CRISPR and Stem Cells — Changing Cellular Identity and Saving Lives

According to the United Network for Organ Sharing, every ten minutes, there is someone added to the donor list. At the same time, on average, 20 die waiting for an organ each day. In 2016 alone, more than 7,000 patients died while on the wait list…

If there is something worse than dying, it is waiting to see whether or not you’re are actually going to die. And you never know.

Something has to happen. Fortunately, it did. Ten years ago, Takahashi and Yamanaka from Kyoto University, Japan, successfully transformed somatic cells to induced pluripotent stem cells — a type of cell that is similar to that extracted from our embryo. In other words, they can take any cell from your body that is not reproductive and turn it to an embryonic-like cell that can divide indefinitely, proliferate, and differentiate into a target cell type, such as blood cells or neurons.

These cardiomyocytes were reprogrammed from normal adult human skin samples. Credit: Matt Spindler/Gladstone Institutes

Let’s dig in and understand how this really works!

Cellular Reprogramming: “The Yamanaka Experiment”

The idea was simple: a small set of transcription factors (TFs), when expressed in a somatic cell, can reprogram it back into a pluripotent state. You can think of TFs as an instructor that tells the cells what to do. If the cells receive the right instructions, it will move in the right direction. After some analysis, Yamanaka’s team took 24 candidate genes, selected mostly for their high expression and specificity in pluripotent cells. They then integrated retroviruses, carrying the genes, into adult somatic cells (for example, skin cell) to express them. After a period of incubation, they introduce marker gene that is only activated in pluripotent cells.

They continued the process to narrow down the cocktail of genes to four reprogramming factors: Klf4, Sox2, Oct4, and Myc, a.k.a. KSOM.

In short, they proved that by introducing these four factors into any somatic cells, the cells will go pluripotent, having the ability to differentiate into different cell types and form tissues.

In real life, adults arguably dominate the world. But in the cellular worlds, even “adults” are forced to become “babies” to have the superpower to be immortal, to keep dividing, and to “remake” their life by becoming the cell type we aspire them to be.

These iPSC-derived neurons were generated from tissue taken from human patients with Huntington’s Disease. The hope for the future is that abnormal cells from patients with inherited diseases such as Huntington’s could be reprogrammed to the pluripotent stem cell state, “edited” using CRISPR and then transplanted into patients to restore normal function. Credit: Julia Kaye/Gladstone Institutes

Far beyond iPSC-based cell replacement therapies

In basic science, the ability to derive iPSCs from patients’ cells had a huge impact on human disease modeling. For decades, we have modeled genetic diseases and conducted drug testing or gene therapy experiments on animals, such as mice or zebrafish.

Now, iPSC technology allows us to investigate familial genetic diseases in a context of patient-derived neurons and tissue.

Pictured is a microscopic view of brain cells generated from induced pluripotent stem cells in the laboratory of University of Wisconsin-Madison neuroscientist Su-Chun Zhang. The induced cells, derived from reprogrammed skin cells, seem to have many of the all-purpose qualities of human embryonic stem cells.

The advent of iPSCs also broke the ‘cancer cell line monopoly’. Previously, cancer cells were the only reliable source for human immortal cells. Like cancers, iPSCs are immortal, but they don’t suffer from the disadvantages of the pathologically altered genomes of cancer cells, yet still retain their capacity to differentiate into any cell type of interest. In the realm of academia, Allen Institute for Cell Science has launched an industrial-scale library of characterized iPSCs that will be used to create a visual, animated model of the cell, suggesting that iPSCs will soon replace cancer cells as a model system for basic cell biology.

iPSC is awesome, but it’s not perfect… yet

One challenge is no individual iPSC lines are identical, and we’re not sure how these variabilities affect a line’s potential to differentiate into function cells.

Some differences are simply Single nucleotide polymorphisms (SNP). Each SNP represents a difference in a single DNA building block, called a nucleotide. For example, a SNP may replace the nucleotide cytosine (C) with the nucleotide thymine (T) in a certain stretch of DNA. There are millions of SNPs within a human genome, and they vary between people. While most of SNPs are known to be non-coding or regulatory, they generate data noise when we try to identify meaningful genetic differences to come up a safe, effective clinical application.

Illustration of Single nucleotide polymorphisms (SNP) from DNA Encyclopedia

The data interpretation situation is exacerbated with sporadic, polygenic diseases. While some diseases, like Fragile Syndrome X, are caused by the mutation on a single allele (a.k.a monoallelic), others are caused by multiple genetic risk factors, as outlined in the Genome Wide Association Studies (GWAS) — a genome-wide association studies between different individuals to see if there is a common variant that leads to a common trait. These are known as polygenic diseases (poly- means many). It has been shown that the environment also affect these multiple risk factors.

FMR1 transcription is silenced due to DNA hypermethylation, and the absence of FMRP results in fragile X syndrome. (Retrieved from “Mouse models of the fragile X premutation and fragile X-associated tremor/ataxia syndrome” in Journal of Neurodevelopmental Disorders (6)1:25)
Our priority to sort these data to discriminate confounding technical/ methodological variations from meaningful biological ones.

On our quest to understand iPSC lines’ potential to differentiate, it is important to understand what drives cellular differentiation to begin with.

Think of the interactions in our cell as a puppet show. There are people behind in, controlling how the process turns out, giving rise to different “characters” (a.k.a our cells) with unique identity.

DNA methylation is a process in which methyl (CH3-) groups are added to the DNA molecule. When located in a gene promoter, DNA methylation typically acts to repress gene transcription. (Image from Wikipedia)
Possible methylation and demethylation pathways (Image from Wikipedia)

After some investigation, scientists have found that the main controller is regulators of DNA methylation and histone modification. Thus, the number of differentially methylated regions (DMR) would be an important factor in understanding differentiation capacity of cell. Basically, you just gotta figure out how many DMRs that puppet controller have on the list, and how many there is within each cell.

It is also interesting to see if is any secret agent behind this puppet controller to inform him what to do. The answer is a resounding yes — it’s sex factor! During cell reprogramming, female-derived somatic cells must overcome an additional barrier compared to male-derived cells, which is the reactivation of the inactive X chromosome. Moreover, it is known that there are more X chromosome-localized DMRs in the female iPSCs than in males. Indeed, sex is a major contributing factor to explain differential methylation patterns among iPSC lines! Another factor is age, so it’s important to stratify the different iPSC cell lines by different age groups.

Let’s recap what we have known about t iPSC differentiation potential so far:

DMRs → Differentiate cell types. But, the ‘SNP and polygenic diseases’ problem is unsolved → Need to sort data to know the effects of each risk factor on the expression of a certain trait.

Okay, cool. Moving on. We’re almost there!

CRISPR-Cas: Stepping in to Up the iPSC Game

(Before you continue reading, you can watch this video here or read my previous article here to understand how CRISPR works.)

To study the effects of different risk factors on the expression of a diseases, we need to do two things:

  1. Establish a control group and a test group
  2. Knock out each risk factor gene one by one to see if there is any loss of function

In fancier terms (knowing them may help you understand future papers), the two steps are involved in establishing an isogenic cell line. Isogenic cell lines are created via a process called homologous gene-targeting. Essentially, this means that we can use tool like CRISPR to knock-in or knock-out the desired disease-causing mutation or SNPs.

Wild-type human epithelial cells are subjected to gene targeting to create isogenic derivatives that contain a single PIK3CA oncogenic mutation (knock-in) or the same PIK3CA mutation along with a KRAS oncogenic mutation (double knock-in). Cells are then subjected to drugs in parallel to assess resistance sensitivity (J Clin Invest. 2010;120(8):2655–2658. doi:10.1172/JCI44026.)

Recent studies have shown success in such method, as in the case of deciphering the impact of Parkinson-associated risk variants. After introducing a common PD-associated risk variant in a non-coding enhancer region, SNCA gene was deregulated by 10%. As SNCA is responsible for producing alpha-synuclein — a protein at presynaptic transmitters in the brain, where neurotransmitters are released. The lack of SNCA can severely impair normal brain activity. This is only one example of using CRISPR to establish isogenic cell lines to eliminate SNP (“data noises”) and study individual (or a combination) or different risk factors in polygenic diseases.

However, the impact of CRISPR in iPSC models are beyond the fast and efficient gene editing. As we have known, a catalytically active Cas protein have two domains — RuVC like and HNH — both of them act as a scissor to induce double-stranded breaks (DSB) at our desired genomic loci.

Mutating both of these domains will make them lose their “cutting” feature and become a deactivated Cas protein (dCas).

You may ask yourself: Why on earth would we turn off the editing function of a gene editing tool like CRISPR? The answer is: to fuse dCas9 with other functional proteins to activate or repress gene activity at a target site.

  • When dCas9 is fused to Kruppel associated box (KRAB), a transcriptional repressor domain, transcription is repressed and the system is referred to as CRISPR interference (CRISPRi).
  • When dCas9 is fused to the SunTag, a sequence containing multiple copies of the activator recruitment domain of general control protein (GCN4), the system activates transcription and is referred to as CRISPR activation (CRISPRa).

The activation and repression of certain genes can help us study the function of those genes. Further, the fusion between dCas and fluorescent reporter allow us to visualize nuclear organization and specific genomic sites.

… So what do we need to know?

  • We need a replacement for organs in donation, and induced pluripotent stem cells (iPSC) is a promising solution. It has the potential for both replacement therapies and serve as a game-changing model for studying diseases.
  • CRISPR helps establish isogenic cell lines to study the impact of multiple risk factors in polygenic diseases, mainly by generating knock-outs. It also eliminate data noises by turning off single nucleotide polymorphisms (SNP). It gives testing cells a kind of uniformity, so we can find the most effective, reliable iPSC for clinical application.
  • dCas9 activate and repress genes, allowing us to studying their functions. This can be used in genome-wide screenings, one popular type of which is loss-of-function screening.

Undoubtedly, the marriage between the iPSC and CRISPR are game-changers at the forefront of regenerative medicine, moving a step closer to practical clinical applications!

My Personal Note and Further Reading

The progress made in stem cells and CRISPR to me is just mind-blowing. The collective efforts of scientists throughout their seven years studying iPSC — something that they didn’t even know would work at the time — and their potential applications are seriously admirable. Simply by reading these papers, they teach me not only the knowledge, but the attitude to scientific research — patience, optimism, and persistence.

If you are as excited as I am and love envisioning the future of regenerative medicine, I’d recommend the following readings:

Enjoy and stay tuned for my future articles!