Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Analysis of the oligomeric states of nucleophosmin using size exclusion chromatography.

ABSTRACT: Nucleophosmin (NPM1) is a multifunctional phosphoprotein which plays important roles in diverse biological processes. NPM1 can form homo- or hetero-oligomers through its N-terminal region, and bind DNA and RNA through its C-terminal region. However, the monomer-oligomer distribution of NPM1, and the extent of NPM1 binding and unbinding to RNA in living cells, are not fully understood. In this work, we analysed molecular complexes of NPM1 using size exclusion chromatography. We found that a substantial fraction of NPM1 behaves as an oligomer in HeLa cells. Furthermore, we identified three distinct oligomeric states of NPM1 using molecular characterization techniques such as subcellular localization and RNA binding. Finally, we found that heterozygous expression of a leukemia-associated NPM1 mutant significantly decreases the RNA binding level. Our data demonstrate that size exclusion chromatography provides a powerful tool for analysing NPM1 oligomers.

SUBMITTER: Sakashita G

PROVIDER: S-EPMC5838202 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Analysis of the oligomeric states of nucleophosmin using size exclusion chromatography.

Sakashita Gyosuke G Kiyoi Hitoshi H Naoe Tomoki T Urano Takeshi T

Scientific reports 20180305 1

Nucleophosmin (NPM1) is a multifunctional phosphoprotein which plays important roles in diverse biological processes. NPM1 can form homo- or hetero-oligomers through its N-terminal region, and bind DNA and RNA through its C-terminal region. However, the monomer-oligomer distribution of NPM1, and the extent of NPM1 binding and unbinding to RNA in living cells, are not fully understood. In this work, we analysed molecular complexes of NPM1 using size exclusion chromatography. We found that a subst ...[more]

PMID: 29507312

Similar Datasets

Analysis using size exclusion chromatography of poly(N-isopropyl acrylamide) using methanol as an eluent.

Project description:Size Exclusion Chromatography is traditionally carried out in either aqueous or non-polar solvents. A system to present molar mass distributions of polymers using methanol as a mobile phase is presented. This is shown to be a suitable system for determining the molar mass distributions poly(N-isopropylacrylamide)s (PNIPAM); a polymer class that is often difficult to analyze by size exclusion chromatography. DOSY NMR was used to provide intrinsic viscosity data that was used in conjunction with a viscometric detector to provide absolute calibration. Then the utility of the system was shown by providing the absolute molar mass distributions of dispersed highly branched PNIPAM with biologically functional end groups.

| S-EPMC5486375 | biostudies-literature

Probing Protein Denaturation during Size-Exclusion Chromatography Using Native Mass Spectrometry.

Project description:Size-exclusion chromatography employing aqueous mobile phases with volatile salts at neutral pH combined with electrospray-ionization mass spectrometry (SEC-ESI-MS) is a useful tool to study proteins in their native state. However, whether the applied eluent conditions actually prevent protein-stationary phase interactions, and/or protein denaturation, often is not assessed. In this study, the effects of volatile mobile phase additives on SEC retention and ESI of proteins were thoroughly investigated. Myoglobin was used as the main model protein, and eluents of varying ionic strength and pH were applied. The degree of interaction between protein and stationary phase was evaluated by calculating the SEC distribution coefficient. Protein-ion charge state distributions obtained during offline and online native ESI-MS were used to monitor alterations in protein structure. Interestingly, most of the supposedly mild eluent compositions induced nonideal SEC behavior and/or protein unfolding. SEC experiments revealed that the nature, ionic strength, and pH of the eluent affected protein retention. Protein-stationary phase interactions were effectively avoided using ammonium acetate at ionic strengths above 0.1 M. Direct-infusion ESI-MS showed that the tested volatile eluent salts seem to follow the Hofmeister series: no denaturation was induced using ammonium acetate (kosmotropic), whereas ammonium formate and bicarbonate (both chaotropic) caused structural changes. Using a mobile phase of 0.2 M ammonium acetate (pH 6.9), several proteins (i.e., myoglobin, carbonic anhydrase, and cytochrome c) could be analyzed by SEC-ESI-MS using different column chemistries without compromising their native state. Overall, with SEC-ESI-MS, the effect of nonspecific interactions between protein and stationary phase on the protein structure can be studied, even revealing gradual structural differences along a peak.

| S-EPMC7081181 | biostudies-literature

Extensive heterogeneity of glycopeptides in plasma revealed by deep glycoproteomic analysis using size-exclusion chromatography.

Project description:Several plasma glycoproteins are clinically useful as biomarkers in a variety of diseases. Although thousands of proteins are present in plasma, >95% of the plasma proteome by mass is represented by only 22 proteins. This necessitates strategies to deplete the abundant proteins and enrich other subsets of proteins. Although glycoproteins are abundant in plasma, in routine proteomic analyses, glycopeptides are not often investigated. Traditional methods such as lectin-based enrichment of glycopeptides followed by deglycosylation have helped understand the glycoproteome, but they lack any information about the attached glycans. Here, we apply size-exclusion chromatography (SEC) as a simple strategy to enrich intact N-glycopeptides based on their larger size which achieves broad selectivity regardless of the nature of attached glycans. Using this approach, we identified 1317 N-glycopeptides derived from 266 glycosylation sites on 154 plasma glycoproteins. The deep coverage achieved by this approach was evidenced by extensive heterogeneity that was observed. For instance, 20-100 glycopeptides were observed per protein for the 15 most-glycosylated glycoproteins. Notably, we discovered 615 novel glycopeptides of which 39 glycosylation sites (from 38 glycoproteins) were not included in protein databases such as Uniprot and GlyConnectDB. Finally, we also identified 12 novel glycopeptides containing di-sialic acid, which is a rare glycan epitope. Our results demonstrate the utility of SEC for efficient LC-MS/MS-based deep glycoproteomics analysis of human plasma. Overall, the SEC-based method described here is a simple, rapid and high-throughput strategy for characterization of any glycoproteome.

| S-EPMC8664156 | biostudies-literature

dichotomic size-exclusion chromatography（SEC）

Project description:directDIA proteomics raw data of plasma extracellular vesicles isolated by SEC and UC

2021-05-17 | PXD026034 |

Studying arsenite-humic acid complexation using size exclusion chromatography-inductively coupled plasma mass spectrometry.

Project description:Arsenic (As) can form complexes with dissolved organic matter (DOM), which affects the fate of arsenic in waste sites and natural environments. It remains a challenge to analyze DOM-bound As, in particular by using a direct chromatographic separation method. Size exclusion chromatography (SEC) hyphenated with UV spectrophotometer and inductively coupled plasma mass spectrometry (ICP-MS) was developed to characterize the complexation of arsenite (As(III)) with DOM. This SEC-UV-ICP-MS method is able to differentiate As(III)-DOM complexes from free As species and has the advantage of direct determination of both free and DOM-bound As(III) through mild separation. The suitability of this method for studying As(III)-DOM complexation was demonstrated by its application, in combination with the Scatchard plot and nonlinear regression of ligand binding model, for characterizing As(III) complexation with humic acid (HA) in the absence or presence of natural sand. The results suggest that, consistent with polyelectrolytic nature of HA, the As(III)-HA complexation should be accounted for by multiple classes of binding sites. By loosely classifying the binding sites into strong (S1) and weak (S2) sites, the apparent stability constants (Ks) of the resulting As-DOM complexes were calculated as logK(s1) = 6.5-7.1 while logK(s2) = 4.7-5.0.

| S-EPMC3612379 | biostudies-literature

Characterization of DNA nanostructure stability by size exclusion chromatography.

Project description:DNA-based nanostructures (DNs) are advantageous for the design of functional materials for biology and medicine due to the nanoscale control provided by their predictable self-assembly. However, the use of DNs in vivo has been limited due to structural instability in biofluids. As the stability of a particular DN sets the scope of its potential biological applications, efficient methods to characterize stability are required. Here, we apply size exclusion chromatography (SEC) to study the stability of a tetrahedron DNA nanostructure (TDN) and demonstrate the analytical capabilities of our method in characterizing degradation by enzymes and a diluted human serum matrix. We show that SEC analysis can reliably assay TDN degradation by a nuclease through direct injection and peak integration. Furthermore, data analysis using a ratio chromatogram technique enables TDN peak deconvolution from the matrix of serum proteins. Using our method, we found that TDNs exhibit half-lives of 23.9 hours and 10.1 hours in 20% and 50% diluted human serum, respectively, which is consistent with reported stability studies in 10% fetal bovine serum. We anticipate that this method can be broadly applicable to characterize a variety of DNs and serve as an efficient technique toward analysis of the stability of new DN designs in complex biological matrixes.

| S-EPMC9491180 | biostudies-literature

Nanoparticle Analysis by Online Comprehensive Two-Dimensional Liquid Chromatography combining Hydrodynamic Chromatography and Size-Exclusion Chromatography with Intermediate Sample Transformation.

Project description:Polymeric nanoparticles have become indispensable in modern society with a wide array of applications ranging from waterborne coatings to drug-carrier-delivery systems. While a large range of techniques exist to determine a multitude of properties of these particles, relating physicochemical properties of the particle to the chemical structure of the intrinsic polymers is still challenging. A novel, highly orthogonal separation system based on comprehensive two-dimensional liquid chromatography (LC × LC) has been developed. The system combines hydrodynamic chromatography (HDC) in the first-dimension to separate the particles based on their size, with ultrahigh-performance size-exclusion chromatography (SEC) in the second dimension to separate the constituting polymer molecules according to their hydrodynamic radius for each of 80 to 100 separated fractions. A chip-based mixer is incorporated to transform the sample by dissolving the separated nanoparticles from the first-dimension online in tetrahydrofuran. The polymer bands are then focused using stationary-phase-assisted modulation to enhance sensitivity, and the water from the first-dimension eluent is largely eliminated to allow interaction-free SEC. Using the developed system, the combined two-dimensional distribution of the particle-size and the molecular-size of a mixture of various polystyrene (PS) and polyacrylate (PACR) nanoparticles has been obtained within 60 min.

| S-EPMC5588091 | biostudies-literature

Extracellular vesicles isolated by size-exclusion chromatography present suitability for RNomics analysis in plasma.

Project description:BackgroundExtracellular vesicles (EVs), known as cell-derived membranous structures harboring a variety of biomolecules, have been widely used in liquid biopsy. Due to the complex biological composition of plasma, plasma RNA omics analysis (RNomics) is easily affected, thus it is necessary to select an optimal strategy from exiting methods according to the performance for intended application.MethodsIn this study, four different strategies for EVs isolation were performed and compared (i.e. ultracentrifugation (UC), size exclusion chromatography (SEC), and two most frequently-used commercially available isolation kit (ExoQuick and exoEasy). We compared the yield, purity, PCR quantification of RNAs, miRNA-seq analyses and mRNA-seq analyses of RNAs from EVs isolated using four methods.ResultsThe results showed that the lowest miRNA binding protein AGO2 (Argonaute-2) and the highest EVs-specific miRNA and lncRNA were observed in EVs obtained through SEC, meanwhile the content of the non-specific miRNA was the lowest. Further RNA-Seq data revealed that RNAs obtained via SEC presented more useful reads for both miRNA and mRNA. Furthermore, the mRNA delivered via SEC tended to have a concentration comparable to the ideal FPKM (Fragments Per Kilobase Million) value.ConclusionsSEC shall be used as an optimal strategy for the isolation of EVs in plasma RNomics analysis.

| S-EPMC7953782 | biostudies-literature

Native Proteomics in Discovery Mode Using Size-Exclusion Chromatography-Capillary Zone Electrophoresis-Tandem Mass Spectrometry.

Project description:Native proteomics aims to characterize complex proteomes under native conditions and ultimately produces a full picture of endogenous protein complexes in cells. It requires novel analytical platforms for high-resolution and liquid-phase separation of protein complexes prior to native mass spectrometry (MS) and MS/MS. In this work, size-exclusion chromatography (SEC)-capillary zone electrophoresis (CZE)-MS/MS was developed for native proteomics in discovery mode, resulting in the identification of 144 proteins, 672 proteoforms, and 23 protein complexes from the Escherichia coli proteome. The protein complexes include four protein homodimers, 16 protein-metal complexes, two protein-[2Fe-2S] complexes, and one protein-glutamine complex. Half of them have not been reported in the literature. This work represents the first example of online liquid-phase separation-MS/MS for the characterization of a complex proteome under the native condition, offering the proteomics community an efficient and simple platform for native proteomics.

| S-EPMC6156775 | biostudies-literature

Reproducible and scalable purification of extracellular vesicles using combined bind-elute and size exclusion chromatography.

Project description:Extracellular vesicles (EVs) play a pivotal role in cell-to-cell communication and have been shown to take part in several physiological and pathological processes. EVs have traditionally been purified by ultracentrifugation (UC), however UC has limitations, including resulting in, operator-dependant yields, EV aggregation and altered EV morphology, and moreover is time consuming. Here we show that commercially available bind-elute size exclusion chromatography (BE-SEC) columns purify EVs with high yield (recovery ~ 80%) in a time-efficient manner compared to current methodologies. This technique is reproducible and scalable, and surface marker analysis by bead-based flow cytometry revealed highly similar expression signatures compared with UC-purified samples. Furthermore, uptake of eGFP labelled EVs in recipient cells was comparable between BE-SEC and UC samples. Hence, the BE-SEC based EV purification method represents an important methodological advance likely to facilitate robust and reproducible studies of EV biology and therapeutic application.

| S-EPMC5599601 | 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