A lack of techniques to image multiple genomic loci in living cells has limited our ability to investigate chromosome dynamics. Here we describe CRISPRainbow, a system for labeling DNA in living cells based on nuclease-dead (d) Cas9 combined with engineered single guide RNA (sgRNA) scaffolds that bind sets of fluorescent proteins. We demonstrate simultaneous imaging of up to six chromosomal loci in individual live cells and document large differences in the dynamic properties of different chromosomal loci.

How CRISPR Cas9–guide RNA complexes navigate the nucleus and interrogate the genome is not well understood. Ma et al. track these complexes in live cells and find that mutations in the guide seed region significantly reduced the complex’s target residence time, with a commensurate impairment of cleavage.

Single-particle imaging in budding yeast demonstrates that mRNP export is fast (∼200 ms) and that mRNPs are retained at NPCs and undergo retrograde transport in a mex67-5 mutant, proving an essential role for Mex67p in directional mRNP transport.

Single-molecule binding assays enable the study of how molecular machines assemble and function. Current algorithms can identify and locate individual molecules, but require tedious manual validation of each spot. Moreover, no solution for high-throughput analysis of single-molecule binding data exists. Here, we describe an automated pipeline to analyze single-molecule data over a wide range of experimental conditions. In addition, our method enables state estimation on multivariate Gaussian signals. We validate our approach using simulated data, and benchmark the pipeline by measuring the binding properties of the well-studied, DNA-guided DNA endonuclease, TtAgo, an Argonaute protein from the Eubacterium Thermus thermophilus. We also use the pipeline to extend our understanding of TtAgo by measuring the protein’s binding kinetics at physiological temperatures and for target DNAs containing multiple, adjacent binding sites.

While the power of modern microscopy techniques is undeniable, rigorous record-keeping and quality control are required to ensure that imaging data may be properly interpreted (quality), reproduced (reproducibility), and used to extract reliable information and scientific knowledge which can be shared for further analysis (value). In the absence of agreed guidelines, it is inherently difficult for scientists to create comprehensive records of imaging experiments and ensure the quality of resulting image data or for manufacturers to incorporate standardized reporting and performance metrics. To solve this problem, the 4D Nucleome (4DN) Initiative and BioImaging North America (BINA) here propose light Microscopy Metadata specifications that scale with experimental intent and with the complexity of the instrumentation and analytical requirements. They consist of a set of three extensions of the Open Microscopy Environment (OME) Data Model, and because of their tiered nature they clearly specify which provenance and quality control metadata should be recorded for a given experiment. This endeavor is closely aligned with the undertakings of the recently established QUAlity Assessment and REProducibility in Light Microscopy (QUAREP-LiMi; quarep.org) global community initiative. As a result, the ensuing flexible 4DN-BINA-OME (NBO) framework represents a turning point towards increasing data fidelity, improving repeatability and reproducibility, easing future analysis, and facilitating the verifiable comparison of different datasets, experimental setups, and assays. The intention of this proposal is to encourage participation, critiques, and contributions from all imaging community stakeholders, including research and imaging scientists, facility personnel, instrument manufacturers, software developers, standards organizations, scientific publishers, and funders.

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Single-molecule binding assays enable the study of how molecular machines assemble and function. Current algorithms can identify and locate individual molecules, but require tedious manual validation of each spot. Moreover, no solution for highthroughput analysis of single-molecule binding data exists. Here, we describe an automated pipeline to analyze single-molecule data over a wide range of experimental conditions. We benchmarked the pipeline by measuring the binding properties of the well-studied, DNA-guided DNA endonuclease, TtAgo, an Argonaute protein from the Eubacterium Thermus thermophilus. We also used the pipeline to extend our understanding of TtAgo by measuring the protein's binding kinetics at physiological temperatures and for target DNAs containing multiple, adjacent binding sites.Internal Reflection Fluorescence (TIRF) Microscopy exploiting the linear relationship between the noise variance and the mean intensity (see SI Manual -Loading data and gain calibration), allowing automatic parameter estimation and optimal detection, localization and co-localization of single molecules.After calibrating the gain, fields of view from the wavelength channels corresponding to the different fluorophores used in the experiment must be aligned 1,7,11 . Alignment corrects differences in rotation, scaling, translation, and shear. The pipeline addresses misalignment by estimating a 'mapping function' to relate positions of the target locations in one camera to the mobile components in the other camera. The