scholarly journals Sequence Divergence and Functional Specializations of the Ancient Spliceosomal SF3b: Implications in Flexibility and Adaptations of the Multi-Protein Complex

2022 ◽  
Vol 12 ◽  
Author(s):  
Arangasamy Yazhini ◽  
Narayanaswamy Srinivasan ◽  
Sankaran Sandhya
Keyword(s):  
Protein Interactions ◽  
Sequence Divergence ◽  
Drug Binding ◽  
Molecular Signatures ◽  
Protein Protein Interactions ◽  
Molecular Systems ◽  
Protein Partners ◽  
Eukaryotic Species ◽  
Conservation Patterns ◽  
Protein Components

Multi-protein assemblies are complex molecular systems that perform highly sophisticated biochemical functions in an orchestrated manner. They are subject to changes that are governed by the evolution of individual components. We performed a comparative analysis of the ancient and functionally conserved spliceosomal SF3b complex, to recognize molecular signatures that contribute to sequence divergence and functional specializations. For this, we recognized homologous sequences of individual SF3b proteins distributed across 10 supergroups of eukaryotes and identified all seven protein components of the complex in 578 eukaryotic species. Using sequence and structural analysis, we establish that proteins occurring on the surface of the SF3b complex harbor more sequence variation than the proteins that lie in the core. Further, we show through protein interface conservation patterns that the extent of conservation varies considerably between interacting partners. When we analyze phylogenetic distributions of individual components of the complex, we find that protein partners that are known to form independent subcomplexes are observed to share similar profiles, reaffirming the link between differential conservation of interface regions and their inter-dependence. When we extend our analysis to individual protein components of the complex, we find taxa-specific variability in molecular signatures of the proteins. These trends are discussed in the context of proline-rich motifs of SF3b4, functional and drug binding sites of SF3b1. Further, we report key protein-protein interactions between SF3b1 and SF3b6 whose presence is observed to be lineage-specific across eukaryotes. Together, our studies show the association of protein location within the complex and subcomplex formation patterns with the sequence conservation of SF3b proteins. In addition, our study underscores evolutionarily flexible elements that appear to confer adaptive features in individual components of the multi-protein SF3b complexes and may contribute to its functional adaptability.

scholarly journals A unified resource and configurable model of the synapse proteome and its role in disease

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Oksana Sorokina ◽  
Colin Mclean ◽  
Mike D. R. Croning ◽  
Katharina F. Heil ◽  
Emilia Wysocka ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Synaptic Proteins ◽  
Protein Protein Interactions ◽  
Network Resource ◽  
Unique Protein ◽  
Co Morbidity ◽  
Genes Encoding ◽  
Protein Components ◽  
Accessible Format ◽  
Neuronal Disorders

AbstractGenes encoding synaptic proteins are highly associated with neuronal disorders many of which show clinical co-morbidity. We integrated 58 published synaptic proteomic datasets that describe over 8000 proteins and combined them with direct protein–protein interactions and functional metadata to build a network resource that reveals the shared and unique protein components that underpin multiple disorders. All the data are provided in a flexible and accessible format to encourage custom use.

Structure, Function, Involvement in Diseases and Targeting of 14-3-3 Proteins: An Update

2018 ◽  
Vol 25 (1) ◽  
pp. 5-21 ◽  
Author(s):  
Ylenia Cau ◽  
Daniela Valensin ◽  
Mattia Mori ◽  
Sara Draghi ◽  
Maurizio Botta
Keyword(s):  
Protein Interactions ◽  
Molecular Mechanisms ◽  
Physiological Role ◽  
Specific Protein ◽  
Protein Protein Interactions ◽  
Cellular Processes ◽  
Protein Partners ◽  
High Sequence Homology ◽  
Small Molecule Modulators

14-3-3 is a class of proteins able to interact with a multitude of targets by establishing protein-protein interactions (PPIs). They are usually found in all eukaryotes with a conserved secondary structure and high sequence homology among species. 14-3-3 proteins are involved in many physiological and pathological cellular processes either by triggering or interfering with the activity of specific protein partners. In the last years, the scientific community has collected many evidences on the role played by seven human 14-3-3 isoforms in cancer or neurodegenerative diseases. Indeed, these proteins regulate the molecular mechanisms associated to these diseases by interacting with (i) oncogenic and (ii) pro-apoptotic proteins and (iii) with proteins involved in Parkinson and Alzheimer diseases. The discovery of small molecule modulators of 14-3-3 PPIs could facilitate complete understanding of the physiological role of these proteins, and might offer valuable therapeutic approaches for these critical pathological states.

scholarly journals First person – Jia Yu and Pei-Ju Liao

2021 ◽  
Vol 134 (24) ◽  
Keyword(s):  
Protein Interactions ◽  
Structural Model ◽  
Early Career ◽  
Drug Binding ◽  
First Person ◽  
Protein Protein Interactions ◽  
Early Career Researchers ◽  
Complex Simulation ◽  
Drug Binding Sites ◽  
Selection Of

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Jia Yu and Pei-Ju Liao are co-first authors on ‘ Structural model of human PORCN illuminates disease-associated variants and drug-binding sites’, published in JCS. Jia is a senior postdoc in the lab of David Virshup at Duke-NUS Medical School, Singapore, investigating Wnt secretion and signalling; in particular, how Wnt trafficking and secretion is regulated by two integral membrane proteins, porcupine and WLS. Pei-Ju is a research assistant in the same lab, investigating protein–protein interactions in the systems biology of signalling pathways using protein structure modelling and protein complex simulation.

scholarly journals Molecular Characterization and Elucidation of Pathways to Identify Novel Therapeutic Targets in Pulmonary Arterial Hypertension

2021 ◽  
Vol 12 ◽  
Author(s):  
Xiaoting Yao ◽  
Tian Jing ◽  
Tianxing Wang ◽  
Chenxin Gu ◽  
Xi Chen ◽  
...  
Keyword(s):  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Lung Tissue ◽  
Protein Interactions ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Molecular Signatures ◽  
Protein Protein Interactions ◽  
Pulmonary Arterial ◽  
Microarray Datasets

Background: Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disease. However, there are limited studies reflecting the available biomarkers from separate gene expression profiles in PAH. This study explored two microarray datasets by an integrative analysis to estimate the molecular signatures in PAH.Methods: Two microarray datasets (GSE53408 and GSE113439) were exploited to compare lung tissue transcriptomes of patients and controls with PAH and to estimate differentially expressed genes (DEGs). According to common DEGs of datasets, gene and protein overrepresentation analyses, protein–protein interactions (PPIs), DEG–transcription factor (TF) interactions, DEG–microRNA (miRNA) interactions, drug–target protein interactions, and protein subcellular localizations were conducted in this study.Results: We obtained 38 common DEGs for these two datasets. Integration of the genome transcriptome datasets with biomolecular interactions revealed hub genes (HSP90AA1, ANGPT2, HSPD1, HSPH1, TTN, SPP1, SMC4, EEA1, and DKC1), TFs (FOXC1, FOXL1, GATA2, YY1, and SRF), and miRNAs (hsa-mir-17-5p, hsa-mir-26b-5p, hsa-mir-122-5p, hsa-mir-20a-5p, and hsa-mir-106b-5p). Protein–drug interactions indicated that two compounds, namely, nedocromil and SNX-5422, affect the identification of PAH candidate biomolecules. Moreover, the molecular signatures were mostly localized in the extracellular and nuclear areas.Conclusions: In conclusion, several lung tissue-derived molecular signatures, highlighted in this study, might serve as novel evidence for elucidating the essential mechanisms of PAH. The potential drugs associated with these molecules could thus contribute to the development of diagnostic and therapeutic strategies to ameliorate PAH.

scholarly journals Selectivity of Protein Interactions along the Aggregation Pathway of α-Synuclein

2021 ◽  
Author(s):  
André D. G. Leitão ◽  
Paulina Rudolffi Soto ◽  
Alexandre Chappard ◽  
Akshay Bhumkar ◽  
Dominic J. B. Hunter ◽  
...  
Keyword(s):  
Single Molecule ◽  
Protein Interactions ◽  
Self Assembly ◽  
Amyloid Fibrils ◽  
Lewy Bodies ◽  
Coincidence Detection ◽  
Protein Protein Interactions ◽  
Assembly Pathway ◽  
Protein Partners ◽  
Molecular Complexity

AbstractThe aggregation of α-SYN follows a cascade of oligomeric, prefibrillar and fibrillar forms, culminating in the formation of Lewy Bodies (LB), the pathological hallmarks of Parkinson’s Disease in neurons. Whilst α-synuclein is a major contributor to LB, these dense accumulations of protein aggregates and tangles of fibrils contain over 70 different proteins. However, the potential for interactions between these proteins and the different aggregated species of α-SYN is largely unknown. We hypothesized that the proteins present in the Lewy Bodies are trapped or pulled into the aggregates in a hierarchical manner, by binding at specific stages of the aggregation of α-SYN.In this study we uncover a map of interactions of a total of 65 proteins, against different species formed by α-SYN. We measured binding to monomeric α-SYN using AlphaScreen, a sensitive nano-bead assay for detection of protein-protein interactions. To access different oligomeric species, we made use of the pathological mutants of α-SYN (A30P, G51D and A53T), which form oligomeric species with distinct properties. Finally, we used bacterially expressed recombinant α-SYN to generate amyloid fibrils and measure interactions with a pool of GFP-tagged potential partners. Binding to oligomers and fibrils was measured by two-color coincidence detection (TCCD) on a single molecule spectroscopy setup. Overall, we demonstrate that LB components are selectively recruited to specific steps in the formation of the LB, explaining their presence in the inclusions. Only a few proteins were found to interact with α-SYN monomers at detectable levels, and only a subset recognizes the oligomeric α-SYN including autophagosomal proteins. We therefore propose a new model for the formation of Lewy Bodies, where selectivity of protein partners at different steps drives the arrangement of these structures, uncovering new ways to modulate aggregation.Significance StatementThe molecular complexity of the Lewy Bodies has been a major hindrance to a bottom-up reconstruction of these inclusions, protein by protein. This work presents an extensive dataset of protein-protein interactions, showing that despite its small size and absence of structure, α-SYN binds to specific partners in the LB, and that there is a clear selectivity of interactions between the different α-SYN species along the self-assembly pathway. We use single-molecule methods to deconvolute number and size of the co-aggregates, to gain detailed information about the mechanisms of interaction. These observations constitute the basis for the elaboration of a global interactome of α-SYN.

scholarly journals Expanding Interactome Analyses beyond Model Eukaryotes

2021 ◽  
Author(s):  
Katherine James ◽  
Anil Wipat ◽  
Simon Cockell
Keyword(s):  
Genome Sequence ◽  
Protein Interactions ◽  
Model Organisms ◽  
Protein Protein Interactions ◽  
Data Types ◽  
Interaction Prediction ◽  
Diverse Species ◽  
Eukaryotic Species

Interactome analyses have traditionally been applied to yeast, human and other model organisms due to the availability of protein-protein interactions data for these species. Recently these techniques have been applied to more diverse species using computational interaction prediction from genome sequence and other data types. This review describes the various types of computational interactome networks that can be created and how they have been used in diverse eukaryotic species, highlighting some of the key interactome studies in non-model organisms.

scholarly journals Integrative analysis identified common and unique molecular signatures in hepatobiliary cancers

2021 ◽  
Author(s):  
Nabanita Roy ◽  
Ria Lodh ◽  
Anupam Sarma ◽  
Dhruba Kumar Bhattacharyya ◽  
Pankaj Barah
Keyword(s):  
Protein Interactions ◽  
Metabolic Pathways ◽  
Expression Patterns ◽  
Molecular Signature ◽  
Cancer Type ◽  
Molecular Signatures ◽  
Protein Protein Interactions ◽  
Hub Genes ◽  
Cellular Processes ◽  
Differential Gene

Hepatobiliary cancers (HBCs) are the most aggressive and sixth most diagnosed cancers globally. Biomarkers for timely diagnosis and targeted therapy in HBCs are still limited. Considering the gap, our objective is to identify unique and overlapping molecular signatures associated with HBCs. We analyzed publicly available transcriptomic datasets on Gallbladder cancer (GBC), Hepatocellular carcinoma (HCC), and Intrahepatic cholangiocarcinoma (ICC) to identify potential biomarkers using integrative systems approaches. An effective Common and Unique Molecular Signature Identification (CUMSI) approach has been employed, which contains analysis of differential gene expression (DEG), gene co-expression networks (GCN), and protein-protein interactions (PPIs) networks. Functional analysis of the DEGs unique for GBC, HCC, and ICC indicated that GBC is associated with cellular processes, HCC is associated with immune signaling pathways, and ICC is associated with lipid metabolic pathways. Our findings shows that the hub genes and pathways identified for each individual cancer type of the HBS are related with the primary function of each organ and each cancer exhibit unique expression patterns despite being part of the same organ system.

scholarly journals Regulating SWI/SNF Subunit Levels via Protein-Protein Interactions and Proteasomal Degradation: BAF155 and BAF170 Limit Expression of BAF57

2005 ◽  
Vol 25 (20) ◽  
pp. 9016-9027 ◽  
Author(s):  
Jianguang Chen ◽  
Trevor K. Archer
Keyword(s):  
Chromatin Remodeling ◽  
Protein Interactions ◽  
Wild Type ◽  
Protein Protein Interactions ◽  
Physiological Mechanisms ◽  
Protein Levels ◽  
Chromatin Remodeling Complex ◽  
Exogenous Expression ◽  
Protein Components ◽  
Enzyme Complexes

ABSTRACT The mammalian SWI/SNF chromatin remodeling complex, whose function is of critical importance in transcriptional regulation, contains approximately 10 protein components. The expression levels of the core SWI/SNF subunits, including BRG1/Brm, BAF155, BAF170, BAF60, hSNF/Ini1, and BAF57, are stoichiometric, with few to no unbound molecules in the cell. Here we report that exogenous expression of the wild type or certain deletion mutants of BAF57, a key subunit that mediates the interaction between the remodeling complex and transcription factors, results in diminished expression of endogenous BAF57. This down-regulation process is mediated by an increase in proteasome-dependent degradation of the BAF57 protein. Furthermore, the protein levels of BAF155/170 dictate the maximum cellular amount of BAF57. We mapped the domains responsible for the interaction between BAF57 and BAF155 and demonstrated that protein-protein interactions between them play an important role in this regulatory process. These findings provide insights into the physiological mechanisms responsible for maintaining the proper stoichiometric levels of the protein components comprising multimeric enzyme complexes.

Heat stability of homogenized milk: role of interfacial protein

1994 ◽  
Vol 61 (4) ◽  
pp. 507-516 ◽  
Author(s):  
Catharina H. McCrae ◽  
David Hirst ◽  
Andrew J. R. Law ◽  
D. Donald Muir
Keyword(s):  
Serum Protein ◽  
Protein Interactions ◽  
Protein Composition ◽  
Surface Protein ◽  
Heat Stability ◽  
Protein Protein Interactions ◽  
Ph Profile ◽  
Protein Components ◽  
The Individual

SummaryThe role of interfacial protein in determining the heat stability of recombined milk was investigated by removing serum protein prior to homogenization and reincorporating it after homogenization. In addition, the surface protein composition of recombined fat globules was probed by analyses of protein load and by quantification of the individual surface protein components using FPLC. In the absence of serum protein, substantially more casein was bound to the fat surface during homogenization. Despite this, the detrimental effect of homogenization on heat stability did not occur when serum protein had been removed from the system. Reincorporation of serum protein after homogenization caused the heat coagulation time–pH profile to revert to a form very similar to that observed without removing serum protein from the system. Thus, adsorption of serum protein did not affect heat stability. It is more likely that heat-induced interactions of serum protein with surface-adsorbed casein promoted heat coagulation. Fat surface area rather than casein load affected these interfacial protein-protein interactions during heating.

scholarly journals Internetwork connectivity of molecular networks across species of life

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tarun Mahajan ◽  
Roy D. Dar
Keyword(s):  
Molecular Interactions ◽  
Protein Interactions ◽  
Transcriptional Regulatory Network ◽  
Building Blocks ◽  
Hierarchical Organization ◽  
Molecular Networks ◽  
Protein Protein Interactions ◽  
Interacting Protein ◽  
Protein Protein Interaction ◽  
Eukaryotic Species

AbstractMolecular interactions are studied as independent networks in systems biology. However, molecular networks do not exist independently of each other. In a network of networks approach (called multiplex), we study the joint organization of transcriptional regulatory network (TRN) and protein–protein interaction (PPI) network. We find that TRN and PPI are non-randomly coupled across five different eukaryotic species. Gene degrees in TRN (number of downstream genes) are positively correlated with protein degrees in PPI (number of interacting protein partners). Gene–gene and protein–protein interactions in TRN and PPI, respectively, also non-randomly overlap. These design principles are conserved across the five eukaryotic species. Robustness of the TRN–PPI multiplex is dependent on this coupling. Functionally important genes and proteins, such as essential, disease-related and those interacting with pathogen proteins, are preferentially situated in important parts of the human multiplex with highly overlapping interactions. We unveil the multiplex architecture of TRN and PPI. Multiplex architecture may thus define a general framework for studying molecular networks. This approach may uncover the building blocks of the hierarchical organization of molecular interactions.

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