title: GSM6703387: MHb, WT, Nicotine; Mus musculus; RNA-Seq
library_construction_protocol: Warm water bath to 37˚C. Prewarm neuronal culturing medium (NbActiv1) to 37˚C (4 degrees). Prepare papain solution by dissolving papain to a final concentration of 2mg/ml in dissociation solution (Hibernate AB). Add 3.2ml to a vial of 6.4mg papain and mix. Transfer to a 15ml conical tube and incubate at 37˚C for 10 min prior to use – (can use 2 papain vials and divide equally between the tissue). Using a 1000ul wide bore pipette tip, transfer the tissue along with Hibernate AB medium to a new 15ml conical tube and wait until tissue settles at the bottom. Transfer the medium from the tissue to a new 15ml conical tube, leaving only enough medium to cover the tissue. Add 2ml papain solution (divide equally the 6.4ml prepped from above so will be under 2ml) to tissue and incubate at 37˚C for 20 minutes. Gently swirl to mix, repeat 2-3x during the incubation. Remove and discard the papain solution without disrupting the tissue at the bottom, leaving only enough solution to cover the tissue. Add medium from step 5 back to the tissue. Aspirate the tissue with the medium into a fire polished silanized Pasteur pipette (laurens bench) and immediately dispense the contents back to the tube. Triturate with 8-10x MAXIMUM passes through the pipette from when the first piece of tissue is taken up. The goal is to achieve 85% dissociation. Allow the tissue debris to settle for 1 minute. Transfer the supernatant containing dispersed cells to a new 15ml conical tube, leaving tissue debris at the bottom. Centrifuge cells at 200rcf for 2 minutes. Remove and discard the supernatant without disturbing the cell pellet. Leave only enough media to cover the cell pellet. Use a regular bore pipette tip and resuspend the cell in 1ml pre warmed NbActiv1 by gently pipetting 20x or until cells are completely suspended. This volume results in a cell concentration of 2000cells/ul approx. Single cell RNA Seq was performed on these samples using the Chromium platform (10X Genomics, Pleasanton, CA) with the 3' gene expression (3' GEX) V3 kit, using an input of ~12,000 cells. Briefly, Gel-Bead in Emulsions (GEMs) were generated on the sample chip in the Chromium controller. Barcoded cDNA was extracted from the GEMs by Post-GEM RT-cleanup and amplified for 12 cycles. Amplified cDNA was fragmented and subjected to end-repair, poly A-tailing, adapter ligation, and 10X-specific sample indexing following the manufacturer's protocol. Libraries were quantified using Bioanalyzer (Agilent) and QuBit (Thermofisher) analysis. Libraries were sequenced in paired end mode on a NovaSeq instrument (Illumina, San Diego, CA) targeting a depth of 50,000-100,000 reads per cell.  Sequencing data was aligned and quantified using the Cell Ranger Single-Cell Software Suite (version 3.0, 10X Genomics) against the provided mm10 mouse reference genome. Downstream analyses, such as graph-based clustering, and differential expression analysis/visualization, were performed using the Loupe Cell Browser (version 3.0.1, 10X Genomics) and the Seurat R package. Further data analyses were run on a Dell Precision T7810 Workstation running Ubuntu 18.04LTS with 128GB RAM and 16 threads. Clustering and differential expression analysis was performed using a combination of ScanPy v1.5.1 and custom Python code (available at github.com/alexcwsmith/singleCellTools). Cells were filtered by <= 5,000 and >= 200 unique genes, and <= 10 percent mitochondrial reads. Genes expressed in less than 3 cells were then filtered out. Filtered data were then scaled to the median number of unique molecules and log(x+1) transformed. Highly variable genes were defined with a dispersion over 0.3, and total counts and percent mito were then regressed out of the data prior. Principal component analysis was then used to reduce dimensionality to 30. A neighborhood graph was computed using 25 neighbors and 15 principal components, and visualization used the uniform manifold approximation and projection (UMAP) learning technique. The Louvain algorithm was then used to assign cluster identities with default settings. Following clustering, differential expression analysis was conducted between nicotine and saline treated cells within each cluster using Wilcoxon's ranked-sign test and corrected with a false-discovery rate of 0.05.