In the fast-evolving landscape of multimodal single-cell analysis, antibody oligo -conjugates (AOCs) have revolutionized our ability to simultaneously profile gene expression and surface protein markers. However, with great resolution comes the challenge of optimizing reagent use for cost-effective, high-quality data.
A study by Buus et al. (eLife, 2021) tackled a critical issue: how to fine-tune antibody concentration, staining volume, and cell number to enhance signal, reduce background, and cut sequencing costs in CITE-seq, spatial transcriptomics, and antibody-derived DNA tag methods like Immuno-PCR. The findings?
1.Many antibodies are used at unnecessarily high concentrations, leading to wasted reagents and increased sequencing costs due to excessive background signal.
2. Reducing staining volume has minimal impact on most markers.
3. Lowering antibody concentrations in a 50-plex panel led to a 3.9x cost reduction while improving signal-to-noise and sequencing efficiency.
For those developing or optimizing single-cell multiomics, spatial proteomics, or AOC workflows, this study provides a practical road map for improving performance while reducing reagent costs.
Reference - Improving oligo-conjugated antibody signal in multimodal single-cell analysis.