Simultaneous measurement of surface proteins and gene expression within single cells offers high resolution snapshots of complex cell populations. These methods rely on staining cells with oligo-conjugated antibodies analogous to staining for flow- and mass cytometry. Unlike flow- and mass cytometry, signal from oligo-conjugated antibodies is not hampered by spectral overlap or limited by the number of metal isotopes, making it a highly sensitive and scalable approach. Signal from oligo-conjugated antibodies is quantified by counting reads from high-throughput sequencing. Consequently, cost of sequencing is strictly dependent on the signal intensities and background from the pool of antibodies used in analysis. Thus, considering the “cost-of-signal” as well as optimizing “signal-to-noise”, makes titration of oligo-conjugated antibody panels more complex and even more important than for flow- and mass cytometry. In this study, we investigated the titration response of a panel of oligo-conjugated antibodies towards four variables: Antibody concentration, staining volume, cell number at staining, and tissue of origin. We find that staining with high antibody concentrations recommended by published protocols and commercial vendors cause unnecessarily high background signal and that concentrations of many antibodies can be drastically reduced without loss of biological information. Reducing staining volume only affects antibodies targeting highly abundant epitopes used at low concentrations and can be counteracted by reducing cell numbers at staining. We find that background signal from empty droplets can account for a major fraction of the total sequencing reads and is primarily derived from antibodies used at high concentrations. Together, this study provides new insight into the titration response and background signal of oligo-conjugated antibodies and offers concrete guidelines on how such panels can be improved.
This repository contains the dataset included in the study.
All code used in the study is deposited at GitHub: https://github.com/Terkild/CITE-seq_optimization
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Buus, Terkild Brink; Herrera, Alberto; Ivanova, Ellie; Mimitou, Eleni; Cheng, Anthony; Papagiannakopoulos, Thales; et al. (2020). Improving oligo-conjugated antibody signal in multimodal single-cell analysis. figshare. Collection. https://doi.org/10.6084/m9.figshare.c.5018987.v1