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Brancotte, B.

Publications and source records attributed to Brancotte, B..

6 recordsLinked to original sources

InSillyClo, a user-friendly web application to assist large-scale Golden Gate Cloning and MoClo workflows

Systems and synthetic biology developments often require the construction of many variants of a genetic circuit of interest, resulting in large-scale cloning campaigns. Golden Gate and Modular Cloning (MoClo), two powerful technologies enabling the scale-up of cloning workflows, play a central role for efficient circuit construction. These workflows include a number of dry-lab tasks, which are time-consuming and error-prone at scale. Currently, no software tool is available to handle these tasks in a dedicated, time-saving, and user-friendly manner. We present InSillyClo, an open-source web application to assist large-scale Golden Gate cloning and MoClo workflows. It supports an easy specification of genetic designs at any scale, followed by the automated generation of comprehensive workflow-related data. Moreover, InSillyClo leverages Modular Cloning with a versatile typing system of parts to generate user-defined workflows. InSillyClo is open source, accessible with or without user registration, and can also be used locally.

synthetic biology↗

Bacterial strain nomenclature in the genomic era: Life Identification Numbers using a gene-by-gene approach

Unified strain taxonomies are needed for the epidemiological surveillance of bacterial pathogens and international communication in microbiological research. Core genome multilocus sequence typing (cgMLST) holds great promise for standardized high-resolution strain genotyping. However, this approach faces challenges including classification instability and disconnection of new nomenclature from widely adopted classical MLST identifiers. This essay discusses the cgMLST-based Life Identification Number (LIN) method, recently proposed as a stable multilevel strain taxonomy system applicable to most bacterial pathogens. We describe how LIN codes are implemented and used in practice for precise strain definitions and epidemiological tracking. Glossary Multilocus sequence typing (MLST)A genotyping method applied mostly to microbial strains to study population structure and epidemiology, based on comparing the nucleotide sequences of a small number (typically seven) of housekeeping protein-coding genes. In MLST, allele numbers are assigned to each sequence variant (allele) of a given gene. The MLST genotype of a bacterial strain is defined by the combination of the allele numbers observed at the genes that are included in the genotyping scheme. A sequence type (ST) is assigned to each unique combination of alleles, called an MLST profile. MLST was invented in 1998 and became a de-facto standard taxonomy of bacterial strains, albeit at low resolution. Core genome MLSTAn extension of MLST that analyzes sequence variation across hundreds to thousands of conserved (core) genes, shared by all strains of a species, providing higher resolution typing for genomic epidemiology and evolutionary studies. cgMLST schemes typically comprise 2000 to 4000 genes, depending on the genome size and genetic variation (in terms of presence/absence of genes) within bacterial species. A core genome sequence type (cgST) can be assigned to unique cgMLST profiles, i.e., a unique combination of cgMLST allelic numbers. Whole Genome Sequencing (WGS)A method that determines the complete DNA sequence of an organisms genome in a single process, providing comprehensive information for comparative genetic analyses based on cgMLST or other analytic methods. Single Nucleotide Polymorphisms (SNPs)Variations at a single base position in the DNA sequence among individuals isolates, strains or species, used as genetic markers for studying for example, evolutionary relationships or strain identity. Average nucleotide identity (ANI)A measure of genomic similarity between two organisms, calculated as the average percentage of identical nucleotides in orthologous genomic regions; commonly used to assess species-level relatedness in prokaryotes. TaxonomyHere, we apply the word taxonomy to bacterial strains as a system of classifying, naming and identifying strains based on shared genetic characteristics as defined by e.g., cgMLST.

microbiology↗

A Comprehensive Resource for Exploring Antiphage Defense: DefenseFinder Webservice, Wiki and Databases.

In recent years, a vast number of novel antiphage defense mechanisms were uncovered. To facilitate the exploration of mechanistic, ecological, and evolutionary aspects related to antiphage defense systems, we released DefenseFinder in 2021 (Tesson et al., 2022). DefenseFinder is a bioinformatic program designed for the systematic identification of known antiphage defense mechanisms. The initial release of DefenseFinder v1.0.0 included 60 systems. Over the past three years, the number of antiphage systems incorporated into DefenseFinder has grown to 152. The increasing number of known systems makes it a challenge to enter the field and makes the interpretation of detections of antiphage systems difficult. Moreover, the rapid development of sequence-based predictions of structures offers novel possibilities of analysis and should be easily available. To overcome these challenges, we present a hub of resources on defense systems, including: 1) an updated version of DefenseFinder with a web-service search function, 2) a community-curated repository of knowledge on the systems, and 3) precomputed databases, which include annotations done on RefSeq genomes and structure predictions generated by AlphaFold. These pages can be freely accessed for users as a starting point on their journey to better understand a given system. We anticipate that these resources will foster the use of bioinformatics in the study of antiphage systems and will serve the community of researchers who study antiphage systems. This resource is available at: https://defensefinder.mdmlab.fr.

genomics↗

Trait selection strategy in multi-trait GWAS: Boosting SNPs discoverability

Since the first Genome-Wide Association Studies (GWAS), thousands of variant-trait associations have been discovered. However, the sample size required to detect additional variants using standard univariate association screening is increasingly prohibitive. Multi-trait GWAS offers a relevant alternative: it can improve statistical power and lead to new insights about gene function and the joint genetic architecture of human phenotypes. Although many methodological hurdles of multi-trait testing have been discussed, the strategy to select trait, among overwhelming possibilities, has been overlooked. In this study, we conducted extensive multi-trait tests using JASS (Joint Analysis of Summary Statistics) and assessed which genetic features of the analysed sets were associated with anincreased detection of variants as compared to univariate screening. Our analyses identified multiple factors associated with the gain in the association detection in multi-trait tests. Together, these factors of the analysed sets are predictive of the gain of the multi-trait test (Pearsons {rho} equal to 0.43 between the observed and predicted gain, P < 1.6 x 10-60). Applying an alternative multi-trait approach (MTAG, multi-trait analysis of GWAS), we found that in most scenarios but particularly those with larger numbers of traits, JASS outperformed MTAG. Finally, we benchmark several strategies to select set of traits including the prevalent strategy of selecting clinically similar traits, which systematically underperformed selecting clinically heterogenous traits or selecting sets that issued from our data-driven models. This work provides a unique picture of the determinant of multi-trait GWAS statistical power and outline practical strategies for multi-trait testing.

genetics↗

BioConvert: a comprehensive format converter for life sciences

AO_SCPLOWBSTRACTC_SCPLOWBioinformatics is a field known for the numerous standards and formats that have been developed over the years. This plethora of formats, sometimes complementary, and often redundant, poses many challenges to bioinformatics data analysts. They constantly need to find the best tool to convert their data into the suitable format, which is often a complex, technical and time consuming task. Moreover, these small yet important tasks are often difficult to make reproducible. To over-come these difficulties, we initiated BioConvert, a collaborative project to facilitate the conversion of life science data from one format to another. BioConvert aggregates existing software within a single framework and complemented them with original code when needed. It provides a common interface to make the user experience more streamlined instead of having to learn tens of them. Currently, BioConvert supports about 50 formats and 100 direct conversions in areas such as alignment, sequencing, phylogeny, and variant calling. In addition to being useful for end-users, BioConvert can also be utilized by developers as a universal benchmarking framework for evaluating and comparing numerous conversion tools. Additionally, we provide a web server implementing an online user-friendly interface to BioConvert, hence allowing direct use for the community.

bioinformatics↗

Genomic library of Bordetella

BackgroundThe re-emergence of whooping cough and geographic disparities in vaccine escape or antimicrobial resistance dynamics, underline the importance of a unified definition of Bordetella pertussis strains. Understanding of the evolutionary adaptations of Bordetella pathogens to humans and animals requires comparative studies with environmental bordetellae. MethodsWe have set-up a unified library of Bordetella genomes by merging previously existing Oxford and Pasteur databases, importing genomes from public repositories, and developing harmonized genotyping schemes. We developed a genus-wide cgMLST genotyping scheme and incorporated a previous B. pertussis cgMLST scheme. Specific schemes were developed to define antigenic, virulence and macrolide resistance profiles. Genomic sequencing of 83 French B. bronchiseptica isolates and of B. tumulicola, B. muralis and B. tumbae type strains was performed. ResultsThe public library currently includes 2,581 Bordetella isolates and their provenance data, and 2,084 genomes. The "classical Bordetella" (B. bronchiseptica, B. parapertussis and B. pertussis), which form a single genomic species (B. bronchiseptica genomic species, BbGS), were overrepresented (n=2,382). The phylogenetic analysis of Bordetella genomes associated the three novel species B. tumulicola, B. muralis and B. tumbae in a clade with B. petrii and revealed 18 yet undescribed species. A sister lineage of the classical bordetellae, provisionally named Bbs lineage II, was uncovered and may represent a novel species (average nucleotide identity with BbGS strains: [~]95%). It comprised strain HT200 from India, two strains of genogroup 6 from the USA and six clinical isolates from France; this lineage lacked ptxP and its fim2 gene was divergent. Within B. pertussis, vaccine antigen sequence types marked important phylogenetic subdivisions, and macrolide resistance markers (23S_rRNA allele 13 and fhaB3) confirmed the current restriction of this phenotype in China with few exceptions. ConclusionsThe genomic platform provides an expandable resource for unified genotyping of Bordetella strains and will facilitate collective evolutionary and epidemiological understanding of the re-emergence of whooping cough and other Bordetella infections. Data summaryBordetella genomes list and accession numbers: Supplementary Table S4 Bordetella genus phylogeny dataset (92 isolates): https://bigsdb.pasteur.fr/cgi-bin/bigsdb/bigsdb.pl?db=pubmlst_bordetella_isolates&page=query&project_list=23&submit=1 B. bronchiseptica phylogeny dataset (213 isolates): https://bigsdb.pasteur.fr/cgi-bin/bigsdb/bigsdb.pl?db=pubmlst_bordetella_isolates&page=query&project_list=24&submit=1 B. pertussis phylogeny (124 isolates): https://bigsdb.pasteur.fr/cgi-bin/bigsdb/bigsdb.pl?db=pubmlst_bordetella_isolates&page=query&project_list=25&submit=1 iTOL interactive trees: https://itol.embl.de/shared/1l7Fw0AvKOoCF

microbiology↗