Basel Khraiwesh, Kenan Jijakli, Joseph Swift,

Amphun Chaiboonchoe, Rasha Abdrabu, Pei-Wen Chao, Laising Yen and Kourosh Salehi-Ashtiani

Abstract Synthetic Biology is an interdisciplinary approach combining biotech­nology, evolutionary biology, molecular biology, systems biology and biophysics. While the exact definition of Synthetic Biology might still be debatable, its focus on design and construction of biological devices that perform useful functions is clear and of great utility to engineering algae. This relies on the re-engineering of bio­logical circuits and optimization of certain metabolic pathways to reprogram algae and introduce new functions in them via the use of genetic modules. Genetic editing tools are primary enabling techniques in Synthetic Biology and this chapter dis­cusses common techniques that show promise for algal gene editing. The genetic editing tools discussed in this chapter include RNA interference (RNAi) and arti­ficial microRNAs, RNA scaffolds, transcription activator-like effector nucleases (TALENs), RNA guided Cas9 endonucleases (CRISPR), and multiplex automated genome engineering (MAGE). DNA and whole genome synthesis is another enabling technology in Synthetic Biology and might present an alternative approach to drastically and readily modify algae. Clear and powerful examples of the potential of whole genome synthesis for algal engineering are presented. Also, the development of relevant computational tools, and genetic part registries has stim­ulated further advancements in the field and their utility in algal research and engineering is described. For now, the majority of synthetic biology efforts are

B. Khraiwesh • A. Chaiboonchoe • R. Abdrabu • K. Salehi-Ashtiani (H)

Division of Science and Math, and Center for Genomics and Systems Biology (CGSB), New York University Abu Dhabi, 129188, Abu Dhabi, United Arab Emirates e-mail: ksa3@nyu. edu

K. Jijakli

Division of Engineering, New York University Abu Dhabi, 129188, Abu Dhabi United Arab Emirates

J. Swift

Department of Biology, New York University, 12 Waverly Place, New York 10003, USA P.-W. Chao • L. Yen

Department of Pathology and Immunology, Department of Molecular and Cellular Biology, Dan L. Duncan Cancer Center, Baylor College of Medicine, Houston, TX 77030, USA

© Springer International Publishing Switzerland 2015

N. R. Moheimani et al. (eds.), Biomass and Biofuels from Microalgae,

Biofuel and Biorefinery Technologies 2, DOI 10.1007/978-3-319-16640-7_8 focused on microbes as many pressing problems, such as sustainability in food and energy production rely on modification of microorganisms. Synthetic modifications of algal strains to enhance desired physiological properties could lead to improvements in their utility.

8.1 Introduction

More basic research is needed before algal biotechnology can reach a capacity to compete with other systems (Stephen and Joshi 2010). Because many physiologi­cal, morphological, biochemical, or molecular characteristics of algae are quite different from higher plants or animals, algae can meet several requirements that other systems cannot (Hallmann 2007). The demand for improved systems of production of nutraceuticals and cost-effective protein expression systems (both industrial and pharmaceutical applications) lend themselves to explore the potential useful capacities of algae (Hallmann 2007).

Synthetic biology is the design and construction of biological devices and systems for a specific purpose (Ferry et al. 2012). This is an area of biological research and technology that combines biology and engineering, thus often over­lapping with bioengineering and biomedical engineering (Serrano 2007). It encompasses a variety of different approaches, methodologies, and disciplines with a focus on bioengineering and biotechnology. Through the innovative re-engineering of biological circuits and optimization of certain metabolic path­ways, biological modules can be designed to reprogram organisms to produce products, or exhibit desired metabolic behaviors (Khalil and Collins 2010). Synthetic biology can enable model transferability to address a multitude of industrial needs and projects (Anderson et al. 2012). Researchers in this field are realistically optimistic that synthetic biology can provide solutions to a multitude of worldwide problems from health to energy (Purnick and Weiss 2009). The success of synthetic biology as a promising approach is demonstrated by a number of successful attempts in constructing microbial strains to lower production cost of pharmaceutical products (Khalil and Collins 2010). Similarly, there are ongoing works to introduce desirable traits into algae, and to re-engineer algal cells (Ferry et al. 2012; Gimpel et al. 2013; Rabinovitch-Deere et al. 2013).

Although sometimes referred to as genetic engineering, synthetic biology differs in terms of scale, scope, techniques of manipulation, and application (Serrano

2007) . Genetic engineering focuses on the alteration of a single characteristic of an organism through transgenic hybrids or genetic chimeras that carry altered genes, or genes from other organisms. In contrast, synthetic biology seeks to reconfigure, design, and construct new pathways, whole processes, or novel systems for the purpose of achieving some desired biosynthetic activity or phenotype (Alper and Stephanopoulos 2009; Khalil and Collins 2010).

Microalgae exhibit enormous biodiversity, and have the potential for producing large quantities of biomass containing high concentrations of lipids (Gimpel et al.

2013) . Synthetic, systems, and post-genomics biology are terms that are increas­ingly encountered in the biofuels and biotechnology research space with all such approaches likely to be deployed to enable algal biofuels to become economically competitive with fossil fuels. In order to create a viable technology, the field of synthetic biology has been moving towards modular genetic systems. Modularity encompasses the reliance on standardized genetic parts and circuitry models—just like the field of electronics and electric circuits relies on standard collections of resistors, transistors, and capacitors (Fig. 8.1).

RNA-mediated silencing and targeted genome editing tools, including artificial microRNA (Khraiwesh et al. 2011), RNA scaffolds (Delebecque et al. 2012), TALENs, and RNA guided Cas9 endonucleases (Gaj et al. 2013), have allowed synthetic biology to develop gene circuits designed to perform specific functions, often by combining components from multiple organisms to generate novel func­tionality. These new research endeavors will undoubtedly increase our knowledge and usage of these important primary-producing organisms.

Conventional methods used for the removal of heavy metal ions include chemical precipitation, adsorption, chemical oxidation/reduction, membrane filtration, ion exchange, and electrochemical processes. However, these techniques have some drawback, such as partial removal of metal ions, costly installation requirements, high energy demands, and the generation of toxic waste products which require additional elimination stages (Aksu et al. 2002).

Both live and dead cells can be successfully used for the biosorption of metal ions, while uptake of metal ions by living microorganisms, referred to as bioac­cumulation, occurs when an active metabolic process is involved (Aksu et al. 2002; Brady and Duncan 1994; Moreno-Garrido et al. 1998). Biosorption is a reversible process, since it is possible to desorb the metal ions bound to the surfaces of cells by a simple acid treatment, whereas bioaccumulation processes are only partially reversible (de-Bashan and Bashan 2010; Donmez and Aksu 2002; Velasquez and Dussan 2009).

Compared to the other organisms used for biosorption processes, namely fungi, cyanobacteria, and bacteria, algal cells have higher heavy metal biosorption capacities which relates to the different structure and composition of their cell wall (Bayramoglu et al. 2006; Gekeler et al. 1988). Cell walls of different microor­ganisms have different functional groups which are involved in metal ion binding, such as amino, amide, carbonyl, carboxyl, hydroxyl, imidazole, phosphate, sulfate, sulfhydryl, and phenol moieties (Barkley 1991; Schiewer and Volesky 2000). Depending on the variations in the cell wall composition, there will also be dif­ferences in the metal ion binding mechanisms and affinities (Godlewska-Zylkiewicz 2003; Leusch et al. 1995).

The chemical characteristics of the functional adsorbent (i. e., functional groups, polarity, and solubility) are responsible for determining the binding mechanism and the nature of the adsorption process. Different physicochemical forces, such as covalent bonding, van der Waals bonding, ion exchange, and dipole/dipole inter­actions can be responsible for the uptake of ions on the adsorbents (Aksu et al. 2002).

Free cells have some disadvantages when used for large-scale applications of metal ion biosorption studies, due to the otherwise risk of clogging problems on the filters and flow lines. Nevertheless, this problem was overcome by using immo­bilized cells in natural matrices such as carrageenan, alginate, chitosan, agarose; polymeric supports such as polyacrylamide, polypropylene, and polysulfone; cross — linked copolymers; or biomatrices such as sponges (Akhtar et al. 2003a, b; Rob­inson 1998). Some of those studies are highlighted in Table 2.2.

The presence of more than one type of metal ion within the wastewater might have a negative effect on the adsorption of one type of metal ion over another. Mehta and Gaur (2001) observed nearly complete removal of copper and nickel metals by alginate-entrapped C. vulgaris cells when they were in separate solutions. On the other hand, the presence of copper in the nickel solution inhibited the biosorption of both metals either by immobilized or free cells, due to the compe­tition of different metal ions on the same active sites of microalgae. da Costa and Leite (1991) used alginate-immobilized Chlorella homosphaera for the removal of cadmium and zinc metals. They also observed that the biosorption of cadmium and zinc alone was much higher than the case when these two metal ions were combined.

Biological materials were also used as the immobilization matrices for micro­algal cells. da Costa and de Franfa (1996) attached the microalgae Tetraselmis chuii and cyanobacteria Spirulina maxima on the surface of two different seaweeds (Sargassum sp. and the Ulva sp.), which eventually increased the overall cadmium biosorption efficiencies. In series of studies by Akhtar et al., C. sorokiniana algal cells were immobilized on a biological matrix of Luffa cylindrica sponge for the removal of nickel (Akhtar et al. 2003a), cadmium (Akhtar et al. 2003b), chromium (Akhtar et al. 2008), and lead (Akhtar et al. 2004) ions from liquid effluents. L. cylindrica sponge was chosen as the immobilization matrix due its rigid struc­ture, low cost, and high porosity, while its fibrous network provides an efficient contact between the immobilized cells with their surrounding aqueous environment (see Fig. 2.1b). They reported high maximum adsorption capacities in a continuous liquid flow column, as 192 mg cadmium and 71 mg nickel per gram of immobilized biomass. They also achieved successful desorption of cadmium and nickel metal ions with HCl solution, and the regenerated immobilized samples were reusable with a similar biosorption efficiency.

The biosorption of lead (Pb) ions by C. sorokiniana cells immobilized on L. cylindrica sponge was another efficient method, with 96 % adsorption efficiency of the metal ions within the first 5 min of the experiments (Akhtar et al. 2004). They also observed a maximum adsorption of lead ions at around pH 5.0. Higher removal rates were associated with the fibrous structure of the immobilization matrix, increased surface area, and easier access of the targeted metal ion to the sorption sites (Akhtar et al. 2003a, b).

Leusch et al. (1995) used two marine brown algae, Sargassum fluitans and Ascophyllum nodosum, for the biosorption of cadmium, copper, nickel, lead, and zinc heavy metal ions. They observed the highest metal uptakes when the cells were cross-linked with glutaraldehyde, followed by cross-linking with formaldehyde. Both species had the highest biosorption efficiencies for lead and the lowest for zinc. Introducing formaldehyde possibly involves cross-linking of the hydroxylic groups with the sugars of the cell wall, while glutaraldehyde cross-links mostly with the amino groups (Leusch et al. 1995).

Significant amounts of pollutants were removed using a mixed-immobilization of selected consortium of several microalgal species (Chlorella sp., S. obliquus, Stichococcus sp.) and several bacteria (Rhodococcus sp., Kibdelosporangium ari — dum) inside a highly contaminated pond, after the separate immobilization of microalgae and bacteria in solid carriers such as capron fibers and ceramics. They established 62 % copper, 62 % nickel, 90 % zinc, 70 % manganese, and 64 % iron removal efficiencies (Safonova et al. 2004).

Bayramoglu et al. (2006) used immobilized Chlamydomonas reinhardtii cells in calcium alginate beads for the removal of mercury, cadmium, and lead ions from aqueous solutions. They observed the highest adsorption capacities for immobilized cells for a pH in the range 5.0-6.0, achieving mercury, cadmium, and lead ion adsorption capacities of 89.5, 66.5, and 253.6 mg g 1 dry adsorbent, respectively. On the other hand, control samples composed of only calcium alginate beads provided less metal-binding sites and yielded lower adsorption capacities of mercury, cadmium, and lead ions at 32.4, 27.9, and 173.9 mg g-1 dry adsorbent, respectively. Acidic pH conditions were not optimal due to the protonation of the cell wall components. In contrast, mildly acid conditions (pH range 5.0-6.0) allowed sufficient interaction of the heavy metal ions with the carboxylate and phosphate groups of the algal cell wall (Bayramoglu et al. 2006). Neutral pH was found to be the optimal condition for an efficient chromium biosorption by immobilized C. vulgaris and freshwater cyanobacterium A. doliolum cells in alginate (Mallick and Rai 1993).

Barkley (1991) investigated the utilization of immobilized algae in a permeable polymeric matrix for the adsorption of mercury ions from groundwater in both laboratory and pilot-scale field tests. Their resulting immobilization product (AlgaSORB) was quite robust and can be packed within adsorption columns, having sufficient porosity to allow easy diffusion of the ions toward the cells. Field test results showed that AlgaSORB was a highly reasonable alternative to the conventional ion-exchange resins (Barkley 1991).

Nakajima et al. (1982) achieved the removal of uranium ions from both fresh­water and seawater samples using the immobilized cells of Chlorella sp. in poly­acrylamide gels. They also reported that this system can be used several times by applying consecutive adsorption and desorption stages.

Recovery of precious metals with immobilization methods can be a highly cost — effective process. da Costa and Leite (1991) used immobilized C. homosphaera cells within alginate beads for the adsorption of gold metal, which achieved a very high absorption yield of around 90 % of the initial quantity of gold present in solution.

Due to their exclusive catalytic properties, corrosion, and oxidation resistivity, palladium and platinum noble metals have been widely used in various areas from metallurgical processes, chemical synthesis, petroleum processing, electronics to automotive industry (Dziwulska et al. 2004). As a result of the high emission risks of these metals into the environment, it has become important to monitor their concentration in environmental samples. Thus, several microorganisms have been investigated for the separation and preconcentration of some trace metals such as palladium, platinum, copper, cadmium, lead, and gold via biosorption processes, which then allows the use of analytical methods such as atomic absorption spec­trometry and inductively coupled plasma optical emission spectrometry (Carrilho et al. 2003; Dziwulska et al. 2004; Elmahadi and Greenway 1991; Godlewska — Zylkiewicz 2003).

Dziwulska et al. (2004) demonstrated the selective biosorption of palladium and platinum ions from strong acidic solutions (pH below 2), using immobilized C. vulgaris cells on anion-exchange resin Cellex-T. This technique was also used for the preconcentration and analysis of these noble metals for graphite furnace atomic absorption spectrometry in different environmental samples including wastewater, tap water, and grass. Elmahadi and Greenway (1991) used Chlamy — domonus reinhartii and S. capricornutum algal cells immobilized on controlled — pore glass for the preconcentration of copper, silver, and chromium metals for atomic adsorption spectrophotometric detection. In their work, they also found that the presence of some compounds, such as sodium chloride, humic acid, and sodium bicarbonate, can interfere with metal biosorption process by competing for the metal ions. Silica gel was used as the immobilization matrix for Stichococcus bacillaris microalgae for lead preconcentration (Mahan and Holcombe 1992), while silica gel-entrapped Pilayella littoralis brown microalgae was used for the preconcentration of copper, iron, aluminum, and cobalt ions for their detection by inductively coupled plasma optical emission spectrometry (Carrilho et al. 2003).

Due to the low biomass concentration of microalgae (about 0.5 g L-1 in open ponds) and the small size of microalgal cells (usually 5-50 pm), harvesting mic­roalgal biomass is a major challenge (Uduman et al. 2010). Centrifugation is an efficient method for harvesting microalgae; however, this is too energy-intensive for most low-value applications (i. e., biofuels). Options such as flocculation are a promising approach to reduce harvesting costs (Vandamme et al. 2013). During flocculation, individual cells form larger aggregates that can easily be separated from the culture medium by gravity sedimentation, flotation, or enhanced settling in an inclined lamella separator. Using flocculation, the biomass can be concentrated from a dilute culture with a dry matter content of about 0.05 % to a sludge with a dry matter content of 0.5-5 %. Mechanical techniques such as centrifugation or a filter press are required to remove the remaining extracellular water and to obtain a thick paste with a dry matter content of 20 %.

Most HRAPs used for wastewater treatment today contain mixed consortia of microalgae rather than pure cultures. Usually, these communities are dominated relatively large, colony-forming chlorophytes such as Pediastrum, Microctinium, Scenedesmus, Dictyosphaerium, and Coelastrum (Benemann et al. 1980; Park et al. 2013). Possibly, these species are favored by the flow regime generated by the paddle wheel in high-rate algal ponds. These relatively large colonial microalgae often flocculate spontaneously, a process that is referred to as bioflocculation (Park et al. 2011a). Bioflocculating microalgae may form aggregates with other non — bioflocculating species (Salim et al. 2011), and bioflocculated microalgae have high settling rates and can be relatively easily concentrated to a slurry of 1 -3 % dry matter by simple gravity sedimentation (Sheehan et al. 1998). By recycling part of the harvested biomass, the dominance of these bioflocculating microalgae can be maintained (Benemann et al. 1980; Park et al. 2011b, 2013). Bacteria present in the wastewater may also play a role in bioflocculation (Su et al. 2011). Bacteria grow on organic matter present in wastewater, and research by Lee et al. (2008) and Lee et al. (2012) showed that the presence of bacteria in cultures of Chrysotila and Chlorella resulted in flocculation of the microalgal cells. In both studies, it appeared that extracellular polymeric substances produced by the microalgae were involved in the flocculation process. Van den Hende et al. (2011) showed that a sufficient supply of organic matter is important to sustain mixed algal-bacterial flocs.

The high pH that is typical of microalgal cultures can induce precipitation of Ca or Mg salts and can also induce flocculation of microalgal cells; a process that is referred to as autoflocculation. Ca phosphates precipitate at a relatively low pH of about 8.5-9 and can induce flocculation of microalgae. Such pH levels are regularly encountered in outdoor microalgal cultures when irradiance levels and temperatures are high. Flocculation by Ca phosphate precipitation requires relatively high Ca and phosphate concentrations in the wastewater and is therefore only applicable in hard waters with excess phosphate levels (Sukenik and Shelef 1984; Sukenik et al. 1985). While autoflocculation by Ca phosphate works well in laboratory conditions, it often fails in large-scale systems, even when Ca and phosphate concentrations are sufficiently high (Nurdogan and Oswald 1995). This may be due to autoflocculation by Ca phosphate is inhibited by the presence of organic matter in microalgal cultures (Beuckels et al. 2013). Bioflocculation and autoflocculation have been studied in the past 30 years in laboratory conditions and pilot systems. It appears that their performance depends strongly on species and cultivation conditions, yet, the reliability of these methods remains to be proven in long-term and large-scale operations (Benemann et al. 2012). More details on the recent developments on harvesting and dewatering can be found in Chaps. 12—14.

In general, molecular genetic techniques are concerned with manipulating, repro­ducing, adding, and deleting DNA and RNA molecules in an organism. Manipu­lations, deletions, and additions are accomplished via genetic transformation and genetic editing, while reproduction is accomplished via cloning. There are also numerous other methods for genetic and genomic editing; however, transformation and cloning remain an integral part of even the most recently developed methods. Novel techniques are required to make those molecular changes easier to manifest, less time consuming, and more permanent in their effect.

Many organic carbon sources have been investigated for biodiesel production. These include various sugars such as glucose, galactose, fructose, and even some disaccharides. Polyhydric alcohols, such as glycerol, and some organic acids, such as acetate and propionate, have also been investigated. For example, Chlorella protothecoides can grow on a variety of carbon sources such as glucose (Shen et al. 2010; Xiong et al. 2008; Xu et al. 2006), fructose (Gao et al. 2009), sucrose (Gao et al. 2009), glycerol (Heredia-Arroyo et al. 2010), acetate (Heredia-Arroyo et al.

2010) , and reducing sugars from Jerusalem artichoke and sugarcane (Cheng et al.

2009) . Many species have also been reported to grow heterotrophically on ethanol (Ogbonna et al. 1998; Yokochi et al. 1998), lactose, galactose and mannose (Liang et al. 2009), and molasses (Andrade and Costa 2007). Schizochytrium limacinum produced palmitic acid (16:0) as 45-60 % of their dry weight when supplied with glucose, fructose, or glycerol (Yokochi et al. 1998; Chi et al. 2009). The effec­tiveness of these carbon sources varies with the species as well as on the culture conditions such as the light intensity, the pH, dissolved oxygen concentration, and on the presence of other carbon sources. Some carbon sources are good for mixotrophic culture, but not in heterotrophic cultures. For example, according to

Ceron Garcia et al. (2006), Phaeodactylum tricornutum UTEX-640 did not grow heterotrophically in media containing 0.005-0.2 M of fructose, glucose, mannose, lactose, or glycerol. However, addition of any of these organic carbons in mixo — trophic culture increased the biomass concentration and productivity relative to photoautotrophic controls. The biomass, lipids, eicosapentanoic acid (EPA), and pigment contents were considerably enhanced with glycerol and fructose in relation to photoautotrophic controls. The EPA content was barely affected by the sugars, but was more than twofold higher in glycerol-fed cultures than in photoautotrophic controls (Ceron Garcia et al. 2006).

Liu et al. (1999) compared several carbon sources and concluded that glucose was the best in terms of cell growth rate. This contradicts the work of Chen and Walker (2011) who reported that crude glycerol gave the highest growth of Chlorella protothecoides, followed by pure glycerol, while the least biomass concentration was obtained with glucose. In the case of Chlorella vulgaris, Kong et al. (2011) reported that glucose was the best carbon source for mixotrophic cultivation, followed by sucrose and then glycerin, while sodium acetate did not support good growth. Effectiveness of carbon source in supporting cell growth may depend on their energy content (Chojnacka and Marquez-Rocha 2004; Wang et al. 2012). For instance, glucose produces about 2.8 kJ/mol of energy compared to

0. 8 kJ/mol for acetate (Boyle and Morgan 2009), and glucose was more effective as a substrate for mixotrophic cultivation of Phaeodactylum tricornutum than acetate (Wang et al. 2012). The carbon source that gives high biomass productivity may not be the one that gives high oil production. Although for many strains, glucose has been reported to be the best in terms of cell growth, Das et al. (2011) ranked the effectiveness of different organic substrates in terms of intracellular lipid contents in mixotrophic culture in the following order: glycerol > sucrose > glucose.

The cost is another major factor determining the choice of carbon source for mixotrophic/heterotrophic cultures. The present cost of microalgae oil at US$2.4/L (Li et al. 2007; Xu et al. 2006) is 3-4 times higher than that of plant oils. However, Liu et al. (2010) estimated oil production cost of US$0.9/L for heterotrophic cul­tures of Chlorella zofingiensis using sugar as substrate. In heterotrophic/mixo — trophic cultures, the cost of organic carbon represents a very high percentage of the total production cost. Economic analysis shows that organic carbon source con­tributes 45.4 %; inorganic chemicals, 3.2 %; electricity, 30.6 %; steam, 14.2 %; and aseptic air, 6.6 % of the total production cost (Li et al. 2007; Xu et al. 2006). The cost of glucose has also been estimated to be about 80 % of the total medium cost (Li et al. 2007). Thus, there is a need to drastically reduce the cost of the organic carbon source. Many cheap carbon sources such as non-sugar carbon sources (Heredia-Arroyo et al. 2011), corn powder hydrolysate, impure glycerol, and molasses have been investigated.

Currently glycerol is an inexpensive and abundant carbon source generated as a by-product of biodiesel fuel production. About 0.45 kg of glycerol is produced per

4.5 kg of biodiesel, and the price of crude glycerol is now about 0.025USD/0.45 kg (Chen and Walker 2011). It has been reported that crude glycerol is better than pure glycerol and glucose (Chen and Walker 2011; Liang et al. 2010) because of the residual nitrogen in crude glycerol. The use of corn powder hydrolysate has also been widely investigated, and it has been reported that it is superior to glucose solution since it contains some other components that are beneficial for cell growth. For example, C. protothecoides produced 55.2 % crude lipids in a medium con­taining corn hydrolysate, with a cell dry weight concentration of 15.5 g/L (Xu et al.

2006) , which is higher than the values reported for glucose. Li et al. (2007) noted that if hydrolyzed starch is used as a carbon source for Chlorella, the cost of medium can be reduced to about 60-70 %. Cheng et al. (2009) used hydrolysate of Jerusalem artichoke tuber as a carbon source for heterotrophic cultivation of C. protothecoides, and the resulting biomass contained 44 % lipid. The lipid content of microalgae cultivated in the presence of the enzymatic hydrolyzates of sweet sor­ghum (which contains 10 g/L of reducing sugars) was 52.5 %. This is 35.7 % higher than the value obtained by cultivation using glucose (Gao et al. 2009). Anaerobi­cally digested dairy manure (Wang et al. 2010) and wastewater containing 85-90 % carpet mill effluents (Chinnasamy et al. 2010) were used as carbon sources for production of lipids for biofuel. Many agro-industrial wastes such as dry-grind ethanol thin stillage (TS) and soy whey (SW) have been used as nutrient feedstock for mixotrophic/heterotrophic cultivation of Chlorella vulgaris (Mitra et al. 2012). Both the cell concentration (9.8 g/L) and oil content (43 %) obtained with TS were higher than those obtained with modified basal medium containing glucose as the carbon source (8 g/L and 27 %, respectively) under mixotrophic conditions.

The optimal concentrations of these carbon sources vary with both strain and other culture conditions. Concentrations of glycerol used ranged from 3 to 12 % (Yokochi et al. 1998), while Liang et al. (2009) reported that 1 or 2 % glycerol resulted in a higher lipid content of microalgae compared to the value obtained with 5 % glycerol. The tolerable concentration of glycerol is within the range of

0. 7-10 % (Chi et al. 2009). The optimum cassava starch hydrolysate concentration for cell growth and lipid accumulation was 5 g/L, but the values were not signif­icantly different from those obtained with 10 g/L. A higher concentration of 15 g/L of hydrolysate resulted in lower biomass and lipid contents (Salim 2013). The optimum concentration of glucose for growth was 1 g/L, but there were no significant effects of varying acetate or starch concentrations between 0.5 and 5 g/L on cell growth. The highest values of the lipid content and lipid productivity with glucose in media were approximately 2.8 times (at 2.0 g/L glucose) and 4.6 times (at 1.0 g/L glucose) compared to control (photoautotrophic culture). As the content of glucose increased to 5.0 g/L, the total lipid content and lipid productivity decreased, but were still higher than the values obtained in photoautotrophic culture (Wang et al. 2012). On the other hand, starch in the medium did not influence the specific growth rate with concentrations below 1.0 g/L, but was inhibited signifi­cantly above 2.0 g/L (p < 0.05) (Wang et al. 2012).

One of the areas of microalgae biofuels that must be optimized or re-engineered to make production cost-effective is oil extraction. It is estimated that up to 60 % of the cost of algae biodeisel production involves solvent emulsification and recovery (Molina-Grima et al. 2003). The best studied approach to biodiesel production, first developed for oil seed plants, is the extraction and TAGs or triglycerides into FAMEs. The spent biomass can be used for a variety of applications including biogas, feed, and fertilizers. In the past ten years, a number of alternative forms of catalysis have been developed that use lipases (Ranganathan et al. 2008) or make use of solid bases (hydroxyl groups added to mineral crystals) or catalysts that form biodiesel under high pressure. However, the expense of harvesting, drying, and breaking cell walls remains problematic. In addition, organic solvents for oil extraction are expensive and generate hazardous wastes that must be disposed of at further cost (Williams and Laurens 2010).

HTL has recently been adapted to circumvent many of these problems inherent in lipid extraction processes. HTL is a thermal process that heats a wet slurry of intact algae to 250-350 °C at 1500-3000 psi, converting the biomass to several products including an oil portion ranging from 29 to 52 % yield (See Frank et al. 2013 for a recent review). While TLC produces more oil from algae than lipid extraction, there are several issues with the quality of the oil produced based on the inclusion of other cell components (proteins, nucleic acids, carbohydrates) in the thermal process. A life cycle analysis of TLC of several algal strains (Frank et al. 2012) indicated that the lipid fraction had high levels of N (Williams and Laurens

2010) , leaving questions on combustion emissions for fuel use.

Another recent advancement in the field, supercritical fluid extraction (SFE) of algal biomass, may be an efficient means to extract oils that avoids the use of toxic organic solvents, eliminates the need for the energy-intensive drying of biomass, and avoids high N content in the oil. In addition, SFE allows for the co-extraction of high-value chemicals and leaves a residual biomass that is solvent free and could be marketed as a livestock feed supplement or fertilizer. A carbon dioxide supercritical fluid extraction (CO2-SFE) apparatus for oil extraction using water as a co-solvent would avoid the high cost of drying algae while extracting triglycerides and the co-extraction of valuable nutraceuticals using wet algal biomass.

SFE technology is well developed for processes such as decaffeination and dry­cleaning and is now widely accepted for extraction, purification, and fractionation operations in many industries, especially in the nutraceutical and other “green” industries. SFE is far more efficient than traditional solvent separation methods and is selective, providing high purity of specific products. Additionally, there are no organic solvent residues in the extract or spent biomass. Extraction is efficient at modest operating temperatures, for example, at less than 50 °C, thus ensuring product stability (Herrero et al. 2010). CO2-SFE has been shown to be an efficient solvent for the extraction of a valuable nutraceutical docosahexaenoic acid (DHA) (Couto et al. 2010), for which there is a large growing market.

Based on the literature (Patil and Gude 2011; Choi et al. 1987; Couto et al. 2010; Herrero et al. 2010), there are reasonable starting parameters of temperature, chamber, and release pressures for maximum lipid extraction using dry algal bio­mass. The development of CO2-SFE lipid extraction from wet algae cultures has been explored but is still in its infancy. Adjustments of parameters must be made to use water and methanol co-solvents that alter the overall behavior of the extraction process. Slight variation in temperature will significantly alter the density of the solvent, and therefore the efficiency of the extraction of specific lipoid compounds. An increase in temperature also reduces yield of specific fractions due to product degradation (Patil and Gude 2011; Choi et al. 1987). Cell disruption is a major factor in lipid yields independent of extraction process. Using SFE, cell disruption of wet algae is based on chamber and release pressures, water content, and tem­perature treatment to determine the need for cell lysis prior to CO2-SFE. Halim et al. (2011) have demonstrated the efficiency of SFE extraction of triglyceride fractions from intact wet algal biomass. The extraction efficiency for total lipid extraction including valuable co-products, specifically the marketable nutraceuti — cals, DHA, and luteins, makes the cost-benefit analysis of the whole process favorable. The fractionated products of CO2-SFE, ranging in size from free fatty acids, DHA, triglycerides (the feedstock for biodiesel), and carotenoid compounds such as lutein may be fractionated further using liquid chromatography and the triglycerides transesterified to FAMEs. The parameters for extraction of specific lipids from algae and developing methods that balance cost with production of each specific lipid product that can be scaled up for industrial use is of paramount importance. The CO2 used for extraction can also be recycled to support algal photosynthetic growth. The process outlined here has the potential to be entirely renewable and recyclable as well as cost competitive with liquid fuels.

Once the draft network is ready, a mathematical formulation of the network is made through forming a stoichiometric matrix (S). In the matrix (Fig. 10.3b), rows cor­respond to metabolites, and columns assign reactions. The entries in the matrix correspond to the stoichiometric coefficients of each individual metabolite that contributes to each reaction. A negative coefficient indicates the consumption of a metabolite in a reaction. A positive coefficient indicates the production of a metabolite in a reaction. A zero coefficient is for metabolites that have no contri­bution to the reaction.

The economic viability of the current microalgae to fuel (or chemical) processes (summarised in Fig. 1.1) is limited by the high cost and energy burdens for growth inputs, capital and operating costs for dewatering, and the operating and capital costs of the growth system (Clarens et al. 2010; Lardon et al. 2009; Stephenson et al. 2010). Advances in growth, harvesting and extraction systems provide incremental improvement to these systems. The persistence of companies/research institutions and governments in continuing to pursue these systems indicates that many believe that such incremental improvement over time will ultimately result in an economically viable process. Others believe that a step change is required and are pursuing an entirely different biofuel production model in which the product of interest is continually secreted by the microalgae. This novel method is generally referred to as ‘milking’, as the product of interest is ‘milked’ from the algae without the need to destroy it and subsequently regrow it.

Koenraad Muylaert, Annelies Beuckels, Orily Depraetere, Imogen Foubert, Giorgos Markou and Dries Vandamme

Abstract Production of microalgal biomass requires large amounts of nitrogen (N) and phosphorus (P). The sustainability and economic viability of microalgae pro­duction could be significantly improved if N and P are not supplied by synthetic fertilizers but with wastewater. Microalgae already play an important role in wastewater treatment, yet several challenges remain to optimally convert waste­water nutrients into microalgal biomass. This book chapter aims to give an over­view of the potential of using wastewater for microalgae production, as well some challenges that should be taken into account. We also review the benefits of combining microalgal biomass production with wastewater treatment.

5.1 Introduction

Microalgae have a high areal productivity, do not require fertile land, and are seen as a promising new source of biomass that could complement production by conventional agricultural crops. Microalgae have attracted a lot of interest in recent [1] [2]

years as a novel feedstock for biofuels (Schenk et al. 2008). But microalgae also hold a lot of potential for production of food (Draaisma et al. 2013), animal feed (Benemann 2013), or feedstock for the chemical industry (Wijffels et al. 2010). When compared to conventional agricultural crops, microalgae have a high content of proteins and lipids, and a low content of structural carbohydrates such as cel­lulose (Lam and Lee 2011). This is an attractive property of microalgae, because it implies that most of the biomass can be valorized. On the contrary, with conven­tional crops, only a small fraction of the biomass is used (e. g., seeds or tubers) and a large proportion of the biomass is left on the field (i. e., the fraction that contains mostly cellulose and lignin). Because of the low content of structural carbohydrates such as lignin or cellulose, microalgal biomass has a high content of nitrogen (N) and phosphorus (P): about 10 % N and 1 % P per unit dry weight. This is almost three times higher than the N and P content of terrestrial plants (Elser et al. 2000). Because of the high content of N and P in microalgal biomass, production of microalgae requires vast quantities of inorganic fertilizer, much more than the production of terrestrial crops (Sialve et al. 2009). This high fertilizer demand is a challenge to the sustainability of microalgae biomass production, and several life cycle analyses studies have shown that the energy required for synthetic fertilizer production contributes significantly the total energy demand for microalgal biofuels (Lardon et al. 2009; Clarens et al. 2010; Benemann et al. 2012). Production of N fertilizers through the Haber-Bosch process is highly energy-intensive and is reliant on fossil fuels (Smil 2002; Pfromm et al. 2011). Extraction and processing of mineral phosphates for production of P fertilizer is also energy-intensive (Johnson et al. 2013). Moreover, mineral phosphates reserves are limited and are rapidly being depleted (Cordell et al. 2011). If microalgae are to be produced on a large scale, e. g., large enough to contribute significantly to fuel demand, consumption of synthetic fertilizers is expected to increase strongly above current levels (Venteris et al. 2014). Microalgae are often promoted as a biomass source that does not compete with agricultural biomass production, and thus avoids the food versus fuel discussion. However, as both microalgae and agricultural crops require mineral fertilizers, microalgae may indirectly compete with agricultural crops and thus indirectly impact food production through increases in fertilizer prices (Pate et al.

2011) . Many studies and opinion papers have in recent years suggested to use wastewater rather than synthetic fertilizers as a source of nutrients for microalgae production and showed that this could significantly improve the sustainability and economic feasibility of microalgae production (Lundquist et al. 2010; Clarens et al. 2010; Christenson and Sims 2011; Pittman et al. 2011; Park et al. 2011b; Olguin 2012; Prajapati et al. 2013). Because microalgae are already being used for wastewater treatment, replacing synthetic fertilizer with nutrients from wastewater is feasible. The goal of this book chapter is to discuss both the potential as well as limitations of using wastewater as a nutrient source for microalgae production.

Part registries are lists and collections of standardized biological parts that can be strung together to build advanced and more complicated biological devices. Parts in this context mean DNA constructs that encode a given function. On the other hand, biological devices perform more complicated functions and are made from combining different parts. An example would be that a part encodes a specific enzyme in a pathway, while a device performs a complicated function like biological arsenic detection or bioplastics production. These registries are a list of DNA constructs (parts) and synthetic circuits (biological devices) that are ready for genetic insertion. The idea behind creating such registries is to list reliable and well tested biological parts that can be manufactured to a given standard and that serve as the building blocks of sophisticatedly engineered biological tools and devices (Canton et al. 2008). This standardization liberates the process of designing and fabricating complex biological devices from the daunting task of designing and fabricating each individual and necessary component. In addition, the fabricators of those devices can rely on specialized manufacturers of those standard parts to provide the components needed for fabricating the advanced biological devices. All in all, this has the effect of opening up the field and providing the impetus for more advanced applications (Baker 2006).

In biological part registries, standardization is of essence. Standardization in the context of biological parts refers to the ability of a part to assimilate into a larger structure without any complications. In other words, the part does not have any restriction sites that interfere with the process of assembling into larger devices. Another important aspect of standardization is with respect to function. Biological parts should serve a given function that is both well-defined and consistent. Perhaps the most widely known and used registry is the Registry for Standard Biological Parts (http://parts. igem. org/Main_Page) (Kahl and Endy 2013). The registry, like most other registries, relies on community contributions to expand its biological part offerings. The community accessible approach of the registry has expanded the registry’s offering to include thousands of parts serving numerous functions. The registry’s part types include promoters, ribosome binding sites, protein domains, protein coding sequences, translational units, terminators, plasmid backbones, primers and composite parts which are a composition of two or more simpler parts. To ensure openness, efficiency and consistency, parts offered by the registry comply with the BioBricks assembly standard (http://parts. igem. org/Help:Standards/Assembly). The current standard relies on defining a DNA prefix and suffix on a standard plasmid backbone. The part is then inserted into the plasmid backbone specifically between the prefix and suffix. The prefix and suffix also contain specific restriction sites, and this precise definition that is included in the standard also forbids the introduction of restriction sites that interfere with the part assembly and usage process. In general, those features allow the smooth and immediate use of the biological parts.

Algae-specific registries with the ambition of the registry for standard biological parts are yet to be fully developed. However many repositories are available that provide cell lines, several thousand algal strains, DNA constructs, and specific genetic engineering tools. One prominent example is the Chlamydomonas Resource Center, a repository of Chlamydomonas reinhardtii strains, plasmids, kits, and cDNA libraries among other things (http://chlamycollection. org/). While most of these registries are not registries of synthetic biological parts specifically, they still offer many tools and products of value to synthetic biology endeavors in algae. Also, the availability of standard and customized algal optimized plasmids prepared and sold by private companies, such as Life Technologies, (a brand of Thermo Fisher Scientific, Carlsbad, CA, USA), is another step forward into easing up synthetic biology applications with microalgae.

While the breadth of registries and repositories up and running is a call for optimism in the field of synthetic biology, certain challenges still permeate the part registry model. For example, characterization of many biological parts and the precise definition of their functions are still lacking. Furthermore, many parts display different behavior in different cells or organisms and in different laboratory conditions; this introduces a major challenge to the field with respect to repro­ducibility of function. Stability and reliability become even more daunting chal­lenges as the organism’s complexity increases. This means that extending biological parts and the registry model to algae, or organisms of higher complexity than simple microbes, becomes additively challenging quite quickly. Still, another challenge is in the long-term behavior of parts and their behavior as components of increasingly complex devices. Cell functions are prone to seemingly random behavior and noise which can complicate the ability of biological parts and complex devices to behave consistently for a significantly long period (Kwok 2010).