Live-seq enables temporal transcriptomic recording of single cells.
Live-seq enables temporal transcriptomic recording of single cells.
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DOI：
10.1038/s41586-022-05046-9
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发表时间：
2022-08
期刊：
影响因子：
64.8
通讯作者：
Deplancke, Bart
中科院分区：
文献类型：
--
作者：
Chen, Wanze;Guillaume-Gentil, Orane;Rainer, Pernille Yde;Gaebelein, Christoph G.;Saelens, Wouter;Gardeux, Vincent;Klaeger, Amanda;Dainese, Riccardo;Zachara, Magda;Zambelli, Tomaso;Vorholt, Julia A.;Deplancke, Bart
单细胞转录学(scRNA-seq)极大地提高了我们表征细胞异质性的能力。然而，scRNA-seq需要裂解细胞，这阻碍了对相同细胞的进一步分子或功能分析。在这里，我们建立了Live-Seq，这是一种单细胞转录组分析方法，在使用流体力显微镜提取RNA期间保留细胞活性，从而允许将细胞的基态转录组与其下游分子或表型行为耦合。为了对Live-Seq进行基准测试，我们使用了细胞生长、功能反应和全细胞转录组读出来证明Live-Seq可以准确地对不同的细胞类型和状态进行分层，而不会引起重大的细胞扰动。作为概念的证明，我们展示了Live-Seq可以通过顺序地描绘单个巨噬细胞在脂多糖(LPS)刺激之前和之后以及脂肪基质细胞在分化前和分化后的转录图谱来直接绘制细胞的轨迹。此外，我们证明Live-Seq可以通过预先注册单个巨噬细胞的转录本来发挥转录记录器的功能，这些转录本随后在脂多糖暴露后通过时间推移成像进行监测。这使得能够根据基因影响巨噬细胞内毒素反应异质性的能力对基因进行无监督的全基因组排序，揭示了基础Nfkbia表达水平和细胞周期状态是重要的表型决定因素，我们通过实验验证了这一点。因此，Live-Seq可以通过将scRNA-seq从终点转换为时间分析方法来解决广泛的生物学问题。LIVE-SEQ是一种单细胞转录组分析方法，在使用流体力显微镜提取RNA的过程中保持细胞活性，可以通过将scRNA-SEQ从终点转换为时间分析方法来解决一系列生物学问题。
Single-cell transcriptomics (scRNA-seq) has greatly advanced our ability to characterize cellular heterogeneity. However, scRNA-seq requires lysing cells, which impedes further molecular or functional analyses on the same cells. Here, we established Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy, thus allowing to couple a cell’s ground-state transcriptome to its downstream molecular or phenotypic behaviour. To benchmark Live-seq, we used cell growth, functional responses and whole-cell transcriptome read-outs to demonstrate that Live-seq can accurately stratify diverse cell types and states without inducing major cellular perturbations. As a proof of concept, we show that Live-seq can be used to directly map a cell’s trajectory by sequentially profiling the transcriptomes of individual macrophages before and after lipopolysaccharide (LPS) stimulation, and of adipose stromal cells pre- and post-differentiation. In addition, we demonstrate that Live-seq can function as a transcriptomic recorder by preregistering the transcriptomes of individual macrophages that were subsequently monitored by time-lapse imaging after LPS exposure. This enabled the unsupervised, genome-wide ranking of genes on the basis of their ability to affect macrophage LPS response heterogeneity, revealing basal Nfkbia expression level and cell cycle state as important phenotypic determinants, which we experimentally validated. Thus, Live-seq can address a broad range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach. Live-seq, a single-cell transcriptome profiling approach that preserves cell viability during RNA extraction using fluidic force microscopy, can address a range of biological questions by transforming scRNA-seq from an end-point to a temporal analysis approach.
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DOI：
10.1093/bioinformatics/btu638
发表时间：
2015-01-15
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Anders S;Pyl PT;Huber W
通讯作者：
Huber W
影响因子：
64.5
作者：
Guillaume-Gentil, Orane;Grindberg, Rashel V.;Vorholt, Julia A.
通讯作者：
Vorholt, Julia A.
DOI：
10.1126/science.1256272
发表时间：
2014-11-14
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Farzadfard F;Lu TK
通讯作者：
Lu TK
影响因子：
14.8
作者：
Islam, Saiful;Kjallquist, Una;Linnarsson, Sten
通讯作者：
Linnarsson, Sten
影响因子：
14.9
作者：
Ji Z;Ji H
通讯作者：
Ji H