scholarly journals A proximity proteomics screen in three-dimensional spheroid cultures identifies novel regulators of lumen formation

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Li-Ting Wang ◽  
Marie-Ève Proulx ◽  
Anne D. Kim ◽  
Virginie Lelarge ◽  
Luke McCaffrey
Keyword(s):  
Cell Polarity ◽  
Basal Cell ◽  
Protein Interactions ◽  
Proteomic Analysis ◽  
Three Dimensional ◽  
Culture Method ◽  
Protein Protein Interactions ◽  
Down Regulation ◽  
Lumen Formation ◽  
Functional Analyses

AbstractApical-basal cell polarity and lumen formation are essential features of many epithelial tissues, which are disrupted in diseases like cancer. Here, we describe a proteomics-based screen to identify proteins involved in lumen formation in three-dimensional spheroid cultures. We established a suspension-based culture method suitable for generating polarized cysts in sufficient quantities for proteomic analysis. Using this approach, we identified several known and unknown proteins proximally associated with PAR6B, an apical protein involved in lumen formation. Functional analyses of candidates identified PARD3B (a homolog of PARD3), RALB, and HRNR as regulators of lumen formation. We also identified PTPN14 as a component of the Par-complex that is required for fidelity of apical-basal polarity. Cells transformed with KRASG12V exhibit lumen collapse/filling concomitant with disruption of the Par-complex and down-regulation of PTPN14. Enforced expression of PTPN14 maintained the lumen and restricted the transformed phenotype in KRASG12V-expressing cells. This represents an applicable approach to explore protein–protein interactions in three-dimensional culture and to identify proteins important for lumen maintenance in normal and oncogene-expressing cells.

scholarly journals Activation and assembly of the NADPH oxidase: a structural perspective

2005 ◽  
Vol 386 (3) ◽  
pp. 401-416 ◽  
Author(s):  
Yvonne GROEMPING ◽  
Katrin RITTINGER
Keyword(s):  
Nadph Oxidase ◽  
Protein Interactions ◽  
Structural Information ◽  
Three Dimensional ◽  
Protein Protein Interactions ◽  
Crucial Component ◽  
Enzyme Subunits ◽  
Membrane Components ◽  
Inhibitory Interactions ◽  
Encompassing Model

The NADPH oxidase of professional phagocytes is a crucial component of the innate immune response due to its fundamental role in the production of reactive oxygen species that act as powerful microbicidal agents. The activity of this multi-protein enzyme is dependent on the regulated assembly of the six enzyme subunits at the membrane where oxygen is reduced to superoxide anions. In the resting state, four of the enzyme subunits are maintained in the cytosol, either through auto-inhibitory interactions or through complex formation with accessory proteins that are not part of the active enzyme complex. Multiple inputs are required to disrupt these inhibitory interactions and allow translocation to the membrane and association with the integral membrane components. Protein interaction modules are key regulators of NADPH oxidase assembly, and the protein–protein interactions mediated via these domains have been the target of numerous studies. Many models have been put forward to describe the intricate network of reversible protein interactions that regulate the activity of this enzyme, but an all-encompassing model has so far been elusive. An important step towards an understanding of the molecular basis of NADPH oxidase assembly and activity has been the recent solution of the three-dimensional structures of some of the oxidase components. We will discuss these structures in the present review and attempt to reconcile some of the conflicting models on the basis of the structural information available.

scholarly journals Protein-protein docking using learned three-dimensional representations

2019 ◽  
Author(s):  
Georgy Derevyanko ◽  
Guillaume Lamoureux
Keyword(s):  
Protein Interactions ◽  
Network Architecture ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Spatial Arrangement ◽  
Protein Docking ◽  
Protein Protein Interactions ◽  
Translational Invariance ◽  
Shape Complementarity ◽  
Spatial Features

AbstractProtein-protein interactions are determined by a number of hard-to-capture features related to shape complementarity, electrostatics, and hydrophobicity. These features may be intrinsic to the protein or induced by the presence of a partner. A conventional approach to protein-protein docking consists in engineering a small number of spatial features for each protein, and in minimizing the sum of their correlations with respect to the spatial arrangement of the two proteins. To generalize this approach, we introduce a deep neural network architecture that transforms the raw atomic densities of each protein into complex three-dimensional representations. Each point in the volume containing the protein is described by 48 learned features, which are correlated and combined with the features of a second protein to produce a score dependent on the relative position and orientation of the two proteins. The architecture is based on multiple layers of SE(3)-equivariant convolutional neural networks, which provide built-in rotational and translational invariance of the score with respect to the structure of the complex. The model is trained end-to-end on a set of decoy conformations generated from 851 nonredundant protein-protein complexes and is tested on data from the Protein-Protein Docking Benchmark Version 4.0.

scholarly journals Schistosoma mansoni polo-like kinases and their function in control of mitosis and parasite reproduction

2011 ◽  
Vol 83 (2) ◽  
pp. 627-635 ◽  
Author(s):  
Colette Dissous ◽  
Christoph G Grevelding ◽  
Thavy Long
Keyword(s):  
Cell Cycle ◽  
Schistosoma Mansoni ◽  
Protein Interactions ◽  
Cell Cycle Progression ◽  
Gonad Development ◽  
Cancer Drug ◽  
Protein Protein Interactions ◽  
Centriole Duplication ◽  
Regulation Of Cell Cycle ◽  
Functional Analyses

Polo-like kinases are important regulators of cell cycle progression and mitosis. They constitute a family of conserved serine/threonine kinases which are highly related in their catalytic domains and contain polo boxes involved in protein-protein interactions and subcellular localization. In mammals, five Plks (Plk 1-5) encompass diverse roles in centrosome dynamics, spindle formation, intra S-phase and G2/M checkpoints and DNA damage response. Plk1 is a key positive regulator of mitosis and is overexpressed in various types of cancers. Plk4 is a divergent member of the Plk family, with essential functions in centriole duplication. Homozygous disruption of Plk1 or Plk4 in mice is lethal in embryos. Two Plk members SmPlk1 and SmSak, homologous to Plk1 and Plk4 respectively, are present in the parasitic platyhelminth Schistosoma mansoni. Structural and functional analyses of SmPlk1 have demonstrated its conserved function in the regulation of cell cycle G2/M transition in Xenopus oocytes. The anti-cancer drug BI 2536 (the most potent and selective Plk1 inhibitor) inhibits specifically the catalytic activity of SmPlk1 and induced profound alterations in schistosome gonads, indicating a role of SmPlk1 in parasite gametogenesis and its potential as a novel chemotherapeutic target against schistosomiasis. Functions of SmSak in cell cycle regulation and schistosome gonad development are currently investigated

scholarly journals Tianlongkechuanling Inhibits Pulmonary Fibrosis Through Down-Regulation of Arginase-Ornithine Pathway

2021 ◽  
Vol 12 ◽  
Author(s):  
Peng Wang ◽  
Yuanyuan Shi ◽  
Yadong Li ◽  
Lili Zhang ◽  
Sihao Qu ◽  
...  
Keyword(s):  
Pulmonary Fibrosis ◽  
Protein Interactions ◽  
Smooth Muscle Actin ◽  
Collagen Deposition ◽  
Protein Protein Interactions ◽  
Down Regulation ◽  
Kegg Pathways ◽  
Ppi Networks ◽  
Tandem Mass Tag ◽  
Pathway Expression

Background: Pulmonary Fibrosis (PF) is an interstitial lung disease characterized by excessive accumulation of extracellular matrix in the lungs, which disrupts the structure and gas exchange of the alveoli. There are only two approved therapies for PF, nintedanib (Nib) and pirfenidone. Therefore, the use of Chinese medicine for PF is attracting attention. Tianlongkechuanling (TL) is an effective Chinese formula that has been applied clinically to alleviate PF, which can enhance lung function and quality of life.Purpose: The potential effects and specific mechanisms of TL have not been fully explored, yet. In the present study, proteomics was performed to explore the therapeutic protein targets of TL on Bleomycin (BLM)-induced Pulmonary Fibrosis.Method: BLM-induced PF mice models were established. Hematoxylineosin staining and Masson staining were used to analyze histopathological changes and collagen deposition. To screen the differential proteins expression between the Control, BLM, BLM + TL and BLM + Nib (BLM + nintedanib) groups, quantitative proteomics was performed using tandem mass tag (TMT) labeling with nanoLC-MS/MS [nano liquid chromatographymass spectrometry]). Changes in the profiles of the expressed proteins were analyzed using the bioinformatics tools Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The protein–protein interactions (PPI) were established by STRING. Expressions of α-smooth muscle actin (α-SMA), Collagen I (Col1a1), Fibronectin (Fn1) and enzymes in arginase-ornithine pathway were detected by Western blot or RT-PCR.Result: TL treatments significantly ameliorated BLM-induced collagen deposition in lung tissues. Moreover, TL can inhibit the protein expressions of α-SMA and the mRNA expressions of Col1a1 and Fn1. Using TMT technology, we observed 253 differentially expressed proteins related to PPI networks and involved different KEGG pathways. Arginase-ornithine pathway is highly significant. The expression of arginase1 (Arg1), carbamoyltransferase (OTC), carbamoy-phosphate synthase (CPS1), argininosuccinate synthase (ASS1), ornithine aminotransferase (OAT) argininosuccinate lyase (ASL) and inducible nitric oxide synthase (iNOS) was significantly decreased after TL treatments.Conclusion: Administration of TL in BLM-induced mice resulted in decreasing pulmonary fibrosis. Our findings propose that the down regulation of arginase-ornithine pathway expression with the reduction of arginase biosynthesis is a central mechanism and potential treatment for pulmonary fibrosis with the prevention of TL.

scholarly journals A protein interaction map for cell polarity development

2001 ◽  
Vol 154 (3) ◽  
pp. 549-576 ◽  
Author(s):  
Becky L. Drees ◽  
Bryan Sundin ◽  
Elizabeth Brazeau ◽  
Juliane P. Caviston ◽  
Guang-Chao Chen ◽  
...  
Keyword(s):  
Cell Polarity ◽  
Protein Interactions ◽  
Large Scale ◽  
Interaction Network ◽  
Open Reading Frames ◽  
Actin Assembly ◽  
Protein Protein Interactions ◽  
Microtubule Organization ◽  
Two Hybrid ◽  
Secretory Apparatus

Many genes required for cell polarity development in budding yeast have been identified and arranged into a functional hierarchy. Core elements of the hierarchy are widely conserved, underlying cell polarity development in diverse eukaryotes. To enumerate more fully the protein–protein interactions that mediate cell polarity development, and to uncover novel mechanisms that coordinate the numerous events involved, we carried out a large-scale two-hybrid experiment. 68 Gal4 DNA binding domain fusions of yeast proteins associated with the actin cytoskeleton, septins, the secretory apparatus, and Rho-type GTPases were used to screen an array of yeast transformants that express ∼90% of the predicted Saccharomyces cerevisiae open reading frames as Gal4 activation domain fusions. 191 protein–protein interactions were detected, of which 128 had not been described previously. 44 interactions implicated 20 previously uncharacterized proteins in cell polarity development. Further insights into possible roles of 13 of these proteins were revealed by their multiple two-hybrid interactions and by subcellular localization. Included in the interaction network were associations of Cdc42 and Rho1 pathways with proteins involved in exocytosis, septin organization, actin assembly, microtubule organization, autophagy, cytokinesis, and cell wall synthesis. Other interactions suggested direct connections between Rho1- and Cdc42-regulated pathways; the secretory apparatus and regulators of polarity establishment; actin assembly and the morphogenesis checkpoint; and the exocytic and endocytic machinery. In total, a network of interactions that provide an integrated response of signaling proteins, the cytoskeleton, and organelles to the spatial cues that direct polarity development was revealed.

scholarly journals Inferring interaction partners from protein sequences

2016 ◽  
Author(s):  
Anne-Florence Bitbol ◽  
Robert S. Dwyer ◽  
Lucy J. Colwell ◽  
Ned S. Wingreen
Keyword(s):  
Protein Interactions ◽  
Sequence Data ◽  
Protein Complexes ◽  
A Priori ◽  
Specific Interaction ◽  
Three Dimensional ◽  
Specific Protein ◽  
Protein Protein Interactions ◽  
Entropy Model ◽  
Interaction Partners

Specific protein-protein interactions are crucial in the cell, both to ensure the formation and stability of multi-protein complexes, and to enable signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interaction partners. Hence, the sequences of interacting partners are correlated. Here we exploit these correlations to accurately identify which proteins are specific interaction partners from sequence data alone. Our general approach, which employs a pairwise maximum entropy model to infer direct couplings between residues, has been successfully used to predict the three-dimensional structures of proteins from sequences. Building on this approach, we introduce an iterative algorithm to predict specific interaction partners from among the members of two protein families. We assess the algorithm's performance on histidine kinases and response regulators from bacterial two-component signaling systems. The algorithm proves successful without any a priori knowledge of interaction partners, yielding a striking 0.93 true positive fraction on our complete dataset, and we uncover the origin of this surprising success. Finally, we discuss how our method could be used to predict novel protein-protein interactions.

scholarly journals Inferring interaction partners from protein sequences using mutual information

2018 ◽  
Author(s):  
Anne-Florence Bitbol
Keyword(s):  
Mutual Information ◽  
Protein Interactions ◽  
Sequence Data ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Specific Protein ◽  
Amino Acid Residues ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Interaction Partners

AbstractSpecific protein-protein interactions are crucial in most cellular processes. They enable multiprotein complexes to assemble and to remain stable, and they allow signal transduction in various pathways. Functional interactions between proteins result in coevolution between the interacting partners, and thus in correlations between their sequences. Pairwise maximum-entropy based models have enabled successful inference of pairs of amino-acid residues that are in contact in the three-dimensional structure of multi-protein complexes, starting from the correlations in the sequence data of known interaction partners. Recently, algorithms inspired by these methods have been developed to identify which proteins are specific interaction partners among the paralogous proteins of two families, starting from sequence data alone. Here, we demonstrate that a slightly higher performance for partner identification can be reached by an approximate maximization of the mutual information between the sequence alignments of the two protein families. This stands in contrast with structure prediction of proteins and of multiprotein complexes from sequence data, where pairwise maximum-entropy based global statistical models substantially improve performance compared to mutual information. Our findings entail that the statistical dependences allowing interaction partner prediction from sequence data are not restricted to the residue pairs that are in direct contact at the interface between the partner proteins.Author summarySpecific protein-protein interactions are at the heart of most intra-cellular processes. Mapping these interactions is thus crucial to a systems-level understanding of cells, and has broad applications to areas such as drug targeting. Systematic experimental identification of protein interaction partners is still challenging. However, a large and rapidly growing amount of sequence data is now available. Recently, algorithms have been proposed to identify which proteins interact from their sequences alone, thanks to the co-variation of the sequences of interacting proteins. These algorithms build upon inference methods that have been used with success to predict the three-dimensional structures of proteins and multi-protein complexes, and their focus is on the amino-acid residues that are in direct contact. Here, we propose a simpler method to identify which proteins interact among the paralogous proteins of two families, starting from their sequences alone. Our method relies on an approximate maximization of mutual information between the sequences of the two families, without specifically emphasizing the contacting residue pairs. We demonstrate that this method slightly outperforms the earlier one. This result highlights that partner prediction does not only rely on the identities and interactions of directly contacting amino-acids.

scholarly journals Protein Interaction Z Score Assessment (PIZSA): an empirical scoring scheme for evaluation of protein–protein interactions

2019 ◽  
Vol 47 (W1) ◽  
pp. W331-W337 ◽  
Author(s):  
Ankit A Roy ◽  
Abhilesh S Dhawanjewar ◽  
Parichit Sharma ◽  
Gulzar Singh ◽  
M S Madhusudhan
Keyword(s):  
Protein Interactions ◽  
Protein Complexes ◽  
Three Dimensional ◽  
Optimal Number ◽  
Dimensional Structure ◽  
Side Chain ◽  
Interface Residue ◽  
Z Score ◽  
Protein Protein Interactions ◽  
Residue Contacts

Abstract Our web server, PIZSA (http://cospi.iiserpune.ac.in/pizsa), assesses the likelihood of protein–protein interactions by assigning a Z Score computed from interface residue contacts. Our score takes into account the optimal number of atoms that mediate the interaction between pairs of residues and whether these contacts emanate from the main chain or side chain. We tested the score on 174 native interactions for which 100 decoys each were constructed using ZDOCK. The native structure scored better than any of the decoys in 146 cases and was able to rank within the 95th percentile in 162 cases. This easily outperforms a competing method, CIPS. We also benchmarked our scoring scheme on 15 targets from the CAPRI dataset and found that our method had results comparable to that of CIPS. Further, our method is able to analyse higher order protein complexes without the need to explicitly identify chains as receptors or ligands. The PIZSA server is easy to use and could be used to score any input three-dimensional structure and provide a residue pair-wise break up of the results. Attractively, our server offers a platform for users to upload their own potentials and could serve as an ideal testing ground for this class of scoring schemes.

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