Single Cell Technologies

Single Cell Technologies

by Caitlin Smith

Gene expression studies have deepened our understanding of important cellular functions. However, they often assume that cells of a particular type are homogeneous—and this is not necessarily the case. “Just like people, even genetically identical cells have their own personalities,” says Lisa Isailovic, product manager at Fluidigm. “Pioneering single-cell studies are bringing a new appreciation of the extent of variation in gene expression even among apparently identical members of a population.”

Indeed, averaging cellular responses may mask important events within cell subpopulations. “Even within identical cell types, microenvironments can cause significantly different gene expression profiles, and furthermore, mutations and cell cycle differences can result in gene expression changes at the single-cell level,” says Richard Fekete, senior manager of research and development in molecular biology systems at Life Technologies. “Even genetically identical cells exposed to identical conditions display heterogeneity in gene expression.” Isailovic says that single-cell studies will be key for understanding mysteries such as “how immune systems differ between individuals and how they respond differently, how an early developing embryo begins to differentiate, and how circulating tumor cells really work.”

Teasing out live cell subpopulations with gene expression tools

Working with single cells is difficult, but the tools for single-cell analysis are becoming more available. Life Technologies’ TaqMan® PreAmp Cells-to-CT™ kit is now optimized for studying single cells, and includes reagents used in sample preparation, reverse transcription, preamplification of selected targets, and qPCR. “This method utilizes a direct lysis and analysis technology which stabilizes RNA profiles and removes genomic DNA after placing cells into a lysis solution. Importantly, it eliminates sample loss which is typically a problem with traditional purification of limited samples,” says Fekete. “Because components of the workflow have been co-developed, the complexity of the workflow is significantly decreased while increasing sensitivity. Each of these benefits is even more important for limited samples such as single cells. By linking dyes from Molecular Probes to the workflow, we are now able to optimize selection of live cells.”

Fekete believes that looking at patterns of gene expression in single cells can shed light on interactions between genes, and between genes and their environment. “For example, it is known that cells do not differentiate or progress through the cell cycle identically, and can be influenced by age, accumulation of mutations, and epigenetic factors, and these can potentially be dissected with single-cell analysis,” says Fekete. Some fields may benefit greatly from this analysis, according to Fekete: “Cell replacement therapies using stem cells require that a low number of tumor-forming cells be present in a population of transplanted cells. The ability to detect these subpopulations can have a dramatic improvement for this field.”

High-throughput studies of single cells

The ability to study gene expression in single cells opens new opportunities to researchers, says Isailovic. “First, it enables molecular profiling of an individual cell within critical populations of cells, be they a rare type of immune cell, a cancer stem cell, or a single-cell embryo,” she says. “Second, it enables molecular profiling of a population known to be heterogeneous, but where the molecular basis of the heterogeneity is unknown.”

For studying single cell gene expression, Invitrogen offers their Dynabeads® mRNA DIRECT™ Micro Kit, for isolating mRNA from single cells. “[It can detect] down to single cells from 1 ml of whole blood, using magnetic beads in both the cell isolation step and the mRNA isolation step,” says Lise Aagaard, an application scientist with Invitrogen Dynal. “The oligo(dT) Dynabeads allow isolation of polyadenylated mRNA. Immobilized mRNA on the Dynabeads enables the generation of solid-phase cDNA, which can be re-used for multiple analyses, or the mRNA can be analysed directly in reverse transcription qPCR.”

To ramp up the throughput considerably, Fluidigm offers their BioMark™ Real-Time PCR System, for high throughput real-time qPCR assays. Isailovic says that until recently, the number of genes or cells that could be profiled was limited. As a result, single-cell work was sacrificed and sample had to be pooled, masking important cell-to-cell variability. With Fluidigm's system, though, “volume requirements are so low that researchers will be able to study as many as 1,000 genes from an individual cell,” says Isailovic. “The technology facilitates thousands of single cell experiments allowing the biological differences between single cells to manifest themselves.” To profile single cells, “Fluidigm's Dynamic Arrays enable 96 single cells to be tested against 96 gene expression assays, which means the system is capable of producing 9,216 real-time qPCR data points in the same amount of time as a single 384-well plate, while using just 1/200th the amount of reagents,” she says.

Isailovic notes the importance of single-cell studies. “The movement of scientists away from the study of averages is an exciting trend in and of itself,” she says. “In many fields of biology, rare populations of cells are critical players, yet our ability to probe the biology of these populations has been hampered by a lack of available technologies. In order to gain depth of understanding, we need to be able to understand the molecular profiles of these rare populations of cells. For example, even after separation by fluorescence activated cell sorting, it's apparent that populations of seemingly identical stem cells can have different fates: some can self-review, some can differentiate. The application of single cell technologies to stem cell research will help us understand how a single stem cell can give rise to a particular lineage of cells.”

Re-thinking cell population vs. single-cell analysis

Analyzing single-cell gene expression results, as opposed to the results from a population of cells, may prove challenging. “The patterns seen in single cells are significantly different than the patterns in the whole cell population and require new and creative analysis methods,” says Isailovic. In addition, one must consider which cells should be included in the analysis, says Fekete. “Ensuring the correct cells (even live cells) are physically selected and are included in the data analysis is pivotal to the interpretation of an experiment,” he says. “What cells are included and analyzed? Every cell in a population, or just a specific cell population based on a factor that is subjectively chosen? Another aspect to think about is that since there are cells in almost every state of growth or differentiation, what becomes the true profile of a type of cell? Since work until now to define cell profiles has been done by averaging a population, a cell matching a predetermined profile most likely will not exist.”

Molecular Machines and Industries AG Zurichhas recently developed a new type of cell selection device in their microscopy-based, fully automated mmi CellEctor, according to Antje Plaschke-Schlütter, who works in business development and is head of applications. “This unique instrumentation set-up allows for automated single-cell sorting under visual control, based on an inverted microscope of type Olympus IX 81, a cell recognition unit (mmi CellExplorer), a microcapillary, and an x/y stage for the integrated cell recognition, aspiration and deposition of single cells,” says Plaschke-Schlütter. “This system is currently employed to transfer circulating tumor cells and other rare cell populations from suspensions onto a so-called AmpliGrid or into any other collection device, like a PCR-tube or a microfluidic device, for single-cell PCR and qPCR.”

“The analysis of molecular changes on the level of a single cell is currently a big challenge in the scientific community,” says Plaschke-Schlütter. “Although reliable protocols with and without pre-amplification steps have been developed for qPCR and PCR from single cells, the analyses of point mutations and larger genomic aberrations via genomic hybridization or even the analysis of epigenetic changes, are still in their ‘Kinder Shoes.’ In a next step, such technologies must be automated in order to become an integrated and reliable tool for the concepts of cellular diagnostics and personalized medicine.”

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