Chromatin modifications regulate genome function by recruiting protein factors to the genome. However, the protein composition at distinct chromatin modifications remains to be fully characterized. Here, we use natural protein domains as modular building blocks to develop engineered chromatin readers (eCRs) selective for DNA methylation and histone tri-methylation at H3K4, H3K9 a H3K27 residues. We first demonstrate their utility as selective chromatin binders in living cells by stably expressing eCRs in mouse embryonic stem cells and measuring their subnuclear localisation, genomic distribution and histone modification–binding preference. By fusing eCRs to the biotin ligase BASU, we establish ChromID, a method for identifying the chromatin-dependent protein interactome based on proximity biotinylation, and apply it to distinct chromatin modifications in mouse stem cells. Using a synthetic dual-modification reader, we also uncover the protein composition at bivalent promoters marked by H3K4me3 and H3K27me3. These results highlight the ability of ChromID to obtain a detailed view of protein interaction networks on chromatin.

Characterising cellular phenotypic heterogeneity is essential to understand the relationship between the molecular and morphological determinants of cellular state. Here we report that publicly available self-supervised vision transformers (ss-ViTs) accurately elucidate phenotypic stem cell heterogeneity out-of-the-box. Moreover, we introduce scDINO, an adapted ss-ViT trained on five-channel automated microscopy data, attaining excellent performance in delineating peripheral blood immune cell identity. Thus, ss-ViTs represent a leap forward in the unsupervised analysis of phenotypic heterogeneity.