Gene & Genome Duplication in Acanthamoeba Polyphaga Mimivirus

Gene duplication is key to molecular evolution in all three domains of life and may be the first step in the emergence of new gene function. It is a well recognized feature in large DNA viruses, but has not been studied extensively in the largest known virus to date, the recently discovered Acanthamoeba Polyphaga Mimivirus. Here we present a systematic analysis of gene and genome duplication events in the Mimivirus genome. We find that one third of the Mimivirus genes are related to at least one other gene in the Mimivirus genome, either through a large segmental genome duplication event that occurred in the more remote past, either through more recent gene duplication events, which often occur in tandem. This shows that gene and genome duplication played a major role in shaping the Mimivirus genome. Using multiple alignments together with remote homology detection methods based on Hidden Markov Model comparison, we assign putative functions to some of the paralogous gene families. We suggest that a large part of the duplicated Mimivirus gene families are likely to interfere with important host cell processes, such as transcription control, protein degradation, and cell regulatory processes. Our findings support the view that large DNA viruses are complex evolving organisms, possibly deeply rooted within the tree of life, and oppose the paradigm that viral evolution is dominated by lateral gene acquisition, at least in what concerns large DNA viruses

Phydbac "Gene Function Predictor" : a gene annotation tool based on genomic context analysis

BACKGROUND: The large amount of completely sequenced genomes allows genomic context analysis to predict reliable functional associations between prokaryotic proteins. Major methods rely on the fact that genes encoding physically interacting partners or members of shared metabolic pathways tend to be proximate on the genome, to evolve in a correlated manner and to be fused as a single sequence in another organism. RESULTS: The new "Gene Function Predictor", linked to the web server Phydbac proposes putative associations between Escherichia coli K-12 proteins derived from a combination of these methods. We show that associations made by this tool are more accurate than linkages found in the other established databases. Predicted assignments to GO categories, based on pre-existing functional annotations of associated proteins are also available. This new database currently holds 9,379 pairwise links at an expected success rate of at least 80%, the 6,466 functional predictions to GO terms derived from these links having a level of accuracy higher than 70%. CONCLUSION: The "Gene Function Predictor" is an automatic tool that aims to help biologists by providing them hypothetical functional predictions out of genomic context characteristics. The "Gene Function predictor" is available at

Determination of strongly overlapping signaling activity from microarray data

BACKGROUND: As numerous diseases involve errors in signal transduction, modern therapeutics often target proteins involved in cellular signaling. Interpretation of the activity of signaling pathways during disease development or therapeutic intervention would assist in drug development, design of therapy, and target identification. Microarrays provide a global measure of cellular response, however linking these responses to signaling pathways requires an analytic approach tuned to the underlying biology. An ongoing issue in pattern recognition in microarrays has been how to determine the number of patterns (or clusters) to use for data interpretation, and this is a critical issue as measures of statistical significance in gene ontology or pathways rely on proper separation of genes into groups. RESULTS: Here we introduce a method relying on gene annotation coupled to decompositional analysis of global gene expression data that allows us to estimate specific activity on strongly coupled signaling pathways and, in some cases, activity of specific signaling proteins. We demonstrate the technique using the Rosetta yeast deletion mutant data set, decompositional analysis by Bayesian Decomposition, and annotation analysis using ClutrFree. We determined from measurements of gene persistence in patterns across multiple potential dimensionalities that 15 basis vectors provides the correct dimensionality for interpreting the data. Using gene ontology and data on gene regulation in the Saccharomyces Genome Database, we identified the transcriptional signatures of several cellular processes in yeast, including cell wall creation, ribosomal disruption, chemical blocking of protein synthesis, and, criticially, individual signatures of the strongly coupled mating and filamentation pathways. CONCLUSION: This works demonstrates that microarray data can provide downstream indicators of pathway activity either through use of gene ontology or transcription factor databases. This can be used to investigate the specificity and success of targeted therapeutics as well as to elucidate signaling activity in normal and disease processes

metaP-Server: A Web-Based Metabolomics Data Analysis Tool

Metabolomics is an emerging field that is based on the quantitative measurement of as many small organic molecules occurring in a biological sample as possible. Due to recent technical advances, metabolomics can now be used widely as an analytical high-throughput technology in drug testing and epidemiological metabolome and genome wide association studies. Analogous to chip-based gene expression analyses, the enormous amount of data produced by modern kit-based metabolomics experiments poses new challenges regarding their biological interpretation in the context of various sample phenotypes. We developed metaP-server to facilitate data interpretation. metaP-server provides automated and standardized data analysis for quantitative metabolomics data, covering the following steps from data acquisition to biological interpretation: (i) data quality checks, (ii) estimation of reproducibility and batch effects, (iii) hypothesis tests for multiple categorical phenotypes, (iv) correlation tests for metric phenotypes, (v) optionally including all possible pairs of metabolite concentration ratios, (vi) principal component analysis (PCA), and (vii) mapping of metabolites onto colored KEGG pathway maps. Graphical output is clickable and cross-linked to sample and metabolite identifiers. Interactive coloring of PCA and bar plots by phenotype facilitates on-line data exploration. For users of commercial metabolomics kits, cross-references to the HMDB, LipidMaps, KEGG, PubChem, and CAS databases are provided. metaP-server is freely accessible at http://metabolomics.helmholtz-muenchen.de/metap2/

Bipolar disorders in the Arab world: a critical review

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111799/1/nyas12652.pd

Mimivirus and the emerging concept of "giant" virus

The recently discovered Acanthamoeba polyphaga Mimivirus is the largest known DNA virus. Its particle size (>400 nm), genome length (1.2 million bp) and large gene repertoire (911 protein coding genes) blur the established boundaries between viruses and parasitic cellular organisms. In addition, the analysis of its genome sequence identified new types of genes not expected to be seen in a virus, such as aminoacyl-tRNA synthetases and other central components of the translation machinery. In this article, we examine how the finding of a giant virus for the first time overlapping with the world of cellular organisms in terms of size and genome complexity might durably influence the way we look at microbial biodiversity, and force us to fundamentally revise our classification of life forms. We propose to introduce the word "girus" to recognize the intermediate status of these giant DNA viruses, the genome complexity of which make them closer to small parasitic prokaryotes than to regular viruses.Comment: Submitted to Virus Researc

Reductive Genome Evolution from the Mother of Rickettsia

The Rickettsia genus is a group of obligate intracellular α-proteobacteria representing a paradigm of reductive evolution. Here, we investigate the evolutionary processes that shaped the genomes of the genus. The reconstruction of ancestral genomes indicates that their last common ancestor contained more genes, but already possessed most traits associated with cellular parasitism. The differences in gene repertoires across modern Rickettsia are mainly the result of differential gene losses from the ancestor. We demonstrate using computer simulation that the propensity of loss was variable across genes during this process. We also analyzed the ratio of nonsynonymous to synonymous changes (Ka/Ks) calculated as an average over large sets of genes to assay the strength of selection acting on the genomes of Rickettsia, Anaplasmataceae, and free-living γ-proteobacteria. As a general trend, Ka/Ks were found to decrease with increasing divergence between genomes. The high Ka/Ks for closely related genomes are probably due to a lag in the removal of slightly deleterious nonsynonymous mutations by natural selection. Interestingly, we also observed a decrease of the rate of gene loss with increasing divergence, suggesting a similar lag in the removal of slightly deleterious pseudogene alleles. For larger divergence (Ks > 0.2), Ka/Ks converge toward similar values indicating that the levels of selection are roughly equivalent between intracellular α-proteobacteria and their free-living relatives. This contrasts with the view that obligate endocellular microorganisms tend to evolve faster as a consequence of reduced effectiveness of selection, and suggests a major role of enhanced background mutation rates on the fast protein divergence in the obligate intracellular α-proteobacteria

Mendelian inheritance of trimodal CpG methylation sites suggests distal cis-acting genetic effects.

Environmentally influenced phenotypes, such as obesity and insulin resistance, can be transmitted over multiple generations. Epigenetic modifications, such as methylation of DNA cytosine-guanine (CpG) pairs, may be carriers of inherited information. At the population level, the methylation state of such "heritable" CpG sites is expected to follow a trimodal distribution, and their mode of inheritance should be Mendelian. Using the Illumina Infinium 450 K DNA methylation array, we determined DNA CpG-methylation in blood cells from a family cohort 123 individuals of Arab ethnicity, including 18 elementary father-mother-child trios, we asked whether Mendelian inheritance of CpG methylation is observed, and most importantly, whether it is independent of any genetic signals. Using 40× whole genome sequencing, we therefore excluded all CpG sites with possibly confounding genetic variants (SNP) within the binding regions of the Illumina probes. We identified a total of 955 CpG sites that displayed a trimodal distribution and confirmed trimodality in a study of 1805 unrelated Caucasians. Of 955 CpG sites, 99.9% observed a strict Mendelian pattern of inheritance and had no SNP within +/-110 nucleotides of the CpG site by design. However, in 97% of these cases a distal cis-acting SNP within a +/-1 Mbp window was found that explained the observed CpG distribution, excluding the hypothesis of epigenetic inheritance for these clear-cut trimodal sites. Using power analysis, we showed that in 46% of all cases, the closest CpG-associated SNP was located more than 1000 bp from the CpG site. Our findings suggest that CpG methylation is maintained over larger genomic distances. Furthermore, nearly half of the SNPs associated with these trimodal sites were also associated with the expression of nearby genes (P = 4.08 × 10(-6)), implying a regulatory effect of these trimodal CpG sites

Effect of induced hypoglycemia on inflammation and oxidative stress in type 2 diabetes and control subjects

Intensive diabetes control has been associated with increased mortality in type 2 diabetes (T2DM); this has been suggested to be due to increased hypoglycemia. We measured hypoglycemia-induced changes in endothelial parameters, oxidative stress markers and inflammation at baseline and after a 24-hour period in type 2 diabetic (T2DM) subjects versus age-matched controls. Case-control study: 10 T2DM and 8 control subjects. Blood glucose was reduced from 5 (90 mg/dl) to hypoglycemic levels of 2.8 mmol/L (50 mg/dl) for 1 hour by incremental hyperinsulinemic clamps using baseline and 24 hour samples. Measures of endothelial parameters, oxidative stress and inflammation at baseline and at 24-hours post hypoglycemia were performed: proteomic (Somalogic) analysis for inflammatory markers complemented by C-reactive protein (hsCRP) measurement, and proteomic markers and urinary isoprostanes for oxidative measures, together with endothelial function. Between baseline and 24 -hours after hypoglycemia, 15 of 140 inflammatory proteins differed in T2DM whilst only 1 of 140 differed in controls; all returned to baseline at 24-hours. However, elevated hsCRP levels were seen at 24-hours in T2DM (2.4 mg/L (1.2–5.4) vs. 3.9 mg/L (1.8–6.1), Baseline vs 24-hours, P < 0.05). In patients with T2DM, between baseline and 24-hour after hypoglycemia, only one of 15 oxidative stress proteins differed and this was not seen in controls. An increase (P = 0.016) from baseline (73.4 ng/mL) to 24 hours after hypoglycemia (91.7 ng/mL) was seen for urinary isoprostanes. Hypoglycemia resulted in inflammatory and oxidative stress markers being elevated in T2DM subjects but not controls 24-hours after the event