白鸟
(2024-01-31 23:02):
#paper doi:10.1038/s41592-023-02117-1 SEVtras delineates small extracellular vesicles at droplet resolution from single-cell transcriptomes.因工作需要搜到这篇文献,
1.囊泡功能简介:胞外小囊泡(sEV)是由细胞分泌的微小囊泡,携带蛋白质、脂质和RNA等多种内容物,广泛存在于组织微环境中,充当细胞间信息交流的“信使”角色,生理病理过程中的关键参与者。
2.待解决:目前缺乏能够捕获到sEV复杂异质性和追踪sEV分泌的潜在细胞的高通量技术,需要证实检出的滴液为囊泡,
3.胞外小囊泡异质性追踪算法SEVtras:判定囊泡的算法,单细胞数据中追踪分泌囊泡的细胞来源;不同样本来源,广泛论证算法可行性;
从公共数据库中汇总胞外小囊泡关联基因集,利用最大期望算法(expectation–maximization, EM)推断单个液滴中胞外小囊泡的信号分值;
4.我的疑惑:对于细胞的身份和生物学功能研究是不容易的,囊泡的研究更甚,该算法可能需要更多的基准测试来证实;单细胞技术和囊泡是否适用;如何解析有限信息的囊泡表达谱?
问题1:判定捕获的barcode是不是为真实的囊泡--->通过SEVtras判别;
问题2:先暂不判定barcode身份(假定为真实的囊泡),基因表达谱可以分析出哪些内容?--->通过高表达基因的富集分析;
SEVtras delineates small extracellular vesicles at droplet resolution from single-cell transcriptomes
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Abstract:
Small extracellular vesicles (sEVs) are emerging as pivotal players in a wide range of physiological and pathological processes. However, a pressing challenge has been the lack of high-throughput techniques capable of unraveling the intricate heterogeneity of sEVs and decoding the underlying cellular behaviors governing sEV secretion. Here we leverage droplet-based single-cell RNA sequencing (scRNA-seq) and introduce an algorithm, SEVtras, to identify sEV-containing droplets and estimate the sEV secretion activity (ESAI) of individual cells. Through extensive validations on both simulated and real datasets, we demonstrate SEVtras' efficacy in capturing sEV-containing droplets and characterizing the secretion activity of specific cell types. By applying SEVtras to four tumor scRNA-seq datasets, we further illustrate that the ESAI can serve as a potent indicator of tumor progression, particularly in the early stages. With the increasing importance and availability of scRNA-seq datasets, SEVtras holds promise in offering valuable extracellular insights into the cell heterogeneity.
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