MINFLUX reveals nonnormal distribution of linkage errors in immunofluorescence labeling

As the localization precision of single-molecule localization microscopy (SMLM) advances, labeling uncertainty from linkage errors increasingly limits imaging accuracy. The distributions of these errors across common labeling strategies remain unclear, complicating corrections. In this study, we used MINFLUX, with a localization precision of 1-3 nm, to examine the probability distributions of linkage errors across three antibody labeling strategies: nanobody labeling, primary “Y” antibody labeling, and primary antibody with secondary antibody labeling. We found that the distribution of linkage errors for each strategy deviates from a normal distribution, exhibiting left skewness and a flattened shape. These distributions also vary in skewness and kurtosis between strategies, and the range of linkage error values partially overlaps between strategies. Simulations confirmed our experimental findings, revealing that antibody size and geometric orientation jointly influence linkage errors. Our results provide insight into the mechanisms driving linkage errors and suggest statistical approaches to enhance SMLM imaging accuracy. As single-molecule localization microscopy (SMLM) achieves higher precision, linkage errors from antibody labeling increasingly hinder imaging accuracy. Here, the authors employ MINFLUX to analyze linkage error distributions across various antibody labeling strategies, revealing deviations from normality and suggesting statistical methods to enhance SMLM accuracy, with implications for super-resolution imaging advancements.