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中国生物工程杂志

China Biotechnology
China Biotechnology
China Biotechnology  2018, Vol. 38 Issue (11): 42-50    DOI: 10.13523/j.cb.20181106
    
Identification of a Marine Microalgae and Optimization of Protoplast Preparation
Li ZHANG1,Juan DING1,Yu-cheng HAO2,Cheng YE2,Yang PU2,**()
1. School of Life Sciences Ludong University, Yantai 264000, China
2. School of Agriculture Ludong University, Yantai 264000, China
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Abstract  

A unicellular marine microalgae was isolated at the seaside of Yantai. Both morphological identification and sequence analysis of 18S rDNA showed that this eukaryotic marine microalgae strain is Tetraselmis sp., named 138 algae. A Box-Behnken central composite design was utilized as an optimization of protoplast preparation rate within the experimental range. An equation was obtained to fit the empirical evidence of protoplast formation rate (Y).Y1=88.30-0.19X1+2.44X2+2.28X3-0.95X1X2-3.13X1X3+3.78X2X3-9.85$X_{1}^{2}$-7.95$X_{2}^{2}$-7.22$X_{3}^{2}$. The optimum conditions of protoplasts formation was cellulose: macerozyme at 5:2, concentration of mixed enzymes at 4.5% (2.7% cellulose and 1.8% macerozyme) and buffer pH at 6.4. The theoretical maximum rate is 81.5%. Three parallel verification test proved actual measured rate is 80.5%. The error between model prediction and experimental testing is about 1.24%. Then the transformation efficiency of protoplast was confirmed by the transient expression of GFP gene.

Key words： Molecular identification      Protoplast preparation      Response surface optimization     
Received: 13 July 2018      Published: 06 December 2018
ZTFLH:  Q813  
Corresponding Authors: Yang PU     E-mail: 176736518@qq.com
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Li ZHANG
Juan DING
Yu-cheng HAO
Cheng YE
Yang PU
Cite this article:

Li ZHANG,Juan DING,Yu-cheng HAO,Cheng YE,Yang PU. Identification of a Marine Microalgae and Optimization of Protoplast Preparation. China Biotechnology, 2018, 38(11): 42-50.

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https://manu60.magtech.com.cn/biotech/10.13523/j.cb.20181106     OR     https://manu60.magtech.com.cn/biotech/Y2018/V38/I11/42

变量 -1 0 1
酶比例 1:1 3:2 4:1
酶浓度(%) 1.25 2.5 5
pH 6.0 6.5 7.0
Table 1 Factors and levels used in response surface experiments
Fig.1 The morphology of 138
Fig.2 Agarose gel electrophoresis of total DNA (a) and PCR (b) S: Total DNA of 138; 1, 2: Produces of PCR; M: DL 2000 DNA marker
Fig.3 Sequence of 18S rDNA gene of 138
Fig.4 Phylogenetic tree based on 18S rDNA
Fig.5 The protoplast morphology of 138 under different enzymatic hydrolysis treats (10×100) (a)Untreated (b) 8h treated (c) 10h treated (d) 30h treated (e) In hypertonic solution (f) In hypotonic solution
Fig.6 The protoplast rate with different enzyme ratios (a), different concentrations of enzyme (b) and different pH (c)
Run No. X1 X2 X3 Y1(%)
1 -1 -1 0 69.4
2 -1 1 0 69.7
3 1 -1 0 73.2
4 1 1 0 70.1
5 0 -1 -1 68.3
6 0 -1 1 66.6
7 0 1 -1 72.1
8 0 1 1 85.5
9 -1 0 -1 67.8
10 1 0 -1 71.4
11 -1 0 1 77.3
12 1 0 1 68.4
13 0 0 0 86.3
14 0 0 0 90.1
15 0 0 0 92.4
16 0 0 0 88.4
17 0 0 0 84.3
Table 2 Box-Behnken experimental design with three independent variable
项目平方和 自由度 均方 F值 P值
模型 1 185.95 9 131.77 6.70 0.010 1 Significant
X1酶比 0.28 1 0.28 0.014 0.908 2
X2浓度 47.53 1 47.53 2.42 0.164 0
X3 pH 41.41 1 41.41 2.11 0.190 0
X1X2 3.61 1 3.61 0.18 0.681 2
X1X3 39.06 1 39.06 1.99 0.201 5
X2X3 57.00 1 57.00 2.90 0.132 4
X12 408.52 1 408.52 20.78 0.002 6
X22 266.12 1 266.12 13.53 0.007 9
X32 219.79 1 219.79 11.18 0.012 4
残差 137.64 7 19.66
失拟项 97.58 3 32.53 3.25 0.142 5 Not significant
净误差 40.06 4 10.02
总离差 1 323.59 16
Table 3 Analysis of variance regression model of 138
Fig.7 Protoplast preparation rate of 138 response surface map
Fig.8 GFP transient expression(a) Image under white light (b) Image under fluorescence excitation Bar = 10μm
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