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Single-Cell Digital Lysates Generated by Phase-Switch Microfluidic Device Reveal Transcriptome Perturbation of Cell Cycle

机译:由相控微流装置产生的单细胞数字裂解物揭示了细胞周期的转录组扰动。

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摘要

With conventional gene expression profiling, information concerning cellular heterogeneity is often lost in the physical mixing and averaging of millions of cells. Single-cell transcriptome analysis has the potential to address these issues. However, there is a need to determine how many cells are needed to draw meaningful conclusions in each single-cell study. Here, we introduce the concept of “digital lysate” for assessing cellular heterogeneity with a phase-switch microfluidic platform and apply it to construct a molecular map of transcriptome perturbation during the cell cycle. Using a phase-switch droplet microfluidic platform and next-generation sequencing, we obtained transcriptomes of single cells by random sampling. Digital lysates were generated by permutating and averaging multiple single-cell transcriptomes. In our studied cell populations, digital lysates converged to physical lysates (r = 0.93), and the sample-to-sample repeatability was comparable to that of conventional analysis of a physical lysate (r = 0.98). After determining the number of cells needed, single-cell transcriptomes were used to organize cells into a map by molecular similarity, and the map was validated by cell cycle-specific markers (p = 0.003). Cell cycle regulatory genes were inferred using this molecular map and verified with siRNA assays. The study described here provides an effective approach, the generation and analysis of digital lysates, to investigate cellular heterogeneity.
机译:使用常规的基因表达谱分析,有关细胞异质性的信息经常在数百万个细胞的物理混合和平均过程中丢失。单细胞转录组分析具有解决这些问题的潜力。但是,需要确定每个单细胞研究需要多少个细胞才能得出有意义的结论。在这里,我们介绍了“数字裂解物”的概念,用于通过相控微流平台评估细胞异质性,并将其应用于构建细胞周期中转录组扰动的分子图。使用相控滴微流控平台和下一代测序,我们通过随机采样获得了单细胞的转录组。通过对多个单细胞转录组进行置换和平均来生成数字裂解物。在我们研究的细胞群体中,数字裂解物收敛于物理裂解物(r = 0.93),并且样品间的重复性与传统的物理裂解物分析相当(r = 0.98)。在确定所需的细胞数量后,使用单细胞转录组通过分子相似性将细胞组织成图​​,并通过细胞周期特异性标记物验证该图(p = 0.003)。使用该分子图谱推断细胞周期调节基因,并用siRNA测定法验证。此处描述的研究提供了一种有效的方法,数字裂解物的产生和分析,以研究细胞异质性。

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