The three-dimensional organization of chromosomes plays a key role in chromosomal function and gene expression. Chromosomes exhibit structural differences on a regional basis, both within and between chromosomes. Understanding these structural differences likely will prove useful in understanding chromosomal function in both normal and pathological states. Traditional approaches to understanding chromosomal organization, chromosome conformation capture assays, are ensemble-sequencing techniques capable of providing an average structure of the genome from millions of cells. While this provides a good overview of DNA organization in the average cell, it lacks cellular context due to the ensemble nature of data collection. Visualizing genomic organization and structure on a sub-chromosomal level is necessary for understanding relationships between genes and their environment.
Based on the use of OligoSTORM (B. J. Beliveau et al., 2015), the laboratory of Ting Wu at Harvard University, in collaboration with Bruker, has developed a method for imaging and visualizing DNA sequences in specific chromosomal regions at the super-resolution level using the Vutara VXL (view webinar). Specially designed oligonucleotides are hybridized to a chromosomal sequence. By sequentially labelling a sample with secondary oligos and then imaging with localization microscopy, a 3D image of the structure of that labeled region can be generated.
In addition to super-resolution workflows for genomic imaging, the Vutara platform with SRX software is fully capable of performing ORCA (Optical Reconstruction of Chromatin Architecture) experiments from acquisition through analysis. ORCA, originating in the laboratory of Alistair Boettiger at Stanford University, is a widefield genomic imaging technique useful for looking at small genomic regions or single genes with small probe step sizes (2-10 kb). While diffraction-limited, this method provides high sequence resolution because of smaller probe step sizes in comparison to OligoSTORM and allows for higher throughput studies due to the faster acquisition of widefield images compared to single-molecule localization data (L. J. Mateo et al., 2019).
Key features that make Vutara VXL an ideal genomic imaging platform:
SRX software offers a full suite of data filtering and statistical analysis tools for performing a wide variety of analysis. Clustering algorithms such as DBScan, OPTICS, and Delaunay analysis are available for identifying clusters of genomic data. After clusters are identified, further metrics such as particles in a cluster, volume, sphericity ratio, density of particles and radius of gyration can then be calculated.
SRX software is also equipped with analysis workflows for automatic image segmentation and reconstruction of ORCA data sets. This includes generation of distance and contact frequency maps similar to Hi-C maps obtained by ensemble chromosome conformation capture techniques.
Imaging the genome via super-resolution or widefield requires labeling a large number of probes, far more than there are spectrally distinct probes available. Thus, these methods rely heavily on sequential labeling strategies. Full integration of fluidics with the Vutara and SRX is available for all sequential labeling needs.
SRX software has been optimized to meet the requirements of this demanding application. A critical step was to implement microfluidics control in order to perform sequential labelling steps. The SRX microfluidics control module allows users to create fluidic sequences containing an unlimited number of buffers and reagents per fluidics step, as well as an unlimited number of steps per experiment. SRX assigns a user defined color for localizations in each step, and during visualization and analysis, the entire data set is merged. An unlimited number of steps can be visualized and analyzed.