Type IV-A3 CRISPR-Cas systems drive inter-plasmid conflicts by acquiring spacers in trans.

Plasmid-encoded type IV-A CRISPR-Cas systems lack an acquisition module, feature a DinG helicase instead of a nuclease, and form ribonucleoprotein complexes of unknown biological functions. Type IV-A3 systems are carried by conjugative plasmids that often harbor antibiotic-resistance genes and their CRISPR array contents suggest a role in mediating inter-plasmid conflicts, but this function remains unexplored. Here, we demonstrate that a plasmid-encoded type IV-A3 system co-opts the type I-E adaptation machinery from its host, Klebsiella pneumoniae (K. pneumoniae), to update its CRISPR array. Furthermore, we reveal that robust interference of conjugative plasmids and phages is elicited through CRISPR RNA-dependent transcriptional repression. By silencing plasmid core functions, type IV-A3 impacts the horizontal transfer and stability of targeted plasmids, supporting its role in plasmid competition. Our findings shed light on the mechanisms and ecological function of type IV-A3 systems and demonstrate their practical efficacy for countering antibiotic resistance in clinically relevant strains.

Systematic interrogation of CRISPR antimicrobials in Klebsiella pneumoniae reveals nuclease-, guide- and strain-dependent features influencing antimicrobial activity.

CRISPR-Cas systems can be utilized as programmable-spectrum antimicrobials to combat bacterial infections. However, how CRISPR nucleases perform as antimicrobials across target sites and strains remains poorly explored. Here, we address this knowledge gap by systematically interrogating the use of CRISPR antimicrobials using multidrug-resistant and hypervirulent strains of Klebsiella pneumoniae as models. Comparing different Cas nucleases, DNA-targeting nucleases outperformed RNA-targeting nucleases based on the tested targets. Focusing on AsCas12a that exhibited robust targeting across different strains, we found that the elucidated modes of escape varied widely, restraining opportunities to enhance killing. We also encountered individual guide RNAs yielding different extents of clearance across strains, which were linked to an interplay between improper gRNA folding and strain-specific DNA repair and survival. To explore features that could improve targeting across strains, we performed a genome-wide screen in different K. pneumoniae strains that yielded guide design rules and trained an algorithm for predicting guide efficiency. Finally, we showed that Cas12a antimicrobials can be exploited to eliminate K. pneumoniae when encoded in phagemids delivered by T7-like phages. Altogether, our results highlight the importance of evaluating antimicrobial activity of CRISPR antimicrobials across relevant strains and define critical parameters for efficient CRISPR-based targeting.

Cassette recombination dynamics within chromosomal integrons are regulated by toxin-antitoxin systems.

Integrons are adaptive bacterial devices that rearrange promoter-less gene cassettes into variable ordered arrays under stress conditions, thereby sampling combinatorial phenotypic diversity. Chromosomal integrons often carry hundreds of silent gene cassettes, with integrase-mediated recombination leading to rampant DNA excision and integration, posing a potential threat to genome integrity. How this activity is regulated and controlled, particularly through selective pressures, to maintain such large cassette arrays is unknown. Here, we show a key role of promoter-containing toxin-antitoxin (TA) cassettes as systems that kill the cell when the overall cassette excision rate is too high. These results highlight the importance of TA cassettes regulating the cassette recombination dynamics and provide insight into the evolution and success of integrons in bacterial genomes.

Viral proteins activate PARIS-mediated tRNA degradation and viral tRNAs rescue infection.

Viruses compete with each other for limited cellular resources, and some viruses deliver defense mechanisms that protect the host from competing genetic parasites. PARIS is a defense system, often encoded in viral genomes, that is composed of a 53 kDa ABC ATPase (AriA) and a 35 kDa TOPRIM nuclease (AriB). Here we show that AriA and AriB assemble into a 425 kDa supramolecular immune complex. We use cryo-EM to determine the structure of this complex which explains how six molecules of AriA assemble into a propeller-shaped scaffold that coordinates three subunits of AriB. ATP-dependent detection of foreign proteins triggers the release of AriB, which assembles into a homodimeric nuclease that blocks infection by cleaving the host tRNALys. Phage T5 subverts PARIS immunity through expression of a tRNALys variant that prevents PARIS-mediated cleavage, and thereby restores viral infection. Collectively, these data explain how AriA functions as an ATP-dependent sensor that detects viral proteins and activates the AriB toxin. PARIS is one of an emerging set of immune systems that form macromolecular complexes for the recognition of foreign proteins, rather than foreign nucleic acids.

Computational design of novel Cas9 PAM-interacting domains using evolution-based modelling and structural quality assessment.

We present here an approach to protein design that combines (i) scarce functional information such as experimental data (ii) evolutionary information learned from a natural sequence variants and (iii) physics-grounded modeling. Using a Restricted Boltzmann Machine (RBM), we learn a sequence model of a protein family. We use semi-supervision to leverage available functional information during the RBM training. We then propose a strategy to explore the protein representation space that can be informed by external models such as an empirical force-field method (FoldX). Our approach is applied to a domain of the Cas9 protein responsible for recognition of a short DNA motif. We experimentally assess the functionality of 71 variants generated to explore a range of RBM and FoldX energies. Sequences with as many as 50 differences (20% of the protein domain) to the wild-type retained functionality. Overall, 21/71 sequences designed with our method were functional. Interestingly, 6/71 sequences showed an improved activity in comparison with the original wild-type protein sequence. These results demonstrate the interest in further exploring the synergies between machine-learning of protein sequence representations and physics grounded modeling strategies informed by structural information.

Machine learning for evolutionary-based and physics-inspired protein design: Current and future synergies.

Computational protein design facilitates the discovery of novel proteins with prescribed structure and functionality. Exciting designs were recently reported using novel data-driven methodologies that can be roughly divided into two categories: evolutionary-based and physics-inspired approaches. The former infer characteristic sequence features shared by sets of evolutionary-related proteins, such as conserved or coevolving positions, and recombine them to generate candidates with similar structure and function. The latter approaches estimate key biochemical properties, such as structure free energy, conformational entropy, or binding affinities using machine learning surrogates, and optimize them to yield improved designs. Here, we review recent progress along both tracks, discuss their strengths and weaknesses, and highlight opportunities for synergistic approaches.

Cas9 off-target binding to the promoter of bacterial genes leads to silencing and toxicity.

Genetic tools derived from the Cas9 RNA-guided nuclease are providing essential capabilities to study and engineer bacteria. While the importance of off-target effects was noted early in Cas9's application to mammalian cells, off-target cleavage by Cas9 in bacterial genomes is easily avoided due to their smaller size. Despite this, several studies have reported experimental setups in which Cas9 expression was toxic, even when using the catalytic dead variant of Cas9 (dCas9). Specifically, dCas9 was shown to be toxic when in complex with guide RNAs sharing specific PAM (protospacer adjacent motif)-proximal sequence motifs. Here, we demonstrate that this toxicity is caused by off-target binding of Cas9 to the promoter of essential genes, with silencing of off-target genes occurring with as little as 4 nt of identity in the PAM-proximal sequence. Screens performed in various strains of Escherichia coli and other enterobacteria show that the nature of toxic guide RNAs changes together with the evolution of sequences at off-target positions. These results highlight the potential for Cas9 to bind to hundreds of off-target positions in bacterial genomes, leading to undesired effects. This phenomenon must be considered in the design and interpretation of CRISPR-Cas experiments in bacteria.

Within-patient evolution of plasmid-mediated antimicrobial resistance.

Antimicrobial resistance (AMR) in bacteria is a major threat to public health; one of the key elements in the spread and evolution of AMR in clinical pathogens is the transfer of conjugative plasmids. The drivers of AMR evolution have been studied extensively in vitro but the evolution of plasmid-mediated AMR in vivo remains poorly explored. Here, we tracked the evolution of the clinically relevant plasmid pOXA-48, which confers resistance to the last-resort antibiotics carbapenems, in a large collection of enterobacterial clones isolated from the gut of hospitalized patients. Combining genomic and experimental approaches, we first characterized plasmid diversity and the genotypic and phenotypic effects of multiple plasmid mutations on a common genetic background. Second, using cutting-edge genomic editing in wild-type multidrug-resistant enterobacteria, we dissected three cases of within-patient plasmid-mediated AMR evolution. Our results revealed compensatory evolution of plasmid-associated fitness cost and the evolution of enhanced plasmid-mediated AMR in bacteria evolving in the gut of hospitalized patients. Crucially, we observed that the evolution of pOXA-48-mediated AMR in vivo involves a pivotal trade-off between resistance levels and bacterial fitness. This study highlights the need to develop new evolution-informed approaches to tackle plasmid-mediated AMR dissemination.

Phage-host coevolution in natural populations.

Coevolution between bacteriophages (phages) and their bacterial hosts occurs through changes in resistance and counter-resistance mechanisms. To assess phage-host evolution in wild populations, we isolated 195 Vibrio crassostreae strains and 243 vibriophages during a 5-month time series from an oyster farm and combined these isolates with existing V. crassostreae and phage isolates. Cross-infection studies of 81,926 host-phage pairs delineated a modular network where phages are best at infecting co-occurring hosts, indicating local adaptation. Successful propagation of phage is restricted by the ability to adsorb to closely related bacteria and further constrained by strain-specific defence systems. These defences are highly diverse and predominantly located on mobile genetic elements, and multiple defences are active within a single genome. We further show that epigenetic and genomic modifications enable phage to adapt to bacterial defences and alter host range. Our findings reveal that the evolution of bacterial defences and phage counter-defences is underpinned by frequent genetic exchanges with, and between, mobile genetic elements.

Phages and their satellites encode hotspots of antiviral systems.

Bacteria carry diverse genetic systems to defend against viral infection, some of which are found within prophages where they inhibit competing viruses. Phage satellites pose additional pressures on phages by hijacking key viral elements to their own benefit. Here, we show that E. coli P2-like phages and their parasitic P4-like satellites carry hotspots of genetic variation containing reservoirs of anti-phage systems. We validate the activity of diverse systems and describe PARIS, an abortive infection system triggered by a phage-encoded anti-restriction protein. Antiviral hotspots participate in inter-viral competition and shape dynamics between the bacterial host, P2-like phages, and P4-like satellites. Notably, the anti-phage activity of satellites can benefit the helper phage during competition with virulent phages, turning a parasitic relationship into a mutualistic one. Anti-phage hotspots are present across distant species and constitute a substantial source of systems that participate in the competition between mobile genetic elements.

Microbial defenses against mobile genetic elements and viruses: Who defends whom from what?

Prokaryotes have numerous mobile genetic elements (MGEs) that mediate horizontal gene transfer (HGT) between cells. These elements can be costly, even deadly, and cells use numerous defense systems to filter, control, or inactivate them. Recent studies have shown that prophages, conjugative elements, their parasites (phage satellites and mobilizable elements), and other poorly described MGEs encode defense systems homologous to those of bacteria. These constitute a significant fraction of the repertoire of cellular defense genes. As components of MGEs, these defense systems have presumably evolved to provide them, not the cell, adaptive functions. While the interests of the host and MGEs are aligned when they face a common threat such as an infection by a virulent phage, defensive functions carried by MGEs might also play more selfish roles to fend off other antagonistic MGEs or to ensure their maintenance in the cell. MGEs are eventually lost from the surviving host genomes by mutational processes and their defense systems can be co-opted when they provide an advantage to the cell. The abundance of defense systems in MGEs thus sheds new light on the role, effect, and fate of the so-called "cellular defense systems," whereby they are not only merely microbial defensive weapons in a 2-partner arms race, but also tools of intragenomic conflict between multiple genetic elements with divergent interests that shape cell fate and gene flow at the population level.

How has microbiology changed 200 years after Pasteur's birth?

The last two centuries have seen major scientific and technological advances that have turned the field of microbiology upside down. If Louis Pasteur came out of his vault to celebrate his two hundredth birthday with us, would he recognize the field of study of which he was one of the founders? Are the objectives of the discipline still the same? What is the influence of new technologies on our scientific approach? What are the new horizons and future challenges?

Les deux derniers siècles ont connu des avancées scientifiques et technologiques majeures qui ont bouleversé le domaine de la microbiologie. Si Louis Pasteur sortait de son caveau pour fêter ses deux ans en notre compagnie, reconnaitrait-il le champ d'étude dont il est l'un des fondateurs ? Les objectifs de la discipline sont-ils toujours les mêmes ? Quelle est l'influence des nouvelles technologies sur notre démarche scientifique ? Quels sont les nouveaux horizons et futurs défis à relever ?

High-throughput identification of viral termini and packaging mechanisms in virome datasets using PhageTermVirome.

Viruses that infect bacteria (phages) are increasingly recognized for their importance in diverse ecosystems but identifying and annotating them in large-scale sequence datasets is still challenging. Although efficient scalable virus identification tools are emerging, defining the exact ends (termini) of phage genomes is still particularly difficult. The proper identification of termini is crucial, as it helps in characterizing the packaging mechanism of bacteriophages and provides information on various aspects of phage biology. Here, we introduce PhageTermVirome (PTV) as a tool for the easy and rapid high-throughput determination of phage termini and packaging mechanisms using modern large-scale metagenomics datasets. We successfully tested the PTV algorithm on a mock virome dataset and then used it on two real virome datasets to achieve the rapid identification of more than 100 phage termini and packaging mechanisms, with just a few hours of computing time. Because PTV allows the identification of free fully formed viral particles (by recognition of termini present only in encapsidated DNA), it can also complement other virus identification softwares to predict the true viral origin of contigs in viral metagenomics datasets. PTV is a novel and unique tool for high-throughput characterization of phage genomes, including phage termini identification and characterization of genome packaging mechanisms. This software should help researchers better visualize, map and study the virosphere. PTV is freely available for downloading and installation at https://gitlab.pasteur.fr/vlegrand/ptv .

Improving sequence-based modeling of protein families using secondary-structure quality assessment.

MOTIVATION: Modeling of protein family sequence distribution from homologous sequence data recently received considerable attention, in particular for structure and function predictions, as well as for protein design. In particular, direct coupling analysis, a method to infer effective pairwise interactions between residues, was shown to capture important structural constraints and to successfully generate functional protein sequences. Building on this and other graphical models, we introduce a new framework to assess the quality of the secondary structures of the generated sequences with respect to reference structures for the family. RESULTS: We introduce two scoring functions characterizing the likeliness of the secondary structure of a protein sequence to match a reference structure, called Dot Product and Pattern Matching. We test these scores on published experimental protein mutagenesis and design dataset, and show improvement in the detection of nonfunctional sequences. We also show that use of these scores help rejecting nonfunctional sequences generated by graphical models (Restricted Boltzmann Machines) learned from homologous sequence alignments. AVAILABILITY AND IMPLEMENTATION: Data and code available at https://github.com/CyrilMa/ssqa. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Lipoprotein DolP supports proper folding of BamA in the bacterial outer membrane promoting fitness upon envelope stress.

In Proteobacteria, integral outer membrane proteins (OMPs) are crucial for the maintenance of the envelope permeability barrier to some antibiotics and detergents. In Enterobacteria, envelope stress caused by unfolded OMPs activates the sigmaE (σE) transcriptional response. σE upregulates OMP biogenesis factors, including the ß-barrel assembly machinery (BAM) that catalyses OMP folding. Here we report that DolP (formerly YraP), a σE-upregulated and poorly understood outer membrane lipoprotein, is crucial for fitness in cells that undergo envelope stress. We demonstrate that DolP interacts with the BAM complex by associating with outer membrane-assembled BamA. We provide evidence that DolP is important for proper folding of BamA that overaccumulates in the outer membrane, thus supporting OMP biogenesis and envelope integrity. Notably, mid-cell recruitment of DolP had been linked to regulation of septal peptidoglycan remodelling by an unknown mechanism. We now reveal that, during envelope stress, DolP loses its association with the mid-cell, thereby suggesting a mechanistic link between envelope stress caused by impaired OMP biogenesis and the regulation of a late step of cell division.

Generating functional protein variants with variational autoencoders.

The vast expansion of protein sequence databases provides an opportunity for new protein design approaches which seek to learn the sequence-function relationship directly from natural sequence variation. Deep generative models trained on protein sequence data have been shown to learn biologically meaningful representations helpful for a variety of downstream tasks, but their potential for direct use in the design of novel proteins remains largely unexplored. Here we show that variational autoencoders trained on a dataset of almost 70000 luciferase-like oxidoreductases can be used to generate novel, functional variants of the luxA bacterial luciferase. We propose separate VAE models to work with aligned sequence input (MSA VAE) and raw sequence input (AR-VAE), and offer evidence that while both are able to reproduce patterns of amino acid usage characteristic of the family, the MSA VAE is better able to capture long-distance dependencies reflecting the influence of 3D structure. To confirm the practical utility of the models, we used them to generate variants of luxA whose luminescence activity was validated experimentally. We further showed that conditional variants of both models could be used to increase the solubility of luxA without disrupting function. Altogether 6/12 of the variants generated using the unconditional AR-VAE and 9/11 generated using the unconditional MSA VAE retained measurable luminescence, together with all 23 of the less distant variants generated by conditional versions of the models; the most distant functional variant contained 35 differences relative to the nearest training set sequence. These results demonstrate the feasibility of using deep generative models to explore the space of possible protein sequences and generate useful variants, providing a method complementary to rational design and directed evolution approaches.