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1. Bioinformatics Identification of Anti-CRISPR Loci by Using Homology, Guilt-by-Association, and CRISPR Self-Targeting Spacer Approaches

   https://doi.org/10.1128/mSystems.00455-19  

   Yin, Yanbin; Yang, Bowen; Entwistle, Sarah; Claesson, Marcus J. (October 2019, mSystems)

   ABSTRACT Anti-CRISPR (Acr) loci/operons encode Acr proteins and Acr-associated (Aca) proteins. Forty-five Acr families have been experimentally characterized inhibiting seven subtypes of CRISPR-Cas systems. We have developed a bioinformatics pipeline to identify genomic loci containing Acr homologs and/or Aca homologs by combining three computational approaches: homology, guilt-by-association, and self-targeting spacers. Homology search found thousands of Acr homologs in bacterial and viral genomes, but most are homologous to AcrIIA7 and AcrIIA9. Investigating the gene neighborhood of these Acr homologs revealed that only a small percentage (23.0% in bacteria and 8.2% in viruses) of them have neighboring Aca homologs and thus form Acr-Aca operons. Surprisingly, although a self-targeting spacer is a strong indicator of the presence of Acr genes in a genome, a large percentage of Acr-Aca loci are found in bacterial genomes without self-targeting spacers or even without complete CRISPR-Cas systems. Additionally, for Acr homologs from genomes with self-targeting spacers, homology-based Acr family assignments do not always agree with the self-targeting CRISPR-Cas subtypes. Last, by investigating Acr genomic loci coexisting with self-targeting spacers in the same genomes, five known subtypes (I-C, I-E, I-F, II-A, and II-C) and five new subtypes (I-B, III-A, III-B, IV-A, and V-U4) of Acrs were inferred. Based on these findings, we conclude that the discovery of new anti-CRISPRs should not be restricted to genomes with self-targeting spacers and loci with Acr homologs. The evolutionary arms race of CRISPR-Cas systems and anti-CRISPR systems may have driven the adaptive and rapid gain and loss of these elements in closely related genomes. IMPORTANCE As a naturally occurring adaptive immune system, CRISPR-Cas (clustered regularly interspersed short palindromic repeats–CRISPR-associated genes) systems are widely found in bacteria and archaea to defend against viruses. Since 2013, the application of various bacterial CRISPR-Cas systems has become very popular due to their development into targeted and programmable genome engineering tools with the ability to edit almost any genome. As the natural off-switch of CRISPR-Cas systems, anti-CRISPRs have a great potential to serve as regulators of CRISPR-Cas tools and enable safer and more controllable genome editing. This study will help understand the relative usefulness of the three bioinformatics approaches for new Acr discovery, as well as guide the future development of new bioinformatics tools to facilitate anti-CRISPR research. The thousands of Acr homologs and hundreds of new anti-CRISPR loci identified in this study will be a valuable data resource for genome engineers to search for new CRISPR-Cas regulators. 

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2. Network-Based Prediction of Novel CRISPR-Associated Genes in Metagenomes

   https://doi.org/10.1128/mSystems.00752-19  

   Weissman, Jake L.; Johnson, Philip L. (February 2020, mSystems)

   Chia, Nicholas (Ed.)

   ABSTRACT A diversity of clustered regularly interspaced short palindromic repeat (CRISPR)-Cas systems provide adaptive immunity to bacteria and archaea through recording “memories” of past viral infections. Recently, many novel CRISPR-associated proteins have been discovered via computational studies, but those studies relied on biased and incomplete databases of assembled genomes. We avoided these biases and applied a network theory approach to search for novel CRISPR-associated genes by leveraging subtle ecological cooccurrence patterns identified from environmental metagenomes. We validated our method using existing annotations and discovered 32 novel CRISPR-associated gene families. These genes span a range of putative functions, with many potentially regulating the response to infection. IMPORTANCE Every branch on the tree of life, including microbial life, faces the threat of viral pathogens. Over the course of billions of years of coevolution, prokaryotes have evolved a great diversity of strategies to defend against viral infections. One of these is the CRISPR adaptive immune system, which allows microbes to “remember” past infections in order to better fight them in the future. There has been much interest among molecular biologists in CRISPR immunity because this system can be repurposed as a tool for precise genome editing. Recently, a number of comparative genomics approaches have been used to detect novel CRISPR-associated genes in databases of genomes with great success, potentially leading to the development of new genome-editing tools. Here, we developed novel methods to search for these distinct classes of genes directly in environmental samples (“metagenomes”), thus capturing a more complete picture of the natural diversity of CRISPR-associated genes. 

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3. CRISPR Spacers Indicate Preferential Matching of Specific Virioplankton Genes

   https://doi.org/10.1128/mBio.02651-18  

   Nasko, Daniel J.; Ferrell, Barbra D.; Moore, Ryan M.; Bhavsar, Jaysheel D.; Polson, Shawn W.; Wommack, K. Eric; Martiny, Jennifer (April 2019, mBio)

   ABSTRACT Viral infection exerts selection pressure on marine microbes, as virus-induced cell lysis causes 20 to 50% of cell mortality, resulting in fluxes of biomass into oceanic dissolved organic matter. Archaeal and bacterial populations can defend against viral infection using the clustered regularly interspaced short palindromic repeat (CRISPR)-associated (Cas) system, which relies on specific matching between a spacer sequence and a viral gene. If a CRISPR spacer match to any gene within a viral genome is equally effective in preventing lysis, no viral genes should be preferentially matched by CRISPR spacers. However, if there are differences in effectiveness, certain viral genes may demonstrate a greater frequency of CRISPR spacer matches. Indeed, homology search analyses of bacterioplankton CRISPR spacer sequences against virioplankton sequences revealed preferential matching of replication proteins, nucleic acid binding proteins, and viral structural proteins. Positive selection pressure for effective viral defense is one parsimonious explanation for these observations. CRISPR spacers from virioplankton metagenomes preferentially matched methyltransferase and phage integrase genes within virioplankton sequences. These virioplankton CRISPR spacers may assist infected host cells in defending against competing phage. Analyses also revealed that half of the spacer-matched viral genes were unknown, some genes matched several spacers, and some spacers matched multiple genes, a many-to-many relationship. Thus, CRISPR spacer matching may be an evolutionary algorithm, agnostically identifying those genes under stringent selection pressure for sustaining viral infection and lysis. Investigating this subset of viral genes could reveal those genetic mechanisms essential to virus-host interactions and provide new technologies for optimizing CRISPR defense in beneficial microbes. IMPORTANCE The CRISPR-Cas system is one means by which bacterial and archaeal populations defend against viral infection which causes 20 to 50% of cell mortality in the ocean. We tested the hypothesis that certain viral genes are preferentially targeted for the initial attack of the CRISPR-Cas system on a viral genome. Using CASC, a pipeline for CRISPR spacer discovery, and metagenome data from oceanic microbes and viruses, we found a clear subset of viral genes with high match frequencies to CRISPR spacers. Moreover, we observed a many-to-many relationship of spacers and viral genes. These high-match viral genes were involved in nucleotide metabolism, DNA methylation, and viral structure. It is possible that CRISPR spacer matching is an evolutionary algorithm pointing to those viral genes most important to sustaining infection and lysis. Studying these genes may advance the understanding of virus-host interactions in nature and provide new technologies for leveraging CRISPR-Cas systems in beneficial microbes. 

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4. A CRISPR-Cas9–integrase complex generates precise DNA fragments for genome integration

   https://doi.org/10.1093/nar/gkab123  

   Jakhanwal, Shrutee; Cress, Brady F; Maguin, Pascal; Lobba, Marco J; Marraffini, Luciano A; Doudna, Jennifer A (March 2021, Nucleic acids research)

   null (Ed.)

   CRISPR-Cas9 is an RNA-guided DNA endonuclease involved in bacterial adaptive immunity and widely repurposed for genome editing in human cells, animals and plants. In bacteria, RNA molecules that guide Cas9′s activity derive from foreign DNA fragments that are captured and integrated into the host CRISPR genomic locus by the Cas1-Cas2 CRISPR integrase. How cells generate the specific lengths of DNA required for integrase capture is a central unanswered question of type II-A CRISPR-based adaptive immunity. Here, we show that an integrase supercomplex comprising guide RNA and the proteins Cas1, Cas2, Csn2 and Cas9 generates precisely trimmed 30-base pair DNA molecules required for genome integration. The HNH active site of Cas9 catalyzes exonucleolytic DNA trimming by a mechanism that is independent of the guide RNA sequence. These results show that Cas9 possesses a distinct catalytic capacity for generating immunological memory in prokaryotes. 

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5. Evolutionary trends in Bombella apis CRISPR-Cas systems

   https://doi.org/10.1128/msystems.00166-25  

   Ganote, Carrie L; Caesar, Lílian; Rice, Danny W; Whitaker, Rachel J; Newton, Irene_L G (July 2025, mSystems)

   Gilbert, Jack A (Ed.)

   ABSTRACT Bacteria and archaea employ a rudimentary immune system, CRISPR-Cas, to protect against foreign genetic elements such as bacteriophage. CRISPR-Cas systems are found inBombella apis.B. apisis an important honey bee symbiont, found primarily in larvae, queens, and hive compartments.B. apisis found in the worker bee gut but is not considered a core member of the bee microbiome and has therefore been understudied with regard to its importance in the honey bee colony. However,B. apisappears to play beneficial roles in the colony, by protecting developing brood from fungal pathogens and by bolstering their development under nutritional stress. Previously, we identified CRISPR-Cas systems as being acquired byB. apisin its transition to bee association, as they are absent in a sister clade. Here, we assess the variation and distribution of CRISPR-Cas types acrossB. apisstrains. We found multiple CRISPR-Cas types, some of which have multiple arrays, within the sameB. apisgenomes and also in the honey bee queen gut metagenomes. We analyzed the spacers between strains to identify the history of mobile element interaction for eachB. apisstrain. Finally, we predict interactions between viral sequences and CRISPR systems from different honey bee microbiome members. Our analyses show that theB. apisCRISPR-Cas systems are dynamic; that microbes in the same niche have unique spacers, which supports the functionality of these CRISPR-Cas systems; and that acquisition of new spacers may be occurring in multiple locations in the genome, allowing for a flexible antiviral arsenal for the microbe. IMPORTANCEHoney bee worker gut microbes have been implicated in everything from protection from pathogens to breakdown of complex polysaccharides in the diet. However, there are multiple niches within a honey bee colony that host different groups of microbes, including the acetic acid bacteriumBombella apis.B. apisis found in the colony food stores, in association with brood, in worker hypopharyngeal glands, and in the queen’s digestive tract. The roles thatB. apismay serve in these environments are just beginning to be discovered and include the production of a potent antifungal that protects developing bees and supplementation of dietary lysine to young larvae, bolstering their nutrition. Niche specificity inB. apismay be affected by the pressures of bacteriophage and other mobile elements, which may target different strains in each specific bee environment. Studying the interplay betweenB. apisand its mobile genetic elements (MGEs) may help us better understand microbial community dynamics within the colony and the potential ramifications for the honey bee host. 

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