PROJECT SUMMARY Various bacterial CRISPR-Cas systems and their variants have been engineered and repurposed for gene editing in animals, plants, and microbes since 2013. However, the current CRISPR-Cas genome editing tools are not perfectly safe to use. This is primarily due to the lack of an effective brake system and the off-target effect that may create unwanted cuts in the genome. Different strategies are being developed to reduce off- target effect and make CRISPR-Cas safer to use. A fact often overshadowed by the great success of genome editing is that, in the microbial world, CRISPR-Cas is an adaptive anti-viral immune mechanism present in ~50% of bacterial and ~90% of archaeal genomes. As a counterstrategy, anti-CRISPRs are produced by viruses and proviruses, as an anti-anti-viral mechanism, to inhibit the CRISPR-Cas systems of their prokaryote hosts. Thus, as the naturally occurring inhibitors of CRISPR-Cas, anti-CRISPR (Acr) proteins have obvious advantages to be used for developing safer and more controllable CRISPR-Cas genome editing technologies. The objective of this project is to develop a genomic context-based tool (AOMiner) for bioinformatics data mining of new Acr operons in human gut microbiome and virome. The significances of this project include: (i) it will enhance the experimental characterization of new anti-CRISPRs, which is fundamental to the understanding of phage-host interactions, and further to the development of novel phage-based technologies to combat pathogenic bacteria and infectious diseases; (ii) it will deliver new open source computer programs and online databases to provide novel anti-CRISPR candidates to be exploited for building safer and more controllable CRISPR-Cas genome editing tools. We recently developed AcrFinder (http://bcb.unl.edu/AcrFinder/), a bioinformatics software package for automated discovery of Acr operons, primarily based on sequence homology search. However, its ability to identify new Acrs is limited because it is largely based on homology search. The innovation of this project is that AOMiner (http://bcb.unl.edu/AOMiner) will implement a genomic context-based algorithm focusing on discovery of new Acr operons instead of Acr proteins. Additionally, this project will be the first large-scale genome mining for Acrs operons from human gut microbiome and virome, which will be developed into a gutAO database (http://bcb.unl.edu/gutAO). In summary, this project will deliver a suite of bioinformatics software tools in the form of open-source computer programs and online databases to assist the characterization of novel anti-CRISPRs.