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Molecular characterization of the endoplasmic reticulum: insights from proteomic studies.

ABSTRACT: The endoplasmic reticulum (ER) is a multifunctional intracellular organelle responsible for the synthesis, processing and trafficking of a wide variety of proteins essential for cell growth and survival. Therefore, comprehensive characterization of the ER proteome is of great importance to the understanding of its functions and has been actively pursued in the past decade by scientists in the proteomics field. This review summarizes major proteomic studies published in the past decade that focused on the ER proteome. We evaluate the data sets obtained from two different organs, liver and pancreas each of which contains a primary cell type (hepatocyte and acinar cell) with specialized functions. We also discuss how the nature of the proteins uncovered is related to the methods of organelle purification, organelle purity and the techniques used for protein separation prior to MS. In addition, this review also puts emphasis on the biological insights gained from these studies regarding the molecular functions of the ER including protein synthesis and translocation, protein folding and quality control, ER-associated degradation and ER stress, ER export and membrane trafficking, calcium homeostasis and detoxification and drug metabolism.

SUBMITTER: Chen X

PROVIDER: S-EPMC3517137 | biostudies-literature | 2010 Nov

REPOSITORIES: biostudies-literature

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Molecular characterization of the endoplasmic reticulum: insights from proteomic studies.

Chen Xuequn X Karnovsky Alla A Sans Maria Dolors MD Andrews Philip C PC Williams John A JA

Proteomics 20101102 22

The endoplasmic reticulum (ER) is a multifunctional intracellular organelle responsible for the synthesis, processing and trafficking of a wide variety of proteins essential for cell growth and survival. Therefore, comprehensive characterization of the ER proteome is of great importance to the understanding of its functions and has been actively pursued in the past decade by scientists in the proteomics field. This review summarizes major proteomic studies published in the past decade that focus ...[more]

PMID: 21080494

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Project description:BackgroundThe N-terminal proline-rich domain (Zera) of the maize storage protein γ-zein, is able to induce the formation of endoplasmic reticulum (ER)-derived protein bodies (PBs) when fused to proteins of interest. This encapsulation enables a recombinant fused protein to escape from degradation and facilitates its recovery from plant biomass by gradient purification. The aim of the present work was to evaluate if induced PBs encapsulate additional proteins jointly with the recombinant protein. The exhaustive analysis of protein composition of PBs is expected to facilitate a better understanding of PB formation and the optimization of recombinant protein purification approaches from these organelles.ResultsWe analysed the proteome of PBs induced in Nicotiana benthamiana leaves by transient transformation with Zera fused to a fluorescent marker protein (DsRed). Intact PBs with their surrounding ER-membrane were isolated on iodixanol based density gradients and their integrity verified by confocal and electron microscopy. SDS-PAGE analysis of isolated PBs showed that Zera-DsRed accounted for around 85% of PB proteins in term of abundance. Differential extraction of PBs was performed for in-depth analysis of their proteome and structure. Besides Zera-DsRed, 195 additional proteins were identified including a broad range of proteins resident or trafficking through the ER and recruited within the Zera-DsRed polymer.ConclusionsThis study indicates that Zera-protein fusion is still the major protein component of the new formed organelle in tobacco leaves. The analysis also reveals the presence of an unexpected diversity of proteins in PBs derived from both the insoluble Zera-DsRed polymer formation, including ER-resident and secretory proteins, and a secretory stress response induced most likely by the recombinant protein overloading. Knowledge of PBs protein composition is likely to be useful to optimize downstream purification of recombinant proteins in molecular farming applications.

Project description:Introduction: Bronchopulmonary dysplasia (BPD) is a life-threatening lung illness that affects premature infants and has a high incidence and mortality. Using interpretable machine learning, we aimed to investigate the involvement of endoplasmic reticulum (ER) stress-related genes (ERSGs) in BPD patients. Methods: We evaluated the expression profiles of endoplasmic reticulum stress-related genes and immune features in bronchopulmonary dysplasia using the GSE32472 dataset. The endoplasmic reticulum stress-related gene-based molecular clusters and associated immune cell infiltration were studied using 62 bronchopulmonary dysplasia samples. Cluster-specific differentially expressed genes (DEGs) were identified utilizing the WGCNA technique. The optimum machine model was applied after comparing its performance with that of the generalized linear model, the extreme Gradient Boosting, the support vector machine (SVM) model, and the random forest model. Validation of the prediction efficiency was done by the use of a calibration curve, nomogram, decision curve analysis, and an external data set. Results: The bronchopulmonary dysplasia samples were compared to the control samples, and the dysregulated endoplasmic reticulum stress-related genes and activated immunological responses were analyzed. In bronchopulmonary dysplasia, two distinct molecular clusters associated with endoplasmic reticulum stress were identified. The analysis of immune cell infiltration indicated a considerable difference in levels of immunity between the various clusters. As measured by residual and root mean square error, as well as the area under the curve, the support vector machine machine model showed the greatest discriminative capacity. In the end, an support vector machine model integrating five genes was developed, and its performance was shown to be excellent on an external validation dataset. The effectiveness in predicting bronchopulmonary dysplasia subtypes was further established by decision curves, calibration curves, and nomogram analyses. Conclusion: We developed a potential prediction model to assess the risk of endoplasmic reticulum stress subtypes and the clinical outcomes of bronchopulmonary dysplasia patients, and our work comprehensively revealed the complex association between endoplasmic reticulum stress and bronchopulmonary dysplasia.

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Molecular characterization of the endoplasmic reticulum: insights from proteomic studies.

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Molecular characterization of the endoplasmic reticulum: insights from proteomic studies.

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