We report a robust, versatile approach called CRISPR live-cell fluorescent in situ hybridization (LiveFISH) using fluorescent oligonucleotides for genome tracking in a broad range of cell types, including primary cells. An intrinsic stability switch of CRISPR guide RNAs enables LiveFISH to accurately detect chromosomal disorders such as Patau syndrome in prenatal amniotic fluid cells and track multiple loci in human T lymphocytes. In addition, LiveFISH tracks the real-time movement of DNA double-strand breaks induced by CRISPR-Cas9–mediated editing and consequent chromosome translocations. Finally, by combining Cas9 and Cas13 systems, LiveFISH allows for simultaneous visualization of genomic DNA and RNA transcripts in living cells. The LiveFISH approach enables real-time live imaging of DNA and RNA during genome editing, transcription, and rearrangements in single cells.

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Botnets have become one of the major threats on the Internet for serving as a vector for carrying attacks against organizations and committing cybercrimes. They are used to generate spam, carry out DDOS attacks and click-fraud, and steal sensitive information. In this paper, we propose a new approach for characterizing and detecting botnets using network traffic behaviors. Our approach focuses on detecting the bots before they launch their attack. We focus in this paper on detecting P2P bots, which represent the newest and most challenging types of botnets currently available. We study the ability of five different commonly used machine learning techniques to meet on line botnet detection requirements, namely adaptability, novelty detection, and early detection. The results of our experimental evaluation based on existing datasets show that it is possible to detect effectively botnets during the botnet Command-and Control (C&C) phase and before they launch their attacks using traffic behaviors only. However, none of the studied techniques can address all the above requirements at once.

SUMMARY Comprehensive identification of factors that can specify neuronal fate could provide valuable insights into lineage specification and reprogramming, but systematic interrogation of transcription factors, and their interactions with each other, has proven technically challenging. We developed a CRISPR activation (CRISPRa) approach to systematically identify regulators of neuronal fate specification. We activated expression of all endogenous transcription factors and other regulators via a pooled CRISPRa screen in embryonic stem cells, revealing genes including epigenetic regulators such as Ezh2 that can induce neuronal fate. Systematic CRISPR-based activation of factor pairs allowed us to generate a genetic interaction map for neuronal differentiation, with confirmation of top individual and combinatorial hits as bona fide inducers of neuronal fate. Several factor pairs could directly reprogram fibroblasts into neurons, which shared similar transcriptional programs with endogenous neurons. This study provides an unbiased discovery approach for systematic identification of genes that drive cell fate acquisition.

Repurposed CRISPR-Cas molecules provide a useful tool set for broad applications of genomic editing and regulation of gene expression in prokaryotes and eukaryotes. Recent discovery of phage-derived proteins, anti-CRISPRs, which serve to abrogate natural CRISPR anti-phage activity, potentially expands the ability to build synthetic CRISPR-mediated circuits. Here, we characterize a panel of anti-CRISPR molecules for expanded applications to counteract CRISPR-mediated gene activation and repression of reporter and endogenous genes in various cell types. We demonstrate that cells pre-engineered with anti-CRISPR molecules become resistant to gene editing, thus providing a means to generate “write-protected” cells that prevent future gene editing. We further show that anti-CRISPRs can be used to control CRISPR-based gene regulation circuits, including implementation of a pulse generator circuit in mammalian cells. Our work suggests that anti-CRISPR proteins should serve as widely applicable tools for synthetic systems regulating the behavior of eukaryotic cells.

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The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) system, a versatile RNA-guided DNA targeting platform, has been revolutionizing our ability to modify, manipulate, and visualize the human genome, which greatly advances both biological research and therapeutics development. Here, we review the current development of CRISPR/Cas9 technologies for gene editing, transcription regulation, genome imaging, and epigenetic modification. We discuss the broad application of this system to the study of functional genomics, especially genome-wide genetic screening, and to therapeutics development, including establishing disease models, correcting defective genetic mutations, and treating diseases.

Mammalian genomes possess multiple enhancers spanning an ultralong distance (>megabases) to modulate important genes, yet it is unclear how these enhancers coordinate to achieve this task. Here, we combine multiplexed CRISPRi screening with machine learning to define quantitative enhancer-enhancer interactions. We find that the ultralong distance enhancer network possesses a nested multi-layer architecture that confers functional robustness of gene expression. Experimental characterization reveals that enhancer epistasis is maintained by three-dimensional chromosomal interactions and BRD4 condensation. Machine learning prediction of synergistic enhancers provides an effective strategy to identify non-coding variant pairs associated with pathogenic genes in diseases beyond Genome-Wide Association Studies (GWAS) analysis. Our work unveils nested epistasis enhancer networks, which can better explain enhancer functions within cells and in diseases.