Computational protocol: Antibody Tumor Targeting Is Enhanced by CD27 Agonists through Myeloid Recruitment

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Protocol publication

[…] The spleens of mice treated with isotype controls, anti-CD20 (200 μg, day 1), anti-CD27 (100 μg day 2-5) or in combination were harvested on day 13 and digested with Liberase (Sigma Aldrich). Single-cells (100 cells/ul) and barcoded mRNA-binding micro-particles (100 beads/μl) were suspended in droplets containing cell lysis buffer (∼1nl; 50 cell /μl final concentration). Droplets were then broken and collected by centrifugation and subjected to cDNA synthesis (Maxima H- RTase), introducing the molecule and cell barcode to every transcript from a single cell (termed a ‘STAMP’). 800 STAMPs from each condition were then selected for PCR amplification (15 cycles), library preparation (Nextera XT, Illumina) and Illumina sequencing by synthesis using a custom read 1 primer (NextSeq-500 platform; version 2 chemistry - high output setting; 20 bp read 1, 50 bp read 2 and an 8 bp index 1). Species-mixing experiments are routinely performed in our laboratory and have determined that our implementation of the Drop-Seq protocol robustly achieves single-cell encapsulation and captures transcriptomes from single-cells with high specificity (98.5% of cell encapsulation events are single-species; data not shown). Raw sequencing reads were converted to a sorted unmapped BAM file (FastqToSam, Picard bundled in Dropseq-tools v1.0) and filtered to remove all read-pairs with a barcode base quality of <10. The second read was trimmed at the 5’ end to remove any TSO-adapter sequence and at the 3’ end to remove polyA tails. Reads were aligned against mouse reference genome (mm10) using STAR aligner (v2.5.0a), then sorted/converted/merged to a BAM with a tag “GE” onto reads for data extraction. The DigitalExpression program (Dropseq-tools v1.0) performed digital counting (DGE) of the mRNA transcripts (unique molecular identifiers to avoid double counting reads/PCR duplicates) and created a DGE matrix (one measurement per gene per cell). Cells expressing less than 300 or more than 3,000 genes were excluded from further analysis. To normalize counts between samples, scaling factors were calculated using a trimmed mean of M-values using edgeR (). Cluster-specific genes were detected using the t-test algorithm in Seurat (Rahul Satija (NA). Seurat: R toolkit for single cell genomics. R package version 1.4.0.) (p < 1 × 10-3 was considered significant). Annotation of the resulting gene lists relative to the coexpression atlas of the Immunological Genome Project () was performed using the on-line ToppGene suite. […]

Pipeline specifications

Software tools Picard, edgeR, ToppGene Suite
Databases ImmGen
Application scRNA-seq analysis
Organisms Mus musculus