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Journal ArticleDOI

The origin of GPCRs: identification of mammalian like Rhodopsin, Adhesion, Glutamate and Frizzled GPCRs in fungi.

04 Jan 2012-PLOS ONE (Public Library of Science)-Vol. 7, Iss: 1
TL;DR: This study provides the first evidence of the presence of four of the five main GRAFS families in Fungi and clarifies the early evolutionary history of the GPCR superfamily.
Abstract: G protein-coupled receptors (GPCRs) in humans are classified into the five main families named Glutamate, Rhodopsin, Adhesion, Frizzled and Secretin according to the GRAFS classification. Previous results show that these mammalian GRAFS families are well represented in the Metazoan lineages, but they have not been shown to be present in Fungi. Here, we systematically mined 79 fungal genomes and provide the first evidence that four of the five main mammalian families of GPCRs, namely Rhodopsin, Adhesion, Glutamate and Frizzled, are present in Fungi and found 142 novel sequences between them. Significantly, we provide strong evidence that the Rhodopsin family emerged from the cAMP receptor family in an event close to the split of Opisthokonts and not in Placozoa, as earlier assumed. The Rhodopsin family then expanded greatly in Metazoans while the cAMP receptor family is found in 3 invertebrate species and lost in the vertebrates. We estimate that the Adhesion and Frizzled families evolved before the split of Unikonts from a common ancestor of all major eukaryotic lineages. Also, the study highlights that the fungal Adhesion receptors do not have N-terminal domains whereas the fungal Glutamate receptors have a broad repertoire of mammalian-like N-terminal domains. Further, mining of the close unicellular relatives of the Metazoan lineage, Salpingoeca rosetta and Capsaspora owczarzaki, obtained a rich group of both the Adhesion and Glutamate families, which in particular provided insight to the early emergence of the N-terminal domains of the Adhesion family. We identified 619 Fungi specific GPCRs across 79 genomes and revealed that Blastocladiomycota and Chytridiomycota phylum have Metazoan-like GPCRs rather than the GPCRs specific for Fungi. Overall, this study provides the first evidence of the presence of four of the five main GRAFS families in Fungi and clarifies the early evolutionary history of the GPCR superfamily.

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Citations
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Journal ArticleDOI
16 May 2013-Nature
TL;DR: Although the SMO receptor shares the seven-transmembrane helical fold, most of the conserved motifs for class A GPCRs are absent, and the structure reveals an unusually complex arrangement of long extracellular loops stabilized by four disulphide bonds.
Abstract: The smoothened (SMO) receptor, a key signal transducer in the hedgehog signalling pathway, is responsible for the maintenance of normal embryonic development and is implicated in carcinogenesis. It is classified as a class frizzled (class F) G-protein-coupled receptor (GPCR), although the canonical hedgehog signalling pathway involves the GLI transcription factors and the sequence similarity with class A GPCRs is less than 10%. Here we report the crystal structure of the transmembrane domain of the human SMO receptor bound to the small-molecule antagonist LY2940680 at 2.5 A resolution. Although the SMO receptor shares the seven-transmembrane helical fold, most of the conserved motifs for class A GPCRs are absent, and the structure reveals an unusually complex arrangement of long extracellular loops stabilized by four disulphide bonds. The ligand binds at the extracellular end of the seven-transmembrane-helix bundle and forms extensive contacts with the loops. The crystal structure of the human smoothened (SMO) receptor is presented in complex with a small-molecule antitumour agent; this represents the first example of a non-class-A, 7-transmembrane (7TM) receptor structure, revealing different conserved motifs common within class frizzled 7TM receptors and an unusually complex arrangement of long extracellular loops stabilized by disulphide bonds. The smoothened (SMO) receptor is a key signal transducer in the hedgehog signalling pathway that is responsible for the maintenance of normal embryonic development and is also implicated in carcinogenesis. The SMO receptor was classified as a class frizzled (class F) G-protein-coupled receptor (GPCR). In this paper the authors report the X-ray crystal structure of the human SMO receptor bound to the small-molecule antagonist LY2940680, an orally active anticancer compound that is in clinical trials. This is the first published structure of a non-class-A GPCR; most conserved motifs for class A GPCRs are absent, and the structure reveals an unusually complex arrangement of long extracellular loops stabilized by four disulphide bonds.

454 citations

Journal ArticleDOI
TL;DR: Key signaling pathways are presented to provide a context for the gene manipulations summarized herein and will undoubtedly provide a rich resource for future innovation toward intervention and prevention of the number one cause of death in the modern world.
Abstract: At least 468 individual genes have been manipulated by molecular methods to study their effects on the initiation, promotion, and progression of atherosclerosis. Most clinicians and many investigators, even in related disciplines, find many of these genes and the related pathways entirely foreign. Medical schools generally do not attempt to incorporate the relevant molecular biology into their curriculum. A number of key signaling pathways are highly relevant to atherogenesis and are presented to provide a context for the gene manipulations summarized herein. The pathways include the following: the insulin receptor (and other receptor tyrosine kinases); Ras and MAPK activation; TNF-α and related family members leading to activation of NF-κB; effects of reactive oxygen species (ROS) on signaling; endothelial adaptations to flow including G protein-coupled receptor (GPCR) and integrin-related signaling; activation of endothelial and other cells by modified lipoproteins; purinergic signaling; control of leukocyte adhesion to endothelium, migration, and further activation; foam cell formation; and macrophage and vascular smooth muscle cell signaling related to proliferation, efferocytosis, and apoptosis. This review is intended primarily as an introduction to these key signaling pathways. They have become the focus of modern atherosclerosis research and will undoubtedly provide a rich resource for future innovation toward intervention and prevention of the number one cause of death in the modern world.

442 citations


Cites background from "The origin of GPCRs: identification..."

  • ...The 748 human GPCR (683 of the Rhodopsin class, 33 Adhesion, 22 Glutamate, and 10 Frizzled) (952) are all characterized by multiple transmembrane helical domains....

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Journal ArticleDOI
TL;DR: The remarkable structural conservation and distinct features of the Na(+) pocket in this most populous GPCR class, as well as the conformational collapse of the pocket upon receptor activation are discussed.

393 citations

Journal ArticleDOI
TL;DR: This review covers all major biologic aspects of Adhesion GPCRs, including evolutionary origins, interaction partners, signaling, expression, physiologic functions, and therapeutic potential.
Abstract: The Adhesion family forms a large branch of the pharmacologically important superfamily of G protein–coupled receptors (GPCRs). As Adhesion GPCRs increasingly receive attention from a wide spectrum of biomedical fields, the Adhesion GPCR Consortium, together with the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification, proposes a unified nomenclature for Adhesion GPCRs. The new names have ADGR as common dominator followed by a letter and a number to denote each subfamily and subtype, respectively. The new names, with old and alternative names within parentheses, are: ADGRA1 (GPR123), ADGRA2 (GPR124), ADGRA3 (GPR125), ADGRB1 (BAI1), ADGRB2 (BAI2), ADGRB3 (BAI3), ADGRC1 (CELSR1), ADGRC2 (CELSR2), ADGRC3 (CELSR3), ADGRD1 (GPR133), ADGRD2 (GPR144), ADGRE1 (EMR1, F4/80), ADGRE2 (EMR2), ADGRE3 (EMR3), ADGRE4 (EMR4), ADGRE5 (CD97), ADGRF1 (GPR110), ADGRF2 (GPR111), ADGRF3 (GPR113), ADGRF4 (GPR115), ADGRF5 (GPR116, Ig-Hepta), ADGRG1 (GPR56), ADGRG2 (GPR64, HE6), ADGRG3 (GPR97), ADGRG4 (GPR112), ADGRG5 (GPR114), ADGRG6 (GPR126), ADGRG7 (GPR128), ADGRL1 (latrophilin-1, CIRL-1, CL1), ADGRL2 (latrophilin-2, CIRL-2, CL2), ADGRL3 (latrophilin-3, CIRL-3, CL3), ADGRL4 (ELTD1, ETL), and ADGRV1 (VLGR1, GPR98). This review covers all major biologic aspects of Adhesion GPCRs, including evolutionary origins, interaction partners, signaling, expression, physiologic functions, and therapeutic potential.

343 citations


Cites background from "The origin of GPCRs: identification..."

  • ...Recently, Adhesion GPCRs with short extracellular regions have been identified in several basal fungi, indicating that the Adhesion family is likely to have evolved before the split of unikonts from the common ancestor of eukaryotes about 1275 million years ago (Krishnan et al., 2012)....

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  • ...…domains, with as primary examples the emergence of the GPCR proteolysis site (GPS) and Calx_beta domains in the unicellular filasterean C. owczarzaki and the appearance of EGF_CA domains in free-living unicellular organisms, such as the choanoflagellate Salpingoeca rosetta (Krishnan et al., 2012)....

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  • ...Adhesion GPCRs, like other GPCR families, were proposed to have evolved from a common ancestor with the ancient cAMP receptors (Nordstrom et al., 2011; Krishnan et al., 2012) typically found in Dictyostelium discoideum....

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  • ...However, there are also Adhesion GPCR genes in the genomes of choanoflagellates and fungi that cannot be classified according to the specific metazoan families (Krishnan et al., 2012)....

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  • ...…(Kamesh et al., 2008; Nordstrom et al., 2008), primitive animals (Putnam et al., 2007; Nordstrom et al., 2011), the most ancient metazoan phyla (Srivastava et al., 2010), and also in unicellular metazoan relatives, such as Capsaspora owczarzaki and Monosiga brevicollis (Krishnan et al., 2012)....

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Journal ArticleDOI
TL;DR: This work interrogated genomic sequence databases and used phylogenetic reconstruction tools to show that a large fraction of human PSs were already present in the last common ancestor of flies, mollusks, urchins, and mammals, and indicated that many vertebrate and arthropod PSs that were previously thought to be phyla specific are in fact of bilaterian origin.
Abstract: Peptide hormones and their receptors are widespread in metazoans, but the knowledge we have of their evolutionary relationships remains unclear. Recently, accumulating genome sequences from many different species have offered the opportunity to reassess the relationships between protostomian and deuterostomian peptidergic systems (PSs). Here we used sequences of all human rhodopsin and secretin-type G protein-coupled receptors as bait to retrieve potential homologs in the genomes of 15 bilaterian species, including nonchordate deuterostomian and lophotrochozoan species. Our phylogenetic analysis of these receptors revealed 29 well-supported subtrees containing mixed sets of protostomian and deuterostomian sequences. This indicated that many vertebrate and arthropod PSs that were previously thought to be phyla specific are in fact of bilaterian origin. By screening sequence databases for potential peptides, we then reconstructed entire bilaterian peptide families and showed that protostomian and deuterostomian peptides that are ligands of orthologous receptors displayed some similarity at the level of their primary sequence, suggesting an ancient coevolution between peptide and receptor genes. In addition to shedding light on the function of human G protein-coupled receptor PSs, this work presents orthology markers to study ancestral neuron types that were probably present in the last common bilaterian ancestor.

336 citations


Cites background from "The origin of GPCRs: identification..."

  • ...GPCRs are seven-pass membrane receptors that can bind to a wide variety of ligands (1) and form the largest family of integral membrane proteins in the human genome (2)....

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References
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Journal ArticleDOI
TL;DR: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models to analyze heterogeneous data sets and explore a wide variety of structured models mixing partition-unique and shared parameters.
Abstract: Summary: MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types—e.g. morphological, nucleotide, and protein— and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.

25,931 citations

Journal ArticleDOI
TL;DR: A new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves and a new test to assess the support of the data for internal branches of a phylogeny are introduced.
Abstract: PhyML is a phylogeny software based on the maximum-likelihood principle. Early PhyML versions used a fast algorithm performing nearest neighbor interchanges to improve a reasonable starting tree topology. Since the original publication (Guindon S., Gascuel O. 2003. A simple, fast and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst. Biol. 52:696-704), PhyML has been widely used (>2500 citations in ISI Web of Science) because of its simplicity and a fair compromise between accuracy and speed. In the meantime, research around PhyML has continued, and this article describes the new algorithms and methods implemented in the program. First, we introduce a new algorithm to search the tree space with user-defined intensity using subtree pruning and regrafting topological moves. The parsimony criterion is used here to filter out the least promising topology modifications with respect to the likelihood function. The analysis of a large collection of real nucleotide and amino acid data sets of various sizes demonstrates the good performance of this method. Second, we describe a new test to assess the support of the data for internal branches of a phylogeny. This approach extends the recently proposed approximate likelihood-ratio test and relies on a nonparametric, Shimodaira-Hasegawa-like procedure. A detailed analysis of real alignments sheds light on the links between this new approach and the more classical nonparametric bootstrap method. Overall, our tests show that the last version (3.0) of PhyML is fast, accurate, stable, and ready to use. A Web server and binary files are available from http://www.atgc-montpellier.fr/phyml/.

14,385 citations

Journal ArticleDOI
TL;DR: The definition and use of family-specific, manually curated gathering thresholds are explained and some of the features of domains of unknown function (also known as DUFs) are discussed, which constitute a rapidly growing class of families within Pfam.
Abstract: Pfam is a widely used database of protein families and domains. This article describes a set of major updates that we have implemented in the latest release (version 24.0). The most important change is that we now use HMMER3, the latest version of the popular profile hidden Markov model package. This software is approximately 100 times faster than HMMER2 and is more sensitive due to the routine use of the forward algorithm. The move to HMMER3 has necessitated numerous changes to Pfam that are described in detail. Pfam release 24.0 contains 11,912 families, of which a large number have been significantly updated during the past two years. Pfam is available via servers in the UK (http://pfam.sanger.ac.uk/), the USA (http://pfam.janelia.org/) and Sweden (http://pfam.sbc.su.se/).

14,075 citations


"The origin of GPCRs: identification..." refers methods in this paper

  • ...The putative dataset was aligned to the complete Pfam database version 24, which has 11912 families with sensitive HMM models built using HMMER3 software [41]....

    [...]

Journal ArticleDOI
TL;DR: Pfam as discussed by the authors is a widely used database of protein families, containing 14 831 manually curated entries in the current version, version 27.0, and has been updated several times since 2012.
Abstract: Pfam, available via servers in the UK (http://pfam.sanger.ac.uk/) and the USA (http://pfam.janelia.org/), is a widely used database of protein families, containing 14 831 manually curated entries in the current release, version 27.0. Since the last update article 2 years ago, we have generated 1182 new families and maintained sequence coverage of the UniProt Knowledgebase (UniProtKB) at nearly 80%, despite a 50% increase in the size of the underlying sequence database. Since our 2012 article describing Pfam, we have also undertaken a comprehensive review of the features that are provided by Pfam over and above the basic family data. For each feature, we determined the relevance, computational burden, usage statistics and the functionality of the feature in a website context. As a consequence of this review, we have removed some features, enhanced others and developed new ones to meet the changing demands of computational biology. Here, we describe the changes to Pfam content. Notably, we now provide family alignments based on four different representative proteome sequence data sets and a new interactive DNA search interface. We also discuss the mapping between Pfam and known 3D structures.

9,415 citations


"The origin of GPCRs: identification..." refers methods in this paper

  • ...The putative dataset was aligned to the complete Pfam database version 24, which has 11912 families with sensitive HMM models built using HMMER3 software [41]....

    [...]

Journal ArticleDOI
TL;DR: Cd-hit-2d compares two protein datasets and reports similar matches between them; cd- Hit-est clusters a DNA/RNA sequence database and cd- hit-est-2D compares two nucleotide datasets.
Abstract: Motivation: In 2001 and 2002, we published two papers (Bioinformatics, 17, 282--283, Bioinformatics, 18, 77--82) describing an ultrafast protein sequence clustering program called cd-hit. This program can efficiently cluster a huge protein database with millions of sequences. However, the applications of the underlying algorithm are not limited to only protein sequences clustering, here we present several new programs using the same algorithm including cd-hit-2d, cd-hit-est and cd-hit-est-2d. Cd-hit-2d compares two protein datasets and reports similar matches between them; cd-hit-est clusters a DNA/RNA sequence database and cd-hit-est-2d compares two nucleotide datasets. All these programs can handle huge datasets with millions of sequences and can be hundreds of times faster than methods based on the popular sequence comparison and database search tools, such as BLAST. Availability: http://cd-hit.org Contact: [email protected]

8,306 citations