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1.
Plant Cell ; 23(4): 1556-72, 2011 Apr.
Article in English | MEDLINE | ID: mdl-21487095

ABSTRACT

In the postgenomic era, accurate prediction tools are essential for identification of the proteomes of cell organelles. Prediction methods have been developed for peroxisome-targeted proteins in animals and fungi but are missing specifically for plants. For development of a predictor for plant proteins carrying peroxisome targeting signals type 1 (PTS1), we assembled more than 2500 homologous plant sequences, mainly from EST databases. We applied a discriminative machine learning approach to derive two different prediction methods, both of which showed high prediction accuracy and recognized specific targeting-enhancing patterns in the regions upstream of the PTS1 tripeptides. Upon application of these methods to the Arabidopsis thaliana genome, 392 gene models were predicted to be peroxisome targeted. These predictions were extensively tested in vivo, resulting in a high experimental verification rate of Arabidopsis proteins previously not known to be peroxisomal. The prediction methods were able to correctly infer novel PTS1 tripeptides, which even included novel residues. Twenty-three newly predicted PTS1 tripeptides were experimentally confirmed, and a high variability of the plant PTS1 motif was discovered. These prediction methods will be instrumental in identifying low-abundance and stress-inducible peroxisomal proteins and defining the entire peroxisomal proteome of Arabidopsis and agronomically important crop plants.


Subject(s)
Arabidopsis Proteins/metabolism , Arabidopsis/metabolism , Artificial Intelligence , Computational Biology/methods , Peroxisomes/metabolism , Protein Sorting Signals , Amino Acid Sequence , Arabidopsis/genetics , Arabidopsis Proteins/chemistry , Databases, Protein , Genome, Plant/genetics , Models, Biological , Molecular Sequence Data , Peptides , Protein Transport , Reproducibility of Results , Subcellular Fractions/metabolism
2.
J Bacteriol ; 188(8): 3063-72, 2006 Apr.
Article in English | MEDLINE | ID: mdl-16585766

ABSTRACT

The natural plasmid pBM19 carries the key mdh gene needed for the oxidation of methanol into formaldehyde by Bacillus methanolicus. Five more genes, glpX, fba, tkt, pfk, and rpe, with deduced roles in the cell primary metabolism, are also located on this plasmid. By using real-time PCR, we show that they are transcriptionally upregulated (6- to 40-fold) in cells utilizing methanol; a similar induction was shown for two chromosomal genes, hps and phi. These seven genes are involved in the fructose bisphosphate aldolase/sedoheptulose bisphosphatase variant of the ribulose monophosphate (RuMP) pathway for formaldehyde assimilation. Curing of pBM19 causes higher methanol tolerance and reduced formaldehyde tolerance, and the methanol tolerance is reversed to wild-type levels by reintroducing mdh. Thus, the RuMP pathway is needed to detoxify the formaldehyde produced by the methanol dehydrogenase-mediated conversion of methanol, and the in vivo transcription levels of mdh and the RuMP pathway genes reflect the methanol tolerance level of the cells. The transcriptional inducer of hps and phi genes is formaldehyde, and not methanol, and introduction of multiple copies of these two genes into B. methanolicus made the cells more tolerant of growth on high methanol concentrations. The recombinant strain also had a significantly higher specific growth rate on methanol than the wild type. While pBM19 is critical for growth on methanol and important for formaldehyde detoxification, the maintenance of this plasmid represents a burden for B. methanolicus when growing on mannitol. Our data contribute to a new and fundamental understanding of the regulation of B. methanolicus methylotrophy.


Subject(s)
Bacillus/genetics , Bacillus/metabolism , Gene Expression Regulation, Bacterial , Methanol/metabolism , Methanol/pharmacology , Plasmids/genetics , Alcohol Oxidoreductases/genetics , Anti-Bacterial Agents/metabolism , Anti-Bacterial Agents/pharmacology , Bacillus/drug effects , Bacillus/growth & development , Bacterial Proteins/genetics , Chromosomes, Bacterial/genetics , DNA, Bacterial/chemistry , DNA, Bacterial/genetics , Formaldehyde/metabolism , Formaldehyde/pharmacology , Fructose-Bisphosphate Aldolase/genetics , Gene Deletion , Genetic Complementation Test , Molecular Sequence Data , Phosphoric Monoester Hydrolases/genetics , RNA, Bacterial/analysis , RNA, Messenger/analysis , Reverse Transcriptase Polymerase Chain Reaction , Sequence Analysis, DNA
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