Jochen Förster

Evolutionary programming as a platform for in silico metabolic engineering.

BackgroundThrough genetic engineering it is possible to introduce targeted genetic changes and hereby engineer the metabolism of microbial cells with the objective to obtain desirable phenotypes. However, owing to the complexity of metabolic networks, both in terms of structure and regulation, it is often difficult to predict the effects of genetic modifications on the resulting phenotype. Recently genome-scale metabolic models have been compiled for several different microorganisms where structural and stoichiometric complexity is inherently accounted for. New algorithms are being developed by using genome-scale metabolic models that enable identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem, and it is therefore interesting to develop new faster algorithms.ResultsIn this study we report an evolutionary programming based method to rapidly identify gene deletion strategies for optimization of a desired phenotypic objective function. We illustrate the proposed method for two important design parameters in industrial fermentations, one linear and other non-linear, by using a genome-scale model of the yeast Saccharomyces cerevisiae. Potential metabolic engineering targets for improved production of succinic acid, glycerol and vanillin are identified and underlying flux changes for the predicted mutants are discussed.ConclusionWe show that evolutionary programming enables solving large gene knockout problems in relatively short computational time. The proposed algorithm also allows the optimization of non-linear objective functions or incorporation of non-linear constraints and additionally provides a family of close to optimal solutions. The identified metabolic engineering strategies suggest that non-intuitive genetic modifications span several different pathways and may be necessary for solving challenging metabolic engineering problems.

Saccharomyces cerevisiae phenotypes can be predicted by using constraint-based analysis of a genome-scale reconstructed metabolic network

Full genome sequences of prokaryotic organisms have led to reconstruction of genome-scale metabolic networks and in silico computation of their integrated functions. The first genome-scale metabolic reconstruction for a eukaryotic cell, Saccharomyces cerevisiae, consisting of 1,175 metabolic reactions and 733 metabolites, has appeared. A constraint-based in silico analysis procedure was used to compute properties of the S. cerevisiae metabolic network. The computed number of ATP molecules produced per pair of electrons donated to the electron transport system (ETS) and energy-maintenance requirements were quantitatively in agreement with experimental results. Computed whole-cell functions of growth and metabolic by-product secretion in aerobic and anaerobic culture were consistent with experimental data, and thus mRNA expression profiles during metabolic shifts were computed. The computed consequences of gene knockouts on growth phenotypes were consistent with experimental observations. Thus, constraint-based analysis of a genome-scale metabolic network for the eukaryotic S. cerevisiae allows for computation of its integrated functions, producing in silico results that were consistent with observed phenotypic functions for ≈70–80% of the conditions considered.

Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

Chinese hamster ovary (CHO) cells, first isolated in 1957, are the preferred production host for many therapeutic proteins. Although genetic heterogeneity among CHO cell lines has been well documented, a systematic, nucleotide-resolution characterization of their genotypic differences has been stymied by the lack of a unifying genomic resource for CHO cells. Here we report a 2.4-Gb draft genome sequence of a female Chinese hamster, Cricetulus griseus, harboring 24,044 genes. We also resequenced and analyzed the genomes of six CHO cell lines from the CHO-K1, DG44 and CHO-S lineages. This analysis identified hamster genes missing in different CHO cell lines, and detected >3.7 million single-nucleotide polymorphisms (SNPs), 551,240 indels and 7,063 copy number variations. Many mutations are located in genes with functions relevant to bioprocessing, such as apoptosis. The details of this genetic diversity highlight the value of the hamster genome as the reference upon which CHO cells can be studied and engineered for protein production.

Large-scale evaluation of in silico gene deletions in Saccharomyces cerevisiae.

A large-scale in silico evaluation of gene deletions in Saccharomyces cerevisiae was conducted using a genome-scale reconstructed metabolic model. The effect of 599 single gene deletions on cell viability was simulated in silico and compared to published experimental results. In 526 cases (87.8%), the in silico results were in agreement with experimental observations when growth on synthetic complete medium was simulated. Viable phenotypes were correctly predicted in 89.4% (496 out of 555) and lethal phenotypes were correctly predicted in 68.2% (30 out of 44) of the cases considered. The in silico evaluation was solely based on the topological properties of the metabolic network which is based on well-established reaction stoichiometry. No interaction or regulatory information was accounted for in the in silico model. False predictions were analyzed on a case-by-case basis for four possible inadequacies of the in silico model: (1) incomplete media composition, (2) substitutable biomass components, (3) incomplete biochemical information, and (4) missing regulation. This analysis eliminated a number of false predictions and suggested a number of experimentally testable hypotheses. A genome-scale in silico model can thus be used to systematically reconcile existing data and fill in our knowledge gaps about an organism.

EasyClone: method for iterative chromosomal integration of multiple genes in Saccharomyces cerevisiae

Development of strains for efficient production of chemicals and pharmaceuticals requires multiple rounds of genetic engineering. In this study, we describe construction and characterization of EasyClone vector set for bakers yeast Saccharomyces cerevisiae, which enables simultaneous expression of multiple genes with an option of recycling selection markers. The vectors combine the advantage of efficient uracil excision reaction-based cloning and Cre-LoxP-mediated marker recycling system. The episomal and integrative vector sets were tested by inserting genes encoding cyan, yellow, and red fluorescent proteins into separate vectors and analyzing for co-expression of proteins by flow cytometry. Cells expressing genes encoding for the three fluorescent proteins from three integrations exhibited a much higher level of simultaneous expression than cells producing fluorescent proteins encoded on episomal plasmids, where correspondingly 95% and 6% of the cells were within a fluorescence interval of Log10 mean ± 15% for all three colors. We demonstrate that selective markers can be simultaneously removed using Cre-mediated recombination and all the integrated heterologous genes remain in the chromosome and show unchanged expression levels. Hence, this system is suitable for metabolic engineering in yeast where multiple rounds of gene introduction and marker recycling can be carried out.

Establishing a synthetic pathway for high-level production of 3-hydroxypropionic acid in Saccharomyces cerevisiae via β-alanine.

Microbial fermentation of renewable feedstocks into plastic monomers can decrease our fossil dependence and reduce global CO2 emissions. 3-Hydroxypropionic acid (3HP) is a potential chemical building block for sustainable production of superabsorbent polymers and acrylic plastics. With the objective of developing Saccharomyces cerevisiae as an efficient cell factory for high-level production of 3HP, we identified the β-alanine biosynthetic route as the most economically attractive according to the metabolic modeling. We engineered and optimized a synthetic pathway for de novo biosynthesis of β-alanine and its subsequent conversion into 3HP using a novel β-alanine-pyruvate aminotransferase discovered in Bacillus cereus. The final strain produced 3HP at a titer of 13.7±0.3gL(-1) with a 0.14±0.0C-molC-mol(-1) yield on glucose in 80h in controlled fed-batch fermentation in mineral medium at pH 5, and this work therefore lays the basis for developing a process for biological 3HP production.

Highly Active and Specific Tyrosine Ammonia-Lyases from Diverse Origins Enable Enhanced Production of Aromatic Compounds in Bacteria and Saccharomyces cerevisiae

ABSTRACT Phenylalanine and tyrosine ammonia-lyases form cinnamic acid and p-coumaric acid, which are precursors of a wide range of aromatic compounds of biotechnological interest. Lack of highly active and specific tyrosine ammonia-lyases has previously been a limitation in metabolic engineering approaches. We therefore identified 22 sequences in silico using synteny information and aiming for sequence divergence. We performed a comparative in vivo study, expressing the genes intracellularly in bacteria and yeast. When produced heterologously, some enzymes resulted in significantly higher production of p-coumaric acid in several different industrially important production organisms. Three novel enzymes were found to have activity exclusively for phenylalanine, including an enzyme from the low-GC Gram-positive bacterium Brevibacillus laterosporus, a bacterial-type enzyme from the amoeba Dictyostelium discoideum, and a phenylalanine ammonia-lyase from the moss Physcomitrella patens (producing 230 μM cinnamic acid per unit of optical density at 600 nm [OD600]) in the medium using Escherichia coli as the heterologous host). Novel tyrosine ammonia-lyases having higher reported substrate specificity than previously characterized enzymes were also identified. Enzymes from Herpetosiphon aurantiacus and Flavobacterium johnsoniae resulted in high production of p-coumaric acid in Escherichia coli (producing 440 μM p-coumaric acid OD600 unit−1 in the medium) and in Lactococcus lactis. The enzymes were also efficient in Saccharomyces cerevisiae, where p-coumaric acid accumulation was improved 5-fold over that in strains expressing previously characterized tyrosine ammonia-lyases.

Design and application of genome-scale reconstructed metabolic models.

In this chapter, the process for the reconstruction of genome-scale metabolic networks is described, and some of the main applications of such models are illustrated. The reconstruction process can be viewed as an iterative process where information obtained from several sources is combined to construct a preliminary set of reactions and constraints. This involves steps such as genome annotation; identification of the reactions from the annotated genome sequence and available literature; determination of the reaction stoichiometry; definition of compartmentation and assignment of localization; determination of the biomass composition; measurement, calculation, or fitting of energy requirements; and definition of additional constraints. The reaction and constraint sets, after debugging, may be integrated into a stoichiometric model that can be used for simulation using tools such as Flux Balance Analysis (Section 3.8). From the flux distributions obtained, physiologic parameters such as growth yields or minimal medium components can be calculated, and their distance from similar experimental data provides a basis from where the model may need to be improved.

Evolution reveals a glutathione-dependent mechanism of 3-hydroxypropionic acid tolerance

Biologically produced 3-hydroxypropionic acid (3 HP) is a potential source for sustainable acrylates and can also find direct use as monomer in the production of biodegradable polymers. For industrial-scale production there is a need for robust cell factories tolerant to high concentration of 3 HP, preferably at low pH. Through adaptive laboratory evolution we selected S. cerevisiae strains with improved tolerance to 3 HP at pH 3.5. Genome sequencing followed by functional analysis identified the causal mutation in SFA1 gene encoding S-(hydroxymethyl)glutathione dehydrogenase. Based on our findings, we propose that 3 HP toxicity is mediated by 3-hydroxypropionic aldehyde (reuterin) and that glutathione-dependent reactions are used for reuterin detoxification. The identified molecular response to 3 HP and reuterin may well be a general mechanism for handling resistance to organic acid and aldehydes by living cells.

Assembly of a novel biosynthetic pathway for production of the plant flavonoid fisetin in Escherichia coli

Plant secondary metabolites are an underutilized pool of bioactive molecules for applications in the food, pharma and nutritional industries. One such molecule is fisetin, which is present in many fruits and vegetables and has several potential health benefits, including anti-cancer, anti-viral and anti-aging activity. Moreover, fisetin has recently been shown to prevent Alzheimers disease in mice and to prevent complications associated with diabetes type I. Thus far the biosynthetic pathway of fisetin in plants remains elusive. Here, we present the heterologous assembly of a novel fisetin pathway in Escherichia coli. We propose a novel biosynthetic pathway from the amino acid, tyrosine, utilizing nine heterologous enzymes. The pathway proceeds via the synthesis of two flavanones never produced in microorganisms before--garbanzol and resokaempferol. We show for the first time a functional biosynthetic pathway and establish E. coli as a microbial platform strain for the production of fisetin and related flavonols.