Baohui Chen

Expanding the CRISPR imaging toolset with Staphylococcus aureus Cas9 for simultaneous imaging of multiple genomic loci

In order to elucidate the functional organization of the genome, it is vital to directly visualize the interactions between genomic elements in living cells. For this purpose, we engineered the Cas9 protein from Staphylococcus aureus (SaCas9) for the imaging of endogenous genomic loci, which showed a similar robustness and efficiency as previously reported for Streptococcus pyogenes Cas9 (SpCas9). Imaging readouts allowed us to characterize the DNA-binding activity of SaCas9 and to optimize its sgRNA scaffold. Combining SaCas9 and SpCas9, we demonstrated two-color CRISPR imaging with the capability to resolve genomic loci spaced by <300 kb. Combinatorial color-mixing further enabled us to code multiple genomic elements in the same cell. Our results highlight the potential of combining SpCas9 and SaCas9 for multiplexed CRISPR-Cas9 applications, such as imaging and genome engineering.

Versatile protein tagging in cells with split fluorescent protein

In addition to the popular method of fluorescent protein fusion, live cell protein imaging has now seen more and more application of epitope tags. The small size of these tags may reduce functional perturbation and enable signal amplification. To address their background issue, we adapt self-complementing split fluorescent proteins as epitope tags for live cell protein labelling. The two tags, GFP11 and sfCherry11 are derived from the eleventh β-strand of super-folder GFP and sfCherry, respectively. The small size of FP11-tags enables a cost-effective and scalable way to insert them into endogenous genomic loci via CRISPR-mediated homology-directed repair. Tandem arrangement FP11-tags allows proportional enhancement of fluorescence signal in tracking intraflagellar transport particles, or reduction of photobleaching for live microtubule imaging. Finally, we show the utility of tandem GFP11-tag in scaffolding protein oligomerization. These experiments illustrate the versatility of FP11-tag as a labelling tool as well as a multimerization-control tool for both imaging and non-imaging applications.

Imaging Specific Genomic DNA in Living Cells

The three-dimensional organization of the genome plays important roles in regulating the functional output of the genome and even in the maintenance of epigenetic inheritance and genome stability. Here, we review and compare a number of newly developed methods-especially those that utilize the CRISPR (clustered regularly interspaced short palindromic repeat)-Cas9 (CRISPR-associated protein 9) system-that enable the direct visualization of specific, endogenous DNA sequences in living cells. We also discuss the practical considerations in implementing the CRISPR imaging technique to achieve sufficient signal-to-background levels, high specificity, and high labeling efficiency. These DNA labeling methods enable tracking of the copy number, localization, and movement of genomic elements, and we discuss the potential applications of these methods in understanding the searching and targeting mechanism of the Cas9-sgRNA complex, investigating chromosome organization, and visualizing genome instability and rearrangement.

Imaging Genomic Elements in Living Cells Using CRISPR/Cas9

In addition to their applications in genome editing and gene expression regulation, programmable DNA recognition systems, including both CRISPR and TALE, have been recently engineered for the visualization of endogenous genomic elements in living cells. This capability greatly helps the study of genome function regulation by its physical organization and interaction with other nuclear structures. This chapter first discusses the general considerations in designing and implementing the imaging system. The subsequent sections provide detailed protocols to use the CRISPR/Cas9 system to label and image specific genomic loci, including the establishment of expression systems for dCas9-GFP and sgRNA, the procedure to label repetitive sequences of telomeres and protein-coding genes, the simultaneous expression of many sgRNAs to label a nonrepetitive locus, and the verification of signal specificity by FISH.

CRISPR-Tag: an Efficient DNA Tagging System in Living Cells

A lack of efficient tools to image non-repetitive genes in living cells has limited our ability to explore the functional impact of spatiotemporal dynamics of genes. Here, we addressed this issue by developing the CRISPR-Tag system as a new DNA tagging strategy to label protein-coding genes with high signal-to-noise ratio under wild-field fluorescence microscopy by using 1 to 4 highly active sgRNAs. The CRISPR-Tag, with minimal size of ∼ 250 bp, represents an easily and broadly applicable technique to study spatiotemporal organization of genomic elements in living cells.

Correlation analysis framework for localization-based superresolution microscopy

Significance Correlation analysis is one of the most widely used image-processing methods. In the quantitative analysis of localization-based superresolution images, there still lacks a generalized coordinate-based correlation analysis framework to take full advantage of the superresolution information. We propose a coordinate-based correlation analysis framework for localization-based superresolution microscopy. We mathematically prove that point-point distance distribution is equivalent to pixel-based correlation function. This framework can be easily extended to model the effect of localization uncertainty, to the time domain and other distance definitions. We demonstrated the versatility and advantages of our framework in three applications of superresolution microscopy: model-free image alignment and averaging for structural analysis, spatiotemporal correlation analysis for mapping molecule diffusion, and quantifying spatial relationships between complex structures. Superresolution images reconstructed from single-molecule localizations can reveal cellular structures close to the macromolecular scale and are now being used routinely in many biomedical research applications. However, because of their coordinate-based representation, a widely applicable and unified analysis platform that can extract a quantitative description and biophysical parameters from these images is yet to be established. Here, we propose a conceptual framework for correlation analysis of coordinate-based superresolution images using distance histograms. We demonstrate the application of this concept in multiple scenarios, including image alignment, tracking of diffusing molecules, as well as for quantification of colocalization, showing its superior performance over existing approaches.