PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 16414315

Protein depletion from blood plasma using a volatile buffer.

Dmitri Sitnikov·Donovan Chan·Eric Thibaudeau·Marc Pinard·Joanna M Hunter
View original source ↗Export metadata ↓

Abstract

Removal of high abundance proteins is widely used in sample processing for proteomics studies of blood plasma. Immunoaffinity (IA) depletion is currently the most specific method for performing this step. Historically, IA depletion matrices have been designed to be used with inorganic buffers. However, the presence of salts in depleted samples presents a particular problem, and these must be removed in order to make samples compatible with post-depletion processing. Desalting (dialysis, ultrafiltration, size-exclusion, etc.) usually diminishes sample integrity due to labware associated losses. Moreover, these steps require additional labor, increasing the processing time and cost of analysis. In order to avoid these problems, we have developed an IA method using a volatile buffer that can be removed from depleted samples by lyophilization. This method allows the execution of reproducible and efficient depletion of blood plasma in a semi-automated manner.

Explore related subjects

Blood ProteinsBuffersChromatography, Ion ExchangeElectrophoresis, Polyacrylamide GelFreeze DryingHumansPlasmaReproducibility of ResultsUltrafiltrationJournal Article

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Dmitri Sitnikov, Donovan Chan, Eric Thibaudeau, Marc Pinard, Joanna M Hunter. 2006-01-18. Protein depletion from blood plasma using a volatile buffer.. https://doi.org/10.1016/j.jchromb.2005.12.013

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2006

Reversible hexacoordination of alpha-hemoglobin-stabilizing protein (AHSP)/alpha-hemoglobin Versus pressure. Evidence for protection of the alpha-chains by their chaperone.

Using high hydrostatic pressure or hydrogen peroxide as perturbing agents, we demonstrate a protective effect of the chaperone AHSP for the alpha-chains of Hb. High pressure induces an irreversible aggregation of the ferrous deoxy alpha-chains, whereas the AHSP/alpha-Hb complex shows reversible hexacoordination of the alpha-Hb without protein aggregation. Upon pressure release, the relaxation kinetics of the transition from the hexacoordinated to pentacoordinated form of alpha-Hb in the presence of AHSP exhibit a biphasic shape. High pressure did not induce dissociation of alpha-Hb from its chaperone, as evidenced by the ligand binding kinetics that show a unique rate for the AHSP/alpha-Hb complex. For both free alpha-Hb and the AHSP/alpha-Hb complex, the bimolecular rate constant of CO binding (k(CO)(on)) versus pressure exhibits a bell shape, attributed to the transition of the rate-determining step from the chemical barrier to the migration of CO within the protein matrix. These results reveal a plasticity of the alpha-Hb active site in the presence of the chaperone and indicate that the AHSP was still active at 300 MPa. The ferric state of the AHSP/alpha-Hb complex shows hexacoordination even at atmospheric pressures, indicating a His-Fe-His binding scheme as previously observed in neuroglobin and cytoglobin. The reaction with hydrogen peroxide of ferric alpha-Hb within the complex also demonstrates a protection against aggregation.

Blood Proteins↗
PubMed2006

QSAR modeling of human serum protein binding with several modeling techniques utilizing structure-information representation.

Four modeling techniques, using topological descriptors to represent molecular structure, were employed to produce models of human serum protein binding (% bound) on a data set of 1008 experimental values, carefully screened from publicly available sources. To our knowledge, this data is the largest set on human serum protein binding reported for QSAR modeling. The data was partitioned into a training set of 808 compounds and an external validation test set of 200 compounds. Partitioning was accomplished by clustering the compounds in a structure descriptor space so that random sampling of 20% of the whole data set produced an external test set that is a good representative of the training set with respect to both structure and protein binding values. The four modeling techniques include multiple linear regression (MLR), artificial neural networks (ANN), k-nearest neighbors (kNN), and support vector machines (SVM). With the exception of the MLR model, the ANN, kNN, and SVM QSARs were ensemble models. Training set correlation coefficients and mean absolute error ranged from r2=0.90 and MAE=7.6 for ANN to r2=0.61 and MAE=16.2 for MLR. Prediction results from the validation set yielded correlation coefficients and mean absolute errors which ranged from r2=0.70 and MAE=14.1 for ANN to a low of r2=0.59 and MAE=18.3 for the SVM model. Structure descriptors that contribute significantly to the models are discussed and compared with those found in other published models. For the ANN model, structure descriptor trends with respect to their affects on predicted protein binding can assist the chemist in structure modification during the drug design process.

Blood Proteins↗
PubMed2006

Identification of a novel mitochondrial complex containing mitofusin 2 and stomatin-like protein 2.

A reverse genetics approach was utilized to discover new proteins that interact with the mitochondrial fusion mediator mitofusin 2 (Mfn2) and that may participate in mitochondrial fusion. In particular, in vivo formaldehyde cross-linking of whole HeLa cells and immunoprecipitation with purified Mfn2 antibodies of SDS cell lysates were used to detect an approximately 42-kDa protein. This protein was identified by liquid chromatography and tandem mass spectrometry as stomatin-like protein 2 (Stoml2), previously described as a peripheral plasma membrane protein of unknown function associated with the cytoskeleton of erythrocytes (Wang, Y., and Morrow, J. S. (2000) J. Biol. Chem. 275, 8062-8071). Immunoblot analysis with anti-Stoml2 antibodies showed that Stoml2 could be immunoprecipitated specifically with Mfn2 antibody either from formaldehyde-cross-linked and SDS-lysed cells or from cells lysed with digitonin. Subsequent immunocytochemistry and cell fractionation experiments fully supported the conclusion that Stoml2 is indeed a mitochondrial protein. Furthermore, demonstration of mitochondrial membrane potential-dependent import of Stoml2 accompanied by proteolytic processing, together with the results of sublocalization experiments, suggested that Stoml2 is associated with the inner mitochondrial membrane and faces the intermembrane space. Notably, formaldehyde cross-linking revealed a "ladder" of high molecular weight protein species, indicating the presence of high molecular weight Stoml2-Mfn2 hetero-oligomers. Knockdown of Stoml2 by the short interfering RNA approach showed a reduction of the mitochondrial membrane potential, without, however, any obvious changes in mitochondrial morphology.

Blood Proteins↗