Isolation of exosome-like nanoparticles and analysis of microRNAs

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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

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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,*

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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.

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Abstract

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

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

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differences in microRNA content between immature and mature coconut water were

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

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

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

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

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

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nanoparticles were isolated from coconut water. After ultracentrifugation, some

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

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staining. Subsequent SEM observation and DLS analysis also revealed some

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

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

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

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

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

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was smaller than that of animal-derived exosomes.

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

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sequencing 2

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Introduction

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

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

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

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apoptosis , developmental timing , and the immune response .

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

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

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

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milk suggest that miRNAs are present in certain exosomes

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

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diagnosis

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

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

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

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

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

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during mammalian reticulocyte maturation.

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nanoparticles with potential exosome marker proteins in extracellular fluids from

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sunflower seeds in 2009.

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

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olive pollen tubes.

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, and these exosomes

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9–11

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

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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

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

As an

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

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nanoparticles from plants have become hot topics for research again.

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

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

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

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

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

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

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

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

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

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in meat but has far less juice than immature coconut.

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

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

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

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coconut.

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sequences.

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November 2017 by Xiao et al.

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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

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

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

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

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

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

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

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

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

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

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centrifuged by ultracentrifugation, and nanoparticles were observed and detected by

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scanning electron microscopy, fluorescence microscopy and dynamic light scattering.

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Materials and Methods

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Collection and processing of coconut samples

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

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

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

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

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

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

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

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

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

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

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

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Coconut water samples used for centrifugation were collected from immature

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coconuts, and samples were immediately used for subsequent centrifugal separation

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

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

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

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

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centrifugation samples were not subjected cryopreservation to ensure sample integrity.

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Small RNA sequencing analysis

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

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

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

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

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

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

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

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

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

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(Agilent Technologies, CA, USA).

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Bioanalyzer 2100 system using DNA High-Sensitivity Chips.

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

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

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

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

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generated.

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

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

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sequence alignment and classification.

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miRNA target gene prediction and annotation

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

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sequencing results.

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

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

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

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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

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pathway analysis for all microRNA target genes.

According to the type of GO

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

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components and analysis functions.

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Extracellular RNA extraction

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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miRNAs.

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microRNA reverse transcription and quantitative PCR

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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Extracellular nanoparticle isolation

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

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nanoparticles were isolated by using a previously described method.

Fresh

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

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

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

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

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

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

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

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Dynamic light scattering (DLS)

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

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

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

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

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Scanning electron microscopy (SEM)

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

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

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

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

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

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

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Fluorescence staining of exosome-like nanoparticles

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

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

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

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of a phospholipid layer

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

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

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

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Statistical analysis

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and can be stained with a membrane-specific dye.

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

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

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

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

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*p