Identification of lily pollen 14-3-3 isoforms and their subcellular and time-dependent expression profile.

14-3-3 proteins are major regulators in plant development and physiology including primary metabolism and signal transduction pathways, typically via a phosphorylation-dependent interaction with a target protein. Four full-length 14-3-3 isoforms were identified in pollen grains of Lilium longiflorum by screening of a cDNA library and RACE (rapid amplification of cDNA ends)-PCR. Mass spectrometry analysis of partially purified 14-3-3s confirmed the presence of the four isoforms but also indicated the presence of additional, less abundant 14-3-3 isoforms in lily pollen. Separation of partially purified 14-3-3 proteins by two-dimensional gel electrophoresis resulted in nine spots that mainly contained the four major 14-3-3 isoforms. In a first step to examine putative physiological roles of specific 14-3-3 isoforms, their subcellular expression profile during pollen germination and tube growth was monitored using a characterized set of antibodies against 14-3-3 proteins with distinct crossreactivity. The abundance profile of 14-3-3 proteins associated with the cytosol, endomembranes (tonoplast, endoplasmic reticulum, Golgi, mitochondria) and plasma membrane showed high spatial-temporal dynamics. This indicates different targets of 14-3-3 proteins at different organelles and time points during pollen germination and growth.

Hierarchical classification of gene ontology terms using the GOstruct method.

Protein function prediction is an active area of research in bioinformatics. Yet, the transfer of annotation on the basis of sequence or structural similarity remains widely used as an annotation method. Most of today's machine learning approaches reduce the problem to a collection of binary classification problems: whether a protein performs a particular function, sometimes with a post-processing step to combine the binary outputs. We propose a method that directly predicts a full functional annotation of a protein by modeling the structure of the Gene Ontology hierarchy in the framework of kernel methods for structured-output spaces. Our empirical results show improved performance over a BLAST nearest-neighbor method, and over algorithms that employ a collection of binary classifiers as measured on the Mousefunc benchmark dataset.

Numerous novel annotations of the human genome sequence supported by a 5'-end-enriched cDNA collection.

A collection of 90,000 human cDNA clones generated to increase the fraction of "full-length" cDNAs available was analyzed by sequence alignment on the human genome assembly. Five hundred fifty-two gene models not found in LocusLink, with coding regions of at least 300 bp, were defined by using this collection. Exon composition proposed for novel genes showed an average of 4.7 exons per gene. In 20% of the cases, at least half of the exons predicted for new genes coincided with evolutionary conserved regions defined by sequence comparisons with the pufferfish Tetraodon nigroviridis. Among this subset, CpG islands were observed at the 5' end of 75%. In-frame stop codons upstream of the initiator ATG were present in 49% of the new genes, and 16% contained a coding region comprising at least 50% of the cDNA sequence. This cDNA resource also provided candidate small protein-coding genes, usually not included in genome annotations. In addition, analysis of a sample from this cDNA collection indicates that approximately 380 gene models described in LocusLink could be extended at their 5' end by at least one new exon. Finally, this cDNA resource provided an experimental support for annotations based exclusively on predictions, thus representing a resource substantially improving the human genome annotation.

Molecular dissection of the 11S REG (PA28) proteasome activators.

The proteasome activators known as 11S REG or PA28 were discovered about 10 years ago. They are homo- or heteroheptameric rings that bind to the ends of 20S proteasomes and activate cleavage of peptides but not folded proteins. In this article, we focus on structural features of three homologous REG subunits (termed alpha, beta, gamma) that contribute to their oligomerization, proteasome binding and proteasome activation. We review a number of published studies on the biochemical properties of REGs and present new results in which N-terminal sequences and sequences flanking REG activation loops have been exchanged between homologs. Characterization of these chimeras and previously constructed C-terminal chimeras reveal that N-terminal and loop flanking sequences affect oligomerization, whereas C-terminal sequences are essential for proteasome binding. None of these regions is responsible for the broad activation specificity of REGs alpha/beta versus the narrow specificity of REGgamma. Rather, mutation in a single residue lining the channel through the REGgamma heptamer changes the activation property of the gamma homolog to match that of REGs alpha and beta.

Identification and sequencing of a cDNA encoding 6-phosphogluconate dehydrogenase from a fungus, Cunninghamella elegans and expression of the gene in Escherichia coli.

The fungus, Cunninghamella elegans has been widely used in bioremediation and microbial models of mammalian studies in many laboratories. Using the polymerase chain reaction to randomly amplify the insert directly from the single non-blue plaques of a C. elegans cDNA library, then partly sequencing and comparing with GenBank sequences, we have identified a clone which contains C. elegans 6-phosphogluconate dehydrogenase gene. The polymerase chain reaction product was cloned into a plasmid, pGEM-T Easy vector for full insert DNA sequencing. The 6-phosphogluconate dehydrogenase gene (1458 bases) and the deduced protein sequence were determined from the insert DNA sequence. The gene was found by open reading frame analysis and confirmed by the alignment of the deduced protein sequence with other published 6-phosphogluconate dehydrogenase sequences. Several highly conserved regions were found for the 6-phosphogluconate dehydrogenase sequences. The 6-phosphogluconate dehydrogenase gene was subcloned and over-expressed in a plasmid-E. coli system (pQE30). The cell lysate of this clone has a very high 6-phosphogluconate dehydrogenase enzyme activity. Most of the recombinant protein in this system was formed as insoluble inclusion bodies, but soluble in high concentration of urea-buffer. Ni-NTA resin was used to purify the recombinant protein which showed 6-phosphogluconate dehydrogenase enzyme activity. The recombinant protein has a predicted molecular size correlating with that revealed by sodium dodecylsulfate-polyacrylamide gel electrophoresis analysis. The C. elegans 6-phosphogluconate dehydrogenase was in a cluster with yeast' 6-phosphogluconate dehydrogenase in the phylogenetic tree. Bacterial 6-phosphogluconate dehydrogenase and higher organisms' 6-phosphogluconate dehydrogenase were found in different clusters.

Two highly related regulatory proteins, Shigella flexneri VirF and enterotoxigenic Escherichia coli Rns, have common and distinct regulatory properties.

The Rns protein of enterotoxigenic Escherichia coli (ETEC) and the VirF protein of Shigella flexneri are members of the AraC family of transcription regulators. Rns is required for positive activation of the CS1 fimbrial genes, while VirF is a positive regulator of an invasion gene regulon. The amino acid sequences of the proteins are 36% identical, and both proteins activate transcription in response to increases in temperature. Here, we show that Rns is capable of complementing fully a null mutation in the S. flexneri virF gene. However, the VirF protein cannot replace Rns as an activator of CS1 gene expression in ETEC. This failure is not due to the absence from ETEC of a co-factor required by VirF since it also occurs when the CS1 system is moved into an S. flexneri genetic background. Nor is it a function of growth medium composition or a failure in virF gene expression. Instead, these findings point to important differences in the mechanisms by which these related transcription factors regulate gene expression in Gram-negative pathogens.

A structure-based multiple sequence alignment of all class I aminoacyl-tRNA synthetases.

The superimposable dinucleotide fold domains of MetRS, GlnRS and TyrRS define structurally equivalent amino acids which have been used to constrain the sequence alignments of the 10 class I aminoacyl-tRNA synthetases (aaRS). The conservation of those residues which have been shown to be critical in some aaRS enables to predict their location and function in the other synthetases, particularly: i) a conserved negatively-charged residue which binds the alpha-amino group of the amino acid substrate; ii) conserved residues within the inserted domain bridging the two halves of the dinucleotide-binding fold; and iii) conserved residues in the second half of the fold which bind the amino acid and ATP substrate. The alignments also indicate that the class I synthetases may be partitioned into two subgroups: a) MetRS, IleRS, LeuRS, ValRS, CysRS and ArgRS; b) GlnRS, GluRS, TyrRS and TrpRS.

A comparison of several similarity indices used in the classification of protein sequences: a multivariate analysis.

The present work describes an attempt to identify reliable criteria which could be used as distance indices between protein sequences. Seven different criteria have been tested: i and ii) the scores of the alignments as given by the BESTFIT and the FASTA programs; iii) the ratio parameter, i.e. the BESTFIT score divided by the length of the aligned peptides; iv and v) the statistical significance (Z-scores) of the scores calculated by BESTFIT and FASTA, as obtained by comparison with shuffled sequences; vi) the Z-scores provided by the program RELATE which performs a segment-by-segment comparison of 2 sequences, and vii) an original distance index calculated by the program DOCMA from all the pairwise dotplots between the sequences. These 7 criteria have been tested against the aminoacid sequences of 39 globins and those of the 20 aminoacyl-tRNA synthetases from E. coli. The distances between the sequences were analyzed by the multivariate analysis techniques. The results show that the distances calculated from the scores of the pairwise alignments are not adequately sensitive. The Z-score from RELATE is not selective enough and too demanding in computer time. Three criteria gave a classification consistent with the known similarities between the sequences in the sets, namely the Z-scores from BESTFIT and FASTA and the multiple dotplot comparison distance index from DOCMA.