2014 Steinhoff etal

2014 Steinhoff etal
Algal Research 5 (2014) 42–51
Contents lists available at ScienceDirect
Algal Research
journal homepage: www.elsevier.com/locate/algal
Cyanobacteria in Scandinavian coastal waters — A potential source for
biofuels and fatty acids?
Franciska S. Steinhoff a,b,c,⁎,1, Maria Karlberg a,1, Martin Graeve c, Angela Wulff a
a
b
c
University of Gothenburg, Department of Biological and Environmental Sciences, P.O. Box 461, SE 40530 Göteborg, Sweden
Norwegian University of Science and Technology (NTNU), Industrial Ecology Programme and Department of Energy and Process Engineering, Sem Sælands vei 7, NO 7491 Trondheim, Norway
Alfred-Wegener Institute, Helmholtz Centre for Polar and Marine Research, Section Ecological Chemistry, Am Handelshafen 12, D 27570 Bremerhaven, Germany
a r t i c l e
i n f o
Article history:
Received 14 March 2013
Received in revised form 7 May 2014
Accepted 11 May 2014
Available online xxxx
Keywords:
Harvest
Industrial application
Nutrient depletion
Fatty acid
Baltic Sea
Pigment
a b s t r a c t
Since land-based biofuel production competes with conventional food production, a water-based biomass and
biofuel production from cyanobacteria offers large potential. This study investigates the application potential
of cyanobacteria for fuel production and by-products by mimicking nutrient depleted environmental conditions.
Three Baltic cyanobacteria strains (Aphanizomenon flos-aquae, Dolichospermum lemmermannii and Nodularia
spumigena) were inoculated in full nutrient levels, as well as phosphorus and nitrogen depleted medium, before
being monitored for 14 days. For screening reasons, multiple parameters such as fatty acids, photosynthetic pigments including phycobilins, biovolume, photosynthetic activity, inorganic nutrients, particulate organic carbon,
nitrogen and phosphorous were investigated every seven days. We observed a strong negative relationship between lipid content, growth and nutrient availability, resulting in high lipid and pigment production in combination with a limited growth rate in nutrient depleted treatments. Our results suggest that cultivation and harvest
of bloom-forming cyanobacteria for fuel and by-product production are feasible in Scandinavia, but strongly depends on the desired compounds and biomass. Each cyanobacteria species originally has a species-specific chemical fingerprint that may be modified by rearing conditions and harvesting period to meet the needs of the
consumer. This leads to important conclusions regarding future culturing conditions and biomass production
of the desired compounds.
© 2014 Elsevier B.V. All rights reserved.
1. Introduction
The interest and the demand of biofuels derived from water-living
organisms skyrocketed during the last decade. Since land-based biofuel
production competes with conventional food production, a water-based
biomass and biofuel production offers a large potential. However, the
idea of using aquatic primary producers, e.g., algae, for production of
various bio-chemicals such as lipids and antimicrobial substances, is
not new. After the end of World War II, several working groups around
the globe studied the “scientific and economic feasibility of the commercial production of algae in mass cultures” [1–4].
1.1. Biofuels
For the production of biodiesel, biomethane, bioethanol and
biohydrogen, many potential biofuel sources have been identified so far
(e.g. corn, switchgrass, sugarcane, wheat). Aquatic primary producers
⁎ Corresponding author at: Norwegian University of Science and Technology (NTNU),
Industrial Ecology Programme and Department of Energy and Process Engineering, Sem
Sælands vei 7, NO 7491 Trondheim, Norway.
E-mail address: [email protected] (F.S. Steinhoff).
1
Both authors contributed equally.
http://dx.doi.org/10.1016/j.algal.2014.05.005
2211-9264/© 2014 Elsevier B.V. All rights reserved.
are known to have better solar-to-biomass energy conversion efficiencies
(~2–10%) than current biofuels from land-based plants (~0.2–2% [5]) and
therefore become increasingly more and more attractive as biofuel precursors [6]. Biodiesel production from microalgae via transesterification
is regarded as one of the most efficient ways of generating biofuels and
is to present knowledge the “only current renewable source of oil [lipids]
that could meet the global demand for transport fuels” [7,8].
Although many lobbying groups have been established to govern
green energy, such as the European Algae Biomass Association (EABA)
or the Carbon Trust in the UK, the total energy content in biodiesel
and bioethanol is still less than 1% of the world's energy consumption
[9]. Consequently, the perseverative questions remain: Are these
biofuels suitable for mass production? Can we grow, harvest and extract
the required products in an appropriate and efficient way, considering
both economic and sustainable factors? What are the impacts on the
ecosystems now and in the future?
Cyanobacteria, sometimes called blue-green algae, have the advantage of carrying characteristics from both algae and bacteria. Their ability to perform photosynthesis is based on their association with algae,
while the fixation of atmospheric nitrogen by several cyanobacteria species indicates their bacterial roots. Filamentous cyanobacteria are
known to form massive blooms in the Baltic Proper during summer,
resulting in greenish carpets of biomass in the upper water layer. The
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
43
Table 1
Nutrient treatments [μM] of the experiment for D. lemmermannii, A. flos-aquae and N. spumigena for phosphorus depleted f/2 medium (−P), nitrogen depleted f/2 medium (−N) and full
nutrient treatment (f/2 medium).
Species
Nutrients
Treatment
D.lemmermannii
A. flos-aquae
N. spumigena
Controla
−P
−N
f/2
Controla
−P
−N
f/2
Controla
−P
−N
f/2
P
N
nitrite + nitrate
Si
Nitrite
Mean
SD
Mean
SD
Mean
SD
Mean
SD
b2.00
b2.00
44.9
44.8
3.77
2.4
45.2
47.7
b2.00
b2.00
38.9
38.8
–
–
0.4
0.5
2.5
0.2
1.0
1.2
–
–
0.4
0.1
144.9
1153.4
129.2
1123.6
24.5
1005.8
10.8
1032.3
52.9
949.3
41.1
967.7
6.5
3.8
1.3
9.9
14.8
1.9
1.4
2.0
2.5
3.8
0.5
1.6
26.8
34.9
34.5
32.2
23.0
29.0
26.5
26.3
27.0
25.0
24.4
24.6
0.8
11.0
0.8
3.8
0.2
9.9
0.2
2.3
9.8
5.4
0.2
0.5
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
b2.00
–
–
–
–
–
–
–
–
–
–
–
–
The control shows the nutrient values before addition of artificial media. SD refers to standard deviation.
a
Baltic seawater + respective species.
three dominating species are Aphanizomenon sp., Dolichospermum sp.
and Nodularia spumigena. Regional and global climate change, as well
as human-induced nutrient over-enrichment, may lead to an increase
in growth rates, biomass and oxygen depletion. This could alter food
webs and ecosystem structures [10,11] as well as harm tourism industries in the Baltic Sea [12]. To turn the threat [13] into gain, further research related to the application and harvest of cyanobacteria, as
precursors for fuel production and by-products, is pressing [14].
Since some cyanobacteria species represent the only phototrophs
capable of fixing atmospheric nitrogen, they prosper in low ratios of nitrogen:phosphorus supply. However, nutrient ratios and availabilities
influence cell contents. In order to obtain optimal culture conditions,
maximum biomass, or maximum output of certain lipids or byproducts, nutrient availabilities have to be determined and carefully
considered. In contrast to many other prokaryotes, cyanobacteria have
a direct correlation between growth and secondary metabolite production [15–17]. Various types of chemical compounds and toxins are produced by cyanobacteria; Nagle et al. [18] classified 424 marine
cyanobacterial natural products (Marin Lit database [16]) resulting in
40.2% lipopeptides (amino-acid derived fragment linked to a fatty-acid
derived portion [19]), 9.4% amides, 5.6% with pure amino acid composition, 4.2% fatty acids (FA), 4.2% macrolides and 36.4% others (lactones,
indoles, esters, pyrroles and undefined substances). Biological activities
of the compounds were reported to be anticarcinogenic, cytotoxic, antibiotic, antifungal, and antiviral and some had either other or no activities [16]. Because polyunsaturated Ω-3 fatty acids have proven health
benefits, demand for them is rising. Presently, these compounds are
commonly extracted from natural fish and krill populations, pressing
the global fish stocks. Accordingly, the search and the market for
alternative sources are speeding up [20]. Cyanobacteria are known to
be a source of several fuel types. Hydrogen, for example, can be produced by many strains, ethanol is produced from their carbohydrates,
biogas (methane) via anaerobic digestion of their biomass, photanol,
short-chained alcohols produced by combining phototrophy and
chemotrophy in genetically engineered cyanobacteria [21] and diesel
from their FA and hydrocarbons [22]. The demand for present and
new industrial applications of cyanobacteria has set the frame for this
study.
In this study we investigated three bloom-forming cyanobacteria
strains of the Baltic Sea. Our aim was to study: 1) whether their FA content is suitable for a potential biofuel production; 2) whether nutrient
enrichment and depletion under simulated natural radiation conditions
can change and enrich total FA content or FA composition and 3)
whether these cyanobacteria contain promising marine products, such
as lipopeptidic compounds, of importance for future industrial use.
2. Material and methods
For the experiments, cultures of the Kalmar Algal Collection (KAC,
Linnaeus University, Kalmar, Sweden) isolated from the Baltic Proper
were used. The three cyanobacterial strains Aphanizomenon flos-aquae
Ralfs ex Bornet & Flahault (KAC 15), Dolichospermum lemmermannii (P.
Richter) Wacklin, Hoffmann et Komărek (syn: Anabaena lemmermannii;
KAC 16) and N. spumigena Mertens (KAC 12) were inoculated for two
weeks at full nutrient levels (f/2 according to [23]) and salinity 7
to obtain desired biovolumes. The cultures were aerated and grown at
~ 450 μmol photons m2 s− 1 photosynthetically active radiation (PAR
400–700 nm) similar to expected natural radiation intensities in the
upper water layer of the Baltic Proper during summer. PAR was provided by six fluorescent tubes (Osram L 36W/72-965 Biolux, Osram,
München, Germany) and logged continuously during the course of the
experiment.
Before the start of the experiment, the number of cells L−1 and the
biovolume in mm3 L−1 were analyzed and adjusted to obtain comparable biovolumes [24] for all three species. Control samples for all parameters (FA, photosynthetic pigments including phycobilin pigments,
biovolume, photosynthetic activity, inorganic nutrients, particulate organic carbon (POC), particulate organic nitrogen (PON) as well as particulate organic phosphorous (POP)) were taken in five replicates.
Each bottle containing one cyanobacteria species was then divided
into three additional bottles, before adding nutrient solutions
(Table 1), creating three different nutrient treatments: 1. Nitrogen
depletion (− N treatment, f/2 medium without NO−
3 ), 2. Phosphorus
depletion (−P treatment, f/2 medium without PO3−
4 ) and 3. Full nutrient levels (f/2 treatment, f/2 medium). Nutrient samples were also
taken in five replicates for each nutrient treatment and for each species.
After this, 180 mL of the respective cyanobacteria and nutrient solutions
were distributed into 250 mL Nunc-bottles (NUNC, Numbrecht,
Germany). The bottles were subsequently placed in a thermoconstant
room at 17 °C for two weeks. Nutrients were added after seven days
to assure nutrient availabilities comparable to the initial values
(Table 1) throughout the experimental period. Sampling of all parameters was done initially (Day 0) and repeated after 7 and 14 days (Day 7
and Day 14).
2.1. Fatty acid analysis
For each treatment, 20 mL from each of the five replicates was prepared for FA analysis by filtration on precombusted GF/C Filters
(Whatman, Maidstone, UK), covered with dichloromethane/methanol
(2:1 v/v, Merck, Darmstadt, Germany), frozen in liquid nitrogen and
44
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
Table 2
FA profiles, TFA, ratios of monounsaturated to polyunsaturated fatty acids (MUFA:PUFA) and saturated to monounsaturated fatty acids (SAFA:MUFA) [μg mm−3] for D. lemmermannii,
A. flos-aquae and N. spumigena at Day 0, Day 7 and Day 14 for phosphorus depleted f/2 medium (−P), nitrogen depleted f/2 medium (−N) and full nutrient treatment (f/2 medium).
SD refers to standard deviation.
A. flos-aquae
D. lemmermannii
Day
0
7
Treatment
Initial
−P
−N
f/2
−P
−N
f/2
Initial
−P
−N
f/2
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
Mean SD
2.4
1.3
0.4
0.4
12.1
2.5
0.0
0.3
0.4
0.0
8.2
2.2
8.8
1.0
0.1
2.7
0.3
0.3
0.0
0.0
0.1
0.0
0.0
1.2
0.0
44.7
26.5
13.5
4.7
2.9
2.0
1.8
1.4
0.5
0.4
15.7
1.8
0.0
0.0
0.7
0.0
9.9
3.3
8.5
1.1
0.1
5.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
50.3
29.7
13.5
7.1
1.9
2.2
4.2
1.7
1.1
0.6
21.6
4.6
0.0
0.0
0.2
1.9
8.0
7.1
10.9
2.6
0.4
19.2
2.5
0.6
0.3
0.5
0.8
0.4
1.2
0.1
0.4
90
38.2
23.2
31.9
0.7
1.6
14:0
0.3
i-15:0
1.1
a-15:0
0.6
15:0
0.0
16:0
3.1
16:1(n-7)
1.3
16:2(n-4)
0.0
17:0
0.0
16:3(n-4)
0.2
16:4(n-1)
0.1
18:0
1.8
18:1(n-9).cis + trans
0.8
18:1(n-7)
3.5
18:2(n-6) cis
06
18:3(n-6) & 19:0
0.0
18:3(n-3)
0.9
18:4(n-3)
0.1
20:0
0.0
20:4(n-6)
0.0
20:3(n-3)
0.0
20:4(n-3)
0.0
20:5(n-3)
0.0
22:5(n-3)
0.0
24:0
0.2
22:6(n-3)
0.0
Total Σ fatty acids
14.7
SAFA
7.2
MUFA
5.6
PUFA
1.9
MUFA/PUFA
2.9
SAFA/MUFA
1.3
0.1
0.8
0.3
0.0
0.7
0.3
0.0
0.0
0.1
0.0
0.3
0.2
0.6
0.2
0.0
0.3
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.2
0.0
3.6
2.2
0.9
0.7
14
17.4
6.7 12.6
6.6
5.2
37.7
24.3 16.8
10.1
8.5
18.7
12.7
6.6
4.1
3.3
5.7
3.6
2.0
1.2
2.8
109.9
45.9 60.9
30.8 29.3
29.0
17.8 15.2
8.6
7.8
0.0
0.0
0.0
0.0
0.0
0.3
0.6
0.6
0.5
0.0
0.4
0.8
0.0
0.0
1.1
0.0
0.0
0.9
1.3
0.0
43.6
23.2 15.4
6.7 13.3
26.9
12.8 12.6
6.2
7.1
62.9
38.2 28.0
16.0 14.1
27.1
11.8 14.5
5.5
8.3
0.0
0.0
0.0
0.0
0.1
42.6
23.2 66.5
25.6 29.8
1.6
1.2
1.7
2.2
1.6
1.5
1.1
0.3
0.1
1.1
1.2
0.6
1.3
0.5
0.6
0.6
0.6
1.1
0.4
0.8
0.0
0.0
1.9
2.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.0
1.8
0.0
0.0
0.0
0.0
0.0
0.0
427.0 182.2 259.8 122.2 134.7
234.7 115.5 116.3
58.8 63.5
118.8
67.7 55.8
30.8 29.0
73.4
27.7 87.8
33.0 42.2
1.6
0.6
0.7
2.0
2.1
2.2
2.1
2.0
5.5 10.3
2.4
5.8
1.9
1.6
16.3 31.1
5.7 13.1
0.1
4.8
0.0
1.3
1.4
0.1
0.0
0.2
16.6 25.4
7.7
9.8
10.8 34.4
5.6
5.4
0.1
2.0
11.4
8.6
3.0
2.8
2.1
1.2
0.3
1.5
0.7
1.6
0.0
5.4
0.0
1.8
0.0
0.9
0.0
0.2
0.0
2.2
82.1 173.8
45.9 79.1
24.0 57.2
15.2 37.4
1.5
1.4
stored at −80 °C until extraction. For extraction, filters were homogenized by ultrasonication in dichloromethane:methanol (2:1, v/v) following the method described by Folch et al. [25]. An internal standard
was added (23:0 FAME) prior to extraction. For gas–liquid chromatography of FA, methyl esters were prepared from aliquots of the extracted
cyanobacteria by transesterification with 3% sulfuric acid in absolute
methanol for 4 h at 80 °C. After extraction with hexane, fatty acid
methylesters (FAMEs) were analyzed with a gas–liquid chromatograph
(HP 6890, Hewlett-Packard GmbH, Waldbronn, Germany) on a capillary
column (30 m × 0.25 mm I.D.; film thickness: 0.25 μm; liquid phase: DBFFAP, J&W, Cologne, Germany) using temperature programming [26].
FAMEs were identified by comparison with known standard mixtures.
If necessary, identification of FAMEs was confirmed by gas chromatography–mass spectrometry (GC–MS) measurements. Total lipid concentration refers to the sum of total FAME.
0
1.2
6.5
2.9 11.6
1.6
4.5
0.6
1.1
8.4 38.7
4.7 10.4
7.5
0.0
0.6
0.6
0.3
0.4
0.5
0.0
9.4
9.7
3.6
7.2
24.1 23.5
3.9
8.2
4.4
0.0
5.6 35.3
4.6
0.0
0.8
0.0
1.0
0.5
3.1
0.6
10.1
0.0
3.5
0.0
1.3
0.0
0.4
0.0
1.6
0.0
57.1 158.9
22.6 72.7
30.6 41.1
29.3 45.1
0.9
1.8
3.0 11.3
9.5 0.2
4.8 22.4
19.2 0.0
1.9
8.3
6.9 0.0
0.5
2.0
1.6 0.0
18.5 65.7
59.3 2.6
4.4 16.4
12.0 0.1
0.1
0.4
0.9 0.0
0.3
0.6
0.6 0.1
1.0
0.5
1.1 0.3
0.0
0.0
0.0 0.0
4.3 17.9
15.1 1.4
3.4 14.7
12.6 0.4
10.3 32.1
19.7 0.4
3.7 10.0
6.2 0.5
0.0
0.0
0.0 0.0
16.0 43.5
26.3 2.7
0.0
0.1
0.2 0.0
0.0
0.0
0.0 0.0
0.2
0.6
0.6 0.0
0.3
0.6
0.6 0.0
0.0
0.0
0.0 0.0
0.0
0.0
0.0 0.0
0.0
0.0
0.0 0.0
0.0
0.0
0.0 0.4
0.0
0.0
0.0 0.0
66.3 247.2 178.4 9.1
32.7 156.3
85.6 4.8
17.6 79.0
23.6 0.9
19.0 72.1
14.4 3.5
1.1
0.3
2.0
5.3
7
0.2
0.0
0.0
0.0
1.2
0.0
0.0
0.0
0.1
0.0
0.6
0.1
0.1
0.2
0.0
1.3
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
1.7
2.2
0.2
1.6
3.4
1.4
0.5
0.3
6.3
3.1
0.0
0.1
0.9
0.0
3.7
1.9
7.5
0.8
0.1
2.8
0.4
0.2
0.0
0.0
0.1
0.0
0.0
0.8
0.0
30.9
14.4
12.3
4.6
0.8
0.9
0.3
0.4
8.1
0.9
0.0
0.1
0.6
0.0
7.4
1.7
6.8
0.5
0.1
3.6
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.0
0.0
24.5
16.5
9.1
4.3
0.4
0.5
0.4
0.0
1.5
0.7
0.0
0.1
0.3
3.8
2.9
6.1
2.4
1.8
0.7
7.4
4.4
0.7
0.7
0.6
1.5
0.8
2.4
0.3
0.7
16.5
13.6
11.3
19.6
Torrance, USA). To identify peaks, the HPLC system was calibrated
with pigment standards (DHI Water and Environment, Hørsholm,
Denmark). Identification of peaks was confirmed by online recording
of absorbance spectra (400–700 nm) as described in Jeffrey and Wright
[27] and are presented as concentrations (mg L−1) or ratios (w/w) to
chlorophyll a (Chl a). For phycocyanin (PC) analysis, PC was extracted
by the thaw–freeze method according to Sarada et al. [29] and
Siegelmann and Kycia [30] and measured spectrophotometrically (UV2401PC, Shimadzu, Kyoto, Japan) in a quartz cuvette. The PC content
was calculated using the formula PC = (OD615 − 0.474 ∗ OD652) / 5.34
[31] where OD615 is the optical density at 615 nm and OD652 the optical
density at 652 nm, giving mg mL−1. The result was subsequently converted to mg PC per biovolume of cyanobacteria (mg PC mm−3).
2.3. Filament length and growth
2.2. Pigment analysis
For each treatment, 20 mL from each of the five replicates was filtered on GF/F filters (Whatman, Maidstone, UK), frozen in liquid nitrogen and stored for two months at − 80 °C before extraction and
analysis. Pigments on filters, except phycocyanin samples, were extracted according to Wright and Jeffrey [27] and Wulff et al. [28] in 1.5 mL
100% methanol by ultrasonication (Vibra-cell) equipped with a 3 mm
diameter probe operating at 80% in 5 s pulses. Vials with filtered extracts
(0.45 μm) were transferred to a cooled autosampler and analyzed via
HPLC [27] using an absorbance diode-array detector (Spectraphysics
UV6000LP, Santa Clara, USA). The column used was a Kinetex 2.6 μm
C18, 150 × 3.00 mm (Phenomenex, Torrance, USA) equipped with a
guard column (SecurityGuard, Phenomenex C18, 4 mm × 3.0 mm,
For each treatment, 4 mL from each of the five replicates was preserved with acidified Lugol's solution, kept in the dark and analyzed
within six months. Each Lugol sample was gently mixed before being
analyzed in 40× magnification (Axiovert 40CFL, micrometerocular 44
42 32 E-Pl 10 ×/20, Zeiss, Oberkochen, Germany) in a gridded
Sedgewick rafter (1801-G20 Wildlife Supply Company, Yulee, USA).
The length and width for each filament in 100 randomly selected
squares (100 μL) were measured and the total biovolume (mm3 L−1)
per species was calculated by considering each filament a cylinder.
The growth for each species was measured by specific growth rate
(μ day− 1) and calculated according to (ln DB − ln DA) / (tB − tA)
where DA is the biovolume at the first day of the experiments and DB
the biovolume at the end, tA as day A and tB as day B. In addition, the
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
45
Table 2
FA profiles, TFA, ratios of monounsaturated to polyunsaturated fatty acids (MUFA:PUFA) and saturated to monounsaturated fatty acids (SAFA:MUFA) [μg mm−3] for D. lemmermannii,
A. flos-aquae and N. spumigena at Day 0, Day 7 and Day 14 for phosphorus depleted f/2 medium (−P), nitrogen depleted f/2 medium (−N) and full nutrient treatment (f/2 medium).
SD refers to standard deviation.
A. flos-aquae
N. spumigena
14
−P
−N
f/2
0
7
Initial
−P
14
−N
−P
f/2
−N
f/2
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
Mean
SD
4.7
2.4
0.8
1.1
18.9
4.6
0.0
0.0
0.0
0.0
8.2
3.8
13.6
5.2
0.0
9.0
0.6
0.3
0.0
0.3
0.0
0.0
0.0
0.0
0.0
73.7
36.5
22.0
15.1
1.5
1.7
1.5
0.8
0.3
0.6
6.4
2.1
0.0
0.0
0.0
0.0
3.7
2.6
7.3
1.6
0.0
6.0
0.3
0.1
0.0
0.2
0.0
0.0
0.0
0.0
0.0
30.5
12.8
11.9
7.6
8.2
4.7
1.6
1.1
36.3
5.6
0.0
0.0
0.0
0.0
14.1
8.4
17.0
4.0
0.0
17.1
0.4
0.2
0.0
0.0
0.0
0.0
0.0
0.4
0.0
119.4
66.8
31.0
21.6
1.4
2.2
5.2
4.7
1.4
1.2
26.6
6.6
0.0
0.1
0.0
0.0
13.9
7.1
21.2
3.5
0.0
14.2
0.8
0.2
0.0
0.0
0.0
0.0
0.0
1.0
0.0
104.0
53.1
34.5
18.3
3.8
3.5
2.6
0.6
20.0
4.5
0.1
0.3
0.3
0.1
3.2
3.4
12.9
2.3
0.2
14.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
71.9
34.0
20.8
17.2
1.2
1.6
2.0
2.7
2.1
0.4
10.7
3.2
0.2
0.2
0.7
0.2
1.6
1.9
10.0
1.0
0.5
6.6
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.0
0.0
36.4
19.1
14.7
6.8
0.9
0.0
0.0
0.0
30.5
5.8
0.0
0.0
0.0
0.0
5.2
8.0
1.5
2.8
0.9
7.0
9.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
71.9
36.7
15.3
19.9
0.8
2.4
0.5
0.0
0.0
0.0
12.3
2.6
0.0
0.0
0.0
0.0
2.3
3.5
0.6
1.4
0.6
3.7
5.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
30.6
14.8
6.6
10.7
0.1
0.0
0.0
0.0
4.1
1.1
0.0
0.0
0.0
0.0
0.7
0.8
0.4
0.5
0.1
1.3
1.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
10.6
5.0
2.3
3.3
0.7
2.2
0.1
0.0
0.0
0.0
4.0
1.1
0.0
0.0
0.0
0.0
0.6
0.7
0.4
0.5
0.1
1.2
1.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
9.8
4.8
2.2
2.9
0.4
0.0
0.0
0.0
25.5
2.1
0.0
0.1
0.0
0.0
4.3
2.5
2.5
0.8
0.3
3.6
4.1
0.0
0.0
0.1
0.0
0.0
0.1
0.0
0.0
46.3
30.3
7.0
8.9
0.8
4.3
0.5
0.0
0.0
0.0
14.5
1.3
0.0
0.1
0.0
0.0
1.5
1.0
1.3
0.6
0.3
2.3
2.7
0.0
0.0
0.1
0.1
0.0
0.1
0.0
0.0
21.0
16.1
3.4
5.7
0.4
0.0
0.0
0.0
21.2
2.8
0.0
0.1
0.0
0.0
3.4
2.7
4.6
0.9
0.1
4.2
5.0
0.0
0.0
0.1
0.0
0.0
0.0
0.1
0.0
45
25.2
10.1
10.4
1.0
2.5
0.1
0.0
0.0
0.0
9.1
0.7
0.0
0.1
0.0
0.0
1.8
1.2
2.3
0.3
0.2
1.4
2.0
0.0
0.0
0.1
0.1
0.0
0.0
0.2
0.0
15.7
11.0
3.9
4.0
0.1
0.0
0.0
0.0
2.2
0.4
0.0
0.0
0.0
0.0
0.3
0.3
0.4
0.2
0.1
0.6
0.8
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
5
2.6
1.2
1.7
0.7
2.2
0.0
0.0
0.0
0.0
0.4
0.1
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.9
0.4
0.2
0.4
0.0
0.0
0.0
0.0
1.5
0.3
0.0
0.0
0.0
0.0
0.2
0.2
0.3
0.1
0.0
0.5
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
9
1.8
0.8
1.3
0.6
2.2
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.4
0.1
0.1
0.2
0.4
0.2
0.1
0.0
27.2
3.9
0.0
0.2
0.1
0.0
4.0
4.0
5.9
1.5
0.5
6.3
7.9
0.0
0.0
0.2
0.2
0.0
0.0
0.0
0.0
62
32.1
13.8
16.7
0.8
2.3
0.1
0.1
0.1
0.0
8.2
0.7
0.0
0.0
0.1
0.0
1.3
0.6
0.8
0.5
0.3
2.0
2.9
0.0
0.0
0.1
0.1
0.0
0.0
0.1
0.0
11.7
9.3
0.4
5.8
number of cells and heterocysts were counted in 30 random filaments
from each sample.
2.4. Photosynthetic activity
To measure the maximum photosynthetic activity of PSII in the
cyanobacteria, the Fv/Fm yield was measured [32] with a Pulse Amplitude Modulation (PAM) fluorometer (WATER-PAM, Walz GmbH,
Effeltrich, Germany) in all treatments at each sampling day. Fv/Fm is calculated according to (Fm − F0) / Fm = Fv/Fm, where Fm is the maximum
fluorescent yield and F0 the fluorescent yield before the light pulse in a
dark-adapted state. The measurements were obtained in the emitter–
detector unit of the CUVETTE version, with red LED light (650–
730 nm) optimized for cyanobacteria (WATER-ED 8, 487, Walz GmbH,
Effeltrich, Germany) and equipped with a stirring device (WATER-S,
Walz GmbH, Effeltrich, Germany) to homogenize the sample prior to
measurement [33]. For effective quantum yield measurement, 3 mL of
each sample was transferred to the quartz cuvette, kept dark for 3 min
and stirred 10 s before a light pulse of 600 ms was applied.
Waltham, USA). POP samples were analyzed within six months [34] at
Tvärminne Zoological Station, University of Helsinki, Finland. For POC/
PON analysis, filters were ground into fine powder (MM301, Retsch,
Haan, Germany) and analyzed in an elemental analyzer (EA 1108
CHNS-O, Fisons Instruments, Ipswich, UK) applying 2,5-bis-[5-tertbutyl-benzoxazol-2-yl]-thiophen as a standard. Dry weight calculations
were derived from the POC, PON and POP measurements in mol L−1 and
the molar mass for C, N and P.
2.6. Nutrient analysis
For each treatment, 10 mL from each of the five replicates was
0.2 μm filtered (Filtropur, Sarstedt, Numbrecht, Germany) and stored
at −80 °C until analysis of inorganic nitrite, nitrate, phosphate and silicate. The nutrient analysis, based on colorimetric methods [35], was
performed by the Swedish Meteorological and Hydrological Institute
(SMHI, Göteborg, Sweden).
2.5. POC, PON & POP analyses
2.7. Statistics
For each treatment, 20 mL from each of the five replicates was filtered onto precombusted (400 °C for 4 h) 25 mm GF/C filters
(Whatman, Maidstone, UK) for POC/PON and additional 20 mL for
POP analysis. Filters for POP were washed prior to filtering with 0.1 M
HCl and rinsed with Milli-Q. All filters were then frozen at −20 °C and
freeze-dried for 36 h (Heto Power Dry PL3000, Thermo Scientific,
Data was analyzed by one-way ANOVA and Tukey's Post-Hoc test,
using SPSS software (PASW Statistics ver. 20, IBM, Armonk, USA) for
each sampling day, with either species or nutrient treatment as factor.
Homogeneity was tested with Cochran's test and, where needed, data
was transformed according to Underwood [36]. Significant differences
were set as p b 0.0005 after Bonferroni correction [37].
0.01
0.07
0.02
0.04
0.00
0.01
–
0.03
–
0.07
0.38
0.09
0.26
0.04
–
–
–
0.00
–
0.01
0.05
0.01
0.02
0.00
–
–
0.12
0.56
0.14
0.32
0.03
0.00
0.11
0.00
0.02
0.00
0.00
0.03
0.00
0.01
0.00
0.05
0.17
0.01
0.01
0.03
0.00
0.01
0.20
0.02
0.01
0.00
0.00
0.00
0.04
0.00
0.00
0.02
0.01
0.01
0.16
0.03
0.29
0.03
0.00
0.00
0.95
0.11
0.01
0.33
2.13
0.33
–
0.89
0.07
1.42
0.05
0.03
0.00
0.01
0.27
0.03
0.69
0.19
0.005
0.03
2.08
0.14
–
0.39
0.04
0.03
0.17
0.02
0.00
0.05
0.48
0.06
0.67
0.12
0.007
0.12
1.39
0.22
–
0.60
0.04
0.07
0.04
0.01
0.00
0.04
0.13
0.01
0.57
0.09
0.006
0.10
1.12
0.18
–
0.57
0.05
0.07
0.04
0.01
0.00
0.03
0.12
0.01
0.45
0.09
0.02
0.11
1.06
0.16
–
0.09
0.01
0.02
0.04
0.00
0.00
0.01
0.07
0.01
0.23
0.02
0.02
0.05
0.26
0.04
0.03
0.00
0.00
0.00
0.04
0.00
–
0.03
0.00
0.00
0.48
0.07
0.03
0.08
0.68
0.12
–
0.43
0.04
0.04
0.03
0.01
0.00
0.01
0.11
0.01
0.96
0.13
0.08
0.19
1.39
0.28
–
0.76
0.07
0.06
0.21
0.03
0.02
0.05
0.26
0.07
–
0.16
–
0.07
1.83
0.21
0.44
0.05
–
–
0.01
0.00
–
0.05
–
0.08
0.45
0.11
0.29
0.04
–
–
Mean
Mean
SD
Mean
SD
Mean
Mean
Mean
Mean
SD
Mean
Mean
Mean
Mean
SD
Mean
Pigments
Aphanizophyll
β-Carotene
β-Cryptoxanthin
Canthaxanthin
Chl a
Echinenone
4-Keto-myxoxanthophyll
Myxoxanthophyll
Oscillaxanthin
Zeaxanthin
D. lemmermannii
−P
Treatment
Initial
SD
−N
SD
f/2
SD
Initial
A. flos-aquae
−P
SD
−N
SD
f/2
SD
Initial
N. spumigena
−P
SD
f/2
−N
SD
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
Table 3
Pigment concentration [μg mm−3] within D. lemmermannii, A. flos-aquae and N. spumigena for phosphorus depleted f/2 medium (-P), nitrogen depleted f/2 medium (−N) and full nutrient treatment (f/2 medium) after 14 days in comparison to the
initial concentration. SD refers to standard deviation.
46
3. Results and discussion
For screening reasons, we have obtained multiple parameters during
the experiment. Based on the direction of the present publication, we
decided to show information only relevant to potential future applications. More detailed information can be accessed in the supplementary
material provided.
3.1. Total and single fatty acids
Total lipid content rather than profile is often the main important
factor for industrial applications such as biofuel production (biomass
to fuel) [38,39]. At Day 0 of our study, average total fatty acid (TFA) content per biovolume was lowest, but not statistically different (Table A.1)
in A. flos-aquae (9.1 μg mm− 3), almost double in D. lemmermannii
(14.7 μg mm−3) and largest in N. spumigena (71.9 μg mm− 3)
(Table 2). Due to optimum lipid composition and content being seldom
related to optimal industrial biomass production [40], we modeled both
natural as well as assumingly optimal nutrient conditions (f/2) to get indications about industrial harvest and production under natural seasonal conditions. According to our obtained FA profiles (Table 2) and [41],
all three species investigated can be classified as type 4, based on the assumption that cyanobacteria can be classified into four groups in terms
of their FA composition [42]. Group 4 is characterized by the presence of
the FA 18:1, 18:2, 18:3a (α-linolenic acid), 18:3γ (γ-linolenic acid) and
18:4 which relative proportions can be affected by growth conditions.
The FA 16:1 is present in low levels [41]. The most promising of the
three species investigated for biofuel production according to the TFA
content was D. lemmermannii, reaching average maximum TFA values
(Table 2) after 7 days in the P depleted treatment (427.0 μg mm−3).
Maximum TFA of A. flos-aquae was obtained after 14 days within the
N depleted treatment (119.4 μg mm−3). N. spumigena had highest TFA
initially. However, the TFA was statistically significantly higher after
14 days in the f/2 treatment and lowest under N depletion for
N. spumigena (Table A.1). The enhanced FA production under nutrient
depletion could be explained by the need for carbon storage under suboptimal conditions, as observed also by Siron et al. [43] and Malzahn
et al. [44]. This may prove advantageous for industrial FA production.
In contrast to biofuel production, single FA are used in the food and
pharmaceutical industry due to their inter alia antioxidant, antiinflammatory and anti-microbial activities [45]. The FA 14:0, 15:0,
16:0, 17:0, 18:0, 19:0, 20:0 and 24:0 are indicated in the following as
saturated FA (SAFA),16:1(n-7), 18:1(n-7), 18:1(n-9) as monounsaturated FA (MUFA) and the FA 16:2(n-4), 16:3(n-4), 16:4(n-1), 18:2(n6), 18:3(n-3), 18:3(n-6), 18:4(n-3), 20:3(n-3), 20:4(n-3), 20:4(n-6),
20:5(n-3), 22:5(n-3) and 22:6(n-3) as polyunsaturated FA (PUFA). Of
particular interest in commercial production [45,46] and for use in several anti-cancer and anti-heart disease drugs of the pharmaceutical industry are the monounsaturated hexadecanoic acid (16:1(n-7)),
octadecanoic acid (18:1(n-9)), polyunsaturated octadecatrienoic
acid (18:3(n-3)), eicosapentaenoic acid (EPA; 20:5(n-3)) and
docosahexaenoic acid (DHA; 22:6(n-3)), which are present in the
three investigated species (Table 2). Nevertheless, the amounts of essential FA are known to be dependent on species and growing conditions [44,47].
3.1.1. Species differences in FA
Initial values indicated that N. spumigena contained high amounts of
SAFA (51.3%), MUFA (21.6%) and PUFA (27.1%), while the proportion of
MUFA was highest in D. lemmermannii (27.8%) and lowest in A. flosaquae (9.9%). Results are related to the overall TFA contents (Table 2)
and indicate how the ratios of SAFA, MUFA and PUFA may develop
under certain nutrient conditions. Galhano et al. [48] observed SAFA of
61.7%, MUFA of 24.8% and PUFA of 13.5% in Aphanizomenon gracile and
SAFA of 46.3%, MUFA of 17.7% and PUFA of 36.0% in Anabaena cylindrica.
The results for both species are, in terms of SAFA, similar to our species
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
47
might not be strong enough, interference thereof cannot be fully
excluded.
Fig. 1. Biovolumes [mm3 L−1] for D. lemmermannii, A. flos-aquae and N. spumigena at Day 0,
Day 7 and Day 14 for phosphorus depleted f/2 medium (− P), nitrogen depleted f/2
medium (− N) and full nutrient treatment (f/2 medium). Error bars show standard
deviation, n = 5.
before the experiment started, but vary up to four fold within MUFA and
PUFA. Additionally, Li et al. [49] observed 3-hydroxyl FA 12:0 and 15:1
in A. flos-aquae and 15:1 in Anabaena affinis; these FA could not be identified in our analysis but seem to be of less taxonomic value [50]. As earlier studies indicate, e.g., [51], the morphological distinction of Anabaena
(Dolichospermum) and Aphanizomenon is difficult. FA results from the
present study (Table 2) and those obtained in Li et al. [52] suggest
that FA seem to be more sensitive to environmental parameters than
anticipated, leading to consequences in the FA use as characteristic
markers. Consequently, ratios between MUFA, PUFA and SAFA seem to
be highly variable for different cyanobacterial species [48], but appear
rather constant within certain species under comparable environmental
conditions [53].
The amount of 18:1(n-7) in D. lemmermannii and A. flos-aquae
throughout the treatments is far higher compared to N. spumigena.
The latter shows, in contrast, higher values of 18:1(n-9). Due to
18:1(n-7) being more related to bacterial metabolism [54,55], one
could suspect that D. lemmermannii and A. flos-aquae are more bacterial
related species, while N. spumigena is a more autotrophic species,
exhibiting an algal related biosynthesis. Although the FA-signal from
heterotrophic bacteria, commonly associated with the cyanobacteria,
3.1.2. Treatment effect on FA
Nutrient starvation and high radiation regimes for a limited period
are known to increase the lipid yield in outdoor algal cultures [56]. In
our study, ratios of SAFA/MUFA + PUFA (Table 2) in D. lemmermannii
under f/2 and N depletion and in A. flos-aquae under N depletion are
comparable to ratios obtained by Galhano et al. [48].
As previously mentioned, there is a strong negative relationship between lipid content, growth and nutrient availability [57] leading to important conclusions for future culturing conditions and biomass
production of the desired species. The results of the present study and
of De Figueiredo et al. [58] show decreasing growth rates in
Aphanizomenon strains under P depletion and varying responses to N
depletion, which point to the carbon storage hypothesis of Siron et al.
[43] and Malzahn et al. [44]. Recent results [59] highlight the physiological response cascade of cyanobacteria to N starvation occurring at different time scales, ranging from an immediate response to a long term
scaled reaction. This might indicate a connection between results obtained in the present study of A. flos-aquae after 7 and 14 days and transcriptome regulation of cyanobacteria.
3.2. Pigments
It is known that increased lipid content reduces other valuable compounds in the biomass, suggesting that, “the high lipid containing algae
may not necessarily be the most favorable candidate organisms” [9].
Cyanobacterial pigments are characterized by high diversity and richness, which could revolutionize the industrial use of color in the near future [60].
For total carotenoids, at Day 0 D. lemmermannii already had statistically significantly higher total pigment content than both A. flos-aquae
and N. spumigena (Table 3, Table A.1). This observation continued
after Day 7 and Day 14 in both N and P depleted treatments.
Phycobiliproteins in particular are used as fluorescent tracers and
natural dyes in the food and cosmetic industries [61,62]. Regarding
phycobiliprotein content, D. lemmermannii would be an excellent candidate with contents up to 19% of dry weight [63]. Within the carotenoid
subgroup of xanthophyll, the present cyanobacteria (Table 3) comprise
canthaxanthin, β-cryptoxanthin (except N. spumigena), echinenone,
Fig. 2. POC:PON, PON:POP and POC:POP ratios for (a) D. lemmermannii, (b) A. flos-aquae and (c) N. spumigena at Day 0, Day 7 and Day 14 for phosphorus depleted f/2 medium (−P), nitrogen depleted f/2 medium (−N) and full nutrient treatment (f/2 medium). Error bars show standard deviation, n = 5.
48
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
myxoxanthophyll and oscillaxanthin (except N. spumigena). In addition,
N. spumigena contains the species-specific xanthophyll 4-ketomyxoxanthophyll [64]. It is known that carotenoids are especially affected by radiation intensity and quality [28,64,65], nitrogen source
and concentration [28], species and strain type [64] as well as growth
stage [28,66]. In this study, carotenoids in D. lemmermannii were positively affected by P depletion, A. flos-aquae by N depletion and under
full nutrients, while N. spumigena showed no response to the applied
treatments (Table 3). In particular, the zeaxanthin concentration in
D. lemmermannii increased in P depletion at Day 14. Zeaxanthin is a
radiation protective pigment and in the low biovolume concentration
(P depletion) this pigment could protect the cells from excess radiation.
In addition, N. spumigena and D. lemmermannii (former Anabaena) are
reported to contain UV absorbing pigments porphyra 334 and shinorine
[67–70].
Phycocyanin levels in mg mm−3 were not significantly different
between any of the species or treatments, nor between phycocyanin
levels, biovolume or cell concentration (data not shown). We hypothesize
that the method used [29] was not optimal for extraction of phycocyanins
in these species. A new extraction method [71] has, in a later pilot study
(Karlberg et al., unpublished), been proven to better extract phycobilins
in N. spumigena (21.3 SD8.5 μg mm−3 compared to 7.6 SD2.5). The
extraction efficiency of this new method in D. lemmermannii and A. flosaquae is yet to be performed.
3.3. Biovolume and growth
At Day 7 N. spumigena had statistically significantly higher
biovolume than both A. flos-aquae and D. lemmermannii in full f/2
medium and N depletion, but not under P depletion. This trend continued at Day 14 and then also under P depletion (Fig. 1, Table A.1). The
higher biovolume for N. spumigena, compared to A. flos-aquae and
D. lemmermannii in all treatments on both Day 7 and Day 14, may also
be due to N. spumigena high irradiance tolerance [64,72,73]. During
the summer-blooms in the Baltic Sea, N. spumigena is distributed in
the top 5 m of the water column, Anabaena sp. (Dolichospermum sp.)
down to 10 m depth and Aphanizomenon sp. equally distributed between 0 and 20 m throughout the water column [74]. The comparably
high radiation intensities in this study may therefore have favored
N. spumigena over the other two species. However, the Fv/Fm showed
only a possible photoinhibition in A. flos-aquae and D. lemmermannii
after 14 days under P depletion, with yields of 0.08 (SD0.01) and 0.08
(SD0.01) respectively, compared to 0.27 (SD0.02) for N. spumigena
(Table A.2). Potential photoinhibition can occur when the biovolume
is low and all cells are exposed to high irradiances with no chance of
self-shading. The lower Fv/Fm in P depleted treatments could have
been a result of this effect. However, since all three species showed
low Fv/Fm under P depletion, regardless of biovolume, it is more likely
that P depletion has a strong negative effect on Fv/Fm for these nitrogen
fixating species, as phosphorus is also the limiting nutrient during
bloom conditions in the Baltic Sea [75,76]. After 14 days there was no
statistical difference in biovolume between the nutrient treatments for
either A. flos-aquae or N. spumigena (Fig. 1, Table A.1), but the negative
effect of the P depleted treatment, seen by the low Fv/Fm, was significant
for the biovolume of D. lemmermannii.
N. spumigena had continuously positive specific growth rate in all
treatments throughout the experiment (data not shown). N. spumigena
generally has higher specific growth rate than A. flos-aquae ([73], Wulff
et al., unpublished). This may be a competitive advantage, allowing
N. spumigena to reach and maintain high biovolume and cell concentration during the bloom. A. flos-aquae exists as vegetative cells in filaments
in the water column throughout the year [77], meaning it has an advantage when light and temperature reaches optimal levels in early summer
and need not only germinate from akinetes, as D. lemmermannii and
N. spumigena do. Although the specific growth rate for A. flos-aquae was
negative between Day 0 and Day 7 in all treatments, it is positive
between Day 7 and Day 14. This indicates a longer acclimatization time
for A. flos-aquae and it would have been interesting to continue
the experiment (compare e.g., [59,78], Wulff et al., unpublished).
D. lemmermannii had negative specific growth rate in all treatments
throughout the experiment. Since the cyanobacteria strains were reared
at similar radiation conditions and in full nutrient medium, the negative
growth rate results cannot be linked to non-adaptation towards the light
regime, temperature or medium. In contrast, Moreno et al. [63] observed
production rates for D. lemmermannii (former Anabaena) of up to 24
g DW m−2 per day under N depleted outdoor conditions; the highest
reported growth rate under manipulated experimental outdoor
conditions. Our study obtained up to 93.7 mg DW L−1 in N. spumigena,
61.0 mg DW L−1 in A. flos-aquae and 54.3 mg DW L−1 in
D. lemmermannii (Tables A.1 and A.3), which is comparable to the studies
of Reichert et al. [79] with Spirulina cultures.
Overall, in all treatments and on both Day 7 and Day 14, N. spumigena
had statistically significantly higher biovolume and specific growth rate
than both A. flos-aquae and D. lemmermannii, but not TFA per biovolume
(Table A.1). Highest values of TFA per biovolume were observed in
D. lemmermannii after 7 days in the P depleted treatment (Table 2). Increased concentration of FA under nutrient stress is common for many
microalgal genera and species, e.g., [80,81] and references therein. For
D. lemmermannii, the biovolume L−1 after 7 days under P depletion was
very low. Therefore the TFA L−1 was highest after 7 days in the N depleted treatment (~16 mg L−1) compared to A. flos-aquae and N. spumigena
and the other treatments. A. flos-aquae had highest TFA L−1 after 7 days
in f/2 (~6 mg L−1) while N. spumigena reached highest TFA L−1 in f/2
after 14 days (14 mg L−1). Naturally, these values cannot be compared
to genetically modified Synechocystis sp. with a maximum TFA of
197 mg L−1 [82]. Consequently, one has to distinguish between the use
of biomass for fuels and the use of lipids, derived from biological organisms, to obtain the maximum output with a certain species.
3.4. POC, PON & POP to FA ratios with applications for energy yield
We can support the hypothesis that nutrient deficient cyanobacteria
and microalgae are favorable food for higher trophic levels regarding
their FA profiles. This finding is of special interest to applications such
as the recently introduced and seminal multi-trophic aquacultures, a
co-culturing and interaction of species with benefits for both the environment and economy.
Earlier studies have shown (summarized in [83]) that phytoplankton stoichiometry is most variable at low growth rates, with PON:POP
ratios ranging from 5 to 1000 and POC:POP from 60 to 1200. In Fig. 2,
Table 4
Conclusion summary of the present study addressing the questions: which species appear to be the most suitable for harvesting of different compounds, which harvesting period seems
the most promising and which culturing conditions appear to be the most efficient.
Desired parameter/compound
Species with highest values in
desired parameter/compound
Potentially best “harvesting” period
for desired parameter/compound
Nutrient conditions with highest
results of desired parameter/compound
Biovolume
FA/biovolume
FA/L
Pigments/biovolume
Pigments/L
N. spumigena
D. lemmermannii
D. lemmermannii
A. flos-aquae
A. flos-aquae
8–14 days
1–7 days
1–7 days
1–7 days
1–7 days
−N (−P, f/2)
−P
−N
f/2
f/2
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
49
ratios of POC:PON, ranging from 5.2 to 8.5, PON:POP (5.7 to 237.4) and
POC:POP (30.4 to 1454.4) are shown for all three cyanobacteria species
and all treatments over the experimental period. According to Goldman
et al. [84], culturing phytoplankton under N depletion results in PON:
POP ratios of less than 10:1, while under P depletion, ratios of more
than 30:1 occur. In our study, POC, PON and POP differed slightly initially due to species-specific compositions, with D. lemmermannii having
statistically lowest POC and PON values and A. flos-aquae highest
(Table A.1, Table A.4). The wide range of POC, PON and POP might be related to low growth rates with respect to observations in phytoplankton, matching nutrient input ratios at low growth rates [83].
Consumers in higher trophic levels are often constrained with respect to their body C:N:P ratios while the actual primary production reflects the nutrient ratios of the surrounding environment [85]. The body
C:N:P is therefore influenced by the food quality constraints on growth/
reproduction, resource competition, trophic efficiency and nutrient
recycling [86]. Effects of nutrient depletion and/or full nutrient treatments on stoichiometry (Table 2) and FA profiles were observed in
cyanobacteria (present study) and in the cryptophyte Rhodomonas salina [87]. For industrial applications culturing and/or harvesting
cyanobacteria, it is of high relevance to consider these stoichiometry
effects. For example, D. lemmermannii contained the most FA under P
depletion, while the most TFAs were produced under N depletion in
A. flos-aquae. Likewise, R. salina [77] has shown significant differences
between nutrient treatments, with generally higher TFA and higher unsaturated FA contents (e.g., Ω-3 and Ω-6 FA) in nutrient depleted
treatments.
optimized by usage of the remaining biomass cake as fertilizer, or to obtain biogas via aerobic fermentation [94,95].
Our experiment suggests laboratory rearing, as well as harvest of
algal biomass under natural conditions, every few days or on a daily
basis, depending on their growth rates within favorable nutrient and
temperature conditions (compare [96,97]). Since the nutrient depleted
treatment worked best, it would lower the costs of the culture medium
in bioreactors.
3.5. Inorganic nutrients
The authors would thank Monica Appelgren and Mats Räntfors for
their technical help, Jaana Koistinen at Tvärminne Zoological Station,
University of Helsinki for POP analysis, Lucy Tripp for language advice,
the Alfred-Wegener Institute for Polar and Marine Research in Bremerhaven, the Swedish Institute and the University of Gothenburg. This
study is supported by a guest scholarship of the Swedish Institute
(00185/2010) and the University of Gothenburg. The funding source
did not have a role in the data collection, analysis and interpretation
nor in the writing of the present publication.
In Table 1, the initial nutrient treatments for the different experimental scenarios with the three different species are presented. Nutrient conditions remained stable due to the addition of treatmentspecific nutrients, on Day 7, to all experimental bottles. Under natural
bloom conditions, the elemental content of phytoplankton can reflect
the ratio of N:P supply, while the chemico-physical context or the presence or absence of N-fixating organisms can modify this expectation
[88]. Since nutrient depleted treatments mimic reasonably natural conditions before, during and after a summer bloom of the three dominant
N-fixing cyanobacteria species, with low values of both N and P, the results obtained can be used to optimize nutrient conditions within laboratory or seasonal in-situ harvest, dependent on desired parameter or
compound.
3.6. Costs, feasibility and other issues
Although the presented results sound promising, we have to keep in
mind that mass cyanobacteria production is not simply extrapolating
controlled laboratory experiments to large scale outdoor production
systems [89]. There is an urgent need to develop a detailed and feasible
procedure for the production of biochemically active compounds and
secondary metabolites of cyanobacteria [15] in cooperation with the industry. As scientists, we can only give advice and point out knowledge
gaps; the technical challenges are a different kettle of fish. The obtained
results might be of interest to an endless group of buyers, such as the
aquaculture industry, animal farms, biomass production and incineration. In addition, regulatory and commercial factors might inhibit the
large-scale deployment of algae farms for production of biofuel [90],
food additives and pharmaceuticals. Consequently, it may have to be explored in more detail in the future. By-products of algae [91], the algae
meal, and cyanobacteria seem to be promising as feed for animals, but
toxic substances such as nodularin in N. spumigena have to be considered. Two possible solutions were suggested by Vuori et al. [92]; removing nodularin effectively by reverse osmosis or vacuum distillation [93]
and destroying nodularin by ultraviolet and high PAR. Overall biomass
production costs of aquatic microorganisms could additionally be
4. Concluding remarks
From the initial results of this pilot experiment, we can draw the following conclusions.
The choice of species strongly depends on the desired compounds.
Each species originally has a species dependent chemical fingerprint
that may be modified by the culture conditions and harvesting period
to meet the needs of the consumer. The conclusions presented in
Table 4 only indicate that the investigated cyanobacteria could be of interest for biofuel and secondary metabolites, in addition to already
existing genetically modified cyanobacteria as well as other biofuels.
Further research needs to be carried out in terms of technological feasibility on large scales, outdoor bioreactors, natural occurrences, impact
on ecosystems and toxicity issues.
Supplementary data to this article can be found online at http://dx.
doi.org/10.1016/j.algal.2014.05.005.
Acknowledgments
References
[1] H.V. Witsch, Beobachtungen zur Physiologie des Wachstums von Chlorella in
Massenkulturen, Biol. Zent. Bl. 67 (1948) 95–100.
[2] J.S. Burlew, Algal Culture From Laboratory to Pilot Plant, Carnegie Institution of
Washington, Washington DC, 1953.
[3] H. Tamiya, Mass culture of algae, Annu. Rev. Plant Physiol. Plant Mol. Biol. 8 (1957)
309–334.
[4] W.O. Pipes, H.B. Gotaas, Utilization of organic matter by Chlorella grown in sewage,
Appl. Microbiol. 8 (1960) 163–169.
[5] A. Melis, Solar energy conversion efficiencies in photosynthesis: minimizing the
chlorophyll antennae to maximize efficiency, Plant Sci. 177 (2009) 272–280.
[6] G.C. Dismukes, D. Carrieri, N. Bennette, G.M. Ananyev, M.C. Posewitz, Aquatic
phototrophs: efficient alternatives to land-based crops for biofuels, Curr. Opin.
Biotechnol. 19 (2008) 235–240.
[7] Y. Chisti, Response to Reijnders: do biofuels from microalgae beat biofuels from terrestrial plants? Trends Biotechnol. 26 (2008) 351–352.
[8] S. Pabbi, D.W. Dhar, Feasibility of Algal Biomass for Biodiesel Production, Studium
Press LLC, Po Box 722200, Houston, TX 77072 USA, 2011.
[9] P.J.L. Williams, L.M.L. Laurens, Microalgae as biodiesel & biomass feedstocks: review
& analysis of the biochemistry, energetics & economics, Energy Environ. Sci. 3
(2010) 554–590.
[10] M. Scheffer, Ecology of shallow lakes, Population and Community Biology Series,
221998. (i-xx, 1-357).
[11] H.W. Paerl, J. Huisman, Climate change: a catalyst for global expansion of harmful
cyanobacterial blooms, Environ. Microbiol. Rep. 1 (2009) 27–37.
[12] T. Söderqvist, L. Hasselström, The Economic Value of Ecosystem Services Provided
by the Baltic Sea and Skagerrak, Swedish Agency for Marine and Water Management, Stockholm, Sweden, 2008.
[13] S. Suikkanen, M. Laamanen, M. Huttunen, Long-term changes in summer phytoplankton communities of the open northern Baltic Sea, Estuar. Coast. Shelf Sci. 71
(2007) 580–592.
[14] F. Grondahl, Removal of surface blooms of the cyanobacteria Nodularia spumigena: a
pilot project conducted in the Baltic Sea, Ambio 38 (2009) 79–84.
[15] S. Singh, B.N. Kate, U.C. Banerjee, Bioactive compounds from cyanobacteria and
microalgae: an overview, Crit. Rev. Biotechnol. 25 (2005) 73–95.
50
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
[16] A.M. Burja, B. Banaigs, E. Abou-Mansour, J.G. Burgess, P.C. Wright, Marine
cyanobacteria — a prolific source of natural products, Tetrahedron 57 (2001)
9347–9377.
[17] A.M. Burja, M.E. Barrios-Llerena, P.C. Wright, Combinatorial biosynthesis of
cyanobacterial natural products: current status, Biomol. Eng. 20 (2003) 46.
[18] D.G. Nagle, V.J. Paul, M.A. Roberts, Ypaoamide, a new broadly acting feeding deterrent from the marine cyanobacterium Lyngbya majuscula, Tetrahedron Lett. 37
(1996) 6263–6266.
[19] L.T. Tan, T. Okino, W.H. Gerwick, Hermitamides A and B, toxic malyngamide-type
natural products from the marine cyanobacterium Lyngbya majuscula, J. Nat. Prod.
63 (2000) 952–955.
[20] T.C. Adarme-Vega, D.K.Y. Lim, M. Timmins, F. Vernen, Y. Li, P.M. Schenk, Microalgal
biofactories: a promising approach towards sustainable omega-3 fatty acid production, Microb. Cell Fact. 11 (2012).
[21] K.J. Hellingwerf, M.J.T. de Mattos, Alternative routes to biofuels: light-driven biofuel
formation from CO2 and water based on the ‘photanol’ approach, J. Biotechnol. 142
(2009) 87–90.
[22] N. Quintana, F. Van der Kooy, M.D. Van de Rhee, G.P. Voshol, R. Verpoorte, Renewable energy from cyanobacteria: energy production optimization by metabolic pathway engineering, Appl. Microbiol. Biotechnol. 91 (2011) 471–490.
[23] R.R.L. Guillard, Culture of phytoplankton for feeding marine invertebrates, in: W.L.
Smith, M.H. Chanley (Eds.), Culture of Marine Invertebrate Animals, Plenum Press,
New York, 1975, pp. 29–60.
[24] H. Hillebrand, C.D. Durselen, D. Kirschtel, U. Pollingher, T. Zohary, Biovolume calculation for pelagic and benthic microalgae, J. Phycol. 35 (1999) 403–424.
[25] J. Folch, M. Lees, G.H.S. Stanley, A simple method for the isolation and purification of
total lipides from animal tissues, J. Biol. Chem. 226 (1957) 497–509.
[26] G. Kattner, H.S.G. Fricke, Simple gas–liquid-chromatographic method for the simultaneous determination of fatty-acids and alcohols in wax esters of marine organisms, J. Chromatogr. 361 (1986) 263–268.
[27] J.S., S.W. Wright, High-resolution HPLC system for chlorophylls and carotenoids of
marine phytoplankton, in: M.R. Jeffrey SW, S.W. Wright (Eds.), Phytoplankton Pigments in Oceanography, UNESCO, Paris, 1997, pp. 327–341.
[28] A. Wulff, M. Mohlin, K. Sundback, Intraspecific variation in the response of the cyanobacterium Nodularia spumigena to moderate UV-B radiation, Harmful Algae 6
(2007) 388–399.
[29] R. Sarada, M.G. Pillai, G.A. Ravishankar, Phycocyanin from Spirulina sp: influence of
processing of biomass on phycocyanin yield, analysis of efficacy of extraction
methods and stability studies on phycocyanin, Process Biochem. 34 (1999)
795–801.
[30] H.W. Siegelman, J.H. Kycia, Algal biliproteins, in: J.A.A.J.S.C. Hellebust (Ed.), Handbook of Phycological Methods, Cambridge University Press, Cambridge, UK, 1978,
pp. 71–79.
[31] A. Bennett, L. Bogorad, Complementary chromatic adaptation in a filamentous bluegreen-alga, J. Cell Biol. 58 (1973) 419–435.
[32] D. Campbell, V. Hurry, A.K. Clarke, P. Gustafsson, G. Oquist, Chlorophyll fluorescence
analysis of cyanobacterial photosynthesis and acclimation, Microbiol. Mol. Biol. Rev.
62 (1998) (667−+).
[33] J. Cosgrove, M. Borowitzka, Applying Pulse Amplitude Modulation (PAM) fluorometry to microalgae suspensions: stirring potentially impacts fluorescence,
Photosynth. Res. 88 (2006) 343–350.
[34] L. Solorzano, J.H. Sharp, Determination of total dissolved phosphorus and particulate
phosphorus in natural-waters, Limnol. Oceanogr. 25 (1980) 754–757.
[35] K.K., K. Grasshoff, M. Ehrhardt, Methods of Seawater Analysis, Wiley-VCH,
Weinheim, 1999.
[36] A.J. Underwood, Experiments in Ecology: Their Logical Design and Interpretation
Using Analysis of Variance, Cambridge University Press, Cambridge, 1997.
[37] S. Holm, A simple sequentially rejective multiple test procedure, Scand. J. Stat. 6
(1979) 65–70.
[38] M.J. Griffiths, S.T.L. Harrison, Lipid productivity as a key characteristic for choosing
algal species for biodiesel production, J. Appl. Phycol. 21 (2009) 493–507.
[39] D.B. Stengel, S. Connan, Z.A. Popper, Algal chemodiversity and bioactivity: sources of
natural variability and implications for commercial application, Biotechnol. Adv. 29
(2011) 483–501.
[40] I.A. Guschina, J.L. Harwood, Lipids and lipid metabolism in eukaryotic algae, Prog.
Lipid Res. 45 (2006) 160–186.
[41] N. Murata, H. Wada, Z. Gombos, Modes of fatty-acid desaturation in cyanobacteria,
Plant Cell Physiol. 33 (1992) 933–941.
[42] C.N. Kenyon, R.Y. Stanier, R. Rippka, Fatty-acid composition and physiological properties of some filamentous blue-green algae, Arch. Mikrobiol. 83 (1972) (216-&).
[43] R. Siron, G. Giusti, B. Berland, Changes in the fatty-acid composition of
Phaeodactylum tricornutum and Dunaliella tertiolecta during growth and under
phosphorus deficiency, Mar. Ecol. Prog. Ser. 55 (1989) 95–100.
[44] A.M. Malzahn, N. Aberle, C. Clemmesen, M. Boersma, Nutrient limitation of primary
producers affects planktivorous fish condition, Limnol. Oceanogr. 52 (2007)
2062–2071.
[45] M. Plaza, M. Herrero, A. Cifuentes, E. Ibanez, Innovative natural functional ingredients from microalgae, J. Agric. Food Chem. 57 (2009) 7159–7170.
[46] L. Gouveia, A.C. Oliveira, Microalgae as a raw material for biofuels production, J. Ind.
Microbiol. Biotechnol. 36 (2009) 269–274.
[47] K.I. Reitan, J.R. Rainuzzo, G. Oie, Y. Olsen, A review of the nutritional effects of algae
in marine fish larvae, Aquaculture 155 (1997) 207–221.
[48] V. Galhano, D.R. de Figueiredo, A. Alves, A. Correia, M.J. Pereira, J. Gomes-Laranjo,
et al., Morphological, biochemical and molecular characterization of Anabaena,
Aphanizomenon and Nostoc strains (Cyanobacteria, Nostocales) isolated from Portuguese freshwater habitats, Hydrobiologia 663 (2011) 187–203.
[49] R. Li, A. Yokota, J. Sugiyama, M. Watanabe, M. Hiroki, M.M. Watanabe, Chemotaxonomy of planktonic cyanobacteria based on non-polar and 3-hydroxy fatty acid composition, Phycol. Res. 46 (1998) 21–28.
[50] R.H. Li, M.M. Watanabe, Fatty acid composition of planktonic species of Anabaena
(Cyanobacteria) with coiled trichomes exhibited a significant taxonomic value,
Curr. Microbiol. 49 (2004) 376–380.
[51] M. Horecka, J. Komarek, Taxonomic position of 3 planktonic blue-green algae from
the genera Aphanizomenon and Cylindrospermopsis, Preslia (Prague) 51 (1979)
289–312.
[52] R.H. Li, M.M. Watanabe, Fatty acid profiles and their chemotaxonomy in planktonic
species of Anabaena (Cyanobacteria) with straight trichomes, Phytochemistry 57
(2001) 727–731.
[53] T. Rezanka, I. Dor, A. Prell, V.M. Dembitsky, Fatty acid composition of six freshwater
wild cyanobacterial species, Folia Microbiol. 48 (2003) 71–75.
[54] J.R. Sargent, K.J. Whittle, Lipids and Hydrocarbons in the Marine Food Web, Academic Press, London, New York etc., 1981
[55] J. Dalsgaard, M. St John, G. Kattner, D. Muller-Navarra, W. Hagen, Fatty acid trophic
markers in the pelagic marine environment, Adv. Mar. Biol. 46 (46) (2003) 225–340.
[56] L. Rodolfi, G.C. Zittelli, N. Bassi, G. Padovani, N. Biondi, G. Bonini, et al., Microalgae for
oil: strain selection, induction of lipid synthesis and outdoor mass cultivation in a
low-cost photobioreactor, Biotechnol. Bioeng. 102 (2009) 100–112.
[57] P.G. Roessler, Environmental-control of glycerolipid metabolism in microalgae —
commercial implications and future research directions, J. Phycol. 26 (1990)
393–399.
[58] D.R. De Figueiredo, A.M.M. Goncalves, B.B. Castro, F. Goncalves, M.J. Pereira, A.
Correia, Differential inter- and intra-specific responses of Aphanizomenon strains
to nutrient limitation and algal growth inhibition, J. Plankton Res. 33 (2011)
1606–1616.
[59] V. Krasikov, E.A. von Wobeser, H.L. Dekker, J. Huisman, H.C.P. Matthijs, Time-series
resolution of gradual nitrogen starvation and its impact on photosynthesis in the cyanobacterium Synechocystis PCC 6803, Physiol. Plant. 145 (2012) 426–439.
[60] R. Prasanna, A. Sood, A. Suresh, S. Nayak, B.D. Kaushik, Potentials and applications of
algal pigments in biology and industry, Acta Bot. Hung. 49 (2007) 131–156.
[61] A.N. Glazer, L. Stryer, Phycofluor probes, Trends Biochem. Sci. 9 (1984) 423–427.
[62] J. Perdomo, Phycobiliproteins as fluorescence tracers, Biomedia News 1986. pp. 1–
12
[63] J. Moreno, M.A. Vargas, H. Rodríguez, et al., Outdoor cultivation of a nitrogen-fixing
marine cyanobacterium, Anabaena sp. ATCC 33047, Biomol. Eng. 20 (2003)
191–197.
[64] M. Mohlin, A. Wulff, Interaction effects of ambient UV radiation and nutrient limitation on the toxic cyanobacterium Nodularia spumigena, Microb. Ecol. 57 (2009)
675–686.
[65] R. Prasanna, A. Sood, P. Jaiswal, S. Nayak, V. Gupta, V. Chaudhary, et al.,
Rediscovering cyanobacteria as valuable sources of bioactive compounds, Prikl.
Biokhim. Mikrobiol. 46 (2010) 133–147.
[66] J. Hirschberg, D. Chamovitz, Carotenoids in cyanobacteria, in: B. D.A. (Ed.), The Molecular Biology of Cyanobacteria, Kluwer Academic, Dordrecht, 1994, pp. 559–579.
[67] W.M. Bandaranayake, Mycosporines: are they nature's sunscreens? Nat. Prod. Rep.
15 (1998) 159–172.
[68] G.A. Bohm, W. Pfleiderer, P. Boger, S. Scherer, Structure of a novel oligosaccharide–
mycosporine-amino acid ultraviolet a/B sunscreen pigment from the terrestrial cyanobacterium Nostoc commune, J. Biol. Chem. 270 (1995) 8536–8539.
[69] F. Garcia-Pichel, C.E. Wingard, R.W. Castenholz, Evidence regarding the UV sunscreen role of a mycosporine-like compound in the Cyanobacterium gloeocapsa sp,
Appl. Environ. Microbiol. 59 (1993) 170–176.
[70] R.P. Sinha, M. Klisch, E. Walter Helbling, D.-P. Häder, Induction of mycosporine-like
amino acids (MAAs) in cyanobacteria by solar ultraviolet-B radiation, J. Photochem.
Photobiol. B Biol. 60 (2001) 129–135.
[71] P.V. Zimba, An improved phycobilin extraction method, Harmful Algae 17 (2012)
35–39.
[72] J. Lehtimaki, P. Moisander, K. Sivonen, K. Kononen, Growth, nitrogen fixation, and
nodularin production by two Baltic Sea cyanobacteria, Appl. Environ. Microbiol. 63
(1997) 1647–1656.
[73] M. Mohlin, M.Y. Roleda, B. Pattanaik, S.J. Tenne, A. Wulff, Interspecific resource competition—combined effects of radiation and nutrient limitation on two diazotrophic
filamentous cyanobacteria, Microb. Ecol. 63 (2012) 736–750.
[74] S. Hajdu, H. Hoglander, U. Larsson, Phytoplankton vertical distributions and composition in Baltic Sea cyanobacterial blooms, Harmful Algae 6 (2007) 189–205.
[75] E. Graneli, K. Wallstrom, U. Larsson, W. Graneli, R. Elmgren, Nutrient limitation of
primary production in the Baltic Sea area, Ambio 19 (1990) 142–151.
[76] U. Larsson, S. Hajdu, J. Walve, R. Elmgren, Baltic Sea nitrogen fixation estimated from
the summer increase in upper mixed layer total nitrogen, Limnol. Oceanogr. 46
(2001) 811–820.
[77] S. Suikkanen, H. Kaartokallio, S. Hallfors, M. Huttunen, M. Laamanen, Life cycle strategies of bloom-forming, filamentous cyanobacteria in the Baltic Sea, Deep-Sea Res. II
57 (2010) 199–209.
[78] M. Gorl, J. Sauer, T. Baier, K. Forchhammer, Nitrogen-starvation-induced chlorosis in
Synechococcus PCC 7942: adaptation to long-term survival, Microbiology (UK) 144
(1998) 2449–2458.
[79] C.C. Reichert, C.O. Reinehr, J.A.V. Costa, Semicontinuous cultivation of the cyanobacterium Spirulina platensis in a closed photobioreactor, Braz. J. Chem. Eng. 23 (2006)
23–28.
[80] G. Ahlgren, I.B. Gustafsson, M. Boberg, Fatty-acid content and chemical composition
of fresh-water microalgae, J. Phycol. 28 (1992) 37–50.
[81] K.K. Sharma, H. Schuhmann, P.M. Schenk, High lipid induction in microalgae for biodiesel production, Energies 5 (2012) 1532–1553.
F.S. Steinhoff et al. / Algal Research 5 (2014) 42–51
[82] X.Y. Liu, J. Sheng, R. Curtiss, Fatty acid production in genetically modified
cyanobacteria, Proc. Natl. Acad. Sci. U. S. A. 108 (2011) 6899–6904.
[83] C.A. Klausmeier, E. Litchman, S.A. Levin, Phytoplankton growth and stoichiometry
under multiple nutrient limitation, Limnol. Oceanogr. 49 (2004) 1463–1470.
[84] J.C. Goldman, J.J. McCarthy, D.G. Peavey, Growth-rate influence on the chemical composition of phytoplankton in oceanic waters, Nature 279 (1979)
210–215.
[85] J.J. Elser, Stoichiometric Analysis of Pelagic Ecosystems: The Biogeochemistry of
Planktonic Food Webs, Springer-Verlag GmbH and Co. KG, Heidelberger Platz 3,
D-14197, Berlin, Germany, 175 Fifth Avenue, New York, NY, 10010-7858, USA,
2000.
[86] J.J. Elser, D.R. Dobberfuhl, N.A. MacKay, J.H. Schampel, Organism size, life history, and
N:P stoichiometry, Bioscience 46 (1996) 674–684.
[87] A.M. Malzahn, F. Hantzsche, K.L. Schoo, M. Boersma, N. Aberle, Differential effects of
nutrient-limited primary production on primary, secondary or tertiary consumers,
Oecologia 162 (2010) 35–48.
[88] R.W. Sterner, D.O. Hessen, Algal nutrient limitation and the nutrition of aquatic herbivores, in: D.G. Fautin (Ed.), Annual Review of Ecology and Systematics, vol. 25, Annual Reviews Inc. {a}, P.O. Box 10139, 4139 El Camino Way, Palo Alto, California
94306, USA, 1994, pp. 1–29.
51
[89] J.U. Grobbelaar, Microalgal biomass production: challenges and realities,
Photosynth. Res. 106 (2010) 135–144.
[90] P. Hunter, The tide turns towards microalgae. Current research aims to produce traditional biofuels from algae, but their potential to generate sustainable energy might
be even greater and more 'natural', EMBO Rep. 11 (2010) 583–586.
[91] E.W. Becker, Micro-algae as a source of protein, Biotechnol. Adv. 25 (2007) 207–210.
[92] E. Vuori, A. Pelander, K. Himberg, M. Waris, K. Niinivaara, Removal of nodularin from
brackish water with reverse osmosis or vacuum distillation, Water Res. 31 (1997)
2922–2924.
[93] H. Twist, G.A. Codd, Degradation of the cyanobacterial hepatotoxin, nodularin, under
light and dark conditions, FEMS Microbiol. Lett. 151 (1997) 83–88.
[94] Y. Chisti, Biodiesel from microalgae beats bioethanol, Trends Biotechnol. 26 (2008)
126–131.
[95] Y. Chisti, Biodiesel from microalgae, Biotechnol. Adv. 25 (2007) 294–306.
[96] J.R. Benemann, W.J. Oswald, Systems and Economic Analysis of Microalgae Ponds for
Conversion of CO2 to Biomass, 1996.
[97] M. Huntley, D. Redalje, CO2 mitigation and renewable oil from photosynthetic microbes: a new appraisal, Mitig. Adapt. Strateg. Glob. Chang. 12 (2007) 573–608.
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