Pornkamol Unrean

Minimal Escherichia coli Cell for the Most Efficient Production of Ethanol from Hexoses and Pentoses

ABSTRACT To obtain an efficient ethanologenic Escherichia coli strain, we reduced the functional space of the central metabolic network, with eight gene knockout mutations, from over 15,000 pathway possibilities to 6 pathway options that support cell function. The remaining pathways, identified by elementary mode analysis, consist of four pathways with non-growth-associated conversion of pentoses and hexoses into ethanol at theoretical yields and two pathways with tight coupling of anaerobic cell growth with ethanol formation at high yields. Elimination of three additional genes resulted in a strain that selectively grows only on pentoses, even in the presence of glucose, with a high ethanol yield. We showed that the ethanol yields of strains with minimized metabolic functionality closely matched the theoretical predictions. Remarkably, catabolite repression was completely absent during anaerobic growth, resulting in the simultaneous utilization of pentoses and hexoses for ethanol production.

Rational design and construction of an efficient E. coli for production of diapolycopendioic acid

We applied elementary mode analysis to a recombinant metabolic network of carotenoid-producing E. coli in order to identify multiple-gene knockouts for an enhanced synthesis of the carotenoids diapolycopendial (DPL) and diapolycopendioic acid (DPA). Based on the model, all inefficient carotenoid biosynthesis pathways were eliminated in a strain containing a combination of eight gene deletions. To validate the model prediction, the designed strain was constructed and tested for its performance. The designed mutant produces the carotenoids at significantly increased yields and rates as compared to the wild-type. The consistency between model prediction and experimental results demonstrates that elementary mode analysis is useful as a guiding tool also for the rational strain design of more complex pathways for secondary metabolite production.

Metabolic networks evolve towards states of maximum entropy production

A metabolic network can be described by a set of elementary modes or pathways representing discrete metabolic states that support cell function. We have recently shown that in the most likely metabolic state the usage probability of individual elementary modes is distributed according to the Boltzmann distribution law while complying with the principle of maximum entropy production. To demonstrate that a metabolic network evolves towards such state we have carried out adaptive evolution experiments with Thermoanaerobacterium saccharolyticum operating with a reduced metabolic functionality based on a reduced set of elementary modes. In such reduced metabolic network metabolic fluxes can be conveniently computed from the measured metabolite secretion pattern. Over a time span of 300 generations the specific growth rate of the strain continuously increased together with a continuous increase in the rate of entropy production. We show that the rate of entropy production asymptotically approaches the maximum entropy production rate predicted from the state when the usage probability of individual elementary modes is distributed according to the Boltzmann distribution. Therefore, the outcome of evolution of a complex biological system can be predicted in highly quantitative terms using basic statistical mechanical principles.

A Statistical Thermodynamical Interpretation of Metabolism

The metabolic network of a cell can be decomposed into discrete elementary modes that contribute, each with a certain probability, to the overall flux through the metabolism. These modes are cell function supporting, fundamental pathways that represent permissible ‘quantum’ states of the metabolism. For the case that cellular regulatory mechanisms for pathway fluxes evolved in an unbiased way, we demonstrate theoretically that the usage probabilities of individual elementary modes are distributed according to Boltzmann’s distribution law such that the rate of entropy production is maximized. Such distribution can be observed experimentally in highly evolved metabolic networks. Therefore, cell function has a natural tendency to operate at a maximum rate of entropy generation using preferentially efficient pathways with small reaction entropies. Ultimately, evolution of metabolic networks appears to be driven by forces that can be quantified by the distance of the current metabolic state from the state of maximum entropy generation that represents the unbiased, most probable selection of fundamental pathway choices.

Continuous production of ethanol from hexoses and pentoses using immobilized mixed cultures of Escherichia coli strains

We have developed highly efficient ethanologenic Escherichia coli strains that selectively consume pentoses and/or hexoses. Mixed cultures of these strains can be used to selectively adjust the sugar utilization kinetics in ethanol fermentations. Based on the kinetics of sugar utilization, we have designed and implemented an immobilized cell system for the optimized continuous conversion of sugars into ethanol. The results confirm that immobilized mixed cultures support a simultaneous conversion of hexoses and pentoses into ethanol at high yield and at a faster rate than immobilized homogenous cells. Continuous ethanol production has been maintained for several weeks at high productivity with near complete sugar utilization. The control of sugar utilization using immobilized mixed cultures can be adapted to any composition of hexoses and pentoses by adjusting the strain distribution of immobilized cells. The approach, therefore, holds promise for ethanol fermentation from lignocellulosic hydrolysates where the feedstock varies in sugar composition.

Predicting the adaptive evolution of Thermoanaerobacterium saccharolyticum

A fully evolved metabolic network can be described as a weighted sum of elementary modes where the usage probabilities of modes are distributed according to the Boltzmann distribution law (Srienc and Unrean, 2010). An organism presumably achieves the fully evolved state through adaptive changes in the kinetics of rate-controlling enzymes. Metabolic control analysis identifies reactions catalyzed by such enzymes. Comparison of the experimentally determined metabolic flux distributions of Thermoanaerobacterium saccharolyticum AS411 with the predicted flux distribution of a fully evolved metabolic network identified phosphoglucose isomerase (PGI) as the enzyme with the greatest flux control, the rate-controlling enzyme. The analysis predicts that an increased activity of PGI would enable the metabolic network to approach the fully evolved state and result in a faster specific growth rate. The prediction was confirmed by experimental results that showed an increased specific activity of PGI in a culture of strain AS411 that adaptively evolved over 280 generations. Sequencing of the gene confirmed the occurrence of a group of mutations clustered in the subunit binding domain of the dimeric enzyme. The results indicate that the evolutionary path is predictable as the strain AS411 adapted toward the fully evolved state by increasing the PGI activity. This experimental finding confirms that enzymes with predicted highest metabolic flux control are the targets of adaptive metabolic pathway evolution.

Production of d-xylonic acid using a non-recombinant Corynebacterium glutamicum strain

It was found that Corynebacterium glutamicum ΔiolR devoid of the transcriptional regulator IolR accumulates high amounts of d-xylonate when cultivated in the presence of d-xylose. Detailed analyses of constructed deletion mutants revealed that the putative myo-inositol 2-dehydrogenase IolG also acts as d-xylose dehydrogenase and is mainly responsible for d-xylonate oxidation in this organism. Process development for d-xylonate production was initiated by cultivating C. glutamicum ΔiolR on defined d-xylose/d-glucose mixtures under batch and fed-batch conditions. The resulting yield matched the theoretical maximum of 1 mol mol-1 and high volumetric productivities of up to 4 g L-1 h-1 could be achieved. Subsequently, a novel one-pot sequential hydrolysis and fermentation process based on optimized medium containing hydrolyzed sugarcane bagasse was developed. Cost-efficiency and abundance of second-generation substrates, good performance indicators, and enhanced market access using a non-recombinant strain open the perspective for a commercially viable bioprocess for d-xylonate production in the near future.

Elucidating cellular mechanisms of Saccharomyces cerevisiae tolerant to combined lignocellulosic-derived inhibitors using high-throughput phenotyping and multiomics analyses

A robust cell factory that can tolerate combined inhibitory lignocellulosic compounds is essential for the cost-effective lignocellulose-based production of second-generation bioethanol and other bulk chemicals. Following high-throughput phenotyping of a yeast genomic overexpression library, we identified a Saccharomyces cerevisiae mutant (denoted AFb.01) with improved growth and fermentation performance under combined toxicity of acetic acid and furfural. AFb.01 carries overexpression of TRX1, which encodes for thioredoxin, a cellular redox machinery. Through comparative proteomics and metabolomics, the resulting cell-wide changes in the mutant were elucidated and these primarily target on the maintenance of energy and redox homeostasis and the minimization of stress-induced cell damages. In particular, the upregulation of the stress-response proteins Hsp26p and Fmp16p conferred tolerance of AFb.01 against protein denaturation and DNA damage. Moreover, increased levels of protectant metabolites such as trehalose, fatty acids, GABA and putrescine provided additional defense mechanisms for the mutant against oxidative and redox stresses. Future studies will concentrate on targeted genetic engineering to validate these mechanisms as well as to support the creation of more robust yeast strains, applicable for industrial, cost-competitive biorefinery production.