Systems-level engineering of nonfermentative metabolism in yeast

Efficient genome editing in filamentous fungi via an improved CRISPR-Cas9 ribonucleoprotein method facilitated by chemical reagents

DNA double-strand break (DSB) repair induced by the RNA-programmed nuclease Cas9 has become a popular method for genome editing. Direct genome editing via Cas9-CRISPR gRNA (guide RNA) ribonucleoprotein (RNP) complexes assembled in vitro has also been successful in some fungi. However, the efficiency of direct RNP transformation into fungal protoplasts is currently too low. Here, we report an optimized genome editing approach for filamentous fungi based on RNPs facilitated by adding chemical reagents. We increased the transformation efficiency of RNPs significantly by adding Triton X-100 and prolonging the incubation time, and the editing efficiency reached 100% in Trichoderma reesei and Cordyceps militaris. The optimized RNP-based method also achieved efficient (56.52%) homologous recombination integration with short homology arms (20 bp) and gene disruption (7.37%) that excludes any foreign DNA (selection marker) in T. reesei. In particular, after adding reagents related to mitosis and cell division, the further optimized protocol showed an increased ratio of edited homokaryotic transformants (from 0% to 40.0% for inositol and 71.43% for benomyl) from Aspergillus oryzae, which contains multinucleate spores and protoplasts. Furthermore, the multi-target engineering efficiency of the optimized RNP transformation method was similar to those of methods based on in vivo expression of Cas9. This newly established genome editing system based on RNPs may be widely applicable to construction of genome-edited fungi for the food and medical industries, and has good prospects for commercialization.

Rewired cellular signaling coordinates sugar and hypoxic responses for anaerobic xylose fermentation in yeast

Microbes can be metabolically engineered to produce biofuels and biochemicals, but rerouting metabolic flux toward products is a major hurdle without a systems-level understanding of how cellular flux is controlled. To understand flux rerouting, we investigated a panel of Saccharomyces cerevisiae strains with progressive improvements in anaerobic fermentation of xylose, a sugar abundant in sustainable plant biomass used for biofuel production. We combined comparative transcriptomics, proteomics, and phosphoproteomics with network analysis to understand the physiology of improved anaerobic xylose fermentation. Our results show that upstream regulatory changes produce a suite of physiological effects that collectively impact the phenotype. Evolved strains show an unusual co-activation of Protein Kinase A (PKA) and Snf1, thus combining responses seen during feast on glucose and famine on non-preferred sugars. Surprisingly, these regulatory changes were required to mount the hypoxic response when cells were grown on xylose, revealing a previously unknown connection between sugar source and anaerobic response. Network analysis identified several downstream transcription factors that play a significant, but on their own minor, role in anaerobic xylose fermentation, consistent with the combinatorial effects of small-impact changes. We also discovered that different routes of PKA activation produce distinct phenotypes: deletion of the RAS/PKA inhibitor IRA2 promotes xylose growth and metabolism, whereas deletion of PKA inhibitor BCY1 decouples growth from metabolism to enable robust fermentation without division. Comparing phosphoproteomic changes across ira2Δ and bcy1Δ strains implicated regulatory changes linked to xylose-dependent growth versus metabolism. Together, our results present a picture of the metabolic logic behind anaerobic xylose flux and suggest that widespread cellular remodeling, rather than individual metabolic changes, is an important goal for metabolic engineering.

Genome scale models of yeast: towards standardized evaluation and consistent omic integration

Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are currently used for metabolic engineering and elucidating biological interactions. Here we review the history of yeast's GEMs, focusing on recent developments. We study how these models are typically evaluated, using both descriptive and predictive metrics. Additionally, we analyze the different ways in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted.

Systems Biology of Microbial Exopolysaccharides Production

Exopolysaccharides (EPSs) produced by diverse group of microbial systems are rapidly emerging as new and industrially important biomaterials. Due to their unique and complex chemical structures and many interesting physicochemical and rheological properties with novel functionality, the microbial EPSs find wide range of commercial applications in various fields of the economy such as food, feed, packaging, chemical, textile, cosmetics and pharmaceutical industry, agriculture, and medicine. EPSs are mainly associated with high-value applications, and they have received considerable research attention over recent decades with their biocompatibility, biodegradability, and both environmental and human compatibility. However, only a few microbial EPSs have achieved to be used commercially due to their high production costs. The emerging need to overcome economic hurdles and the increasing significance of microbial EPSs in industrial and medical biotechnology call for the elucidation of the interrelations between metabolic pathways and EPS biosynthesis mechanism in order to control and hence enhance its microbial productivity. Moreover, a better understanding of biosynthesis mechanism is a significant issue for improvement of product quality and properties and also for the design of novel strains. Therefore, a systems-based approach constitutes an important step toward understanding the interplay between metabolism and EPS biosynthesis and further enhances its metabolic performance for industrial application. In this review, primarily the microbial EPSs, their biosynthesis mechanism, and important factors for their production will be discussed. After this brief introduction, recent literature on the application of omics technologies and systems biology tools for the improvement of production yields will be critically evaluated. Special focus will be given to EPSs with high market value such as xanthan, levan, pullulan, and dextran.

Comparative Analysis of Yeast Metabolic Network Models Highlights Progress, Opportunities for Metabolic Reconstruction

We have compared 12 genome-scale models of the Saccharomyces cerevisiae metabolic network published since 2003 to evaluate progress in reconstruction of the yeast metabolic network. We compared the genomic coverage, overlap of annotated metabolites, predictive ability for single gene essentiality with a selection of model parameters, and biomass production predictions in simulated nutrient-limited conditions. We have also compared pairwise gene knockout essentiality predictions for 10 of these models. We found that varying approaches to model scope and annotation reflected the involvement of multiple research groups in model development; that single-gene essentiality predictions were affected by simulated medium, objective function, and the reference list of essential genes; and that predictive ability for single-gene essentiality did not correlate well with predictive ability for our reference list of synthetic lethal gene interactions (R = 0.159). We conclude that the reconstruction of the yeast metabolic network is indeed gradually improving through the iterative process of model development, and there remains great opportunity for advancing our understanding of biology through continued efforts to reconstruct the full biochemical reaction network that constitutes yeast metabolism. Additionally, we suggest that there is opportunity for refining the process of deriving a metabolic model from a metabolic network reconstruction to facilitate mechanistic investigation and discovery. This comparative study lays the groundwork for developing improved tools and formalized methods to quantitatively assess metabolic network reconstructions independently of any particular model application, which will facilitate ongoing efforts to advance our understanding of the relationship between genotype and cellular phenotype.

Contemplating 3-Hydroxypropionic Acid Biosynthesis in Klebsiella pneumoniae

3-Hydroxypropionic acid (3-HP) is a commercially valuable platform chemical from which an array of C3 compounds can be generated. Klebsiella pneumoniae has been considered a promising species for biological production of 3-HP. Despite a wealth of reports related to 3-HP biosynthesis in K. pneumoniae, its commercialization is still in infancy. The major hurdle hindering 3-HP overproduction lies in the poor understanding of glycerol dissimilation in K. pneumoniae. To surmount this problem, this review aims to portray a picture of 3-HP biosynthesis, involving 3-HP-synthesizing strains, biochemical attributes, metabolic pathways and key enzymes. Inspired by the state-of-the-art advances in metabolic engineering and synthetic biology, here we advocate protocols for overproducing 3-HP in K. pneumoniae. These protocols range from cofactor regeneration, alleviation of metabolite toxicity, genome editing, remodeling of transport system, to carbon flux partition via logic gate. The feasibility for these protocols was also discussed.

Identification and treatment of heme depletion attributed to overexpression of a lineage of evolved P450 monooxygenases

Recent advances in metabolic engineering have demonstrated that microbial biosynthesis can provide a viable alternative to chemical synthesis for the production of bulk and fine chemicals. Introduction of a new biosynthetic pathway typically requires the expression of multiple heterologous enzymes in the production host, which can impose stress on the host cell and, thereby, limit performance of the pathway. Unfortunately, analysis and treatment of the host stress response can be difficult, because there are many sources of stress that may interact in complex ways. We use a systems biological approach to analyze the stress imposed by expressing different enzyme variants from a lineage of soluble P450 monooxygenases, previously evolved for heterologous activity in Saccharomyces cerevisiae. Our analysis identifies patterns of stress imposed on the host by heterologous enzyme overexpression that are consistent across the evolutionary lineage, ultimately implicating heme depletion as the major stress. We show that the monooxygenase evolution, starting from conditions of either high or low stress, caused the cellular stress to converge to a common level. Overexpression of rate-limiting enzymes in the endogenous heme biosynthetic pathway alleviates the stress imposed by expression of the P450 monooxygenases and increases the enzymatic activity of the final evolved P450 by an additional 2.3-fold. Heme overexpression also increases the total activity of an endogenous cytosolic heme-containing catalase but not a heterologous P450 that is membrane-associated. This work demonstrates the utility of combining systems and synthetic biology to analyze and optimize heterologous enzyme expression.

A BioBrick compatible strategy for genetic modification of plants

Background

Plant biotechnology can be leveraged to produce food, fuel, medicine, and materials. Standardized methods advocated by the synthetic biology community can accelerate the plant design cycle, ultimately making plant engineering more widely accessible to bioengineers who can contribute diverse creative input to the design process.

Results

This paper presents work done largely by undergraduate students participating in the 2010 International Genetically Engineered Machines (iGEM) competition. Described here is a framework for engineering the model plant Arabidopsis thaliana with standardized, BioBrick compatible vectors and parts available through the Registry of Standard Biological Parts (http://www.partsregistry.org). This system was used to engineer a proof-of-concept plant that exogenously expresses the taste-inverting protein miraculin.

Conclusions

Our work is intended to encourage future iGEM teams and other synthetic biologists to use plants as a genetic chassis. Our workflow simplifies the use of standardized parts in plant systems, allowing the construction and expression of heterologous genes in plants within the timeframe allotted for typical iGEM projects.

Transcriptional regulation of fermentative and respiratory metabolism in Saccharomyces cerevisiae industrial bakers' strains

Bakers' yeast-producing companies grow cells under respiratory conditions, at a very high growth rate. Some desirable properties of bakers' yeast may be altered if fermentation rather than respiration occurs during biomass production. That is why differences in gene expression patterns that take place when industrial bakers' yeasts are grown under fermentative, rather than respiratory conditions, were examined. Macroarray analysis of V1 strain indicated changes in gene expression similar to those already described in laboratory Saccharomyces cerevisiae strains: repression of most genes related to respiration and oxidative metabolism and derepression of genes related to ribosome biogenesis and stress resistance in fermentation. Under respiratory conditions, genes related to the glyoxylate and Krebs cycles, respiration, gluconeogenesis, and energy production are activated. DOG21 strain, a partly catabolite-derepressed mutant derived from V1, displayed gene expression patterns quite similar to those of V1, although lower levels of gene expression and changes in fewer number of genes as compared to V1 were both detected in all cases. However, under fermentative conditions, DOG21 mutant significantly increased the expression of SNF1 -controlled genes and other genes involved in stress resistance, whereas the expression of the HXK2 gene, involved in catabolite repression, was considerably reduced, according to the pleiotropic stress-resistant phenotype of this mutant. These results also seemed to suggest that stress-resistant genes control desirable bakers' yeast qualities.

Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering

BACKGROUND

2,3-Butanediol is a chemical compound of increasing interest due to its wide applications. It can be synthesized via mixed acid fermentation of pathogenic bacteria such as Enterobacter aerogenes and Klebsiella oxytoca. The non-pathogenic Saccharomyces cerevisiae possesses three different 2,3-butanediol biosynthetic pathways, but produces minute amount of 2,3-butanediol. Hence, we attempted to engineer S. cerevisiae strain to enhance 2,3-butanediol production.

RESULTS

We first identified gene deletion strategy by performing in silico genome-scale metabolic analysis. Based on the best in silico strategy, in which disruption of alcohol dehydrogenase (ADH) pathway is required, we then constructed gene deletion mutant strains and performed batch cultivation of the strains. Deletion of three ADH genes, ADH1, ADH3 and ADH5, increased 2,3-butanediol production by 55-fold under microaerobic condition. However, overproduction of glycerol was observed in this triple deletion strain. Additional rational design to reduce glycerol production by GPD2 deletion altered the carbon fluxes back to ethanol and significantly reduced 2,3-butanediol production. Deletion of ALD6 reduced acetate production in strains lacking major ADH isozymes, but it did not favor 2,3-butanediol production. Finally, we introduced 2,3-butanediol biosynthetic pathway from Bacillus subtilis and E. aerogenes to the engineered strain and successfully increased titer and yield. Highest 2,3-butanediol titer (2.29 . l-1) and yield (0.113 g . g-1) were achieved by Δadh1 Δadh3 Δadh5 strain under anaerobic condition.

CONCLUSIONS

With the aid of in silico metabolic engineering, we have successfully designed and constructed S. cerevisiae strains with improved 2,3-butanediol production.

Constraining the metabolic genotype-phenotype relationship using a phylogeny of in silico methods

Reconstructed microbial metabolic networks facilitate a mechanistic description of the genotype-phenotype relationship through the deployment of constraint-based reconstruction and analysis (COBRA) methods. As reconstructed networks leverage genomic data for insight and phenotype prediction, the development of COBRA methods has accelerated following the advent of whole-genome sequencing. Here, we describe a phylogeny of COBRA methods that has rapidly evolved from the few early methods, such as flux balance analysis and elementary flux mode analysis, into a repertoire of more than 100 methods. These methods have enabled genome-scale analysis of microbial metabolism for numerous basic and applied uses, including antibiotic discovery, metabolic engineering and modelling of microbial community behaviour.

Parts plus pipes: synthetic biology approaches to metabolic engineering

Synthetic biologists combine modular biological "parts" to create higher-order devices. Metabolic engineers construct biological "pipes" by optimizing the microbial conversion of basic substrates to desired compounds. Many scientists work at the intersection of these two philosophies, employing synthetic devices to enhance metabolic engineering efforts. These integrated approaches promise to do more than simply improve product yields; they can expand the array of products that are tractable to produce biologically. In this review, we explore the application of synthetic biology techniques to next-generation metabolic engineering challenges, as well as the emerging engineering principles for biological design.

Modular electron transfer circuits for synthetic biology: insulation of an engineered biohydrogen pathway

Electron transfer is central to a wide range of essential metabolic pathways, from photosynthesis to fermentation. The evolutionary diversity and conservation of proteins that transfer electrons makes these pathways a valuable platform for engineered metabolic circuits in synthetic biology. Rational engineering of electron transfer pathways containing hydrogenases has the potential to lead to industrial scale production of hydrogen as an alternative source of clean fuel and experimental assays for understanding the complex interactions of multiple electron transfer proteins in vivo. We designed and implemented a synthetic hydrogen metabolism circuit in Escherichia coli that creates an electron transfer pathway both orthogonal to and integrated within existing metabolism. The design of such modular electron transfer circuits allows for facile characterization of in vivo system parameters with applications toward further engineering for alternative energy production.

Engineering strategy of yeast metabolism for higher alcohol production

Background

While Saccharomyces cerevisiae is a promising host for cost-effective biorefinary processes due to its tolerance to various stresses during fermentation, the metabolically engineered S. cerevisiae strains exhibited rather limited production of higher alcohols than that of Escherichia coli. Since the structure of the central metabolism of S. cerevisiae is distinct from that of E. coli, there might be a problem in the structure of the central metabolism of S. cerevisiae. In this study, the potential production of higher alcohols by S. cerevisiae is compared to that of E. coli by employing metabolic simulation techniques. Based on the simulation results, novel metabolic engineering strategies for improving higher alcohol production by S. cerevisiae were investigated by in silico modifications of the metabolic models of S. cerevisiae.

Results

The metabolic simulations confirmed that the high production of butanols and propanols by the metabolically engineered E. coli strains is derived from the flexible behavior of their central metabolism. Reducing this flexibility by gene deletion is an effective strategy to restrict the metabolic states for producing target alcohols. In contrast, the lower yield using S. cerevisiae originates from the structurally limited flexibility of its central metabolism in which gene deletions severely reduced cell growth.

Conclusions

The metabolic simulation demonstrated that the poor productivity of S. cerevisiae was improved by the introduction of E. coli genes to compensate the structural difference. This suggested that gene supplementation is a promising strategy for the metabolic engineering of S. cerevisiae to produce higher alcohols which should be the next challenge for the synthetic bioengineering of S. cerevisiae for the efficient production of higher alcohols.

Statistics-based model for prediction of chemical biosynthesis yield from Saccharomyces cerevisiae

Background

The 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.

Results

Based 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.

Conclusions

We 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.

Aspergillus fumigatus AcuM regulates both iron acquisition and gluconeogenesis

Relatively few transcription factors that govern the virulence of Aspergillus fumigatus are known. We constructed 11 A. fumigatus transcription factor mutants and screened them for altered virulence in Galleria mellonella larvae. We discovered that the zinc cluster transcription factor, AcuM, is essential for maximal virulence in this model, as well as in murine models of haematogenously disseminated and invasive pulmonary aspergillosis. Transcriptional profiling experiments suggested that AcuM suppresses sreA and induces hapX to stimulate expression of genes involved in both reductive iron assimilation and siderophore-mediated iron uptake. Consistent with these results, a ΔacuM mutant had reduced iron incorporation, decreased extracellular siderophore production and impaired capacity to grow under iron-limited conditions. Interestingly, an Aspergillus nidulansΔacuM mutant had normal extracellular siderophore production and growth under iron-limited conditions, indicating that AcuM does not govern iron acquisition in this organism. A. fumigatus AcuM also regulated genes involved in gluconeogenesis, and the ΔacuM mutant had impaired growth on gluconeogenic carbon sources. Deletion of sreA in the ΔacuM mutant restored iron uptake, extracellular siderophore production and virulence, but not the defect in gluconeogenesis. Thus, AcuM represses SreA and thereby induces iron acquisition, a process that is essential for the maximal virulence of A. fumigatus.

Redox biocatalysis and metabolism: molecular mechanisms and metabolic network analysis

Whole-cell biocatalysis utilizes native or recombinant enzymes produced by cellular metabolism to perform synthetically interesting reactions. Besides hydrolases, oxidoreductases represent the most applied enzyme class in industry. Oxidoreductases are attributed a high future potential, especially for applications in the chemical and pharmaceutical industries, as they enable highly interesting chemistry (e.g., the selective oxyfunctionalization of unactivated C-H bonds). Redox reactions are characterized by electron transfer steps that often depend on redox cofactors as additional substrates. Their regeneration typically is accomplished via the metabolism of whole-cell catalysts. Traditionally, studies towards productive redox biocatalysis focused on the biocatalytic enzyme, its activity, selectivity, and specificity, and several successful examples of such processes are running commercially. However, redox cofactor regeneration by host metabolism was hardly considered for the optimization of biocatalytic rate, yield, and/or titer. This article reviews molecular mechanisms of oxidoreductases with synthetic potential and the host redox metabolism that fuels biocatalytic reactions with redox equivalents. The tools discussed in this review for investigating redox metabolism provide the basis for studies aiming at a deeper understanding of the interplay between synthetically active enzymes and metabolic networks. The ultimate goal of rational whole-cell biocatalyst engineering and use for fine chemical production is discussed.

Harnessing nature's toolbox: regulatory elements for synthetic biology

Synthetic biologists seek to engineer complex biological systems composed of modular elements. Achieving higher complexity in engineered biological organisms will require manipulating numerous systems of biological regulation: transcription; RNA interactions; protein signalling; and metabolic fluxes, among others. Exploiting the natural modularity at each level of biological regulation will promote the development of standardized tools for designing biological systems.