scholarly journals Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Sanchari Bhattacharyya ◽  
Shimon Bershtein ◽  
Jin Yan ◽  
Tijda Argun ◽  
Amy I Gilson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Gene Dosage ◽  
Protein Protein Interactions ◽  
Molecular Systems ◽  
E Coli ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Proteome Level ◽  
Metabolic Imbalance

Gene dosage toxicity (GDT) is an important factor that determines optimal levels of protein abundances, yet its molecular underpinnings remain unknown. Here, we demonstrate that overexpression of DHFR in E. coli causes a toxic metabolic imbalance triggered by interactions with several functionally related enzymes. Though deleterious in the overexpression regime, surprisingly, these interactions are beneficial at physiological concentrations, implying their functional significance in vivo. Moreover, we found that overexpression of orthologous DHFR proteins had minimal effect on all levels of cellular organization – molecular, systems, and phenotypic, in sharp contrast to E. coli DHFR. Dramatic difference of GDT between ‘E. coli’s self’ and ‘foreign’ proteins suggests the crucial role of evolutionary selection in shaping protein-protein interaction (PPI) networks at the whole proteome level. This study shows how protein overexpression perturbs a dynamic metabolon of weak yet potentially functional PPI, with consequences for the metabolic state of cells and their fitness.

scholarly journals Transient protein-protein interactions perturb E.coli metabolome and cause gene dosage toxicity

2016 ◽  
Author(s):  
Sanchari Bhattacharyya ◽  
Shimon Bershtein ◽  
Jin Yan ◽  
Tijda Argun ◽  
Amy I. Gilson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Gene Dosage ◽  
Bacterial Species ◽  
Dynamic Network ◽  
Catalytic Efficiency ◽  
Evolutionary Divergence ◽  
Protein Protein Interactions ◽  
E Coli ◽  
Metabolic Imbalance

Several genes exhibit gene dosage toxicity yet its molecular underpinnings remain unknown. Here we demonstrate that overexpression of DHFR in E. coli causes toxic metabolic imbalance triggered by interactions with several enzymes involved in 1-carbon metabolism, in particular GlyA and PurH. DHFR overexpression partially inhibits activity of these enzymes, but at physiological concentrations, PurH-DHFR interaction enhances catalytic efficiency of DHFR, implying a functional interaction in vivo. Surprisingly, overexpression of orthologous DHFRs from other bacterial species caused minimal metabolic and fitness perturbations, despite pulling out more interacting partners than overexpressed endogenous DHFR. Orthologous DHFRs were less potent in inhibiting E. coli GlyA and PurH, or gaining a catalytic improvement upon interaction with PurH, indicating a partial loss of interaction specificity due to evolutionary divergence. This study shows how protein overexpression perturbs a dynamic network of weak yet potentially functional PPI with consequences for the metabolic state of cells and their fitness.

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.

Molecular Biology of Protein-Protein Interactions for Computer Scientists

2009 ◽  
pp. 1-13 ◽  
Author(s):  
Christian Schönbach
Keyword(s):  
Molecular Biology ◽  
Protein Interactions ◽  
Wnt Signaling Pathway ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Detection Technology ◽  
Challenges And Opportunities ◽  
Computer Scientists ◽  
Assay Methods

Advances in protein-protein interaction (PPI) detection technology and computational analysis methods have produced numerous PPI networks, whose completeness appears to depend on the extent of data derived from different PPI assay methods and the complexity of the studied organism. Despite the partial nature of human PPI networks, computational data integration and analyses helped to elucidate new interactions and disease pathways. The success of computational analyses considerably depends on PPI data understanding. Exploration of the data and verification of their quality requires basic knowledge of the molecular biology of PPIs and familiarity with the assay methods used to detect PPIs. Both topics are reviewed in this chapter. After introducing various types of PPIs the principles of selected PPI assays are explained and their limitations discussed. Case studies of the Wnt signaling pathway and splice regulation demonstrate some of the challenges and opportunities that arise from assaying and analyzing PPIs. The chapter is concluded with an extrapolation to human systems biology that offers a glimpse into the future of PPI networks.

scholarly journals Evolutionary diversification of protein–protein interactions by interface add-ons

2017 ◽  
Vol 114 (40) ◽  
pp. E8333-E8342 ◽  
Author(s):  
Maximilian G. Plach ◽  
Florian Semmelmann ◽  
Florian Busch ◽  
Markus Busch ◽  
Leonhard Heizinger ◽  
...  
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Protein Complexes ◽  
Evolutionary Strategy ◽  
Structural Level ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
Evolutionary Diversification

Cells contain a multitude of protein complexes whose subunits interact with high specificity. However, the number of different protein folds and interface geometries found in nature is limited. This raises the question of how protein–protein interaction specificity is achieved on the structural level and how the formation of nonphysiological complexes is avoided. Here, we describe structural elements called interface add-ons that fulfill this function and elucidate their role for the diversification of protein–protein interactions during evolution. We identified interface add-ons in 10% of a representative set of bacterial, heteromeric protein complexes. The importance of interface add-ons for protein–protein interaction specificity is demonstrated by an exemplary experimental characterization of over 30 cognate and hybrid glutamine amidotransferase complexes in combination with comprehensive genetic profiling and protein design. Moreover, growth experiments showed that the lack of interface add-ons can lead to physiologically harmful cross-talk between essential biosynthetic pathways. In sum, our complementary in silico, in vitro, and in vivo analysis argues that interface add-ons are a practical and widespread evolutionary strategy to prevent the formation of nonphysiological complexes by specializing protein–protein interactions.

scholarly journals MIPPIE: the mouse integrated protein–protein interaction reference

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Gregorio Alanis-Lobato ◽  
Jannik S Möllmann ◽  
Martin H Schaefer ◽  
Miguel A Andrade-Navarro
Keyword(s):  
Protein Interaction ◽  
Protein Interactions ◽  
Model Organism ◽  
Web Interface ◽  
Protein Protein Interactions ◽  
Environmental Signals ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
User Friendly

Abstract Cells operate and react to environmental signals thanks to a complex network of protein–protein interactions (PPIs), the malfunction of which can severely disrupt cellular homeostasis. As a result, mapping and analyzing protein networks are key to advancing our understanding of biological processes and diseases. An invaluable part of these endeavors has been the house mouse (Mus musculus), the mammalian model organism par excellence, which has provided insights into human biology and disorders. The importance of investigating PPI networks in the context of mouse prompted us to develop the Mouse Integrated Protein–Protein Interaction rEference (MIPPIE). MIPPIE inherits a robust infrastructure from HIPPIE, its sister database of human PPIs, allowing for the assembly of reliable networks supported by different evidence sources and high-quality experimental techniques. MIPPIE networks can be further refined with tissue, directionality and effect information through a user-friendly web interface. Moreover, all MIPPIE data and meta-data can be accessed via a REST web service or downloaded as text files, thus facilitating the integration of mouse PPIs into follow-up bioinformatics pipelines.

scholarly journals Evidence for Multimerization of Neu Proteins Involved in Polysialic Acid Synthesis in Escherichia coliK1 Using Improved LexA-Based Vectors

2000 ◽  
Vol 182 (18) ◽  
pp. 5267-5270 ◽  
Author(s):  
Dayle A. Daines ◽  
Richard P. Silver
Keyword(s):  
Protein Interactions ◽  
Polysialic Acid ◽  
Genetic System ◽  
Acid Synthesis ◽  
Full Length ◽  
Protein Protein Interactions ◽  
Protein Fragment ◽  
Reading Frame ◽  
E Coli

ABSTRACT Recently, M. Dmitrova et al. (Mol. Gen. Genet. 257:205–212, 1998) described a LexA-based genetic system to monitor protein-protein interactions in an Escherichia coli background. However, the plasmids used in this system, pMS604 and pDP804, were not readily amenable for general use. In this report, we describe modifications of both plasmids that allow fragments of DNA to be fused to either vector in any reading frame. Homodimerization and heterodimerization of full-length proteins involved in polysialic acid synthesis in E. coli K1, as well as heterodimerization between a full-length protein and a protein fragment, demonstrate the usefulness of the modified plasmids for investigating bacterial protein-protein interactions in vivo.

scholarly journals Global query on bacterial sirtuin CobB interactants reveals crosstalk with PRPP synthase Prs

2020 ◽  
Author(s):  
Beata M. Walter ◽  
Joanna Morcinek-Orłowska ◽  
Aneta Szulc ◽  
Andrew L. Lovering ◽  
Manuel Banzhaf ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Global Analysis ◽  
Stable Complex ◽  
Protein Protein Interactions ◽  
Cellular Functions ◽  
Nad Metabolism ◽  
E Coli ◽  
Nad Synthesis ◽  
Wide Range

AbstractProtein lysine acetylation regulates a wide range of cellular functions. It is controlled by a family of NAD-dependent protein deacetylases called sirtuins. In eukaryotes, sirtuins activity is coupled to spatiotemporally-controlled NAD+ level, whereas the mechanism of their regulation in bacteria is less clear. E. coli possesses a single sirtuin – CobB. However, it is unclear how CobB activity is coupled to NAD+ metabolism. In this work we show that this coordination is achieved in E. coli cells through a CobB interaction with PRPP synthase Prs, an enzyme necessary for NAD+ synthesis. Employing global analysis of protein-protein interactions formed by CobB, we demonstrate that it forms a stable complex with Prs. This assembly stimulates CobB deacetylase activity and partially protects it from inhibition by nicotinamide. We provide evidence that Prs acetylation is not necessary for CobB binding but affects the global acetylome in vivo. Our results show that CobB ameliorates Prs activity under conditions of Prs cofactors deficiency. Therefore, we propose that CobB-Prs crosstalk orchestrates the NAD+ metabolism and protein acetylation in response to environmental cues.

scholarly journals Author response: Transient protein-protein interactions perturb E. coli metabolome and cause gene dosage toxicity

2016 ◽  
Author(s):  
Sanchari Bhattacharyya ◽  
Shimon Bershtein ◽  
Jin Yan ◽  
Tijda Argun ◽  
Amy I Gilson ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Gene Dosage ◽  
Author Response ◽  
Protein Protein Interactions ◽  
E Coli

scholarly journals A split protease-E. coli ClpXP system quantifies protein–protein interactions in Escherichia coli cells

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Shengchen Wang ◽  
Faying Zhang ◽  
Meng Mei ◽  
Ting Wang ◽  
Yueli Yun ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Protein Function ◽  
High Efficiency ◽  
Cellular Protein ◽  
Type I ◽  
Protein Protein Interactions ◽  
E Coli ◽  
Protein Protein Interaction ◽  
Quantitative Fluorescence ◽  
Temperature Adaptability

AbstractCharacterizing protein–protein interactions (PPIs) is an effective method to help explore protein function. Here, through integrating a newly identified split human Rhinovirus 3 C (HRV 3 C) protease, super-folder GFP (sfGFP), and ClpXP-SsrA protein degradation machinery, we developed a fluorescence-assisted single-cell methodology (split protease-E. coli ClpXP (SPEC)) to explore protein–protein interactions for both eukaryotic and prokaryotic species in E. coli cells. We firstly identified a highly efficient split HRV 3 C protease with high re-assembly ability and then incorporated it into the SPEC method. The SPEC method could convert the cellular protein-protein interaction to quantitative fluorescence signals through a split HRV 3 C protease-mediated proteolytic reaction with high efficiency and broad temperature adaptability. Using SPEC method, we explored the interactions among effectors of representative type I-E and I-F CRISPR/Cas complexes, which combining with subsequent studies of Cas3 mutations conferred further understanding of the functions and structures of CRISPR/Cas complexes.

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