scholarly journals Comparative interactomes of HSF1 in stress and disease reveal a role for CTCF in HSF1-mediated gene regulation

2020 ◽  
pp. jbc.RA120.015452
Author(s):  
Eileen T. Burchfiel ◽  
Anniina Vihervaara ◽  
Michael J. Guertin ◽  
Rocio Gomez-Pastor ◽  
Dennis J. Thiele
Keyword(s):  
Heat Shock ◽  
Rna Polymerase Ii ◽  
Protein Interactions ◽  
Target Genes ◽  
Regulatory Protein ◽  
Normal Growth ◽  
Gene Repression ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Acute And Chronic Stress

Heat Shock Transcription Factor 1 (HSF1) orchestrates cellular stress protection by activating or repressing gene transcription in response to protein misfolding, oncogenic cell proliferation and other environmental stresses. HSF1 is tightly regulated via intramolecular repressive interactions, post-translational modifications, and protein-protein interactions. How these HSF1 regulatory protein interactions are altered in response to acute and chronic stress is largely unknown. To elucidate the profile of HSF1 protein interactions under normal growth, chronic and acutely stressful conditions, quantitative proteomics studies identified interacting proteins in the response to heat shock or in the presence of a poly-glutamine aggregation protein cell-based model of Huntington’s Disease. These studies identified distinct protein interaction partners of HSF1 as well as changes in the magnitude of shared interactions as a function of each stressful condition. Several novel HSF1-interacting proteins were identified that encompass a wide variety of cellular functions, including roles in DNA repair, mRNA processing, regulation of RNA polymerase II and others. One HSF1 partner, CTCF, interacted with HSF1 in a stress-inducible manner and functions in repression of specific HSF1 target genes. Understanding how HSF1 regulates gene repression is a crucial question, given the dysregulation of HSF1 target genes in both cancer and neurodegeration. These studies expand our understanding of HSF1-mediated gene repression and provide key insights into HSF1 regulation via protein-protein interactions.

scholarly journals Ways into Understanding HIF Inhibition

Cancers ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 159
Author(s):  
Tina Schönberger ◽  
Joachim Fandrey ◽  
Katrin Prost-Fingerle
Keyword(s):  
Protein Interactions ◽  
Target Genes ◽  
Protein Protein Interactions ◽  
Low Oxygen ◽  
Drug Candidates ◽  
Open Questions ◽  
Wide Range ◽  
Hif Pathway

Hypoxia is a key characteristic of tumor tissue. Cancer cells adapt to low oxygen by activating hypoxia-inducible factors (HIFs), ensuring their survival and continued growth despite this hostile environment. Therefore, the inhibition of HIFs and their target genes is a promising and emerging field of cancer research. Several drug candidates target protein–protein interactions or transcription mechanisms of the HIF pathway in order to interfere with activation of this pathway, which is deregulated in a wide range of solid and liquid cancers. Although some inhibitors are already in clinical trials, open questions remain with respect to their modes of action. New imaging technologies using luminescent and fluorescent methods or nanobodies to complement widely used approaches such as chromatin immunoprecipitation may help to answer some of these questions. In this review, we aim to summarize current inhibitor classes targeting the HIF pathway and to provide an overview of in vitro and in vivo techniques that could improve the understanding of inhibitor mechanisms. Unravelling the distinct principles regarding how inhibitors work is an indispensable step for efficient clinical applications and safety of anticancer compounds.

Dependence of KCC2 K-Cl cotransporter activity on a conserved carboxy terminus tyrosine residue

2000 ◽  
Vol 279 (3) ◽  
pp. C860-C867 ◽  
Author(s):  
Kevin Strange ◽  
Thomas D. Singer ◽  
Rebecca Morrison ◽  
Eric Delpire
Keyword(s):  
Protein Interactions ◽  
Regulatory Protein ◽  
Phosphorylation Site ◽  
Fold Increase ◽  
Tyrosine Residue ◽  
Carboxy Terminus ◽  
Protein Protein Interactions ◽  
Pharmacological Studies ◽  
Osmotic Homeostasis ◽  
Tyrosine Phosphorylation Site

K-Cl cotransporters (KCC) play fundamental roles in ionic and osmotic homeostasis. To date, four mammalian KCC genes have been identified. KCC2 is expressed exclusively in neurons. Injection of Xenopus oocytes with KCC2 cRNA induced a 20-fold increase in Cl−-dependent, furosemide-sensitive K+ uptake. Oocyte swelling increased KCC2 activity 2–3 fold. A canonical tyrosine phosphorylation site is located in the carboxy termini of KCC2 (R1081–Y1087) and KCC4, but not in other KCC isoforms. Pharmacological studies, however, revealed no regulatory role for phosphorylation of KCC2 tyrosine residues. Replacement of Y1087 with aspartate or arginine dramatically reduced K+ uptake under isotonic and hypotonic conditions. Normal or near-normal cotransporter activity was observed when Y1087 was mutated to phenylalanine, alanine, or isoleucine. A tyrosine residue equivalent to Y1087 is conserved in all identified KCCs from nematodes to humans. Mutation of the Y1087 congener in KCC1 to aspartate also dramatically inhibited cotransporter activity. Taken together, these results suggest that replacement of Y1087 and its congeners with charged residues disrupts the conformational state of the carboxy terminus. We postulate that the carboxy terminus plays an essential role in maintaining the functional conformation of KCC cotransporters and/or is involved in essential regulatory protein-protein interactions.

scholarly journals Sequence conservation, domain architectures, and phylogenetic distribution of the HD-GYP type c-di-GMP phosphodiesterases

2021 ◽  
Author(s):  
Michael Y. Galperin ◽  
Shan-Ho Chou
Keyword(s):  
Protein Interactions ◽  
Regulatory Protein ◽  
Second Messenger ◽  
Distribution Patterns ◽  
Distribution Functions ◽  
Amino Acid Residues ◽  
Sequence Motifs ◽  
Protein Protein Interactions ◽  
Conserved Sequence ◽  
Common Domain

The HD-GYP domain, named after two of its conserved sequence motifs, was first described in 1999 as a specialized version of the widespread HD phosphohydrolase domain that had additional highly conserved amino acid residues. Domain associations of HD-GYP indicated its involvement in bacterial signal transduction and distribution patterns of this domain suggested that it could serve as a hydrolase of the bacterial second messenger c-di-GMP, in addition to or instead of the EAL domain. Subsequent studies confirmed the ability of various HD-GYP domains to hydrolyze c-di-GMP to linear pGpG and/or GMP. Certain HD-GYP-containing proteins hydrolyze another second messenger, cGAMP, and some HD-GYP domains participate in regulatory protein-protein interactions. The recently solved structures of HD-GYP domains from four distinct organisms clarified the mechanisms of c-di-GMP binding and metal-assisted hydrolysis. However, the HD-GYP domain is poorly represented in public domain databases, which causes certain confusion about its phylogenic distribution, functions, and domain architectures. Here, we present a refined sequence model for the HD-GYP domain and describe the roles of its most conserved residues in metal and/or substrate binding. We also calculate the numbers of HD-GYPs encoded in various genomes and list the most common domain combinations involving HD-GYP, such as the RpfG (REC-HD-GYP), Bd1817 (DUF3391-HD-GYP), and PmGH (GAF-HD-GYP) protein families. We also provide the descriptions of six HD-GYP-associated domains, including four novel integral membrane sensor domains. This work is expected to stimulate studies of diverse HD-GYP-containing proteins, their N-terminal sensor domains, and the signals to which they respond.

scholarly journals Critical Protein–Protein Interactions Determine the Biological Activity of Elk-1, A Master Regulator of Stimulus-Induced Gene Transcription

Molecules ◽  
2021 ◽  
Vol 26 (20) ◽  
pp. 6125
Author(s):  
Gerald Thiel ◽  
Tobias M. Backes ◽  
Lisbeth A. Guethlein ◽  
Oliver G. Rössler
Keyword(s):  
Protein Kinase ◽  
Rna Polymerase Ii ◽  
Histone Deacetylase ◽  
Gene Transcription ◽  
Protein Interactions ◽  
Cellular Proliferation ◽  
Biological Function ◽  
Protein Protein Interactions ◽  
Inactive State ◽  
Serum Response

Elk-1 is a transcription factor that binds together with a dimer of the serum response factor (SRF) to the serum-response element (SRE), a genetic element that connects cellular stimulation with gene transcription. Elk-1 plays an important role in the regulation of cellular proliferation and apoptosis, thymocyte development, glucose homeostasis and brain function. The biological function of Elk-1 relies essentially on the interaction with other proteins. Elk-1 binds to SRF and generates a functional ternary complex that is required to activate SRE-mediated gene transcription. Elk-1 is kept in an inactive state under basal conditions via binding of a SUMO-histone deacetylase complex. Phosphorylation by extracellular signal-regulated protein kinase, c-Jun N-terminal protein kinase or p38 upregulates the transcriptional activity of Elk-1, mediated by binding to the mediator of RNA polymerase II transcription (Mediator) and the transcriptional coactivator p300. Strong and extended phosphorylation of Elk-1 attenuates Mediator and p300 recruitment and allows the binding of the mSin3A-histone deacetylase corepressor complex. The subsequent dephosphorylation of Elk-1, catalyzed by the protein phosphatase calcineurin, facilitates the re-SUMOylation of Elk-1, transforming Elk-1 back to a transcriptionally inactive state. Thus, numerous protein–protein interactions control the activation cycle of Elk-1 and are essential for its biological function.

scholarly journals Phylogenetic correlations can suffice to infer protein partners from sequences

2019 ◽  
Author(s):  
Guillaume Marmier ◽  
Martin Weigt ◽  
Anne-Florence Bitbol
Keyword(s):  
Protein Interactions ◽  
Evolutionary History ◽  
Sequence Data ◽  
Sequence Similarity ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Coupling Analysis ◽  
Interaction Partners ◽  
Direct Coupling Analysis ◽  
Partner Proteins

AbstractDetermining which proteins interact together is crucial to a systems-level understanding of the cell. Recently, algorithms based on Direct Coupling Analysis (DCA) pairwise maximum-entropy models have allowed to identify interaction partners among the paralogs of ubiquitous prokaryotic proteins families, starting from sequence data alone. Since DCA allows to infer the three-dimensional structure of protein complexes, its success in predicting protein-protein interactions could be mainly based on contacting residues coevolving to remain physicochemically complementary. However, interacting proteins often possess similar evolutionary histories, which also gives rise to correlations among their sequences. What is the role of purely phylogenetic correlations in the performance of DCA-based methods to infer interaction partners? To address this question, we employ controlled synthetic data that only involves phylogeny and no interactions or contacts. We find that DCA accurately identifies the pairs of synthetic sequences that only share evolutionary history. It performs as well as methods explicitly based on sequence similarity, and even slightly better with large and accurate training sets. We further demonstrate the ability of these various methods to correctly predict pairings among actual paralogous proteins with genome proximity but no known direct physical interaction, which illustrates the importance of phylogenetic correlations in real data. However, for actually interacting and strongly coevolving proteins, DCA and mutual information outperform sequence similarity.Author summaryMany biologically important protein-protein interactions are conserved over evolutionary time scales. This leads to two different signals that can be used to computationally predict interactions between protein families and to identify specific interaction partners. First, the shared evolutionary history leads to highly similar phylogenetic relationships between interacting proteins of the two families. Second, the need to keep the interaction surfaces of partner proteins biophysically compatible causes a correlated amino-acid usage of interface residues. Employing simulated data, we show that the shared history alone can be used to detect partner proteins. Similar accuracies are achieved by algorithms comparing phylogenetic relationships and by coevolutionary methods based on Direct Coupling Analysis, which are a priori designed to detect the second type of signal. Using real sequence data, we show that in cases with shared evolutionary but without known physical interactions, both methods work with similar accuracy, while for physically interacting systems, methods based on correlated amino-acid usage outperform purely phylogenetic ones.

scholarly journals Identification of key microRNAs in the carotid arteries of ApoE−/− mice exposed to disturbed flow

Hereditas ◽  
2019 ◽  
Vol 156 (1) ◽  
Author(s):  
Xinzhou Wang ◽  
Shuibo Gao ◽  
Liping Dai ◽  
Zhentao Wang ◽  
Hong Wu
Keyword(s):  
Blood Flow ◽  
Protein Interactions ◽  
Carotid Arteries ◽  
Target Genes ◽  
Pathological Process ◽  
Mitogen Activated Protein Kinase ◽  
Molecular Pathways ◽  
Protein Protein Interactions ◽  
Mitogen Activated Protein ◽  
Limma Package

Abstract Background Atherosclerosis (AS) is one of the main causes of cardiovascular disease. AS plaques often occur in blood vessels with oscillatory blood flow and their formation can be regulated by microRNAs (miRNAs). The aim of this study is to identify the key miRNAs and molecular pathways involved in this pathological process. Methods In this study, gene chip data obtained from the GEO database was analyzed using the LIMMA package to find differentially expressed miRNAs (DE miRNAs) in the carotid arteries of ApoE−/− mice exposed to different blood flow rates. Predicted targets of the DE miRNAs were identified using the TargetScan, miRDB, and DIANA databases respectively, and the potential target genes (PTGs) were found by analyzing the common results of three databases. The DAVID database was used to enrich the PTGs based on gene ontology (GO) and pathway (Kyoto Encyclopedia of Genes and Genomes, KEGG), and the STRING database was used to uncover any protein-protein interactions (PPI) of the PTGs. Results The networks of the DE miRNAs-PTGs, Pathway-PTGs-DE miRNAs, and PTGs PPI, were constructed using Cytoscape, and 11 up-regulated and 13 down-regulated DE miRNAs and 1479 PTGs were found. GO results showed that PTGs were significantly enriched in functions such as transcriptional regulation and DNA binding. KEGG results showed that PTGs were significantly enriched in inflammation-related mitogen-activated protein kinase (MAPK) and AS-related FOXO pathways. The PPI network revealed some key target genes in the PTGs. Conclusions The analysis of key miRNAs and molecular pathways that regulate the formation of AS plaques induced by oscillatory blood flow will provide new ideas for AS treatment.

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