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

Genetic Optimization Algorithm for Metabolic Engineering Revisited

To date, several independent methods and algorithms exist for exploiting constraint-based stoichiometric models to find metabolic engineering strategies that optimize microbial production performance. Optimization procedures based on metaheuristics facilitate a straightforward adaption and expansion of engineering objectives, as well as fitness functions, while being particularly suited for solving problems of high complexity. With the increasing interest in multi-scale models and a need for solving advanced engineering problems, we strive to advance genetic algorithms, which stand out due to their intuitive optimization principles and the proven usefulness in this field of research. A drawback of genetic algorithms is that premature convergence to sub-optimal solutions easily occurs if the optimization parameters are not adapted to the specific problem. Here, we conducted comprehensive parameter sensitivity analyses to study their impact on finding optimal strain designs. We further demonstrate the capability of genetic algorithms to simultaneously handle (i) multiple, non-linear engineering objectives; (ii) the identification of gene target-sets according to logical gene-protein-reaction associations; (iii) minimization of the number of network perturbations; and (iv) the insertion of non-native reactions, while employing genome-scale metabolic models. This framework adds a level of sophistication in terms of strain design robustness, which is exemplarily tested on succinate overproduction in Escherichia coli.

Engineering and Evolution of Saccharomyces cerevisiae to Produce Biofuels and Chemicals

To mitigate global climate change caused partly by the use of fossil fuels, the production of fuels and chemicals from renewable biomass has been attempted. The conversion of various sugars from renewable biomass into biofuels by engineered baker's yeast (Saccharomyces cerevisiae) is one major direction which has grown dramatically in recent years. As well as shifting away from fossil fuels, the production of commodity chemicals by engineered S. cerevisiae has also increased significantly. The traditional approaches of biochemical and metabolic engineering to develop economic bioconversion processes in laboratory and industrial settings have been accelerated by rapid advancements in the areas of yeast genomics, synthetic biology, and systems biology. Together, these innovations have resulted in rapid and efficient manipulation of S. cerevisiae to expand fermentable substrates and diversify value-added products. Here, we discuss recent and major advances in rational (relying on prior experimentally-derived knowledge) and combinatorial (relying on high-throughput screening and genomics) approaches to engineer S. cerevisiae for producing ethanol, butanol, 2,3-butanediol, fatty acid ethyl esters, isoprenoids, organic acids, rare sugars, antioxidants, and sugar alcohols from glucose, xylose, cellobiose, galactose, acetate, alginate, mannitol, arabinose, and lactose.

FOCuS: a metaheuristic algorithm for computing knockouts from genome-scale models for strain optimization

Although handful tools are available for constraint-based flux analysis to generate knockout strains, most of these are either based on bilevel-MIP or its modifications. However, metaheuristic approaches that are known for their flexibility and scalability have been less studied. Moreover, in the existing tools, sectioning of search space to find optimal knocks has not been considered. Herein, a novel computational procedure, termed as FOCuS (Flower-pOllination coupled Clonal Selection algorithm), was developed to find the optimal reaction knockouts from a metabolic network to maximize the production of specific metabolites. FOCuS derives its benefits from nature-inspired flower pollination algorithm and artificial immune system-inspired clonal selection algorithm to converge to an optimal solution. To evaluate the performance of FOCuS, reported results obtained from both MIP and other metaheuristic-based tools were compared in selected case studies. The results demonstrated the robustness of FOCuS irrespective of the size of metabolic network and number of knockouts. Moreover, sectioning of search space coupled with pooling of priority reactions based on their contribution to objective function for generating smaller search space significantly reduced the computational time.

Rapid and stable production of 2,3-butanediol by an engineered Saccharomyces cerevisiae strain in a continuous airlift bioreactor

Utilization of renewable feedstocks for the production of bio-based bulk chemicals, such as 2,3-butanediol (2,3-BDO), by engineered strains of the non-pathogenic yeast, Saccharomyces cerevisiae, has recently become an attractive option. In this study, to realize rapid production of 2,3-BDO, a flocculent, 2,3-BDO-producing S. cerevisiae strain YPH499/dPdAdG/BDN6-10/FLO1 was constructed from a previously developed 2,3-BDO-producing strain. Continuous 2,3-BDO fermentation was carried out by the flocculent strain in an airlift bioreactor. The strain consumed more than 90 g/L of glucose, which corresponded to 90% of the input, and stably produced more than 30 g/L of 2,3-BDO over 380 h. The maximum 2,3-BDO productivity was 7.64 g/L/h at a dilution rate of 0.200/h, which was higher than the values achieved by continuous fermentation using pathogenic bacteria in the previous reports. These results demonstrate that continuous 2,3-BDO fermentation with flocculent 2,3-BDO-producing S. cerevisiae is a promising strategy for practical 2,3-BDO production.

Recent advances on production of 2, 3-butanediol using engineered microbes

As a significant platform chemical, 2, 3-butanediol (2, 3-BD) has found wide applications in industry. The success of microbial 2, 3-BD production was limited by the use of pathogenic microorganisms and low titer in engineered hosts. The utilization of cheaply available feedstock such as lignocellulose was another major challenge to achieve economic production of 2, 3-BD. To address those issues, engineering strategies including both genetic modifications and process optimization have been employed. In this review, we summarized the state-of-the-art progress in the biotechnological production of 2, 3-BD. Metabolic engineering and process engineering strategies were discussed.

Biological conversion of methane to chemicals and fuels: technical challenges and issues

Methane is a promising next-generation carbon feedstock for industrial biotechnology due to its low price and huge availability. Biological conversion of methane to valuable products can mitigate methane-induced global warming as greenhouse gas. There have been challenges for the conversion of methane into various chemicals and fuels using engineered non-native hosts with synthetic methanotrophy or methanotrophs with the reconstruction of synthetic pathways for target products. Herein, we analyze the technical challenges and issues of potent methane bioconversion technology. Pros and cons of metabolic engineering of methanotrophs for methane bioconversion, and perspectives on the bioconversion of methane to chemicals and liquid fuels are discussed.

Efficient production of 2,3-butanediol by recombinant Saccharomyces cerevisiae through modulation of gene expression by cocktail δ-integration

In this study, the expression of 4 genes encoding α-acetolactate synthase, α-acetolactate decarboxylase, 2,3-butanediol dehydrogenase, and NADH oxidase was modulated using a previously developed cocktail δ-integration strategy. The resultant strain, YPH499/dPdAdG/BD6-10, was used in a fed-batch cultivation for the production of 2,3-butanediol. The concentration, production rate, and yield obtained were 80.0g/L, 4.00g/L/h, and 41.7%, respectively. The production rate and yield of the compound obtained are higher for this strain compared to reports published for Saccharomyces cerevisiae so far. The cocktail δ-integration strategy allows for modulation of multiple gene expression, without the exact knowledge of rate-limiting steps, and therefore, could be used as a promising strategy for the production of bio-based chemicals in recombinant S. cerevisiae.

Acetolactate synthase (AlsS) in Bacillus licheniformis WX-02: enzymatic properties and efficient functions for acetoin/butanediol and L-valine biosynthesis

Acetolactate synthase catalyzes two molecules of pyruvates to form α-acetolactate, which is further converted to acetoin and 2,3-butanediol. In this study, by heterologous expression in Escherichia coli, the enzymatic properties of acetolactate synthase (AlsS) from Bacillus licheniformis WX-02 were characterized. Its K _m and k _cat for pyruvate were 3.96 mM and 514/s, respectively. It has the optimal activity at pH 6.5, 37 °C and was feedback inhibited by L-valine, L-leucine and L-isoleucine. Furthermore, the alsS-deficient strain could not produce acetoin, 2,3-butanediol, and L-valine, while the complementary strain was able to restore these capacities. The alsS overexpressing strain produced higher amounts of acetoin/2,3-butanediol (57.06 g/L) and L-valine (2.68 mM), which were 10.90 and 92.80% higher than those of the control strain, respectively. This is the first report regarding the in-depth understanding of AlsS enzymatic properties and its functions in B. licheniformis, and overexpression of AlsS can effectively improve acetoin/2,3-butanediol and L-valine production in B. licheniformis. We envision that this AlsS can also be applied in the improvement of acetoin/2,3-butanediol and L-valine production in other microbes.

Sniffing out the hypoxia volatile metabolic signature of Aspergillus fumigatus

Invasive aspergillosis (IA) is a life-threatening infectious disease caused by fungi from the genus Aspergillus, with an associated mortality as high as 90% in certain populations. IA-associated pulmonary lesions are characteristically depleted in oxygen relative to normal lung tissue, and it has been shown that the most common causal agent of IA, Aspergillus fumigatus, must respond to low-oxygen environments for pathogenesis and disease progression. Previous studies have demonstrated marked alterations to the Aspergillus fumigatus transcriptome in response to low-oxygen environments that induce a 'hypoxia response'. Consequently, we hypothesized that these transcriptomic changes would alter the volatile metabolome and generate a volatile hypoxia signature. In the present study, we analyzed the volatile molecules produced by A. fumigatus in both oxygen replete (normoxia) and depleted (hypoxia) environments via headspace solid-phase micro-extraction coupled to two-dimensional gas chromatography-time-of-flight mass spectrometry. Using the machine learning algorithm random forest, we identified 19 volatile molecules that were discriminatory between the four growth conditions assessed in this study (i.e., early hypoxia (1 h), late hypoxia (8 h), early normoxia (1 h), and late normoxia (8 h)), as well as a set of 19 that were discriminatory between late hypoxia cultures and all other growth conditions in aggregate. Nine molecules were common to both comparisons, while the remaining 20 were specific to only one of two. We assigned putative identifications to 13 molecules, of which six were most highly abundant in late hypoxia cultures. Previously acquired transcriptomic data identified putative biochemical pathways induced in hypoxia conditions that plausibly account for the production of a subset of these molecules, including 2,3-butanedione and 3-hydroxy-2-butanone. These two molecules may represent a novel hypoxia fitness pathway in A. fumigatus, and could be useful in the detection of hypoxia-associated A. fumigatus lesions that develop in established IA infections.

Genome-scale modeling of yeast: chronology, applications and critical perspectives

Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed.

The gluconate shunt is an alternative route for directing glucose into the pentose phosphate pathway in fission yeast

Glycolysis and the pentose phosphate pathway both play a central role in the degradation of glucose in all domains of life. Another metabolic route that can facilitate glucose breakdown is the gluconate shunt. In this shunt glucose dehydrogenase and gluconate kinase catalyze the two-step conversion of glucose into the pentose phosphate pathway intermediate 6-phosphogluconate. Despite the presence of these enzymes in many organisms, their only established role is in the production of 6-phosphogluconate for the Entner-Doudoroff pathway. In this report we performed metabolic profiling on a strain of Schizosaccharomyces pombe lacking the zinc-responsive transcriptional repressor Loz1 with the goal of identifying metabolic pathways that were altered by cellular zinc status. This profiling revealed that loz1Δ cells accumulate higher levels of gluconate. We show that the altered gluconate levels in loz1Δ cells result from increased expression of gcd1 By analyzing the activity of recombinant Gcd1 in vitro and by measuring gluconate levels in strains lacking enzymes of the gluconate shunt we demonstrate that Gcd1 encodes a novel NADP⁺-dependent glucose dehydrogenase that acts in a pathway with the Idn1 gluconate kinase. We also find that cells lacking gcd1 and zwf1, which encode the first enzyme in the pentose phosphate pathway, have a more severe growth phenotype than cells lacking zwf1 We propose that in S. pombe Gcd1 and Idn1 act together to shunt glucose into the pentose phosphate pathway, creating an alternative route for directing glucose into the pentose phosphate pathway that bypasses hexokinase and the rate-limiting enzyme glucose-6-phosphate dehydrogenase.

Growth-coupled overproduction is feasible for almost all metabolites in five major production organisms

Computational modelling of metabolic networks has become an established procedure in the metabolic engineering of production strains. One key principle that is frequently used to guide the rational design of microbial cell factories is the stoichiometric coupling of growth and product synthesis, which makes production of the desired compound obligatory for growth. Here we show that the coupling of growth and production is feasible under appropriate conditions for almost all metabolites in genome-scale metabolic models of five major production organisms. These organisms comprise eukaryotes and prokaryotes as well as heterotrophic and photoautotrophic organisms, which shows that growth coupling as a strain design principle has a wide applicability. The feasibility of coupling is proven by calculating appropriate reaction knockouts, which enforce the coupling behaviour. The study presented here is the most comprehensive computational investigation of growth-coupled production so far and its results are of fundamental importance for rational metabolic engineering.

Engineering tolerance to industrially relevant stress factors in yeast cell factories

The main focus in development of yeast cell factories has generally been on establishing optimal activity of heterologous pathways and further metabolic engineering of the host strain to maximize product yield and titer. Adequate stress tolerance of the host strain has turned out to be another major challenge for obtaining economically viable performance in industrial production. Although general robustness is a universal requirement for industrial microorganisms, production of novel compounds using artificial metabolic pathways presents additional challenges. Many of the bio-based compounds desirable for production by cell factories are highly toxic to the host cells in the titers required for economic viability. Artificial metabolic pathways also turn out to be much more sensitive to stress factors than endogenous pathways, likely because regulation of the latter has been optimized in evolution in myriads of environmental conditions. We discuss different environmental and metabolic stress factors with high relevance for industrial utilization of yeast cell factories and the experimental approaches used to engineer higher stress tolerance. Improving stress tolerance in a predictable manner in yeast cell factories should facilitate their widespread utilization in the bio-based economy and extend the range of products successfully produced in large scale in a sustainable and economically profitable way.

Genomics of lactic acid bacteria: Current status and potential applications

Lactic acid bacteria (LAB) are widely used for the production of a variety of foods and feed raw materials where they contribute to flavor and texture of the fermented products. In addition, specific LAB strains are considered as probiotic due to their health-promoting effects in consumers. Recently, the genome sequencing of LAB is booming and the increased amount of published genomics data brings unprecedented opportunity for us to reveal the important traits of LAB. This review describes the recent progress on LAB genomics and special emphasis is placed on understanding the industry-related physiological features based on genomics analysis. Moreover, strategies to engineer metabolic capacity and stress tolerance of LAB with improved industrial performance are also discussed.

Metabolic anchor reactions for robust biorefining

Microbial cell factories based on renewable carbon sources are fundamental to a sustainable bio-economy. The economic feasibility of producer cells requires robust performance balancing growth and production. However, the inherent competition between these two objectives often leads to instability and reduces productivity. While algorithms exist to design metabolic network reduction strategies for aligning these objectives, the biochemical basis of the growth-product coupling has remained unresolved. Here, we reveal key reactions in the cellular biochemical repertoire as universal anchor reactions for aligning cell growth and production. A necessary condition for a reaction to be an anchor is that it splits a substrate into two or more molecules. By searching the currently known biochemical reaction space, we identify 62 C-C cleaving anchor reactions, such as isocitrate lyase (EC 4.1.3.1) and L-tryptophan indole-lyase (EC 4.1.99.1), which are relevant for biorefining. The here identified anchor reactions mark network nodes for basing growth-coupled metabolic engineering and novel pathway designs.

In silico screening for candidate chassis strains of free fatty acid-producing cyanobacteria

BACKGROUND

Finding a source from which high-energy-density biofuels can be derived at an industrial scale has become an urgent challenge for renewable energy production. Some microorganisms can produce free fatty acids (FFA) as precursors towards such high-energy-density biofuels. In particular, photosynthetic cyanobacteria are capable of directly converting carbon dioxide into FFA. However, current engineered strains need several rounds of engineering to reach the level of production of FFA to be commercially viable; thus new chassis strains that require less engineering are needed. Although more than 120 cyanobacterial genomes are sequenced, the natural potential of these strains for FFA production and excretion has not been systematically estimated.

RESULTS

Here we present the FFA SC (FFASC), an in silico screening method that evaluates the potential for FFA production and excretion of cyanobacterial strains based on their proteomes. A literature search allowed for the compilation of 64 proteins, most of which influence FFA production and a few of which affect FFA excretion. The proteins are classified into 49 orthologous groups (OGs) that helped create rules used in the scoring/ranking of algorithms developed to estimate the potential for FFA production and excretion of an organism. Among 125 cyanobacterial strains, FFASC identified 20 candidate chassis strains that rank in their FFA producing and excreting potential above the specifically engineered reference strain, Synechococcus sp. PCC 7002. We further show that the top ranked cyanobacterial strains are unicellular and primarily include Prochlorococcus (order Prochlorales) and marine Synechococcus (order Chroococcales) that cluster phylogenetically. Moreover, two principal categories of enzymes were shown to influence FFA production the most: those ensuring precursor availability for the biosynthesis of lipids, and those involved in handling the oxidative stress associated to FFA synthesis.

CONCLUSION

To our knowledge FFASC is the first in silico method to screen cyanobacteria proteomes for their potential to produce and excrete FFA, as well as the first attempt to parameterize the criteria derived from genetic characteristics that are favorable/non-favorable for this purpose. Thus, FFASC helps focus experimental evaluation only on the most promising cyanobacteria.

Engineering an NADPH/NADP+ Redox Biosensor in Yeast

Genetically encoded biosensors have emerged as powerful tools for timely and precise in vivo evaluation of cellular metabolism. In particular, biosensors that can couple intercellular cues with downstream signaling responses are currently attracting major attention within health science and biotechnology. Still, there is a need for bioprospecting and engineering of more biosensors to enable real-time monitoring of specific cellular states and controlling downstream actuation. In this study, we report the engineering and application of a transcription factor-based NADPH/NADP⁺ redox biosensor in the budding yeast Saccharomyces cerevisiae. Using the biosensor, we are able to monitor the cause of oxidative stress by chemical induction, and changes in NADPH/NADP⁺ ratios caused by genetic manipulations. Because of the regulatory potential of the biosensor, we also show that the biosensor can actuate upon NADPH deficiency by activation of NADPH regeneration. Finally, we couple the biosensor with an expression of dosage-sensitive genes (DSGs) and thereby create a novel tunable sensor-selector useful for synthetic selection of cells with higher NADPH/NADP⁺ ratios from mixed cell populations. We show that the combination of exploitation and rational engineering of native signaling components is applicable for diagnosis, regulation, and selection of cellular redox states.

Mass spectrometry for the characterization of brewing process

Beer is a carbonated alcoholic beverage produced by fermenting ingredients containing starch, especially malted cereals, and other compounds such as water, hops and yeast. The process comprises five main steps: malting, mashing, boiling, fermentation and maturation. There has been growing interest in the subject, since there is increasing demand for beer quality aspects and beer is a ubiquitous alcoholic beverage in the world. This study is based on the manufacturing process of a Brazilian craft brewery, which is characterized by withdrawing samples during key production stages and using electrospray ionization (ESI) high-resolution mass spectrometry (HRMS), a selective and reliable technique used in the identification of substances in an expeditious and practical way. Multivariate data analysis, namely partial least squares discriminant analysis (PLS-DA) is used to define its markers. In both positive and negative modes of PLS-DA score plot, it is possible to notice differences between each stage. VIP score analysis pointed out markers coherent with the process, such as barley components ((+)-catechin), small peptide varieties, hop content (humulone), yeast metabolic compounds and, in maturation, flavoring compounds (caproic acid, glutaric acid and 2,3-butanediol). Besides that, it was possible to identify other important substances such as off-flavor precursors and other different trace compounds, according to the focus given. This is an attractive alternative for the control of food and beverage industry, allowing a quick assessment of process status before it is finished, preventing higher production costs, ensuring quality and helping the control of desirable features, as flavor, foam stability and drinkability. Covering different classes of compounds, this approach suggests a novel analytical strategy: "processomics", aiming at understanding processes in detail, promoting control and being able to make improvements.

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.

Applications of Genome-Scale Metabolic Models in Biotechnology and Systems Medicine

Genome-scale metabolic models (GEMs) have become a popular tool for systems biology, and they have been used in many fields such as industrial biotechnology and systems medicine. Since more and more studies are being conducted using GEMs, they have recently received considerable attention. In this review, we introduce the basic concept of GEMs and provide an overview of their applications in biotechnology, systems medicine, and some other fields. In addition, we describe the general principle of the applications and analyses built on GEMs. The purpose of this review is to introduce the application of GEMs in biological analysis and to promote its wider use by biologists.

Enhanced production of 2,3-butanediol by engineered Saccharomyces cerevisiae through fine-tuning of pyruvate decarboxylase and NADH oxidase activities

BACKGROUND

2,3-Butanediol (2,3-BD) is a promising compound for various applications in chemical, cosmetic, and agricultural industries. Pyruvate decarboxylase (Pdc)-deficient Saccharomyces cerevisiae is an attractive host strain for producing 2,3-BD because a large amount of pyruvate could be shunted to 2,3-BD production instead of ethanol synthesis. However, 2,3-BD yield, productivity, and titer by engineered yeast were inferior to native bacterial producers because of the following metabolic limitations. First, the Pdc-deficient yeast showed growth defect due to a shortage of C₂-compounds. Second, redox imbalance during the 2,3-BD production led to glycerol formation that lowered the yield.

RESULTS

To overcome these problems, the expression levels of Pdc from a Crabtree-negative yeast were optimized in S. cerevisiae. Specifically, Candida tropicalis PDC1 (CtPDC1) was used to minimize the production of ethanol but maximize cell growth and 2,3-BD productivity. As a result, productivity of the BD5_G1CtPDC1 strain expressing an optimal level of Pdc was 2.3 folds higher than that of the control strain in flask cultivation. Through a fed-batch fermentation, 121.8 g/L 2,3-BD was produced in 80 h. NADH oxidase from Lactococcus lactis (noxE) was additionally expressed in the engineered yeast with an optimal activity of Pdc. The fed-batch fermentation with the optimized 2-stage aeration control led to production of 154.3 g/L 2,3-BD in 78 h. The overall yield of 2,3-BD was 0.404 g 2,3-BD/g glucose which corresponds to 80.7% of theoretical yield.

CONCLUSIONS

A massive metabolic shift in the engineered S. cerevisiae (BD5_G1CtPDC1_nox) expressing NADH oxidase was observed, suggesting that redox imbalance was a major bottleneck for efficient production of 2,3-BD by engineered yeast. Maximum 2,3-BD titer in this study was close to the highest among the reported microbial production studies. The results demonstrate that resolving both C₂-compound limitation and redox imbalance is critical to increase 2,3-BD production in the Pdc-deficient S. cerevisiae. Our strategy to express fine-tuned PDC and noxE could be applicable not only to 2,3-BD production, but also other chemical production systems using Pdc-deficient S. cerevisiae.

Metabolic engineering of Zymomonas mobilis for 2,3-butanediol production from lignocellulosic biomass sugars

BACKGROUND

To develop pathways for advanced biofuel production, and to understand the impact of host metabolism and environmental conditions on heterologous pathway engineering for economic advanced biofuels production from biomass, we seek to redirect the carbon flow of the model ethanologen Zymomonas mobilis to produce desirable hydrocarbon intermediate 2,3-butanediol (2,3-BDO). 2,3-BDO is a bulk chemical building block, and can be upgraded in high yields to gasoline, diesel, and jet fuel.

RESULTS

2,3-BDO biosynthesis pathways from various bacterial species were examined, which include three genes encoding acetolactate synthase, acetolactate decarboxylase, and butanediol dehydrogenase. Bioinformatics analysis was carried out to pinpoint potential bottlenecks for high 2,3-BDO production. Different combinations of 2,3-BDO biosynthesis metabolic pathways using genes from different bacterial species have been constructed. Our results demonstrated that carbon flux can be deviated from ethanol production into 2,3-BDO biosynthesis, and all three heterologous genes are essential to efficiently redirect pyruvate from ethanol production for high 2,3-BDO production in Z. mobilis. The down-selection of best gene combinations up to now enabled Z. mobilis to reach the 2,3-BDO production of more than 10 g/L from glucose and xylose, as well as mixed C6/C5 sugar streams derived from the deacetylation and mechanical refining process.

CONCLUSIONS

This study confirms the value of integrating bioinformatics analysis and systems biology data during metabolic engineering endeavors, provides guidance for value-added chemical production in Z. mobilis, and reveals the interactions between host metabolism, oxygen levels, and a heterologous 2,3-BDO biosynthesis pathway. Taken together, this work provides guidance for future metabolic engineering efforts aimed at boosting 2,3-BDO titer anaerobically.

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.

In Silico Constraint-Based Strain Optimization Methods: the Quest for Optimal Cell Factories

Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise

Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

Expression of Lactococcus lactis NADH oxidase increases 2,3-butanediol production in Pdc-deficient Saccharomyces cerevisiae

To minimize glycerol production during 2,3-BD fermentation by the engineered Saccharomyces cerevisiae, the Lactococcus lactis water-forming NADH oxidase gene (noxE) was expressed at five different levels. The expression of NADH oxidase substantially decreased the intracellular NADH/NAD(+) ratio. The S. cerevisiae BD5_T2nox strain expressing noxE produced 2,3-BD with yield of 0.359 g 2,3-BD/gglucose and glycerol with 0.069gglycerol/gglucose, which are 23.8% higher and 65.3% lower than those of the isogenic strain without noxE. These results demonstrate that the carbon flux could be redirected from glycerol to 2,3-BD through alteration of the NADH/NAD(+) ratio by the expression of NADH oxidase.

Inactivation of the virulence factors from 2,3-butanediol-producing Klebsiella pneumoniae

The microbiological production of 2,3-butanediol (2,3-BDO) has attracted considerable attention as an alternative way to produce high-value chemicals from renewable sources. Among the number of 2,3-BDO-producing microorganisms, Klebsiella pneumoniae has been studied most extensively and is known to produce large quantity of 2,3-BDO from a range of substrates. On the other hand, the pathogenic characteristics of the bacteria have limited its industrial applications. In this study, two major virulence traits, outer core LPS and fimbriae, were removed through homologous recombination from 2,3-BDO-producing K. pneumoniae 2242 to expand its uses to the industrial scale. The K. pneumoniae 2242 ∆wabG mutant strain was found to have an impaired capsule, which significantly reduced its ability to bind to the mucous layer and evade the phagocytic activity of macrophage. The association with the human ileocecal epithelial cell, HCT-8, and the bladder epithelial cell, T-24, was also reduced dramatically in the K. pneumoniae 2242 ∆fimA mutant strain that was devoid of fimbriae. However, the growth rate and production yield for 2,3-BDO were unaffected. The K. pneumoniae strains developed in this study, which are devoid of the major virulence factors, have a high potential for the efficient and sustainable production of 2,3-BDO.

Co-evolution of strain design methods based on flux balance and elementary mode analysis

More than a decade ago, the first genome-scale metabolic models for two of the most relevant microbes for biotechnology applications, Escherichia coli and Saccaromyces cerevisiae, were published. Shortly after followed the publication of OptKnock, the first strain design method using bilevel optimization to couple cellular growth with the production of a target product. This initiated the development of a family of strain design methods based on the concept of flux balance analysis. Another family of strain design methods, based on the concept of elementary mode analysis, has also been growing. Although the computation of elementary modes is hindered by computational complexity, recent breakthroughs have allowed applying elementary mode analysis at the genome scale. Here we review and compare strain design methods and look back at the last 10 years of in silico strain design with constraint-based models. We highlight some features of the different approaches and discuss the utilization of these methods in successful in vivo metabolic engineering applications.

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Computational strain design methods are divided into two main families.

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We trace the evolutionary history of these two families.

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Surveyed successful cases of model-guided strain design for industrial applications.

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Most proposed methods have not yet been tested in real applications.

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Agreement between in silico and in vivo results shows potential of tested methods.

RobOKoD: microbial strain design for (over)production of target compounds

Sustainable production of target compounds such as biofuels and high-value chemicals for pharmaceutical, agrochemical, and chemical industries is becoming an increasing priority given their current dependency upon diminishing petrochemical resources. Designing these strains is difficult, with current methods focusing primarily on knocking-out genes, dismissing other vital steps of strain design including the overexpression and dampening of genes. The design predictions from current methods also do not translate well-into successful strains in the laboratory. Here, we introduce RobOKoD (Robust, Overexpression, Knockout and Dampening), a method for predicting strain designs for overproduction of targets. The method uses flux variability analysis to profile each reaction within the system under differing production percentages of target-compound and biomass. Using these profiles, reactions are identified as potential knockout, overexpression, or dampening targets. The identified reactions are ranked according to their suitability, providing flexibility in strain design for users. The software was tested by designing a butanol-producing Escherichia coli strain, and was compared against the popular OptKnock and RobustKnock methods. RobOKoD shows favorable design predictions, when predictions from these methods are compared to a successful butanol-producing experimentally-validated strain. Overall RobOKoD provides users with rankings of predicted beneficial genetic interventions with which to support optimized strain design.

Synthetic scaffold based on a cohesin–dockerin interaction for improved production of 2,3-butanediol in Saccharomyces cerevisiae

Substrate channeling is a process of transferring an intermediate from one enzyme to the next enzyme without diffusion into the bulk phase, thereby leading to an enhanced reaction rate. Here, we newly designed substrate channeling modules in Saccharomyces cerevisiae based on a high affinity interaction between dockerin and cohesin domains, which is a key process in the formation of cellulosome structure. Synthetic scaffolds containing two, three, or seven cohesin domains were constructed, and the assembly of dockerin-tagged proteins onto the scaffolds was confirmed by pull-down assay and bimolecular fluorescent complementation (BiFC) assay in vivo. This system was applied to produce 2,3-butanediol in S. cerevisiae by using dockerin-tagged AlsS, AlsD, and Bdh1 enzymes, resulting in a gradual increase in 2,3-butanediol production depending on the number of cohesin domains in the scaffold.

Enhanced hexose fermentation by Saccharomyces cerevisiae through integration of stoichiometric modeling and genetic screening

In order to determine beneficial gene deletions for ethanol production by the yeast Saccharomyces cerevisiae, we performed an in silico gene deletion experiment based on a genome-scale metabolic model. Genes coding for two oxidative phosphorylation reactions (cytochrome c oxidase and ubiquinol cytochrome c reductase) were identified by the model-based simulation as potential deletion targets for enhancing ethanol production and maintaining acceptable overall growth rate in oxygen-limited conditions. Since the two target enzymes are composed of multiple subunits, we conducted a genetic screening study to evaluate the in silico results and compare the effect of deleting various portions of the respiratory enzyme complexes. Over two-thirds of the knockout mutants identified by the in silico study did exhibit experimental behavior in qualitative agreement with model predictions, but the exceptions illustrate the limitation of using a purely stoichiometric model-based approach. Furthermore, there was a substantial quantitative variation in phenotype among the various respiration-deficient mutants that were screened in this study, and three genes encoding respiratory enzyme subunits were identified as the best knockout targets for improving hexose fermentation in microaerobic conditions. Specifically, deletion of either COX9 or QCR9 resulted in higher ethanol production rates than the parental strain by 37% and 27%, respectively, with slight growth disadvantages. Also, deletion of QCR6 led to improved ethanol production rate by 24% with no growth disadvantage. The beneficial effects of these gene deletions were consistently demonstrated in different strain backgrounds and with four common hexoses. The combination of stoichiometric modeling and genetic screening using a systematic knockout collection was useful for narrowing a large set of gene targets and identifying targets of interest.

Multi-capillary column-ion mobility spectrometry of volatile metabolites emitted by Saccharomyces cerevisiae

Volatile organic compounds (VOCs) produced during microbial fermentations determine the flavor of fermented food and are of interest for the production of fragrances or food additives. However, the microbial synthesis of these compounds from simple carbon sources has not been well investigated so far. Here, we analyzed the headspace over glucose minimal salt medium cultures of Saccharomyces cerevisiae using multi-capillary column-ion mobility spectrometry (MCC-IMS). The high sensitivity and fast data acquisition of the MCC-IMS enabled online analysis of the fermentation off-gas and 19 specific signals were determined. To four of these volatile compounds, we could assign the metabolites ethanol, 2-pentanone, isobutyric acid, and 2,3-hexanedione by MCC-IMS measurements of pure standards and cross validation with thermal desorption-gas chromatography-mass spectrometry measurements. Despite the huge biochemical knowledge of the biochemistry of the model organism S. cerevisiae, only the biosynthetic pathways for ethanol and isobutyric acid are fully understood, demonstrating the considerable lack of research of volatile metabolites. As monitoring of VOCs produced during microbial fermentations can give valuable insight into the metabolic state of the organism, fast and non-invasive MCC-IMS analyses provide valuable data for process control.

2-Butanol and butanone production in Saccharomyces cerevisiae through combination of a B12 dependent dehydratase and a secondary alcohol dehydrogenase using a TEV-based expression system

2-Butanol and its chemical precursor butanone (methyl ethyl ketone – MEK) are chemicals with potential uses as biofuels and biocommodity chemicals. In order to produce 2-butanol, we have demonstrated the utility of using a TEV-protease based expression system to achieve equimolar expression of the individual subunits of the two protein complexes involved in the B₁₂-dependent dehydratase step (from the pdu-operon of Lactobacillus reuterii), which catalyze the conversion of meso-2,3-butanediol to butanone. We have furthermore identified a NADH dependent secondary alcohol dehydrogenase (Sadh from Gordonia sp.) able to catalyze the subsequent conversion of butanone to 2-butanol. A final concentration of 4±0.2 mg/L 2-butanol and 2±0.1 mg/L of butanone was found. A key factor for the production of 2-butanol was the availability of NADH, which was achieved by growing cells lacking the GPD1 and GPD2 isogenes under anaerobic conditions.

2,3-butanediol production from cellobiose by engineered Saccharomyces cerevisiae

Production of renewable fuels and chemicals from cellulosic biomass is a critical step towards energy sustainability and reduced greenhouse gas emissions. Microbial cells have been engineered for producing chemicals from cellulosic sugars. Among these chemicals, 2,3-butanediol (2,3-BDO) is a compound of interest due to its diverse applications. While microbial production of 2,3-BDO with high yields and productivities has been reported, there are concerns associated with utilization of potential pathogenic bacteria and inefficient utilization of cellulosic sugars. To address these problems, we engineered 2,3-BDO production in Saccharomyces cerevisiae, especially from cellobiose, a prevalent sugar in cellulosic hydrolysates. Specifically, we overexpressed alsS and alsD from Bacillus subtilis to convert pyruvate into 2,3-BDO via α-acetolactate and acetoin in an engineered cellobiose fermenting S. cerevisiae. Under oxygen-limited conditions, the resulting strain was able to produce 2,3-BDO. Still, major carbon flux went to ethanol, resulting in substantial amounts of ethanol produced as a byproduct. To enhance pyruvate flux to 2,3-BDO through elimination of the pyruvate decarboxylation reaction, we employed a deletion mutant of both PDC1 and PDC5 for producing 2,3-BDO. When a cellobiose utilization pathway, consisting of a cellobiose transporter and intracellular β-glucosidase, and the 2,3-BDO producing pathway were introduced in a pyruvate decarboxylase deletion mutant, the resulting strain produced 2,3-BDO without ethanol production from cellobiose under oxygen-limited conditions. A titer of 5.29 g/l 2,3-BDO with a productivity of 0.22 g/l h and yield of 0.29 g 2,3-BDO/g cellobiose was attained. These results suggest the possibility of producing 2,3-BDO safely and sustainably from cellulosic hydrolysates.

Metabolic engineering of Candida glabrata for diacetyl production

In this study, Candida glabrata, an efficient pyruvate-producing strain, was metabolically engineered for the production of the food ingredient diacetyl. A diacetyl biosynthetic pathway was reconstructed based on genetic modifications and medium optimization. The former included (i) channeling carbon flux into the diacetyl biosynthetic pathway by amplification of acetolactate synthase, (ii) elimination of the branched pathway of α-acetolactate by deleting the ILV5 gene, and (iii) restriction of diacetyl degradation by deleting the BDH gene. The resultant strain showed an almost 1∶1 co-production of α-acetolactate and diacetyl (0.95 g L(-1)). Furthermore, addition of Fe3+ to the medium enhanced the conversion of α-acetolactate to diacetyl and resulted in a two-fold increase in diacetyl production (2.1 g L(-1)). In addition, increased carbon flux was further channeled into diacetyl biosynthetic pathway and a titer of 4.7 g L(-1) of diacetyl was achieved by altering the vitamin level in the flask culture. Thus, this study illustrates that C. glabrata could be tailored as an attractive platform for enhanced biosynthesis of beneficial products from pyruvate by metabolic engineering strategies.