references.bib

@article{larralde_pyhmmer_2023,
	title = {{PyHMMER}: a {Python} library binding to {HMMER} for efficient sequence analysis},
	volume = {39},
	issn = {1367-4811},
	shorttitle = {{PyHMMER}},
	url = {https://doi.org/10.1093/bioinformatics/btad214},
	doi = {10.1093/bioinformatics/btad214},
	abstract = {PyHMMER provides Python integration of the popular profile Hidden Markov Model software HMMER via Cython bindings. This allows the annotation of protein sequences with profile HMMs and building new ones directly with Python. PyHMMER increases flexibility of use, allowing creating queries directly from Python code, launching searches, and obtaining results without I/O, or accessing previously unavailable statistics like uncorrected P-values. A new parallelization model greatly improves performance when running multithreaded searches, while producing the exact same results as HMMER.PyHMMER supports all modern Python versions (Python 3.6+) and similar platforms as HMMER (x86 or PowerPC UNIX systems). Pre-compiled packages are released via PyPI (https://pypi.org/project/pyhmmer/) and Bioconda (https://anaconda.org/bioconda/pyhmmer). The PyHMMER source code is available under the terms of the open-source MIT licence and hosted on GitHub (https://github.com/althonos/pyhmmer); its documentation is available on ReadTheDocs (https://pyhmmer.readthedocs.io).},
	number = {5},
	urldate = {2024-05-22},
	journal = {Bioinformatics},
	author = {Larralde, Martin and Zeller, Georg},
	month = may,
	year = {2023},
	pages = {btad214},
	file = {Full Text PDF:/home/jarnoux/Zotero/storage/GZI2ZE28/Larralde et Zeller - 2023 - PyHMMER a Python library binding to HMMER for eff.pdf:application/pdf},
}

@article{johnson_core_2023,
	title = {Core defense hotspots within {Pseudomonas} aeruginosa are a consistent and rich source of anti-phage defense systems},
	volume = {51},
	issn = {0305-1048},
	url = {https://doi.org/10.1093/nar/gkad317},
	doi = {10.1093/nar/gkad317},
	abstract = {Bacteria use a diverse arsenal of anti-phage immune systems, including CRISPR-Cas and restriction enzymes. Recent advances in anti-phage system discovery and annotation tools have unearthed many unique systems, often encoded in horizontally transferred defense islands, which can be horizontally transferred. Here, we developed Hidden Markov Models (HMMs) for defense systems and queried microbial genomes on the NCBI database. Out of the 30 species with \>200 completely sequenced genomes, our analysis found Pseudomonas aeruginosa exhibits the greatest diversity of anti-phage systems, as measured by Shannon entropy. Using network analysis to identify the common neighbors of anti-phage systems, we identified two core defense hotspot loci (cDHS1 and cDHS2). cDHS1 is up to 224 kb (median: 26 kb) with varied arrangements of more than 30 distinct immune systems across isolates, while cDHS2 has 24 distinct systems (median: 6 kb). Both cDHS regions are occupied in a majority of P. aeruginosa isolates. Most cDHS genes are of unknown function potentially representing new anti-phage systems, which we validated by identifying a novel anti-phage system (Shango) commonly encoded in cDHS1. Identifying core genes flanking immune islands could simplify immune system discovery and may represent popular landing spots for diverse MGEs carrying anti-phage systems.},
	number = {10},
	urldate = {2024-03-18},
	journal = {Nucleic Acids Research},
	author = {Johnson, Matthew C and Laderman, Eric and Huiting, Erin and Zhang, Chi and Davidson, Alan and Bondy-Denomy, Joseph},
	month = jun,
	year = {2023},
	pages = {4995--5005},
	file = {Full Text PDF:/home/jarnoux/Zotero/storage/PUCX9V32/Johnson et al. - 2023 - Core defense hotspots within Pseudomonas aeruginos.pdf:application/pdf;Snapshot:/home/jarnoux/Zotero/storage/NJKMM3RT/7151348.html:text/html},
}

@article{flores_ramos_genomic_2021,
	title = {Genomic {Stability} and {Genetic} {Defense} {Systems} in {Dolosigranulum} pigrum, a {Candidate} {Beneficial} {Bacterium} from the {Human} {Microbiome}},
	volume = {6},
	url = {https://journals.asm.org/doi/10.1128/msystems.00425-21},
	doi = {10.1128/msystems.00425-21},
	abstract = {Dolosigranulum pigrum is positively associated with indicators of health in multiple epidemiological studies of human nasal microbiota. Knowledge of the basic biology of D. pigrum is a prerequisite for evaluating its potential for future therapeutic use; however, such data are very limited. To gain insight into D. pigrum’s chromosomal structure, pangenome, and genomic stability, we compared the genomes of 28 D. pigrum strains that were collected across 20 years. Phylogenomic analysis showed closely related strains circulating over this period and closure of 19 genomes revealed highly conserved chromosomal synteny. Gene clusters involved in the mobilome and in defense against mobile genetic elements (MGEs) were enriched in the accessory genome versus the core genome. A systematic analysis for MGEs identified the first candidate D. pigrum prophage and insertion sequence. A systematic analysis for genetic elements that limit the spread of MGEs, including restriction modification (RM), CRISPR-Cas, and deity-named defense systems, revealed strain-level diversity in host defense systems that localized to specific genomic sites, including one RM system hot spot. Analysis of CRISPR spacers pointed to a wealth of MGEs against which D. pigrum defends itself. These results reveal a role for horizontal gene transfer and mobile genetic elements in strain diversification while highlighting that in D. pigrum this occurs within the context of a highly stable chromosomal organization protected by a variety of defense mechanisms.
IMPORTANCE Dolosigranulum pigrum is a candidate beneficial bacterium with potential for future therapeutic use. This is based on its positive associations with characteristics of health in multiple studies of human nasal microbiota across the span of human life. For example, high levels of D. pigrum nasal colonization in adults predicts the absence of Staphylococcus aureus nasal colonization. Also, D. pigrum nasal colonization in young children is associated with healthy control groups in studies of middle ear infections. Our analysis of 28 genomes revealed a remarkable stability of D. pigrum strains colonizing people in the United States across a 20-year span. We subsequently identified factors that can influence this stability, including genomic stability, phage predators, the role of MGEs in strain-level variation, and defenses against MGEs. Finally, these D. pigrum strains also lacked predicted virulence factors. Overall, these findings add additional support to the potential for D. pigrum as a therapeutic bacterium.},
	number = {5},
	urldate = {2024-03-18},
	journal = {mSystems},
	author = {Flores Ramos, Stephany and Brugger, Silvio D. and Escapa, Isabel Fernandez and Skeete, Chelsey A. and Cotton, Sean L. and Eslami, Sara M. and Gao, Wei and Bomar, Lindsey and Tran, Tommy H. and Jones, Dakota S. and Minot, Samuel and Roberts, Richard J. and Johnston, Christopher D. and Lemon, Katherine P.},
	month = sep,
	year = {2021},
	note = {Publisher: American Society for Microbiology},
	pages = {10.1128/msystems.00425--21},
	file = {Full Text PDF:/home/jarnoux/Zotero/storage/HDZSWLWB/Flores Ramos et al. - 2021 - Genomic Stability and Genetic Defense Systems in D.pdf:application/pdf},
}

@article{hardy_immunite_2023,
	title = {Immunité bactérienne : à la découverte d’un nouveau monde},
	volume = {39},
	copyright = {© 2023 médecine/sciences – Inserm},
	issn = {0767-0974, 1958-5381},
	shorttitle = {Immunité bactérienne},
	url = {https://www.medecinesciences.org/articles/medsci/abs/2023/10/msc230130/msc230130.html},
	doi = {10.1051/medsci/2023163},
	abstract = {Les virus sont des parasites qui infectent tous les organismes vivants, et les bactéries n’y font pas exception. Pour se défendre contre leurs virus (les bactériophages ou phages), les bactéries se sont dotées d’un éventail de mécanismes élaborés, dont la découverte et la compréhension sont en pleine expansion. Dans les années 2000, seuls quelques systèmes de défense étaient connus et deux semblaient présents chez la plupart des bactéries. En 2018, une nouvelle méthode fondée sur l’analyse des génomes a révélé l’existence potentielle de nombreux autres. Plus de 150 nouveaux systèmes anti-phages ont été découverts au cours des cinq dernières années. On estime maintenant qu’il en existe probablement des milliers. Cette formidable diversité, qui est à mettre en parallèle avec la considérable diversité virale, s’exprime tant en termes de combinaisons de systèmes possibles dans les génomes bactériens que de mécanismes moléculaires. Une des observations les plus surprenantes qui émerge est la découverte de similarités entre certains systèmes de défense bactériens et des mécanismes antiviraux eucaryotes. Contrairement au paradigme jusqu’alors en place, des organismes aussi différents que des champignons, des plantes, des bactéries ou des êtres humains partagent certaines stratégies moléculaires pour combattre des infections virales, suggérant qu’une part sous-estimée de l’immunité antivirale eucaryote a directement évolué à partir des systèmes de défense bactériens.},
	language = {fr},
	number = {11},
	urldate = {2024-03-18},
	journal = {médecine/sciences},
	author = {Hardy, Aël and Shomar, Helena and Bernheim, Aude},
	month = nov,
	year = {2023},
	note = {Number: 11
Publisher: EDP Sciences},
	pages = {862--868},
	file = {Full Text PDF:/home/jarnoux/Zotero/storage/YDCDU274/Hardy et al. - 2023 - Immunité bactérienne  à la découverte d’un nouvea.pdf:application/pdf},
}

@article{abby_macsyfinder_2014,
	title = {{MacSyFinder}: {A} {Program} to {Mine} {Genomes} for {Molecular} {Systems} with an {Application} to {CRISPR}-{Cas} {Systems}},
	volume = {9},
	issn = {1932-6203},
	shorttitle = {{MacSyFinder}},
	url = {https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0110726},
	doi = {10.1371/journal.pone.0110726},
	abstract = {Motivation Biologists often wish to use their knowledge on a few experimental models of a given molecular system to identify homologs in genomic data. We developed a generic tool for this purpose. Results Macromolecular System Finder (MacSyFinder) provides a flexible framework to model the properties of molecular systems (cellular machinery or pathway) including their components, evolutionary associations with other systems and genetic architecture. Modelled features also include functional analogs, and the multiple uses of a same component by different systems. Models are used to search for molecular systems in complete genomes or in unstructured data like metagenomes. The components of the systems are searched by sequence similarity using Hidden Markov model (HMM) protein profiles. The assignment of hits to a given system is decided based on compliance with the content and organization of the system model. A graphical interface, MacSyView, facilitates the analysis of the results by showing overviews of component content and genomic context. To exemplify the use of MacSyFinder we built models to detect and class CRISPR-Cas systems following a previously established classification. We show that MacSyFinder allows to easily define an accurate “Cas-finder” using publicly available protein profiles. Availability and Implementation MacSyFinder is a standalone application implemented in Python. It requires Python 2.7, Hmmer and makeblastdb (version 2.2.28 or higher). It is freely available with its source code under a GPLv3 license at https://github.com/gem-pasteur/macsyfinder. It is compatible with all platforms supporting Python and Hmmer/makeblastdb. The “Cas-finder” (models and HMM profiles) is distributed as a compressed tarball archive as Supporting Information.},
	language = {en},
	number = {10},
	urldate = {2022-04-04},
	journal = {PLOS ONE},
	author = {Abby, Sophie S. and Néron, Bertrand and Ménager, Hervé and Touchon, Marie and Rocha, Eduardo P. C.},
	month = oct,
	year = {2014},
	note = {Publisher: Public Library of Science},
	keywords = {Bacterial genomics, CRISPR, Genetics, Genomics, Hidden Markov models, Macromolecules, Operons, Sequence similarity searching},
	pages = {e110726},
	file = {Full Text PDF:/home/jarnoux/Zotero/storage/QHAZMUDG/Abby et al. - 2014 - MacSyFinder A Program to Mine Genomes for Molecul.pdf:application/pdf;Snapshot:/home/jarnoux/Zotero/storage/8FYCIN9Z/article.html:text/html},
}