Researchers at the Broad Institute and MIT have developed a molecular method that enables scientists to follow gene activity over time within the same living cells, MIT reported. The technique, detailed in Cell, programs cells to package and export their own RNA into their growth medium, allowing researchers to sequence the material without destroying the source cells.
Standard transcriptomic tools measure all the RNA a cell produces to identify its genetic state, but conventional approaches destroy the cell to extract its contents. Those methods provide only a single snapshot of cellular behavior. The newly developed “cellular self-reporting” approach allows scientists to take repeated samples from a cell population as it matures, encounters drugs, or develops disease.
Virus-like particles
Senior author Paul Blainey and first author Jacob Borrajo began developing the molecular approach more than a decade ago to eliminate destructive extraction techniques. The team took inspiration from retroviruses, which naturally encapsulate their RNA genomes within protein shells to move between cells. To replicate that transport mechanism, the researchers engineered mammalian cells to express a retroviral structural protein capable of packaging host RNA.
Once integrated into the cell membrane, the viral protein gathers cellular RNA, wraps it in a virus-like particle, and buds outward into the surrounding liquid culture medium. Researchers then collect fluid samples, isolate the exported RNA, and sequence it without damaging the underlying culture. Co-first author Mohamad Najia noted that the molecular approach provides an accessible alternative to mechanical biopsies or robotic sampling systems for tracking dynamic changes over time.
Model testing
The research team demonstrated the method across a range of laboratory systems, including cancer cell lines, immortalized human cells, stem cells, stem-cell-derived neurons, and primary cells collected from human donors. In mixed cultures containing two human cell types, the scientists added distinct molecular tags to the virus-like particles to differentiate RNA signals from each population during sequencing.
The scientists also used the approach on three-dimensional spheroids of human endothelial cells, recording rapid shifts in transcription after applying biochemical stimulants. In a separate collaboration with MIT professor Linda Griffith, the team deployed the system inside organ-on-a-chip devices. Those microfluidic platforms mimic organ physiology but make physical cell extraction difficult. By sampling the fluid medium, the researchers monitored endothelial gene dynamics over time, revealing that vascular network formation genes responded differently depending on whether supporting fibroblasts originated from lung or uterine tissue.
Co-first author Anna Le led the research alongside Borrajo and Najia. The team is now working to refine the self-reporting platform so that scientists can apply it to individual single cells.
