Proteomics

Dataset Information

Identification of Unknown Biological Toxin Protein Using Mass Spectrometry: A Case Study on De Novo Sequencing of Ricin


ABSTRACT: Currently, the genomes of many toxin proteins remain unsequenced. Characterizing these toxin proteins and their active peptide segments is crucial for the development of detoxification agents and for discovering proteins with potential therapeutic applications. Existing methods for identifying and detecting toxin proteins primarily focus on known proteins, making them less applicable for identifying toxins from unknown sources. In this study, we employed a combination of multiple enzymatic digestion techniques, de novo mass spectrometry sequencing, and sequence assembly methods based on graph theory to perform high-precision, full-length sequencing of multi-subunit toxin proteins. After de novo sequencing and identifying Ricin toxin proteins, we utilized a strategy based on multiple alignments and error correction through the construction of overlapping scaffolds to differentiate between homologous isomers I and L and to detect unexpected post-translational modifications. This approach, referred to as the Heuristic Denovo protein sequencing(HDPS), facilitated the rapid hydrolysis and identification of proteins. The method achieved a 100% coverage rate for protein/peptide biological toxins and an amino acid-level accuracy of over 95%. Through de novo sequencing of Ricin toxin, this study provides a stable and reliable solution for identifying highly mutated proteins and those from unknown sequence sources.

INSTRUMENT(S):

ORGANISM(S): Ricinus Communis

SUBMITTER: Yubo Song  

LAB HEAD: Fuli Wang

PROVIDER: PXD061213 | Pride | 2025-12-01

REPOSITORIES: Pride

Dataset's files

Source:
Action DRS
1_ProteinaseK1.raw Raw
2_ProteinaseK2.raw Raw
3_Glu-C.raw Raw
4_Chymotrysin.raw Raw
5_Trypsin.raw Raw
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