STAMP
Surveying Targets by APOBEC-Mediated Profiling
A Tool for Studying RBP-RNA Interactomes
RNA-binding proteins (RBPs) are critical regulators of gene expression and RNA processing that are required for gene function. The dynamics of RBP regulation remain poorly understood, in part because transcriptome-wide, scalable, robust and sensitive and methods to detect RBP interaction sites on RNAs are lacking. To address this gap in understanding, we developed STAMP (Surveying Targets by APOBEC-Mediated Profiling), which efficiently detects RBP-RNA interactions. In STAMP, the RBP of interest is expressed in cells as a fusion to the RNA editing enzyme ABOBEC1 that converts cytosine to inosine. RNA sites bound by the RBP are then detected by standard RNA-seq using edit-aware analysis tools that we developed (Deffit et al., eLife 2018; Kofman et al., BMC Bioinformatics 2023). Critically, STAMP does not rely on ultraviolet cross-linking or immunoprecipitation and, when coupled with single-cell capture, can identify RBP-specific and cell-type-specific RNA-protein interactions for multiple RBPs and cell types in single, pooled experiments. Pairing STAMP with long-read sequencing yields RBP target sites in an isoform-specific manner. Finally, Ribo-STAMP uses APOBEC-tagged small ribosomal subunits to measure transcriptome-wide ribosome association in single cells. To illustrate, in Einstein et al., Molecular Cell 2021, we used single-cell Ribo-STAMP to characterize the heterogeneous translation landscape of myc-dependent breast cancer cells. STAMP enables the study of RBP-RNA interactomes and translational landscapes with unprecedented cellular resolution.
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Team Members
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Between October 2015-2018, we have developed STAMP (Surveying Targets by Antibody-free Mutation Profiling) and its companion computational workflow to allow antibody-free detection of RBP and ribosome interactomes (Ribo-STAMP) by standard RNA-seq and quantification of binding-site-specific C-to-U edits directed by fusions of RBPs and ribosomal proteins, respectively, to APOBEC1 (Brannan et al., Nature Methods, 202138). STAMP has distinct advantages over TRIBE, as APOBEC enzymes modify cytosines in single-stranded RNA, which constitutes ~25%-35% of nucleotides in any given mammalian transcript and produce clusters of edits (between 10 and 1,000 edits per transcript). We demonstrated the specificity of STAMP for diverse, full-length RBPs that bind both polyadenylated (RBFOX2, TIA1) and non-polyadenylated mRNAs (SLBP). We also showed that some ribosomal proteins when fused to APOBEC1 enable the measurement of ribosome association that correlates well with metrics such as translation efficiency computed from ribo-seq experiments, which often require separate mRNA-seq data as normalizing denominators. In a single experiment, Ribo-STAMP uses edited and non-edited reads to reflect ribosome-associated and input gene expression values simultaneously. We envision that these simultaneous readouts will be extremely useful in complex and heterogeneous cellular or in vivo models to address questions concerning cell identity or disease states.
As RNA sequencing is amenable to high-throughput single-cell capture technologies, STAMP enables single-cell resolution in the detection of RNA binding and ribosome-associated substrates. We demonstrated that STAMP can be used reliably at single-cell resolution to identify RNA targets, binding sites and even extract RBP motifs from a single cell. To enable dissemination of single-cell STAMP, we also developed computational methods that demultiplex multiple RBPs by clustering cells using only edit signatures. STAMP also enables the combined identification of RBP binding sites and global measurement of gene expression and allows long-read assessment to distinguish RBP binding or translation efficiency on different full-length transcript isoforms.
Cell type-specific CLIP or ribo-seq from in vivo models has remained a challenge in the field. The STAMP approach, utilizing cell-type specific promoters and gene expression profiles, would overcome these. We anticipate that targeted genomic integrations of editing modules in animal and organoid models will be powerful for in vivo tracing of RNA-protein interaction landscapes in many previously inaccessible contexts. Organoid or animal model systems expressing STAMP fusions for RBPs of interest hold the potential to unveil isoform specific RNA binding and translation landscapes at the organismal level and allow for tissue and cell type-specific profiling in development and disease.