Corinne Rancurel

Bio: Corinne Rancurel is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Genome & Biology. The author has an hindex of 22, co-authored 46 publications receiving 7557 citations. Previous affiliations of Corinne Rancurel include Institut national de la recherche agronomique & University of Provence.

The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics

Abstract: The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL: http://www.cazy.org/.

Dividing the large glycoside hydrolase family 13 into subfamilies: towards improved functional annotations of α-amylase-related proteins

Abstract: Family GH13, also known as the alpha-amylase family, is the largest sequence-based family of glycoside hydrolases and groups together a number of different enzyme activities and substrate specificities acting on alpha-glycosidic bonds. This polyspecificity results in the fact that the simple membership of this family cannot be used for the prediction of gene function based on sequence alone. In order to establish robust groups that show an improved correlation between sequence and enzymatic specificity, we have performed a large-scale analysis of 1691 family GH13 sequences by combining clustering, similarity search and phylogenetic methods. About 80% of the sequences could be reliably classified into 35 subfamilies. Most subfamilies appear monofunctional (i.e. contain enzymes with the same substrate and the same product). The close examination of the other, apparently polyspecific, subfamilies revealed that they actually group together enzymes with strongly related (or even sometimes virtually identical) activities. Overall our subfamily assignment allows to set the limits for genomic function prediction on this large family of biologically and industrially important enzymes.

A hierarchical classification of polysaccharide lyases for glycogenomics

Abstract: Carbohydrate-active enzymes face huge substrate diversity in a highly selective manner using only a limited number of available folds. They are therefore subjected to multiple divergent and convergent evolutionary events. This and their frequent modularity render their functional annotation in genomes difficult in a number of cases. In the present paper, a classification of polysaccharide lyases (the enzymes that cleave polysaccharides using an elimination instead of a hydrolytic mechanism) is shown thoroughly for the first time. Based on the analysis of a large panel of experimentally characterized polysaccharide lyases, we examined the correlation of various enzyme properties with the three levels of the classification: fold, family and subfamily. The resulting hierarchical classification, which should help annotate relevant genes in genomic efforts, is available and constantly updated at the Carbohydrate-Active Enzymes Database (http://www.cazy.org).

The severe acute respiratory syndrome-coronavirus replicative protein nsp9 is a single-stranded RNA-binding subunit unique in the RNA virus world

Abstract: The recently identified etiological agent of the severe acute respiratory syndrome (SARS) belongs to Coronaviridae (CoV), a family of viruses replicating by a poorly understood mechanism. Here, we report the crystal structure at 2.7-A resolution of nsp9, a hitherto uncharacterized subunit of the SARS-CoV replicative polyproteins. We show that SARS-CoV nsp9 is a single-stranded RNA-binding protein displaying a previously unreported, oligosaccharide/oligonucleotide fold-like fold. The presence of this type of protein has not been detected in the replicative complexes of RNA viruses, and its presence may reflect the unique and complex CoV viral replication/transcription machinery.

Complete Genome Sequence of the Complex Carbohydrate-Degrading Marine Bacterium, Saccharophagus degradans Strain 2-40T

Abstract: The marine bacterium Saccharophagus degradans strain 2-40 (Sde 2-40) is emerging as a vanguard of a recently discovered group of marine and estuarine bacteria that recycles complex polysaccharides. We report its complete genome sequence, analysis of which identifies an unusually large number of enzymes that degrade >10 complex polysaccharides. Not only is this an extraordinary range of catabolic capability, many of the enzymes exhibit unusual architecture including novel combinations of catalytic and substrate-binding modules. We hypothesize that many of these features are adaptations that facilitate depolymerization of complex polysaccharides in the marine environment. This is the first sequenced genome of a marine bacterium that can degrade plant cell walls, an important component of the carbon cycle that is not well-characterized in the marine environment.

The Pfam protein families database

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/).

SPAdes, a new genome assembly algorithm and its applications to single-cell sequencing ( 7th Annual SFAF Meeting, 2012)

Abstract: The lion's share of bacteria in various environments cannot be cloned in the laboratory and thus cannot be sequenced using existing technologies. A major goal of single-cell genomics is to complement gene-centric metagenomic data with whole-genome assemblies of uncultivated organisms. Assembly of single-cell data is challenging because of highly non-uniform read coverage as well as elevated levels of sequencing errors and chimeric reads. We describe SPAdes, a new assembler for both single-cell and standard (multicell) assembly, and demonstrate that it improves on the recently released E+V-SC assembler (specialized for single-cell data) and on popular assemblers Velvet and SoapDeNovo (for multicell data). SPAdes generates single-cell assemblies, providing information about genomes of uncultivatable bacteria that vastly exceeds what may be obtained via traditional metagenomics studies. SPAdes is available online ( http://bioinf.spbau.ru/spades ). It is distributed as open source software.

The Carbohydrate-Active EnZymes database (CAZy): an expert resource for Glycogenomics

Abstract: The Carbohydrate-Active Enzyme (CAZy) database is a knowledge-based resource specialized in the enzymes that build and breakdown complex carbohydrates and glycoconjugates. As of September 2008, the database describes the present knowledge on 113 glycoside hydrolase, 91 glycosyltransferase, 19 polysaccharide lyase, 15 carbohydrate esterase and 52 carbohydrate-binding module families. These families are created based on experimentally characterized proteins and are populated by sequences from public databases with significant similarity. Protein biochemical information is continuously curated based on the available literature and structural information. Over 6400 proteins have assigned EC numbers and 700 proteins have a PDB structure. The classification (i) reflects the structural features of these enzymes better than their sole substrate specificity, (ii) helps to reveal the evolutionary relationships between these enzymes and (iii) provides a convenient framework to understand mechanistic properties. This resource has been available for over 10 years to the scientific community, contributing to information dissemination and providing a transversal nomenclature to glycobiologists. More recently, this resource has been used to improve the quality of functional predictions of a number genome projects by providing expert annotation. The CAZy resource resides at URL: http://www.cazy.org/.

The carbohydrate-active enzymes database (CAZy) in 2013

Abstract: The Carbohydrate-Active Enzymes database (CAZy; http://www.cazy.org) provides online and continuously updated access to a sequence-based family classification linking the sequence to the specificity and 3D structure of the enzymes that assemble, modify and breakdown oligo- and polysaccharides. Functional and 3D structural information is added and curated on a regular basis based on the available literature. In addition to the use of the database by enzymologists seeking curated information on CAZymes, the dissemination of a stable nomenclature for these enzymes is probably a major contribution of CAZy. The past few years have seen the expansion of the CAZy classification scheme to new families, the development of subfamilies in several families and the power of CAZy for the analysis of genomes and metagenomes. This article outlines the changes that have occurred in CAZy during the past 5 years and presents our novel effort to display the resolution and the carbohydrate ligands in crystallographic complexes of CAZymes.

A SARS-CoV-2 protein interaction map reveals targets for drug repurposing.

Abstract: A newly described coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the causative agent of coronavirus disease 2019 (COVID-19), has infected over 2.3 million people, led to the death of more than 160,000 individuals and caused worldwide social and economic disruption1,2. There are no antiviral drugs with proven clinical efficacy for the treatment of COVID-19, nor are there any vaccines that prevent infection with SARS-CoV-2, and efforts to develop drugs and vaccines are hampered by the limited knowledge of the molecular details of how SARS-CoV-2 infects cells. Here we cloned, tagged and expressed 26 of the 29 SARS-CoV-2 proteins in human cells and identified the human proteins that physically associated with each of the SARS-CoV-2 proteins using affinity-purification mass spectrometry, identifying 332 high-confidence protein–protein interactions between SARS-CoV-2 and human proteins. Among these, we identify 66 druggable human proteins or host factors targeted by 69 compounds (of which, 29 drugs are approved by the US Food and Drug Administration, 12 are in clinical trials and 28 are preclinical compounds). We screened a subset of these in multiple viral assays and found two sets of pharmacological agents that displayed antiviral activity: inhibitors of mRNA translation and predicted regulators of the sigma-1 and sigma-2 receptors. Further studies of these host-factor-targeting agents, including their combination with drugs that directly target viral enzymes, could lead to a therapeutic regimen to treat COVID-19. A human–SARS-CoV-2 protein interaction map highlights cellular processes that are hijacked by the virus and that can be targeted by existing drugs, including inhibitors of mRNA translation and predicted regulators of the sigma receptors.