Evaluation of bottom-up and top-down mass spectrum identifications with different customized protein sequences databases

Engineering Biological Nanopore Approaches toward Protein Sequencing

Biotechnological innovations have vastly improved the capacity to perform large-scale protein studies, while the methods we have for identifying and quantifying individual proteins are still inadequate to perform protein sequencing at the single-molecule level. Nanopore-inspired systems devoted to understanding how single molecules behave have been extensively developed for applications in genome sequencing. These nanopore systems are emerging as prominent tools for protein identification, detection, and analysis, suggesting realistic prospects for novel protein sequencing. This review summarizes recent advances in biological nanopore sensors toward protein sequencing, from the identification of individual amino acids to the controlled translocation of peptides and proteins, with attention focused on device and algorithm development and the delineation of molecular mechanisms with the aid of simulations. Specifically, the review aims to offer recommendations for the advancement of nanopore-based protein sequencing from an engineering perspective, highlighting the need for collaborative efforts across multiple disciplines. These efforts should include chemical conjugation, protein engineering, molecular simulation, machine-learning-assisted identification, and electronic device fabrication to enable practical implementation in real-world scenarios.

Protein identification by nanopore peptide profiling

Nanopores are single-molecule sensors used in nucleic acid analysis, whereas their applicability towards full protein identification has yet to be demonstrated. Here, we show that an engineered Fragaceatoxin C nanopore is capable of identifying individual proteins by measuring peptide spectra that are produced from hydrolyzed proteins. Using model proteins, we show that the spectra resulting from nanopore experiments and mass spectrometry share similar profiles, hence allowing protein fingerprinting. The intensity of individual peaks provides information on the concentration of individual peptides, indicating that this approach is quantitative. Our work shows the potential of a low-cost, portable nanopore-based analyzer for protein identification.

Peptide mass fingerprinting is a traditional approach for protein identification by mass spectrometry. Here, the authors provide evidence that peptide mass fingerprinting is also feasible using FraC nanopores, demonstrating protein identification based on nanopore measurements of digested peptides.

Proteoform Identification by Combining RNA-Seq and Top-Down Mass Spectrometry

In proteogenomic studies, genomic and transcriptomic variants are incorporated into customized protein databases for the identification of proteoforms, especially proteoforms with sample-specific variants. Most proteogenomic research has been focused on combining genomic or transcriptomic data with bottom-up mass spectrometry data. In the last decade, top-down mass spectrometry has attracted increasing attention because of its capacity to identify various proteoforms with alterations. However, top-down proteogenomics, in which genomic or transcriptomic data are combined with top-down mass spectrometry data, has not been widely adopted, and there is still a lack of software tools for top-down proteogenomic data analysis. In this paper, we introduce TopPG, a proteogenomic tool for generating proteoform sequence databases with genetic alterations and alternative splicing events. Experiments on top-down proteogenomic data of DLD-1 colorectal cancer cells showed that TopPG coupled with database search confidently identified proteoforms with sample-specific alterations.