Real-time dynamic single-molecule protein sequencing on an integrated semiconductor device

Proteins are the main structural and functional components of cells, and their dynamic regulation and post-translational modifications (PTMs) underlie cellular phenotypes. Next-generation DNA sequencing technologies have revolutionized our understanding of heredity and gene regulation, but the complex and dynamic states of cells are not fully captured by the genome and transcriptome. Sensitive measurements of the proteome are needed to fully understand biological processes and changes to the proteome that occur in disease states. Studies of the proteome would benefit greatly from methods to directly sequence and digitally quantify proteins and detect PTMs with single-molecule sensitivity and precision. However current methods for studying the proteome lag behind DNA sequencing in throughput, sensitivity, and accessibility due to the complexity and dynamic range of the proteome, the chemical properties of proteins, and the inability to amplify proteins. Here, we demonstrate single-molecule protein sequencing on a compact benchtop instrument using a dynamic sequencing by stepwise degradation approach in which single surface-immobilized peptide molecules are probed in real-time by a mixture of dye-labeled N-terminal amino acid recognizers and simultaneously cleaved by aminopeptidases. By measuring fluorescence intensity, lifetime, and binding kinetics of recognizers on an integrated semiconductor chip we are able to annotate amino acids and identify the peptide sequence. We describe the expansion of the number of recognizable amino acids and demonstrate the kinetic principles that allow individual recognizers to identify multiple amino acids in a highly information-rich manner that is sensitive to adjacent residues. Furthermore, we demonstrate that our method is compatible with both synthetic and natural peptides, and capable of detecting single amino acid changes and PTMs. We anticipate that with further development our protein sequencing method will offer a sensitive, scalable, and accessible platform for studies of the proteome. ### Competing Interest Statement All authors affiliated with Quantum-Si, Inc, along with ADG and AMvO are shareholders of Quantum-Si, Inc.