Single cell & microfluidics service lab

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We are one of the 3 nodes of HiLIFE Single cell omics platform at University of Helsinki, and offer the following single cell and bulk RNAseq services jointly with Illumina sequencing service at Functional Genomics Unit (FuGU). Most of our libraries are sequenced with the NextSeq500 High output 75 cycle kit producing up to 400 million reads, or with the new NovaSeq platform at FIMM.

Single cell RNAseq. The cost efficient DropSeq droplet microfluidics method with barcoded microbeads was originally developed at McCarroll lab at Harvard Medical School (Macosko et al, Cell 2015), and we run the protocol with Dolomite-Bio microfluidics device. Approximately 5% of the input cells will get barcoded, so this method is suitable if your starting material is at least 100 000 cells. The read sequences locate to 3' end of the poly-A mRNA transcripts. We have also set up the Seq-Well protocol for cell capture with microwell slides instead droplets, developed by Shalek lab at MIT (Gierahn et al, Nat Methods 2017). For samples with low number of cells available the Seq-Well is beneficial due to higher cell capture rate than Drop-seq. It needs just 10.000 cells or even less as input.

FACS sorted single cell RNAseq. If your cells of interest are very rare and of limited number, you can also manually pick or FACS sort the desired cell fractions cell by cell into 96-well plates with lysis buffer and well-specific poly-A capture oligos. Our in-house modified protocol with Drop-seq like oligos allow pooled tagmentation, sequencing and analysis pipeline similar to Drop-seq. In addition to current 3' tagging protocol we will soon set this up also to 5' tagging as well as full length coverage versions. Please plan this well beforehand with us and e.g. Biomedicum FACS core.

Bulk RNAseq with Drop-seq chemistry. The FACS sorted single cell method on 96-well plates can be used also as a very cost-efficient bulk RNAseq method for your total RNA samples. Cell fractions of very limited cell numbers can be also lysed and analyzed directly without separate RNA extraction.

Single cell Western blotting. We have the ProteinSimple MILO device for expression level and size isoform detection of any protein from up to 1000 single cells per slide. Our Agilent scanner reads red and green fluorescence, and several stripping rounds can be performed for the slides for detection of multiple proteins from the same cells.

Automated capillary Western blotting. With this ProteinSimple JESS system you can run and stain up to 24 samples in each 3h run, with very small sample and antibody volumes, and minimal hands on time. JESS reads chemiluminescent, fluorescent (IR and NIR) and total protein signals, all even from the same capillary.

Custom microfluidic chip fabrication. In addition to single cell droplet capturing, the Dolomite-Bio microfluidics device with 3 pressure chambers/flow controllers and high speed camera microscope can be adapted to various other assays using chip designs available at Dolomite-Microfluidics web catalogue. Set-up costs of new assays will be additionally charged. We can also help in design and production of custom PDMS microfluidic chips at Micronova Nanofabrication Centre of Aalto University and VTT in Espoo. We have recently purchased own SU-8 mold fabrication and PDMS/Flexdym chip replication stations which will be set up in spring 2019. Lab-on-a-chip workshop course has been preliminary planned for April-May 2019.

Chip and slide imaging. We have the high speed digital imaging system by Meros, and Grundium OCUS whole slide scanner.

DNA, RNA and library quality checks. We use Perkin Elmer LabChip GX Touch HT capillary electrophoresis system to check the DNA or RNA integrity and NGS library size and concentration of up to 384 samples per each run. Especially for large numbers of samples LabChip is very cost efficient and quick.

Bioinformatics of single cell/bulk RNAseq data. If you are not familiar with RNAseq data analysis, we can teach you how to process the Illumina raw FASTQ files into genome aligned digital expression matrix, and further into biologically meaningfull cell type cluster and differential expression data. If you are not comfortable with R and command line working, we can guide you how to analyze your own data with user friendly CSC Chipster platform in which the e.g. Drop-seq pipeline and Seurat tools have been installed and more single cell tools to be added in future.

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