Dataset Information

SEC-TMT facilitates quantitative differential analysis of protein interaction networks.

ABSTRACT: The majority of cellular proteins interact with at least one partner or assemble into molecular-complexes to exert their function. This network of protein-protein interactions (PPIs) and the composition of macromolecular machines differ between cell types and physiological conditions. Therefore, characterizing PPI networks and their dynamic changes is vital for discovering novel biological functions and underlying mechanisms of cellular processes. However, producing an in-depth, global snapshot of PPIs from a given specimen requires measuring tens to thousands of LC-MS/MS runs. Consequently, while recent works made seminal contributions by mapping PPIs at great depth, almost all focused on just 1-2 conditions, generating comprehensive but mostly static PPI networks. In this study we report the development of SEC-TMT, a method that enables identifying and measuring PPIs in a quantitative manner from only 4-8 LC-MS/MS runs per biological sample. This was accomplished by incorporating tandem mass tag (TMT) multiplexing with a size exclusion chromatography mass spectrometry (SEC-MS) work-flow. SEC-TMT reduces measurement time by an order of magnitude while maintaining resolution and coverage of thousands of cellular interactions, equivalent to the gold standard in the field. We show that SEC-TMT provides benefits for conducting differential analyses to measure changes in the PPI network between conditions. This development makes it feasible to study dynamic systems at scale and holds the potential to drive more rapid discoveries of PPI impact on cellular processes.

SUBMITTER: Doron-Mandel E

PROVIDER: S-EPMC9882152 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

A Multiplexed SEC-MS Approach to Systematically Study the Interplay Between Protein Assembly-States and Phosphorylation Events.

Doron-Mandel Ella E Bokor Benjamin Judah BJ Ma Yanzhe Y Street Lena Annika LA Tang Lauren Clarissa LC Abdou Ahmed Ali AA Shah Neel H NH Rosenberger George G Jovanovic Marko M

bioRxiv : the preprint server for biology 20240801

Protein molecular interactions and post-translational modifications (PTMs), such as phosphorylation, can be co-dependent and reciprocally co-regulate each other. Although this interplay is central for many biological processes, a systematic method to simultaneously study assembly-states and PTMs from the same sample is critically missing. Here, we introduce SEC-MX (Size Exclusion Chromatography fractions MultipleXed), a global quantitative method combining Size Exclusion Chromatography and PTM-e ...[more]

PMID: 36711903

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Project description:BACKGROUND: A genetic interaction refers to the deviation of phenotypes from the expected when perturbing two genes simultaneously. Studying genetic interactions help clarify relationships between genes, such as compensation and masking, and identify gene groups of functional modules. Recently, several genome-scale experiments for measuring quantitative (positive and negative) genetic interactions have been conducted. The results revealed that genes in the same module usually interact with each other in a consistent way (pure positive or negative); this phenomenon was designated as monochromaticity. Monochromaticity might be the underlying principle that can be utilized to unveil the modularity of cellular networks. However, no appropriate quantitative measurement for this phenomenon has been proposed. RESULTS: In this study, we propose the monochromatic index (MCI), which is able to quantitatively evaluate the monochromaticity of potential functional modules of genes, and the MCI was used to study genetic landscapes in different cellular subsystems. We demonstrated that MCI not only amend the deficiencies of MP-score but also properly incorporate the background effect. The results showed that not only within-complex but also between-complex connections present significant monochromatic tendency. Furthermore, we also found that significantly higher proportion of protein complexes are connected by negative genetic interactions in metabolic network, while transcription and translation system adopts relatively even number of positive and negative genetic interactions to link protein complexes. CONCLUSION: In summary, we demonstrate that MCI improves deficiencies suffered by MP-score, and can be used to evaluate monochromaticity in a quantitative manner. In addition, it also helps to unveil features of genetic landscapes in different cellular subsystems. Moreover, MCI can be easily applied to data produced by different types of genetic interaction methodologies such as Synthetic Genetic Array (SGA), and epistatic miniarray profile (E-MAP).

Project description:Lotus is an aquatic plant that is sensitive to water loss, but its seeds are longevous after seed embryo dehydration and maturation. The great difference between the responses of vegetative organs and seeds to dehydration is related to the special protective mechanism in embryos. In this study, tandem mass tags (TMT)-labeled proteomics and parallel reaction monitoring (PRM) technologies were used to obtain novel insights into the physiological regulatory networks during lotus seed dehydration process. Totally, 60,266 secondary spectra and 32,093 unique peptides were detected. A total of 5,477 proteins and 815 differentially expressed proteins (DEPs) were identified based on TMT data. Of these, 582 DEPs were continuously downregulated and 228 proteins were significantly up-regulated during the whole dehydration process. Bioinformatics and protein-protein interaction network analyses indicated that carbohydrate metabolism (including glycolysis/gluconeogenesis, galactose, starch and sucrose metabolism, pentose phosphate pathway, and cell wall organization), protein processing in ER, DNA repair, and antioxidative events had positive responses to lotus embryo dehydration. On the contrary, energy metabolism (metabolic pathway, photosynthesis, pyruvate metabolism, fatty acid biosynthesis) and secondary metabolism (terpenoid backbone, steroid, flavonoid biosynthesis) gradually become static status during lotus embryo water loss and maturation. Furthermore, non-enzymatic antioxidants and pentose phosphate pathway play major roles in antioxidant protection during dehydration process in lotus embryo. Abscisic acid (ABA) signaling and the accumulation of oligosaccharides, late embryogenesis abundant proteins, and heat shock proteins may be the key factors to ensure the continuous dehydration and storage tolerance of lotus seed embryo. Stress physiology detection showed that H2O2 was the main reactive oxygen species (ROS) component inducing oxidative stress damage, and glutathione and vitamin E acted as the major antioxidant to maintain the REDOX balance of lotus embryo during the dehydration process. These results provide new insights to reveal the physiological regulatory networks of the protective mechanism of embryo dehydration in lotus.

Dataset Information

SEC-TMT facilitates quantitative differential analysis of protein interaction networks.

Publications

A Multiplexed SEC-MS Approach to Systematically Study the Interplay Between Protein Assembly-States and Phosphorylation Events.

Similar Datasets

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