The ability to alter gene expression, and as such, metabolic pathways within green microalgae, is of a crucial importance in optimizing those algae for biofuel pro­duction. Achieving such alterations and rational modifications of expression relies primarily on the identification of transcription factors (TFs), genes, and enzymes implicated in metabolic pathways driving the synthesis of oil and hydrogenated metabolites that can potentially be used as biofuels. Post-identification, via struc­tural and functional annotations of genomes, the establishment of a library of cloned, ready to transform, open reading frames (ORFs) and TFs makes the optimization process one step closer (Fig. 9.3). Attempts to clone the metabolic ORFeome of model green algae, C. reinhardtti, have been made and published by Ghamsari et al. (2011) and Chang et al. (2011). The structural annotation of the ORFs was based on models generated by the Joint Genome Institute (JGI) (Merchant et al. 2007) and AUGUSTUS gene prediction algorithm (http://augustus. gobics. de/predictions/chlamydomonas/). The outcome leads to the generation of Gateway-compatible clones that can easily be moved to a plethora of available expression vectors.

Another attempt, as part of an ongoing work, is the genome-wide cloning of TFs in C. reinhardtti to add a regulatory dimension to the available clone resources (unpublished data). The completion of such an endeavor will result in a library of TF clones that are Gateway compatible and readily available for transformation to

alter and modify the expression of target genes. Clones can also be obtained from the Chlamydomonas Resource Center (http://www. chlamy. org/). The center hosts a multitude of C. reinhardtti strains, plasmids, molecular kits, and cDNA libraries.

The importance and relevance of cloning has been underlined as a major initial step in the process of algal optimization for biofuel production by making available a library of metabolic and transcription factor clones that can be used to modify the genetic information and expression patterns and, subsequently, directionally alter the metabolism in algal cells toward a higher yield of hydrogenated metabolites suitable for biofuel use.

Navid R. Moheimani, David Parlevliet, Mark P. McHenry, Parisa A. Bahri and Karne de Boer

Abstract Microalgae cultivation is a promising methodology for solving some of the future problems of biomass production (i. e. renewable food, feed and bioenergy production). There is no doubt that in conjunction with conventional growth sys­tems, novel technologies must be developed in order to produce the large-scale sustainable microalgae products. Here, we review some of the most promising existing microalgae biomass growth technologies and summarise some of the novel methodologies for sustainable microalgae production.

1.1 Introduction

There has recently been extensive research focus on biology, physiology, engi­neering and their integration for microalgae cultivation to produce sustainable products such as biofuel, food, feed and high-value products. Algae belong to many different and unrelated taxonomic groups that all contain chlorophyll a and are able to utilise solar energy and fix CO2 to produce organic compounds (Borowitzka 2012). More than a dozen algal species have been mentioned in the literature as potential candidates for large-scale cultivation. However, conclusive information obtained through commercial trials is not yet available to assess suitability of most of these species. The ideal microalga must be able to grow very well even under high biomass concentration and varying environmental conditions. It must be able to produce high concentration of product of interest (i. e. high-value products, lipids and hydrocarbons). However, it is unknown how many species of algae exist, with

N. R. Moheimani (H)

Algae R&D Center, School of Veterinary and Life Sciences, Murdoch University, Murdoch, WA 6150, Australia e-mail: n. moheimani@murdoch. edu. au

D. Parlevliet • M. P. McHenry • P. A. Bahri • K. de Boer

School of Engineering and Information Technology, Murdoch University,

Murdoch, WA 6150, Australia © 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_1

estimates ranging between several hundred thousand and several million different species—with new types identified all of the time (Guiry 2012). Only a small portion of microalgal species (several thousand) can be kept alive in culture, and only a handful of them have been successfully grown commercially. Table 1.1 summarises the main microalgae species tested for medium — to large-scale pro­duction (especially for feed, high-value products and biofuel).

However, to date, only a few of these species were successfully grown in large scale. Commercial large-scale production of microalgae for bioproducts began in early 1960s and 1970s with Chlorella and Spirulina and followed in the 1980s with production of P-carotene from Dunaliella salina (Borowitzka 2013a). All three species were successfully grown in mixed or unmixed open ponds (Craggs et al. 2013). The ability to grow at highly selective environments is the main reason for the successful growth of these species (Spirulina = high pH and high HCO3-, D. salina = high salinity and Chlorella = high nutrients) (Craggs et al. 2013). Moheimani and Borowitzka (2006) also showed that Chrysotila carterae reliable long-term culture in raceway pond is successful due to the ability of this alga to grow at very high pH. Other species that do not have this selective advantage may need to be grown in closed photobioreactors. The selection of growth technologies or production systems for microalgae will need to be based to a large extent on the microalga of choice and cultivation system.

Many strains of microalgae are able to simultaneously produce oil and many other useful and expensive metabolites, such as antioxidants (Fujita et al. 2008; Ogbonna

2009) and bioactive compounds. Such metabolites can be separated and purified, thereby making the process profitable. After oil extraction, residual biomass can be converted to biofuels, such as bioethanol, biohydrogen, and biomethane via ther­mochemical and biochemical methods (Golueke et al. 1957; Gunaseelan 1997). As an example, the anaerobic digestion of microalgae produces methane, which can then be used to generate electricity. The generated electricity can be used for microalgae cultivation, dewatering, extraction, and transesterification process. Harun et al. (2011) estimated that the electricity generated from methane reduces the cost of biodiesel production by as much as 33 %. It can also be used to produce bioplastic materials (Chiellini et al. 2008), or used as a fertilizer, soil amendment, or feed for fish or livestock (Mulbry and Wilkie 2001; Mulbry et al. 2005; Roeselers et al. 2008).

3.8 Conclusions

Although microalgae biodiesel has many advantages over plant biodiesel in terms of effects on food security and sustainability, the present cost of microalgae oil is still much higher than that of vegetable oils. This is mainly due to low cell growth rate and low final cell concentrations in photoautotrophic cultures. Cell growth rates, final cell concentrations, and in some cases intracellular oil contents are higher in heterotrophic and mixotrophic cultures than photoautotrophic cultures. These lead to increase in oil productivity and reduction in the cost of production. The qualities of oil produced under these culture conditions have also been reported to be more suitable for biodiesel oil production than photoautotrophic microalgae oils. Heterotrophic and mixotrophic culture systems should therefore be exploited for large-scale biodiesel oil production.

Various microalgae species accumulate biomass under different CO2 concentrations. Two experiments on S. obliquus supplied with 12 % CO2 resulted in 1.14 and 1.81 g L 1 as a maximum dry weight biomass yield, whereas a higher biomass concentration (3.5 g L-1) was obtained with Spirulina sp. when using a higher light intensity at the same 12 % CO2 input gas (Table 7.2) (De Morais and Costa 2007a, b). As shown in Table 7.2, the highest biomass concentration of Chlorococcum littorale in three runs under 20 % CO2 was 14.4 g L 1 in a small PBR (Kurano et al.

1995) . There has been several research publications evaluating the biomass pro­ductivity of different strains of microalgae under different CO2 concentrations (De Morais and Costa 2007a; Radmann et al. 2011; Yoo et al. 2010). Table 7.3 shows the biomass productivity of 0.077 g L-1 d-1 for Botryococcus braunii under

5.5 % CO2 (Yoo et al. 2010). A biomass productivity of 0.09 g L-1 d-1 for C. vulgaris was achieved (under 12 % CO2) (Radmann et al. 2011). Similarly, Spirulina sp. was used under 6 % CO2 and biomass productivity of 0.18 g L-1 d-1, signifi­cantly higher than most other reports, was obtained (De Morais and Costa 2007a). This higher biomass productivity might be due to lower CO2 concentration (6 %) used for Spirulina sp. in comparison with 12 and 20 % CO2 supplied for species in other reports. Similarly, microalgal species have shown differing capabilities for CO2 fixation at different concentrations of CO2 (10-20 % is a common range of CO2 for microalgae production systems with enhanced CO2 delivery (Ho et al. 2011)). The CO2 fixation rate of 0.17 g L-1 d-1 was obtained (Eberly and Ely 2012) for Thermosynechococcus elongates at 20 % CO2. Similar input CO2 concentration (20 %) (Tang et al. 2011) was supplied for S. obliquus SJTU-3 and C. pyrenoidosa SJTU-2, fixing 0.244 and 0.223 g L 1 d 1 CO2, respectively. However, the researchers also cultured the same strains under 10 % CO2 and obtained higher fixation rates, such as 0.288 g L-1 d-1 for S. obliquus SJTU-3 and 0.260 for C. pyrenoidosa SJTU-2, when providing high levels of CO2 into culture mediums that leads to acidification and lowering fixation rates of S. obliquus SJTU-3 and C. pyrenoidosa SJTU-2 at 20 % CO2. Research (Kurano et al. 1995) with C. littorale under 20 % CO2 assessed removing CO2 by 4, 0.65, and 0.85 g L-1 d-1 for selected culture volumes of 10 mL, 4 L and 20 L, respectively. The research indicated that C. littorale may achieve a better CO2 fixation rate than T. elongates, S. obliquus SJTU-3, and C. pyrenoidosa SJTU-2, although the differences were not significant. The higher CO2 fixation rate may be either due to engineering issues in scaling up or due to higher light intensity used for C. littorale (15650 lux) compared to other

investigations (11,200 lux) (Table 7.4). Light intensity controls photosynthetic growth in any microalgal system, CO2 removal rates, biomass concentrations, and overall growth rates. While increasing light intensity is usually accompanied by increasing CO2 removal rates in microalgal systems, any photosynthetic system has a saturation point where further increasing light intensity will either produce no benefit or may decrease productivity.

Several integrated toolsets are available for constraint-based analysis. These include Pathway Tools, COBRA Toolbox, SNA, and MetaFluxNet (Table 10.1). The most widely used tools are Pathway Tools and COBRA Toolbox, with COBRA offering

the largest number of tools. A few of these tools (mostly available in COBRA) are described below (Fig. 10.5).

The growth of algae, irrespective of cultivation system, requires large volumes of water. Almost all areas with high solar energy also have a high evaporation rate. Therefore, it is logical to use sea water for large-scale algae biomass production. As highlighted previously, it is also critical to recycle the culture medium to reduce the nutrient use. Sea water must also be used to replace evaporative loss. This means that the salt concentration in the pond will gradually increase over the time. For instance, in conditions with evaporations rate of 2 m year-1, productivity of 20 g m 2 day 1 and 80 % medium recycling, the medium salinity will rise from

3.5 % NaCl to 25 % NaCl in 490 days. Salinity is usually growth-limiting at the extremes of salt tolerance in some microalgal species, and every microalga has an optimum salinity range (Borowitzka and Moheimani 2013a). The effect of salinity on microalgal growth relates to osmoregulation, which in microalgae is achieved through diverse strategies. Osmoregulatory metabolites are organic substances produced by microalgae that, when the latter are exposed to water stress conditions, respond appropriately to the changes in extracellular water activity. Microalgae main osmoregulators (function as intracellular osmotic regulators) are as follows: (a) polyhydric alcohols (i. e. glycerol, mannitol or sorbitol), (b) variety of glycosides (i. e. galactosyl glycerides, floridoside and isofloridoside) and (c) amino acids (i. e. glutamic acid and proline).

Freshwater algae grow between 0 and 1-2 % NaCl; hypotonic algae grow between 3.0 and 5-5.5 % NaCl; halotolerant algae grow between 6-7 and 14-15 % NaCl; and halophylic algae can grow above 15-16 % NaCl. The majority of microalgae can grow in freshwater and hypotonic conditions. Some microalgae (i. e. diatom, chlorophyta and cyanobacteria) are capable of growth under halotol — erant conditions. However, only a few species of microalgae are hypersaline (i. e. D. salina). There is no single strain of algae capable of optimal growth in the whole range of salinity from sea water to saturation. Interestingly, almost all companies interested in large-scale algae production focus on growing either freshwater or hypotonic algae which will not be sustainable (Moheimani et al. 2013c). Halotolerant algae can normally grow under optimal condition in a wider range of salinities (Fon Sing 2010).

An alternative method of cultivation is to mix microalgae while salinity is being increased. In such a method, a new species can be introduced to the culture of a mono-species while the salinity is rising. That is, a halotolerant microalga species will be introduced to the culture of hypotonic algae when salinity is above the optimum growth condition of the hypotonic algae. If the halotolerant alga can flourish while salinity is increased, the medium use can be maximised. The same technique can be applied for mixed cultures of halotolerant and halophylic mic­roalgae. Such a mixed cultivation technique is yet to be tested at the laboratory or outdoor conditions. One very important advantage of mixed microalgae cultivation is avoiding unnecessary water and nutrient discharge. Considering the species change throughout the cultivation, less negative effect of autoinhibitors is also expected. When the salinity of the culture becomes very high, one option is to have large evaporation ponds for the hypersaline wastewater. Alternatively, this hyper­saline water can also be used in salt gradient solar ponds for generating additional energy.

In open raceway ponds, microalgal biomass concentrations are typically about 0.5 g L-1. The N content of this biomass is about 7 % and the P content 1 %. As a result, the minimal nutrient concentration in the culture medium to achieve a biomass concentration of 0.5 g L-1 should be around 5 mg P L-1 and 35 mg N L-1. In photobioreactors, microalgal biomass concentrations are higher (up to tenfold), and a higher nutrient concentration is needed in the medium to achieve the maximal biomass concentration. If nutrient concentrations in the wastewater are lower, microalgal biomass will be nutrient-limited and the biomass concentration and productivity will be lower than can be achieved under optimal conditions. If the biomass concentration in the medium is too low, this may in turn result in higher harvesting costs.

Concentrations of N and P vary considerably between different types of wastewaters. Domestic wastewater contains about 15-40 mg N L-1 (Rahman et al. 2012; Peccia et al. 2013), which is perhaps just sufficient to achieve the maximal productivity of microalgae in raceway ponds (Olguin 2012), but too low for pho­tobioreactors. If wastewater with a lower concentration of N and P is used as a source of nutrients, the retention time of the microalgae in the system can be increased relative to that of the nutrients. This can be achieved in several ways. One option is to grow microalgae on a fixed support rather than suspended in the culture medium (Hoffmann 1998; Mulbry et al. 2008; Zamalloa et al. 2013; Boelee et al. 2013; Kesaano and Sims 2014). The fixed microalgae can be unicellular or fila­mentous species and can be grown on a variety of supports. Another option, as summarized in Chap. 2, is to immobilize suspended microalgae in alginate beads or alginate mats (e. g., Mallick 2002; Ruiz-Marin et al. 2010; Eroglu et al. 2012). However, it may be difficult to separate the microalgae from the alginate and use the biomass. Also, membrane photobioreactors can be used that retain microalgae in the photobioreactors but allow a high throughput of wastewater (Bilad et al. 2014). Wastewater derived from animal manure or industrial effluents are often high- strength wastewaters and can contain up to several grams of N L-1. When nutrient concentrations are higher than the requirements for microalgal production, the microalgae will be light-limited due to self-shading before all nutrients are con­sumed (Huisman et al. 2002). Wastewater with high “N” and “P” concentration can be diluted with water to match the nutrient supply with the productivity of the microalgae, yet the use of pure water to dilute wastewater is unsustainable (Mar — cilhac et al. 2014). Concentrated wastewaters can be diluted with seawater to produce a growth medium for marine microalgae (e. g., Craggs et al. 1995; Zhang and Hu 2008; Jiang et al. 2011). Alternatively, low nutrient domestic wastewater could be used to dilute concentrated wastewater. If this is not possible, the culture medium may be repeatedly recycled until all nutrients have been consumed by the microalgae. Few studies, however, have attempted this to date.

The ability to make specific changes to DNA, such as changing, inserting or deleting sequences that encode proteins, enables researchers to engineer cells, tis­sues and organisms for practical applications. Clustered regularly interspaced short palindromic repeats (CRISPR), a bacterial adaptive immune system effector, has been shown to facilitate RNA-guided site-specific DNA cleavage in bacteria, suggesting a simple alternative strategy for genome engineering (Sorek et al. 2013). The CRISPRs are a diverse family of DNA repeats that all share a common architecture. Each CRISPR locus consists of a series of short repeat sequences (typically 20-50 bp long) separated by unique spacer sequences of a similar length. The CRISPR/Cas systems are phylogenetically and functionally diverse, but each of these systems relies on three common steps: new sequence integration, CRISPR RNA biogenesis, and crRNA-guided target interference (Fig. 8.2c).

The CRISPR/Cas system allows targeted cleavage of genomic DNA guided by a customizable small noncoding RNA, resulting in gene modifications by both non­homologous end joining (NHEJ) and homology-directed repair (HDR) mechanisms. CRISPRs are unevenly distributed between Bacteria and Archaea. Currently, CRISPR loci have been identified in 90 % of the archaeal genomes and 50 % of the bacterial genomes (Sorek et al. 2013). CRISPR-Cas systems have emerged as potent new tools for targeted gene knockout in bacteria, yeast, fruit fly, zebrafish, human cells and plants (Belhaj et al. 2013; Gaj et al. 2013). In August 2012, Jinek et al. (2012) showed that a synthetic RNA chimera (single guide RNA, or sgRNA) created by fusing crRNA with tracrRNA is functional to a similar level as the crRNA and tracrRNA complex. As a result, the number of components in the CRISPR/Cas system was brought down to two, Cas9 and sgRNA (Jinek et al. 2012). For appli­cations in eukaryotic organisms, codon optimized versions of Cas9, which is orig­inally from the bacterium Streptococcus pyogenes, have been used. Four of the studies on the application of the CRISPR/Cas technology in plants used a plant codon-optimized version of Cas9, as using the previously described human codon — optimized version was not highly effective (Belhaj et al. 2013; Jiang et al. 2013).

All tested versions of Cas9 appear to work in plants with very high rates. Transgenic plants, generated using the CRISPR/Cas system, have been reported (up to 89 % for Arabidopsis and up to 92 % for rice) with bi-allelic mutation being recovered in the case of both plant species (Jiang et al. 2013). The discussed studies indicate the possibility of introducing functional CRISPR/Cas system in algae to target any sequence of choice, thus offering new opportunity for implementation in algal biotechnology for biomass production.

Together, these technologies promise to expand our ability to explore and alter any genome and constitute a new and promising paradigm to develop new synthetic biology tools for algal biofuels optimization.

Biosensor research often focuses on the application of enzyme sensors for the detection of toxic chemicals (Dennison and Turner 1995; Shul’ga et al. 1994). Due to the drawbacks of this technology, such as enzyme stability, cost of the process, and difficulty to prepare multienzymatic biosensors, immobilized cells have been proposed as an alternative biosensor technology. Using the entire cells has the advantage of involving various enzymes at the same time, which allows estab­lishing information about the toxicological effects of different pollutants directly on the selected organisms. Immobilized cells had more stable metabolic activities than free cells during the long testing periods (Lukavsky et al. 1986) and also higher resistivity to turbid/colored effluents (Bozeman et al. 1989).

The generation or consumption of charged chemicals during bioreactions results in a significant change in the ionic composition of the test sample that can be detected by conductometric biosensors. For this reason, Chouteau et al. (2004) investigated the development of conductometric biosensors using immobilized C. vulgaris cells for alkaline phosphatase analysis and cadmium ion detection. C. vulgaris cells were immobilized inside bovine serum albumin membranes that were cross-linked with glutaraldehyde vapors.

Frense et al. (1998) used immobilized Scenesdesmus subspicatus algal cells as optical biosensors for the determination of the herbicide content in wastewater samples. The algal cells were initially immobilized on a filter paper, which was then covered by alginate and then cross-linked with CaCl2 solution. They used a fiber optics-based electronic device for measuring the chlorophyll fluorescence of algal cells as a response to the presence or absence of the toxic substances in the liquid sample.

C. vulgaris cells immobilized in a membrane of oxygen electrode has been used as a biosensor for the detection of perchloroethylene aerosols by monitoring the pho­tosynthetic activity of the microalgae through oxygen production (Naessens and Tran-Minh 1999). Shitanda et al. (2005) also immobilized alginate-entrapped C. vulgaris cells on the surface of an indium tin oxide electrode, for the monitoring toxic compounds such as atrazine, toluene, benzene, and 3-(3,4-dichlorophenyl)-1, 1-diethylurea (DCMU).

Immobilized algal cells of S. capricornutum in alginate beads were used for the toxicity testing of various chemicals, such as cadmium ions, copper ions, penta- chlorophenol, sodium dodecyl sulfate, and herbicides (glyphosate, hydrothol, paraquat) (Bozeman et al. 1989). In subsequent studies, alginate-immobilized S. capricornutum cells were also successively used for the toxicity testing of various pesticides, herbicides, and fungicide (Abdel-Hamid 1996; Van Donk et al. 1992). The immobilization process reduced the toxic effect of these tested chemicals on the algal cells compared to their free-cell equivalents.

Key parameters determining the economic feasibility of algae biofuels include biomass productivity, lipid content, and lipid productivity. Microalgae produce a variety of lipids, tri — and diglycerides, phospholipids, glycolipids, alkenes, and pigments such as the carotenoids. Reports of total lipid content for specific strains (i. e., compounds soluble in organic solvents per dry weight, as originally described by Bligh and Dyer 1959) vary in the literature (Griffiths and Harrison 2009). This is due, in part, to variations in the sequence and polarity of solvent systems used for extraction (Guckert et al. 1988). Because of the complexity of lipid compounds in algae and that the fractions of each class can vary with environmental conditions, lipid quantification, which is essential to the development of production models for algae biofuels, needs refinement. The biodiesel industry is currently based on transesterification of plant triglycerides forming alkyl esters of the fatty acid moiety. The fate of other cellular lipid compounds in the tranesterification process, potentially a large fraction of lipoidal extracts, will require more attention.

Perhaps a more important consideration of reported variations in lipid content, even within a specific species, is the physiological responses in lipid metabolism due to culture conditions including temperature, salinity, growth phase, nutrient deprivation, and the diurnal light cycle, all of which have a strong influence on lipid content (Roessler 1988, 1990). Unfortunately, biomass productivity is often inversely correlated with overall lipid productivity. High lipid and carotenoid content is usually produced under stress conditions, especially nutrient limitation which prevents cell growth and division resulting in excess photosynthate shunted toward triglyceride accumulation (Griffiths and Harrison 2009; Illman et al. 2000; Jakobsen et al. 2008; Lv et al. 2010; Rodolfi et al. 2009).

Lipid productivity is the product of lipid content and productivity. A survey of the literature on growth rates and lipid content under nutrient-replete and nutrient — deficient conditions showed a stronger correlation between biomass and lipid productivity rather than simply lipid content (Griffiths and Harrison 2009). In continuous ponding operations, selection of fast-growing strains increases yield and decreases the cost of harvesting and extraction (Borowitzka 1997) and reduces competition by invading strains. High productivity is also advantageous in a two — stage process, as described above, with the first stage designed to optimize biomass production and nutrient removal from wastewater followed by a second phase to induce hyper-lipid production.