Isolation of Exosome-Like Nanoparticles and ... - ACS Publications

Feb 25, 2018 - In this study, the presence of microRNAs in coconut water was ... Small Interfering RNA in Milk Exosomes Is Resistant to Digestion and ...
0 downloads 0 Views 3MB Size
Subscriber access provided by MT ROYAL COLLEGE

Article

Isolation of exosome-like nanoparticles and analysis of microRNAs derived from coconut water based on small RNA high-throughput sequencing Zhehao Zhao, Siran Yu, Min Li, Xin Gui, and Ping Li J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.7b05614 • Publication Date (Web): 25 Feb 2018 Downloaded from http://pubs.acs.org on February 25, 2018

Just Accepted “Just Accepted” manuscripts have been peer-reviewed and accepted for publication. They are posted online prior to technical editing, formatting for publication and author proofing. The American Chemical Society provides “Just Accepted” as a service to the research community to expedite the dissemination of scientific material as soon as possible after acceptance. “Just Accepted” manuscripts appear in full in PDF format accompanied by an HTML abstract. “Just Accepted” manuscripts have been fully peer reviewed, but should not be considered the official version of record. They are citable by the Digital Object Identifier (DOI®). “Just Accepted” is an optional service offered to authors. Therefore, the “Just Accepted” Web site may not include all articles that will be published in the journal. After a manuscript is technically edited and formatted, it will be removed from the “Just Accepted” Web site and published as an ASAP article. Note that technical editing may introduce minor changes to the manuscript text and/or graphics which could affect content, and all legal disclaimers and ethical guidelines that apply to the journal pertain. ACS cannot be held responsible for errors or consequences arising from the use of information contained in these “Just Accepted” manuscripts.

Journal of Agricultural and Food Chemistry is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Published by American Chemical Society. Copyright © American Chemical Society. However, no copyright claim is made to original U.S. Government works, or works produced by employees of any Commonwealth realm Crown government in the course of their duties.

Page 1 of 36

Journal of Agricultural and Food Chemistry

Isolation of exosome-like nanoparticles and analysis of microRNAs derived from coconut water based on small RNA high-throughput sequencing

Zhehao Zhao1, Siran Yu1, Min Li1, Xin Gui1, Ping Li1,*

1

Research Center for Translational Medicine at Shanghai East Hospital, School of

Life Science and Technology, Tongji University, Shanghai 200092, PR China

*Corresponding Author: Prof. Ping, Li. Research Center for Translational Medicine at Shanghai East Hospital, School of Life Sciences and Technology, Tongji University, No. 1239, Siping Road, 200092, Shanghai, China. E-mail: [email protected] Tel.: +86 21 65981051; Fax: +86 21 65981041.

1

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 2 of 36

1

Abstract

2

In this study, the presence of microRNAs in coconut water was identified by real-time

3

PCR based on the results of high-throughput small RNA sequencing. In addition, the

4

differences in microRNA content between immature and mature coconut water were

5

compared. A total of 47 known microRNAs belonging to 25 families and 14 new

6

microRNAs were identified in coconut endosperm. Through analysis using a target

7

gene prediction software, potential microRNA target genes were identified in the

8

human genome. Real-time PCR showed that the level of most microRNAs was higher

9

in mature coconut water than in immature coconut water. Then, exosome-like

10

nanoparticles were isolated from coconut water. After ultracentrifugation, some

11

particle structures were seen in coconut water samples by using DiI fluorescence

12

staining. Subsequent SEM observation and DLS analysis also revealed some

13

exosome-like nanoparticles in coconut water, and the mean diameters of the particles

14

detected by the two methods were 13.16 nm and 59.72 nm, respectively. In conclusion,

15

there are extracellular microRNAs in coconut water, and their levels are higher in

16

mature coconut water than in immature coconut water. Some exosome-like

17

nanoparticles were isolated from coconut water, and the diameter of these particles

18

was smaller than that of animal-derived exosomes.

19

20

Keywords: Coconut water; Cocos nucifera; MicroRNA; Nanoparticles; Small RNA

21

sequencing 2

ACS Paragon Plus Environment

Page 3 of 36

Journal of Agricultural and Food Chemistry

22

3

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

23

Page 4 of 36

Introduction

24

MicroRNAs (miRNAs) are small, non-coding RNAs that were first discovered in

25

1993 in Caenorhabditis elegans . miRNAs have been recognized to play a crucial

26

role in a wide range of physiological processes, including cell proliferation and

27

apoptosis , developmental timing , and the immune response .

1

2

3

4

28

According to a study conducted in 2010, despite differences in their types and

29

content, miRNAs could be detected in various body fluids in humans (pleural fluid,

30

peritoneal fluid, cerebrospinal fluid, urine and tears). Current studies on cells and

31

milk suggest that miRNAs are present in certain exosomes

32

from body fluids can reflect the growth status of cells , be used for disease

33

diagnosis

34

exosome-like nanoparticles containing proteins and RNAs have also been found in

35

many kinds of plant sources such as ginger , carrot , watermelon, grapes , olives

36

and melon seeds . Moreover, it was found that exogenous miRNAs in plants can

37

affect mammalian genes; for example, miR168a inhibits LDLRAP1 , and miR159

38

inhibits breast cancer growth . Exosomes in animals were first identified in 1987

39

during mammalian reticulocyte maturation.

40

nanoparticles with potential exosome marker proteins in extracellular fluids from

41

sunflower seeds in 2009.

42

structures, of diameters 28-60 nm, by electron microscopy during the development of

43

olive pollen tubes.

5

6,7

, and these exosomes

8

9–11

12

and affect the growth of cells . In addition to animal body fluids,

13

13

14

15

16

17

18

16

15

19

For plants, Regente et al. found some

In 2014, Prado et al. observed the secretion of nanocystic

However, exosomes had not been given enough attention until 4

ACS Paragon Plus Environment

Page 5 of 36

Journal of Agricultural and Food Chemistry

20–22

44

the discovery of extracellular RNAs in serum and milk in recent years.

As an

45

important part of extracellular vesicles, exosomes form animals and exosome-like

46

nanoparticles from plants have become hot topics for research again.

47

Cocos nucifera L. is the main oil crop in tropical areas (southeastern Asia, from

48

Indonesia to the Pacific Islands) and is also distributed in Hainan and Yunnan

49

provinces in China. The diameter of the coconut fruit is approximately 20 cm, with a

50

rich juice-filled cavity on the inside. The internal juice is called coconut water, also

51

known as liquid endosperm. Coconut water, which is drinkable after being removed

52

from the coconut fruit, is a common drink in tropical areas, with refreshing and

53

thirst-quenching effects. According to the maturity of the fruit, coconut can be divided

54

into young coconut (immature) and old coconut (mature). Juicy immature coconut is

55

sweeter and more delicious than mature coconut. However, the mature coconut is rich

56

in meat but has far less juice than immature coconut.

57

Molecular biological study in coconut has started relatively late compared with 23

58

that in other plants. The coconut chloroplast genome was sequenced in 2013.

59

same year, Fan et al. used RNA-Seq techniques to analyze the transcriptome of

60

coconut.

61

sequences.

62

November 2017 by Xiao et al.

24

In the

The authors also predicted and analyzed a total of 14 conserved microRNA 25

Additionally, the full genome sequence of C. nucifera was publish in 26

63

In this study, total RNA extracted from the water of mature and immature

64

coconut was used for miRNA real-time PCR analysis. However, due to the 5

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 6 of 36

65

particularity of the study sample, not enough total RNA was extracted from the

66

coconut water to be sequenced. Therefore, we carried out small RNA sequencing

67

analysis of coconut endosperm and focused on the type and content of microRNAs.

68

After the species information and sequence data of coconut-derived microRNAs were

69

obtained, we detected extracellular microRNAs in the water of immature and mature

70

coconut by fluorescence-mediated quantitative polymerase chain reaction (PCR) and

71

analyzed the differences in miRNA species and content. The samples were

72

centrifuged by ultracentrifugation, and nanoparticles were observed and detected by

73

scanning electron microscopy, fluorescence microscopy and dynamic light scattering.

74

Materials and Methods

75

Collection and processing of coconut samples

76

Samples from the “Hainan Tall” coconut variant (C. nucifera L.) were obtained

77

from Wenchang City, Hainan Province, China by express delivery, and coconut

78

endosperm and water samples were immediately collected after sample receipt. The

79

method was as follows: after the coconut was opened under aseptic conditions,

80

approximately 10 g of endosperm was taken out by a knife, and endosperms from four

81

coconuts were mixed. After grinding in liquid nitrogen, samples were collected for

82

subsequent experiments or stored at -80°C. The coconut water harvesting method was

83

as follows: under sterile conditions, coconut water was collected from four coconut

84

samples and mixed. Immature and mature coconut water was marked YQ and YH,

85

respectively. Then, 1 mL of the sample was immediately used for RNA extraction, and 6

ACS Paragon Plus Environment

Page 7 of 36

Journal of Agricultural and Food Chemistry

86

the remaining samples were stored at -80°C for subsequent analysis.

87

Coconut water samples used for centrifugation were collected from immature

88

coconuts, and samples were immediately used for subsequent centrifugal separation

89

after collection. The specific steps are described in a later section on coconut water

90

extracellular cystic structure extraction. According to a study by Bosch et al., it was

91

shown that freezing can affect the diameter and morphology of the exosomes.

92

Therefore, to avoid the destruction of cystic structures in coconut water, all

93

centrifugation samples were not subjected cryopreservation to ensure sample integrity.

94

Small RNA sequencing analysis

27

95

Due to the particularity of the sample, total RNA content in coconut water was

96

insufficient for sequencing analysis. Therefore, total RNA was extracted from the

97

coconut endosperm for small RNA sequencing. The sequencing results were used for

98

subsequent primer design for miRNA detection. Total RNA was extracted from 500

99

mg coconut endosperm using TRIzol (Invitrogen, Carlsbad, CA, USA) according to

100

the manufacturer’s instruction. The quality and concentration of total RNA were

101

measured using a Nano Photometer spectrophotometer (IMPLEN, CA, USA). RNA

102

integrity was tested using 1% agarose gels. RNA quality and integrity were further

103

tested using the RNA Nano 6000 Assay Kit and an Agilent Bioanalyzer 2100 system

104

(Agilent Technologies, CA, USA).

105

Approximately 3 µg total RNA was used as input material to construct small

106

RNA library. Sequencing libraries were generated using NEBNext® Multiplex Small 7

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 8 of 36

107

RNA Library Prep Set for Illumina® (NEB, USA) following the manufacturer’s

108

recommendations, and index codes were added to identify each sample. Briefly, NEB

109

3' SR Adaptor was directly and specifically ligated to the 3' end of miRNAs, piRNAs

110

and siRNAs. After the 3' ligation reaction, the SR RT Primer was hybridized to excess

111

3' SR Adaptor to transform the single-stranded DNA adaptor into a double-stranded

112

DNA molecule. This step was important to prevent adaptor-dimer formation.

113

Additionally, as dsDNA is not a substrate for ligation mediated by T4 RNA Ligase 1,

114

it cannot be ligated to the 5´ SR Adaptor in the subsequent ligation step. Thus, 5´ SR

115

Adaptors were ligated to the 5´ ends of miRNAs, siRNAs and piRNAs. Then,

116

first-strand cDNA was synthesized using M-MuLV Reverse Transcriptase (RNase H–).

117

PCR amplification was performed using LongAmp Taq 2X Master Mix, SR Primers

118

for Illumina and index (X) primers. PCR products were purified on an 8%

119

polyacrylamide gel (100 V, 80 min). DNA fragments corresponding to 140~160 bp

120

(the length of small, non-coding RNA plus the 3' and 5' adaptors) were recovered and

121

dissolved in 8 µL elution buffer. Last, library quality was assessed on an Agilent

122

Bioanalyzer 2100 system using DNA High-Sensitivity Chips.

123

Clustering of the index-coded samples was performed on a cBot Cluster

124

Generation System using TruSeq SR Cluster Kit v3-cBot-HS (Illumina) according to

125

the manufacturer’s instructions. After cluster generation, the prepared libraries were

126

sequenced on an Illumina Hiseq 2500/2000 platform, and 50 bp single-end reads were

127

generated.

8

ACS Paragon Plus Environment

Page 9 of 36

Journal of Agricultural and Food Chemistry

128

After obtaining the raw data and removing contaminating sequences, we used the

129

oil palm (Elaeis guineensis) genome as a reference for subsequent small RNA

130

sequence alignment and classification.

131

miRNA target gene prediction and annotation

132

In this study, miRanda was used to predict target genes of all miRNAs in sRNA 28

133

sequencing results.

134

on human genes, the human genome was used as a reference genome for target gene

135

prediction. The following software parameters were used in miRNA target gene

136

prediction: -sc 168 -en -10 -scale 4 -strict -out. All results were used for GO analysis.

137

Because this study focused on the effects of coconut miRNAs

In this study, KOBAS 3.0 was used to perform GO annotation and KEGG 29,30

138

pathway analysis for all microRNA target genes.

According to the type of GO

139

annotation, the genetic functions were divided into biological processes, cell

140

components and analysis functions.

141

Extracellular RNA extraction

142

Total RNA in coconut water samples was isolated by using TRIzol LS Reagent

143

(Invitrogen, Carlsbad, CA, USA) according to the manufacturer’s protocol. Briefly,

144

250 µL sample was mixed well with three volumes of TRIzol LS, followed by

145

incubation for 5 min at room temperature. Next, 200 µL chloroform was added to the

146

homogenate, which was mixed thoroughly by hand, incubated for 15 min at room

147

temperature, and centrifuged (12,000 g, 4°C, 15 min). The resulting aqueous phase

9

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

Page 10 of 36

148

was transferred to another tube, and 500 µL isopropanol was added, and the tube was

149

incubated for 10 min at room temperature and then centrifuged (12,000 g, 4°C, 10

150

min) again. The precipitate was resuspended in 75% ethanol and centrifuged (7500 g,

151

4°C, 5 min). The air-dried RNA was finally eluted with 8 µL RNase-free water. The

152

concentration of RNA was determined with a spectrophotometer (NanoVue PLUS,

153

GE Healthcare, USA). The purified total RNA samples were used for the following

154

experiments, and remaining samples were stored at -80°C for further analysis.

155

In addition, due to the absence of a suitable internal reference gene in coconut

156

water, an additional synthetic short-chain miRNA was used as an exogenous gene for

157

the quantification of miRNA concentration in this study. Synthetic miRNA CR100

158

(Tiangen Biotech (Beijing) Co., Ltd., China) was used as an external control for

159

miRNAs.

160

microRNA reverse transcription and quantitative PCR

161

Quantitative PCR (QPCR) was performed using an ABI PRISM 7500 system

162

(Applied Biosystems, USA). Briefly, 200 ng of miRNA was reverse transcribed using

163

the miRcute Plus miRNA First-Strand cDNA Kit (KR211, Tiangen, China).

164

Quantitative PCR was performed with the miRcute Plus miRNA QPCR Detection Kit

165

(FP411, Tiangen, China). An external control for miRNAs was used (CR100, Tiangen,

166

China). The reaction solution was prepared on ice and was composed of 10 µL of 2×

167

miRcute miRNA Premix, 0.4 µL of PCR forward primer (10 µM), 0.4 µL of PCR

168

reverse Primer (10 µM), 2 µL of cDNA, and ddH2O in a final volume of 20 µL. The 10

ACS Paragon Plus Environment

Page 11 of 36

Journal of Agricultural and Food Chemistry

169

following QPCR program was used: initial activation (95°C, 15 min), 5 cycles of low

170

level microRNA enrichment (94°C, 20 s; 65°C, 30 s; and 72°C, 34 s) followed by 40

171

to 45 cycles of denaturation (94°C, 20 s) and extension (60°C, 34 s). All reactions

172

were performed in triplicate. The forward primers for the miRNA had the same

173

sequences as those used for sRNA sequencing, and the Tm of all of the forward

174

primers was adjusted to 65°C following the manufacturer’s instructions.

175

Extracellular nanoparticle isolation

176

Fresh coconut water and milk were used for nanoparticle isolation. The 31,32

177

nanoparticles were isolated by using a previously described method.

Fresh

178

coconut water or milk samples were centrifuged three times at 4°C for 30 min each at

179

300 g, 1500 g and 7000 g to remove cells, large debris and fat, respectively.

180

Supernatant was prepared by ultracentrifugation (Avanti J-25 and Optima L-100XP,

181

Beckman Coulter, U.S.) at 50,000 g, 70,000 g, 100,000 g and 130,000 g for 1 h,

182

followed by filtration through 0.22-µm filters to obtain solutions of nanoparticles.

183

Nanoparticle samples were stored at 4°C for SEM and DLS analysis. The remaining

184

samples were stored at -80°C for further analysis.

185

Dynamic light scattering (DLS)

186

The size distribution of nanoparticles was determined at 25°C using a Zetasizer

187

range (Nano-ZS 90, Malvern, UK) with standard settings. The size distribution of

188

nanoparticles is related to the intensity of the light scattered by each particle. All the

189

nanoparticles were diluted 1:1000 with PBS before DLS analysis. 11

ACS Paragon Plus Environment

Journal of Agricultural and Food Chemistry

190

Page 12 of 36

Scanning electron microscopy (SEM)

191

The exosome-like vesicles were fixed with 3.7% glutaraldehyde in PBS for 24 h

192

at 4°C, followed by washing with PBS for 10 min. Next, the samples were dehydrated

193

in an ethanol series (50%, 60%, 70%, 80%, 90% and 99%). The samples were

194

maintained in contact with each solution for 10 min. Finally, the samples were

195

air-dried for at least 24 h, mounted on aluminum stubs, and gold-plated before

196

examination with an SEM instrument (S-4800, Hitachi, Japan) operating at 3.0 kV.

197

Fluorescence staining of exosome-like nanoparticles

198

In this study, we used DiI as a fluorescent dye to label the isolated nanoparticles.

199

DiI is a lipophilic dye that is commonly used to stain the cell membrane. According to

200

the report that the outer layer of exosomes is similar to the cell membrane and made

201

of a phospholipid layer

202

Therefore, DiI was used to stain the samples obtained by ultracentrifugation. The final

203

concentration of the dye was 1 µM. The fluorescence microscope used was Nikon

204

ECLIPSE 80i. The excitation wavelength was 549 nm corresponding to green laser.

205

Statistical analysis

33

and can be stained with a membrane-specific dye.

34,35

206

Data are expressed as the mean±standard error of the mean. Multiple

207

comparisons were performed using one-way ANOVA. Statistical analysis was

208

performed using Excel 2016. All data are representative of three independent

209

experiments (n=3 error bars, SEM) Statistical significance was represented as follows:

12

ACS Paragon Plus Environment

Page 13 of 36

Journal of Agricultural and Food Chemistry

210

*p