scholarly journals Genome-Wide Identification and Analysis of the Polycomb Group Family in Medicago truncatula

2021 ◽  
Vol 22 (14) ◽  
pp. 7537
Author(s):  
Yuanyuan Zhao ◽  
Junchao Zhang ◽  
Zhanmin Sun ◽  
Yixiong Tang ◽  
Yanmin Wu
Keyword(s):  
Medicago Truncatula ◽  
Protein Interactions ◽  
Stress Responses ◽  
Regulatory Networks ◽  
Developmental Stages ◽  
Interaction Network ◽  
Polycomb Group ◽  
Protein Protein Interactions ◽  
Group I ◽  
Gene Structures

Polycomb group (PcG) proteins, which are important epigenetic regulators, play essential roles in the regulatory networks involved in plant growth, development, and environmental stress responses. Currently, as far as we know, no comprehensive and systematic study has been carried out on the PcG family in Medicago truncatula. In the present study, we identified 64 PcG genes with distinct gene structures from the M. truncatula genome. All of the PcG genes were distributed unevenly over eight chromosomes, of which 26 genes underwent gene duplication. The prediction of protein interaction network indicated that 34 M. truncatula PcG proteins exhibited protein–protein interactions, and MtMSI1;4 and MtVRN2 had the largest number of protein–protein interactions. Based on phylogenetic analysis, we divided 375 PcG proteins from 27 species into three groups and nine subgroups. Group I and Group III were composed of five components from the PRC1 complex, and Group II was composed of four components from the PRC2 complex. Additionally, we found that seven PcG proteins in M. truncatula were closely related to the corresponding proteins of Cicer arietinum. Syntenic analysis revealed that PcG proteins had evolved more conservatively in dicots than in monocots. M. truncatula had the most collinearity relationships with Glycine max (36 genes), while collinearity with three monocots was rare (eight genes). The analysis of various types of expression data suggested that PcG genes were involved in the regulation and response process of M. truncatula in multiple developmental stages, in different tissues, and for various environmental stimuli. Meanwhile, many differentially expressed genes (DEGs) were identified in the RNA-seq data, which had potential research value in further studies on gene function verification. These findings provide novel and detailed information on the M. truncatula PcG family, and in the future it would be helpful to carry out related research on the PcG family in other legumes.

Algorithmic and Stochastic Representations of Gene Regulatory Networks and Protein-Protein Interactions

2019 ◽  
Vol 19 (6) ◽  
pp. 413-425 ◽  
Author(s):  
Athanasios Alexiou ◽  
Stylianos Chatzichronis ◽  
Asma Perveen ◽  
Abdul Hafeez ◽  
Ghulam Md. Ashraf
Keyword(s):  
Protein Interactions ◽  
Biological Networks ◽  
Regulatory Networks ◽  
Review Paper ◽  
Boolean Networks ◽  
Diagnostic Tools ◽  
Complex Nature ◽  
Cellular Interactions ◽  
Protein Protein Interactions ◽  
Deterministic Models

Background:Latest studies reveal the importance of Protein-Protein interactions on physiologic functions and biological structures. Several stochastic and algorithmic methods have been published until now, for the modeling of the complex nature of the biological systems.Objective:Biological Networks computational modeling is still a challenging task. The formulation of the complex cellular interactions is a research field of great interest. In this review paper, several computational methods for the modeling of GRN and PPI are presented analytically.Methods:Several well-known GRN and PPI models are presented and discussed in this review study such as: Graphs representation, Boolean Networks, Generalized Logical Networks, Bayesian Networks, Relevance Networks, Graphical Gaussian models, Weight Matrices, Reverse Engineering Approach, Evolutionary Algorithms, Forward Modeling Approach, Deterministic models, Static models, Hybrid models, Stochastic models, Petri Nets, BioAmbients calculus and Differential Equations.Results:GRN and PPI methods have been already applied in various clinical processes with potential positive results, establishing promising diagnostic tools.Conclusion:In literature many stochastic algorithms are focused in the simulation, analysis and visualization of the various biological networks and their dynamics interactions, which are referred and described in depth in this review paper.

scholarly journals Short loop functional commonality identified in leukaemia proteome highlights crucial protein sub-networks

2021 ◽  
Vol 3 (1) ◽  
Author(s):  
Sun Sook Chung ◽  
Joseph C F Ng ◽  
Anna Laddach ◽  
N Shaun B Thomas ◽  
Franca Fraternali
Keyword(s):  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Short Loop ◽  
New Strategy ◽  
Loop Network ◽  
Protein Protein Interaction Network

Abstract Direct drug targeting of mutated proteins in cancer is not always possible and efficacy can be nullified by compensating protein–protein interactions (PPIs). Here, we establish an in silico pipeline to identify specific PPI sub-networks containing mutated proteins as potential targets, which we apply to mutation data of four different leukaemias. Our method is based on extracting cyclic interactions of a small number of proteins topologically and functionally linked in the Protein–Protein Interaction Network (PPIN), which we call short loop network motifs (SLM). We uncover a new property of PPINs named ‘short loop commonality’ to measure indirect PPIs occurring via common SLM interactions. This detects ‘modules’ of PPI networks enriched with annotated biological functions of proteins containing mutation hotspots, exemplified by FLT3 and other receptor tyrosine kinase proteins. We further identify functional dependency or mutual exclusivity of short loop commonality pairs in large-scale cellular CRISPR–Cas9 knockout screening data. Our pipeline provides a new strategy for identifying new therapeutic targets for drug discovery.

scholarly journals Short Linear Motifs Characterizing Snake Venom and Mammalian Phospholipases A2

Toxins ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 290
Author(s):  
Caterina Peggion ◽  
Fiorella Tonello
Keyword(s):  
Snake Venom ◽  
Protein Interactions ◽  
Biological Properties ◽  
Protein Protein Interactions ◽  
Sequence Alignments ◽  
Toxic Activity ◽  
Short Linear Motifs ◽  
Phospholipases A2 ◽  
Group I ◽  
Linear Motifs

Snake venom phospholipases A2 (PLA2s) have sequences and structures very similar to those of mammalian group I and II secretory PLA2s, but they possess many toxic properties, ranging from the inhibition of coagulation to the blockage of nerve transmission, and the induction of muscle necrosis. The biological properties of these proteins are not only due to their enzymatic activity, but also to protein–protein interactions which are still unidentified. Here, we compare sequence alignments of snake venom and mammalian PLA2s, grouped according to their structure and biological activity, looking for differences that can justify their different behavior. This bioinformatics analysis has evidenced three distinct regions, two central and one C-terminal, having amino acid compositions that distinguish the different categories of PLA2s. In these regions, we identified short linear motifs (SLiMs), peptide modules involved in protein–protein interactions, conserved in mammalian and not in snake venom PLA2s, or vice versa. The different content in the SLiMs of snake venom with respect to mammalian PLA2s may result in the formation of protein membrane complexes having a toxic activity, or in the formation of complexes whose activity cannot be blocked due to the lack of switches in the toxic PLA2s, as the motif recognized by the prolyl isomerase Pin1.

scholarly journals Frequent assembly of chimeric complexes in the protein interaction network of an interspecies yeast hybrid

2020 ◽  
Author(s):  
Rohan Dandage ◽  
Caroline M Berger ◽  
Isabelle Gagnon-Arsenault ◽  
Kyung-Mee Moon ◽  
Richard Greg Stacey ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Molecular Level ◽  
Yeast Species ◽  
Protein Complexes ◽  
Mitochondrial Protein ◽  
Chimeric Protein ◽  
Interaction Network ◽  
Protein Protein Interactions ◽  
Extreme Phenotypes ◽  
Yeast Hybrid

Abstract Hybrids between species often show extreme phenotypes, including some that take place at the molecular level. In this study, we investigated the phenotypes of an interspecies diploid hybrid in terms of protein-protein interactions inferred from protein correlation profiling. We used two yeast species, Saccharomyces cerevisiae and Saccharomyces uvarum, which are interfertile, but yet have proteins diverged enough to be differentiated using mass spectrometry. Most of the protein-protein interactions are similar between hybrid and parents, and are consistent with the assembly of chimeric complexes, which we validated using an orthogonal approach for the prefoldin complex. We also identified instances of altered protein-protein interactions in the hybrid, for instance in complexes related to proteostasis and in mitochondrial protein complexes. Overall, this study uncovers the likely frequent occurrence of chimeric protein complexes with few exceptions, which may result from incompatibilities or imbalances between the parental proteins.

scholarly journals PIPINO: A Software Package to Facilitate the Identification of Protein-Protein Interactions from Affinity Purification Mass Spectrometry Data

2016 ◽  
Vol 2016 ◽  
pp. 1-13
Author(s):  
Stefan Kalkhof ◽  
Stefan Schildbach ◽  
Conny Blumert ◽  
Friedemann Horn ◽  
Martin von Bergen ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Interactions ◽  
Isotope Labeling ◽  
Affinity Purification ◽  
Interaction Network ◽  
Mass Spectrometry Data ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Binding Behavior ◽  
Bona Fide

The functionality of most proteins is regulated by protein-protein interactions. Hence, the comprehensive characterization of the interactome is the next milestone on the path to understand the biochemistry of the cell. A powerful method to detect protein-protein interactions is a combination of coimmunoprecipitation or affinity purification with quantitative mass spectrometry. Nevertheless, both methods tend to precipitate a high number of background proteins due to nonspecific interactions. To address this challenge the software Protein-Protein-Interaction-Optimizer (PIPINO) was developed to perform an automated data analysis, to facilitate the selection of bona fide binding partners, and to compare the dynamic of interaction networks. In this study we investigated the STAT1 interaction network and its activation dependent dynamics. Stable isotope labeling by amino acids in cell culture (SILAC) was applied to analyze the STAT1 interactome after streptavidin pull-down of biotagged STAT1 from human embryonic kidney 293T cells with and without activation. Starting from more than 2,000 captured proteins 30 potential STAT1 interaction partners were extracted. Interestingly, more than 50% of these were already reported or predicted to bind STAT1. Furthermore, 16 proteins were found to affect the binding behavior depending on STAT1 phosphorylation such as STAT3 or the importin subunits alpha 1 and alpha 6.

scholarly journals Genome-wide analysis of autophagy-related genes in Medicago truncatula highlights their roles in seed development and response to drought stress

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingkang Yang ◽  
Liping Wang ◽  
Chumin Chen ◽  
Xu Guo ◽  
Chuanglie Lin ◽  
...  
Keyword(s):  
Drought Stress ◽  
Seed Development ◽  
Medicago Truncatula ◽  
Interaction Network ◽  
Abiotic Stress Response ◽  
Biotic And Abiotic Stress ◽  
Comprehensive Overview ◽  
Network Analyses ◽  
Atg Genes ◽  
Gene Structures

AbstractAutophagy is a highly conserved process of degradation of cytoplasmic constituents in eukaryotes. It is involved in the growth and development of plants, as well as in biotic and abiotic stress response. Although autophagy-related (ATG) genes have been identified and characterized in many plant species, little is known about this process in Medicago truncatula. In this study, 39 ATGs were identified, and their gene structures and conserved domains were systematically characterized in M. truncatula. Many cis-elements, related to hormone and stress responsiveness, were identified in the promoters of MtATGs. Phylogenetic and interaction network analyses suggested that the function of MtATGs is evolutionarily conserved in Arabidopsis and M. truncatula. The expression of MtATGs, at varied levels, was detected in all examined tissues. In addition, most of the MtATGs were highly induced during seed development and drought stress, which indicates that autophagy plays an important role in seed development and responses to drought stress in M. truncatula. In conclusion, this study gives a comprehensive overview of MtATGs and provides important clues for further functional analysis of autophagy in M. truncatula.

scholarly journals Group I Metabotropic Glutamate Receptors and Interacting Partners: An Update

2022 ◽  
Vol 23 (2) ◽  
pp. 840
Author(s):  
Li-Min Mao ◽  
Alaya Bodepudi ◽  
Xiang-Ping Chu ◽  
John Q. Wang
Keyword(s):  
Synaptic Plasticity ◽  
Protein Interactions ◽  
Metabotropic Glutamate Receptors ◽  
Adaptor Proteins ◽  
Mammalian Brain ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Metabotropic Glutamate ◽  
Group I ◽  
Associated Proteins

Group I metabotropic glutamate (mGlu) receptors (mGlu1/5 subtypes) are G protein-coupled receptors and are broadly expressed in the mammalian brain. These receptors play key roles in the modulation of normal glutamatergic transmission and synaptic plasticity, and abnormal mGlu1/5 signaling is linked to the pathogenesis and symptomatology of various mental and neurological disorders. Group I mGlu receptors are noticeably regulated via a mechanism involving dynamic protein–protein interactions. Several synaptic protein kinases were recently found to directly bind to the intracellular domains of mGlu1/5 receptors and phosphorylate the receptors at distinct amino acid residues. A variety of scaffolding and adaptor proteins also interact with mGlu1/5. Constitutive or activity-dependent interactions between mGlu1/5 and their interacting partners modulate trafficking, anchoring, and expression of the receptors. The mGlu1/5-associated proteins also finetune the efficacy of mGlu1/5 postreceptor signaling and mGlu1/5-mediated synaptic plasticity. This review analyzes the data from recent studies and provides an update on the biochemical and physiological properties of a set of proteins or molecules that interact with and thus regulate mGlu1/5 receptors.

scholarly journals Genome-wide Identification and Expression Analysis of Autophagy-related Genes (ATGs) in Medicago Truncatula

2020 ◽  
Author(s):  
Mingkang Yang ◽  
Liping Wang ◽  
Xu Guo ◽  
Chuanglie Lin ◽  
Wei Huang ◽  
...  
Keyword(s):  
Medicago Truncatula ◽  
Expression Analysis ◽  
Interaction Network ◽  
Degradation Process ◽  
Abiotic Stress Response ◽  
Biotic And Abiotic Stress ◽  
Comprehensive Overview ◽  
Genome Wide ◽  
Evolutionarily Conserved ◽  
Gene Structures

Abstract Background: Autophagy is a highly conserved degradation process of cytoplasmic constituents in eukaryotes. Autophagy is known to be involved in the regulation of plant growth and development, as well as biotic and abiotic stress response. Although autophagy-related genes (ATGs) have been identified and characterized in many plant species, little is known about the autophagy process in Medicago truncatula. Results: In this study, 39 ATGs were identified in M. truncatula (MtATGs), and the gene structures and conserved domains of MtATGs were systematically characterized. In addition, many cis-elements which are related to hormone and stress responsiveness were identified in the promoters of MtATGs. Furthermore, phylogenetic analysis and interaction network analysis suggested that the function of MtATGs is evolutionarily conserved in Arabidopsis and M. truncatula. Gene expression analysis showed that most MtATGs were largely induced during seed development, but repressed by nodulation. Moreover, MtATGs were up-regulated in response to salt and drought stresses.Conclusion: These results provide a comprehensive overview of the MtATGs, which provided important clues for further functional analysis of autophagy in M. truncatula.

A silencer is required for maintenance of transcriptional repression throughout Drosophila development

Development ◽  
1997 ◽  
Vol 124 (21) ◽  
pp. 4343-4350 ◽  
Author(s):  
A. Busturia ◽  
C.D. Wightman ◽  
S. Sakonju
Keyword(s):  
Protein Interactions ◽  
Transcriptional Repression ◽  
Transcriptional Silencing ◽  
Active Role ◽  
Polycomb Group ◽  
Homeotic Genes ◽  
Protein Protein Interactions ◽  
Drosophila Development ◽  
Larval Stages ◽  
Associated Proteins

Transcriptional silencing by the Polycomb Group of genes maintains the position-specific repression of homeotic genes throughout Drosophila development. The Polycomb Group of genes characterized to date encode chromatin-associated proteins that have been suggested to form heterochromatin-like structures. By studying the expression of reporter genes, we have identified a 725 bp fragment, called MCP725, in the homeotic gene Abdominal-B, that accurately maintains position-specific silencing during proliferation of imaginal cells. Silencing by MCP725 requires the Polycomb and the Polycomblike genes, indicating that it contains a Polycomb response element To investigate the mechanisms of transcriptional silencing by MCP725, we have studied its temporal requirements by removing MCP725 from the transgene at various times during development. We have discovered that excision of MCP725 during larval stages leads to loss of silencing. Our findings indicate that the silencer is required for the maintenance of the repressed state throughout cell proliferation. They also suggest that propagation of the silenced state does not occur merely by templating of a heterochromatin structure by virtue of protein-protein interactions. Rather, they suggest that silencers play an active role in the maintenance of the position-specific repression throughout development.

In Silico Recognition of Protein-Protein Interaction

2011 ◽  
pp. 248-268
Author(s):  
Byung-Hoon Park ◽  
Phuongan Dam ◽  
Chongle Pan ◽  
Ying Xu ◽  
Al Geist ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Regulatory Networks ◽  
Machine Learning Techniques ◽  
Translation Regulation ◽  
Future Research ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Protein Levels ◽  
Protein Functions ◽  
Model Protein

Protein-protein interactions are fundamental to cellular processes. They are responsible for phenomena like DNA replication, gene transcription, protein translation, regulation of metabolic pathways, immunologic recognition, signal transduction, etc. The identification of interacting proteins is therefore an important prerequisite step in understanding their physiological functions. Due to the invaluable importance to various biophysical activities, reliable computational methods to infer protein-protein interactions from either structural or genome sequences are in heavy demand lately. Successful predictions, for instance, will facilitate a drug design process and the reconstruction of metabolic or regulatory networks. In this chapter, we review: (a) high-throughput experimental methods for identification of protein-protein interactions, (b) existing databases of protein-protein interactions, (c) computational approaches to predicting protein-protein interactions at both residue and protein levels, (d) various statistical and machine learning techniques to model protein-protein interactions, and (e) applications of protein-protein interactions in predicting protein functions. We also discuss intrinsic drawbacks of the existing approaches and future research directions.

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