcus oeni, the bacterium responsible for the malolactic fermentation (MLF) of wine, is still scarcely understood. Here, we characterized the global metabolic response in O. oeni PSU-1 to increasing ethanol contents, ranging from 0 to 12% (v/v). We first optimized a wine-like, defined culture medium, MaxOeno, to allow sufficient bacterial growth to be able to quantitate different metabolites in batch cultures of O. oeni. Then, taking advantage of the recently reconstructed genome-scale metabolic model iSM454 for O. oeni PSU-1 and the resulting experimental data, we determined the redistribution of intracellular metabolic fluxes, under the different ethanol conditions. Four growth phases were clearly identified during the batch cultivation of O. oeni PSU-1 strain, according to the temporal consumption of malic and citric acids, sugar and amino acids uptake, and biosynthesis rates of metabolic products - biomass, erythritol, mannitol and acetic acid, among others. We showed that, under increasing ethanol conditions, O. oeni favors anabolic reactions related with cell maintenance, as the requirements of NAD(P)+ and ATP increased with ethanol content. Specifically, cultures containing 9 and 12% ethanol required 10 and 17 times more NGAM (non-growth associated maintenance ATP) during phase I, respectively, than cultures without ethanol. MLF and citric acid consumption are vital at high ethanol concentrations, as they are the main source for proton extrusion, allowing higher ATP production by F0F1-ATPase, the main route of ATP synthesis under these conditions. Mannitol and erythritol synthesis are the main sources of NAD(P)+, countervailing for 51-57% of its usage, as predicted by the model. Finally, cysteine shows the fastest specific consumption rate among the amino acids, confirming its key role for bacterial survival under ethanol stress. As a whole, this study provides a global insight into how ethanol content exerts a differential physiological response in O. oeni PSU-1 strain. It will help to design better strategies of nutrient addition to achieve a successful MLF of wine.

Genome-Scale Reconstruction of the Metabolic Network in Oenococcus oeni to Assess Wine Malolactic Fermentation.

Oenococcus oeni is the main responsible agent for malolactic fermentation in wine, an unpredictable and erratic process in winemaking. To address this, we have constructed and exhaustively curated the first genome-scale metabolic model of Oenococcus oeni, comprising 660 reactions, 536 metabolites and 454 genes. In silico experiments revealed that nutritional requirements are predicted with an accuracy of 93%, while 14 amino acids were found to be essential for the growth of this bacterial species. When the model was applied to determine the non-growth associated maintenance, results showed that O. oeni grown at 12% ethanol concentration spent 30 times more ATP to stay alive than in the absence of ethanol. Most of this ATP is employed for extruding protons outside of the cell. A positive relationship was also found between specific consumption rates of fructose, amino acids, oxygen, and malic acid and the specific production rates of erythritol, lactate, and acetate, according to the ethanol content of the medium. The metabolic model reconstructed here represents a unique tool to predict the successful completion of wine malolactic fermentation carried out either by different strains of Oenococcus oeni, as well as at any particular physico-chemical composition of wine. It will also allow the development of consortium metabolic models that could be applied to winemaking to simulate and understand the interactions between O. oeni and other microorganisms that share this ecological niche.

Analysis of Piscirickettsia salmonis Metabolism Using Genome-Scale Reconstruction, Modeling, and Testing.

Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen's biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.