scholarly journals Unveiling a Ghost Proteome in the Glioblastoma Non-Coding RNAs

2021 ◽  
Vol 9 ◽  
Author(s):  
Tristan Cardon ◽  
Isabelle Fournier ◽  
Michel Salzet
Keyword(s):  
Signaling Pathways ◽  
Protein Interaction ◽  
Brain Cancer ◽  
Transfer Rna ◽  
Open Reading Frame ◽  
Total Resection ◽  
Rna Regulation ◽  
Reading Frame ◽  
Protein Protein Interaction ◽  
Non Coding Rnas

Glioblastoma is the most common brain cancer in adults. Nevertheless, the median survival time is 15 months, if treated with at least a near total resection and followed by radiotherapy in association with temozolomide. In glioblastoma (GBM), variations of non-coding ribonucleic acid (ncRNA) expression have been demonstrated in tumor processes, especially in the regulation of major signaling pathways. Moreover, many ncRNAs present in their sequences an Open Reading Frame (ORF) allowing their translations into proteins, so-called alternative proteins (AltProt) and constituting the “ghost proteome.” This neglected world in GBM has been shown to be implicated in protein–protein interaction (PPI) with reference proteins (RefProt) reflecting involvement in signaling pathways linked to cellular mobility and transfer RNA regulation. More recently, clinical studies have revealed that AltProt is also involved in the patient’s survival and bad prognosis. We thus propose to review the ncRNAs involved in GBM and highlight their function in the disease.

DISTANCE-WISE PATHWAY DISCOVERY FROM PROTEIN–PROTEIN INTERACTION NETWORKS WEIGHTED BY SEMANTIC SIMILARITY

2014 ◽  
Vol 12 (01) ◽  
pp. 1450004 ◽  
Author(s):  
SLAVKA JAROMERSKA ◽  
PETR PRAUS ◽  
YOUNG-RAE CHO
Keyword(s):  
Signaling Pathways ◽  
Semantic Similarity ◽  
Protein Interaction ◽  
Protein Pair ◽  
Semantic Analysis ◽  
Topological Analysis ◽  
Cellular Mechanisms ◽  
Semantic Similarity Measure ◽  
Protein Protein Interaction ◽  
Ppi Networks

Reconstruction of signaling pathways is crucial for understanding cellular mechanisms. A pathway is represented as a path of a signaling cascade involving a series of proteins to perform a particular function. Since a protein pair involved in signaling and response have a strong interaction, putative pathways can be detected from protein–protein interaction (PPI) networks. However, predicting directed pathways from the undirected genome-wide PPI networks has been challenging. We present a novel computational algorithm to efficiently predict signaling pathways from PPI networks given a starting protein and an ending protein. Our approach integrates topological analysis of PPI networks and semantic analysis of PPIs using Gene Ontology data. An advanced semantic similarity measure is used for weighting each interacting protein pair. Our distance-wise algorithm iteratively selects an adjacent protein from a PPI network to build a pathway based on a distance condition. On each iteration, the strength of a hypothetical path passing through a candidate edge is estimated by a local heuristic. We evaluate the performance by comparing the resultant paths to known signaling pathways on yeast. The results show that our approach has higher accuracy and efficiency than previous methods.

scholarly journals Structure of the Open Reading Frame 49 Protein Encoded by Kaposi's Sarcoma-Associated Herpesvirus

2016 ◽  
Vol 91 (2) ◽  
Author(s):  
Kelly Hew ◽  
Saranya Veerappan ◽  
Daniel Sim ◽  
Tobias Cornvik ◽  
Pär Nordlund ◽  
...  
Keyword(s):  
Crystal Structure ◽  
Life Cycle ◽  
Dna Binding ◽  
Protein Interaction ◽  
Kaposi's Sarcoma ◽  
Kaposi’S Sarcoma ◽  
Open Reading Frame ◽  
Reading Frame ◽  
Kaposi's Sarcoma Associated Herpesvirus ◽  
Kaposi’S Sarcoma Associated Herpesvirus

ABSTRACT Herpesviruses alternate between the latent and the lytic life cycle. Switching into the lytic life cycle is important for herpesviral replication and disease pathogenesis. Activation of a transcription factor replication and transcription activator (RTA) has been demonstrated to govern this switch in Kaposi's sarcoma-associated herpesvirus (KSHV). The protein encoded by open reading frame 49 from KSHV (ORF49KSHV) has been shown to upregulate lytic replication in KSHV by enhancing the activities of the RTA. We have solved the crystal structure of the ORF49KSHV protein to a resolution of 2.4 Å. The ORF49KSHV protein has a novel fold consisting of 12 alpha-helices bundled into two pseudodomains. Most notably are distinct charged patches on the protein surface, which are possible protein-protein interaction sites. Homologs of the ORF49KSHV protein in the gammaherpesvirus subfamily have low sequence similarities. Conserved residues are mainly located in the hydrophobic regions, suggesting that they are more likely to play important structural roles than functional ones. Based on the identification and position of three sulfates binding to the positive areas, we performed some initial protein-DNA binding studies by analyzing the thermal stabilization of the protein in the presence of DNA. The ORF49KSHV protein is stabilized in a dose-responsive manner by double-stranded oligonucleotides, suggesting actual DNA interaction and binding. Biolayer interferometry studies also demonstrated that the ORF49KSHV protein binds these oligonucleotides. IMPORTANCE Kaposi's sarcoma-associated herpesvirus (KSHV) is a tumorigenic gammaherpesvirus that causes multiple cancers and lymphoproliferative diseases. The virus exists mainly in the quiescent latent life cycle, but when it is reactivated into the lytic life cycle, new viruses are produced and disease symptoms usually manifest. Several KSHV proteins play important roles in this reactivation, but their exact roles are still largely unknown. In this study, we report the crystal structure of the open reading frame 49 protein encoded by KSHV (ORF49KSHV). Possible regions for protein interaction that could harbor functional importance were found on the surface of the ORF49KSHV protein. This led to the discovery of novel DNA binding properties of the ORF49KSHV protein. Evolutionary conserved structural elements with the functional homologs of ORF49KSHV were also established with the structure.

scholarly journals Divergent degeneration of creA antitoxin genes from minimal CRISPRs and the convergent strategy of tRNA-sequestering CreT toxins

2021 ◽  
Vol 49 (18) ◽  
pp. 10677-10688
Author(s):  
Feiyue Cheng ◽  
Rui Wang ◽  
Haiying Yu ◽  
Chao Liu ◽  
Jun Yang ◽  
...  
Keyword(s):  
Adaptive Immunity ◽  
Deep Sequencing ◽  
Small Rnas ◽  
Transfer Rna ◽  
Open Reading Frame ◽  
Type I ◽  
Essential Information ◽  
Reading Frame ◽  
Crea Gene

Abstract Aside from providing adaptive immunity, type I CRISPR-Cas was recently unearthed to employ a noncanonical RNA guide (CreA) to transcriptionally repress an RNA toxin (CreT). Here, we report that, for most archaeal and bacterial CreTA modules, the creA gene actually carries two flanking ‘CRISPR repeats’, which are, however, highly divergent and degenerated. By deep sequencing, we show that the two repeats give rise to an 8-nt 5′ handle and a 22-nt 3′ handle, respectively, i.e., the conserved elements of a canonical CRISPR RNA, indicating they both retained critical nucleotides for Cas6 processing during divergent degeneration. We also uncovered a minimal CreT toxin that sequesters the rare transfer RNA for isoleucine, tRNAIleCAU, with a six-codon open reading frame containing two consecutive AUA codons. To fully relieve its toxicity, both tRNAIleCAU overexpression and supply of extra agmatine (modifies the wobble base of tRNAIleCAU to decipher AUA codons) are required. By replacing AUA to AGA/AGG codons, we reprogrammed this toxin to sequester rare arginine tRNAs. These data provide essential information on CreTA origin and for future CreTA prediction, and enrich the knowledge of tRNA-sequestering small RNAs that are employed by CRISPR-Cas to get addictive to the host.

scholarly journals Insight into Bacterial Virulence Mechanisms against Host Immune Response via the Yersinia pestis-Human Protein-Protein Interaction Network

2011 ◽  
Vol 79 (11) ◽  
pp. 4413-4424 ◽  
Author(s):  
Huiying Yang ◽  
Yuehua Ke ◽  
Jian Wang ◽  
Yafang Tan ◽  
Sebenzile K. Myeni ◽  
...  
Keyword(s):  
Signaling Pathways ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Mapk Signaling ◽  
Human Protein ◽  
Content Type ◽  
Protein Protein Interaction ◽  
Human Proteins ◽  
Protein Protein Interaction Network

ABSTRACTAYersinia pestis-human protein interaction network is reported here to improve our understanding of its pathogenesis. Up to 204 interactions between 66Y. pestisbait proteins and 109 human proteins were identified by yeast two-hybrid assay and then combined with 23 previously published interactions to construct a protein-protein interaction network. Topological analysis of the interaction network revealed that human proteins targeted byY. pestiswere significantly enriched in the proteins that are central in the human protein-protein interaction network. Analysis of this network showed that signaling pathways important for host immune responses were preferentially targeted byY. pestis, including the pathways involved in focal adhesion, regulation of cytoskeleton, leukocyte transendoepithelial migration, and Toll-like receptor (TLR) and mitogen-activated protein kinase (MAPK) signaling. Cellular pathways targeted byY. pestisare highly relevant to its pathogenesis. Interactions with host proteins involved in focal adhesion and cytoskeketon regulation pathways could account for resistance ofY. pestisto phagocytosis. Interference with TLR and MAPK signaling pathways byY. pestisreflects common characteristics of pathogen-host interaction that bacterial pathogens have evolved to evade host innate immune response by interacting with proteins in those signaling pathways. Interestingly, a large portion of human proteins interacting withY. pestis(16/109) also interacted with viral proteins (Epstein-Barr virus [EBV] and hepatitis C virus [HCV]), suggesting that viral and bacterial pathogens attack common cellular functions to facilitate infections. In addition, we identified vasodilator-stimulated phosphoprotein (VASP) as a novel interaction partner of YpkA and showed that YpkA could inhibitin vitroactin assembly mediated by VASP.

scholarly journals Translated anti-sense product of the Na/phosphate co-transporter (NaPi-II)

1998 ◽  
Vol 332 (2) ◽  
pp. 483-489 ◽  
Author(s):  
Birgit HUELSEWEH ◽  
Beate KOHL ◽  
Hartmut HENTSCHEL ◽  
Rolf K. H. KINNE ◽  
Andreas WERNER
Keyword(s):  
Genomic Sequence ◽  
Biological Significance ◽  
Rnase H ◽  
Open Reading Frame ◽  
Regulatory Function ◽  
Female Gonad ◽  
Putative Open Reading Frame ◽  
Reading Frame ◽  
Sense Transcript ◽  
Protein Protein Interaction

The homeostasis of Pi in marine teleosts is maintained by renal Pi secretion as well as by Pi reabsorption. A Na/Pi co-transport system belonging to the NaPi-II protein family is instrumental in tightly controlled renal Pi handling in mammals and fish. We have isolated an NaPi-II related cDNA from winter flounder. It was cloned from a female gonad cDNA library and is 624 bp long. The transcript is expressed in female and male flounder gonads as well as in kidney and intestine, although at very low levels. RNase H digestion experiments revealed an opposite orientation of the transcript with regard to NaPi-II-related mRNA. The anti-sense orientation was confirmed by genomic sequence analysis and Southern blotting. Alluding to the sense transcript, the anti-sense transcript was denoted IPAN. The open reading frame of IPAN encodes a basic protein of 68 amino acid residues. Immunohistochemistry confined the anti-sense related protein, Ipan, to a submembranous compartment of immature oocytes, suggesting a role in oocyte development. In kidney and intestine Ipan is partly co-localized with the Na/Pi co-transporter, implying a regulatory function for the anti-sense protein. However, direct protein–protein interaction could not be established. The existence of a putative open reading frame in other species extends the biological significance of the novel protein.

scholarly journals Computational identification of signaling pathways in protein interaction networks

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 1522
Author(s):  
Angela U. Makolo ◽  
Temitayo A. Olagunju
Keyword(s):  
Signaling Pathways ◽  
High Throughput ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Protein Protein Interaction

The knowledge of signaling pathways is central to understanding the biological mechanisms of organisms since it has been identified that in eukaryotic organisms, the number of signaling pathways determines the number of ways the organism will react to external stimuli. Signaling pathways are studied using protein interaction networks constructed from protein-protein interaction data obtained from high-throughput experiments. However, these high-throughput methods are known to produce very high rates of false positive and negative interactions. To construct a useful protein interaction network from this noisy data, computational methods are applied to validate the protein-protein interactions. In this study, a computational technique to identify signaling pathways from a protein interaction network constructed using validated protein-protein interaction data was designed.A weighted interaction graph of Saccharomyces Cerevisiae was constructed. The weights were obtained using a Bayesian probabilistic network to estimate the posterior probability of interaction between two proteins given the gene expression measurement as biological evidence. Only interactions above a threshold were accepted for the network model.We were able to identify some pathway segments, one of which is a segment of the pathway that signals the start of the process of meiosis in S. Cerevisiae.

scholarly journals A Machine Learning Framework for Predicting Drug-drug Interactions

2021 ◽  
Author(s):  
Suyu Mei ◽  
Kun Zhang
Keyword(s):  
Drug Interactions ◽  
Signaling Pathways ◽  
Protein Interaction ◽  
Drug Target ◽  
Target Genes ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Model Complexity ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks

Abstract Understanding drug-drug interaction is an essential step to reduce the risk of adverse drug events before clinical drug co-prescription. Existing methods commonly integrate multiple heterogeneous data sources to increase model performance but result in a high model complexity. To elucidate the molecular mechanisms behind drug-drug interactions and reserve rational biological interpretability is a major concern in computational modeling. In this study, we propose a simple representation of drug target profiles to depict drug pairs, based on which an l2-regularized logistic regression model is built to predict drug-drug interactions. In addition, we develop several statistical metrics to measure the communication intensity, interaction efficacy and action range between two drugs in the context of human protein-protein interaction networks and signaling pathways. Cross validation and independent test show that the simple feature representation via drug target profiles is effective to predict drug-drug interactions and outperforms the existing data integration methods. Statistical results show that two drugs easily interact when they target common genes, or their target genes communicate with each other via short paths in protein-protein interaction networks or through cross-talks between signaling pathways. The unravelled mechanisms provide biological insights into potential pharmacological risks of known drug-drug interactions and drug target genes.

scholarly journals PADPIN: protein-protein interaction networks of angiogenesis, arteriogenesis, and inflammation in peripheral arterial disease

2015 ◽  
Vol 47 (8) ◽  
pp. 331-343 ◽  
Author(s):  
Liang-Hui Chu ◽  
Chaitanya G. Vijay ◽  
Brian H. Annex ◽  
Joel S. Bader ◽  
Aleksander S. Popel
Keyword(s):  
Peripheral Arterial Disease ◽  
Signaling Pathways ◽  
Protein Interaction ◽  
Arterial Disease ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Mouse Strains ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Networks ◽  
Peripheral Arterial

Peripheral arterial disease (PAD) results from an obstruction of blood flow in the arteries other than the heart, most commonly the arteries that supply the legs. The complexity of the known signaling pathways involved in PAD, including various growth factor pathways and their cross talks, suggests that analyses of high-throughput experimental data could lead to a new level of understanding of the disease as well as novel and heretofore unanticipated potential targets. Such bioinformatic analyses have not been systematically performed for PAD. We constructed global protein-protein interaction networks of angiogenesis (Angiome), immune response (Immunome), and arteriogenesis (Arteriome) using our previously developed algorithm GeneHits. The term “PADPIN” refers to the angiome, immunome, and arteriome in PAD. Here we analyze four microarray gene expression datasets from ischemic and nonischemic gastrocnemius muscles at day 3 posthindlimb ischemia (HLI) in two genetically different C57BL/6 and BALB/c mouse strains that display differential susceptibility to HLI to identify potential targets and signaling pathways in angiogenesis, immune, and arteriogenesis networks. We hypothesize that identification of the differentially expressed genes in ischemic and nonischemic muscles between the strains that recovers better (C57BL/6) vs. the strain that recovers more poorly (BALB/c) will help for the prediction of target genes in PAD. Our bioinformatics analysis identified several genes that are differentially expressed between the two mouse strains with known functions in PAD including TLR4, THBS1, and PRKAA2 and several genes with unknown functions in PAD including EphA4, TSPAN7, SLC22A4, and EIF2a.

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