Jeffrey S. Buguliskis Ph.D. Technical Editor Genetic Engineering & Biotechnology News

The Art of Isolating One Genome Away from Many

In the middle of the 19th century, medicine began to undergo a philosophical transformation away from the holistic thinking of a diseased entity and shifted toward training students to think more microscopically. This approach was epitomized by the observations of Rudolf Virchow, often referred to as the father of modern pathology, when he stated that a whole organism does not get sick—only specific cells or group of cells do.

By 1855, Virchow expanded upon his original observations and published his now famous precept “omnis cellula e cellula” (“every cell stems from another cell”), which ushered in the field of cellular pathology and cemented him as a leader in diagnostic medicine at the time.

The profound impact of Virchow’s statement cannot be overstated, as it came almost five years before Charles Darwin published his now seminal dissertation on evolution, “On the Origin of Species by Means of Natural Selection,” which was released in November of 1859. Virchow’s ideas that “there is no life except through direct succession” and that “no matter how we twist and turn, we shall eventually come back to the cell,” not only revolutionized the field of anatomical pathology, but had sweeping implications across a breadth of the biological sciences. One of his biggest achievements that has arguably had the greatest impact for modern medicine was correctly linking the origin of cancers from what were seemingly normal cells.

Virchow’s ideas on cancer have been expanded upon over the years but many of his central premises still hold true. Today, we better understand that tumor evolution is a series of clonal cell expansions that are each triggered by the serial acquisition of somatic driver mutations, each conferring a selective advantage. Over the past decade we have learned a great deal about how cancers develop due to initiatives that have utilized massive parallel sequencing methods employed by next-generation sequencing (NGS) platforms. Much of the data collected from these studies compares cancers from various anatomical sites or different time points and often reveals a dynamic competition between subclonal populations forcing tumors to undergo a fragmented evolutionary selection processes.

Additionally, most large-scale cancer sequencing projects have processed genetic material from the millions of cells comprising whole tumors. While this can provide useful baseline information about cancer variation from patient to patient, the heterogeneity across individual cancer cell populations contained within each tumor can be overlooked or undervalued. However, recent advances in NGS technology have made it feasible to analyze the genome of single cells that reside within a tumor.

Single-cell genomics allows physicians and clinical researchers to definitively characterize intratumoral cell diversity by isolating, sorting, and amplifying cellular genomes—a practice that is becoming an integral requirement for precision medicine in oncology. However, the technology is still relatively new to many researchers and faces a few obstacles before it becomes commonplace within clinical settings.

“Single-cell research is still in its infancy,” points out Howard High, fellow and corporate communications officer at Fluidigm. “As such, securing funding, creating experiments that give results that matter, figuring out how to manage and use the huge amount of data generated (bioinformatics), creating researchers that are expert in both genomics and cell development, and driving down costs while building our understanding and knowledge base are just a few of the hurdles single-cell researchers are tackling as this field of study rapidly grows.”

Isolate and Conquer

On paper, the dissociation of cells from solid tumors and isolating them in order to extract their nuclear DNA seems a straightforward enough process. However in practice, scientists know that this is rarely true. By their very nature, cells have great affinity for one another and don’t separate easily. Moreover, due to overexpression of various cell surface molecules, many tumors can be even more difficult to pry apart than their nonmutant counterparts. Luckily, over the years researchers have become quite adept at disassembling tissues, employing an array of mechanical and chemical techniques.

Two main methods have emerged that allow investigators to isolate the genetic material within cancer cells. The first utilizes a florescent DNA dye (DAPI) and precision flow cytometry (FC) and cell sorting. Typically, a frozen sample from a tumor is placed into a DAPI-containing cell lysis buffer that strips away the cell membrane and leaves the nuclear membrane intact. The FC then separates cells on the basis of ploidy, which is the number of sets of chromosomes in a given cell.

For all normal human cells, with the exception of germline cells, the nucleus is diploid, containing 23 pairs of chromosomes. Cancerous cells can either have too many chromosomes or chromosomal fragments (polyploidy) or too few (aneuploidy).

The main drawback of the FC method is that it limits the possibility of obtaining transcriptomic data from the isolated cells, as that genetic material would be contained within the cytosol, which is dispersed upon addition of the lysis buffer. A second method addresses these concerns and allows for use of microfluidic devices—growing in popularity with many researchers due to their portability and cost.

Using enzymatic treatments on tumor samples researchers can acquire a suspension of single cells that can be cataloged by cell sorting platforms. As mentioned, this technique can be combined with microfluidic devices that have the advantage of not only being able to capture single cells, but also having reaction chambers that can be used to process DNA or RNA from the cancer cells that being analyzed.

After Conquering, Analyze the Spoils

Before a single-cell genomic study even begins, investigators often weigh their options and decide which analysis method is going to provide them with most bang for their buck, from an informational standpoint. Whole genome amplification (WGA) provides the underlying data about the genome of each isolated tumor cell or nuclei and given the appropriate analysis method can be used to profile gene copy numbers or single nucleotide polymorphism data. Alternatively RNA-Seq analysis for isolated cancer cells has been making a lot of headway lately, as this method will provide data only about genes that are expressed by mutant cells.

In recent years, scientists have begun to piece together a more comprehensive picture about how the regulation of gene expression is a significant factor for cancer cell progression. “Single-cell epigenomics is just starting, yet substantial accomplishments are emerging,” explained Xinghua Pan, M.D., Ph.D., research scientist in the department of genetics at Yale University. “Single-cell chromatin accessibility (sc-ATAC) has now been reported, and genome-wide or reduced representation bisulfite sequencing for CpG methylome analysis (scRRBS and scBS, scWGBS) are also scaled down to the single-cell level.”

Dr. Pan’s own research is breaking ground even further as he is heavily involved in understanding the role of CpG methylation in normal and diseased cells, as well as “developing new technology for the co-detection of both RNA and DNA from a single cell.” Dr. Pan believes that his novel approaches could promote new studies in cancer cell regulation, which due to their heterogeneity require multidimension sequence analysis. 

Companies are also trying to aid researchers with new single-cell platforms that combine an array of evaluation methods. For example, Fluidigm recently launched a new single-cell system called Polaris. “It is a single-cell research system that is the first to integrate cell selection, isolation, dose, culture, and molecular preparation into a single workflow, thereby enabling researchers to directly correlate gene expression with environmental conditions and phenotypic information,” explains High. “Researchers will be able to conduct dose-response and time-course studies on live, single cells to identify interesting genes that regulate critical pathways, as well as better evaluate the diversity of biological effects across cell types.”

Genetic Isolation Equals Proteomic Freedom

They say a house is only as good as the blueprints from which it was derived, but at the end of the day, one can’t live within the blueprints. Our genetic blueprint leads to the production of proteins that constitute the bulk of the contents within the cellular abode. In the end these proteins are the molecules most affected by mutations passed along through the DNA code, which in turn leads to drastic changes in the cellular residence. Thankfully, there are a number of researchers who have focused their attention toward single-cell proteomic studies of cancer cells.

Over the years there have been a number of methods established in order to identify the diverse chemistry of cellular proteins. While mass spectrometry analysis, such as LC-MS, is still the gold standard for many endeavors, the technique can require large capital equipment costs, be labor intensive, and doesn’t allow for the recovery of viable cells for downstream analysis.

With so many research institutions and biopharmaceutical companies looking to high-throughput analysis platforms to speed up and streamline their analysis efforts, single-cell proteomic scientists are working on developing new analysis techniques and equipment.

Tania Vu, Ph.D., associate professor in the department of biomedical engineering at the Oregon Health & Science University School of Medicine, is developing technology that she hopes will “allow us to assay proteomic expression in single-cell populations and pick out heterogeneity, or differences among cells, as well as handle a very small number of patient samples without loss of cells—which allows for a lot of different kinds of combinatorial drug testing.”

Dr. Vu went on to explain that “this technology can have an impact on the single-cell proteomics field by measuring the changes in proteomic content of single cells with extremely high sensitivity—superseding what is in conventional use. This is important for looking at differences in single-cell subpopulations, as such differences can point to the underlying biological mechanisms of drug resistance for example.”

Alternative methods are once again using microfluidic devices and combing them with microarray type chips to create chambers that can often fit a full panel of antibodies for detection of vast array of protein biomarkers. Additionally, some researcher groups are employing microetching techniques in order to create micro detection chambers for single-cell proteomic analysis. 

Regardless of the methodology employed it would seem that the future of single-cell omics is embracing and pushing the boundaries of miniaturization analysis. This positions single-cell approaches to provide unprecedented views into the progression of cancer cells.


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