Lipid production in the industrial microalga Nannochloropsis gaditana exceeds that of model algal species and can be maximized by nutrient starvation in batch culture. However, starvation halts growth, thereby decreasing productivity. Efforts to engineer N. gaditana strains that can accumulate biomass and overproduce lipids have previously met with little success. We identified 20 transcription factors as putative negative regulators of lipid production by using RNA-seq analysis of N. gaditana during nitrogen deprivation. Application of a CRISPR–Cas9 reverse-genetics pipeline enabled insertional mutagenesis of 18 of these 20 transcription factors. Knocking out a homolog of fungal Zn(II)2Cys6-encoding genes improved partitioning of total carbon to lipids from 20% (wild type) to 40–55% (mutant) in nutrient-replete conditions. Knockout mutants grew poorly, but attenuation of Zn(II)2Cys6 expression yielded strains producing twice as much lipid (∼5.0 g m−2 d−1) as that in the wild type (∼2.5 g m−2 d−1) under semicontinuous growth conditions and had little effect on growth.
Subscribe to Journal
Get full journal access for 1 year
only $20.83 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Rent or Buy article
Get time limited or full article access on ReadCube.
All prices are NET prices.
Sequence Read Archive
Goncalves, E.C., Wilkie, A.C., Kirst, M. & Rathinasabapathi, B. Metabolic regulation of triacylglycerol accumulation in the green algae: identification of potential targets for engineering to improve oil yield. Plant Biotechnol. J. 14, 1649–1660 (2016).
Hu, Q. et al. Microalgal triacylglycerols as feedstocks for biofuel production: perspectives and advances. Plant J. 54, 621–639 (2008).
Vasudevan, V. et al. Environmental performance of algal biofuel technology options. Environ. Sci. Technol. 46, 2451–2459 (2012).
Wijffels, R.H. & Barbosa, M.J. An outlook on microalgal biofuels. Science 329, 796–799 (2010).
Ngan, C.Y. et al. Lineage-specific chromatin signatures reveal a regulator of lipid metabolism in microalgae. Nature Plants 1, 15107 (2015).
Goold, H.D. et al. Whole genome re-sequencing identifies a quantitative trait locus repressing carbon reserve accumulation during optimal growth in Chlamydomonas reinhardtii. Sci. Rep. 6, 25209 (2016).
Schulz-Raffelt, M. et al. Hyper-accumulation of starch and oil in a Chlamydomonas mutant affected in a plant-specific DYRK kinase. Biotechnol. Biofuels 9, 55 (2016).
Trentacoste, E.M. et al. Metabolic engineering of lipid catabolism increases microalgal lipid accumulation without compromising growth. Proc. Natl. Acad. Sci. USA 110, 19748–19753 (2013).
Daboussi, F. et al. Genome engineering empowers the diatom Phaeodactylum tricornutum for biotechnology. Nat. Commun. 5, 3831 (2014).
Levitan, O., Dinamarca, J., Zelzion, E., Gorbunov, M.Y. & Falkowski, P.G. An RNA interference knock-down of nitrate reductase enhances lipid biosynthesis in the diatom Phaeodactylum tricornutum. Plant J. 84, 963–973 (2015).
Radakovits, R. et al. Draft genome sequence and genetic transformation of the oleaginous alga Nannochloropis gaditana. Nat. Commun. 3, 686 (2012).
Griffiths, M.J. & Harrison, S.T.L. Lipid productivity as a key characteristic for choosing algal species for biodiesel production. J. Appl. Phycol. 21, 493–507 (2009).
Ma, X.N., Chen, T.P., Yang, B., Liu, J. & Chen, F. Lipid production from Nannochloropsis. Mar. Drugs 14, 61 (2016).
Kilian, O., Benemann, C.S., Niyogi, K.K. & Vick, B. High-efficiency homologous recombination in the oil-producing alga Nannochloropsis sp. Proc. Natl. Acad. Sci. USA 108, 21265–21269 (2011).
Rodolfi, L. et al. Microalgae for oil: strain selection, induction of lipid synthesis and outdoor mass cultivation in a low-cost photobioreactor. Biotechnol. Bioeng. 102, 100–112 (2009).
Sukenik, A. et al. Photosynthetic perfromance of outdoor Nannochloropsis mass cultures under a wide range of environmental conditions. Aquat. Microb. Ecol. 56, 297–308 (2009).
Blazeck, J. et al. Harnessing Yarrowia lipolytica lipogenesis to create a platform for lipid and biofuel production. Nat. Commun. 5, 3131 (2014).
Friedlander, J. et al. Engineering of a high lipid producing Yarrowia lipolytica strain. Biotechnol. Biofuels 9, 77 (2016).
Zienkiewicz, K., Du, Z.Y., Ma, W., Vollheyde, K. & Benning, C. Stress-induced neutral lipid biosynthesis in microalgae: molecular, cellular and physiological insights. Biochim. Biophys. Acta 1861 9 Pt B, 1269–1281 (2016).
Boussiba, S.V.A., Cohen, Z., Avissar, Y. & Richmond, A. Lipid and biomass production by the halotolerant microalga Nannochloropsis salina. Biomass 12, 37–47 (1987).
Li, J. et al. Choreography of transcriptomes and lipidomes of nannochloropsis reveals the mechanisms of oil synthesis in microalgae. Plant Cell 26, 1645–1665 (2014).
Corteggiani Carpinelli, E. et al. Chromosome scale genome assembly and transcriptome profiling of Nannochloropsis gaditana in nitrogen depletion. Mol. Plant 7, 323–335 (2014).
Pérez-Rodríguez, P. et al. PlnTFDB: updated content and new features of the plant transcription factor database. Nucleic Acids Res. 38, D822–D827 (2010).
Cerutti, H., Ma, X., Msanne, J. & Repas, T. RNA-mediated silencing in algae: biological roles and tools for analysis of gene function. Eukaryot. Cell 10, 1164–1172 (2011).
Wang, Q. et al. Genome editing of model oleaginous microalgae Nannochloropsis spp. by CRISPR/Cas9. Plant J. 88, 1071–1081 (2016).
Kennerdell, J.R. & Carthew, R.W. Heritable gene silencing in Drosophila using double-stranded RNA. Nat. Biotechnol. 18, 896–898 (2000).
Vieler, A., Brubaker, S.B., Vick, B. & Benning, C. A lipid droplet protein of Nannochloropsis with functions partially analogous to plant oleosins. Plant Physiol. 158, 1562–1569 (2012).
Xiao, Y., Zhang, J., Cui, J., Feng, Y. & Cui, Q. Metabolic profiles of Nannochloropsis oceanica IMET1 under nitrogen-deficiency stress. Bioresour. Technol. 130, 731–738 (2013).
Schmollinger, S. et al. Nitrogen-sparing mechanisms in Chlamydomonas affect the transcriptome, the proteome, and photosynthetic metabolism. Plant Cell 26, 1410–1435 (2014).
Gargouri, M. et al. Identification of regulatory network hubs that control lipid metabolism in Chlamydomonas reinhardtii. J. Exp. Bot. 66, 4551–4566 (2015).
Hu, J. et al. Genome-wide identification of transcription factors and transcription-factor binding sites in oleaginous microalgae Nannochloropsis. Sci. Rep. 4, 5454 (2014).
Xu, P., Qiao, K., Ahn, W.S. & Stephanopoulos, G. Engineering Yarrowia lipolytica as a platform for synthesis of drop-in transportation fuels and oleochemicals. Proc. Natl. Acad. Sci. USA 113, 10848–10853 (2016).
Biddy, M.J. et al. The techno-economic basis for coproduct manufacturing to enable hydrocarbon fuel production from lignocellulosic biomass. ACS Sustain. Chem.& Eng. 4, 3196–3211 (2016).
Davis, R., Aden, A. & Pienkos, P.T. Techno-economic analysis of autotrophic microalgae for fuel production. Appl. Energy 88, 3524–3531 (2011).
Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L. & Wold, B. Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat. Methods 5, 621–628 (2008).
Li, B. & Dewey, C.N. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC Bioinformatics 12, 323 (2011).
McCarthy, D.J., Chen, Y. & Smyth, G.K. Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation. Nucleic Acids Res. 40, 4288–4297 (2012).
Young, M.D., Wakefield, M.J., Smyth, G.K. & Oshlack, A. Gene ontology analysis for RNA-seq: accounting for selection bias. Genome Biol. 11, R14 (2010).
Shen, B. et al. Generation of gene-modified mice via Cas9/RNA-mediated gene targeting. Cell Res. 23, 720–723 (2013).
Cho, S.W., Kim, S., Kim, J.M. & Kim, J.S. Targeted genome engineering in human cells with the Cas9 RNA-guided endonuclease. Nat. Biotechnol. 31, 230–232 (2013).
Mali, P. et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013).
Bligh, E.G. & Dyer, W.J. A rapid method of total lipid extraction and purification. Can. J. Biochem. Physiol. 37, 911–917 (1959).
Ruiz-Matute, A.I., Hernández-Hernández, O., Rodríguez-Sánchez, S., Sanz, M.L. & Martínez-Castro, I. Derivatization of carbohydrates for GC and GC-MS analyses. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 879, 1226–1240 (2011).
Kaspar, H. Amino acid analysis in biological fluids by GC-MS. Dr. rer. nat. thesis, Univ. Regensburg (2009).
Lichtenthaler, H.K. Chlorophylls and carotenoids: pigments of photosynthetic biomembranes. Methods Enzymol. 148, 32 (1987).
Littler, M.M. & Arnold, K.E. In Handbook of Phycological Methods. Ecological Field Methods: Macroalgae (eds. Littler M.M. & Littler, D.S.) 349–375 (Cambridge University Press, 1985).
This work was funded by ExxonMobil and Synthetic Genomics, Inc. We thank A. Withrow (Center for Advanced Microscopy at Michigan State University) for producing the TEM images and C. Packard, B. Scherer, E. Wang and the rest of the analytical team at SGI for processing FAME and TOC samples. This work is dedicated to our colleague Tom Carlson, who passed away during the preparation of this manuscript.
I.A., J.V., M.A., J.C., K. Kwok, L.P., E.O., R.K., K. Konigsfeld, A.S., W.L., R.B. and E.R.M. are employees of Synthetic Genomics, Inc. Synthetic genomics has filed patents related to this work, with I.A., J.V., M.A., L.B.S. and E.R.M. listed as inventors.
Integrated supplementary information
A) FAME/TOC comparison of knockout lines for 18 –N down-regulated transcription regulators (see Supplementary Table 1 for full gene annotation information). FAME/TOC values represent the average and standard deviation of 3 time-points from biological duplicates during batch growth. The knockout line in gene Naga_100104g1g (referred to as ZnCys-KO) selected for further study is shown in red. B) Confirmation of the increased FAME/TOC ratio in a second Cas9-mediated ZnCys-KO line 2; the ZnCys-KO line 1 was used in the remainder of the study and is referred to as ZnCys-KO. C) FAME (mg/L) and D) TOC values (mg/L) of ZnCys-KO and WT grown in batch mode on SM-NO3- (n=2) E) FAME profiles (as mol % of total FAME) showing most abundant fatty acid species for ZnCys-KO in N-replete conditions and WT in +N and -N. C# indicates the fatty acid carbon chain length and:# indicates the number of double bonds. F) TAG content normalized to TOC (g/g) as determined by LC-MS. See Materials and Methods for further details on growth conditions.
Supplementary Figure 2 Initial batch-mode assessment of ZnCys-attenuated lines (ZnCys-BASH-3, ZnCys-BASH-12 and ZnCys-RNAi-7) grown in nitrate-replete medium (SM-NO3−).
A) FAME (mg/L) and B) TOC (mg/L) measurements corresponding to days 3, 5 and 7 of the screen. TOC productivity values displayed in Fig 2C were derived from these values.
Supplementary Figure 3 Productivity assessment of ZnCys-KO and ZnCys-RNAi-7 grown in semicontinuous mode on nitrate-rich medium (SM-NO3−).
Daily (A) FAME (mg/L), (B) TOC (mg/L), and (C) C/N values derived from cellular N-content. (D) FAME and E) TOC productivities (g/m2/day) for WT and ZnCys-RNAi-7 calculated for the entire 13-day assay. ZnCys-KO failed to reach steady-state at a 30 % daily dilution scheme and essentially washed away as the run progressed, therefore lipid and biomass productivity values were not calculated for this line (N/A, not available). Due to the severe growth defect of ZnCys-KO on medium containing nitrate as the sole N source, this strain was scaled up in SM-NH4+/NO3- to obtain enough biomass for the assay, but grown on SM-NO3- medium for the duration of semi-continuous productivity assessment.
Supplementary Figure 4 Productivity assessment of ZnCys mutants grown in semicontinuous mode for 8 d on NO3−-rich medium (SM-NO3−).
A) Daily FAME and B) TOC (mg/L) measurements for ZnCys mutants (ZnCys-RNAi-7, ZnCys-BASH-12 and ZnCys-BASH-3) compared to their parental lines Ng-CAS9+ and WT. Productivity values displayed in Fig 3A were derived from these values. Error bars represent standard deviations for 3 biological replicates (n=3). See Materials and Methods section for a detailed description on the assay and productivity calculations. C) Cell counts for various strains. Shown is the average and standard deviation of biological triplicate cultures for three consecutive days under semi-continuous growth (N = 9; corresponding to days 6 through 8 in Figure S4A).
Supplementary Figure 5 Repression of the lipid-accumulation phenotype of ZnCys-KO by NH4+ supplementation.
Daily A) FAME (mg/L), B) TOC (mg/L) and C) FAME/TOC values of ZnCys-KO and WT grown in batch mode on medium supplemented with NH4+ (SM-NH4+/NO3-). Error bars are standard deviations of 2 biological replicates.
Cultures were grown as in Fig. 4, and treated with the indicated amount of cycloheximide at 0 h. FAME/TOC measurements were taken 48 h after treatment.
Incident irradiance profiles for batch growth assessment (A), and the Semi-Continuous Productivity Assay (B).
Vector used to generate the Nannochloropsis Cas9 expression strain Ng-Cas9+ (A), and the hygromycin resistance cassette used for generating Cas9-mediated insertional mutants in the Ng-Cas9+ background (B). The coding sequences (yellow) for BSD (blasticidin deaminase), Cas9, and GFP, are driven by the TCT_P, RPL24_P, and 4AIII_P endogenous promoters, and terminated by the EIF3_T, FRD_T, and GNPDA_T endogenous terminator sequences, respectively. See Supplementary Table 7 for a further description of gene sources for promoter and terminator elements.
Supplementary Figure 9 Selection of the Ng-CAS9+ editor line and validation of transgenic Cas9 protein expression.
(A) Flow cytometry histogram (using the Accuri c6 cytometer) showing fluorescence in the FL1-A channel to detect GFP fluorescence. Wild-type fluorescence is shown in the black trace, whereas Ng-CAS9+ is shown in red. Histograms are drawn in the Accuri c6 Sampler software using data collected from 50,000 events. (B) Western blot detection of transgenic Cas9 protein in the Ng-CAS9+ editor line.
About this article
Cite this article
Ajjawi, I., Verruto, J., Aqui, M. et al. Lipid production in Nannochloropsis gaditana is doubled by decreasing expression of a single transcriptional regulator. Nat Biotechnol 35, 647–652 (2017). https://doi.org/10.1038/nbt.3865
Emerging Technologies to Enable Sustainable Controlled Environment Agriculture in the Extreme Environments of Middle East-North Africa Coastal Regions
Frontiers in Plant Science (2020)
Plastidial and ER Triacylglycerol Biosynthesis in a Growth Phase-Dependent Manner in the Heterokont Nannochloropsis oceanica
Frontiers in Marine Science (2020)
Photoprotection capacity of microalgae improved by regulating the antenna size of light-harvesting complexes
Journal of Applied Phycology (2020)
Biotechnology Progress (2020)
Trends in Biotechnology (2020)