Cornell researchers have discovered a new application of spatial transcriptomics, an imaging technique that analyzes and maps the gene activity in a tissue sample.
The researchers used this technique to create a detailed map of when and where genes are active during ovulation in mice. Ovulation is the process by which an egg is released from the female sex gland, the ovaries. This map will help them understand how cells communicate and interact during this crucial event.
The research, which was published in Cell Biology on Jan. 22, was conducted through a collaboration between Prof. Iwijn De Vlaminck, biomedical engineering, and Prof. Yi Athena Ren, animal science.
Ren, with a background in fertility and women’s reproductive health, approached Vlaminck at the Intercampus Immunology Symposium. The two-day event brought scientists together to discuss advances in immunology, the study of the body’s defense system.
De Vlaminck gave a talk about a 2022 study from his lab on how heart muscle cells can die of inflammation and infection. Ren was in the audience and speculated during the talk that the cell death process might play an important role in ovulation.
The two hypothesized that the spatial transcriptomics technique developed in the study could be used to study cellular communication during ovulation. After receiving a seed grant from the Cornell Center for Vertebrate Genomics, De Vlaminck and Ren began initial experiments to test this hypothesis.
The spatial transcriptomics technique was used to map cell types in the mouse ovary by capturing the timing and location of genetic activity. Transcriptomics converts RNA into a DNA copy, which then incorporates barcodes — short, standardized DNA segments — that act as molecular tags corresponding to specific locations in the ovaries.
“Every cell has a unique gene expression program, and they produce RNA from different genes,” De Vlamnick said. “Our goal was to quantify the abundance of these different RNA molecules that are derived from different genes as a function of location within the tissue.”
To accomplish this goal, DeVlamnick and Ren used multiple methods to develop multi-dimensional understanding.
“We incorporated the high-resolution technique from the lab with high-density sampling over time, which allowed us to achieve both spatial and temporal rates,” Ren said. “It was fascinating to look at things happening in both time and space.”
The samples were visualized using the barcode system. In this system, the barcode associated with the imaged RNA is computationally interpreted to find its specific location in the tissue. Ten years ago, this spatial resolution technique could image only a quarter millimeter. Now, it has evolved to now measure pixels of 10 micrometers, which is the diameter of a typical animal cell.
“We’re more recently surpassing the resolution that would be needed to map the gene expression profile, the transcriptome of individual cells, within the context of a tissue,” De Vlaminck said.
This increased level of resolution helped the researchers accomplish their goal. However, one drawback of this technique, De Vlaminck noted, is the invasive measurements that must be taken. The ovary must be removed from the mouse and sliced to collect tissue for imaging.
While the ovulatory process takes around 28 days in humans, this process occurs every four to five days in mice, allowing the researchers to capture the entire process in snapshots within a brief 12-hour time frame.
“That allowed us to create a digital representation of this very complex molecular process where different cell types that make up the ovary are communicating with one another,” De Vlaminck said.
After imaging, the transcriptomes, or the types of RNAs, of the cells were mapped, and phenotypes were collected. The phenotype is an observable trait of gene expression, which can give insight about cell function and activity.
“The processes that happen in one follicle are completely different from the processes that happened in another follicle, so you really need this type of spatial measurement in order to be able to make sense of this biology,” De Vlaminck said.
These techniques allowed the researchers to visualize which cell signaling programs enable egg cells to communicate with surrounding cells during ovulation. By identifying different cell types, the researchers seek to find new markers that are important for the stages of development.
“Having this molecular map, we can find markers that then inspire new chemical and biological approaches to inhibit certain pathways or promote certain pathways,” De Vlaminck said. “We can now start mining this to better understand what kind of therapeutics might be possible.”
De Vlamnick expresses excitement to continue exploring this area of biology. He hopes to use this technology to see the effects of aging on ovulation, the interaction between obesity and ovulation and how obesity is coupled to infertility.
“The biology of this formulation is incredibly beautiful, and it’s remarkable the complexity of the process and all that has to happen at the molecular level for this important event to succeed,” De Vlamnick said.
Ren also hopes to follow up on this research, using this large dataset to explore particular genes of interest.
“Cells change so much during ovulation, and it is fundamental how cells talk to each other and change tissue structure through remodeling,” Ren said. “I think the ovary is the perfect model to study how changes are controlled in a tissue that can be applied to all different tissues in the body.”
Brooke Greenfield can be reached at [email protected].