Computational prediction of virus–human protein–protein interactions using embedding kernelized heterogeneous data

KIN (Kin17) protein is overexpressed in a number of cancerous cell lines, and is therefore considered a possible cancer biomarker. It is a well-conserved protein across eukaryotes and is ubiquitously expressed in all cell types studied, suggesting an important role in the maintenance of basic cellular function which is yet to be well determined. Early studies on KIN suggested that this nuclear protein plays a role in cellular mechanisms such as DNA replication and/or repair; however, its association with chromatin depends on its methylation state. In order to provide a better understanding of the cellular role of this protein, we investigated its interactome by proximity-dependent biotin identification coupled to mass spectrometry (BioID-MS), used for identification of protein–protein interactions. Our analyses detected interaction with a novel set of proteins and reinforced previous observations linking KIN to factors involved in RNA processing, notably pre-mRNA splicing and ribosome biogenesis. However, little evidence supports that this protein is directly coupled to DNA replication and/or repair processes, as previously suggested. Furthermore, a novel interaction was observed with PRMT7 (protein arginine methyltransferase 7) and we demonstrated that KIN is modified by this enzyme. This interactome analysis indicates that KIN is associated with several cell metabolism functions, and shows for the first time an association with ribosome biogenesis, suggesting that KIN is likely a moonlight protein.

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An atlas of protein-protein interactions across mammalian tissues

10.1101/351247 ◽

2018 ◽

Cited By ~ 5

Author(s):

Michael A. Skinnider ◽

Nichollas E. Scott ◽

Anna Prudova ◽

Nikolay Stoynov ◽

R. Greg Stacey ◽

...

Keyword(s):

High Throughput ◽

Protein Interactions ◽

Protein Protein Interactions ◽

Cellular Mechanisms ◽

Stable Isotope Labelling ◽

Proteomic Approach ◽

Mouse Tissues ◽

Mammalian Tissues ◽

Genetically Manipulated

SummaryCellular processes arise from the dynamic organization of proteins in networks of physical interactions. Mapping the complete network of biologically relevant protein-protein interactions, the interactome, has therefore been a central objective of high-throughput biology. Yet, because widely used methods for high-throughput interaction discovery rely on heterologous expression or genetically manipulated cell lines, the dynamics of protein interactions across physiological contexts are poorly understood. Here, we use a quantitative proteomic approach combining protein correlation profiling with stable isotope labelling of mammals (PCP SILAM) to map the interactomes of seven mouse tissues. The resulting maps provide the first proteome-scale survey of interactome dynamics across mammalian tissues, revealing over 27,000 unique interactions with an accuracy comparable to the highest-quality human screens. We identify systematic suppression of cross-talk between the evolutionarily ancient housekeeping interactome and younger, tissue-specific modules. Rewiring of protein interactions across tissues is widespread, and is poorly predicted by gene expression or coexpression. Rewired proteins are tightly regulated by multiple cellular mechanisms and implicated in disease. Our study opens up new avenues to uncover regulatory mechanisms that shape in vivo interactome responses to physiological and pathophysiological stimuli in mammalian systems.

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β-Subunit overexpression alters the stoicheometry of assembled Na-K-ATPase subunits in MDCK cells

AJP Renal Physiology ◽

10.1152/ajprenal.90406.2008 ◽

2008 ◽

Vol 295 (5) ◽

pp. F1314-F1323 ◽

Cited By ~ 12

Author(s):

Rebecca J. Clifford ◽

Jack H. Kaplan

Keyword(s):

Protein Interactions ◽

Mdck Cells ◽

Β Subunit ◽

Protein Protein Interactions ◽

Cellular Mechanisms ◽

Atpase Subunit ◽

Subunit Expression ◽

Atpase Subunits ◽

Confocal Images ◽

The Individual

In eukaryotic cells, the apparent maintenance of 1:1 stoicheometry between the Na-K-ATPase α- and β-subunits led us to question whether this was alterable and thus if some form of regulation was involved. We have examined the consequences of overexpressing Na-K-ATPase β1-subunits using Madin-Darby canine kidney (MDCK) cells expressing flag-tagged β1-subunits (β1flag) or Myc-tagged β1-subunits (β1myc) under the control of a tetracycline-dependent promoter. The induction of β1flag subunit synthesis in MDCK cells, which increases β1-subunit expression at the plasma membrane by more than twofold, while maintaining stable α1 expression levels, revealed that all mature β1-subunits associate with α1-subunits, and no evidence of “free” β1-subunits was obtained. Consequently, the ratio of assembled β1- to α1-subunits is significantly increased when “extra” β-subunits are expressed. An increased β1/α1 stoicheometry is also observed in cells treated with tunicamycin, suggesting that the protein-protein interactions involved in these complexes are not dependent on glycosylation. Confocal images of cocultured β1myc-expressing and β1flag-expressing MDCK cells show colocalization of β1myc and β1flag subunits at the lateral membranes of neighboring cells, suggesting the occurrence of intercellular interactions between the β-subunits. Immunoprecipitation using MDCK cells constitutively expressing β1myc and tetracycline-regulated β1flag subunits confirmed β-β-subunit interactions. These results demonstrate that the equimolar ratio of assembled β1/α1-subunits of the Na-K-ATPase in kidney cells is not fixed by the inherent properties of the interacting subunits. It is likely that cellular mechanisms are present that regulate the individual Na-K-ATPase subunit abundance.

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UniProt-Related Documents (UniReD): assisting wet lab biologists in their quest on finding novel counterparts in a protein network

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqaa005 ◽

2020 ◽

Vol 2 (1) ◽

Cited By ~ 1

Author(s):

Theodosios Theodosiou ◽

Nikolaos Papanikolaou ◽

Maria Savvaki ◽

Giulia Bonetto ◽

Stella Maxouri ◽

...

Keyword(s):

Protein Interactions ◽

Computational Prediction ◽

Biomedical Literature ◽

Protein Network ◽

Protein Protein Interactions ◽

High Coverage ◽

Depth Study ◽

Experimental Approaches ◽

Wet Lab ◽

User Friendly

Abstract The in-depth study of protein–protein interactions (PPIs) is of key importance for understanding how cells operate. Therefore, in the past few years, many experimental as well as computational approaches have been developed for the identification and discovery of such interactions. Here, we present UniReD, a user-friendly, computational prediction tool which analyses biomedical literature in order to extract known protein associations and suggest undocumented ones. As a proof of concept, we demonstrate its usefulness by experimentally validating six predicted interactions and by benchmarking it against public databases of experimentally validated PPIs succeeding a high coverage. We believe that UniReD can become an important and intuitive resource for experimental biologists in their quest for finding novel associations within a protein network and a useful tool to complement experimental approaches (e.g. mass spectrometry) by producing sorted lists of candidate proteins for further experimental validation. UniReD is available at http://bioinformatics.med.uoc.gr/unired/

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