An efficient and scalable extraction and 
quantification method for algal derived 
biofuel
Authors: Egan J. Lohman, Robert D. Gardner, Luke 
Halverson, Richard E. Macur, Brent M. Peyton, & 
Robin Gerlach
NOTICE: this is the author’s version of a work that was accepted for publication in Journal of 
Microbiological Methods. Changes resulting from the publishing process, such as peer review, 
editing, corrections, structural formatting, and other quality control mechanisms may not be 
reflected in this document. Changes may have been made to this work since it was submitted for 
publication. A definitive version was subsequently published in Journal of Microbiological 
Methods, 94, 3, September 2013. DOI# 10.1016/j.mimet.2013.06.007. 
Lohman EJ, Gardner RD, Halverson L, Macur RE, Peyton BM, Gerlach R, "An efficient and 
scalable extraction and quantification method for algal derived biofuel," Journal of Microbiological 
Methods, September 2013 94(3): 235–244.
Made available through Montana State University’s ScholarWorks 
scholarworks.montana.edu 
An efficient and scalable extraction and quantification method 
for algal derived biofuel
Egan J. Lohman, Robert D. Gardner, Luke H
Peyt
Montan g a
A B S
Keywor
Triacylg tty acid
Micro nd cts 
such a sp nce 
slight t th ent 
a met nd eir 
charac cu nes 
which esp ed; 
inform algae candidates as a biodiesel source. Traditional methods of 
analyz tal 
conditions. Here we detail a new method  to 
extract lipids from live cultures of microa ds, 
mono-, di- or tri-acylglycerides) and carbo ed 
into FAMEs and directly compared to tota  of 
total FAMEs derived from extractable lip nd 
phospholipids, ste-rols, etc.). This approach ive 
abundance, is responsible for each FAM om 
Phaeo l Chlo ris. 
The m hly re me 
course e-res  to 
obtain 2 h.
Con
current
percen
politica
resourc
fuels (D
2008; 
biofuel
market
sources
mass r
2008). 
food” 
(Ferrel
 in 
nd 
om 
eat 
Es) 
uel 
 the current distribution 
s. Biodiesel has similar 
nd a higher combustion 
um 
I N T, they hold great potential for truly displacing traditional 
 due to their high biomass productivity, relatively small land 
equirements and high lipid yield (Chisti, 2007; Hu et al., 
efficiency than gasoline (Demirbas, 2007).
However, if biodiesel is to replace a large part of petroleismukes et al., 2008; Greenwell et al., 2010; Groom et al., 
Hill et al., 2006; Sheehan, 1998). Although algae-derived 
s command a relatively small percentage of this emerging 
since no modifications have to be made to
infrastructure or diesel combustion engine
combustion properties to petroleum diesel at-age being imported from foreign sources (EIA, 2012). The 
l, economic and environmental controversies over these 
es have resulted in increased interest in advanced alternative 
mono, di, and tri-acylglycerides (MAG, DAG, TAG), derived fr
plant or animal sources, react with methanol in the presence of h
and base or acid, to produce fatty acid methyl esters (FAM
(Laurens et al., 2012a). Biodiesel is considered a “drop-in” fFurther, algal fuels do not directly cont
debate because they can grow in non-a
l and Sarisky-Reed, 2010). in the United States 
 with a significant 
Biodiesel is the end result of a transesterification reaction
which lipids such as phospholipids, free fatty acids (FFA), asumption rates of traditional fossil fuels
ly exceed 18 million barrels per dayds:
lycerol (TAG) - Microalgae - Biodiesel - Fa
dactylum tricornutum, the mode
ethod is shown to be robust, hig
 of culturing, thus providing tim
ing analytical results is less than 
R O D U C T I O N methyl ester (FAME) Nile Red fluorescence - GC–FID/MS
which uses microwave energy as a reliable, single-step cell disruption technique
lgae. After extractable lipid characterization (including lipid type (free fatty aci
n chain length determination) by GC–FID, the same lipid extracts are transesterifi
l biodiesel potential by GC–MS. This approach provides insight into the fraction
ids compared to FAMEs derived from the residual fraction (i.e. membrane bou
can also indicate which extractable lipid compound, based on chain length and relat
E. This method was tested on three species of microalgae; the marine diat
rophyte Chlamydomonas reinhardtii, and the freshwater green alga Chlorella vulga
producible, and fast, allowing for multiple samples to be analyzed throughout the ti
olved information regard-ing lipid quantity and quality. Total time from harvestinging these precursor molecules are time intensive and prone to high degrees of variation between species and experimen
ation that is fundamental for identifying preferred microon, Robin Gerlach ⁎ 
a State University, Department of Chemical and Biological Engineerin
T R A C T
algae are capable of synthesizing a multitude of compou
s omega-3-fatty acids. However, accurate analysis of the 
variations in saturation and carbon chain length can affec
hod that allows for fast and reliable extraction of lipids a
terization using gas chromato-graphic analysis with a fo
 range of biologically synthesized compounds is likely rend in the “fuel vs. 
rable environments alverson, Richard E. Macur, Brent M. 
nd Center for Biofilm Engineering, Bozeman, MT 59717, United States
s including biofuel precursors and other high value produ
ecific compounds produced by microalgae is important si
e quality, and thus the value, of the end product. We pres
similar compounds from a range of algae, followed by th
s on biodiesel-relevant compounds. This method determi
onsible for each fatty acid methyl ester (FAME) produchydro-carbon based fuels, the compositional makeup of biodiesel 
will be-come highly important since biodiesel can have poorer 
performance than petroleum-based diesel (Hunter-Cevera et al., 
2012). For exam-ple, (i) the viscosity of fully saturated 
hydrocarbons increases signifi-cantly at low temperatures and can 
lead to operational issues and (ii) short chain fatty acid methyl 
esters tend to be more susceptible to oxidation which can lead to 
corrosion, resulting in reduced engine durability (Xue et al., 2011). 
Therefore a comprehensive and diverse
Gardner et al., 2011, 2013). Hence, Nile Red-based measurements may
underestimate the total biofuel potential of algal species that produce
high fractions of FFA, MAG, DAG or membrane lipids. Additionally, the
Nile Red assay is qualitative (possibly semi-quantitative) and cannot
be compared between species. In contrast, gravimetric analysis can
overestimate total biofuel potential by including non-fuel components
(e.g. chlorophyll) in the total weight (Laurens et al., 2012b). Gas chro-
matographic analysis of FAMEs has proven to be a reliable method for
quantifying total biodiesel potential (Eustance et al., in press; Laurens
et al., 2012b), but fails to identify the biological precursor molecules.
Here, a new method is described which allows for high-throughput
harvesting and extraction of live cultures by utilizingmicrowave energy
for a one-step cell disruption-and-extraction of lipid precursors (FFA,
MAG, DAG, TAG). Microwave energy has recently been shown to be
an effective cell disruption technique, generating comparative or better
lipid yields than more traditional methods such as sonication or bead
beating (Lee et al., 2010; Patil et al., 2012; Prabakaran and Ravindran,
2011). Additionally, extraction of lipids from live culture significantly
reduces process time and decreases the potential for degradation of
intracellular lipid compounds. A portion of the lipid extract is analyzed
by GC coupled with flame ionization detection (GC–FID) to identify the
lipid class and carbon chain length of the fatty acid(s). In parallel, a
portion of the lipid extract is transesterified and analyzed by GC–MS to
identify FAMEs derived from extractable lipid. Additionally, total
biodiesel potential is determined by direct in situ transesterification of
live cultures. Comparisons can bemade between extractable lipid precur-
sors, FAMEs derived from extractable lipids and total biodiesel potential
by contrasting the carbon chain length and saturation of each molecule
respectively. This approach was demonstrated for three different fre-
quently usedmicroalgae species; themodel Chlorophyte Chlamydomonas
reinhardtii, the marine diatom Phaeodactylum tricornutum and the fresh-
water green alga Chlorella vulgaris. These three organisms have been
extensively studied (e.g. Gardner et al., 2012; Merchant et al., 2007;
Stephenson et al., 2010; Valenzuela et al., 2012) and represent a diverse
set of microalgae which are commonly used for biofuel investigations
(Gardner et al., 2013; Liu et al., 2011; Spiekermann et al., 2003). The
method described herein is relatively simple, fast, utilizes fairly standard
equipment, and results in a comprehensive lipid profile within 2 h of
harvesting.
2. Materials and methods
2.1. Microalgae strains
2.1.1. Phaeodactylum tricornutum
P. tricornutum strain Pt-1 (CCMP 2561) (Pt-1) was acquired from the
Provasoli-Guillard National Center for Culture of Marine Phytoplankton
(East Boothbay, Maine, USA) and accessions of P. tricornutum have pre-
viously been described (Martino et al., 2007). Pt-1 was cultured on ASP2
medium (Provasoli et al., 1957) amended with 50 mM Tris buffer
(Sigma-Aldrich, USA), pKa 7.8, to maintain a stable pH throughout
culturing. Cultures were continuously sparged with ambient air andfeedstock of lipid precursors along with the derived fatty acid methyl
esters will be necessary to achieve the desired properties of the
biodiesel fuel (Knothe, 2005).
Traditionally, microalgae species have been screened for strains that
produce a high abundance of TAGusingfluorometric techniques such as
the Nile Red assay (Cooksey et al., 1987) and total lipid extracts have
been quantified gravimetrically (Bligh and Dyer, 1959) or by gas chro-
matography after transesterification (e.g. Guckert and Cooksey, 1990).
However, these methods are limited by their inherent inability to iden-
tify all, or only those, compounds which may be utilized for fuel. Nile
Red, for instance, roughly correlates with the amount of TAG precursors
per cell (Chen et al., 2009; Cooksey et al., 1987; Elsey et al., 2007;amended with 25 mM of sodium bicarbonate (final concentration)just prior to nitrate depletion in the medium to induce TAG accumula-
tion as demonstrated by Gardner et al. (2012).
2.1.2. Chlorella vulgaris
C. vulgaris, UTEX 395 (University of Texas at Austin) was cultured
on Bold's basal medium (Nichols and Bold, 1965) with pH adjusted to
8.7 prior to autoclaving. Cultures were sparged with 5% CO2 in air
during the light hours.
2.1.3. Chlamydomonas reinhardtii
C. reinhardtii CC124, obtained from the Chlamydomonas Center
(Minnesota State University, Minneapolis MN), was kindly provided
by John Peters, Department of Chemistry and Biochemistry at Montana
State University, and was cultured on Sager's minimal medium (Harris,
1989). Cultures were sparged with 5% CO2 (v/v) until just prior to
ammonium depletion, at which time the gas sparge was switched to
ambient concentrations of CO2 (0.04%; v/v) and 50 mM of sodium
bicarbonate (final concentration) were added to induce TAG accumula-
tion (Gardner et al., 2013).
2.2. Culturing conditions
All organisms were checked for bacterial contamination by inocu-
lation into respective medium supplemented with 0.05% yeast extract
and 0.05% glucose and incubation in the dark. Experiments were
conducted in triplicate batch cultures using 70 × 500 mm glass
tubes containing 1.2 L medium submersed in a water bath to control
temperature. Rubber stoppers, containing ports for aeration and
sampling, were used to seal the tubes. Temperature was maintained
at 24 °C ± 1 °C. Light (400 μmol photons m−2 s−1) was maintained
on a 14:10 light–dark cycle using a light bank containing T5 tubes.
Aeration (400 mL min−1) was supplied by humidified compressed
air (supplemented with 5% CO2 (v/v) for C. reinhardtii and C. vulgaris)
and controlled using individual rotameters for each bioreactor
(Cole-Parmer, USA). ACS grade sodium bicarbonate was used in all
experiments involving bicarbonate addition (Sigma-Aldrich, St. Louis,
MO).
2.3. Culture analysis
Cell concentrations were determined using an optical hemacy-
tometer with a minimum of 400 cells counted per sample for statisti-
cal reliability. Cell dry weights (CDWs) for C. reinhardtii and C. vulgaris
were determined by harvesting 30 mL of culture into a tared 50 mL
Falcon tube (Fisher Scientific, Palatine, IL) followed by centrifugation
at 4800 ×g and 4 °C for 10 min (Thermo Scientific, Sorvall Legend
XTR, Waltham, MA). The concentrated biomass was rinsed with
deionized H2O (diH2O), 18 MΩ, to remove media salts and excess
bicarbonate, before centrifuging again. Remaining algae pellets were
frozen and lyophilized (Labconco lyophilizer, Kansas City, MO) for
48 h. CDWs were calculated by subtracting the weight of the
biomass-free Falcon tube from the weight of the Falcon tube with
freeze-dried biomass.
CDWs for P. tricornutum were determined by filtering 10 mL of
culture using 1 μm pore size glass fiber filters (Fisher Scientific) to
collect the biomass. The biomass was washed with diH2O to remove
media salts and excess bicarbonate. Algal cells were dried at 70 °C
until the weight of the filter (plus biomass) remained constant.
CDWswere calculated by subtracting the dry weight of the clean filter
from the oven-dried weight of the filter with biomass. This method
was employed for the diatom due to the concern that the fragility of
the organism's silicon-based frustules may result in cell disruption
during the centrifugation and lyophilization steps utilized for the
Chlorophytes, thereby underestimating overall CDWs. This technique
was not employed for the Chlorophytes because it has been shown by
us and others (Laurens et al., 2012a) that the freeze drying method is
more reliable for green microalgae.
2.4. Analysis of media components
Medium pH was measured using a standard bench top pH meter.
Ammonium and nitrate concentrations were measured using Nessler
reagent (Hach, Loveland, CO) and ion chromatography (Dionex,
Sunnyvale, CA), respectively, using previously described protocols
(Gardner et al., 2013).
2.5. Harvesting
At the end of each experiment, cultures were transferred to a grad-
uated cylinder and total harvest volume was recorded. Two aliquots of
45 mL were dispensed into 50-mL Falcon tubes (Fisher Scientific,
Palatine, IL) and centrifuged (Thermo Scientific, Sorvall Legend XTR,
Waltham, MA) at 5800 ×g and 4 °C for 10 min. Concentrated biomass
was then transferred to Pyrex test tubes with Teflon lined screw caps
(Kimble-Chase, Vineland, NJ) for microwave extraction of lipid precur-
sors (Section 2.6.1) and direct in situ transesterification for total biodie-
sel potential (Section 2.7), respectively. The remaining ~1 L of culture
was centrifuged (Thermo Scientific, Sorvall Legend XTR, Waltham,
MA) at 5800 ×g and 4 °C for 10 min. The supernatant was discarded
and the remaining concentrated biomass was combined in a 50 mL
Falcon tube, washed with diH2O, re-centrifuged, and the supernatant
discarded. The washed biomass pellets were frozen at −80 °C,
lyophilized, and stored at −20 °C for subsequent cell disruption/lipid
extraction method comparisons (Section 2.6).
2.6. Cell disruption and extraction of lipids
Six different cell disruption and lipid extraction techniques were
tested in biological triplicate to compare their extraction yields
against yields from microwave extraction on live cultures. Unless
otherwise stated, all methods were performed using approximately
30 mg of dried biomass, and the final extract was supplemented with
10 μL/mL of a 10 mg/mL internal standardmix (isooctane in chloroform)
to monitor instrument performance. All mixtures involving solvent and
heat were carefully sealed in Pyrex test tubes with Teflon lined screw
caps (Kimble-Chase, Vineland, NJ). Final extracts were analyzed for
lipid precursors by gas chromatography–flame ionization detection
(GC–FID) (Section 2.9.2).
2.6.1. Microwave extraction of lipid from wet biomass
45 mL of culture were (45 milliliters) transferred into a 50 mL Fal-
con tube and centrifuged at 4800 ×g and 4 °C for 10 min. The super-
natant was discarded and the pellets were re-suspended in 3 mL
diH2O to facilitate transfer from Falcon tubes to screw-cap glass
tubes for subsequent lipid extraction. Three mL of chloroform were
added to the algal slurry in the test tubes, and the mixture was ho-
mogenized by vortexing for 10 s. Caps were securely fastened and
samples were microwaved (Sharp Carousel, Mahwah, NJ) at 1000 W
on power level 1 (~100 °C and 2450 MHz) for 1 min and then
allowed to cool for 5 min. This process of vortexing for 10 s,
microwaving for 1 min and cooling for 5 min was repeated until op-
timal extraction efficacy was established for each culture (Supple-
mental data). A total of 3 min microwave exposure was required for
samples of P. tricornutum and C. reinhardtii. Samples of C. vulgaris re-
quired a total of 10 min microwave exposure to completely disrupt
cells and release lipids into the organic solvent. Transmitted light mi-
croscopy was used to verify complete disruption of cells, and
epifluorescence microscopy was used to verify all extractable lipid
(stained with Nile Red) had been released into the organic solvent
(Nikon Eclipse E800).It should be noted that extreme caution should be taken when
applying microwave energy to an organic solvent under high heat
and pressure. To address this inherent safety concern this method has
since been modified by adding only 5 mL diH2O to the algal pellet
before transferring the slurry to screw cap test tubes, and test tubes
were further secured by placing them in a microwaveable Tupperware
container. Samples were then microwaved at 1000 W power level 4
(2450 MHz) for a continuous 5 min and allowed to cool. Three mL
of chloroform were added to each test tube when they had reached
room temperature. Test tubes were vortexed for 10 s and heated at
90 °C for 5 min to improve partitioning of the extracted lipids into
the organic phase. Equivalent results were obtained with both
versions of the method. The latter (i.e. water only-based extraction)
being inherently safer, it is the recommended approach. In either case,
samples were then centrifuged at 1200 ×g for 2 min to enhance phase
separation. One mL of the organic phase was removed from the bottom
of the test tube using a glass syringe and transferred to a 2 mL GC vial
(Fisher Scientific, Palatine, IL) for GC–FID analysis and subsequent
transesterification (Sections 2.9.2 and 2.8, respectively).
2.6.2. Microwave extraction of lipids from dry biomass
Microwave extraction of lipids from dry biomass was conducted as
described in Section 2.6.1 except ~30 mg of dried algae biomass were
used instead of live culture. Samples of P. tricornutum and C. vulgaris
were extracted using the optimized microwave extraction technique
with just diH2O and no organic solvent during the microwave step.
Samples of C. reinhardtii were collected before the optimized method
was established; therefore they were extracted with diH2O and solvent
together in the microwave extraction step.
2.6.3. Sonication extraction of lipids from dry biomass
Dried biomass was combined with 3 mL of chloroform in a dispos-
able 15 mL boro-silicate test tube. Samples were sonicated with a
Branson S-450D sonifier equipped with a microtip probe set to
80 W (Branson, Danbury, CT) for six 20 s pulses, with each pulse
followed by a 1 min cool down period in ice water. Total sonication
time was 2 min. Samples were then centrifuged at 1200 ×g for
2 min to pellet the residual biomass. One mL of the organic phase
was removed from the test tube using a glass syringe and transferred
to a 2 mL GC vial for GC–FID analysis.
2.6.4. Bead beating extraction of lipids from dry biomass
Dried biomass was combined with 1 mL of chloroform in a 1.5 mL
stainless steel bead beating microvial with silicone cap (BioSpec
Products, Bartlesville, OK). Three types of beads (0.6 g of 0.1 mm
zirconium/silica beads, 0.4 g of 1.0 mm glass beads, two 2.7 mm
glass beads) were added to each vial before capping. A FastPrep
bead beater (Bio101/Thermo Savant, Carlsbad, CA) was used to
agitate the vials for six 20 s pulses at power level 6.5 followed by a
1 min cool down period between pulses. Total bead beating exposure
time was 2 min. The mixture of solvent, residual biomass and beads
was then transferred to a disposable 15 mL boro-silicate test tube,
and the steel microvial was rinsed twice with 1 mL of chloroform,
which was also added to the test tube, bringing the total solvent
volume to 3 ml. Samples were then centrifuged at 1200 ×g for
2 min to pellet the residual biomass. One mL of the organic phase
was removed from the bottom of the test tube using a glass syringe
and transferred to a 2 mL GC vial for GC–FID analysis.
2.6.5. Heat induced extraction of lipids from dry biomass
Dried biomass was combined with 3 mL of chloroform and 3 mL
diH2O in a test tube. Samples were homogenized by vortexing for 10 s.
Caps were securely fastened to test tubes and samples were heated in
an oven at 95–100 °C for 1 h with vortexing every 10–15 min. Samples
were then centrifuged at 1200 ×g for 2 min to enhance phase separa-
tion. One mL of the organic phase was removed from the bottom of the
test tube using a glass syringe and transferred to a 2 mL GC vial for GC–
FID analysis.
2.6.6. Bligh and Dyer extraction of lipid from dry biomass
The modified Bligh and Dyer method (as described by Guckert et al.
(1988), without phosphate buffer) was used without any additional
physical cell disruption steps. Briefly ~50 mg of dry biomass from
each of the three organisms in triplicate was transferred to Pyrex test
tubes with Teflon lined screw caps. 1.5 mL of chloroform and 3 mL of
methanol were added to each test tube and sampleswere homogenized
by vortexing for 10 s. Capswere securely fastened, sampleswere placed
horizontally on a shaker table and allowed tomix continuously for 18 h.
1.5 mL diH2O and 1.5 mL chloroform were then added, and samples
were vortexed for 10 s before being centrifuged at 1200 ×g for 2 min
to enhance phase separation. One mL of the chloroform phase was
removed from the bottom of the test tube using a glass syringe and
transferred to a 2 mL GC vial for GC–FID analysis.
2.7. Direct in situ transesterification for FAME analysis
Direct in situ transesterification of live cultures was conducted using
a previously described protocol (Griffiths et al., 2010) with modifica-
tions. FAME composition was analyzed using gas chromatography–
mass spectroscopy detection (GC–MS) (Section 2.9.3). Briefly, 45 mL
of culture were transferred into a 50 mL Falcon tube and centrifuged
at 4800 ×g and 4 °C for 10 min. The supernatant was discarded and
the pellets were re-suspended in 3 mL diH2O to facilitate transfer
from Falcon tubes to screw-cap glass tubes for subsequent
transesterification. The tubes were centrifuged at 1200 ×g to remove
as much water from the remaining biomass as possible. One mL of tol-
uene and 2 mL sodium methoxide (Fisher Scientific, Pittsburgh PA)
were added to each test tube along with 10 μL of a 10 mg/mL standard
mix (C11:0 and C17:0 TAG) to monitor transesterification efficiency of
the TAG into FAMEs. Samples were heated in an oven for 30 min at
90 °C and vortexed every 10 min. Samples were allowed to cool to
room temperature before 2 mL of 14% boron tri-fluoride in methanol
(Sigma-Aldrich, St. Louis, MO) were added and samples were heated
again for an additional 30 min. Samples were again allowed to cool be-
fore 10 μL of a 10 mg/mL of C23:0 FAMEwere added to assess the com-
pleteness of partitioning FAMEs into the organic phase. Additionally,
0.8 mL of hexane and 0.8 mL of a saturated salt water solution (NaCl
in diH2O) were added. Samples were heated for 10 min to facilitate
FAME partitioning into the organic phase, vortexed for 10 s and
centrifuged at 1200 ×g for 2 min to enhance phase separation. One
mL of the organic phase was removed from the top layer using a glass
syringe and transferred to a 2 mL GC vial for GC–MS analysis.
2.8. Transesterification of extractable lipids from wet biomass
Lipids extracted fromwet biomass (described in Section 2.6.1) were
transesterified for FAME analysis. Briefly, 0.5 mL of the extract was
removed from the GC vial and transferred to a screw-cap glass tube.
One half mL of a 5% HCl in methanol mixture was added to each test
tube along with 10 μL of a 10 mg/mL standard mix (C11:0 and C17:0
TAG) to assess transesterification efficiency. Samples were capped
with a Teflon lined screw cap, heated for 1 h at 90 °C and vortexed
every 10 min. Samples were allowed to cool to room temperature
before 0.5 mL of a 15% salt water solution (NaCl in diH2O) was added
along with 10 μL of 10 mg/mL C23:0 FAME to assess completeness of
FAME partitioning into the organic phase. Samples were heated for an
additional 10 min to help partition FAMEs into the organic phase,
vortexed for 10 s and centrifuged at 1200 ×g for 2 min to enhance
phase separation. One mL of the organic phase was removed from the
bottom organic layer using a glass syringe and transferred to a 2 mL
GC vial for GC–MS analysis.2.9. Lipid analysis
2.9.1. Nile Red
Cellular TAG accumulation was monitored throughout the experi-
ments using the Nile Red (9-diethylamino-5H-benzo(α)phenoxazine-
5-one) (Sigma-Aldrich, St. Louis, MO) fluorescence method (Cooksey
et al., 1987), which has become a generally accepted screening meth-
od for analyzing TAG in algal cultures both in academia and industry
(e.g. Chen et al., 2009; Cooksey et al., 1987; da Silva et al., 2009; Elsey
et al., 2007). Furthermore, Nile Red fluorescence has been correlated
to TAG content using gas chromatography (GC) analysis on extracted
lipid from C. reinhardtii, r2 = 0.998 (Gardner et al., 2013). Briefly,
1 mL aliquots were removed from cultures and assayed directly with
Nile Red (4 μL from 250 μL/mL in acetone) or by diluting 1:5 with
diH2O or salt water, for freshwater or marine cultures respectively,
before staining with Nile Red (20 μL from 250 μL/mL in acetone). To
maintain linearity of the Nile Red assay, dilution was required when
population counts exceeded 1 × 107 cells/mL. Total Nile Red fluores-
cence was quantified on a microplate reader (Bio-Tek, USA) utilizing a
monochromator set to 480/580 nm excitation/emission wavelengths.
A baseline sensitivity setting of 50 was experimentally determined to
maximize the signal-to-noise ratio, while accommodating fluorescent
level changes over 10,000 units. To minimize fluorescence spillover,
black walled 96 well plates were loaded with 200 μL of sample.
Unstained samples were used for background medium and cellular
autofluorescence correction.
2.9.2. GC–FID
GC–FID (Agilent 6890N, Santa Clara, CA) analysis was conducted
using 1-μL splitless injections onto a 15 m (fused silica) RTX biodiesel
column (Restek, Bellefonte, PA). The initial column temperature was
held at 100 °C for 1 min, before being increased to 370 °C at a rate
of 10 °C min−1. The injector temperature was held constant at
320 °C. Helium was used as the carrier gas and column flow was
held at 1.3 mL min−1 for 22 min, increased to 1.5 mL min−1, held
for 2 min, increased to 1.7 mL min−1 and held for 12 min. All flow
rate increases were set to 0.2 mL min−2. Calibration curves were
constructed for each of the following standards: C10:0, C12:0,
C14:0, C16:0, C18:0, C20:0 FFA; C12:0, C14:0, C16:0, C18:0 MAG;
C12:0, C14:0, C16:0, C18:0 DAG; and C11:0, C12:0, C14:0, C16:0,
C17:0, C18:0, C20:0, C22:0 TAG (Sigma-Aldrich, St. Louis, MO) for
quantification (r2 N 0.99). This GC method allows for an estimate of
the amounts of FFA, MAG, DAG and TAG in a single analysis (Fig. 1a).
2.9.3. GC–MS
GC–MS analysis was performed according to a previously published
protocol (Bigelow et al., 2011). Briefly, 1 μL splitless injections were
performed via an autosampler into a GC–MS (Agilent 6890N GC and
Agilent 5973NetworkedMS) equippedwith a 30 m × 0.25 mmAgilent
HP-5MS column (0.25 μm film thickness). The injector temperature
was 250 °C and the detector temperature was 280 °C. The initial col-
umn temperature was 80 °C and was increased to 110 °C at a rate of
8.0 °C min−1, immediately followed by a ramp at 14.0 °C min−1 to a
final temperature of 310 °Cwhichwas held for 3 min before run termi-
nation. Heliumwas used as the carrier gas and column flowwas held at
0.5 mL min−1. Quantities of FAMEs were determined by quantifying
each response peak with the nearest eluting calibration standard
based on retention time, using MSD ChemStation software (Ver.
D.02.00.275), with additional analyses performed using a custom pro-
gram described in Section 2.9.4. A 28-component fatty acid methyl
ester standard prepared in methylene chloride (“NLEA FAME mix”;
Restek, Bellefonte, PA) was used for GC–MS retention time identifica-
tion and response curve generation (r2 N 0.99). It should be noted
that C18:1, C18:2 and C18:3 co-elute on the columnused and have sim-
ilar fragmentation patterns. They were therefore quantitated together
as C18:1–3.
2.9.4. Lipid quantification and analysis
Lipid quantification was performed using a custom program
developed specifically for this purpose. Chromatogram data from
the GC–FID and GC–MS were exported from the instrument software
(Chemstation Ver. B.02.01-SR1) as a Microsoft Excel spreadsheet. The
spreadsheet was then imported into a web-based software application
written in Microsoft's ASP.NET framework using C# and MVC as the
coding language and paradigm, respectively. Data were stored with
unique identifiers in a Microsoft SQL database. Six point calibration
Fig. 1. GC–FID chromatograms: (a) Standard mix of 22 analytical grade lipid standards
(0.1 mg/mL); from left to right — C10:0, C12:0, C14:0, C16:0, C18:0 FFA, C12:0 MAG,
C20:0 FFA, C14:0, C16:0, C18:0 MAG, C12:0, C14:0 DAG, C11:0 TAG, C16:0 DAG,
C12:0 TAG, C18:0 DAG, C14:0, C16:0, C17:0, C18:0, C20:0, C22:0 TAG. (b) Olive oil
(1 mg/mL) was used as a control (black line) against (c) a sample of the same concen-
tration which was microwaved for 10 min (dashed line) to assess the potential for
thermal degradation of TAG. Lipid extracted viamicrowave energy from (d) C. vulgaris,
(e) C. reinhardtii and (f) P. tricornutum. Chromatograms are offset to allow for
alignment with standards.curves were constructed using the LINEST function which is built into
the ASP.NET framework library. Chromatogram peaks were quantified
based on the closest standard, as determined by retention time of the
sample peak and standard peak, respectively. All chromatograms were
manually integrated and inspected prior to export to ensure accuracy
and reliability. Manual calculations were performed periodically using
Excel to verify software results.
2.9.5. Control samples
Olive oil controls were analyzed by GC–FID to verify no thermal
degradation of TAG was occurring when samples were exposed to
microwave energy. Olive oil is predominantly comprised of C16 and
C18 TAG compounds (Kiritsakis et al., 1998). A stock solution of
olive oil dissolved in chloroform (1 mg mL−1) was prepared, and
aliquots (n = 3) were run directly on the GC–FID as a control (Fig. 1b).
To verify thermal degradation was not occurring, 3 mL of the stock solu-
tion were transferred to a Pyrex test tube with Teflon lined screw caps
and an additional 3 mL of diH2Owere added. Samples (n = 3)were ho-
mogenized by vortexing for 10 s, caps were securely fastened, samples
microwaved (Sharp Carousel, Mahwah, NJ) at 1000 W on power level
1 (~100 °C and 2450 MHz) for 1 min and then allowed to cool for
5 min. This process of vortexing for 10 s, microwaving for 1 min and
cooling for 5 min was repeated 10 times, for a total of 10 min exposure
to microwave energy. Samples were then centrifuged at 1200 ×g for
2 min to enhance phase separation. One mL of the organic phase was
removed from thebottomof the test tube using a glass syringe and trans-
ferred to a 2 mLGC vial (Fisher Scientific, Palatine, IL) for GC–FID analysis
(Fig. 1c).
Microorganisms are known to produce a wider range of mono-, di-
and triacylglycerides than higher plants with carbon chain length
varying by more than six carbon atoms and a range of saturation
states (Brown et al., 2009). However, it is uncommon to find a
glycerolipid synthesized by any organism with individual fatty acids
deviating by more than two carbon atoms, albeit saturation states
can differ significantly (Brown et al., 2009). Therefore, the challenge
of separating and quantifying all potentially possible glycerolipids
was addressed by developing calibration ranges based on the resi-
dence time of each of the twenty even-chain length standards as
described in Section 2.9.2 and further comparing these results to
mass spectroscopy analysis of FAMEs derived from the extractable2.9.6. Statistical analysis
A “two one-sided tests” (TOST) procedure (Richter and Richter,
2002) was performed on the control samples described in Section 2.9.5
to determine statistical equivalency between treated and untreated sam-
ples. Equivalence was determined for each response peak based on peak
area using n = 3 samples for each group. The TOST procedure requires
an acceptance parameter “θ” to represent the hypothesized mean differ-
ence boundary. Samplemeans are considered equivalent if |μ1 − μ2| ≤ θ
with a 95% confidence interval. Statistical parameters were set at: θ =
0.5, α = 0.05.
3. Results and discussion
3.1. Chromatograph calibration, quantification and data compilation
The quality of the results obtained using the methods described
in this paper relies heavily on proper calibration, chromatogram
quantification, quality control and quality assurance. Fig. 1 depicts
GC–FID chromatograms for a surrogate mix of calibration standards
(Fig. 1a), two olive oil standards (to check for the potential of ther-
mal degradation during microwave treatment; Fig. 1b, c), and sam-
ples from each of the three organisms used in this study (Fig. 1d, e,
f). The surrogatemix of standards is comprised of twenty two analyt-
ical grade lipid standards; six free fatty acids (C10:0–C20:0), four
monoacylglycerides (C12:0–C18:0), four diacylglycerides (C12:0–
C18:0), and eight triacylglycerides (C11:0–C22:0). All of these stan-
dards are fully saturated and of even chain length, except for the
C11:0 and C17:0 TAG. Six different calibration standard concentra-
tions (0.005, 0.01, 0.05, 0.1, 0.25 and 0.5 mg/mL) were used to create
the calibration curves for each compound listed above. Regression
coefficients for each linear calibration curve were r2 N 0.99. Excellent
peak shape and resolution were achieved for each of the standards in
the mix (Fig. 1a). The algae extract chromatograms exhibit more
noise, presumably due to a range of different lipids (chain length
and saturation) being produced. As an example, consider the TAG
range for C. vulgaris (Fig. 1d). The increase in baseline response
during retention times of approximately 25–30 min is likely the re-
sult of the presence of a number of TAG with different combinations
of fatty acids of different chain lengths per molecule of TAG. In com-
parison, the chromatogram of olive oil has a mostly flat baseline and
exhibits only three groups of peaks in the TAG region. Olive oil consists
predominantly of TAG with fatty acid chains consisting of 55–83% oleic
acid (C18:1), 3.5–21% linoleic acid (C18:2) and 7.5–20% palmitic acid
(C16:0) (Kiritsakis et al., 1998). The three groups of peaks in Fig. 1b and
c for the olive oil standards are TAG with various combinations of these
three fatty acids at the sn− 1, sn− 2 and sn− 3 positions of the glycerol
backbone. The peak at 27.15 min (longest retention time (RT)) is a
TAG with oleic acid at each position (sn− 1, sn− 2 and sn− 3). The
left-most TAG peak (ret. time 25.76) is predominantly palmitic
acid, but the shift in retention time compared to the C16:0 TAG stan-
dard suggests oleic acid or linoleic acid must also be present at one
position.lipids (Section 2.8).
The details are discussed in detail in Section 3.3.
the timecourse of culturing and implement adjustments as necessary.
Furthermore, extensive processing times carry a greater risk of the sam-
ple composition changing between collection and analysis. For example,
it has been shown that TAG can be degraded during dark hours in some
algal cultures (Bigelow et al., 2011; Gardner et al., 2012) making long
processing times undesirable.
Microwave extraction of lipid precursors from live culture required
less than 2 h from time-of-harvest to generation of GC data and was
shown to yield as much, if not more, lipid than the other techniques
tested on these three organisms (Fig. 2). Further, relatively small
for the sample and control are shown in Fig. 1 (b and c). Statistical
equivalence was determined for each response peak as described in3.2. Comparison of various cell disruption and lipid extraction techniques
To test the validity of microwave energy as a suitable and rapid
method for cell disruption and lipid extraction, it was necessary to com-
pare the results of the microwave technique to those from more tradi-
tional methods (Fig. 2). Historically, the Bligh and Dyer (1959)
gravimetric method for quantifying lipid has been considered the stan-The described GC–FID analysis of extractable lipid provides infor-
mation regarding the lipid class and chain length (cf. Fig. 1), however,
it is not capable of chromatographically separating a number of the
acylglycerides based on the degree of fatty acid chain saturation.
This limitation was addressed to a large extent by transesterifying
the lipid extract and comparing the FAME profile to the relative
abundance of the lipid classes, based on chain length and saturation.
Fig. 2. Average and standard deviation of extractable lipid % (w/w) using various cell
disruption techniques on P. tricornutum, C. vulgaris and C. reinhardtii: Microwave
extraction of wet biomass (Wet MW), bead beating (Beads), microwave extraction
ondry biomass (DryMW), heat induced extraction (Oven), sonicationprobe (Sonication),
a modified Bligh and Dyer method and direct in situ transesterification for total biodiesel
potential (Direct trans.) (n = 3).dard for lipid extraction (Gouveia and Oliveira, 2009; Laurens et al.,
2012b; Singh and Kumar, 1992; Teixeira, 2012). However, it has been
shown that the Bligh and Dyer method can produce significantly
lower estimates of lipid content, and this underestimation tends to
increase significantly with increasing lipid content of the sample
(Iverson et al., 2001). More recently, researchers have demonstrated
that cell lysis bymechanical means such as sonication and bead beating
aids in lipid extraction (Lee et al., 1998, 2010; Zheng et al., 2011).
However, these techniques require significant processing time due to
limitations of the instruments and extensive preparation of sample and
materials. For example, biomass must first be frozen and lyophilized,
requiring up to 48 h or more from the time of harvest until processing
can commence, and often only one sample can be processed at a time.
These factors can limit one's ability to acquire lipid profiles throughout
Table 1
Comparison of mean and standard deviation of final culture growth and TAG accumulation, m
Organism Dry weight
(g L−1; DCW)a
Final cell density
(×106 cells mL−1)
P. tricornutum 0.18 ± 0.06 8.65 ± 0.49
C. vulgaris 0.88 ± 0.05 200 ± 10
C. reinhardtii 0.9 ± 0.02 7.55 ± 0.3
a Dry cell weight (DCW) determined gravimetrically with lyophilized biomass.
b Calculated by fluorescence signal/cell density × 10,000 (scaling factor).Section 2.9.6 with 95% confidence.
3.3. Comparison of extractable lipid-derived FAMEs to total biodiesel
potential
Another significant benefit of this method is the ability to deter-
mine which fraction of total biodiesel potential was derived from
extractable lipid precursors (e.g. FFA, MAG, DAG, TAG) as opposed
to residual precursors (e.g. membrane lipids). Additionally, the lipid
class itself can be determined by the carbon chain length of the
extractable lipid-derived FAMEs. This advancement was achieved
due to the relative simplicity of extracting lipids from live cultures
using microwave energy, transesterifying the extract and quantifying
both the extract and transesterified extract by GC–FID and GC–MS,
respectively. This approach results in two chromatograms for each
sample whose comparison allows for an estimate of the lipid class
and carbon chain length of the extractable lipid precursors as well
as the carbon chain length and saturation of the extractable lipid-
derived FAMEs. The comparison of the results of extractable lipid-
derived FAMEs with direct in situ transesterified FAMEs (Griffiths et
al., 2010, which was modified here to allow for the processing of small
quantities of live cultures), makes it possible to assess which fraction
onitored by Nile Red fluorescence, of P. tricornutum, C. vulgaris and C. reinhardtii (n = 3).
Final total Nile Red fluorescence
(×103 units)
Final Nile Red specific fluorescence
(units cell−1)b
9.71 ± 0.27 1.12 ± 0.03
4.06 ± 0.6 0.02 ± 0.003
3.37 ± 0.16 0.45 ± 0.003volumes of culture (usually b50 mL) are necessary for each sample
point, resulting in the ability to potentially collect multiple data points
throughout even lab scale experiments.
Results from these techniques were also compared against results
from direct in situ transesterification of live culture. Exhaustive direct
in situ transesterification converts free and bound fatty acids into
FAMEs (Laurens et al., 2012b), thereby generating larger amounts of
FAMEs than the other techniques due to the additional conversion
of fatty acids from non-extractable cellular sources (i.e. membrane
bound lipids, chlorophyll, etc.).
It is important to assess potential losses or degradation of lipids due
to the extraction technique. There was a concern that high heat gener-
ated during the microwave disruption process may result in thermal
degradation of lipid compounds such as TAG. Hence, samples of olive
oil were subjected to the microwave extraction process and compared
to the untreated olive oil sample. Briefly, 3 mL of a 1 mg/mL (olive oil/
chloroform) mixture was microwaved for 10 min according to the
protocol described in Section 2.9.5. One mL of this mixture was re-
moved and analyzed byGC–FID against a control of the same concentra-
tion which had not been exposed to microwave heat. Chromatograms
these C16 FAMEs derived from extractable lipid potentially originated
as C16 TAG. Additionally, Fig. 3 shows that all unsaturated C18 FAMEs
were derived from extractable lipid. The sum of these unsaturated C18
FAMEs was 3.9 ± 0.35% (w/w) (Table 4) and total C18 TAG was 3.4 ±
0.04% (w/w) (Table 3), indicating that the majority of unsaturated C18
FAMEs originated as C18 TAG. Furthermore, under these conditions
P. tricornutum produced 4.52 ± 0.07% (w/w) eicosapentaenoic acid
(EPA) (Table 4), which is a valuable omega-3 fatty acid marketed for
its suggested beneficial effects on human health (Alonso et al., 1996).
Over half of the total EPA produced was derived from extractable lipid
(Table 4), all of which originated as C20 TAG (Table 3). Of the 1.99 ±
nd total biodiesel potential from direct in situ transesterification of P. tricornutum, C. vulgaris
)a Tri-glyceride (%)a Sum of extracted (%)b Total biodiesel potential (%)c
27.39 ± 0.32 31.51 ± 0.33 51.19 ± 0.75
17.35 ± 0.95 21.56 ± 0.06 32.96 ± 0.93
3.46 ± 0.28 8.53 ± 0.18 14.45 ± 0.95of total biodiesel potential was likely derived from extractable lipid. The
remaining difference between direct in situ transesterified FAMEs and
extractable lipid-derived FAMEs is considered to be the residual
fraction (e.g. membrane lipids). Further, the originating lipid class of
the extractable lipid-derived FAMEs can be determined with relatively
high confidence by comparing the carbon chain length of the molecule
to the extractable lipid precursors quantified by GC–FID. This approach
makes it possible to gain a comprehensive lipid assessment of a
microalgae culture. It should be noted, that while themethods described
here are capable of detecting a multitude of lipid compounds, e.g. cyclo-
propane fatty acids or amide-linked fatty acids (sphingolipids), by
mass-spectroscopy, such compounds were not detected in significant
abundance in any of the cultures. If these compounds are present and
quantifiable in samples, theywould be grouped into the “Other” category
in the reported values. Additionally, two different transesterification
techniques were used to derive total FAMEs versus extractable FAMEs.
The direct in situ transesterification (Section 2.7) was used for total
cellular fatty acid conversion to FAMEs. This method uses both a base
(sodium methoxide) and an acid (boron tri-fluoride in methanol) to
fully transesterify all cellular fatty acid compounds into FAMEs. The
sequential addition of a basic and acidic catalyst has been shown to im-
prove the efficiency of direct transesterification when water is present,
as is the case when using live cultures (Griffiths et al., 2010). The basic
catalyst, in the presence of water, promotes the saponification of
glycerolipids via alkaline hydrolysis, thereby cleaving the ester bonds be-
tween fatty acids and glycerol. The subsequent addition of acid catalyst
increases the rate of esterification of liberated free fatty acids. These com-
bined steps reduce the detrimental effects of water and result in faster
and more efficient conversion of lipids to FAMEs (Griffiths et al., 2010).
Extractable lipid compounds were transesterified using only acid (HCl)
as a catalyst (Section 2.8). This was determined to be sufficient because
there was no significant amount of water present in the extract
containing the extractable lipid. Both techniques were compared using
the precursor lipid extract and no yield differences were found. Since
the acid only method is faster and uses less material, it was determined
to be more suitable.
3.3.1. Phaeodactylum tricornutum
P. tricornutum was cultured as previously described by Gardner et
al. (2012) and harvested at peak TAG accumulation, as monitored by
Nile Red fluorescence (Table 1). Lipids were extracted by the micro-
wave extraction method described in Section 2.6.1. Total FAMEs
were determined as described in Section 2.7, and FAMEs derived
Table 2
Comparison of mean and standard deviation of lipid extracted with microwave energy, a
and C. reinhardtii (n = 3). All values expressed as % (lipid/CDW).
Organism Free fatty acid (%)a Mono-glyceride (%)a Di-glyceride (%
P. tricornutum 1.4 ± 0.2 0.65 ± 0.02 2.08 ± 0.22
C. vulgaris 1.88 ± 0.54 0.06 ± 0.01 2.26 ± 0.36
C. reinhardtii 2.56 ± 0.15 0.07 ± 0.01 2.43 ± 0.03
a From microwave extraction of wet biomass.
b Sum of neutral lipid precursors — free fatty acids, mono, di, tri-glycerides.
c Total FAMEs from direct in situ transesterification.from extractable lipid were determined as described in Section 2.8.
Total FAME was 51.2% (w/w) and the sum of all extractable lipids
was 31.5% (w/w) with TAG contributing the majority at 27.4% (w/
w) or 87% of the extract (Table 2). Fig. 3 shows the complete FAME
profile for P. tricornutum. Results from direct in situ transesterification
indicate that under these growth conditions this organism preferen-
tially synthesized C16:1 and C16:0 lipid compounds. Total C16:1
and C16:0 FAMEs were 24.8% (w/w) and 14.7% (w/w) respectively
(Table 4). The fractions of total C16 FAMEs from extractable lipids were
54.5% for C16:1 and 51.8% for C16:0 (Table 4). The sum of all C16
FAMEs derived from extractable lipid was 21.1 ± 0.3% (w/w) (Table 4)
and total C16 TAG was 21.4 ± 0.8% (w/w) (Table 3), indicating that0.02% (w/w) C14:0 FAMEs produced by this culture, 58% were derived
from extractable lipid, of which 57% originated as C14 TAG and 43%
originated as C14 MAG.
3.3.2. Chlorella vulgaris
Cultures of C. vulgaris were sparged continuously with air
amended with 5% CO2. Once peak TAG accumulation was reached,
as monitored by Nile Red fluorescence (Table 1), the cultures were
harvested for lipid extraction (Section 2.6.1), total FAMEs determina-
tion (Section 2.7) and an estimate of FAMEs derived from extractable
lipids (Section 2.8). Fig. 4 shows the complete FAME profile for
C. vulgaris. Interestingly, this freshwater greenmicroalga preferentially
synthesized unsaturated C18 fatty acids under the culture conditions
employed here, compared to P. tricornutumwhich predominantly syn-
thesized unsaturated C16 fatty acids. Total FAME content for C. vulgaris
was 33% (w/w) and the sum of all extractable lipids was 21.6% (w/w)
with TAG contributing the majority at 17.4% (w/w) or 80.6% of the
total extract (Table 2). Twenty two percent (w/w) of total FAME was
unsaturated C18 fatty acids, of which 66%were derived from extractable
lipid (Table 4). The sum of these unsaturated C18 FAMEs derived
from extractable lipids was 14.7 ± 0.2% (w/w) (Table 4) and total C18Fig. 3. Average and standard deviation of the FAME profile for P. tricornutum comparing
direct in situ transesterification of all fatty acids (Direct) to FAMEs derived from only
extractable lipid precursors (Extractable). The residual fraction is the difference
between direct and extractable transesterification (n = 3).
Table 3
Comparisons of mean and standard deviation of lipid class and carbon chain length percen
(n = 3). All values expressed as % (lipid/CDW).
Organism C12 C14 C1
Free fatty acid (%)a
P. tricornutum N/D 0.25 ± 0.02 1 ±
C. vulgaris 0.11 ± 0.03 0.23 ± 0.04 0.5
C. reinhardtii N/D N/D 1.1
Mono-glyceride (%)a
P. tricornutum N/D 0.56 ± 0.04 0.0
C. vulgaris N/D N/D N/
C. reinhardtii N/D N/D 0.0
Di-glyceride (%)a
P. tricornutum 0.39 ± 0.08 0.02 ± 0.01 1.0
C. vulgaris 0.24 ± 0.03 0.07 ± 0.01 0.4
C. reinhardtii 0.24 ± 0 0.38 ± 0.02 0.4
Tri-glyceride (%)a
P. tricornutum N/D 0.73 ± 0.06 21
C. vulgaris N/D 0.1 ± 0.1 4.2
C. reinhardtii N/D 0.01 ± 0.01 2.0
N/D — not detected.
a From microwave extraction of wet biomass.
Table 4
Comparisons of mean and standard deviation of percent composition of FAMEs derived fro
being reported as the residual fraction of total FAME for P. tricornutum, C. vulgaris and C. re
Organism C14:0 C16:1 C16:0 C18:1–3b C18:0
Direct trans-esterification % lipid content (w/w)
P. tricornutum 1.99 ± 0.02 24.81 ± 0.4 14.66 ± 0.59 3.62 ± 0.32 0.39 ± 0
C. vulgaris 0.04 ± 0 3.07 ± 0.07 6.88 ± 0.17 22.18 ± 0.72 0.67 ± 0
C. reinhardtii 0.04 ± 0 2.01 ± 0.1 3.35 ± 0.22 8.64 ± 0.53 0.33 ± 0
% Extractable lipid fraction (w/w)a
P. tricornutum 1.16 ± 0.04 13.52 ± 0.22 7.59 ± 0.12 3.89 ± 0.52 0.25 ± 0
C. vulgaris N/D 2.57 ± 0.16 4.04 ± 1.08 14.72 ± 0.19 0.65 ± 0
C. reinhardtii 0.03 ± 0 1.99 ± 0.31 1.7 ± 0.14 4.28 ± 0.27 0.03 ± 0
% Residual lipid fraction (w/w)
P. tricornutum 0.83 ± 0.06 11.29 ± 0.62 7.07 ± 0.7 −0.27 ± 0.2 0.14 ± 0
C. vulgaris 0.04 ± 0 0.49 ± 0.05 2.84 ± 0.42 7.46 ± 1.1 0.02 ± 0
C. reinhardtii 0.02 ± 0 0.02 ± 0.71 1.65 ± 0.83 4.36 ± 0.21 0.3 ± 0.0
N/D — not detected.
a From microwave extraction of wet biomass, followed by transesterification of extracted
b C18:1, C18:2, and C18:3 taken together.
c Sum of other compounds detected.
Fig. 4. Average and standard deviation of the FAME profile for C. vulgaris comparing
direct in situ transesterification of all fatty acids (Direct) to FAMEs derived from only
extractable lipid precursors (Extractable). The residual fraction is the difference
between direct and extractable transesterification (n = 3).tages of extractable lipid constituents from P. tricornutum, C. vulgaris and C. reinhardtii
6 C18 C20 C22
0.19 0.13 ± 0 0.01 ± 0.01 N/D
7 ± 0.18 0.92 ± 0.28 0.05 ± 0.02 N/D
3 ± 0.05 1.43 ± 0.11 N/D N/D
4 ± 0.03 0.06 ± 0.01 N/D N/D
D 0.06 ± 0.01 N/D N/D
2 ± 0.01 0.06 ± 0.03 N/D N/D
6 ± 0.04 0.61 ± 0.19 N/D N/D
8 ± 0.09 1.47 ± 0.24 N/D N/D
5 ± 0.01 1.36 ± 0.04 N/D N/D
.38 ± 0.81 3.4 ± 0.04 1.87 ± 0.47 N/D
9 ± 0.5 12.81 ± 0.35 0.15 ± 0.07 N/D
5 ± 0.12 1.4 ± 0.17 N/D N/D
m in situ transesterification, FAMEs derived from extractable lipid, and the differenceTAGwas 12.8 ± 0.35% (w/w) (Table 3). This indicates that themajority
of unsaturated C18 FAMEs were derived from extractable lipid and
originated as C18 TAG, with the remainder originating as C18 DAG
(1.5% w/w) and C18 FFA (1% w/w) (Table 3). Furthermore, 10% (w/w)
of total FAMEs for this culture of C. vulgaris were C16 fatty acid methyl
ester, with 6.6% (w/w) derived from extractable lipid. Table 3 shows
that 65% of the C16 FAMEs derived from extractable lipidwere originally
C16 TAG with the remainder originating as C16 DAG and C16 FFA.
3.3.3. Chlamydomonas reinhardtii
The model Chlorophyte, C. reinhardtii, was cultured as previously
reported by Gardner et al. (2013) until peak TAG accumulation was
achieved as monitored by Nile Red fluorescence (Table 1). The cul-
tures were harvested and lipid was extracted using the microwave
extraction method described in Section 2.6.1. Total FAMEs were
determined as described in Section 2.7, and FAMEs derived from
extractable lipid were determined as described in Section 2.8. Total
FAME content was determined to be 14.5% (w/w) and the sum of all ex-
tractable lipids was 8.5% (w/w) with TAG contributing the majority at
3.5% (w/w) or 41.2% of the extract and DAG accounting for 2.4% (w/w)
or 28.2% of the extract (Table 2). C. reinhardtii is not known as an
organism capable of producing a significant amount of TAG, and
therefore is not typically regarded as a contender for industrial produc-
tion of algal biofuel (Hu et al., 2008). However, it is widely studied and
inhardtii (n = 3). All values expressed as % (lipid/CDW).
C20:5 C20:1 C20:0 C22:6 C24:0 Otherc
.01 4.52 ± 0.07 0.37 ± 0.01 0.12 ± 0 0.34 ± 0.01 0.25 ± 0 0.13 ± 0.02
.02 N/D 0.05 ± 0.03 0.04 ± 0 N/D 0.05 ± 0 0.03 ± 0.02
.03 N/D 0.07 ± 0.04 0.05 ± 0.03 N/D N/D 0.02 ± 0.0
.02 2.45 ± 0.12 0.23 ± 0.01 N/D 0.16 ± 0.02 N/D N/D
.05 N/D N/D N/D N/D N/D N/D
N/D 0.04 ± 0.02 0.03 ± 0.02 N/D N/D N/D
.03 2.07 ± 0.19 0.14 ± 0.01 0.12 ± 0 0.18 ± 0.02 0.25 ± 0 0.13 ± 0.02
.02 N/D 0.05 ± 0.03 0.04 ± 0 N/D 0.05 ± 0 0.03 ± 0.02
3 N/D 0.04 ± 0.06 0.01 ± 0.01 N/D N/D 0.02 ± 0.0
lipid.
one of the firstmicroalgae to have its genome fully sequenced. Thus, it is
still a reasonable candidate for future research regarding lipid profile
and metabolite analysis. Fig. 5 shows the complete FAME profile for
C. reinhardtii.
Similar to C. vulgaris, C. reinhardtii predominantly synthesized
unsaturated C18 lipid compounds. Total unsaturated C18 FAMEs
were 8.6% (w/w), of which ~50% were derived from extractable
lipid. Unlike C. vulgaris, in this culture of C. reinhardtii, not all of the
C18 FAMEs derived from extractable lipid came from C18 TAG. Instead,
~33% were originally C18 FFA, ~33% C18 DAG and ~33% C18 TAG
(Table 3). All unsaturated C16 FAME compounds were derived from
extractable lipid. However, the original source of these compounds
is ambiguous. Total unsaturated C16 FAMEs derived from extractable
lipid were 1.99 ± 0.31% (w/w), total C16 FFA were 1.0 ± 0.19%
(w/w), total C16 DAG were 0.45 ± 0.01% (w/w) and total C16 TAG
were 2.05 ± 0.12% (w/w). Unambiguously discerning which fraction of
these extractable lipid precursors was responsible for the unsaturated
C16 FAMEs is not possible with this method and will require additional
method development.
Fig. 5. Average and standard deviation of the FAME profile for C. reinhardtii comparing
direct in situ transesterification of all fatty acids (Direct) to FAMEs derived from only
extractable lipid precursors (Extractable). The residual fraction is the difference
between direct and extractable transesterification (n = 3).4. Conclusion
We describe a new rapid method for the efficient extraction of
lipids from live cultures of microalgae for the purpose of quantifying
the lipid content and characterizing the lipid carbon chain length
and saturation. Additionally, we developed methods to determine
the fraction of total biodiesel potential (as FAME) derived either
from extractable lipid or from the residual fraction. Furthermore,
the method can frequently determine from which lipid class (FFA,
MAG, DAG, TAG) a particular FAME was derived. Since properties of
biodiesel depend heavily on the length and degree of saturation of
the FAME, the methods described here can assist in ‘fine-tuning’ the
final product, be it biodiesel or a higher value product, through the
choice of certain algae or growth conditions.
Specifically, here we demonstrate the usefulness of this method
by demonstrating differences in lipid profiles for three frequently
studied microalgae. It is demonstrated that the marine diatom
P. tricornutum preferentially produced unsaturated C16 lipid com-
pounds, whereas the two freshwater green microalgae, C. vulgaris
and C. reinhardtii, predominantly synthesized unsaturated C18 com-
pounds. From an industrial standpoint, it will be beneficial to choose
the appropriate algae and culture conditions to produce the largest
possible amount of biodiesel with the appropriate FAME profile orto screen for algal products with higher value than biodiesel. For in-
stance P. tricornutum was shown to produce an omega-3 fatty acid,
specifically eicosapentaenoic acid (C20:5), which has been suggested
to benefit human health. This method has determined that these
compounds were primarily derived from triacylglyceride storage
molecules.
In order to apply the methods described here to other algae, plants
or different culturing conditions, verification of extraction and
transesterification efficacy will have to be conducted. Such checks
are fairly quick and are described in detail for the algae and culturing
conditions employed here.
Financial disclosure
This material is based upon work supported by the National
Science Foundation (NSF) under CHE-1230632. A portion of this re-
search was supported by the U.S. Department of Energy (DOE) Office
of Energy Efficiency and Renewable Energy (EERE) Biomass Program
under Contract Nos. DE-EE0003136 and DE-EE0005993. Support for
EL and RDG was also provided by the NSF IGERT Program in
Geobiological Systems (DGE 0654336). Instrumental support was
provided through the Center for Biofilm Engineering (CBE) at Montana
State University (MSU) as well as by the Environmental and Biofilm
Mass Spectrometry Facility (EBMSF) funded through DURIP Contract
Number: W911NF0510255 and the MSU Thermal Biology Institute
from the NASA Exobiology Program Project NAG5-8807.
References
Alonso, D.L., Segura, C.I., Grima, E.M., 1996. First insights into improvement of
eicosapentanoic acid content in Phaeodactylum tricornutum (Bacillariophyceae)
by induced mutagenesis. J. Phycol. 32, 339–345.
Bigelow, N.W., Hardin, W.R., Barker, J.P., Ryken, S. a, Macrae, A.C., Cattolico, R.A., 2011. A
comprehensive GC–MS sub-microscale assay for fatty acids and its applications.
J. Am. Oil Chem. Soc. 88, 1329–1338.
Bligh, E.G., Dyer, W.J., 1959. A rapid method of total lipid extraction and purification.
Can. J. Biochem. Physiol. 37, 911–917.
Brown, A.P., Slabas, A.R., Rafferty, J.B., 2009. Fatty acid biosynthesis in plants — metabolic
pathways, structure and organization. In: Govindjee, Wada, H., Murata, N. (Eds.),
Lipids in Photosynthesis: Essential and Regulatory Functions. Advances in Photosyn-
thesis and Respiration, pp. 11–34.
Chen, W., Zhang, C., Song, L., Sommerfeld, M., Hu, Q., 2009. A high throughput Nile red
method for quantitative measurement of neutral lipids in microalgae. J. Microbiol.
Methods 77, 41–47.
Chisti, Y., 2007. Biodiesel from microalgae. Biotechnol. Adv. 25, 294–306.
Cooksey, K.E., Guckert, J.B., Williams, S.A., Callis, P.R., 1987. Fluorometric determination
of the neutral lipid content of microalgal cells using Nile Red. J. Microbiol. Methods
6, 333–345.
Da Silva, T.L., Reis, A., Medeiros, R., Oliveira, A.C., Gouveia, L., 2009. Oil production towards
biofuel from autotrophic microalgae semicontinuous cultivations monitorized by
flow cytometry. Appl. Biochem. Biotechnol. 159, 568–578.
Demirbas, A., 2007. Importance of biodiesel as transportation fuel. Energy Policy 35,
4661–4670.
Dismukes, G.C., Carrieri, D., Bennette, N., Ananyev, G.M., Posewitz, M.C., 2008. Aquatic
phototrophs: efficient alternatives to land-based crops for biofuels. Curr. Opin.
Biotechnol. 19, 235–240.
EIA, 2012. How Dependent Are We on Foreign Oil? [WWW Document]. U.S. Energy
Information Administration. (URL http://www.eia.gov/energy_in_brief/foreign_oil_
dependence.cfm).
Elsey, D., Jameson, D., Raleigh, B., Cooney, M.J., 2007. Fluorescent measurement of
microalgal neutral lipids. J. Microbiol. Methods 68, 639–642.
Eustance, E., Gardner, R.D., Moll, K., Menicucci, J., Gerlach, R., Peyton, B.M., 2013.
Growth, nitrogen utilization and biodiesel potential for two chlorophytes grown
on ammonium or nitrate. J. Appl. Phycol. http://dx.doi.org/10.1007/s10811-013-
0008-5 (in press).
Ferrell, J., Sarisky-Reed, V., 2010. National Algal Biofuels Technology Roadmap. U.S.
Department of Energy's Office of Fuels Development.
Gardner, R., Peters, P., Peyton, B., Cooksey, K.E., 2011. Medium pH and nitrate concentra-
tion effects on accumulation of triacylglycerol in two members of the chlorophyta.
J. Appl. Phycol. 23, 1005–1016.
Gardner, R.D., Cooksey, K.E., Mus, F., Macur, R., Moll, K., Eustance, E., Carlson, R.P.,
Gerlach, R., Fields, M.W., Peyton, B.M., 2012. Use of sodium bicarbonate to stimu-
late triacylglycerol accumulation in the chlorophyte Scenedesmus sp. and the dia-
tom Phaeodactylum tricornutum. J. Appl. Phycol. 1311–1320.
Gardner, R.D., Lohman, E., Gerlach, R., Cooksey, K.E., Peyton, B.M., 2013. Comparison of
CO(2) and bicarbonate as inorganic carbon sources for triacylglycerol and starch
accumulation in Chlamydomonas reinhardtii. Biotechnol. Bioeng. 110, 87–96.
Gouveia, L., Oliveira, A.C., 2009. Microalgae as a raw material for biofuels production.
J. Ind. Microbiol. Biotechnol. 36, 269–274.
Greenwell, H.C., Laurens, L.M.L., Shields, R.J., Lovitt, R.W., Flynn, K.J., 2010. Placing
microalgae on the biofuels priority list: a review of the technological challenges.
J. R. Soc. Interface 7, 703–726.
Griffiths, M.J., Van Hille, R.P., Harrison, S.T.L., 2010. Selection of direct transesterification as
the preferred method for assay of fatty acid content of microalgae. Lipids 45,
1053–1060.
Groom, M.J., Gray, E.M., Townsend, P. a, 2008. Biofuels and biodiversity: principles for
creating better policies for biofuel production. Conserv. Biol. 22, 602–609.
Guckert, J.B., Cooksey, K.E., 1990. Triglyceride accumulation and fatty acid profile changes
in Chlorella (Chlorophyta) during high pH-induced cell inhibition. J. Phycol. 26, 72–79.
Guckert, J.B., Cooksey, K.E., Jackson, L., 1988. Lipid solvent systems are not equivalent
for analysis of lipid classes in the microeukaryotic green-alga, Chlorella. J. Microbiol.
Methods 8, 139–149.
Harris, E.H., 1989. The Chlamydomonas Sourcebook: A Comprehensive Guide to Biology
and Laboratory Use. Academic Press, San Diego.
Hill, J., Nelson, E., Tilman, D., Polasky, S., Tiffany, D., 2006. Environmental, economic,
and energetic costs and benefits of biodiesel and ethanol biofuels. Proc. Natl.
Acad. Sci. U. S. A. 103, 11206–11210.
Hu, Q., Sommerfeld, M., Jarvis, E., Ghirardi, M., Posewitz, M., Seibert, M., Darzins, A.,
2008. Microalgal triacylglycerols as feedstocks for biofuel production: perspectives
and advances. Plant J. 54, 621–639.
Hunter-Cevera, J.C., Boussiba, S., Cuello, J.L., Duke, C.S., Efroymson, R.A., Golden, S.S.,
Holmgren, J., Johnson, D.L., Jones, M.E., Smith, V.H., Steger, C., Stephanapoulos,
G.N., Walker, L.P., Williams, E., Zimba, P.V., 2012. Sustainable development of
algal biofuels committee on the sustainable development of algal biofuels.
Board on Agriculture and Natural Resources. Board on Energy and Environmental
Systems.
Iverson, S.J., Lang, S.L., Cooper, M.H., 2001. Comparison of the Bligh and Dyer and Folch
methods for total lipid determination in a broad range of marine tissue. Lipids 36,
1283–1287.
alkyl esters. Fuel Process. Technol. 86, 1059–1070.
Laurens, L., Quinn, M., Van Wychen, S., Templeton, D.W., Wolfrum, E.J., 2012a. Accurate
and reliable quantification of total microalgal fuel potential as fatty acid methyl
esters by in situ transesterification. Anal. Bioanal. Chem. 403, 167–178.
Laurens, L., Dempster, T. a, Jones, H.D.T., Wolfrum, E.J., VanWychen, S., McAllister, J.S.P.,
Lee, J.-Y., Yoo, C., Jun, S.-Y., Ahn, C.-Y., Oh, H.-M., 2010. Comparison of several methods for
effective lipid extraction frommicroalgae. Bioresour. Technol. 101, S75–S77 (Suppl.).
Liu, J., Huang, J., Sun, Z., Zhong, Y., Jiang, Y., Chen, F., 2011. Differential lipid and fatty
acid profiles of photoautotrophic and heterotrophic Chlorella zofingiensis: assessment
of algal oils for biodiesel production. Bioresour. Technol. 102, 106–110.
Martino, A. De, Meichenin, A., Shi, J., Pan, K., Bowler, C., 2007. Genetic and phenotypic
characterization of Phaeodactylum tricornutum (Bacillariophyceae) accessions 1.
J. Phycol. 43, 992–1009.
Merchant, S.S., Prochnik, S.E., Vallon, O., Harris, E.H., Karpowicz, S.J., et al., 2007. The
Chlamydomonas genome reveals the evolution of key animal and plant functions.
Science (New York, N.Y.) 318, 245–250.
Nichols, H., Bold, H., 1965. Trichosarcina polymorpha gen. et sp. nov. J. Phycol. 1, 34–38.
Patil, P.D., Reddy, H., Muppaneni, T., Mannarswamy, A., Schuab, T., Holguin, F.O.,
Lammers, P., Nirmalakhandan, N., Cooke, P., Deng, S.G., 2012. Power dissipation
in microwave-enhanced in situ transesterification of algal biomass to biodiesel.
Green Chem. 14, 809–818.
Prabakaran, P., Ravindran, a D., 2011. A comparative study on effective cell disruption
methods for lipid extraction from microalgae. Lett. Appl. Microbiol. 53, 150–154.
Provasoli, L., McLaughlin, J., Droop, M., 1957. The development of artificial media for
marine algae. Arch. Microbiol. 25.
Richter, S.J., Richter, C., 2002. A method for determining equivalence in industrial appli-
cations. Qual. Eng. 14, 375–380.
Sheehan, J., 1998. A Look Back at the U.S. Department of Energy's Aquatic Species
Program: Biodiesel from Algae. U.S. Department of Energy's Office of Fuels
Development.
Singh, Y., Kumar, H.D., 1992. Lipid and hydrocarbon production by Botryococcus spp.
under nitrogen limitation and anaerobiosis. 8, 121–124.
Spiekermann, P., Lerchl, J., Beckmann, C., Kilian, O., Kroth, P.G., Boland, W., Za, U., Heinz,
E., 2003. New insight into Phaeodactylum tricornutum fatty acid metabolism.
Cloning and Functional Characterization of Plastidial and Microsomal Δ12-Fatty
Acid Desaturases 1 [w], 131, pp. 1648–1660.
Stephenson, A.L., Dennis, J.S., Howe, C.J., Scott, S.A., Smith, A.G., 2010. Influence of
nitrogen-limitation regime on the production by Chlorella vulgaris of lipids for bio-
diesel feedstocks. 1, 47–58.
Valenzuela, J., Mazurie, A., Carlson, R.P., Gerlach, R., Cooksey, K.E., Peyton, B.M., Fields,
M.W., 2012. Potential role of multiple carbon fixation pathways during lipid
accumulation in Phaeodactylum tricornutum. Biotechnol. Biofuels 5, 40.
Xue, J., Grift, T.E., Hansen, A.C., 2011. Effect of biodiesel on engine performances and
Rencenberger, M., Parchert, K.J., Gloe, L.M., 2012b. Algal biomass constituent
analysis: method uncertainties and investigation of the underlying measuring
chemistries. Anal. Chem. 84, 1879–1887.
Lee, S.J., Yoon, B., Oh, H., 1998. Rapid method for the determination of lipid from the
green alga Botryococcus braunii. 12, 553–556.emissions. Renewable Sustainable Energy Rev. 15, 1098–1116.
Zheng, H., Yin, J., Gao, Z., Huang, H., Ji, X., Dou, C., 2011. Disruption of Chlorella vulgaris
cells for the release of biodiesel-producing lipids: a comparison of grinding,
ultrasonication, bead milling, enzymatic lysis, and microwaves. Appl. Biochem.
Biotechnol. 164, 1215–1224.Teixeira, R.E., 2012. Energy-efficient extraction of fuel and chemical feedstocks from
algae. Green Chem. 14, 419.Kiritsakis, A.K., Lenart, E.B., Willet, W.C., Hernandez, R.J., 1998. Olive Oil: from the Tree
to the Table, 2nd ed. Food & Nutrition Press, Trumbull, CT.
Knothe, G., 2005. Dependence of biodiesel fuel properties on the structure of fatty acid