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Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling.

ABSTRACT: Labeling approaches using isobaric chemical tags (e.g., isobaric tagging for relative and absolute quantification, iTRAQ and tandem mass tag, TMT) have been widely applied for the quantification of peptides and proteins in bottom-up MS. However, until recently, successful applications of these approaches to top-down proteomics have been limited because proteins tend to precipitate and "crash" out of solution during TMT labeling of complex samples making the quantification of such samples difficult. In this study, we report a top-down TMT MS platform for confidently identifying and quantifying low molecular weight intact proteoforms in complex biological samples. To reduce the sample complexity and remove large proteins from complex samples, we developed a filter-SEC technique that combines a molecular weight cutoff filtration step with high-performance size exclusion chromatography (SEC) separation. No protein precipitation was observed in filtered samples under the intact protein-level TMT labeling conditions. The proposed top-down TMT MS platform enables high-throughput analysis of intact proteoforms, allowing for the identification and quantification of hundreds of intact proteoforms from Escherichia coli cell lysates. To our knowledge, this represents the first high-throughput TMT labeling-based, quantitative, top-down MS analysis suitable for complex biological samples.

SUBMITTER: Yu D

PROVIDER: S-EPMC8323476 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Wheat (Triticum aestivum L.) is an important crop worldwide. The physiological deterioration of seeds during storage and seed priming is closely associated with germination, and thus contributes to plant growth and subsequent grain yields. In this study, wheat seeds during different stages of artificial ageing (45°C; 50% relative humidity; 98%, 50%, 20%, and 1% Germination rates) and priming (hydro-priming treatment) were subjected to proteomics analysis through a proteomic approach based on the isobaric tandem mass tag labeling. A total of 162 differentially expressed proteins (DEPs) mainly involved in metabolism, energy supply, and defense/stress responses, were identified during artificial ageing and thus validated previous physiological and biochemical studies. These DEPs indicated that the inability to protect against ageing leads to the incremental decomposition of the stored substance, impairment of metabolism and energy supply, and ultimately resulted in seed deterioration. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the up-regulated proteins involved in seed ageing were mainly enriched in ribosome, whereas the down-regulated proteins were mainly accumulated in energy supply (starch and sucrose metabolism) and stress defense (ascorbate and aldarate metabolism). Proteins, including hemoglobin 1, oleosin, agglutinin, and non-specific lipid-transfer proteins, were first identified in aged seeds and might be regarded as new markers of seed deterioration. Of the identified proteins, 531 DEPs were recognized during seed priming compared with unprimed seeds. In contrast to the up-regulated DEPs in seed ageing, several up-regulated DEPs in priming were involved in energy supply (tricarboxylic acid cycle, glycolysis, and fatty acid oxidation), anabolism (amino acids, and fatty acid synthesis), and cell growth/division. KEGG and protein-protein interaction analysis indicated that the up-regulated proteins in seed priming were mainly enriched in amino acid synthesis, stress defense (plant-pathogen interactions, and ascorbate and aldarate metabolism), and energy supply (oxidative phosphorylation and carbon metabolism). Therefore, DEPs associated with seed ageing and priming can be used to characterize seed vigor and optimize germination enhancement treatments. This work reveals new proteomic insights into protein changes that occur during seed deterioration and priming.

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Quantitative Top-Down Proteomics in Complex Samples Using Protein-Level Tandem Mass Tag Labeling.

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