scholarly journals The yeast mitochondrial transport proteins: new sequences and consensus residues, lack of direct relation between consensus residues and transmembrane helices, expression patterns of the transport protein genes, and protein–protein interactions with other proteins

2000 ◽  
Vol 1467 (1) ◽  
pp. 207-218 ◽  
Author(s):  
Roman Belenkiy ◽  
Amanda Haefele ◽  
Michael B. Eisen ◽  
Hartmut Wohlrab
Keyword(s):  
Protein Interactions ◽  
Expression Patterns ◽  
Transport Proteins ◽  
Transport Protein ◽  
Direct Relation ◽  
Transmembrane Helices ◽  
Protein Protein Interactions ◽  
Mitochondrial Transport

scholarly journals On the Detection and Functional Significance of the Protein–Protein Interactions of Mitochondrial Transport Proteins

Biomolecules ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1107
Author(s):  
Youjun Zhang ◽  
Alisdair R. Fernie
Keyword(s):  
Protein Interactions ◽  
Transport Proteins ◽  
Interacting Proteins ◽  
Protein Protein Interactions ◽  
Protein Assemblies ◽  
Mitochondrial Transport ◽  
Receptor Complexes ◽  
Membrane Surfaces ◽  
Regulation Of Metabolism ◽  
Important Means

Protein–protein assemblies are highly prevalent in all living cells. Considerable evidence has recently accumulated suggesting that particularly transient association/dissociation of proteins represent an important means of regulation of metabolism. This is true not only in the cytosol and organelle matrices, but also at membrane surfaces where, for example, receptor complexes, as well as those of key metabolic pathways, are common. Transporters also frequently come up in lists of interacting proteins, for example, binding proteins that catalyze the production of their substrates or that act as relays within signal transduction cascades. In this review, we provide an update of technologies that are used in the study of such interactions with mitochondrial transport proteins, highlighting the difficulties that arise in their use for membrane proteins and discussing our current understanding of the biological function of such interactions.

scholarly journals Roles of the 14-3-3 gene family in cotton flowering

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Na Sang ◽  
Hui Liu ◽  
Bin Ma ◽  
Xianzhong Huang ◽  
Lu Zhuo ◽  
...  
Keyword(s):  
Gene Family ◽  
Protein Interactions ◽  
Leucine Zipper ◽  
Expression Patterns ◽  
Bimolecular Fluorescence Complementation ◽  
Structural Motif ◽  
Virus Induced Gene Silencing ◽  
Protein Protein Interactions ◽  
Basic Leucine Zipper ◽  
Genome Wide

Abstract Background In plants, 14-3-3 proteins, also called GENERAL REGULATORY FACTORs (GRFs), encoded by a large multigene family, are involved in protein–protein interactions and play crucial roles in various physiological processes. No genome-wide analysis of the GRF gene family has been performed in cotton, and their functions in flowering are largely unknown. Results In this study, 17, 17, 31, and 17 GRF genes were identified in Gossypium herbaceum, G. arboreum, G. hirsutum, and G. raimondii, respectively, by genome-wide analyses and were designated as GheGRFs, GaGRFs, GhGRFs, and GrGRFs, respectively. A phylogenetic analysis revealed that these proteins were divided into ε and non-ε groups. Gene structural, motif composition, synteny, and duplicated gene analyses of the identified GRF genes provided insights into the evolution of this family in cotton. GhGRF genes exhibited diverse expression patterns in different tissues. Yeast two-hybrid and bimolecular fluorescence complementation assays showed that the GhGRFs interacted with the cotton FLOWERING LOCUS T homologue GhFT in the cytoplasm and nucleus, while they interacted with the basic leucine zipper transcription factor GhFD only in the nucleus. Virus-induced gene silencing in G. hirsutum and transgenic studies in Arabidopsis demonstrated that GhGRF3/6/9/15 repressed flowering and that GhGRF14 promoted flowering. Conclusions Here, 82 GRF genes were identified in cotton, and their gene and protein features, classification, evolution, and expression patterns were comprehensively and systematically investigated. The GhGRF3/6/9/15 interacted with GhFT and GhFD to form florigen activation complexs that inhibited flowering. However, GhGRF14 interacted with GhFT and GhFD to form florigen activation complex that promoted flowering. The results provide a foundation for further studies on the regulatory mechanisms of flowering.

scholarly journals Shared Blood Transcriptomic Signatures between Alzheimer’s Disease and Diabetes Mellitus

Biomedicines ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 34
Author(s):  
Taesic Lee ◽  
Hyunju Lee
Keyword(s):  
Diabetes Mellitus ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Protein Interactions ◽  
Expression Patterns ◽  
Protein Protein Interactions ◽  
Hub Genes ◽  
Gene Modules ◽  
Gene Regulatory ◽  
The Brain

Alzheimer’s disease (AD) and diabetes mellitus (DM) are known to have a shared molecular mechanism. We aimed to identify shared blood transcriptomic signatures between AD and DM. Blood expression datasets for each disease were combined and a co-expression network was used to construct modules consisting of genes with similar expression patterns. For each module, a gene regulatory network based on gene expression and protein-protein interactions was established to identify hub genes. We selected one module, where COPS4, PSMA6, GTF2B, GTF2F2, and SSB were identified as dysregulated transcription factors that were common between AD and DM. These five genes were also differentially co-expressed in disease-related tissues, such as the brain in AD and the pancreas in DM. Our study identified gene modules that were dysregulated in both AD and DM blood samples, which may contribute to reveal common pathophysiology between two diseases.

scholarly journals Distinct p53 acetylation cassettes differentially influence gene-expression patterns and cell fate

2006 ◽  
Vol 173 (4) ◽  
pp. 533-544 ◽  
Author(s):  
Chad D. Knights ◽  
Jason Catania ◽  
Simone Di Giovanni ◽  
Selen Muratoglu ◽  
Ricardo Perez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Fate ◽  
Protein Interactions ◽  
Posttranslational Modifications ◽  
Biological Activities ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Gene Expression Profiles ◽  
P53 Gene ◽  
Protein Protein Interactions

The activity of the p53 gene product is regulated by a plethora of posttranslational modifications. An open question is whether such posttranslational changes act redundantly or dependently upon one another. We show that a functional interference between specific acetylated and phosphorylated residues of p53 influences cell fate. Acetylation of lysine 320 (K320) prevents phosphorylation of crucial serines in the NH2-terminal region of p53; only allows activation of genes containing high-affinity p53 binding sites, such as p21/WAF; and promotes cell survival after DNA damage. In contrast, acetylation of K373 leads to hyperphosphorylation of p53 NH2-terminal residues and enhances the interaction with promoters for which p53 possesses low DNA binding affinity, such as those contained in proapoptotic genes, leading to cell death. Further, acetylation of each of these two lysine clusters differentially regulates the interaction of p53 with coactivators and corepressors and produces distinct gene-expression profiles. By analogy with the “histone code” hypothesis, we propose that the multiple biological activities of p53 are orchestrated and deciphered by different “p53 cassettes,” each containing combination patterns of posttranslational modifications and protein–protein interactions.

scholarly journals Identification and characterization of interactions between the vertebrate polycomb-group protein BMI1 and human homologs of polyhomeotic.

1997 ◽  
Vol 17 (4) ◽  
pp. 2326-2335 ◽  
Author(s):  
M J Gunster ◽  
D P Satijn ◽  
K M Hamer ◽  
J L den Blaauwen ◽  
D de Bruijn ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Expression Patterns ◽  
Polycomb Group ◽  
Polycomb Group Protein ◽  
Protein Protein Interactions ◽  
Human Proteins ◽  
Group Protein ◽  
The Individual ◽  
Domain I ◽  
Homology Domains

In Drosophila melanogaster, the Polycomb-group (PcG) genes have been identified as repressors of gene expression. They are part of a cellular memory system that is responsible for the stable transmission of gene activity to progeny cells. PcG proteins form a large multimeric, chromatin-associated protein complex, but the identity of its components is largely unknown. Here, we identify two human proteins, HPH1 and HPH2, that are associated with the vertebrate PcG protein BMI1. HPH1 and HPH2 coimmunoprecipitate and cofractionate with each other and with BMI1. They also colocalize with BMI1 in interphase nuclei of U-2 OS human osteosarcoma and SW480 human colorectal adenocarcinoma cells. HPH1 and HPH2 have little sequence homology with each other, except in two highly conserved domains, designated homology domains I and II. They share these homology domains I and II with the Drosophila PcG protein Polyhomeotic (Ph), and we, therefore, have named the novel proteins HPH1 and HPH2. HPH1, HPH2, and BMI1 show distinct, although overlapping expression patterns in different tissues and cell lines. Two-hybrid analysis shows that homology domain II of HPH1 interacts with both homology domains I and II of HPH2. In contrast, homology domain I of HPH1 interacts only with homology domain II of HPH2, but not with homology domain I of HPH2. Furthermore, BMI1 does not interact with the individual homology domains. Instead, both intact homology domains I and II need to be present for interactions with BMI1. These data demonstrate the involvement of homology domains I and II in protein-protein interactions and indicate that HPH1 and HPH2 are able to heterodimerize.

scholarly journals Integrative analysis identified common and unique molecular signatures in hepatobiliary cancers

2021 ◽  
Author(s):  
Nabanita Roy ◽  
Ria Lodh ◽  
Anupam Sarma ◽  
Dhruba Kumar Bhattacharyya ◽  
Pankaj Barah
Keyword(s):  
Protein Interactions ◽  
Metabolic Pathways ◽  
Expression Patterns ◽  
Molecular Signature ◽  
Cancer Type ◽  
Molecular Signatures ◽  
Protein Protein Interactions ◽  
Hub Genes ◽  
Cellular Processes ◽  
Differential Gene

Hepatobiliary cancers (HBCs) are the most aggressive and sixth most diagnosed cancers globally. Biomarkers for timely diagnosis and targeted therapy in HBCs are still limited. Considering the gap, our objective is to identify unique and overlapping molecular signatures associated with HBCs. We analyzed publicly available transcriptomic datasets on Gallbladder cancer (GBC), Hepatocellular carcinoma (HCC), and Intrahepatic cholangiocarcinoma (ICC) to identify potential biomarkers using integrative systems approaches. An effective Common and Unique Molecular Signature Identification (CUMSI) approach has been employed, which contains analysis of differential gene expression (DEG), gene co-expression networks (GCN), and protein-protein interactions (PPIs) networks. Functional analysis of the DEGs unique for GBC, HCC, and ICC indicated that GBC is associated with cellular processes, HCC is associated with immune signaling pathways, and ICC is associated with lipid metabolic pathways. Our findings shows that the hub genes and pathways identified for each individual cancer type of the HBS are related with the primary function of each organ and each cancer exhibit unique expression patterns despite being part of the same organ system.

scholarly journals Bioinformatics and Multi-omics Approach to Identify Comorbidities with Application in Schizophrenia with Psychiatric Disorders

2021 ◽  
pp. 35-47
Keyword(s):  
Gene Expression ◽  
Signaling Pathway ◽  
Protein Interactions ◽  
Depressive Disorders ◽  
Expression Patterns ◽  
Mapk Signaling ◽  
Protein Protein Interactions ◽  
Obsessive Compulsive ◽  
Psychiatric Comorbidities ◽  
Compulsive Disorder

Schizophrenia (SCZ) is a major psychiatric disorder and often presents with psychiatric comorbidities. But, the interactions or links between the pathogenesis of SCZ and comorbidities are not known. In this study, we aimed to develop an integrated multi-omics approach based on gene expression, gene ontology, pathways, protein-protein interactions data that help clinical researchers to assess the links between SCZ and major psychiatric pathologies. We compared the transcriptomic alterations between diseases and controls and observed significant perturbed gene expression patterns i.e. differentially expressed (DEGs) shared among SCZ and major depressive disorders, obsessive-compulsive disorder, alcoholism, eating disorder. We observed deregulated expression of three DEGs, namely, HAPLN1, CNDP1, SLC12A2 in SCZ and pathologies, which were common among the selected pathologies suggesting the selected disorders are comorbidities of SCZ. The pathways including FoxO signaling pathway, MAPK signaling pathway, transcriptional misregulation in cancer, cellular senescence, cell cycle, PI3-Akt signaling pathway, TNF signaling pathway, and TGF-beta signaling pathway altered by the shared SCZ and psychiatric comorbidities also identified. The present study revealed biomolecules (DEGs), ontologies, and cellular pathways of the etiopathogenetic mechanisms of SCZ and psychiatric comorbidities.

Mass spectrometry enables the discovery of inhibitors of an LPS transport assembly via disruption of protein-protein interactions

2021 ◽  
Author(s):  
Francesco Fiorentino ◽  
Dante Rotili ◽  
Antonello Mai ◽  
Jani Bolla ◽  
Carol Vivien Robinson
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Native Mass Spectrometry ◽  
Transport Protein ◽  
Protein Protein Interactions

We developed a native mass spectrometry-based approach to quantify the monomer-dimer equilibrium of the LPS transport protein LptH. We use this method to assess the potency and efficacy of an...

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