Many algae species exhibit phenotypes that are of great interest for industrial applications. Systems biology approaches including large-scale metabolic reconstructions can guide and enhance production of biobased commodities such as fuel and human therapeutic proteins. Here we review the existing computational models of metabolism in algal species, as well as the databases and tools that are available to improve the sustainability of algae-to-energy production at industrial scales. As this field has progressed with genome sequencing, computational techniques, novel annotation tools and databases, systems biology will continue to evolve to advance the appeal of algae to a wide array of industries.
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References
1.
MenetrezMY. An overview of algae biofuel production and potential environmental impact. Environ Sci Technol, 2012; 46:7073–7085.
2.
CardinaleBJ, MatulichKL, HooperDUet al.The functional role of producer diversity in ecosystems. Am J Bot, 2011; 98:572–592.
3.
HuQ, SommerfeldM, JarvisEet al.Microalgal triacylglycerols as feedstocks for biofuel production: Perspectives and advances. Plant J, 2008; 54:621–639.
4.
GongY, JiangM. Biodiesel production with microalgae as feedstock: From strains to biodiesel. Biotechnol Lett, 2011; 33:1269–1284.
BrownMR, JeffreySW, VolkmanJK, DunstanGA. Nutritional properties of microalgae for mariculture. Aquaculture, 1997; 151:315–331.
8.
PulzO, GrossW. Valuable products from biotechnology of microalgae. Appl Microbiol Biotechnol, 2004; 65:635–648.
9.
SkjanesK, ReboursC, LindbladP. Potential for green microalgae to produce hydrogen, pharmaceuticals and other high value products in a combined process. Crit Rev Biotechnol, 2013; 33,2:172–215.
10.
DalrympleOK, HalfhideT, UdomIet al.Wastewater use in algae production for generation of renewable resources: A review and preliminary results. Aquat Biosyst, 2013; 9,1:2.
11.
KishimotoM, OkakuraT, NagashimaetHet al.Co2 fixation and oil production using microalgae. J Ferment Bioeng, 1994; 78:479–482.
12.
FranklinSE, MayfieldSP. Recent developments in the production of human therapeutic proteins in eukaryotic algae. Expert Opin Biol Ther, 2005; 5:225–235.
13.
WangB, WangJ, ZhangW, MeldrumDR. Application of synthetic biology in cyanobacteria and algae. Front Microbiol, 2012; 3:344.
14.
GeorgiannaDR, MayfieldSP. Exploiting diversity and synthetic biology for the production of algal biofuels. Nature, 2012; 488:329–335.
15.
DerelleE, FerrazC, RombautsSet al.Genome analysis of the smallest free-living eukaryote Ostreococcus tauri unveils many unique features. Proc Natl Acad Sci, 2006; 103:11647–11652.
16.
MerchantSS, ProchnikSE, VallonOet al.The Chlamydomonas genome reveals the evolution of key animal and plant functions. Science, 2007; 318:245–250.
17.
MolnarI, LopezD, WisecaverJHet al.Bio-crude transcriptomics: Gene discovery and metabolic network reconstruction for the biosynthesis of the terpenome of the hydrocarbon oil-producing green alga, Botryococcus braunii race B (Showa)BMC Genomics, 2012; 13:576.
18.
BoydAR, ChampagneP, McGinnPJet al.Switchable hydrophilicity solvents for lipid extraction from microalgae for biofuel production. Bioresour Technol, 2012; 118:628–632.
19.
KimBH, RamananR, ChoDHet al.Simple, rapid and cost-effective method for high quality nucleic acids extraction from different strains of Botryococcus braunii. PloS One, 2012; 7:e37770.
20.
ZhangF, ChengLH, GaoWLet al.Mechanism of lipid extraction from Botryococcus braunii FACHB 357 in a biphasic bioreactor. J Biotechnol, 2011; 154:281–284.
21.
RaoAR, SaradaR, BaskaranV, RavishankarGA. Antioxidant activity of Botryococcus braunii extract elucidated in vitro models. J Agric Food Chem, 2006; 54:4593–4599.
22.
BuonoS, LangellottiAL, MartelloAet al.Biological activities of dermatological interest by the water extract of the microalga Botryococcus braunii. Arch Dermatol Res, 2012; 304:755–764.
23.
FangJY, ChiuHC, WuJTet al.Fatty acids in Botryococcus braunii accelerate topical delivery of flurbiprofen into and across skin. Int J Pharm, 2004; 276:163–173.
24.
HondaR, BoonnoratJ, ChiemchaisriCet al.Carbon dioxide capture and nutrients removal utilizing treated sewage by concentrated microalgae cultivation in a membrane photobioreactor. Bioresour Technol, 2012; 125:59–64.
25.
GeY, LiuJ, TianG. Growth characteristics of Botryococcus braunii 765 under high CO2 concentration in photobioreactor. Bioresour Technol, 2011; 102:130–134.
26.
SydneyEB, SturmW, de CarvalhoJCet al.Potential carbon dioxide fixation by industrially important microalgae. Bioresour Technol, 2010; 101:5892–5896.
27.
YooC, JunSY, LeeJYet al.Selection of microalgae for lipid production under high levels carbon dioxide. Bioresour Technol, 2010; 101,Suppl 1:S71–S74.
28.
CasadevallE, DifD, LargeauCet al.Studies on batch and continuous cultures of Botryococcus braunii: Hydrocarbon production in relation to physiological state, cell ultrastructure, and phosphate nutrition. Biotechnol Bioeng, 1985; 27:286–295.
29.
Ranga RaoA, RavishankarGA, SaradaR. Cultivation of green alga Botryococcus braunii in raceway, circular ponds under outdoor conditions and its growth, hydrocarbon production. Bioresour Technol, 2012; 123:528–533.
30.
MagotaA, SagaK, OkadaS, AtobeS, ImouK. Effect of thermal pretreatments on hydrocarbon recovery from Botryococcus braunii. Bioresour Technol, 2012; 123:195–198.
31.
SongL, QinJG, SuSet al.Micronutrient requirements for growth and hydrocarbon production in the oil producing green alga Botryococcus braunii (Chlorophyta)PloS One, 2012; 7:e41459.
32.
La RussaM, BogenC, UhmeyerAet al.Functional analysis of three type-2 DGAT homologue genes for triacylglycerol production in the green microalga Chlamydomonas reinhardtii. J Biotechnol, 2012; 162:13–20.
33.
CastruitaM, CaseroD, KarpowiczSJet al.Systems biology approach in Chlamydomonas reveals connections between copper nutrition and multiple metabolic steps. Plant Cell, 2011; 23:1273–1292.
34.
VilaM, GalvanA, FernandezE, LeonR. Ketocarotenoid biosynthesis in transgenic microalgae expressing a foreign beta-C-4-carotene oxygenase gene. Methods Mol Biol, 2012; 892:283–295.
35.
MerchantSS, AllenMD, KropatJet al.Between a rock and a hard place: Trace element nutrition in Chlamydomonas. Biochim Biophys Acta, 2006; 1763:578–594.
36.
YoonSM, KimSY, LiKFet al.Transgenic microalgae expressing Escherichia coli AppA phytase as feed additive to reduce phytate excretion in the manure of young broiler chicks. Appl Microbiol Biotechnol, 2011; 91:553–563.
37.
GenkovT, MeyerM, GriffithsH, SpreitzerRJ. Functional hybrid rubisco enzymes with plant small subunits and algal large subunits: Engineered rbcS cDNA for expression in Chlamydomonas. J Biological Chem, 2010; 285:19833–19841.
38.
TimminsM, Thomas-HallSR, DarlingAet al.Phylogenetic and molecular analysis of hydrogen-producing green algae. J Exp Bot, 2009; 60:1691–1702.
39.
BurgessSJ, TamburicB, ZemichaelFet al.Solar-driven hydrogen production in green algae. Adv Appl Microbiol, 2011; 75:71–110.
40.
PhilippsG, KrawietzD, HemschemeierA, HappeT. A pyruvate formate lyase-deficient Chlamydomonas reinhardtii strain provides evidence for a link between fermentation and hydrogen production in green algae. Plant J, 2011; 66:330–340.
41.
BabaM, SuzukiI, ShiraiwaY. Proteomic analysis of high-CO(2)-inducible extracellular proteins in the unicellular green alga, Chlamydomonas reinhardtii. Plant Cell Physiol, 2011; 52:1302–1314.
42.
KliphuisAM, MartensDE, JanssenM, WijffelsRH. Effect of O(2):CO(2) ratio on the primary metabolism of Chlamydomonas reinhardtii. Biotechnol Bioeng, 2011, 10.1002/bit.23194
43.
KongQX, LiL, MartinezB, ChenP, RuanR. Culture of microalgae Chlamydomonas reinhardtii in wastewater for biomass feedstock production. Appl Biochem Biotechnol, 2010; 160:9–18.
44.
WangY, DuanmuD, SpaldingMH. Carbon dioxide concentrating mechanism in Chlamydomonas reinhardtii: Inorganic carbon transport and CO2 recapture. Photosynth Res, 2011; 109:115–122.
45.
OhnishiN, MukherjeeB, TsujikawaTet al.Expression of a low CO(2)-inducible protein, LCI1, increases inorganic carbon uptake in the green alga Chlamydomonas reinhardtii. Plant Cell, 2010; 22:3105–3117.
46.
RenbergL, JohanssonAI, ShutovaTet al.A metabolomic approach to study major metabolite changes during acclimation to limiting CO2 in Chlamydomonas reinhardtii. Plant Physiol, 2010; 154:187–196.
47.
TranM, VanC, BarreraDJet al.Production of unique immunotoxin cancer therapeutics in algal chloroplasts. Proc Natl Acad Sci, 2013; 110:E15–22.
48.
RasalaBA, MayfieldSP. The microalga Chlamydomonas reinhardtii as a platform for the production of human protein therapeutics. Bioeng Bugs, 2011; 2:50–54.
49.
RasalaBA, MutoM, SullivanJ, MayfieldSP. Improved heterologous protein expression in the chloroplast of Chlamydomonas reinhardtii through promoter and 5′ untranslated region optimization. Plant Biotechnol J, 2011; 9:674–683.
50.
JamesGO, HocartCH, HillierWet al.Temperature modulation of fatty acid profiles for biofuel production in nitrogen deprived Chlamydomonas reinhardtii. Bioresour Technol, 2013; 127:441–447.
51.
CakmakT, AngunP, DemirayYEet al.Differential effects of nitrogen and sulfur deprivation on growth and biodiesel feedstock production of Chlamydomonas reinhardtii. Biotechnol Bioeng, 2012; 109:1947–1957.
52.
LamersPP, JanssenM, De VosRCet al.Carotenoid and fatty acid metabolism in nitrogen-starved Dunaliella salina, a unicellular green microalga. J Biotechnol, 2012; 162:21–27.
53.
KleinegrisDM, JanssenM, BrandenburgWA, WijffelsRH. Continuous production of carotenoids from Dunaliella salina. Enzyme Microb Technol, 2011; 48:253–259.
54.
PrietoA, Pedro CanavateJ, Garcia-GonzalezM. Assessment of carotenoid production by Dunaliella salina in different culture systems and operation regimes. J Biotechnol, 2011; 151:180–185.
55.
YangC, JiaL, SuSet al.Utilization of CO2 and biomass char derived from pyrolysis of Dunaliella salina: The effects of steam and catalyst on CO and H2 gas production. Bioresour Technol, 2012; 110:676–681.
TaylorRL, RandJD, CaldwellGS. Treatment with algae extracts promotes flocculation, and enhances growth and neutral lipid content in Nannochloropsis oculata—a candidate for biofuel production. Mar Biotechnol, 2012; 14:774–781.
58.
DavidiL, KatzA, PickU. Characterization of major lipid droplet proteins from Dunaliella. Planta, 2012; 236:19–33.
59.
PetrieJR, ShresthaP, MansourMPet al.Metabolic engineering of omega-3 long-chain polyunsaturated fatty acids in plants using an acyl-CoA Delta6-desaturase with omega3-preference from the marine microalga Micromonas pusilla. Metab Eng, 2010; 12:233–240.
60.
MisraN, PandaPK, ParidaBK, MishraBK. Phylogenomic study of lipid genes involved in microalgal biofuel production-candidate gene mining and metabolic pathway analyses. Evol Bioinform Online, 2012; 8:545–564.
61.
SayanovaO, Ruiz-LopezN, HaslamRP, NapierJA. The role of Delta6-desaturase acyl-carrier specificity in the efficient synthesis of long-chain polyunsaturated fatty acids in transgenic plants. Plant Biotechnol J, 2012; 10:195–206.
62.
YamanoT, FujitaA, FukuzawaH. Photosynthetic characteristics of a multicellular green alga Volvox carteri in response to external CO2 levels possibly regulated by CCM1/CIA5 ortholog. Photosynthe Res, 2011; 109:151–159.
63.
ValenzuelaJ, MazurieA, CarlsonRPet al.Potential role of multiple carbon fixation pathways during lipid accumulation in Phaeodactylum tricornutum. Biotechnol Biofuels, 2012; 5:40.
64.
RyckeboschE, MuylaertK, EeckhoutMet al.Influence of drying and storage on lipid and carotenoid stability of the microalga Phaeodactylum tricornutum. J Agric Food Chem, 2011; 59:11063–11069.
65.
HempelF, LauJ, KlinglA, MaierUG. Algae as protein factories: Expression of a human antibody and the respective antigen in the diatom Phaeodactylum tricornutum. PloS One, 2011; 6:e28424.
66.
DesboisAP, LeblT, YanL, SmithVJ. Isolation and structural characterisation of two antibacterial free fatty acids from the marine diatom, Phaeodactylum tricornutum. Appl Microbiol Biotechnol, 2008; 81:755–764.
67.
DesboisAP, Mearns-SpraggA, SmithVJ. A fatty acid from the diatom Phaeodactylum tricornutum is antibacterial against diverse bacteria including multi-resistant Staphylococcus aureus (MRSA)Mar Biotechnol, 2099; 11:45–52.
68.
HorstI, ParkerBM, DennisJSet al.Treatment of Phaeodactylum tricornutum cells with papain facilitates lipid extraction. J Biotechnol, 2012; 162:40–49.
69.
WilemanA, OzkanA, BerberogluH. Rheological properties of algae slurries for minimizing harvesting energy requirements in biofuel production. Bioresour Technol, 2012; 104:432–439.
70.
ZendejasFJ, BenkePI, LanePDet al.Characterization of the acylglycerols and resulting biodiesel derived from vegetable oil and microalgae (Thalassiosira pseudonana and Phaeodactylum tricornutum)Biotechnol Bioeng, 2012; 109:1146–1154.
71.
JiangY, YoshidaT, QuiggA. Photosynthetic performance, lipid production and biomass composition in response to nitrogen limitation in marine microalgae. Plant Physiol Biochem, 2012; 54:70–77.
72.
van GinnekenVJ, HelsperJP, de VisserWet al.Polyunsaturated fatty acids in various macroalgal species from North Atlantic and tropical seas. Lipids Health Dis, 2011; 10:104.
73.
SatoN, MoriyamaT. Genomic and biochemical analysis of lipid biosynthesis in the unicellular rhodophyte Cyanidioschyzon merolae: lack of a plastidic desaturation pathway results in the coupled pathway of galactolipid synthesis. Eukaryot Cell, 2007; 6:1006–1017.
74.
GrazianiG, SchiavoS, NicolaiMAet al.Microalgae as human food: Chemical and nutritional characteristics of the thermo-acidophilic microalga Galdieria sulphuraria. Food Funct, 2013; 4:144–152.
75.
EriksenNT. Production of phycocyanin—a pigment with applications in biology, biotechnology, foods and medicine. Appl Microbiol Biotechnol, 2008; 80:1–14.
76.
WeberAP, OesterheltC, GrossWet al.EST-analysis of the thermo-acidophilic red microalga Galdieria sulphuraria reveals potential for lipid A biosynthesis and unveils the pathway of carbon export from rhodoplasts. Plant Mol Biol, 2004; 55:17–32.
77.
KimHU, SohnSB, LeeSY. Metabolic network modeling and simulation for drug targeting and discovery. Biotechnol J, 2012; 7:330–342.
BroC, RegenbergB, ForsterJ, NielsenJ. In silico aided metabolic engineering of Saccharomyces cerevisiae for improved bioethanol production. Metab Eng, 2006; 8:102–111.
80.
XuG, ZouW, ChenXet al.Fumaric acid production in Saccharomyces cerevisiae by in silico aided metabolic engineering. PloS One, 2012; 7:e52086.
81.
MayP, ChristianJO, KempaS, WaltherD. ChlamyCyc: An integrative systems biology database and web-portal for Chlamydomonas reinhardtii. BMC Genomics, 2009; 10:209.
82.
UniProt Consortium. The Universal Protein Resource (UniProt) in 2010. Nucleic Acids Res, 2010; 38:D142–148.
83.
KanehisaM, ArakiM, GotoSet al.KEGG for linking genomes to life and the environment. Nucleic Acids Res, 2008; 36:D480–484.
84.
ChangA, ScheerM, GroteAet al.BRENDA, AMENDA and FRENDA the enzyme information system: New content and tools in 2009. Nucleic Acids Res, 2009; 37:D588–592.
85.
TardifM, AtteiaA, SpechtMet al.PredAlgo: A new subcellular localization prediction tool dedicated to green algae. Mol Bio Evol, 2012; 29:3625–3639.
86.
de Oliveira Dal'MolinCG, NielsenLK. Plant genome-scale metabolic reconstruction and modelling. Curr Opin Biotechnol, 2013; 24:271–277.
87.
de Oliveira Dal'MolinCG, QuekLE, PalfreymanRWet al.AraGEM, a genome-scale reconstruction of the primary metabolic network in Arabidopsis. Plant Physiol, 2010; 152:579–589.
88.
PinneyJW, ShirleyMW, McConkeyGA, WestheadDR. metaSHARK: Software for automated metabolic network prediction from DNA sequence and its application to the genomes of Plasmodium falciparum and Eimeria tenella. Nucleic Acids Res, 2005; 33:1399–1409.
89.
HenryCS, DeJonghM, BestAAet al.High-throughput generation, optimization and analysis of genome-scale metabolic models. Nat Biotechnol, 2010; 28:977–982.
LopezD, CaseroD, CokusSJet al.Algal Functional Annotation Tool: A web-based analysis suite to functionally interpret large gene lists using integrated annotation and expression data. BMC Bioinformatics, 2011; 12:282.
92.
SwarbreckD, WilksC, LameschPet al.The Arabidopsis Information Resource (TAIR): Gene structure and function annotation. Nucleic Acids Res, 2008; 36:D1009–1014.
93.
LameschP, BerardiniTZ, LiDet al.The Arabidopsis Information Resource (TAIR): Improved gene annotation and new tools. Nucleic Acids Res, 2012; 40:D1202–1210.
94.
SchomburgI, ChangA, HofmannOet al.BRENDA: A resource for enzyme data and metabolic information. Trends Biochemic Sci, 2002; 27:54–56.
95.
SchomburgI, ChangA, PlaczekSet al.BRENDA in 2013: Integrated reactions, kinetic data, enzyme function data, improved disease classification: New options and contents in BRENDA. Nucleic Acids Res, 2013; 41:D764–772.
MagraneM, ConsortiumU. UniProt Knowledgebase: A hub of integrated protein data. Database (Oxford), 2011; bar009.
98.
MuellerLA, ZhangP, RheeSY. AraCyc: A biochemical pathway database for Arabidopsis. Plant Physiol, 2003; 132:453–460.
99.
KarpPD, OuzounisCA, Moore-KochlacsCet al.Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res, 2005; 33:6083–6089.
100.
KanehisaM, GotoS. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res, 2000; 28:27–30.
101.
CaspiR, FoersterH, FulcherCAet al.MetaCyc: A multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res, 2006; 34:D511–516.
102.
CaspiR, AltmanT, DaleJMet al.The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res, 2010; 38:D473–479.
103.
Joshi-TopeG, GillespieM, VastrikIet al.Reactome: A knowledgebase of biological pathways. Nucleic Acids Res, 2005; 33:D428–D432.
104.
SchellenbergerJ, ParkJO, ConradTM, PalssonBO. BiGG: A biochemical genetic and genomic knowledgebase of large scale metabolic reconstructions. BMC Bioinformatics, 2010; 11:213.
105.
BeckerSA, FeistAM, MoMLet al.Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox. Nat Protoc, 2007; 2:727–738.
OrthJD, ThieleI, PalssonBO. What is flux balance analysis?Nat Biotechnol, 2010; 28:245–248.
108.
PriceND, ReedJL, PalssonBO. Genome-scale models of microbial cells: Evaluating the consequences of constraints. Nat Rev Microbiol, 2004; 2:886–897.
109.
ParkJM, KimTY, LeeSY. Constraints-based genome-scale metabolic simulation for systems metabolic engineering. Biotechnol Adv, 2009; 27:979–988.
110.
PatilKR, AkessonM, NielsenJ. Use of genome-scale microbial models for metabolic engineering. Curr Opin Biotechnol, 2004; 15:64–69.
111.
BurgardAP, PharkyaP, MaranasCD. Optknock: A bilevel programming framework for identifying gene knockout strategies for microbial strain optimization. Biotechnol Bioeng, 2003; 84:647–657.
112.
PatilKR, RochaI, ForsterJ, NielsenJ. Evolutionary programming as a platform for in silico metabolic engineering. BMC Bioinformatics, 2005; 6:308.
113.
PharkyaP, BurgardAP, MaranasCD. OptStrain: A computational framework for redesign of microbial production systems. Genome Res, 2004; 14:2367–2376.
114.
PharkyaP, MaranasCD. An optimization framework for identifying reaction activation/inhibition or elimination candidates for overproduction in microbial systems. Metab Eng, 2006; 8:1–13.
115.
KimJ, ReedJL. OptORF: Optimal metabolic and regulatory perturbations for metabolic engineering of microbial strains. BMC Syst Biol, 2010; 4:53.
116.
SegreD, VitkupD, ChurchGM. Analysis of optimality in natural and perturbed metabolic networks. Proc Natl Acad Sci, 2002; 99:15112–15117.
117.
ShlomiT, BerkmanO, RuppinE. Regulatory on/off minimization of metabolic flux changes after genetic perturbations. Proc Natl Acad Sci, 2005; 102:7695–7700.
JensenPA, PapinJA. Functional integration of a metabolic network model and expression data without arbitrary thresholding. Bioinformatics, 2011; 27:541–547.
124.
BlazierAS, PapinJA. Integration of expression data in genome-scale metabolic network reconstructions. Front Physiol, 2012; 3:299.
125.
RenS, ZengB, QianX. Adaptive bi-level programming for optimal gene knockouts for targeted overproduction under phenotypic constraints. BMC Bioinformatics, 2013; 14,Suppl 2:S17.
126.
BoyleNR, MorganJA. Flux balance analysis of primary metabolism in Chlamydomonas reinhardtii. BMC Syst Biol, 2009; 3:4.
127.
ManichaikulA, GhamsariL, HomEFet al.Metabolic network analysis integrated with transcript verification for sequenced genomes. Nat Methods, 2009; 6:589–592.
128.
CogneG, RügenM, BockmayrAet al.A model-based method for investigating bioenergetic processes in autotrophically growing eukaryotic microalgae: Application to the green algae Chlamydomonas reinhardtii. Biotechnol Prog, 2011; 27:631–640.
129.
ChangRL, GhamsariL, ManichaikulAet al.Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism. Mol Syst Biol, 2011; 7:518.
130.
Dal'MolinCG, QuekLE, PalfreymanRW, NielsenLK. AlgaGEM—a genome-scale metabolic reconstruction of algae based on the Chlamydomonas reinhardtii genome. BMC Genomics, 2011; 12,Suppl 4:S5.
131.
KrumholzEW, YangH, WeisenhornPet al.Genome-wide metabolic network reconstruction of the picoalga Ostreococcus. J Exp Bot, 2012; 63:2353–2362.
132.
RugenM, BockmayrA, LegrandJ, CogneG. Network reduction in metabolic pathway analysis: Elucidation of the key pathways involved in the photoautotrophic growth of the green alga Chlamydomonas reinhardtii. Metab Eng, 2012; 14:458–467.
133.
Le BihanT, MartinSF, ChirnsideESet al.Shotgun proteomic analysis of the unicellular alga Ostreococcus tauri. J Proteomics, 2011; 74:2060–2070.
134.
SchellenbergerJ, QueR, FlemingRMet al.Quantitative prediction of cellular metabolism with constraint-based models: The COBRA Toolbox v2.0. Nature Protoc, 2011; 6:1290–1307.
135.
ClarensAF, ResurreccionEP, WhiteMA, ColosiLM. Environmental life cycle comparison of algae to other bioenergy feedstocks. Environ Sci Technol, 2010; 44:1813–1819.
136.
LiuX, ClarensAF, ColosiLM. Algae biodiesel has potential despite inconclusive results to date. Bioresour Technol, 2012; 104:803–806.
137.
ResurreccionEP, ColosiLM, WhiteMA, ClarensAF. Comparison of algae cultivation methods for bioenergy production using a combined life cycle assessment and life cycle costing approach. Bioresour Technol, 2012; 126:298–306.
138.
SchmidtBJ, Lin-SchmidtX, ChamberlinAet al.Metabolic systems analysis to advance algal biotechnology. Biotechnol J, 2010; 5:660–670.
139.
WaltzE. Biotech's green gold?Nature Biotechnol, 2009; 27:15–18.
140.
SinghR. Facts, growth, and opportunities in industrial biotechnology. Org Process Res Dev, 2001; 175–179.
141.
SinghJ, CuS. Commercialization potential of microalgae for biofuels production. Renew Sust Energ Rev, 2010; 14:2596–2610.
142.
ThomasWH, SeibertDLR, AldenMet al.Yields, photosynthetic efficiencies and proximate composition of dense marine microalgal cultures. II. Dunaliella primolecta and Tetraselmis suecica experiments. Biomass, 1984; 5:211–225.
143.
HawkinsT, HendricksonC, HigginsCet al.A mixed-unit input-output model for environmental life-cycle assessment and material flow analysis. Environ Sci Technol, 2007; 41:1024–1031.
144.
HendricksonC, HorvathA, JoshiS, LaveL. Economic input-output models for environmental life-cycle assessment. Environ Sci Technol, 1998; 32:184A–191A.
145.
HeijungsR, SuhS. The Computational Structure of Life Cycle Assessment. Boston, MA: Kluwer Academic Publishers, Dordrecht, 2002.
146.
WeidemaB. ecoinvent data v2.0. Vol. 2008. Duebendorf, Switzerland: Swiss Federal Laboratories for Materials Testing and Research, 2007.
147.
CampbellPK, BeerT, BattenD. Life cycle assessment of biodiesel production from microalgae in ponds. Bioresour Technol, 2010; 102:50–56.
148.
KhooHH, TanRBH. Life cycle evaluation of CO2 recovery and mineral sequestration alternatives. Environ Prog, 2066; 25:208–217.
149.
StephensonAL, KazamiaE, DennisJet al.Life-cycle assessment of potential algal biodiesel production in the United Kingdom: A comparison of raceways and air-lift tubular bioreactors. Energy Fuels, 2010; 24:4062–4077.
