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SMARTer ICELL8 citations
Our collaborators and customers are constantly making scientific breakthroughs. Here are the latest published results obtained using the SMARTer ICELL8 Single-Cell System.
Aarts, M. et al. Coupling shRNA screens with single-cell RNA-seq identifies a dual role for mTOR in reprogramming-induced senescence. Genes Dev. 31, 2085–2098 (2017).
By carrying out single-cell RNA-seq and shRNA screening in parallel, the speed at which gene candidates from such functional screenings can be identified and validated can be significantly increased. The authors of this study investigated mediators of reprogramming-induced senescence. After an initial shRNA screen identified four candidate genes (MTOR, CDKN1A, MYOT, and UBE2E1) whose knockdown bypassed reprogramming-induced senescence, the SMARTer ICELL8 Single-Cell System was used to prepare RNA-seq libraries on cells infected with shRNAs targeting each of these candidates. Further investigation revealed that mTOR inhibition has an antagonistic effect during cellular reprogramming. The SMARTer ICELL8 platform's flexible cell-size isolation and its available sensitive library preparation chemistries were key to accelerating discovery from the screening process by simultaneously allowing shRNA identification and transcriptome analysis from the RNA-seq data of the processed single cells.
Bergiers, I. et al. Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis. Elife 7, e29312 (2018).
Researchers from the European Molecular Biology Laboratory describe applying single-cell transcriptomics to characterize complex transcription factor dynamics during embryonic hematopoiesis in mouse endothelium in this study. The SMARTer ICELL8 Single-Cell System was used to isolate and process i8TF embryonic stem cells for single-cell RNA sequencing to understand the gene regulatory network. Overall the researchers identified seven transcription factors whose co-expression was specific to pre-hematopoietic stem and progenitor cells. Furthermore, within this heptad, Erg and Fli1 promoted an endothelial cell fate, while Runx1 and Gata2 promoted a hematopoietic fate.
Gao, R. et al. Nanogrid single-nucleus RNA sequencing reveals phenotypic diversity in breast cancer. Nat. Commun. 8, 228 (2017).
The researchers utilized the SMARTer ICELL8 Single-Cell System to demonstrate strong concordance between transcriptional profiling data generated from single cells and nuclei obtained from a cancer cell line. Common single-cell RNA-seq protocols for transcriptome analysis are incompatible with cancer cells derived from flash frozen archival tissue specimens because the preservation process disrupts the cell membranes. The SMARTer ICELL8 platform's flexibility to allow isolation of nuclei and fixed frozen cells enabled the generation of representative, high-quality RNA-seq data from the samples. This method provides a powerful new solution for working with archival samples because nuclear membranes are not usually disrupted by freeze-thaw cycles. In the article, the authors state that "transcriptome profiles of nuclei are highly representative of whole cells, and can be used to study many cancer genes and signaling pathways."
Goldstein, L. D. et al. Massively parallel nanowell-based single-cell gene expression profiling. BMC Genomics 18, 519 (2017).
In this study, RNA-seq was performed to profile the transcriptomes of single cells derived from cultured cells and complex tissues. Using the SMARTer ICELL8 Single-Cell System, the researchers were able to discriminate profiles obtained from a mixture of human and mouse cells processed on a single chip, as demonstrated by a low multiplet rate (<3%). Furthermore, minimal cross-contamination was observed in this experiment as indicated by the high single-cell purity (94–97%). Other findings show the ability to distinguish representative cell types within mouse pancreatic islet samples. The SMARTer ICELL8 platform's imaging capabilities for identifying single-cell-containing wells from empty and multiple-cell-containing wells was crucial for ensuring the high single-cell purity and low multiplet rate observed in this study.
Hochgerner, H. et al. STRT-seq-2i: dual-index 5ʹ single cell and nucleus RNA-seq on an addressable microwell array. Sci. Rep. 7, 16327 (2017).
The researchers developed the STRT-seq-2i method, a 9,600-microwell array platform compatible with adapted STRT-seq chemistry that allows dual indexing. First, cells are sorted by limiting dilution or FACS. Taking advantage of the high-throughput dispensing of the SMARTer ICELL8 Single-Cell System, the cells are then dispensed to the microwell plate. The imaging capabilities of the SMARTer ICELL8 system then allowed for the verification of true single-cell wells. This method allowed a high degree of flexibility for performing STRT-seq-2 at a competitive cost.
Kim, C. et al. Chemoresistance evolution in triple-negative breast cancer delineated by single-cell sequencing. Cell 173, 879–893.e13 (2018).
This study describes a model for chemoresistance evolution in triple-negative breast cancer (TNBC) in response to neoadjuvant chemotherapy (NAC). A combination of single-cell DNA and RNA sequencing was used for the overall study. The SMARTer ICELL8 Single-Cell System was used to extract nuclei from frozen longitudinal samples from TNBC patients treated with NAC. RNA-seq was performed to profile the transcriptomes of 3,370 single nuclei from patients with clonal extinction. The SMARTer ICELL8 system allowed an average of ~500 nuclei to be examined from patients with clonal extinction, resulting in 1.2 million reads and 4,107 genes detected per cell. Additionally, an average ~400 nuclei were analyzed from patients with clonal persistence, resulting in 1.2 million reads and 5,166 genes detected per well.
Liang, Q. et al. Single-nuclei RNA-seq on human retinal tissue provides improved transcriptome profiling. bioRxiv 468207 (2018).
This paper presents the first single-nuclei, RNA-seq-based transcriptomic study on human neural retinal tissue. As an alternative to single-cell RNA-seq, this method is more practical for human tissue study, as it can be applied to frozen neuronal tissue. Single nuclei capture was performed on the SMARTer ICELL8 Single-Cell System and automated well selection was performed using the included CellSelect Software. The authors sequenced 6,544 nuclei from six samples, and on average, 31,783 mapped reads were obtained per nucleus.Single-nuclei profiles showed good correlation with bulk RNA-seq of the same sample, and cell type profiles also displayed consistency with published human retinal cell markers.
Massaia, A et al. Single Cell Gene Expression to Understand the Dynamic Architecture of the Heart. Frontiers in Cardiovascular Medicine 5, 167 (2018).
In this review article, researchers from the British Heart Foundation Center and the Wellcome Trust Sanger Institute discuss guidelines for designing single cell experiments. The need for a single cell automation system, like the SMARTer ICELL8 Single-Cell System, that can work with cardiomyocytes and other similar large cells is highlighted. Such tools can lead to significant advancements in single cell transcriptomics and contribute to outstanding exploratory and functional studies of cardiac development and disease models.
Mezger, A. et al. High-throughput chromatin accessibility profiling at single-cell resolution. Nat. Commun. 9, 3647 (2018).
To measure the physical accessibility of DNA in whole cells, the researchers developed a single-cell-based assay for transposase-accessible chromatin using sequencing (scATAC-seq). The method takes advantage of the SMARTer ICELL8 Single-Cell System open platform system, and nanowell-based chips to improve throughput by nearly 20-fold compared to microfluidic systems. An additional benefit of this high-throughput workflow was the reduced cost per cell (~$0.98).
Tirier, S. M. et al. Pheno-seq - linking 3D phenotypes of clonal tumor spheroids to gene expression. bioRxiv 311472 (2018).
For this study, researchers at the German Cancer Research Center (DKFZ) leveraged the SMARTer ICELL8 Single-Cell System for a high-throughput pheno-seq workflow. The system enabled the automated dispensing and confocal imaging of recovered spheroids in barcoded SMARTer ICELL8 nanowell chips. The custom-developed workflow illustrates the open nature of the SMARTer ICELL8 workflow for which modified image analysis and lysis procedures were developed to accommodate pheno-seq analysis. They were able to successfully demonstrate the correlation of morphological characteristics with the transcriptional profiles, noting that profiling single-spheroids increases sensitivity compared to single-cell analysis of tumor cells (identification of key transcripts missed by scRNA-seq).
Wu, L. et al. Full-length single-cell RNA-seq applied to a viral human cancer: applications to HPV expression and splicing analysis in HeLa S3 cells. Gigascience 4, 51 (2015).
The authors of this study were interested in examining the heterogeneity of a virally induced cancer cell line. The SMARTer ICELL8 Single-Cell System was used to develop a high-throughput method to prepare RNA from single cells. Sequencing of HeLa S3 cells revealed extensive heterogeneity of the cell line in regards to gene expression, alternative splicing, and fusion. Their work not only provides a transcriptome characterization of HeLa S3 cells at the single-cell level but is a demonstration of the power of single-cell RNA-seq analysis of virally infected cells and cancers.
Yang, S. H. et al. ZIC3 controls the transition from naïve to primed pluripotency. bioRxiv 435131 (2018).
The authors examined chromatin accessibility changes accompanying the early transition of mouse ESCs from naïve state to epiblast-like cells (EpiLCs). Single-cell RNA-seq was performed on the SMARTer ICELL8 Single-Cell System using cryogenically frozen cells. A custom script was used to perform assignment and error correction of UMIs, trimming of low-quality reads, and to run checks for corss-species contamination. Expression analysis identified ZIC3 as an important regulatory transcription factor in the establishment and maintenance of the EpiLC state.
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