Dataset Information

Prediction and analysis of protein hydroxyproline and hydroxylysine.

ABSTRACT:

Background

Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.

Methodology/principal findings

In this study, we developed a novel sequence-based method for identifying the two main types of hydroxylation sites--hydroxyproline and hydroxylysine. First, feature selection was made on three kinds of features consisting of amino acid indices (AAindex) which includes various physicochemical properties and biochemical properties of amino acids, Position-Specific Scoring Matrices (PSSM) which represent evolution information of amino acids and structural disorder of amino acids in the sliding window with length of 13 amino acids, then the prediction model were built using incremental feature selection method. As a result, the prediction accuracies are 76.0% and 82.1%, evaluated by jackknife cross-validation on the hydroxyproline dataset and hydroxylysine dataset, respectively. Feature analysis suggested that physicochemical properties and biochemical properties and evolution information of amino acids contribute much to the identification of the protein hydroxylation sites, while structural disorder had little relation to protein hydroxylation. It was also found that the amino acid adjacent to the hydroxylation site tends to exert more influence than other sites on hydroxylation determination.

Conclusions/significance

These findings may provide useful insights for exploiting the mechanisms of hydroxylation.

SUBMITTER: Hu LL

PROVIDER: S-EPMC3013141 | biostudies-literature | 2010 Dec

REPOSITORIES: biostudies-literature

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Publications

Prediction and analysis of protein hydroxyproline and hydroxylysine.

Hu Le-Le LL Niu Shen S Huang Tao T Wang Kai K Shi Xiao-He XH Cai Yu-Dong YD

PloS one 20101231 12

<h4>Background</h4>Hydroxylation is an important post-translational modification and closely related to various diseases. Besides the biotechnology experiments, in silico prediction methods are alternative ways to identify the potential hydroxylation sites.<h4>Methodology/principal findings</h4>In this study, we developed a novel sequence-based method for identifying the two main types of hydroxylation sites--hydroxyproline and hydroxylysine. First, feature selection was made on three kinds of f ...[more]

PMID: 21209839

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Project description:BackgroundArabinogalactan-proteins (AGPs) are structurally complex hydroxyproline-rich cell wall glycoproteins ubiquitous in the plant kingdom. AGPs biosynthesis involves a series of post-translational modifications including the addition of type II arabinogalactans to non-contiguous Hyp residues. To date, eight Hyp-galactosyltransferases (Hyp-GALTs; GALT2-GALT9) belonging to CAZy GT31, are known to catalyze the addition of the first galactose residues to AGP protein backbones and enable subsequent AGP glycosylation. The extent of genetic redundancy, however, remains to be elucidated for the Hyp-GALT gene family.ResultsTo examine their gene redundancy and functions, we generated various multiple gene knock-outs, including a triple mutant (galt5 galt8 galt9), two quadruple mutants (galt2 galt5 galt7 galt8, galt2 galt5 galt7 galt9), and one quintuple mutant (galt2 galt5 galt7 galt8 galt9), and comprehensively examined their biochemical and physiological phenotypes. The key findings include: AGP precipitations with β-Yariv reagent showed that GALT2, GALT5, GALT7, GALT8 and GALT9 act redundantly with respect to AGP glycosylation in cauline and rosette leaves, while the activity of GALT7, GALT8 and GALT9 dominate in the stem, silique and flowers. Monosaccharide composition analysis showed that galactose was decreased in the silique and root AGPs of the Hyp-GALT mutants. TEM analysis of 25789 quintuple mutant stems indicated cell wall defects coincident with the observed developmental and growth impairment in these Hyp-GALT mutants. Correlated with expression patterns, galt2, galt5, galt7, galt8, and galt9 display equal additive effects on insensitivity to β-Yariv-induced growth inhibition, silique length, plant height, and pollen viability. Interestingly, galt7, galt8, and galt9 contributed more to primary root growth and root tip swelling under salt stress, whereas galt2 and galt5 played more important roles in seed morphology, germination defects and seed set. Pollen defects likely contributed to the reduced seed set in these mutants.ConclusionAdditive and pleiotropic effects of GALT2, GALT5, GALT7, GALT8 and GALT9 on vegetative and reproductive growth phenotypes were teased apart via generation of different combinations of Hyp-GALT knock-out mutants. Taken together, the generation of higher order Hyp-GALT mutants demonstrate the functional importance of AG polysaccharides decorating the AGPs with respect to various aspects of plant growth and development.

Project description:BackgroundHydroxyproline-rich glycoproteins (HRGPs) constitute a plant cell wall protein superfamily that functions in diverse aspects of growth and development. This superfamily contains three members: the highly glycosylated arabinogalactan-proteins (AGPs), the moderately glycosylated extensins (EXTs), and the lightly glycosylated proline-rich proteins (PRPs). Chimeric and hybrid HRGPs, however, also exist. A bioinformatics approach is employed here to identify and classify AGPs, EXTs, PRPs, chimeric HRGPs, and hybrid HRGPs from the proteins predicted by the completed genome sequence of poplar (Populus trichocarpa). This bioinformatics approach is based on searching for biased amino acid compositions and for particular protein motifs associated with known HRGPs with a newly revised and improved BIO OHIO 2.0 program. Proteins detected by the program are subsequently analyzed to identify the following: 1) repeating amino acid sequences, 2) signal peptide sequences, 3) glycosylphosphatidylinositol lipid anchor addition sequences, and 4) similar HRGPs using the Basic Local Alignment Search Tool (BLAST).ResultsThe program was used to identify and classify 271 HRGPs from poplar including 162 AGPs, 60 EXTs, and 49 PRPs, which are each divided into various classes. This is in contrast to a previous analysis of the Arabidopsis proteome which identified 162 HRGPs consisting of 85 AGPs, 59 EXTs, and 18 PRPs. Poplar was observed to have fewer classical EXTs, to have more fasciclin-like AGPs, plastocyanin AGPs and AG peptides, and to contain a novel class of PRPs referred to as the proline-rich peptides.ConclusionsThe newly revised and improved BIO OHIO 2.0 bioinformatics program was used to identify and classify the inventory of HRGPs in poplar in order to facilitate and guide basic and applied research on plant cell walls. The newly identified poplar HRGPs can now be examined to determine their respective structural and functional roles, including their possible applications in the areas plant biofuel and natural products for medicinal or industrial uses. Additionally, other plants whose genomes are sequenced can now be examined in a similar way using this bioinformatics program which will provide insight to the evolution of the HRGP family in the plant kingdom.

Dataset Information

Prediction and analysis of protein hydroxyproline and hydroxylysine.

Background

Methodology/principal findings

Conclusions/significance

Publications

Prediction and analysis of protein hydroxyproline and hydroxylysine.

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