Genome Characterization of the Oleaginous Fungus Mortierella alpina

  • Lei Wang ,

    Contributed equally to this work with: Lei Wang, Wei Chen

    Affiliations: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China, Tianjin Research Center for Functional Genomics and Biochip, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China, Key Laboratory of Molecular Microbiology and Technology of the Ministry of Education, TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin, People's Republic of China

  • Wei Chen ,

    Contributed equally to this work with: Lei Wang, Wei Chen

    Affiliation: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China

  • Yun Feng,

    Affiliations: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China, Tianjin Research Center for Functional Genomics and Biochip, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Yan Ren,

    Affiliation: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Zhennan Gu,

    Affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

  • Haiqin Chen,

    Affiliations: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China, Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

  • Hongchao Wang,

    Affiliation: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China

  • Michael J. Thomas,

    Affiliation: Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

  • Baixi Zhang,

    Affiliation: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China

  • Isabelle M. Berquin,

    Affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

  • Yang Li,

    Affiliation: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Jiansheng Wu,

    Affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

  • Huanxin Zhang,

    Affiliation: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Yuanda Song,

    Affiliation: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China

  • Xiang Liu,

    Affiliation: Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, South Carolina, United States of America

  • James S. Norris,

    Affiliation: Department of Microbiology and Immunology, Medical University of South Carolina, Charleston, South Carolina, United States of America

  • Suriguga Wang,

    Affiliation: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Peng Du,

    Affiliation: Tianjin Biochip Corporation, Tianjin Economic-Technological Development Area, Tianjin, China

  • Junguo Shen,

    Affiliation: Tianjin Biochip Corporation, Tianjin Economic-Technological Development Area, Tianjin, China

  • Na Wang,

    Affiliation: Tianjin Biochip Corporation, Tianjin Economic-Technological Development Area, Tianjin, China

  • Yanlin Yang,

    Affiliation: Tianjin Biochip Corporation, Tianjin Economic-Technological Development Area, Tianjin, China

  • Wei Wang,

    Affiliation: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China

  • Lu Feng,

    Affiliations: TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China, Tianjin Research Center for Functional Genomics and Biochip, Tianjin Economic-Technological Development Area, Tianjin, People's Republic of China, Key Laboratory of Molecular Microbiology and Technology of the Ministry of Education, TEDA School of Biological Sciences and Biotechnology, Nankai University, Tianjin, People's Republic of China

  • Colin Ratledge,

    Affiliation: Department of Biological Sciences, University of Hull, Hull, United Kingdom

  • Hao Zhang , (HZ); (YQC)

    Affiliation: State Key Laboratory of Food Science and Technology, School of Food Science and Technology, Jiangnan University, Wuxi, People's Republic of China

  •  [ ... ],
  • Yong Q. Chen (HZ); (YQC)

    Affiliation: Department of Cancer Biology, Wake Forest School of Medicine, Winston-Salem, North Carolina, United States of America

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Genome Characterization of the Oleaginous Fungus Mortierella alpina

  • Lei Wang, 
  • Wei Chen, 
  • Yun Feng, 
  • Yan Ren, 
  • Zhennan Gu, 
  • Haiqin Chen, 
  • Hongchao Wang, 
  • Michael J. Thomas, 
  • Baixi Zhang, 
  • Isabelle M. Berquin
  • Published: December 8, 2011
  • DOI: 10.1371/journal.pone.0028319


Mortierella alpina is an oleaginous fungus which can produce lipids accounting for up to 50% of its dry weight in the form of triacylglycerols. It is used commercially for the production of arachidonic acid. Using a combination of high throughput sequencing and lipid profiling, we have assembled the M. alpina genome, mapped its lipogenesis pathway and determined its major lipid species. The 38.38 Mb M. alpina genome shows a high degree of gene duplications. Approximately 50% of its 12,796 gene models, and 60% of genes in the predicted lipogenesis pathway, belong to multigene families. Notably, M. alpina has 18 lipase genes, of which 11 contain the class 2 lipase domain and may share a similar function. M. alpina's fatty acid synthase is a single polypeptide containing all of the catalytic domains required for fatty acid synthesis from acetyl-CoA and malonyl-CoA, whereas in many fungi this enzyme is comprised of two polypeptides. Major lipids were profiled to confirm the products predicted in the lipogenesis pathway. M. alpina produces a complex mixture of glycerolipids, glycerophospholipids and sphingolipids. In contrast, only two major sterol lipids, desmosterol and 24(28)-methylene-cholesterol, were detected. Phylogenetic analysis based on genes involved in lipid metabolism suggests that oleaginous fungi may have acquired their lipogenic capacity during evolution after the divergence of Ascomycota, Basidiomycota, Chytridiomycota and Mucoromycota. Our study provides the first draft genome and comprehensive lipid profile for M. alpina, and lays the foundation for possible genetic engineering of M. alpina to produce higher levels and diverse contents of dietary lipids.


Single cell oils have garnered great interest in recent years as a source of both energy and dietary fat. Mortierella alpina belongs to the subphylum of Mucoromycotina [1]. In its haploid life cycle, hyphae germinate from sporangiospores and then form sporangiophores (Figure 1A). Lipids accumulate inside the hyphae and, over time, form lipid droplets on the mycelia (Figure 1B). M. alpina can produce lipids amounting up to 50% of its dry weight [2], [3], [4], mostly composed of triacylglycerol with high quantities of arachidonic acid (AA; 20:4n-6) [5], [6]. It is used for the industrial production of AA for incorporation into infant formulas with a record of complete safety [6], [7], [8], [9].

Figure 1. Asexual lifecycle and lipid staining of M. alpina.

(A) Asexual lifecycle of the fungus. Haploid cells form sporangiophores, and sporangiospores germinate to hypha. (B) Fungal culture grown on PDA plate stained with 0.5% triphenoltetrazolium chloride. Lipid droplets are stained brown.


Unlike saturated fatty acids (SAFA) and mono-unsaturated fatty acids (MUFA), mammals cannot synthesize de novo, omega-6 or omega-3 polyunsaturated fatty acids (PUFA). Therefore, PUFA are essential fatty acids for human health and must be acquired via diet [10], [11], [12]. Fungi, however, such as M. alpina, can synthesize SAFA, MUFA, and PUFA de novo, and due to its high lipid content, provides an interesting model for studying lipid metabolism.

Some of the genes necessary for lipid synthesis in M. alpina have been cloned and partially characterized [13], [14], [15], [16], [17], and several biochemical reactions have been studied in detail [6], [18]. However, the molecular mechanism of efficient lipid biosynthesis is still not well understood in oleaginous fungi in general and in M. alpina in particular. The purpose of current study was to obtain M. alpina genome and transcript information, map its lipid metabolic pathway and analyze major lipid species, in order to better understand the mechanism of its efficient lipid biosynthesis.


Features of the M. alpina genome

In the present study, we have assembled the M. alpina genome, annotated its transcripts, analyzed its mitochondrial genome, and determined its relationship to other oleaginous fungi. The genome of M. alpina ATCC#32222 was sequenced with 31.75-fold coverage (Table S1) and the sequence deposited in public genome databases (DDBJ/EMBL/GenBank accession ADAG00000000, first version ADAG01000000). The assembly contains a total contig length of 38.38 Mb with a GC content of 51.72% (Table 1). Comparison between the genome assembly and EST sequences shows that 99.94% of the EST sequences can be aligned to the assembly, covering 99.16% of the total length of EST sequences. This confirms that the current assembly represents more than 99% of the coding region of the genome.

Table 1. Features of the M. alpina genome.


Annotation of the assembled genome sequence generated 12,796 gene models with an average transcript length of 1.5 kb. There is an average of 3.32 introns per multi-exon gene and 26% of the predicted genes are single-exon transcripts. The average exon size is 435 bp and the average intron size is 140 bp. Approximately 33% of the predicted genes encode proteins with no homologs in the NR protein databases. Among those genes with homologs in other organisms, 8,382 genes were mapped to the KEGG database (Table 1). The 12,796 predicted genes can be classified into 25 functional categories with approximately 4% of the predicted genes belonging to the lipid transport and metabolism category (Figure 2). Although no novel lipogenic genes were identified, sequencing revealed that the genome of M. alpina has a high degree of gene duplications, with approximately 50% of gene models belonging to multigene families (Table 2). Fungal genome comparison indicates that species in the Mucoromycotina subphylum have 50–70% genes in multigene families, whereas species in the Ascomycota, Basidiomycota and Chytridiomycota have 20–60% genes in multigene families (Table 2).

Figure 2. Distribution of predicted M. alpina proteins among functional groups.

Gene prediction and annotation were performed as described in the Materials and Methods. KOG category assignment is shown. X-axis represents percent of predicted gene models.


Table 2. Comparative analysis of multi-gene families.


The number of transfer RNA (tRNA) units is estimated at 228 (Table 1). Repetitive elements that can be explicitly classified account for 1.76% of the genome sequence (Table S2), a relatively low level compared with other sequenced fungi, which range between 1 and 20%. A high level of repetitive elements may accelerate species evolution.

The mitochondrial genome of M. alpina measures 67,445 bp and presents 36.2% sequence homology with the mitochondrial genome of M. verticillata [19]. The M. alpina mitochondrial genome encodes 28 tRNAs, 3 noncoding RNAs (rnl, rns and rnpB), 12 known proteins (NAD1, NAD2, NAD3, NAD4, NAD5, NAD6, ATP6, ATP8, ATP9, RPS3, COX1, COX3) and 13 uncharacterized proteins (Figure 3).

Figure 3. Map of M. alpina mitochondrial genome.

The outer circle represents the scale in kb. From the outside in, circles 1 and 2 indicate the location of ORF transcribed in a clockwise and counter-clockwise direction, respectively. Transcripts were predicted according to KOG categories. Circle 3 depicts tRNA and noncoding RNA.


To determine a possible evolutional relationship between oleaginous fungi (≥20% lipid/biomass dry weight) and non-oleaginous fungi, twelve orthologous proteins involved in lipid metabolism were identified among 43 genera and used for phylogenetic analysis. The phylogeny segregated fungal species of the Ascomycota, Mucoromycotina and Basidiomycota. Batrachochytrium dendrobatidis in the Chytridiomycota was clustered with species in the Mucoromycotina. Furthermore, it placed ten oleaginous fungi into four clusters (Figure 4). M. alpina, Rhizopus oryzae and Mucor circinelloides, sharing an average amino acid identity of 79%, were grouped in one cluster. Four Aspergillus genera, with an average amino acid identity of 89%, were placed in another. Fusarium oxysporum and Gibberella zeae (Fusarium graminearum) were also congregated with an average amino acid identity of 92%. Yarrowia lipolytica was a singleton in a separated branch. These results suggest that oleaginous fungi may have acquired their lipogenic capacity during evolution after the divergence of Ascomycota, Basidiomycota, Chytridiomycota and Mucoromycota.

Figure 4. Phylogenetic analysis.

Cladogram based on genes involved in fatty acid metabolic pathway. Orthologous proteins were defined as reciprocal best hit proteins with a minimum of 50% identity and 70% of the length of the query protein as calculated by the BLAST algorithm with a threshold value of E≤1×10−5. Phylogenies were analyzed based on 12 orthologous proteins identified among 43 genera and inferred from the resulting 98,765 amino character alignment using the Neighbor-Joining method. Numbers on the left are percent of bootstrapping, performed on 1000 replicates with alpha parameters and the fraction of invariant sites estimated once from the original data. Phytophthora infestans T30-4 in the Oomycetes was used as the outgroup. Scale bar shows evolutionary distances in replacements per site. The orthologous proteins used for this analysis were carnitine O-acetyltransferases, fatty acid desaturase 9, phospholipid:diacylglycerol acyltransferase, lysophosphatidate acyltransferase, acetyl-CoA carboxylase, 3-oxoacyl-[acyl-carrier-protein] synthase II, fatty acid desaturase 6I and 6II, fatty acid synthase, and 5-aminolevulinate synthase. Numbers in parentheses are reported lipid production in the corresponding fungus. Question marks indicate species in which lipid production is uncertain. Species in red are oleaginous, with lipid production greater than 20%.


Lipogenesis pathway

Because of its high capacity to produce lipid, we focused on M. alpina's lipid metabolic pathway. Based upon the genome information, a lipogenesis pathway was constructed, which mapped the utilization of glucose, generation of acetyl-CoA and NADPH, and biosynthesis of fatty acids, glycerolipids, glycerophospholipids, sphingolipids and sterols (Figure 5). M. alpina can grow on glucose as the single carbon source. The glycolysis pathway provides pyruvate, a key precursor for acetyl-CoA. The pentose phosphate pathway generates NADPH, a critical reductant for fatty acid synthesis, and other precursors needed for amino acid and nucleic acid biosynthesis. Most enzymes in the glycolysis and pentose phosphate pathways are encoded by 1 to 3 genes, except for hexokinase (HK) and phosphoenolpyruvate carboxykinase (PCK) which are each encoded by 6 genes (Figure 5). HK phosphorylates glucose to produce glucose-6-phosphate, the first step in most glucose metabolism pathways. PCK catalyzes the formation of phosphoenolpyruvate from oxaloacetate, and phosphoenolpyruvate is then converted by pyruvate kinase to pyruvate. Two genes encode a type of PCK that is GTP-dependent (EC4.1.1.32) and four genes encode another type of PCK that is ATP-dependent (EC4.1.1.49).

Figure 5. Predicted lipogenesis pathway in M. alpina.

The glycolysis, pentose phosphate pathway, fatty acid synthesis, tricarboxylic acid cycle, malate/pyruvate cycle, sterol, glycerophospholipid, sphingolipid and glycerolipid synthesis pathways are outlined. Lipids detected by lipidomics are highlighted in yellow. Enzyme names are indicated and followed in parentheses by the number of genes encoding them. Enzymes conventionally thought to occur in a given pathway but for which homologs were not found in M. alpina are followed by a question mark. Hexokinase (HK, EC2.7.1.1), glucose-6-phosphate 1-dehydrogenase (G6PD, EC1.1.1.49), 6-phosphogluconolactonase (PGLS, EC3.1.1.31), phosphogluconate dehydrogenase (PGD, EC1.1.1.44), ribose 5-phosphate isomerase (RPIA, EC5.3.1.6), ribulose-5-phosphate-3-epimerase (RPE, EC5.1.3.1), transketolase (TKT, EC2.2.1.1), transaldolase (TALDO, EC2.2.1.2), glucose-6-phosphate isomerase (GPI, EC5.3.1.9), phosphofructokinase (PFK, EC2.7.1.11), fructose-bisphosphatase (FBP, EC3.1.3.11), aldolase A fructose-bisphosphate (ALDOA, EC4.1.2.13), glyceraldehyde 3-phosphate dehydrogenase (GAPDH, EC1.2.1.12), phosphoglycerate kinase (PGK, EC2.7.2.3), triose-phosphate isomerase (TPI, EC5.3.1.1), phosphoglycerate mutase (PGAM, EC5.4.2.1), enolase (ENO, EC4.2.1.11), pyruvate kinase (PK, EC2.7.1.40), lactate dehydrogenase (LDH, EC1.1.1.27), phosphoenolpyruvate carboxykinase (PCK, EC4.1.1.32 and EC4.1.1.49), acetyl-CoA carboxylase (ACC, EC6.4.1.2), malonyl-CoA decarboxylase (MLYCD, EC4.1.1.9), fatty acid synthase (FASN, EC2.3.1.86), acyl-CoA synthetase (ACSL, EC6.2.1.3), acyl-CoA thioesterase (ACOT, EC3.1.2.27), fatty acid elongase (ELOVL, EC2.3.1.-), fatty acid delta 9 desaturase (FADS9, EC1.14.19.1), fatty acid delta 12 desaturase (FADS12, EC1.14.19.6), fatty acid delta 15 desaturase (FADS15, EC1.14.19.-), fatty acid delta 6 desaturase (FADS6, EC1.14.19.3), fatty acid delta 5 desaturase (FADS5, EC1.14.19.-), malate dehydrogenase (MDH, EC1.1.1.37), malic enzyme (ME, EC1.1.1.40), pyruvate carboxylase (PC, EC6.4.1.1), ATP-citrate lyase (ACLY, EC2.3.3.8), pyruvate dehydrogenase (PDH, EC1.2.4.1), dihydrolipoamide acetyltransferase (DLAT, EC2.3.1.12), citrate synthase (CS, EC2.3.3.1), aconitase (ACO, EC4.2.1.3), isocitrate dehydrogenase (IDH, EC1.1.1.41 and EC1.1.1.42), glutamate dehydrogenase (GLUD, EC1.4.1.2 and EC1.4.1.3), 2-oxoglutarate dehydrogenase (OGDH, EC1.2.4.2), dihydrolipoamide succinyltransferase (DLST, EC2.3.1.61), succinyl-CoA ligase (SUCLG, EC6.2.1.4 and EC6.2.1.5), succinate dehydrogenase (SDH, EC1.3.5.1), fumarase (FH, EC4.2.1.2), acetyl-CoA acetyltransferase (ACAT, EC2.3.1.9), hydroxymethylglutaryl-CoA synthase (HMGCS, EC2.3.3.10), 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR, EC1.1.1.34), mevalonate kinase (MVK, EC2.7.1.36), phosphomevalonate kinase (PMVK, EC2.7.4.2), mevalonate pyrophosphate decarboxylase (MVD, EC4.1.1.33), isopentenyl diphosphate isomerase (IDI, EC5.3.3.2), farnesyl diphosphate synthase (FDPS, EC2.5.1.10), farnesyl-diphosphate farnesyltransferase (FDFT, EC2.5.1.21), squalene epoxidase (SQLE, EC1.14.99.7), cycloartenol synthase (CAS, EC5.4.99.8), delta24-sterol methyltransferase (SMT, EC2.1.1.41), cycloeucalenol cycloisomerase (CEI, EC5.5.1.9), sterol 14-demethylase/cytochrome p450 family 51 (CYP51, EC1.14.13.70), delta14-sterol reductase/(ERG24, EC1.3.1.70), cholestenol isomerase/emopamil binding protein (EBP, EC5.3.3.5), sterol C5 desaturase (SC5DL, EC1.14.21.6), 7-dehydrocholesterol reductase (DHCR7, EC1.3.1.21), lanosterol synthase (LSS, EC5.4.99.7), C4 sterol methyl oxidase (SMO, EC1.14.13.72), hydroxysteroid (3-beta) dehydrogenase (HSD3B, EC1.1.1.170), hydroxysteroid (17-beta) dehydrogenase (HSD17B, EC1.1.1.270), serine palmitoyltransferase (SPTLC, EC2.3.1.50), 3-ketodihydrosphingosine reductase (KDSR, EC1.1.1.102), alkaline ceramidase (ACER, EC3.5.1.23), ceramide synthetase (CERS, EC2.3.1.24), sphingolipid delta-4 desaturase/degenerative spermatocyte homolog (DEGS, EC1.14.-.-), phosphatic acid phosphatase (PPAP, EC3.1.3.4), ceramide kinase (CERK, EC2.7.1.138), sphingomyelin phosphodiesterase (SMPD, EC3.1.4.12), sphingomyelin synthase (SGMS, EC2.7.8.27), UDP-glucose ceramide glucosyltransferase (UGCG, EC2.4.1.80), glucosylceramidase (GLCM, EC3.2.1.45), sphingosine kinase (SPHK, EC2.7.1.91), sphingosine-1-phosphate lyase (SGPL, EC4.1.2.27), CDP-diacylglycerol synthase (CDS, EC2.7.7.41), CDP-diacylglycerol inositol 3-phosphatidyltransferase (CDIPT, EC2.7.8.11), phosphatidylserine synthase (PTDSS, EC2.7.8.8), phosphatidylethanolamine methyltransferase (PEMT, EC2.1.1.17), phosphatidylserine decarboxylase (PISD, EC4.1.1.65), choline/ethanolamine phosphotransferase (CEPT, EC2.7.8.1), phospholipase C (PLC, EC3.1.4.3), glycerate kinase (GLYCTK, EC2.7.1.31), aldehyde dehydrogenase (ALDH, EC1.2.1.3), alcohol dehydrogenase (ADH, EC1.1.1.2), glycerol kinase (GK, EC2.7.1.30), glycerol-3-phosphate dehydrogenase (GPD, EC1.1.1.8), glycero-3-phosphate acyltransferase (GPAT, EC2.3.1.15), 1-acylglycerol-3-phosphate acyltransferase (AGPAT, EC2.3.1.51), phospholipase D (PLD, EC3.1.4.4), diacylglycerol kinase (DGK, EC2.7.1.107), diacylglycerol acyltransferase (DGAT, EC2.3.1.20), phospholipid diacylglycerol acyltransferase (PDAT, EC2.3.1.158), triglyceride lipase (GL, EC3.1.1.3).


Among the enzymes directly involved in fatty acid synthesis, acetyl-CoA carboxylase (ACC) converts acetyl-CoA to malonyl-CoA, and this conversion is a rate-limiting step in fatty acid biosynthesis. Fatty acid synthase (FASN) carries out enzymatic reactions necessary for the synthesis of SAFA [typically palmitic acid (PA, 16:0)] from acetyl-CoA and malonyl-CoA. Fatty acid delta 9 desaturase (FADS9) introduces the first double bond into SAFA producing MUFA. Fatty acid elongases (ELOVL) extend fatty acid carbon chains and other fatty acid desaturases introduce additional double bonds to generate PUFA. Fatty acids can exist as a free form or an acyl-CoA form, interconverted by acyl-CoA thioesterase (ACOT) and acyl-CoA synthetase (ACSL). There is one gene each encoding ACC, FASN, fatty acid delta 5 desaturase (FADS5), fatty acid delta 12 desaturase (FADS12) and omega-3 desaturase (FADS15). There are two genes encoding fatty acid delta 6 desaturase (FADS6), three for FADS9, three for ELOVL and two for ACOT; however, ACSL is encoded by six genes (Figure 5). A homolog for malonyl-CoA decarboxylase (MLYCD), which counters ACC action, was not identified. If M. alpina has no enzyme with MLYCD function, this could increase malonyl-CoA levels, thus favoring lipid synthesis.

Interestingly, in M. alpina, FASN is encoded as a single polypeptide with an acetyltransferase, β-enoyl reductase, dehydratase, malonyl/palmitoyl transferase, β-ketoacyl reductase, β-ketoacyl synthase, phosphopantetheine transferase activity and an acyl carrier protein domain (Figure 6).

Figure 6. FASN domain comparison.

Enzymatic domain organization of mammalian, S. cerevisiae and M. alpina Fasn is shown. Note: S. cerevisiae Fasn comprises two genes, Fas1 and Fas2, encoding two peptides. AT: acetyltransferase, ER: β-enoyl reductase, DH: dehydratase, MAT: malonyl-CoA-/acetyl-CoA-ACP transacylase, MPT: malonyl/palmitoyl transferase, ACP: acyl carrier protein, KR: β-ketoacyl reductase, KS: β-ketoacyl synthase, PPT: phosphopantetheine transferase, TE: thioesterase. Domains are not drawn to scale.


The tricarboxylic acid (TCA) cycle is important in generating ATP, NAD(P)H, and citrate. TCA derived citrate can be converted to acetyl-CoA through the action of ATP-citrate lyase (ACLY). The enzymes in the TCA cycle are encoded by two or more genes, with the exception of fumarase (FH) (Figure 5). Three genes encode a type of isocitrate dehydrogenase (IDH, EC1.1.1.41) that generates NADH, and three genes encode another type of IDH (EC1.1.1.42) that generates NADPH. Similarly, two genes encode a type of glutamate dehydrogenase (GLUD, EC1.4.1.2) that produces NADH and two genes encode another type of GLUD (EC1.4.1.3) that generates NADPH.

Besides the TCA cycle, there are two other major sources of NADPH: the pentose phosphate pathway, as mentioned earlier, and the malate/pyruvate cycle (Figure 5). Two malic enzyme genes were identified in M. alpina: one is identical to the gene coding for isoforms III/IV, which is presumed to be cytosolic and provides NADPH [20], [21], and the other is homologous to the malic enzyme gene coding for isoform II in Mucor circinelloides, which is not considered to be associated with fatty acid biosynthesis, but rather, is involved in anaerobic metabolism [22].

Enzymes involved in glycerolipid, glycerophospholipid, and sphingolipid synthesis are encoded by various numbers of genes. Most notably, there are 18 genes encoding triglyceride lipase (GL, EC3.1.1.3). Amino acid homology analysis suggests that eleven contain the class 2 lipase domain (pfam01674), one contains the class 3 lipase domain (pfam01764), three contain the PGAP1-like domain (pfam07819), two contain the CVT17 domain (COG5153), and one contains the DUF2424 domain (pfam10340).

Sterols can be synthesized from acetyl-CoA. Enzymes involved in this pathway are encoded by either 1 or 2 genes each (Figure 5). Fifteen cytochrome P450 genes were identified in M. alpina. Amino acid homology analysis suggests that their products are distantly related to the enzymes in family 51, which in other organisms have sterol 14-demethylase activity. Interestingly, homologs for cycloartenol synthase (CAS, EC5.4.99.8) and cycloeucalenol cycloisomerase (CEI, EC5.5.1.9) were not found.

Major lipid products

To confirm the lipid products predicted from our gene pathway analysis (Figure 5), total fatty acids, glycerolipids, glycerophospholipids, sphingolipids and sterol lipids were determined. M. alpina was cultured at 25°C and 12°C for 6 days. As expected, it synthesized a large quantity of lipid, representing approximately 45% of dry mycelial weight, and more than 50% of the fatty acids were AA (Table 3). There were no significant temperature-associated differences in the levels of SAFA or omega-6 PUFAs. Interestingly, omega-3 PUFA accumulation was 40-fold higher in cultures grown at 12°C than at 25°C (Table 3).

Table 3. Total fatty acid distribution*.


One outstanding characteristic of M. alpina is the efficient synthesis of glycerolipids, which are non-polar species stored as lipid droplets primarily in the form of triacylglycerols. According to our analysis, M. alpina synthesized more than 400 different triacylglycerols with various fatty acyl groups arranged on the glycerol moiety. Major species of triacylglycerols are shown in Figure 7. AA was the most common fatty acids incorporated into triacylglycerols, with a ratio of approximately 0.6–1.1 mol per mol triacylglycerols (ratios over 1 reflect the incorporation of more than one AA chain in a single triacylglycerol molecule). The most prominent triacylglycerol species were 56:8GL [which likely contained one palmitic acid (16:0) and two arachidonic acid (20:4) chains on the glycerol backbone] and 60:12GL [which likely contained three arachidonic acid chains].

Figure 7. Glycerolipid distribution.

Major glycerolipid (GL) species detected in M. alpina cultures grown at 12°C and 25°C (A) and percent distribution (B) are shown. The number before the colon indicates the total number of carbons in the three fatty acyl chains, and the number after the colon represents the total number of double bonds (e.g. 56:8 represents several species with a combined number of fatty acyl carbon atoms of 56 and 8 double-bonds).


There are four major types of glycerophospholipids: phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidyl-serine (PS) and phosphatidylinositol (PI). PC, PE, PS, PI and intermediate products, phosphatidic acid (PA) and lysophosphatidylcholine (lysoPC) were detected, but not diphosphatidylglycerol (Figure 8). Multiple species of PC, PE, PS, PI and PA were identified with various fatty acyl groups arranged on the sn-1 and sn-2 position of the glycerol backbone (Figure 8). Overall, between 0.4 and 0.6 mole of AA was incorporated per mole of glycerophospholipids. The molar ratios of AA in each type of glycerolipid were as follows: 0.6–0.7 in PC, 04–0.6 in PE, 0.3–0.7 in PS, 0.2 in PI, 0.6–0.8 in PA and 0.5 in LysoPC. Interestingly, an increased incorporation of highly unsaturated PUFAs into glycerophospholipids was observed at 12°C compared to 25°C (Figure 8). It is likely that this change, which results in an increased desaturation of glycerophospholipids, is an adaptation to enhance the plasma membrane fluidity at lower temperatures.

Figure 8. Glycerophospholipid distribution.

Phosphatidylcholine (PC), phosphatidylethanolamine (PE), phosphatidylserine (PS), phosphatidylinositol (PI), phosphatidic acid (PA), and lysophosphatidylcholine (LysoPC) species distributions are shown. Arrows indicate the major differences in glycerophospholipid between cultures at 12°C and 25°C.


M. alpina produced various species of ceramides and ceramide-1Ps, which comprised more than 80% of the sphingolipids (Figure 9). Other sphingolipids were also detectable, including sphingosine, sphingosine-1P, dihydrosphingosine and dihydrosphingosine-1P, but not sphingomyelin (Figure 9).

Figure 9. Sphingolipid distribution.

Sphingolipid species (A) and percent distribution (B) are shown. Cer: ceramide; Cer-1P: ceramide-1-phosphate; GluCer: glucosyl ceramide; Sph: sphingosine; Sph-1P: sphingosine-1-phosphate; dhSph: dihydrosphingosine; dhSph-1P: dihydrosphingosine-1-phosphate. Numbers in parentheses are percent of total sphingolipids.


In contrast to the complexity of glycerolipids, glycerophospholipids and sphingolipids, only two sterol lipids, desmosterol and 24(28)-methylene-cholesterol, were detected. Collectively, lipid profile results support the predicted lipogenesis pathway.


Microbial oil is a great source of energy and dietary fat. In the present study, we have assembled the first draft genome of M. alpina, partially mapped its lipogenesis pathway, and determined its major fatty acid, glycerolipid, glycerophospholipid, sphingolipid and sterol species.

M. alpina is one of many oleaginous fungi. It is unclear how oleaginous fungi evolved. Our phylogenic result, based upon lipid metabolic genes, is consistent with the phylogeny constructed on the basis of 440 core orthologs [23]. It suggests that the evolutionary history of lipid metabolic genes was largely dominated by vertical inheritance rather than lateral gene transfer. Our analysis also placed ten oleaginous fungi into four clusters, indicating that oleaginous fungi may have acquired their lipogenic capacity during evolution. In addition, the divergence level of lipid metabolic genes is lower than that of core orthologs. For instance, within the cluster of Schizosaccharomyces genus, the average amino acid identity is 64% for core orthologs [23] and 79% for lipid metabolic genes (our study). The data suggests that lipid metabolic genes have a lower mutation rate than the average rate of core orthologs. A low divergence of genes is indicative of their essentiality for the survival of organism.

One noticeable feature of the M. alpina genome is its high percentage (50%) of genes in multigene families, a feature shared by all three highly oleaginous fungi in the Mucoromycotina subphylum (Table 2). In the predicted M. alpina lipogenesis pathway (Figure 5), approximately 60% of genes are in multigene families. The number of genes encoding each enzyme varies widely.

Cytochrome P450s are heme-thiolate proteins involved in the oxidative degradation of various compounds. They can be divided into 4 classes, according to the method by which electrons from NAD(P)H are delivered to the catalytic site. Primary amino acid sequence identity between different P450s are relatively low, however their secondary structure is conserved. Several thousands of P450s have been identified among fungi [24]. Our study identified 15 cytochrome P450 genes in M. alpina. Protein BLAST analysis of M. alpina P450s shows homology between P450 family 83A1, 90A, abscisic acid 8′-hydroxylase and other cytochrome P450 related domains. However, it is unclear which cytochrome P450 is involved in sterol synthesis in M. alpina. None of the P450 genes in this organism presented strong homology to the cytochrome P450 family 51, which has sterol 14-demethylase activity in other organisms.

Eighteen lipases identified contain either the class 2 lipase, class 3 lipase, PGAP1-like, CVT17 or DUF2424 domain. Lipases with a class 2 or 3 domain may function as glyceride lipases which hydrolyze ester bonds in acylglycerols, releasing diacylglycerol, monoacylglycerol, glycerol and free fatty acids. Lipases with the PGAP1-like domain may work as a GPI inositol-deacylase. This deacylation is important for the efficient transport of GPI-anchored proteins from the endoplasmic reticulum to the Golgi body. Lipases with the CVT17 domain may operate as autophagic enzymes inside the cell vacuoles. The function of lipases with the DUF2424 domain is still unknown.

Cycloartenol synthase (CAS) and cycloeucalenol cycloisomerase (CEI) form cycloartenol and obtusifoliol intermediates in the synthesis of sterol lipids. While homologs to these enzymes were not identified, we cannot exclude their presence in M. alpina. It is possible that they have low homologies to proteins reported from other species.

Our lipogenesis pathway shows five enzymes in three different pathways that can generate NADPH (Figure 5), a critical reductant for lipid biosynthesis. It is unclear whether some, or all, of these enzymes play significant roles in the generation of NADPH. However, over-expression of malic enzyme (ME) can increase fatty acid synthesis in fungi [20], suggesting that ME may be a major generator of NADPH, and elevation of NADPH level is a mechanism to increase lipid production in fungi.

There are two types of fatty acid synthases: type-I FASN, found in fungi and mammals, are proteins containing several domains with distinct enzymatic activities [25], whereas type-II FASN, found in bacteria and plants, are a group of proteins with a single enzymatic activity, and multiple enzymes are required for fatty acid synthesis [26]. Although M. alpina has a type-I FASN gene, which like the mammalian FASN gene [27], [28], encodes a single polypeptide, the organization of the enzyme's domains is very different. Unlike the mammalian counterpart, the organization of domains in M. alpina FASN resembles that of the FASN in yeast, such as S. cerevisiae, S. pombe, and T. languinosus [29], [30], [31], where the domains are rearranged but on two polypeptides (Figure 6). However, the single peptide type-I FASN is not unique to Mortierella in the fungal kingdom; Ustilago maydis, Coprinopsis cinerea, Laccaria bicolor, and Omphalotus olearius also have a single peptide form of FASN.

M. alpina FADS12 and FADS15 catalyze the formation of omega-6 and omega-3 PUFA, respectively. M. alpina produces very low amounts of eicosapentaenoic acid (EPA, 20:5n-3) but maintains a high rate of AA synthesis, which in this study, constituted greater than 50% of the total fatty acids. Although the M. alpina genome shows extensive gene duplication, this differential capacity cannot be explained by gene numbers since there is only one gene for each desaturase. However, it is possible that expression levels or catalytic activity of FADS12 and FADS15 could account for the difference, as studies have demonstrated that forced expression of FADS15 in M. alpina 1S-4 drastically increases EPA production [32], [33]. Omega-6 and omega-3 PUFA are essential fatty acids which humans cannot synthesize de novo. Dietary omega-3 fatty acids mainly come from deep water fish. With increasing ocean pollution and decreasing fish populations, there is an urgent need to identify alternative sources of omega-3 PUFA. To this end, M. alpina may be engineered to produce omega-3 PUFA efficiently.

Concurrently, there is a worldwide effort in sequencing fungal genomes, however, most of the genomes sequenced (33/43) are in the Ascomycota phylum (Table 2). Our study will be the second published genome in the Mucoromycotina which, together with Rhizopus oryzae genome [34], will be useful for better characterization of fungi in this subphylum.

In summary, genome sequencing, pathway mapping and major lipid profiling have, for the first time, provided a comprehensive picture of lipid metabolism in M. alpina. It will be important to determine how gene expression is regulated during the lipogenesis in M. alpina, and how it is coordinated between the generation of precursor molecules such as pyruvate and acetyl-CoA, the production of reductant NADPH, and the synthesis of lipids. We are currently conducting transcriptome analysis is to address these issues.

Materials and Methods

Fungal culture

Mortierella alpina (#32222, American Type Culture Collection, Manassas, Virginia) was inoculated on PDA plates (BD DifcoTM Potato Dextrose Agar cat# 213400) and incubated for 20–30 days at 25°C. Five ml broth (20 g/L Glucose, 5 g/L Bacto yeast extract BD Biosciences cat# 212750, 1 g/L KH2PO4, 0.25 g/L MgSO4, 10 g/L KNO3) were added to three plates. Spores were gently scraped off the surface with a sterile loop, and then filtrated through a 40 micron cell strainer. Spores were concentrated by centrifuging at 12,000× g for 15 min, suspended in a small volume of broth, enumerated using a hemocytometer, and kept at −80°C in 30% glycerol at a density of approximately 107 spores/ml. Alternatively, three ml of unconcentrated spore suspension were directly added into 45 ml broth without KNO3 in a 250-ml flask covered with 8 layers of cheese cloth, and shaken at 200 rpm, 25°C for 5 days. Cultures were blended using a Braun hand blender for 5 sec/pulse, 8 pulses, then 0.3 g wet mycelia were inoculated into 45 ml broth without KNO3 in a 250-ml flask and shaken at 200 rpm, 25°C for 24 h. The above step was repeated once, by which time the whole fungal culture was in proliferative phase and ready for experiments. Mycelia were collected by filtration and weighed. Samples were snap-frozen in liquid nitrogen, pulverized and kept at −80°C until analysis.

Genome sequencing and analysis

Isolation of genomic DNA.

Genomic DNA of M. alpina was extracted using a modified protocol from Murray and Thompson [35]. Mycelia of M. alpina were ground to a fine powder with liquid nitrogen prior to extraction. The powder was gently dispersed in extraction buffer [1.4 M NaCl, 2% cetyltrimethyl ammonium bromide (CTAB), 100 mM Tris-HCl (pH 8.0), 20 mM EDTA, and 1% 2-mercaptoethanol] with a ratio of 10 ml buffer per gram of mycelia. The mixture was incubated for 30 min at 60°C with occasional gentle mixing. The extract was emulsified by gentle inversion with an equal volume of chloroform/isoamyl alcohol (24:1). After centrifugation at 12,000× g for 10 min, the aqueous phase was removed with a large bore pipette. One tenth volume of 10% CTAB, 1 M NaCl was added and incubated for 10 min at 60°C. The chloroform/isoamyl alcohol treatment was repeated. RNase was added to a final concentration of 100 µg/ml and incubated in a 65°C water bath for 30 min. The DNA sample was extracted with an equal volume of phenol/chloroform/isoamyl alcohol (25:24:1), and then with chloroform/isoamyl alcohol (24:1). DNA was precipitated with one tenth volume of 3 M sodium acetate (pH 5.5) and 2.5 volumes of absolute ethanol and was kept at −80°C for one h. After spinning at 12,000× g at 4°C for 30 min, the pellet was washed with 70% v/v ethanol, briefly dried and dissolved in an appropriate volume of TE buffer.

Sequencing and assembly.

High molecular weight DNA was used to construct plasmid libraries with inserts of 3–8 kb and fosmid libraries with inserts of 35–40 kb. In total, 92 Mb high quality paired-end data (Phred Q20) was generated by AB 3730 Sanger sequencing platform from the plasmid and fosmid libraries. In addition, 490 MB pyrosequencing data with average read length of 207 bp and 710 Mb pyrosequencing data with average read length of 308 bp were obtained using the Roche 454 Genome Sequencer FLX platform. Pyrosequencing reads were assembled by gsAssembler ( with default parameter settings [36] and assembled contigs were spliced into overlapping fragments of about 5 kb in length accompanied with quality values. Sanger sequencing reads from plasmid and fosmid clones were combined with overlapping fragments from pyrosequencing contigs [37]. The combined data were assembled by Phrap ( using default settings. Resequencing of low quality regions and closing of gaps were performed by walking on plasmid and fosmid clones and by PCR using custom primers designed by Consed [38].

Gene prediction and annotation.

Ab initio gene prediction was performed on the genome assembly by Augustus [39], GlimmerHMM [40], SNAP [41] trained by M. alpina ESTs from this study, and by GeneMark [42] without supervised training. A final set of gene models was selected by EVidenceModeler with equal weight for evidence from each gene prediction software [43]. Predicted genes were annotated by BLAST [44] searches against protein databases with E-value 1E-5: NR (, KOGs and COGs [45], KEGG [46], Swiss-Prot and UniRef100 [47], BRENDA [48], and by InterProScan [49] against protein domain databases with default parameter settings: Pfam [50], PRINTS [51], SMART [52], PROSITE [53], TigrPfam [54], PANTHER [55]. Pathway mapping was conducted by associating EC assignment and KO assignment with KEGG metabolic pathways based on BLAST search results. Multigene family analysis on predicted genes in the M. alpina genome and other sequenced fungal genomes was performed using OrthoMCL [56] with E-value 1E-20.

Repetitive elements.

Repetitive sequences in the genome assembly were identified by searching Repbase [57] using RepeatMasker ( with default parameter settings, and by de novo repetitive sequences search using RepeatModeler (​r.html) with default settings.

Non-coding RNAs.

Transfer RNAs were predicted by tRNAscan [58] using default settings. Ribosomal RNAs were identified by BLAST search with E-value 1E-10 of known rRNA modules in other fungal genomes. Other non-coding RNAs were predicted by searching the Rfam database [59] by Infernal ( using default parameter settings.

Mitochondrial genome.

A preliminary mitochondrial genome sequence was assembled as a single contig from pyrosequencing data using gsAssembler (version with default parameter settings and was compared with mitochondrial genome of M. verticillata [19]. Coding sequences, tRNA and rRNA were identified as described above.

Other fungal genomes.

Genome sequences of Candida albicans SC5314 [60], Rhizopus oryzae 99–880 [34], Aspergillus fumigatus Af293 [61] and A1163 [62], Aspergillus clavatus NRRL 1 [62], Ashbya gossypii ATCC10895 (Eremothecium gossypii) [63], Aspergillus nidulans FGSC A4 [64], Aspergillus niger CBS 513.88 [65] and ATCC1015 [66], Aspergillus oryzae RIB40 [67], Sclerotinia sclerotiorum 1980 UF-70, Botryotinia fuckeliana B05.10 and T4 [68], Fusarium oxysporum Fo5176 [69], Candida glabrata CBS138, Debaryomyces hansenii CBS767, Kluyveromyces lactis NRRL Y-1140 and Yarrowia lipolytica CLIB122 [70], Cryptococcus neoformans var. neoformans B-3501A [71], Gibberella zeae PH-1 (Fusarium graminearum) [72], Laccaria bicolor S238N-H82 [73], Malassezia globosa CBS 7966 [74], Magnaporthe grisea 70-15 [75], Neurospora crassa OR74A [76], Podospora anserina S mat+ [77], Scheffersomyces stipitis CBS 6054 (pichia stipitis CBS 6054) [78], Saccharomyces cerevisiae S288C [79], Schizosaccharomyces pombe 972h- [80], Ustilago maydis 521 [81], Vanderwaltozyma polyspora DSM 70294 [82], Schizosaccharomyces cryophilus OY26, Schizosaccharomyces japonicus yFS275 and Schizosaccharomyces octosporus ATCC4206 [83] were published. Genome sequences of, Nectria haematococca MPVI (Fusarium solani) (Joint Genome Institute), Trichoderma atroviride P1 (Joint Genome Institute), Trichoderma virens Gv29-8 (Joint Genome Institute), Batrachochytrium dendrobatidis JAM81 (Joint Genome Institute), Mucor circinelloides (Joint Genome Institute), Trichoderma reesei QM6a (Joint Genome Institute), (Broad Institute), Phanerochaete chrysosporium RP78 (Broad Institute), Neosartorya fischeri NRRL 181 (Broad Institute), Gibberella moniliformis 7600 (Fusarium verticillioides) (Broad Institute), Phytophthora infestans T30-4 (Broad Institute) were downloaded from the corresponding websites.

EST sequencing and analysis

An EST library was constructed from M. alpina cultured at 25°C and sequencing by the Illumina Genome Analyzer IIx platform, generating 0.64 Gb single-end sequences with read length of 36 bp and 1.14 Gb paired-end sequences with read length of 45 bp. The raw data was filtered by EULER [84] to remove reads and regions of low quality. Transcript sequences assembled by Velvet [85] with K-mer set to 25 were used to evaluate the completeness of the genome assembly by BLAST with E-value 1E-5. PASA [86] was used with default parameter settings to align transcript sequences to the genome sequence and 3,400 transcript sequences with associated gene structures were used to train ab initio gene prediction software.

Lipid analysis

Fatty acid analysis.

Approximately 20 mg of mycelia were used for each lipid extraction. Accurately weighed portions of pulverized mycelium were extracted using the method of Bligh and Dyer [87] under acidified conditions with pentadecanoic acid and heneicosanoic acid added as internal standards. The solvent from the fungal extract was removed under a stream of nitrogen. Lipids were saponified in 1 ml of freshly prepared 5% ethanolic potassium hydroxide at 60°C for 1 h under an argon atmosphere. After cooling, 1 ml of water was added to the samples and non-saponifiable lipids were extracted into 3 ml of hexane. The aqueous layer was acidified with 220 µl of 6 M hydrochloric acid and the fatty acids extracted into 3 ml of hexane. After removing the hexane in a stream of nitrogen, fatty acids were converted to methyl esters by first treating with 1 ml of 0.5 M methanolic sodium hydroxide at 100°C for 5 min under argon followed by 1 ml of 14% methanolic boron trifluoride at 100°C for 5 min under argon [88]. After cooling the sample was mixed with 2 ml of hexane followed by 4 ml of saturated aqueous sodium chloride. After separating the phases, aliquots of the hexane layers were diluted 24-fold with hexane and then analyzed by GC/MS. One µl was injected in the splitless mode onto a 30 m×250 µm DB-WAXETR column (Agilent Technologies, Santa Clara, California) with 0.25 µm film thickness. The temperature program was as follows: 100°C for 2 min, ramp to 200°C at 16°C per min, hold for one min, ramp to 220°C at 4°C per min, hold one min, ramp to 260°C at 10°C per min, and hold for 11 min. Helium was the carrier gas at a constant flow of 1.5 ml/min. The mass spectrometer was operated in positive-ion electron impact mode with interface temperature 260°C, source temperature 200°C, and filament emission 250 µA. Spectra were acquired from m/z 50 to 450 with a scan time of 0.433 s. Lower-boiling fatty acid methyl esters were quantified using the pentadecanoic acid internal standard, whereas higher-boiling methyl esters were quantified using the heneicosanoic acid internal standard.

Glycerolipid analysis.

Total lipid extracts from 20 mg pulverized mycelium were evaporated under a stream of nitrogen and redissolved in 1 ml of chloroform/methanol (1:1). Aliquots (50 µl) were evaporated under a stream of nitrogen, solubilized in Triton X-100, and enzymatically assayed for triacylglycerol content as described [89]. For relative quantification of triacylglycerol molecular species, 2 µl or 4 µl aliquots of the lipid extracts were diluted to 1 ml with methanol containing 1 µg/ml sodium formate. Samples were infused at 5 µl/min into the electrospray source of a TSQ triple quadrupole tandem mass spectrometer (Thermo Fisher Scientific, Waltham, Massachusetts). The spray potential was 3.8 kV. Nitrogen was used as the sheath gas and ion sweep gas at 15 and 1.5 psi, respectively. The ion transfer capillary was held at a temperature of 270°C and a potential of 35 V. Spectra of the [M+Na]+ ions were averaged over 1 min and corrected for carbon isotope effects. For qualitative identification of triglyceride molecular species the same sample solutions were infused with the same source parameters. The TSQ was programmed to acquire product ion spectra of the 50 most abundant [M+Na]+ ions in the sample. The collision gas pressure was 1.5 mTorr; collision energy (CE) was 40 eV. Each product ion spectrum was averaged over 10 s ( = 10 scans). For each sample the product ion spectrum lists were compiled into a single Excel spreadsheet using a modification of the Xcalibur software's export.exe utility (Xcalibur Inc., Vienna, Virginia). Excel functions were then used to interpret the daughter ion spectra. Peaks with m/z inconsistent with neutral loss of a free fatty acid were filtered out and then putative fatty acid nominal masses were calculated by rounding and subtraction. Lastly, an Excel macro identified molecular species by searching for sets of three putative fatty acid nominal masses that, together with the mass of the glycerol backbone and sodium, added up to the corresponding precursor ion mass.

Glycerophospholipid analysis.

Aliquots (50 µl) from the lipid extracts were digested with perchloric acid and assayed for phosphorus as described [90]. Using the lipid phosphorus data, aliquots of each sample amounting to 30 nmol of total phospholipid were analyzed by normal-phase high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS) using modifications of previously described methods [91], [92]. Samples (70 µl) were injected in chloroform:methanol (2:1) onto a μPorasil silica column, 3.9×300 mm; 10 µm particle size (Waters Corporation, Milford, Massachusetts). Phospholipids were eluted at 2 ml/min with the following gradient: 100% hexane/isopropanol/water/ammonium hydroxide (150:200:5:2, v/v) (Solvent A) for 1 min, ramp to 100% hexane/isopropanol/water/ammonium hydroxide (150:200:35:2, v/v) (Solvent B) over 59 min, hold 100% Solvent B for 10 min, and regenerate the column with 100% Solvent A for 20 min. A splitting tee directed 5% of the column effluent to the TSQ mass spectrometer (Thermo Fisher Scientific) for monitoring the elution of phospholipid classes. The remaining 95% of the column effluent was collected for analysis. The following phospholipid classes were detected as [M+H]+ ions by scanning in positive-ion mode: PE by common neutral loss of 141 Da with CE = 25 eV; PS by common neutral loss of 185 Da with CE = 22 eV; and choline-containing lipids (PC, lysoPC, and SM) as precursors of m/z 184.1 with CE = 35 eV. Phospholipids detected in negative-ion mode as [M-H] ions were PI, measured as precursors of m/z 241 with CE = 48 eV, and PA/PG/cardiolipin, measured as precursors of m/z 153 with CE = 40 eV. Scanning was initiated using the Scan Events function of Xcalibur 2.0 software. The spray potential was 4 kV in positive-ion mode and −2.8 kV in negative-ion mode with a nitrogen sheath gas pressure of 10 psi. The collision gas pressure was 0.8 mTorr and the ion transfer capillary temperature 270°C. Each phospholipid subclass was collected, evaporated under a stream of nitrogen, digested with perchloric acid, and then assayed for phosphorus. PA and PC co-eluted in this HPLC system but were separated by subjecting the collected PA/PC fraction to thin-layer chromatography on silica gel G plates developed with chloroform/methanol/ammonium hydroxide (60:35:8). PA and PC bands were visualized with iodine vapor, scraped from the plates, digested with perchloric acid, and assayed for phosphorus [90]. A profile mass spectrum was generated for each phospholipid class by averaging the appropriate precursor or neutral loss spectra acquired during the elution. Molecular species were quantified as mol% of the class by correcting the profile spectrum list for carbon isotope and mass-dependent ion throughput effects. For confirmation of molecular species assignments to the peaks in the profile spectrum, fresh aliquots of the lipid extracts were diluted to 10 µM total phospholipid in chloroform:methanol:water (49:49:2) and infused directly into the electrospray source at 5 µl/min. Samples were analyzed by a profile scan in precursor or neutral loss mode for the appropriate class followed by data-directed acquisition (DDA) product ion scans in negative-ion mode for fatty acyl anion products of the 25 most abundant ions in the profile scan. Product ion data were exported to Excel and interpreted in a manner analogous to that described above for triglycerides.

Sterol lipid analysis.

Non-saponifiable lipid fractions prepared as described above were evaporated under a stream of nitrogen then redissolved in 175 µl hexane for GC-MS analysis. Samples were analyzed on a 30 m×250 µm (0.25 µm film thickness) HP-5MS column with 1 µl injection volume in the splitless mode. Helium carrier gas was used at constant flow 1.2 ml/min. The temperature program was as follows: 170°C for 1 min, ramp to 280°C at 20°C/min, and then hold for 16 min. Mass spectrometer settings were as described above for fatty acid analysis, except that spectra were acquired from m/z 50 to 550 with a scan time of 0.517 s. For the quantification of known sterols, approximately 150 mg fresh weight mycelia were saponified in the presence of 25 µg of 5α-cholestane internal standard. Non-saponifiable lipids were extracted into 1 ml of hexane and analyzed on GC with flame ionization detection using a 6890N GC-FID (Agilent Technologies). Samples (1 µl) were injected directly onto a ZB-50 column 15 m×530 µm, 1 µm film thickness (Phenomenex, Torrance, California). The column was maintained at 250°C throughout the 15-min run. Hydrogen carrier gas was set at constant head pressure of 6 psi (flow rate approx. 15 ml/min). Nitrogen was the makeup gas, and the detector temperature was 280°C.

Sphingolipid analysis.

Analyses of ceramide species and sphingosine were performed on a Thermo Finnigan TSQ 7000, triple-stage quadrupole mass spectrometer (Thermo Fisher Scientific) operating in a Multiple Reaction Monitoring positive ionization mode as described [93], [94]. Samples were fortified with the internal standards and extracted into a one-phase solvent system with ethyl acetate/isopropanol/water (60:30:10%, v/v). 4 ml was separated followed by evaporation under nitrogen. After reconstitution in 100 µl of acidified (0.2% formic acid) methanol, samples were injected on the HP1100/TSQ 7000 LC/MS system and gradient-eluted from the BDS Hypersil C8, 150×3.2 mm, 3-µm particle size column, with 1.0 mM methanolic ammonium formate/2 mM aqueous ammonium formate mobile phase system. Peaks corresponding to the target analytes and IS were collected and processed using the Xcalibur software. Final results were calculated as the level of the particular SPLs normalized by sample weight and expressed as SPLs/g.

Supporting Information

Table S1.

Summary of genomic data.



Table S2.

Summary of repetitive sequences.




We would like to thank Miss Janel Suburu for reviewing the manuscript.

Author Contributions

Conceived and designed the experiments: LW WC HZ YQC. Performed the experiments: YF YR ZG HC HW MJT BZ YL JW HXZ YS XL JSN SW PD JS NW YY WW LF. Analyzed the data: LW YF HC IMB YL YQC. Wrote the paper: LW HC IMB CR HZ YQC.


  1. 1. Hibbett DS, Binder M, Bischoff JF, Blackwell M, Cannon PF, et al. (2007) A higher-level phylogenetic classification of the Fungi. Mycol Res 111: 509–547.
  2. 2. Bajpai PK, Bajpai P, Ward OP (1991) Arachidonic Acid Production by Fungi. Appl Environ Microbiol 57: 1255–1258.
  3. 3. Ratledge C, Wynn JP (2002) The biochemistry and molecular biology of lipid accumulation in oleaginous microorganisms. Adv Appl Microbiol 51: 1–51.
  4. 4. Ho SY, Jiang Y, Chen F (2007) Polyunsaturated fatty acids (PUFAs) content of the fungus Mortierella alpina isolated from soil. J Agric Food Chem 55: 3960–3966.
  5. 5. Jang HD, Lin YY, Yang SS (2005) Effect of culture media and conditions on polyunsaturated fatty acids production by Mortierella alpina. Bioresour Technol 96: 1633–1644.
  6. 6. Ratledge C (2004) Fatty acid biosynthesis in microorganisms being used for Single Cell Oil production. Biochimie 86: 807–815.
  7. 7. Burns RA, Wibert GJ, Diersen-Schade DA, Kelly CM (1999) Evaluation of single-cell sources of docosahexaenoic acid and arachidonic acid: 3-month rat oral safety study with an in utero phase. Food Chem Toxicol 37: 23–36.
  8. 8. Streekstra H (1997) On the safety of Mortierella alpina for the production of food ingredients, such as arachidonic acid. J Biotechnol 56: 153–165.
  9. 9. Hempenius RA, Lina BA, Haggitt RC (2000) Evaluation of a subchronic (13-week) oral toxicity study, preceded by an in utero exposure phase, with arachidonic acid oil derived from Mortierella alpina in rats. Food Chem Toxicol 38: 127–139.
  10. 10. Simopoulos AP (1999) Essential fatty acids in health and chronic disease. Am J Clin Nutr 70: 560S–569S.
  11. 11. Berquin IM, Edwards IJ, Chen YQ (2008) Multi-targeted therapy of cancer by omega-3 fatty acids. Cancer Lett 269: 363–377.
  12. 12. Chen YQ, Edwards IJ, Kridel SJ, Thornburg T, Berquin IM (2007) Dietary fat-gene interactions in cancer. Cancer Metastasis Rev 26: 535–551.
  13. 13. Michaelson LV, Lazarus CM, Griffiths G, Napier JA, Stobart AK (1998) Isolation of a Delta5-fatty acid desaturase gene from Mortierella alpina. J Biol Chem 273: 19055–19059.
  14. 14. Sakuradani E, Kobayashi M, Shimizu S (1999) Delta6-fatty acid desaturase from an arachidonic acid-producing Mortierella fungus. Gene cloning and its heterologous expression in a fungus, Aspergillus. Gene 238: 445–453.
  15. 15. Sakuradani E, Kobayashi M, Shimizu S (1999) Delta 9-fatty acid desaturase from arachidonic acid-producing fungus. Unique gene sequence and its heterologous expression in a fungus, Aspergillus. Eur J Biochem 260: 208–216.
  16. 16. Sakuradani E, Kobayashi M, Ashikari T, Shimizu S (1999) Identification of Delta12-fatty acid desaturase from arachidonic acid-producing mortierella fungus by heterologous expression in the yeast Saccharomyces cerevisiae and the fungus Aspergillus oryzae. Eur J Biochem 261: 812–820.
  17. 17. Sakuradani E, Abe T, Iguchi K, Shimizu S (2005) A novel fungal omega3-desaturase with wide substrate specificity from arachidonic acid-producing Mortierella alpina 1S-4. Appl Microbiol Biotechnol 66: 648–654.
  18. 18. Ratledge C (2002) Regulation of lipid accumulation in oleaginous micro-organisms. Biochem Soc Trans 30: 1047–1050.
  19. 19. Seif E, Leigh J, Liu Y, Roewer I, Forget L, et al. (2005) Comparative mitochondrial genomics in zygomycetes: bacteria-like RNase P RNAs, mobile elements and a close source of the group I intron invasion in angiosperms. Nucleic Acids Res 33: 734–744.
  20. 20. Zhang Y, Adams IP, Ratledge C (2007) Malic enzyme: the controlling activity for lipid production? Overexpression of malic enzyme in Mucor circinelloides leads to a 2.5-fold increase in lipid accumulation. Microbiology 153: 2013–2025.
  21. 21. Zhang Y, Ratledge C (2008) Multiple isoforms of malic enzyme in the oleaginous fungus, Mortierella alpina. Mycol Res 112: 725–730.
  22. 22. Li Y, Adams IP, Wynn JP, Ratledge C (2005) Cloning and characterization of a gene encoding a malic enzyme involved in anaerobic growth in Mucor circinelloides. Mycol Res 109: 461–468.
  23. 23. Tatusov RL, Natale DA, Garkavtsev IV, Tatusova TA, Shankavaram UT, et al. (2001) The COG database: new developments in phylogenetic classification of proteins from complete genomes. Nucleic Acids Res 29: 22–28.
  24. 24. Cresnar B, Petric S (2011) Cytochrome P450 enzymes in the fungal kingdom. Biochim Biophys Acta 1814: 29–35.
  25. 25. Leibundgut M, Maier T, Jenni S, Ban N (2008) The multienzyme architecture of eukaryotic fatty acid synthases. Curr Opin Struct Biol 18: 714–725.
  26. 26. White SW, Zheng J, Zhang YM, Rock CO (2005) The structural biology of type II fatty acid biosynthesis. Annu Rev Biochem 74: 791–831.
  27. 27. Maier T, Jenni S, Ban N (2006) Architecture of mammalian fatty acid synthase at 4.5 A resolution. Science 311: 1258–1262.
  28. 28. Maier T, Leibundgut M, Ban N (2008) The Crystal Structure of a Mammalian Fatty Acid Synthase. Science 321: 1315–1322.
  29. 29. Jenni S, Leibundgut M, Maier T, Ban N (2006) Architecture of a fungal fatty acid synthase at 5 A resolution. Science 311: 1263–1267.
  30. 30. Jenni S, Leibundgut M, Boehringer D, Frick C, Mikolasek B, et al. (2007) Structure of fungal fatty acid synthase and implications for iterative substrate shuttling. Science 316: 254–261.
  31. 31. Lomakin IB, Xiong Y, Steitz TA (2007) The crystal structure of yeast fatty acid synthase, a cellular machine with eight active sites working together. Cell 129: 319–332.
  32. 32. Ando A, Sumida Y, Negoro H, Suroto DA, Ogawa J, et al. (2009) Establishment of Agrobacterium tumefaciens-mediated transformation of an oleaginous fungus, Mortierella alpina 1S-4, and its application for eicosapentaenoic acid producer breeding. Appl Environ Microbiol 75: 5529–5535.
  33. 33. Sakuradani E, Shimizu S (2009) Single cell oil production by Mortierella alpina. J Biotechnol 144: 31–36.
  34. 34. Ma LJ, Ibrahim AS, Skory C, Grabherr MG, Burger G, et al. (2009) Genomic analysis of the basal lineage fungus Rhizopus oryzae reveals a whole-genome duplication. PLoS Genet 5: e1000549.
  35. 35. Murray MG, Thompson WF (1980) Rapid isolation of high molecular weight plant DNA. Nucleic Acids Res 8: 4321–4325.
  36. 36. Margulies M, Egholm M, Altman WE, Attiya S, Bader JS, et al. (2005) Genome sequencing in microfabricated high-density picolitre reactors. Nature 437: 376–380.
  37. 37. Goldberg SM, Johnson J, Busam D, Feldblyum T, Ferriera S, et al. (2006) A Sanger/pyrosequencing hybrid approach for the generation of high-quality draft assemblies of marine microbial genomes. Proc Natl Acad Sci U S A 103: 11240–11245.
  38. 38. Gordon D, Desmarais C, Green P (2001) Automated finishing with autofinish. Genome Res 11: 614–625.
  39. 39. Stanke M, Waack S (2003) Gene prediction with a hidden Markov model and a new intron submodel. Bioinformatics 19: Suppl 2ii215–225.
  40. 40. Majoros WH, Pertea M, Salzberg SL (2004) TigrScan and GlimmerHMM: two open source ab initio eukaryotic gene-finders. Bioinformatics 20: 2878–2879.
  41. 41. Korf I (2004) Gene finding in novel genomes. BMC Bioinformatics 5: 59.
  42. 42. Ter-Hovhannisyan V, Lomsadze A, Chernoff YO, Borodovsky M (2008) Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res 18: 1979–1990.
  43. 43. Haas BJ, Salzberg SL, Zhu W, Pertea M, Allen JE, et al. (2008) Automated eukaryotic gene structure annotation using EVidenceModeler and the Program to Assemble Spliced Alignments. Genome Biol 9: R7.
  44. 44. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25: 3389–3402.
  45. 45. Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, et al. (2003) The COG database: an updated version includes eukaryotes. BMC Bioinformatics 4: 41.
  46. 46. Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32: D277–280.
  47. 47. Wu CH, Apweiler R, Bairoch A, Natale DA, Barker WC, et al. (2006) The Universal Protein Resource (UniProt): an expanding universe of protein information. Nucleic Acids Res 34: D187–191.
  48. 48. Chang A, Scheer M, Grote A, Schomburg I, Schomburg D (2009) BRENDA, AMENDA and FRENDA the enzyme information system: new content and tools in 2009. Nucleic Acids Res 37: D588–592.
  49. 49. Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, et al. (2005) InterProScan: protein domains identifier. Nucleic Acids Res 33: W116–120.
  50. 50. Finn RD, Mistry J, Schuster-Bockler B, Griffiths-Jones S, Hollich V, et al. (2006) Pfam: clans, web tools and services. Nucleic Acids Res 34: D247–251.
  51. 51. Attwood TK, Bradley P, Flower DR, Gaulton A, Maudling N, et al. (2003) PRINTS and its automatic supplement, prePRINTS. Nucleic Acids Res 31: 400–402.
  52. 52. Letunic I, Copley RR, Pils B, Pinkert S, Schultz J, et al. (2006) SMART 5: domains in the context of genomes and networks. Nucleic Acids Res 34: D257–260.
  53. 53. Hulo N, Bairoch A, Bulliard V, Cerutti L, De Castro E, et al. (2006) The PROSITE database. Nucleic Acids Res 34: D227–230.
  54. 54. Haft DH, Selengut JD, White O (2003) The TIGRFAMs database of protein families. Nucleic Acids Res 31: 371–373.
  55. 55. Thomas PD, Campbell MJ, Kejariwal A, Mi H, Karlak B, et al. (2003) PANTHER: a library of protein families and subfamilies indexed by function. Genome Res 13: 2129–2141.
  56. 56. Li L, Stoeckert CJ Jr, Roos DS (2003) OrthoMCL: identification of ortholog groups for eukaryotic genomes. Genome Res 13: 2178–2189.
  57. 57. Jurka J, Kapitonov VV, Pavlicek A, Klonowski P, Kohany O, et al. (2005) Repbase Update, a database of eukaryotic repetitive elements. Cytogenet Genome Res 110: 462–467.
  58. 58. Lowe TM, Eddy SR (1997) tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 25: 955–964.
  59. 59. Griffiths-Jones S, Moxon S, Marshall M, Khanna A, Eddy SR, et al. (2005) Rfam: annotating non-coding RNAs in complete genomes. Nucleic Acids Res 33: D121–124.
  60. 60. Braun BR, van Het Hoog M, d'Enfert C, Martchenko M, Dungan J, et al. (2005) A human-curated annotation of the Candida albicans genome. PLoS Genet 1: 36–57.
  61. 61. Nierman WC, Pain A, Anderson MJ, Wortman JR, Kim HS, et al. (2005) Genomic sequence of the pathogenic and allergenic filamentous fungus Aspergillus fumigatus. Nature 438: 1151–1156.
  62. 62. Fedorova ND, Khaldi N, Joardar VS, Maiti R, Amedeo P, et al. (2008) Genomic islands in the pathogenic filamentous fungus Aspergillus fumigatus. PLoS Genet 4: e1000046.
  63. 63. Dietrich FS, Voegeli S, Brachat S, Lerch A, Gates K, et al. (2004) The Ashbya gossypii genome as a tool for mapping the ancient Saccharomyces cerevisiae genome. Science 304: 304–307.
  64. 64. Galagan JE, Calvo SE, Cuomo C, Ma LJ, Wortman JR, et al. (2005) Sequencing of Aspergillus nidulans and comparative analysis with A. fumigatus and A. oryzae. Nature 438: 1105–1115.
  65. 65. Pel HJ, de Winde JH, Archer DB, Dyer PS, Hofmann G, et al. (2007) Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88. Nat Biotechnol 25: 221–231.
  66. 66. Andersen MR, Salazar MP, Schaap PJ, van de Vondervoort PJ, Culley D, et al. (2011) Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88. Genome Res 21: 885–897.
  67. 67. Machida M, Asai K, Sano M, Tanaka T, Kumagai T, et al. (2005) Genome sequencing and analysis of Aspergillus oryzae. Nature 438: 1157–1161.
  68. 68. Amselem J, Cuomo CA, van Kan JA, Viaud M, Benito EP, et al. (2011) Genomic analysis of the necrotrophic fungal pathogens Sclerotinia sclerotiorum and Botrytis cinerea. PLoS Genet 7: e1002230.
  69. 69. Thatcher LF, Gardiner DM, Kazan K, Manners J (2011) A Highly Conserved Effector in Fusarium oxysporum is Required for Full Virulence on Arabidopsis. Mol Plant Microbe Interact.
  70. 70. Dujon B, Sherman D, Fischer G, Durrens P, Casaregola S, et al. (2004) Genome evolution in yeasts. Nature 430: 35–44.
  71. 71. Loftus BJ, Fung E, Roncaglia P, Rowley D, Amedeo P, et al. (2005) The genome of the basidiomycetous yeast and human pathogen Cryptococcus neoformans. Science 307: 1321–1324.
  72. 72. Cuomo CA, Guldener U, Xu JR, Trail F, Turgeon BG, et al. (2007) The Fusarium graminearum genome reveals a link between localized polymorphism and pathogen specialization. Science 317: 1400–1402.
  73. 73. Martin F, Aerts A, Ahren D, Brun A, Danchin EG, et al. (2008) The genome of Laccaria bicolor provides insights into mycorrhizal symbiosis. Nature 452: 88–92.
  74. 74. Xu J, Saunders CW, Hu P, Grant RA, Boekhout T, et al. (2007) Dandruff-associated Malassezia genomes reveal convergent and divergent virulence traits shared with plant and human fungal pathogens. Proc Natl Acad Sci U S A 104: 18730–18735.
  75. 75. Dean RA, Talbot NJ, Ebbole DJ, Farman ML, Mitchell TK, et al. (2005) The genome sequence of the rice blast fungus Magnaporthe grisea. Nature 434: 980–986.
  76. 76. Galagan JE, Calvo SE, Borkovich KA, Selker EU, Read ND, et al. (2003) The genome sequence of the filamentous fungus Neurospora crassa. Nature 422: 859–868.
  77. 77. Espagne E, Lespinet O, Malagnac F, Da Silva C, Jaillon O, et al. (2008) The genome sequence of the model ascomycete fungus Podospora anserina. Genome Biol 9: R77.
  78. 78. Jeffries TW, Grigoriev IV, Grimwood J, Laplaza JM, Aerts A, et al. (2007) Genome sequence of the lignocellulose-bioconverting and xylose-fermenting yeast Pichia stipitis. Nat Biotechnol 25: 319–326.
  79. 79. Goffeau A, Barrell BG, Bussey H, Davis RW, Dujon B, et al. (1996) Life with 6000 genes. Science 274: 546, 563–547.
  80. 80. Wood V, Gwilliam R, Rajandream MA, Lyne M, Lyne R, et al. (2002) The genome sequence of Schizosaccharomyces pombe. Nature 415: 871–880.
  81. 81. Kamper J, Kahmann R, Bolker M, Ma LJ, Brefort T, et al. (2006) Insights from the genome of the biotrophic fungal plant pathogen Ustilago maydis. Nature 444: 97–101.
  82. 82. Scannell DR, Frank AC, Conant GC, Byrne KP, Woolfit M, et al. (2007) Independent sorting-out of thousands of duplicated gene pairs in two yeast species descended from a whole-genome duplication. Proc Natl Acad Sci U S A 104: 8397–8402.
  83. 83. Rhind N, Chen Z, Yassour M, Thompson DA, Haas BJ, et al. (2011) Comparative functional genomics of the fission yeasts. Science 332: 930–936.
  84. 84. Chaisson MJ, Brinza D, Pevzner PA (2009) De novo fragment assembly with short mate-paired reads: Does the read length matter? Genome Res 19: 336–346.
  85. 85. Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Res 18: 821–829.
  86. 86. Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK Jr, et al. (2003) Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Res 31: 5654–5666.
  87. 87. Bligh EG, Dyer WJ (1959) A rapid method of total lipid extraction and purification. Can J Biochem Physiol 37: 911–917.
  88. 88. Metcalfe LD, Schmitz AA, Pelka JR (1966) Rapid preparation of fatty acids esters from lipids for gas chromatographic analysis. Analytical Chemistry 38: 514–515.
  89. 89. Carr TP, Andresen CJ, Rudel LL (1993) Enzymatic determination of triglyceride, free cholesterol, and total cholesterol in tissue lipid extracts. Clin Biochem 26: 39–42.
  90. 90. Rouser G, Siakotos AN, Fleischer S (1966) Quantitative analysis of phospholipids by thin-layer chromatography and phosphorus analysis of spots. Lipids 1: 85–86.
  91. 91. Van Kessel WS, Hax WM, Demel RA, De Gier J (1977) High performance liquid chromatographic separation and direct ultraviolet detection of phospholipids. Biochim Biophys Acta 486: 524–530.
  92. 92. Brugger B, Erben G, Sandhoff R, Wieland FT, Lehmann WD (1997) Quantitative analysis of biological membrane lipids at the low picomole level by nano-electrospray ionization tandem mass spectrometry. Proc Natl Acad Sci U S A 94: 2339–2344.
  93. 93. Pettus BJ, Kroesen BJ, Szulc ZM, Bielawska A, Bielawski J, et al. (2004) Quantitative measurement of different ceramide species from crude cellular extracts by normal-phase high-performance liquid chromatography coupled to atmospheric pressure ionization mass spectrometry. Rapid Commun Mass Spectrom 18: 577–583.
  94. 94. Bielawski J, Szulc ZM, Hannun YA, Bielawska A (2006) Simultaneous quantitative analysis of bioactive sphingolipids by high-performance liquid chromatography-tandem mass spectrometry. Methods 39: 82–91.