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Interaction proteomics by using in-cell NMR spectroscopy.

ABSTRACT: A synopsis of in-cell NMR spectroscopic approaches to study interaction proteomics in prokaryotic and eukaryotic cells is presented. We describe the use of in-cell NMR spectroscopy to resolve high resolution protein structures, discuss methodologies for determining and analyzing high and low affinity protein-target structural interactions, including intrinsically disordered proteins, and detail important functional interactions that result from these interactions. SIGNIFICANCE: The ultimate goal of structural and biochemical research is to understand how macromolecular interactions give rise to and regulate biological activity in living cells. The challenge is formidable due to the complexity that arises not only from the number of proteins (genes) expressed by the organism, but also from the combinatorial interactions between them. Despite ongoing efforts to decipher the complex nature of protein interactions, new methods for structurally characterizing protein complexes are needed to fully understand molecular networks. With the onset of in-cell NMR spectroscopy, molecular structures and interactions can be studied under physiological conditions shedding light on the structural underpinning of biological activity.

SUBMITTER: Breindel L

PROVIDER: S-EPMC6082733 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Interaction proteomics by using in-cell NMR spectroscopy.

Breindel Leonard L Burz David S DS Shekhtman Alexander A

Journal of proteomics 20180208

A synopsis of in-cell NMR spectroscopic approaches to study interaction proteomics in prokaryotic and eukaryotic cells is presented. We describe the use of in-cell NMR spectroscopy to resolve high resolution protein structures, discuss methodologies for determining and analyzing high and low affinity protein-target structural interactions, including intrinsically disordered proteins, and detail important functional interactions that result from these interactions. SIGNIFICANCE: The ultimate goal ...[more]

PMID: 29427760

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Project description:BackgroundAmbiguity in malignant transformation of glioma has made prognostic diagnosis very challenging. Tumor malignant transformation is closely correlated with specific alterations of the metabolic profile. Exploration of the underlying metabolic alterations in glioma cells of different malignant degree is therefore vital to develop metabolic biomarkers for prognosis monitoring.MethodsWe conducted (1)H nuclear magnetic resonance (NMR)-based metabolic analysis on cell lines (CHG5, SHG44, U87, U118, U251) developed from gliomas of different malignant grades (WHO II and WHO IV). Several methods were applied to analyze the (1)H-NMR spectral data of polar extracts of cell lines and to identify characteristic metabolites, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), fuzzy c-means clustering (FCM) analysis and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). The expression analyses of glial fibrillary acidic protein (GFAP) and matrix metal proteinases (MMP-9) were used to assess malignant behaviors of cell lines. GeneGo pathway analysis was used to associate characteristic metabolites with malignant behavior protein markers GFAP and MMP-9.ResultsStable and distinct metabolic profiles of the five cell lines were obtained. The metabolic profiles of the low malignancy grade group (CHG5, SHG44) were clearly distinguished from those of the high malignancy grade group (U87, U118, U251). Seventeen characteristic metabolites were identified that could distinguish the metabolic profiles of the two groups, nine of which were mapped to processes related to GFAP and MMP-9. Furthermore, the results from both quantitative comparison and metabolic correlation analysis indicated that the significantly altered metabolites were primarily involved in perturbation of metabolic pathways of tricarboxylic acid (TCA) cycle anaplerotic flux, amino acid metabolism, anti-oxidant mechanism and choline metabolism, which could be correlated with the changes in the glioma cells' malignant behaviors.ConclusionsOur results reveal the metabolic heterogeneity of glioma cell lines with different degrees of malignancy. The obtained metabolic profiles and characteristic metabolites are closely associated with the malignant features of glioma cells, which may lay the basis for both determining the molecular mechanisms underlying glioma malignant transformation and exploiting non-invasive biomarkers for prognosis monitoring.

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Interaction proteomics by using in-cell NMR spectroscopy.

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Interaction proteomics by using in-cell NMR spectroscopy.

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