Single-Cell Sequencing: The Power of One Cell
For just a moment, take a look at yourself. You are made up of anywhere from 10^12 to 10^16 cells [1]. Each one of them working together endlessly to help you breathe, read, eat, sleep, and walk. But if we take a closer look, and analyze a single cell, we find that there is a completely other story to tell. We like to think that all of our cells are the same, but that simply isn’t the case. Even within a single tissue, the cell population is heterogeneous, due in large part to the high mutation rate in DNA replication. Of course, that isn’t anything to be concerned about. Mutations occur throughout the body. On average, the human body creates 37 million mutations throughout all of its cells [4]. Some, such as silent mutations, are called silent because they have no effect on the body. Other mutations, which may not be silent, still do not necessarily pose an immediate threat. About 99% of the human genome is noncoding, which means our body has no use for it, so if there is a mutation there, it has no effect on us [2]. This is because there are several ways to code for the same protein in the body. Along with that, since most of the genome is non-coding, there is a higher chance of a mutation occurring in a section of the genetic code that humans don’t use. With that being said, the mutations and variations in the genetic code of a single cell can unlock a series of scientific answers about cell lineage and evolution.
However, with current sequencing technologies, scientists must rely on the equivalent of a sequencing average across cells. This means that large cell populations are required, and information of heterogeneity in the sample is lost. This becomes an issue in particular when analyzing rare cell groups such as cancers, tumors, or other anomalies in the body that cannot be easily replicated or cultured. Because of the need for a rapid method of sequencing cells at an individual level, researchers are currently pushing to improve single-cell sequencing methods that make the process cheaper and more efficient. However, there were two major issues that scientists have run into. The first is dealing with single-cell transcriptomics, which is the study of all coding and noncoding RNA in a cell. This field of study is critical for understanding a cell, but the current popular process requires a large quantity of starting RNA which can be difficult when dealing with a rare cell which cannot be replicated to meet that requirement. The second issue that must be addressed is the number of cells that can be sequenced. Current techniques do not efficiently sequence a high percentage of the cells or microbes in a sample. Most techniques can sample 1-10% of a cell population in a sample. While this is great, it leaves out 90-99% of the data that can be acquired from the sample, which is very valuable when one sample is all that is available. Addressing this issue allows researchers to take advantage of their sample and gather as much sequencing data as possible.
Researchers have attempted to resolve both issues. One paper showed a potential solution by changing how the cells are lysed and the resulting genome fragments are recovered by the sequencing tools. The change in protocol resulted in improved full-length coverage of transcripts longer than 1kb [2]. This may not seem like much, but with a larger read coverage, there is a greater understanding of the full genome in the sequence. This gives researchers a better understanding of what proteins are and are not created by an organism. A paper published by Lan Freeman shows that by using microfluidic processing, more cells could be sequenced. The results demonstrated that the improved method had better read coverage of the fragments, that it was sensitive enough to detect bacteriophage sequences, and could sequence over 50,000 cells in a single pass [3].
Both approaches have paved the way to allow for an expansion in advanced research into rare cells. Using single-cell sequencing can be leveraged to study cell lineage, heterogeneity, and development of organs and tissue. This is critical for understanding origins of diseases, cancers, and tumors. Scientists could better develop medicines to help combat these issues. Single-cell sequencing can also allow for exploring unique characteristics such as potentially characterizing microbial dark matter. These microbes aren’t from space or actually made of dark matter. They are simply microbes that cannot be cultured in labs because scientists are not sure how to. Due to the limited supply, single-cell sequencing has become an attractive method for sequencing these rare organisms. The possibilities for single-cell sequencing are endless, and each new innovation makes the process cheaper and faster. As the demand for the technology increases, new innovations will pave the way for future applications.
Works Cited:
What is Zinc Finger Nuclease (ZFN) Technology? (n.d.). Retrieved September 23, 2020, from,https://www.sigmaaldrich.com/life-science/zinc-finger-nuclease-technology/learning-center/what-is-zfn.html
Ramsköld, D., Luo, S., Wang, Y., Li, R., Deng, Q., Faridani, O. R., . . . Sandberg, R. (2012). Full-length mRNA-Seq from single-cell levels of RNA and individual circulating tumor cells. Nature Biotechnology, 30(8), 777-782. doi:10.1038/nbt.2282
Lan, F., Demaree, B., Ahmed, N. et al. Single-cell genome sequencing at ultra-high-throughput with microfluidic droplet barcoding. Nat Biotechnol 35, 640–646 (2017). https://doi.org/10.1038/nbt.3880
Zhang, S. (2018, May 07). Your Body Acquires Trillions of New Mutations Every Day. Retrieved September 29, 2020, from https://www.theatlantic.com/science/archive/2018/05/your-body-acquires-trillions-of-new-mutations-every-day/559472/
Edited by Sean Francis
