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Structure-guided identification of a new catalytic motif of oligosaccharyltransferase.

ABSTRACT: Asn-glycosylation is widespread not only in eukaryotes but also in archaea and some eubacteria. Oligosaccharyltransferase (OST) catalyzes the co-translational transfer of an oligosaccharide from a lipid donor to an asparagine residue in nascent polypeptide chains. Here, we report that a thermophilic archaeon, Pyrococcus furiosus OST is composed of the STT3 protein alone, and catalyzes the transfer of a heptasaccharide, containing one hexouronate and two pentose residues, onto peptides in an Asn-X-Thr/Ser-motif-dependent manner. We also determined the 2.7-A resolution crystal structure of the C-terminal soluble domain of Pyrococcus STT3. The structure-based multiple sequence alignment revealed a new motif, DxxK, which is adjacent to the well-conserved WWDYG motif in the tertiary structure. The mutagenesis of the DK motif residues in yeast STT3 revealed the essential role of the motif in the catalytic activity. The function of this motif may be related to the binding of the pyrophosphate group of lipid-linked oligosaccharide donors through a transiently bound cation. Our structure provides the first structural insights into the formation of the oligosaccharide-asparagine bond.

SUBMITTER: Igura M

PROVIDER: S-EPMC2206122 | biostudies-literature | 2008 Jan

REPOSITORIES: biostudies-literature

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Structure-guided identification of a new catalytic motif of oligosaccharyltransferase.

Igura Mayumi M Maita Nobuo N Kamishikiryo Jun J Yamada Masaki M Obita Takayuki T Maenaka Katsumi K Kohda Daisuke D

The EMBO journal 20071129 1

Asn-glycosylation is widespread not only in eukaryotes but also in archaea and some eubacteria. Oligosaccharyltransferase (OST) catalyzes the co-translational transfer of an oligosaccharide from a lipid donor to an asparagine residue in nascent polypeptide chains. Here, we report that a thermophilic archaeon, Pyrococcus furiosus OST is composed of the STT3 protein alone, and catalyzes the transfer of a heptasaccharide, containing one hexouronate and two pentose residues, onto peptides in an Asn- ...[more]

PMID: 18046457

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Project description:BackgroundGenes work coordinately as gene modules or gene networks. Various computational approaches have been proposed to find gene modules based on gene expression data; for example, gene clustering is a popular method for grouping genes with similar gene expression patterns. However, traditional gene clustering often yields unsatisfactory results for regulatory module identification because the resulting gene clusters are co-expressed but not necessarily co-regulated.ResultsWe propose a novel approach, motif-guided sparse decomposition (mSD), to identify gene regulatory modules by integrating gene expression data and DNA sequence motif information. The mSD approach is implemented as a two-step algorithm comprising estimates of (1) transcription factor activity and (2) the strength of the predicted gene regulation event(s). Specifically, a motif-guided clustering method is first developed to estimate the transcription factor activity of a gene module; sparse component analysis is then applied to estimate the regulation strength, and so predict the target genes of the transcription factors. The mSD approach was first tested for its improved performance in finding regulatory modules using simulated and real yeast data, revealing functionally distinct gene modules enriched with biologically validated transcription factors. We then demonstrated the efficacy of the mSD approach on breast cancer cell line data and uncovered several important gene regulatory modules related to endocrine therapy of breast cancer.ConclusionWe have developed a new integrated strategy, namely motif-guided sparse decomposition (mSD) of gene expression data, for regulatory module identification. The mSD method features a novel motif-guided clustering method for transcription factor activity estimation by finding a balance between co-regulation and co-expression. The mSD method further utilizes a sparse decomposition method for regulation strength estimation. The experimental results show that such a motif-guided strategy can provide context-specific regulatory modules in both yeast and breast cancer studies.

Dataset Information

Structure-guided identification of a new catalytic motif of oligosaccharyltransferase.

Publications

Structure-guided identification of a new catalytic motif of oligosaccharyltransferase.

Similar Datasets

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