Biomedical subjects

Berend Snel

Publications and source records attributed to Berend Snel.

9 recordsLinked to original sources

PubMed2003

Systematic discovery of analogous enzymes in thiamin biosynthesis.

In all genome-sequencing projects completed to date, a considerable number of 'gaps' have been found in the biochemical pathways of the respective species. In many instances, missing enzymes are displaced by analogs, functionally equivalent proteins that have evolved independently and lack sequence and structural similarity. Here we fill such gaps by analyzing anticorrelating occurrences of genes across species. Our approach, applied to the thiamin biosynthesis pathway comprising approximately 15 catalytic steps, predicts seven instances in which known enzymes have been displaced by analogous proteins. So far we have verified four predictions by genetic complementation, including three proteins for which there was no previous experimental evidence of a role in the thiamin biosynthesis pathway. For one hypothetical protein, biochemical characterization confirmed the predicted thiamin phosphate synthase (ThiE) activity. The results demonstrate the ability of our computational approach to predict specific functions without taking into account sequence similarity.

Alkyl and Aryl Transferases↗

PubMed2003

STRING: a database of predicted functional associations between proteins.

Functional links between proteins can often be inferred from genomic associations between the genes that encode them: groups of genes that are required for the same function tend to show similar species coverage, are often located in close proximity on the genome (in prokaryotes), and tend to be involved in gene-fusion events. The database STRING is a precomputed global resource for the exploration and analysis of these associations. Since the three types of evidence differ conceptually, and the number of predicted interactions is very large, it is essential to be able to assess and compare the significance of individual predictions. Thus, STRING contains a unique scoring-framework based on benchmarks of the different types of associations against a common reference set, integrated in a single confidence score per prediction. The graphical representation of the network of inferred, weighted protein interactions provides a high-level view of functional linkage, facilitating the analysis of modularity in biological processes. STRING is updated continuously, and currently contains 261 033 orthologs in 89 fully sequenced genomes. The database predicts functional interactions at an expected level of accuracy of at least 80% for more than half of the genes; it is online at http://www.bork.embl-heidelberg.de/STRING/.

Algorithms↗

PubMed2003

Predicting gene function by conserved co-expression.

We show that gene co-expression, which generally provides only a very weak signal for the prediction of functional interactions, can provide a reliable signal by exploiting evolutionary conservation. The encoded proteins of conserved co-expressed gene pairs are highly likely to be part of the same pathway not only after speciation (98%), but also after parallel gene duplication (97%). Conserved co-expression combined with homology data enables us to predict specific gene functions. The use of conservation between parallel duplicated gene pairs to predict function is especially promising given that gene duplication is common in eukaryotes, and that data from only a single organism can be used.

Animals↗

PubMed2003

Function prediction and protein networks.

In the genomics era, the interactions between proteins are at the center of attention. Genomic-context methods used to predict these interactions have been put on a quantitative basis, revealing that they are at least on an equal footing with genomics experimental data. A survey of experimentally confirmed predictions proves the applicability of these methods, and new concepts to predict protein interactions in eukaryotes have been described. Finally, the interaction networks that can be obtained by combining the predicted pair-wise interactions have enough internal structure to detect higher levels of organization, such as 'functional modules'.

Animals↗

PubMed2002

The genome sequence of Bifidobacterium longum reflects its adaptation to the human gastrointestinal tract.

Bifidobacteria are Gram-positive prokaryotes that naturally colonize the human gastrointestinal tract (GIT) and vagina. Although not numerically dominant in the complex intestinal microflora, they are considered as key commensals that promote a healthy GIT. We determined the 2.26-Mb genome sequence of an infant-derived strain of Bifidobacterium longum, and identified 1,730 possible coding sequences organized in a 60%-GC circular chromosome. Bioinformatic analysis revealed several physiological traits that could partially explain the successful adaptation of this bacteria to the colon. An unexpectedly large number of the predicted proteins appeared to be specialized for catabolism of a variety of oligosaccharides, some possibly released by rare or novel glycosyl hydrolases acting on "nondigestible" plant polymers or host-derived glycoproteins and glycoconjugates. This ability to scavenge from a large variety of nutrients likely contributes to the competitiveness and persistence of bifidobacteria in the colon. Many genes for oligosaccharide metabolism were found in self-regulated modules that appear to have arisen in part from gene duplication or horizontal acquisition. Complete pathways for all amino acids, nucleotides, and some key vitamins were identified; however, routes for Asp and Cys were atypical. More importantly, genome analysis provided insights into the reciprocal interactions of bifidobacteria with their hosts. We identified polypeptides that showed homology to most major proteins needed for production of glycoprotein-binding fimbriae, structures that could possibly be important for adhesion and persistence in the GIT. We also found a eukaryotic-type serine protease inhibitor (serpin) possibly involved in the reported immunomodulatory activity of bifidobacteria.

Adaptation, Physiological↗

PubMed2002

Comparative assessment of large-scale data sets of protein-protein interactions.

Comprehensive protein protein interaction maps promise to reveal many aspects of the complex regulatory network underlying cellular function. Recently, large-scale approaches have predicted many new protein interactions in yeast. To measure their accuracy and potential as well as to identify biases, strengths and weaknesses, we compare the methods with each other and with a reference set of previously reported protein interactions.

Bias↗

PubMed2002

The identification of functional modules from the genomic association of genes.

By combining the pairwise interactions between proteins, as predicted by the conserved co-occurrence of their genes in operons, we obtain protein interaction networks. Here we study the properties of such networks to identify functional modules: sets of proteins that together are involved in a biological process. The complete network contains 3,033 orthologous groups of proteins in 38 genomes. It consists of one giant component, containing 1,611 orthologous groups, and of 516 small disjointed clusters that, on average, contain only 2.7 orthologous groups. These small clusters have a homogeneous functional composition and thus represent functional modules in themselves. Analysis of the giant component reveals that it is a scale-free, small-world network with a high degree of local clustering (C = 0.6). It consists of locally highly connected subclusters that are connected to each other by linker proteins. The linker proteins tend to have multiple functions, or are involved in multiple processes and have an above average probability of being essential. By splitting up the giant component at these linker proteins, we identify 265 subclusters that tend to have a homogeneous functional composition. The rare functional inhomogeneities in our subclusters reflect the mixing of different types of (molecular) functions in a single cellular process, exemplified by subclusters containing both metabolic enzymes as well as the transcription factors that regulate them. Comparative genome analysis, thus, allows identification of a level of functional interaction between that of pairwise interactions, and of the complete genome.

Animals↗

PubMed2002

SHOT: a web server for the construction of genome phylogenies.

With the increasing availability of genome sequences, new methods are being proposed that exploit information from complete genomes to classify species in a phylogeny. Here we present SHOT, a web server for the classification of genomes on the basis of shared gene content or the conservation of gene order that reflects the dominant, phylogenetic signal in these genomic properties. In general, the genome trees are consistent with classical gene-based phylogenies, although some interesting exceptions indicate massive horizontal gene transfer. SHOT is a useful tool for analysing the tree of life from a genomic point of view. It is available at http://www.Bork.EMBL-Heidelberg.de/SHOT.

Animals↗

PubMed2002

Genomes in flux: the evolution of archaeal and proteobacterial gene content.

In the course of evolution, genomes are shaped by processes like gene loss, gene duplication, horizontal gene transfer, and gene genesis (the de novo origin of genes). Here we reconstruct the gene content of ancestral Archaea and Proteobacteria and quantify the processes connecting them to their present day representatives based on the distribution of genes in completely sequenced genomes. We estimate that the ancestor of the Proteobacteria contained around 2500 genes, and the ancestor of the Archaea around 2050 genes. Although it is necessary to invoke horizontal gene transfer to explain the content of present day genomes, gene loss, gene genesis, and simple vertical inheritance are quantitatively the most dominant processes in shaping the genome. Together they result in a turnover of gene content such that even the lineage leading from the ancestor of the Proteobacteria to the relatively large genome of Escherichia coli has lost at least 950 genes. Gene loss, unlike the other processes, correlates fairly well with time. This clock-like behavior suggests that gene loss is under negative selection, while the processes that add genes are under positive selection.

Amino Acid Substitution↗