From Gene to Protein and the Role Transcription Factors Play
Every person’s body is filled with multiple varieties of cells, each with a different structure and function. However, every cell in someone’s body has the same DNA: the genetic material that carries the “instructions” for each cell. This is due to gene regulation. In gene regulation, your body regulates which genes are expressed by controlling how often they are produced into a protein. What genes are expressed changes with each cell type.
The DNA gene is first copied onto mRNA through a process called transcription. The mRNA is then used, through a process called translation, to create a protein. The proteins then go on to perform the desired function in the cell. Most gene regulation is done during transcription because if the mRNA is never produced, then the effect the protein is supposed to create will never happen.
This is where transcription factors play in. Transcription factors control how likely RNA polymerase — the protein that copies the DNA to the mRNA in transcription — is to act on a particular gene. Each gene has a sequence called the promoter. This promoter helps proteins like RNA polymerase or transcription factors recognize the specific gene that they want to act on.
Transcription factors work by attaching to the promoter of the gene and helping or inhibiting RNA polymerase from attaching. If a cell wants to reduce production of a certain protein, it will create transcription factors that attach to the promoter and repel RNA polymerases near by from transcribing the gene. Conversely, if a cell wants to generate more of a protein, it can produce transcription factors that will attract RNA polymerases in the area so that more of the gene is transcribed and translated into a protein.
This is why the researchers focused on transcription factors. Say, if a cancer cell wasn’t producing enough proteins that regulate the cell cycle, then researchers could take a look at the transcription factors and see if there was an overactive transcription factor causing the inhibition of that protein. If there was, they could then degrade that transcription factor and allow for that protein to begin being produced again, effectively killing off the cancer cell.
(You can read my article on PROTACs if you want to learn more about a way to degrade proteins that cause cellular problems)
scFAN: The Deep Learning Network Used to Predict Transcription Factor Activity
scFAN, which stands for single-cell factor analysis network, is a deep learning network that predicts transcription factor activity across the entire human genome in individual cells. The fact that it can do this on a cell by cell basis is pretty significant, since prior to the development of scFAN, there was really no way to look at transcription factors in an individual cell; you were limited to the tissue level.
To train scFAN, researchers drew from multiple different datasets. They fed it both the variables that it would be looking for in a cell along with the results, allowing it to better predict future cell makeups. With the data, scFAN is able to report a “transcription factor activity score” that is identifies known transcription factors and how often they are used in the cell, allowing researchers to see how genes are being regulated.
By allowing us to see transcription factor activity on a single-cell level, scFAN has the possibility to give us significant insight into cells and how they regulate genes, allowing us to further work in understanding and treating diseases.
References
Campbell Biology, 11th Edition
https://advances.sciencemag.org/content/6/51/eaba9031
https://www.sciencedaily.com/releases/2021/01/210113090954.htm
