Nematode and Arthropod Genomes Provide New Insights into the Evolution of Class 2 B1 GPCRs

Nematodes and arthropods are the most speciose animal groups and possess Class 2 B1 G-protein coupled receptors (GPCRs). Existing models of invertebrate Class 2 B1 GPCR evolution are mainly centered on Caenorhabditis elegans and Drosophila melanogaster and a few other nematode and arthropod representatives. The present study reevaluates the evolution of metazoan Class 2 B1 GPCRs and orthologues by exploring the receptors in several nematode and arthropod genomes and comparing them to the human receptors. Three novel receptor phylogenetic clusters were identified and designated cluster A, cluster B and PDF-R-related cluster. Clusters A and B were identified in several nematode and arthropod genomes but were absent from D. melanogaster and Culicidae genomes, whereas the majority of the members of the PDF-R-related cluster were from nematodes. Cluster A receptors were nematode and arthropod-specific but shared a conserved gene environment with human receptor loci. Cluster B members were orthologous to human GCGR, PTHR and Secretin members with which they probably shared a common origin. PDF-R and PDF-R related clusters were present in representatives of both nematodes and arthropods. The results of comparative analysis of GPCR evolution and diversity in protostomes confirm previous notions that C. elegans and D. melanogaster genomes are not good representatives of nematode and arthropod phyla. We hypothesize that at least four ancestral Class 2 B1 genes emerged early in the metazoan radiation, which after the protostome-deuterostome split underwent distinct selective pressures that resulted in duplication and deletion events that originated the current Class 2 B1 GPCRs in nematode and arthropod genomes.This work was supported by the Portuguese Foundation for Science and Technology (FCT) project PTDC/BIA-BCM/114395/2009, by the European Regional Development Fund through COMPETE and FCT under the project ‘‘PEst-C/MAR/LA0015/2011.’’ RCF is in receipt of an FCT grant (SFRH/BPD/89811/2012) and JCRC is supported by auxiliary research contract FCT Pluriannual funds attributed to CCMAR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Origin of Secretin Receptor Precedes the Advent of Tetrapoda: Evidence on the Separated Origins of Secretin and Orexin

At present, secretin and its receptor have only been identified in mammals, and the origin of this ligand-receptor pair in early vertebrates is unclear. In addition, the elusive similarities of secretin and orexin in terms of both structures and functions suggest a common ancestral origin early in the vertebrate lineage. In this article, with the cloning and functional characterization of secretin receptors from lungfish and X. laevis as well as frog (X. laevis and Rana rugulosa) secretins, we provide evidence that the secretin ligand-receptor pair has already diverged and become highly specific by the emergence of tetrapods. The secretin receptor-like sequence cloned from lungfish indicates that the secretin receptor was descended from a VPAC-like receptor prior the advent of sarcopterygians. To clarify the controversial relationship of secretin and orexin, orexin type-2 receptor was cloned from X. laevis. We demonstrated that, in frog, secretin and orexin could activate their mutual receptors, indicating their coordinated complementary role in mediating physiological processes in non-mammalian vertebrates. However, among the peptides in the secretin/glucagon superfamily, secretin was found to be the only peptide that could activate the orexin receptor. We therefore hypothesize that secretin and orexin are of different ancestral origins early in the vertebrate lineage

Reconstruction and analysis of genome-scale metabolic model of a photosynthetic bacterium

<p>Abstract</p> <p>Background</p> <p><it>Synechocystis </it>sp. PCC6803 is a cyanobacterium considered as a candidate photo-biological production platform - an attractive cell factory capable of using CO₂and light as carbon and energy source, respectively. In order to enable efficient use of metabolic potential of <it>Synechocystis </it>sp. PCC6803, it is of importance to develop tools for uncovering stoichiometric and regulatory principles in the <it>Synechocystis </it>metabolic network.</p> <p>Results</p> <p>We report the most comprehensive metabolic model of <it>Synechocystis </it>sp. PCC6803 available, <it>i</it>Syn669, which includes 882 reactions, associated with 669 genes, and 790 metabolites. The model includes a detailed biomass equation which encompasses elementary building blocks that are needed for cell growth, as well as a detailed stoichiometric representation of photosynthesis. We demonstrate applicability of <it>i</it>Syn669 for stoichiometric analysis by simulating three physiologically relevant growth conditions of <it>Synechocystis </it>sp. PCC6803, and through <it>in silico </it>metabolic engineering simulations that allowed identification of a set of gene knock-out candidates towards enhanced succinate production. Gene essentiality and hydrogen production potential have also been assessed. Furthermore, <it>i</it>Syn669 was used as a transcriptomic data integration scaffold and thereby we found metabolic hot-spots around which gene regulation is dominant during light-shifting growth regimes.</p> <p>Conclusions</p> <p><it>i</it>Syn669 provides a platform for facilitating the development of cyanobacteria as microbial cell factories.</p

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models

Sex differences in oncogenic mutational processes.

Sex differences have been observed in multiple facets of cancer epidemiology, treatment and biology, and in most cancers outside the sex organs. Efforts to link these clinical differences to specific molecular features have focused on somatic mutations within the coding regions of the genome. Here we report a pan-cancer analysis of sex differences in whole genomes of 1983 tumours of 28 subtypes as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. We both confirm the results of exome studies, and also uncover previously undescribed sex differences. These include sex-biases in coding and non-coding cancer drivers, mutation prevalence and strikingly, in mutational signatures related to underlying mutational processes. These results underline the pervasiveness of molecular sex differences and strengthen the call for increased consideration of sex in molecular cancer research

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe