Biomedical subjects

Sébastien Rey

Publications and source records attributed to Sébastien Rey.

3 recordsLinked to original sources

PubMed2006

Photochemistry of peroxoborates: borate inhibition of the photodecomposition of hydrogen peroxide.

The UV absorbance and photochemical decomposition kinetics of hydrogen peroxide in borate/boric acid buffers were investigated as a function of pH, total peroxide concentration, and total boron concentration. At higher pH borate/boric acid inhibits the photodecomposition of hydrogen peroxide (molar absorptivity and quantum yield of H(2)O(2) and HO(2) (-), (19.0+/-0.3) M(-1) cm(-1) and 1, and (237+/-7) M(-1) cm(-1) and 0.8+/-0.1, respectively). The results are consistent with the equilibrium formation of the anions monoperoxoborate, K(BOOH)=[H(+)][HOOB(OH)(3) (-)]/([B(OH)(3)][H(2)O(2)]), 2.0 x 10(-8), R. Pizer, C. Tihal, Inorg. Chem. 1987, 26, 3639-3642, and monoperoxodiborate, K(BOOB)=[BOOB(2-)]/([B(OH)(4) (-)][HOOB(OH)(3) (-)]), 1.0+/-0.3 or 4.3+/-0.9, depending upon the conditions, with molar absorptivity, (19+/-1) M(-1) cm(-1) and (86+/-15) M(-1) cm(-1), respectively, and respective quantum yields, 1.1+/-0.1 and 0.04+/-0.04. The low quantum yield of monoperoxodiborate is discussed in terms of the slower diffusion apart of incipient (.)OB(OH)(3) (-) radicals than may be possible for (.)OH radicals, or a possible oxygen-bridged cyclic structure of the monoperoxodiborate.

Journal Article↗

PubMed2005

Assessing the precision of high-throughput computational and laboratory approaches for the genome-wide identification of protein subcellular localization in bacteria.

BACKGROUND: Identification of a bacterial protein's subcellular localization (SCL) is important for genome annotation, function prediction and drug or vaccine target identification. Subcellular fractionation techniques combined with recent proteomics technology permits the identification of large numbers of proteins from distinct bacterial compartments. However, the fractionation of a complex structure like the cell into several subcellular compartments is not a trivial task. Contamination from other compartments may occur, and some proteins may reside in multiple localizations. New computational methods have been reported over the past few years that now permit much more accurate, genome-wide analysis of the SCL of protein sequences deduced from genomes. There is a need to compare such computational methods with laboratory proteomics approaches to identify the most effective current approach for genome-wide localization characterization and annotation. RESULTS: In this study, ten subcellular proteome analyses of bacterial compartments were reviewed. PSORTb version 2.0 was used to computationally predict the localization of proteins reported in these publications, and these computational predictions were then compared to the localizations determined by the proteomics study. By using a combined approach, we were able to identify a number of contaminants and proteins with dual localizations, and were able to more accurately identify membrane subproteomes. Our results allowed us to estimate the precision level of laboratory subproteome studies and we show here that, on average, recent high-precision computational methods such as PSORTb now have a lower error rate than laboratory methods. CONCLUSION: We have performed the first focused comparison of genome-wide proteomic and computational methods for subcellular localization identification, and show that computational methods have now attained a level of precision that is exceeding that of high-throughput laboratory approaches. We note that analysis of all cellular fractions collectively is required to effectively provide localization information from laboratory studies, and we propose an overall approach to genome-wide subcellular localization characterization that capitalizes on the complementary nature of current laboratory and computational methods.

Bacterial Proteins↗

PubMed2005

PSORTdb: a protein subcellular localization database for bacteria.

Information about bacterial subcellular localization (SCL) is important for protein function prediction and identification of suitable drug/vaccine/diagnostic targets. PSORTdb (http://db.psort.org/) is a web-accessible database of SCL for bacteria that contains both information determined through laboratory experimentation and computational predictions. The dataset of experimentally verified information (approximately 2000 proteins) was manually curated by us and represents the largest dataset of its kind. Earlier versions have been used for training SCL predictors, and its incorporation now into this new PSORTdb resource, with its associated additional annotation information and dataset version control, should aid researchers in future development of improved SCL predictors. The second component of this database contains computational analyses of proteins deduced from the most recent NCBI dataset of completely sequenced genomes. Analyses are currently calculated using PSORTb, the most precise automated SCL predictor for bacterial proteins. Both datasets can be accessed through the web using a very flexible text search engine, a data browser, or using BLAST, and the entire database or search results may be downloaded in various formats. Features such as GO ontologies and multiple accession numbers are incorporated to facilitate integration with other bioinformatics resources. PSORTdb is freely available under GNU General Public License.

Bacterial Proteins↗