High contents of very long-chain polyunsaturated fatty acids in different moss species
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Mosses have high contents of polyunsaturated fatty acids. Tissue-specific differences in fatty acid contents and fatty acid desaturase (FADS)-encoding gene expression exist. The arachidonic acid-synthesizing FADS operate in the ER.
Polyunsaturated fatty acids (PUFAs) are important cellular compounds with manifold biological functions. Many PUFAs are essential for the human diet and beneficial for human health. In this study, we report on the high amounts of very long-chain (vl) PUFAs (≥C20) such as arachidonic acid (AA) in seven moss species. These species were established in axenic in vitro culture, as a prerequisite for comparative metabolic studies under highly standardized laboratory conditions. In the model organism Physcomitrella patens, tissue-specific differences in the fatty acid compositions between the filamentous protonema and the leafy gametophores were observed. These metabolic differences correspond with differential gene expression of fatty acid desaturase (FADS)-encoding genes in both developmental stages, as determined via microarray analyses. Depending on the developmental stage and the species, AA amounts for 6–31 %, respectively, of the total fatty acids. Subcellular localization of the corresponding FADS revealed the endoplasmic reticulum as the cellular compartment for AA synthesis. Our results show that vlPUFAs are highly abundant metabolites in mosses. Standardized cultivation techniques using photobioreactors along with the availability of the P. patens genome sequence and the high rate of homologous recombination are the basis for targeted metabolic engineering in moss. The potential of producing vlPUFAs of interest from mosses will be highlighted as a promising area in plant biotechnology.
KeywordsPhyscomitrella patens Polyunsaturated fatty acids Arachidonic acid In vitro cultivation Mosses Metabolite profiling
Polyunsaturated fatty acids (PUFAs) are ubiquitous metabolites with a large variety of biological functions. Their functions range from key roles in cellular signaling as precursors of hormones and phytohormones to the maintenance of membrane integrity and dynamics as major components of the biomembrane system. Many very long-chain (vl) PUFAs (≥C20), especially ω-3 PUFAs, are beneficial for human health as they contribute to the prevention of cardiovascular and inflammatory diseases (Calder 2004; Xue et al. 2013). Vl ω-6 PUFAs such as dihomo-γ-linolenic acid (DGLA, 20:3Δ8,11,14) and arachidonic acid (AA, 20:4Δ5,8,11,14) as well as the ω-3 vlPUFA eicosapentaenoic acid (EPA, 20:5Δ5,8,11,14,17) are the precursors of biologically active signaling compounds in humans, namely, eicosanoid hormones, which comprise prostaglandins, leukotrienes and thromboxanes (Samuelsson 1983; Harizi et al. 2008). Eicosanoid hormones mediate important physiological processes such as hypersensitivity reactions and inflammatory responses, but also immunity (Samuelsson 1983; Samuelsson et al. 1987; Harizi et al. 2008). Furthermore, the semi-essential fatty acid AA plays an important role in infant nutrition, as AA levels correlate with first year growth of preterm infants (Carlson et al. 1993).
Essential PUFAs for the human diet are linoleic acid (LA, 18:2Δ9,12), α-(ALA, 18:3Δ9,12,15) and γ-linolenic acid (GLA, 18:3 Δ6,9,12) that need to be ingested via plant-based nutrition, while nutritional sources for AA and EPA are mainly marine fishes (Gill and Valivety 1997). However, alternative sources for AA can also be bacteria, fungi (Yuan et al. 2002), algae (Bigogno et al. 2002) and mosses (Hartmann et al. 1986; Girke et al. 1998; Kaewsuwan et al. 2006). In contrast to mosses which contain large amounts of vlPUFAs (Grimsley et al. 1981; Hartmann et al. 1986; Girke et al. 1998; Zank et al. 2002; Mikami and Hartmann 2004; Kaewsuwan et al. 2006), higher plants rarely possess these as they lack the corresponding enzymes for vlPUFA-synthesis (Gill and Valivety 1997). In the moss model organism, Physcomitrella patens, the genes that encode the key enzymes of AA synthesis, namely Δ6- and a Δ5-fatty acid desaturases (FADS) and a Δ5-fatty acid elongase have already been identified via targeted gene replacement and biochemical characterization (Girke et al. 1998; Zank et al. 2002; Kaewsuwan et al. 2006). Recently, also two P. patens Δ12-FADS, that are associated with linoleic acid biosynthesis, were identified and characterized by heterologous expression in the yeast Saccharomyces cerevisiae (Chodok et al. 2013).
The high abundance of vlPUFAs, which are uncommon in higher plants, marks clear metabolic differences between mosses and higher plants. On the one hand the use of moss genes in a transgenic approach, e.g., for the optimization of oil seed crops as an alternative to the use of genes from microalgae or fish (Jiao and Zhang 2013), forms a promising research field. On the other hand, mosses themselves provide the potential for the discovery of yet uncharacterized metabolites (Cove et al. 2006; Asakawa 2007; Xie and Lou 2009; Erxleben et al. 2012), but also for the production of metabolites in the moss bioreactor that was established for cultivation of P. patens (Decker and Reski 2008, 2012). Due to the high rate of homologous recombination, i.e., the ability to integrate homologous nucleotide sequences into the genome, metabolic engineering, but also the production of recombinant proteins, has already been realized in P. patens (Büttner-Mainik et al. 2011; Chodok et al. 2012; Parsons et al. 2012). The high rate of homologous recombination in P. patens is unique among land plants at the current state of knowledge, being comparable with the gene targeting efficiency in yeast and several times higher than in vascular plants (Strepp et al. 1998; Schaefer 2001; Hohe et al. 2004; Kamisugi et al. 2006). Beside P. patens, homologous recombination-based gene targeting is also applicable in the moss Ceratodon purpureus (Brücker et al. 2005) and the liverwort Marchantia polymorpha (Ishizaki et al. 2013), indicating that this might be a common feature among certain Bryopsida and liverworts, thus expanding the selection of species to be analyzed with regard to genetic engineering and the production of metabolites of interest.
To quantify the abundance of vlPUFAs among Bryopsida, comparative fatty acid profiles of seven moss species from different phylogenetic groups were established. The cellular compartment of AA synthesis is the endoplasmic reticulum (ER) as confirmed via green fluorescent protein (GFP)-tagging of the AA-producing FADS from P. patens. It has previously been shown that the different developmental stages of P. patens protonema and gametophores show distinct metabolic profiles for sugar derivates, amino acids and nitrogen-rich storage compounds (Erxleben et al. 2012). Here, we established comparative fatty acid profiles of protonema and gametophores to characterize tissue-specific fatty acid contents. The observed differences in the PUFA profiles of protonema and gametophores were compared with and supported by microarray-derived gene expression profiles of putative FADS-encoding genes, which for some FADS-coding genes revealed significantly higher expression levels in protonema than in gametophores.
Materials and methods
Plant material and growth conditions
Fatty acid extraction and GC–MS analysis
Lipid extraction from moss tissue was adapted from Welti et al. (2002). In brief, 100 mg pulverized moss tissue was transferred into 1 mL 75 °C hot isopropanol containing 0.01 % (w/v) butylated hydroxytoluene (BHT) as an antioxidant. After shaking the mixture for 15 min at 75 °C on a thermomixer (Eppendorf, Hamburg, Germany), tubes were centrifuged for 5 min (1,000×g, room temperature) and the supernatant was transferred to a new tube with a Pasteur pipette. The remaining pellet was re-extracted with fresh chloroform–methanol (2:1 v/v; Folch et al. 1957) containing 0.01 % BHT for 10 min at room temperature. After centrifugation, the supernatants were combined, evaporated under a stream of nitrogen and dissolved in 1.5 mL chloroform–methanol (2:1 v/v). Following addition of 0.75 volumes 1 M KCl to remove polar contaminants (Folch et al. 1957), the organic phase was isolated and evaporated under a stream of nitrogen.
Fatty acids were converted into their methyl esters by acidic esterification (Christie 1989). In brief, 1 mL 2.5 % sulfuric acid in methanol was added to the dried organic phase and esterification was carried out for 90 min at 80 °C on a thermomixer. After 5 min at room temperature, 1.5 mL 0.9 % NaCl and 1 mL hexane were added to the reaction, from which the organic phase was isolated after short mixing and centrifugation. After evaporation under nitrogen, fatty acid methyl esters were dissolved in 100 μL chloroform and transferred to GC vials. All extraction and derivatization steps were carried out in screw-cap glass tubes sealed with Teflon-coated caps. 1 μL sample aliquots were injected into an Agilent 7890A/5975C GC–MS system (Agilent, Waldbronn, Germany). A split/splitless injector was used in pulsed splitless mode at 230 °C and 9.3 psi pressure. Chromatographic separation was achieved on a 30 m × 0.25 mm × 0.25 μm HP-5MS capillary column (Agilent Technologies, Waldbronn, Germany) with helium as carrier gas at a flow rate of 1 mL/min. The temperature ramp was programmed as follows: 80 °C for 2 min, 5 °C/min increase to 325 °C, 325 °C held for 10 min. The transfer line connecting GC oven with quadrupole MS detector was heated to 260 °C. 70 eV electron impact (EI) mass spectra of eluting compounds were acquired in full-scan mode (m/z 50–500) over a total runtime of 61 min.
Peak identification was performed with the AMDIS software (Stein 1999) that integrates raw data processing (deconvolution, compound detection) and comparison of acquired mass spectra/retention times with reference libraries. To identify fatty acids, a custom reference library was created from a 37-component fatty acid methyl ester (FAME) mix (Sigma, Deisenhofen, Germany). In addition, current versions of the commercial libraries FiehnLib (Kind et al. 2009) and NIST (NIST 2008) were used. Fatty acids were considered identified when mass spectral similarity between sample and standard was 95 % or higher and retention times did not deviate more than 3 s. In cases where retention time deviation was higher, only chain length and degree of unsaturation (but not the exact structural isomer) were determined from the FAME mass spectrum where possible (Christie 1989). Such fatty acids were specified by systematic names without indication of double bond position, e.g., “hexadecadienoic acid”. For quantification, peak areas of fatty acids were determined after baseline correction and normalized to the total peak area of all fatty acids. Levels of background contamination were determined from chemical blanks, obtained by the above procedure under omission of biological material, and subtracted from sample fatty acid levels.
Cloning of desaturase-GFP fusion constructs and protoplast transfection
For subcellular localization of the fatty acid desaturases, moss protoplasts were isolated according to Rother et al. (1994) and transiently transfected with desaturase-green fluorescent protein (GFP) fusion constructs. The fusion constructs contained the PpAct5 promoter (Weise et al. 2005) and the coding sequence (CDS) of each fatty acid desaturase, respectively (Δ5-FADS: Phypa_165175, Δ6-FADS: Phypa_164045, putative ω-3-FADS: Phypa_183309), within a GFP-reporter plasmid described before (Kiessling et al. 2004). RNA was extracted from protonema with TRIzol® reagent (Invitrogen, Karlsruhe, Germany) according to the manufacturer’s protocol. Complementary DNA (cDNA) was generated with SuperScript III (Invitrogen, Karlsruhe, Germany) and PolyT-primers according to the manufacturer’s protocol. The CDS were amplified from cDNA using oligonucleotides that contained restriction enzyme binding sites (165175-GFP-SalI-for: GGTCGACATGGCGCCCCACTCTGCGGAT, 165175-GFP-Acc65I-rev: CGGTACCGCCATCGAGCCGAAACTCTGTC, 164045-GFP-Acc65I-for: GGGTACCGAAATGGTATTCGCGGGCGGTG, 164045-GFP-BglII-rev: CAGATCTACTGGTGGTAGCATGCTGCTC, 183309-GFP-XhoI-f: GCTCGAGATGGCGGCCTCTCTGTTGTCCA, 183309-GFP-BglII-r: CAGATCTGAAGGTAGGATCTGTCTGGTAG). Protoplasts were isolated and transfected as described by Hohe et al. (2004). After transfection, the protoplasts were resuspended in a regeneration medium (Rother et al. 1994) and incubated in the dark for 3–4 days before microscopic analysis.
As a control for mitochondria-specific fluorescence patterns, the protoplasts were stained with MitoTracker® Orange CMTMRos (MTO, Invitrogen, Karlsruhe, Germany), a mitochondria-specific fluorescence dye. Before microscopic analysis, 1 μL MTO was added to 1 mL protoplast solution. After incubation for 10 min, the protoplasts were centrifuged at 45×g for 10 min. The supernatant was removed, leaving 100 μL for confocal laser scanning electron microscopy. As a control for plastid-localization, a putative ω-3-FADS predicted to be localized with 99 % probability and a confidence of 0.85 in the chloroplasts using YLoc (LowRes Plants) (Briesemeister et al. 2010) was tagged with GFP.
Confocal laser scanning electron microscopy
Confocal microscopy was done with the Zeiss LSM 510 with inverted microscope Axiovert 200 at the Life Imaging Center (LIC, University of Freiburg). The LD LCI Plan-Apochromat 25x/0.8 DIC ImmKorr water immersion objective was used to search for transformed protoplasts, while the C-Apochromat 63x/1,2 W VIS-IRKorr water immersions objective was used to take images. For the detection of GFP and chlorophyll autofluorescence, the sample was excited with an Argon laser at 488 nm. For MTO detection a helium-neon laser at 543 nm was used. Fluorescence signals are false-colored in green (GFP), orange (MTO) and red (chlorophyll), respectively. Three-dimensional reconstruction was performed via z-stacking with the Imaris v3.1 software (Bitplane).
Analysis of gene expression
Gene expression analyses of protonema and gametophores were performed using a Combimatrix 90 K microarray (Combimatrix Corp., Mukilteo/WA, USA) based on the v1.2 gene models of P. patens (Rensing et al. 2008) as described in Wolf et al. (2010). RNA extraction, sample preparation and computational data analysis were done as described previously (Richardt et al. 2010; Wolf et al. 2010). The microarray experiments were performed in three biological replicates. Statistical data analyses were done with the Expressionist Analyst 7.5 software (www.genedata.com, Genedata, Basel, Switzerland). The putative FADS-coding genes were selected based on the KEGG pathway database (Kanehisa and Goto 2000; Kanehisa et al. 2012) using the pathway map “Biosynthesis of unsaturated fatty acids” for P. patens (ppp01040).
To test for significant differences between the fatty acid contents of protonema and gametophores, an unpaired t-test was performed with the GraphPad software (http://www.graphpad.com). Averages and standard deviations were calculated with Microsoft Excel.
Mosses contain high amounts of vlPUFAs
Highly abundant fatty acids in Physcomitrella patens
Fatty acid (C:D, common name)
Gametophores (%) (±SD)
Protonema (%) (±SD)
16:0, Palmitic acid
16:2, Hexadecadienoic acid
16:3, Hexadecatrienoic acid
18:2, Linoleic acid
18:3, Linolenic acid
20:4, Arachidonic acid
20:5, Eicosapentaenoic acid
Tissue-specific fatty acid contents correspond with differential gene expression
Corresponding to the higher relative levels of PUFAs in protonema than in gametophores, putative Δ9-, Δ12-, and Δ15-fatty acid desaturase (FADS)-encoding genes also showed a higher level of relative gene expression in protonema than in gametophores (Fig. 3b). Three of these genes (Phypa_22981, Phypa_183309, Phypa_211380) were significantly higher expressed in protonema than in gametophores (Benjamini–Hochberg-corrected p-value < 0.05) (Benjamini and Hochberg 1995). One putative Δ12-FADS-encoding gene (Phypa_22981) was 7.39-fold higher expressed in protonema than in gametophores, while two putative Δ15-FADS-coding genes were 7.09-fold (Phypa_183309) and 4.70-fold (Phypa_211380) higher expressed in protonema than in gametophores (Table S2). In accordance to the similar AA contents in gametophores and protonema (Fig. 3a), the AA-producing Δ5- and Δ6-FADS-encoding genes showed no significantly deviating gene expression levels in the two developmental stages (Fig. 3b).
Arachidonic acid is produced in the endoplasmic reticulum
The control for localization in mitochondria using MitoTracker® Orange CMTMRos (MTO, Invitrogen, Karlsruhe, Germany) showed mitochondria-specific fluorescence patterns distinct from the fluorescence patterns of the two AA-producing FADS:GFP (Fig. 4e). The putative ω-3-FADS is localized in the chloroplasts, showing co-localization with the fluorescence of the chlorophyll (Fig. 4f), but distinct from the fluorescence patterns of the two Δ6-FADS- and Δ5-FADS:GFP.
In this work, we describe seven moss species as rich sources for very long-chain PUFAs. The comparative fatty acid profiles were established from plants grown in axenic in vitro culture, a technique that we regard as a prerequisite for metabolic studies under standardized conditions. All analyzed mosses contained considerable amounts of arachidonic acid (AA, 20:4Δ5,8,11,14), a vlPUFA that is usually found in algae, fish and mammals. According to our analyses, AA is produced in the endoplasmic reticulum (ER) in P. patens. Beside AA smaller amounts of EPA and saturated very long-chain fatty acids (C22–26) were determined in all analyzed mosses. The high content of vlPUFAs in mosses highlights their potential for biotechnological application. Especially ω-3 PUFAs such as eicosapentaenoic acid (EPA, 20:5Δ5,8,11,14,17) and docosahexaenoic acid (DHA, 22:6Δ4,7,10,13,16,19) are of importance for human nutrition and need to be produced in larger amounts, as limited natural sources basically comprise algae and marine fish (Chodok et al. 2012; Xue et al. 2013). Artificial production of EPA is already achieved with metabolic engineering of the yeast Yarrowia lipolytica (Xue et al. 2013). However, well-directed modifications of metabolic pathways are also possible in P. patens due to its well-annotated genome sequence (Zimmer et al. 2013) and the high rate of homologous recombination in mitotic cells that facilitates the generation of genetically modified strains. This technique enables the production of vlPUFAs of interest via metabolic engineering (Kaewsuwan et al. 2010; Chodok et al. 2012). On the other hand, transgenic engineering of crops, e.g., oil seed crops using moss genes, as recently reviewed regarding genes from microalgae or fish (Jiao and Zhang 2013) is also a promising research area.
The model organism P. patens has already been established as a production platform for recombinant proteins and biopharmaceuticals using highly standardized in vitro cultivation techniques in photobioreactors (Decker and Reski 2012). However, the opportunity of metabolic engineering along with cultivation under highly standardized conditions represents one step further towards the biotechnological use of mosses as PUFA sources under good manufacturing practice (GMP) conditions. Recently, the C22-PUFAs adrenic acid (ADA, 22:4Δ7,10,13,16) and the DHA-precursor ω-3 docosapentaenoic acid (DPA, 22:5 Δ7,10,13,16,19) were produced in P. patens by heterologous expression of a Δ5-elongase from a marine alga (Kaewsuwan et al. 2010; Chodok et al. 2012). Considering the biotechnological techniques available, an increased production of the ω-3 fatty acids EPA or DHA might also be possible in P. patens and other mosses.
However, it should be taken into account that fatty acid profiles from different developmental stages showed remarkable differences with regard to PUFA contents in P. patens. These findings are in accordance with the previously reported distinct metabolic profiles of protonema and gametophores regarding saccharides, sugar derivates, amino acids and nitrogen-rich storage compounds (Erxleben et al. 2012). According to our analyses, the relative amounts of PUFAs were higher in protonema than in gametophores, a finding that is supported by the significantly increased expression of putative fatty acid desaturase (FADS)-encoding genes in protonema when compared with the gene expression level in gametophores.
The biological meaning of the higher PUFA levels in protonema in comparison to gametophores remains a question for further research. It is known that PUFAs including AA form the precursors of signaling molecules, which are collectively named oxylipins (Andreou et al. 2009; Stumpe et al. 2010; Scholz et al. 2012). Oxylipins are produced by lipid peroxidation based on the enzymatic activity of lipoxygenases and occur in bacteria, algae, plants, fungi and animals (Andreou et al. 2009). In P. patens oxylipins can be produced from C20 and C18 fatty acids, while in seed plants oxylipins are produced from C18 fatty acids only (Wichard et al. 2005; Anterola et al. 2009). As recently shown for the moss Dicranum scoparium oxylipins possess anti-feeding activity against slugs and contribute to biochemical defense mechanisms (Rempt and Pohnert 2010). In P. patens, cyclopentenone–oxylipins, which are precursors of the phytohormone jasmonic acid in vascular plants, accumulate during pathogen attack by the fungus Botrytis cinerea (Ponce de León et al. 2012). Furthermore, cyclopentenone–oxylipins contribute to fertility and sporogenesis of P. patens (Stumpe et al. 2010). However, the lipid-derived phytohormone jasmonic acid itself has not been detected in this moss so far (Stumpe et al. 2010; Ponce de León et al. 2012). Considering this, clear differences not only in the lipid metabolism, but also in lipid-derived signaling exist between mosses and higher plants. The high contents of vlPUFAs may represent a key physiological characteristic that contributes to the considerable biotic and abiotic stress tolerance of mosses.
This work was supported by the Deutsche Forschungsgemeinschaft (DFG, GRK 1305), the MOSSCLONE FP7- ENV.2011.3.1.9-1 and the Excellence Initiative of the German Federal and State Governments (EXC294 to Ralf Reski). We are grateful to Jan-Peter Frahm for his help with the classification of the moss species, the team of the Life Imaging Center Freiburg and Dr. Stefanie Müller for their help with confocal microscopy and Anne Katrin Prowse for proofreading of the manuscript.
Conflict of interest
The authors declare that they have no conflict of interest.
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