Metabolic Engineering and Cultivation Strategies for Recombinant Production of (R)-3-Hydroxybutyrate
Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Mariel Perez Zabaleta
KTH Royal Institute of Technology Stockholm, 2019
© Mariel Perez Zabaleta KTH Royal Institute of Technology School of Engineering Sciences in Chemistry, Biotechnology, and Health (CBH) Department of Industrial Biotechnology AlbaNova University Center SE-106 91 Stockholm, Sweden
TRITA-CBH-FOU-2019:20 ISBN: 978-91-7873-216-6 Printed by Universitetsservice US-AB 2019
To my grandma Mery Mercado
Abstract
Metabolic engineering and process engineering are two powerful disciplines to design and improve microbial processes for sustainable production of an extensive number of compounds ranging from chemicals to pharmaceuticals. The aim of this thesis was to synergistically combine these two disciplines to improve the production of a model chemical called (R)-3-hydroxybutyrate (3HB), which is a medium-value product with a stereocenter and two functional groups. These features make 3HB an interesting building block, especially for the pharmaceutical industry. Recombinant production of 3HB was achieved by expression of two enzymes from Halomonas boliviensis in the model microorganism Escherichia coli, which is a microbial cell factory with proven track record and abundant knowledge on its genome, metabolism and physiology. Investigations on cultivation strategies demonstrated that nitrogen- depleted conditions had the biggest impact on 3HB yields, while nitrogen- limited cultivations predominantly increased 3HB titers and volumetric productivities. To further increase 3HB production, metabolic engineering strategies were investigated to decrease byproduct formation, enhance NADPH availability and improve the overall 3HB-pathway activity. Overexpression of glucose-6-phosphate dehydrogenase (zwf) increased cofactor availability and together with the overexpression of acyl-CoA thioesterase YciA resulted in a 2.7-fold increase of the final 3HB concentration, 52% of the theoretical product yield and a high specific productivity (0.27 g g-1 h-1). In a parallel strategy, metabolic engineering and process design resulted in an E. coli BL21 strain with the hitherto highest reported volumetric 3HB productivity (1.52 g L-1 h-1) and concentration (16.3 g L-1) using recombinant production. The concepts developed in this thesis can be applied to industrial 3HB production processes, but also advance the knowledge base to benefit design and expansion of the product range of biorefineries. Keywords: Escherichia coli, (R)-3-hydroxybutyrate, nitrogen limitation, nitrogen depletion, lignocellulose, fed batch, acetate, β-ketothiolase, acetoacetyl-CoA reductase, Halomonas boliviensis. Sammanfattning
Metabolisk ingenjörskonst och processdesign är två discipliner för att skapa och förbättra mikrobiella processer för hållbar produktion av ett stort antal substanser, alltifrån kemikalier till läkemedel. Målet med denna avhandling var att kombinera dessa tekniker för att förbättra produktionen av modellkemikalien (R)-3-hydroxybutyrat (3HB), en mellanvärdesprodukt med ett stereocenter och två funktionella grupper. Dessa egenskaper gör 3HB till en intressant byggsten, speciellt för läkemedelsindustrin. Rekombinant produktion av 3HB uppnåddes genom utryck av två enzymer från Halomonas boliviensis i modellorganismen Escherichia coli, vilken är en välstuderad mikrobiell cellfabrik med tillgänglig detaljerad information om dess genom, metabolism och fysiologi. Genom att studera olika odlingsstrategier fanns att betingelser med helt förbrukat kväve (nitrogen depletion) hade störst inverkan på utbytet av 3HB, medan odlingar med begränsad mängd kväve (nitrogen limitation) huvudsakligen ökade slutkoncentrationen av 3HB och den volymetriska produktiviteten. För att ytterligare öka 3HB-produktionen användes metabolisk ingenjörskonst för att minska biprodukter, öka tillgängligheten av NADPH och öka den totala aktiviteten i reaktionerna för 3HB-produktion. Överuttryck av glukos-6-fosfatdehydrogenas (zwf) ökade kofaktortillgängligheten, vilket tillsammans med överuttryck av acyl-CoA tioesteras (yciA) resulterade i 2.7 gånger ökning av den slutgiltiga 3HB koncentrationen, med ett utbyte på 52 % av det maximala teoretiska utbytet och en hög specifik produktivitet (0.27 g g-1 h-1). Som en parallell strategi studerades effekten av att kombinera metabolisk ingenjörskonst och processdesign, vilket ledde till utvecklingen av en E. coli BL21-stam med den hittills högsta rapporterade volymetriska 3HB produktiviteten (1.52 g L-1 h-1) och koncentrationen (16.3 g L-1). Koncepten utvecklade i denna avhandling kan appliceras på industriella processer för 3HB produktion och även avancera kunskapsbasen för att gynna design och expansion av bioraffinaderiers produktutbud.
List of publications
This thesis is based on the following publications, which are referred to in the text by their roman numerals:
I. Jarmander J, Belotserkovsky J, Sjöberg G, Guevara-Martínez M, Perez-Zabaleta M, Quillaguamán J, Larsson G (2015) Cultivation strategies for production of (R)-3-hydroxybutyric acid from simultaneous consumption of glucose, xylose and arabinose by Escherichia coli. Microbial Cell Factories 14:51 II. Guevara-Martínez M, Sjöberg Gällnö K, Sjöberg G, Jarmander J, Perez-Zabaleta M, Quillaguamán J, Larsson G (2015) Regulating the production of (R)-3-hydroxybutyrate in Escherichia coli by N or P limitation. Frontiers in Microbiology 6:844 III. Perez-Zabaleta M, Sjöberg G, Guevara-Martínez M, Jarmander J, Gustavsson M, Quillaguamán J, Larsson G (2016) Increasing the production of (R)-3-hydroxybutyrate in recombinant Escherichia coli by improved cofactor supply. Microbial Cell Factories 15:91 IV. Guevara-Martínez M, Perez-Zabaleta M, Gustavsson M, Quillaguamán J, Larsson G, van Maris A J A (2019) The role of the acyl-CoA thioesterase ‘“YciA’” in the production of (R)-3- hydroxybutyrate by recombinant Escherichia coli. Applied Microbiology and Biotechnology 103:3693-3704 V. Perez-Zabaleta M, Guevara-Martínez M, Gustavsson M, Quillaguamán J, Larsson G, van Maris A J A (2019) Comparison of engineered Escherichia coli AF1000 and BL21 strains for (R)-3- hydroxybutyrate production in fed-batch cultivation. Accepted for publication in Applied Microbiology and Biotechnology
The author’s contribution
I. Contributed to the experimental work and revised the manuscript. II. Contributed to the experimental work and revised the manuscript. III. Designed and performed most of the experiments, wrote the manuscript. IV. Contributed to the experiments and the manuscript. V. Designed and performed the experiments, wrote the manuscript. Table of contents
1. INTRODUCTION ______1 1.1. Towards a Bioeconomy ______1 1.2. The biorefinery ______3 1.2.1. Lignocellulose-based biorefinery ______5 1.3. Products of microbial conversion in the biorefinery ____ 8 1.3.1. Biofuels ______10 1.3.2. Biopolymers ______13 1.3.3. Commodity chemicals and monomers ______15 1.3.4. Fine chemicals ______20 1.4. Improvement of microbial biorefinery processes ______23 1.4.1. Improvement by process engineering ______24 1.4.2. Improvement by cell factory design ______31 1.5. Opportunities and challenges ______44 2. PRESENT INVESTIGATION ______45 2.1. Aim of investigation ______45 2.2. Choice of the model product and production process __ 46 2.3. Choice of the model microorganism ______50 2.4. Design of concepts for improved 3HB production _____ 57 2.4.1. Extension of substrate range for 3HB production (Paper I) ______57 2.4.2. Influencing yield, titer and rate by cultivation strategies ______60 2.4.2.1. Nitrogen- or phosphorus-depleted cultivations (Paper I and Paper II) __ 60 2.4.2.2. Nitrogen- or phosphorus-limited cultivations (Paper I and Paper II) ____ 64 2.4.2.3. Minimizing NADPH consumption (Paper III) ______66 2.4.3. Influencing yield, titer and rate by metabolic engineering ______67 2.4.3.1. Enhancing cofactor supply to steer 3HB production (Paper III) ______67 2.4.3.2. Decreasing byproduct formation (Paper IV and Paper V) ______69 3. CONCLUSION AND FUTURE PERSPECTIVES ___ 85 4. ACKNOWLEDGEMENTS ______88 5. ABBREVIATIONS ______90 6. REFERENCES ______93 Mariel Perez-Zabaleta | 1
1. INTRODUCTION 1.1. Towards a Bioeconomy Since the beginning of the industrial revolution, society has become strongly dependent on the use of fossil resources. Petroleum is used for a wide range of purposes and the majority of fuels and chemicals that we use today are derived from it. For example in 2006, 95.8% of all organic chemical substances produced in Europe used fossil resources [1]. The petroleum refinery fractionates crude oil into different compounds ranging from petroleum gas, petrochemicals, gasoline, diesel to asphalt. The efficacy and wide range of products make petroleum refineries economically competitive. However, one problem that petroleum refineries face is price fluctuations, for example, the price changed from 146 US$/barrel in July 2008 to 36 US$/barrel in December of the same year and the average price in 2018 was 72 US$/barrel (Figure 1) [2, 3]. Petroleum prices have steadily increased since the first oil crisis in 1973 (Figure 1). The oil crises in 1973 and 1979 not only resulted in an increase in petroleum prices, but also resulted in a concern regarding oil dependence, in which renewable alternatives to produce fuels, heat and chemicals were considered. Recently, the concern on oil dependence was again raised with the debate regarding the peak oil, which is the point where the petroleum production will reach its maximum and thereafter the reserves of petroleum are expected to decrease [4]. Despite different opinions regarding the timing of peak oil, there is a global awareness that reserves of petroleum are finite. In 2017, globally proven oil reserves fell slightly by 0.5 billion barrels (-0.03%) to 1696.6 billion barrels, which would be sufficient to meet 50.2 years of global production at 2017 consumption levels [5]. However, the worldwide petroleum consumption still increases every year (Figure 1). Together, these trends gave rise to a desire to find alternatives for petroleum and thereby decrease oil dependence and develop a more sustainable economy.
2 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Price and consumption of crude oil per year 120 5000 4500
100 Consumption(MT) 4000 3500 80 3000
60 2500 2000 40 1500
Price (US$/barrel ) Price (US$/barrel 1000 20 500
0 0 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 Year Yearly average price (US$/barrel) Consumption (million tonnes) Figure 1. Average yearly price and consumption volume of crude oil from 1970 to 2018. The data from 1970 to 2017 were taken from the BP's oil prices [2] and the data for 2018 was taken from Business insider [3]. Worldwide consumption data from 1970 to 2017 were taken from BP [6]. Climate change is another concern that created an incentive to find renewable alternatives for the production of fuels, heat and chemicals. Increasing carbon emissions from the oil-based industries together with other factors, such as deforestation and fires, has led to an imbalance and an increase in the concentration of greenhouse gases in the atmosphere [7, 8]. In 2017, the yearly growth of global CO2 emissions was 1.6%, which was higher growth than the last 10-year average (1.3%) [9]. All the above-mentioned challenges have driven the development of a new economic model, “the Bioeconomy”, which has the potential to be more sustainable and environmentally friendly and in line with the “Global goals for sustainable development” set by United Nations [10]. The Bioeconomy is defined by the Organization for Economic Co-operation and Development (OECD) as the set of economic activities relating to the invention, development, production, and use of biological resources [11]. In other words, the Bioeconomy is an economic model that incentives to the use of biomass for efficient transformation into food, feed, bio-based products, energy and services for society by mechanical, chemical or biological processes [12]. The Bioeconomy is a part of a long-term sustainable circular economy (Figure 2, upper right). The development of a sustainable circular economy has different driving forces such as e.g. bioeconomy, food security and mitigation of climate change (Figure 2). All Mariel Perez-Zabaleta | 3
these forces connect to each other and are necessary to build a circular economy, in which the different players (government-academy-society) have an important role. This thesis aims to contribute to the expansion of the current knowledge on one of these goals: moving from a fossil-based economy to a bioeconomy (Figure 2, upper right).
Figure 2. Circular economy for long-term sustainable development. Figure adapted from Europe’s bioeconomy strategy, European commission (2018) [13]. 1.2. The biorefinery The Biorefinery has emerged as an important component of the bioeconomy to reduce oil dependence, with the intention of developing sustainable processes to efficiently convert biomass into a portfolio of marketable bio-based products (food and feed ingredients, chemicals, materials) and bioenergy (fuels, power, and heat) [14]. Biomass is essentially a renewable raw material and can be defined as the organic matter that has stored energy from the sun through the process of
4 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
photosynthesis. Biomass for the biorefinery is provided from four main sectors: agriculture, forestry, marine, and industry-domestic activities (Figure 3). Agriculture includes sugar crops (e.g. sugar-beet, sugarcane), starch crops (e.g. wheat, corn), lignocellulose crops (e.g. residues from cereal harvest) and plants grown as oil sources (e.g. soya, rapeseed). Forestry consists of lignocellulosic crops such as wood, poplar, switchgrass, and grass silage. Marine biomass comprises sources from fisheries, algae, and seaweed. The last sector includes a wide range of organic residues from industry or domestic activities, which can be oil residues (e.g. animal fat, cooking oil), lignocellulosic residues (e.g. saw mill residues) and organic-urban residues (e.g. vegetables residues, meat residues) [15].
Agriculture Forestry Marine Industry-domestic residues
Biomass
Suitable pre-treatment
Proteins Sugars Oils Lignin Fibres
Processes: mechanical/physical, chemical, biotechnological
Chemicals Materials Food Bioenergy e.g. aromatic e.g polymers, e.g. flavours, e.g. biodiesel, essences, paper, modified fodder, power, heat, pigments, wood, glues. bread. bioethanol. organic acids.
Figure 3. Classification of the biomass, processes, and products used/produced in the biorefineries. In the figure, a few examples of products of each category are presented. The general idea is that a biorefinery, like a petroleum refinery, creates maximal value from its feedstock (biomass) by converting it into multiple products ranging from high to low value. An example of Mariel Perez-Zabaleta | 5
biorefinery is dry-milling, in which the grain-feedstocks are hammer milled for the production of mainly ethanol and animal feed. In contrast, wet-milling is a superior type of biorefinery, which also uses grain as a raw material, but is designed to extract more of its components and at a higher value. For example, in wet-milling of corn, the grain is first soaked and then converted into several products such as starch, corn syrup, corn oil, gluten feed, ethanol, and corn meal [16]. In describing biorefineries, it is important to distinguish pre-treatment processes and production processes. In general, pre-treatment processes result in intermediate products, while production processes result in end-products. After a suitable pre-treatment of the biomass, its different components (e.g. oil, lignin, sugars) are separated and subsequently converted to final products by mechanical/physical, chemical and/or biotechnological processes (Figure 3). The first production-process category (mechanical/physical) uses techniques like mechanical extraction, fiber separation, pressing, disruption, mechanical fractionation. The second category transforms the different components of the biomass into end-products by chemicals processes such as extraction, esterification, hydrogenation, gasification, combustion, pyrolysis, etc. [15]. The third category is biotechnological conversion of the biomass components to valuable products with microorganisms or enzymes. In this distinguishes, when enzymes are used in the production step the biorefinery is named “enzymatic biorefinery”, while when microorganisms are used it is named “microbial biorefinery”. Possible end-products obtained by biorefineries are chemicals, food, materials and bioenergy (Figure 3). Whereas fossil-based refineries only use petroleum as the main substrate, the biorefinery can use a wide variety of biomass (Figure 3). Thus, biorefineries can use this advantage to compete with the fossil-based industry in the market by having a wide range of products manufactured from a wide range of renewable substrates [17]. 1.2.1. Lignocellulose-based biorefinery Lignocellulosic biomass is a carbon source that is abundantly available worldwide and has low prices compared to other feedstocks [18, 19]. Additionally, it is non-edible and it does not enter the debate of food versus fuel [20, 21]. Lignocellulosic biomass is composed of cellulose, hemicellulose, and lignin (Figure 4). Lignin is a crosslinked phenolic polymer that acts as a binder of the cellulose and hemicellulose and its
6 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
function is to provide rigidity and cohesion [22]. Hemicellulose is a branched polysaccharide that consists of pentoses (xylose and arabinose) and hexoses (glucose, galactose, and mannose). Cellulose is a homopolymer of β-D-glucopyranose (glucose) joined together by β-1,4 glycosidic bonds. The fraction of each component varies according with the lignocellulosic origin. Lignocellulose generally contains around 35-50% cellulose, around 20-35% hemicellulose and 10-25% lignin. The remaining fraction is usually proteins, oils, and ash [23]. The regeneration time also varies with the lignocellulosic origin, for example, lignocellulose from switchgrass reaches full maturity in three years, while lignocellulose from sugarcane takes about 12 to 18 months and lignocellulose from trees can take up to 20 years to mature [24, 25].
LIGNOCELLULOSIC-BIOMASS
Pre-Treatment
Lignin Hemicellulose Cellulose phenol pentoses, hexoses glucose polymer
Conversion Process
Separation and purification
Biobased products and Bioenergy
Figure 4. Principle of lignocellulosic-biomass biorefinery. Lignocellulosic-biomass can be obtained from agriculture, forestry, marine, and industry/domestic residues. Mariel Perez-Zabaleta | 7
The principle of lignocellulose-based biorefineries is presented in Figure 4. Lignocellulosic-biomass can be obtained from the different types of biomass, such as agriculture, forestry, marine, and industry-domestic residues (Figure 3). The first step of the lignocellulose-based biorefinery is pre-treatment of the biomass to obtain substrates that can be used in the conversion process (Figure 4). A successful example of a lignocellulosic biorefinery that mostly used mechanical conversion is production of lumber, paper and pulp from trees. To increase the diversity of products obtained from biorefineries, it is desirable to further fractionate the lignocellulose. However, the conversion of lignocellulose into easy-utilized sub-fractions is difficult due to its dense and heterogeneous structure. Depending on the type of lignocellulosic-biomass and the conversion process used, different pre-treatments are needed. These pre-treatments can be mechanical (e.g. milling), chemical (e.g. acid hydrolysis) or biological (e.g. enzymatic hydrolysis). A common type of pre-treatment, first fractionates the lignocellulose into its three major components: hemicellulose, cellulose and lignin. Generally, the lignocellulose treatment starts with a mechanical process like milling to reduce the particle size. Then lignin is separated from the other two polymers (cellulose and hemicellulose) since it is impenetrable by cellulolytic and hemicellulolytic enzymes. To separate the lignin, physical, chemical or physicochemical treatment can be applied, such as the use of an aqueous/organic solvent together with an inorganic acid at temperatures between 140 to 220 °C. This results in release of the lignin and three separate fractions are obtained: dry lignin, an aqueous phase of hemicellulose, and a relatively pure cellulose fraction [26, 27]. After separation of lignin, enzymatic or chemical hydrolysis can be used to convert cellulose and hemicellulose into C5 and C6 sugars. The use of enzymes is often more effective than the use of inorganic catalysts, because enzymes are highly specific and can work at mild process conditions [28]. The composition of sugars extracted after the pre-treatment of the lignocellulose depends on the type of resource used, but they are mainly D-glucose, D-xylose and L-arabinose. For example, hydrolyzed wheat straw result in a relative composition of 55.6% D- glucose, 37.6 % D-xylose, 4.1% L-arabinose and 2.7% other minor sugars [29]. After pretreatment, the next step is the conversion process (Figure 4). In the conversion step, sugars, and preferably also lignin, obtained from the lignocellulose are converted into valuable products. Microbial
8 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
conversion in the biorefinery is generally not able to use lignin, but this fraction can be used either in mechanical/physical or chemical conversions (Figure 3). For example, lignin can be chemically-converted into aromatic compounds, such as ferulic- and gallic acid [30, 31]. The sugars obtained from the hemicellulose and cellulose can be converted into a broad range of products. For example, xylose can be chemically converted by acid catalysis to furfural, which it is the precursor of furan resins [32]. These sugars can also be converted to several products like ethanol, polyhydroxyalkanoates (bioplastics) and organic acids by microbial processes. However, when these sugars are used in microbial-conversion processes, it is important to also consider inhibitory compounds formed during the degradation of hemicellulose and lignin. Lignin generates phenolic compounds such as vanillic acid, vanillin, syringic acid, or syringaldehyde, while presence of acetyl groups in the hemicellulose generates acetic acid. These are inhibitory compounds for the microorganisms and ideally their formation should be minimized. Removal of these inhibitors by detoxifying treatments, such as activated charcoal or membrane filtration, are cost-prohibitive and preferably must be avoided [33]. After the conversion process, the obtained products are separated and purified in the downstream processes in order to obtain biobased products or bioenergy (Figure 4). 1.3. Products of microbial conversion in the biorefinery This thesis focuses on microbial conversions in the biorefinery, which it is a sub-category of biotechnological biorefinery (Figure 3). Microbial biorefineries can be classified according to the type of biomass used in the process. First-generation biorefineries are based on easily utilized sugars, whilst second-generation biorefineries use lignocellulosic-biomass. Another type of microbial biorefineries is the third-generation, in which organisms like cyanobacteria or microalgae capture CO2 from the air or other sources and convert it directly to products by using sunlight as energy. Thus, lignocellulosic-biomass biorefineries using a microbial- conversion process are also called a second-generation biorefinery. Once the biomass is pre-treated, the next step is the conversion of the carbon source into valuable products (Figure 3, Figure 4), which in microbial biorefineries is performed by microorganisms. The Mariel Perez-Zabaleta | 9
microorganisms are cell-factories that can be improved and modified (e.g. genetic modification) according to the requirements of the process. An ideal microbial producer should (1) convert different substrates efficiently, (2) enable production at high concentration and have high tolerance to the product, (3) grow and/or produce the target compound at high rates, (4) have high production yields near to the theoretical-maximum. Furthermore, an ideal producing platform needs to be (5) genetically stable and (6) robust for a large-scale industrial process [34, 35]. Many different compounds can be produced by microbial biorefinery. Jullesson et al. [36] summarize and point out some important examples of different compounds produced by microorganisms, classifying them into four major categories: food, chemicals, biofuels, and pharmaceuticals (Figure 5). Inside each category, they distinguished the current stages of development of the products showing that several compounds are produced at small-scale with an early stage of development. However, other compounds such as artemisinin, vanillin, isobutanol and farnesene are produced at commercial scale with an established technology and advanced development (Figure 5). This figure presents the great variety of compounds that can be produced using cell factories in microbial biorefineries. A clear differentiation between chemicals, food and pharmaceuticals is sometimes difficult to make (Figure 5) since this categorization mainly depends on the product application and the same product can be considered either food, pharma or chemical. For example, lactic acid is considered a food product when it is used as e.g. food preservative, a pharma product when it is used as e.g. anti-caries agent or a chemical product if it is used for the synthesis of e.g. polymers and chemical- solvents. Therefore, this thesis will present the microbial biorefinery products in a different categorization: (i) biofuels, (ii) biopolymers, (iii) commodity chemicals and monomers, and (iv) fine chemicals. These four categories will be discussed and explained below by giving some examples of relevant accomplishment of biotechnology in each category.
10 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Figure 5. Overview of compounds produced by microorganisms in 2014. Compounds are classified in four categories: food, biofuel, chemicals and pharmaceuticals. Each category shows some examples of compounds produced by companies. Numbers represent the current stage of development: (1) small-scale, (2) pilot-scale, (3) commercial scale. Figure reprinted from Jullesson et al. (2015) [36] with permission from Elsevier.
1.3.1. Biofuels Biofuels have been produced by microorganisms since the early 1900s [37-39]. However, they have gained a greater interest worldwide in the last two decades, since their production helps to move from a fossil- based economy to a bioeconomy and also mitigate climate change. Biofuels serve as a renewable alternative to oil-based fuels in the transport sector and help to reduce greenhouse gas emissions and also improve supply security. Biofuel was defined by the European Commission on Energy as “liquid or gaseous transport fuels such as biodiesel and bioethanol, which are made from biomass” [40]. Ethanol, biogas and biodiesel are examples of well-studied and established biofuels. Ethanol is currently one of the main bio-combustibles used worldwide and its production in the United States surpassed 14.8 billion gallons in 2015 and by September 2018 the production increased to 16.7 billion gallons [41, 42]. Brazil is currently the world's second largest ethanol producer and, together with the United States, they share around 85% of the global production. The European Union is the third biggest producer of ethanol with 5% of the global Mariel Perez-Zabaleta | 11
production [43]. Several microorganisms have been studied for ethanol production, but Saccharomyces cerevisiae still remains as the prime species for industrial production [44]. Although ethanol is currently mainly produced from corn or sugarcane (first-generation biorefinery), a lot of effort and research was done the past years for second-generation ethanol production [45]. Industrial production of lignocellulosic ethanol has increased in the United States since 2014 and by September 2018 the second-generation ethanol production was 50 million gallons (0.05 billion gallons) [46]. However, the global production of second-generation ethanol is still below 1% of that of first-generation ethanol [47]. The major remaining limitation of second-generation biofuels is the pre-treatment of lignocellulose since it is a costly process and generates inhibitory degradation-products that lower titer, rate, and yield of biofuels. Ethanol has furthermore some disadvantages as biofuel, it is hygroscopic and it has a lower energy content (30 kJ g-1) than for example butanol (37 kJ g-1) or gasoline (47 kJ g-1) [35]. Compared to ethanol, butanol is less volatile and explosive, which makes it safer to handle. It is less hygroscopic, and it can be easily mixed with gasoline in any proportion. Butanol has been suggested as an alternative to replace gasoline because can be used in conventional combustion engines without modification [48]. Microbial production of butanol uses mainly Clostridia species and the most widely studied is Clostridium acetobutylicum [49, 50]. These microorganisms produce butanol from renewable resources by the acetone-butanol-ethanol (ABE) process (Figure 6). Typically, Clostridia strains produces a total concentration of solvents (acetone, butanol, and ethanol) of 20 g L-1, where the ratio of butanol, acetone, and ethanol is 6:3:1 respectively [51, 52]. The butanol titer of ca. 13 g L-1 is often the upper limit of tolerance of Clostridia strains [53]. The low tolerance to the product together with the byproduct formation make butanol yet too expensive as fuel and restrict its production to the fine chemical market [54]. Other examples of biofuel that are currently being development at lab scale and are still too expensive to compete with fossil-based fuels (with a few niche exceptions) are fatty acid methyl esters [55], alkanes [56], farnesane [57], and microbially produced biodiesel [58-60].
12 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Figure 6. Metabolic pathway for the production of butanol in the ABE fermentation process. Two phases of fermentation are present in the production of butanol: acid formation phase (green) and solvent formation phase (yellow). Figure credit Emply shell China dry CC BY-SA 4.0 (https://creativecommons.org/licenses/by-sa/4.0). The major hurdle of biofuel production is the price, which has to be very low to compete with fossil-based fuels. In order to have economically viable processes, low investment cost is required and operational cost need to be minimized, requiring continuous processes and low energy input. The raw material is a dominant part in the final cost; thus, substrates must be widely available at lower cost and an effective bioconversion of the substrate into the product is highly important to maximize the yield. Reduction of byproduct formation can help to increase the yield as well as the production rate and final concentrations. High final concentrations of the product are beneficial for the downstream process, which is one of the most expensive steps in the biorefinery, and high titers are related to high product tolerance. Thus, the desired microorganism for biofuel production should tolerate and produce the fuel at high levels. Biofuels production have many challenges to overcome, however, this Mariel Perez-Zabaleta | 13
stimulates and motivates the academy and the industry to new investigations and discoveries to advance the field. 1.3.2. Biopolymers A biopolymer is a macromolecule produced by living organisms, composed of one (homopolymer) or more (heteropolymers) chemical subunits (monomers) that are repeated throughout a chain. In this thesis, a synthetic biopolymer is defined as a polymer in which the microorganisms produce the monomers but do not polymerize them and the polymerization is subsequently done, e.g. in a chemical process. A natural biopolymer is defined in this thesis as a polymer in which the production of the monomer and the polymerization process are carried out by a microorganism. Numerous types of microbial biopolymers exist including polynucleotides, polypeptides, polysaccharides, polyesters, polyanhydrides and polyamides. In 2018, the global production capacities of bioplastics were 2.11 million tons [61]. Some examples of synthetic biopolymer are polyethylene made from bioethanol, polybutylene succinate made from succinic acid and polylactide (PLA) where the monomer is the lactic acid. Polylactide is a biopolymer that has gained considerable attention in the last decade mainly because of its application as packaging material, but it can also be used in the medical industry of devices in tissue engineering, surgical sutures and orthopedics devices [62, 63]. Polymerization of PLA does not naturally occur inside microorganisms; therefore, the first step of the production is microbial fermentation to produce lactic acid and subsequently, the second step is the physicochemical polymerization. One challenge of the production of PLA is the high purity of lactic acid required, which increases the final cost of the product. NatureWorks produces PLA on large scale since 2001. This company uses starch as a carbon source and lactic acid is polymerized by a melt process (condensation reaction typically conducted at 130-190 °C and produces water as a byproduct) [64].
14 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
R O
O n Figure 7. Chemical structure of polyhydroxyalkanoates (PHAs). PHAs are generally composed of (R)-β-hydroxy fatty acids, where (R) varies from methyl (C1) to tridecyl (C13). The best-known PHAs are poly(3-hydroxybutyrate) (PHB) (R = methyl) and poly(3- hydroxybutyrate-3-hydroxyvalerate) (P3HB-3HV) (R = methyl or ethyl) [65]. Specifically relevant in the context of this thesis are the polyhydroxyalkanoates (PHA) (Figure 7), which are biopolyesters naturally accumulated in some microorganisms when the carbon source is in excess and another nutrient is limited/depleted [66]. These natural biopolymers are biodegradable, biocompatible and have thermoplastic properties similar to petrochemical plastics. PHAs have diverse applications ranging from packaging, paints, and adhesives to medical applications, where they are used as artificial skin, drug delivery agent and to develop devices including surgical sutures, repair patches, slings, cardiovascular patches, orthopedic pins, adhesion barriers, stents, guided tissue repair/regeneration devices, articular cartilage repair devices, nerve guides, tendon repair devices, bone marrow scaffolds and wound dressings [65, 67]. There are over 150 known PHA copolymers found in the literature, resulting in an enormous diversity of material properties [68, 69]. According to the number of carbon atoms of the monomers, PHAs can be classified in short-chain-length, consisting of monomers having 3 to 5 carbon atoms, and medium-chain-length, consisting of monomers having 6 to 14 carbon atoms [70]. The most common and best studied PHA is poly(3-hydroxybutyrate) (PHB) and it is naturally produced by numerous bacterial strains such as Alcaligenes latus, Azotobacter vinelandii, Cupriavidus necator, Halomonas boliviensis [71-75]. Medium-chain- length PHAs can be naturally synthesize by Pseudomonas species such as P. putida and P. oleovorans, [76, 77]. More than 10 companies worldwide produced or are producing PHAs by microorganisms. PHA has been produced industrially since the 1980s and some of the pioneer industries in the field are Chemie Linz Mariel Perez-Zabaleta | 15
(Austria), ICI (UK), Metabolix (now known as yield10 Bioscience) (USA) and P&G (USA) [69]. Since the 1990s, the company Tepha Inc. (USA) produces medical devices using PHAs [78]. The economics of microbial production of biopolymers and specifically PHAs is largely dependent on the cost of the substrate, the pre- treatment of the biomass, the yields and production rates, and the downstream processing. Different attempts were proposed and studied to lower the price of PHAs and make them more industrially competitive. Some of these studies were focused on the cost of the carbon source since raw materials usually account for as much as 50% of the total cost. Therefore, lignocellulosic materials (e.g. grass) [79-81], food waste (e.g. bakery waste) [82], agricultural residues (e.g. bagasse) [83, 84] and activated sludges [85] have been used as substrates for the production of PHAs. Some processing cost such as the pre-treatment of the biomass or the sterilization of the medium are difficult to reduce unless robust strains that can grow rapidly under simple conditions are used. To overcome this problem, for example, it has been proposed to use Halomonas spp., which can grow in highly alkaline NaCl-rich medium under open and non-sterile conditions without danger of contamination [86]. However, these conditions (high NaCl concentrations, high alkalinity) can be corrosive and decrease the lifetime of steel equipment used in production. In general, downstream processing for PHA production is relatively complicated and costly, however, metabolic engineering has been performed to change bacterial cell shape, giving cells that can accumulate higher amounts of PHA, in which the recovery and separation process is also facilitated [87]. Despite all the efforts made to lower the costs of PHAs, these remain high compared to synthetic plastics. Currently, 1.4% of the bioplastics market for packaging is covered by PHAs [88]. However, PHAs are not common packaging plastics and they have the advantage of their physicochemical properties (wide medical applications and great variety) compared to petrochemical plastics, where quality parameters such as purity, monomer composition or biodegradability are more important than the final price. 1.3.3. Commodity chemicals and monomers For more than 150 years, the traditional chemical industry has been producing a huge variety of chemicals coming from mining and petroleum. A sustainable alternative to increase the competitiveness of the chemical industry is the microbial conversion of renewable resources into
16 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
chemicals. Chemicals can be classified in several categories one of which is commodity chemicals and they are chemicals produced in large quantities to satisfy global markets with relatively low prices and used for a large variety of applications [89]. There is a large list of commodity chemicals produced by microorganisms such as citric acid, lactic acid, succinic acid, and adipic acid [90]. Some of these commodity chemicals can be used as monomers to produce synthetic biopolymers. A monomer is a chemical compound that has at least two functional groups or reactive sites like alcohol, amine or carboxylic acid groups. Lactic acid and succinic acid are examples of commodity chemicals used as monomers for the production of biopolymers (polylactide and polybutylene succinate respectively). In addition to their application as monomers, both carboxylic acids are used as building blocks and are considered platform chemicals because they can be converted into a large number of products (Figure 8, Figure 9). Due to these wide applications and important properties, these two carboxylic acids belong to the “Top 10 biobased chemicals” list made by the US Department of Energy [91]. Lactic acid is used for the manufacture of several products in the food, pharmaceutical, cosmetic and chemical industries (Figure 8). It has two isomers, L and D, and lactic acid (L) is used in the food industry as emulsifier, acidulant, preservative, flavoring, and pH buffering agent [92, 93]. In the pharmaceutical industry, its sodium salts are used in dialysis applications, its calcium salts are used as anti-caries agents, and its polymer, PLA, is used as drug delivery agent. In the cosmetic industry, this acid is used as intermediate for the synthesis of additives in lotions and humectants, and ethyl lactate is an active ingredient in many anti-acne preparations. In the chemical industry, lactic acid is used for the synthesis of diverse products, which can be used as polymer (e.g. PLA), solvent (e.g. lactate esters), fluid for low-temperature heat-exchange (e.g. propylene glycol), additives in production of detergent and flocculants (e.g. acrylic acid) (Figure 8) [91, 93]. Bioproduction of lactic acid has been studied since the late 19th century and it is commercially produced by fermentation using lactic bacteria such as Lactobacillus delbrueckii, L. amylophilus, L. bulgaricusand, L. leichmanii [93, 94]. Lactobacillus species are natural producers and the homofermentative ones are preferred for commercial production, since the heterofermentative bacteria accumulate other compounds such as ethanol, succinic acid or acetic acid, lowering the yields [94, 95]. Lactobacillus species require complex medium and pH between Mariel Perez-Zabaleta | 17
5 to 7, which demand a pH titration during the whole fermentation. Commercial fermentations using homofermentative lactic bacteria give high yields of lactate salt, usually higher than 90%, and then these lactate salts are neutralized to give pure lactic acid. The neutralization process produces approximately 1 ton of gypsum for every ton of lactic acid, becoming a waste problem and increasing the final cost of lactic acid [91]. To solve this problem, recombinant S. cerevisiae or other yeasts are an alternative to produce lactic acid since they grow in minimal medium and naturally tolerates lower pH than lactic bacteria [96, 97]. Lactic acid is worldwide produced by several companies including Cargill/NatureWorks (USA), Archer Daniels Midland company (USA), Corbion (The Netherlands), Galactic S.A. (Belgium), and Musashino Chemical Co. Ltd. (China).
O O
HO O OR Lactate esters O OH 2,3-Pentadione
O OH Pyruvic acid OH O O Propylene glycol HO HO O OH Ethyl lactate O Lactic acid H Propylene oxide Acetaldehyde O OH O
O OH O Acrylic acid HO O n O O Polylactide (PLA) Figure 8. Lactic acid as platform chemical. The chemical compounds in the figure are some examples of the possible products synthesized from lactic acid.
18 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Succinic acid is another platform chemical, which can be converted into a huge variety of chemicals such as synthetic biopolymers (e.g. polybutylene succinate and polyamides), succinate esters, succinimide, succinonitrile, 1,2-butanediamine, and tetrahydrofuran (Figure 9) [98, 99]. Succinic acid production can be accomplished by natural producers (e.g. Actinobacillus succinogenes, Anaerobiospirillu succiniciproducens), however, most of them are not suitable for industrial production since they need complex media [100]. Recombinant production of succinic acid using microorganisms such as E. coli, S. cerevisiae, Yarrowia lipolytica, and Corynebacterium glutamicum has been proposed as an industrial alternative [101-104]. Since 2012, DSM-Roquette (joint venture Reverdia) commercialized succinic acid using an engineered S. cerevisiae and wheat starch as the carbon source [105]. Its plant is located in Cassano Spinola, Italy and it has a production capacity of 10 kilotons per year [106]. GC Innovation America (formerly Myriant Corporation) commercialized succinic acid since 2013, using a recombinant E. coli. This industry has a plant with a production capacity of 14 kilotons of succinic acid per year and it is located in Louisiana, USA [105, 107]. BASF/Corbion-Purac (joint venture Succinity) isolated a natural producer of succinic acid from bovine rumen, called Basfia succiniproducens. This strain was further engineered by the company to be used at industrial scale [108]. Its plant has a production capacity of 10 kilotons per year and it is located in Barcelona, Spain [109]. The largest plant of succinic acid was built by BioAmber in collaboration with Mitsui with a production capacity of 30 kilotons per year and it is located in Ontario, Canada. BioAmber/Mitsui has initially worked with E. coli but then they switched to Candida krusei as the producing microorganism [105]. However, none of the factories mentioned are running production at their maximum capacities because the market is currently not yet large enough and biobased succinic acid has to compete with succinic acid from petroleum. The total market demand of succinic acid was estimated around 50 kilotons in 2016 and it is expected to reach 94 kilotons by the end of 2025 [110]. Mariel Perez-Zabaleta | 19
Figure 9. Succinic acid as platform chemical. The chemical compounds in the figure are some examples of the possible products synthesized from succinic acid. Commodity chemicals and monomers are sold at high volumes and low prices, and to compete with the prices of chemicals from the petroleum industry, their final cost should be low enough to succeed in the market. The price is highly related to the yield and this parameter is the most important and critical indicator in the production of commodity chemicals. Less critical parameters, but still important to reduce the final cost of the product, are the titer and the productivity. Nevertheless, yield, titer and productivity are often connected and an improvement in one of them can have a positive impact on the other ones. In addition, a lower accumulation of byproducts also has a positive impact on the yield by prioritizing the conversion of the carbon source to the product. It is evident that reducing waste streams and in the case of acidic products, low pH fermentations that use less titrant favors the process economics. Most of the applications of the commodity chemicals do not require high purity levels of the product, which help to reduce processing cost. However, there are some exceptions (e.g. PLAs, PBS) where the purity is very important and an equilibrium between price/quality need to be found. There are several examples of successful bioproduction of commodity chemicals and
20 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
monomers such as lactic acid and succinic acid that inspire the industry and academia to continue progressing in this field. 1.3.4. Fine chemicals Fine chemicals are complex and pure chemical substances that are produced in limited quantities (less than 1000 metric tons per year) and due to their specific applications are usually sold for more than 10 US$/kg [89]. Fine chemicals can be synthesized by chemical or enzymatic reactions, or can be produced and extracted from living organisms such as plants and microorganisms. Fine chemicals can used directly or as building blocks to produce a wide variety of compounds in the pharmaceutical industry (e.g. antibiotics), in the agrochemical industry (e.g. fungicides) and in other specialty-chemical industries (e.g. electronic chemicals, catalyst, pigments and resins). Among these industries, the pharmaceutical industry is the most important for the manufacture of fine chemicals, since it is an industry with high sales but also very competitive, which demands a high expenditure in research to develop new pharmaceuticals or improve the existing ones [89]. To improve the competitiveness of its industries, the European Union has increased the industrial manufacture and research on novel and high-value fine chemicals in the last two decades [111, 112]. The number of chemicals recognized by the United States Department of Agriculture (USDA) as fine chemicals has rapidly increased from 1,800 in 2014 to 2,900 in 2016 [42]. Not only the amount of research or the number of fine chemicals has been increased in the last years, but also the market has grown throughout the 2000s (Table 1). The production of fine chemicals by the biobased industry increased at a much faster rate than its production by the petrochemical industry and by 2025, the USDA prediction is that the biobased production will be about 50% of the global market (Table 1).
Mariel Perez-Zabaleta | 21
Table 1. Global growth of the fine chemical market. The amounts are in billion U.S. dollars (bn US$). The data of 2025 was a prediction according to the compound annual growth rate (CAGR) percentage. In the table, `Total´ refer to the production of fine chemicals by the petrochemical and the biobased industry. Data adapted from USDA report (2008) and Pollak P. (2011) [89, 113].
Year 2005 2010 2025 Total Biobased Total Biobased Total Biobased Sector (bn US$) (bn US$) (bn US$) (bn US$) (bn US$) (bn US$) Fine 100 15 125 32 195 88-98 chemicals Microorganisms are widely used to produce numerous fine chemicals such as vitamins, antibiotics, hormones, vaccines, food supplements, pesticides etc. A successful example of a fine chemical production by microorganisms is artemisinin, which is an effective anti- malarial drug. This compound is a sesquiterpene lactone, naturally produced from plant Artemisia annua, however, the instability in price and supply of artemisinin by the plant extraction motivated industry and academia to develop alternative methods for its production [114]. Therefore since 2003, several studies have been performed by the University of California, Berkeley and the company Amyris Inc. Artemisinin can be produced through the mevalonate pathway in recombinant microorganisms such as S. cerevisiae and E. coli. After a great effort to optimize the production process by metabolic engineering and cultivation strategies, they achieved a successful production of artemisinic acid (artemisinin precursor) by overexpressing the mevalonate pathway and inserting a three-step oxidation pathway from A. annua in S. cerevisiae. The microbially produced artemisinic acid was subsequently purified and chemically converted to artemisinin [115-117]. This process was used to produce semi-synthetic artemisinin since 2013 by Amyris and Sanofi with the capacity to meet about one-third of global demand [114]. Due to the broad applications and great versatility of the terpenoids that result from the mevalonate pathway, Amyris investigated other possible high-value compounds that can be produced by engineering S. cerevisiae. Thereby, farnesyl diphosphate is considered a platform intermediate in the mevalonate pathway and depending on the metabolic engineering strategy used, compounds such as pharmaceuticals, biofuels, performance materials, adhesives, fragrances (e.g. limonene, geraniol, linalool), surfactants, stabilizers, oligomers, polymers, resins, foams, coatings, sealants, emulsifiers, vitamin precursors (e.g. β-carotene, ergosterol) and
22 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
crop-protection substances can be produced (Figure 10). Some commercially interesting fine chemicals inside the terpenoids family are taxadiene, squalene and β-farnesene (Figure 10). Taxadiene is a precursor for the synthesis of anti-cancer drug taxol. Squalene, commercially produced since 2011, is an important ingredient for cosmetic and personal care products [118, 119]. Farnesene can be hydrogenated to farnesane and used as biofuel with remarkable qualities, which can be mixed directly with diesel or jet fuel and does not require engine modifications and can be used in cold weathers [120]. Additionally, farnesane is used as fuel additive and in the manufacture of personal care products. It is industrially produced by Amyris Inc. using its patented yeast and sugar cane as the carbon source [121]. The production of these interesting fine chemicals provides a good example of how academia and industry can work together in this relatively new biotechnology approach to find alternatives to the traditional chemical production of fine chemicals. Glucose
Acetyl-CoA
Mevalonate pathway
Isopentenyl diphosphate Dimethylallyl diphosphate (IPP) (DMAPP)
Limonene, Geraniol, Geranyl pyrophosphate Linalool (GPP)
Farnesyl diphosphate Amorphadiene Squalene (FPP)
Ergosterol β-carotene Taxadiene β-farnesene Artemisinic acid
Figure 10. Biosynthesis of different terpenoids using the mevalonate pathway. As the world's population grows, the demand for fine chemicals also increases. Hence there is an urgent need to develop sustainable production Mariel Perez-Zabaleta | 23
processes that can satisfy the demand in terms of quantity, quality and specialty, where academia and industry frequently need to join forces to design commercially-competitive production of fine chemicals. These chemicals are usually subject to strict regulations before reach the market and behind each product, there is a great effort of research made. The market-selling price is important as in many other products; however, the quality and purity are even more important in this type of products. 1.4. Improvement of microbial biorefinery processes Several successful microbial-processes are currently used in the industry, however, there is a constant need to develop new and improved bioprocesses. In the optimization of bioprocesses, cultivations are evaluated using different process conditions such as strain background, medium composition, temperature, pH, etc. The performance of a production process is typically evaluated through three factors: titer, rate, and yield. Titer or concentration can be defined as the amount of a component per unit of volume (Ci, where ‘i’ can be cells, a product, a substrate, a byproduct, etc.). The rates are the parameters that show the production/consumption per unit of time, there are three main types: the specific rate, the volumetric rate and the total rate. In a microbial process, each cell is considered a cell factory that in optimal conditions has to be greatly productive, thus, the specific rate (qi, gi gcell h-1) can be defined as the amount of a component produced/consumed per gram of cells per unit of time. The specific production rate of cells is called the specific growth rate, it is represented by µ and its unit is h-1. Regularly, it is desired to improve the production/consumption rate per unit of volume and thus the volumetric rate (ri, gi L-1 h-1) is evaluated, it can be calculated by multiplying the specific rate of the component ‘i’ with the cell concentration (Equation 1). When it is desired to scale up a process, another important factor to evaluate is the total rate (Qi, gi h-1), which is defined as the amount of a component produced or consumed per unit of time in a particular operational system (e.g. bioreactor). The total rate can be calculated by multiplying the volumetric rate with the total volume of the cultivation broth (Equation 2). The yield (Yi/j, gi gj-1) is an important factor that shows the efficiency of a process by comparing two rates (Equation 3), for example the yield of product on substrate (Yp/s) is the grams of a product formed per grams of substrate consumed.
24 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
(1) � = � ∗ � (2) � = � ∗� = � ∗ � ∗ � (3) � / = = = Where ‘i’ and ‘j’ can for example be cells (x), a product (p), or a substrate (s). Cx is the grams of cells per unit of volume and V is the volume of the cultivation broth in the bioreactor. Titer, rate, and yield are key factors to develop commercially- competitive processes. In addition to these three factors, robustness and quality play also important roles in the production and improvement of a process. Robustness refers to the ability to maintain stable cultivation- parameters and phenotype of the cells when a process confronts diverse perturbations. A robust process should work at a selected range of conditions and be able to obtain the same results. Quality is the totality of characteristics of a product that satisfy specific user requirements and, in an ideal process, these characteristics should not have significant variations to achieve uniformity in the product. The improvement of titer, rate, yield, robustness and quality is of relevant importance to in the design of industrial bioprocesses and can be done through process engineering and/or cell engineering. 1.4.1. Improvement by process engineering Processing engineering can be used to enhance the titer, the rate, and the yield of a particular microbial process but in addition can also be used to improve the robustness and the quality. The design criteria and the actions taken to improve these five factors by process engineering vary depending on the process and the product. These design criteria are exemplified and discussed below. [1] Yield The yield is a main factor to improve in the manufacture of compounds with low prices and large production volume, in which the raw material takes generally an important part of the final cost. This is for example the case of commodity chemicals and biofuels where it is always desired to maximize the substrate conversion into the product since their prices should be as low as possible to compete with the petroleum industry. Frequently, the enhancement of the yield by process engineering starts Mariel Perez-Zabaleta | 25
from the selection of the feedstock since different carbon sources gives different yields. For example, in the production of ethanol, Brazil uses as the main feedstock sugarcane while USA uses corn and the yield of ethanol using sugar cane is much higher (664 gallons per acre) than the yield obtained using corn (354 gallons per acre) [122]. In both cases, S. cerevisiae is used for the microbial conversion of fermentable sugars into ethanol. USA and Brazil are the world’s largest producers of ethanol, but have great differences in their fermentation processes. In addition to the different feedstock used by each country, the main difference is the recycling of cells. Brazil uses a batch process with cell recycling that begins with concentrations of cells between 150 and 250 g L-1 [39]. This design criteria helps to increase the ethanol yield since less sugar was deviated to the formation of new cells and instead more sugar was available for the formation of ethanol [123]. Ethanol production is an anaerobic process that uses high concentration of sugars, around 200 g L-1 and at these sugar concentrations, the growth rate of S. cerevisiae is reduced due to a low water activity in the medium. A comparison study between continuous and batch fermentations with cell recycling in Brazil showed that batch fermentations give higher ethanol yields, thus more ethanol is produced and the process is less susceptible to bacterial and wild yeast contamination [124]. Another approach to increase the yield is reducing byproduct formation. Byproduct is a product derived from a process that is formed in addition to the main product. In the production of ethanol, the byproducts can be the cellular biomass, CO2, acetate, glycerol, 2,3-butanediol, and heat [125]. However, in the production of baker’s yeast, the cells are the product and ethanol is considered a byproduct. To avoid alcoholic fermentation in the production of bakers’ yeast, the design criterion is to use aerobic fed-batch cultivation where two factors are essential to obtain high yields: aerobic metabolism and control of glucose concentration (below 100 mg L-1) [126]. Ethanol is produced in yeast by the Crabtree effect when the growth rate is high or there is a high glucose concentration in the medium. The process starts with a batch set-up in which the growth rate is at the maximum, after that the growth is controlled (below the critical µ) by the limitation of the carbon source. By controlling the growth rate, oxygen limitation is avoided during the whole process. The process is performed until the bioreactor reaches its maximum oxygen transfer capacity. This procedure allows producing ca. 54 g of yeast dry mass per
26 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
100 g of sugars and less than 2 mL of ethanol per 100 g of glucose consumed [126]. [2] Titer The titer is strongly connected with yield and frequently the enhancement of the yield also results in enhancement of the final titer. Therefore, the previous examples presented for ethanol and baker’s yeast production are also valid to increase the final titers of the products. A high product titer is beneficial to the downstream processing where the separation and purification processes such as distillation and crystallization are facilitated by high product concentration, which consequently allow reducing costs. For example, industrial production of 1,3-propanediol (PDO) is not economically feasible if high titers are not present for the distillation process. The strain selection is an important factor to consider when final titers need to be improved in a process. In the case of PDO, a final concentration of around 60–70 g L-1 is usually tolerated by the natural producers while recombinant E. coli can tolerate more than 100 g L-1 [127, 128]. Several cultivation techniques including batch, fed batch and chemostat were evaluated for production of PDO [129-131]. By using continuous cultivation with cell immobilization, volumetric productivity was improved but not the final PDO concentration [132]. Among all the approaches used to improve PDO production, aerobic fed- batch cultivation using recombinant E. coli and glucose as the limiting nutrient resulted in the higher titer of 135 g L-1 and the higher volumetric productivity of 3.5 g L-1 h-1 (yield of 51% of the theoretical) [133]. Comparing these results with an anaerobic process (yield 55% of the theoretical and 78 g L-1 PDO) [127], the small reduction of the yield in aerobic fed batch was compensated with an almost two times higher concentration. Mariel Perez-Zabaleta | 27
[3] Rate: Total rate, volumetric rate and specific rate The production rates are very important parameters to show how much product is produced per unit of time. In most industrial processes, time is money since the faster the product leaves the factory, the faster will be the return of the investment and the lower will be the production cost due to lower storage cost, lower energy consumption, lower personnel cost, etc. The recycling of cells is a strategy to improve production rates since the cultivation starts with high-cell density maximizing the product produced per unit of time. It is commonly used in fermentation processes when the production of ATP per sugar is low, which causes low cellular production. Cell-recycling method can be used either in batch, fed batch and continuous cultivations. In cell-recycling batch or fed-batch cultivations, the process begins with high amount of cell from a previous cultivation. Cells need to be fully active after recycling and the number of recycles is an important element to study in the process development. A cell-recycling process might suffer the risk of contamination, a decreased viability or genetic instability (mutations related to the number of generations). In the production of beverage like beer or ethanol, cells are usually recycled five times [134]. In contrast, in the production of ethanol for biofuel use in Brazil, cells are recycled during the whole period of production (ca. nine months) where the ethanol yield is approximately the same. Cell-recycling can also be performed in continuous cultivations. In this process, the cells are separated from the outgoing flow and returned to the bioreactor, thus the processes work at higher cell concentrations increasing volumetric productions rates. This technique has been used to maximize rates in many processes including ethanol [135], lactic acid [136] and butanol [137]. In addition, continuous cultivations allow high volumetric productivities since the process does not have to be temporarily shut down avoiding unproductive time between batches, which includes the charge and discharge of the fermenter vessel, cleaning, sterilization, and re-start the process [138]. In addition to cell-recycling strategy, other strategies such as fed- bath cultivations can be used to increase production rates. For example, penicillin production was improved by using a fed-batch cultivation with a feed solution containing ammonia, glucose and phenylacetic acid, where the latter compound was used as product precursor and nitrogen and glucose limitation was used to induce the production. Since penicillin is a
28 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
secondary metabolite (non-growth coupled product), this process was designed with two-stage, a cells production phase and a penicillin production phase and the total production rate (Qp) was increased in 25% [139]. [4] Robustness In all industrial production, robust processes are desired to obtain the same results in a set of different conditions. In comparison to lab scale bioreactors, large bioreactors are more susceptible to problems such as oxygen transfer (oxygen concentration gradients), carbon dioxide removal, heat transfer (temperature gradients) and mixing that influence the previous conditions but also to the pH (titrant gradient) and concentrations of other compounds added to the bioreactor including concentration gradients of the limiting substrate. All these gradients are mainly related to the mixing time in the bioreactor, which can be improved e.g. by the type of impellers or the type of bioreactor used. Furthermore, it is very common that raw materials properties change depending on the period of the year or on the specific supplier and in all industrial processes raw material should be evaluated ahead of the production [140]. To design a robust process, a valid approach is to use a scale-down simulator system (lab/pilot simulator) to mimic all these changes presented in the large- scale bioreactor and evaluate them in a less expensive set-up (lab/pilot scale). As long as the lab-scale evaluation is performed in the same conditions as the large-scale (keeping the end in mind), this simulator can properly identify critical scale-up parameters and improvement factors that can be modified or more strictly controlled in the industrial process [141]. There are several factors that can be enhanced in a process such as poor mixing, high viscosity broth, cultivation medium, pH, temperature. For example, the variation of physical parameters such as temperature, pH, or aeration has been suggested as factors that can influence the cell membranes [142]. A change in the temperature can reduce the transport of products in the cells since the membrane changes from a liquid-crystalline bilayer to a more-ordered gel phase when the temperature decreases [143]. Another parameter influencing the outer membrane is the aeration, well- oxygenated conditions are known to increase the amount of fatty acids and this increases the rigidity of the membrane [144]. Producer cells need to be robust to encounter all these changes during the cultivation avoiding great impact on their performance and good examples of robust microorganisms Mariel Perez-Zabaleta | 29
for large-scale processes are S. cerevisiae and E. coli [145, 146]. Therefore, a more robust process is the synergy between the cultivation conditions, the production steps and the microbial producer. [5] Quality Quality is a crucial factor in microbial biorefinery products but it has a higher impact in the production of fine chemicals such as pharmaceuticals, in which the quality is by far more important than the final cost, the yield, the titer or the rate. The substrate has a large influence on the quality of the product and the selection of the raw material is an important design factor. In the production of high-value products that mainly have medical applications, such as insulin and hyaluronic acid, the price of the substrate is not as important as for cheaper products. Industrial production of recombinant human insulin using E. coli was brought to market in 1983 by the company Genentech [147]. The industrial production was performed in fed-batch cultivations, but this production system faced the problem of endotoxin contamination that lowers the product quality [148]. Endotoxins are lipopolysaccharides found in the outer membrane of gram-negative bacteria and have been associated with insulin resistance in humans [149]. To overcome this problem of quality, the endotoxins are removed in the downstream process. In addition to E. coli, S. cerevisiae has been used by Novo-Nordisk to industrially-produce human insulin. Continuous cultivation is frequently used in the industry to maintain constant quality since production is performed in steady state (constant cultivation parameters). However, in this approach, it is important to pay attention to the number of cell generations to avoid mutations or a reduced viability of cells, which can cause a fluctuation in the quality. Novo-Nordisk produces insulin with a constant quality using recombinant S. cerevisiae in continuous cultivation for 3 to 4 weeks. Another example where the quality is of high importance is in the production of hyaluronic acid, which is a commercially-valuable medical biopolymer used in eye surgery, implants, treatment of osteoarthritis and as scaffold in tissue engineering. Hyaluronic acid is a linear polymer composed of D-glucuronic acid and N-acetyl glucosamine [150], and it can be accumulated by natural producers in different length affecting the quality of the product. The preferred natural-producer is a homolactic bacterium Streptococcus equi, which can grow both anaerobically and aerobically. Given the high viscosity of hyaluronic acid, it is not possible to
30 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
obtain concentration higher than 10 g L-1, but due to its high value, quality rather than quantity has been the focus of process and strain development. The two key quality parameters in the production of hyaluronic acid are molecular weight distribution and purity [151]. To increase these two important factors during hyaluronic acid production, glucose-limited fed- batch were used. However, limitation of glucose negatively affected the quality and productivity of hyaluronic acid, which indicated that under glucose limited conditions, this product competes with the biomass formation [151]. Therefore, other cultivations techniques such as arginine- limited fed-batch were proposed to reduce biomass formation without reducing the supply of the precursors (glucose-6-phosphate and fructose- 6-phosphate) of hyaluronic acid. The highest specific hyaluronic acid productivities and the highest molecular weight (highest quality) were observed at low growth rates (Figure 11), where the growth was controlled either by arginine-limited fed-batch or changes in pH/temperature (Figure 11) [151].
Figure 11. Hyaluronic acid productivity and molecular weight at different growth rates. The growth rates were modified by changing temperature (range: 32–40°C) and pH (range: 6.3– 7.5) in complex medium (filled circle) and by arginine-limited fed-batch cultivation (filled squares). Figure reprinted from Chong et al. (2005) [151] with permission from Springer Nature. Mariel Perez-Zabaleta | 31
1.4.2. Improvement by cell factory design To improve a microbial process by cell factory design, it is essential to know the cell metabolism. In section 2.3 of this thesis, the central metabolism of E. coli will be explained in more detail, but for a practical explanation in this section, it is important to state that twelve precursors metabolites are needed to build a new cell and they are intermediates of three primary metabolic pathways in the cell: glycolysis, TCA cycle and the pentose phosphate pathway. A good understanding of the central metabolism of a producer-cell gives the possibility to design different metabolic strategies to e.g. insert a new metabolic pathway or to give a new-desired characteristic to the cell. Sometimes the microorganisms that naturally produce a compound are not suitable for industrial production. In this case, a model microorganism can be selected as platform cell in which the production pathway and other features are added to allow high production of the target compound. Depending on the process and the product, one model microorganism can be more suitable than the other. The most common model cells are [152-154]: • Bacteria: Escherichia coli • Yeast: Saccharomyces cerevisiae, Pichia pastoris • Mammalian cell: Chinese hamster ovary (CHO) cells Improvement of cellular function has been performed for several decades and the earliest examples date back to the use of random mutagenesis. Before the development of genetic technology tools, microorganisms were subjected to reagents or UV light to increase the mutation frequency. The mutated cells were subsequently screened for a desirable feature and an improved production phenotype was obtained. This approach was very popular and was applied extensively to industrial strains [155]. An example of UV random mutagenesis in Penicillium chrysogenum dates back to 1955 [156] and by this method penicillin production was increased 4000-fold (50 g L-1) compared to the original strain [157]. In the beginning of the 1950s, an laboratory evolution experiment using a microorganism was for the first time described by Novick and Szilard [158]. This approach used a specific selection pressure (low tryptophan concentration) to allow mutation of the strain and, under these conditions, the strain was cultivated for a longer time in a chemostat. This resulted in a strain more "fit" than the previous one. Nowadays, this mutation technique is mainly known as evolutionary engineering or
32 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
adaptive evolution. With the successive revolutionary advances in DNA- sequencing, sequence analysis and databases, the analyses of entire genomes were greatly improved and, in the latest 90s, a new cell-design approach was proposed that was named inverse metabolic engineering. This approach extended the use of random mutagenesis and adaptive evolution technologies by relating the phenotype variances with changes of genotype, which facilitated the rational reconstruction of an improved producer-cell via molecular biology [159]. The design of competitive production systems in microbial biorefinery would not be possible without a redesign of the microorganisms and in addition of the fields described above, metabolic engineering is an important field that has been greatly developed the last two decades. Metabolic engineering has been defined by J. E. Bailey (1991) as “the improvement of cellular activities by manipulations of enzymatic, transport, and regulatory functions of the cell with the use of recombinant DNA technology” [160]. An improved microorganism can be obtained by modifying cell function and metabolic pathways according to the requirements of the process [36]. For example, the expression of proteins can be regulated by varying promoter strengths, using inducible promoters, or varying ribosomal binding sites. Sometimes, a specific feature of an enzyme needs to be modified and this can be done by changes in the amino acid sequence or codon optimization. Cell function can also be altered by deleting or overexpressing native genes and expressing heterologous genes and this is usually performed by plasmid-based methods, which are good for ‘proof of principles’ during the early design stage. However, plasmid-based methods have limitation at industrial scale since they require selection markers (e.g. antibiotics), can cause a metabolic burden to the cells and have limited capacity for harboring genes. Therefore, chromosomal integration is a more desired method for cell-design in industry since it results in a more robust and genetically- stable strain. Since 2013, another important method that has gained great attention for gene editing is CRISPR/Cas9 systems (clustered regularly interspaced short palindromic repeats/CRISPR-associated proteins), which rapidly, easily and efficiently modify endogenous genes [161]. Metabolic engineering studies usually start with a review of the literature about the current knowledge of the metabolism and physiology of the microorganism of interest. The analysis of the potential genetic modifications can be performed by genome-scale metabolic models. These Mariel Perez-Zabaleta | 33
simulation-models provide a stoichiometric mathematical representation of thousands of metabolic reactions that occur in a cell. This information is extracted from databases such as Kyoto Encyclopedia of Genes and Genomes (KEGG), which is available for several organisms. With this information, constraint-based reconstruction and analysis (COBRA) methods such as metabolic flux analysis (MFA) are used to predict changes in the cell metabolism and simulate metabolic flux distributions. Additionally, different omics technologies (e.g. genomics, transcriptomics, metabolomics, proteomics, metagenomics) and bioinformatics studies such as phylogenetic studies, allow better understanding of the cell metabolism and they also help to evaluate the outcomes when the modifications are performed. Once the possible genetic modifications are identified, these alterations are designed and implemented in the target cells. The cell metabolism is a complex well-connected network and one modification can alter other metabolic reactions in the cell. Therefore, each potential modification in the cell needs to be carefully evaluated, always considering the final cultivation condition. Ideally, this assessment should be performed in three consecutive steps: (1) confirmation of genetic modification using methods such as SDS-PAGE, western blot or DNA sequencing, (2) evaluation of the cell functionality and the outcomes achieved by the redesigned cell and (3) evaluation of cell-robustness performed in the same conditions as the final set-up of the process. The cell improvement is considered successful if the potential modification fulfills the expectations, however, if not, the cycle starts again with the analysis of the possible genetic modifications. The cycle continues until an optimal result is achieved. The enhancement of a cell factory by metabolic engineering depends on the process as well as the desired features that want to be added to the microorganism. There are different types of enhancement that can be performed in the microorganisms [162], this thesis discusses the following four [1] introduction of new product formation pathways, [2] improvement of cultivation parameters (yield, titer, rate, quality, robustness), [3] substrate range extension, and [4] engineering the physiological response of the microbial host to a given set of environmental conditions. [1] Introduction of new product formation pathways Cell factories can be genetically modified to produce a vast range of compounds. Many microorganisms have been found to naturally
34 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
produce a wide variety of compounds. However, the production not always fulfills industrial demand and requirements. Frequently, the genetic optimization of natural producers is limited due to the lack of genetic tools and physiological knowledge. Therefore, in many cases, another microorganism is selected as a model system to incorporate in its metabolism new pathways. Synthetic biology, one of the tools of metabolic engineering, allows to optimize natural enzymes or create new enzymes, which allows having an even larger list of compounds produced by microorganisms [163]. One example of the introduction of pathways is the production of artemisinic acid, which is the precursor of the antimalaria drug artemisinin and for its industrial production, S. cerevisiae was selected as the model system. Several metabolic engineering strategies have been applied to this microorganism to achieve a successful industrial production and since artemisinic acid is not naturally produced by S. cerevisiae the first strategy was to insert the necessary genes for its production. Artemisinic acid was produced through the mevalonate pathway and its precursor was farnesyl diphosphate, which was also precursor of several more compounds including squalene (Figure 12). S. cerevisiae has this pathway in its metabolism but it lacks the genes involved in the conversion of farnesyl diphosphate into artemisinic acid. Therefore, six genes encoding the respective enzymes (ADS, CYP71AV1, CPR1, CYB5, ADH1 and ALDH1) from A. annua (natural producer) were codon optimized and expressed in S. cerevisiae (Figure 12). The enzyme Ads convert farnesyl diphosphate in amorphadiene, subsequently Cyp71Av1, Cpr1 and Cyb5 catalyze the reaction of amorphadiene to artemisinic alcohol, which was then oxidized to artemisinic aldehyde by Adh1 and the aldehyde was finally oxidized to artemisinic acid by Aldh1 [116, 117]. In artemisinic acid production by S. cerevisiae, the main pathway that competes for the farnesyl diphosphate was the biosynthesis of sterols such as squalene. The first step in this pathway was catalyzed by squalene synthase, which converts two molecules of farnesyl diphosphate into squalene in a two-step reaction. Sometimes byproduct formation can be reduced by deleting the genes involved in the competitive pathway, but in other cases as the production of artemisinic acid, the stringent regulation systems of the cells do not allow the deletion. The intermediate products of the mevalonate pathway are essential in S. cerevisiae and deletion of squalene synthase can result in cell death [164]. Therefore, to redirect the consumption of farnesyl Mariel Perez-Zabaleta | 35
diphosphate to mainly artemisinic-acid, the expression of squalene synthase was repressed by replacing the natural promoter, firstly, to a methionine-regulated promoter and then to a copper-regulated promoter since the use of a copper salt to regulate the expression is cheaper than the use of methionine [116, 165, 166]. This metabolic engineering technique resulted in an increase of two-fold in the production of amorphadiene [165]. For a further improvement, the activity of the mevalonate pathway was increased by overexpressing each of the eight involved genes in this pathway, which resulted in 2-fold increase of artemisinic acid [117]. This efficient biosynthetic route in S. cerevisiae achieved fermentation titers of 25 g L-1 of artemisinic acid [116].
IDI1 Glucose Acetyl-CoA Isopentenyl-2-P Dimethylallyl-2-P Glycolysis Mevalonate (IPP) (DMAPP) pathway Geranyl pyrophosphate (GPP) Copper/methionine ERG20
Ergosterol Squalene Farnesyl-2-P PCRT3-ERG9 (FPP) PMET3-ERG9 ADS Amorphadiene CYP71AV1, CPR1, CYB5 Artemisinic alcohol ADH1 Artemisinic aldehyde ALDH1
Artemisinic acid
Figure 12. Artemisinic acid production pathway in S. cerevisiae. Copper or methionine repressed squalene synthase (ERG9). ADS from A. annua convert farnesyl diphosphate in amorphadiene Three-step oxidation of amorphadiene to artemisinic acid from A. annua was expressed in S. cerevisiae. Cyp71av1, Cpr1 and Cyb5 oxidize amorphadiene to artemisinic alcohol, Adh1 oxidizes artemisinic alcohol to artemisinic aldehyde and Aldh1 oxidizes artemisinic aldehyde to artemisinic acid.
36 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
[2] Improvement of cultivation parameters (yield, titer, rate, quality, robustness) Metabolic pathways of a target compound can be engineered and optimized to increase titers, rates, yields, quality of the product and robustness of the strain. These improvements usually have positive impacts on the economy of the process and even if the yield is very close to the maximum theoretical, it is feasible to further increase the productivity or the titer. This improvement can be achieved for example by reducing byproduct formation, which competes for the substrate affecting not just the yield but also the production rates and final concentrations. In some cases, byproducts can be inhibitors causing even higher perturbations in the cells as e.g. low growth rates and low substrate-uptake rates. Production of L-lysine is an interesting example to show different metabolic strategies. L-lysine is an essential amino acid that is widely used in animal feed in swine and poultry production. Lysine is mainly produced by Corynebacterium glutamicum, which is a natural-producer microorganism. Large-scale production of this amino acid started as early as 1958, since then, the process has been constantly improved by cell- design and process engineering [167]. The first improvement of this strain was in 1961 by random mutagenesis, in which the yield was increased from 0.26 g g-1 to 0.29 g g-1 and the final concentration of lysine obtained was 53.2 g L-1 [168]. Normally, cells do not overproduce amino acids, since they are required for the formation of new cells and their productions are strictly regulated in the cell metabolism. The first feedback control that regulates lysine production is allosteric inhibition of aspartate kinase (lysC) by L-lysine or L-threonine [169]. Due to its importance in flux control of lysine production, the strict control of aspartate kinase needs to be removed (Figure 13). More than twelve patented mutations were proposed to change the β-domain structure of this protein (lysC), which resulted in a higher yield (0.5 g g-1) and a final lysine concentration of 100 g L-1 [168]. Mariel Perez-Zabaleta | 37
Glucose
Glyceraldehyde-3P Dihydroxyacetone
BIOMASS Phosphoenolpyruvate pyk Glutamate CO2 Pyruvate NADPH pck NH3 Isocitrate ppc pyc NADPH α-Ketoglutarate CO2 Citrate Acetyl-CoA CO2
NADH CO2 Aspartate Glyoxalate Oxaloacetate Succinate-CoA lysC NADH Asparatyl-P NADPH Malate Succinate Aspartatesemialdehyde
Fumarate Dihydrodipicolinate FADH2 NADPH Piperideine dicarboxilate NADPH
Lysine Diaminopimelate lysE
L-Lysine Figure 13. Production pathway of lysine in Corynebacterium glutamicum. Main metabolite precursor of lysine is oxaloacetate (green). In pink are showed important genes for production of lysine, aspartate kinase (lysC), lysine exporter (lysE), phosphoenolpyruvate carboxylase (ppc), phosphoenolpyruvate carboxykinase (pck), pyruvate carboxylase (pyc), pyruvate kinase (pyk) [168]. The precursor of lysine is oxaloacetate and this metabolite is at a node of multiple reactions (Figure 13). To increase lysine production, this node has been subject of multiple modifications where the enzymes PEP carboxylase (ppc), PEP carboxykinase (pck) and pyruvate carboxylase (pyc) were deleted and/or overexpressed (Figure 13). The impact of these modifications on lysine production was evaluated and it has been
38 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
concluded that a higher lysine production is obtained when ppc and pyc are overexpressed, while pck is deleted [168]. In all recombinant production systems, an important point to consider in the design of the process is the export mechanism of the product from the cell. In some cases, the export occurs by passive diffusion (no specific transporter needed), while in other cases as the lysine, a specific carrier is required to export the product to the medium. The specific carrier in C. glutamicum is LysE and is naturally able to export lysine in an unidirectional way, which prevents re-consumption of lysine [168]. [3] Substrate range extension The use of lignocellulose as substrate is highly desired in industrial processes due to its positive impact on the process cost. However, few microorganisms can metabolize this raw material and consequently lignocellulose has not been extensively used by industries to date. The pretreatment of lignocellulosic biomass yields diverse components in which glucose and xylose are the main products and other sugars such as arabinose are formed in low amounts. In many bacteria including E. coli, certain sugars are preferably consumed before others, which result in a sequential sugar consumption. Depending of the sugars present in the medium, there are different mechanisms to control the sugar uptake. In the case of the lignocellulosic sugars (glucose, xylose and arabinose), there are two layers of control in E. coli, one global control that regulates the uptake of other sugars when glucose is present in the medium and a secondary layer that controls the uptake of xylose when arabinose is present in the medium. The global control of glucose that regulates sugar uptake is called carbon catabolite repression (CCR), which in E. coli also involves the inducer exclusion mechanism. Both regulatory systems involve the phosphoenolpyruvate (PEP): carbohydrate phosphotransferase system (PTS) (Figure 14). The PTS is initiated by the transfer of the phosphate group from PEP to carbohydrate-specific enzyme I (EI), followed by a chain of phosphorylation and ending with the phosphorylation of the sugar (Figure 14). The carbohydrate-specific enzyme II (EII) phosphorylates the respective sugar as it passes the cell membrane. The EII is a regulatory enzyme that consists of several domains, which often are encoded as separate proteins. In the specific case of the glucose PTS system, EII is divided in three proteins EIIAGlc, EIIBGlc and EIICGlc (Figure 14). When Mariel Perez-Zabaleta | 39
glucose is in excess, EIIAGlc is mainly present in the unphosphorylated form, while when there is no glucose in the medium, phosphorylated EIIAGlc is present at higher levels. The unphosphorylated or phosphorylated form of EIIAGlc regulates the uptake of other sugars in relation to presence/absence of glucose by the two previously mentioned mechanisms, carbon catabolite repression and inducer exclusion [170]. Carbon catabolite repression (CCR) is a regulatory mechanism that inhibits the expression of genes needed for the use of secondary carbon sources when a preferred carbon source (glucose) is present. The transcription of these genes requires activation of a complex formed by cyclic adenosine monophosphate (cAMP) and the catabolite activator protein (CAP). The cAMP is produced by adenylate cyclase, which requires activation from phosphorylated EIIAGlc. When glucose is present, as it was stated before, there are a lower amount of phosphorylated EIIAGlc and therefore levels of cAMP will be low. In line with these low levels of cAMP, gene expression will consequently be repressed by lower levels of the complex cAMP-CAP. The second regulatory mechanism is inducer exclusion, here, the unphosphorylated EIIAGlc binds and inactivate enzymes required for the uptake of secondary carbon sources by sterically blocking their permeases, kinases and/or ATP-binding cassette (ABC) transporters [170].
40 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Figure 14. Phosphoenolpyruvate (PEP): carbohydrate phosphotransferase system (PTS) in E. coli and regulation of sugar uptake by carbon catabolite repression and inducer exclusion. In the PEP: PTS, PEP functions as phosphoryl donor for the phosphorylation cascade formed by the proteins EI, HPr, EIIA and EIIB and also provides the energy for the transport step catalyzed by the membrane-bound EIIC. Unphosphorylated EIIAGlc inhibits uptake of secondary sugars by sterically blocking their respective permeases, transporters, or kinases. Phosphorylated EIIAGlc further activates Adenylate Cyclase (AC) to produce cyclic adenosine monophosphate (cAMP), and form the complex cAMP-CAP that actives transcription of catabolite-repressed genes. Figure reprinted from Deutscher (2008) [170] with permission from Elsevier. In addition to these regulatory systems, there are other regulatory mechanisms in bacteria that restrict the consumption of one carbon source over another. In E. coli, xylose uptake is regulated by the activation of the complex xylose-XylR, which subsequently activates the transcription of the xylFGH, xylR, xylAB and xylE operon (Figure 15). The arabinose uptake has a similar mechanism, where arabinose in complex with the AraC protein activates the transcription of the araBAD, araFGH and araE operon (Figure 15) [171]. In addition, the arabinose-AraC complex has been suggested to repress the transcription of the xylose operon [171]. Therefore, when xylose and arabinose are available in the medium, E. coli first consumes arabinose and then xylose. Thereby, E. coli consumes sugars hierarchically in order of glucose> arabinose>xylose, creating a diauxic growth pattern. Mariel Perez-Zabaleta | 41
Figure 15. Xylose and arabinose operons. The complex xylose-XylR is suggested to be an activator of the xylose operon, while arabinose-AraC complex is the activator of the arabinose operon. Arabinose–AraC is suggested to repress transcription of xylose operon. Figure reprinted from Jarmander et al. (2014) [172] with permission from John Wiley and Sons. In other microorganisms such S. cerevisiae, the sugar uptake is controlled by changes in the affinity of the corresponding transporters and by several signaling and metabolic interactions that regulate transcriptional, post-transcriptional and post-translational levels [173, 174]. Wild-type S. cerevisiae can utilize sugars such as glucose, sucrose, maltose but not arabinose or xylose. To improve the efficiency of second-generation processes, simultaneous or a fast-sequential utilization of sugars derived from lignocellulosic biomass is required. To overcome the problem of slow co- consumption or incomplete consumption of specific sugars, metabolic engineering and adaptive evolution can be used to add the desired features to the microorganisms. Extension of the substrate range has been extensively studied and one example is an engineered S. cerevisiae strain able to ferment a mixture of glucose, xylose and arabinose and produce ethanol at high yields. To obtain this engineered strain three strategies were combined (Figure 16): (i) Expression of L-arabinose isomerase (araA), L-ribulokinase (araB), and L-ribulose-5-phosphate epimerase (araD) genes from Lactobacillus plantarum for arabinose consumption.
42 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
(ii) Overexpression of native S. cerevisiae gene xylulokinase (XKS1) and xylose isomerase (xylA) from Piromyces sp. strain E2, for xylose consumption. (iii) Evolutionary engineering [175]. The evolutionary engineering strategy consisted of two steps: a prolonged chemostat cultivation on xylose-arabinose medium and a selective repeated batch cultivation designed with three consecutive phases containing medium of glucose-xylose-arabinose, xylose-arabinose and arabinose, which gave an equal selection pressure on the utilization of three sugars. This evolutionary strategy together with the genes overexpression and genes insertion resulted in an engineered S. cerevisiae with fast-sequential consumption of the three sugar at high rates and high ethanol yield (0.43 g g−1 of total sugar) without formation of the side products xylitol and arabinitol [176].
Figure 16. Metabolism of engineered S. cerevisiae strains described in the literature for consumption of D-xylose and L-arabinose. Abbreviations: aldose/xylose reductase (GRE3/XYL1), xylitol dehydrogenase (XYL2), xylulokinase (XKS1), D-xylose isomerase (xylA), arabinitol 4-dehydrogenase (lad1), L-xylulose reductase (lxr1), L-arabinose isomerase (araA), L-ribulokinase (araB), L-ribulose-5-phosphate 4-epimerase (araD), transaldolase (TAL1), transketolase (TKL1), D-ribulose-5-phosphate 3-epimerase (RPE1), ribose-5- phosphate ketol-isomerase (RKI1), PEP (phosphoenolpyruvate). Figure reprinted from Wisselink et al. (2007) [175] with permission from American Society for Microbiology.
Mariel Perez-Zabaleta | 43
[4] Engineering the physiological response of the microbial host to a given set of environmental conditions In addition to the improvements mentioned before, there are other interesting features that can be inserted to engineered microorganisms to enhance even more the titers, yields and production rates. Microorganisms with robust phenotypes that tolerate harsh industrial condition such as high product concentration, low pH, high or low temperatures, inhibitors provide an alternative to enhance production [177]. The pretreatment of lignocellulosic biomass, generates inhibitors including acetic acid, phenolic and furfural compounds. These inhibitors have been studied and target of tolerance engineering in microorganisms. For example, the expression of a transaldolase and an aldehyde dehydrogenase increased the tolerance to furfural and resulted in an increased ethanol production [178]. Acetic acid is another inhibitor released during the hydrolysis of lignocellulose from the acetyl group of hemicelluloses that causes growth inhibition in several microorganisms. To increase acetic acid tolerance in S. cerevisiae, an evolutionary engineering strategy was proposed, which consist of serial microaerobic batch cultivation where the presence and absence of acetic acid were alternated in cultivation cycles. This strategy yielded an evolved S. cerevisiae strain with constitutive acetic acid tolerance that can be used in the production of second-generation ethanol [179].
44 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
1.5. Opportunities and challenges The bioeconomy is gaining global attention as a sustainable economic model and one of its driving forces is the microbial biorefinery. This versatile field gives many opportunities, such as the use and conversion of a wide variety of renewable potential feedstocks into a wide spectrum of valuable products ranging from biofuels to pharmaceuticals. Developments in this field are supported by rapid advances in molecular biology, which make it possible to develop new with completely redrawn metabolic pathways resulting in new and improved products. Optimal production processes require the integration of metabolic engineering with optimized cultivations strategies. However, to fulfil their full potential, microbial biorefineries still have some challenges to overcome and the most important one is to achieve economic competitiveness, especially with petrochemistry-based products. This means that among all the possible products in microbial biorefineries, it will be more difficult for the low-cost products to reach the market. Microbial biorefinery processes contain a large amount of water and the products are too dilute compared to the petrochemistry industry. Therefore, the target is, in any case, the improvement of the process to obtain the highest possible titers, yields, and production rates. Additionally, the cost of the feedstock is also a crucial factor for economically-viable processes, in which its impact is higher in low-cost products. Compared to traditional processes, development of microbial products often takes significantly longer time from proof-of-principle to the market. In microbial process, the design criteria such as strain, production process, downstream process and feedstock, should always represent the most favorable conditions from an economic point of view and also in terms of process scalability. It is only in this way that information obtained in small-scale processes can be applied to large-scale industrial processes. To realize the great potential of the biotechnology field not only research and development, but also training and education in the design of sustainable, robust and scalable strains and processes are essential.
Mariel Perez-Zabaleta | 45
2. PRESENT INVESTIGATION 2.1. Aim of investigation The aim of this thesis was to use present developments in metabolic engineering in synergy with process engineering to design a production process of a medium-value chemical, leading to a proof-of-principles for a potential commercial production process. The selected model product was (R)-3-hydroxybutyrate, a biocompatible chemical with a stereocenter and two functional groups, which is a potential building block for synthesis of a wide range of sustainable products. To design a microbial system for the production of (R)-3-hydroxybutyrate, a set of genes from a native producer was introduced in the model microorganism Escherichia coli. To improve titer, yield and rate of (R)-3-hydroxybutyrate production in a scalable manner, different process- and metabolic-engineering strategies were designed and proposed. Special attention was paid to the use of concepts that can be translated to economically-viable industrial production. The strategies and concepts proposed in this thesis, might also be applicable to the bioproduction of other products, such as carboxylic acids and poly(3- hydroxybutyrate).
46 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
2.2. Choice of the model product and production process The design of a process should be opposite to the process flow [141], i.e. the design should begin with the end, (i) selection of the desired product, (ii) design of the downstream process, (iii) design of the production process, (iv) selection of the potential producer (model microorganism), (v) selection of the feedstock. However, these five design criteria are interconnected and for example the selection of substrate cannot be made without considering downstream processing or the robustness of the strain. Only when these aspects are properly addressed, the bioprocess has the potential to be economically viable for industrial production. In this thesis, the selected model product is (R)-3-hydroxybutyrate (3HB), a biocompatible molecule with a stereocenter and two functional groups, a hydroxyl-group and a carboxyl-group (Figure 17). These properties make 3HB a potential building block for synthesis of several chemicals, such as vitamins, antibiotics (e.g. b-lactams and thienamycin), nutraceuticals, flavors and pheromones [180-183]. Additionally, 3HB can directly be used as neuroprotector in the treatment or prevention of Parkinson’s and Alzheimer’s diseases [184-186], in the treatment of epilepsy due to its anticonvulsant and anti-epileptogenic effects [187, 188], to treat type 2 diabetes [189], to prevent myocardial damage after coronary occlusion [190], to increase calcium deposition with a positive anti- osteoporosis effect [191], and to increase survivability of hemorrhagic shock [192]. Moreover, 3HB is the monomer of the well-studied biodegradable polymer poly(3-hydroxybutyrate) (PHB) and it can also be used in the synthesis of polyhydroxyalkanoates (PHA). OH O
H C O- 3 Figure 17. Chemical structure of (R)-3-hydroxybutyrate [193]. Mariel Perez-Zabaleta | 47
This valuable chemical, 3-hydroxybutyrate, can be synthesized by different methods including (i) chemical synthesis, which needs a chiral precursor and an expensive metal-complex catalyst [194], (ii) enzymatic synthesis where the product is isolated as methyl ester [195], (iii) chemical depolymerization where purified PHB is depolymerized to 3HB by e.g. acidic alcoholysis [196-198], (iv) enzymatic depolymerization of PHB in vitro, which uses pure PHB as substrate and PHA depolymerase as catalysts [199], (v) enzymatic depolymerization of PHB in vivo, in this process, PHB is first produced by the natural producer and then depolymerization is induced by modifying environmental conditions in the bioreactor (e.g. low pH, microaerobic conditions) [200, 201], and (vi) microbial production by metabolic engineering approaches, which uses engineered microorganisms with diverse pathways to obtain extracellular 3HB (Figure 18). For example, 3HB was produced when genes from the PHB pathway (β-ketothiolase, acetoacetyl-CoA reductase and PHA polymerase) together with the PHA depolymerase gene from Cupriavidus necator (formerly known as Ralstonia eutropha) were inserted in E. coli (Figure 18, option 1) [202]. Alternatively, 3HB can be directly produced from 3HB-CoA, without going through PHB formation (Figure 18, option 2 and 3) [203-205].
48 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
glucose
glucose-6-P glycolysis
pyruvate
acetyl-CoA β-ketothiolase
acetoacetyl-CoA malate TCA-cycle isocitrate NADPH acetoactyl-CoA 3 reductase 3HB-CoA 3HB thioesterase PHA polymerase phosphor- transbutyrylase PHB 3HB-P biomass PHA butyrate 1 depolymerase kinase 2
3HB 3HB
Figure 18. Biosynthesis of (R)-3-hydroxybutyrate (3HB). The numbers 1, 2 and 3 denote different pathways that can be used for production of 3HB. Many methods used to produce 3HB depend on a natural PHA- producing microorganism, either to produce PHB or as source of genes. In this context, Halomonas boliviensis LC1T (DSM 15516T) is an interesting microorganism for the production of 3HB since it is able to accumulate PHB, up to 81% of its cell dry weight (CDW), and shows volumetric PHB productivities of up to 1.1 g L-1 h-1 [206-210]. This microorganism was isolated from a hypersaline-lake located in Bolivia at 4278 m above the sea level, and is a Gram-negative and moderately halophilic aerobic bacterium, (0-25 % (w/v) NaCl) (Figure 19) [211]. However, this microorganism is not suitable for industrial production of 3HB since it requires complex Mariel Perez-Zabaleta | 49
medium, high concentration of NaCl that can be corrosive for the bioreactors, its physiology and metabolism are not well-studied and there is a lack of efficient genetic tools, which makes it difficult to improve production by metabolic engineering. Nevertheless, H. boliviensis seems to be a potential source of enzymes to produce 3HB by microbial production using metabolic engineering approaches. Additionally, production of 3HB by chemical depolymerization and enzymatic depolymerization of PHB in vitro or in vivo are not optimal for industrial production since they are two-step production processes and, in the case of chemical depolymerization and enzymatic depolymerization of PHB in vitro, a double downstream process is required.
Figure 19. Accumulation of PHB by H. boliviensis. Transmission electron microscope figure reprinted from Quillaguamán et. al (2006) [212] with permission from Elsevier. H. boliviensis can utilize various carbon sources such as glucose, fructose, mannose, sucrose, maltose, L- arabinose and D-xylose, its optimum pH is 7.5 and its optimal growth-temperature is 30 °C [211]. Its chromosome size is 4120 kbp and contains 3863 predicted genes. The fewer production steps a process has, the more feasible it will be to decrease the final costs of the product. In this context, a direct conversion from sugars to 3HB (without going through PHB depolymerization) is beneficial. To produce 3HB in this thesis, a microbial one-stage process with the most direct metabolic pathway was selected (Figure 18, option 3). The selected pathway contains three enzymes: (i) β- ketothiolase that catalyzes the condensation of two molecules of acetyl-
50 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
CoA to acetoacetyl-CoA, (ii) acetoacetyl-CoA reductase that catalyzes the reduction of acetoacetyl-CoA to (R)-3HB-CoA, and (iii) acyl-CoA thioesterase that releases CoA from (R)-3HB-CoA to form (R)-3HB. To summarize the design criteria explained above: the selected product is 3HB due to its valuable applications, especially in the pharmaceutical industry; a microbial one-stage process to directly produce 3HB was selected, which avoids a double downstream process; H. boliviensis seems to be a promising gene-donor for production of 3HB by metabolic engineering approaches. 2.3. Choice of the model microorganism When a model microorganism is selected, several traits need to be considered such as generation time, genetic accessibility, modification by process engineering, mutation rate, robustness, sustainability for the desired process and substrates, and potential economic benefit. Moreover, a good understanding of the metabolism of the microorganism not only facilitates insertion of new pathways and in consequence, production of a wide range of potential compounds, but also facilitates the improvement of the production process by genetic modifications and process engineering. Escherichia coli and Saccharomyces cerevisiae are common model microorganisms. In this thesis, E. coli was selected as the model system since it is one of the most studied microorganisms, its metabolism is well- characterized and it is easy to modify genetically (Figure 20). Its genome was one of the first to be sequenced more than 20 years ago [213]. It has the ability to grow in inexpensive mineral salt medium and it can utilize a wide variety of substrates including glucose, xylose, arabinose and galactose. E. coli is able to attain high productivities and yields in part due to its high growth rate (doubling time of around 20 min under optimal conditions), but also due to its tolerance to high concentrations of substrates and products, for example E. coli tolerate higher concentrations of 1,3-propanediol (PDO) than natural producers [214, 215]. Mariel Perez-Zabaleta | 51
Figure 20. Electron microscope image of E. coli credit to Eurekalert (https://www.eurekalert.org/multimedia/pub/103041.php?from=311428) [216]. E. coli is a Gram-negative, facultative anaerobic and rod-shaped bacterium with around 4300 genes, its optimum pH is 7 and its optimum growth occurs at 37 °C. A brief search in the literature to find a suitable E. coli strain for recombinant production will result in dozens of potential candidates. All of them have different features and, depending on the specific application, one may be better than the other. E. coli B, C, W (Waksman) and K-12 are the most frequently used strains for recombinant production [217], and these laboratory strains have a history of safe commercial use, and do not have adverse health effects [218]. E. coli B was for first time reported by Delbrück and Luria in 1942 and posterior modifications of this strain had resulted in well-known strains such as BL21 and B-ATCC 11303 [219]. The strains of this group are known to produce a low amount of acetate and BL21 is commonly used for protein expression since it has deficiency in Lon and OmpT proteases, which increase protein stability [220, 221]. E. coli C strains are mainly used for expression of toxic proteins and they are more morphologically distinct (spherical in shape) than other E. coli strains [222, 223]. E. coli W (ATCC 9637) was isolated from soil by Selman A. Waksman in 1943 and is the only E. coli safe-laboratory strain able to use sucrose as fast as glucose. This strain is interesting for industrial applications since it has a high growth rate facilitating to attain high-cell- densities cultures. It also produces a low amount of acetate and has good tolerance to ethanol, acidic conditions, high temperatures and osmotic
52 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
stress [224]. E. coli K-12, despite having been isolated from the stool of a convalescent diphtheria patient in 1922, is a non-pathogenic strain, widely used in the industry and academia. Since its isolation, thousands of mutant strains have been derived from K-12 [225]. Strains W3110 and MG1655 are K-12 derivatives with limited genetic changes compared to their parent [226] and due to these minimal genetic modifications, these strains have a close-to-wild-type behavior suitable for industrial-scale production. A close related strain to MG1655 is BW25113, which has been extensively used for gene-knockout generations [227, 228]. Another well-known and widely used K-12 strain is MC4100, which is also a MG1655 derivative [229]. Of special importance for this thesis is the K-12 strain AF1000, which was selected as the reference strain and is a derivative of MC4100 and consequently also a MG1655 derivative. AF1000 was constructed from MC4100, in which guanosine tetraphosphate synthetase (relA+) was inserted, since this is a key enzyme involved in the stringent response of E. coli [230]. RelA activates the synthesis of the global regulatory molecule guanosine tetraphosphate (ppGpp) [231] and it has been shown that cells defective of relA have impaired metabolic performance and are less robust, specially at low growth rates (< 0.1 h-1) [232]. After choosing a strain platform, it is important to assess how a metabolic pathway for 3HB production can be integrated into the central metabolism of E. coli. In cellular metabolism, twelve chemicals are precursor metabolites necessary to build a new cell and these are the same in all cells, including E. coli. The precursor metabolites are glucose-6- phosphate, fructose-6-phosphate, ribose-5-phosphate, erythrose-4- phosphate, triose phosphate (dihydroxyacetone-phosphate and glyceraldehyde-3-phosphate), 3-phosphoglycerate, phosphoenolpyruvate, pyruvate, acetyl-CoA, a-ketoglutarate, oxaloacetate and succinyl-CoA. The twelve cellular precursors are intermediates of three central pathways: glycolysis, TCA cycle and the pentose phosphate, from which, all cellular building blocks and products can be derived (Figure 21). Metabolic reactions can be organized into one of two categories: (1) catabolic reactions, pathways that convert the substrate (e.g. carbon, nitrogen) into precursor metabolites, reducing power, and energy, and (2) anabolic reactions, pathways that consume reducing power and energy to produce cellular components (e.g. nucleic acids or proteins) and the desired product. This central metabolism is the unit of operation for strain design, in which the production of a chemical can be designed by changing existing Mariel Perez-Zabaleta | 53
pathways, inserting new pathways and combining them with the central pathways. In this context, it is important to state that acetyl-CoA is the central-precursor from which the pathways for 3HB production considered in this thesis start (Figure 21). Ara Xyl Glc
Ru Xu G6P 6PGL zwf NADPH NADPH 6PGC Ru5P Xu5P G3P F6P FDP gnd CO2
R5P S7P E4P
DDG6P G3P DHAP 1,3DPG
O2 3PG PEP NADH H2O 2PG
ATP CO2 PYR NADPH icd ICT NH3 CO2 CIT Ac-P HAc Glu KG Ac-CoA CO2 NADPH β-ketothiolase ATP
NADH CO2 GLX AcAc-CoA BIOMASS OAA SUC-CoA NADPH NADH acetoacetyl-CoA reductase 3- PO4 MAL 3HB-CoA SUC thioesterase
FUM 3HB FADH2 Figure 21. Central metabolic pathways of E. coli. Possible sugars used as carbon source in pink, precursor metabolites in blue, inserted pathway for the formation of 3HB in green. Abbreviations: Glc (glucose), Xyl (xylose), Ara (arabinose), Ru (ribulose), Xu (xylulose), G6P (glucose-6-P), 6PGL (6-P-gluconolactone), zwf (glucose-6-phosphate dehydrogenase), 6PGC (6-P-gluconate), gnd (6-phosphogluconate dehydrogenase), Ru5P (ribulose-5-P), DDG6P (2-dehydro-3-deoxy-D-gluconate-6-P), Xu5P (xylulose-5-P), R5P (ribose-5-P), S7P (sedoheptulose-7-P), E4P (erythrose-4-P), F6P (fructose-6-P), FDP (fructose-1,6-diP), G3P (glyceraldehyde-3-P), DHAP (dihydroxyacetone-P), 1,3DPG (1,3-diP-glycerate), 3PG (3-P- glycerate), 2PG (2-P-glycerate), PEP (phosphoenolpyruvate), PYR (pyruvate), Ac-CoA (acetyl-CoA), CIT (citrate), ICT (isocitrate), icd (isocitrate dehydrogenase), KG (a- ketoglutarate), SUC-CoA (succinyl-CoA), SUC (succinate), FUM (fumarate), MAL (malate), OAA (oxaloacetate), GLX (glyoxylate), Glu (glutamate), Ac-P (acetyl-P), HAc (acetate), AcAc- CoA (acetoacetyl-CoA), 3HB-CoA ((R)-3-hydroxybutyryl-CoA), 3HB ((R)-3-hydroxybutyrate).
54 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
The first aim in the project was to identify genes encoding efficient β-ketothiolase and acetoacetyl-CoA reductase from H. boliviensis and insert this 3HB pathway in E. coli with metabolic engineering tools. The genome of H. boliviensis was previously sequenced [233] and protein sequences of possible PHB-genes from H. boliviensis were aligned and compared with PHB-genes from other microorganisms. This phylogenetic study showed that seven putative β-ketothiolase alleles in H. boliviensis can catalyze the reaction from acetyl-CoA to acetoacetyl-CoA. However, the results were not conclusive about which of these seven enzymes could be the best for 3HB production. The same phylogenetic study showed that H. bolivienses possesses only one potential allele of acetoacetyl-CoA reductase (rx) for the reaction from acetoacetyl-CoA to (R)-3HB-CoA. To select the best β-ketothiolase for the production of 3HB, each of the β- ketothiolases together with the acetoacetyl-CoA reductase from H. boliviensis were expressed in E. coli AF1000 and screened for 3HB production. For this, a low-copy-number plasmid named pJBG was used, which was constructed from pKM1D, a pACYC184-derived plasmid with ori p15A, a lacUV5 promoter, a multiple cloning site, lacIq repressor and a chloramphenicol resistance gene. The concentration of 3HB, acetate and cell dry weight (CDW) were compared among the variants and the experiments showed that only expression of thiolase 3, thiolase 5 and thiolase 6 resulted in production of 3HB. Thiolase 3 (t3) lead to the highest 3HB concentration in this screening and was selected for the rest of this study (Table 2).
Mariel Perez-Zabaleta | 55
Table 2. Comparison of (R)-3-hydroxybutyrate (3HB) production by recombinant E. coli using seven H. boliviensis alleles of β-ketothiolase together with the acetoacetyl-CoA reductase (rx) from H. boliviensis. The experiments were performed in batch with two phases, an exponential growth phase and a nitrogen-depleted phase. The cultivation time was 9.5 h, minimal medium with 15 g L-1 of glucose was used. The experiments were performed in duplicate and, in the table, the average and mean deviations were presented. Abbreviations: HAc (acetate), CDW (cell dry weight). Unpublished data.
CDW 3HB HAc Allele (g L-1) (g L-1) (g L-1) Thiolase 1 2.74 ± 0.02 < 0.1 1.37 ± 0.02 Thiolase 2 2.58 ± 0.06 < 0.1 0.97 ± 0.11 Thiolase 3 2.85 ± 0.12 0.88 ± 0.01 1.11 ± 0.01 Thiolase 4 2.41 ± 0.01 < 0.1 1.10 ± 0.07 Thiolase 5 2.82 ± 0.06 0.73 ± 0.06 1.05 ± 0.03 Thiolase 6 2.71 ± 0.13 0.60 ± 0.03 0.98 ± 0.02 Thiolase 7 2.50 ± 0.21 < 0.1 1.08 ± 0.05 After identification of the best thiolase, the acetoacetyl-CoA reductase (rx) from H. boliviensis was characterized to determine the kinetics and cofactor preference of this enzyme. Enzyme-kinetic studies revealed that the reductase (rx) can use both NADPH and NADH cofactors but it has a clear preference for NADPH (Table 3) (Paper III). This study showed that the acetoacetyl-CoA reductase (rx) from H. boliviensis has a 16 times higher affinity for acetoacetyl-CoA (kcat/Km = 11.1 s-1 µM-1) than the reductase (PhaB) from the well-known PHB producer C. necator (kcat/Km = 0.685 s-1 µM-1) [234, 235], illustrating the potential benefit of this enzyme.
Table 3. Kinetic parameters of acetoacetyl-CoA reductase (rx) from H. boliviensis. The activity was assayed spectrophotometrically at 340 nm and 25 °C using 125 mM Tris–HCl (pH 8.0) as a buffer.
Cofactor Vmax KM kcat kcat/KM -1 -1 -1 -1 -1 (µmol mg min ) (µM) (s ) (s µM ) NADPH 1.6 ± 0.2 70± 6 780± 100 11.1± 0.3 NADH 0.2± 0.02 24± 6 100± 7 4.2± 0.2
56 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Acetoacetyl-CoA reductase enzymes are stereoselective and can reduce acetoacetyl-CoA to either (R)-3HB-CoA or (S)-3HB-CoA [236]. The phylogenetic study showed that reductase rx was more close-related to (R)- specific reductases. However, to confirm the (R)-stereoselectivity of acetoacetyl-CoA reductase (rx), samples from the 3HB-producing constructs were analyzed by gas chromatography (column CP-chirasil CP7503, Agilent Technologies) confirming that only the R-enantiomer of 3HB was produced (unpublished data). In the last step of 3HB formation, an acyl-CoA thioesterase was required to release the CoA from (R)-3HB-CoA and produce (R)-3HB. E. coli has several native thioesterases with broad specificity that can perform this reaction [237]. In the first part of the present investigation (from section 2.4.1 to 2.4.3.1), the production of 3HB was relying on the native activity of E. coli thioesterases, however, these enzymes were further studied in the last section of this thesis (section 2.4.3.2). For insertion of t3 and rx in E. coli, two plasmid variants were constructed in paper I: pJBGT3RX (gene order t3-rx) and pJBGRXT3 (gene order rx-t3). However, the gene order did not show a significant effect since the concentrations of 3HB obtained were 0.19 g L−1 and 0.18 g L−1 respectively. The plasmid used in all experiments of this thesis was pJBGT3RX. The E. coli strain containing t3 and rx from H. boliviensis (pJBGT3RX) and its native thioesterases produced 3HB extracellularly, which facilitates downstream processing. The export mechanism of 3HB in E. coli is uncertain, however it is hypothesized that is by passive diffusion [238]. In this strain, no intracellular accumulation of 3HB or PHB was observed and intracellular concentrations in washed cells was below the detection limit (unpublished data). These results confirm that 3HB can easily pass through the membranes of E. coli and any remaining of intracellular 3HB was removed by washing the cells once with saline (9% NaCl).
Mariel Perez-Zabaleta | 57
2.4. Design of concepts for improved 3HB production 2.4.1. Extension of substrate range for 3HB production (Paper I) Lignocellulosic biomass is the preferred feedstock in second generation biorefineries due to the wide availability and comparatively low cost. The sugars obtained after pretreatment of lignocellulose are mainly D-glucose, D-xylose and L-arabinose [29]. E. coli can utilize a wide variety of carbon sources, including glucose, xylose, arabinose and galactose. However, E. coli does not simultaneously consume these sugars and it is only able to consume arabinose after glucose is depleted with a considerably long lag-phase and only when arabinose is depleted, it consumes xylose, i.e. this microorganism has a hierarchical consumption of sugars (glucose>arabinose>xylose) in a diauxic growth pattern [239]. The diauxic growth of E. coli increases cultivation time affecting mainly production rates. This growth pattern can be overcome by metabolic engineering and evolutionary engineering such as the case of a previously engineered E. coli strain PPA652ara [172, 240]. This strain is an AF1000 derivative that was constructed by deleting the gene ptsG and subsequent adaptation in L-arabinose [172]. The gene ptsG encodes the regulatory D- glucose-specific enzyme II (EIIBCGlc) of the phosphoenolpyruvate: carbohydrate phosphotransferase system (PEP: PTS) that takes up glucose and simultaneously phosphorylates it and transports it into the cytoplasm. Deletion of ptsG increases levels of cyclic adenosine monophosphate (cAMP), which is a positive regulator of the uptake of sugars other than glucose including arabinose and xylose [241]. This increase in cAMP levels abolishes carbon catabolite repression in E. coli. The ptsG deletion together with an evolutionary strategy resulted in an E. coli strain (PPA652ara) able to simultaneously consume glucose, xylose and arabinose. These added features make PPA652ara a potential strain to be used in second-generation bioprocesses. E. coli PPA652ara was used as strain background in paper I [242], where the aim was to design a production process of (R)-3- hydroxybutyrate from a mixture of glucose, xylose and arabinose, in which all monosaccharides are consumed. For this, a synthetic medium with a sugar composition that could be found in a typical lignocellulose-
58 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
hydrolysate was used. To achieve 3HB production in this glucose-xylose- arabinose-consuming strain background, plasmid pJBGT3RX was inserted into PPA652ara. E. coli AF1000, the parental strain of PPA652ara, was transformed with the 3HB construct and used as the reference strain. E. coli AF1000-T3RX (AF1000 pJBGT3RX) and PPA652ara-T3RX (PPA652ara pJBGT3RX) were evaluated in batch mode in bioreactors, AF1000-T3RX on 10 g L−1 glucose, and PPA652ara-T3RX on 5.47 g L−1 glucose, 3.97 g L−1 xylose and 0.56 g L−1 arabinose (10 g L−1 in total) (Figure 22). Strain PPA652ara-T3RX consumed the three sugars simultaneously, but needed longer time for uptake of the three sugars than the reference strain AF1000-T3RX needed for complete uptake of glucose. In line with this, the growth rate of PPA652ara-T3RX was lower on three sugars (0.39 h−1) than the growth rate of AF1000-T3RX on glucose (0.76 h−1). Under these conditions, PPA652ara-T3RX produced significantly less acetate than AF1000-T3RX (Figure 22). This lower acetate excretion of PPA652ara-T3RX was in line with the previously observed in PtsG- defective strains, in which a low glucose uptake rate decreased the overflow metabolism in E. coli [240, 241]. AF1000-T3RX produced 3HB at a higher q3HB than PPA652ara-T3RX, which was reflected in a higher final titer of 3HB (0.5 g L−1) compared to PPA652ara-T3RX (0.3 g L−1) (Figure 22). Mariel Perez-Zabaleta | 59
A AF1000-T3RX B PPA652ara-T3RX 5 5
) 4 CDW CDW 4 -1 3 3 2 2 CDW (g L 1 1
) 2 4 6 8 2 4 6 8 -1 10 10 Glc Glc 8 Xyl 8 Ara Ara (g L
6 6 4 4 2 2 Glc, Xyl,
2 4 6 8 2 4 6 8 ) 1.2 1.2 -1 HAc HAc 1.0 3HB 3HB 1.0 0.8 0.8 0.6 0.6 0.4 0.4
HAc, 3HB (g L 0.2 0.2
2 4 6 8 2 4 6 8
) 100 100 -1 q3HB q3HB h 80 80 -1 60 60
(mg g 40 40 3HB
q 20 20
0 2 4 6 8 0 2 4 6 8 Time (h) Time (h) Figure 22. Production of 3HB in E. coli (A) AF1000-T3RX during cultivation on glucose and (B) PPA652ara-T3RX during cultivation on glucose, xylose and arabinose in batch mode. Parameters: cell dry weight (CDW, filled circles), glucose (Glc, open circles), xylose (Xyl, open squares), arabinose (Ara, open triangles), acetate (HAc, filled squares), 3HB (filled triangles) and specific productivity of 3HB (q3HB, open diamonds). Industrial-scale bioprocesses most often run in fed-batch or continuous cultivation mode with a desired limiting component. In addition to using mixed sugars, paper I also investigated different cultivation strategies to produce 3HB and one of them was continuous cultivation with carbon limitation. These carbon-limited cultivations showed that at dilution rates (D) lower than 0.4 h-1, residual concentrations of sugars were low for both, AF1ooo and PPA652ara, strains (Paper I) [242]. Since catabolite repression was found to require relatively high glucose fluxes, these results led to conclude that both strains can effectively run up to a rate of 0.4 h-1 for simultaneous sugar uptake. However, carbon- limited cultivations using PPA65ara-T3RX and AF1000-T3RX showed almost no 3HB production and the maximum 3HB concentration reached during the cultivations was 0.02 g L-1 for PPA65ara-T3RX and 0.1 g L-1 for AF1000-T3RX (Paper I) [242]. In comparison to batch cultivations (Figure 22), these low 3HB concentrations under carbon-limited cultivations
60 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
demonstrated that carbon excess was beneficial to produce 3HB in this strain background. Taking the requirement of glucose excess as a starting point for a 3HB production process, other cultivation strategies were proposed in paper I and paper II to improve 3HB production. These cultivation strategies are explained in the next section. 2.4.2. Influencing yield, titer and rate by cultivation strategies 2.4.2.1. Nitrogen- or phosphorus-depleted cultivations (Paper I and Paper II) To design a 3HB production processes that can be scalable at industrial level, yield, titer and rate need to be improved. Carbon-limited continuous cultivation resulted in very low production of 3HB and batch cultivations also gave low yields of 3HB on glucose (Figure 22). This was mainly due to byproduct formation such as cells (biomass), CO2 and acetate (Figure 23). It is known that production of PHB in natural producers occurs usually during carbon excess and limitation or depletion of another essential nutrient, such as nitrogen and phosphorus [66]. A similar approach can be used in the production of 3HB, to uncouple the production of cells from the product formation, which can result in an increased 3HB yield, rate and titer. When nitrogen or phosphorus are depleted, essential building blocks for cell formation cannot be formed, resulting in either stopped or decreased growth. Under these conditions, the cell requires less ATP and, in turn, oxidizes fewer NADH molecules to NAD+ in the respiratory chain, which result in an increased level of NADH [243]. These increased levels of NADH allosterically inhibit the citrate synthase and the activity of the TCA cycle is reduced [244]. In line with this, a lower flux of carbon is used by the TCA cycle, which favors the pathway of 3HB formation (Figure 23). To increase 3HB formation in this thesis, nitrogen/phosphorus-depleted cultivations strategies were proposed that consisted of two phases; a phase with all nutrients in excess to allow biomass formation at maximum growth rate, and a depletion phase that started after complete consumption of ammonium or phosphate to redirected the carbon source to 3HB formation (Paper I and Paper II). Mariel Perez-Zabaleta | 61
glucose
glucose-6-P glycolysis
pyruvate
acetyl-CoA Pi t3 pta TCA-cycle acetoacetyl CoA NADPH Pi rx acetyl-P
NH3 (R)-3-hydroxybutyryl-CoA ATP ackA thioesterase Products (R)-3-hydroxybutyrate acetate CO2 + biomass Figure 23. Schematic overview of the main pathways surrounding acetyl-CoA in 3HB production by recombinant E. coli. The production of 3HB from glucose begins with glycolysis, which lead to the key precursor metabolite acetyl-CoA. At this branch point, the carbon can be diverted to growth and energy through the TCA cycle, to acetate formation, or it can be used for 3HB production. Abbreviations: t3 (β-ketothiolase), rx (acetoacetyl-CoA reductase), pta (phosphotransacetylase) and ackA (acetate kinase), Pi (phosphorus). To increase 3HB production in a medium containing a mixture of sugars (Paper I), nitrogen-depleted batch (N-depleted) cultivations were performed using PPA652ara-T3RX strain and AF1000-T3RX as control strain. In both cases, the three sugars were added to the medium and as expected during glucose excess, AF1000-T3RX did not consume either xylose or arabinose, while PPA652ara-T3RX consumed the three sugars simultaneously (Figure 24). By depleting the nitrogen source, the concentration of cells remained constant in the second phase while 3HB and acetate were continuously produced. Nitrogen-depleted cultivations did not show a positive effect in the volumetric productivities of 3HB due to low production of cell mass but the yield of 3HB on sugar increased 4- fold for both PPA652ara-T3RX and AF1000-T3RX strains when compared
62 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
with their respective batch cultivations (Figure 22 and Figure 24). In the case of PPA652ara-T3RX, higher acetate production was observed in nitrogen-depleted cultivation compared to its batch cultivation (Figure 22B, Figure 24B and Table 4).
A AF1000-T3RX B PPA652ara-T3RX 5 5
) 4 Nitrogen depletion phase CDW Nitrogen depletion phase CDW 4 -1 3 3 2 2 CDW (g L 1 1
) 5 10 15 20 5 10 15 20 -1 10 10 Glc Glc 8 Xyl Xyl 8 Ara Ara Ara (g L
6 6 4 4 2 2 Glc, Xyl,
5 10 15 20 5 10 15 20 ) 1.2 1.2 -1 HAc 1.0 3HB 1.0 0.8 0.8 0.6 HAc 0.6 0.4 3HB 0.4
HAc, 3HB (g L 0.2 0.2
5 10 15 20 5 10 15 20 0.5 NH NH 0.5 ) 3 3 -1 0.4 0.4
(g L 0.3 0.3 3
NH 0.2 0.2 0.1 0.1
5 10 15 20 5 10 15 20
) 100 100 -1 q3HB q3HB h 80 80 -1 60 60
(mg g 40 40 3HB
q 20 20
0 5 10 15 20 0 5 10 15 20 Time (h) Time (h) Figure 24. Production of 3HB in E. coli (A) AF1000-T3RX and (B) PPA652ara-T3RX, during cultivation on glucose, xylose and arabinose in nitrogen-depleted batch mode (Paper I). Parameters: cell dry weight (CDW, filled circles), glucose (Glc, open circles), xylose (Xyl, open squares), arabinose (Ara, open triangles), acetate (HAc, filled squares), 3HB (filled triangles), ammonia (NH3, filled diamonds) and specific productivity of 3HB (q3HB, open diamonds). This depletion approach was also investigated in paper II [245], but in this case, the effects of nitrogen and phosphorus depletion on 3HB production were investigated and compared. In paper II, for a clear comparison, depleted batch cultivations were performed using the reference strain AF1000-T3RX and glucose as the only carbon source. Compared to the batch cultivation (Figure 22A and Table 4), nitrogen- Mariel Perez-Zabaleta | 63
depleted batch increased the yield (Y3HB/s) by 16% (0.07 g g-1), while phosphorus-depleted batch improved the yield by 49% (0.12 g g-1) (Table 4). A greater improvement of the yield in the case of phosphorus-depleted cultivation was not only due to a lower increase of cell concentration compared to batch cultivation, but also due to a lower acetate formation. This might be explained by the fact that phosphate-availability influences the kinetics of the enzymes phosphotransacetylase (pta) and acetate kinase (ackA), which are involved in the pathway of acetate formation (Figure 23). Due to this low acetate formation during phosphorus-depleted cultivation, the final titer of 3HB was also improved and a 2.5-fold increase in 3HB concentration (1.3 g L-1) was obtained compared to batch cultivation (0.5 g L-1) (Table 4). The volumetric production rate of 3HB (r3HB) was improved in the case of phosphorus-depleted batch but not in the nitrogen-depleted batch cultivation (Table 4).
Table 4. Summary of nitrogen-depleted batch (N-depleted), phosphorus-depleted batch (P- depleted) and batch cultivations using E. coli PPA652ara-T3RX or AF1000-T3RX and different carbon sources (Paper I and Paper II). Abbreviations: nitrogen (N), phosphorus (P), glucose (Glc), xylose (Xyl), arabinose (Ara), cell dry weight (CDW), (R)-3-hydroxybutyrate
(3HB), acetate (HAc), yield of 3HB on sugar (Y3HB/s) and volumetric productivity of 3HB (r3HB). The yield was calculated for the whole experiment and, in the case of the depletion cultivations, the time-averaged volumetric productivity was calculated for the respective depleted phase only and did not include the exponential growth phase.
Cultivation CDW 3HB HAc Y3HB/s r3HB Sugars Strain mode (g L-1) (g L-1) (g L-1) (g g-1) (g L-1 h-1) Glc AF1000-T3RX Batch 4.2 0.5 1.0 0.06 0.09 Glc-Ara-Xyl PPA652ara-T3RX Batch 4.9 0.3 0.0 0.03 0.04 Glc-Ara-Xyl PPA652ara-T3RX N-depleted 1.4 0.4 0.7 0.14 0.04 Glc-Ara-Xyl AF1000-T3RX N-depleted 1.3 0.6 0.9 0.23 0.04 Glc AF1000-T3RX N-depleted 2.5 0.5 1.1 0.07 0.04 Glc AF1000-T3RX P-depleted 3.3 1.3 0.7 0.12 0.17 In general, it can be concluded that either nitrogen or phosphorus depletion cultivations are interesting strategies to mainly increase product yields, which it is of great importance to reduce the process cost by redirecting substrate consumption to the product.
64 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
2.4.2.2. Nitrogen- or phosphorus-limited cultivations (Paper I and Paper II) In microbial processes, cell-performance is crucial to increase production and a complete starvation of nutrients can cause severe effects on cell metabolism with a negative impact on productivity. In this context, the limitation of a nutrient can be used as strategy to avoid complete starvation and still redirect the flux of carbon from biomass to 3HB formation. Nutrient-limited fed-batch are widely used in industrial bioprocesses to control the growth rate and improve product titers and productivities. During aerobic growth of E. coli, fed-batch cultivation is the preferred technique to increase cell mass and obtain high-cell-density cultures without restrictions of oxygen or heat transfer. Using this approach to increase 3HB formation in this thesis, a nutrient-limited strategy was proposed that consisted of two phases; a batch phase with all nutrients in excess to allow biomass formation at maximum growth rate, and a limitation phase that started after complete consumption of either the nitrogen or phosphorus source and the growth rate was controlled by feeding either the nitrogen or phosphorus source in limiting amounts to redirect the carbon source to 3HB formation (Paper I and Paper II). Both investigations, paper I and paper II, used nutrient-limited fed-batch strategies to increase 3HB titer and productivities, but with a different focus. Paper I used this strategy to increase 3HB production during simultaneous consumption of three sugars while paper II used this strategy to investigate the effect of nitrogen and phosphorus limitation on 3HB production. Nitrogen-limited fed-batch cultivations with exponential feed of the nitrogen source (ammonium sulfate) were used in paper I. While in paper II, phosphorus-limited and nitrogen-limited fed-batch cultivations were performed with first an exponential feed followed by a linear feed of either ammonium or phosphate. Both strategies, nitrogen-limited and phosphorus-limited fed-batch cultivations, allowed to control the growth rate, while glucose was in excess for 3HB formation. In addition to the different feeding profiles used in paper I and paper II, the fed-batch experiments in paper I started the feed phase with a lower concentration of cells compared to the fed-batch cultivations performed in paper II. In paper I, fed-batch cultivation with nitrogen as limiting substrate resulted for both strains, PPA652ara-T3RX and AF1000-T3RX, in similar 3HB concentration of 1.9 g L-1 and 1.8 g L-1 respectively (Table 5). The advantage to used PPA652ara-T3RX as producing platform in addition of Mariel Perez-Zabaleta | 65
the simultaneous consumption of glucose, xylose and arabinose was the lower production of acetate of this strain background compared to the reference strain AF1000-T3RX (Table 5). In paper I as well as in paper II, high final 3HB concentration were obtained and in all the experiments volumetric productivities were improved compared to the depletion cultivations or the batch cultivations due to an increased cell mass. In paper I and paper II, when nitrogen was used as the limiting substrate, the volumetric productivities were similar in all the cases (0.4 g L-1 h-1) (Table 5). While paper II showed that phosphorus-limited fed-batch gave the highest time-averaged volumetric productivity (0.8 g L-1 h-1) and this can be explained by the fact that specific glucose uptake (qGlc) was considerably higher in phosphorus-limited fed-batch than in nitrogen-limited fed- batch, resulting in a higher glycolytic flux and a higher q3HB and r3HB in the case of phosphorus-limited fed-batch cultivation. Both, paper I and paper II, showed that either nitrogen- or phosphorus-limited fed-batch cultivations are potential strategies to be used in large-scale cultivations since titer and rate can be greatly enhanced. However, these strategies did not improve the product yield as much as nutrient-depleted batch cultivations since a large amount of glucose was diverted to the production of cells and byproduct.
Table 5. Summary of nitrogen-limited fed-batch (N-limited) and phosphorus-limited fed-batch (P-limited) cultivations using E. coli PPA652ara-T3RX or AF1000-T3RX and different carbon sources. Abbreviations: nitrogen (N), phosphorus (P), glucose (Glc), xylose (Xyl), arabinose (Ara), cell dry weight (CDW), (R)-3-hydroxybutyrate (3HB), acetate (HAc), yield of 3HB on sugar (Y3HB/s) and volumetric productivity of 3HB (r3HB). The yield was calculated for the whole experiment and the time-averaged volumetric productivity was calculated for the respective limited phase only and did not include the exponential growth phase (Paper I and Paper II).
Cultivation CDW 3HB HAc Y3HB/s r3HB Sugars Strain mode (g L-1) (g L-1) (g L-1) (g g-1) (g L-1 h-1) Glc-Ara-Xyl PPA652ara-T3RX N-Limited 11.8 1.9 0.8 0.05 0.4 Glc-Ara-Xyl AF1000-T3RX N-Limited 10.4 1.8 2.7 0.05 0.4 Glc AF1000-T3RX N-Limited 20.4 4.1 6.7 0.05 0.4
Glc AF1000-T3RX P-Limited 21.3 6.8 9.0 0.07 0.8 In the following sections of this thesis, E. coli AF1000 was used as the reference strain in the ‘proof of concepts’ for 3HB production. This strain without several genetic modifications was chosen to individually evaluate each metabolic or cultivation strategy and its impact on 3HB production.
66 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
2.4.2.3. Minimizing NADPH consumption (Paper III) In the metabolic engineering of new pathways, a crucial factor is the supply of cofactors as well as their regeneration in the cells that are needed to form the product. In this context, acetoacetyl-CoA reductase (rx) that reduces acetoacetyl-CoA to 3HB-CoA using NADPH as cofactor, requires efficient regeneration of NADPH. To improve availability of NADPH during 3HB production, a cultivation strategy using glutamate as nitrogen source was proposed in paper III [235], since in the assimilation of ammonia by E. coli, α-ketoglutarate is converted to glutamate by a NADPH-specific enzyme (Figure 21 and Figure 25) [246]. If glutamate is added to the medium, the expense of one molecule of NADPH can be avoided during the formation of biomass, which can then be used to produce 3HB. The proposed strategy was to use a mixture of NH4+ and glutamate since the uptake rate of glutamate by E. coli is low and results in a low growth rate if it is used as the only nitrogen source.
+ NADPH NADP TCA cycle α-ketoglutarate glutamate Biomass + NH4
Figure 25. Simplified metabolic scheme showing the assimilation of ammonium + + (NH4 ) by E. coli. Under high concentration of NH4 , the conversion of α- ketoglutarate to glutamate is catalyzed by NADPH-specific glutamate + dehydrogenase while at low NH4 concentrations NADPH-specific glutamate synthase catalyzes the reaction. In paper III, the glutamate strategy was studied in nitrogen- depleted batch cultivations similar to the described previously. When AF1000-T3RX was grown using glutamate as second nitrogen source, the final titer of 3HB was only increased by 10% compared to the reference cultivation without glutamate, which was reflected in a slight improvement of the volumetric productivity (Table 6). However, when glutamate was used in the medium, acetate formation was also increased resulting in a same yield of 3HB on glucose than the reference cultivation (0.07 g g-1). This higher acetate formation can be due to a higher specific glucose consumption rate (qGlc) when glutamate was added to the medium compared to the nitrogen-depleted batch without glutamate, which might Mariel Perez-Zabaleta | 67
be resulted in a higher glycolytic flux to acetate and 3HB. In conclusion, this strategy slightly enhanced the final 3HB titer and the productivity but it did not show a positive effect in the yield or byproduct formation.
Table 6. Production of 3HB by AF1000 pJBGT3RX using two strategies: (i) nitrogen-depleted batch (N-depleted) and (ii) nitrogen-depleted batch with addition of glutamate as second nitrogen source (N-depleted + Glutamate). Abbreviations: nitrogen (N), cell dry weight (CDW),
(R)-3-hydroxybutyrate (3HB), acetate (HAc), yield of 3HB on glucose (Y3HB/s) and volumetric productivity of 3HB (r3HB). The yield was calculated for the whole experiment and the time- averaged volumetric productivity was calculated for the respective depleted phase only and did not include the exponential growth phase (Paper III).
Cultivation time CDW 3HB HAc Y3HB/s r3HB mode (h) (g L-1) (g L-1) (g L-1) (g g-1) (g L-1 h-1) N-depleted 11.8 2.5 0.5 1.1 0.07 0.04 N-depleted + 11.9 2.4 0.6 1.4 0.07 0.05 Glutamate 2.4.3. Influencing yield, titer and rate by metabolic engineering 2.4.3.1. Enhancing cofactor supply to steer 3HB production (Paper III) Since the addition of glutamate to the medium resulted only in a minor improvement of the production, metabolic engineering strategies to increase NADPH availability during 3HB production were examined. There are considerably fewer reactions in the cell that generate NADPH compared to the number of reactions that produce NADH. It is generally accepted that NADH serves primarily for the generation of ATP, while NADPH is mainly used as an electron or hydride donor in reductive biosynthetic reactions [247]. In the oxidation of glucose to CO2 and biomass, only isocitrate dehydrogenase (icd) yields NADPH (Figure 21). E. coli and many other microorganism can produce NADPH via a transhydrogenase, which is membrane-bound and it can only proceed at an energized membrane [246]. An additional source of NADPH in E. coli is the pentose phosphate pathway (PPP) via two enzymes glucose-6- phosphate dehydrogenase (zwf) and 6-phosphogluconate dehydrogenase (gnd) (Figure 21) [246]. Overexpression of zwf seems to be a promising metabolic strategy to increase the availability of NADPH since it is the first enzyme in pentose phosphate pathway and its overexpression can also
68 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
result in a higher flux through Gnd to yield a second molecule of NADPH. Moreover, compared to the production of NADPH by isocitrate dehydrogenase, Zwf is independent of the flux of carbon through the TCA cycle and can also produce NADPH in conditions of nitrogen or phosphorus depletion. In paper III, overexpression of zwf was proposed to improve cofactor supply and the gene zwf was inserted in plasmid pBAD/HisC, which has pBR322 ori, araBAD promoter and an ampicillin resistance gene. The metabolic burden in the cells carrying the production plasmid as well as the additional plasmid for zwf overexpression (pJBGT3RX and pBADzwf) was not high and the specific growth rate of AF1000 pJBGT3RX pBADzwf (AF1000-T3RXzwf) was 0.68 h-1 compared to 0.73 h-1 for the strain with only one plasmid AF1000 pJBGT3RX (AF1000-T3RX). The overexpression of zwf was evaluated under different cultivation conditions including batch, nitrogen-depleted batch, phosphorus-depleted batch and nitrogen-limited fed-batch. When AF1000-T3RXzwf was evaluated in batch mode, titer, yield and rates were enhanced compared to the strain without zwf overexpression (Table 7). For further improvement of 3HB titer, yield and production rate, phosphorus- depleted and nitrogen-depleted batch cultivations were performed using the strain AF1000-T3RXzwf. During phosphorus depletion, production of 3HB did not improve for AF1000-T3RXzwf compared to the strain without zwf overexpression AF1000-T3RX. Phosphorus is a crucial component not only for the formation of NADPH but also for the formation of ATP, nucleic acids (DNA and RNA), sugar phosphates (phosphotransferase system), and phospholipids, all of which play important roles on cell performance and 3HB production. Therefore, cultivations with nitrogen depletion or limitation seem to be better strategies for industrial production of 3HB. When the strain with the overexpression of zwf was evaluated in nitrogen- depleted batch cultivations, both concentration of 3HB and volumetric productivity were enhanced two-fold and the yield increased by 75% compared to the reference strain AF1000-T3RX (Table 7). Mariel Perez-Zabaleta | 69
Table 7. Comparison of 3HB production by AF1000 pJBGT3RX (AF1000-T3RX) and AF1000 pJBGT3RX pBADzwf (AF1000-T3RXzwf). Cultivation conditions used were batch, nitrogen- depleted batch (N-depleted) and nitrogen-limited fed-batch (N-limited). Abbreviations: nitrogen (N), cell dry weight (CDW), (R)-3-hydroxybutyrate (3HB), acetate (HAc), yield of 3HB on glucose (Y3HB/s) and volumetric productivity of 3HB (r3HB). The yield was calculated for the whole experiment and the time-averaged volumetric productivity was calculated for the respective depleted/limited phase only and did not include the exponential growth phase.
Cultivation CDW 3HB HAc Y3HB/s r3HB Strain mode (g L-1) (g L-1) (g L-1) (g g-1) (g L-1 h-1)
AF1000-T3RX Batch 4.2 0.5 1.0 0.06 0.09 AF1000-T3RXzwf Batch 3.7 0.7 1.1 0.07 0.10 AF1000-T3RX N-depleted 2.5 0.5 1.1 0.07 0.04 AF1000-T3RXzwf N-depleted 2.0 1.1 1.2 0.12 0.09 AF1000-T3RXzwf N-Limited 34.8 12.7 26.0 0.13 0.42 Nitrogen-limited fed-batch with AF1000-T3RXzwf resulted in one of the highest reported concentrations of 3HB (12.7 g L-1) and achieved high 3HB yields and volumetric productivities compared to previous studies on recombinant production of 3HB [205, 236, 248]. However, final concentration of acetate was higher than the concentration of 3HB (Table 7), which considerably decreased the 3HB yield and productivity. The limitation of nitrogen together with the overexpression of zwf are scalable concepts that can result in high production of 3HB, but to have a more robust 3HB-producing platform, the formation of byproduct such as acetate needs also to be overcome. 2.4.3.2. Decreasing byproduct formation (Paper IV and Paper V) Since it is of high importance to reduce the formation of acetate for improved 3HB production, three parallel studies were performed each using different metabolic engineering approaches. One of the studies focused on increasing the 3HB pathway activity to redirect acetyl-CoA through the 3HB formation instead of the acetate pathway (Paper IV). Another of the studies investigated the effects of deleting the genes related to acetate formation during 3HB production (Paper V). Lastly, the third parallel research line investigated different strain backgrounds of E. coli to select a low acetate-producing strain that it was able to produce 3HB at high levels (Paper V).
70 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
[1] Increasing activity of the 3HB pathway (Paper IV) This study was based on the hypothesis that an increase in the activity of the 3HB pathway can pull more acetyl-CoA to 3HB and reduce acetate formation. The pathway for 3HB production consists of three consecutive reactions that are well-connected, in which the product of one reaction is the substrate for the other reaction and concentrations of initial substrate, intermediate compounds, final product and cofactors affect the overall thermodynamics and activity of the pathway. By increasing the availability of NADPH, the kinetics of the second reaction was improved, which led to a higher production of 3HB. In line with this, another crucial step to study was the hydrolysis of 3HB-CoA to 3HB, since the highly negative free-energy change of this reaction can also provide a thermodynamic pull on the 3HB pathway. This reaction was catalyzed by acyl-CoA thioesterases from E. coli. The genome of E. coli encodes multiple thioesterases, such as FadM, TesA, TesB, YbgC, YdiI and YciA, which have diverse roles in the metabolism [249]. For example, TesA is located in the periplasm and is involved in fatty acid synthesis, TesB can hydrolyze a broad range of medium- to long-chain acyl-CoA thioesters, YbgC may be involved in phospholipid metabolism [250] and FadM is a long-chain acyl- CoA thioesterase probably involved in the β-oxidation of oleic acid [251]. The production of 3HB in this thesis relied on native E. coli thioesterases, however, it was uncertain which of these enzymes had the most important role in the production of 3HB. In view of their broad substrate specificity, E. coli thioesterases encoded by the genes tesA, tesB, yciA, and fadM were selected as possible candidates for the hydrolysis of 3HB-CoA. As a preliminary study, their contribution was investigated by deleting each thioesterase individually in the AF1000 strain background (Paper IV) [252]. The 3HB production plasmid was inserted in each of the strains and were evaluated in nitrogen-depleted batch cultivations. Reference strain AF1000-T3RX, without any thioesterase deletion, was used as control (Figure 26). These experiments showed that deletion of tesA did not have any significant effect on 3HB production, whereas deletion of tesB and fadM resulted in minor decreases. The thioesterase with the higher impact on 3HB production was yciA, since its deletion decreased the yield by 43%, the final titer by 32% and the specific 3HB productivity by 36% compared to the control strain (Figure 26). Additionally, the specific productivity of acetate increased for the strain with the yciA deletion (0.036 g g−1 h−1) Mariel Perez-Zabaleta | 71
compared to the control strain (0.024 g g−1 h−1), which was in line with a decreased pull on acetyl-CoA by the 3HB pathway.
3HB 1.0 q3HB 0.05 0.20 Y3HB/s
0.8 0.04 Y 3HB/s
q 0.15Lorem ipsum
3HB Lorem ipsum ] -1 [g g
0.6 0.03 [g g -1
0.10 -1 h ] -1 3HB [g L
0.4 0.02 ]
0.05 0.2 0.01
0 0 0 control tesA tesB yciA fadM Figure 26. Evaluation of tesA, tesB, yciA, and fadM deletions on 3HB-producing E. coli AF1000. The figure shows the final (R)-3-hydroxybutyrate concentration (3HB), specific 3HB productivity (q3HB) and yield of 3HB on glucose (Y3HB/s). Both q3HB and Y3HB/s were calculated over the nitrogen-depleted phase. The control strain was E. coli AF1000 pJBGT3RX without thioesterase deletions. Since the preliminary study showed the high contribution of yciA on 3HB production, this gene was overexpressed in E. coli AF1000 using the previously used plasmid for zwf overexpression with the only difference that the ampicillin gene marker was changed for a kanamycin resistance gene (pBAD-(Km)). In addition to the strain with yciA overexpression (AF1000-T3RX-yciA), another construct with the overexpression of zwf was build, which resulted in the strain AF1000- T3RX-zwfyciA and, in this case, the reference strain was AF1000 harboring the plasmid for 3HB production and the empty plasmid pBAD-(Km) (AF1000-T3RX). To evaluate the effect of the overexpression of yciA on 3HB production, these strain variants (AF1000-T3RX, AF1000-T3RX- yciA and AF1000-T3RX-zwfyciA) were tested under nitrogen-depletion (Figure 27). The final 3HB concentration was improved two-fold for AF1000-T3RX-yciA (1.5 g L−1) and 2.7-fold for the strain carrying both overexpression of zwf and yciA, AF1000-T3RX-zwfyciA, (1.9 g L−1) compared to the reference strain (0.7 g L−1) (Figure 27). In line with the increase of the final 3HB concentrations, also the productivity and the 3HB yield on glucose were enhanced with the overexpression of yciA and zwf- yciA compared to the reference strain. In both overexpression strains, the
72 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
production of acetate was lower than in the reference strain. During nitrogen-depletion, AF1000-T3RX-yciA and AF1000-T3RX-zwfyciA even consumed some of the acetate that was formed during the exponential phase (Figure 27).
A: AF1000-T3RX B: AF1000-T3RX-yciA C: AF1000-T3RX-zwfyciA + + + Exp.growth NH4 depleted Exp. growth NH 4 depleted Exp.growth NH4 depleted 3 CDW 3 (g L CDW
) 2 2 -1 -1 ) CDW (g L 1 1
0 0 20 Glc 20 + NH4 (g L Glc NH
+ 4 15 15 -1 ) (mM) 10 10 ) (mM) -1 4 + Glc NH
(g L 5 5
0 0 3HB 2.0 HAc 2.0 (g L 3HB, HAc
) 1.5 1.5 -1 -1 )
(g L 1.0 1.0 3HB, HAc 0.5 0.5
0 0 0 2.5 5.0 7.5 10.0 0 2.5 5.0 7.5 10.0 0 2.5 5.0 7.5 10.0 Time (h) Time (h) Time (h) Figure 27. Production of 3HB by (A) AF1000 pJBGT3RX pBAD-(Km)-Blank (AF1000-T3RX), (B) AF1000 pJBGT3RX pBAD-(Km)-yciA (AF1000-T3RX-yciA) and (C) AF1000 pJBGT3RX pBAD-(Km)-zwf-yciA (AF1000-T3RX-zwfyciA). Cultivations were performed in nitrogen- depleted batch mode. Parameters: cell dry weight (CDW, open squares), glucose (Glc, open + circles), ammonium (NH4 , filled triangles), acetate (HAc, crosses), and (R)-3-hydroxybutyrate (3HB, filled diamonds). The considerable improvements in 3HB production and the decrease in acetate formation during nitrogen-depleted cultivations, indicated that overexpression of yciA was a promising strategy to be used in large-scale. To increase final titers of 3HB, nitrogen-limited fed-batch cultivations were performed using AF1000-T3RX-zwfyciA and, in this case, the reference strain was AF1000 pJBGT3RX pBAD-(Km)-zwf (AF1000-T3RXzwf). The experiments were designed with a batch phase that ends with nitrogen depletion at a final cell concentration of around 4 Mariel Perez-Zabaleta | 73
g L−1, after which the feed ammonium sulfate started. Although glucose was maintained in excess throughout the experiment, ammonium accumulation was observed due to a decreased cell growth, which was likely caused by acetate accumulation and/or the metabolic burden of the induced pathway or pathway proteins. The final titers of 3HB and acetate were 4.1 g L−1 and 6.7 g L−1 for the strain without yciA overexpression (AF1000-T3RXzwf) and 8.9 g L−1 and 7.7 g L−1 for the strain AF1000- T3RX-zwfyciA, respectively (Figure 28).
A: AF1000-T3RXzwf B: AF1000-T3RX-zwfyciA + + Batch NH4 reduced Batch NH4 reduced
15 CDW 15 (g L CDW -1 ) )
-1 10 10 CDW (gL 5 5
0 0 50 150 Glc
+ (mM) NH 40 NH4 120 ) ) 4 +
-1 30 90 Glc
(gL 20 60 10 30 0 0
15 15 (g L 3HB, HAc 3HB 12 HAc 12 ) -1 -1 9 9 )
(gL 6 6 3HB,HAc 3 3 0 0
0.25 q3HB 1.0
q3HBd (g L r ) 0.20 r 0.8 -1 3HB 3HB h 0.15 r3HBd 0.6 -1 -1 h 3HB
-1 q
0.10 0.4 ) (gg 0.05 0.2 0 0 0 5 10 15 20 0 5 10 15 20 Time (h) Time (h) Figure 28. Production of 3HB by AF1000 pJBGT3RX pBAD-(Km)-zwf (AF1000-T3RXzwf) and AF1000 pJBGT3RX pBAD-(Km)-zwf -yciA (AF1000-T3RX-zwfyciA). Cultivations were performed in nitrogen-limited fed-batch mode. Parameters: cell dry weight (CDW, open + squares), glucose (Glc, open circles), ammonium (NH4 , filled triangles), acetate (HAc, crosses), and (R)-3-hydroxybutyrate (3HB, filled diamonds). Specific production rates (q3HB) and volumetric rates (r3HB) are represented as functions obtained from least square fits of the data and are shown for both replicate experiments.
74 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
The concentrations of acetate in fed-batch cultivations did not decrease as much as the cultivations with nitrogen depletion. Under nitrogen starvation conditions, the pull on acetyl-CoA by the 3HB pathway was higher compared to the experiments where the nitrogen source was available (Figure 27 and Figure 28). In line with these observations, another experiment setup was designed that consisted of two phases; a batch phase until a cell concentration of 10 g L-1 with delayed induction of the 3HB pathway (at OD600 9 instead of 0.2) to avoid the metabolic burden during the growth phase and a nitrogen- depleted batch phase that started after complete consumption of ammonium and enables acetate re-consumption (Figure 29). Under those conditions, the strain with the overexpression of zwf-yciA produced 2.6 times higher final 3HB concentration (14.3 g L−1) than the strain with only the overexpression of zwf (5.4 g L−1) (Figure 29). The time-averaged volumetric 3HB productivity of AF1000-T3RX-zwfyciA was 0.6 g L−1 h−1 and its overall 3HB yield on glucose was 0.21 g g−1 (Figure 29B). In addition, after induction of the 3HB pathway, AF1000- T3RX-zwfyciA was able to re-consume acetate and the concentration stayed constant at 0.2 g L−1 during the nitrogen depletion phase (Figure 29B). The yciA overexpression strategy succeeded in decreasing acetate formation by pulling acetyl-CoA towards 3HB formation. Mariel Perez-Zabaleta | 75
A: AF1000-T3RXzwf B: AF1000-T3RX-zwfyciA + + Batch NH4 depleted Batch NH4 depleted
15 15 (g L CDW -1 ) )
-1 10 10 CDW (g L 5 5 0 0 50 150 40 120 (mM) NH ) 4 +
-1 30 90 Glc
(g L 20 60 10 30 0 0
15 15 (g L 3HB, HAc 12 12 ) -1 -1 9 9 )
(g L 6 6 3HB, HAc 3 3 0 0 0.25 1.0 (g L r
) 0.20 0.8 3HB -1 -1 h
0.15 0.6 h -1 3HB
-1 q
0.10 0.4 ) (g g 0.05 0.2 0 0 0 5 10 15 20 25 0 5 10 15 20 25 Time (h) Time (h) Figure 29. Production of 3HB by AF1000 pJBGT3RX pBAD-(Km)-zwf (AF1000-T3RXzwf) and AF1000 pJBGT3RX pBAD-(Km)-zwf -yciA (AF1000-T3RX-zwfyciA). Cultivations were performed in nitrogen-depleted batch mode with delayed induction of the 3HB pathway. Parameters: cell dry weight (CDW, open squares), glucose (Glc, open circles), ammonium + (NH4 , filled triangles), acetate (HAc, crosses), and (R)-3-hydroxybutyrate (3HB, filled diamonds). Specific production rates (q3HB) and volumetric rates (r3HB) are represented as functions obtained from least square fits of the data and are shown for both replicate experiments. The arrow indicates the time of induction.
76 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
[2] Decreasing acetate formation during high-cell-density cultivations by gene deletion (Paper V) One of the approaches used in this thesis to limit acetate accumulation during 3HB production was the deletion of the genes involved in its formation. The two main pathways for acetate formation in E. coli under aerobic conditions are pyruvate oxidase (poxB) and phosphotransacetylase (pta)-acetate kinase (ackA) (Figure 30). To a lesser extent, acetate formation can also be attributed to other acetate-producing pathways such as N-acetylornithine deacetylase and citrate lyase [253, 254]. Deletion of pta and poxB has previously been shown to improve PHB production in E. coli by reducing acetate formation [255, 256]. In addition to these well-studied genes, deletion of isocitrate lyase regulator (iclR) has been proposed to decrease acetate formation [257, 258]. The glyoxylate operon is negatively regulated by iclR (Figure 30) and when iclR was deleted in E. coli MG1655 the flux through the TCA cycle was increased by redirecting 30% of the isocitrate molecules to succinate and malate without CO2 production, which resulted in a reduced production of acetate and less carbon loss as CO2 [257]. Mariel Perez-Zabaleta | 77
glucose
NADPH glucose-6-P 6-P-gluconolactone zwf
glycolysis NADPH
PPP
poxB pyruvate ATP
acs HAc pta ackA acetyl-CoA acetyl-P ATP t3 malate TCA-cycle acetoacetyl-CoA iclR NADPH glyoxylate isocitrate rx succinate 3HB-CoA thioesterase + NH4 biomass 3HB
Figure 30. Schematic overview of the main acetate formation pathways during 3HB production by recombinant E. coli. Abbreviations: t3 (β-ketothiolase), rx (acetoacetyl-CoA reductase), pta (phosphotransacetylase) and ackA (acetate kinase), poxB (pyruvate oxidase), iclR (isocitrate lyase regulator), zwf (Glucose-6-P dehydrogenase), PPP (pentose phosphate pathway). To evaluate the impact of the deletions of genes involved on aerobic acetate formation during 3HB production, pta, poxB and/or iclR were deleted in reference strain AF1000. The 3HB-producing enzymes (pJBGT3RX) and the plasmid with the overexpression of zwf (pBADzwf) were inserted in the variants and the preliminary screening was performed in nitrogen-depleted batch cultivation during 24 hours. Since this research line was performed in parallel to the thioesterase screening, overexpression of yciA was not included in this study. The results showed that neither iclR nor poxB deletion significantly reduced the final
78 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
concentrations of acetate compared to reference strain AF1000-T3RX and the physiology of the ΔiclR strain and the reference strain did not differ significantly (Figure 31). Compared to the reference strain, Δpta and ΔptaΔpoxB decreased the final acetate concentration by 36% and 47%, respectively, whilst no significant improvement in 3HB production were observed. In contrast to the reference and ΔiclR strain, variants with deletions of pta, poxB or pta-poxB accumulated pyruvate at high levels, exceeding even acetate production (Figure 31B).
A 0.15 0.6 ) -1 (g g
0.10 0.4 µ (h HAc/s -1 Y
) ,
3HB/s 0.05 0.2 Y
0 0 Ref pta poxB pta iclR poxB B )
-1 4
3
2
1 [3HB], [HAc], [Pyr] (g L
0 Ref pta poxB pta iclR poxB
Y Y [3HB] [HAc] [Pyr] HAc/s 3HB/s Figure 31. Evaluation of (R)-3-hydroxybutyrate and acetate formation in nitrogen-depleted batch cultivations of pta, poxB and/or iclR deletions in the AF1000 strain background. The final data after 24 hours of cultivation were plotted in the figure. Box (A) shows specific growth rate (μ), yield of 3HB on glucose (Y3HB/s) and yield of acetate on glucose (YHAc/s). Box (B) shows the concentrations of (R)-3-hydroxybutyrate (3HB), acetate (HAc) and pyruvate (Pyr). The yields were calculated for the whole experiment and the specific growth rate was calculated for the exponential growth phase. Mariel Perez-Zabaleta | 79
Although the deletions of pta and pta-poxB did not have an impact on the 3HB yield, it was hypothesized that the shift from acetate- to pyruvate formation can decrease weak-acid toxicity at the later stages in high-cell-density cultivations. In line with this, Δpta and ΔptaΔpoxB strains were evaluated in high-cell-density nitrogen-limited fed-batch cultures. This high-cell-density cultivation consisted of two phases; a repeated batch phase where glucose and ammonium sulfate were added to achieve a cell concentration of around 20 g L-1 and a nitrogen-limited phase, that started after complete consumption of ammonium, during which growth was controlled by feeding the nitrogen source (Figure 32). When Δpta, ΔptaΔpoxB and the reference strain were grown under this cultivation setup, the growth of AF1000-T3RXzwf quickly deteriorated due to acetate accumulation and at the end of the repeated batch, the reference strain accumulated 10.1 g L-1 of acetate (Figure 32A). In contrast, the acetate concentration at the end of this phase was decreased by 73% (2.7 g L-1) for Δpta and by 78% for ΔptaΔpoxB strain (2.3 g L-1). At the end of the repeated batch, the concentration of 3HB was higher for the reference strain (5.4 g L-1) compared to Δpta and ΔptaΔpoxB strains that were 3.3 g L-1 and 3.8 g L-1, respectively (Figure 32). During the nitrogen-limited phase, the predominant product for the Δpta strain was acetate and at the end of this phase, acetate concentration was only reduced by 37% in the Δpta strain (7.6 g L-1) and a higher 62% in ΔptaΔpoxB strain (4.6 g L-1) compared to the reference AF1000-T3RX (12.1 g L-1) (Figure 32). These results confirm that, in E. coli, pta is mainly active during aerobic exponential growth while poxB is mostly associated with acetate formation in the stationary phase [259, 260]. The final 3HB concentrations for the reference, Δpta and ΔptaΔpoxB strains were 7.0 g L-1, 4.6 g L-1 and 5.4 g L-1, respectively. While acetate and 3HB formation decreased in Δpta and ΔptaΔpoxB strains, accumulation of pyruvate greatly increased from undetectable levels in the reference strain to final concentrations of 3.8 g L-1 and 5.3 g L-1 in respectively Δpta and ΔptaΔpoxB (Figure 32). The lower acetate formation in combination with a limited capacity of the 3HB pathway might have resulted in increased intracellular levels of acetyl-CoA. Increased levels of acetyl-CoA are known to allosterically inhibit the pyruvate dehydrogenase complex [261], which might have resulted in the increased formation of pyruvate in Δpta and ΔptaΔpoxB strains. Although deletion of pta and pta-poxB decreased
80 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
acetate formation, these deletions did not improve 3HB production during high-cell-density cultivations.
A: AF1000-T3RXzwf B: AF1000 pta -T3RXzwf C: AF1000 pta poxB -T3RXzwf Rep Batch Fed-batch Rep Batch Fed-batch Rep Batch Fed-batch
50 200 Glucose consumed (g L
) Glucose Glucose Glucose
-1 CDW CDW CDW 40 (NH4)2SO4 (NH4)2SO4 (NH4)2SO4 160
30 120 , CDW (g L 4 20 80 SO 2 ) 4 10 40 -1 ) (NH 0 0 [3HB] [3HB] [3HB] 16 [HAc] [HAc] [HAc] 0.8
) µ µ µ -1 [Pyr] [Pyr] [Pyr] µ (h 12 0.6 -1
8 0.4 )
3HB, HAc (g L 4 0.2
0 0 1.5 r3HB r3HB r3HB 0.3
rHAc rHAc rHAc q ) 3HB
-1 q3HB q3HB q3HB h qHAc qHAc qHAc , q -1
1.0 0.2 HAc (g g (g L HAc -1 , r
0.5 0.1 h -1 3HB r )
0 0 8 12 16 20 24 8 12 16 20 24 8 12 16 20 24 Time (h) Time (h) Time (h) Figure 32. Nitrogen-limited fed-batch cultivations to evaluate (R)-3-hydroxybutyrate and acetate formation by (a) AF1000 (b) AF1000Δpta and (c) AF1000ΔptaΔpoxB containing the plasmids pJBGT3RX and pBADzwf. Samples were taken from OD600=10. Parameters: cell dry weight (CDW, filled circles), accumulative glucose consumed (Glucose, open circles), ammonium sulfate ((NH4)2SO4, inverted open triangles), specific growth rate (μ, crosses and dotted line), (R)-3-hydroxybutyrate ([3HB], closed squares), acetate ([HAc], open squares), pyruvate ([Pyr], open triangles). The specific 3HB production rate (q3HB, dash-dotted line), volumetric 3HB productivity (r3HB, dashed line), specific acetate production rate (qHAc, dotted line) and volumetric acetate productivity (rHAc, solid line) as calculated from spline-fit of the raw data. [3] Low acetate-producing E. coli strains (Paper V) The third parallel approach to decrease acetate formation during 3HB production was to select a low acetate-producing E. coli strain background that it was able to excrete high amount of 3HB and grow to high-cell densities. In this context, AF1000 was used as a reference and six additional E. coli strain backgrounds (B, BL21, W, BW25113, MG1655, W3110) were evaluated for their potential as low acetate-forming, 3HB- producing platforms. This study investigated two strains from group B (B and BL21), one wild type W strain, and three additional K-12 strains Mariel Perez-Zabaleta | 81
(MG1655, W3110, BW25113). A preliminary screening of the seven strains (without addition of the 3HB pathway) was performed in batch cultivations with an excess of glucose to allow overflow metabolism (Table 8). The result showed that E. coli BL21 produced the lowest concentration of acetate (0.03 g L-1), as was also reflected by its low specific acetate production rate (qHAc) and its yield of acetate per glucose consumed (YHAc/s) that was 20 times lower than the YHAc/s of AF1000. Important to highlight was that not all the K-12 strains produced high acetate concentrations and BW25113 produced the same amount of acetate as E. coli B, which was 3.2 times lower than the acetate concentration of AF1000 (1.14 g L-1) (Table 8). E. coli B, BW25113 and W produced acetate at similar qHAc, which was also exemplified by their similar YHAc/s (Table 8). The growth rate of W was the highest (1.04 h-1), which was remarkable since the experiments were performed on minimal medium.
Table 8. Acetate production and specific growth rate of E. coli AF1000, BL21, B, W, W3110, MG1655 and BW25113. Parameters: specific growth rate (μ), final acetate concentration
(HAc) after 6 hours of batch cultivation, specific acetate production rate (qHAc), yield of acetate on glucose (YHAc/s). Table shows the average and mean deviation of duplicate cultivations. The rates were calculated for the whole batch experiment.
µ HAc qHAc YHAc/s Strain (h-1) (g L-1) (mg g-1 h-1) (g g-1) AF1000 0.84 ±0.03 1.14 ± 0.20 187 ± 2 0.11 ± 0.03 BL21 0.71 ± 0.08 0.03 ± 0.00 7 ± 2 0.01 ±0.00 B 0.89 ± 0.01 0.36 ± 0.04 50 ± 3 0.04 ± 0.01 W 1.04 ± 0.04 0.44 ± 0.04 46 ± 3 0.05 ± 0.01 W3110 0.67 ±0.01 0.81 ± 0.06 112 ± 2 0.08 ± 0.02 MG1655 0.65 ± 0.02 0.55 ± 0.02 73 ± 2 0.07 ± 0.02 BW25113 0.80 ± 0.02 0.37 ± 0.02 50 ± 2 0.04 ± 0.02 From this preliminary screening strains BL21, BW25113 and W were selected to be evaluated for 3HB production. The plasmid for 3HB production (pJBGT3RX) was inserted in these three strains and AF1000- T3RX was used as the reference strain. The evaluation for 3HB production was performed in nitrogen-depleted batch with a total duration of 24 hours (Figure 33). In this low-cell-density screening, AF1000-T3RX had the highest 3HB and acetate production, with final concentrations of 4.1 g L-1 and 3.8 g L-1, respectively (Figure 33). Cultivations using the strains
82 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
BW25113-T3RX and W-T3RX resulted in intermediate concentration of 3HB and acetate, with neither the highest 3HB titer nor the lowest acetate formation. Strain BL21-T3RX resulted in the lowest acetate concentration (0.4 g L-1), but also had the lowest final 3HB concentration (2.0 g L-1) (Figure 33). However, comparing the ratio of 3HB produced per acetate produced, 1.1 g g-1 for AF1000-T3RX, 3 g g-1 for W-T3RX, 1.8 g g-1 for BW25113-T3RX and 5.5 g g-1 for BL21-T3RX, shows the potential of BL21 for high-cell-density cultivations during 3HB production, where hitherto one of the main problems was growth inhibition by acetate accumulation.
) 6 1.2 -1
(g g 5 1.0
3HB/HAc 4 0.8 Y )
), -1 -1
3 0.6 µ (h
2 0.4 ), HAc (g L -1 1 0.2
3HB (g L 0 0 AF1000-T3RX W-T3RX BW25113-T3RX BL21-T3RX
[3HB] [HAc] Y3HB/HAc µ
Figure 33. Nitrogen-depleted batch cultivations to evaluate (R)-3-hydroxybutyrate and acetate production by four selected E. coli strains. Box (A) shows the yield of acetate on glucose
(YHAc/s) and the yield of (R)-3-hydroxybutyrate on glucose (Y3HB/s). Box (B) shows the specific growth rate (μ), and the final concentrations of (R)-3-hydroxybutyrate ([3HB]) and acetate ([HAc]) after 24 hours. Bars represent the average and mean deviation of duplicate cultivations, with the exception of W-T3RX, which was performed in triplicate. Subsequently, a BL21 strain with the 3HB pathway and overexpression of zwf was evaluated in the previously successfully used high-cell-density nitrogen-limited fed-batch cultivation. During the initial repeated batch phase, BL21-T3RXzwf did not show any growth inhibition and consequently the duration of this phase was much shorter (11.5 h) compared to the reference strain in which the phase took 19.5 h. At the start of the nitrogen-limited phase the acetate concentration of BL21 was 0.9 g L-1, which it was 12 times lower than AF1000-T3RXzwf (10.1 g L-1) (Figure 34). The decreased acetate inhibition for BL21-T3RXzwf, resulted in Mariel Perez-Zabaleta | 83
increased metabolic activity, which was reflected in a high volumetric productivity of 1.52 g L-1 h-1 at the beginning of the nitrogen-limited phase with an overall average of this phase of 1.27 g L-1 h-1. In contrast to AF1000- T3RXzwf, BL21-T3RXzwf showed a 2.3-fold increase in the final 3HB titer (16.3 g L-1 versus 7.0 g L-1), a 2.3-fold higher final CDW (47.1 g L-1 versus 20.1 g L-1) and a 3-fold higher volumetric 3HB productivity during the nitrogen-limited fed-batch phase (1.27 g L-1 h-1 versus 0.42 g L-1 h-1) (Figure 34).
A: AF1000-T3RXzwf B: BL21-T3RXzwf Repeated Batch Fedbatch Repeated Batch Fedbatch 50 200 Glucose Glucose Glucose consumed (g L
) CDW CDW -1 40 (NH4)2SO4 (NH4)2SO4 160
30 120 , CDW (g L 4 20 80 SO 2 ) 4 10 40 -1 (NH ) 0 0 [3HB] [3HB] 16 [HAc] [HAc] 0.8 µ µ ) µ (h -1 12 0.6 -1 8 0.4 )
3HB, HAc (g L 4 0.2
0 0 1.5 r 0.3 r3HB 3HB rHAc rHAc q q ) 3HB q3HB 3HB -1 qHAc h qHAc , q -1 1.0 0.2 HAc (g L (g g h HAc
, r 0.5 0.1 -1 3HB ) r
0 0 4 8 12 16 20 24 4 8 12 16 20 24 Time (h) Time (h) Figure 34. High-cell-density nitrogen-limited fed-batch cultivations of (A) AF1000-T3RXzwf and (B) BL21-T3RXzwf. Parameters: cell dry weight (CDW, filled circles), accumulative glucose consumed (Glucose, open circles), ammonium sulfate ((NH4)2SO4, inverted open triangles), specific growth rate (μ, crosses and dotted line), (R)-3-hydroxybutyrate ([3HB], closed squares), acetate ([HAc], open squares), pyruvate ([Pyr], open triangles). The specific
3HB production rate (q3HB, dash-dotted line), volumetric 3HB productivity (r3HB, dashed line), specific acetate production rate (qHAc, dotted line) and volumetric acetate productivity (rHAc, solid line) as calculated from spline-fit of the raw data.
84 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
This approach demonstrated how careful selection of the strain background together with an evaluation of all cultivation parameters, such as specific growth rate and byproduct formation, can result in high volumetric productivities of 3HB (1.52 g L-1 h-1) and high 3HB titers (16.3 g L-1). Mariel Perez-Zabaleta | 85
3. CONCLUSION AND FUTURE PERSPECTIVES
The work presented in this thesis contributes knowledge to develop scalable microbial production of (R)-hydroxybutyrate, which is a chiral molecule with two functional groups and it is a promising platform chemical. The starting point for the investigation was microbial 3HB production using Escherichia coli as the model microorganism and the genes β-ketothiolase and acetoacetyl-CoA reductase from Halomonas boliviensis. In order to reach the high rates, titers and yields required for industrial production of a microbial product, extensive enhancement of cell metabolism, growth conditions and scalability is necessary. Process- engineering strategies in this thesis demonstrated that carbon-excess was required for 3HB production and nitrogen-depleted conditions resulted in high yields, while nitrogen-limited cultivations predominantly increased titers and volumetric productivities. To combine the strategies of nitrogen depletion and limitation to further improve 3HB production, the author proposes a cultivation protocol containing three phases: (i) a repeated batch phase, where a large amount of cells are formed at a maximum growth rate without exceeding the heat- and oxygen-transfer capacity of the bioreactor (ii) a nitrogen-limited fed-batch phase, where the growth rate and, consequently, the respiration is controlled by feeding the nitrogen source. This can further increase cell-density, which allows high volumetric productivities and high final 3HB titers (iii) a nitrogen-depleted phase that will start after reaching high cell concentrations and in which the yield can be enhanced by redirecting the sugar consumption to the formation of 3HB. For a further increase of the 3HB yield, it will also be interesting to study 3HB production in nitrogen-depleted batch with cell recycling and nitrogen-limited conditions in retentostat. Additionally, another interesting condition to study is oxygen limitation, in which the process can be performed in two phases, an aerobic exponential growth phase to allow cell formation at maximum growth rates and a second phase of oxygen limitation to redirect the carbon source to 3HB production. Microbial production of 3HB in E. coli requires the introduction of β-ketothiolase and acetoacetyl-CoA reductase. The level of expression of
86 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
these enzymes should be high enough to allow fast synthesis of the product, while being carefully balanced to avoid excretion of intermediates products or imposing a metabolic burden to the cell from overproduction of protein. Under many conditions tested in this thesis, the strains excreted acetate, which might be an indication that there is room for improvement by increasing the pull of the 3HB pathway. One way to achieve this can be optimization of the expression of the thiolase, by either codon optimization, alteration of the ribosomal binding strength or expression of different (heterologous) thiolases. The condensation of two acetyl-CoA molecules into acetoacetyl-CoA catalyzed by thiolase, has a positive Gibbs free-energy under standard conditions. An increased acetyl-CoA pool should make the thiolase-mediated condensation reaction more thermodynamically favorable. Therefore, increasing the availability of acetyl-CoA is expected to have a big impact on the driving force of this reaction. One way to increase the availability of acetyl-CoA is the insertion of a phosphoketolase, which can carry out the phosphorolysis of both fructose-6-phosphate (F6P) and xylulose-5-phosphate (X5P) into glyceraldehyde-3-phosphate and acetyl phosphate. Acetyl phosphate can subsequently be converted to acetyl-CoA by phosphotransacetylase. For this strategy it is important to avoid conversion of acetyl phosphate to acetate through either direct hydrolysis or the action of acetate kinase (ackA). Cofactor regeneration is a common limiting factor in recombinant production and alleviating this limitation can increase the activity of the 3HB pathway. In this thesis, the 3HB production pathway used an acetoacetyl-CoA reductase (rx), that has a cofactor preference for NADPH. To increase the cofactor availability, the overexpression of glucose-6- phosphate dehydrogenase encoded by the gene zwf resulted in an overall improvement of 3HB production. If the Entner Doudoroff pathway is activated or expressed, deletion of glyceraldehyde-3-phosphate dehydrogenase (gapA) can re-route the metabolic flux through this pathway, and thereby further improve regeneration of NADPH. Alternatively, incorporation of phosphoribulokinase and ribulose-1,5- bisphosphate carboxylase/oxygenase (RuBisCo) might enable re-use of excess NADH from the current metabolic pathway, thereby increasing the 3HB yield on sugar. In this thesis two strategies were identified that both decreased acetate formation: (i) Overexpression of yciA decreased acetate formation Mariel Perez-Zabaleta | 87
by providing a bigger pull on the acetyl-CoA pool by the 3HB pathway. (ii) E. coli BL21 showed dramatically reduced acetate formation and consequently produced the hitherto highest described volumetric productivity of 3HB (1.52 g L-1 h-1) and the highest 3HB concentration (16.3 g L-1) achieved by a recombinant process. Future research should investigate if these two strategies can be combined to even further improve 3HB production. Chromosomal insertion of the heterologous genes might decrease the plasmid burden, as well as simultaneously create a more robust strain applicable at industrial scale. In addition to proof-of-principle cultivation and metabolic engineering concepts, this thesis also demonstrated 3HB production by simultaneous consumption of a mixture of glucose, xylose and arabinose. Although promising, translation of these results to real-life lignocellulosic hydrolysates requires further study on the effect of inhibitory compounds present in lignocellulosic hydrolysates on growth and 3HB production. In summary, the work presented in this thesis contributes to the current knowledge of design of strains and processes for production of a medium value product in a biorefinery context. In the future, these concepts can not only contribute to economically-viable production of 3HB, but are also applicable to a wider range of biorefinery products.
88 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
4. ACKNOWLEDGEMENTS
Thanks to everyone who has made possible the present work! I express my sincerest gratitude. First, I would like to start by thanking my wonderful supervisors, without you this journey would never be possible. Thank you, Gen Larsson, my supervisor who always motivated me and pushed me to give the best, who is my friend and has always shown me her support. Thank you, Ton van Maris, for all the nice discussions that always make me grow up as a scientist, for always had time for me, no matter how busy you were, for all your dedication in this thesis and for teaching me so many things, I have learned incredibly much from you! Thank you for always had an advice for me when I needed it. Thank you, Jorge Quillaguamán, for your invaluable help, for always had time to discuss my experiments, for your dedication in this project and for all your support along these years. Thanks to Sida and Formas for the financing support and make possible this research. Thank you, Martin Gustavsson, for all your help regarding cloning research, for your contribution to the articles, for your patience to teach me to use some of the equipment in the lab and always be willing to help. Thanks to Per Berglund for his valuable comments and help me to increase the quality of this thesis. Thanks to my co-authors. Mónica Guevara-Martínez, thanks for all the shared moments, for our scientific and not so scientific discussions and for all the work that we have done together. Gustav Sjöberg, the “magic hands” as we say to you, who always was willing to help in the lab. Thanks for all the fruitful discussion we had, for your contribution to article III and for always keeping interested in what we are doing. Thanks to Johan Jarmander and Jaroslav Belotserkovsky for a short but pleasant time together, for all the help in the lab and all the work that resulted in paper I. Thanks to Magnus Lindroos, David Hörnström, Teun Keil and Johannes Yayo for all the laughter moments, for your contagious enthusiasm, and nice lunches together. Mariel Perez-Zabaleta | 89
Thanks to all colleagues at the Department of Industrial Biotechnology for providing a nice work environment, an especial thank you to Ye, Nils, Hubert, Liang, Caijuan, Brigita, Lina, Atefeh, Johan N., Caroline B., Anna Klara, Sandhya, Berndt, Meeri, Emil, Martin D., Veronique, Guna, Andres, Lubna, Kaj, Erika R., Erika H. Thanks to all my Bolivian and not Bolivian friends, for all the nice moments together and for be part of my life. Thanks to my lovely husband, Daniel Doria Medina, who has always believed in me and in my capacity, much more than I myself had mostly. You have seen all the faces that my PhD has placed on me, you have always been present in my happy and not so happy moments and you always have a magical ability to turn most things into something positive. Without all your love and support, I would not have enjoyed this PhD as much as I did. ¡Gracias mi amor, te amo mucho! Gracias a mi mamita, Roxana, por ser mi consejera y el motor que me incentiva a seguir, por todo el esfuerzo que pusiste en mi formación, por siempre haber creído en mí, por mostrarme tu amor cada día y siempre estar pendiente de mí. Esta tesis es un logro tuyo también, te amo muchísimo. Gracias a mis dos hermanas Ane y Anahita, por ser mis cómplices, mis amigas, por todo el amor que me demuestran aun cuando no estemos cerca, son demasiado importantes en mi vida, las amo muchísimo. Gracias a toda mi familia: a mi abuelito Jaime Zavaleta y a mi tío Jaime que siempre estuvieron en mi vida demostrándome su amor y por que fueron como mis papás; a mi tía Rocío que siempre me llena de elogios, por motivarme y alentarme a seguir; a mis primos Gabito y Ale; a mis hermosos sobrinos Santiago, Ignacio y Alejandro a los que amo muchísimo y me llenan de amor; a mi cuñado Adolfo; y a mi familia política Nancy, Luis, Sergio, Adrian, Zoe y Sofia. Gracias a todos por ser parte de mi vida, sin todo su amor y apoyo no estaría donde estoy ahora.
90 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
5. ABBREVIATIONS
3HB (R)-3-hydroxybutyrate 3HB-CoA (R)-3-hydroxybutyrate-Coenzyme A ABC ATP-binding cassette ABE Acetone-butanol-ethanol AC Adenylate cyclase Ac-CoA Acetyl- Coenzyme A AcAc-CoA Acetoacetyl- Coenzyme A ackA Acetate kinase AF1000-T3RX AF1000 pJBGT3RX AF1000-T3RXzwf AF1000 pJBGT3RX pBADzwf AF1000-T3RX-yciA AF1000 pJBGT3RX pBAD-(Km)-yciA AF1000-T3RX-zwfyciA AF1000 pJBGT3RX pBAD-(Km)- zwf-yciA Ara Arabinose ATP Adenosine triphosphate BL21-T3RX BL21 pJBGT3RX BL21-T3RXzwf BL21 pJBGT3RX pBADzwf BW25113-T3RX BW25113 pJBGT3RX cAMP Cyclic adenosine monophosphate CAP Catabolite activator protein CCR Carbon catabolite repression CDW Cell dry weight CoA Coenzyme A D Dilution rate DNA Deoxyribonucleic acid E. coli Escherichia coli EII Enzyme II EIIGlc Enzyme II D-glucose-specific FDA Food and Drug Administration gnd 6-phosphogluconate dehydrogenase Glc Glucose Glu Glutamate HAc Acetic acid H. boliviensis Halomonas boliviensis His6-tag Hexa histidine-tag HPr Histidine protein Mariel Perez-Zabaleta | 91
IEA International Energy Agency iclR Isocitrate lyase regulator icd Isocitrate dehydrogenase IPTG Isopropyl β-D-1-thiogalactopyranoside kDa Kilodalton KG a-ketoglutarate NAD Nicotinamide adenine dinucleotide NADP Nicotinamide adenine dinucleotide phosphate N-depleted Nitrogen-depleted N-limited Nitrogen-limited OD600 Optical density at 600 nm Omp Outer membrane protein PBS Polybutylene succinate PDO 1,3-Propanediol PEP Phosphoenolpyruvate PET Polyethylene terephthalate PHA Polyhydroxyalkanoate PHB Poly(3-hydroxybutyrate) Pi Phosphorous P-depleted Phosphorous -depleted P-limited Phosphorous -limited p Product PLA Polylactide PPP Pentose phosphate pathway PEP: PTS Phosphoenolpyruvate (PEP): carbohydrate phosphotransferase system (PTS) ppGpp Guanosine tetraphosphate poxB Pyruvate oxidase Pyr Pyruvate PPA652ara-T3RX PPA652ara pJBGT3RX pta Phosphotransacetylase q Specific production rate Q Total production rate r Volumetric production rate RNA Ribonucleic acid rx Acetoacetyl-CoA reductase s Substrate S. cerevisiae Saccharomyces cerevisiae
92 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
t3 β-ketothiolase TCA cycle Tricarboxylic acid cycle USDA United States Department of Agriculture W-T3RX W pJBGT3RX Xyl Xylose x Cells Y Yield yciA YciA acyl-CoA thioesterase zwf Glucose-6-phosphate dehydrogenase µ Specific growth rate Mariel Perez-Zabaleta | 93
6. REFERENCES
1. Soetaert W, Vandamme E: The impact of industrial biotechnology. Biotechnol J 2006, 1:756-769. 2. BP statistical oil prices [https://www.bp.com/en/global/corporate/energy- economics/statistical-review-of-world-energy/oil/oil-prices.html] 3. Oil (brent) in usd - historical prices [https://markets.businessinsider.com/commodities/historical-prices/oil- price/usd/1.1.2004_13.12.2018?type=brent] 4. Madureira NL: Oil reserves and peak oil. In Key Concepts in Energy. Edited by Madureira NL. Cham: Springer International Publishing; 2014: 101-130. 5. BP statistical oil reserves [https://www.bp.com/en/global/corporate/energy- economics/statistical-review-of-world-energy/oil/oil-reserves.html] 6. Statistical review of world energy – all data, 1965-2017 [https://www.bp.com/en/global/corporate/energy-economics/statistical-review-of- world-energy.html] 7. Szulejko JE, Kumar P, Deep A, Kim KH: Global warming projections to 2100 using simple CO2 greenhouse gas modeling and comments on CO2 climate sensitivity factor. Atmos Pollut Res 2017, 8:136-140. 8. Boden TA, Marland G, Andres RJ: Global, regional, and national fossil-fuel CO2 Emissions.: U.S. Department of Energy; 2017. 9. BP statistical CO₂ emissions [https://www.bp.com/en/global/corporate/energy- economics/statistical-review-of-world-energy/co2-emissions.html] 10. Sustainable development goals [https://www.un.org/sustainabledevelopment/] 11. (OECD) Ofec-oad: The bioeconomy to 2030: designing a policy agenda. 2009. 12. A sustainable bioeconomy for Europe: strengthening the connection between economy, society and the environment [https://ec.europa.eu/research/bioeconomy/pdf/ec_bioeconomy_strategy_2018.pdf# view=fit&pagemode=none] 13. The bioeconomy strategy [https://ec.europa.eu/research/bioeconomy/images/bioeconomy_graphic_full.jpg] 14. Task 42: Biorefineries [https://www.iea-bioenergy.task42- biorefineries.com/en/ieabiorefinery/Activities.htm] 15. Cherubini F, Jungmeier G, Wellisch M, Willke T, Skiadas I, Van Ree R, de Jong E: Toward a common classification approach for biorefinery systems. Biofuels Bioprod Biorefin 2009, 3:534-546. 16. Kamm B, Kamm M: Principles of biorefineries. Appl Microbiol Biotechnol 2004, 64:137-145. 17. Cherubini F: The biorefinery concept: using biomass instead of oil for producing energy and chemicals. Energ Convers Manage 2010, 51:1412-1421. 18. Lynd LR, Wyman CE, Gerngross TU: Biocommodity engineering. Biotechnol Prog 1999, 15:777-793. 19. Willke T, Vorlop KD: Industrial bioconversion of renewable resources as an alternative to conventional chemistry. Appl Microbiol Biotechnol 2004, 66:131- 142. 20. Taarning E, Osmundsen CM, Yang X, Voss B, Andersen SI, Christensen CH: Zeolite-catalyzed biomass conversion to fuels and chemicals. Energy Environ Sci 2011, 4:793-804. 21. Huber GW: Breaking the chemical and engineering barriers to lignocellulosic biofuels: next generation hydrocarbon biorefineries. NSF: University of
94 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
Massachusetts Amherst. National Science Foundation. Chemical, Bioengineering, Environmental, and Transport Systems Division.; 2008. 22. Mussatto SI, Teixeira JA: Lignocellulose as raw material in fermentation processes. In Current research, technology and education topics in applied microbiology and microbial biotechnology. Formatex; 2010: 897-907. 23. Saha BC: Enzymes as biocatalysts for conversion of lignocellulosic biomass to fermentable sugars. Boca Raton: CRC Press LLC; 2005: 1-12. 24. All about switchgrass [http://milan.tennessee.edu/research/switchgrass%20info.asp] 25. Sugarcane crop cycle (India) [https://agrocommodities.wordpress.com/sugar/sugarcane-growth-cycleindia/] 26. FitzPatrick M, Champagne P, Cunningham MF, Whitney RA: A biorefinery processing perspective: treatment of lignocellulosic materials for the production of value-added products. Bioresour Technol 2010, 101:8915-8922. 27. Mosier N, Wyman C, Dale B, Elander R, Lee YY, Holtzapple M, Ladisch M: Features of promising technologies for pretreatment of lignocellulosic biomass. Bioresour Technol 2005, 96:673-686. 28. Parisi F: Advances in lignocellulosics hydrolysis and in the utilization of the hydrolyzates. (Engineering/Biotechnology AiB ed., vol. 38. pp. 53-87. Berlin, Heidelberg: Springer Berlin Heidelberg; 1989: 53-87. 29. Saha BC, Iten LB, Cotta MA, Wu YV: Dilute acid pretreatment, enzymatic saccharification and fermentation of wheat straw to ethanol. Process Biochem 2005, 40:3693-3700. 30. Werpy T, Petersen G: Top value added chemicals from biomass: volume I - results of screening for potential candidates from sugars and synthesis gas. United States: U.S. Department of Energy; 2004. 31. Isikgor FH, Becer CR: Lignocellulosic biomass: a sustainable platform for the production of bio-based chemicals and polymers. Polym Chem 2015, 6:4497- 4559. 32. Zhang J, Zhuang J, Lin L, Liu S, Zhang Z: Conversion of D-xylose into furfural with mesoporous molecular sieve MCM-41 as catalyst and butanol as the extraction phase. Biomass Bioenergy 2012, 39:73-77. 33. Palmqvist E, Hahn-Hägerdal B: Fermentation of lignocellulosic hydrolysates. I: inhibition and detoxification. Bioresour Technol 2000, 74:17-24. 34. Zabed H, Faruq G, Sahu JN, Azirun MS, Hashim R, Boyce AN: Bioethanol production from fermentable sugar juice. Sci World J 2014, 2014:957102. 35. Huffer S, Roche CM, Blanch HW, Clark DS: Escherichia coli for biofuel production: bridging the gap from promise to practice. Trends Biotechnol 2012, 30:538-545. 36. Jullesson D, David F, Pfleger B, Nielsen J: Impact of synthetic biology and metabolic engineering on industrial production of fine chemicals. Biotechnol Adv 2015, 33:1395-1402. 37. Gabriel CL: Butanol Fermentation Process. Ind Eng Chem 1928, 20:1063-1067. 38. Gabriel CL, Crawford FM: Development of the butyl-acetonic fermentation industry. Ind Eng Chem 1930, 22:1163-1165. 39. Paulino de Souza J, Dias do Prado C, Eleutherio ECA, Bonatto D, Malavazi I, Ferreira da Cunha A: Improvement of Brazilian bioethanol production - challenges and perspectives on the identification and genetic modification of new strains of Saccharomyces cerevisiae yeasts isolated during ethanol process. Fungal Biol 2018, 122:583-591. 40. Biofuels [https://ec.europa.eu/energy/en/topics/renewable-energy/biofuels] 41. U.S. ethanol prodution plants [http://www.ethanolproducer.com/plants/listplants/US/Operational/All] Mariel Perez-Zabaleta | 95
42. Golden JS, Handfield R, Pascual-Gonzalez J, Agsten B, Brennan T, Khan L, True E: Indicators of the U.S. biobased economy. (USDA USDoA ed. United States: Office of Energy Policy and New Uses. Office of the Chief Economist; 2018. 43. World fuel ethanol production [https://ethanolrfa.org/resources/industry/statistics/#1537559649968-e206480c- 7160] 44. Bai FW, Anderson WA, Moo-Young M: Ethanol fermentation technologies from sugar and starch feedstocks. Biotechnol Adv 2008, 26:89-105. 45. Jansen MLA, Bracher JM, Papapetridis I, Verhoeven MD, de Bruijn H, de Waal PP, van Maris AJA, Klaassen P, Pronk JT: Saccharomyces cerevisiae strains for second-generation ethanol production: from academic exploration to industrial implementation. FEMS Yeast Res 2017, 17. 46. U.S. ethanol second-generation production plants [http://www.ethanolproducer.com/plants/listplants/US/Operational/D3] 47. Public data for the Renewable Fuel Standard 2018 [https://www.epa.gov/fuels- registration-reporting-and-compliance-help/public-data-renewable-fuel-standard] 48. Durre P: Biobutanol: an attractive biofuel. Biotechnol J 2007, 2:1525-1534. 49. Berezina OV, Zakharova NV, Yarotsky CV, Zverlov VV: Microbial producers of butanol. Appl Biochem Microbiol 2012, 48:625-638. 50. Nair RV, Green EM, Watson DE, Bennett GN, Papoutsakis ET: Regulation of the sol locus genes for butanol and acetone formation in Clostridium acetobutylicum ATCC 824 by a putative transcriptional repressor. J Bacteriol 1999, 181:319-330. 51. Ezeji TC, Qureshi N, Blaschek HP: Acetone butanol ethanol (ABE) production from concentrated substrate: reduction in substrate inhibition by fed-batch technique and product inhibition by gas stripping. Appl Microbiol Biotechnol 2004, 63:653-658. 52. Qureshi N, Blaschek H: Recent advances in ABE fermentation: hyper-butanol producing Clostridium beijerinckii BA101. J Ind Microbiol Biotechnol 2001, 27:287-291. 53. García V, Päkkilä J, Ojamo H, Muurinen E, Keiski RL: Challenges in biobutanol production: How to improve the efficiency? Renewable Sustainable Energy Rev 2011, 15:964-980. 54. Gu Y, Jiang Y, Wu H, Liu X, Li Z, Li J, Xiao H, Shen Z, Dong H, Yang Y, et al: Economical challenges to microbial producers of butanol: feedstock, butanol ratio and titer. Biotechnol J 2011, 6:1348-1357. 55. Xu P, Gu Q, Wang W, Wong L, Bower AG, Collins CH, Koffas MA: Modular optimization of multi-gene pathways for fatty acids production in E. coli. Nat Commun 2013, 4:1409. 56. Choi YJ, Lee SY: Microbial production of short-chain alkanes. Nature 2013, 502:571-574. 57. Amyris: a cutting-edge biotechnology platform, from farnesene to farnesane. [https://www.total.com/en/energy-expertise/projects/bioenergies/amyris- biotechnology-platform] 58. Cho HU, Park JM: Biodiesel production by various oleaginous microorganisms from organic wastes. Bioresour Technol 2018, 256:502-508. 59. Gujjala LKS, Kumar SPJ, Talukdar B, Dash A, Kumar S, Sherpa KC, Banerjee R: Biodiesel from oleaginous microbes: opportunities and challenges. Biofuels 2017:1-15. 60. Li Y, Horsman M, Wu N, Lan CQ, Dubois-Calero N: Biofuels from microalgae. Biotechnol Prog 2008, 24:815-820. 61. Bioplastics, facts and figures [https://docs.european- bioplastics.org/publications/EUBP_Facts_and_figures.pdf] 62. Auras R, Harte B, Selke S: An overview of polylactides as packaging materials. Macromol Biosci 2004, 4:835-864.
96 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
63. Pawar RP, Tekale SU, Shisodia SU, Totre JT, Domb AJ: Biomedical Applications of poly(Lactic Acid). Recent Pat Regener Med 2014, 4:40-51. 64. Natureworks: green chemistry’s contribution to biotechnology innovation, commercialization, and strategic positioning [https://www.acs.org/content/dam/acsorg/greenchemistry/industriainnovation/Nature Works-business-case-study.pdf] 65. Madison LL, Huisman GW: Metabolic engineering of poly(3- hydroxyalkanoates): from DNA to plastic. Microbiol Mol Biol Rev 1999, 63:21-53. 66. Steinbuchel A, Fuchtenbusch B: Bacterial and other biological systems for polyester production. Trends Biotechnol 1998, 16:419-427. 67. Chen GQ, Wu Q: The application of polyhydroxyalkanoates as tissue engineering materials. Biomaterials 2005, 26:6565-6578. 68. Rehm BHA: Bacterial polymers: biosynthesis, modifications and applications. Nat Rev Microbiol 2010, 8:578. 69. Chen GQ: A microbial polyhydroxyalkanoates (PHA) based bio- and materials industry. Chem Soc Rev 2009, 38:2434-2446. 70. Park SJ, Choi JI, Lee SP: Short-chain-length polyhydroxyalkanoates: synthesis in metabolically engineered Escherichia coli and medical applications. J Microbiol Biotechnol 2005, 15:206-215. 71. Balakrishna PA, Jaya KA, Kumarapillai H: Enhanced production of poly(3- hydroxybutyrate) in recombinant Escherichia coli and EDTA-microwave- assisted cell lysis for polymer recovery. AMB Express 2018, 8:142. 72. Berwig KH, Baldasso C, Dettmer A: Production and characterization of poly(3- hydroxybutyrate) generated by Alcaligenes latus using lactose and whey after acid protein precipitation process. Bioresour Technol 2016, 218:31-37. 73. Dey P, Rangarajan V: Improved fed-batch production of high-purity PHB (poly- 3 hydroxybutyrate) by Cupriavidus necator (MTCC 1472) from sucrose-based cheap substrates under response surface-optimized conditions. 3 Biotech 2017, 7:310. 74. Diaz-Barrera A, Urtuvia V, Padilla-Cordova C, Pena C: Poly(3-hydroxybutyrate) accumulation by Azotobacter vinelandii under different oxygen transfer strategies. J Ind Microbiol Biotechnol 2018, 46:13-19. 75. Rivera-Terceros P, Tito-Claros E, Torrico S, Carballo S, Van-Thuoc D, Quillaguamán J: Production of poly(3-hydroxybutyrate) by Halomonas boliviensis in an air-lift reactor. J Biol Res (Thessalon) 2015, 22:8. 76. Lee SY, Wong HH, Choi J, Lee SH, Lee SC, Han CS: Production of medium- chain-length polyhydroxyalkanoates by high-cell-density cultivation of Pseudomonas putida under phosphorus limitation. Biotechnol Bioeng 2000, 68:466-470. 77. Chodak I: Polyhydroxyalkanoates: origin, properties and applications. In Monomers, Polymers and Composites from Renewable Resources. Edited by Belgacem MN, Gandini A. Amsterdam: Elsevier; 2008: 451-477. 78. Tepha medical devices [https://www.tepha.com/about-us/overview/] 79. Davis R, Kataria R, Cerrone F, Woods T, Kenny S, O'Donovan A, Guzik M, Shaikh H, Duane G, Gupta VK, et al: Conversion of grass biomass into fermentable sugars and its utilization for medium chain length polyhydroxyalkanoate (mcl- PHA) production by Pseudomonas strains. Bioresour Technol 2013, 150:202- 209. 80. Cerrone F, Choudhari SK, Davis R, Cysneiros D, O'Flaherty V, Duane G, Casey E, Guzik MW, Kenny ST, Babu RP, O'Connor K: Medium chain length polyhydroxyalkanoate (mcl-PHA) production from volatile fatty acids derived from the anaerobic digestion of grass. Appl Microbiol Biotechnol 2014, 98:611- 620. Mariel Perez-Zabaleta | 97
81. Cesário MTF, de Almeida MCMD: Lignocellulosic hydrolysates for the production of polyhydroxyalkanoates. In Microorganisms in biorefineries. Edited by Kamm B. Berlin, Heidelberg: Springer Berlin Heidelberg; 2015: 79-104. 82. Pleissner D, Lam WC, Han W, Lau KY, Cheung LC, Lee MW, Lei HM, Lo KY, Ng WY, Sun Z, et al: Fermentative polyhydroxybutyrate production from a novel feedstock derived from bakery waste. Biomed Res Int 2014, 2014:819474. 83. Yu J, Stahl H: Microbial utilization and biopolyester synthesis of bagasse hydrolysates. Bioresour Technol 2008, 99:8042-8048. 84. Koller M, Atlić A, Dias M, Reiterer A, Braunegg G: Microbial PHA production from waste raw materials. In Plastics from bacteria: natural functions and applications. Edited by Chen GG-Q. Berlin, Heidelberg: Springer Berlin Heidelberg; 2010: 85- 119. 85. Bengtsson S, Werker A, Christensson M, Welander T: Production of polyhydroxyalkanoates by activated sludge treating a paper mill wastewater. Bioresour Technol 2008, 99:509-516. 86. Chen X, Yin J, Ye J, Zhang H, Che X, Ma Y, Li M, Wu L-P, Chen G-Q: Engineering Halomonas bluephagenesis TD01 for non-sterile production of poly(3- hydroxybutyrate-co-4-hydroxybutyrate). Bioresour Technol 2017, 244:534-541. 87. Jiang X-R, Chen G-Q: Morphology engineering of bacteria for bio-production. Biotechnol Adv 2016, 34:435-440. 88. Xiao-Ran J, Jin Y, Xiangbin C, Guo-Qiang C: Halomonas and pathway engineering for bioplastics production. Methods Enzymol 2018, 608:309-328. 89. Pollak P: Fine chemicals: the industry and the business. 2nd edn2011. 90. Saxena S: Microbes in production of commodity chemicals. In Applied Microbiology. New Delhi: Springer India; 2015: 71-81. 91. Bozell JJ, Petersen GR: Technology development for the production of biobased products from biorefinery carbohydrates-the US Department of Energy’s “Top 10” revisited. Green Chem 2010, 12:539. 92. Castillo Martinez FA, Balciunas EM, Salgado JM, Domínguez González JM, Converti A, Oliveira RPdS: Lactic acid properties, applications and production: a review. Trends Food Sci Technol 2013, 30:70-83. 93. Datta R, Henry M: Lactic acid: recent advances in products, processes and technologies -a review. J Appl Chem Biotechnol 2006, 81:1119-1129. 94. Es I, Mousavi Khaneghah A, Barba FJ, Saraiva JA, Sant'Ana AS, Hashemi SMB: Recent advancements in lactic acid production - a review. Food Res Int 2018, 107:763-770. 95. Sauer M, Porro D, Mattanovich D, Branduardi P: Microbial production of organic acids: expanding the markets. Trends Biotechnol 2008, 26:100-108. 96. Valli M, Sauer M, Branduardi P, Borth N, Porro D, Mattanovich D: Improvement of lactic acid production in Saccharomyces cerevisiae by cell sorting for high intracellular pH. Appl Environ Microbiol 2006, 72:5492-5499. 97. Porro D, Brambilla L, Ranzi BM, Martegani E, Alberghina L: Development of metabolically engineered Saccharomyces cerevisiae cells for the production of lactic acid. Biotechnol Prog 1995, 11:294-298. 98. Bretz I, Bretz K, Kabasci S, Kopitzky R, Springer A: Succinic acid: a new platform chemical for biobased polymers from renewable resources. Chem Eng Technol 2008, 31:647-654. 99. Li Q, Xing J: Microbial succinic acid production using different bacteria species. In Microorganisms in biorefineries. Edited by Kamm B. Berlin, Heidelberg: Springer Berlin Heidelberg; 2015: 183-206. 100. Beauprez JJ, De Mey M, Soetaert WK: Microbial succinic acid production: Natural versus metabolic engineered producers. Process Biochem 2010, 45:1103-1114.
98 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
101. Yan D, Wang C, Zhou J, Liu Y, Yang M, Xing J: Construction of reductive pathway in Saccharomyces cerevisiae for effective succinic acid fermentation at low pH value. Bioresour Technol 2014, 156:232-239. 102. Ma JF, Jiang M, Chen KQ, Xu B, Liu SW, Wei P, Ying HJ, Chang HN, Ouyang PK: Strategies for efficient repetitive production of succinate using metabolically engineered Escherichia coli. Bioprocess Biosyst Eng 2011, 34:411-418. 103. Li C, Gao S, Yang X, Lin CSK: Green and sustainable succinic acid production from crude glycerol by engineered Yarrowia lipolytica via agricultural residue based in situ fibrous bed bioreactor. Bioresour Technol 2018, 249:612-619. 104. Okino S, Noburyu R, Suda M, Jojima T, Inui M, Yukawa H: An efficient succinic acid production process in a metabolically engineered Corynebacterium glutamicum strain. Appl Microbiol Biotechnol 2008, 81:459-464. 105. Jansen ML, van Gulik WM: Towards large scale fermentative production of succinic acid. Curr Opin Biotechnol 2014, 30:190-197. 106. Reverdia’s bio-based succinic acid plant, Italy [https://www.chemicals- technology.com/projects/reverdia-bio-based-succinic-acid-plant-italy/] 107. Myriant succinic acid biorefinery (MySAB) [https://www1.eere.energy.gov/bioenergy/pdfs/ibr_arra_myriant.pdf] 108. Kuhnert P, Scholten E, Haefner S, Mayor D, Frey J: Basfia succiniciproducens gen. nov., sp. nov., a new member of the family Pasteurellaceae isolated from bovine rumen. Int J Syst Evol Microbiol 2010, 60:44-50. 109. Biobased succinic acid, technology [http://www.succinity.com/biobased-succinic- acid/technology] 110. Biobased succinic acid report looks at technology, market, and applications [http://biofuelsdigest.com/nuudigest/2018/02/28/biobased-succinic-acid-report- looks-at-technology-market-and-applications/] 111. (OECD) OfEC-oaD: Future prospects for industrial biotechnology.2011. 112. Philp JC, Ritchie RJ, Allan JE: Biobased chemicals: the convergence of green chemistry with industrial biotechnology. Trends Biotechnol 2013, 31:219-222. 113. United States Department of Agriculture (USDA) Ootce, Office of energy policy and new uses: U.S. Biobased products market potential and projections through 2025. 2008. 114. Peplow M: Looking for cheaper routes to malaria medicines. In Chemical&Engineering news, vol. 96. pp. 29-312018: 29-31. 115. Martin VJJ, Pitera DJ, Withers ST, Newman JD, Keasling JD: Engineering a mevalonate pathway in Escherichia coli for production of terpenoids. Nat Biotechnol 2003, 21:796. 116. Paddon CJ, Westfall PJ, Pitera DJ, Benjamin K, Fisher K, McPhee D, Leavell MD, Tai A, Main A, Eng D, et al: High-level semi-synthetic production of the potent antimalarial artemisinin. Nature 2013, 496:528. 117. Westfall PJ, Pitera DJ, Lenihan JR, Eng D, Woolard FX, Regentin R, Horning T, Tsuruta H, Melis DJ, Owens A, et al: Production of amorphadiene in yeast, and its conversion to dihydroartemisinic acid, precursor to the antimalarial agent artemisinin. Proc Natl Acad Sci U S A 2012, 109:E111-118. 118. Ding MZ, Yan HF, Li LF, Zhai F, Shang LQ, Yin Z, Yuan YJ: Biosynthesis of taxadiene in Saccharomyces cerevisiae : selection of geranylgeranyl diphosphate synthase directed by a computer-aided docking strategy. PLoS One 2014, 9:e109348. 119. McPhee D, Pin A, Kizer L, Perelman L: Squalane from sugarcane. In Cosmetics & Toiletries magazine vol. 129. Emeryville, CA, USA 2014. 120. Trans-β-farnesene. Amyris's renewable hydrocarbon bulding-block [http://farnesene.net/] 121. Patents Assigned to Amyris Biotechnologies, Inc. [https://patents.justia.com/assignee/amyris-biotechnologies-inc] Mariel Perez-Zabaleta | 99
122. What’s the most energy-efficient crop source for ethanol? [https://grist.org/article/biofuel-some-numbers/] 123. Lopes ML, Paulillo SC, Godoy A, Cherubin RA, Lorenzi MS, Giometti FH, Bernardino CD, Amorim Neto HB, Amorim HV: Ethanol production in Brazil: a bridge between science and industry. Braz J Microbiol 2016, 47 Suppl 1:64-76. 124. Godoy A, Amorim H, Lopes M, Oliveira AJ: Continuous and batch fermentation processes: Advantages and disadvantages of these processes in the Brazilian ethanol production. Int Sugar J 2008, 110:175-181. 125. Macedo N, Brigham C: From beverages to biofuels: The journeys of ethanol- producing microorganisms. Int J Biotechnol Wellness Ind 2014, 3:79-87. 126. Schmid RD, Hammelehle R: Pocket guide to biotechnology and genetic engineering.: Wiley; 2003. 127. Zeng A-P, Biebl H: Bulk chemicals from biotechnology: the case of 1,3- propanediol production and the new trends. Adv Biochem Eng Biotechnol 2002, 74:239-259. 128. Cameron DC, Altaras NE, Hoffman ML, Shaw AJ: Metabolic engineering of propanediol pathways. Biotechnol Prog 1998, 14:116-125. 129. Boenigk R, Bowien S, Gottschalk G: Fermentation of glycerol to 1,3-propanediol in continuous cultures of Citrobacter freundii. Appl Microbiol Biotechnol 1993, 38:453-457. 130. Günzel B, Yonsel S, Deckwer W-D: Fermentative production of 1,3-propanediol from glycerol by Clostridium butyricum up to a scale of 2 m3. Appl Microbiol Biotechnol 1991, 36:289-294. 131. Reimann A, Biebl H: Production of 1,3-propanediol by Clostridium butyricum DSM 5431 and product tolerant mutants in fedbatch culture: feeding strategy for glycerol and ammonium. Biotechnol Lett 1996, 18:827-832. 132. Pflugmacher U, Gottschalk G: Development of an immobilized cell reactor for the production of 1,3-propanediol by Citrobacter freundii. Appl Microbiol Biotechnol 1994, 41:313-316. 133. Nakamura CE, Whited GM: Metabolic engineering for the microbial production of 1,3-propanediol. Curr Opin Biotechnol 2003, 14:454-459. 134. Silva VF, Nakanishi SC, Dionísio SR, Rossell CE, Ienczak JL, Gonçalves AR, Rocha GJ: Using cell recycling batch fermentations to validate a setup for cellulosic ethanol production. J Chem Technol Biotechnol 2016, 91:1853-1859. 135. Lee CW, Chang HN: Kinetics of ethanol fermentations in membrane cell recycle fermentors. Biotechnol Bioeng 1987, 29:1105-1112. 136. Kwon S, Yoo IK, Lee WG, Chang HN, Chang YK: High-rate continuous production of lactic acid by Lactobacillus rhamnosus in a two-stage membrane cell-recycle bioreactor. Biotechnol Bioeng 2001, 73:25-34. 137. Tashiro Y, Takeda K, Kobayashi G, Sonomoto K: High production of acetone- butanol-ethanol with high cell density culture by cell-recycling and bleeding. J Biotechnol 2005, 120:197-206. 138. Chisti Y: Fermentation technology. In Industrial Biotechnology. Edited by W. Soetaert, Vandamme EJ2010. 139. Nielsen J: Penicillin production in fed-batch cultures. In Physiological engineering aspects of Penicillium Chrysogenum. 1997: 241-260. 140. Lievense JC, Crater JS: Scale-up of industrial microbial processes. FEMS Microbiol Lett 2018, 365. 141. Noorman HJ, Heijnen JJ: Biochemical engineering’s grand adventure. Chem Eng Sci 2017, 170:677-693. 142. Shokri A, Sanden AM, Larsson G: Cell and process design for targeting of recombinant protein into the culture medium of Escherichia coli. Appl Microbiol Biotechnol 2003, 60:654-664. 143. DiRienzo JM, Inouye M: Lipid fluidity-dependent biosynthesis and assembly of the outer membrane proteins of E. coli. Cell 1979, 17:155-161.
100 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
144. Knivett VA, Cullen J: Some factors affecting cyclopropane acid formation in Escherichia coli. Biochem J 1965, 96:771-776. 145. Otero JM, Nielsen J: Industrial systems biology. Biotechnol Bioeng 2010, 105:439-460. 146. Buschke N, Schäfer R, Becker J, Wittmann C: Metabolic engineering of industrial platform microorganisms for biorefinery applications – Optimization of substrate spectrum and process robustness by rational and evolutive strategies. Bioresour Technol 2013, 135:544-554. 147. Goeddel DV, Kleid DG, Bolivar F, Heyneker HL, Yansura DG, Crea R, Hirose T, Kraszewski A, Itakura K, Riggs AD: Expression in Escherichia coli of chemically synthesized genes for human insulin. Proc Natl Acad Sci U S A 1979, 76:106- 110. 148. Baeshen NA, Baeshen MN, Sheikh A, Bora RS, Ahmed MM, Ramadan HA, Saini KS, Redwan EM: Cell factories for insulin production. Microb Cell Fact 2014, 13:141. 149. Lassenius MI, Pietiläinen KH, Kaartinen K, Pussinen PJ, Syrjänen J, Forsblom C, Pörsti I, Rissanen A, Kaprio J, Mustonen J, et al: Bacterial endotoxin activity in human serum is associated with dyslipidemia, insulin resistance, obesity, and chronic inflammation. Diabetes Care 2011, 34:1809. 150. Ivanova EP, Bazaka K, Crawford RJ: Natural polymer biomaterials: advanced applications. In New Functional Biomaterials for Medicine and Healthcare. Edited by Ivanova EP, Bazaka K, Crawford RJ: Woodhead Publishing; 2014: 32-70. 151. Chong BF, Blank LM, Mclaughlin R, Nielsen LK: Microbial hyaluronic acid production. Appl Microbiol Biotechnol 2005, 66:341-351. 152. Adamczyk PA, Reed JL: Escherichia coli as a model organism for systems metabolic engineering. Curr Opin Syst Biol 2017, 6:80-88. 153. Porro D, Gasser B, Fossati T, Maurer M, Branduardi P, Sauer M, Mattanovich D: Production of recombinant proteins and metabolites in yeasts: when are these systems better than bacterial production systems? Appl Microbiol Biotechnol 2011, 89:939-948. 154. Wurm FM: Production of recombinant protein therapeutics in cultivated mammalian cells. Nat Biotechnol 2004, 22:1393-1398. 155. Woolston BM, Edgar S, Stephanopoulos G: Metabolic engineering: past and future. Annu Rev Chem Biomol Eng 2013, 4:259-288. 156. Backus MP, Stauffer JF: The production and selection of a family of strains in Penicillium chrysogenum. Mycologia 1955, 47:429-463. 157. Barrios-Gonzalez J, Fernández F, Tomasini A: Microbial secondary metabolites production and strain improvement. Indian J Biotechnol 2003, 2:322-333. 158. Novick A, Szilard L: Experiments with the chemostat on spontaneous mutations of bacteria. Proc Natl Acad Sci 1950, 36:708. 159. Bailey JE, Sburlati A, Hatzimanikatis V, Lee K, Renner WA, Tsai PS: Inverse metabolic engineering: a strategy for directed genetic engineering of useful phenotypes. Biotechnol Bioeng 2002, 79:568-579. 160. Bailey J: Toward a science of metabolic engineering. Science 1991, 252:1668- 1675. 161. Sander JD, Joung JK: CRISPR-Cas systems for editing, regulating and targeting genomes. Nat Biotechnol 2014, 32:347-355. 162. Nielsen J: Metabolic engineering. Appl Microbiol Biotechnol 2001, 55:263-283. 163. Keasling JD: Manufacturing molecules through metabolic engineering. Science 2010, 330:1355-1358. 164. Gardner RG, Hampton RY: A highly conserved signal controls degradation of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase in eukaryotes. J Biol Chem 1999, 274:31671-31678. Mariel Perez-Zabaleta | 101
165. Ro DK, Paradise EM, Ouellet M, Fisher KJ, Newman KL, Ndungu JM, Ho KA, Eachus RA, Ham TS, Kirby J, et al: Production of the antimalarial drug precursor artemisinic acid in engineered yeast. Nature 2006, 440:940-943. 166. Paradise EM, Kirby J, Chan R, Keasling JD: Redirection of flux through the FPP branch-point in Saccharomyces cerevisiae by down-regulating squalene synthase. Biotechnol Bioeng 2008, 100:371-378. 167. Pfefferle W, Mockel B, Bathe B, Marx A: Biotechnological manufacture of lysine. Adv Biochem Eng Biotechnol 2003, 79:59-112. 168. Eggeling L, Bott M: Handbook of Corynebacterium glutamicum.2005. 169. de Graaf AA, Eggeling L, Sahm H: Metabolic engineering for L-lysine production by Corynebacterium glutamicum. In Metabolic Engineering. Edited by Nielsen J, Eggeling L, Dynesen J, Gárdonyi M, Gill RT, de Graaf AA, Hahn-Hägerdal B, Jönsson LJ, Khosla C, Licari R, et al. Berlin, Heidelberg: Springer Berlin Heidelberg; 2001: 9-29. 170. Deutscher J: The mechanisms of carbon catabolite repression in bacteria. Curr Opin Microbiol 2008, 11:87-93. 171. Desai TA, Rao CV: Regulation of arabinose and xylose metabolism in Escherichia coli. Appl Environ Microbiol 2010, 76:1524-1532. 172. Jarmander J, Hallström BM, Larsson G: Simultaneous uptake of lignocellulose- based monosaccharides by Escherichia coli. Biotechnol Bioeng 2014, 111:1108- 1115. 173. Kayikci O, Nielsen J: Glucose repression in Saccharomyces cerevisiae. FEMS Yeast Res 2015, 15. 174. Lagunas R: Sugar transport in Saccharomyces cerevisiae. FEMS Microbiol Rev 1993, 10:229-242. 175. Wisselink HW, Toirkens MJ, del Rosario Franco Berriel M, Winkler AA, van Dijken JP, Pronk JT, van Maris AJ: Engineering of Saccharomyces cerevisiae for efficient anaerobic alcoholic fermentation of L-arabinose. Appl Environ Microbiol 2007, 73:4881-4891. 176. Wisselink HW, Toirkens MJ, Wu Q, Pronk JT, van Maris AJ: Novel evolutionary engineering approach for accelerated utilization of glucose, xylose, and arabinose mixtures by engineered Saccharomyces cerevisiae strains. Appl Environ Microbiol 2009, 75:907-914. 177. Gong Z, Nielsen J, Zhou YJ: Engineering robustness of microbial cell factories. Biotechnol J 2017, 12. 178. Hasunuma T, Ismail KSK, Nambu Y, Kondo A: Co-expression of TAL1 and ADH1 in recombinant xylose-fermenting Saccharomyces cerevisiae improves ethanol production from lignocellulosic hydrolysates in the presence of furfural. J Biosci Bioeng 2014, 117:165-169. 179. Gonzalez-Ramos D, Gorter de Vries AR, Grijseels SS, van Berkum MC, Swinnen S, van den Broek M, Nevoigt E, Daran JM, Pronk JT, van Maris AJ: A new laboratory evolution approach to select for constitutive acetic acid tolerance in Saccharomyces cerevisiae and identification of causal mutations. Biotechnol Biofuels 2016, 9:173. 180. Ohashi T, Hasegawa J: D-(-)-β-hydroxycarboxylic acids as raw materials for captopril and β-Lactams. Cheminform 1992:269. 181. Ren Q, Ruth K, Thöny-Meyer L, Zinn M: Process engineering for production of chiral hydroxycarboxylic acids from bacterial polyhydroxyalkanoates. Macromol Rapid Commun 2007, 28:2131-2136. 182. Seebach D, Chow H-F, Jackson RFW, Sutter MA, Thaisrivongs S, Zimmermann J: (+)-11,11′-di-o-methylelaiophylidene – preparation from elaiophylin and total synthesis from (R)-3-hydroxybutyrate and (S)-malate. Liebigs Ann Chem 1986, 1986:1281-1308.
102 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
183. Toshiyuki C, Takeshi N: A synthetic approach to (+)-thienamycin from methyl (R)-3-hydroxybutanoate. A new entry to (3R, 4R)-3-[(R)-1-hydroxyethyl]-4- acetoxy-2-azetidinone. Chem Lett 1985, 14:651-654. 184. Kashiwaya Y, Takeshima T, Mori N, Nakashima K, Clarke K, Veech RL: D-beta- hydroxybutyrate protects neurons in models of Alzheimer's and Parkinson's disease. Proc Natl Acad Sci U S A 2000, 97:5440-5444. 185. Leoni V, Masterman T, Mousavi FS, Wretlind B, Wahlund LO, Diczfalusy U, Hillert J, Bjorkhem I: Diagnostic use of cerebral and extracerebral oxysterols. Clin Chem Lab Med 2004, 42:186-191. 186. Zou XH, Li HM, Wang S, Leski M, Yao YC, Yang XD, Huang QJ, Chen GQ: The effect of 3-hydroxybutyrate methyl ester on learning and memory in mice. Biomaterials 2009, 30:1532-1541. 187. Si J, Wang S, Liu N, Yang X, Wang Y, Li L, Wang J, Lv X: Anticonvulsant effect of exogenous β-hydroxybutyrate on kainic acid-induced epilepsy. Exp Ther Med 2017, 14:765-770. 188. Massieu L, Haces ML, Montiel T, Hernandez-Fonseca K: Acetoacetate protects hippocampal neurons against glutamate-mediated neuronal damage during glycolysis inhibition. Neurosci 2003, 120:365-378. 189. Newman JC, Verdin E: β-hydroxybutyrate: much more than a metabolite. Diabetes Res Clin Pract 2014, 106:173-181. 190. Zou Z, Sasaguri S, Rajesh KG, Suzuki R: dl-3-Hydroxybutyrate administration prevents myocardial damage after coronary occlusion in rat hearts. Am J Physiol Heart Circ Physiol 2002, 283:H1968-H1974. 191. Zhao Y, Zou B, Shi Z, Wu Q, Chen G-Q: The effect of 3-hydroxybutyrate on the in vitro differentiation of murine osteoblast MC3T3-E1 and in vivo bone formation in ovariectomized rats. Biomaterials 2007, 28:3063-3073. 192. Klein AH, Wendroth SM, Drewes LR, Andrews MT: Small-volume d-beta- hydroxybutyrate solution infusion increases survivability of lethal hemorrhagic shock in rats. Shock 2010, 34:565-572. 193. Beta-hydroxybutyrate [https://pubchem.ncbi.nlm.nih.gov/compound/3- hydroxybutyrate#section=Top] 194. Ren Q, Ruth K, Thöny-Meyer L, Zinn M: Enatiomerically pure hydroxycarboxylic acids: current approaches and future perspectives. Appl Microbiol Biotechnol 2010, 87:41-52. 195. Utaka M, Watabu H, Higashi H, Sakai T, Tsuboi S, Torii S: Asymmetric reduction of aliphatic short- to long-chain beta-keto acids by use of fermenting bakers' yeast. J Org Chem 1990, 55:3917-3921. 196. Lee Y, Park SH, Lim IT, Han K, Lee SY: Preparation of alkyl (R)-(-)-3- hydroxybutyrate by acidic alcoholysis of poly-(R)-(-)-3-hydroxybutyrate. Enzyme Microb Technol 2000, 27:33-36. 197. Seebach D, Züger M: Über die depolymerisierung von poly-(R)-3-hydroxy- buttersäureester (PHB). 1982, 65:495-503. 198. Seebach D, Beck AK, Breitschuh R, Job K: Direct degradation of the biopolymer poly[(R)-3-hydroxybutyric acid] to (R)-3-hydroxybutanoic acid and its methyl ester. In Organic Syntheses. Volume 71. Edited by Wiley1993: 39-47. 199. Calabia BP, Tokiwa Y: A novel PHB depolymerase from a thermophilic Streptomyces sp. Biotechnol Lett 2006, 28:383-388. 200. Lee SY, Lee Y, Wang F: Chiral compounds from bacterial polyesters: Sugars to plastics to fine chemicals. Biotechnol Bioeng 1999, 65:363-368. 201. Kawata Y, Kawasaki K, Shigeri Y: Efficient secreted production of (R)-3- hydroxybutyric acid from living Halomonas sp. KM-1 under successive aerobic and microaerobic conditions. Appl Microbiol Biotechnol 2012, 96:913- 920. Mariel Perez-Zabaleta | 103
202. Lee SY, Lee Y: Metabolic engineering of Escherichia coli for production of enantiomerically pure (R)-(-)-hydroxycarboxylic acids. Appl Environ Microbiol 2003, 69:3421-3426. 203. Wu Q, Zheng Z, Xi J-Z, Gao H, Chen G-Q: Production of hydroxyalkanoate monomers by microbial fermentation. J Chem Eng Jpn 2003, 36:1170-1173. 204. Zhao K, Tian G, Zheng Z, Chen J-C, Chen G-Q: Production of D-(−)-3- hydroxyalkanoic acid by recombinant Escherichia coli. FEMS Microbiol Lett 2003, 218:59-64. 205. Gao HJ, Wu Q, Chen GQ: Enhanced production of D-(-)-3-hydroxybutyric acid by recombinant Escherichia coli. FEMS Microbiol Lett 2002, 213:59-65. 206. Quillaguamán J, Hashim S, Bento F, Mattiasson B, Hatti-Kaul R: Poly(beta- hydroxybutyrate) production by a moderate halophile, Halomonas boliviensis LC1 using starch hydrolysate as substrate. J Appl Microbiol 2005, 99:151-157. 207. Quillaguamán J, Muñoz M, Mattiasson B, Hatti-Kaul R: Optimizing conditions for poly(beta-hydroxybutyrate) production by Halomonas boliviensis LC1 in batch culture with sucrose as carbon source. Appl Microbiol Biotechnol 2007, 74:981-986. 208. Quillaguamán J, Doan-Van T, Guzmán H, Guzmán D, Martin J, Everest A, Hatti- Kaul R: Poly(3-hydroxybutyrate) production by Halomonas boliviensis in fed- batch culture. Appl Microbiol Biotechnol 2008, 78:227-232. 209. Van-Thuoc D, Quillaguamán J, Mamo G, Mattiasson B: Utilization of agricultural residues for poly(3-hydroxybutyrate) production by Halomonas boliviensis LC1. J Appl Microbiol 2008, 104:420-428. 210. Guzmán H, Van-Thuoc D, Martin J, Hatti-Kaul R, Quillaguamán J: A process for the production of ectoine and poly(3-hydroxybutyrate) by Halomonas boliviensis. Appl Microbiol Biotechnol 2009, 84:1069-1077. 211. Quillaguamán J, Hatti-Kaul R, Mattiasson B, Alvarez MT, Delgado O: Halomonas boliviensis sp. nov., an alkalitolerant, moderate halophile isolated from soil around a Bolivian hypersaline lake. Int J Syst Evol Microbiol 2004, 54:721-725. 212. Quillaguamán J, Delgado O, Mattiasson B, Hatti-Kaul R: Poly(β-hydroxybutyrate) production by a moderate halophile, Halomonas boliviensis LC1. Enzyme Microb Technol 2006, 38:148-154. 213. Blattner FR, Plunkett G, Bloch CA, Perna NT, Burland V, Riley M, Collado-Vides J, Glasner JD, Rode CK, Mayhew GF, et al: The complete genome sequence of Escherichia coli K-12. Science 1997, 277:1453-1462. 214. Clomburg JM, Gonzalez R: Biofuel production in Escherichia coli: the role of metabolic engineering and synthetic biology. Appl Microbiol Biotechnol 2010, 86:419-434. 215. Rosano GL, Ceccarelli EA: Recombinant protein expression in Escherichia coli: advances and challenges. Front Microbiol 2014, 5:172. 216. E. coli (IMAGE), Michigan State University. [https://www.eurekalert.org/multimedia/pub/103041.php?from=311428] 217. Bauer AP, Dieckmann SM, Ludwig W, Schleifer KH: Rapid identification of Escherichia coli safety and laboratory strain lineages based on Multiplex- PCR. FEMS Microbiol Lett 2007, 269:36-40. 218. Agency USEP: Final risk assessment of Escherichia coli K-12 derivatives. 1997. 219. Daegelen P, Studier FW, Lenski RE, Cure S, Kim JF: Tracing ancestors and relatives of Escherichia coli B, and the derivation of B strains REL606 and BL21(DE3). J Mol Biol 2009, 394:634-643. 220. Gottesman S: Proteases and their targets in Escherichia coli. Annu Rev Genet 1996, 30:465-506. 221. Phue JN, Noronha SB, Hattacharyya R, Wolfe AJ, Shiloach J: Glucose metabolism at high density growth of E. coli B and E. coli K: differences in metabolic pathways are responsible for efficient glucose utilization in E. coli
104 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
B as determined by microarrays and Northern blot analyses. Biotechnol Bioeng 2005, 90:805-820. 222. Casali N: Escherichia coli host strains. Methods Mol Biol 2003, 235:27-48. 223. Lieb M, Weigle JJ, Kellenberger E: A study of hybrids between two strains of Escherichia coli. J Bacteriol 1955, 69:468-471. 224. Archer CT, Kim JF, Jeong H, Park JH, Vickers CE, Lee SY, Nielsen LK: The genome sequence of E. coli W (ATCC 9637): comparative genome analysis and an improved genome-scale reconstruction of E. coli. BMC Genomics 2011, 12:9. 225. Bachmann BJ: Pedigrees of some mutant strains of Escherichia coli K-12. Bacteriol Rev 1972, 36:525-557. 226. Hayashi K, Morooka N, Yamamoto Y, Fujita K, Isono K, Choi S, Ohtsubo E, Baba T, Wanner BL, Mori H, Horiuchi T: Highly accurate genome sequences of Escherichia coli K-12 strains MG1655 and W3110. Mol Syst Biol 2006, 2:2006.0007. 227. Baba T, Ara T, Hasegawa M, Takai Y, Okumura Y, Baba M, Datsenko KA, Tomita M, Wanner BL, Mori H: Construction of Escherichia coli K-12 in-frame, single- gene knockout mutants: the Keio collection. Mol Syst Biol 2006, 2:2006.0008. 228. Grenier F, Matteau D, Baby V, Rodrigue S: Complete genome sequence of Escherichia coli BW25113. Genome Announc 2014, 2:e01038-01014. 229. Peters JE, Thate TE, Craig NL: Definition of the Escherichia coli MC4100 genome by use of a DNA array. J Bacteriol 2003, 185:2017-2021. 230. Sanden AM, Prytz I, Tubulekas I, Forberg C, Le H, Hektor A, Neubauer P, Pragai Z, Harwood C, Ward A, et al: Limiting factors in Escherichia coli fed-batch production of recombinant proteins. Biotechnol Bioeng 2003, 81:158-166. 231. Magnusson LU, Farewell A, Nyström T: ppGpp: a global regulator in Escherichia coli. Trends Microbiol 2005, 13:236-242. 232. Carneiro S, Villas-Bôas SG, Ferreira EC, Rocha I: Influence of the RelA activity on E. coli metabolism by metabolite profiling of glucose-limited chemostat cultures. Metabolites 2012, 2:717-732. 233. Guzmán D, Balderrama-Subieta A, Cardona-Ortuño C, Guevara-Martínez M, Callisaya-Quispe N, Quillaguamán J: Evolutionary patterns of carbohydrate transport and metabolism in Halomonas boliviensis as derived from its genome sequence: influences on polyester production. Aquat Biosyst 2012, 8:9. 234. Matsumoto Ki, Tanaka Y, Watanabe T, Motohashi R, Ikeda K, Tobitani K, Yao M, Tanaka I, Taguchi S: Directed evolution and structural analysis of NADPH- dependent acetoacetyl Coenzyme A (acetoacetyl-CoA) reductase from Ralstonia eutropha reveals two mutations responsible for enhanced kinetics. Appl Environ Microbiol 2013, 79:6134-6139. 235. Perez-Zabaleta M, Sjöberg G, Guevara-Martínez M, Jarmander J, Gustavsson M, Quillaguamán J, Larsson G: Increasing the production of (R)-3-hydroxybutyrate in recombinant Escherichia coli by improved cofactor supply. Microb cell fact 2016, 15:91-91. 236. Tseng H-C, Martin CH, Nielsen DR, Prather KLJ: Metabolic engineering of Escherichia coli for enhanced production of (R)- and (S)-3-Hydroxybutyrate. Appl Environ Microbiol 2009, 75:3137. 237. McMahon MD, Prather KLJ: Functional screening and in vitro analysis reveal thioesterases with enhanced substrate specificity profiles that improve short- chain fatty acid production in Escherichia coli. Appl Environ Microbiol 2014, 80:1042. 238. Kaback HR: Active transport in Escherichia coli: passage to permease. Annu Rev Biophys Biophys Chem 1986, 15:279-319. 239. Postma PW, Lengeler JW, Jacobson GR: Phosphoenolpyruvate: carbohydrate phosphotransferase systems of bacteria. Microbiol Rev 1993, 57:543-594. Mariel Perez-Zabaleta | 105
240. Picon A, Teixeira de Mattos MJ, Postma PW: Reducing the glucose uptake rate in Escherichia coli affects growth rate but not protein production. Biotechnol Bioeng 2005, 90:191-200. 241. Steinsiek S, Bettenbrock K: Glucose transport in Escherichia coli mutant strains with defects in sugar transport systems. J Bacteriol 2012, 194:5897. 242. Jarmander J, Belotserkovsky J, Sjöberg G, Guevara-Martínez M, Perez-Zabaleta M, Quillaguamán J, Larsson G: Cultivation strategies for production of (R)-3- hydroxybutyric acid from simultaneous consumption of glucose, xylose and arabinose by Escherichia coli. Microb Cell Fact 2015, 14:51. 243. Shimizu K: Regulation systems of bacteria such as Escherichia coli in response to nutrient limitation and environmental stresses. Metabolites 2013, 4:1-35. 244. Wanner U, Egli T: Dynamics of microbial growth and cell composition in batch culture. FEMS Microbiol Rev 1990, 6:19-43. 245. Guevara-Martínez M, Sjöberg Gällnö K, Sjöberg G, Jarmander J, Perez-Zabaleta M, Quillaguamán J, Larsson G: Regulating the production of (R)-3-hydroxybutyrate in Escherichia coli by N or P limitation. Front Microbiol 2015, 6:844. 246. Gottschalk G: Bacterial Metabolism. Second Edition edn. New York, NY: New York, NY: Springer New York; 1986. 247. Brumaghim JL, Li Y, Henle E, Linn S: Effects of hydrogen peroxide upon nicotinamide nucleotide metabolism in Escherichia coli: changes in enzyme levels and nicotinamide nucleotide pools and studies of the oxidation of NAD(P)H by Fe(III). J Biol Chem 2003, 278:42495-42504. 248. Liu Q, Ouyang SP, Chung A, Wu Q, Chen GQ: Microbial production of R-3- hydroxybutyric acid by recombinant E. coli harboring genes of phbA, phbB, and tesB. Appl Microbiol Biotechnol 2007, 76:811-818. 249. Cantu DC, Chen Y, Reilly PJ: Thioesterases: a new perspective based on their primary and tertiary structures. Protein Sci 2010, 19:1281-1295. 250. Gully D, Bouveret E: A protein network for phospholipid synthesis uncovered by a variant of the tandem affinity purification method in Escherichia coli. Proteomics 2006, 6:282-293. 251. Ren Y, Aguirre J, Ntamack AG, Chu C, Schulz H: An alternative pathway of oleate beta-oxidation in Escherichia coli involving the hydrolysis of a dead end intermediate by a thioesterase. J Biol Chem 2004, 279:11042-11050. 252. Guevara-Martínez M, Perez-Zabaleta M, Gustavsson M, Quillaguamán J, Larsson G, van Maris AJA: The role of the acyl-CoA thioesterase "YciA" in the production of (R)-3-hydroxybutyrate by recombinant Escherichia coli. Appl Microbiol Biotechnol 2019, 103:3693-3704. 253. Javid-Majd F, Blanchard JS: Mechanistic analysis of the argE-encoded N- acetylornithine deacetylase. Biochem 2000, 39:1285-1293. 254. Kakuda H, Shiroishi K, Hosono K, Ichihara S: Construction of Pta-Ack pathway deletion mutants of Escherichia coli and characteristic growth profiles of the mutants in a rich medium. Biosci Biotechnol Biochem 1994, 58:2232-2235. 255. Chang DE, Shin S, Rhee JS, Pan JG: Acetate metabolism in a pta mutant of Escherichia coli W3110: importance of maintaining acetyl coenzyme A flux for growth and survival. J Bacteriol 1999, 181:6656-6663. 256. Jian J, Zhang SQ, Shi ZY, Wang W, Chen GQ, Wu Q: Production of polyhydroxyalkanoates by Escherichia coli mutants with defected mixed acid fermentation pathways. Appl Microbiol Biotechnol 2010, 87:2247-2256. 257. Waegeman H, Beauprez J, Moens H, Maertens J, De Mey M, Foulquie-Moreno MR, Heijnen JJ, Charlier D, Soetaert W: Effect of iclR and arcA knockouts on biomass formation and metabolic fluxes in Escherichia coli K12 and its implications on understanding the metabolism of Escherichia coli BL21 (DE3). BMC Microbiol 2011, 11:70.
106 | Metabolic engineering and cultivation strategies for recombinant production of (R)-3-hydroxybutyrate
258. Waegeman H, Maertens J, Beauprez J, De Mey M, Soetaert W: Effect of iclR and arcA deletions on physiology and metabolic fluxes in Escherichia coli BL21 (DE3). Biotechnol Lett 2012, 34:329-337. 259. De Mey M, De Maeseneire S, Soetaert W, Vandamme E: Minimizing acetate formation in E. coli fermentations. J Ind Microbiol Biotechnol 2007, 34:689-700. 260. Dittrich CR, Bennett GN, San K-Y: Characterization of the acetate-producing pathways in Escherichia coli. Biotechnol Prog 2005, 21:1062-1067. 261. Berg JM, Tymoczko JL, Stryer L: Entry to the citric acid cycle and metabolism through it are controlled. In Biochemistry. 5th edition. Edited by Freeman WH. New York2002.