Scientists have developed a new method that allows them to select individual cells from a population that is growing on the surface of a laboratory dish, and then study their contents using DNA and protein sequencing technologies to analyze the cell genome, transcriptome, and proteome. Developed by University of Toronto researchers, the approach is claimed to be the first to marry cell microscopy with -omics technologies, to link cells’ physical parameters that are visible by eye—such as appearance, the presence of surface markers, or cell-cell contacts—to their molecular makeup. The team has called the new tool DISCO (digital microfluidic isolation of single cells for –omics), and claims it will enable a deeper study of stem cells and other rare cell types for the development of new therapeutic approaches.
“We give the user the power to take beautiful fluorescence microscopy images to learn everything that can be learned about cells growing in situ and then connect that information with the cell’s genome, transcriptome, and proteome,” said research lead Aaron Wheeler, PhD, a professor of chemistry and biomedical engineering in the Donnelly Centre for Cellular and Biomolecular Research who led the work. Wheeler and colleagues describe the platform in a paper in Nature Communications, which is titled, “Digital microfluidic isolation of single cells for –Omics.”
Single-cell -omics analysis methods are having a transformative effect on research in the life sciences, the authors stated. The rise of single-cell analyses over the past five years has enabled researchers to measure tens of thousands of molecules in each cell, transforming their ability to study tissues and organs on a granular level. “Specifically, the capacity to assess genomes, transcriptomes, or proteomes of individual cells in place of (or in addition to) measuring the average states of populations of cells is leading to important advances in cancer biology, neuroscience, neural stem cell therapeutics, and beyond.”
These new capabilities are possible thanks to microfluidics-based techniques, which typically involving partitioning cells into droplets, microchannels or microwells, and then analyzed by whichever –omics technology is relevant. However, such approaches miss important information about the cells’ physical features and local microenvironment, because the cells have to be placed in suspension and separated from each other prior to analysis. “A drawback of these methods, however, is a lack of capacity to correlate the single-cell genomes, transcriptomes, or proteomes with the phenotypes of adherent cells in situ (e.g., size, shape, intracellular marker expression, distance to neighboring cells),” the team continued.
“There’s a revolution going on right now with single cell omics,” said Wheeler, who is Canada Research Chair in Microfluidic Bioanalysis. “But I came across people who were disappointed that there weren’t able to capture phenotypic information about the cell in its in situ environment. And I thought we might be able to come up with a way to select particular cells from that population and analyze them,” he says.
To try and address these drawbacks, the team developed their new tool, DISCO, which is composed of a microscope fitted with a high frequency laser and a microfluidic chip for the collection of cellular material. The microscope allows the user to take detailed images of the target cell before shining the laser on it. The energy from the laser causes a tiny bubble to form and pop in the proximity of the cell, rupturing its membrane and shooting its contents up into a droplet on the microfluidic chip, from where it is retrieved for molecular sequencing. “Specifically, DISCO combines digital microfluidics, laser cell lysis, and artificial intelligence-driven image processing to collect the contents of single cells from heterogeneous populations, followed by analysis of single-cell genomes and transcriptomes by next-generation sequencing, and proteomes by nanoflow liquid chromatography and tandem mass spectrometry,” the investigators continued.
“Our platform focuses on the metadata that you lose when you do single cell suspension, things like cell position, what were its morphological properties, who were its neighbors? Those are all the things that we can capture before we do the single cell sequencing ,” further explained co-author Erica Scott, PhD, a postdoctoral fellow in the lab who spearheaded the work along with two PhD students in the lab, Julian Lamanna and Harrison Edwards. “To our knowledge, this is the only platform that can take cells in culture and do this kind of thing.”
For their proof of principle experiments, the researchers demonstrated DISCO’s ability to faithfully relate omics data to individual human and mouse brain cancer cells that were cultured side by side. The findings brought into sharp focus the extent to which the contacts between cells can influence their molecular states. The studies showed that the expression of 5,000 mouse genes—about a fifth of the genome—was altered in individual B16 mouse cells that had been surrounded by human cells instead of murine cells. “The transcriptome profiles were found to be radically different for B16 cells collected from monoculture versus co-culture,” the researchers continued.
The findings could have important implications for many labs that seek to gain a better understanding of healthy and diseased human tissue, such as tumors, by growing them in mice so that they can be studied in a whole-body environment. “This kind of analysis can lend insight into the often competitive relationship exhibited by transplanted human cells in resident murine cells in the brain,” they noted. If gene expression is similarly affected in the human graft, these changes could have ramification for treatment development, said Wheeler.
Fortunately, DISCO may soon offer a window into the cells in their natural environment as the researchers are working to adapt it to the analysis of tissue slices. Their ultimate goal is to apply DISCO to the study of rare cell types, such as stem cells, whose regenerative potential is in large part regulated by their immediate environment, to help advance new therapies. “The levels of context and accountability of the single cell analyses produced by DISCO provide some of the most efficient usage of single cell -omics data to date, with the potential to extend its utility to any rare cell population, while incorporating contextual dependencies,” the authors concluded. “The application of evaluating tissue slices is an important one, and although not addressed here, we propose that application represents an exciting horizon for DISCO studies in the future.”