摘要
采用超高速离心法从人乳中提取出囊泡结构物质,从粒径、形态和外秘体特异性标记蛋白3个方面来确定提取的物质为外泌体。采用高通量测序得到不同泌乳期外泌体中microRNA(miRNA)的表达谱。对表达谱进行分析,在人乳外泌体中共检出852种miRNA,有283种miRNA在早、中、晚3个泌乳期中均有所表达。其中,表达量排名前10位的miRNA占到总量的50%以上。在外泌体中高表达的miRNA(占总外泌体miRNA表达量2%以上的)并没有受到泌乳期的显著影响;而在外泌体中低表达的一些miRNA(占总外泌体miRNA表达量0.01%以下的)容易受到泌乳期的显著影响。此外,发现在人乳外泌体中有88种miRNA与炎症相关,其中有65种在不同泌乳期均稳定表达。综上,人乳外泌体可能具有调控炎症的功能,本研究为更好地研究不同泌乳期人乳外泌体生理功能提供基础数据。
Human milk exosomes were obtained by the ultracentrifugation method and they were identified with particle size,morphology and biomarker proteins.The expestion of microRNA(miRNA)in human milk exosomes of different lactation periods wereobtained by high throughput sequencing technology.This study found that total 852 miRNA were detected in human milk exosomes and there were 283 miRNA expressed stably during the three periods after analyzing the profile of miRNAs.Among them,the top ten miRNA accounted for more than 50%of the total.The expression of high-expressed miRNA(accounted for more than 2%of the total)had no significantly changed during three lactation periods,while the expression of low-expressed miRNA(accounted for less than 0.01%of the total)were significantly changed in different lactation.In addition,there were 88 inflammation-related miRNA in human milk exosome,in which 65 miRNA were stable during different lactation periods.This study suggested that maybe human milk exosomes could regulate inflammation and provided a basis for better understanding the physiological functions of human milk exosomes in different lactation period.
作者
罗雨佳
黄子彧
林莹莹
郭慧媛
Luo Yujia;Huang Ziyu;Lin Yingying;Guo Huiyuan(College of Food Science and Nutritional Engineering,China Agricultural University,Beijing 100083;Department of Nutrition and Health,China Agricultural University,Beijing 100193;National Center of Technology Innovation for Dairy,Beijing 100193)
出处
《中国食品学报》
EI
CAS
CSCD
北大核心
2022年第11期335-342,共8页
Journal of Chinese Institute Of Food Science and Technology
基金
国家自然科学基金面上项目(32072219)。
关键词
人乳外泌体
MIRNA
高通量测序
炎症
human milk exosomes
micoRNA
high throughput sequencing
inflammation
