Five Exciting Cell and Molecular Biology Discoveries from 2019
By Lori King PhD, Content Writer, Sartorius
Lori King takes a look back at innovations which resonate with herself. These techniques may herald new eras in Cell and Molecular Biology, with the ultimate aim of producing new treatments for existing diseases, and perhaps also opening new frontiers in the Biosciences.
Hachimoji DNA
Hoshika et al. reported in Science in February that they had engineered DNA molecules with four synthetic nucleotides, P, Z, B, and S, added to the natural four, adenine, guanine, thymine, and cytosine. They named these synthetic DNA molecules Hachimoji DNA; hachimoji is Japanese for “eight letters.” Hoshika et al. were able to transcribe the Hachimoji DNA into Hachimoji RNA by adding an engineered T7 polymerase.
Hoshika et al. performed the research with funding from NASA with the goal of expanding what may be found in the search for extraterrestrial life; however, the applications for synthetic DNA could be innumerable, including such things as new diagnostics for human diseases, DNA-based digital data storage, DNA-based barcoding, and self-assembling nanostructures.
Prime Editing DNA with a new CRISPR Variant
CRISPR-based DNA editing has been much in the news lately, including the highly controversial human DNA-editing experiments by Jiankui He in late 2018. In just a short time, CRISPR has become even more precise and efficient. Anzalone et al. reported in Nature in October that they had created a new version of CRISPR that can perform what they call “prime editing.”
Researchers can use prime editing to insert new genetic sequences into the human genome using RNA. Anzalone et al. used prime editing to perform more than 175 edits in human cells, including correcting the point mutation that causes sickle-cell anemia, as well as removing codes for four nucleotides that are associated with Tay Sachs disease. The authors believe that prime editing substantially expands the scope and capabilities of genome editing, and could correct up to 89% of known genetic variants associated with human diseases.
Dual Expressing Immune Cells?
Ahmed et al. reported in Cell in May that they discovered cells in type 1 diabetes patients that expressed both B cell receptors (BCRs) and T cell receptors (TCRs). In these patients, most of these dual expressing immune cells express a peptide that encodes a CD4 T cell autoantigen in its antigen binding site. Using simulations, researchers found that this peptide has an optimal binding register for HLA-DQ8, a serotype implicated in the development of autoimmune conditions, especially diabetes and celiac disease.
Potential areas for continued research are showing a direct connection between these new dual expressing immune cells and insulin, identifying where and when these cells develop in the body, and identifying this new cell type in patients with other autoimmune conditions.
Using Deep Learning Algorithms in Microscopy
The use of deep learning algorithms is a new technological innovation that has generated some excitement in cell biology and other fields. In November, Nature Methods compiled a list of 33 articles, correspondences, and commentary going back to 2017, that they have published on the use of deep learning in microscopy.
As just one example, according to this article in The Scientist, researchers have used deep learning to identify cellular components in a living cell from images taken using brightfield microscopy.
Brightfield microscopy has some advantages over fluorescent microscopy, for instance it is cheaper and avoids cellular phototoxicity. However, because the images appear in shades of gray, it makes internal cellular structures difficult to decipher. Using a computer algorithm, researchers were able mimic the way fluorescent images can detect cellular structures using brightfield images.
This article in Nature Methods outlines some exciting ways you can use deep learning in your cellular imaging analysis.
Label-free 3D Cellular Mapping
Sandoz et al. reported in December in PLoS Biology on their technique of using holo-tomographic microscopy (HTM) as a method for label-free microscopy with high spatial and temporal resolution. This technique also uses low-intensity light, so that the cells remain unperturbed during imaging. These researchers used HTM to study how multiple organelles spin inside cells, but note how the use of computer-based advanced image analysis may involve strategies “that can be broadly used to quantify HTM images.”