ILANIT 2023

Strategies for Samples Multiplexing in Single Cell Analysis

Merav Kedmi 1 David Pilzer 1 Varun Suresh 3,4 Tamar Sapir 3 Shahar Halevi 5 Hadas Keren- Shaul 1,2
1Life Science Core Facilities, Weizmann Institute of Science, Israel
2G-INCPM, Weizmann Institute of Science, Israel
3Department of Molecular Genetics, Weizmann Institute of Science, Israel
4Department of Biology Sciences, Tata Institute of Fundamental Research, India
5Department of Systems Immunology, Weizmann Institute of Science, Israel

Single cell RNA sequencing has revolutionized our understanding of cellular diversity in health and disease. The 10x genomics microfluidics technology enables high-throughput single cell analysis for many biological systems using microfluidics chips and beads. Nonetheless, this technology presents a relatively high multiplet rate and a high price per sample, which can limit the scale of the projects done. In order to overcome these issues, it is possible to label cells in each sample and to pool several samples together prior to their loading on 10x genomics chip. One way of doing this is to label the cells with unique barcode oligonucleotides conjugated to hashing TotalSeq antibodies (BioLegend). These tags are presented as feature barcodes that can be captured by the 10x genomics beads and sequenced with the gene expression libraries to enable de-multiplexing of the samples. However, this method is not suitable for all cell types or when working with nuclei and not cells. A new technique by 10x genomics offers to multiplex both cells and nuclei using Cell Muliplexing oligonucleotides (CMOs) conjugated to a lipid (CellPlex). We successfully performed multiple experiments of cell multiplexing using hashing antibodies and CMO labeling. In this work, we will present the quality results of each strategy, showing good separation of the samples after CMO labeling of cells. These strategies will greatly increase the ability to perform large-scale single cell analysis projects and decipher the complexity of many cellular systems.