Abstract

   With rapid growth and high lipid contents, microalgae have become
   promising environmentally friendly candidates for renewable biodiesel
   and health supplements in our era of global warming and energy
   depletion. Various pathways have been explored to enhance algal lipid
   production, especially gene editing. Previously, we found that the
   functional loss of PhoD-type alkaline phosphatase (AP), a
   phosphorus-stress indicator in phytoplankton, could lead to increased
   lipid contents in the model diatom Phaeodactylum tricornutum, but how
   the AP mutation may change lipid composition remains unexplored. This
   study addresses the gap in the research and investigates the effects of
   PhoD-type AP mutation on the lipid composition and metabolic regulation
   in P. tricornutum using transcriptomic and lipidomic analyses. We
   observed significantly modified lipid composition and elevated
   production of fatty acids, lysophosphatidylcholine,
   lysophosphatidylethanolamine, ceramide, phosphatidylinositol
   bisphosphate, and monogalactosylmonoacylglycerol after PhoD_45757
   mutation. Meanwhile, genes involved in fatty acid biosynthesis were
   upregulated in mutant cells. Moreover, the mutant exhibited increased
   contents of ω-3 long-chain polyunsaturated fatty acid (LC-PUFA)-bound
   phospholipids, indicating that PhoD_45757 mutation could improve the
   potential bioavailability of PUFAs. Our findings indicate that AP
   mutation could influence cellular lipid synthesis and probably redirect
   carbon toward lipid production and further demonstrate that AP mutation
   is a promising approach for the development of high-value microalgal
   strains for biomedical and other applications.

   Keywords: alkaline phosphatase, microalgae, fatty acids, CRISPR/Cas9
   genome editing, lipid composition, PhoD

1. Introduction

   In face of the rising demand for energy and food, microalgae with fast
   growth, high protein, and high lipid contents have received
   intensifying interest in both bioenergy and health products
   [[30]1,[31]2]. Algae are carbon-neutral and renewable resources for
   both energy and high-value products [[32]3]. Microalgae grow rapidly
   (doubling within one day), and their oil content can reach up to 25–75%
   of their dry weight [[33]4]. The biodiesel production per unit area
   from microalgae is conservatively estimated to be more than 10 times
   that of typical terrestrial oil crops [[34]5]. Therefore, oleaginous
   algae may now be the most promising environmentally friendly candidates
   for renewable biodiesel [[35]3,[36]4]. Moreover, algal lipids are
   surprisingly diverse and unique in structure, including valuable
   species such as triglycerides (TAGs) and long-chain polyunsaturated
   fatty acids (LC-PUFAs) [[37]6], which can serve as a source of biofuel
   and health supplements, respectively.

   LC-PUFAs, including ω-3 and ω-6 LC-PUFAs, are indispensable nutrients
   that cannot be synthesized de novo by the human body [[38]7]. Omega-3
   LC-PUFAs such as eicosapentaenoic acid (EPA) and docosahexaenoic acid
   (DHA) have been shown to have health benefits on cardiovascular,
   lactation, brain, and visual functions and have thus been used as a
   nutraceutical additive [[39]8,[40]9]. Meanwhile, it has been shown that
   DHA-bound lysophosphatidylcholine (LPC) is the preferred carrier form
   of DHA in the brain [[41]10]. As for ω-6 LC-PUFAs, arachidonic acid
   (ARA) is an important component of biological membranes and a precursor
   of various bioactive lipids and eicosanoids (e.g., prostaglandins)
   [[42]11,[43]12]. Thus, ARA and its metabolites have important roles in
   skeletal muscle, the nervous system, and the immune system against
   allergies and parasites [[44]12]. In addition, the application of algal
   lipids in cosmetics [[45]13] and other industrial fields is emerging
   [[46]14]. Given the great application prospects of algal lipids, ways
   to enhance lipid production have been a hot topic of research.

   Multiple pathways have been reported to enhance microalgal lipid
   production. Firstly, the growth conditions, especially nutrient
   conditions, could be manipulated to modulate the cellular lipid profile
   of phytoplankton [[47]15,[48]16,[49]17]. Lipid abundance and
   composition in algae can be changed by nitrogen stress, phosphorus
   starvation, and high-iron conditions [[50]18,[51]19,[52]20]. For
   instance, phosphorus nutrient (P) deficiency could reprogram membrane
   lipid composition (replacing phospholipids with sulfolipids and
   nitrolipids) and significantly increase the lipid contents of algae
   [[53]21,[54]22,[55]23]. Secondly, increased lipid production can also
   be achieved by altering the expression of genes involved in the lipid
   biosynthesis pathway through molecular techniques. The suppression or
   overexpression of glycerol-3-phosphate acyltransferase (GPAT),
   long-chain acyl-CoA synthetase (LACS), acyl-CoA:diacylglycerol
   acyltransferase (DGAT), and 1-acyl-sn-glycerol-3-phosphate
   acyltransferase (AGPAT1) could elevate algal lipid biosynthesis
   [[56]24,[57]25,[58]26,[59]27]. Thirdly, with the aid of gene silencing
   (e.g., RNA interference) and knockout/knockdown techniques (e.g.,
   CRISPR-Cas9), researchers have found that the functional loss of
   certain genes not directly involved in lipid metabolic pathways can
   also affect oil yield [[60]17]. For instance, significant increases in
   cellular lipid synthesis were observed after gene silencing of
   UDP-glucose pyrophosphorylase, nitrate reductase, and
   phosphoenolpyruvate carboxykinase in the model diatom Phaeodactylum
   tricornutum [[61]17,[62]28,[63]29]. Recently, we found that the
   mutation of two different types of the alkaline phosphatase (AP) gene
   (both PhoA and PhoD), a P-stress indicator, could increase the lipid
   content in P. tricornutum [[64]30,[65]31]. However, it is not clear
   which lipid components were increased after AP null mutation.

   Thanks to recent advances in analysis tools such as mass spectrometry,
   lipidomics has grown rapidly [[66]32,[67]33]. Particularly, the
   combination of lipidomics with transcriptomics analysis provides a
   powerful tool to deepen our understanding of phytoplankton lipid
   metabolism [[68]25]. In this study, using combined
   transcriptomics-lipidomic analysis, we investigated the effects of
   PhoD-type AP (PhoD_45757) mutation on lipid composition and metabolic
   regulation in P. tricornutum. We observed significantly promoted lipid
   production and modified lipid composition after PhoD_45757 mutation,
   especially the induced production of LC-PUFAs and ω-3 (LC-PUFA)-bound
   phospholipids in P. tricornutum. Correspondingly, we also observed the
   upregulation of genes involved in fatty acid biosynthesis. With these
   findings, we demonstrate the high potential of AP mutagenesis for the
   development of high-value microalgae for health supplements and other
   applications.

2. Results

2.1. Lipidomic Profile in mPhoD Cells

   Generally, the lipidomic profile dramatically changed after PhoD_45757
   mutation ([69]Figure 1 and [70]Table S1). First, the total lipid
   content showed an 8% increase in PhoD_45757 mutant (mPhoD) cells
   compared to wild-type (WT) cells (t-test, p < 0.01) ([71]Figure 1). In
   total, 439 lipid molecules were identified in P. tricornutum ([72]Table
   S1) and further classified into seven categories based on the lipid
   metabolites and pathways strategy (LIPID MAPS) lipid classification
   system, including fatty acyls (6), glycerolipids (53),
   gylcerophospholipids (171), prenol lipids (1), saccharolipids (188),
   sphingolipids (16), and sterol lipids (4) ([73]Figure 1 and [74]Table
   S1). Among the seven categories, fatty acyls, sphingolipids,
   saccharolipids, prenol lipids, and glycerophospholipids showed
   2.0-fold, 0.4-fold, 0.3-fold, 0.2-fold, and 0.05-fold higher contents
   in mPhoD cells, respectively (t-test, p < 0.01 in saccharolipids,
   sphingolipids, and fatty acyls) ([75]Figure 1).

Figure 1.

   [76]Figure 1
   [77]Open in a new tab

   The content and components of the different lipid categories in WT and
   mPhoD cells. The lipid categories were divided based on LIPID MAPS. The
   average peak intensity values of each lipid molecule detected from each
   sample were calculated at the level of category and subclass and log2
   converted.

   At the level of lipid subclasses, PhoD_45757 mutation significantly
   induced the production of lysophosphatidylcholine (LPC),
   monogalactosylmonoacylglycerol (MGMG), ceramide (Cer),
   lysophosphatidylethanolamine (LPE), fatty acids (FAs),
   phosphatidylinositol bisphosphate (PIP2), and lysophosphatidylinositol
   (LPI) (t-test, p < 0.05 in all comparisons) ([78]Figure 2 and [79]Table
   S1). The most abundant lipid subclass in mPhoD cells was LPC, with a
   1.1-fold increase compared to that observed in WT cells (t-test, p <
   0.001) ([80]Figure 2a). Meanwhile, LPC accounted for up to 34.88% of
   the total lipid content in mPhoD cells, which was also significantly
   higher than that in the WT cells (17.45%) (t-test, p < 0.001)
   ([81]Figure 2b). Moreover, the contents of MGMG, Cer, LPE, FA, PIP2,
   and LPI in the mPhoD cells were 0.6-fold, 0.4-fold, 1.0-fold, 2.2-fold,
   11.7-fold, and 1.1-fold more enhanced than those in the WT cells,
   respectively (t-test, p < 0.05) ([82]Figure 2a). Accordingly, the
   proportion of MGMG, Cer, and FA in mPhoD cells was significantly higher
   than that in the WT cells (t-test, p < 0.05) ([83]Figure 2b).

Figure 2.

   [84]Figure 2
   [85]Open in a new tab

   The contents (a) and proportion (b) of different lipid subclasses in
   the WT and mPhoD cells. Only the lipid subclasses with the top 20
   contents are shown. LPC, lysophosphatidylcholine; PC,
   phosphatidylcholine; MGMG, monogalactosyl monoacylglycerol; TG,
   triglyceride; PE, phosphatidylethanolamine; SQDG, sulfoquinovosyl
   diacylglycerol; DG, diglyceride; Cer, ceramide; PS, phosphatidylserine;
   SQMG, sulfoquinovosyl monoacylglycerol; PG, phosphatidylglycerol; MGDG,
   monogalactosyl diacylglycerol; DGMG, digalactosyl monoacylglycerol;
   PIP, phosphatidylinositol phosphate; LPE, lysophosphatidylethanolamine;
   DGDG, digalactosyl diacylglycerol; LPG, lysophosphatidylglycerol; PI,
   phosphatidylinositol; Co, coenzyme; FA, fatty acid. * p < 0.05; ** p <
   0.01; *** p < 0.001.

2.2. Differential Lipids and Lipid Metabolism-Related DEGs in the mPhoD/WT
Comparison

   Using partial least-squares discriminant analysis (PLS-DA) based on the
   detected lipids in P. tricornutum, the principal components 1 and 2
   together can explain 77.81% of the overall variance ([86]Figure 3a).
   Furthermore, orthogonal partial least-squares discriminant analysis
   (OPLS-DA) was used to establish the relationship between lipid contents
   and algal strains (WT and mPhoD) and calculate the variable important
   for the projection (VIP) to identify differentially changed lipids in
   the mPhoD cells ([87]Figure 3b). Both PLS-DA and OPLS-DA showed large
   differences in lipidome between mPhoD and WT ([88]Figure 3a,b). In
   total, 174 lipid species were significantly differentially regulated in
   the mPhoD/WT comparison, including 88 induced and 86 depressed lipid
   species ([89]Figure 3c and [90]Table S2). Among them, all 37 lipid
   species belonging to PIP2 (1), MGMG (6), LPE (2), LPC (20), FA (3), and
   Cer (5) were all induced in the mPhoD/WT comparison ([91]Figure 3c).
   Moreover, these 37 differential lipids showed a positive correlation
   with each other ([92]Figure S1). The differential lipids were
   significantly enriched to four KEGG pathways, including α-linolenic
   acid metabolism, glycerophospholipid metabolism, the biosynthesis of
   unsaturated fatty acids, and arachidonic acid metabolism (p < 0.05)
   ([93]Figure 3d).

Figure 3.

   [94]Figure 3
   [95]Open in a new tab

   Differential lipids in the mPhoD/WT comparison. PLS-DA (a) and OPLS-DA
   (b) results of the WT and mPhoD groups. Ellipses represent 95%
   confidence intervals. (c) General distribution of 174 differential
   lipids in the mPhoD/WT comparison. Each point represents one
   differential lipid. Red fonts indicate significantly increased lipid
   subclasses in the mPhoD cells. (d) Significantly enriched KEGG pathway
   of differential lipids detected in the mPhoD/WT comparison.
   Abbreviations: TG, triglyceride; SQMG, sulfoquinovosyl
   monoacylglycerol; SQDG, sulfoquinovosyl diacylglycerol; PS,
   phosphatidylserine; PIP2, phosphatidylinositol bisphosphate; PG,
   phosphatidylglycerol; PE, phosphatidylethanolamine; PC,
   phosphatidylcholine; OAHFA, (O-acyl)-1-hydroxy fatty acid; MGMG,
   monogalactosyl monoacylglycerol; MGDG, monogalactosyl diacylglycerol;
   LPG, lysophosphatidylglycerol; LPE, lysophosphatidylethanolamine; LPC,
   lysophosphatidylcholine; GM3, ganglioside; FA, fatty acid; DGMG,
   digalactosyl monoacylglycerol; DGDG, digalactosyl diacylglycerol; DG,
   diglyceride; CL, cardiolipin; CerG2GNAc1, simple Glc series; CerG1,
   monogylcosylceramide; Cer, ceramide.

   Besides the lipidome, the transcriptomic analysis of WT and mPhoD cells
   was also conducted to identify transcriptomic regulations on lipid
   metabolism after PhoD_45757 mutation. A great difference in transcript
   levels after PhoD_45757 mutation was clearly reflected in the PCA
   analysis ([96]Figure 4a). A total of 118 DEGs were detected as
   participating in lipid metabolism in P. tricornutum ([97]Table S3).
   These DEGs were significantly enriched to 17 lipid metabolic pathways
   including fatty acid metabolism, glycerolipid metabolism, sphingolipid
   metabolism, and four pathways significantly enriched by the
   differential lipids ([98]Figure 4b).

Figure 4.

   [99]Figure 4
   [100]Open in a new tab

   Transcriptomic responses after PhoD_45757 mutation. (a) PCA results of
   the WT and mPhoD groups. Ellipses represent 95% confidence intervals.
   (b) Significantly enriched KEGG pathway of DEG involved in lipid
   metabolism in the mPhoD/WT comparison. Red fonts indicate four pathways
   significantly enriched by the differential lipids.

2.3. Increased FA, PUFAs, LPC, PIP2, and Cer Synthesis in Both Transcriptomic
and Lipidomic Levels after PhoD_45757 Mutation

   According to the increased FA content, we observed significant
   increases in three polyunsaturated fatty acid (PUFA) species in the
   mPhoD/WT comparison, including arachidonic acid (ARA, C20:4) which
   displayed 3.0-fold upregulation and stearidonic acid (SDA, C18:4) which
   displayed with 4.7-fold upregulation ([101]Figure 5a). Meanwhile, key
   enzymes throughout the fatty acid biosynthesis process showed
   upregulation in mPhoD cells, including acetyl-CoA carboxylase (ACC),
   [acyl-carrier-protein] S-malonyltransferase (FabD),
   3-hydroxyacyl-[acyl-carrier-protein] dehydratase (FabZ), and
   enoyl-[acyl-carrier protein] reductase (FabI) ([102]Figure 5b).
   Moreover, the acyl-lipid Δ12 desaturase (Δ12Des), Δ6 desaturase
   (Δ6Des), Δ4 desaturase (Δ4Des), and very-long-chain enoyl-CoA reductase
   (Δ9Elo) performing PUFA synthesis in the chloroplast and endoplasmic
   reticulum (ER) showed upregulation in mPhoD cells ([103]Figure 5b).

Figure 5.

   [104]Figure 5
   [105]Open in a new tab

   Upregulated fatty acid synthesis and other lipid metabolic regulation
   in mPhoD cells. (a) Increase in differential lipid species belonging to
   FA, LPC, LPE, LPG, PIP2, and Cer in mPhoD cells. (b) Upregulated fatty
   acid synthesis, phosphatidylinositol signaling system, and ceramide
   synthesis in mPhoD cells. Red and green fonts indicate upregulation and
   downregulation in mPhoD cells, respectively. PM, plasma membrane; ER,
   endoplasmic reticulum. The detailed information on genes shown in this
   figure can be found in [106]Table S4.

   As the most abundant subclass in mPhoD cells, all 20 LPC species were
   significantly increased after PhoD_45757 mutation ([107]Figure 5a).
   Notably, four ω-3 PUFA-bound LPCs were detected in the mPhoD/WT
   comparison, including one eicosatetraenoic acid (ETA)-LPC (LPC C20:4)
   with a 2.4-fold increase, two eicosapentaenoic acid (EPA)-LPCs (LPC
   C20:5) with 2.7- and 3.8-fold increases, and one docosahexaenoic acid
   (DHA)-LPC (LPC C22:6) with 2.3-fold increase in the mPhoD cells
   ([108]Figure 5a). Moreover, two more ω-3 PUFA-bound lysophospholipids,
   EPA-LPE (LPE C20:5) and DHA-LPG (LPG C22:6), were significantly induced
   after PhoD_45757 mutation ([109]Figure 5a).

   As crucial signaling molecules and cell membrane components, PIP2 and
   Cer were induced after PhoD_45757 mutation ([110]Figure 5a). PIP2
   showed up to a 12.7-fold increase in mPhoD cells, while five
   differential Cer species were upregulated by 2.1 to 3.8 folds in the
   mPhoD/WT comparison ([111]Figure 5a). Meanwhile, we also noticed the
   strong transcriptomic regulation of the phosphatidylinositol signaling
   system after PhoD_45757 mutation ([112]Figure 5b). The interaction
   between membrane phosphatidylinositol phosphates (PIs) was activated by
   the upregulation of PI4K (phosphatidylinositol 4-kinase),
   phosphatidylinositol 4-phosphatase (SAC1),
   1-phosphatidylinositol-4-phosphate 5-kinase (PIP5K), and inositol
   polyphosphate 5-phosphatase (INPP5B) in the mPhoD cells ([113]Figure
   5b). Meanwhile, the synthesis of IP[6] from IP[3] was promoted in the
   mPhoD cells as shown by the upregulation of inositol-polyphosphate
   multikinase (IPMK) and inositol-pentakisphosphate 2-kinase (IPPK)
   ([114]Figure 5b). Moreover, ceramide synthesis was promoted as
   3-dehydrosphinganine reductase (KDSR) and very-long-chain ceramide
   synthase (CERS) were upregulated in the mPhoD/WT comparison
   ([115]Figure 5b).

3. Discussion

   Microalgae are a promising source of fatty acids and lipids for human
   use as a health supplement [[116]1]. Nutritional and environmental
   stresses can significantly affect cellular lipid composition [[117]15].
   Meanwhile, advances in genetic editing techniques and multi-omics
   studies have also greatly facilitated algal lipid research
   [[118]34,[119]35]. AP is a typical indicator of P-starvation and DOP
   utilization in phytoplankton. However, recently, we found that
   PhoD_45757 (a PhoD-type AP) could potentially also regulate cellular
   nutrition homeostasis, cell cycle, and even lipid metabolism in P.
   tricornutum [[120]30]. Meanwhile, researchers have proposed that
   altering the expression of genes not directly belonging to the lipid
   biosynthesis pathway can achieve carbon redirection toward lipid
   production [[121]17]. In this study, increased lipid content and
   remodeled lipid composition in PhoD-mutated P. tricornutum were
   observed, among which the increases in LC-PUFAs and PUFA-bound
   lysophospholipids and ceramide were the most remarkable. Therefore, our
   results further confirm that PhoD_45757 mutation could influence
   cellular lipid synthesis and probably redirect carbon toward lipid
   production. Because AP mutagenesis has become routine, this provides a
   promising approach for algal genetic engineering to improve lipid- and
   fatty acid-related traits in this and other genetically tractable
   algae.

3.1. Improved Ceramide Synthesis after PhoD_45757 Mutation

   In the mPhoD cells, the ceramide content increased by 40%, and 5 of the
   14 detected ceramide species were significantly increased ([122]Figure
   2 and [123]Figure 5a, and [124]Table S1). Moreover, the major genes
   (KDSR and CERS) involved in the biosynthesis of ceramide were
   upregulated after PhoD_45757 mutation ([125]Figure 5b). In the previous
   report, the ceramide content was <0.5% of the total lipids in the
   northern diatoms Coscinodiscus concinnus and Porosira glacialis, while
   it was 1.6% in Chaetoceros socialis [[126]36]. Here, ceramide accounted
   for 3.9% of the total lipids in the mPhoD cells (3.0% in WT cells),
   which also showed a significant increase in the cellular proportion of
   ceramide after PhoD_45757 mutation ([127]Figure 2). Ceramide is an
   important member of the sphingolipids and plays an important role as a
   second messenger in cell signaling, cell differentiation, growth, and
   apoptosis [[128]37,[129]38]. We previously found that mPhoD cells
   showed a depressed cell cycle and decreased growth rate [[130]30]. It
   has been reported that the accumulation of ceramide by the inhibitors
   of ceramide metabolism could lead to cell cycle arrest at G2–M
   [[131]39]. Therefore, the enrichment of ceramide after PhoD_45757
   mutation indicates that PhoD_45757 could probably modulate the cell
   cycle by regulating the cellular ceramide contents in P. tricornutum
   [[132]30]. Furthermore, ceramides are now widely applied in cosmetic
   products for their skin moisturizing and barrier repair effects
   [[133]14]. Thus, the enhancement of ceramide production can also
   benefit the application of the PhoD_45757 mutant strain in cosmetic
   development. It is worth mentioning that, recently, ceramides isolated
   from red algae Hypnea musciformis were found to have anticancer effects
   and antiangiogenic and apoptotic effects in an experimentally induced
   mammary tumor [[134]40]. Therefore, the potential of PhoD_45757
   mutagenesis in anticancer drug development is worth further exploring.

3.2. PhoD_45757 Mutation Could Improve the Production and Potential
Bioavailability of PUFAs

   PhoD_45757 mutation promoted the expression of genes involved in fatty
   acid synthesis and led to a 2.2-fold increase in fatty acid content in
   P. tricornutum ([135]Figure 2 and [136]Figure 5). Accordingly, we
   observed upregulation of PUFA synthesis-related genes and increased
   PUFA contents (especially SDA and ARA) in mPhoD cells ([137]Figure 5).
   ARA is one of the major components of brain membrane phospholipids and
   has great nutritional importance for muscle growth and brain health in
   the human body [[138]12]. Therefore, the dramatic increase in ARA
   production here raises the possibility of exploiting the PhoD_45757
   mutant for ARA industrial production or dietary supplementation.

   Moreover, lysophospholipids, especially LPC, significantly increased in
   the mPhoD cells ([139]Figure 2). Among them, we noticed the abundant
   ω-3 LC-PUFA-enriched lysophospholipids (including LPC-EPA, LPC-DHA,
   LPE-EPA, and LPG-DHA) after PhoD_45757 mutation ([140]Figure 5a).
   Marine animals and plankton are the primary sources of ω-3 PUFA, and
   the ω-3 LC-PUFAs (in particular EPA and DHA) are of vital importance
   for human health [[141]41,[142]42]. The level of ω-3 LC-PUFA in the
   human body (mainly the brain) can be influenced by age, gender, and
   living habits, and researchers have found that dietary supplementation
   is effective in replenishing ω-3 LC-PUFA [[143]43]. Moreover, compared
   to the ω-3 LC-PUFA in triacylglycerol forms, ω-3 LC-PUFA bound to
   phospholipid showed higher bioavailability and bioactivity [[144]44].
   As a DHA carrier, LPC-DHA can cross the blood–brain barrier and
   efficiently transport DHA into the brain, enriching brain DHA levels
   and improving memory [[145]45,[146]46]. Similarly, the dietary addition
   of LPC-DHA significantly increased retinal DHA in mice [[147]47]. Thus,
   PhoD_45757 mutant strains with enriched DHA/EPA-bound lysophospholipids
   can be considered as a potential resource for dietary supplementation
   of the brain EPA and DHA. This implies the potential to exploit
   PhoD_45757 mutants for the dietary enhancement of brain function and
   the prevention of retinal disease. In addition, LPC-DHA has been
   recently reported to possess a cytotoxic effect on breast cancer cells
   [[148]48]. Therefore, the induction of LPC-DHA by AP mutation is
   promising for biomedical applications.

4. Materials and Methods

4.1. Mutant Culture and Cell Collection

   The P. tricornutum strain CCAP 1055/1 WT was obtained from the Culture
   Collection of Algae and Protozoa (Scottish Marine Institute, UK). The
   mutants of one PhoD-type AP (Phatr3_J45757, referred to as PhoD_45757)
   were created using CRISPR/Cas9 technology in our laboratory [[149]49],
   and the strain with higher lipid fluorescence, mPhoD7, was selected for
   this experiment (hereafter mPhoD). Both WT and mPhoD were cultured in
   f/2 medium prepared with autoclaved 0.22 µm filtered seawater (salinity
   30) at 20 °C with a photon flux of 100 µE m^−2 s^−1 under a 14:10 h
   light:dark cycle [[150]30,[151]50]. The batch culture experiment was
   set up with six biological replicates. After eight-day cultivation, >4
   × 10^8 cells from each culture were collected by centrifugation (5000
   rpm, room temperature, 10 min). The obtained cell pellets were washed
   with PBS twice and stored in 50% glycerin at −80 °C.

4.2. Lipid Extraction and UPLC-MS Analysis

   Firstly, mill magnetic beads, 800 µL of pre-chilled
   dichloromethane/methanol (3:1, v/v) precipitant, and 10 µL of the
   prepared internal standard were added to each sample. Then, the cell
   samples were ground using a TissueLyser for 5 min, sonicated in an ice
   bath for 10 min and left overnight in a −20 °C refrigerator. Next, 600
   µL of supernatant was collected after centrifugation (25,000× g, 4 °C,
   15 min) and lyophilized in a freeze drier. Subsequently, 120 µL of
   lipid-extracting solution (isopropyl alcohol: acetonitrile: water =
   2:1:1) was added and fully mixed (10 min), and the mixture was
   centrifuged (25,000× g, 4 °C, 15 min).

   A Waters UPLC I-Class Plus (Waters, Milford, MA, USA) Tandem Q Exactive
   High Resolution Mass Spectrometer (Thermo Fisher Scientific, Waltham,
   MA, USA) was used for lipid separation and detection (LC-MS/MS).
   Chromatographic separation was performed on a CSH C18 column (1.7 μm
   2.1 × 100 mm, Waters, Milford, MA, USA). The positive ion mode
   consisted of mobile phase A (containing 60% acetonitrile in water, 10
   mM ammonium formate, and 0.1% formic acid) and mobile phase B
   (consisting of 90% isopropanol, 10% acetonitrile, 10 mM ammonium
   formate, and 0.1% formic acid). The negative ion mode consisted of
   mobile phase A (containing 60% acetonitrile in water, 10 mM ammonium
   formate) and mobile phase B (containing 90% isopropanol, 10%
   acetonitrile, 10 mM ammonium formate). Elution was performed using the
   following gradients: 40~43% B over 0 to 2 min, 43~50% B over 2 to 2.1
   min, 50~54% B over 2.1 to 7 min, 54~70% B over 7 to 7.1 min, 70~99% B
   over 7.1 to 13 min, 99~40% B over 13 to 13.1 min, held constant at
   99~40% B over 13.1 to 15 min, and washed with 40% B over 13.1 to 15
   min. The flow rate was 0.4 mL per min and the injection volume was 5
   μL. The column temperature was maintained at 55 °C. Meanwhile, the
   primary and secondary mass spectrometry data acquisition was performed
   using Q Exactive (Thermo Fisher Scientific, Waltham, MA, USA). The full
   scan range was 70–1050 m z^−1 with a maximum ion injection time of 100
   ms and resolution of 70,000, and the automatic gain control (AGC)
   target for MS acquisitions was 3 × 10^6. The top three precursors were
   selected for subsequent MSMS fragmentation with a maximum ion injection
   time of 50 ms and resolution of 17,500, and the AGC was 1e5. The
   stepped normalized collision energy was 15, 30, and 45 eV. The sheath
   gas flow rate and aux gas flow rate of the ESI were 40 and 10,
   respectively. The spray voltage (|KV|) of positive- and negative-ion
   modes were 3.80 and 3.20, respectively. The capillary temperature and
   aux gas heater temperature were 320 °C and 350 °C, respectively.

4.3. Lipid Identification and Annotation

   The mass spectrometry data were analyzed using lipidsearch v.4.1
   (Thermo Fisher Scientific, Waltham, MA, USA) software to identify and
   quantify the lipid molecules detected in the mPhoD and WT cells. Lipid
   classification was based on The Lipid Metabolites and Pathways Strategy
   (LIPID MAPS) Lipid Classification System. Then, the KEGG pathway
   database was used for the taxonomic and functional annotation of the
   identified lipids [[152]51]. Furthermore, the overall differences in
   lipid species between mPhoD and WT were determined by partial
   least-squares–discriminant analysis (PLS-DA) and orthogonal partial
   least-squares discriminant analysis (OPLSDA) instead of traditional
   PCA. The fold change (FC) analysis and p-value were calculated by the
   t-test. Lipid species that met the following criteria can be considered
   as differential lipids: 1) variable importance in the projection (VIP)
   of the OPLS-DA model ≥ 1; 2) FC ≥ 1.2 or ≤0.83; and 3) p-value < 0.05.
   After that, the expression patterns and biological functions of the
   differential lipids in the mPhoD/WT comparison were further explored by
   pathway enrichment and correlation analyses.

4.4. Gene Expression Analysis and Differentially Expressed Genes
Identification

   Libraries for RNAseq were obtained from BioProject PRJNA841772 of the
   Short Read Archive (SRA) database in our previous report [[153]30]. The
   latest genome annotation of P. tricornutum strain CCAP 1055/1
   ([154]ftp.ensemblgenomes.org, accessed on 17 September 2023) was used
   to perform the clean reads annotation using HISAT2 (v2.1.0) and Bowtie2
   (v2.2.5) [[155]52,[156]53,[157]54,[158]55]. The gene expression level
   was quantified using RSEM (v1.2.8) [[159]56]. Principal component
   analysis (PCA) was analyzed on the Majorbio Cloud platform [[160]57].
   Then, differentially expressed gene detection was based on Poisson
   distribution. False discovery rate (FDR) was used for the correction of
   the p-value to the q-value [[161]58,[162]59]. After that, genes with
   |log[2] fold change (FC)| ≥1 and q-value ≤ 0.001 were defined as
   significantly differentially expressed genes (DEGs) in the mPhoD/WT
   comparison [[163]60,[164]61]. Using the phyper function in R software,
   the KEGG pathway enrichment analysis of DEGs with q-value ≤ 0.05 was
   regarded as significant enrichment.

4.5. Statistical Analysis

   In this study, the samples for the lipidomics analysis were in
   sextuplicate (n = 6) and samples for the transcriptomics analysis were
   in triplicate (n = 3). Means and standard deviations were calculated
   based on the biological replicates. One-way analysis of variance
   (ANOVA) was carried out using SPSS 16.0 (IBM, Armonk, NY, USA) to
   assess the statistically significant differences between WT and mPhoD
   at the level of p < 0.05.

5. Conclusions

   In this study, PhoD_45757 mutation led to enhanced lipid production in
   P. tricornutum, making the mutant strain a promising candidate for
   health supplements. Among the lipid components, the increases in fatty
   acids, LC-PUFAs (especially ARA), PUFA-bound lysophospholipids, and
   ceramide were observed in mutant cells. The increased production of
   PUFA-bound lysophospholipids, especially PUFA-bound LPC, indicates the
   improvement of PUFA bioavailability after PhoD_45757 mutation. Overall,
   the potential of AP mutation in microalgae lipids for biofuel and
   biomedical applications is well established, and its widespread
   application may be on the horizon.

Acknowledgments