| Literature DB >> 30622648 |
Jia Wang1, Weijun Lin2, Zhongdong Yin1, Libing Wang3, ShuBin Dong1, Jiyong An1, Zixin Lin1, Haiyan Yu3, Lingling Shi1, Shanzhi Lin1, Shaoliang Chen1.
Abstract
BACKGROUND: Based on our previous studies of 17 Prunus sibirica germplasms, one plus tree with high quality and quantity of seed oils has emerged as novel potential source of biodiesel. To better develop P. sibirica seed oils as woody biodiesel, a concurrent exploration of oil content, FA composition, biodiesel yield and fuel properties as well as prediction model construction for fuel properties was conducted on developing seeds to determine the optimal seed harvest time for producing high-quality biodiesel. Oil synthesis required supply of carbon source, energy and FA, but their transport mechanisms still remains enigmatic. Our recent 454 sequencing of P. sibirica could provide long-read sequences to identify membrane transporters for a better understanding of regulatory mechanism for high oil production in developing seeds.Entities:
Keywords: Biodiesel fuel properties; Differential transcript profiles; Intracellular transporter; Oil synthesis; Prunus sibirica seeds; Transporter-mediated mechanism
Year: 2019 PMID: 30622648 PMCID: PMC6318995 DOI: 10.1186/s13068-018-1347-x
Source DB: PubMed Journal: Biotechnol Biofuels ISSN: 1754-6834 Impact factor: 6.040
Fig. 1Dynamic changes of oil accumulation and biodiesel yield in developing P. sibirica seeds. a The feature of P. sibirica seeds from seven developing stages. b Dynamic change of the seed fresh weight during development. c Dynamic change of seed size (longitudinal and transverse diameter) during development. d Dynamic changes in oil content and biodiesel yield of dry seeds from different developing stages. Error bars are standard deviations (SD) of three biological replicates
Dynamic changes of FA compositions and their relative proportions in developing seeds of P. sibirica
| DAF | C14:0 (%) | C16:0 (%) | C16:1 (%) | C18:0 (%) | C18:1 (%) | C18:2 (%) | C18:3 (%) | C20:0 (%) | C20:1 (%) |
|---|---|---|---|---|---|---|---|---|---|
| 10 | 0.71 ± 0.01 | 19.92 ± 1.58 | 0.94 ± 0.09 | 2.51 ± 0.51 | 11.59 ± 0.91 | 57.95 ± 1.21 | 6.38 ± 0.42 | – | – |
| 20 | – | 11.30 ± 1.07 | 1.05 ± 0.11 | 3.01 ± 0.81 | 21.80 ± 1.05 | 52.79 ± 1.01 | 9.80 ± 0.63 | 0.11 ± 0.02 | 0.14 ± 0.05 |
| 30 | – | 5.02 ± 0.82 | 0.81 ± 0.04 | 4.97 ± 0.51 | 27.14 ± 1.02 | 51.62 ± 1.22 | 10.23 ± 0.71 | 0.10 ± 0.03 | 0.11 ± 0.01 |
| 40 | – | 4.11 ± 0.51 | 0.70 ± 0.05 | 1.50 ± 0.07 | 32.51 ± 1.03 | 50.49 ± 1.01 | 10.51 ± 0.61 | 0.08 ± 0.01 | 0.10 ± 0.02 |
| 50 | – | 3.92 ± 0.23 | 0.61 ± 0.01 | 1.24 ± 0.02 | 36.42 ± 1.81 | 47.14 ± 1.02 | 10.43 ± 0.54 | 0.13 ± 0.02 | 0.11 ± 0.01 |
| 60 | – | 2.91 ± 0.32 | 0.61 ± 0.02 | 1.07 ± 0.03 | 72.22 ± 2.01 | 22.47 ± 0.98 | 0.51 ± 0.03 | 0.09 ± 0.04 | 0.12 ± 0.04 |
| 70 | – | 2.86 ± 0.13 | 0.59 ± 0.01 | 1.01 ± 0.01 | 76.39 ± 3.02 | 18.49 ± 0.71 | 0.39 ± 0.01 | 0.14 ± 0.03 | 0.13 ± 0.02 |
Error bars are standard deviations (SD) of three biological replicates
Fig. 2Construction of prediction model for biodiesel fuel properties of raw oils from developing P. sibirica seeds. a Change of relative proportion of saturated, monounsaturated and polyunsaturated FAs in developing P. sibirica seeds. b Prediction triangular chart of FA compositions on biodiesel fuel properties. The yellow part of region was clearly delineated to predict the biodiesel fuel properties that could fully meet the limit of cetane number, iodine number, cold filter plugging point and oxidation stability. Error bars are standard deviations (SD) of three biological replicates
Evaluation of biodiesel fuel properties of oils from different developing seeds of P. sibirica
| DAF | Biodiesel fuel properties | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| DU | LCSF | CN | IV (g/100 g) | CFPP (°C) | CP (°C) | OS (h) | KV (mm2 s−1, 40 °C) | D (kg/m−3, 15 °C) | |
| 10 | 147.72 ± 3.1 | 7.17 ± 0.8 | 47.24 ± 3.5 | 123.76 ± 2.5 | − 2.18 ± 0.1 | 0.32 ± 0.1 | 2.32 ± 0.02 | 4.08 ± 0.09 | 882.75 ± 1.21 |
| 20 | 158.19 ± 2.6 | 4.67 ± 0.7 | 45.97 ± 3.8 | 130.75 ± 2.8 | − 6.57 ± 0.1 | − 3.99 ± 0.1 | 2.76 ± 0.03 | 4.14 ± 0.10 | 881.18 ± 1.05 |
| 30 | 162.13 ± 2.4 | 3.53 ± 0.2 | 45.49 ± 1.2 | 133.40 ± 1.5 | − 8.58 ± 0.2 | − 5.97 ± 0.2 | 2.90 ± 0.01 | 4.23 ± 0.11 | 879.39 ± 1.31 |
| 40 | 162.80 ± 2.2 | 1.89 ± 0.1 | 45.81 ± 0.9 | 133.38 ± 1.3 | − 11.46 ± 0.3 | − 8.79 ± 0.1 | 2.91 ± 0.01 | 4.28 ± 0.08 | 876.28 ± 0.89 |
| 50 | 165.29 ± 2.1 | 1.75 ± 0.3 | 45.11 ± 0.8 | 135.49 ± 1.1 | − 11.71 ± 0.1 | − 9.03 ± 0.2 | 2.94 ± 0.04 | 4.32 ± 0.11 | 878.45 ± 0.91 |
| 60 | 116.31 ± 1.5 | 1.30 ± 0.2 | 51.58 ± 0.7 | 105.65 ± 0.5 | − 12.47 ± 0.1 | − 9.81 ± 0.1 | 3.30 ± 0.01 | 4.36 ± 0.08 | 877.57 ± 0.97 |
| 70 | 115.63 ± 1.5 | 1.31 ± 0.3 | 51.71 ± 0.6 | 102.35 ± 1.5 | − 12.48 ± 0.2 | − 9.79 ± 0.1 | 3.33 ± 0.01 | 4.48 ± 0.10 | 876.09 ± 1.01 |
DU degree of unsaturation, LCSF chain length saturated factor, CN cetane number, IV iodine value, CFPP cold filter plugging point, CP cloud point, OS oxidation stability, KV kinematic viscosity, D density. Error bars are standard deviations (SD) of three biological replicates
Fig. 3Transcriptional analysis of transporters for carbon allocation and energy provision in developing P. sibirica seeds by qRT-PCR. a Temporal transcript profiles for transporters of plastid membrane involved in carbon allocation and metabolite transport. b Temporal transcript profiles for mitochondrial transporters implicated in TCA cycle, ATP synthesis and oil mobilization. c Temporal transcript profiles for transporters of tonoplast involved in sugar transport. d Temporal transcript profiles for transporters of peroxisomal and ER membrane involved in oil synthesis and mobilization. The genes for cyclophilin (CYP) and ubiquitin-conjugating enzyme (UBC) were used as internal controls. Expression level from seed sample at 10 DAF was arbitrarily set to 1.00 for standardization. Error bars are SD of three biological replicates with three technical repetitions each
Fig. 4Transcriptional analysis of enzymes for carbon assimilation and OPPP in developing P. sibirica seeds by qRT-PCR. a Comparative analysis of transcript levels for enzymes involved in both cytosolic and plastidial OPPP. b Differential transcript for genes involved in carbon assimilation of Calvin cycle. Both CYP and UBC genes were used as internal controls. Expression level from seed sample at 10 DAF was arbitrarily set to 1.00 for standardization. The cytosolic (c) and plastidial (p) isoforms of the enzymes are indicated by a prefix in a. Error bars are SD of three biological replicates with three technical repetitions each
Fig. 5Transcriptional analysis of enzymes for TAG mobilization in developing P. sibirica seeds by qRT-PCR. a Temporal transcript patterns of TAG lipases (TAGL1/2) and sugar dependent 1 (SDP1) protein involved in TAG hydrolysis. b Temporal transcript patterns of enzymes involved in β-oxidation. c Temporal transcript patterns of enzymes for glyoxylate cycle. d Temporal transcript patterns of PEP carboxykinase (PEPCK1/2) involved in gluconeogenesis. Both CYP and UBC genes were used as the internal controls. The relative expression values in heatmap were counted as 2−△△Ct, and expression level from seed sample at 10 DAF was arbitrarily set to 1.00 for standardization
Fig. 6Transcriptional analysis of transport proteins for TAG synthesis in developing P. sibirica seeds by qRT-PCR. a Temporal transcript patterns of genes encoding for acyl-CoA-binding proteins (ACBPs). b Temporal transcript patterns of genes for membrane protein of fatty acid export (FAX). c Temporal transcript patterns of genes for some important ATP-binding cassette (ABC) proteins. d Temporal transcript patterns of genes for lipid transfer proteins (LTPs). e Temporal transcript pattern of gene for trigalactosyldiacylglycerol 1 (TGD1) protein. Both CYP and UBC genes were used as the internal controls. The relative expression values in heatmap were counted as 2−△△Ct, and the expression level from seed sample at 10 DAF was arbitrarily set to 1.00 for standardization
Fig. 7Characterization of complex transporter-mediated model of carbon allocation and energy supply for oil synthesis in developing P. sibirica seeds. The identified intracellular metabolite transport routes of carbon allocation and energy supply for oil synthesis are mainly based on a combination of our previous 454 sequencing data analysis and qRT-PCR detection. The background color distinguishes different subcellular locations and/or pathways as follows: Light green signifies a direct involvement in glyoxysomal glyoxylate cycle and β-oxidation; light blue signifies a cytosolic location; yellow signifies mitochondrial TCA cycle; orange signifies plastidial glycolysis and OPPP; light purple signifies the vacuole; pink signifies the ER membrane. Dark purple arrows represent the transports of metabolite and energy across intracellular membrane by specific transporters. All transporters involved in carbon flux allocation and energy provision for oil synthesis and TAG mobilization are shown in yellow. Abbreviations for the transporters, enzymes and metabolites are as follows: AAC ATP/ADP carrier, ACBP acyl-CoA-binding protein, ACO aconitase, ACX acyl-CoA oxidase, ADNT adenine nucleotide carrier, AtUTr nucleotide sugar transporter, BASS pyruvate (PYR) carrier (bile acid: sodium symporter family protein), BOU acetyl-carnitine/carnitine carrier, BT1L adenine nucleotide uniporter, CN cetane number, CFPP cold filter plugging point, CP cloud point, CTS COMATOSE, CYS citrate synthase, D density, DIC dicarboxylate carrier, DTC dicarboxylate/tricarboxylate carrier, ER endoplasmic reticulum, ER-ANT1 ER membrane ATP transporter, F6P fructose-6-phosphate, FAMEs FA methyl esters, FAX FA exporter, GAP glyceraldehyde 3-phosphate, GLT glycolipid transporter, GPT glucose-6-phosphate (G6P) transporter, ICL isocitrate lyase, IV iodine value, KAT 3-ketoacyl-CoA thiolase, KV kinematic viscosity, LACS long-chain acyl-CoA synthase, LTPs lipid transfer proteins, MLS malate (Mal) synthase, gMDH glyoxysomal NAD-Mal dehydrogenase, MPC1 PYR carrier, NTT nucleoside triphosphate (NTP) transporter, OPPP oxidative pentose phosphate pathway, OS oxidation stability, PC phosphatidylcholine, PEPCK phosphoenolpyruvate (PEP) carboxykinase, PHT phosphate (Pi) transporter, PIC Pi carriers, PNC peroxisomal adenine nucleotide carrier, PPT PEP transporter, PRK phosphoribulokinase, RBCS ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) small subunit, RPE ribulose-5-phosphate (Ru5P) epimerase, RPI ribose 5-phosphate isomerase, SBP sedoheptulose-bisphosphatase, SDP1 sugar dependent 1, SFC succinate (SUC)/fumarate carrier, SUT sucrose transporter, TA transaldolase, TAG triacylglycerol, TAGL TAG lipase, TCA tricarboxylic acid, TK transketolase, TMT tonoplast monosaccharide transporter, TPT triose phosphate (TP) transporter, VGT vacuolar glucose transporter, XPT xylulose 5-phosphate (X5P)/phosphate transporter