Industrial Systems Biology of Saccharomyces cerevisiae Enables Novel Succinic Acid Cell Factory.

Saccharomyces cerevisiae is the most well characterized eukaryote, the preferred microbial cell factory for the largest industrial biotechnology product (bioethanol), and a robust commerically compatible scaffold to be exploitted for diverse chemical production. Succinic acid is a highly sought after added-value chemical for which there is no native pre-disposition for production and accmulation in S. cerevisiae. The genome-scale metabolic network reconstruction of S. cerevisiae enabled in silico gene deletion predictions using an evolutionary programming method to couple biomass and succinate production. Glycine and serine, both essential amino acids required for biomass formation, are formed from both glycolytic and TCA cycle intermediates. Succinate formation results from the isocitrate lyase catalyzed conversion of isocitrate, and from the alpha-keto-glutarate dehydrogenase catalyzed conversion of alpha-keto-glutarate. Succinate is subsequently depleted by the succinate dehydrogenase complex. The metabolic engineering strategy identified included deletion of the primary succinate consuming reaction, Sdh3p, and interruption of glycolysis derived serine by deletion of 3-phosphoglycerate dehydrogenase, Ser3p/Ser33p. Pursuing these targets, a multi-gene deletion strain was constructed, and directed evolution with selection used to identify a succinate producing mutant. Physiological characterization coupled with integrated data analysis of transcriptome data in the metabolically engineered strain were used to identify 2nd-round metabolic engineering targets. The resulting strain represents a 30-fold improvement in succinate titer, and a 43-fold improvement in succinate yield on biomass, with only a 2.8-fold decrease in the specific growth rate compared to the reference strain. Intuitive genetic targets for either over-expression or interruption of succinate producing or consuming pathways, respectively, do not lead to increased succinate. Rather, we demonstrate how systems biology tools coupled with directed evolution and selection allows non-intuitive, rapid and substantial re-direction of carbon fluxes in S. cerevisiae, and hence show proof of concept that this is a potentially attractive cell factory for over-producing different platform chemicals

The genome sequence of E. coli W (ATCC 9637): comparative genome analysis and an improved genome-scale reconstruction of E. coli

Background: Escherichia coli is a model prokaryote, an important pathogen, and a key organism for industrial biotechnology. E. coli W (ATCC 9637), one of four strains designated as safe for laboratory purposes, has not been sequenced. E. coli W is a fast-growing strain and is the only safe strain that can utilize sucrose as a carbon source. Lifecycle analysis has demonstrated that sucrose from sugarcane is a preferred carbon source for industrial bioprocesses

Reengineering Escherichia coli for Succinate Production in Mineral Salts Medium▿

The fermentative metabolism of glucose was redirected to succinate as the primary product without mutating any genes encoding the native mixed-acid fermentation pathway or redox reactions. Two changes in peripheral pathways were together found to increase succinate yield fivefold: (i) increased expression of phosphoenolpyruvate carboxykinase and (ii) inactivation of the glucose phosphoenolpyruvate-dependent phosphotransferase system. These two changes increased net ATP production, increased the pool of phosphoenolpyruvate available for carboxylation, and increased succinate production. Modest further improvements in succinate yield were made by inactivating the pflB gene, encoding pyruvate formate lyase, resulting in an Escherichia coli pathway that is functionally similar to the native pathway in Actinobacillus succinogenes and other succinate-producing rumen bacteria

Metabolic evolution of energy-conserving pathways for succinate production in Escherichia coli

During metabolic evolution to improve succinate production in Escherichia coli strains, significant changes in cellular metabolism were acquired that increased energy efficiency in two respects. The energy-conserving phosphoenolpyruvate (PEP) carboxykinase (pck), which normally functions in the reverse direction (gluconeogenesis; glucose repressed) during the oxidative metabolism of organic acids, evolved to become the major carboxylation pathway for succinate production. Both PCK enzyme activity and gene expression levels increased significantly in two stages because of several mutations during the metabolic evolution process. High-level expression of this enzyme-dominated CO2 fixation and increased ATP yield (1 ATP per oxaloacetate). In addition, the native PEP-dependent phosphotransferase system for glucose uptake was inactivated by a mutation in ptsI. This glucose transport function was replaced by increased expression of the GalP permease (galP) and glucokinase (glk). Results of deleting individual transport genes confirmed that GalP served as the dominant glucose transporter in evolved strains. Using this alternative transport system would increase the pool of PEP available for redox balance. This change would also increase energy efficiency by eliminating the need to produce additional PEP from pyruvate, a reaction that requires two ATP equivalents. Together, these changes converted the wild-type E. coli fermentation pathway for succinate into a functional equivalent of the native pathway that nature evolved in succinate-producing rumen bacteria

A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli

In the past decades, metabolic engineering has received great attention from different sectors of science due to its important role in enhancing the over expression of the target phenotype by manipulating the metabolic pathway. The advent of metabolic engineering has further laid the foundation for computational biology, leading to the development of computational approaches for suggesting genetic manipulation. Previously, conventional methods have been used to enhance the production of lactate and succinate in E. coli. However, these products are always far below their theoretical maxima. In this research, a hybrid algorithm is developed to seek optimal solutions in order to increase the overproduction of lactate and succinate by gene knockout in E. coli. The hybrid algorithm employed the Simple Constrained Artificial Bee Colony (SCABC) algorithm, using swarm intelligence as an optimization algorithm to optimize the objective function, where lactate and succinate productions are maximized by simulating gene knockout in E. coli. In addition, Flux Balance Analysis (FBA) is used as a fitness function in the SCABC algorithm to assess the growth rate of E. coli and the productivity of lactate and succinate. As a result of the research, the gene knockout list which induced the highest production of lactate and succinate is obtained