Computational epitope heterogeneity analysis in immunostainings from antibody-dilution series

TL;DR

This paper introduces a computational method to analyze and improve antibody staining by studying epitope heterogeneity through dilution experiments.

Contribution

A new computational approach to quantify epitope heterogeneity and optimize antibody dilutions for better staining and multiplexing.

Findings

The method identifies optimal antibody dilutions to maximize signal specificity.

It enables single-channel antibody multiplexing based on binding properties.

The approach helps analyze binding targets of multi-specific antibodies.

Abstract

Antibodies are widely used in life sciences and medical therapy. Broadly applicable methods to determine epitope heterogeneity in immunostaining systems are missing. Here, we present a simple-to-use approach to characterize and quantify antibody binding properties that constitute the staining directly in the system of choice. We determine an epitope heterogeneity on the basis of a computational analysis of antibody-dilution immunofluorescence stainings. This allows us to choose signal-specificity maximizing dilutions and to improve signal quantification. Furthermore, the computational analysis provides approaches to obtain a single-channel antibody multiplexing. Our approach could help improving immunostainings in many laboratories by guiding the choice of antibody dilution, by increasing the possibility of antibody-multiplexing in the same color-channel and by allowing for the analysis of binding targets of multi-specific antibodies.

Computational epitope heterogeneity analysis from simple dilution-series experiments can improve immunostaining in many laboratories. The analysis enables a computational single-color channel multiplexing based on binding properties.

Figures