scholarly journals The unfolded protein response to endoplasmic reticulum stress in cultured astrocytes and rat brain during experimental diabetes

2013 ◽  
Vol 62 (5) ◽  
pp. 784-795 ◽  
Author(s):  
Katrine R. Lind ◽  
Kelly K. Ball ◽  
Nancy F. Cruz ◽  
Gerald A. Dienel
Keyword(s):  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Rat Brain ◽  
Unfolded Protein Response ◽  
Experimental Diabetes ◽  
Unfolded Protein ◽  
Cultured Astrocytes ◽  
The Unfolded Protein Response ◽  
Protein Response

scholarly journals Human Cytomegalovirus Infection Activates and Regulates the Unfolded Protein Response

2005 ◽  
Vol 79 (11) ◽  
pp. 6890-6899 ◽  
Author(s):  
Jennifer A. Isler ◽  
Alison H. Skalet ◽  
James C. Alwine
Keyword(s):  
Endoplasmic Reticulum ◽  
Transcription Factor ◽  
Endoplasmic Reticulum Stress ◽  
Viral Infection ◽  
Unfolded Protein Response ◽  
Human Cytomegalovirus ◽  
Hcmv Infection ◽  
Unfolded Protein ◽  
The Unfolded Protein Response ◽  
Protein Response

ABSTRACT Viral infection causes stress to the endoplasmic reticulum. The response to endoplasmic reticulum stress, known as the unfolded protein response (UPR), is designed to eliminate misfolded proteins and allow the cell to recover by attenuating translation and upregulating the expression of chaperones, degradation factors, and factors that regulate the cell's metabolic and redox environment. Some consequences of the UPR (e.g., expression of chaperones and regulation of the metabolism and redox environment) may be advantageous to the viral infection; however, translational attenuation would not. Thus, viruses may induce mechanisms which modulate the UPR, maintaining beneficial aspects and suppressing deleterious aspects. We demonstrate that human cytomegalovirus (HCMV) infection induces the UPR but specifically regulates the three branches of UPR signaling, PKR-like ER kinase (PERK), activating transcription factor 6 (ATF6), and inositol-requiring enzyme 1 (IRE-1), to favor viral replication. HCMV infection activated the eIF2α kinase PERK; however, the amount of phosphorylated eIF2α was limited and translation attenuation did not occur. Interestingly, translation of select mRNAs, which is dependent on eIF2α phosphorylation, did occur, including the transcription factor ATF4, which activates genes which may benefit the infection. The endoplasmic reticulum stress-induced activation of the transcription factor ATF6 was suppressed in HCMV-infected cells; however, specific chaperone genes, normally activated by ATF6, were activated by a virus-induced, ATF6-independent mechanism. Lastly, HCMV infection activated the IRE-1 pathway, as indicated by splicing of Xbp-1 mRNA. However, transcriptional activation of the XBP-1 target gene EDEM (ER degradation-enhancing α-mannosidase-like protein, a protein degradation factor) was inhibited. These results suggest that, although HCMV infection induces the unfolded protein response, it modifies the outcome to benefit viral replication.

scholarly journals Endoplasmic reticulum stress, the unfolded protein response, and gene network modeling in antiestrogen resistant breast cancer

2011 ◽  
Vol 5 (1) ◽  
Author(s):  
Robert Clarke ◽  
Ayesha N. Shajahan ◽  
Yue Wang ◽  
John J. Tyson ◽  
Rebecca B. Riggins ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Endoplasmic Reticulum ◽  
Endoplasmic Reticulum Stress ◽  
Unfolded Protein Response ◽  
Network Modeling ◽  
Endocrine Resistance ◽  
Molecular Signaling ◽  
Unfolded Protein ◽  
The Unfolded Protein Response ◽  
Protein Response

AbstractLack of understanding of endocrine resistance remains one of the major challenges for breast cancer researchers, clinicians, and patients. Current reductionist approaches to understanding the molecular signaling driving resistance have offered mostly incremental progress over the past 10 years. As the field of systems biology has begun to mature, the approaches and network modeling tools being developed and applied therein offer a different way to think about how molecular signaling and the regulation of crucial cellular functions are integrated. To gain novel insights, we first describe some of the key challenges facing network modeling of endocrine resistance, many of which arise from the properties of the data spaces being studied. We then use activation of the unfolded protein response (UPR) following induction of endoplasmic reticulum stress in breast cancer cells by antiestrogens, to illustrate our approaches to computational modeling. Activation of UPR is a key determinant of cell fate decision-making and regulation of autophagy and apoptosis. These initial studies provide insight into a small subnetwork topology obtained using differential dependency network analysis and focused on the UPR gene XBP1. The XBP1 subnetwork topology incorporates BCAR3, BCL2, BIK, NF-κB, and other genes as nodes; the connecting edges represent the dependency structures among these nodes. As data from ongoing cellular and molecular studies become available, we will build detailed mathematical models of this XBP1-UPR network.

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