Integron cassettes integrate into bacterial genomes via widespread non-classical attG sites.

Integrons are genetic elements involved in bacterial adaptation which capture, shuffle and express genes encoding adaptive functions embedded in cassettes. These events are governed by the integron integrase through site-specific recombination between attC and attI integron sites. Using computational and molecular genetic approaches, here we demonstrate that the integrase also catalyses cassette integration into bacterial genomes outside of its known att sites. Once integrated, these cassettes can be expressed if located near bacterial promoters and can be excised at the integration point or outside, inducing chromosomal modifications in the latter case. Analysis of more than 5 × 105 independent integration events revealed a very large genomic integration landscape. We identified consensus recombination sequences, named attG sites, which differ greatly in sequence and structure from classical att sites. These results unveil an alternative route for dissemination of adaptive functions in bacteria and expand the role of integrons in bacterial evolution.

Expanding the stdpopsim species catalog, and lessons learned for realistic genome simulations.

Simulation is a key tool in population genetics for both methods development and empirical research, but producing simulations that recapitulate the main features of genomic datasets remains a major obstacle. Today, more realistic simulations are possible thanks to large increases in the quantity and quality of available genetic data, and the sophistication of inference and simulation software. However, implementing these simulations still requires substantial time and specialized knowledge. These challenges are especially pronounced for simulating genomes for species that are not well-studied, since it is not always clear what information is required to produce simulations with a level of realism sufficient to confidently answer a given question. The community-developed framework stdpopsim seeks to lower this barrier by facilitating the simulation of complex population genetic models using up-to-date information. The initial version of stdpopsim focused on establishing this framework using six well-characterized model species (Adrion et al., 2020). Here, we report on major improvements made in the new release of stdpopsim (version 0.2), which includes a significant expansion of the species catalog and substantial additions to simulation capabilities. Features added to improve the realism of the simulated genomes include non-crossover recombination and provision of species-specific genomic annotations. Through community-driven efforts, we expanded the number of species in the catalog more than threefold and broadened coverage across the tree of life. During the process of expanding the catalog, we have identified common sticking points and developed the best practices for setting up genome-scale simulations. We describe the input data required for generating a realistic simulation, suggest good practices for obtaining the relevant information from the literature, and discuss common pitfalls and major considerations. These improvements to stdpopsim aim to further promote the use of realistic whole-genome population genetic simulations, especially in non-model organisms, making them available, transparent, and accessible to everyone.

Cultural transmission of reproductive success impacts genomic diversity, coalescent tree topologies, and demographic inferences.

Cultural transmission of reproductive success has been observed in many human populations as well as other animals. Cultural transmission of reproductive success consists of a positive correlation of nongenetic origin between the progeny size of parents and children. This correlation can result from various factors, such as the social influence of parents on their children, the increase of children's survival through allocare from uncles and aunts, or the transmission of resources. Here, we study the evolution of genomic diversity over time under cultural transmission of reproductive success. Cultural transmission of reproductive success has a threefold impact on population genetics: (1) the effective population size decreases when cultural transmission of reproductive success starts, mimicking a population contraction, and increases back to its original value when cultural transmission of reproductive success stops; (2) coalescent tree topologies are distorted under cultural transmission of reproductive success, with higher imbalance and a higher number of polytomies; and (3) branch lengths are reduced nonhomogenously, with a higher impact on older branches. Under long-lasting cultural transmission of reproductive success, the effective population size stabilizes but the distortion of tree topology and the nonhomogenous branch length reduction remain, yielding U-shaped site frequency spectra under a constant population size. We show that this yields a bias in site frequency spectra-based demographic inference. Considering that cultural transmission of reproductive success was detected in numerous human and animal populations worldwide, one should be cautious because inferring population past histories from genomic data can be biased by this cultural process.

dnadna: a deep learning framework for population genetics inference.

MOTIVATION: We present dnadna, a flexible python-based software for deep learning inference in population genetics. It is task-agnostic and aims at facilitating the development, reproducibility, dissemination and re-usability of neural networks designed for population genetic data. RESULTS: dnadna defines multiple user-friendly workflows. First, users can implement new architectures and tasks, while benefiting from dnadna utility functions, training procedure and test environment, which saves time and decreases the likelihood of bugs. Second, the implemented networks can be re-optimized based on user-specified training sets and/or tasks. Newly implemented architectures and pre-trained networks are easily shareable with the community for further benchmarking or other applications. Finally, users can apply pre-trained networks in order to predict evolutionary history from alternative real or simulated genetic datasets, without requiring extensive knowledge in deep learning or coding in general. dnadna comes with a peer-reviewed, exchangeable neural network, allowing demographic inference from SNP data, that can be used directly or retrained to solve other tasks. Toy networks are also available to ease the exploration of the software, and we expect that the range of available architectures will keep expanding thanks to community contributions. AVAILABILITY AND IMPLEMENTATION: dnadna is a Python (≥3.7) package, its repository is available at gitlab.com/mlgenetics/dnadna and its associated documentation at mlgenetics.gitlab.io/dnadna/.

Systematic and quantitative view of the antiviral arsenal of prokaryotes.

Bacteria and archaea have developed multiple antiviral mechanisms, and genomic evidence indicates that several of these antiviral systems co-occur in the same strain. Here, we introduce DefenseFinder, a tool that automatically detects known antiviral systems in prokaryotic genomes. We use DefenseFinder to analyse 21000 fully sequenced prokaryotic genomes, and find that antiviral strategies vary drastically between phyla, species and strains. Variations in composition of antiviral systems correlate with genome size, viral threat, and lifestyle traits. DefenseFinder will facilitate large-scale genomic analysis of antiviral defense systems and the study of host-virus interactions in prokaryotes.

CRISPR-Cas and restriction-modification team up to achieve long-term immunity.

Bacteria have been shown to harbor a growing arsenal of various defense systems against phages. Maguin et al. have uncovered how two of the most frequent defense systems interact: the clustered regularly interspaced short palindromic repeats-Cas (CRISPR-Cas) system recycles by-products of the restriction-modification (RM) system to increase bacterial defense in the long run.

IntegronFinder 2.0: Identification and Analysis of Integrons across Bacteria, with a Focus on Antibiotic Resistance in Klebsiella.

Integrons are flexible gene-exchanging platforms that contain multiple cassettes encoding accessory genes whose order is shuffled by a specific integrase. Integrons embedded within mobile genetic elements often contain multiple antibiotic resistance genes that they spread among nosocomial pathogens and contribute to the current antibiotic resistance crisis. However, most integrons are presumably sedentary and encode a much broader diversity of functions. IntegronFinder is a widely used software to identify novel integrons in bacterial genomes, but has aged and lacks some useful functionalities to handle very large datasets of draft genomes or metagenomes. Here, we present IntegronFinder version 2. We have updated the code, improved its efficiency and usability, adapted the output to incomplete genome data, and added a few novel functions. We describe these changes and illustrate the relevance of the program by analyzing the distribution of integrons across more than 20,000 fully sequenced genomes. We also take full advantage of its novel capabilities to analyze close to 4000 Klebsiella pneumoniae genomes for the presence of integrons and antibiotic resistance genes within them. Our data show that K. pneumoniae has a large diversity of integrons and the largest mobile integron in our database of plasmids. The pangenome of these integrons contains a total of 165 different gene families with most of the largest families being related with resistance to numerous types of antibiotics. IntegronFinder is a free and open-source software available on multiple public platforms.

Deep learning for population size history inference: Design, comparison and combination with approximate Bayesian computation.

For the past decades, simulation-based likelihood-free inference methods have enabled researchers to address numerous population genetics problems. As the richness and amount of simulated and real genetic data keep increasing, the field has a strong opportunity to tackle tasks that current methods hardly solve. However, high data dimensionality forces most methods to summarize large genomic data sets into a relatively small number of handcrafted features (summary statistics). Here, we propose an alternative to summary statistics, based on the automatic extraction of relevant information using deep learning techniques. Specifically, we design artificial neural networks (ANNs) that take as input single nucleotide polymorphic sites (SNPs) found in individuals sampled from a single population and infer the past effective population size history. First, we provide guidelines to construct artificial neural networks that comply with the intrinsic properties of SNP data such as invariance to permutation of haplotypes, long scale interactions between SNPs and variable genomic length. Thanks to a Bayesian hyperparameter optimization procedure, we evaluate the performance of multiple networks and compare them to well-established methods like Approximate Bayesian Computation (ABC). Even without the expert knowledge of summary statistics, our approach compares fairly well to an ABC approach based on handcrafted features. Furthermore, we show that combining deep learning and ABC can improve performance while taking advantage of both frameworks. Finally, we apply our approach to reconstruct the effective population size history of cattle breed populations.

Structure-specific DNA recombination sites: Design, validation, and machine learning-based refinement.

Recombination systems are widely used as bioengineering tools, but their sites have to be highly similar to a consensus sequence or to each other. To develop a recombination system free of these constraints, we turned toward attC sites from the bacterial integron system: single-stranded DNA hairpins specifically recombined by the integrase. Here, we present an algorithm that generates synthetic attC sites with conserved structural features and minimal sequence-level constraints. We demonstrate that all generated sites are functional, their recombination efficiency can reach 60%, and they can be embedded into protein coding sequences. To improve recombination of less efficient sites, we applied large-scale mutagenesis and library enrichment coupled to next-generation sequencing and machine learning. Our results validated the efficiency of this approach and allowed us to refine synthetic attC design principles. They can be embedded into virtually any sequence and constitute a unique example of a structure-specific DNA recombination system.

Author Correction: The chromosomal organization of horizontal gene transfer in bacteria.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Intracellular Positioning Systems Limit the Entropic Eviction of Secondary Replicons Toward the Nucleoid Edges in Bacterial Cells.

Bacterial genomes, organized intracellularly as nucleoids, are composed of the main chromosome coexisting with different types of secondary replicons. Secondary replicons are major drivers of bacterial adaptation by gene exchange. They are highly diverse in type and size, ranging from less than 2 to more than 1000 kb, and must integrate with bacterial physiology, including to the nucleoid dynamics, to limit detrimental costs leading to their counter-selection. We show that large DNA circles, whether from a natural plasmid or excised from the chromosome tend to localize in a dynamic manner in a zone separating the nucleoid from the cytoplasm at the edge of the nucleoid. This localization is in good agreement with silico simulations of DNA circles in the nucleoid volume. Subcellular positioning systems counteract this tendency, allowing replicons to enter the nucleoid space. In enterobacteria, these systems are found in replicons above 25 kb, defining the limit with small randomly segregated plasmids. Larger replicons carry at least one of the three described family of systems, ParAB, ParRM, and StbA. Replicons above 180 kb all carry a ParAB system, suggesting this system is specifically required in the cases of large replicons. Simulations demonstrated that replicon size profoundly affects localization, compaction, and dynamics of DNA circles in the nucleoid volume. The present work suggests that presence of partition systems on the larger plasmids or chromids is not only due to selection for accurate segregation but also to counteract their unmixing with the chromosome and consequent exclusion from the nucleoid.

Identifying Conjugative Plasmids and Integrative Conjugative Elements with CONJscan.

We present a computational method to identify conjugative systems in plasmids and chromosomes using the CONJscan module of MacSyFinder. The method relies on the identification of the protein components of the system using hidden Markov model profiles and then checking that the composition and genetic organization of the system is consistent with that expected from a conjugative system. The method can be assessed online using the Galaxy workflow or locally using a standalone software. The latter version allows to modify the models of the module (i.e., to change the expected components, their number, and their organization).CONJscan identifies conjugative systems, but when the mobile genetic element is integrative (ICE), one often also wants to delimit it from the chromosome. We present a method, with a script, to use the results of CONJscan and comparative genomics to delimit ICE in chromosomes. The method provides a visual representation of the ICE location. Together, these methods facilitate the identification of conjugative elements in bacterial genomes.

A simple, reproducible and cost-effective procedure to analyse gut phageome: from phage isolation to bioinformatic approach.

The microbiota of the human gut is a complex and rich community where bacteria and their viruses, the bacteriophages, are dominant. There are few studies on the phage community and no clear standard for isolating them, sequencing and analysing their genomes. Since this makes comparisons between studies difficult, we aimed at defining an easy, low-cost, and reproducible methodology. We analysed five different techniques to isolate phages from human adult faeces and developed an approach to analyse their genomes in order to quantify contamination and classify phage contigs in terms of taxonomy and lifestyle. We chose the polyethylene glycol concentration method to isolate phages because of its simplicity, low cost, reproducibility, and of the high number and diversity of phage sequences that we obtained. We also tested the reproducibility of this method with multiple displacement amplification (MDA) and showed that MDA severely decreases the phage genetic diversity of the samples and the reproducibility of the method. Lastly, we studied the influence of sequencing depth on the analysis of phage diversity and observed the beginning of a plateau for phage contigs at 20,000,000 reads. This work contributes to the development of methods for the isolation of phages in faeces and for their comparative analysis.

Host Range and Genetic Plasticity Explain the Coexistence of Integrative and Extrachromosomal Mobile Genetic Elements.

Self-transmissible mobile genetic elements drive horizontal gene transfer between prokaryotes. Some of these elements integrate in the chromosome, whereas others replicate autonomously as plasmids. Recent works showed the existence of few differences, and occasional interconversion, between the two types of elements. Here, we enquired on why evolutionary processes have maintained the two types of mobile genetic elements by comparing integrative and conjugative elements (ICE) with extrachromosomal ones (conjugative plasmids) of the highly abundant MPFT conjugative type. We observed that plasmids encode more replicases, partition systems, and antibiotic resistance genes, whereas ICEs encode more integrases and metabolism-associated genes. ICEs and plasmids have similar average sizes, but plasmids are much more variable, have more DNA repeats, and exchange genes more frequently. On the other hand, we found that ICEs are more frequently transferred between distant taxa. We propose a model where the different genetic plasticity and amplitude of host range between elements explain the co-occurrence of integrative and extrachromosomal elements in microbial populations. In particular, the conversion from ICE to plasmid allows ICE to be more plastic, while the conversion from plasmid to ICE allows the expansion of the element's host range.

The chromosomal organization of horizontal gene transfer in bacteria.

Bacterial adaptation is accelerated by the acquisition of novel traits through horizontal gene transfer, but the integration of these genes affects genome organization. We found that transferred genes are concentrated in only ~1% of the chromosomal regions (hotspots) in 80 bacterial species. This concentration increases with genome size and with the rate of transfer. Hotspots diversify by rapid gene turnover; their chromosomal distribution depends on local contexts (neighboring core genes), and content in mobile genetic elements. Hotspots concentrate most changes in gene repertoires, reduce the trade-off between genome diversification and organization, and should be treasure troves of strain-specific adaptive genes. Most mobile genetic elements and antibiotic resistance genes are in hotspots, but many hotspots lack recognizable mobile genetic elements and exhibit frequent homologous recombination at flanking core genes. Overrepresentation of hotspots with fewer mobile genetic elements in naturally transformable bacteria suggests that homologous recombination and horizontal gene transfer are tightly linked in genome evolution.Horizontal gene transfer (HGT) is an important mechanism for genome evolution and adaptation in bacteria. Here, Oliveira and colleagues find HGT hotspots comprising ~ 1% of the chromosomal regions in 80 bacterial species.

Integrative and conjugative elements and their hosts: composition, distribution and organization.

Conjugation of single-stranded DNA drives horizontal gene transfer between bacteria and was widely studied in conjugative plasmids. The organization and function of integrative and conjugative elements (ICE), even if they are more abundant, was only studied in a few model systems. Comparative genomics of ICE has been precluded by the difficulty in finding and delimiting these elements. Here, we present the results of a method that circumvents these problems by requiring only the identification of the conjugation genes and the species' pan-genome. We delimited 200 ICEs and this allowed the first large-scale characterization of these elements. We quantified the presence in ICEs of a wide set of functions associated with the biology of mobile genetic elements, including some that are typically associated with plasmids, such as partition and replication. Protein sequence similarity networks and phylogenetic analyses revealed that ICEs are structured in functional modules. Integrases and conjugation systems have different evolutionary histories, even if the gene repertoires of ICEs can be grouped in function of conjugation types. Our characterization of the composition and organization of ICEs paves the way for future functional and evolutionary analyses of their cargo genes, composed of a majority of unknown function genes.

Evolutionary dynamics and genomic features of the Elizabethkingia anophelis 2015 to 2016 Wisconsin outbreak strain.

An atypically large outbreak of Elizabethkingia anophelis infections occurred in Wisconsin. Here we show that it was caused by a single strain with thirteen characteristic genomic regions. Strikingly, the outbreak isolates show an accelerated evolutionary rate and an atypical mutational spectrum. Six phylogenetic sub-clusters with distinctive temporal and geographic dynamics are revealed, and their last common ancestor existed approximately one year before the first recognized human infection. Unlike other E. anophelis, the outbreak strain had a disrupted DNA repair mutY gene caused by insertion of an integrative and conjugative element. This genomic change probably contributed to the high evolutionary rate of the outbreak strain and may have increased its adaptability, as many mutations in protein-coding genes occurred during the outbreak. This unique discovery of an outbreak caused by a naturally occurring mutator bacterial pathogen provides a dramatic example of the potential impact of pathogen evolutionary dynamics on infectious disease epidemiology.

Differences in Integron Cassette Excision Dynamics Shape a Trade-Off between Evolvability and Genetic Capacitance.

Integrons ensure a rapid and "on demand" response to environmental stresses driving bacterial adaptation. They are able to capture, store, and reorder functional gene cassettes due to site-specific recombination catalyzed by their integrase. Integrons can be either sedentary and chromosomally located or mobile when they are associated with transposons and plasmids. They are respectively called sedentary chromosomal integrons (SCIs) and mobile integrons (MIs). MIs are key players in the dissemination of antibiotic resistance genes. Here, we used in silico and in vivo approaches to study cassette excision dynamics in MIs and SCIs. We show that the orientation of cassette arrays relative to replication influences attC site folding and cassette excision by placing the recombinogenic strands of attC sites on either the leading or lagging strand template. We also demonstrate that stability of attC sites and their propensity to form recombinogenic structures also regulate cassette excision. We observe that cassette excision dynamics driven by these factors differ between MIs and SCIs. Cassettes with high excision rates are more commonly found on MIs, which favors their dissemination relative to SCIs. This is especially true for SCIs carried in the Vibrio genus, where maintenance of large cassette arrays and vertical transmission are crucial to serve as a reservoir of adaptive functions. These results expand the repertoire of known processes regulating integron recombination that were previously established and demonstrate that, in terms of cassette dynamics, a subtle trade-off between evolvability and genetic capacitance has been established in bacteria.IMPORTANCE The integron system confers upon bacteria a rapid adaptation capability in changing environments. Specifically, integrons are involved in the continuous emergence of bacteria resistant to almost all antibiotic treatments. The international situation is critical, and in 2050, the annual number of deaths caused by multiresistant bacteria could reach 10 million, exceeding the incidence of deaths related to cancer. It is crucial to increase our understanding of antibiotic resistance dissemination and therefore integron recombination dynamics to find new approaches to cope with the worldwide problem of multiresistance. Here, we studied the dynamics of recombination and dissemination of gene encoding cassettes carried on integrons. By combining in silico and in vivo analyses, we show that cassette excision is highly regulated by replication and by the intrinsic properties of cassette recombination sites. We also demonstrated differences in the dynamics of cassette recombination between mobile and sedentary chromosomal integrons (MIs and SCIs). For MIs, a high cassette recombination rate is favored and timed to conditions when generating diversity (upon which selection can act) allows for a rapid response to environmental conditions and stresses. In contrast, for SCIs, cassette excisions are less frequent, limiting cassette loss and ensuring a large pool of cassettes. We therefore confirm a role of SCIs as reservoirs of adaptive functions and demonstrate that the remarkable adaptive success of integron recombination system is due to its intricate regulation.

Identification and analysis of integrons and cassette arrays in bacterial genomes.

Integrons recombine gene arrays and favor the spread of antibiotic resistance. Their broader roles in bacterial adaptation remain mysterious, partly due to lack of computational tools. We made a program - IntegronFinder - to identify integrons with high accuracy and sensitivity. IntegronFinder is available as a standalone program and as a web application. It searches for attC sites using covariance models, for integron-integrases using HMM profiles, and for other features (promoters, attI site) using pattern matching. We searched for integrons, integron-integrases lacking attC sites, and clusters of attC sites lacking a neighboring integron-integrase in bacterial genomes. All these elements are especially frequent in genomes of intermediate size. They are missing in some key phyla, such as α-Proteobacteria, which might reflect selection against cell lineages that acquire integrons. The similarity between attC sites is proportional to the number of cassettes in the integron, and is particularly low in clusters of attC sites lacking integron-integrases. The latter are unexpectedly abundant in genomes lacking integron-integrases or their remains, and have a large novel pool of cassettes lacking homologs in the databases. They might represent an evolutionary step between the acquisition of genes within integrons and their stabilization in the new genome.