Naturally, many aerobic organisms degrade lignin-derived aromatics through conserved intermediates including protocatechuate and catechol. Employing this microbial approach offers a potential solution for valorizing lignin into valuable chemicals for a potential lignocellulosic biorefinery and enabling bioeconomy. In this study, two hybrid biochemical routes combining lignin chemical depolymerization, plant metabolic engineering, and synthetic pathway reconstruction were demonstrated for valorizing lignin into value-added products. In the biochemical route 1, alkali lignin was chemically depolymerized into vanillin and syringate as major products, which were further bio-converted into cis, cis-muconic acid (ccMA) and pyrogallol, respectively, using engineered Escherichia coli strains. In the second biochemical route, the shikimate pathway of Tobacco plant was engineered to accumulate protocatechuate (PCA) as a soluble intermediate compound. The PCA extracted from the engineered Tobacco was further converted into ccMA using the engineered E. coli strain. This study reports a direct process for converting lignin into ccMA and pyrogallol as value-added chemicals, and more importantly demonstrates benign methods for valorization of polymeric lignin that is inherently heterogeneous and recalcitrant. Our approach also validates the promising combination of plant engineering with microbial chassis development for the production of value added and speciality chemicals.

Sphingobium sp. SYK-6 is a soil bacterium boasting a well-studied ligninolytic pathway and the potential for development into a microbial chassis for lignin valorization. An improved understanding of its metabolism will help researchers in the engineering of SYK-6 for the production of value-added chemicals through lignin valorization. We used 13 C-fingerprinting, 13C metabolic flux analysis ( 13 C-MFA), and RNA-sequencing differential expression analysis to uncover the following metabolic traits: (i) SYK-6 prefers alkaline conditions, making it an efficient host for the consolidated bioprocessing of lignin, and it also lacks the ability to metabolize sugars or organic acids; (ii) the CO 2 release (i.e., carbon loss) from the ligninolysis-based metabolism of SYK-6 is significantly greater than the CO 2 release from the sugar-based metabolism of Escherichia coli; (iii) the vanillin catabolic pathway (which is the converging point of majority of the lignin catabolic pathways) is coupled with the tetrahydrofolate-dependent C1 pathway that is essential for the biosynthesis of serine, histidine, and methionine; (iv) catabolic end products of lignin (pyruvate and oxaloacetate) must enter the tricarboxylic acid (TCA) cycle first and then use phosphoenolpyruvate carboxykinase to initiate gluconeogenesis; and (v) 13 C-MFA together with RNA-sequencing differential expression analysis establishes the vanillin catabolic pathway as the major contributor of NAD(P)H synthesis. Therefore, the vanillin catabolic pathway is essential for SYK-6 to obtain sufficient reducing equivalents for its healthy growth; cosubstrate experiments support this finding. This unique energy feature of SYK-6 is particularly interesting because most heterotrophs rely on the transhydrogenase, the TCA cycle, and the oxidative pentose phosphate pathway to obtain NADPH.

Global warming and decreasing fossil fuel reserves have prompted great interest in the synthesis of advanced biofuels from renewable resources. In an effort to address these concerns, we performed metabolic engineering of the cyanobacterium Synechocystis sp. strain PCC 6803 to develop a strain that can synthesize isobutanol under both autotrophic and mixotrophic conditions. With the expression of two heterologous genes from the Ehrlich pathway, the engineered strain can accumulate 90 mg/ liter of isobutanol from 50 mM bicarbonate in a gas-tight shaking flask. The strain does not require any inducer (i.e., isopropyl ␤-D-1-thiogalactopyranoside [IPTG]) or antibiotics to maintain its isobutanol production. In the presence of glucose, isobutanol synthesis is only moderately promoted (titer ‫؍‬ 114 mg/liter). Based on isotopomer analysis, we found that, compared to the wild-type strain, the mutant significantly reduced its glucose utilization and mainly employed autotrophic metabolism for biomass growth and isobutanol production. Since isobutanol is toxic to the cells and may also be degraded photochemically by hydroxyl radicals during the cultivation process, we employed in situ removal of the isobutanol using oleyl alcohol as a solvent trap. This resulted in a final net concentration of 298 mg/liter of isobutanol under mixotrophic culture conditions. G lobal energy needs continue to increase rapidly due to industrial and development demands, raising environmental concerns. Much of the worldwide energy consumption comes from the burning of fossil fuels, which produces about 6 gigatons of CO 2 annually (1). Increasing CO 2 levels may act as a feedback loop to increase the soil emissions of other greenhouse gases, such as methane and nitrous oxide, raising the global temperature (2). For energy security and due to environmental concerns, there is an urgent demand for the development of bioenergy. Bioethanol is the most common biofuel, but it also has low energy density and absorbs moisture. Isobutanol (IB) is a better fuel, because it is less water soluble and has an energy density/octane value close to that of gasoline (3, 4). Among the next-generation biofuels synthesized from pyruvate, IB possesses fewer reaction steps (5 reaction steps from pyruvate to IB) than the synthesis of 1-butanol or biodiesel. IB is less toxic to microbes (5), so it may achieve a higher product titer and yield (6, 7). For example, a maximum titer of 50.8 g/liter of IB can be achieved in an engineered Escherichia coli strain (8).On the other hand, cyanobacteria not only can convert CO 2 into bioproducts, but also can play an important role in environmental bioremediation. The photosynthetic efficiency of cyanobacteria (3 to 9%) is high compared to that of higher plants (Յ0.25 to 3%) (9, 10). Furthermore, some species of cyanobacteria are amenable to genetic engineering. Table 1 lists the various biofuels that have been synthesized through the metabolic engineering of cyanobacteria. Autotrophic IB production in cyanobacteria was first demons...

BackgroundThe world faces the challenge to develop sustainable technologies to replace thousands of products that have been generated from fossil fuels. Microbial cell factories serve as promising alternatives for the production of diverse commodity chemicals and biofuels from renewable resources. For example, polylactic acid (PLA) with its biodegradable properties is a sustainable, environmentally friendly alternative to polyethylene. At present, PLA microbial production is mainly dependent on food crops such as corn and sugarcane. Moreover, optically pure isomers of lactic acid are required for the production of PLA, where D-lactic acid controls the thermochemical and physical properties of PLA. Henceforth, production of D-lactic acid through a more sustainable source (CO2) is desirable.ResultsWe have performed metabolic engineering on Synechocystis sp. PCC 6803 for the phototrophic synthesis of optically pure D-lactic acid from CO2. Synthesis of optically pure D-lactic acid was achieved by utilizing a recently discovered enzyme (i.e., a mutated glycerol dehydrogenase, GlyDH*). Significant improvements in D-lactic acid synthesis were achieved through codon optimization and by balancing the cofactor (NADH) availability through the heterologous expression of a soluble transhydrogenase. We have also discovered that addition of acetate to the cultures improved lactic acid production. More interestingly, 13C-pathway analysis revealed that acetate was not used for the synthesis of lactic acid, but was mainly used for synthesis of certain biomass building blocks (such as leucine and glutamate). Finally, the optimal strain was able to accumulate 1.14 g/L (photoautotrophic condition) and 2.17 g/L (phototrophic condition with acetate) of D-lactate in 24 days.ConclusionsWe have demonstrated the photoautotrophic production of D-lactic acid by engineering a cyanobacterium Synechocystis 6803. The engineered strain shows an excellent D-lactic acid productivity from CO2. In the late growth phase, the lactate production rate by the engineered strain reached a maximum of ~0.19 g D-lactate/L/day (in the presence of acetate). This study serves as a good complement to the recent metabolic engineering work done on Synechocystis 6803 for L-lactate production. Thereby, our study may facilitate future developments in the use of cyanobacterial cell factories for the commercial production of high quality PLA.

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In the production of chemicals via microbial fermentation, achieving a high yield is one of the most important objectives. We developed a statistical model to analyze influential factors that determine product yield by compiling data obtained from engineered Escherichia coli developed within last 10 years. Using both numerical and ordinal variables (e.g., enzymatic steps, cultivation conditions, and genetic modifications) as input parameters, our model revealed that cultivation modes, nutrient supplementation, and oxygen conditions were the three significant factors for improving product yield. Generally, the model showed that product yield decreases as the number of enzymatic steps in the biosynthesis pathway increases (7-9% loss of yield per enzymatic step). Moreover, overexpression of enzymes or removal of competitive pathways (e.g., knockout) does not necessarily result in an amplification of product yield (P-value>0.1), possibly because of limited capacity in the biosynthesis pathway to accommodate an increase in flux. The model not only provides general guidelines for metabolic engineering and fermentation processes, but also allows a priori estimation and comparison of product yields under designed cultivation conditions.

BackgroundThe robustness of Saccharomyces cerevisiae in facilitating industrial-scale production of ethanol extends its utilization as a platform to synthesize other metabolites. Metabolic engineering strategies, typically via pathway overexpression and deletion, continue to play a key role for optimizing the conversion efficiency of substrates into the desired products. However, chemical production titer or yield remains difficult to predict based on reaction stoichiometry and mass balance. We sampled a large space of data of chemical production from S. cerevisiae, and developed a statistics-based model to calculate production yield using input variables that represent the number of enzymatic steps in the key biosynthetic pathway of interest, metabolic modifications, cultivation modes, nutrition and oxygen availability.ResultsBased on the production data of about 40 chemicals produced from S. cerevisiae, metabolic engineering methods, nutrient supplementation, and fermentation conditions described therein, we generated mathematical models with numerical and categorical variables to predict production yield. Statistically, the models showed that: 1. Chemical production from central metabolic precursors decreased exponentially with increasing number of enzymatic steps for biosynthesis (>30% loss of yield per enzymatic step, P-value = 0); 2. Categorical variables of gene overexpression and knockout improved product yield by 2~4 folds (P-value < 0.1); 3. Addition of notable amount of intermediate precursors or nutrients improved product yield by over five folds (P-value < 0.05); 4. Performing the cultivation in a well-controlled bioreactor enhanced the yield of product by three folds (P-value < 0.05); 5. Contribution of oxygen to product yield was not statistically significant. Yield calculations for various chemicals using the linear model were in fairly good agreement with the experimental values. The model generally underestimated the ethanol production as compared to other chemicals, which supported the notion that the metabolism of Saccharomyces cerevisiae has historically evolved for robust alcohol fermentation.ConclusionsWe generated simple mathematical models for first-order approximation of chemical production yield from S. cerevisiae. These linear models provide empirical insights to the effects of strain engineering and cultivation conditions toward biosynthetic efficiency. These models may not only provide guidelines for metabolic engineers to synthesize desired products, but also be useful to compare the biosynthesis performance among different research papers.