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Immune defence mechanisms exist across the tree of life in such diversity that prokaryotic antiviral responses have historically been considered unrelated to eukaryotic immunity. Mechanisms of defence in divergent eukaryotes were similarly believed to be largely clade specific. However, recent data indicate that a subset of modules (domains and proteins) from prokaryote defence systems are conserved in eukaryotes and populate many stages of innate immune pathways. In this Essay, we propose the notion of ancestral immunity, which corresponds to the set of immune modules conserved between prokaryotes and eukaryotes. After offering a typology of ancestral immunity, we speculate on the selective pressures that could have led to the differential conservation of specific immune modules across domains of life. The exploration of ancestral immunity is in its infancy and appears full of promises to illuminate immune evolution, and also to identify and decipher immune mechanisms of economic, ecological, and therapeutic importance. A subset of prokaryotic antiviral systems are conserved in eukaryotes and have crucial roles in immune pathways. This Essay introduces the concept of ancestral immunity, which refers to the set of immune modules (domains and proteins) conserved between prokaryotes and eukaryotes, discussing the topology of ancestral immunity and a putative evolutionary scenario for its existence. [ABSTRACT FROM AUTHOR]

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. Bacteria and archaea have developed multiple antiviral mechanisms. Here, Tesson et al. present a tool that automatically detects known antiviral systems in prokaryotic genomes, and show that variations in antiviral strategies correlate with genome size, viral threat, and lifestyle traits. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Bacterial genomics has greatly expanded our understanding of microdiversification patterns within a species, but analyses at higher taxonomical levels are necessary to understand and predict the independent rise of pathogens in a genus. We have sampled, sequenced, and assessed the diversity of genomes of validly named and tentative species of the Acinetobacter genus, a clade including major nosocomial pathogens and biotechnologically important species. We inferred a robust global phylogeny and delimited several new putative species. The genus is very ancient and extremely diverse: Genomes of highly divergent species share more orthologs than certain strains within a species. We systematically characterized elements and mechanisms driving genome diversification, such as conjugative elements, insertion sequences, and natural transformation. We found many error-prone polymerases that may play a role in resistance to toxins, antibiotics, and in the generation of genetic variation. Surprisingly, temperate phages, poorly studied in Acinetobacter, were found to account for a significant fraction of most genomes. Accordingly, many genomes encode clustered regularly interspaced short palindromic repeats (CRISPR)-Cas systems with some of the largest CRISPR-arrays found so far in bacteria. Integrons are strongly overrepresented in Acinetobacter baumannii, which correlates with its frequent resistance to antibiotics. Our data suggest that A. baumannii arose from an ancient population bottleneck followed by population expansion under strong purifying selection. The outstanding diversification of the species occurred largely by horizontal transfer, including some allelic recombination, at specific hotspots preferentially located close to the replication terminus. Our work sets a quantitative basis to understand the diversification of Acinetobacter into emerging resistant and versatile pathogens. [ABSTRACT FROM AUTHOR]

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

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]