Advances in Water Science and Technology
Volume 1 | Issue 1 | Pages 15-26
Journal homepage: http://www.ajournals.com/journals/awst
Glucose addition in microalgae consortium cultivation as substitute for the absence of CO2
Malorie Gélinas 1*, Mélissa Lemire 1, Kokou Adjallé 1 and Simon Barnabé 1
1Université du Québec à Trois-Rivières, Lignocellulosic Materials Research Centre, CRIEB, 3351 Blvd. des Forges, Trois-Rivières, Québec G9A 5H7
Abstract
Microalgal biomass represents a sustainable alternative to fossil consumption. Biofuel, bioenergy and valuable coproducts can be produced by microalgae. This study sought to determine the impact of organic carbon in the absence of inorganic CO2 in mixed microalgae consortium cultivation while wastewaters from a smelter were used as the culture medium. Microalgae density, neutral lipid concentration, metabolic activity and reactive oxygen species were measured using flow cytometry. Lipid peroxidation (LPO), mitochondrial electron transport and ascorbate peroxidase (APX) were also measured. The results revealed that mixed microalgae grow and produce more cells under mixotrophic or heterotrophic cultivation. Surprisingly, the absence of CO2 did not affect microalgae consortium growth in mixotrophic and heterotrophic culture. The presence of glucose addition leads to the highest algal density and growth rate, while neutral lipids remained constant. A decline of lipids concentration was even observed in heterotrophic condition. In addition, glucose supplementation triggers the activity of the antioxidant enzyme ascorbate peroxidase, whereas a decrease in lipid peroxidation and mitochondrial electron transport was measured. Our study showed that mixotrophic and heterotrophic conditions favour the highest algal growth through fast cellular division while presence of bacteria in the medium might represent an advantage due to the CO2 produced by bacteria metabolism.
Key words: Glucose, microalgae consortium, wastewaters, mixotrophy, neutral lipids
Introduction
As a potential source of biofuel, microalgae generate interest due to their photosynthesis capability and their conversion of carbon dioxide (CO2) into biomass (Chisti 2007; Liu et al. 2008; Rosenberg et al. 2008). The high efficiency of some microalgae to produce biomass surpasses those of traditional agricultural crops. Large amounts of cellular lipids, polyunsaturated fatty acids, pigments and other bioactive compounds are targeted as promising alternative or economical components of the emerging bio-economy. For biofuel production, high yield of lipids production could be induced by limiting the nutrients (De la Hoz Siegler et al. 2012; Scarsella et al. 2010) or by genetic engineering (Roessler et al. 1994; Rosenberg et al. 2008). Mata et al. (2010) listed 44 species of microalgae with yields between 10 and 1214 mg/L/day of cellular lipids. Furthermore, several species of microalgae have shown the ability to utilize sugars or other organic carbon compounds that increase their growth rate and drastically enhance their lipid content, which is particularly in the case for Chlorella prototecoides and C. vulgaris (Xu et al. 2004; Liu et al. 2008; Liu et al. 2011; Wan et al. 2011). On the other hand, uptake of organic carbon favours algal cell division, which significantly decreases the cellular energy storage within the cell (Hu et al. 2008).
Major inputs for algae cultivation are light, CO2, water and nutrients. To ensure the lowest production costs, alternative resources such as waste materials with the potential to outcompete normal inputs need to be integrated as inexpensive alternatives, which will reduce the total cost. Many studies have use wastewater to grow algae which eliminate the need for freshwater. In fact, nutrients required for microalgae growth could be found in wastewater in various concentrations. However, even if industrial outlets possess excess of nutrients, the metal and other potential toxic components contained in some wastewaters represent harsh environmental conditions for many most microalgae strains. Indeed, competition among algae strains allows the most tolerant species to dominate.
In the intent of mass cultivation, microalgae produced in open ponds are one way among others. However, microbial contamination is a major issue in algae cultivation. Nonetheless, microalgae and some bacteria or fungi can coexist in symbiotic interactions in nature—dynamic interactions that either inhibit or promote each other’s growth by excreting diverse substances (Seyedsayamdost et al. 2011; Guo and Tong 2013). For example, bacterial activity in the wastewater supplies CO2 to algae (Bhatnagar et al. 2010). Various applications of bacteria and microalgae interactions have been explored in wastewater treatment, commercial production of microalgae, and management of harmful algal blooms. Hence, in microalgal biomass production for biofuel, the photoautotrophic or heterotrophic condition using Chlorella is often “contaminated” by bacteria, but it could be beneficial (Watanabe et al. 2005; Park et al. 2008; Guo and Tong 2013).
About the metabolism of microalgae, esterase is a common enzyme present in viable cells and is directly related to growth. Therefore, examining its intensity could be viewed as a general index of the metabolic activity of the microalgae (Geary et al. 1998; Brookes et al. 2000; Zhang et al. 2007). The metabolic activity in microalgae is related to microalgae density, which is a biomass component. Furthermore, photosynthesis (the transformation of light into energy) must be extracted through electron transport. In chloroplasts, the conversion of light into energy triggers electron leakage, which creates oxygen. This oxygen may generate toxic superoxide that potentially leads to oxidative stress such as reactive oxygen species (ROS). A too-high concentration of intracellular ROS could cause damage and lead to lipid peroxidation (LPO) in membranes and potentially to cell mortality. Both ROS and LPO are good biomarkers of the free radical that indicates cell injury (Foyer 1997; Dixit et al. 2002), but a phenomenon to counteract these deleterious effects exists as detoxifying antioxidant enzymes that include the ascorbate peroxidase (APX) (Mallick 2004; Feng et al. 2013). These biomarkers can establish the intensity of toxicity from the cultivation parameters such as the use of wastewaters from a smelter.
In this study, we evaluated the potential of organic versus inorganic carbon in a microalgae-bacteria consortium cultivated in wastewater from a smelter. This microalgae consortium was isolated from the smelter wastewater and has been adapted to grow in a culture medium based on the same wastewater.. Autotrophic, heterotrophic and mixotrophic cultures of mixed microalgae consortium investigated in the absence or presence of atmospheric CO2. The aim was to determine some attributes of cellular metabolism of the microalgae, such as esterase activity, ROS, and neutral lipids using flow cytometry to determine the cytotoxicity in microalgae. Furthermore, LPO, mitochondrial electron transport (MET) and ascorbic peroxidase (APX) were also measured to establish the level of stress and possible damages in the microalgae population.
Materials and Methods
Medium and cultivated conditions
The bacteria-microalgae consortium was mainly composed of Chlorella spp, and was cultivated in smelter wastewater with the addition of nutrients to mimic Bold’s basal medium (BBM): 0.75 g/L of potassium nitrate (KNO3); 0.7 g/L of monopotassium phosphate (KH2PO4); 0.3 g/L of magnesium sulfate (MgSO4); and 0.028 g/L of chelated iron. The ionic composition of the smelter wastewater is described in Table 1. The consortium was inoculated and cultivated in 300 ml of the medium in 1-L Erlenmeyer flasks at room temperature for 4 d and stirred at 150 rpm. A 12:12 h light/dark cycle with 20 µmol photon/m2/s was provided by two cool white fluorescent lamps. Mixotrophic or heterotrophic condition was induced by adding 0.5 g/L of glucose twice during the experiment (1h and 49h time). The dark condition was obtained by wrapping the flask with aluminum foil. The absence of CO2 was obtained by the use of flue gas containing 21% oxygen (O2)and 79% nitrogen (N) using a flowmeter (Sho-Rate) with a debit of 0.42 L/min. All the experiments lasted 72 h and were performed in duplicata.
Growth rate
Chlorophyll a was measured using an YSI 6600V2 probe (Xylem). The specific growth rate (µ) day-1 was determined according to the following formula (Vonshak and Maske 1982):
Flow cytometry
Flow cytometric analysis was carried out with a Cytomics FC500 series flow cytometer (Beckman Coulter) equipped with a 488 nm argon-ion laser set up with the standard configuration. Algal density was evaluated by flow cytometry. An aliquot of 200 μl of diluted microalgae sample (phosphate buffer [PBS]) was counted for 5 min, until no more particles were detected.
Metabolic activity in the algal cell was measured using fluoresceine diacetate (FDA) (Dorsey et al. 1989). Using the flow cytometer, the probe was excited at 488 nm and its green fluorescence emission was detected and measured at 530 nm (FL1). FDA can freely enter into the cells due to its small size and lipophilic nature. FDA was then converted into its brightly fluorescent derivative, fluorescein, by cellular esterases. A stock solution of 1 mg/mL FDA (Sigma, dissolved in ethanol) was added to a 500 µl solution of cells, previously diluted in PBS, to attain a final concentration of 5 µg/mL (Debenest et al. 2011). The data were expressed as the mean fluorescence intensity measured on a minimum of 5000 cells and up to 10 000 cells after a 20 min incubation period at room temperature in the dark.
Intracellular ROS levels were also measured. The oxidation-sensitive fluorescent probe 2′,7′-dichlorodihydrofluorescein diacetate(Sigma: H2DCFDA) was used as described previously (Gerber and Dubery 2004). Using the flow cytometer, the probe was excited at 488 nm, and its green fluorescence emission was detected and measured at 530 nm (FL1). Cellular esterase hydrolyzed the probe to the non-fluorescence H2DCF, which was then oxidized by ROS and cellular peroxidases to form the fluorescent dye H2DCF (Amodio et al. 2003). A 500 µl cells solution diluted in PBS was incubated with 100 µM dissolved dimethyl sulfoxide (DMSO) at room temperature for 60 min in the dark. The data were expressed as the mean fluorescence intensity measured on a minimum of 5000 cells and until 10 000 cells.
Neutral lipids were estimated in the microalgae cell using Nile Red solution, which excited at 488 nm, and its orange fluorescence emission was detected at 580 nm (FL2) (Greenspan et al. 1985). A stock solution of Nile Red 10 mg/ml was diluted in 10% DMSO (Sigma). The dye was added directly to a 500 µl cells solution diluted in PBS to a final concentration of 20 µg/ml and incubated for 30 min at room temperature in the dark. The data were expressed as the mean fluorescence intensity measured on a minimum of 5000 cells and up to 10 000 cells.
All probes fluorescence measurements were analyzed with the CXP analyzer program (Beckman Coulter). Data were collected and displayed in one-dimensional histograms versus cells number, where the geometric mean of the histogram was used.
Lipid extraction
The hexane extraction procedure was modified from Halim et al. (2011). Typically, cells were harvested by centrifugation at 5000 g for 10 min and then washed twice with distilled water. Then, the samples were dried using a speedvac system (Thermo Savant, New York, USA), for 12 h at 60°C, and were pulverized with a mortar in liquid N. Afterwards, 4 ml of n-hexane was added to 0.05 g of microalgae powder, and sealed overnight to retrieve lipids in the mixture at room temperature. Ultrasonication of samples for 4 min was carried out after the soaking step, and the solid phase was removed by centrifugation of the samples at 5000 g for 10 min. The hexane phase from each extraction was collected in a pre-weighed flask, and then evaporated to dryness in order to enable gravimetric quantification of the lipid extract.
Biochemical analysis
At the end of the experiment, 50 ml of cultivated microalgae were sampled and centrifuged at 4500 rpm for 10 min. The pellet was resuspended in 1 ml of PBS containing 0.67% trichloroacetic acid (TCA). Each tube was ultrasonicated for 2 min, repeated 3 times, with a UIS250v ultrasonic processor and a Vial tweeter sonotrode (amplitude: 75, cycle:1) (Hielsher, Teltow, Germany). Approximately 500 µl were used to measure LPO, whereas the other 500 µl were centrifuged at 15 000 g for 10 min at 4°C to measure total proteins and MET activity. Samples were kept at -80°C until analysis.
LPO was measured according to the thiobarbituric acid (TBA) method modified from Heath and Packer (1968). Briefly, 300 µl of the sonicated algal solution was mixed with 300 µl of 20% TCA and 0.5% TBA, and then heated at 90°C for 10 min. Afterward, the mixture was cooled down on ice for 10 min and centrifuged at 10 000 rpm for 5 min. The supernatant was used to measure the absorbance at 600 nm and 520 nm, using a microplate reader (BioTek PowerWave). The concentration of thiobarbituric acid reactants (TBARS) was calculated using an extinction coefficient of 155 nM-1cm-1. Standard solutions of tetramethoxypropane were used for calibration. Results were expressed as µg of TBARS per mg of protein.
MET activity was determined using the p-iodonitrotetrazolium dye reduction method (King and Packard 1975). Briefly, 25 μl of the supernatant was mixed with 100 mM Tris-HCl, at pH 8.5, containing 100 μM MgSO4, 0.1% Triton X-100 and 0.1% polyvinylpyrrolidone for 1 min. The reaction mixture was initiated with the addition of, respectively, 1 and 0.2 mM of nicotinamide adenine dinucleotide (NADH) and nicotinamide adenine dinucleotide (NADPH). The reaction has occured in the presence of 5 mM p‑iodonitrotetrazolium. Absorbance was measured each min for 20 min at 520 nm in a microplate reader (BioTek PowerWave). The concentration was calculated using the extinction coefficient 15.9 mM-1cm-1. Data were expressed as U/mg protein.
APX activity was adapted from Nakano and Asada (1981). Briefly, 50µl of the supernatant was mixed with a phosphate buffer containing 0.1 mM ethylenediaminetetraacetic acid (EDTA), 0.5mµ ascorbate and 50 mM phosphate pH 7; the reaction started with the addition of 30 mM hydrogen peroxide (H2O2). Absorbance was measured each min for 5 min at 290 nm in a microplate reader (BioTek PowerWave). The concentration was calculated using the extinction coefficient 2.8 mM-1cm-1. Data were expressed as U/mg protein.
Total protein concentration was determined using bovine serum albumin as standard, via the protein-dye binding principle (Bradford 1976), with the absorption at 595 nm measured with a microplate reader (BioTek PowerWave).
Statistical analysis
Data were normally distributed, and homogeneity of the variance was achieved prior to analysis; otherwise, the data were log10-transformed to achieve normality and homogeneity. The specific growth rates, algal cell density, metabolic activity, ROS and neutral lipids were analyzed using repeated-measured analyses of variance (ANOVAs) to test for significant effects of time (0, 24 h, 48 h and 72 h), glucose (presence or absence), CO2 (absence or atmospheric concentration), light (12:12 L/D photoperiod or dark), and their interactions. Due to the low number of replicas, LPO, MET and APX were analyzed using one-way ANOVAs to test for significant effects of glucose (presence or absence), CO2 (absence or atmospheric concentration) and trophic mode effect (photoautotrophy and mixotrophy [light] or heterotrophy [dark]). All statistics were analyzed using Systat 12.
Results
Chemical composition of the wastewater used in the study is presented in Table 1. Three ions not included in a normal medium composition for microalgae growth, are found: aluminum (0.65 mg/L), bromine (0.576 mg/L) and fluorine (5.1 mg/L). In addition, the chemical analyses revealed that polycyclic aromatic hydrocarbons (PAHs) were also present in concentration up to 0.8 µg/L).
|
Table 1: Ion concentrations in waster waters from the smelter. LOD = limit of detection. |
||||
|
Ion |
mg/L |
|||
|
Cl¯ |
166.28 |
|||
|
Br¯ |
0.576 |
|||
|
NO3¯ |
54.476 |
|||
|
PO4¯ |
2.012 |
|||
|
SO42¯ |
< LD |
|||
|
Al |
0.65 |
|||
|
Mn |
0.01 |
|||
|
Mg |
6.653 |
|||
|
Mo |
0.088 |
|||
|
Zn |
0.379 |
|||
|
F |
5.1 |
|||
|
Co |
< LD |
|||
|
Cr |
< LD |
|||
|
Cu |
< LD |
|||
|
Fe |
< LD |
|||
|
oil and grease |
0.4 |
|||
|
aliphatic hydrocarbons |
– |
|||
|
HAP |
0.0008 |
|||
Algae cell counts were significantly impacted by time (p < 0.001). The density increased 24 h after the first addition of glucose and a second time at 72 h, which corresponds to the second addition of glucose under heterotrophic and mixotrophic conditions (Figure 1). Algae cell density under photoautotrophic cultivation increased poorly. A significant interaction was measured between time, CO2 and glucose (p = 0.027). The highest density was measured in mixotrophic conditions in the absence of CO2 (Figure 1).
Figure 1 : Algae cell density (A & B) measured by flow cytometry and specific growth rate (C & D) calculated from the chlorophyll concentration of microalgae consortium exposed to different cultivated conditions over 72h. Results represent the means ± sd, n = 2.
he specific growth rate, measured using chlorophyll a (µ d-1), was significantly impacted by time (p = 0.023), and a significant interaction between time and glucose was measured (p < 0.001). Under photoautotrophic condition, the growth rate was constant, whereas under heterotrophic and mixotrophic conditions the glucose addition increased the specific growth rate during the first 24 h, followed by a second expansion at 72 h (Figure 1).
Metabolic activity was quantified by esterase fluorescence activity using an FDA probe. Metabolic activity was significantly affected by time (p < 0.001), and significant interactions between time and the three variables were determined (t*light = 0.007; t*CO2 = 0.012; t*glucose = 0.022). A significant interaction between time, light and glucose was also measured (p = 0.017). Under photoautotrophic and heterotrophic conditions, metabolic activities were constant, whereas a more pronounced decrease was observed under mixotrophic condition when CO2 was absent in the culture medium (Figure 2). The second addition of glucose did not trigger any additional metabolic activity.
Figure 2 : Metabolic activity (A & B), reactive oxygen species (C & D) and neutral lipids (E & F) measured by flux cytometry of microalgae consortium exposed to different cultivated conditions over 72h. Results represent the means ± sd, n = 2.
As shown in Figure 2, no significant induction of ROS formation was measured by the oxidative-sensitive indicator H2DCFDA, despite the trend observed in Figure 2. A strong decrease under heterotrophic conditions in algae cultivated under atmospheric CO2 was observed in ROS.
The results on neutral lipids showed that the interaction between time and glucose was marginally not significant (p = 0.068). Under the heterotrophic condition, the concentration of neutral lipids seems to decrease over time (Figure 2).The neutral lipids in algae under the photoautotrophic condition appeared to stay relatively constant. Heterotrophic cells accumulated neutral lipids up to 6% and 3.1% in the absence and presence of CO2, respectively. Lipid concentration under mixotrophic cultivation attained 5.8% and 4.5% of dry weight, in the absence and presence of CO2, respectively. Unfortunately, enough biomass was obtained to allow hexane extraction.
LPO in microalgae, measured at the end of the exposure period, was marginally not significantly affected by light or by CO2 concentration (p = 0.081 and p = 0.057, respectively). The glucose addition in the medium triggers a decrease in microalgae LPO (p > 0.0001). MET in microalgae also showed a significant decrease when supplemented with glucose (p = 0.003). Neither light nor CO2 concentration affect the MET (p < 0.05). APX was significantly affected by light (p = 0.005) and by glucose addition (p = 0.001), but not by CO2 (p = 0.712). A higher APX activity was measured in microalgae under the mixotrophic condition.
Figure 3: A: Lipid peroxidation (LPO), B : mitochondrial electron transport (MET) and C: ascorbic peroxidase (APX) of microalgae consortium exposed to different cultivated conditions. Results represent the means ± sd, n = 2.
Discussion
Even if the wastewater from the smelter contained three harmful ions (aluminum, bromine and fluorine), the results suggested that the microalgae consortium growth was not affect by these components. Addition of the organic carbon source supported a greater algal density and specific growth rate. The highest growth rate was achieved under mixotrophic cultivation of the microalgae consortium after 72 h and reached 1 µ d-1. Notwithstanding, the smelter wastewater used for media preparation is known to contain chemical elements that are potentially noxious for the cultivation of the microalgae consortium. However, all of these toxic ions were 500 to 4 times lower than the concentration needed to inhibit Chlorella growth. For example, De Jong (1965) reported that Chlorella vulgaris growth was inhibited at a concentration of 72 mg/L of fluorine, 500 mg/L of bromine or 4 mg/L of aluminum. In the smelter wastewater used in this study, fluorine concentration was 5 mg F– /L, bromine concentration was 0.565 mg Br/L and aluminum concentration was 0.65 mg Al/L. Furthermore, PAHs were present in smelter wastewaters. Due to the carcinogenic nature of PAHs (reviewed in Haritash and Kaushik 2009), toxic effects could be exerted on microalgae intracellular biochemical. A study by Borde et al. (2003) showed a synergetic effect in the biodegradation of PAHs by algae-bacteria consortium. Chlorella sorokiniana removed up to 85% of the pollutants when inoculated with bacteria and under continuous lighting. However, phenanthrene, one of the PAHs, inhibits C. sorokiniana growth at concentration higher than 10 mg/L, but this concentration is over 1000 times higher than the concentration measured in the smelter wastewater used in this study.
Microalgae density yields achieved in this study under mixotrophic conditions were lower than other reported values. In our study, low light intensity of 20 µmol photon/m2/s, which is below the necessary 80 µmol photon/m2/s (Yu et al. 2009) might not have been sufficient for optimal photosynthesis. Bhatnagar et al. (2010) have reported a 75% decrease in lipids in C. minutissima under a low light intensity of 30 µmol photon/m2/s. Liu et al. (2009) suggested that photosynthetic efficiency is reduced under uptake of organic carbon without affecting the biomass production. This might be explained by the formation and utilization of CO2 as a final metabolite of heterotrophic growth, which can be recycled by photoautotrophic growth (Xu et al. 2004). Therefore, the addition of glucose weakened photosynthetic activity without negatively affecting microalgae growth. This observation suggests an ability to integrate these two types of energy.
Hence, another possible explanation might be the low concentration of glucose (1 g/L) added in a mixed microalgae consortium as an organic carbon source. The complex synergy between bacteria and microalgae may be altered depending on the nutritional balance in the cultivation condition. For example, the fungal strain CSSF-1 is symbiotic with Chlorella sorokiniani under photoautotrophic conditions, but not under eutrophic conditions (Watanabe et al. 2005). Biofilms represent another type of system where the presence of bacteria is detected even if microalgae are dominant (Schnurr et al. 2013). Among plausible symbiotic interactions between microalgae and bacteria, an O2/CO2 exchange in our bacteria-microalgae consortium is suggested. In the absence of atmospheric CO2, none of the measured variables was significantly affected or was different than with atmospheric CO2. Therefore, the presence of preferably aerobic bacteria in the consortium might release CO2 within the medium that is later consumed by the microalgae.
Lipid concentration in algae cells declined after 72 h in the presence of organic carbon, glucose. This trend was particularly important for heterotrophic conditions. In our study, lipid production was relatively low, as estimated by neutral lipids and measured by gravimetric quantification, after hexane extraction. Less than 6% of neutral lipids were extracted in our mixed microalgae consortium in the presence of glucose. Our result showed the opposite trend of other studies, which have demonstrated a positive increase in biomass and in lipid production (Bhatnagar et al. 2010; Liu et al. 2011; Wan et al. 2011). For example, C. minutissima has a 5% lipid content that was improved to 15% under mixotrophic conditions in the presence of organic carbon (Bhatnagar et al. 2010).
Higher metabolic activities were measured under mixotrophic conditions (particularly in conditions without CO2), whereas heterotrophic conditions showed weaker or constant metabolic activities. Jochem (1999) showed that phytoflagellates did not adjust their metabolic activity upon prolonged darkness and that the FDA fluorescence remained constant. In the present study, the lowest esterase activity was measured after 72 h exposition for all conditions, even in the mixotrophic condition where the algal density was the highest measured. This unexpected result can be explained by the accelerated cell cycle growth due to the addition of glucose; we may have missed the appropriate timing of cell division.
Oxidative stress measured by ROS has been reported in many toxicity studies (Stauber et al. 2002; Mallick 2004). Overproduction of ROS can be detrimental to algal cells because of direct damage to proteins, amino acids, membrane lipids, etc. The present study revealed that ROS were not stimulated by addition of glucose in the medium and were relatively constant. MET was negatively affected by the glucose supplement; therefore, no additional free O2 originates from this oxidation reaction. The low light intensity, which is approximately 4–5 times lower than other studies (Yu et al. 2009; Wan et al. 2011), might explain the low ROS activity. The photosynthetic system is the dominant site producing ROS, and was not intensively used in microalgae fed glucose. Under mixotrophic and heterotrophic conditions, glucose addition accelerated the cellular division which is not the case in photoautotrophic condition. The lack of formation of free radical demonstrated that no major deterioration was observed at the cellular constituents, which usually concatenated into lipid peroxidation of the membrane. In our study, LPO decline all microalgae supplemented with glucose. At the biomembrane level, the production of LPO is a highly deleterious reaction that eventually leads to algal death. Living cells have developed defense mechanisms to detoxify these free radicals, such as the antioxidant enzyme APX. In our study, microalgae cultivated under mixotrophic or heterotrophic conditions produced APX to combat the free radicals. However, this is not the only antioxidant in algae to counter free radicals. For example, Mallick (2004) showed that copper exposure trigger superoxide dismutase activity, while the reverse trend was measured in activities of catalase, APX and glutathione reductase. All of these enzymatic mechanisms act as antioxidant defenses.
In general, photoautotrophic conditions that are sunlight and CO2 requirements can be directly converted into lipids by microalgae. Because of the decelerated cell growth cycle, lipids can be stored due to this excess of energy that is normally required for cellular division. Mixotrophic condition has to be considered as a potential alternative for microalgae cultivation in open pond systems. Mixotrophic and heterotrophic conditions favour the development of the antioxidant enzyme APX, which modified the algal biochemical component to prevent potential mortality. However, even if we could attain high density yield, the lipid concentration of our microalgae consortium was too low. Therefore, adjustment of the experimental parameters used in our study are needed to improved lipid yields Other possible explanations include that our selected strain from its natural environment might not be adequate for lipids production
Acknowledgements
This research was funded by BioFuelNet Canada, a network focusing on the development of advanced biofuels and associated bioproducts. BioFuelNet is a member of the Networks of Centres of Excellence of Canada program (www.biofuelnet.ca). We wish to thank Frédérique Bélanger-Lépine and Nathalie Boudreau for their technical assistance, Mélodie B. Plourde for her assistance with the cytometer, as well as Nathalie Dubois and Rachel Olette.
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