scholarly journals Interactome of vertebrate GAF/ThPOK reveals its diverse functions in gene regulation and DNA repair

2019 ◽  
Author(s):  
Avinash Srivastava ◽  
Rakesh Mishra
Keyword(s):  
Dna Damage ◽  
Dna Repair ◽  
Protein Interaction ◽  
Cutaneous Melanoma ◽  
Molecular Basis ◽  
Gene Activation ◽  
Biological Significance ◽  
Protein Interaction Data ◽  
Protein Protein Interaction ◽  
Ribonucleoprotein Complexes

Evolutionary conservation and lineage-specific diversification of existing proteins forms the basis for evolving complexity of protein-protein interaction networks and presumably, thereby that of the organism. GAGA associated factor (GAF) belongs to BTB/POZ and zinc finger family of transcription factors and it is conserved from flies to humans. Emerging evidence shows indispensable roles of vertebrate GAF (vGAF a.k.a. ThPOK) in functionally divergent developmental processes like hematopoiesis, adipogenesis, and lactation. vGAF is a sequence-specific DNA binding transcription factor with multiple context-dependent roles in gene activation/repression, enhancer-blocking and more recently, it has shown to be the part of ribonucleoprotein complexes as well. In order to understand the molecular basis of these diverse functions, we analyzed the protein-protein interactome of vGAF. This analysis shows vGAF association with chromatin remodelers, RNA metabolic machinery, transcriptional activators/repressors, and components of DNA repair machinery, thereby provides a plausible explanation for the diverse molecular functions of vGAF. Our findings discern the novel role of vGAF in several molecular processes like DNA repair and RNA metabolism. We further tested the biological significance of our protein-protein interaction data and show a novel function of vGAF in DNA repair and cell survival after UV induced DNA damage. Consistent with these results, analysis of high-throughput RNA-seq data shows the downregulation of vGAF in samples of skin cutaneous melanoma for which the primary cause is UV induced DNA damage. These findings suggest vGAF as an early diagnostic biomarker for skin cutaneous melanoma. Taken together, our study reveals a molecular basis for the diverse functions of vGAF. We uncover its role in DNA repair and provide an explanation for key roles of such evolutionary conserved factors in processes like development and disease.

scholarly journals Transcription factor regulatory modules provide the molecular mechanisms for functional redundancy observed among transcription factors in yeast

2019 ◽  
Vol 20 (S23) ◽  
Author(s):  
Tzu-Hsien Yang
Keyword(s):  
Transcription Factor ◽  
Protein Interaction ◽  
Molecular Mechanisms ◽  
Target Genes ◽  
Regulatory Gene ◽  
Biological Significance ◽  
Functional Redundancy ◽  
Protein Interaction Data ◽  
Regulatory Modules ◽  
Protein Protein Interaction

Abstract Background Current technologies for understanding the transcriptional reprogramming in cells include the transcription factor (TF) chromatin immunoprecipitation (ChIP) experiments and the TF knockout experiments. The ChIP experiments show the binding targets of TFs against which the antibody directs while the knockout techniques find the regulatory gene targets of the knocked-out TFs. However, it was shown that these two complementary results contain few common targets. Researchers have used the concept of TF functional redundancy to explain the low overlap between these two techniques. But the detailed molecular mechanisms behind TF functional redundancy remain unknown. Without knowing the possible molecular mechanisms, it is hard for biologists to fully unravel the cause of TF functional redundancy. Results To mine out the molecular mechanisms, a novel algorithm to extract TF regulatory modules that help explain the observed TF functional redundancy effect was devised and proposed in this research. The method first searched for candidate TF sets from the TF binding data. Then based on these candidate sets the method utilized the modified Steiner Tree construction algorithm to construct the possible TF regulatory modules from protein-protein interaction data and finally filtered out the noise-induced results by using confidence tests. The mined-out regulatory modules were shown to correlate to the concept of functional redundancy and provided testable hypotheses of the molecular mechanisms behind functional redundancy. And the biological significance of the mined-out results was demonstrated in three different biological aspects: ontology enrichment, protein interaction prevalence and expression coherence. About 23.5% of the mined-out TF regulatory modules were literature-verified. Finally, the biological applicability of the proposed method was shown in one detailed example of a verified TF regulatory module for pheromone response and filamentous growth in yeast. Conclusion In this research, a novel method that mined out the potential TF regulatory modules which elucidate the functional redundancy observed among TFs is proposed. The extracted TF regulatory modules not only correlate the molecular mechanisms to the observed functional redundancy among TFs, but also show biological significance in inferring TF functional binding target genes. The results provide testable hypotheses for biologists to further design subsequent research and experiments.

scholarly journals A computational and structural analysis of germline and somatic variants affecting the DDR mechanism, and their impact on human diseases

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lorena Magraner-Pardo ◽  
Roman A. Laskowski ◽  
Tirso Pons ◽  
Janet M. Thornton
Keyword(s):  
Prostate Cancer ◽  
Dna Damage ◽  
Dna Damage Response ◽  
Protein Interaction ◽  
Three Dimensional ◽  
Protein Protein Interaction ◽  
Variants Of Unknown Significance ◽  
Damage Response ◽  
Dna Variants ◽  
Unknown Significance

AbstractDNA-Damage Response (DDR) proteins are crucial for maintaining the integrity of the genome by identifying and repairing errors in DNA. Variants affecting their function can have severe consequences since failure to repair damaged DNA can result in cells turning cancerous. Here, we compare germline and somatic variants in DDR genes, specifically looking at their locations in the corresponding three-dimensional (3D) structures, Pfam domains, and protein–protein interaction interfaces. We show that somatic variants in metastatic cases are more likely to be found in Pfam domains and protein interaction interfaces than are pathogenic germline variants or variants of unknown significance (VUS). We also show that there are hotspots in the structures of ATM and BRCA2 proteins where pathogenic germline, and recurrent somatic variants from primary and metastatic tumours, cluster together in 3D. Moreover, in the ATM, BRCA1 and BRCA2 genes from prostate cancer patients, the distributions of germline benign, pathogenic, VUS, and recurrent somatic variants differ across Pfam domains. Together, these results provide a better characterisation of the most recurrent affected regions in DDRs and could help in the understanding of individual susceptibility to tumour development.

Discovering Interaction Motifs from Protein Interaction Networks

2009 ◽  
pp. 99-116 ◽  
Author(s):  
Hugo Willy
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Protein Patterns ◽  
Protein Protein Interaction ◽  
Family Based ◽  
High Throughput Experiments

Recent breakthroughs in high throughput experiments to determine protein-protein interaction have generated a vast amount of protein interaction data. However, most of the experiments could only answer the question of whether two proteins interact but not the question on the mechanisms by which proteins interact. Such understanding is crucial for understanding the protein interaction of an organism as a whole (the interactome) and even predicting novel protein interactions. Protein interaction usually occurs at some specific sites on the proteins and, given their importance, they are usually well conserved throughout the evolution of the proteins of the same family. Based on this observation, a number of works on finding protein patterns/motifs conserved in interacting proteins have emerged in the last few years. Such motifs are collectively termed as the interaction motifs. This chapter provides a review on the different approaches on finding interaction motifs with a discussion on their implications, potentials and possible areas of improvements in the future.

Mining Functional Modules in Uncertain Protein-Protein Interaction Network

2011 ◽  
Vol 135-136 ◽  
pp. 602-608
Author(s):  
Ya Meng ◽  
Xue Qun Shang ◽  
Miao Miao ◽  
Miao Wang
Keyword(s):  
Protein Interaction ◽  
Protein Complexes ◽  
Biological Significance ◽  
Interaction Network ◽  
Biological Data ◽  
Experimental Results ◽  
Functional Modules ◽  
Go Annotation ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Mining functional modules with biological significance has attracted lots of attention recently. However, protein-protein interaction (PPI) network and other biological data generally bear uncertainties attributed to noise, incompleteness and inaccuracy in practice. In this paper, we focus on received PPI data with uncertainties to explore interesting protein complexes. Moreover, some novel conceptions extended from known graph conceptions are used to develop a depth-first algorithm to mine protein complexes in a simple uncertain graph. Our experiments take protein complexes from MIPS database as standard of accessing experimental results. Experiment results indicate that our algorithm has good performance in terms of coverage and precision. Experimental results are also assessed on Gene Ontology (GO) annotation, and the evaluation demonstrates proteins of our most acquired protein complexes show a high similarity. Finally, several experiments are taken to test the scalability of our algorithm. The result is also observed.

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