No detectable alloreactive transcriptional responses under standard sample preparation conditions during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells.
No detectable alloreactive transcriptional responses under standard sample preparation conditions during donor-multiplexed single-cell RNA sequencing of peripheral blood mononuclear cells.
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DOI：
10.1186/s12915-020-00941-x
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发表时间：
2021-01-20
期刊：
影响因子：
5.4
通讯作者：
Lee SA
中科院分区：
文献类型：
--
作者：
McGinnis CS;Siegel DA;Xie G;Hartoularos G;Stone M;Ye CJ;Gartner ZJ;Roan NR;Lee SA
单细胞RNA测序（scRNA - seq）可对单个细胞中的转录本数量进行高维度测量。然而，检测成本高昂以及在多个测序批次中分析样本时产生的人为误差限制了对大量样本的研究。样本复用技术，如MULTI - seq以及使用单细胞复用试剂盒（SCMK）试剂（BD生物科学公司）的抗体哈希技术，利用样本特异性序列标签使单个样本能够以混合形式进行测序，显著降低了每个样本的处理和测序成本，同时将技术人为误差降至最低。但关键的是，混合样本可能会引入新的人为误差，部分抵消了样本复用的优势。特别是，到目前为止，还没有研究评估在标准的scRNA - seq样本制备条件下（例如，在4°C下共孵育30分钟）混合来自无亲缘关系供体的外周血单个核细胞（PBMC）是否会因同种异体反应（即对非自身的反应）导致基因表达发生显著变化。能够证明同种异体反应极小甚至不存在对于避免数据混淆分析至关重要，特别是对于评估免疫基因特征变化的横断面研究。
在此，我们将10x Genomics的scRNA - seq平台应用于来自单个供体的经MULTI - seq和/或SCMK标记的PBMC，以及在4°C下将其与来自无亲缘关系供体的PBMC混合或不混合共孵育30分钟的情况。我们通过多种指标未检测到混合与未混合的PBMC之间存在任何同种异体反应信号，这些指标包括CD4 + T细胞中同种异体反应标记基因的表达、细胞类型比例的变化以及使用基因集富集分析和詹森 - 香农散度进行的全局基因表达谱比较。这些结果在使用类似实验设计生成的公开可用的scRNA - seq数据中也得到了印证。此外，我们还发现了与PBMC制备方法（例如，Trima血细胞分离术）相关的混淆性基因表达特征，以及SCMK样本对活化的CD4 + T细胞的分类偏差，这在另外两个包含SCMK的scRNA - seq数据集中也有所体现。
我们证明了（i）在标准的scRNA - seq样本制备条件下（例如，在4°C下共孵育30分钟）混合来自无亲缘关系供体的PBMC不会引起同种异体反应，以及（ii）使用SCMK试剂进行的Trima血细胞分离术和PBMC样本复用会给scRNA - seq数据引入不良的技术人为误差。总体而言，这些观察结果为未来的横断面免疫scRNA - seq实验建立了重要的基准。
本文的补充信息可在10.1186/s12915 - 020 - 00941 - x获取。
Single-cell RNA sequencing (scRNA-seq) provides high-dimensional measurements of transcript counts in individual cells. However, high assay costs and artifacts associated with analyzing samples across multiple sequencing runs limit the study of large numbers of samples. Sample multiplexing technologies such as MULTI-seq and antibody hashing using single-cell multiplexing kit (SCMK) reagents (BD Biosciences) use sample-specific sequence tags to enable individual samples to be sequenced in a pooled format, markedly lowering per-sample processing and sequencing costs while minimizing technical artifacts. Critically, however, pooling samples could introduce new artifacts, partially negating the benefits of sample multiplexing. In particular, no study to date has evaluated whether pooling peripheral blood mononuclear cells (PBMCs) from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) results in significant changes in gene expression resulting from alloreactivity (i.e., response to non-self). The ability to demonstrate minimal to no alloreactivity is crucial to avoid confounded data analyses, particularly for cross-sectional studies evaluating changes in immunologic gene signatures. Here, we applied the 10x Genomics scRNA-seq platform to MULTI-seq and/or SCMK-labeled PBMCs from a single donor with and without pooling with PBMCs from unrelated donors for 30 min at 4 °C. We did not detect any alloreactivity signal between mixed and unmixed PBMCs across a variety of metrics, including alloreactivity marker gene expression in CD4+ T cells, cell type proportion shifts, and global gene expression profile comparisons using Gene Set Enrichment Analysis and Jensen-Shannon Divergence. These results were additionally mirrored in publicly-available scRNA-seq data generated using a similar experimental design. Moreover, we identified confounding gene expression signatures linked to PBMC preparation method (e.g., Trima apheresis), as well as SCMK sample classification biases against activated CD4+ T cells which were recapitulated in two other SCMK-incorporating scRNA-seq datasets. We demonstrate that (i) mixing PBMCs from unrelated donors under standard scRNA-seq sample preparation conditions (e.g., 30 min co-incubation at 4 °C) does not cause an allogeneic response, and (ii) that Trima apheresis and PBMC sample multiplexing using SCMK reagents can introduce undesirable technical artifacts into scRNA-seq data. Collectively, these observations establish important benchmarks for future cross-sectional immunological scRNA-seq experiments. Supplementary information accompanies this paper at 10.1186/s12915-020-00941-x.
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