Martijn A. Huynen

Conservation of gene order: a fingerprint of proteins that physically interact

A systematic comparison of nine bacterial and archaeal genomes reveals a low level of gene-order (and operon architecture) conservation. Nevertheless, a number of gene pairs are conserved. The proteins encoded by conserved gene pairs appear to interact physically. This observation can therefore be used to predict functions of, and interactions between, prokaryotic gene products.

STRING: known and predicted protein–protein associations, integrated and transferred across organisms

A full description of a proteins function requires knowledge of all partner proteins with which it specifically associates. From a functional perspective, ‘association’ can mean direct physical binding, but can also mean indirect interaction such as participation in the same metabolic pathway or cellular process. Currently, information about protein association is scattered over a wide variety of resources and model organisms. STRING aims to simplify access to this information by providing a comprehensive, yet quality-controlled collection of protein–protein associations for a large number of organisms. The associations are derived from high-throughput experimental data, from the mining of databases and literature, and from predictions based on genomic context analysis. STRING integrates and ranks these associations by benchmarking them against a common reference set, and presents evidence in a consistent and intuitive web interface. Importantly, the associations are extended beyond the organism in which they were originally described, by automatic transfer to orthologous protein pairs in other organisms, where applicable. STRING currently holds 730 000 proteins in 180 fully sequenced organisms, and is available at http://string.embl.de/.

Deciphering the evolution and metabolism of an anammox bacterium from a community genome

Anaerobic ammonium oxidation (anammox) has become a main focus in oceanography and wastewater treatment. It is also the nitrogen cycles major remaining biochemical enigma. Among its features, the occurrence of hydrazine as a free intermediate of catabolism, the biosynthesis of ladderane lipids and the role of cytoplasm differentiation are unique in biology. Here we use environmental genomics—the reconstruction of genomic data directly from the environment—to assemble the genome of the uncultured anammox bacterium Kuenenia stuttgartiensis from a complex bioreactor community. The genome data illuminate the evolutionary history of the Planctomycetes and allow us to expose the genetic blueprint of the organisms special properties. Most significantly, we identified candidate genes responsible for ladderane biosynthesis and biological hydrazine metabolism, and discovered unexpected metabolic versatility.

Genome phylogeny based on gene content

Species phylogenies derived from comparisons of single genes are rarely consistent with each other, due to horizontal gene transfer, unrecognized paralogy and highly variable rates of evolution. The advent of completely sequenced genomes allows the construction of a phylogeny that is less sensitive to such inconsistencies and more representative of whole-genomes than are single-gene trees. Here, we present a distance-based phylogeny constructed on the basis of gene content, rather than on sequence identity, of 13 completely sequenced genomes of unicellular species. The similarity between two species is defined as the number of genes that they have in common divided by their total number of genes. In this type of phylogenetic analysis, evolutionary distance can be interpreted in terms of evolutionary events such as the acquisition and loss of genes, whereas the underlying properties (the gene content) can be interpreted in terms of function. As such, it takes a position intermediate to phylogenies based on single genes and phylogenies based on phenotypic characteristics. Although our comprehensive genome phylogeny is independent of phylogenies based on the level of sequence identity of individual genes, it correlates with the standard reference of prokarytic phylogeny based on sequence similarity of 16s rRNA (ref. 4). Thus, shared gene content between genomes is quantitatively determined by phylogeny, rather than by phenotype, and horizontal gene transfer has only a limited role in determining the gene content of genomes.

Neutral evolution of mutational robustness.

We introduce and analyze a general model of a population evolving over a network of selectively neutral genotypes. We show that the populations limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the networks adjacency matrix. Moreover, the average number of neutral mutant neighbors per individual is given by the matrix spectral radius. These results quantify the extent to which populations evolve mutational robustness-the insensitivity of the phenotype to mutations-and thus reduce genetic load. Because the average neutrality is independent of evolutionary parameters-such as mutation rate, population size, and selective advantage-one can infer global statistics of neutral network topology by using simple population data available from in vitro or in vivo evolution. Populations evolving on neutral networks of RNA secondary structures show excellent agreement with our theoretical predictions.

Predicting disease genes using protein–protein interactions

Background: The responsible genes have not yet been identified for many genetically mapped disease loci. Physically interacting proteins tend to be involved in the same cellular process, and mutations in their genes may lead to similar disease phenotypes. Objective: To investigate whether protein–protein interactions can predict genes for genetically heterogeneous diseases. Methods: 72 940 protein–protein interactions between 10 894 human proteins were used to search 432 loci for candidate disease genes representing 383 genetically heterogeneous hereditary diseases. For each disease, the protein interaction partners of its known causative genes were compared with the disease associated loci lacking identified causative genes. Interaction partners located within such loci were considered candidate disease gene predictions. Prediction accuracy was tested using a benchmark set of known disease genes. Results: Almost 300 candidate disease gene predictions were made. Some of these have since been confirmed. On average, 10% or more are expected to be genuine disease genes, representing a 10-fold enrichment compared with positional information only. Examples of interesting candidates are AKAP6 for arrythmogenic right ventricular dysplasia 3 and SYN3 for familial partial epilepsy with variable foci. Conclusions: Exploiting protein–protein interactions can greatly increase the likelihood of finding positional candidate disease genes. When applied on a large scale they can lead to novel candidate gene predictions.

POMT2 mutations cause alpha-dystroglycan hypoglycosylation and Walker-Warburg syndrome

Background: Walker-Warburg syndrome (WWS) is an autosomal recessive condition characterised by congenital muscular dystrophy, structural brain defects, and eye malformations. Typical brain abnormalities are hydrocephalus, lissencephaly, agenesis of the corpus callosum, fusion of the hemispheres, cerebellar hypoplasia, and neuronal overmigration, which causes a cobblestone cortex. Ocular abnormalities include cataract, microphthalmia, buphthalmos, and Peters anomaly. WWS patients show defective O-glycosylation of α-dystroglycan (α-DG), which plays a key role in bridging the cytoskeleton of muscle and CNS cells with extracellular matrix proteins, important for muscle integrity and neuronal migration. In 20% of the WWS patients, hypoglycosylation results from mutations in either the protein O-mannosyltransferase 1 (POMT1), fukutin, or fukutin related protein (FKRP) genes. The other genes for this highly heterogeneous disorder remain to be identified. Objective: To look for mutations in POMT2 as a cause of WWS, as both POMT1 and POMT2 are required to achieve protein O-mannosyltransferase activity. Methods: A candidate gene approach combined with homozygosity mapping. Results: Homozygosity was found for the POMT2 locus at 14q24.3 in four of 11 consanguineous WWS families. Homozygous POMT2 mutations were present in two of these families as well as in one patient from another cohort of six WWS families. Immunohistochemistry in muscle showed severely reduced levels of glycosylated α-DG, which is consistent with the postulated role for POMT2 in the O-mannosylation pathway. Conclusions: A fourth causative gene for WWS was uncovered. These genes account for approximately one third of the WWS cases. Several more genes are anticipated, which are likely to play a role in glycosylation of α-DG.

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.

An anaerobic mitochondrion that produces hydrogen.

Hydrogenosomes are organelles that produce ATP and hydrogen, and are found in various unrelated eukaryotes, such as anaerobic flagellates, chytridiomycete fungi and ciliates. Although all of these organelles generate hydrogen, the hydrogenosomes from these organisms are structurally and metabolically quite different, just like mitochondria where large differences also exist. These differences have led to a continuing debate about the evolutionary origin of hydrogenosomes. Here we show that the hydrogenosomes of the anaerobic ciliate Nyctotherus ovalis, which thrives in the hindgut of cockroaches, have retained a rudimentary genome encoding components of a mitochondrial electron transport chain. Phylogenetic analyses reveal that those proteins cluster with their homologues from aerobic ciliates. In addition, several nucleus-encoded components of the mitochondrial proteome, such as pyruvate dehydrogenase and complex II, were identified. The N. ovalis hydrogenosome is sensitive to inhibitors of mitochondrial complex I and produces succinate as a major metabolic end product—biochemical traits typical of anaerobic mitochondria. The production of hydrogen, together with the presence of a genome encoding respiratory chain components, and biochemical features characteristic of anaerobic mitochondria, identify the N. ovalis organelle as a missing link between mitochondria and hydrogenosomes.

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.