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Garcia, B.

Publications and source records attributed to Garcia, B..

2 recordsLinked to original sources

Potent Cas9 inhibition in bacterial and human cells by new anti-CRISPR protein families

CRISPR-Cas systems are widely used for genome engineering technologies, and in their natural setting, they play crucial roles in bacterial and archaeal adaptive immunity, protecting against phages and other mobile genetic elements. Previously we discovered bacteriophage-encoded Cas9-specific anti-CRISPR (Acr) proteins that serve as countermeasures against host bacterial immunity by inactivating their CRISPR-Cas systems1. We hypothesized that the evolutionary advantages conferred by anti-CRISPRs would drive the widespread occurrence of these proteins in nature2-4. We have identified new anti-CRISPRs using the bioinformatic approach that successfully identified previous Acr proteins1 against Neisseria meningitidis Cas9 (NmeCas9). In this work we report two novel anti-CRISPR families in strains of Haemophilus parainfluenzae and Simonsiella muelleri, both of which harbor type II-C CRISPR-Cas systems5. We characterize the type II-C Cas9 orthologs from H. parainfluenzae and S. muelleri, show that the newly identified Acrs are able to inhibit these systems, and define important features of their inhibitory mechanisms. The S. muelleri Acr is the most potent NmeCas9 inhibitor identified to date. Although inhibition of NmeCas9 by anti-CRISPRs from H. parainfluenzae and S. muelleri reveals cross-species inhibitory activity, more distantly related type II-C Cas9s are not inhibited by these proteins. The specificities of anti-CRISPRs and divergent Cas9s appear to reflect co-evolution of their strategies to combat or evade each other. Finally, we validate these new anti-CRISPR proteins as potent off-switches for Cas9 genome engineering applications.

molecular biology

The Virtual Metabolic Human database: integrating human and gut microbiome metabolism with nutrition and disease

A multitude of factors contribute to complex diseases and can be measured with \"omics\" methods. Databases facilitate data interpretation for underlying mechanisms. Here, we describe the Virtual Metabolic Human (VMH, http://vmh.life) database encapsulating current knowledge of human metabolism within five interlinked resources \"Human metabolism\", \"Gut microbiome\", \"Disease\", \"Nutrition\", and \"ReconMaps\". The VMH captures 5,180 unique metabolites, 17,730 unique reactions, 3,288 human genes, 255 Mendelian diseases, 818 microbes, 632,685 microbial genes, and 8,790 food items. The VMHs unique features are i) the hosting the metabolic reconstructions of human and gut microbes amenable for metabolic modeling; ii) seven human metabolic maps for data visualization; iii) a nutrition designer; iv) a user-friendly webpage and application-programming interface to access its content; and v) user feedback option for community engagement. We demonstrate with four examples the VMHs utility. The VMH represents a novel, interdisciplinary database for data interpretation and hypothesis generation to the biomedical community.

systems biology