Anti-CRISPR prediction using deep learning reveals an inhibitor of Cas13b nucleases

Structures, mechanisms and applications of RNA-centric CRISPR-Cas13

Prokaryotes are equipped with a variety of resistance strategies to survive frequent viral attacks or invading mobile genetic elements. Among these, CRISPR-Cas surveillance systems are abundant and have been studied extensively. This Review focuses on CRISPR-Cas type VI Cas13 systems that use single-subunit RNA-guided Cas endonucleases for targeting and subsequent degradation of foreign RNA, thereby providing adaptive immunity. Notably, distinct from single-subunit DNA-cleaving Cas9 and Cas12 systems, Cas13 exhibits target RNA-activated substrate RNase activity. This Review outlines structural, biochemical and cell biological studies toward elucidation of the unique structural and mechanistic principles underlying surveillance effector complex formation, precursor CRISPR RNA (pre-crRNA) processing, self-discrimination and RNA degradation in Cas13 systems as well as insights into suppression by bacteriophage-encoded anti-CRISPR proteins and regulation by endogenous accessory proteins. Owing to its programmable ability for RNA recognition and cleavage, Cas13 provides powerful RNA targeting, editing, detection and imaging platforms with emerging biotechnological and therapeutic applications.

Regulatory sequence-based discovery of anti-defense genes in archaeal viruses

In silico identification of viral anti-CRISPR proteins (Acrs) has relied largely on the guilt-by-association method using known Acrs or anti-CRISPR associated proteins (Acas) as the bait. However, the low number and limited spread of the characterized archaeal Acrs and Aca hinders our ability to identify Acrs using guilt-by-association. Here, based on the observation that the few characterized archaeal Acrs and Aca are transcribed immediately post viral infection, we hypothesize that these genes, and many other unidentified anti-defense genes (ADG), are under the control of conserved regulatory sequences including a strong promoter, which can be used to predict anti-defense genes in archaeal viruses. Using this consensus sequence based method, we identify 354 potential ADGs in 57 archaeal viruses and 6 metagenome-assembled genomes. Experimental validation identified a CRISPR subtype I-A inhibitor and the first virally encoded inhibitor of an archaeal toxin-antitoxin based immune system. We also identify regulatory proteins potentially akin to Acas that can facilitate further identification of ADGs combined with the guilt-by-association approach. These results demonstrate the potential of regulatory sequence analysis for extensive identification of ADGs in viruses of archaea and bacteria.

Inhibitors of bacterial immune systems: discovery, mechanisms and applications

To contend with the diversity and ubiquity of bacteriophages and other mobile genetic elements, bacteria have developed an arsenal of immune defence mechanisms. Bacterial defences include CRISPR-Cas, restriction-modification and a growing list of mechanistically diverse systems, which constitute the bacterial 'immune system'. As a response, bacteriophages and mobile genetic elements have evolved direct and indirect mechanisms to circumvent or block bacterial defence pathways and ensure successful infection. Recent advances in methodological and computational approaches, as well as the increasing availability of genome sequences, have boosted the discovery of direct inhibitors of bacterial defence systems. In this Review, we discuss methods for the discovery of direct inhibitors, their diverse mechanisms of action and perspectives on their emerging applications in biotechnology and beyond.

Structure-guided discovery of anti-CRISPR and anti-phage defense proteins

Bacteria use a variety of defense systems to protect themselves from phage infection. In turn, phages have evolved diverse counter-defense measures to overcome host defenses. Here, we use protein structural similarity and gene co-occurrence analyses to screen >66 million viral protein sequences and >330,000 metagenome-assembled genomes for the identification of anti-phage and counter-defense systems. We predict structures for ~300,000 proteins and perform large-scale, pairwise comparison to known anti-CRISPR (Acr) and anti-phage proteins to identify structural homologs that otherwise may not be uncovered using primary sequence search. This way, we identify a Bacteroidota phage Acr protein that inhibits Cas12a, and an Akkermansia muciniphila anti-phage defense protein, termed BxaP. Gene bxaP is found in loci encoding Bacteriophage Exclusion (BREX) and restriction-modification defense systems, but confers immunity independently. Our work highlights the advantage of combining protein structural features and gene co-localization information in studying host-phage interactions.

Diversity of Bathyarchaeia viruses in metagenomes and virus-encoded CRISPR system components

Bathyarchaeia represent a class of archaea common and abundant in sedimentary ecosystems. Here we report 56 metagenome-assembled genomes of Bathyarchaeia viruses identified in metagenomes from different environments. Gene sharing network and phylogenomic analyses led to the proposal of four virus families, including viruses of the realms Duplodnaviria and Adnaviria, and archaea-specific spindle-shaped viruses. Genomic analyses uncovered diverse CRISPR elements in these viruses. Viruses of the proposed family "Fuxiviridae" harbor an atypical Type IV-B CRISPR-Cas system and a Cas4 protein that might interfere with host immunity. Viruses of the family "Chiyouviridae" encode a Cas2-like endonuclease and two mini-CRISPR arrays, one with a repeat identical to that in the host CRISPR array, potentially allowing the virus to recruit the host CRISPR adaptation machinery to acquire spacers that could contribute to competition with other mobile genetic elements or to inhibit host defenses. These findings present an outline of the Bathyarchaeia virome and offer a glimpse into their counter-defense mechanisms.

Rapid characterization of anti-CRISPR proteins and optogenetically engineered variants using a versatile plasmid interference system

Anti-CRISPR (Acr) proteins are encoded by mobile genetic elements to overcome the CRISPR immunity of prokaryotes, displaying promises as controllable tools for modulating CRISPR-based applications. However, characterizing novel anti-CRISPR proteins and exploiting Acr-related technologies is a rather long and tedious process. Here, we established a versatile plasmid interference with CRISPR interference (PICI) system in Escherichia coli for rapidly characterizing Acrs and developing Acr-based technologies. Utilizing the PICI system, we discovered two novel type II-A Acrs (AcrIIA33 and AcrIIA34), which can inhibit the activity of SpyCas9 by affecting DNA recognition of Cas9. We further constructed a circularly permuted AcrIIA4 (cpA4) protein and developed optogenetically engineered, robust AcrIIA4 (OPERA4) variants by combining cpA4 with the light-oxygen-voltage 2 (LOV2) blue light sensory domain. OPERA4 variants are robust light-dependent tools for controlling the activity of SpyCas9 by approximately 1000-fold change under switching dark-light conditions in prokaryotes. OPERA4 variants can achieve potent light-controllable genome editing in human cells as well. Together, our work provides a versatile screening system for characterizing Acrs and developing the Acr-based controllable tools.

Diversity of Bathyarchaeia viruses in metagenomes and virus-encoded CRISPR system components

Bathyarchaeia represent a class of archaea common and abundant in sedimentary ecosystems. The virome of Bathyarchaeia so far has not been characterized. Here we report 56 metagenome-assembled genomes of Bathyarchaeia viruses identified in metagenomes from different environments. Gene sharing network and phylogenomic analyses led to the proposal of four virus families, including viruses of the realms Duplodnaviria and Adnaviria, and archaea-specific spindle-shaped viruses. Genomic analyses uncovered diverse CRISPR elements in these viruses. Viruses of the proposed family 'Fuxiviridae' harbor an atypical type IV-B CRISPR-Cas system and a Cas4 protein that might interfere with host immunity. Viruses of the family 'Chiyouviridae' encode a Cas2-like endonuclease and two mini-CRISPR arrays, one with a repeat identical to that in the host CRISPR array, potentially allowing the virus to recruit the host CRISPR adaptation machinery to acquire spacers that could contribute to competition with other mobile genetic elements or to inhibition of host defenses. These findings present an outline of the Bathyarchaeia virome and offer a glimpse into their counter-defense mechanisms.

Phages are unrecognized players in the ecology of the oral pathogen Porphyromonas gingivalis

BACKGROUND

Porphyromonas gingivalis (hereafter "Pg") is an oral pathogen that has been hypothesized to act as a keystone driver of inflammation and periodontal disease. Although Pg is most readily recovered from individuals with actively progressing periodontal disease, healthy individuals and those with stable non-progressing disease are also colonized by Pg. Insights into the factors shaping the striking strain-level variation in Pg, and its variable associations with disease, are needed to achieve a more mechanistic understanding of periodontal disease and its progression. One of the key forces often shaping strain-level diversity in microbial communities is infection of bacteria by their viral (phage) predators and symbionts. Surprisingly, although Pg has been the subject of study for over 40 years, essentially nothing is known of its phages, and the prevailing paradigm is that phages are not important in the ecology of Pg.

RESULTS

Here we systematically addressed the question of whether Pg are infected by phages-and we found that they are. We found that prophages are common in Pg, they are genomically diverse, and they encode genes that have the potential to alter Pg physiology and interactions. We found that phages represent unrecognized targets of the prevalent CRISPR-Cas defense systems in Pg, and that Pg strains encode numerous additional mechanistically diverse candidate anti-phage defense systems. We also found that phages and candidate anti-phage defense system elements together are major contributors to strain-level diversity and the species pangenome of this oral pathogen. Finally, we demonstrate that prophages harbored by a model Pg strain are active in culture, producing extracellular viral particles in broth cultures.

CONCLUSION

This work definitively establishes that phages are a major unrecognized force shaping the ecology and intra-species strain-level diversity of the well-studied oral pathogen Pg. The foundational phage sequence datasets and model systems that we establish here add to the rich context of all that is already known about Pg, and point to numerous avenues of future inquiry that promise to shed new light on fundamental features of phage impacts on human health and disease broadly. Video Abstract.

Deep learning in CRISPR-Cas systems: a review of recent studies

In genetic engineering, the revolutionary CRISPR-Cas system has proven to be a vital tool for precise genome editing. Simultaneously, the emergence and rapid evolution of deep learning methodologies has provided an impetus to the scientific exploration of genomic data. These concurrent advancements mandate regular investigation of the state-of-the-art, particularly given the pace of recent developments. This review focuses on the significant progress achieved during 2019-2023 in the utilization of deep learning for predicting guide RNA (gRNA) activity in the CRISPR-Cas system, a key element determining the effectiveness and specificity of genome editing procedures. In this paper, an analytical overview of contemporary research is provided, with emphasis placed on the amalgamation of artificial intelligence and genetic engineering. The importance of our review is underscored by the necessity to comprehend the rapidly evolving deep learning methodologies and their potential impact on the effectiveness of the CRISPR-Cas system. By analyzing recent literature, this review highlights the achievements and emerging trends in the integration of deep learning with the CRISPR-Cas systems, thus contributing to the future direction of this essential interdisciplinary research area.

CRISPRimmunity: an interactive web server for CRISPR-associated Important Molecular events and Modulators Used in geNome edIting Tool identifYing

The CRISPR-Cas system is a highly adaptive and RNA-guided immune system found in bacteria and archaea, which has applications as a genome editing tool and is a valuable system for studying the co-evolutionary dynamics of bacteriophage interactions. Here introduces CRISPRimmunity, a new web server designed for Acr prediction, identification of novel class 2 CRISPR-Cas loci, and dissection of key CRISPR-associated molecular events. CRISPRimmunity is built on a suite of CRISPR-oriented databases providing a comprehensive co-evolutionary perspective of the CRISPR-Cas and anti-CRISPR systems. The platform achieved a high prediction accuracy of 0.997 for Acr prediction when tested on a dataset of 99 experimentally validated Acrs and 676 non-Acrs, outperforming other existing prediction tools. Some of the newly identified class 2 CRISPR-Cas loci using CRISPRimmunity have been experimentally validated for cleavage activity in vitro. CRISPRimmunity offers the catalogues of pre-identified CRISPR systems to browse and query, the collected resources or databases to download, a well-designed graphical interface, a detailed tutorial, multi-faceted information, and exportable results in machine-readable formats, making it easy to use and facilitating future experimental design and further data mining. The platform is available at http://www.microbiome-bigdata.com/CRISPRimmunity. Moreover, the source code for batch analysis are published on Github (https://github.com/HIT-ImmunologyLab/CRISPRimmunity).

Genome mining for anti-CRISPR operons using machine learning

MOTIVATION

Encoded by (pro-)viruses, anti-CRISPR (Acr) proteins inhibit the CRISPR-Cas immune system of their prokaryotic hosts. As a result, Acr proteins can be employed to develop more controllable CRISPR-Cas genome editing tools. Recent studies revealed that known acr genes often coexist with other acr genes and with phage structural genes within the same operon. For example, we found that 47 of 98 known acr genes (or their homologs) co-exist in the same operons. None of the current Acr prediction tools have considered this important genomic context feature. We have developed a new software tool AOminer to facilitate the improved discovery of new Acrs by fully exploiting the genomic context of known acr genes and their homologs.

RESULTS

AOminer is the first machine learning based tool focused on the discovery of Acr operons (AOs). A two-state HMM (hidden Markov model) was trained to learn the conserved genomic context of operons that contain known acr genes or their homologs, and the learnt features could distinguish AOs and non-AOs. AOminer allows automated mining for potential AOs from query genomes or operons. AOminer outperformed all existing Acr prediction tools with an accuracy = 0.85. AOminer will facilitate the discovery of novel anti-CRISPR operons.

AVAILABILITY AND IMPLEMENTATION

The webserver is available at: http://aca.unl.edu/AOminer/AOminer_APP/. The python program is at: https://github.com/boweny920/AOminer.

Anti-CRISPR Discovery: Using Magnets to Find Needles in Haystacks

CRISPR-Cas immune systems in bacteria and archaea protect against viral infection, which has spurred viruses to develop dedicated inhibitors of these systems called anti-CRISPRs (Acrs). Like most host-virus arms races, many diverse examples of these immune and counter-immune proteins are encoded by the genomes of bacteria, archaea, and their viruses. For the case of Acrs, it is almost certain that just a small minority of nature's true diversity has been described. In this review, I discuss the various approaches used to identify these Acrs and speculate on the future for Acr discovery. Because Acrs can determine infection outcomes in nature and regulate CRISPR-Cas activities in applied settings, they have a dual importance to both host-virus conflicts and emerging biotechnologies. Thus, revealing the largely hidden world of Acrs should provide important lessons in microbiology that have the potential to ripple far beyond the field.

AcrPred: A hybrid optimization with enumerated machine learning algorithm to predict Anti-CRISPR proteins

CRISPR-Cas, as a tool for gene editing, has received extensive attention in recent years. Anti-CRISPR (Acr) proteins can inactivate the CRISPR-Cas defense system during interference phase, and can be used as a potential tool for the regulation of gene editing. In-depth study of Anti-CRISPR proteins is of great significance for the implementation of gene editing. In this study, we developed a high-accuracy prediction model based on two-step model fusion strategy, called AcrPred, which could produce an AUC of 0.952 with independent dataset validation. To further validate the proposed model, we compared with published tools and correctly identified 9 of 10 new Acr proteins, indicating the strong generalization ability of our model. Finally, for the convenience of related wet-experimental researchers, a user-friendly web-server AcrPred (Anti-CRISPR proteins Prediction) was established at http://lin-group.cn/server/AcrPred, by which users can easily identify potential Anti-CRISPR proteins.

Ecology and evolution of phages encoding anti-CRISPR proteins

CRISPR-Cas are prokaryotic defence systems that provide protection against invasion by mobile genetic elements (MGE), including bacteriophages. MGE can overcome CRISPR-Cas defences by encoding anti-CRISPR (Acr) proteins. These proteins are produced in the early stages of the infection and inhibit the CRISPR-Cas machinery to allow phage replication. While research on Acr has mainly focused on their discovery, structure and mode of action, and their applications in biotechnology, the impact of Acr on the ecology of MGE as well as on the coevolution with their bacterial hosts only begins to be unravelled. In this review, we summarise our current understanding on the distribution of anti-CRISPR genes in MGE, the ecology of phages encoding Acr, and their coevolution with bacterial defence mechanisms. We highlight the need to use more diverse and complex experimental models to better understand the impact of anti-CRISPR in MGE-host interactions.