Institut de génétique et de biologie moléculaire et cellulaire

A new software suite, called Crystallography & NMR System (CNS), has been developed for macromolecular structure determination by X-ray crystallography or solution nuclear magnetic resonance (NMR) spectroscopy. In contrast to existing structure-determination programs, the architecture of CNS is highly flexible, allowing for extension to other structure-determination methods, such as electron microscopy and solid-state NMR spectroscopy. CNS has a hierarchical structure: a high-level hypertext markup language (HTML) user interface, task-oriented user input files, module files, a symbolic structure-determination language (CNS language), and low-level source code. Each layer is accessible to the user. The novice user may just use the HTML interface, while the more advanced user may use any of the other layers. The source code will be distributed, thus source-code modification is possible. The CNS language is sufficiently powerful and flexible that many new algorithms can be easily implemented in the CNS language without changes to the source code. The CNS language allows the user to perform operations on data structures, such as structure factors, electron-density maps, and atomic properties. The power of the CNS language has been demonstrated by the implementation of a comprehensive set of crystallographic procedures for phasing, density modification and refinement. User-friendly task-oriented input files are available for nearly all aspects of macromolecular structure determination by X-ray crystallography and solution NMR.

Diffraction (X-ray, neutron and electron) and electron cryo-microscopy are powerful methods to determine three-dimensional macromolecular structures, which are required to understand biological processes and to develop new therapeutics against diseases. The overall structure-solution workflow is similar for these techniques, but nuances exist because the properties of the reduced experimental data are different. Software tools for structure determination should therefore be tailored for each method. Phenix is a comprehensive software package for macromolecular structure determination that handles data from any of these techniques. Tasks performed with Phenix include data-quality assessment, map improvement, model building, the validation/rebuilding/refinement cycle and deposition. Each tool caters to the type of experimental data. The design of Phenix emphasizes the automation of procedures, where possible, to minimize repetitive and time-consuming manual tasks, while default parameters are chosen to encourage best practice. A graphical user interface provides access to many command-line features of Phenix and streamlines the transition between programs, project tracking and re-running of previous tasks.

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

phenix.refine is a program within the PHENIX package that supports crystallographic structure refinement against experimental data with a wide range of upper resolution limits using a large repertoire of model parameterizations. It has several automation features and is also highly flexible. Several hundred parameters enable extensive customizations for complex use cases. Multiple user-defined refinement strategies can be applied to specific parts of the model in a single refinement run. An intuitive graphical user interface is available to guide novice users and to assist advanced users in managing refinement projects. X-ray or neutron diffraction data can be used separately or jointly in refinement. phenix.refine is tightly integrated into the PHENIX suite, where it serves as a critical component in automated model building, final structure refinement, structure validation and deposition to the wwPDB. This paper presents an overview of the major phenix.refine features, with extensive literature references for readers interested in more detailed discussions of the methods.

This article describes the implementation of real-space refinement in the phenix.real_space_refine program from the PHENIX suite. The use of a simplified refinement target function enables very fast calculation, which in turn makes it possible to identify optimal data-restraint weights as part of routine refinements with little runtime cost. Refinement of atomic models against low-resolution data benefits from the inclusion of as much additional information as is available. In addition to standard restraints on covalent geometry, phenix.real_space_refine makes use of extra information such as secondary-structure and rotamer-specific restraints, as well as restraints or constraints on internal molecular symmetry. The re-refinement of 385 cryo-EM-derived models available in the Protein Data Bank at resolutions of 6 Å or better shows significant improvement of the models and of the fit of these models to the target maps.

The Clustal programs are widely used for carrying out automatic multiple alignment of nucleotide or amino acid sequences. The most familiar version is ClustalW, which uses a simple text menu system that is portable to more or less all computer systems. ClustalX features a graphical user interface and some powerful graphical utilities for aiding the interpretation of alignments and is the preferred version for interactive usage. Users may run Clustal remotely from several sites using the Web or the programs may be downloaded and run locally on PCs, Macintosh, or Unix computers. The protocols in this unit discuss how to use ClustalX and ClustalW to construct an alignment, and create profile alignments by merging existing alignments.

Retinoids play an important role in development, differentiation, and homeostasis. The discovery of retinoid receptors belonging to the superfamily of nuclear ligand-activated transcriptional regulators has revolutionized our molecular understanding as to how these structurally simple molecules exert their pleiotropic effects. Diversity in the control of gene expression by retinoid signals is generated through complexity at different levels of the signaling pathway. A major source of diversity originates from the existence of two families of retinoid acid (RA) receptors (R), the RAR isotypes (alpha, beta, and gamma) and the three RXR isotypes (alpha, beta, and gamma), and their numerous isoforms, which bind as RXR/RAR heterodimers to the polymorphic cis-acting response elements of RA target genes. The possibility of cross-modulation (cross-talk) with cell-surface receptors signaling pathways, as well as the finding that RARs and RXRs interact with multiple putative coactivators and/or corepressors, generates additional levels of complexity for the array of combinatorial effects that underlie the pleiotropic effects of retinoids. This review focuses on recent developments, particularly in the area of structure-function relationships.

Neurologic Features in SARS-CoV-2 Infection In a consecutive series of 64 patients with Covid-19 and ARDS, 58 of whom underwent neurologic examination, severe agitation and corticospinal signs were...

Friedreich's ataxia (FRDA) is an autosomal recessive, degenerative disease that involves the central and peripheral nervous systems and the heart. A gene, X25, was identified in the critical region for the FRDA locus on chromosome 9q13. This gene encodes a 210-amino acid protein, frataxin, that has homologs in distant species such as Caenorhabditis elegans and yeast. A few FRDA patients were found to have point mutations in X25, but the majority were homozygous for an unstable GAA trinucleotide expansion in the first X25 intron.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Humans expressing a defective form of the transcription factor AIRE (autoimmune regulator) develop multiorgan autoimmune disease. We used aire- deficient mice to test the hypothesis that this transcription factor regulates autoimmunity by promoting the ectopic expression of peripheral tissue- restricted antigens in medullary epithelial cells of the thymus. This hypothesis proved correct. The mutant animals exhibited a defined profile of autoimmune diseases that depended on the absence of aire in stromal cells of the thymus. Aire-deficient thymic medullary epithelial cells showed a specific reduction in ectopic transcription of genes encoding peripheral antigens. These findings highlight the importance of thymically imposed "central" tolerance in controlling autoimmunity.

Disorders of the brain can exhibit considerable epidemiological comorbidity and often share symptoms, provoking debate about their etiologic overlap. We quantified the genetic sharing of 25 brain disorders from genome-wide association studies of 265,218 patients and 784,643 control participants and assessed their relationship to 17 phenotypes from 1,191,588 individuals. Psychiatric disorders share common variant risk, whereas neurological disorders appear more distinct from one another and from the psychiatric disorders. We also identified significant sharing between disorders and a number of brain phenotypes, including cognitive measures. Further, we conducted simulations to explore how statistical power, diagnostic misclassification, and phenotypic heterogeneity affect genetic correlations. These results highlight the importance of common genetic variation as a risk factor for brain disorders and the value of heritability-based methods in understanding their etiology.

The phosphorylation of the human estrogen receptor (ER) serine residue at position 118 is required for full activity of the ER activation function 1 (AF-1). This Ser118 is phosphorylated by mitogen-activated protein kinase (MAPK) in vitro and in cells treated with epidermal growth factor (EGF) and insulin-like growth factor (IGF) in vivo. Overexpression of MAPK kinase (MAPKK) or of the guanine nucleotide binding protein Ras, both of which activate MAPK, enhanced estrogen-induced and antiestrogen (tamoxifen)-induced transcriptional activity of wild-type ER, but not that of a mutant ER with an alanine in place of Ser118. Thus, the activity of the amino-terminal AF-1 of the ER is modulated by the phosphorylation of Ser118 through the Ras-MAPK cascade of the growth factor signaling pathways.

During the last 3 years, a number of approaches for the normalization of RNA sequencing data have emerged in the literature, differing both in the type of bias adjustment and in the statistical strategy adopted. However, as data continue to accumulate, there has been no clear consensus on the appropriate normalization method to be used or the impact of a chosen method on the downstream analysis. In this work, we focus on a comprehensive comparison of seven recently proposed normalization methods for the differential analysis of RNA-seq data, with an emphasis on the use of varied real and simulated datasets involving different species and experimental designs to represent data characteristics commonly observed in practice. Based on this comparison study, we propose practical recommendations on the appropriate normalization method to be used and its impact on the differential analysis of RNA-seq data.

We explored the effects of bile acids on triglyceride (TG) homeostasis using a combination of molecular, cellular, and animal models. Cholic acid (CA) prevents hepatic TG accumulation, VLDL secretion, and elevated serum TG in mouse models of hypertriglyceridemia. At the molecular level, CA decreases hepatic expression of SREBP-1c and its lipogenic target genes. Through the use of mouse mutants for the short heterodimer partner (SHP) and liver X receptor (LXR) alpha and beta, we demonstrate the critical dependence of the reduction of SREBP-1c expression by either natural or synthetic farnesoid X receptor (FXR) agonists on both SHP and LXR alpha and LXR beta. These results suggest that strategies aimed at increasing FXR activity and the repressive effects of SHP should be explored to correct hypertriglyceridemia.

Ribosomes translate genetic information encoded by messenger RNA into proteins. Many aspects of translation and its regulation are specific to eukaryotes, whose ribosomes are much larger and intricate than their bacterial counterparts. We report the crystal structure of the 80S ribosome from the yeast Saccharomyces cerevisiae--including nearly all ribosomal RNA bases and protein side chains as well as an additional protein, Stm1--at a resolution of 3.0 angstroms. This atomic model reveals the architecture of eukaryote-specific elements and their interaction with the universally conserved core, and describes all eukaryote-specific bridges between the two ribosomal subunits. It forms the structural framework for the design and analysis of experiments that explore the eukaryotic translation apparatus and the evolutionary forces that shaped it.

We generated two complementary systems for Cre-mediated recombination of target genes in the mouse digestive epithelium and tested them with a Cre-reporter mouse strain. Cre was expressed under the control of a 9 kb regulatory region of the murine villin gene (vil-Cre). Genetic recombination was initiated at embryonic day (E) 9 in the visceral endoderm, and by E12.5 in the entire intestinal epithelium, but not in other tissues. Cre expression was maintained throughout adulthood. Furthermore, transgenic mice bearing a tamoxifen-dependent Cre recombinase (vil-Cre-ERT2) expressed under the control of the villin promoter were created to perform targeted spatiotemporally controlled somatic recombination. After tamoxifen treatment, recombination was detectable throughout the digestive epithelium. The recombined locus persisted for 60 days after tamoxifen administration, despite rapid intestinal cell renewal, indicating that epithelial progenitor cells had been targeted. The villin-Cre and villin-Cre-ERT2 mice provide valuable tools for studies of cell lineage allocation and gene function in the developing and adult intestine.

The opioid system consists of three receptors, mu, delta, and kappa, which are activated by endogenous opioid peptides processed from three protein precursors, proopiomelanocortin, proenkephalin, and prodynorphin. Opioid receptors are recruited in response to natural rewarding stimuli and drugs of abuse, and both endogenous opioids and their receptors are modified as addiction develops. Mechanisms whereby aberrant activation and modifications of the opioid system contribute to drug craving and relapse remain to be clarified. This review summarizes our present knowledge on brain sites where the endogenous opioid system controls hedonic responses and is modified in response to drugs of abuse in the rodent brain. We review 1) the latest data on the anatomy of the opioid system, 2) the consequences of local intracerebral pharmacological manipulation of the opioid system on reinforced behaviors, 3) the consequences of gene knockout on reinforced behaviors and drug dependence, and 4) the consequences of chronic exposure to drugs of abuse on expression levels of opioid system genes. Future studies will establish key molecular actors of the system and neural sites where opioid peptides and receptors contribute to the onset of addictive disorders. Combined with data from human and nonhuman primate (not reviewed here), research in this extremely active field has implications both for our understanding of the biology of addiction and for therapeutic interventions to treat the disorder.

Pyruvate constitutes a critical branch point in cellular carbon metabolism. We have identified two proteins, Mpc1 and Mpc2, as essential for mitochondrial pyruvate transport in yeast, Drosophila, and humans. Mpc1 and Mpc2 associate to form an ~150-kilodalton complex in the inner mitochondrial membrane. Yeast and Drosophila mutants lacking MPC1 display impaired pyruvate metabolism, with an accumulation of upstream metabolites and a depletion of tricarboxylic acid cycle intermediates. Loss of yeast Mpc1 results in defective mitochondrial pyruvate uptake, and silencing of MPC1 or MPC2 in mammalian cells impairs pyruvate oxidation. A point mutation in MPC1 provides resistance to a known inhibitor of the mitochondrial pyruvate carrier. Human genetic studies of three families with children suffering from lactic acidosis and hyperpyruvatemia revealed a causal locus that mapped to MPC1, changing single amino acids that are conserved throughout eukaryotes. These data demonstrate that Mpc1 and Mpc2 form an essential part of the mitochondrial pyruvate carrier.

Recent advances in the field of electron cryomicroscopy (cryo-EM) have resulted in a rapidly increasing number of atomic models of biomacromolecules that have been solved using this technique and deposited in the Protein Data Bank and the Electron Microscopy Data Bank. Similar to macromolecular crystallography, validation tools for these models and maps are required. While some of these validation tools may be borrowed from crystallography, new methods specifically designed for cryo-EM validation are required. Here, new computational methods and tools implemented in PHENIX are discussed, including d 99 to estimate resolution, phenix.auto_sharpen to improve maps and phenix.mtriage to analyze cryo-EM maps. It is suggested that cryo-EM half-maps and masks should be deposited to facilitate the evaluation and validation of cryo-EM-derived atomic models and maps. The application of these tools to deposited cryo-EM atomic models and maps is also presented.