Protein Nanocages as Tunable Stoichiometric Benchmarks for Quantitative SMLM.

Abstract

Quantitative interpretation of single-molecule localization microscopy (SMLM) data remains limited by fluorophore blinking, incomplete or variable labeling, and the lack of calibration standards that are tunable, synthetic, and compatible with cellular imaging. Here, we evaluate self-assembling protein nanocages as stoichiometric benchmarks for copy-number calibration in STORM imaging. We generated mammalian expression constructs encoding nanocages containing 60- or 120-copies of different GFP variants and repositioned the fluorescent protein to the N-terminus to improve accessibility for anti-GFP nanobody labeling. Among the variants tested, mCitrine-tagged nanocages showed the most consistent expression and labeling with commercially available AF647-conjugated anti-GFP nanobodies. Using an analysis pipeline that matched widefield-detected nanocages to STORM-localized clusters, we found that mCitrine 120-mer nanocages produced localization distribution in which the mean of the distribution was shifted by approximately two-fold compared to the 60-mer. These results suggest that optimized protein nanocages can serve as useful calibration standards for STORM in the moderate to high copy-number range. More broadly, this approach provides a flexible framework that could be extended to additional nanocage stoichiometries, labeling strategies, and SMLM modalities.