Translational control of intron splicing in eukaryotes.

Most eukaryotic genes are interrupted by non-coding introns that must be accurately removed from pre-messenger RNAs to produce translatable mRNAs. Splicing is guided locally by short conserved sequences, but genes typically contain many potential splice sites, and the mechanisms specifying the correct sites remain poorly understood. In most organisms, short introns recognized by the intron definition mechanism cannot be efficiently predicted solely on the basis of sequence motifs. In multicellular eukaryotes, long introns are recognized through exon definition and most genes produce multiple mRNA variants through alternative splicing. The nonsense-mediated mRNA decay (NMD) pathway may further shape the observed sets of variants by selectively degrading those containing premature termination codons, which are frequently produced in mammals. Here we show that the tiny introns of the ciliate Paramecium tetraurelia are under strong selective pressure to cause premature termination of mRNA translation in the event of intron retention, and that the same bias is observed among the short introns of plants, fungi and animals. By knocking down the two P. tetraurelia genes encoding UPF1, a protein that is crucial in NMD, we show that the intrinsic efficiency of splicing varies widely among introns and that NMD activity can significantly reduce the fraction of unspliced mRNAs. The results suggest that, independently of alternative splicing, species with large intron numbers universally rely on NMD to compensate for suboptimal splicing efficiency and accuracy.

Global trends of whole-genome duplications revealed by the ciliate Paramecium tetraurelia.

The duplication of entire genomes has long been recognized as having great potential for evolutionary novelties, but the mechanisms underlying their resolution through gene loss are poorly understood. Here we show that in the unicellular eukaryote Paramecium tetraurelia, a ciliate, most of the nearly 40,000 genes arose through at least three successive whole-genome duplications. Phylogenetic analysis indicates that the most recent duplication coincides with an explosion of speciation events that gave rise to the P. aurelia complex of 15 sibling species. We observed that gene loss occurs over a long timescale, not as an initial massive event. Genes from the same metabolic pathway or protein complex have common patterns of gene loss, and highly expressed genes are over-retained after all duplications. The conclusion of this analysis is that many genes are maintained after whole-genome duplication not because of functional innovation but because of gene dosage constraints.

Core and panmetabolism in Escherichia coli.

Escherichia coli exhibits a wide range of lifestyles encompassing commensalism and various pathogenic behaviors which its highly dynamic genome contributes to develop. How environmental and host factors shape the genetic structure of E. coli strains remains, however, largely unknown. Following a previous study of E. coli genomic diversity, we investigated its diversity at the metabolic level by building and analyzing the genome-scale metabolic networks of 29 E. coli strains (8 commensal and 21 pathogenic strains, including 6 Shigella strains). Using a tailor-made reconstruction strategy, we significantly improved the completeness and accuracy of the metabolic networks over default automatic reconstruction processes. Among the 1,545 reactions forming E. coli panmetabolism, 885 reactions were common to all strains. This high proportion of core reactions (57%) was found to be in sharp contrast to the low proportion (13%) of core genes in the E. coli pangenome, suggesting less diversity of metabolic functions compared to that of all gene functions. Core reactions were significantly overrepresented among biosynthetic reactions compared to the more variable degradation processes. Differences between metabolic networks were found to follow E. coli phylogeny rather than pathogenic phenotypes, except for Shigella networks, which were significantly more distant from the others. This suggests that most metabolic changes in non-Shigella strains were not driven by their pathogenic phenotypes. Using a supervised method, we were yet able to identify small sets of reactions related to pathogenicity or commensalism. The quality of our reconstructed networks also makes them reliable bases for building metabolic models.

Genome-scale models of bacterial metabolism: reconstruction and applications.

Genome-scale metabolic models bridge the gap between genome-derived biochemical information and metabolic phenotypes in a principled manner, providing a solid interpretative framework for experimental data related to metabolic states, and enabling simple in silico experiments with whole-cell metabolism. Models have been reconstructed for almost 20 bacterial species, so far mainly through expert curation efforts integrating information from the literature with genome annotation. A wide variety of computational methods exploiting metabolic models have been developed and applied to bacteria, yielding valuable insights into bacterial metabolism and evolution, and providing a sound basis for computer-assisted design in metabolic engineering. Recent advances in computational systems biology and high-throughput experimental technologies pave the way for the systematic reconstruction of metabolic models from genomes of new species, and a corresponding expansion of the scope of their applications. In this review, we provide an introduction to the key ideas of metabolic modeling, survey the methods, and resources that enable model reconstruction and refinement, and chart applications to the investigation of global properties of metabolic systems, the interpretation of experimental results, and the re-engineering of their biochemical capabilities.

A complete collection of single-gene deletion mutants of Acinetobacter baylyi ADP1.

We have constructed a collection of single-gene deletion mutants for all dispensable genes of the soil bacterium Acinetobacter baylyi ADP1. A total of 2594 deletion mutants were obtained, whereas 499 (16%) were not, and are therefore candidate essential genes for life on minimal medium. This essentiality data set is 88% consistent with the Escherichia coli data set inferred from the Keio mutant collection profiled for growth on minimal medium, while 80% of the orthologous genes described as essential in Pseudomonas aeruginosa are also essential in ADP1. Several strategies were undertaken to investigate ADP1 metabolism by (1) searching for discrepancies between our essentiality data and current metabolic knowledge, (2) comparing this essentiality data set to those from other organisms, (3) systematic phenotyping of the mutant collection on a variety of carbon sources (quinate, 2-3 butanediol, glucose, etc.). This collection provides a new resource for the study of gene function by forward and reverse genetic approaches and constitutes a robust experimental data source for systems biology approaches.

Cyclone: java-based querying and computing with Pathway/Genome databases.

UNLABELLED: Cyclone aims at facilitating the use of BioCyc, a collection of Pathway/Genome Databases (PGDBs). Cyclone provides a fully extensible Java Object API to analyze and visualize these data. Cyclone can read and write PGDBs, and can write its own data in the CycloneML format. This format is automatically generated from the BioCyc ontology by Cyclone itself, ensuring continued compatibility. Cyclone objects can also be stored in a relational database CycloneDB. Queries can be written in SQL, and in an intuitive and concise object-oriented query language, Hibernate Query Language (HQL). In addition, Cyclone interfaces easily with Java software including the Eclipse IDE for HQL edition, the Jung API for graph algorithms or Cytoscape for graph visualization. AVAILABILITY: Cyclone is freely available under an open source license at: http://sourceforge.net/projects/nemo-cyclone. SUPPLEMENTARY INFORMATION: For download and installation instructions, tutorials, use cases and examples, see http://nemo-cyclone.sourceforge.net.

Model of interactions in biology and application to heterogeneous network in yeast.

A major challenge for bioinformatics and theoretical biology is to build and analyse a unified model of biological knowledge resulting from high-throughput experiment data. Former work analyzed heterogeneous data (protein-protein interactions, genetic regulation, metabolism, synexpression) by modelling them by graphs. These models are unable to represent the qualitative dynamics of the reactions or to model the n-ary interactions. Here, MIB, the Model of Interactions in Biology, a bipartite model of biological networks, is introduced, and its use for topological analysis of the heterogeneous network is presented. Heterogeneous loops and links between synexpression pattern and underlying molecular mechanisms are proposed.

Protein-interaction networks: from experiments to analysis.

Functional proteomics approaches aim to characterize comprehensively the function of gene products, and provide a first-level understanding of cellular mechanisms. Here, we review recent techniques for the construction and prediction of large-scale protein-interaction networks, with a particular emphasis on computational processing steps and comparative assessment of the reliability and completeness of the various approaches. We also discuss the use of protein-interaction network information in functional annotation and in the generation of higher-level biological hypotheses on pathways.

Bioinformatics of large-scale protein interaction networks.

We survey recent techniques for construction and prediction of large-scale protein interaction networks, focusing on computational processing steps. Special emphasis is placed on critical assessment of data completeness and reliability of the various approaches. Once built, protein interaction networks can be used for functional annotation or to generate higher-level biological hypotheses on pathways.

Iterative reconstruction of a global metabolic model of Acinetobacter baylyi ADP1 using high-throughput growth phenotype and gene essentiality data.

BACKGROUND: Genome-scale metabolic models are powerful tools to study global properties of metabolic networks. They provide a way to integrate various types of biological information in a single framework, providing a structured representation of available knowledge on the metabolism of the respective species. RESULTS: We reconstructed a constraint-based metabolic model of Acinetobacter baylyi ADP1, a soil bacterium of interest for environmental and biotechnological applications with large-spectrum biodegradation capabilities. Following initial reconstruction from genome annotation and the literature, we iteratively refined the model by comparing its predictions with the results of large-scale experiments: (1) high-throughput growth phenotypes of the wild-type strain on 190 distinct environments, (2) genome-wide gene essentialities from a knockout mutant library, and (3) large-scale growth phenotypes of all mutant strains on 8 minimal media. Out of 1412 predictions, 1262 were initially consistent with our experimental observations. Inconsistencies were systematically examined, leading in 65 cases to model corrections. The predictions of the final version of the model, which included three rounds of refinements, are consistent with the experimental results for (1) 91% of the wild-type growth phenotypes, (2) 94% of the gene essentiality results, and (3) 94% of the mutant growth phenotypes. To facilitate the exploitation of the metabolic model, we provide a web interface allowing online predictions and visualization of results on metabolic maps. CONCLUSION: The iterative reconstruction procedure led to significant model improvements, showing that genome-wide mutant phenotypes on several media can significantly facilitate the transition from genome annotation to a high-quality model.

The adaptive filter of the yeast galactose pathway.

In the yeast Saccharomyces cerevisiae, the interplay between galactose, Gal3p, Gal80p and Gal4p determines the transcriptional status of the genes required for galactose utilization. After an increase in galactose concentration, galactose molecules bind onto Gal3p. This event leads via Gal80p to the activation of Gal4p, which then induces GAL3 and GAL80 gene transcription. Here we propose a qualitative dynamical model, whereby these molecular interaction events represent the first two stages of a functional feedback loop that closes with the capture of activated Gal4p by newly synthesized Gal3p and Gal80p, decreasing transcriptional activation and creating again the protein complex that can bind incoming galactose molecules. Based on the differential time-scales of faster protein interactions versus slower biosynthetic steps, this feedback loop functions as a derivative filter where galactose is the input step signal, and released Gal4p is the output derivative signal. One advantage of such a derivative filter is that GAL genes are expressed in proportion to cellular requirements. Furthermore, this filter adaptively protects the cellular receptors from saturation by galactose, allowing cells to remain sensitive to variations in galactose concentrations rather than to absolute concentrations. Finally, this feedback loop, by allowing phosphorylation of some active Gal4p, may be essential to initiate the subsequent long-term response.

ASEtrap: a biological method for speeding up the exploration of spliceomes.

Alternative splicing (AS) of pre-messenger RNA is a major mechanism for generating protein diversity from a limited number of genes in higher eukaryotes, and it constitutes a central mode of genetic regulation. Thus, efficient methods are needed to systematically identify new AS events at a genomic scale across different tissues, stages of development, and physiological or pathological conditions in order to better understand gene expression. To fulfill this goal, we have designed the ASEtrap, which is a cloning procedure for producing AS libraries that is based on a single-stranded trap consisting of an ssDNA-binding protein. In this paper, we have applied our approach to the construction of an AS library and a Control library from human placenta. By analyzing 9226 and 9999 sequences of the AS and Control libraries, respectively, we show that internal AS events (events that can be identified by the sole resources provided by either the AS or the Control library) and the discovery rate of new AS events measured at early stages of sequencing were nine to 10 times higher in the former than in the latter. Moreover, by performing a search for new AS events within a group of 162 known drug target genes, we identified six new events in six genes, and we observed that they all were discovered exclusively through the AS library. Thus, it appears that ASEtrap has the potential to greatly facilitate the determination of the total complement of splice variants expressed in human, as well as other organisms.

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.

Whole genome sequence comparisons and "full-length" cDNA sequences: a combined approach to evaluate and improve Arabidopsis genome annotation.

To evaluate the existing annotation of the Arabidopsis genome further, we generated a collection of evolutionary conserved regions (ecores) between Arabidopsis and rice. The ecore analysis provides evidence that the gene catalog of Arabidopsis is not yet complete, and that a number of these annotations require re-examination. To improve the Arabidopsis genome annotation further, we used a novel "full-length" enriched cDNA collection prepared from several tissues. An additional 1931 genes were covered by new "full-length" cDNA sequences, raising the number of annotated genes with a corresponding "full-length" cDNA sequence to about 14,000. Detailed comparisons between these "full-length" cDNA sequences and annotated genes show that this resource is very helpful in determining the correct structure of genes, in particular, those not yet supported by "full-length" cDNAs. In addition, a total of 326 genomic regions not included previously in the Arabidopsis genome annotation were detected by this cDNA resource, providing clues for new gene discovery. Because, as expected, the two data sets only partially overlap, their combination produces very useful information for improving the Arabidopsis genome annotation.