Visualisation of dCas9 target search in vivo using an open-microscopy framework

Martens, Koen J.A.; Beljouw, Sam P. B. van; der, Simon van; Vink, Jochem N.A.; Baas, Sander; Vogelaar, George A.; Brouns, Stan J. J.; Baarlen, Peter van; Kleerebezem, Michiel; Hohlbein, Johannes

doi:10.1038/s41467-019-11514-0

Cited by 102 publications

(151 citation statements)

References 74 publications

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“…Cascade was suggested to spend approximately 50% of its search time on DNA and the rest distributed in the cytoplasm, however, the impact of phage infection and Cas3 localization have not determined. Similar binding kinetics have also been suggested for Cas9 expressed in E. coli and Lactococcus lactis (Jones et al, 2017;Martens et al, 2019). Thus, unlike other DNA interacting proteins like LacI, which spends 90% of its time in the DNA (Elf et al, 2007), these CRISPR-Cas complexes exhibit dynamic association-dissociation kinetics potentially for rapid target identification (Vink et al, 2020).…”

Section: Introductionmentioning

confidence: 58%

Distinct subcellular localization of a Type I CRISPR complex and the Cas3 nuclease in bacteria

Govindarajan

Borges

Bondy‐Denomy

2020

Preprint

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CRISPR-Cas systems are prokaryotic adaptive immune systems that target mobile genetic elements including phages. While CRISPR-Cas systems have been well characterized biochemically and structurally, in vivo spatiotemporal regulation and cell biology remains largely unaddressed. Here, we studied the localization of native Type I-F CRISPR-Cas system of the pathogen Pseudomonas aeruginosa via fluorescent fusions to Csy1 (Cas8), Csy4 (Cas6) and Cas3 which are involved in PAM recognition, crRNA processing, and nuclease activity, respectively. Chromosomally tagged proteins were fully functional for phage targeting and inhibited by anti-CRISPR proteins. When targeted to an integrated prophage, the Csy complex and Cas3 generated a single cellular focus, however when lacking a protospacer target, the Csy complex is broadly nucleoid bound, while Cas3 is diffuse in the cytoplasm. Nucleoid association for the Csy proteins is crRNA-dependent, but crRNA-sequence independent, suggesting formation of the Csy complex engenders genome surveillance. Expression of anti-CRISPR AcrIF2, known to prevent the Csy complex from binding to DNA via protospacer adjacent motif (PAM) competition, abolished nucleoid surveillance, while AcrIF1, which blocks crRNA:DNA hybridization downstream of the PAM, did not. These results suggest the genome surveillance is a result of direct PAM interactions, independent of other host factors. The Cas9 nuclease, when heterologously expressed in P. aeruginosa, also appears nucleoid localized when its gRNA is provided, which is abolished by PAM mimic, AcrIIA4. Finally, by employing fluorescently labeled phages, we observe that phage infection does not significantly modulate the distribution of the Csy complex and Cas3, despite doing so as a prophage. In summary, our findings demonstrate that a Type I CRISPR-Cas complex in its natural environment is localized in the nucleoid, separated from nuclease-helicase, Cas3.

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Section: Introductionmentioning

confidence: 58%

Distinct subcellular localization of a Type I CRISPR complex and the Cas3 nuclease in bacteria

Govindarajan

Borges

Bondy‐Denomy

2020

Preprint

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“…That is excellent for sensors and logic gates, but we show a time-varying system that fluctuates between on/off reporter states in an analog manner. In addition, our characterization method is one of the first examples of single-cell analysis of a dCas9 or dCas12a circuit in bacteria (Jones et al 2017, Martens et al 2019, Camsund et al 2020. We also use our setup to explicitly measure single-cell dCas9-sgRNA and dCas12a-crRNA repression times in thousands of individual cells.…”

Section: Resultsmentioning

confidence: 99%

Towards a translationally-independent RNA-based synthetic oscillator using deactivated CRISPR-Cas

Kuo

Yuan

Sánchez

et al. 2020

Preprint

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In synthetic circuits, CRISPR-Cas systems have been used effectively for endpoint changes from an initial state to a final state, such as in logic gates. Here, we use deactivated Cas9 (dCas9) and deactivated Cas12a (dCas12a) to construct dynamic RNA ring oscillators that cycle continuously between states over time in bacterial cells. While our dCas9 circuits using 103nucleotide guide RNAs showed irregular fluctuations with a wide distribution of peak-to-peak period lengths averaging ~9 generations, a dCas12a oscillator design with 40-nucleotide CRISPR RNAs performed much better, having a strongly repressed off-state, distinct autocorrelation function peaks, and an average peak-to-peak period length of ~7.5 generations. Along with freerunning oscillator circuits, we measure repression response times in open-loop systems with inducible RNA steps to compare with oscillator period times. We track thousands of cells for 24+ hours at the single-cell level using a microfluidic device. In creating a circuit with nearly translationally-independent behavior, as the RNAs control each others' transcription, we present the possibility for a synthetic oscillator generalizable across many organisms and readily linkable for transcriptional control.

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“…Compared to other simulation-based frameworks for estimating transition rates [48][49][50] , anaDDA holds several advantages. First, the distributions of simulations are not exact as they are generated from a limited number of particles and therefore do not allow for using an MLE approach, which requires convergence based on exact probability even for small changes in the parameter space.…”

Section: Discussionmentioning

confidence: 99%

Extracting transition rates in single-particle tracking using analytical diffusion distribution analysis

Vink

Brouns

Hohlbein

2020

Preprint

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Single-particle tracking is an important technique in the life sciences to understand the kinetics of biomolecules. Observed diffusion coefficients in vivo, for example, enable researchers to determine whether biomolecules are moving alone, as part of a larger complex or are bound to large cellular components such as the membrane or chromosomal DNA. A remaining challenge has been to retrieve quantitative kinetic models especially for molecules that rapidly interchange between different diffusional states. Here, we present analytic diffusion distribution analysis (anaDDA), a framework that allows extracting transition rates from distributions of observed diffusion coefficients. We show that theoretically predicted distributions accurately match simulated distributions and that anaDDA outperforms existing methods to retrieve kinetics especially in the fast regime of 0.1-10 transitions per imaging frame. AnaDDA does account for the effects of confinement and tracking window boundaries. Furthermore, we added the option to perform global fitting of data acquired at different frame times, to allow complex models with multiple states to be fitted confidently. Previously, we have started to develop anaDDA to investigate the target search of CRISPR-Cas complexes. In this work, we have optimized the algorithms and reanalysed experimental data of DNA polymerase I diffusing in live E. coli. We found that long-lived DNA interaction by DNA polymerase are more abundant upon DNA damage, suggesting roles in DNA repair. We further revealed and quantified fast DNA probing interactions that last shorter than 10 ms. AnaDDA pushes the boundaries of the timescale of interactions that can be probed with single-particle tracking and is a mathematically rigorous framework that can be further expanded to extract detailed information about the behaviour of biomolecules in living cells. the apparent diffusion coefficient D* is calculated from the mean squared displacement (MSD).The different mobilities of proteins switching between a DNA-bound state, in which proteins diffuse very slowly, and a DNA-free state, in which proteins diffuse through the cytoplasm, can provide kinetic information on the frequency and longevity of DNA-protein interactions.The ability to extract this information, however, is compromised by photo bleaching, which limits the length of each track to a few localisations in the case of fluorescent proteins 19 . Furthermore, the limited localization precision increases the apparent diffusion of immobile states. Therefore, measured displacements cannot be unambiguously assigned to either a bound or a diffusing state.As a consequence, histograms of D* values are often rather broad making a clear distinction between two diffusional states of a single species impossible. For the special case of noninterconverting D* distributions, the shape of distributions can be calculated for a fixed number of analysed steps 20,21 and, via fitting of the experimental data, used to extract the fractions of mobile and immobile proteins.Anothe...

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Visualisation of dCas9 target search in vivo using an open-microscopy framework

Cited by 102 publications

References 74 publications

Distinct subcellular localization of a Type I CRISPR complex and the Cas3 nuclease in bacteria

Distinct subcellular localization of a Type I CRISPR complex and the Cas3 nuclease in bacteria

Towards a translationally-independent RNA-based synthetic oscillator using deactivated CRISPR-Cas

Extracting transition rates in single-particle tracking using analytical diffusion distribution analysis

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