MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes

Néron, Bertrand; Denise, Rémi; Coluzzi, Charles; Touchon, Marie; Rocha, Eduardo P. C.; Abby, Sophie S.

doi:10.24072/pcjournal.250

Cited by 25 publications

(16 citation statements)

References 41 publications

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“…Finally, for Lamassu-Fam 29 , we separated the systems into different subsystems according to the evolving literature on the topic. Models were also adapted to the latest version of MacSyFinder 30 To evaluate the proportion of newly detected systems, we ran DefenseFinder v1.2.3 on the RefSeq complete genome database of prokaryotes (Bacteria N = 22,422; Archaea N = 381). We found a total of 152,386 different systems, among which 33% correspond to systems present in v1.2.3 but absent from v1.0.0 (Figure 1B ).…”

Section: Resultsmentioning

confidence: 99%

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

Tesson,

Planel,

Egorov

et al. 2024

Preprint

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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 all 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) a search tool (DefenseFinder as a web service) 2) a knowledge base, and 3) precomputed databases (results of DefenseFinder ran on RefSeq database, predicted structure database computed with 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.

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Section: Resultsmentioning

confidence: 99%

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

Tesson,

Planel,

Egorov

et al. 2024

Preprint

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“…Plasmids were classified according to the different schemes available: (1) Plasmids were assigned to a Plasmid Taxonomic Unit (PTU) when possible using COPLA, version 1.0 57 ; (2) Each plasmid was assigned to a Incompatibility (Inc) group according to PlasmidFinder, version 2.0.1 (database available on January 2023) 58 ; (3) Plasmids encoding a relaxase and/or a mating pair formation (MPF) system were assigned to a specific MOB group and MPF type by the module CONJscan of MacSyFinder, version 2.0 59 .…”

Section: Methodsmentioning

confidence: 99%

Identification of novel origins of transfer across bacterial plasmids

Ares-Arroyo,

Nucci,

Rocha

2024

Preprint

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Conjugative plasmids are important drivers of bacterial evolution, but most plasmids lack genes for conjugation. It is currently not known if the latter can transfer because origins of transfer by conjugation (oriT), which would allow their mobilization by conjugative plasmids, are poorly known. Here, we identify and characterize occurrences of known oriT families across thousands of plasmids confirming that most conjugative and mobilizable plasmids still lack identifiable families of oriTs. They reveal clear patterns in terms of intergenic position, distance to the relaxases, and MOB-type association. This allowed to develop a computational method to discover novel oriTs. As a proof of concept, we identify 21 novel oriTs from the nosocomial pathogens Escherichia coli, Klebsiella pneumoniae, and Acinetobacter baumannii, some of them responsible for the mobility of critical antimicrobial resistance genes. These 21 oriT families share key characteristics of the others and fill most of the missing diversity of oriTs in relaxase-encoding plasmids both in terms of frequency and phylogeny. We confirmed experimentally the function of six of them. The ability to identify novel oriTs paves the way to explore conjugation across bacterial plasmids, notably among the majority lacking conjugation-related genes.

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“…Beav incorporates additional annotation tools that identify other conserved gene clusters or provide further context for gene function. MacSyFinder with the TXSScan models is used to identify genes and gene clusters encoding for diverse secretion systems 24, 55 . DefenseFinder is used to characterize the presence of microbial defense systems 56 .…”

Section: Methodsmentioning

confidence: 99%

“…Comprehensive characterization of specific genetic regions of interest requires multiple genome annotation tools. Many independent tools for the annotation of specific genetic systems have recently been published 24–28 . However, the results of these separate analyses must be combined to get a full picture of gene function and context.…”

Section: Introductionmentioning

confidence: 99%

Beav: A bacterial genome and mobile element annotation pipeline

Jung,

Rahman,

Schiffer

et al. 2024

Preprint

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Comprehensive and accurate genome annotation is crucial for inferring the predicted functions of an organism. Numerous tools exist to annotate genes, gene clusters, mobile genetic elements, and other diverse features. However, these tools and pipelines can be difficult to install and run, be specialized for a particular element or feature, or lack annotations for larger elements that provide important genomic context. Integrating results across analyses is also important for understanding gene function. To address these challenges, we present the Beav annotation pipeline. Beav is a command-line tool that automates the annotation of bacterial genome sequences, mobile genetic elements, molecular systems and gene clusters, key regulatory features, and other elements. Beav uses existing tools in addition to custom models, scripts, and databases to annotate diverse elements, systems, and sequence features. Custom databases for plant-associated microbes are incorporated to improve annotation of key virulence and symbiosis genes in agriculturally important pathogens and mutualists. Beav includes an optional Agrobacterium-specific pipeline that identifies and classifies oncogenic plasmids and annotates plasmid-specific features. Following the completion of all analyses, annotations are consolidated to produce a single comprehensive output. Finally, Beav generates publication-quality genome and plasmid maps. Beav is on Bioconda and is available for download at https://github.com/weisberglab/beav.

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MacSyFinder v2: Improved modelling and search engine to identify molecular systems in genomes

Cited by 25 publications

References 41 publications

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

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

Identification of novel origins of transfer across bacterial plasmids

Beav: A bacterial genome and mobile element annotation pipeline

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