New method allows scientists to follow gene activity over time in the same cells

In recent years, scientists have built methods to measure a cell’s transcriptome, or all the RNA produced by a cell, to study the cell’s identity and genetic activity. However, these methods rely on killing the cell to access the bits of RNA within, and offer only a one-time snapshot.

Now, Broad Institute researchers have invented a “cellular self-reporting” approach to make living cells share their own transcriptomes, so that scientists can analyze them without killing the cells. Described in Cell, the live cell transcriptomic method relies on virus-like particles, which the cells use to package and deliver RNA to the culture medium they’re bathed in. Scientists can simply sample the medium to isolate the RNA, and do this repeatedly to reveal how gene activity in the same cell population changes as the cells mature or respond to perturbations. The researchers applied their method to a variety of cellular model systems, demonstrating its potential to help reveal how cells go awry over time in disease and how drugs affect cells.

“Our lab focuses our time and resources on developing tools that will actually get used and make real impact on the broader field,” said study senior author Paul Blainey, who is a core member of the Broad and a professor of biological engineering at MIT. “It's so gratifying to see a real coming to fruition of this concept, which was complete science fiction when we started. It’s a great example of the innovative impact long-term high-risk, high-reward research can have."

A cellular special delivery

The effort to build the new method began more than a decade ago, when the Blainey lab set out to find a new way to do RNA sequencing without killing cells. “The existing methods were a bit medieval and involved stabbing cells or cutting pieces off of them,” recalled Blainey. Inspired by the performance of molecular technologies such as CRISPR-based technology and their ease of adoption, Blainey and study first author Jacob Borrajo committed to developing a molecular method, which they knew would be challenging and take time, but would also make the approach scalable and easy for other labs to perform.

The team found inspiration in retroviruses, which over millions of years evolved the ability to package their RNA genomes in protein shells to spread from one infected cell to another. To build their method, the team engineered mammalian cells to express a retroviral structural protein that can encapsulate not only viral RNA but also a cell’s RNA. Integrated into the cell’s membrane, the viral protein is able to recruit cellular RNA, form a shell around it to create a virus-like particle, and bud off from the membrane to enter the liquid medium around the cell. The scientists then take a sample of the medium, isolate the RNA, and sequence it to get a view of the transcriptome from that cell population — all without destroying or damaging the cells.

“Compared to methods using robotics or mechanical biopsies of cells, our molecularly encoded solution could be much more broadly enabling for the average life science or biomedical lab, particularly the time dynamic questions that we hope to elucidate with this technology,” said co-first author Mohamad Najia, research fellow in the Blainey lab and the lab of George Daley at Boston Children’s Hospital. Najia and Borrajo led the work along with co-first author Anna Le, a postdoctoral researcher in the Blainey lab.

Message in a bottle

To test the method’s broad applicability, the researchers showed that it worked in immortalized human cells, in cancer cell lines, in stem cells and neuronal cells made from them, and in primary cells from human donors. They also tested a culture of two human cell types growing together, using tags on the virus-like particles so that the signals from the two cell types could be distinguished during analysis.

In addition, cellular self-reporting is useful for studying systems with crucial three-dimensional structures that researchers would rather not disturb. The team demonstrated their method on spheroids of human endothelial cells, capturing short-term transcriptional changes after biochemically stimulating the cells.

They also collaborated with Linda Griffith, a professor of biological and mechanical engineering at MIT, to apply their method to her lab’s organ-on-a-chip devices. These models mimic the physiology of organs and can help minimize preclinical or animal model testing, but their complexity makes retrieving cells from the devices for analysis difficult. With cellular self-reporting, the researchers monitored gene expression dynamics in endothelial cells within the devices over time, revealing changes in genes related to how tissues form vascular networks that depended upon the source of supporting fibroblasts, such as from either uterus or lung.

The Broad team is continuing to look for new applications and biological questions to ask with their system, and are working to make the approach feasible for studying single cells. For now, they hope that scientists interested in following how cells and tissues change over time will give their method a try.