The proteome is perhaps the most dynamic and valuable source of functional biological insight. Here, we introduce a novel single-molecule proteomic analysis approach that includes novel biochemistry for single, intact protein molecule immobilization, instrumentation for highly sensitive iterative probing of those protein molecules with a diverse array of affinity-reagents, and machine learning for data interpretation. We call the approach Protein Identification by Short-epitope Mapping (PrISM). PrISM utilizes multi-affinity reagents to target short linear epitopes to overcome the typical challenges of single-reagent sensitivity and specificity and achieve accessible and reproducible sensitivity and scale. PrISM further employs a novel protein decoding algorithm that considers the stochasticity expected for single-molecule binding. In simulations, PrISM is able to identify more than 98% of proteins across the proteomes of a wide range of organisms. PrISM is robust to potential experimental confounders including false negative detection events and noise. Simulations of the approach with a chip containing 10 billion protein molecules show a dynamic range of 11.5 and 9.5 orders of magnitude for blood plasma and HeLa cells, respectively. To further demonstrate this concept, we have successfully identified a set of model proteins using a smaller number of affinity reagents, exemplifying the approach of using short-epitope binding reagents to identify proteins. PrISM becomes increasingly powerful as the number of affinity reagents increases. Additionally, the approach has been used to explore proteoforms at the single-molecule level, uncovering biology invisible to other techniques using bulk or peptide based measurements. By combining single molecule analysis, undigested, intact protein immobilization, and iterative probing, PrISM will enable researchers to explore the breadth of the proteome without sacrificing depth, driving their next discoveries.

 

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