Leonie Kolmar

Leonie Kolmar, Hongxing Hu, Xiaoli Ma, Samantha Seah, Christoph A. Merten

Droplet microfluidic antibody screening platform for functional antibodies at the single-cell level

Antibody screening has become an essential role in modern medicine. Screenings are usually limited to a small subset of target proteins and are based on antibody binding, which does not necessarily correlate with their functionality. Being able to assess the effect of thousands of antibodies on the transcriptome of target cells would allow target-agnostic screens for a variety of functions in a highly multiplexed way. While droplet microfluidic systems have already become a powerful tool for single-cell RNA sequencing and antibody discovery, many key problems remain. First, the sparsity of the single-cell RNA sequencing data hardly allows the detection of individual outliers showing differential gene expression after exposure to an antibody. Furthermore, there are currently no systems for the detection of altered single-cell transcriptomic signatures after stimulation in droplets. Here we address all these challenges and conceptualize a microfluidic workflow for in-droplet stimulation of target cells with antibodies expressed by antibody-secreting cells. In addition, we developed a computational workflow that can detect outliers that remain hidden in commonly used clustering approaches. Lastly, we investigated the effect of labeling newly synthesized mRNA to distinguish between transcriptomic signatures before and after antibody stimulation of a target cell. Taken together, this should pave the way for RNA sequencing-driven functional antibody discovery.

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