scholarly journals Frustration and fidelity in influenza genome assembly

2019 ◽  
Vol 16 (160) ◽  
pp. 20190411 ◽  
Author(s):  
Nida Farheen ◽  
Mukund Thattai
Keyword(s):  
Genome Assembly ◽  
Rna Binding ◽  
Electron Tomography ◽  
Interaction Network ◽  
Interaction Networks ◽  
High Fidelity ◽  
Nearest Neighbour ◽  
Hub And Spoke ◽  
Biological Studies ◽  
Associated Proteins

The genome of the influenza virus consists of eight distinct single-stranded RNA segments, each encoding proteins essential for the viral life cycle. When the virus infects a host cell, these segments must be replicated and packaged into new budding virions. The viral genome is assembled with remarkably high fidelity: experiments reveal that most virions contain precisely one copy of each of the eight RNA segments. Cell-biological studies suggest that genome assembly is mediated by specific reversible and irreversible interactions between the RNA segments and their associated proteins. However, the precise inter-segment interaction network remains unresolved. Here, we computationally predict that tree-like irreversible interaction networks guarantee high-fidelity genome assembly, while cyclic interaction networks lead to futile or frustrated off-pathway products. We test our prediction against multiple experimental datasets. We find that tree-like networks capture the nearest-neighbour statistics of RNA segments in packaged virions, as observed by electron tomography. Just eight tree-like networks (of a possible 262 144) optimally capture both the nearest-neighbour data and independently measured RNA–RNA binding and co-localization propensities. These eight do not include the previously proposed hub-and-spoke and linear networks. Rather, each predicted network combines hub-like and linear features, consistent with evolutionary models of interaction gain and loss.

scholarly journals Frustration and Fidelity in Influenza Genome Assembly

2019 ◽  
Author(s):  
Nida Farheen ◽  
Mukund Thattai
Keyword(s):  
Genome Assembly ◽  
Nearest Neighbor ◽  
Interaction Network ◽  
Interaction Networks ◽  
High Fidelity ◽  
Hub And Spoke ◽  
Linear Networks ◽  
Biological Studies ◽  
Associated Proteins ◽  
Em Tomography

AbstractThe genome of the influenza virus consists of eight distinct single-stranded RNA segments, each encoding proteins essential for the viral life cycle. When the virus infects a host cell these segments must be replicated and packaged into new budding virions. The viral genome is assembled with remarkably high fidelity: experiments reveal that most virions contain precisely one copy of each of the eight RNA segments. Cell-biological studies suggest that genome assembly is mediated by specific reversible and irreversible interactions between the RNA segments and their associated proteins. However, the precise inter-segment interaction network remains unresolved. Here we computationally predict that tree-like irreversible interaction networks guarantee high-fidelity genome assembly, while cyclic interaction networks lead to futile or frustrated off-pathway products. We test our prediction against multiple experimental datasets. We find that tree-like networks capture the nearest-neighbor statistics of RNA segments in packaged virions, as observed by EM tomography. Just eight tree-like networks (of a possible 262,144) optimally capture both the nearest-neighbor data as well as independently measured RNA-RNA contact propensities. These eight do not include the previously-proposed hub-and-spoke and linear networks. Rather, each predicted network combines hub-like and linear features, consistent with evolutionary models of interaction gain and loss.

scholarly journals In vivo reconstitution finds multivalent RNA-RNA interactions as drivers of mesh-like condensates

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Weirui Ma ◽  
Gang Zheng ◽  
Wei Xie ◽  
Christine Mayr
Keyword(s):  
Surface Area ◽  
Protein Trafficking ◽  
Rna Binding ◽  
Interaction Network ◽  
Large Surface Area ◽  
High Propensity ◽  
Membrane Protein Trafficking ◽  
Protein Components

Liquid-like condensates have been thought to be sphere-like. Recently, various condensates with filamentous morphology have been observed in cells. One such condensate is the TIS granule network that shares a large surface area with the rough endoplasmic reticulum and is important for membrane protein trafficking. It has been unclear how condensates with mesh-like shapes, but dynamic protein components are formed. In vitro and in vivo reconstitution experiments revealed that the minimal components are a multivalent RNA-binding protein that concentrates RNAs that are able to form extensive intermolecular mRNA-mRNA interactions. mRNAs with large unstructured regions have a high propensity to form a pervasive intermolecular interaction network that acts as condensate skeleton. The underlying RNA matrix prevents full fusion of spherical liquid-like condensates, thus driving the formation of irregularly shaped membraneless organelles. The resulting large surface area may promote interactions at the condensate surface and at the interface with other organelles.

scholarly journals Systematic discovery of endogenous human ribonucleoprotein complexes

2018 ◽  
Author(s):  
Anna L. Mallam ◽  
Wisath Sae-Lee ◽  
Jeffrey M. Schaub ◽  
Fan Tu ◽  
Anna Battenhouse ◽  
...  
Keyword(s):  
Rna Binding ◽  
Rna Binding Proteins ◽  
Protein Complexes ◽  
Embryonic Stem ◽  
Human Protein ◽  
Disease States ◽  
Ribonucleoprotein Complexes ◽  
Associated Proteins ◽  
Domains Of Life ◽  
Factor C

AbstractRNA-binding proteins (RBPs) play essential roles in biology and are frequently associated with human disease. While recent studies have systematically identified individual RBPs, their higher order assembly intoRibonucleoprotein (RNP) complexes has not been systematically investigated. Here, we describe a proteomics method for systematic identification of RNP complexes in human cells. We identify 1,428 protein complexes that associate with RNA, indicating that over 20% of known human protein complexes contain RNA. To explore the role of RNA in the assembly of each complex, we identify complexes that dissociate, change composition, or form stable protein-only complexes in the absence of RNA. Importantly, these data also provide specific novel insights into the function of well-studied protein complexes not previously known to associate with RNA, including replication factor C (RFC) and cytokinetic centralspindlin complex. Finally, we use our method to systematically identify cell-type specific RNA-associated proteins in mouse embryonic stem cells. We distribute these data as a resource, rna.MAP (rna.proteincomplexes.org) which provides a comprehensive dataset for the study of RNA-associated protein complexes. Our system thus provides a novel methodology for further explorations across human tissues and disease states, as well as throughout all domains of life.SummaryAn exploration of human protein complexes in the presence and absence of RNA reveals endogenous ribonucleoprotein complexes

scholarly journals ProtFinder: finding subcellular locations of proteins using protein interaction networks

2022 ◽  
Author(s):  
Aayush Grover ◽  
Laurent Gatto
Keyword(s):  
Protein Interaction ◽  
Intelligent System ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Protein Subcellular Localization ◽  
Human Protein Atlas ◽  
Protein Subcellular Localization Prediction ◽  
Localization Prediction ◽  
Roc Score

Protein subcellular localization prediction plays a crucial role in improving our understandings of different diseases and consequently assists in building drug targeting and drug development pipelines. Proteins are known to co-exist at multiple subcellular locations which make the task of prediction extremely challenging. A protein interaction network is a graph that captures interactions between different proteins. It is safe to assume that if two proteins are interacting, they must share some subcellular locations. With this regard, we propose ProtFinder - the first deep learning-based model that exclusively relies on protein interaction networks to predict the multiple subcellular locations of proteins. We also integrate biological priors like the cellular component of Gene Ontology to make ProtFinder a more biology-aware intelligent system. ProtFinder is trained and tested using the STRING and BioPlex databases whereas the annotations of proteins are obtained from the Human Protein Atlas. Our model gives an AUC-ROC score of 90.00% and an MCC score of 83.42% on a held-out set of proteins. We also apply ProtFinder to annotate proteins that currently do not have confident location annotations. We observe that ProtFinder is able to confirm some of these unreliable location annotations, while in some cases complementing the existing databases with novel location annotations.

scholarly journals The Putative RNA-Binding Protein Nrp1 Promotes the Loading of Kinesin-14/Klp2 to the Mitotic Spindle and Is Sequestered Into Heat-Induced Protein Aggregates in Fission Yeast

2021 ◽  
Author(s):  
Masashi Yukawa ◽  
Mitsuki Ohishi ◽  
Yusuke Yamada ◽  
Takashi Toda
Keyword(s):  
Fission Yeast ◽  
Rna Binding ◽  
Binding Protein ◽  
Rna Binding Protein ◽  
Protein Aggregates ◽  
Associated Proteins ◽  
Spindle Microtubules ◽  
The Stability ◽  
And Function ◽  
Post Transcriptional Regulation

Cells form a bipolar spindle during mitosis to ensure accurate chromosome segregation. Proper spindle architecture is established by a set of kinesin motors and microtubule-associated proteins. In most eukaryotes, kinesin-5 motors are essential for this process, and genetic or chemical inhibition of their activity leads to the emergence of monopolar spindles and cell death. However, these deficiencies can be rescued by simultaneous inactivation of kinesin-14 motors, as they counteract kinesin-5. We conducted detailed genetic analyses in fission yeast to understand the mechanisms driving spindle assembly in the absence of kinesin-5. Here we show that deletion of the nrp1 gene, which encodes a putative RNA-binding protein with unknown function, can rescue temperature sensitivity caused by cut7-22, a fission yeast kinesin-5 mutant. Interestingly, kinesin-14/Klp2 levels on the spindles in the cut7 mutants were significantly reduced by the nrp1 deletion, although the total levels of Klp2 and the stability of spindle microtubules remained unaffected. Moreover, RNA-binding motifs of Nrp1 are essential for its cytoplasmic localization and function. We have also found that a portion of Nrp1 is spatially and functionally sequestered by chaperone-based protein aggregates upon mild heat stress and limits cell division at high temperatures. We propose that Nrp1 might be involved in post-transcriptional regulation through its RNA-binding ability to promote the loading of Klp2 on the spindle microtubules.

scholarly journals ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis

F1000Research ◽  
2014 ◽  
Vol 3 ◽  
pp. 146 ◽  
Author(s):  
Guanming Wu ◽  
Eric Dawson ◽  
Adrian Duong ◽  
Robin Haw ◽  
Lincoln Stein
Keyword(s):  
Experimental Data ◽  
Data Analysis ◽  
Graphical Models ◽  
High Throughput ◽  
Interaction Network ◽  
Large Data ◽  
Relevant Information ◽  
Data Sets ◽  
Data Types ◽  
Biological Studies

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.

scholarly journals XlinkCyNET: a Cytoscape application for visualization of protein interaction networks based on cross-linking mass-spectrometry identifications

2020 ◽  
Author(s):  
Diogo Borges Lima ◽  
Ying Zhu ◽  
Fan Liu
Keyword(s):  
Mass Spectrometry ◽  
Protein Interaction ◽  
Large Scale ◽  
Interaction Network ◽  
Protein Interaction Networks ◽  
Interaction Networks ◽  
Cross Linking ◽  
Protein Interaction Data ◽  
Interaction Data ◽  
Link Type

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.

scholarly journals UBA1 and UBA2, Two Proteins That Interact with UBP1, a Multifunctional Effector of Pre-mRNA Maturation in Plants

2002 ◽  
Vol 22 (12) ◽  
pp. 4346-4357 ◽  
Author(s):  
Mark H. L. Lambermon ◽  
Yu Fu ◽  
Dominika A. Wieczorek Kirk ◽  
Marcel Dupasquier ◽  
Witold Filipowicz ◽  
...  
Keyword(s):  
Steady State ◽  
Rna Binding ◽  
Rna Recognition Motif ◽  
Dependent Manner ◽  
Binding Domains ◽  
Mrna Maturation ◽  
Associated Proteins ◽  
Steady State Levels ◽  
Transient Overexpression

ABSTRACT Nicotiana plumbaginifolia UBP1 is an hnRNP-like protein associated with the poly(A)+ RNA in the cell nucleus. Consistent with a role in pre-mRNA processing, overexpression of UBP1 in N. plumabaginifolia protoplasts enhances the splicing of suboptimal introns and increases the steady-state levels of reporter mRNAs, even intronless ones. The latter effect of UBP1 is promoter specific and appears to be due to UBP1 binding to the 3′ untranslated region (3′-UTR) and protecting the mRNA from exonucleolytic degradation (M. H. L. Lambermon, G. G. Simpson, D. A. Kirk, M. Hemmings-Mieszczak, U. Klahre, and W. Filipowicz, EMBO J. 19:1638-1649, 2000). To gain more insight into UBP1 function in pre-mRNA maturation, we characterized proteins interacting with N. plumbaginifolia UBP1 and one of its Arabidopsis thaliana counterparts, AtUBP1b, by using yeast two-hybrid screens and in vitro pull-down assays. Two proteins, UBP1-associated proteins 1a and 2a (UBA1a and UBA2a, respectively), were identified in A. thaliana. They are members of two novel families of plant-specific proteins containing RNA recognition motif-type RNA-binding domains. UBA1a and UBA2a are nuclear proteins, and their recombinant forms bind RNA with a specificity for oligouridylates in vitro. As with UBP1, transient overexpression of UBA1a in protoplasts increases the steady-state levels of reporter mRNAs in a promoter-dependent manner. Similarly, overexpression of UBA2a increases the levels of reporter mRNAs, but this effect is promoter independent. Unlike UBP1, neither UBA1a nor UBA2a stimulates pre-mRNA splicing. These and other data suggest that UBP1, UBA1a, and UBA2a may act as components of a complex recognizing U-rich sequences in plant 3′-UTRs and contributing to the stabilization of mRNAs in the nucleus.

scholarly journals Definition of a RACK1 Interaction Network in Drosophila melanogaster Using SWATH-MS

2017 ◽  
Vol 7 (7) ◽  
pp. 2249-2258 ◽  
Author(s):  
Lauriane Kuhn ◽  
Karim Majzoub ◽  
Evelyne Einhorn ◽  
Johana Chicher ◽  
Julien Pompon ◽  
...  
Keyword(s):  
Drosophila Melanogaster ◽  
Rna Binding ◽  
Rna Binding Proteins ◽  
Activated Protein C ◽  
Model Organism ◽  
Interaction Network ◽  
Added Value ◽  
Label Free ◽  
Nucleic Acid Binding ◽  
Entry Site

Abstract Receptor for Activated protein C kinase 1 (RACK1) is a scaffold protein that has been found in association with several signaling complexes, and with the 40S subunit of the ribosome. Using the model organism Drosophila melanogaster, we recently showed that RACK1 is required at the ribosome for internal ribosome entry site (IRES)-mediated translation of viruses. Here, we report a proteomic characterization of the interactome of RACK1 in Drosophila S2 cells. We carried out Label-Free quantitation using both Data-Dependent and Data-Independent Acquisition (DDA and DIA, respectively) and observed a significant advantage for the Sequential Window Acquisition of all THeoretical fragment-ion spectra (SWATH) method, both in terms of identification of interactants and quantification of low abundance proteins. These data represent the first SWATH spectral library available for Drosophila and will be a useful resource for the community. A total of 52 interacting proteins were identified, including several molecules involved in translation such as structural components of the ribosome, factors regulating translation initiation or elongation, and RNA binding proteins. Among these 52 proteins, 15 were identified as partners by the SWATH strategy only. Interestingly, these 15 proteins are significantly enriched for the functions translation and nucleic acid binding. This enrichment reflects the engagement of RACK1 at the ribosome and highlights the added value of SWATH analysis. A functional screen did not reveal any protein sharing the interesting properties of RACK1, which is required for IRES-dependent translation and not essential for cell viability. Intriguingly however, 10 of the RACK1 partners identified restrict replication of Cricket paralysis virus (CrPV), an IRES-containing virus.

Construction and Analysis of Protein-Protein Interaction Network

2019 ◽  
pp. 204-220
Author(s):  
Divya Dasagrandhi ◽  
Arul Salomee Kamalabai Ravindran ◽  
Anusuyadevi Muthuswamy ◽  
Jayachandran K. S.
Keyword(s):  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Data Sets ◽  
Protein Protein Interaction ◽  
Huge Data ◽  
Associated Proteins ◽  
High Throughput Experiments ◽  
Generation Sequencing ◽  
Protein Protein Interaction Network

Understanding the mechanisms of a disease is highly complicated due to the complex pathways involved in the disease progression. Despite several decades of research, the occurrence and prognosis of the diseases is not completely understood even with high throughput experiments like DNA microarray and next-generation sequencing. This is due to challenges in analysis of huge data sets. Systems biology is one of the major divisions of bioinformatics and has laid cutting edge techniques for the better understanding of these pathways. Construction of protein-protein interaction network (PPIN) guides the modern scientists to identify vital proteins through protein-protein interaction network, which facilitates the identification of new drug target and associated proteins. The chapter is focused on PPI databases, construction of PPINs, and its analysis.

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