Polar Lipid Composition of Biodiesel Algae Candidates

Sep 22, 2016 - ‡Future Fuels Institute and §Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Florida State University, 180...
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Polar Lipid Composition of Biodiesel Algae Candidates Nannochloropsis oculata and Haematococcus pluvialis from Nano Liquid Chromatography Coupled with Negative Electrospray Ionization 14.5 T Fourier Transform Ion Cyclotron Resonance Mass Spectrometry Peilu Liu,† Yuri E. Corilo,‡,§ and Alan G. Marshall*,†,§ †

Department of Chemistry and Biochemistry, Florida State University, 95 Chieftain Way, Tallahassee, Florida 32306, United States Future Fuels Institute and §Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, Florida State University, 1800 East Paul Dirac Drive, Tallahassee, Florida 32310, United States

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S Supporting Information *

ABSTRACT: Algae lipids contain long-chain saturated and polyunsaturated fatty acids. The lipids may be transesterified to generate biodiesel fuel. Here, we compare polar lipid compositions for two microalgae, Nannochloropsis oculata and Haematococcus pluvialis, that are prospective lipid-rich feedstock candidates for an emerging biodiesel industry. Online nano liquid chromatography coupled with negative electrospray ionization 14.5 T Fourier transform ion cyclotron resonance mass spectrometry ((−)ESI FT-ICR MS) with newly modified ion optics provides ultrahigh mass accuracy and resolving power to identify hundreds of unique elemental compositions. Assignments are confirmed by isotopic fine structure for a polar lipid extract. Collision-induced-dissociation (CID) MS/MS provides additional structural information. H. pluvialis exhibits more highly polyunsaturated lipids than does N. oculata.

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INTRODUCTION Biodiesel is defined as fatty acid methyl esters (FAME) produced by transesterification of vegetable oils or animal fats. Biodiesel is clean-burning and is derived from renewable resources, making it a promising and environmentally friendly fuel alternative. First generation biodiesel is primarily produced from food feedstocks, such as soybeans and corn, and therefore competes for farmland and freshwater. Second generation biodiesel is made from nonfood feedstocks (e.g., woody crops or agricultural residues); however, the oil yield is less than 5% of that available from biomass.1 The extensive cultivation of oil crops also requires plentiful freshwater. Compared to other crops, microalgae exhibit rapid growth (doubling their number in 24 h, and can be harvested daily) and high photosynthetic efficiency (12−16%). Algae may be grown on nonarable land, and can utilize wastewater or saline water.2 Although all algae species contain protein, carbohydrates, nucleic acids, and lipids, lipids can contribute up to 70− 85% of the dry weight of algae.1 Moreover, oil yield from largescale cultivation of microalgae is projected as high as 20 000 gallons per acre per year, i.e., 7−31 times greater than the next best crop, palm oil.3 Therefore, oil-rich algae have the potential to yield large-scale biodiesel production. Finally, photosynthesis converts CO2 into organic compounds of potential commercial value. Algae are genetically diverse. Red algae comprise one of the largest and oldest families of eukaryotic algae. The reported number of recognized species of red algae varies from 5000− 6000 recognized species4,5 to 10 000 species.6 For green algae, there are ∼16 000 species.5 Even more species of both red and © XXXX American Chemical Society

green algae remain to be described. Among the algae species considered desirable as a third generation biodiesel source,7 we selected the green alga Nannochloropsis oculata (N. oculata) because of its ability to produce a high oil yield (40−60%)8,9 and to survive in saline water. The freshwater alga Haematococcus pluvialis (H. pluvialis) exhibits a total lipid content of ∼16% on a dry weight basis, but the lipid fraction increases by 2-fold under nitrogen starvation or light irradiation stress conditions.10 The fatty acid derivatives from algal lipids (e.g., phospholipids and glycolipids) can differ significantly in composition from those in vegetable oils. Algal oils contain a higher amount of highly polyunsaturated fatty acids (≥4 double bonds).11 The content of polar lipids in algae also varies by species and when and where the algae have been grown and harvested (e.g., 25 to ∼37% in Nannochloropsis species (Seambiotic Ltd., Tel Aviv, Israel),12,13 0.7% in Chlorella vulgaria (UTEX, Austin, TX),12 14% in Schizochytrium (Iowa State University)13). However, Nannochloropsis species show relatively higher amounts of polar lipids among other species (Chlamydomonas, Chlorella, Nannochloropsis, Scenedesmus, and Schizochytrium). Recently, a solid acid catalyst was found to be capable of converting polar and nonpolar lipids to fatty acid methyl esters (FAME) simultaneously with high yield. Therefore, both polar and nonpolar lipids can be utilized as feedstocks for biodiesel.14 Triacyglycerides constitute a key feedstock for biodiesel. Here, Received: June 20, 2016 Revised: August 20, 2016

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DOI: 10.1021/acs.energyfuels.6b01514 Energy Fuels XXXX, XXX, XXX−XXX

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Sample Preparation. A polar lipid extract from green algae was prepared by a modified method.31,32 First, 1.0 mL of Erdschreiber’s medium28 with green algae was centrifuged and frozen/thawed three times. The thawed paste was then sonicated for 10 min followed by addition of 0.4 mL of isopropanol. After sonication for 20 min, 0.4 mL of CH3OH was added, followed by sonication for 20 min. The slurry was incubated overnight at 48 °C in a water bath. The hot extract was centrifuged and supernatant was removed; the residue pellet was further extracted by CH3OH/CHCl3 (1/1, v/v) two more times. The supernatants were pooled and dried under vacuum and later partitioned in H2O/CH3OH/CHCl3 (3/2/1, v/v/v). After phase separation, the upper aqueous layer containing polar lipid was collected and dried by a SpeedVac and stored at −80 °C under N2. We tested the polar lipid extraction procedure with SQDG standard (Avanti Polar Lipids No. 840525), and achieved ∼95% recovery. The cell pellet was frozen and thawed three times to break down cell walls. Overnight incubation after addition of organic solvent allows lipids to diffuse into the solvent. In addition, the sample was exposed to nitrogen during incubation at 48 °C With the protection of inert gas, degradation of lipids, especially polyunsaturated fatty acids, is limited, so that it is not necessary to add an antioxidant. Online Nano LC−MS. The polar lipid extract was separated by use of an Acuity M-Class LC system (Waters, Milford, MA) with a custom-packed phenylhexyl column (75 μm i.d × 5 cm, New Objective, Woburn, MA). The extract was redissolved in 25:75 H2O/ CH3OH with 10 mM NH4OAc and loaded onto the analytical column. Lipids were separated by gradient elution (80% B to 98% B, in which A is 2% methanol, 98% H2O, and 10 mM NH4OAc and B is 98% methanol, 2% H2O, and 10 mM NH4OAc) over 30 min, at a flow rate of 400 nL/min. Afterward, the eluent was analyzed by negative electrospray ionization at −3.0 kV coupled to a custom-built Velos Pro 14.5 T FT-ICR mass spectrometer33 equipped with a modified dynamically harmonized ICR cell.34,35 The LTQ target ion number was set to 1 million by a single fill of ions with automatic gain control (AGC) before transfer to the ICR cell. Time-domain ICR data were acquired for 0.76 s, Hanning apodized, and zero-filled once before discrete Fourier transformation and magnitude calculation. The mass spectra were externally calibrated with Pierce negative ion calibration solution (Thermo Fisher Scientific, San Jose, CA).36,37 To obtain structural information, data-dependent collision-induced dissociation (CID) MS/MS was conducted by fragmenting [M − H]− precursor ions. Based on a survey spectrum, the five most abundant precursor ions were selected for subsequent fragmentation. The optimal normalized collision energy was 50%. The signal threshold for triggering an MS/MS event was set to 500 counts. Dynamic exclusion was enabled (exclusion duration, 12 s; exclusion size list, 50). Data Analysis. All mass spectra were acquired by Xcalibur software (Thermo Scientific, San Jose, CA). Our custom software PetroOrg38 provided elemental composition analysis. Briefly, data from each chromatographic peak were summed over a 30 min retention time window and the resultant mass spectra [m/z 210−1300] were imported into PetroOrg software. A threshold for the minimum peak height was set to 0.01% of the highest mass spectrum peak. Atomic constraints based upon each lipid subclass eluted over a specific chromatographic retention time range were the following: number of carbon (0−60), hydrogen (0−120), nitrogen (0−1), oxygen (1−25), sulfur (0−2), and phosphorus (0−1) atoms. Assigned elemental compositions from all mass spectra were sorted, aligned, and searched against a lipid library to confirm lipid identities.

we focus on polar lipids because of the following: (a) The content of polar lipids is quite high in some species. For example, polar lipid content in N. oculata is 25%12 to 37%13 (dry weight). (b) The quality of algal biofuel is negatively affected by polyunsaturation of fatty acids,11 which are derived from lipids extracted from microalgae. Therefore, polar lipid composition and degree of polyunstaturation profile are important for optimizing upgrading and production of biofuel from algae. The extreme compositional diversity of lipids in algae poses a severe analytical challenge. Moreover, the lack of chromophore or double bonds in lipids greatly reduces the sensitivity of detection by UV−vis or fluorescence spectroscopy. The introduction of mass spectrometry coupled with atmospheric pressure ionization sources such as electrospray ionization (ESI), matrix-assisted laser desorption ionization (MALDI), atmospheric pressure photoionization (APPI), and atmospheric pressure chemical ionization (APCI) facilitates direct mass spectrometric (MS) analysis of many analytes, including lipids. Commercial ESI and MALDI mass spectrometry available since the late 1980s and early 1990s accelerated the analysis of nonvolatile lipids in unfragmented form. Collision-induced dissociation (CID) provided by a triple quadrupole mass spectrometer has been a powerful tool for lipid analysis by virtue of its multiple modes of MS/MS operation: product ion scanning, precursor ion scanning, neutral loss scanning, and selected reaction monitoring (also called multiple reaction monitoring).15−18 The hybrid mass spectrometers that can analyze molecular ion species and product ions after CID based on time-of-flight and orbitrap mass analyzers provided higher mass accuracy and further improved the identification of elemental compositions of lipids extracted from complex samples.19−21 Fourier transform ion cyclotron resonance (FT-ICR) mass spectrometry offers the highest broadband mass resolving power and mass accuracy of any mass analyzer,22 and is thus well-suited for resolution and identification of components of complex organic mixtures.23 However, lipids with low ionization efficiency and/or low abundance cannot be fully accessed by direct infusion mass analysis. High performance reversed-phase liquid chromatography enables separation of lipids based on their hydrophobicity, and greatly increases the number of detectable lipids. Normal phase liquid chromatography facilitates molecular formula identification due to separation of lipids into defined subclasses.15,24,25 Nano liquid chromatography (nano LC) enables higher electrospray ionization efficiency,26,27 and when coupled with FT-ICR MS recently identified polar lipids of more than 200 elemental compositions from N. oculata. Here, we improve and extend that analysis to polar lipids from both N. oculata and H. pluvialis. The resulting fatty acid profiles provide a detailed compositional comparison of the differences in potential biodiesel fuel derived from two algae species.

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EXPERIMENTAL METHODS

RESULTS AND DISCUSSION Online Nano LC−MS. We used a custom-built nano-sprayionization (NSI) source, which requires a lower flow rate than normal ESI. Our typical flow rate was 250−400 nL/min, and low flow rate provides a more stable spray. Moreover, competition for charge and dynamic range issues can bias the MS detection in favor of lipids that are more easily ionized. The use of nanoliter per minute flow increases electrospray ionization efficiency and can reduce the ionization bias. Direct

Materials. Green algae N. oculata and H. pluvialis grown in Erdschreiber’s medium28 were purchased from UTEX (Austin, TX). LC−MS grade methanol and isopropanol were obtained from Burdick & Jackson (Morris Plains, NJ). HPLC-grade chloroform was purchased from J.T. Baker (Phillipsburg, NJ). MS-grade ammonium acetate was obtained from Sigma (St. Louis, MO). Calibration solution Calmix was supplied by Thermo Fisher Scientific (San Jose, CA). Lipid Nomenclature. Lipid nomenclature follows LIPID MAPS nomenclature and shorthand notation.29,30 B

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Energy & Fuels infusion of polar lipids extracted from N. oculata or H. pluvialis yielded only peaks of abundant lipids in the matrix (data not shown). In contrast, 250 elemental compositions could be assigned from nano LC (−)ESI FT-ICR MS for N. oculata, and 214 for H. pluvialis (Table S1 in the Supporting Information and Figure 1). Phospholipids may be ionized as either negative

Figure 3. Selected mass chromatograms, based on nano LC (−)ESI FT-ICR mass spectra for three representative algal polar lipids from N. oculata. Note the clear separation of phosphatidylinositol PI(34:1), PI(34:2), and PI(34:3) constituents, containing one, two, or three double bonds in their fatty acid chains. Order of retention times for PI is PI(34:1) > PI(34:2) > PI(34:3), consistent with their hydrophobicity: the fewer double bonds, the more hydrophobic, resulting in later elution. Approximate 1/50 of the lipid extract was loaded onto the column.

Figure 1. Identified lipid classes for for N. oculata and H. pluvialis shown as a pie chart. The area of each color represents the percentage of number of assigned lipid in each class over total number of assigned lipids.

Lipid Identification. The experimentally measured masses for ions of m/z 210−1300 were imported into PetroOrg,38 which assigns corresponding elemental compositions. The measurement of ion mass with less than 1 ppm mass error can often yield a unique elemental composition.40 For example, elemental composition of the negative singly charged ion of m/ z 807.5029 can be uniquely assigned as C41H76O13P within a defined set of constraints. The molecular formula was searched against the LIPID MAPS database41 to identify the lipid as phosphatidylinositol PI(32:1). Figure S1 in the Supporting Information shows mass error histograms for the two algae species. Note the approximately Gaussian error distribution, centered at +0.1 ppm (slight systematic error due to imperfect mass calibration). However, 226/250 mass errors are less than 0.5 ppm, ensuring unique elemental composition assignments. In addition, resolution of isotopic fine structure (made possible by ultrahigh mass resolving power) can help to confirm elemental composition assignment. For example, Figure S2 in the Supporting Information shows tentative identification of SQDG(32:2) C41H74O12S1 based on the monoisotopic neutral mass. However, 34S has a natural abundance of 4.5% relative to 32 S. Thus, resolution of the 34S isotopologue (separated by only 11.1 mDa from the same compound with 13C2 at 2 Da higher than the monoisotopic mass) confirms the presence of a single sulfur atom in the lipid molecular formula. Figure 4 shows another example of the value of resolved isotopic fine structure: namely, resolution of 13C2 and 12C2H2 from IPC(d32:2) and IPC(d32:1), separated in mass by less than 9 mDa, and requiring a minimum mass resolving power of ∼90 000 at m/z 750. Our experimental resolving power m/ Δm50% (in which Δm50% is the mass spectral peak full width at half-maximum peak height) was 116 000 (equivalent to 220 000 at m/z 400), enabling unique elemental composition identification of 250 and 214 lipids found in N. oculata and H. pluvialis (see Supporting Information, Tables S1 and S2). Assignments for PC, LPC, DGDG, and MGDG are for their

or positive ions. PC, PS, PE, and sphingomyelins can be detected as positive ions. PI, PS, PG, PE, and adducts of PC as well as the lyso forms of these lipids can be detected as negative ions. We chose negative-ion microelectrospray for better signalto-noise (S/N) ratio, especially for SQDG. Due to the presence of acidic groups (e.g., sulfate for SQDG), the S/N for molecular ions is much higher for negative ions.39 A reversed-phase analytical column packed with phenylhexyl bound to silica particles provides selective π−π stacking and hydrophobic interactions between the stationary phase and analytes. Polar lipids are therefore separated according to the length and degree of unsaturation of hydrocarbon side chains as well as polar headgroup (Figure 2). Figure 3 shows selected ion chromatograms for phosphatidylinositols (PI) of different degrees of unsaturation.

Figure 2. Total ion chromatogram (TIC) for N. oculata with representative algal polar lipids labeled. HPLC enables separation of monoacyl lipids (lyso form) from diacyl lipids. C

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Figure 4. Mass scale expanded segments from the broadband mass spectra of inositol phosphorylceramide IPC(d32:1) (left); isotopic fine structure for the second isotopic peak of inositol phosphorylceramide IPC (d32:2) and monoisotopic peak of IPC(d32:1) (right). The isotopic fine structure shows resolution of ions differing in elemental composition by 13C2 vs 12C2H2, resulting in a mass difference of 8.6 mDa.

Figure 5. CID tandem mass spectrum for the PI(34:2) [M − H]− precursor ions (833.5185 Da). Fragmentation sites are shown at top right. The m/ z 577.3 ion reflects neutral loss of 255.1 Da, and the m/z 553.3 ion indicates neutral loss of 279.3 Da. Ions of m/z 415.2, 391.2, 241, and 297 confirm the presence of the phosphoinositol moiety. The structures of characteristic fragment ions are shown at lower right.

acetate adducts. The number of detected N. oculata lipid elemental compositions is 26% (i.e., 52 more lipid compositions) higher than in previous work.14 Structural Elucidation by Collision-Induced Dissociation. Structures of many of the assigned lipids have been confirmed by MS/MS. For example, CID MS/MS for deprotonated negative PI(34:2) ions (Figure 5) yields fragment ions of m/z 577.3 and 553.3, resulting from neutral loss of a 16:0 or 18:3 fatty acyl group, in agreement with previous lowenergy CID.42 Because low-energy CID fragmentation is known to be more favorable at the sn-2 position,42 the higher-magnitude m/z 577.3 signal identifies it as sn-2. Additional fragment ions of m/z 415.2, 391.2, 241, and 297 derive from the inositol polar headgroup,43 as shown in the cleavage diagram in Figure 5. Subsequent dissociation of ions of m/z 415 and 391 yields ions of m/z 279 and 255. Thus, the signal magnitudes of two fatty acyl chain fragments were not needed for position assignment, in view of the further dissociation of ions containing one fatty acyl substituent. Lipid Profile. Of the 250 assigned lipids in N. oculata, and 214 in H. pluvialis, phospholipids PC, PG, PE, PI, and IPC; glycolipids SQDG, DGDG, and MGDG; betaine lipid DGTS; fatty acids; and lyso forms of the diacylglycerol lipids DGMG

and MGMG are found in both algae species. Figure 6 lists the relative (−)ESI FT-ICR MS signal magnitudes for different lipid classes. The glycolipid, SQDG, is the predominant lipid class for both algae species. PI is the most abundant

Figure 6. Relative signal magnitudes for assigned lipid classes. The data represents the sum of (−)ESI FT-ICR mass spectral peak magnitudes for all constituent ions (same polar headgroup, but different numbers of carbons and double bonds). Error bars represent the standard deviation of triplicates from three individual extractions of each algal sample. D

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Figure 7. Fatty acid compositions within lipid subclasses, SQDG, PI, and FA. SQDG(32:1) is the predominant constituent in N. oculata, whereas SQDG(34:3) dominates in H. pluvialis. The PI fatty acid distributions are similar to those for SQDG. The major N. oculata FA is stearic acid FA(18:0), and the major FA for H. pluvialis is palmitic acid FA(16:0).

phospholipid class. In H. pluvialis, fatty acids and PI abundances are roughly equal. Lyso forms of phospholipids, LPC, LPE, and glycolipids MGMG and DGMG are present in minor amounts in both algae species. An important disclaimer is that the relative abundances of ions of different elemental compositions do not necessarily accurately represent the relative abundances of their neutral precursors in the original lipid extract, due to variation in ionization efficiency for different lipid classes.43,44 The ionization efficiency of lipid molecules depends on their polar headgroup and saturation. Moreover, highly abundant lipids, SQDG, PI, and MGDG45 species in N. oculata and H. pluvialis tend to suppress the ionization of other lipid molecules. Figure 7 lists fatty acid compositions for major individual polar lipid subclasses. SQDG subclasses exhibit the most variation (32 and 26 lipids for N. oculata and H. pluvialis). For N. oculata, SQDG(32:1) is the predominant constituent, and consists mainly of (16:0/16:1) diacyl groups, whereas SQDG(34:3) is the most abundant lipid for H. pluvialis. Most SQDGs have more fatty acyl carbons (∼C34) than N. oculata (∼C32). The fatty acid distribution for PI lipid members is approximately the same as for SQDG; i.e., the most abundant PI contains 32 (N. oculata) or 34 (H. pluvialis) fatty acyl carbons. Finally, H. pluvialis exhibits higher abundance for most FAs, especially the dominant species, FA(16:0) and FA(18:0). Biofuel. Biodiesel is produced by transesterification, typically forming fatty acid methyl esters (FAME), which retain the relative fatty acid profile of the feedstock. The polar lipids are typically composed of a polar headgroup bonded to two fatty acids by esterification. The two fatty acids may contain no double bonds (saturated fatty acids) or one double

bond (monounsaturated) or more (polyunsaturated). The fatty acid distributions of N. oculata and H. pluvialis have been examined, focusing on their link to liquid quality for biodiesel applications. Biodiesel is mainly composed of methyl esters with chain lengths of ∼C14−C24 and one, two, or three double bonds.46 Although the lipid fatty acid carbon numbers vary for N. oculata and H. pluvialis, the most abundant lipid species for both algae possess a total of ∼32−34 fatty acid total carbons (Figure 6), thus approaching the ∼14−20 individual fatty acid carbons considered ideal for production of biodiesel.47 Figure 8 shows the fatty acid double bond distributions for the two algae. N. oculata is richer in monounsaturated fatty

Figure 8. Degree of unsaturation profiles for N. oculata and H. pluvialis lipid fatty acyl chains. Each entry represents summed (−)ESI FT-ICR MS peak heights for lipids with various degrees of unsaturation, but different polar headgroups and numbers of fatty acid carbons. Error bars reflect the standard deviation for three technical replicates. E

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Energy & Fuels acids than H. pluvialis, whereas H. pluvialis is richer in lipids with two, three, and four or more double bonds, particularly SQDG and PI. Generally, kinematic viscosity decreases with an increasing number of double bonds in fatty acyl chains.48 According to Figure 7, algal biodiesel fuel from H. pluvialis should therefore exhibit lower viscosity than biodiesel from vegetable oils rich in monounsaturated fatty acids.

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CONCLUSION In this study, we employed a modified extraction method highlighting nano LC coupled with FT-ICR mass spectrometry to determine lipid class compositions for two microalgae, N. oculata and H. pluvialis. The two algae contained similar polar lipid classes, but marked variation in relative abundances (see Figure 6). The characterization of degree of unsaturation of fatty acyl chains is particularly important, because they may negatively affect biodiesel properties after upgrading of biocrude. We found that the highly polyunsaturated lipids were more abundant in H. pluvialis than in N. oculata. Ultrahigh-resolution FT-ICR MS enabled unique elemental composition assignments and fast identification of lipids. Combination of nano LC with FT-ICR mass spectrometry and recent improvements in FT-ICR sensitivity and resolution have increased the number of detected lipids from 198 to 250 peaks with height greater than 6σ of root-mean-square baseline noise for N. oculata alone.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.energyfuels.6b01514. Lipids identified in N. oculata (Table S1) and H. pluvialis (Table S2) (PDF) Mass error histogram for lipid extract obtained by (−)ESI 14.5 T FT-ICR MS (Figure S1) (PDF) Isotopic distribution for deprotonated molecular ions of SQDG(32:2) (Figure S2) (PDF)

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MGMG = monogalactosylmonoacylglycerol DGMG = digalactosylmonoacylglycerol IPC = inositol phosphorylceramide PI = phosphatidylinositol PG = phosphatidylglycerol DGTS = diacylglyceryl-N,N,N-trimethylhomoserine PC = phosphatidylcholine PE = phosphatidylethanolamine FAME = fatty acid methyl esters ESI = electrospray ionization APPI = atmospheric pressure photoionization APCI = atmospheric pressure chemical ionization MALDI = matrix-assisted laser desorption ionization

AUTHOR INFORMATION

Corresponding Author

*Tel.: 850-644-0529. Fax: 850-644-0133. E-mail: marshall@ magnet.fsu.edu. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors thank Donald F. Smith, Nathan K. Kaiser, and John P. Quinn for their continued assistance in instrumental maintenance and operation. The authors also thank Christopher L. Hendrickson and Huan He for helpful discussions. This work was supported by NSF Division of Materials Research through DMR-11-57490 and the State of Florida.

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ABBREVIATIONS N. oculata = Nannochloropsis oculata H. pluvialis = Haematococcus pluvialis FA = fatty acids SQDG = sulfoquinovosyldiacylglycerol DGDG = digalactosyldiacylglycerol MGDG = monogalactosyldiacylglycerol F

DOI: 10.1021/acs.energyfuels.6b01514 Energy Fuels XXXX, XXX, XXX−XXX

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DOI: 10.1021/acs.energyfuels.6b01514 Energy Fuels XXXX, XXX, XXX−XXX