Modeling the Interplay between Photosynthesis, CO2 Fixation, and the Quinone Pool in a Purple Non-Sulfur Bacterium

Increase CO2 recycling of Escherichia coli containing CBB genes by enhancing solubility of multiple expressed proteins from an operon through temperature reduction

IMPORTANCE

In a previous study, we successfully engineered Escherichia coli capable of endogenous CO2 recycling through the heterologous expression of the Calvin-Benson Bassham genes. Establishing an efficient gene expression environment for recombinant strains is crucial, on par with the importance of metabolic engineering design. Therefore, the primary objective of this study was to further mitigate greenhouse gas emissions by investigating the effects of culture temperature on the formation of inclusion bodies (IB) and CO2 fixation activity in the engineered bacterial strain. The findings demonstrate that lowering the culture temperature effectively suppresses IB formation, enhances CO2 recycling, and concurrently increases the accumulation of organic acids. This temperature control approach, without adding or modifying compounds, is both convenient and efficient for enhancing CO2 recycling. As such, additional optimization of various environmental parameters holds promise for further enhancing the performance of recombinant strains efficiently.

The genome-scale metabolic model for the purple non-sulfur bacterium Rhodopseudomonas palustris Bis A53 accurately predicts phenotypes under chemoheterotrophic, chemoautotrophic, photoheterotrophic, and photoautotrophic growth conditions

The purple non-sulfur bacterium Rhodopseudomonas palustris is recognized as a critical microorganism in the nitrogen and carbon cycle and one of the most common members in wastewater treatment communities. This bacterium is metabolically extremely versatile. It is capable of heterotrophic growth under aerobic and anaerobic conditions, but also able to grow photoautotrophically as well as mixotrophically. Therefore R. palustris can adapt to multiple environments and establish commensal relationships with other organisms, expressing various enzymes supporting degradation of amino acids, carbohydrates, nucleotides, and complex polymers. Moreover, R. palustris can degrade a wide range of pollutants under anaerobic conditions, e.g., aromatic compounds such as benzoate and caffeate, enabling it to thrive in chemically contaminated environments. However, many metabolic mechanisms employed by R. palustris to breakdown and assimilate different carbon and nitrogen sources under chemoheterotrophic or photoheterotrophic conditions remain unknown. Systems biology approaches, such as metabolic modeling, have been employed extensively to unravel complex mechanisms of metabolism. Previously, metabolic models have been reconstructed to study selected capabilities of R. palustris under limited experimental conditions. Here, we developed a comprehensive metabolic model (M-model) for R. palustris Bis A53 (iDT1294) consisting of 2,721 reactions, 2,123 metabolites, and comprising 1,294 genes. We validated the model using high-throughput phenotypic, physiological, and kinetic data, testing over 350 growth conditions. iDT1294 achieved a prediction accuracy of 90% for growth with various carbon and nitrogen sources and close to 80% for assimilation of aromatic compounds. Moreover, the M-model accurately predicts dynamic changes of growth and substrate consumption rates over time under nine chemoheterotrophic conditions and demonstrated high precision in predicting metabolic changes between photoheterotrophic and photoautotrophic conditions. This comprehensive M-model will help to elucidate metabolic processes associated with the assimilation of multiple carbon and nitrogen sources, anoxygenic photosynthesis, aromatic compound degradation, as well as production of molecular hydrogen and polyhydroxybutyrate.

Dehazing redox homeostasis to foster purple bacteria biotechnology

Purple non-sulfur bacteria (PNSB) show great potential for environmental and industrial biotechnology, producing microbial protein, biohydrogen, polyhydroxyalkanoates (PHAs), pigments, etc. When grown photoheterotrophically, the carbon source is typically more reduced than the PNSB biomass, which leads to a redox imbalance. To mitigate the excess of electrons, PNSB can exhibit several 'electron sinking' strategies, such as CO₂ fixation, N₂ fixation, and H₂ and PHA production. The lack of a comprehensive (over)view of these redox strategies is hindering the implementation of PNSB for biotechnology applications. This review aims to present the state of the art of redox homeostasis in phototrophically grown PNSB, presenting known and theoretically expected strategies, and discussing them from stoichiometric, thermodynamic, metabolic, and economic points of view.

Novel Production Methods of Polyhydroxyalkanoates and Their Innovative Uses in Biomedicine and Industry

Polyhydroxyalkanoate (PHA), a biodegradable polymer obtained from microorganisms and plants, have been widely used in biomedical applications and devices, such as sutures, cardiac valves, bone scaffold, and drug delivery of compounds with pharmaceutical interests, as well as in food packaging. This review focuses on the use of polyhydroxyalkanoates beyond the most common uses, aiming to inform about the potential uses of the biopolymer as a biosensor, cosmetics, drug delivery, flame retardancy, and electrospinning, among other interesting uses. The novel applications are based on the production and composition of the polymer, which can be modified by genetic engineering, a semi-synthetic approach, by changing feeding carbon sources and/or supplement addition, among others. The future of PHA is promising, and despite its production costs being higher than petroleum-based plastics, tools given by synthetic biology, bioinformatics, and machine learning, among others, have allowed for great production yields, monomer and polymer functionalization, stability, and versatility, a key feature to increase the uses of this interesting family of polymers.

Light intensity defines growth and photopigment content of a mixed culture of purple phototrophic bacteria

Purple bacteria (PPB), anoxygenic photoorganoheterotrophic organisms with a hyper-versatile metabolism and high biomass yields over substrate, are promising candidates for the recovery of nutrient resources from wastewater. Infrared light is a pivotal parameter to control and design PPB-based resource recovery. However, the effects of light intensities on the physiology and selection of PPB in mixed cultures have not been studied to date. Here, we examined the effect of infrared irradiance on PPB physiology, enrichment, and growth over a large range of irradiance (0 to 350 W m−2) in an anaerobic mixed-culture sequencing batch photobioreactor. We developed an empirical mathematical model that suggests higher PPB growth rates as response to higher irradiance. Moreover, PPB adapted to light intensity by modulating the abundances of their phototrophic complexes. The obtained results provide an in-depth phylogenetic and metabolic insight the impact of irradiance on PPB. Our findings deliver the fundamental information for guiding the design of light-driven, anaerobic mixed-culture PPB processes for wastewater treatment and bioproduct valorization.

Characterizing the Interplay of Rubisco and Nitrogenase Enzymes in Anaerobic-Photoheterotrophically Grown Rhodopseudomonas palustris CGA009 through a Genome-Scale Metabolic and Expression Model

Rhodopseudomonas palustris CGA009 is a Gram-negative purple nonsulfur bacterium that grows phototrophically by fixing carbon dioxide and nitrogen or chemotrophically by fixing or catabolizing a wide array of substrates, including lignin breakdown products for its carbon and fixing nitrogen for its nitrogen requirements. It can grow aerobically or anaerobically and can use light, inorganic, and organic compounds for energy production. Due to its ability to convert different carbon sources into useful products during anaerobic growth, this study reconstructed a metabolic and expression (ME) model of R. palustris to investigate its anaerobic-photoheterotrophic growth. Unlike metabolic (M) models, ME models include transcription and translation reactions along with macromolecules synthesis and couple these reactions with growth rate. This unique feature of the ME model led to nonlinear growth curve predictions, which matched closely with experimental growth rate data. At the theoretical maximum growth rate, the ME model suggested a diminishing rate of carbon fixation and predicted malate dehydrogenase and glycerol-3 phosphate dehydrogenase as alternate electron sinks. Moreover, the ME model also identified ferredoxin as a key regulator in distributing electrons between major redox balancing pathways. Because ME models include the turnover rate for each metabolic reaction, it was used to successfully capture experimentally observed temperature regulation of different nitrogenases. Overall, these unique features of the ME model demonstrated the influence of nitrogenases and rubiscos on R. palustris growth and predicted a key regulator in distributing electrons between major redox balancing pathways, thus establishing a platform for in silico investigation of R. palustris metabolism from a multiomics perspective. IMPORTANCE In this work, we reconstructed the first ME model for a purple nonsulfur bacterium (PNSB). Using the ME model, different aspects of R. palustris metabolism were examined. First, the ME model was used to analyze how reducing power entering the R. palustris cell through organic carbon sources gets partitioned into biomass, carbon dioxide fixation, and nitrogen fixation. Furthermore, the ME model predicted electron flux through ferredoxin as a major bottleneck in distributing electrons to nitrogenase enzymes. Next, the ME model characterized different nitrogenase enzymes and successfully recapitulated experimentally observed temperature regulations of those enzymes. Identifying the bottleneck responsible for transferring an electron to nitrogenase enzymes and recapitulating the temperature regulation of different nitrogenase enzymes can have profound implications in metabolic engineering, such as hydrogen production from R. palustris. Another interesting application of this ME model can be to take advantage of its redox balancing strategy to gain an understanding of the regulatory mechanism of biodegradable plastic production precursors, such as polyhydroxybutyrate (PHB).

Rhodopseudomonas palustris: A biotechnology chassis

Rhodopseudomonas palustris is an attractive option for biotechnical applications and industrial engineering due to its metabolic versatility and its ability to catabolize a wide variety of feedstocks and convert them to several high-value products. Given its adaptable metabolism, R. palustris has been studied and applied in an extensive variety of applications such as examining metabolic tradeoffs for environmental perturbations, biodegradation of aromatic compounds, environmental remediation, biofuel production, agricultural biostimulation, and bioelectricity production. This review provides a holistic summary of the commercial applications for R. palustris as a biotechnology chassis and suggests future perspectives for research and engineering.

Synthetic Biology Tool Development Advances Predictable Gene Expression in the Metabolically Versatile Soil Bacterium Rhodopseudomonas palustris

Harnessing the unique biochemical capabilities of non-model microorganisms would expand the array of biomanufacturing substrates, process conditions, and products. There are non-model microorganisms that fix nitrogen and carbon dioxide, derive energy from light, catabolize methane and lignin-derived aromatics, are tolerant to physiochemical stresses and harsh environmental conditions, store lipids in large quantities, and produce hydrogen. Model microorganisms often only break down simple sugars and require low stress conditions, but they have been engineered for the sustainable manufacture of numerous products, such as fragrances, pharmaceuticals, cosmetics, surfactants, and specialty chemicals, often by using tools from synthetic biology. Transferring complex pathways has proven to be exceedingly difficult, as the cofactors, cellular conditions, and energy sources necessary for this pathway to function may not be present in the host organism. Utilization of unique biochemical capabilities could also be achieved by engineering the host; although, synthetic biology tools developed for model microbes often do not perform as designed in other microorganisms. The metabolically versatile Rhodopseudomonas palustris CGA009, a purple non-sulfur bacterium, catabolizes aromatic compounds derived from lignin in both aerobic and anaerobic conditions and can use light, inorganic, and organic compounds for its source of energy. R. palustris utilizes three nitrogenase isozymes to fulfill its nitrogen requirements while also generating hydrogen. Furthermore, the bacterium produces two forms of RuBisCo in response to carbon dioxide/bicarbonate availability. While this potential chassis harbors many beneficial traits, stable heterologous gene expression has been problematic due to its intrinsic resistance to many antibiotics and the lack of synthetic biology parts investigated in this microbe. To address these problems, we have characterized gene expression and plasmid maintenance for different selection markers, started a synthetic biology toolbox specifically for the photosynthetic R. palustris, including origins of replication, fluorescent reporters, terminators, and 5′ untranslated regions, and employed the microbe’s endogenous plasmid for exogenous protein production. This work provides essential synthetic biology tools for engineering R. palustris’ many unique biochemical processes and has helped define the principles for expressing heterologous genes in this promising microbe through a methodology that could be applied to other non-model microorganisms.

Engineered Mutants of a Marine Photosynthetic Purple Nonsulfur Bacterium with Increased Volumetric Productivity of Polyhydroxyalkanoate Bioplastics

Polyhydroxyalkanoates (PHAs) are green and sustainable bioplastics that could replace petrochemical synthetic plastics without posing environmental threats to living organisms. In addition, sustainable PHA production could be achieved using marine photosynthetic purple nonsulfur bacteria (PNSBs) that utilize natural seawater, sunlight, carbon dioxide gas, and nitrogen gas for growth. However, PHA production using marine photosynthetic PNSBs has not been economically feasible yet due to its high cost and low productivity. In this work, strain improvement, using genome-wide mutagenesis coupled with high-throughput screening via fluorescence-activated cell sorting, we were able to create Rhodovulum sulfidophilum mutants with enhanced volumetric PHA productivity, with an up to 1.7-fold increase. The best selected mutants (E6 and E6M4) reached the stationary growth phase 1 day faster and accumulated the maximum PHA content 2 days faster than the wild type. Maximizing volumetric PHA productivity before the stationary growth phase is indeed an additional advantage for R. sulfidophilum as a growth-associated PHA producer.

Microbial methane emissions from the non-methanogenesis processes: A critical review

Methane, a potent greenhouse gas of global importance, has traditionally been considered as an end product of microbial methanogenesis of organic matter. Paradoxically, growing evidence has shown that some microbes, such as cyanobacteria, algae, fungi, purple non-sulfur bacteria, and cryptogamic covers, produce methane in oxygen-saturated aquatic and terrestrial ecosystems. The non-methanogenesis process could be an important potential contributor to methane emissions. This systematic review summarizes the knowledge of microorganisms involved in the non-methanogenesis process and the possible mechanisms of methane formation. Cyanobacteria-derived methane production may be attributed to either demethylation of methyl phosphonates or linked to light-driven primary productivity, while algae produce methane by utilizing methylated sulfur compounds as possible carbon precursors. In addition, fungi produce methane by utilizing methionine as a possible carbon precursor, and purple non-sulfur bacteria reduce carbon dioxide to methane by nitrogenase. The microbial methane distribution from the non-methanogenesis processes in aquatic and terrestrial environments and its environmental significance to global methane emissions, possible mechanisms of methane production in each open water, water-to-air methane fluxes, and the impact of climate change on microorganisms are also discussed. Finally, future perspectives are highlighted, such as establishing more in-situ experiments, quantifying methane flux through optimizing empirical models, distinguishing individual methane sources, and investigating nitrogenase-like enzyme systems to improve our understanding of microbial methane emission from the non-methanogenesis process.

Heterologous phasin expression in Rhodopseudomonas palustris CGA009 for bioplastic production from lignocellulosic biomass

Rhodopseudomonas palustris CGA009 is a metabolically robust microbe that can utilize lignin breakdown products to produce polyhydroxyalkanoates (PHAs), biopolymers with the potential to replace conventional plastics. Our recent efforts suggest PHA granule formation is a limiting factor for maximum production of the bioplastic poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) by R. palustris. The Phap1 phasin (phaP1) from the PHB-producing model bacterium Cupriavidus necator H16 was expressed in R. palustris with the aim of overproducing PHBV from the lignin breakdown product p-coumarate by fostering smaller and more abundant granules. Expression of phaP1 yielded PHBV production from R. palustris aerobically (0.7 g/L), which does not occur in the wild-type strain, and led to a significantly higher PHBV titer than wild-type anaerobic production (0.41 g/L). The 3HV fractions were also significantly increased under both anaerobic and aerobic conditions, which boosts thermomechanical properties and potential for application. Thus, heterologous phasin expression in R. palustris provides flexibility for industrial processing and could foster compositional changes in copolymers with better thermomechanical properties compared to PHB alone.

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Heterologous phasin expression in R. palustris fostered aerobic bioplastic production.

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Offers flexibility for industrial processing of high-value products from lignocellosic biomass.

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Composition increases in desirable monomer fractions occurred due to phasin expression.

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Further develops the metabolically robust R. palustris as a biotechnology chassis.

Synergistic experimental and computational approach identifies novel strategies for polyhydroxybutyrate overproduction

Polyhydroxybutyrate (PHB) is a sustainable bioplastic produced by bacteria that is a potential replacement for conventional plastics. This study delivers an integrated experimental and computational modeling approach to decipher metabolic factors controlling PHB production and offers engineering design strategies to boost production. In the metabolically robust Rhodopseudomonas palustris CGA009, PHB production significantly increased when grown on the carbon- and electron-rich lignin breakdown product p-coumarate (C₉H₈O₃) compared to virtually no PHB titer from acetate (C₂H₃NaO₂). The maximum yield did not improve further when grown on coniferyl alcohol (C₁₀H₁₂O₃), but comparison of the PHB profiles showed that coniferyl alcohol's higher carbon content resulted in a higher rate of PHB production. Combined experimental results revealed that cytoplasmic space may be a limiting factor for maximum PHB titer. In order to obtain a systems-level understanding of factors driving PHB yield, a model-driven investigation was performed. The model yielded several engineering design strategies including utilizing reduced, high molecular weight substrates that bypass the thiolase reaction (phaA). Based on these strategies, utilization of butyrate was predicted and subsequently validated to produce PHB. Model analysis also explained why nitrogen starvation was not essential for PHB production and revealed that renewable and abundant lignin aromatics are ideal candidates for PHB production. Most importantly, the generality of the derived design rules allows them to be applied to any PHB-producing microbe with similar metabolic features.

Up-scale challenges on biopolymer production from waste streams by Purple Phototrophic Bacteria mixed cultures: A critical review

The increasing volume of waste streams require new biological technologies that can address pollution concerns while offering sustainable products. Purple phototrophic bacteria (PPB) are very versatile organisms that present a unique metabolism that allows them to adapt to a variety of environments, including the most complex waste streams. Their successful adaptation to such demanding conditions is partly the result of internal polymers accumulation which can be stored for electron/energy balance or as carbon and nutrients reserves for deprivation periods. Polyhydroxyalkanoates, glycogen, sulphur and polyphosphate are examples of polymers produced by PPB that can be economically explored due to their applications in the plastic, energy and fertilizers sectors. Their large-scale production implies the outdoor operation of PPB systems which brings new challenges, identified in this review. An overview of the current PPB polymer producing technologies and prospects for their future development is also provided.

Polyhydroxyalkanoates from organic waste streams using purple non-sulfur bacteria

Many microorganisms can produce intracellular and extracellular biopolymers, such as polyhydroxyalkanoates (PHA). Despite PHA's benefits, their widespread at the industrial level has not occurred due mainly to high production costs. PHA production under a biorefinery scheme is proposed to improve its economic viability. In this context, purple non-sulfur bacteria (PNSB) are ideal candidates to produce PHA and other substances of economic interest. This review describes the PHA production by PNSB under different metabolic pathways, by using a wide range of wastes and under diverse operational conditions such as aerobic and anaerobic metabolism, irradiance level, light or dark conditions. Some strategies, such as controlling the feed regime, biofilm reactors, and open photobioreactors in outdoor conditions, were identified from the literature review as the approach needed to improve the process's economic viability when using mixed cultures of PNSB and wastes as substrates.

Engineering Photosynthetic Bioprocesses for Sustainable Chemical Production: A Review

Microbial production of chemicals using renewable feedstocks such as glucose has emerged as a green alternative to conventional chemical production processes that rely primarily on petroleum-based feedstocks. The carbon footprint of such processes can further be reduced by using engineered cells that harness solar energy to consume feedstocks traditionally considered to be wastes as their carbon sources. Photosynthetic bacteria utilize sophisticated photosystems to capture the energy from photons to generate reduction potential with such rapidity and abundance that cells often cannot use it fast enough and much of it is lost as heat and light. Engineering photosynthetic organisms could enable us to take advantage of this energy surplus by redirecting it toward the synthesis of commercially important products such as biofuels, bioplastics, commodity chemicals, and terpenoids. In this work, we review photosynthetic pathways in aerobic and anaerobic bacteria to better understand how these organisms have naturally evolved to harness solar energy. We also discuss more recent attempts at engineering both the photosystems and downstream reactions that transfer reducing power to improve target chemical production. Further, we discuss different methods for the optimization of photosynthetic bioprocess including the immobilization of cells and the optimization of light delivery. We anticipate this review will serve as an important resource for future efforts to engineer and harness photosynthetic bacteria for chemical production.

On the non-innocence and reactive versus non-reactive nature of α-diketones in a set of diruthenium frameworks

Slightly modified ligand designs in diruthenium setups have major impacts on the reactivity/stability of coordination complexes. The 1,2-bis(2-hydroxyphenyl)ethane-1,2-dione bridge is also potentially redox non-innocent.

Investigation of microbial community interactions between Lake Washington methanotrophs using -------genome-scale metabolic modeling

Background

The role of methane in global warming has become paramount to the environment and the human society, especially in the past few decades. Methane cycling microbial communities play an important role in the global methane cycle, which is why the characterization of these communities is critical to understand and manipulate their behavior. Methanotrophs are a major player in these communities and are able to oxidize methane as their primary carbon source.

Results

Lake Washington is a freshwater lake characterized by a methane-oxygen countergradient that contains a methane cycling microbial community. Methanotrophs are a major part of this community involved in assimilating methane from lake water. Two significant methanotrophic species in this community are Methylobacter and Methylomonas. In this work, these methanotrophs are computationally studied via developing highly curated genome-scale metabolic models. Each model was then integrated to form a community model with a multi-level optimization framework. The competitive and mutualistic metabolic interactions among Methylobacter and Methylomonas were also characterized. The community model was next tested under carbon, oxygen, and nitrogen limited conditions in addition to a nutrient-rich condition to observe the systematic shifts in the internal metabolic pathways and extracellular metabolite exchanges. Each condition showed variations in the methane oxidation pathway, pyruvate metabolism, and the TCA cycle as well as the excretion of formaldehyde and carbon di-oxide in the community. Finally, the community model was simulated under fixed ratios of these two members to reflect the opposing behavior in the two-member synthetic community and in sediment-incubated communities. The community simulations predicted a noticeable switch in intracellular carbon metabolism and formaldehyde transfer between community members in sediment-incubated vs. synthetic condition.

Conclusion

In this work, we attempted to predict the response of a simplified methane cycling microbial community from Lake Washington to varying environments and also provide an insight into the difference of dynamics in sediment-incubated microcosm community and synthetic co-cultures. Overall, this study lays the ground for in silico systems-level studies of freshwater lake ecosystems, which can drive future efforts of understanding, engineering, and modifying these communities for dealing with global warming issues.

Carbon substrate re-orders relative growth of a bacterium using Mo-, V-, or Fe-nitrogenase for nitrogen fixation

Biological nitrogen fixation is catalyzed by the molybdenum (Mo), vanadium (V) and iron (Fe)‐only nitrogenase metalloenzymes. Studies with purified enzymes have found that the ‘alternative’ V‐ and Fe‐nitrogenases generally reduce N₂ more slowly and produce more byproduct H₂ than the Mo‐nitrogenase, leading to an assumption that their usage results in slower growth. Here we show that, in the metabolically versatile photoheterotroph Rhodopseudomonas palustris, the type of carbon substrate influences the relative rates of diazotrophic growth based on different nitrogenase isoforms. The V‐nitrogenase supports growth as fast as the Mo‐nitrogenase on acetate but not on the more oxidized substrate succinate. Our data suggest that this is due to insufficient electron flux to the V‐nitrogenase isoform on succinate compared with acetate. Despite slightly faster growth based on the V‐nitrogenase on acetate, the wild‐type strain uses exclusively the Mo‐nitrogenase on both carbon substrates. Notably, the differences in H₂:N₂ stoichiometry by alternative nitrogenases (~1.5 for V‐nitrogenase, ~4–7 for Fe‐nitrogenase) and Mo‐nitrogenase (~1) measured here are lower than prior in vitro estimates. These results indicate that the metabolic costs of V‐based nitrogen fixation could be less significant for growth than previously assumed, helping explain why alternative nitrogenase genes persist in diverse diazotroph lineages and are broadly distributed in the environment.

An integrated computational and experimental study to investigate Staphylococcus aureus metabolism

Staphylococcus aureus is a metabolically versatile pathogen that colonizes nearly all organs of the human body. A detailed and comprehensive knowledge of staphylococcal metabolism is essential to understand its pathogenesis. To this end, we have reconstructed and experimentally validated an updated and enhanced genome-scale metabolic model of S. aureus USA300_FPR3757. The model combined genome annotation data, reaction stoichiometry, and regulation information from biochemical databases and previous strain-specific models. Reactions in the model were checked and fixed to ensure chemical balance and thermodynamic consistency. To further refine the model, growth assessment of 1920 nonessential mutants from the Nebraska Transposon Mutant Library was performed, and metabolite excretion profiles of important mutants in carbon and nitrogen metabolism were determined. The growth and no-growth inconsistencies between the model predictions and in vivo essentiality data were resolved using extensive manual curation based on optimization-based reconciliation algorithms. Upon intensive curation and refinements, the model contains 863 metabolic genes, 1379 metabolites (including 1159 unique metabolites), and 1545 reactions including transport and exchange reactions. To improve the accuracy and predictability of the model to environmental changes, condition-specific regulation information curated from the existing knowledgebase was incorporated. These critical additions improved the model performance significantly in capturing gene essentiality, substrate utilization, and metabolite production capabilities and increased the ability to generate model-based discoveries of therapeutic significance. Use of this highly curated model will enhance the functional utility of omics data, and therefore, serve as a resource to support future investigations of S. aureus and to augment staphylococcal research worldwide.

Integration of in vivo experiment with a newly developed model of Staphylococcus aureus metabolism helps explore its metabolic versatility. A multidisciplinary team led by Rajib Saha at the University of Nebraska developed a new genome-scale metabolic model of the multi-drug resistant pathogen S. aureus by combining genome annotation data, reaction stoichiometry, and condition- and mutant-specific regulations from biochemical databases and previous strain-specific models. Extensive manual curation and incorporation of newly generated experimental data on growth and metabolite production improved the accuracy and predictability of the model and increased its ability to generate model-based discoveries of therapeutic significance. Use of this highly curated model will enhance the functional utility of omics data and, therefore, serve as a resource to support future investigations of S. aureus and to augment staphylococcal research worldwide.

OptFill: A Tool for Infeasible Cycle-Free Gapfilling of Stoichiometric Metabolic Models

Stoichiometric metabolic modeling, particularly genome-scale models (GSMs), is now an indispensable tool for systems biology. The model reconstruction process typically involves collecting information from public databases; however, incomplete systems knowledge leaves gaps in any reconstruction. Current tools for addressing gaps use databases of biochemical functionalities to address gaps on a per-metabolite basis and can provide multiple solutions but cannot avoid thermodynamically infeasible cycles (TICs), invariably requiring lengthy manual curation. To address these limitations, this work introduces an optimization-based multi-step method named OptFill, which performs TIC-avoiding whole-model gapfilling. We applied OptFill to three fictional prokaryotic models of increasing sizes and to a published GSM of Escherichia coli, iJR904. This application resulted in holistic and infeasible cycle-free gapfilling solutions. In addition, OptFill can be adapted to automate inherent TICs identification in any GSM. Overall, OptFill can address critical issues in automated development of high-quality GSMs.

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This work presents an alternative to state-of-the-art methods for gapfilling

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Unlike current methods, this method is holistic and infeasible cycle free

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This method is applied to three tests and one published model

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This method might also be used to address infeasible cycling