Current perspectives on integrated approaches to enhance lipid accumulation in microalgae

Abstract

In recent years, research initiatives on renewable bioenergy or biofuels have been gaining momentum, not only due to fast depletion of finite reserves of fossil fuels but also because of the associated concerns for the environment and future energy security. In the last few decades, interest is growing concerning microalgae as the third-generation biofuel feedstock. The CO₂ fixation ability and conversion of it into value-added compounds, devoid of challenging food and feed crops, make these photosynthetic microorganisms an optimistic producer of biofuel from an environmental point of view. Microalgal-derived fuels are currently being considered as clean, renewable, and promising sustainable biofuel. Therefore, most research targets to obtain strains with the highest lipid productivity and a high growth rate at the lowest cultivation costs. Different methods and strategies to attain higher biomass and lipid accumulation in microalgae have been extensively reported in the previous research, but there are fewer inclusive reports that summarize the conventional methods with the modern techniques for lipid enhancement and biodiesel production from microalgae. Therefore, the current review focuses on the latest techniques and advances in different cultivation conditions, the effect of different abiotic and heavy metal stress, and the role of nanoparticles (NPs) in the stimulation of lipid accumulation in microalgae. Techniques such as genetic engineering, where particular genes associated with lipid metabolism, are modified to boost lipid synthesis within the microalgae, the contribution of “Omics” in metabolic pathway studies. Further, the contribution of CRISPR/Cas9 system technique to the production of microalgae biofuel is also briefly described.

Introduction

Microalgae are promising alternative feedstock for the production of third- and fourth-generation biofuels (Lam and Lee 2012). This third-generation feedstock can accumulate a significant amount of neutral lipids, principally triacylglycerols (TAGs) which are produced from free fatty acids and assembled at the endoplasmic reticulum (ER) (Fig. 1). Liquid biofuel such as biodiesel is positively favored due to its non-polluting nature and ability to mix with conventional fuels. Starch is the primary carbon storage compound in microalgae but in different environmental stress conditions, it shifts to the storage of energy-rich compounds, such as lipids (Nordin et al. 2020). Strain selection, optimization of growth conditions, and genetic manipulations are key aspects that contribute to high lipid yield (Lim and Schenk 2017). The potential of lipid production in microalgae can be enhanced by inducing nutrition and various abiotic stress conditions to channel metabolic fluxes into lipid biosynthesis. With stress reversal, TAGs molecules are catabolized back to release fatty acids (FAs) and used for membrane synthesis. Stress environment cause oxidative damage to the cells that suppress microalgae growth which could ultimately diminish the number of products of our interest (Sun et al. 2018). To survive in intense environments, microalgae induce a specific alteration in the chain length or the degree of saturation to make it resistant to stress conditions (Khan et al. 2018a, b). Many studies have shown that the cultivation of algal strains under controlled abiotic stress leads to slow cell growth with low lipid productivity (Tan and Lee 2016). Therefore, to overcome these limits, certain approaches like addition of growth-promoting substances to the cells and two-stage cultivation strategies have been used.

Fig. 1.

Schematic representation of microalgal lipid biosynthesis. The enzymes are shown in red. Free fatty acids are synthesized in the chloroplast and the TAGs are assembled at the Endoplasmic Reticulum (ER)

Numerous studies have gradually been introduced molecular evolution and adaptive changes as an effective means to improve biological properties of microalgae, particularly towards enhancement of lipid content (Sun et al. 2018). Many marine and freshwater microalgae accepted as an appropriate candidate for biofuel production and documented that the lipid content of Neochloris oleoabundans, Haematococcus pluvialis, Nannochloropsis sp., Porphyridium, Chlamydomonas, Dunaliella, Tetraselmis, Isochrysis, Phaeodactylum, Schizochytrium, Scenedesmus sp., Synechococcus sp., and Chlorella sp. fluctuate with 20% and 50% of dry weight (Damiani et al. 2010; Osorio et al. 2019; Shanmugam et al. 2020). Accumulation of lipids in microalgae can also be increased by suitably modifying their genomes using latest molecular biology techniques (Radakovits et al. 2010). Genetic engineering allows us to manipulate genes associated with FA synthesis in green algae, to find a potent strain with higher lipid content. An in-depth understanding of target genes and metabolic pathways related to lipid accumulation can be applied in microalgae genetic engineering to improve algal biofuel production (Khozin-Goldberg and Cohen 2011). Also, remarkable progress has been made in the direction of overexpression or deletion of genes in several strains of microalgal with high potential for biofuel production (Lin et al. 2013). Transcriptome study of Chlamydomonas reinhardtii reveals higher accumulation of lipid with significant up-regulation of Glycerol-3-phosphate dehydrogenase and Lysophosphatidic acid acyltransferase, which indicates a positive correlation between the transcription of those genes and cellular lipid accumulation (Lv et al. 2013). Studies in Chlorella sp., Nannochloropsis sp., Monoraphidium neglectum, and Chlamydomonas reinhardtii have carried out an analysis of correlation between accumulation of stored compound and transcriptome patterns, which signify possible transcription factors and metabolic nodes concerning an exchange of starch and lipid metabolism (De Jaeger et al. 2018; Tibocha-Bonilla et al. 2018; Sturme et al. 2018).

Additionally, omics technique eases to understand the mechanisms of stress-related lipid accumulation in microalgae which ultimately leads to the development of genetically improved microalgal strains with high lipid productivity (Khan et al. 2018a, b; Shahid et al. 2020). This review article studies the classical as well as current strategies used for the improvement of lipid accumulation in microalgae (Fig. 2). The application of NPs in algal biotechnology is still new and known too little; thus, the studies on the role of NPs in lipid enhancement in microalgae are summarized in this review. Additionally, the use of metabolic and genetic modification techniques with Omics approaches for the identification of target genes to improve lipid in microalgae is comprehensively described.

Fig. 2.

Different approaches to improve the lipid production in microalgae

Effect of various abiotic stresses on the lipid accumulation in microalgae

Stress conditions bring changes in cell metabolic activities, activates TAGs synthesis, which provokes lipid accumulation in microalgae (Johnson and Alric 2013; Brindadevi et al. 2021). Nutrients such as nitrogen (N), silicon (Si), phosphorus (P), carbon (C), sulfur (S), and iron (Fe) have important functions on the growth, division, and metabolism of microalgae. According to literature studies, nutrient starvation has been used as a promising strategy to regulate biochemical pathways associated with cell cycle and lipid synthesis (Johnson and Alric 2013) (Table 1). FA content in Chlamydomonas reinhardtii was found to increase under P- and N-deficient conditions (Yang et al. 2018). Further, Mata et al. (2013) observed a tenfold increase in the concentration of N in the growth medium increased lipid productivity by 33.5% and 47.4 mg L⁻¹ day⁻¹, respectively in Dunaliella tertiolecta (Mata et al. 2013). Whereas, Fe concentration increased up to ten times in the culture medium (compared to control), and the lipid yield enhanced from 14.6 mg L⁻¹ day⁻¹ to 28.0 mg L⁻¹ day⁻¹. In green algae, Chlamydomonas moewusii, nutrient starvation resulted in reduced polyunsaturated fatty acids (PUFAs) contents (C16:3, C16:4, and C18:3) while high monounsaturated fatty acids (MUFAs) content (C16:1 and C18:1) (Arisz et al. 2000). In the case of diatom Stephanodiscus minutulus, an increase in TAG accumulation and a decrease in polar lipids were observed during silicon, N, and P limit conditions (Lynn et al. 2000). Cyclotella cryptic accumulated higher levels of TAGs, saturated and monounsaturated FAs when experienced silicon stress in the medium (Miao and Wu 2006). It has been evidenced that lipid content of freshwater green algae Chlorella protothecoides could increase up to 52.5% in N deficiency (Li et al. 2014a, b). Scenedesmus sp. when encountered N and P limit conditions, lipids content increased up to 30% and 53%, respectively (Xin et al. 2010). It has been deliberated that P limit condition possibly blocks starch biosynthesis and tends to biosynthesis of FA to overcome stress effect. In a study, different P concentrations were supplemented to increase the lipid production in Scenedesmus sp. The highest lipid productivity (350 mg L⁻¹) and biomass (approximately 41% of dry weight) were observed in 2 mg L⁻¹ concentration of NaH₂PO₄·2H₂O every 2 days against P replete condition with a significant decrease in carbohydrate content (Yang et al. 2018).

Table 1.

Effect of different stress conditions and genetic modification for enhancing the lipid accumulation in microalgae

Algae strains	Abiotic stress/other environmental factors	Growth media	genetic modification/genes/upregulated pathways	Genetic modification/genes/downregulated pathways	Enhance lipid content/total lipid productivity	References
Scenedesmus acutus	N-deprivation	TAP medium	Genes: The expression of tricarboxylic acid (TCA) genes [(aconitase (c3856_g2_i1), citrate synthase (c20049_g1_i1, c24189_g1_i1, and c28983_g1_i1), fumarase (c15399_g1_i1), isocitrate dehydrogenase (c6837_g1_i3), succinate dehydrogenase (c9370_g1_i1 and i2), and succinyl-CoA ligase (c19990_g1_i1))] Genes: The expression of starch cleavage genes including triose-phosphate transporter was induced [(TPT: c24129_g1_i1), 4-α-glucanotransferase (D-enzyme: c740_g1_i1), glucan water dikinase (GWD: c1277_g1_i1, c10271_g33_i1, and c20068_g1_i1), starch phosphorylase (SP: c9904_g1_i2 and i3), α-amylase (c412_g1_i1, c10493_g9_i2, c28729_g1_i1, and c33377_g1_i1), sucrose synthase (Susy: c8912_g1_i2), and fructokinase (c9298_g4_i1)] In the glycolytic pathways, expression of phosphofructokinase (PFK: c6362_g1_i1 and c10466_g19_i1 and i2), glyceraldehyde 3-phosphate dehydrogenase (GAPDH: c10641_g1_i1 and c24212_g1_i1), phosphoglycerate mutase (PGAM: c3021_g1_i2, c9255_g2_i1, c10485_g24_i3, and c24459_g1_i1), enolase (c19909_g1_i1 and c29129_g1_i1), and pyruvate kinase (PK: c4713_g2_i1, c10123_g12_i1, c10306_g22_i1, and c19619_g1_i1)	The decreased expression of genes involved in starch synthesis [ADP-glucose pyrophosphorylase (AGPase: c9688_g1_i1, c9688_g2_i1, and c24642_g1_i1)], starch branching enzyme [(SB: c9616_g3_i1, c10738_g1_i1, and c24521_g1_i1), and six starch synthases (SS:c8813_g1_i1, c10182_g2_i1, c10540_g1_i1, c10182_g1_i1, c10182_g3_i1, and c15126_g1_i1)]	Shift of carbon flux toward fatty acid and TAG biosynthesis and total lipid increased	Liang and Jiang (2013)
Nannochloropsis oceanica IMET1	N+ and N−	Modified f/2	Genes: DGAT-2I, DGAT-1B, DGAT-2F and 2G and DGAT-2 K (N+ conditions) DGAT 1A and DGAT-2H, DGAT-2C and 2D; DGAT-2A, 2B, and 2E (N−conditions)	–	Increased overall TAG production	Li et al. (2014a, b)
Ettlia oleoabundans	N-starvation	BBM	Genes: Starch metabolism (SSY3, SSG1 and SSG2, SSY2, starch degradation (GWD1) Genes: chloroplastic 3-oxoacyl-ACP synthase I (KASC1), 3-oxoacyl- ACP reductase (FABG), NADPH-dependent enoyl-ACP reductase (FABL) and 3-hydroxyacyl-ACP dehydratase (FABZ), as well as the acyl-ACP thioesterase (FATA) ↑TAG biosynthesis: Early up-regulation of glycerol kinase (GK), glycerol-3-phosphate dehydrogenase (GPDA), two glycerol-3-phosphate O-acyltransferases (GPAT) and the phosphatidic acid phosphatase (PAP), lysophosphatidic acid acyltransferase (LPAT), DGAT-1 and DGAT-2 gene Late up-regulation of TAG lipases	–	–	Sturme et al. (2018)
C. reinhardtii	N-starvation	TAP medium	Gene: sta6 (ADP-glucose pyrophosphorylase) and sta7-10 (isoamylase) mutations Over accumulation of lipid in the sta6 and sta7-10 starchless mutants	–	Tenfold enhancement in TAG accumulation in contrast to wild type	Work et al. (2010)
Phaeodactylum tricornutum	N-deprivation	f/2-Si medium (omitting Na2SiO3·9H2O	Gene: Over expression of Malic enzyme (ME) Overexpression of ME (PtME) significantly enhanced the expression of PtME and its enzymatic activity in transgenic P. tricornutum	–	Neutral lipid content increased 2.5-fold and 57.8% of dry cell weight	Ahmad et al. (2015)
C. reinhardtii	N-starvation	TAP medium	Gene: DGAT-1 and DGTT-1 also show increased mRNA abundance in other TAG-accumulating conditions (minus sulfur, minus phosphorus, minus zinc, and minus iron) ↑of NRR1TF	–	An insertional mutant, nrr1-1, accumulate 50% of the TAG compared with the parental strain	Miller et al. (2010)
C. reinhardtii	N-deprivation	TAP medium	Gene: Repression of major lipid droplet protein (MLDP) gene expression using RNAi	–	40% increase in the average lipid droplet diameter	Moellering and Benning (2010)
C. reinhardtii	N-deficient HSM	TAP medium	Gene: Knockout of citrate synthase gene mRNA levels of DGAT-2 and PAP2 (lipid biosynthesis) significantly increased	CrCIS activity decreased by 16.7%–37% in transgenic strains compared to the control Conversely, over expression of CrCIS gene decreased the TAG level by 45% but increased CrCIS activity by 209%–266% in transgenic algae	TAGs level increased up to 169.5%	Deng et al. (2013)
C. reinhardtii	N-deprivation	TAP medium	Gene: Overexpression of acetyl-CoA synthetase (ACS) acetyl-CoA synthetase	–	Cr-acs2 transformant shows sixfold higher levels of ACS2 transcript and a 2.4-fold higher accumulation of TAGs than the untransformed control	Rengel et al. (2018)
Nannochloropsis oceanica	N-deprivation	YPD	Genes: acyl-CoA diacylglycerols acyltransferase 2A, 2C, 2D	–	SFAs, MUFAs, and PUFAs in TAG varied by 1.3-, 3.7-, and 11.2-fold, respectively	Xin et al. (2017)
Nannochloropsis oceanica	N+ and N−	–	Genes: Overexpression and Knockdown of NoDGAT2J	–	Proportions of LA and EPA in TAG vary by 18.7-fold (between 0.21% and 3.92% dry weight) and 34.7-fold (between 0.09% and 3.12% dry weight), respectively	Xin et al. (2019)
Phaeodactylum tricornutum	N-depletion	Guillard f/2 medium	Genes: UDP-glucose pyrophosphorylase, glycerol-3-phosphate dehydrogenase, enoyl-ACP reductase, long chain acyl-CoA elongase, putative palmitoyl-protein thioesterase, W-3 fatty acid desaturase and D-12-fatty acid desaturase	–	45-fold increase in TAGs production through UDP-glucose pyrophosphorylase mutant	Daboussi et al. (2014)
Botryococcus braunii 779	N-deprivation	Bold’s modified Bristol	Pathway: Citrate cycle, glycolysis, gluconeogenesis, pentose phosphate pathway, carbon fixation metabolism Genes: ammonia permease, glutamine synthases, and glutamate synthases	Pathway: Photosynthesis (light harvesting), ribosomes, N metabolism	–	Fang et al. (2015)
Botryosphaerella sudeticus	N-deprivation	–	Genes: Lipid metabolism enzymes: monoacylglycerol lipase (EC 3.1.1.23), 3-oxoacyl-[acyl-carrier-protein] reductase (EC 1.1.1.100)	Pathway: Photosynthesis	–	Sun et al. (2013)
C. reinhardtii	N-deprivation	TAP medium Sueoka’s high salt medium AP medium	Pathway: Lipid metabolism, Glycolysis Genes: Diacylglycerol acyltransferases (DGTT3), ammonium transporter (AMM4), Protein kinase activity, Protein-Tyr kinase activity, and Protein Ser/Thr kinase Genes: Diacylglycerol: acyl-CoA acyltransferases (DGTT1, DGTT3, DGTT4) Genes: NADPH/NADP + ratio upregulating genes, DGAT-1, DGAT-2, lipases, saposins, mitochondrial glycerol-3-phosphate dehydrogenase, TAG lipases	Pathway: Photosynthesis- Cyclophilin, PSI reaction center, DNA replication initiation Genes: 3-ketoacyl-ACP Synthase I (KASI), 3-ketoacyl-ACP reductase (KAR) Genes: Chaperons, carbon metabolism genes, periplasmic carbonic anhydrase 1, PDC, ACCase, malonyl-coA: ACP, KAR, HAD, chlorophyll genes, isoprenoids genes, porphyrin genes, glycerolipids genes	–	Miller et al. (2010) Msanne et al. (2012) Garcia de Lomana and Baliga (2010)
Chlorella sorokiniana	N-deprivation	Kuhl medium	Genes: RBCL, phosphoglycerate kinase (PGK), DGAT, biotin carboxylase, KAS II, KAS III, KAR, DGAT	Gene: Starch synthase, ACCase, MAT, 1,4 α-glucan branching enzymes	–	Li et al. (2016)
Dunaliella tertriolecta	N-deprivation	f/2	Pathway: Glutamate synthesis, Lipid biosynthesis	Pathway: Photosynthesis, C1 metabolism, TCA cycle Gene: FKBP-peptidyl-propyl cis–trans isomerase, FKBO-methyl transferase, Glutamate-1-semialdehyde amino transferase, methylenetetrahydrofolate reductase (MTHFR), Gammaglutamyl hydrolase (GGH), met E, Phosphoenol pyruvate carboxylase (PEPC), Malate dehydrogenase (MDH), Pyruvate dehydrogenase (PDH)	–	Shin et al. (2015)
Nannochloropsis	N-deprivation	–	Genes: Glutamine synthase, glutamate synthase, glutamine amido transferase, guanine deaminase, cysteine synthase, cullin, Ubiquitin specific proteases, Autophagy-related proteins, ACCase Pathway: Channels and vascular trafficking proteins. Gene: DGAT-2A/2B, PDAT, Galactolipase gene (PSD1), lipases genes, ACP gene, KAS I	Gene: NADH dehydrogenase, α-ketoglutarate dehydrogenase Pathway: Photosynthesis, DNA replication, protein folding/ modifications Gene: ACCase, HAD	–	Carpinelli et al. (2014)
Neochloris oleoabundans	N-deprivation	Modified Bold-3N	Pathway: Carboxylic acid, lipid biosynthetic process, NADPH regeneration, pentose-phosphate pathway, phospholipid, metabolic process, lipid transport, nitrate metabolism and nitrate assimilation Genes: Biotin carboxylase, malonyl-CoA ACP transacylase (MAT), beta-ketoacyl-ACP synthase (KAS), betahydroxyacyl- ACP dehydrase (HAD), enoyl-ACP reductase (EAR), thioesterases oleoyl ACP hydrolase (OAH), Acyl-ACP thioesterase A (FatA), acyl-ACP desaturase (AAD), glycerol-3- phosphate acyltransferase (GPAT), acyl-glycerol- 3-phosphate acyltransferase (AGPAT), phospholipases, pyruvate kinase dehydrogenase complex	Pathway: carbon fixation, photosynthesis, protein synthesis, fatty acid degradation, and starch synthase Genes: ACCase, beta-ketoacyl-ACP reductase (KAR), delta-12 desaturase, acyl-CoA oxidase (ACOX1), acetyl-CoA acetyltransferase (ACAT), AGPase, α-amylase	–	Rismani-Yazdi et al. (2012)
Phaeodactylum tricornutum	N-deprivation	ASPII f/2-Si	Genes: conserved cyclin (Cyc B1), nitrate/ammonia/urea transporters, glutamate dehydrogenase, glutamate synthetases, malic enzyme, α-carbonic anhydrase, β oxidation genes, fatty acid chain modification genes, acyl-ACP desaturase Pathway: nitrogen fixation, carbon fixation, glycolysis and the TCA cycle Genes: ammonium transporters, glutamine synthase, nitrate reductase, ferredoxin-nitrite reductase, light harvesting complex, fucoxanthin chlorophyll a/c protein, phosphoenolpyruvate carboxylase, malic enzyme, fructose-1,6- bisphosphatase, isocitrate dehydrogenase, citrate synthase, isocitrate dehydrogenase, diacylglycerol acyltransferase,	Gene: Carbamoyl phosphate synthase, LHC genes, Chlorophyll a gene, TCA genes, Pyruvate kinase 6, ACCase, lipid particle protein Pathway: photosynthesis, gluconeogenesis, glyoxylate cycle, chrysolaminarin synthesis and sucrose metabolism. Genes: Ferredoxin-NADP + reductase, isocitrate lyase, malate synthase, phosphoenolpyruvate carboxykinase, Lipases	–	Valenzuela et al. (2012) Yang et al. (2015a, b)
C. vulgaris var L3	N-deprivation	Modified BBM	Genes: Nitrate reductase, malic enzyme	Genes: RuBisCo, ADP-glucose pyrophosphorylase (AGPase), starch phosphorylase, ATP citrate lyase, phosphoenolpyruvate carboxylase (PEPCase), biotin carboxylase subunit of the heteromeric form (accC)	–	Ikaran et al. (2015)
Micractinium pusillum	N-deprivation	HSM	Genes: glyceraldehyde 3-phosphate dehydrogenase, glycogen or starch phosphorylase, aldose 1-epimerase, strombine dehydrogenase, dihydrolipoamide dehydrogenase, acyltransferase 3, diacylglycerol kinase, nitrate reductase, cytochrome cd1-nitrite reductase-like superfamily, NADH: cytochrome b5 reductase	Genes: 3-isopropylmalate dehydrogenase, nucleoside diphosphate kinase 1, checkpoint 1-like protein, light harvesting complex I, RNA (uracil-5-) methyltransferase/Trm A	–	Li et al. (2012)
Tisochrysis lutea (lipid mutant)	N-deprivation	Modified Conway medium	Gene: GDLS lipase	Gene: Long-chain fatty acid ligase (ACLS)	–	Carrier et al. (2014)
Monoraphidium neglectum	N-deprivation	ProF medium	Pathway: Glycolysis, TCA Gene: PEP carboxylase	Pathway: Photosynthesis, gluconeogenesis, Protein synthesis	–	Jaeger et al. (2017)
Tetraselmis M8	N-deprivation	F/2	Pathway: Glycolysis, Lipid Genes: HD, KAS, LPAAT, LPAT,	Pathway: Carbon metabolism, Photosynthesis, Protein synthesis, TCA Genes: Fructose 1, 6 bisphosphate, Fructose 1, 6 bisaldolase, ENR, KAR, DGAT	–	Lin et al. (2012)
C. vulgaris	Cu NPs, Mg NPs, Zn NPs, Pb NPs	–	–	–	Metal resistance induction, Total lipid increase (up to 32%) Photosynthesis enhancement, Lipid content increase (0.43 mg L−1); Metal resistance induction, Total lipid content increase (0.74 mg L−1); Increase of growth rate Total lipid content increase (0.76 mg L−1)	Sibi et al. (2017)
Fistulifera solaris	Nutrient stress	Half-strength Guillard's f medium (f/2), ASW	Genes: Overexpression of glucose-6-phosphate dehydrogenase (G6PD) and phosphogluconate dehydrogenase (PGD)	–	Elevated lipid productivity by 1.5-fold	Osada et al. (2017)
Chlorella pyrenoidosa	N, P, and Fe deficiency	–	–	–	Increase in 50.32% and 34.29% of dry cell weight	Fan et al. (2014)
Scenedesmus sp.	P-limitation	Modified soil extract (SE) medium	Genes: encoding for DGAT and pyruvate kinase Activation of carbohydrate metabolism pathway and fatty acid biosynthesis	Repression of carbohydrate synthesis	350 mg L−1 (41.0%)	Yang et al. (2018)
Chlamydomonas sp. JSC4	4% (v/v) CO2 concentration	HSM containing 3.5% sea salt	–	–	Generated maximum lipid content (65.3%) and productivity (169.1 mg L−1 day−1)	Nakanishi et al. (2014)
Chlorococcum littorale	5% (v/v) CO2 concentration	ASW	–	–	Lipid content increased up to 34% wt	Ota et al. (2009)
Scenedesmus obliquus CNW-N	The optimal CO2 consumption rate was 1420.6 mg/L/day	Modified version of Detmer’s Medium (DM)	–	–	The highest productivity of lipid (140.35 mg L−1 day−1) is achieved	Ho et al. (2012)
Synechocystis sp. PCC6803	3% (v/v) CO2 concentration and light intensity	BG-11 medium with fivefold increased P	–	–	The total lipid content increased up to 14% of dry weight at 3% CO2	Cuellar-Bermudez et al. (2015)
Porosira glacialis	20–25% levels of CO2	F/10 medium	–	–	The total lipid content increased from 8.91 to 10.57% in cell dry mass Docosahexaenoic acid content increased from 3.90 to 5.75% EPA decreased from 26.59 to 23.66%	Artamonova et al. (2017)
Scenedesmus sp.; Botryococcus braunii and C. vulgaris	10% CO2	BG-11	–	–	Lipid productivity reached up to 20.65 mg L−1 day−1 (Scenedesmus sp), 5.51 mg L−1 day−1 (Botryococcus braunii) and 6.91 mg L−1 day−1 (Chlorella vulgaris)	Yoo et al. (2010)
C. vulgaris	30% CO2	BG-11	–	–	The highest lipid content (45.68%) and lipid productivity (86.03 mg L−1 day−1)	Huang and Su (2014)
Chlorella pyrenoidosa	CO2	BBM	Genes: Phosphoenolpyruvate carboxylase, malate dehydrogenase, malic enzyme, pyruvate phosphate, pyruvate orthophosphate dikinase, acetyl coenzyme A, nitrite transporter	Genes: fructose-2,6 bisphosphatase (FBP), triose-phosphate isomerase (TIM), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribose-5-phosphate isomerase, malate synthase	–	Fan et al. (2016)
Thalassiosira pseudonana (diatom)	Silicon starvation	ASW (Biotin and Vitamin B12)	knockdown of a multifunctional lipase/phospholipase/acyltransferase	–	Strains 1A6 and 1B1, respectively, contained 2.4- and 3.3-fold higher lipid content than wild type during exponential growth 4.1- and 3.2-fold higher lipid content than wild type after 40 h (silicon starvation)	Trentacoste et al. (2013)
Thalassiosira pseudonana	Silicon deficiency	ASW	↑Pathway: Photorespiration, Calvin-Benson cycle, glycolysis, pigment biosynthesis Genes: ACCase, DGAT-1, FAS II, LPLAT/ AGPAT	Pathway: Cell division. Photosynthesis, Translation, Ribosome	–	Smith et al. (2016)
Picochlorum strain SENEW3	Salinity stress	ASW based Guillard’s f/2 medium	↑Pathway: Photorespiration, proline synthesis, Nitrate and urea assimilation, Starch synthesis Genes: Glycolate dehydrogenase	Genes: Glycolate oxidase	–	Foflonker et al. (2016)
C. reinhardtii (diploidscolcemid treated)	Cold stress	TAP medium	Genes: Ribosomal proteins, PS I, PS II, LHC, NADH dehydrogenase, ATP synthases, NADPH-ubiquinone oxidoreductase, Triose phosphate isomerase, Sedoheptulose 1, 7 bis phosphatase, Fructose 1, 6 bisaldolase, RuBisCo, SNF related kinase I, cytosolic ribosomal protein L22	Genes: Sucrose synthase, AGPase, Transketolase, aconitase, pyruvate kinase	–	Kwak et al. (2017)
Chlorella sp. UMACC 237	UV stress	BBM	–	Pathways: Fatty acid degradation, valine, leucine and Isoleucine degradation, sucrose and starch metabolism Genes: Superoxide dismutase, catalase, trehalose 6 phosphate synthase	–	Poong et al. (2017)
Dunaliella tertiolecta	Mutant	Basal media + 0.5 M NaCl	↑Pathway: Photosynthesis, ATP synthesis, Inositol phosphate metabolism Gene: ACCase,	Gene: FabG, 3-oxoacyl-(ACP) reductase	–	Yao et al. (2015)
C. vulgaris	Nanoscale MgSO4	–	–	–	Photosynthesis enhancement 185.29 ± 4.53% improvement in lipid production	Hu et al. (2013)
Chlorella sp. KR-1	CTAB-decorated Fe3O4 NPs	–	–	–	Improvement of harvesting and cell disruption efficiency. The cells harvested using CTAB–OTES–MNP yielded an approximately 2.3-fold higher lipid content compared with the control extracted by only hexane	Guo et al. (2017)
Nannochloropsis maritima	Fe3O4 NPs	–	–	–	Biomass increased up to 1.02 g L−1 at day 18 (high total lipid)	Kalita et al. (2011)
C. vulgaris and Spirulina platensis	Electrolysis using CaO/KOH–Fe3O4 and KF/KOH–Fe3O4 as magnetic nanocatalysts	–	–	–	Increase in 24–60% TAGs	Farrokheh et al. (2020)

Temperature also has a strong effect on FA synthesis and lipid production; however, it varies with different species of microalgae. Literature studies revealed that biochemical pathways associated with the synthesis of lipids and accumulation are controlled by enzymes that are highly sensitive to thermal variations (Dickinson et al. 2017). Some researchers hypothesized that as temperature increases, microalgae accumulate more saturated FAs; in contrast, at low temperatures, microalgae accumulate high unsaturated FAs. Menegol et al. (2017) experimented the effects of temperature on Heterochlorella luteoviridis and perceived that at 22 °C, 40.7% of PUFAs were obtained. However, a high percentage of saturated FAs was noticed (52.9%), when the temperature was adjusted to 22–27 °C. An investigation on Nannochloropsis limnetica suggests that cells can easily proliferate in the range of 15–27 °C temperature but their maximum biomass and lipid content received at 22 °C (Freire et al. 2016). Another study revealed that 13 °C temperature was an optimal temperature for lipid accumulation for Monoraphidium consortiums and Desmodesmus quadricauda (Bohnenberger and Crossetti 2014). Whereas, it was 20 °C and 30 °C in the case of Tetraselmis subcordiformis and N. oculata, respectively (Wei et al. 2015). A study was also conducted on the influence of temperature on the composition of intracellular FAs and the release of free fatty acids (FFAs) into the medium for cyanobacterium (Spirulina platensis) and green microalgae (Botryococcus braunii and Chlorella vulgaris) (Sushchik et al. 2003). It was observed that despite their taxonomy, microalgal and cyanobacterial strains respond to temperature regimes with similar changes in the composition of their intracellular FAs: the content of unsaturated FAs decreased, and the saturated FAs increases with the rise in temperature (Sushchik et al. 2003).

Salt is also essential for physiological and biochemical pathways, growth, division, and FAs metabolism in microalgae. Thus, variations in salt concentrations are accepted as one of the most enriched approaches to increase lipid yield in microalgae. Salinity stress causes differences in osmotic pressure inside microalgae cells; hence, a stress response has been generated that modifies their metabolism and allows the microalgae to adapt to the fresh conditions (Kan et al. 2012). The variation in concentrations of salt in the growing medium not only increases the total lipids but also can change the composition of lipids in microalgal cells. Bartley et al. (2013) explored effect of varying concentrations of salts on the growth of marine microalgae Nannochloropsis salina (Bartley et al. 2013). Initially, the culture was grown at 22 PSU (particle salinity unit) and concentrations of salts were increased to 34, 46, and 58 PSU until culture attains a stationary phase. The lipid content examined was significantly increased in varying NaCl concentrations and the highest total FAs content (36% dry tissue mass) was found to be at 34 PSU (Bartley et al. 2013). Chlamydomonas Mexicana and Scenedesmus obliquus were raised in a growth medium with varying concentrations of NaCl up to 100 mM and the maximum lipid content (37% and 34%, respectively) in C. Mexicana and S. obliquus was noticed with 25 mM NaCl concentration. Whereas, linoleic acids and oleic acids were found to be dominated FAs with 41% (Salama et al. 2013). Different NaCl concentrations (0.06–0.4 M) were also tested on C. vulgaris and Acutodesmus obliquus and maximum quantity of lipids (49% and 43%, respectively) were achieved at 0.4 M NaCl concentration (Pandit et al. 2017). In another study, accumulation of lipids (33.40 ± 2.29%) was significantly enhanced in 200 mM NaCl concentration was noticed in Acutodesmus dimorphus and noticed a significant increase in lipid accumulation up to 43%, when stress condition extended to three days (Chokshi et al. 2017). Apart from varying concentrations, types of salt also have a positive effect on lipid accumulation in microalgae. Srivastava and Goud (2017) studied the effect of different salts (NaCl, KCl, MgCl₂, and CaCl₂) on Chlorella sorokiniana CG12 (KR905186) and Desmodesmus GS12 (KR905187). It was detected that CG12 and GS12 accumulated lipid up to 40.02% and 44.97% with CaCl₂ (Srivastava and Goud 2017). Cu, Fe, Ni, Zn, and Mn are heavy metals that have an essential role in many biological processes. Microalgae are considered competent and effective in removing heavy metals. Accumulation of high heavy metal concentrations triggers the production of reactive oxygen species in microalgae (Srivastava et al. 2018). In turn, inhibition of chlorophyll synthesis occurs that interrupts cell proliferation (Sharmin et al. 2013) which ultimately affects lipid accumulation within the microalgae cell (Ren et al. 2014). The effects of Mg²⁺ (0–0.73 g L⁻¹), Fe³⁺ (0–0.12 g L⁻¹), and Ca²⁺ (0–0.98 g L⁻¹) metal ions on lipid accumulation by Scenedesmus sp. was evaluated (Ren et al. 2014). The study exposed that the overall lipid content and lipid yield increased by up to 28.2% and 29.7%, respectively, when EDTA was introduced during the cultivation period (Ren et al. 2014). This means that primary metabolic pathways involved in lipid synthesis and breakdown in Scenedesmus sp. cells could be altered by Fe³⁺, Mg²⁺, and Ca²⁺ supplementation (Ren et al. 2014; Liu et al. 2008). Mg²⁺ (signaling ion) and Ca²⁺ (universal messenger) has been documented as an activator and mediator in regulation of CO₂ fixation in chloroplasts during the Calvin cycle. Literature shows that increasing Mg²⁺ could aid the function of Acetyl-CoA carboxylase that is the main controller of FA synthesis, to enhance neutral lipids in microalgae (Huang and Su 2014). Further, the effect of Mn²⁺ and Co²⁺ was checked on the lipid content of C. vulgaris with MnCl₂ amendment at different concentrations (2 μM, 10 μM, and 12 μM) and increased content of lipid by 14%, 16%, and 15%, respectively, was observed (Battah et al. 2015). It was found that lipid yield can be enhanced up to 25% more against control if Co(NO₃)₂ is amended at varying concentrations. An increase in 56.6% of total lipid content was noted in C. vulgaris, with five different Fe³⁺ concentrations (Liu et al. 2008). In another study, TAGs, acetone mobile polar lipids (AMPL), and phospholipids (PL) were the major lipids when C. vulgaris was treated with different concentrations of Cd (2 × 10⁻⁸; 10⁻⁷ M) and N (2.9 × 10⁻⁶ to 1.1 × 10⁻³ M) (Chia et al. 2013).

Role of nanoparticles in the lipid enhancement of microalgae

The use of several forms of metallic NPs within a range of 5–100 nm has been studied by several researchers, with different physical and chemical properties from those of the same metals on the macroscale (Dickinson et al. 2017; Alishah et al. 2017). The presence of NPs could improve the coefficient of mass transfer at the gas–liquid interface; thus, an increase in CO₂ content with NPs could influence the biomass and lipid amount in microalgae. The effect of silica and methyl-functionalized silica (SiO₂–CH₃) NPs was tested in C. vulgaris; it was observed that the NPs regulated the rate of gas–liquid mass transfer in the CO₂/medium culture system, and the biomass and lipid yield in the microalgal cells improved positively. Both NPs have been found to cause 31% and 145% increase in the volumetric mass transfer coefficient (kLa), respectively (Jeon et al. 2017). Further, the addition of silicon NPs increased dry biomass and fatty acid methyl esters (FAMEs) production, the highest dry biomass (1.49 g L⁻¹), and FAME productivity (1.005 g L⁻¹ day⁻¹) was attained by adding 0.2 wt% SiO₂–CH₃ NPs. Beyond, certain metallic NPs such as Ag, Se, Au, Pd, CuO, ZnO, and FeO emerged to be extremely toxic to microorganisms (Ji et al. 2011; Reichelt et al. 2012; Alishah et al. 2016a, 2016b). However, controlling the concentration of dose can reduce toxic effects. He et al. (2017) carried out an experiment to demonstrate the effect of carbon nanotubes (CNTs), α-Fe₂O₃ NPs, and MgO NPs on lipid accumulation in Scenedesmus obliquus, and depicted that when cells were exposed to 5 mg L⁻¹ CNTs, 5 mg L⁻¹ Fe₂O_3, and 40 mg L⁻¹ MgO NPs, lipid content improved up to 8.9%, 39.6%, and 18.5%, respectively. It has been found that when microalgae are supplemented with the right dosages of NPs, it induces oxidative stress and ultimately increases lipid yield. Similarly, the oxidative stress was given using TiO₂ NP and C. Highest FAME content (18.2 g L⁻¹ day⁻¹) perceived at a low dose of TiO₂ NP (0.1 g L⁻¹) that triggers and boosts lipogenesis in C. vulgaris UTEX 265 with a minimum induction time of 2 days (Kang et al. 2014).

Recent cultivation techniques for microalgal growth and lipid production

Two-stage cultivation strategies

To settle the differences between cell biomass and the production of desired product, an effective counter step is a two-stage cultivation strategy, which commits the first stage to optimal growing conditions to obtain full biomass, thus saving the second procedure for lipid accumulation under different conditions of stress. Lipids can generally be overproduced by microalgae due to established stress in the second stage of cultivation, like N-depletion (Kang et al. 2014), light (Khotimchenko and Yakovleva 2005), temperature (Renaud et al. 2002), concentration of salt (Wensel et al. 2014), or concentration of iron in the second phase (Liu et al. 2008). In an examination, the microalgal cells were raised under red light-emitting diodes (LEDs) (660 nm) initially to get maximum biomass, and then stress was applied using green LEDs (520 nm) in the second phase to trigger lipid accumulation (Wensel et al. 2014). Likewise, the two-stage culture method was used to increase the biomass of Isochrysis galbana with adequate nutrients, followed by growth under conditions of low salt stress, which increased the lipid quantity significantly from 24 to 47% (Ra et al. 2015). The lipid yield was 2.82 times greater in two-step process against lipid content obtained by single-stage batch cultivation in Nannochloropsis oculata (Su et al. 2011). To offset the cost of biofuel production, the other beneficial compounds obtained from microalgae such as carotenoids, antioxidants, anti-cancerous, vitamins, pigments, and biopharmaceuticals, positively support biorefineries (Borowitzka 2013). The efficient production of biofuel precursors and other important bioactive co-products such as secondary metabolites are easily achievable due to the low complex structure of microalgal cells (Lam and Lee 2012). High-light stress proves to be the best induction technique for carotenoids overproduction in various species. β-carotene content in microalgal species increases when cell growth is reduced in stress conditions (Lamers et al. 2012). Such a sequential production system is also applied to manufacture of the astaxanthin using Haematococcus pluvialis (Park et al. 2014). In the same way, in Scenedesmus obliquus, a two-stage process with an exchange in light intensity was also induced to boost lutein productivity (Ho et al. 2014a). Recently, a modified staged cultivation process was established to overcome the limitations related to growth of H. pluvialis, resulting in a 1.16-fold increment of biomass (Sun et al. 2017). In an updated finding, Amphiprora sp. is expected to be the best alternative in biodiesel production with 52.94 ± 0.42% oil yield when the cells were grown in controlled conditions at 65 °C (Jayakumar et al. 2021).

Co-culturing techniques

The co-culture system has proven to be the most effective method and the best alternative to reduce the production costs of biodiesel and other by-products. The co-culture system has been reported to lead to an increased FFAs released in the extracellular medium (Tate et al. 2013). N-starvation occurs rapidly in mixed cultures and ultimately improves lipid biosynthesis and other metabolites in vivo pathways (Mendes and Vermelho 2013).

Co-culture with microalgae

Different strains can synthesize certain compounds when grown simultaneously, which a single strain alone cannot produce. Until now, the combination of R. toruloides 21,167 and Saccharomycopsis fibuligera A11 has been synergistically produced compounds (inulases and amylases) which R. toruloides was unable to produce solely. The lipid yield of R. toruloides 21,167 during co-culture accounted for 64.9% of the dry cell and C16:0, C18:0, C18:1, and C18:2 were the major FAs synthesized (Gen et al. 2014). The simultaneous growth of Chlorella sp. U4341 and Monoraphidium sp. FXY-10 has been evaluated for lipid production under photoautotrophic conditions in a co-culture system. This combination allowed Monoraphidium sp. to enhance 20-fold lipid productivity (Liang et al. 2009; Bogen et al. 2013).

Co-culture of Chlorella sp. U4341 and Monoraphidium sp. FXY-10 under heterotrophic or mixotrophic conditions symbiotically improved lipid productivity. However, lipid production was low in photoautotrophic conditions (Zhao et al. 2014). Recently, it has been reported that Rhodotorula mucilaginosa TJY15 accumulated 53.16% (w/w) of oil content of 12.24 g⁻¹ when co-cultured with immobilized cells of P. guilliermondii strain 1 in a medium having 2.0% of inulin (Zhao et al. 2011). In a similar kind of study, it was noted that R. glutinis could generate high biomass and lipid content of 72% of dry weight when cultivated together with Spirulina platensis (Xue et al. 2010). Indeed, R. glutinis offered CO₂ to the microalgae, while later it acted as an oxygen generator.

Co-culture with bacteria

The association is well studied among Chlorella sp., cyanobacteria, and bacteria. Bacteria grow rapidly as compared to algae and, thus, facilitate the rapid division and disintegration of algae cells (Yadav et al. 2021). Pseudomonas sp. and Rhizobium sp. were responsible for the biocenosis of Botryococcus braunii, where Rhizobium sp., acted as a probiotic bacterium promoted the growth of B. braunii (Rivas et al. 2010). A positive link was also witnessed in C. vulgaris and C. sorokiniana co-cultivated with a growth-promoting bacterium, Azospirillum brasilense that increased the content of lipid as well as chlorophyll a and b, and b-carotene violaxanthin and lutein (De-Bashan et al. 2002). The combination of Rhizobium sp. KB10 and Botryococcus braunii enhanced growth of the algae by ninefold and also increased the amount of C18 (Oleate), which was finally patented by Oh and his team (Oh et al. 2014). Previously, an experiment was done in which mixed bacterial culture (activated sludge) and microalgae (Chlorella protothecoides UTEX-1806 and Ettlia sp. YC001) were used mutually. In this experiment, higher lipid production under photoheterotrophic conditions was documented against photoautotrophic conditions (28.7- and 17.3-fold) respectively (Ryu et al. 2014). Bacterial cultures are very well known for surfactants production which modify the hydrophobicity of the cell surface and influence the direct absorption of the substrate and lipid accumulation after that. Other bacterial capacities such as emulsification can, thus, also direct the production of lipid.

Co-culture with fungus

In a symbiotic relationship of fungi and algae, fungi consume carbon from algae through photosynthesis and shield algae by retaining water, and provide a niche for mineral nutrients (Zoller and lutzoni 2003). Co-cultivation of algae with fungus (A. fumigates) has additive and synergistic effects on biomass, lipid yield, and the efficiency of wastewater bioremediation (Wrede et al. 2014). Synergistic effects of co-cultivation of fungus (A. niger, A. oryzae, and C. echinulata) with freshwater green algae (C. vulgaris) on cell biomass and lipid content were studied by many researchers (Xie et al. 2013; Luo et al. 2013; Xia et al. 2011). Mutual cultivation of A. awamori was co-cultured with Chlorella minutissima MCC27 and C. minutissima UTEX2219 shown a considerable amount of lipid production in late exponential phase 22.12 ± 0.99% and 20.00 ± 1.00%, respectively. A similar finding was obtained when Spirulina platensis and R. glutinis were co-cultured (Rivas et al. 2010). Also, a 3.7- and 4.4-fold rise in lipid yield was noticed by axenic C. minutissima UTEX 2219 and A. awamori against C. minutissima UTEX 2219/A. awamori co-culture. Cheirsilp and his co-workers documented 5.7 times increment in biomass and 3.8 times increment in lipid yield in the co-culture system of R. glutinis and C. vulgaris when 3% pure glycerol and urea were added as C and N source (Wayne Orr et al. 2006). The system utilizing pure glycerol as an alternative to glucose could diminish the overall cost of production. C16:0 (31.26–35.02%) and C18:1 (21.14–24.21%) FAs were obtained as major compounds in the study, which suggests that co-culture system could be a reliable approach for biodiesel production (Cheirsilp et al. 2012).

Mechano-transduction mediated method

Mechano-transduction-induced lipid production system is based on the principle of mechano-transduction, in which lipid production is generated by cell membrane disruption, and then fabricated to provoke organic conversion of microalgae (Wayne Orr et al. 2006). Previous findings reveal that shear and compressive stress cause changes in microalgae metabolism particularly stress-induced changes in lipid metabolism, which occur via mechano-transduction transmitted by membrane alteration of the cell surface (Choi and Lee 2016). The latest study illustrates that direct compression/induced membrane distortion has caused microalgae to easily synthesized FFAs and convert these FFAs to TAG in a microfluidic system (Min et al. 2014). Unlike chemical inducers, the compression inductor is strong and controllable because of its stability and easy handling.

Hydrothermal liquefaction

Microalgae processing technique such as the hydrothermal liquefaction process is in high interest nowadays due to the advantages of no pre-drying. In this method, thermochemical conversion of wet biomass of microalgae to ‘bio-oil’ or ‘bio-crude’ and then to by-products (gaseous, liquid, and solid remains) takes place (Toor et al. 2011). Initially, the biomass is treated thermally under moist conditions at a high temperature (up to 200 °C) and up to 25 MPa pressures (Barreiro et al. 2013). Since microalgal biomass can be fed into the hydrothermal liquefaction reactor in a wet state, a comparatively high yield of products (lipids, proteins, and carbohydrates) is obtained that could convert into biofuel. The microalgal cells get dehydrated when going through the drying and freezing process and that is possible to increase the stability of organic matter before the typical hydrolysis reactions of hydrothermal liquefaction occur. On the other side, fresh microalgae have moisture and it may increase the contact surface between organic matter and water. Hydrothermal liquefaction of diverse microalgae, fresh, dried, and frozen biomass has been studied recently and the average yield of bio-oil obtained was 44.07%, 39.97%, and 39.65%, respectively (Vlaskin et al. 2018). Recently, lipid was harvested from diatoms using centrifugal force and pulse electric field techniques, as well as a relation to resonance energy (Khan et al. 2021).

Supplementation of growth-promoting agents

Besides above approaches, amendment of phytohormones also stimulates lipid and pigment production in microalgae by regulating the biochemical pathways. In general, it can act as a growth-promotion mediator in a single-stage cultivation process (Lu and Xu 2015). By controlling cell division, auxin enhances the growth of plants and microalgae (Del Pozo et al. 2005). In an experiment, the addition of 10⁻⁵ M diethyl aminoethyl hexanoate and indole-3-acetic acid to S. obliquus increased cell biomass by up to 1.9–2.5 times, whereas the amount of lipid to 100 mg g⁻¹ dry cell weight (Salama, et al. 2014). Improved growth and high lipid content were reported in C. vulgaris, C. pyrenoidosa, and Scenedesmus quadricauda in the presence of indole-3-acetic acid (Piotrowska-Niczyporuk and Bajguz 2014; Liu et al. 2016).

Genetic engineering approach towards lipid enhancement in microalgae

Using synthetic biology, system biology, and molecular biology methods, the fourth-generation biofuels concentrate on genetic modifications of microalgal genomes to raise lipid amounts without challenging their biomass (Shahid et al. 2020). The use of molecular biology to modify microalgae genetically is a better option for improving lipid productivity. Many researchers aimed at improving lipid accumulation by targeting major enzymes and genes responsible for the enhancement of lipid production by regulation in their expression (Lenka et al. 2016; Song et al. 2015). Improvements in lipid content have been observed in engineered microalgal cells due to the high expression of acetyl-CoA carboxylase gene that mainly controls the level of lipids in the cells (Radakovits et al. 2010). This gene is regulated to inhibit or overexpress one or several related genes to obtain the product of interest. In microalgae, these genes are responsible for photosynthesis, growth, development, and survival against unfavorable conditions such as at different pH, temperature, salinity, and facilitate lipid metabolisms (Dickinson et al. 2017). Many strains of microalgae have been genetically engineered for better TAGs accumulation or to intensify their intracellular lipid content includes T. pseudonana, C. cryptica, P. tricornutum, C. reinhardtii, C. ellipsoidea, Chlorella minutissima, N. gaditana, D. tertiolecta, C. reinhardtii (CC-849), N. oceanica and N. salina (Ho et al. 2014b; Banerjee et al. 2016; Fei et al. 2017; Kang et al. 2017; Wei et al. 2017; Wang et al. 2018).

A new transcription factor (bZIP1 and NobZIP1) was identified whose overexpression leads to significant elevation in lipid content in N. oceanica, without altering its physiological properties (Li et al. 2019). Chromatin immunoprecipitation–quantitative PCR analysis showed up- and down-regulation of NobZIP1 genes involved in lipogenesis and synthesis triggered lipid overproduction and secretion. UDP-glucose dehydrogenase was seen to change cell wall composition among the regulated genes, resulting in improved lipid secretion (Li et al. 2019). A detailed description of the effect of different stress/environmental factors and genetic modification in microalgae for the improvement of lipid accumulation is summarized in Table 1. In an investigation, the analysis of gene expression in response to P stress was determined by using Illumina RNA sequencing technology. Entirely 2897 differentially expressed genes were recorded, out of which 1853 and 1044 genes were correspondingly up- and down-regulated in response to P stress. Up-regulation of DGAT and pyruvate kinase encoding genes, FA biosynthesis, stimulation of carbohydrate metabolism route, and carbohydrate synthesis repression, probably to push the carbon flux toward TAGs biosynthesis was found to be the prime reason for an increase in overexpression of lipid production (Yang et al. 2018). Wang et al. worked on lysophosphatidic acyltransferase gene (c-lpaat) and Glycerol-3-phosphate dehydrogenase (c-gpd1) gene that are involved in lipid enhancement (Wang et al. 2018). The transcription levels of c-lpaat and c-gpd1 were amplified 5.3 and 8.6 times after triple heat shocks, as a result of an elevation of 44.5 and 67.5% lipid yield, respectively. Increased saturated FAs and monounsaturated FAs (C18 and C18:1) and decreased content of unsaturated FAs were noted. Thus, the finding suggests a new approach of combined use of genetic manipulation and intermittent heat shock to enhance lipid production in C. reinhardtii (Wang et al. 2018). Similarly, the addition of chemicals is also an effective and economically feasible strategy that can be easily accessible to large-scale industrial processes (Sun et al. 2019). Genetic engineering coupled with different chemical modulators can also be utilized to regulate the biosynthetic pathways of lipid production, for gene overexpression and blocking competing pathways (Sun et al. 2019). The major chemicals used to regulate or lipid enhancement in microalgae are malonate (Zhao et al. 2018), ethanolamine (Cheng et al. 2012), sethoxydim (Diao et al. 2019), fulvic acid (Che et al. 2017), EDTA (Singh et al. 2016), azide (Zalogin and Pick 2014), and diethyl aminoethyl hexanoate (Salama et al. 2014).

Regulation in biosynthetic pathways

In microalgae, the synthesis of FA and TAGs involves a chain of chemical reactions carried out by different enzymes. Acetyl-CoA carboxylase is the important enzyme involved in lipid synthesis; it converts Acetyl-CoA to the malonyl-CoA which is the main step in lipid biosynthesis. Hence, overexpression of acetyl-CoA carboxylase could be the best strategy for improvement in FA synthesis and could strain improvement in microalgae. It has been studied that microalgal cultivation under nutrients starvation stimulates the increased acetyl-CoA carboxylase production (Fan et al. 2015). The most significant enzymes involved in the TAGs biosynthesis pathways are Acyltransferases such as acyl-CoA: (LPAAT), acyl-CoA: (GPAT), and the acyl-CoA: diacylglycerol acyltransferase (DGAT) which can be focused on overexpression studies (Khozin-Goldberg and Cohen 2011). The lipid accumulation in the stress period is generally related to the amount of cell wet weight. Therefore, it is preferable to consume microalgal-specific inducible promoters, which can regulate lipid overexpression in the presence of sufficient biomass. Up-regulation of the DGAT gene controlled by the P starvation-inducible promoter. Sulfoquinovosyl diacylglycerol 2 in C. reinhardtii showed a 2.5-fold increase in TAGs production in the genetically modified strain, compared to the wild strain (Iwai et al. 2014). The genetically modified microalga (Phaeodactylum tricornutum) showed 2.5 times increase in lipid content and enzyme activity without compromising its biomass (Xue et al. 2015). Ahmad et al. documented enhancement of lipid content in genetically engineered Chlamydomonas reinhardtii, with an important enzyme diacylglycerol acyltransferase (BnDGAT2) from Brassica napus; this gene is mainly known for neutral lipid biosynthesis (Ahmad et al. 2015). The study revealed that approx. 7% decreased of saturated FAs in the transformed alga, whereas proportionately increased in unsaturated FAs in contrast to wild-type cells. Particularly high (up to 12%) α-linolenic acid was found in the transformed line (Ahmad et al. 2015). Currently, to discover the mechanisms underlying lipid accumulation in N-deprived conditions, de novo transcriptome profiling of S. acutus was performed. The transcriptome analysis has shown that glycolysis and starch degradation was up-regulated; in contrast, other pathways such as photosynthesis, gluconeogenesis, TAGs degradation, and starch synthesis were down-regulated in N-deprived state. It was concluded that during N-deprivation, carbon flux might shift toward FAs and TAGs synthesis, and down-regulation of TAG lipase genes may direct towards TAG accumulation (Sirikhachornkit et al. 2018).

Besides interchange, in the competitive metabolic pathways, lipid degradation is another approach that may direct to hyperaccumulation of lipids in microalgae (Liang and Jiang 2013). Carbon is the storage form of starch in microalgae using carbohydrate metabolism (Gonzalez-Fernandez and Ballesteros 2012). Thus, by inhibiting starch metabolism, the pathway will switch to lipid accumulation. It was also observed that up to 51% more TAGs (0.217 g mol⁻¹) were produced by starchless engineered S. obliquus against non-engineered strain (0.144 g mol⁻¹), cultivated in similar conditions (Breuer et al. 2014). One more investigation documented a ten-times increase in TAG accumulation when the enzyme ADP-glucose pyrophosphorylase that involves in the catalysis of committing step in starch metabolism was deactivated in a starchless mutant strain of Chlamydomonas (Li et al. 2010). A new starchless mutant of Chlorella pyrenoidosa STL-PI has also found elevated PFAs content (Ramazanov and Ramazanov 2006). Thus, these finding supports the competent strategy to enhance lipid biosynthesis by switching the starch biosynthesis pathway by suppressing principal genes involved in the pathway of starch biosynthesis. Also, inhibition of lipid catabolism could promote a high accumulation of lipid in microalgae. The 3.3 times higher lipid biosynthesis was seen in a mutant strain of Thalassiosira pseudonana after switching off particular multifunctional enzymes like acyltransferase/lipase/phospholipase (Trentacoste et al. 2013), but generally, this strategy is not very successful due to TAGs production in day or utilization at night time in order to promote cell growth and division by providing ATP. Consequently, blocking of β-oxidation pathway would check the consumption of TAGs during the dark followed by reduced growth of microalgal cells (Guarnieri and Pienkos 2015).

CRISPR–Cas-based genome editing

Genome editing is an important method of developing strains with the desired characteristics. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) associated with protein 9 (CRISPR–Cas9), random mutagenesis, Transcription Activator-Like Effector Nucleases (TALEN), and Zinc-Finger Nucleases (ZFN) are current applications for the genetic modification of microalgae. These are techniques primarily used to alter the sequence of genes, while the use of micro-RNA, small interfering RNA, and homologous recombination can suppress and activate the expression of genes (Aratboni et al. 2019; Sarma et al. 2021). While transferring DNA into microalgal cells, electroporation, and agitation with glass or silicon bead, carbide whiskers, biolistic microparticle bombardment, and Agrobacterium tumefaciens-mediated gene transfer were used (Shin et al. 2016; Kasai et al. 2015). The CRISPR/Cas9 system is a well-adapted genome editing tool, which is used to edit different sites in a genome altogether. In contrast to genetic engineering, genome editing allows inserting multiple genes and modifying the host genome in multiple sites and it is possible with the development of TALENs, zinc finger nucleases which can be modified to slice the genome at any desired site. This technique has been an uprising in genome editing due to its efficiency, specificity, and ease of use (Bharadwaj et al. 2020). Genome editing in microalgal species has been simplified with the efficient and successful application of the CRISPR–Cas technology (Tanwar et al. 2018). This system permits the regulation of multiple target genes and complex trait expressions through multigene engineering (Shrestha et al. 2018). This tool manifested a new era of genome editing in microalgae, though it is challenging due to toxicity by Cas9 expression as described in the case of Chlamydomonas; thus the use of inducible promoters and terminators could be another option (Jiang et al. 2014). Additionally, recombinant Cas9 protein and single-guide RNA could jointly be inserted as ribonucleoproteins (Cas9 RNPs) into the cells to reduce the probability of off-targeting and cytotoxicity (Kim et al. 2014; Shin et al. 2016). To resolve the cytotoxicity of Cas9 protein in cyanobacteria, Cas12a variant was used as an alternative (Naduthodi et al. 2018). This technique has been effectively tested in genome editing of model green algae like Chlamydomonas reinhardtii (Ferenczi et al. 2017; Kao and Ng 2017), Nannochloropsis sp. (Ma et al. 2017; Poliner et al. 2018; Verruto et al. 2018) and model diatoms like Phaeodactylum tricornutum (Nymark et al. 2016; Slattery et al. 2018) and Thalassiosira pseudonana (Hopes et al. 2016). The records on an increase in lipid yield in model microalgae (Chlamydomonas and Chlorella) have been documented in the genetic edition (Yang et al. 2016). Successfully, the first DNA modification was completed by Rochaix and Van Dillewijin in C. reinhardtii. In 1990, Roessler isolated acetyl-CoA carboxylase, an enzyme involved in FA biosynthesis; and then transformed it to the diatoms Cyclotella cryptica and Navicula saprophila (Sharma et al. 2012; Tabatabaei et al. 2011). However, the introduction of extra copies of the acetyl-CoA carboxylase gene to manipulate lipid accumulation in the diatom Cyclotella cryptica was the first experiment reported by Dunahay et al. (1996). Besides, Kang and his team identified the gene of a Wrinkled1 transcription factor type AP2 in Arabidopsis thaliana (AtWRI) that regulates lipid biosynthesis in plants, and this gene was transferred in Nannochloropsis salina (Kang et al. 2017). The results showed that the entire lipid content was increased by 36.5% in transformed cells in contrast to the wild-type strain. The transformation of the expression of the lipid accumulation regulator ZnCys by Cas9-mediated insertional attenuation was done in Nannochloropsis gaditana, which doubled the lipid production over a wild type (Ajjawi et al. 2017).

Genetic engineering advancement with the RNA silencing technique was found to be a better approach. The CrCO gene is a homologous gene of the circadian-regulated CONSTANS gene (CO) and crucial for photoperiod and flowering time is recently explored in C. reinhardtii (Deng et al. 2015; Serrano 2009). The suppression and overexpression of the CrCO gene have been found to alter lipid aggregation in microalgae and gene silencing can also increase 24% of lipids and TAGs (Trentacoste et al. 2013). Further, knockout of multifunctional lipase/phospholipase/acyltransferase genes improved the lipid quantity without disturbing the growth of the T. pseudonana diatom. It was noted that in the exponential growth process, antisense-mediated knockout mutants of the diatom had 3.3 times higher lipid than wild-type variants. Conversely, these methods have many drawbacks, including high cost of production, slow growth rate, low success rate of transformation, and partial genetic and characterization problems in the scaling up of microalgal cultures (Sharma et al. 2012; Tabatabaei et al. 2011; Singh et al. 2016). Genetically modified microalgae also have ethics regarding their release due to their environmental impacts. The intentional release of genetically modified microalgae into the natural environment must be examined in detail and approved by numerous international committees of experts before the release of genetically modified microalgae (Beacham et al. 2017).

Microalgal omics

In all biological studies, the word “omics” is used to describe and quantify broad datasets of structure, functions, and dynamics that involve organism computing to archive and interpret high-resolution molecular maps (Arora et al. 2018; Mishra et al. 2019). This study analyses all classes of molecules that are important to support main regulatory components and the mechanisms that define the physiological details of the development, adaptation, and resistance of microalgae against adverse environmental conditions (Hannon et al. 2010). The current growth of algal genomics in collaboration with other “omics” approaches has stepped up the capability to classify metabolic pathways and genes that are probable targets in the development of genetically modified microalgal strains with the best levels in lipid contents. The first microalgal genome sequence was available in 2004 for Cyanidioschyzon merolae, which is a native sulfur-rich acid hot spring microalga (Sasso et al. 2011). C. merolae with a single nucleus, plastid, and mitochondria has been confirmed to be the smallest genome of all photosynthetic eukaryotes to date (Matsuzaki et al. 2004). Afterward, the genome of the first model organism Chlamydomonas reinhardtii has been sequenced, and then the complete in silico acyl-glycerol pathway was then renovated that gave a clear basis for the analysis of lipid metabolism of green microalgae (Schuhmann et al. 2012). To better understand, the mechanisms in N-starvation-triggered lipid accumulation in algae, diverse omics approaches have been intensively studied (Fig. 3) (Blaby et al. 2013; Boyle et al. 2012; Guarnieri and Pienkos 2015; Arora et al. 2018).

Fig. 3.

Various omics approaches used in the regulation of metabolic pathways involved in TAG synthesis in microalgae

In recent years, use of omics technique to know lipid metabolism of algal in various stress conditions has displayed possible targets in diverse microalgae that can lead the way for targeted genetic engineering (Guarnieri and Pienkos 2015). Major omics-based studies are fundamentally based on the identification of gene targets for improving lipid production in microalgae. Modification in FA profile to include more stearic acids (C18:0) and oleic acid (C18:1) is also considered essential for improving properties of algal-derived Biofuel (Knothe 2009). Systems biology is a good option for a deep understanding of metabolic pathways by incorporating several ‘‘omics’’ platforms. Instead of an individual focus on genes, proteins, or metabolites at a time, it considers interconnections between every element during the regulation of biological activity (Rodriguez-moya and Gonzalez 2017). Many reports have recently executed ‘‘omics’’ approaches parallel to identify differentially expressed genes and enzymes behind various metabolic pathways that are possibly involved in lipid accumulation in microalgae. These genes and gene products are the main targets for reconstructing metabolic pathways for the development of engineered microbes with the required properties of biofuel (Lei et al. 2012; Misra et al. 2013; Radakovits et al. 2012; Valenzuela et al. 2012). Towards this direction, in silico studies amends the prediction of candidate genes whose combination determines the inherent fatty ester composition of microalgae (Hashimoto et al. 2008). These studies conclusively highlight the utilization of emerging ‘‘omics’’ approaches to provide greater insights into the structure of the genome and lipid metabolism of microalgae.

Conclusion

Microalgal-based biofuel will help to meet the growing global demand for renewable energy sources. It provides a low-cost alternative to high-priced biofuels. To reduce the processing costs, high biomass is undoubtedly needed to achieve high lipid yield. Various approaches such as genetic modification and metabolic changes have improved the lipid content that must be thoroughly investigated. More efforts on algal genome analysis are needed to make it easier to find novel genes and metabolic pathway products that are suitable for optimal biofuel development. Also, appropriate bioinformatics tools will become accessible for the organization, visualization, and logical interpretation of broad datasets. To achieve the highest lipid productivity, researchers have primarily focused on the individual effects of several parameters. However, it is preferable to use a combination of different methods and techniques for high lipid accumulation.

Author contributions

JR contributed to the collection of the literature, writing, and editing the manuscript drafts. PKG contributed to drawing the figures and editing the draft and also provided the critical inputs in the review discussion. VP and RP conceptualized, planned, and finalized the manuscript.

Declarations

Conflict of interest

Authors declare no competing interest concerning the work performed in the manuscript.