Effects of salinity on growth and lipid accumulation of biofuel microalga Nannochloropsis salina and invading organisms

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Effects of salinity on growth and lipid accumulation of biofuel microalga Nannochloropsis salina and invading organisms Meridith L. Bartley a, Wiebke J. Boeing a,*, Alina A. Corcoran a,1, F. Omar Holguin b, Tanner Schaub b a b

Department of Fish, Wildlife and Conservation Ecology, New Mexico State University, Las Cruces, NM 88003, USA Chemical Analysis and Instrumentation Laboratory, New Mexico State University, Las Cruces, NM 88003, USA

article info

abstract

Article history:

Mass production of microalgae is currently limited by existing cultivation strategies, which

Received 3 April 2012

rely heavily on open cultivation systems. Increasing lipid production in these systems

Received in revised form

while minimizing the invasion of non-target algae (competitors) and grazers (predators)

22 March 2013

will improve the economic viability of algal biofuel. In this study, we manipulate a basic

Accepted 23 March 2013

environmental parameter, salinity, to promote algal growth and limit invading organisms.

Available online

We monitor the growth of marine microalga Nannochloropsis salina and invasion of algal competitors and predators in open cultures grown at different salinities ranging from

Keywords:

brackish to hypersaline. Algal growth and biomass was greatest at salinities of 22 and 34

Micro-algae biodiesel

PSU, whereas the density of invading organisms was lowest at 22 PSU. To determine if lipid

Salinity

accumulation could be maximized by salinity stress, we grew N. salina at 22 PSU until the

Lipid accumulation

populations were at stationary phase and then increased salinity to 34, 46, and 58 PSU.

Lipid profile

Gravimetrically determined lipid content increased significantly at these higher salinities,

Invasive organisms

and was highest at 34 PSU (36% dry tissue mass). Analysis of Folch extracts by FT-ICR mass

Invaders

spectrometry showed a monotonic increase in triglyceride content and decreased membrane lipid content with increased salinity. Together, this work demonstrates an ecological approach to overcome the current limitations of cultivation strategies. ª 2013 Elsevier Ltd. All rights reserved.

1.

Introduction

The finite nature of fossil fuels demands reductions in energy consumption, as well as research and development of sustainable energy alternatives. Currently, renewable energy sources, including biofuels, account for a mere 1.8% of total world energy consumption [1]. The growth of biofuel production has been skewed towards food and oil crops (e.g., corn, sugarcane), however, these crops do not show production rates that make them economically competitive with

traditional fossil fuels and may have threatened food security [2]. In addition, arable land and water resources limit the production of terrestrial biofuel crops. Microalgae currently represent a viable third-generation biofuel source [3,4], as they are capable of year-round production, require less water than terrestrial crops, produce only point-source wastewater, and create valuable co-products (animal feeds and pharmaceuticals) [2e6]. Yet, the commercial viability of algal biofuel is restricted by current production systems, typically open ponds that are inexpensive to create but unable to restrict the

* Corresponding author. Tel.: þ1 575 646 1707; fax: þ1 575 646 1281. E-mail address: [email protected] (W.J. Boeing). 1 Present address: Fish and Wildlife Research Institute, Florida Fish and Wildlife Conservation Commission, St. Petersburg, FL, USA. 0961-9534/$ e see front matter ª 2013 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.biombioe.2013.03.026

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growth of invading (competing) algae and organisms grazing on algae, like ciliates and rotifers [7]. Indeed, outdoor, open ponds often fail to maintain selected species for more than a few weeks or months due to contamination by invading organisms. As such, the biofuel industry requires optimized systems, which yield productive cultures that are stable and resilient, but resistant to invading organisms. So far, the ecology of algae production systems (how the desired alga strain and invading organisms interact with each other and their environment) has been neglected. A decisive plan with a novel ecological approach will provide unique solutions to address the current limitations of algal biofuel growth systems. A simple approach would be to manipulate environmental factors to simultaneously promote algal growth and limit competitor or predator growth. It is well known that microalgal growth is influenced by environmental parameters, such as salinity [8,9], but the manipulation of environmental parameters to control the aquatic community of invading organisms in biofuel systems has not yet been employed. Potentially growth-limiting factors, such as salinity, within natural biotic communities in outdoor bioreactors act as “bottom-up” regulators of the invasive organisms. The present study explores the use of salinity manipulations to enhance growth rates of Nannochloropsis salina, an alga commonly used in biofuel systems, while minimizing undesirable organisms in the culture. As a commonly cultivated organism, Nannochloropsis has been used to produce biofuel [2e4], pharmaceuticals [10e12], and fish feed [13e15]. Nannochloropsis salina (Class: Eustigmatophyceae) was selected for this study because of its high growth rate, high lipid productivity, and wide environmental tolerance [16]. In the arid conditions of New Mexico and other proposed algae cultivation sites, the medium in open outdoor ponds can rapidly evaporate, increasing salinity. Thus, it is important to understand how the lipid content and growth rate of target biofuel algae change with salinity fluctuations. Nannochloropsis salina has been reported to grow fastest between 20 and 40 PSU [17] and produce the most lipids, as total lipid and percent lipid per unit biomass, at salinities between 30 and 35 PSU. Further, salinity can affect the lipid composition of N. salina [5,18]. In general, lipid accumulation is maximized when Nannochloropsis cells are “stressed”; with a stress, cells shift from actively dividing to storing energy [19]. For example, Nannochloropsis can attain 60% lipid content by weight when exposed to nitrogen starvation and high irradiances [5]. In addition, Renaud and Parry [20] found that when N. oculata was grown in a series of salinities (10e35 PSU), total lipid content increased with increasing salinity and highest percentages of lipids were found at high salinity (30e35 PSU). However, to our knowledge, no research has been conducted to assess how salinity manipulations alter the growth rates and lipid content of N. salina or the success of invading organisms. Anecdotally, invading diatoms and ciliates (competitor and predator, respectively) of outdoor cultures of N. salina was concurrent with low algae culture densities under stress due to nutrient limitation [21]. This work explores the utility of salinity manipulations towards two goals: (1) to enhance N. salina growth while minimizing invader growth and (2) to increase the lipid content and key biofuel lipid species within Nannochloropsis

cultures. This research is novel because of its ecological focus on invading organisms and its attempt to utilize salinity increases as a stressor. The implications of this work may provide cost-effective, viable, and sustainable development of algal biofuels industry.

2.

Methods

2.1.

Microalgae cultures and experimental set-up

Nannochloropsis salina 1776 was obtained from the ProvasoliGuillard National Center for Culture of Marine Phytoplankton via the Los Alamos National Laboratory. The culture medium used during experiments was the f/2 medium for marine algae [22], made with Instant Ocean in non-sterile deionized water. All experiments were conducted in a greenhouse located at New Mexico State University’s Fabian Garcia Science Center (Las Cruces, New Mexico, USA), where open aquaria were subjected to natural light and temperature conditions. One experiment examined the effect of a range of salinity levels on growth rate and abundance of N. salina and abundance of invading organisms. The other examined the effect of inducing stress with varying levels of salinity increase on lipid content. A preliminary experiment explored growth rates at vastly different salinities (0, 8, 17, 25, 34, 68, 102, 136, 170, 204 PSU) to give us an idea about N. salina’s salinity tolerance. N. salina is a marine algae and typically grown at a salinity concentration of 34 PSU. The salinity of 34 PSU, for example, was created by adding 34 g of Instant Ocean salt to 1 L of distilled water. N. salina did not grow above 68 or below 8 PSU (Bartley, unpublished data). Therefore, our experiments were conducted using salinities between 10 and 58 PSU. We maintained stock cultures of N. salina in an outdoor raceway at Fabian Garcia Science Center under standard cultivation conditions. Both experiments were conducted in glass aquaria with 30 L working volume. Temperature, pH, and salinity were monitored mid-day three times a week with a Hydrolab (model MS 5, HachHydromet, Loveland CO). Salinity is calculated as a conductivity ratio of the water sample to a standard KCl solution on the dimensionless Practical Salinity Scale (PSS) and is referred to in Practical Salinity Unit (PSU) throughout this manuscript.

2.1.1. Nannochloropsis growth rates and invading organisms [experiment 1] N. salina cultures were grown at five different salinity levels (10, 22, 34, 46, 58 PSU) each with six replicates, in the experimental aquaria described above. Cultures were inoculated with 250 mL of stock algae so that the initial N. salina abundance in all tanks was approximately 2500 cells mL1. We ran the experiment for 46 days, sampling three times each week for algal biomass, and on the last sampling date for invading organisms (see “Algal Biomass Measurements and Quantification of Invading Organisms”). Since manual counts are very time consuming, we only had resources to evaluate invading organisms on the last day. Furthermore, for this study, we only investigated what organisms were able through natural, passive invasion to enter the experimental units and able to reproduce and sustain high numbers. Although we did not

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observe any direct predation by ciliates and rotifers on Nannochloropsis, both are known to be efficient algae predators. While other invading algae might not be directly harmful to Nannochloropsis, they would compete for nutrients. If those algae have significantly lower lipid accumulation rates, they would make an algae production system less efficient. All samples were preserved with Lugol’s solution. Previous research shows that this preservation method preserves the greatest cell numbers [23], but may shrink or distort cell morphology [24].

2.1.2.

Nannochloropsis lipid accumulation [experiment 2]

We grew 24 algal cultures at a salinity of 22 PSU in the aquaria described above until the populations reached stationary phase. Cultures were inoculated with 1 L of stock algae, resulting in an initial N. salina abundance of approximately 2,400 cells mL1, and were grown until stationary phase was reached, 14 days later. Growth stage was tracked daily with absorbance and cell counts. On day 15, we altered salinity to 22, 34, 46, and 58 PSU (six replicates each). As the salinity switch occurred in the stationary phase, it did not have an effect on growth rate. One-liter samples were collected two weeks after salinity levels were altered, for subsequent measurements of algal biomass and lipid content (see sections below).

2.2. Algal biomass measurements and quantification of invading organisms Three metrics of algal biomass, absorbance at 740 nm, growth rate, and cell number, were used to track population dynamics. Absorbance was measured within 1 h of collection with a Spec 20 (model Dþ, Thermo Fisher Scientific, Waltham MA) and cell count samples were preserved with Lugol’s solution and stored in dark, cool locations for less than six months. Growth rate (m) was calculated from cell counts of experiment 1 for the time from inoculation until all treatments had approximately reached their maximum densities (day 0eday 21) with the following formula:

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supernatant removed. Extraction was repeated and combined supernatants were evaporated in pre-weighed vials under a stream of nitrogen. All lipid extracts were stored under nitrogen at 20  C for FT-ICR MS analysis. Stock algal lipid extracts were prepared by dissolution in methanol:chloroform (1:2 v/v) for a normalized concentration of 10 mg/mL. These stock solutions were further diluted 100 fold into 1 mL of 2:1 methanol:chloroform which contained 5 mL of aqueous 1 M sodium acetate (positive ion mode) or 1 M ammonium hydroxide (negative ion mode) and 10 mg/mL of phosphatidylethanol amine, PE(17:0/17:0), as an internal standard. All solvents used were purchased from Sigma (St. Louis, MO) and were HPLC grade. Direct infusion electrospray ionization mass spectrometry was performed with a hybrid linear ion trap FT-ICR mass spectrometer (LTQ FT, Thermo, San Jose, CA) equipped with an Advion Triversa NanoMate (Advion, Ithaca, NY) at high mass resolving power (m/Dm50% ¼ 400,000 at m/z 400). Elemental compositions were assigned for w1700 intact lipid species and these were then searched against a list of known lipids derived from the Lipid Maps database (Nature Lipidomic Gateway) by an in-house built Microsoft Excel macro [26]. Tentative lipid-molecular assignments were confirmed by tandem mass measurement [27]. Full quantification by application of response factors for each lipid class is not yet possible due to a lack of available analytical standards for many lipid classes. Nonetheless, qualitative FT-ICR mass spectrometry illustrates variation within each lipid class for comparative analysis and provides a detailed view of these materials not otherwise available.

2.4.

Statistical analyses

Regression analyses were used to evaluate the effect of salinity on maximum cell density, growth rate, invading organism abundance and total lipid content. Optimum conditions were estimated for each response variable. All data were checked for equal variance and normality using residual plots. All analyses were conducted in R software and a was set to 0.05.

m ¼ [ln (d21)  ln (d0)]/t where d ¼ density, 21 and 0 ¼ day of experiment, and t ¼ time in days Subsequent cell counts were conducted by counting at least 400 N. salina cells within a Neubauer haemocytometer (Marienfeld GMBH & Co., Germany). A 1-mL gridded Sedgewick-Rafter chamber (model # 1801-G20, Wildlife Supply Company, Yulee, FL) was used to count larger invading organisms (>30 mm), where as smaller organisms were counted using a haemocytometer. At least 100 organisms were counted for each invading organism sample.

3.

Results

3.1. Nannochloropsis growth and invading organisms [experiment 1] Nannochloropsis accumulated the greatest biomass at salinities of 22 and 34 PSU. The maximum cell density (33,035 mL1) was obtained at 22 PSU on day 35. Maximum cell density can be predicted by salinity level (Fig. 1; p < 0.0027).

YDensity ¼ 9395.86 þ 2537.21  Salinity  32.05  Salinity2

2.3.

FT-ICR mass spectrometry

We applied the Folch method [25] for lipid extraction. Dried algal samples (0.1 g) were extracted in triplicate for 30 min with 2 mL of chloroform/methanol (2:1 v/v) at 25  C with continual vortexing. Extracts were centrifuged and the

The optimum salinity was estimated to be 33.3 PSU. This model had an R2 of 0.39. Growth rate results show a similar story with maximum average rates of 0.13 and 0.12 day1 for 22 and 34 PSU, respectively ( p < 0.0001).

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3.2.

Nannochloropsis lipid accumulation [experiment 2]

Lipid accumulation increased with salinity and was greatest in the 3.4% treatment (Fig. 2; p ¼ 0.044).

YLipid ¼ 19.90 þ 2.56  Salinity  0.03  Salinity2

Fig. 1 e Nannochloropsis mean cell number density ± S.E. (n [ 6) in five different salinity levels (10, 22, 34, 46, and 58 PSU).

YGRate ¼ 7.34  102 þ 1.01  102  Salinity  1.41  104  Salinity2 The optimum salinity was estimated to be 35.6 PSU. The R2 for the model was 0.56. Absorbance data showed similar results to cell count and growth rate data (data not shown). Temperature and pH in the aquaria ranged from 23 to 28  C and 8.5 to 9.3, respectively, through all of the treatments for the duration of the experiment. Results from this experiment led to a base salinity level of 22 PSU applied during the second experiment. Densities of invading organisms were evaluated on day 46. Moderate to high salinities limited the growth of rotifers (predators) and cyanobacteria (competitors), however salinity had little effect on the densities of ciliates and diatoms (Table 1). Ciliates experienced a large variability between treatments (630e2500 mL1), with high densities at both low (10 PSU) and moderate (34e46 PSU) salinity levels. Overall, the lowest densities of invading organisms occurred within the algae cultures grown at 22 PSU, however the treatments were not significantly different for any invader category (all p > 0.05).

The optimum salinity was estimated to be 39.2 PSU. The R2 for this model was 0.3074. All cultures that experienced an increase in salinity to 34, 46, or 58 PSU exhibited increased total lipid accumulation (37.5, 21.8, and 26.6%, respectively) in comparison to the cultures that received no change in salinity (18.8%). Fig. 3 illustrates FT-ICR MS determined lipid composition for Folch extracts of N. salina tissue samples harvested at two weeks post-salinity alteration. Triglyceride (TAG) content increased dramatically for 46 and 58 PSU. We observed forty-three individual triglyceride species, with 16:0, 16:1, and 18:1 acylsubstituted species being most abundant. We did not see significant change in the distribution individual triglyceride molecules with variation in salinity level (data not shown). Similarly, we observed increased sterol and acylated sterol glycoside content with increased salinity. Glyco- and phospholipid abundances (including glycerophosopholipids, diacylglycerophosphocholines, 1,alkyl- 2,acyl-glycerophosphocholines, glycerophosphoinositols and diacylglycerophosphoserines) remained relatively unchanged with variable salinity. We observed thirtysix DGTS compounds (Fig. 3) and eighteen MGTS membrane lipid compounds, the abundance of which did not change significantly for salinity levels between 34 and 58 PSU. Betaine lipid and oxidized betaine lipids tentatively identified as DGCC compounds were observed at significantly higher relative abundance (increase of 37e58%) for the 34 PSU Folch extract than other salinity levels (data not shown). The observed abundance of sulfate lipids and oxidized forms of those molecules were significantly reduced at 34 PSU salinity whereas thylakoid membrane lipids SQDG and the mono-acyl forms, SQMG, were seen at elevated levels for the 34 PSU Folch extract.

Table 1 e Mean densities ± S.E. of invading organisms at different salinities. Phytoplankton Salinity (PSU) 10 22 34 46 58

Diatoms 1

Cyanobacteria 1

(mL )

(mL )

    

1400  950 6.7  2.2 0 0 0

410 450 890 560 810

78 140 380 110 380

Zooplankton Ciliates 1

Rotifers

(mL )

(mL1)

    

8.3  6.8 0 0 0 0

2200 630 2500 2000 970

900 430 300 1000 460

Fig. 2 e Mean lipid accumulation ± S.E. (n [ 3) in Nannochloropsis salina by weight two weeks subsequent to salinity alterations. All cultures began growth at 22 PSU and salinity was increased to 34, 46, and 58 PSU in select treatments.

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Fig. 3 e Lipid compositional change of Nannochloropsis salina at variable salinity determined by ultrahigh resolution FT-ICR mass spectrometry.

4.

Discussion

Our study suggests N. salina production for biofuels might work best if algae are grown at a lower, brackish salinity and then increased to a higher salinity when reaching stationary phase as this technique allowed for the highest lipid accumulation rates. Maximum algal growth and minimal invaders occurred at 22 PSU. Our observed optimum salinity range for N. salina growth (22e34 PSU) was consistent with previous research (e.g. (25e30 PSU) [20]; (20e40 PSU) [17]; (22e49 PSU) [28]). Also consistent with previous research was our maximum yield. A maximum density of 33,035 cells mL1 was reached at 22 PSU whereas cultures grown at 34 PSU approached this density with a maximum of 29,797 cells mL1. Previous research found N. oculata reached a maximum density of 25,600 cells mL1 at 25 PSU [20] and that Nannochloropsis reached a maximum cell density of 24,900e32,400 cells mL1 between 20 and 40 PSU [17]. Further research demonstrated that higher salinity (40 PSU) resulted in lower cell abundance, consistent with our findings of decreased N. salina at 46 and 58 PSU [29]. Observed invading organisms during the experiments included species of rotifers, ciliates, cyanobacteria, and diatoms. These invading organisms could jeopardize algae cultures through predation and competition that ultimately may lead to lower biomass or lipid accumulation or even a total population crash. At 22 PSU, the optimum salinity for maximum Nannochloropsis growth also minimized invasion of undesired organisms. While cyanobacteria and rotifer abundance was greatest at 10 PSU, the maximum abundance of diatoms and ciliates was reached at 34 PSU. Cyanobacteria and rotifers found in our experiment were the least tolerant to salinity. The unique spread of ciliates (highest densities at 10 as well as 34 PSU) may be due to the presence of different ciliate species; both fresh- and saltwater adapted ones. Diatoms exhibited a wide salinity tolerance. However, the organisms that invaded our aquaria may be unique to our location and the time of year. These invading organisms often limit open pond cultivation of certain algal

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species. The Department of Energy’s Aquatic Species Program [30] reported that few algal strains had been successfully maintained in large, open ponds for long periods of time. In the most successful cases, Spirulina and Dunaliella strains were maintained in open ponds through the use high bicarbonate and high salinity, respectively. Stressing the algae cells through a one-time salinity increase may cause additional lipid accumulation than stress through nutrient limitation by itself. Through our experiment, we saw all cultures that experienced an increase in salinity from 22 PSU to 34, 46, or 58 PSU exhibited increased total lipid accumulation (Fig. 2) in comparison to the cultures that received no change in salinity. While the concept of stressing cells is not a new one, we believe to be unique in our approach. The addition of salt during key stages of growth and harvesting is a simple yet effective technique to maximize the lipid accumulation of N. salina. Lipid extract composition varies with salinity with a general trend of increased nonpolar lipid content observed for elevated salinity treatments and a concomitant decrease in membrane lipid content. However, the range of observed compounds with respect to carbon number and acyl-double bond content does not shift significantly with salinity for the majority of lipid classes observed. To our knowledge, this technique has not yet been employed in algal biofuel systems. However, nutrient limitation, specifically that of nitrogen, has been shown to enhance the lipid content of algae [5,16,18,19]. Under nitrogen-deplete conditions, many algae species divert carbon into storage, particularly into triacylglyceroles (TAGs), which are ideal reserves for biofuel energy [8]. In addition to lipid accumulation, lipid composition can be modulated by growth conditions, such as salinity (Fig. 2). The development and success of a microalgae-based biofuels industry depends on its ability to find a production process with a positive net energy ratio through high algae growth and lipid accumulation rates. However, predators and competitors might interfere with optimum production of the desired algae strain. Our observations of algae growth and invading organisms, as they were affected by salinity, may advance production through support of previous conclusions along with novel findings. Future studies should examine if a gradual rise in salinity, as could be found in open ponds that show an increase in salinity due to evaporation, would also result in a similar increase in accumulated lipids as the abrupt increase in salinity. Furthermore, the deliberate introductions of various invading organisms could shed light on the mechanisms for excluding certain invaders.

5.

Conclusions

The two salinity-based experiments conducted in this study have provided valuable insight for an ecological approach to remedy the limitations of algae cultivation for use in algal biofuel. N. salina exhibited highest growth rates and biomass accumulation between salinities of 22 and 34 PSU. Our results also indicated that invader organisms could be minimized at 22 PSU. Hence, we recommend algae cultures be grown at an initial salinity of 22 PSU so that the option for a slight increase

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to 34 PSU may be utilized upon increased invading organisms or when stationary phase is reached. This increase will also increase lipid accumulation. The limitations that prevent algal biofuel from attaining commercial viability, which include the need for optimal production and cultures that are resistant to invading organisms, may be continually addressed by identifying additional environmental parameters and methods useful in increasing production efficiency.

Acknowledgments We are grateful for the valuable work from the following undergraduate students: German Camacho, Herman Campos, Dalli Chavez, Levi Chavez, Tim Clawson, Tori Gadney, Justin Monzingo, Richelle Morin, Noah Moss, Lisa Rogash, and Jacob Villalobos. Wayne VanVoorhies and Nirmala Khandan deserve thanks for supplying algae cultures. Darren James provided valuable help with statistical analyses for this research. This work is supported by the U.S. Department of Energy under contract DE-EE0003046 awarded to the National Alliance for Advanced Biofuels and Bioproducts and by the Center for Animal Health, Food Safety and Biosecurity at New Mexico State University. This is a New Mexico Agricultural Experiment Station publication, supported by state funds and the U.S. Hatch Act.

references

[1] British Petroleum. BP statistical review of World energy [accessed 09.03.12], http://www.bp.com/sectionbodycopy. do?categoryId¼7500&contentId¼7068481; 2011. [2] Brennan L, Owende P. Biofuels from microalgaeea review of technologies for production, processing, and extractions of biofuels and co-products. Renew Sust Energ Rev 2010;14(2):557e77. [3] Chisti Y. Biodiesel from microalgae. Biotechnol Adv 2007;25(3):294e306. [4] Mata TM, Martins A, Caetano NS. Microalgae for biodiesel production and other applications: a review. Renew Sust Energ Rev 2010;14(1):217e32. [5] Rodolfi L, Chini Zittelli G, Bassi N, Padovani G, Biondi N, Bonini G, et al. Microalgae for oil: strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnol Bioeng 2008;102(1):100e12. [6] Doan TTY, Sivaloganathan B, Obbard JP. Screening of marine microalgae for biodiesel feedstock. Biomass Bioenerg 2011;35(7):2534e44. [7] Moazami N, Ashori A, Ranjbar R, Tangestani M, Eghtesadi R, Nejad AS. Large-scale biodiesel production using microalgae biomass of Nannochloropsis. Biomass Bioenerg 2012;39:449e53. [8] Roessler PG. Environmental control of glycerolipid metabolism in microalgae: commercial implications and future research directions. J Phycol 1990;26(3):393e9. [9] Rocha J, Garcia JEC, Henriques MHF. Growth aspects of the marine microalga Nannochloropsis gaditana. Biomol Eng 2003;20(4):237e42. [10] Cheng-Wu Z, Zmora O, Kopel R, Richmond A. An industrialsize flat plate glass reactor for mass production of Nannochloropsis sp. (Eustigmatophyceae). Aquaculture 2001;195(1e2):35e49.

[11] Rebolloso-Fuentes MM, Navarro-Pe´rez A, Garcı´a-Camacho F, Ramos-Miras JJ, Guil-Guerrero JL. Biomass nutrient profiles of the microalga Nannochloropsis. J Agric Food Chem 2001;49(6):2966e72. [12] Chini Zittelli G, Rodolfi L, Tredici MR. Mass cultivation of Nannochloropsis sp. in annular reactors. J Appl Phycol 2003;15(2e3):107e14. [13] Chini Zittelli G, Pastorelli R, Tredici MR. A modular flat panel photobioreactor (MFPP) for indoor mass cultivation of Nannochloropsis sp. under artificial illumination. J Appl Phycol 2000;12(3e5):521e6. [14] Richmond A, Cheng-Wu Z. Optimization of a flat plate glass reactor for mass production of Nannochloropsis sp. outdoors. J Biotechnol 2001;85(3):259e69. [15] Rodolfi L, Chini Zittelli G, Barsanti L, Rosati G, Tredici MR. Growth medium recycling in Nannochloropsis sp. mass cultivation. Biomol Eng 2003;20(4e6):243e8. [16] Griffiths MJ, Harrison SL. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J Appl Phycol 2009;21(5):493e507. [17] Abu-Rezq TS, Al-Musallam L, Al-Shimmari J, Dias P. Optimum production conditions for different high-quality marine algae. Hydrobiologia 1999;403(0):97e107. [18] Guschina IA, Harwood JL. Lipids and lipid metabolism in eukaryotic algae. Prog Lipid Res 2006;45(2):160e86. [19] Wang ZT, Ullrich N, Joo S, Waffenschmidt S, Goodenough U. Algal lipid bodies: stress induction, purification, and biochemical characterization in wild-type and starchless Chlamydomonas reinhardtii. Eukaryot Cell 2009;8(12):1856e68. [20] Renaud SM, Parry DL. Microalgae for use in tropical aquaculture II: effect of salinity on growth, gross chemical composition and fatty acid composition of three species of marine microalgae. J Appl Phycol 1994;6(3):347e56. [21] Boussiba S, Vonshak A, Cohen Z, Avissar Y, Richmond A. Lipid and biomass production by the halotolerant microalgae Nannochloropsis salina. Biomass 1987;12(1):37e47. [22] Guillard RRL, Ryther JH. Studies of marine planktonic diatoms. I. Cyclotella nana Hustedt and Detonula confervacea Cleve. Can J Microbiol 1962;8(2):229e39. [23] Leakey RJG, Burkill PH, Sleigh MA. A comparison of fixatives for the estimation of abundance and biovolume of marine planktonic ciliate populations. J Plankton Res 1994;16(4):375e89. [24] Stoecker DK, Gifford DJ, Putt M. Preservation of marine planktonic ciliateselosses and cell shrinkage during fixation. Mar Ecol Prog Ser 1994;110(2e3):293e9. [25] Folch J, Lees M, Stanley GHS. A simple method for the isolation and purification of total lipids from animal tissues. J Biol Chem 1957;226(1):497e509. [26] Holguin FO, Schaub TM. Characterization of microalgal lipid feedstocks by direct infusion FT-ICR mass spectrometry. Algal Res 2013;2(1):43e50. [27] Han XL, Gross RW. Shotgun lipidomics: multidimensional MS analysis of cellular lipidomes. Expert Rev Proteomic 2005;2(2):253e64. [28] Hu H, Gao K. Response of growth and fatty acid compositions of Nannochloropsis sp. to environmental factors under elevated CO2 concentration. Biotechnol Lett 2006;28(3):987e92. [29] Pal D, Khozin-Goldberg I, Cohen Z, Boussiba S. The effect of light, salinity, and nitrogen availability on lipid production by Nannochloropsis sp. Appl Microbiol Biotechnol 2011;90(4):1429e41. [30] Sheehan J, Dunahay T, Benemann J, Roessler P. A look back at the U.S. Department of Energy’s aquatic species programebiodiesel from algae. Golden CO: National Renewable Energy Laboratory; 1998 July328. Report NREL/TP580e24190.