Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Driving integrative structural modeling with serial capture affinity purification.

ABSTRACT: Streamlined characterization of protein complexes remains a challenge for the study of protein interaction networks. Here we describe serial capture affinity purification (SCAP), in which two separate proteins are tagged with either the HaloTag or the SNAP-tag, permitting a multistep affinity enrichment of specific protein complexes. The multifunctional capabilities of this protein-tagging system also permit in vivo validation of interactions using acceptor photobleaching Förster resonance energy transfer and fluorescence cross-correlation spectroscopy quantitative imaging. By coupling SCAP to cross-linking mass spectrometry, an integrative structural model of the complex of interest can be generated. We demonstrate this approach using the Spindlin1 and SPINDOC protein complex, culminating in a structural model with two SPINDOC molecules docked on one SPIN1 molecule. In this model, SPINDOC interacts with the SPIN1 interface previously shown to bind a lysine and arginine methylated sequence of histone H3. Our approach combines serial affinity purification, live cell imaging, and cross-linking mass spectrometry to build integrative structural models of protein complexes.

SUBMITTER: Liu X

PROVIDER: S-EPMC7749342 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Affinity purification strategy to capture human endogenous proteasome complexes diversity and to identify proteasome-interacting proteins.

Project description:An affinity purification strategy was developed to characterize human proteasome complexes diversity as well as endogenous proteasome-interacting proteins (PIPs). This single step procedure, initially used for 20 S proteasome purification, was adapted to purify all existing physiological proteasome complexes associated to their various regulatory complexes and to their interacting partners. The method was applied to the purification of proteasome complexes and their PIPs from human erythrocytes but can be used to purify proteasomes from any human sample as starting material. The benefit of in vivo formaldehyde cross-linking as a stabilizer of protein-protein interactions was studied by comparing the status of purified proteasomes and the identified proteins in both protocols (with or without formaldehyde cross-linking). Subsequent proteomics analyses identified all proteasomal subunits, known regulators, and recently assigned partners. Moreover other proteins implicated at different levels of the ubiquitin-proteasome system were also identified for the first time as PIPs. One of them, the ubiquitin-specific protease USP7, also known as HAUSP, is an important player in the p53-HDM2 pathway. The specificity of the interaction was further confirmed using a complementary approach that consisted of the reverse immunoprecipitation with HAUSP as a bait. Altogether we provide a valuable tool that should contribute, through the identification of partners likely to affect proteasomal function, to a better understanding of this complex proteolytic machinery in any living human cell and/or organ/tissue and in different cell physiological states.

| S-EPMC2689779 | biostudies-literature

Affinity Purification and Structural Features of the Yeast Vacuolar ATPase Vo Membrane Sector.

Project description:The membrane sector (Vo) of the proton pumping vacuolar ATPase (V-ATPase, V1Vo-ATPase) from Saccharomyces cerevisiae was purified to homogeneity, and its structure was characterized by EM of single molecules and two-dimensional crystals. Projection images of negatively stained Vo two-dimensional crystals showed a ring-like structure with a large asymmetric mass at the periphery of the ring. A cryo-EM reconstruction of Vo from single-particle images showed subunits a and d in close contact on the cytoplasmic side of the proton channel. A comparison of three-dimensional reconstructions of free Vo and Vo as part of holo V1Vo revealed that the cytoplasmic N-terminal domain of subunit a (aNT) must undergo a large conformational change upon enzyme disassembly or (re)assembly from Vo, V1, and subunit C. Isothermal titration calorimetry using recombinant subunit d and aNT revealed that the two proteins bind each other with a Kd of ~5 μm. Treatment of the purified Vo sector with 1-palmitoyl-2-hydroxy-sn-glycero-3-[phospho-rac-(1-glycerol)] resulted in selective release of subunit d, allowing purification of a VoΔd complex. Passive proton translocation assays revealed that both Vo and VoΔd are impermeable to protons. We speculate that the structural change in subunit a upon release of V1 from Vo during reversible enzyme dissociation plays a role in blocking passive proton translocation across free Vo and that the interaction between aNT and d seen in free Vo functions to stabilize the Vo sector for efficient reassembly of V1Vo.

| S-EPMC4646912 | biostudies-literature

Integrative structural modeling with small angle X-ray scattering profiles.

Project description:Recent technological advances enabled high-throughput collection of Small Angle X-ray Scattering (SAXS) profiles of biological macromolecules. Thus, computational methods for integrating SAXS profiles into structural modeling are needed more than ever. Here, we review specifically the use of SAXS profiles for the structural modeling of proteins, nucleic acids, and their complexes. First, the approaches for computing theoretical SAXS profiles from structures are presented. Second, computational methods for predicting protein structures, dynamics of proteins in solution, and assembly structures are covered. Third, we discuss the use of SAXS profiles in integrative structure modeling approaches that depend simultaneously on several data types.

| S-EPMC3427135 | biostudies-literature

Optimizing representations for integrative structural modeling using Bayesian model selection.

Project description:MotivationIntegrative structural modeling combines data from experiments, physical principles, statistics of previous structures, and prior models to obtain structures of macromolecular assemblies that are challenging to characterize experimentally. The choice of model representation is a key decision in integrative modeling, as it dictates the accuracy of scoring, efficiency of sampling, and resolution of analysis. But currently, the choice is usually made ad hoc, manually.ResultsHere, we report NestOR (Nested Sampling for Optimizing Representation), a fully automated, statistically rigorous method based on Bayesian model selection to identify the optimal coarse-grained representation for a given integrative modeling setup. Given an integrative modeling setup, it determines the optimal representations from given candidate representations based on their model evidence and sampling efficiency. The performance of NestOR was evaluated on a benchmark of four macromolecular assemblies.AvailabilityNestOR is implemented in the Integrative Modeling Platform (https://integrativemodeling.org) and is available at https://github.com/isblab/nestor.

| S-EPMC10760022 | biostudies-literature

Integrative structure modeling with the Integrative Modeling Platform.

Project description:Building models of a biological system that are consistent with the myriad data available is one of the key challenges in biology. Modeling the structure and dynamics of macromolecular assemblies, for example, can give insights into how biological systems work, evolved, might be controlled, and even designed. Integrative structure modeling casts the building of structural models as a computational optimization problem, for which information about the assembly is encoded into a scoring function that evaluates candidate models. Here, we describe our open source software suite for integrative structure modeling, Integrative Modeling Platform (https://integrativemodeling.org), and demonstrate its use.

| S-EPMC5734277 | biostudies-literature

Bayesian Weighing of Electron Cryo-Microscopy Data for Integrative Structural Modeling.

Project description:Cryo-electron microscopy (cryo-EM) has become a mainstream technique for determining the structures of complex biological systems. However, accurate integrative structural modeling has been hampered by the challenges in objectively weighing cryo-EM data against other sources of information due to the presence of random and systematic errors, as well as correlations, in the data. To address these challenges, we introduce a Bayesian scoring function that efficiently and accurately ranks alternative structural models of a macromolecular system based on their consistency with a cryo-EM density map as well as other experimental and prior information. The accuracy of this approach is benchmarked using complexes of known structure and illustrated in three applications: the structural determination of the GroEL/GroES, RNA polymerase II, and exosome complexes. The approach is implemented in the open-source Integrative Modeling Platform (http://integrativemodeling.org), thus enabling integrative structure determination by combining cryo-EM data with other sources of information.

| S-EPMC6779587 | biostudies-literature

Effect analysis of the driving factors of super-gentrification using structural equation modeling.

Project description:The study of super-gentrification has important practical significance for maintaining social fairness, spatial justice and achieving sustainable urban development. In this article, 23 driving factors influencing super-gentrification are identified by literature research and Delphi method. Then, the 23 driving factors affecting super-gentrification are divided into four dimensions: political, economic, social and spatial dimension. On this basis, hypotheses are proposed and a structural equation model is established. Then, SPSS 25.0 and AMOS 24.0 software are used to test the reliability and validity of the questionnaire data, and the model results are fitted and modified. Finally, the optimization model and path coefficient of super-gentrification driving factors are calculated. The results of the study show that political factors, economic factors, social factors, and spatial factors, all play a positive role in the development of super-gentrification. Social factors are the fundamental factors to promote super-gentrification, political factors, economic factors, and spatial factors also play a key role in the super-gentrification process.

| S-EPMC7954290 | biostudies-literature

Chromatin tandem affinity purification sequencing.

Project description:Chromatin immunoprecipitation coupled with ultra-high-throughput sequencing (ChIP-seq) is a widely used method for mapping the interactions of proteins with DNA. However, the requirements for ChIP-grade antibodies impede wider application of this method, and variations in results can be high owing to differences in affinity and cross-reactivity of antibodies. Therefore, we developed chromatin tandem affinity purification (ChTAP) as an effective alternative to ChIP. Through the use of affinity tags and reagents that are identical for all proteins investigated, ChTAP enables one to directly compare the binding between different transcription factors and to directly assess the background in control experiments. Thus, ChTAP-seq can be used to rapidly map the genome-wide binding of multiple DNA-binding proteins in a wide range of cell types. ChTAP can be completed in 3-4 d, starting from cross-linking of chromatin to purification of ChIP DNA.

| S-EPMC4058862 | biostudies-literature

Affinity purification and refined structural characterization of terminal deoxynucleotidyltransferase.

Project description:A total of 56 stable murine hybridoma monoclones that produce homogeneous antibodies against human or calf terminal deoxynucleotidyltransferase have been established. All of the antibodies exhibited specific binding to various Mr forms of terminal transferase and eight possessed neutralizing activity. Results are presented that permitted characterization of ten of these antibodies with respect to their immunoglobulin class, their recognition of calf or human terminal-transferase Mr species by immunoblotting techniques and their recognition of distinct antigenic sites. Terminal transferase was purified in a single step by using an immunoaffinity column constructed with a monoclonal antibody exhibiting a high binding affinity for the enzyme. Single monoclonal antibodies were also used to bind selectively to terminal-transferase antigen in tissue slices and individual cells.

| S-EPMC1152709 | biostudies-other

Serial interactome capture of the human cell nucleus.

Project description:Novel RNA-guided cellular functions are paralleled by an increasing number of RNA-binding proteins (RBPs). Here we present 'serial RNA interactome capture' (serIC), a multiple purification procedure of ultraviolet-crosslinked poly(A)-RNA-protein complexes that enables global RBP detection with high specificity. We apply serIC to the nuclei of proliferating K562 cells to obtain the first human nuclear RNA interactome. The domain composition of the 382 identified nuclear RBPs markedly differs from previous IC experiments, including few factors without known RNA-binding domains that are in good agreement with computationally predicted RNA binding. serIC extends the number of DNA-RNA-binding proteins (DRBPs), and reveals a network of RBPs involved in p53 signalling and double-strand break repair. serIC is an effective tool to couple global RBP capture with additional selection or labelling steps for specific detection of highly purified RBPs.

| S-EPMC4822031 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data