A Global Map of G Protein Signaling Regulation by RGS Proteins.

The control over the extent and timing of G protein signaling is provided by the regulator of G protein signaling (RGS) proteins that deactivate G protein α subunits (Gα). Mammalian genomes encode 20 canonical RGS and 16 Gα genes with key roles in physiology and disease. To understand the principles governing the selectivity of Gα regulation by RGS, we examine the catalytic activity of all canonical human RGS proteins and their selectivity for a complete set of Gα substrates using real-time kinetic measurements in living cells. The data reveal rules governing RGS-Gα recognition, the structural basis of its selectivity, and provide principles for engineering RGS proteins with defined selectivity. The study also explores the evolution of RGS-Gα selectivity through ancestral reconstruction and demonstrates how naturally occurring non-synonymous variants in RGS alter signaling. These results provide a blueprint for decoding signaling selectivity and advance our understanding of molecular recognition principles.

Selectivity determinants of GPCR-G-protein binding.

The selective coupling of G-protein-coupled receptors (GPCRs) to specific G proteins is critical to trigger the appropriate physiological response. However, the determinants of selective binding have remained elusive. Here we reveal the existence of a selectivity barcode (that is, patterns of amino acids) on each of the 16 human G proteins that is recognized by distinct regions on the approximately 800 human receptors. Although universally conserved positions in the barcode allow the receptors to bind and activate G proteins in a similar manner, different receptors recognize the unique positions of the G-protein barcode through distinct residues, like multiple keys (receptors) opening the same lock (G protein) using non-identical cuts. Considering the evolutionary history of GPCRs allows the identification of these selectivity-determining residues. These findings lay the foundation for understanding the molecular basis of coupling selectivity within individual receptors and G proteins.

Diverse activation pathways in class A GPCRs converge near the G-protein-coupling region.

Class A G-protein-coupled receptors (GPCRs) are a large family of membrane proteins that mediate a wide variety of physiological functions, including vision, neurotransmission and immune responses. They are the targets of nearly one-third of all prescribed medicinal drugs such as beta blockers and antipsychotics. GPCR activation is facilitated by extracellular ligands and leads to the recruitment of intracellular G proteins. Structural rearrangements of residue contacts in the transmembrane domain serve as 'activation pathways' that connect the ligand-binding pocket to the G-protein-coupling region within the receptor. In order to investigate the similarities in activation pathways across class A GPCRs, we analysed 27 GPCRs from diverse subgroups for which structures of active, inactive or both states were available. Here we show that, despite the diversity in activation pathways between receptors, the pathways converge near the G-protein-coupling region. This convergence is mediated by a highly conserved structural rearrangement of residue contacts between transmembrane helices 3, 6 and 7 that releases G-protein-contacting residues. The convergence of activation pathways may explain how the activation steps initiated by diverse ligands enable GPCRs to bind a common repertoire of G proteins.

Metabolic network reconstruction of Chlamydomonas offers insight into light-driven algal metabolism.

Metabolic network reconstruction encompasses existing knowledge about an organism's metabolism and genome annotation, providing a platform for omics data analysis and phenotype prediction. The model alga Chlamydomonas reinhardtii is employed to study diverse biological processes from photosynthesis to phototaxis. Recent heightened interest in this species results from an international movement to develop algal biofuels. Integrating biological and optical data, we reconstructed a genome-scale metabolic network for this alga and devised a novel light-modeling approach that enables quantitative growth prediction for a given light source, resolving wavelength and photon flux. We experimentally verified transcripts accounted for in the network and physiologically validated model function through simulation and generation of new experimental growth data, providing high confidence in network contents and predictive applications. The network offers insight into algal metabolism and potential for genetic engineering and efficient light source design, a pioneering resource for studying light-driven metabolism and quantitative systems biology.

Genome-wide functional annotation and structural verification of metabolic ORFeome of Chlamydomonas reinhardtii.

BACKGROUND: Recent advances in the field of metabolic engineering have been expedited by the availability of genome sequences and metabolic modelling approaches. The complete sequencing of the C. reinhardtii genome has made this unicellular alga a good candidate for metabolic engineering studies; however, the annotation of the relevant genes has not been validated and the much-needed metabolic ORFeome is currently unavailable. We describe our efforts on the functional annotation of the ORF models released by the Joint Genome Institute (JGI), prediction of their subcellular localizations, and experimental verification of their structural annotation at the genome scale. RESULTS: We assigned enzymatic functions to the translated JGI ORF models of C. reinhardtii by reciprocal BLAST searches of the putative proteome against the UniProt and AraCyc enzyme databases. The best match for each translated ORF was identified and the EC numbers were transferred onto the ORF models. Enzymatic functional assignment was extended to the paralogs of the ORFs by clustering ORFs using BLASTCLUST. In total, we assigned 911 enzymatic functions, including 886 EC numbers, to 1,427 transcripts. We further annotated the enzymatic ORFs by prediction of their subcellular localization. The majority of the ORFs are predicted to be compartmentalized in the cytosol and chloroplast. We verified the structure of the metabolism-related ORF models by reverse transcription-PCR of the functionally annotated ORFs. Following amplification and cloning, we carried out 454FLX and Sanger sequencing of the ORFs. Based on alignment of the 454FLX reads to the ORF predicted sequences, we obtained more than 90% coverage for more than 80% of the ORFs. In total, 1,087 ORF models were verified by 454 and Sanger sequencing methods. We obtained expression evidence for 98% of the metabolic ORFs in the algal cells grown under constant light in the presence of acetate. CONCLUSIONS: We functionally annotated approximately 1,400 JGI predicted metabolic ORFs that can facilitate the reconstruction and refinement of a genome-scale metabolic network. The unveiling of the metabolic potential of this organism, along with structural verification of the relevant ORFs, facilitates the selection of metabolic engineering targets with applications in bioenergy and biopharmaceuticals. The ORF clones are a resource for downstream studies.

Molecular determinants underlying functional innovations of TBP and their impact on transcription initiation.

TATA-box binding protein (TBP) is required for every single transcription event in archaea and eukaryotes. It binds DNA and harbors two repeats with an internal structural symmetry that show sequence asymmetry. At various times in evolution, TBP has acquired multiple interaction partners and different organisms have evolved TBP paralogs with additional protein regions. Together, these observations raise questions of what molecular determinants (i.e. key residues) led to the ability of TBP to acquire new interactions, resulting in an increasingly complex transcriptional system in eukaryotes. We present a comprehensive study of the evolutionary history of TBP and its interaction partners across all domains of life, including viruses. Our analysis reveals the molecular determinants and suggests a unified and multi-stage evolutionary model for the functional innovations of TBP. These findings highlight how concerted chemical changes on a conserved structural scaffold allow for the emergence of complexity in a fundamental biological process.

Molecular mechanism of modulating arrestin conformation by GPCR phosphorylation.

Arrestins regulate the signaling of ligand-activated, phosphorylated G-protein-coupled receptors (GPCRs). Different patterns of receptor phosphorylation (phosphorylation barcode) can modulate arrestin conformations, resulting in distinct functional outcomes (for example, desensitization, internalization, and downstream signaling). However, the mechanism of arrestin activation and how distinct receptor phosphorylation patterns could induce different conformational changes on arrestin are not fully understood. We analyzed how each arrestin amino acid contributes to its different conformational states. We identified a conserved structural motif that restricts the mobility of the arrestin finger loop in the inactive state and appears to be regulated by receptor phosphorylation. Distal and proximal receptor phosphorylation sites appear to selectively engage with distinct arrestin structural motifs (that is, micro-locks) to induce different arrestin conformations. These observations suggest a model in which different phosphorylation patterns of the GPCR C terminus can combinatorially modulate the conformation of the finger loop and other phosphorylation-sensitive structural elements to drive distinct arrestin conformation and functional outcomes.

The many faces of the helix-turn-helix domain: transcription regulation and beyond.

The helix-turn-helix (HTH) domain is a common denominator in basal and specific transcription factors from the three super-kingdoms of life. At its core, the domain comprises of an open tri-helical bundle, which typically binds DNA with the 3rd helix. Drawing on the wealth of data that has accumulated over two decades since the discovery of the domain, we present an overview of the natural history of the HTH domain from the viewpoint of structural analysis and comparative genomics. In structural terms, the HTH domains have developed several elaborations on the basic 3-helical core, such as the tetra-helical bundle, the winged-helix and the ribbon-helix-helix type configurations. In functional terms, the HTH domains are present in the most prevalent transcription factors of all prokaryotic genomes and some eukaryotic genomes. They have been recruited to a wide range of functions beyond transcription regulation, which include DNA repair and replication, RNA metabolism and protein-protein interactions in diverse signaling contexts. Beyond their basic role in mediating macromolecular interactions, the HTH domains have also been incorporated into the catalytic domains of diverse enzymes. We discuss the general domain architectural themes that have arisen amongst the HTH domains as a result of their recruitment to these diverse functions. We present a natural classification, higher-order relationships and phyletic pattern analysis of all the major families of HTH domains. This reconstruction suggests that there were at least 6-11 different HTH domains in the last universal common ancestor of all life forms, which covered much of the structural diversity and part of the functional versatility of the extant representatives of this domain. In prokaryotes the total number of HTH domains per genome shows a strong power-equation type scaling with the gene number per genome. However, the HTH domains in two-component signaling pathways show a linear scaling with gene number, in contrast to the non-linear scaling of HTH domains in single-component systems and sigma factors. These observations point to distinct evolutionary forces in the emergence of different signaling systems with HTH transcription factors. The archaea and bacteria share a number of ancient families of specific HTH transcription factors. However, they do not share any orthologous HTH proteins in the basal transcription apparatus. This differential relationship of their basal and specific transcriptional machinery poses an apparent conundrum regarding the origins of their transcription apparatus.

Constraints and consequences of the emergence of amino acid repeats in eukaryotic proteins.

Proteins with amino acid homorepeats have the potential to be detrimental to cells and are often associated with human diseases. Why, then, are homorepeats prevalent in eukaryotic proteomes? In yeast, homorepeats are enriched in proteins that are essential and pleiotropic and that buffer environmental insults. The presence of homorepeats increases the functional versatility of proteins by mediating protein interactions and facilitating spatial organization in a repeat-dependent manner. During evolution, homorepeats are preferentially retained in proteins with stringent proteostasis, which might minimize repeat-associated detrimental effects such as unregulated phase separation and protein aggregation. Their presence facilitates rapid protein divergence through accumulation of amino acid substitutions, which often affect linear motifs and post-translational-modification sites. These substitutions may result in rewiring protein interaction and signaling networks. Thus, homorepeats are distinct modules that are often retained in stringently regulated proteins. Their presence facilitates rapid exploration of the genotype-phenotype landscape of a population, thereby contributing to adaptation and fitness.

Systems level analysis of the Chlamydomonas reinhardtii metabolic network reveals variability in evolutionary co-conservation.

Metabolic networks, which are mathematical representations of organismal metabolism, are reconstructed to provide computational platforms to guide metabolic engineering experiments and explore fundamental questions on metabolism. Systems level analyses, such as interrogation of phylogenetic relationships within the network, can provide further guidance on the modification of metabolic circuitries. Chlamydomonas reinhardtii, a biofuel relevant green alga that has retained key genes with plant, animal, and protist affinities, serves as an ideal model organism to investigate the interplay between gene function and phylogenetic affinities at multiple organizational levels. Here, using detailed topological and functional analyses, coupled with transcriptomics studies on a metabolic network that we have reconstructed for C. reinhardtii, we show that network connectivity has a significant concordance with the co-conservation of genes; however, a distinction between topological and functional relationships is observable within the network. Dynamic and static modes of co-conservation were defined and observed in a subset of gene-pairs across the network topologically. In contrast, genes with predicted synthetic interactions, or genes involved in coupled reactions, show significant enrichment for both shorter and longer phylogenetic distances. Based on our results, we propose that the metabolic network of C. reinhardtii is assembled with an architecture to minimize phylogenetic profile distances topologically, while it includes an expansion of such distances for functionally interacting genes. This arrangement may increase the robustness of C. reinhardtii's network in dealing with varied environmental challenges that the species may face. The defined evolutionary constraints within the network, which identify important pairings of genes in metabolism, may offer guidance on synthetic biology approaches to optimize the production of desirable metabolites.

Internal symmetry in protein structures: prevalence, functional relevance and evolution.

Symmetry has been found at various levels of biological organization in the protein structural universe. Numerous evolutionary studies have proposed connections between internal symmetry within protein tertiary structures, quaternary associations and protein functions. Recent computational methods, such as SymD and CE-Symm, facilitate a large-scale detection of internal symmetry in protein structures. Based on the results from these methods, about 20% of SCOP folds, superfamilies and families are estimated to have structures with internal symmetry (Figure 1d). All-ß and membrane proteins fold classes contain a relatively high number of unique instances of internal symmetry. In addition to the axis of symmetry, anecdotal evidence suggests that, the region of connection or contact between symmetric units could coincide with functionally relevant sites within a fold. General principles that underlie protein internal symmetry and their connections to protein structural integrity and functions remain to be elucidated.

Pharmacological inhibition of gut-derived serotonin synthesis is a potential bone anabolic treatment for osteoporosis.

Osteoporosis is a disease of low bone mass most often caused by an increase in bone resorption that is not sufficiently compensated for by a corresponding increase in bone formation. As gut-derived serotonin (GDS) inhibits bone formation, we asked whether hampering its biosynthesis could treat osteoporosis through an anabolic mechanism (that is, by increasing bone formation). We synthesized and used LP533401, a small molecule inhibitor of tryptophan hydroxylase-1 (Tph-1), the initial enzyme in GDS biosynthesis. Oral administration of this small molecule once daily for up to six weeks acts prophylactically or therapeutically, in a dose-dependent manner, to treat osteoporosis in ovariectomized rodents because of an isolated increase in bone formation. These results provide a proof of principle that inhibiting GDS biosynthesis could become a new anabolic treatment for osteoporosis.