Characterization of Proteoforms with Unknown Post-translational Modifications Using the MIScore

Abstract

Various proteoforms may be generated from a single gene due to primary structure alterations (PSAs) such as genetic variations, alternative splicing, and post-translational modifications (PTMs). Top-down mass spectrometry is capable of analyzing intact proteins and identifying patterns of multiple PSAs, making it the method of choice for studying complex proteoforms. In top-down proteomics, proteoform identification is often performed by searching tandem mass spectra against a protein sequence database that contains only one reference protein sequence for each gene or transcript variant in a proteome. Because of the incompleteness of the protein database, an identified proteoform may contain unknown PSAs compared with the reference sequence. Proteoform characterization is to identify and localize PSAs in a proteoform. Although many software tools have been proposed for proteoform identification by top-down mass spectrometry, the characterization of proteoforms in identified proteoform-spectrum-matches still relies mainly on manual annotation. We propose to use the Modification Identification Score (MIScore), which is based on Bayesian models, to automatically identify and localize PTMs in proteoforms. Experiments showed that the MIScore is accurate in identifying and localizing one or two modifications.

Identification and Quantification of Proteoforms by Mass Spectrometry

“…TopPIC then performs spectrum alignment to match experimental spectra to database sequences and finally uses a generating function method to estimate the statistical significance for each identification. It can further match unknown mass shifts in identified PrSMs to common PTMs provided by the user and localize them using a Bayesian model …”

Targeted Proteomics Comes to the Benchside and the Bedside: Is it Ready for Us?

“…Targeted‐proteomics‐based experiments have been employed successfully for the measurement of post‐translational modification of proteins, in particular, phosphorylation . With the increased use of targeted proteomics, it is possible to explore the repertoire of hundreds of different types of post‐translational modifications which might play an important role in cell functioning that are yet to be discovered . Similarly, there is a vast amount of literature now available for single nucleotide polymorphism (SNP) variants and their role in deciding the response and predisposition to disease in a population‐specific way .…”

“…[49,50] With the increased use of targeted proteomics, it is possible to explore the repertoire of hundreds of different types of post-translational modifications which might play an important role in cell functioning that are yet to be discovered. [51,52] Similarly, there is a vast amount of literature now available for single nucleotide polymorphism (SNP) variants and their role in deciding the response and predisposition to disease in a population-specific way. [53] Although their presence is widely monitored through genomic studies, their functional relevance is less studied.…”

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

“…However, most protein databases used in proteomics studies, such as UniProt proteome databases, contain only reference protein sequences, not proteoforms with various alterations 11 . Many computational methods have been proposed for identifying proteoforms with alterations, which can be divided into three categories 12 . In the first approach, sequence annotations in protein knowledge bases or genomic or transcriptomic data are used to build an extended database that includes proteoforms with alterations 13 .…”