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Our bodies are colonized by a complex ecosystem of bacteria, unicellular eukaryotes and their viruses that together play a major role in our health. Over the past few years tools derived from the prokaryotic immune system known as CRISPR-Cas have empowered researchers to modify and study organisms with unprecedented ease and efficiency. Here we discuss how various types of CRISPR-Cas systems can be used to modify the genome of gut microorganisms and bacteriophages. CRISPR-Cas systems can also be delivered to bacterial population and programmed to specifically eliminate members of the microbiome. Finally, engineered CRISPR-Cas systems can be used to control gene expression and modulate the production of metabolites and proteins. Together these tools provide exciting opportunities to investigate the complex interplay between members of the microbiome and our bodies, and present new avenues for the development of drugs that target the microbiome. This article is part of a discussion meeting issue ‘The ecology and evolution of prokaryotic CRISPR-Cas adaptive immune systems’.

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.

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.

High-throughput CRISPR-Cas9 screens have recently emerged as powerful tools to decipher gene functions and genetic interactions. Here we use a genome-wide library of guide RNAs to direct the catalytically dead Cas9 (dCas9) to block gene transcription in Escherichia coli . Using a machine-learning approach, we reveal that guide RNAs sharing specific 5-nucleotide seed sequences can produce strong fitness defects or even kill E. coli regardless of the other 15 nucleotides of guide sequence. This effect occurs at high dCas9 concentrations and can be alleviated by tuning the expression of dCas9 while maintaining strong on-target repression. Our results also highlight the fact that off-targets with as little as nine nucleotides of homology to the guide RNA can strongly block gene expression. Altogether this study provides important design rules to safely use dCas9 in E. coli . CRISPR interference (CRISPRi) is a method for targeted silencing of transcription that requires the coexpression of protein dCas9 and a customized guide RNA. Here, Cui et al. show that certain guide RNAs induce toxicity in E. coli , and provide design rules to minimize off-target effects.

The worrying rise of antibiotic resistance in pathogenic bacteria is leading to a renewed interest in bacteriophages as a treatment option. Novel sequencing technologies enable description of an increasing number of phage genomes, a critical piece of information to understand their life cycle, phage-host interactions, and evolution. In this work, we demonstrate how it is possible to recover more information from sequencing data than just the phage genome. We developed a theoretical and statistical framework to determine DNA termini and phage packaging mechanisms using NGS data. Our method relies on the detection of biases in the number of reads, which are observable at natural DNA termini compared with the rest of the phage genome. We implemented our method with the creation of the software PhageTerm and validated it using a set of phages with well-established packaging mechanisms representative of the termini diversity, i.e. 5′ cos (Lambda), 3′ cos (HK97), pac (P1), headful without a pac site (T4), DTR (T7) and host fragment (Mu). In addition, we determined the termini of nine Clostridium difficile phages and six phages whose sequences were retrieved from the Sequence Read Archive. PhageTerm is freely available (https://sourceforge.net/projects/phageterm), as a Galaxy ToolShed and on a Galaxy-based server (https://galaxy.pasteur.fr).

The Staphylococcus epidermidis CRISPR-Cas system can prevent lytic infection but tolerate lysogenization by temperate phage through a transcription-dependent DNA targeting mechanism. Target discrimination by bacterial immune systems Temperate phages that integrate into the bacterial genome can carry genes that confer a fitness advantage. However, it has been unclear how this potential beneficial interaction is balanced against host defence by CRISPR-Cas immune systems, which defend bacteria against phage infection using Cas nucleases and small RNA guides that provide sequence specificity for cleavage of target sites in the phage genome. Here Luciano Marraffini and colleagues show that the Staphylococcus epidermidis CRISPR-Cas system can prevent lytic phage infection but tolerate lysogenization by temperate phage through a transcription-dependent DNA targeting mechanism. This work expands the repertoire of CRISPR-based immune functions to include a facility for conditional tolerance of foreign elements. A fundamental feature of immune systems is the ability to distinguish pathogenic from self and commensal elements, and to attack the former but tolerate the latter 1 . Prokaryotic CRISPR-Cas immune systems defend against phage infection by using Cas nucleases and small RNA guides that specify one or more target sites for cleavage of the viral genome 2 , 3 . Temperate phages include viruses that can integrate into the bacterial chromosome, and they can carry genes that provide a fitness advantage to the lysogenic host 4 , 5 . However, CRISPR-Cas targeting that relies strictly on DNA sequence recognition provides indiscriminate immunity both to lytic and lysogenic infection by temperate phages 6 —compromising the genetic stability of these potentially beneficial elements altogether. Here we show that the Staphylococcus epidermidis CRISPR-Cas system can prevent lytic infection but tolerate lysogenization by temperate phages. Conditional tolerance is achieved through transcription-dependent DNA targeting, and ensures that targeting is resumed upon induction of the prophage lytic cycle. Our results provide evidence for the functional divergence of CRISPR-Cas systems and highlight the importance of targeting mechanism diversity. In addition, they extend the concept of ‘tolerance to non-self’ to the prokaryotic branch of adaptive immunity.

Conjugation is one mechanism for intra- and inter-species horizontal gene transfer among bacteria. Conjugative elements have been instrumental in many bacterial species to face the threat of antibiotics, by allowing them to evolve and adapt to these hostile conditions. Conjugative plasmids are transferred to plasmidless recipient cells as single-stranded DNA. We used lacZ and gfp fusions to address whether conjugation induces the SOS response and the integron integrase. The SOS response controls a series of genes responsible for DNA damage repair, which can lead to recombination and mutagenesis. In this manuscript, we show that conjugative transfer of ssDNA induces the bacterial SOS stress response, unless an anti-SOS factor is present to alleviate this response. We also show that integron integrases are up-regulated during this process, resulting in increased cassette rearrangements. Moreover, the data we obtained using broad and narrow host range plasmids strongly suggests that plasmid transfer, even abortive, can trigger chromosomal gene rearrangements and transcriptional switches in the recipient cell. Our results highlight the importance of environments concentrating disparate bacterial communities as reactors for extensive genetic adaptation of bacteria.

Over the past few years, tools that make use of the Cas9 nuclease have led to many breakthroughs, including in the control of gene expression. The catalytically dead variant of Cas9 known as dCas9 can be guided by small RNAs to block transcription of target genes, in a strategy also known as CRISPRi. Here, we reveal that the level of complementarity between the guide RNA and the target controls the rate at which RNA polymerase “kicks out” dCas9 from the target and completes transcription. We use this mechanism to precisely and robustly reduce gene expression by defined relative amounts. Alternatively, tuning repression by changing dCas9 concentration is noisy and promoter‐strength dependent. We demonstrate broad applicability of this method to the study of genetic regulation and cellular physiology. First, we characterize feedback strength of a model auto‐repressor. Second, we study the impact of amount variations of cell‐wall synthesizing enzymes on cell morphology. Finally, we multiplex the system to obtain any combination of fractional repression of two genes. Synopsis When RNA polymerase encounters the dCas9 inactivated nuclease, it has a certain probability of going through depending on the guide RNA sequence. This property is exploited to robustly control the expression level of multiple genes from their native locus. For a high enough dCas9 concentration, the target locus can be saturated and repression strength only depends on the RNAP passage probability. Imperfect complementarity between the guide RNA and the target gene allows fine‐tuning passage probability and consequently gene expression levels. In saturating conditions, repression does not produce any additional noise on gene expression. This strategy is applied to measure the response of a genetic circuit, analyze how cell‐wall synthesis enzymes affect cell shape, and to tune the levels of multiple genes independently. Graphical Abstract When RNA polymerase encounters the dCas9 inactivated nuclease, it has a certain probability of going through depending on the guide RNA sequence. This property is exploited to robustly control the expression level of multiple genes from their native locus.

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.

Cell shape and cell-envelope integrity of bacteria are determined by the peptidoglycan cell wall. In rod-shaped Escherichia coli, two conserved sets of machinery are essential for cell-wall insertion in the cylindrical part of the cell: the Rod complex and the class-A penicillin-binding proteins (aPBPs). While the Rod complex governs rod-like cell shape, aPBP function is less well understood. aPBPs were previously hypothesized to either work in concert with the Rod complex or to independently repair cell-wall defects. First, we demonstrate through modulation of enzyme levels that aPBPs do not contribute to rod-like cell shape but are required for mechanical stability, supporting their independent activity. By combining measurements of cell-wall stiffness, cell-wall insertion, and PBP1b motion at the single-molecule level, we then present evidence that PBP1b, the major aPBP, contributes to cell-wall integrity by repairing cell wall defects.