C1 auto prep system

Manufactured by Standard BioTools

Sourced in Cameroon

The C1 Auto Prep System is a fully automated single-cell preparation platform that enables efficient isolation, processing, and analysis of individual cells from a variety of sample types. It provides a streamlined workflow for cell capture, lysis, and nucleic acid preparation, facilitating downstream applications such as genomic and transcriptomic analysis.

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Lab products found in correlation

Smarter ultra low rna kit, by Takara Bio (1 mentions) Hiseq 4000 platform, by Illumina (1 mentions) Fastqc v0, by Babraham Bioinformatics (1 mentions) Trim galore v0, by Babraham Bioinformatics (1 mentions) Real time pcr analysis software, by Standard BioTools (1 mentions) Ethylene diamine tetraacetic acid (edta), by Nacalai Tesque (1 mentions) Te2000 e, by Nikon (1 mentions) Bioanalyzer, by Agilent Technologies (1 mentions)

Spelling variants of this product

C1 system (16 citations) C1TM System (2 citations) C1TM Single-Cell Auto Prep System (2 citations)

5 protocols using c1 auto prep system

Single-cell RNA-seq of skin T cells

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All samples for scRNA-seq were collected between 2013 and 2017 (Supplementary Table 1) and were processed between 2016 and 2018. Capture and processing of single skin T cells was performed using the Fluidigm C1 Autoprep system. Cells were loaded at a concentration of 2,000 cells/µl onto C1 integrated fluidic circuit chips for 5–10 µm cells. All C1 capture sites were microscopically inspected to identify the sites that contained only a single cell. Empty sites and those with multiple cells were excluded from further analysis. External RNA Controls Consortium spike-in RNAs served as a control. The SMARTer® Ultra® Low RNA Kit (Clontech) was used for reverse transcription and cDNA pre-amplification. The single-cell cDNA products from each cell were then used to prepare Illumina sequencing libraries and sequenced as paired-end 150-base reads on the Illumina HiSeq 4000 platform, which was provided by the Functional Genomic Center Zürich.
Quality control was performed using FastQC v. 0.11.7 (Babraham Bioinformatics, http://www.bioinformatics.babraham.ac.uk/projects/fastqc/), and the adaptors and low-quality bases with a Phred quality score <20 were trimmed from the ends of the reads using Trim Galore v. 0.4.4 (Babraham Bioinformatics)⁶⁸.

Chang Y.T., Prompsy P., Kimeswenger S., Tsai Y.C., Ignatova D., Pavlova O., Iselin C., French L.E., Levesque M.P., Kuonen F., Bobrowicz M., Brunner P.M., Pascolo S., Hoetzenecker W, & Guenova E. (2024). MHC-I upregulation safeguards neoplastic T cells in the skin against NK cell-mediated eradication in mycosis fungoides. Nature Communications, 15, 752.

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Single Cell qPCR of E11.5 MGE Cells

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E11.5 MGE single cells were captured on a small-size IFC STA chip using C1 autoprep system per manufacturers’ protocols (Fluidigm). The cell capture conditions were as described above in the single-cell RNA-seq section. Amplification reagents contained TaqMan gene expression assays for genes of interest (Thermo Fisher). cDNAs from the IFC STA chips were then used to perform one BioMark qPCR assay per manufacturers’ protocols (Fluidigm). Data obtained from the run was analyzed by Real Time PCR Analysis Software (Fluidigm) with the following settings: the Quality Threshold was 0.65; Baseline Correction was Linear (Derivative); Ct Threshold Method was Auto (Global). Missing Ct values were set to 40. Delta Ct for each gene was calculated relative to Actb in each cell and Z score normalization was applied to each gene.

Chen Y.J., Friedman B.A., Ha C., Durinck S., Liu J., Rubenstein J.L., Seshagiri S, & Modrusan Z. (2017). Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types. Scientific Reports, 7, 45656.

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Single-Cell Transcriptome Profiling of Liver Cells

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Single-cell capture, lysis, and RT pre-amplification experiments were performed using the C1 Auto Prep System (Fluidigm, South San Francisco, CA) according to the manufacturer’s instructions. Isolated hepatocytes and NPCs were loaded into the C1 integrated fluidic circuit at a concentration of 300 cells/μL in phosphate-buffered saline containing 5% fetal bovine serum and 5 mmol/L of EDTA (Nacalai Tesque, San Diego, CA). Once cell capture was archived, cells were assessed for viability stain using Calcein-AM and ethidium homodimer 1 (Live/Dead Kit; Life Technologies). Chips were imaged using a BZ-X710 and chambers containing 2 or more, none, or dead cells were removed from further analysis. After lysis, reverse transcription (25°C for 10 min, 42°C for 60 min, 85°C for 5 min) and pre-amplification for 18 cycles (each cycle: 95°C for 15 sec, 60°C for 4 min), single-cell complementary DNA was harvested, transferred to a 96-well plate, and diluted 6 times with complementary DNA dilution buffer.

Katsuda T., Hosaka K., Matsuzaki J., Usuba W., Prieto-Vila M., Yamaguchi T., Tsuchiya A., Terai S, & Ochiya T. (2019). Transcriptomic Dissection of Hepatocyte Heterogeneity: Linking Ploidy, Zonation, and Stem/Progenitor Cell Characteristics. Cellular and Molecular Gastroenterology and Hepatology, 9(1), 161-183.

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Single-cell RNA-seq using Fluidigm C1

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Epidermal cells were captured on a medium microfluidic chip (designed for cells from 10 μm – 17 μm) using the Fluidigm C1 Autoprep System. 14 μl filtered cell suspension (∼750 cells / μl in DK-SFM with DNase I) was mixed with 6 μl C1 Suspension Reagent and 14 μl were loaded onto the chip. Single-cells were then captured for 30 min at 4°C using the “Cell Load (1772x/1773x)” script. Capturing efficiency was evaluated on a Nikon TE2000E automated microscope and both bright field and SCA1-FITC images of every capturing position were taken using μManager. Before proceeding with the tagmentation step, each capture site was manually inspected and only capture sites containing single, healthy cells were processed.
Following the image acquisition, STRT-C1 Lysis, RT and PCR mix was added as previously described (Islam et al., 2014 (link)), and the “RT + AMP (1772x/1773x)” script was executed. After the cDNA synthesis had been finished (∼8.5 h), the amplified cDNA was harvested with 13 μl Harvest Reagent and cDNA quality was measured on an Agilent BioAnalyzer.

Joost S., Zeisel A., Jacob T., Sun X., La Manno G., Lönnerberg P., Linnarsson S, & Kasper M. (2016). Single-Cell Transcriptomics Reveals that Differentiation and Spatial Signatures Shape Epidermal and Hair Follicle Heterogeneity. Cell Systems, 3(3), 221-237.e9.

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Single-cell RNA-seq of Female Fibroblasts

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A dataset of scRNA-seq of female fibroblast UCF1014 was downloaded from the European Genome-phenome Archive (https://www.ebi.ac.uk/ega/home) using accession number EGAD00001001083. The data consist of two sets of scRNA-seq: 104 cells (22 PCR cycles) and 59 cells (12 PCR cycles). The data were collected in a C1 Auto Prep System (Fluidigm) device (Xin et al., 2016 (link)) and sequenced using full transcript Smart-seq2 (Picelli et al., 2014 (link)). DNA-seq of UCF1014 was also downloaded from EGAD00001001084. The sequence data were produced and described by Borel et al. (2015) (link).

Wainer-Katsir K, & Linial M. (2020). BIRD: identifying cell doublets via biallelic expression from single cells. Bioinformatics, 36(Suppl 1), i251-i257.

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