The asparagine-transamidosome from Helicobacter pylori: a dual-kinetic mode in non-discriminating aspartyl-tRNA synthetase safeguards the genetic code

Helicobacter pylori catalyzes Asn-tRNAAsn formation by use of the indirect pathway that involves charging of Asp onto tRNAAsn by a non-discriminating aspartyl-tRNA synthetase (ND-AspRS), followed by conversion of the mischarged Asp into Asn by the GatCAB amidotransferase. We show that the partners of asparaginylation assemble into a dynamic Asn-transamidosome, which uses a different strategy than the Gln-transamidosome to prevent the release of the mischarged aminoacyl-tRNA intermediate. The complex is described by gel-filtration, dynamic light scattering and kinetic measurements. Two strategies for asparaginylation are shown: (i) tRNAAsn binds GatCAB first, allowing aminoacylation and immediate transamidation once ND-AspRS joins the complex; (ii) tRNAAsn is bound by ND-AspRS which releases the Asp-tRNAAsn product much slower than the cognate Asp-tRNAAsp; this kinetic peculiarity allows GatCAB to bind and transamidate Asp-tRNAAsn before its release by the ND-AspRS. These results are discussed in the context of the interrelation between the Asn and Gln-transamidosomes which use the same GatCAB in H. pylori, and shed light on a kinetic mechanism that ensures faithful codon reassignment for Asn

Architecture et évolution des réseaux d'interactions protéines-protéines : exploration de la carte génotype-phénotype

Tableau d'honneur de la Faculté des études supérieures et postdorales, 2014-2015La question des bases structurales du phénotype et de sa variation est une des questions les plus anciennes de la biologie. Le paradigme actuel stipule que le phénotype est exprimé à partir du génotype au travers de réseaux moléculaires dont l’architecture structure l’information génétique. Cette description mécanistique de la carte génotype-phénotype implique que c’est par la perturbation de l’architecture de ces réseaux que des variations génotypiques mènent à des modifications du phénotype. Les protéines constituant le principal vecteur de l’information génétique, comprendre la carte génotype-phénotype requiert de comprendre comment les variations génotypiques perturbent l’architecture du réseau d’interactions protéines-protéines. Au cours de cette thèse, nous avons développé une méthode permettant d’étudier chez la levure Saccharomyces cerevisiae l’impact de la délétion des gènes sur les interactions entre protéines. Nous avons appliqué cette méthode à l’étude des mécanismes moléculaires de la robustesse par lesquels le réseau d’interactions protéines-protéines filtre les variations génotypiques pour préserver le phénotype. Nous avons mis au jour un mécanisme de compensation fonctionnelle entre gènes paralogues basé sur la compensation des interactions protéines-protéines et expliquant un lien entre génotype et phénotype qui était mal compris jusqu’alors. En outre, en appliquant notre méthode à l’identification des régulateurs de la Protéine Kinase A, nous avons approfondi les connaissances sur la façon dont les maîtres régulateurs coordonnent les processus cellulaires et maintiennent l’homéostasie, une propriété distribuée de la robustesse. Ces résultats, et ceux qui seront produits à l’avenir par l’application de cette méthode, promettent une meilleure compréhension des mécanismes moléculaires par lesquels l’information génétique est transmise du génotype au phénotype, condition essentielle à la compréhension du vivant et de son évolution.The question of the structural bases of the phenotype and of its evolution is one of the oldest questions in biology. The present paradigm states that the phenotype is expressed from the genotype through molecular networks, the architecture from which structures genetic information. This mechanistic description of the genotype-phenotype map implies that it is through by perturbing of the architecture of these networks that genotypic variations lead to phenotypic modifications. Since proteins are the main vector of genetic information, understanding the genotype-phenotype map requires the understanding of how genotypic variations perturb the architecture of the protein interaction network. In the course of this thesis, we developped a methodology that allows to study the impact of gene deletions on the interactions between proteins in the yeast Saccharomyces cerevisiae. We applied this method to the study of the molecular mechanisms of robustness by which the protein interaction network filters genotypic variations to preserve the phenotype. We uncovered un mechanism of functional compensation between paralogous genes that is based on protein-protein interaction compensation and that explains the poorly understood link between genotype and phenotype. Moreover, we applied our method to the identification of regulators of Protein Kinase A and deepened our knowledge of how master regulators coordinate cellular processes and maintain homeostasis, a distributed property of robustness. These results, and the ones that will be produced in the future by applying this method, promise a better understanding of the molecular mechanisms through which genetic information is transmitted from the genotype to the phenotype, an essential condition for the understanding of life and its evolution

The genetic landscape of a physical interaction

A key question in human genetics and evolutionary biology is how mutations in different genes combine to alter phenotypes. Efforts to systematically map genetic interactions have mostly made use of gene deletions. However, most genetic variation consists of point mutations of diverse and difficult to predict effects. Here, by developing a new sequencing-based protein interaction assay - deepPCA - we quantified the effects of >120,000 pairs of point mutations on the formation of the AP-1 transcription factor complex between the products of the FOS and JUN proto-oncogenes. Genetic interactions are abundant both in cis (within one protein) and trans (between the two molecules) and consist of two classes - interactions driven by thermodynamics that can be predicted using a three-parameter global model, and structural interactions between proximally located residues. These results reveal how physical interactions generate quantitatively predictable genetic interactions.This work was supported by a European Research Council (ERC) Consolidator grant (616434), the Spanish Ministry of Economy and Competitiveness (BFU2011-26206 and ‘Centro de Excelencia Severo Ochoa' SEV-2012–0208), the AXA Research Fund, the Bettencourt Schueller Foundation, Agencia de Gestio d’Ajuts Universitaris i de Recerca (AGAUR, SGR-831), the EMBL-CRG Systems Biology Program, and the CERCA Program/Generalitat de Catalunya. GD is a non-stipendiary EMBO Fellow and a Marie-Curie Fellow under grant agreement 608959

mutscan—a flexible R package for efficient end-to-end analysis of multiplexed assays of variant effect data

Abstract Multiplexed assays of variant effect (MAVE) experimentally measure the effect of large numbers of sequence variants by selective enrichment of sequences with desirable properties followed by quantification by sequencing. mutscan is an R package for flexible analysis of such experiments, covering the entire workflow from raw reads up to statistical analysis and visualization. The core components are implemented in C++ for efficiency. Various experimental designs are supported, including single or paired reads with optional unique molecular identifiers. To find variants with changed relative abundance, mutscan employs established statistical models provided in the edgeR and limma packages. mutscan is available from https://github.com/fmicompbio/mutscan

A Systematic Approach for the Genetic Dissection of Protein Complexes in Living Cells

Cells contain many important protein complexes involved in performing and regulating structural, metabolic, and signaling functions. One major challenge in cell biology is to elucidate the organization and mechanisms of robustness of these complexes in vivo. We developed a systematic approach to study structural dependencies within complexes in living cells by deleting subunits and measuring pairwise interactions among other components. We used our methodology to perturb two conserved eukaryotic complexes: the retromer and the nuclear pore complex. Our results identify subunits that are critical for the assembly of these complexes, reveal their structural architecture, and uncover mechanisms by which protein interactions are modulated. Our results also show that paralogous proteins play a key role in the robustness of protein complexes and shape their assembly landscape. Our approach paves the way for studying the response of protein interactomes to mutations and enhances our understanding of genotype-phenotype maps

Mapping the energetic and allosteric landscapes of protein binding domains.

Allosteric communication between distant sites in proteins is central to biological regulation but still poorly characterized, limiting understanding, engineering and drug development1-6. An important reason for this is the lack of methods to comprehensively quantify allostery in diverse proteins. Here we address this shortcoming and present a method that uses deep mutational scanning to globally map allostery. The approach uses an efficient experimental design to infer en masse the causal biophysical effects of mutations by quantifying multiple molecular phenotypes-here we examine binding and protein abundance-in multiple genetic backgrounds and fitting thermodynamic models using neural networks. We apply the approach to two of the most common protein interaction domains found in humans, an SH3 domain and a PDZ domain, to produce comprehensive atlases of allosteric communication. Allosteric mutations are abundant, with a large mutational target space of network-altering 'edgetic' variants. Mutations are more likely to be allosteric closer to binding interfaces, at glycine residues and at specific residues connecting to an opposite surface within the PDZ domain. This general approach of quantifying mutational effects for multiple molecular phenotypes and in multiple genetic backgrounds should enable the energetic and allosteric landscapes of many proteins to be rapidly and comprehensively mapped.This work was funded by European Research Council (ERC) Advanced (883742) and Consolidator (616434) grants, the Spanish Ministry of Science and Innovation (PID2020-118723GB-I00, BFU2017-89488-P, EMBL Partnership, Severo Ochoa Centre of Excellence), the Bettencourt Schueller Foundation, the AXA Research Fund, Agencia de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, 2017 SGR 1322), and the CERCA Program/Generalitat de Catalunya. J.M.S. was supported by an EMBO Long-Term Fellowship (ALTF 857-2016) and a Marie Skłodowska-Curie Fellowship (752809, EU Commission Horizon 2020

Evidence for the Robustness of Protein Complexes to Inter-Species Hybridization

<div><p>Despite the tremendous efforts devoted to the identification of genetic incompatibilities underlying hybrid sterility and inviability, little is known about the effect of inter-species hybridization at the protein interactome level. Here, we develop a screening platform for the comparison of protein–protein interactions (PPIs) among closely related species and their hybrids. We examine <em>in vivo</em> the architecture of protein complexes in two yeast species (<em>Saccharomyces cerevisiae</em> and <em>Saccharomyces kudriavzevii</em>) that diverged 5–20 million years ago and in their F1 hybrids. We focus on 24 proteins of two large complexes: the RNA polymerase II and the nuclear pore complex (NPC), which show contrasting patterns of molecular evolution. We found that, with the exception of one PPI in the NPC sub-complex, PPIs were highly conserved between species, regardless of protein divergence. Unexpectedly, we found that the architecture of the complexes in F1 hybrids could not be distinguished from that of the parental species. Our results suggest that the conservation of PPIs in hybrids likely results from the slow evolution taking place on the very few protein residues involved in the interaction or that protein complexes are inherently robust and may accommodate protein divergence up to the level that is observed among closely related species.</p> </div

The absence of Nup120-Nup145C interaction in <i>Skud</i> is likely a PPI loss.

<p>(<i>A</i>) Spot assays on Methotrexate medium (six days of growth at 30°C) to dissect the interaction in <i>Scer</i> (red), <i>Skud</i> (blue), <i>Suva</i> (yellow) and their hybrids. The interaction between Nup145C from <i>Scer</i> and Nup120 from <i>Scer</i>, <i>Skud</i> or <i>Suva</i> is detected, whereas it is lost when Nup145C comes from <i>Skud</i>. The interaction was also absent when it involved Nup120 from <i>Skud</i> and Nup145 from <i>Suva</i>. (<i>B</i>) Schematic structure of the <i>Scer</i> Nup120-Nup85-Nup145 sub-complex adapted from Fernandez-Martinez <i>et al. </i><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1003161#pgen.1003161-FernandezMartinez1" target="_blank">[43]</a>. The three interacting domains are indicated in black. (<i>C</i>) Interactions between Nup85 and Nup145C or Nup120 in three species and their hybrids confirm that not all Nup145C interactions are lost. (<i>D</i>) Evolutionary tree of <i>Scer</i>, <i>Skud</i> and <i>Suva</i> and schematic representation of Nup145-Nup120-Nup85 interactions in species and hybrids according to spot assays (<i>A–C</i>), revealing several other loss of interaction in hybrids with <i>Suva</i>. Line width is proportional to the number of spot growth observed for each interaction. (<i>E</i>) Similar growth for BY4741 <i>Scer</i> wild type (WT) and modified strains (Δ<i>Skud-NUP145</i>) suggest that <i>Skud-Nup145</i> complements the absence of <i>Scer-Nup145</i> (YPD medium, two days of growth at 30°C), as <i>Nup145</i> is essential for growth in <i>Scer</i>.</p