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Methanogenic archaea are important organisms in the global carbon cycle that grow by producing methane gas. Methanosarcina acetivorans is a methanogenic archaeum that can grow using methylated compounds, carbon monoxide, or acetate and produces renewable methane as a byproduct. However, there is limited knowledge of how combinations of substrates may affect metabolic fluxes in methanogens. Previous studies have shown that heterodisulfide reductase, the terminal oxidase in the electron transport system, is an essential enzyme in all methanogens. Deletion of genes encoding the nonessential methylotrophic heterodisulfide reductase enzyme (HdrABC) results in slower growth rate but increased metabolic efficiency. We hypothesized that increased sulfide, supplementation of mercaptoethanesulfonate (coenzyme M, CoM-SH), or acetate would metabolically alleviate the effect of the ΔhdrABC mutation. Increased sulfide improved growth of the mutant as expected; however, supplementation of both CoM-SH and acetate together were necessary to reduce the effect of the ΔhdrABC mutation. Supplementation of CoM-SH or acetate alone did not improve growth. These results support our model for the role of HdrABC in methanogenesis and suggest M.acetivorans is more efficient at conserving energy when supplemented with acetate. Our study suggests decreased Hdr enzyme activity can be overcome by nutritional supplementation with sulfide or coenzyme M and acetate, which are abundant in anaerobic environments. 

ABSTRACT 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). 

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. 

Abstract The growth and development of maize (Zea mays L.) largely depends on its nutrient uptake through the root. Hence, studying its growth, response, and associated metabolic reprogramming to stress conditions is becoming an important research direction. A genome-scale metabolic model (GSM) for the maize root was developed to study its metabolic reprogramming under nitrogen stress conditions. The model was reconstructed based on the available information from KEGG, UniProt, and MaizeCyc. Transcriptomics data derived from the roots of hydroponically grown maize plants were used to incorporate regulatory constraints in the model and simulate nitrogen-non-limiting (N+) and nitrogen-deficient (N−) condition. Model-predicted flux-sum variability analysis achieved 70% accuracy compared with the experimental change of metabolite levels. In addition to predicting important metabolic reprogramming in central carbon, fatty acid, amino acid, and other secondary metabolism, maize root GSM predicted several metabolites (l-methionine, l-asparagine, l-lysine, cholesterol, and l-pipecolate) playing a regulatory role in the root biomass growth. Furthermore, this study revealed eight phosphatidylcholine and phosphatidylglycerol metabolites which, even though not coupled with biomass production, played a key role in the increased biomass production under N-deficient conditions. Overall, the omics-integrated GSM provides a promising tool to facilitate stress condition analysis for maize root and engineer better stress-tolerant maize genotypes. 

Sphingolipids are a vital component of plant cellular endomembranes and carry out multiple functional and regulatory roles. Different sphingolipid species confer rigidity to the membrane structure, facilitate trafficking of secretory proteins, and initiate programmed cell death. Although the regulation of the sphingolipid pathway is yet to be uncovered, increasing evidence has pointed to orosomucoid proteins (ORMs) playing a major regulatory role and potentially interacting with a number of components in the pathway, including both enzymes and sphingolipids. However, experimental exploration of new regulatory interactions is time consuming and often infeasible. In this work, a computational approach was taken to address this challenge. A metabolic network of the sphingolipid pathway in plants was reconstructed. The steady-state rates of reactions in the network were then determined through measurements of growth and cellular composition of the different sphingolipids in Arabidopsis seedlings. The Ensemble modeling framework was modified to accurately account for activation mechanisms and subsequently used to generate sets of kinetic parameters that converge to the measured steady-state fluxes in a thermodynamically consistent manner. In addition, the framework was appended with an additional module to automate screening the parameters and to output models consistent with previously reported network responses to different perturbations. By analyzing the network’s response in the presence of different combinations of regulatory mechanisms, the model captured the experimentally observed repressive effect of ORMs on serine palmitoyltransferase (SPT). Furthermore, predictions point to a second regulatory role of ORM proteins, namely as an activator of class II (or LOH1 and LOH3) ceramide synthases. This activating role was found to be modulated by the concentration of free ceramides, where an accumulation of these sphingolipid species dampened the activating effect of ORMs on ceramide synthase. The predictions pave the way for future guided experiments and have implications in engineering crops with higher biotic stress tolerance.