BackgroundRare cell subtypes can profoundly impact the course of human health and disease, yet their presence within a sample is often missed with bulk molecular analysis. Single-cell analysis tools such as FACS, FISH-FC and single-cell barcode-based sequencing can investigate cellular heterogeneity; however, they have significant limitations that impede their ability to identify and transcriptionally characterize many rare cell subpopulations.ResultsPCR-activated cell sorting (PACS) is a novel cytometry method that uses single-cell TaqMan PCR reactions performed in microfluidic droplets to identify and isolate cell subtypes with high-throughput. Here, we extend this method and demonstrate that PACS enables high-dimensional molecular profiling on TaqMan-targeted cells. Using a random priming RNA-Seq strategy, we obtained high-fidelity transcriptome measurements following PACS sorting of prostate cancer cells from a heterogeneous population. The sequencing data revealed prostate cancer gene expression profiles that were obscured in the unsorted populations. Single-cell expression analysis with PACS was subsequently used to confirm a number of the differentially expressed genes identified with RNA sequencing.ConclusionsPACS requires minimal sample processing, uses readily available TaqMan assays and can isolate cell subtypes with high sensitivity. We have now validated a method for performing next-generation sequencing on mRNA obtained from PACS isolated cells. This capability makes PACS well suited for transcriptional profiling of rare cells from complex populations to obtain maximal biological insight into cell states and behaviors.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-016-2694-2) contains supplementary material, which is available to authorized users.
Single cell analysis tools are crucial to better understand the role that rare or heterogeneous cancer cells play in the evolution of tumor progression. Although, it is now feasible to perform single-cell RNA-Seq on thousands of, several challenges remain for high-throughput single-cell DNA sequencing. To address these challenges and enable the characterization of genetic diversity in cancer cell populations, we developed a novel approach that barcodes amplified genomic DNA of individual cells confined to microfluidic droplets. The barcodes are used to reassemble the genetic profiles of individual cells from next generation sequencing data. A key feature of our approach is the “two-step” microfluidic workflow that releases genomic DNA from cellular proteins prior to amplification. The microfluidic workflow first encapsulates individual cells in droplets, lyses the cells and prepares the lysate for genomic DNA amplification using proteases. Following this lysate preparation step, the proteases are inactivated and droplets containing the genomes of individual cells are then paired with molecular barcodes and PCR reagents. We demonstrate that the two-step microfluidic approach is vastly superior to workflows without the two-step process for efficient DNA amplification on tens of thousands of individual cells per run with high coverage uniformity and low allelic dropout of targeted genomic regions. To apply our single-cell sequencing technology to the study of acute myeloid leukemia (AML), we developed a targeted panel to sequence genes frequently mutated in AML including TP53, DNMT3A, FLT3, NPM1, NRAS, KRAS, JAK2, IDH1 and IDH2. Using this panel, we were able to identify clonal populations from AML research samples; moreover, the single-cell nature of our approach enabled the correlation of multiple mutations within subclones and determination of whether the mutations existed as as a homozygote or heterozygote. Collectively, our results show a greater degree of heterogeneity in AML tumor samples than is commonly appreciated with bulk sequencing methods. Citation Format: Dennis Eastburn, Maurizio Pellegrino, Sebastian Treusch, Adam Sciambi, Bill Hyun, Jamie Yates. High-throughput clonal analysis of AML tumors with droplet microfluidics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 5398. doi:10.1158/1538-7445.AM2017-5398
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