New Method Reads a Cell’s Genes Without Killing It

Every few minutes, a living cell does something quietly extraordinary: it sheds tiny membrane bubbles into the fluid around it. These extracellular vesicles carry molecular cargo (proteins, lipids, fragments of RNA) and cells have been doing this for so long that biologists spent decades trying to understand what the bubbles were for. A team at the Technical University of Munich has now turned that ancient cellular habit into something useful. They have engineered a way to load those bubbles with messenger RNA on demand, collect them from the culture dish, and read out which genes are active in the cell. The cell, meanwhile, keeps living.

The trick sounds simple enough. The implications are rather less so.

Until now, reading a cell’s transcriptome (the full complement of messenger RNAs it is currently producing, which tells you which genes are switched on) meant destroying the cell to get at the contents. You lysed it, extracted the RNA, sequenced it, and that was that. The cell was gone. If you wanted to watch a stem cell transform into a heart muscle cell over the course of a week, you had to sacrifice a fresh batch of cells at each time point and hope the different batches were comparable. It was a bit like trying to understand how a caterpillar becomes a butterfly by dissecting a different caterpillar each morning.

Virus-Like Particles as Molecular Postmen

The Munich team, led by neurobiological engineer Gil Westmeyer, solved this by repurposing machinery from HIV. The virus uses a protein called Gag to bud new particles out through the cell membrane: it is how HIV replicates itself, assembling copies and pinching them off into the bloodstream. Westmeyer’s group stripped the dangerous parts out, leaving just the budding mechanism, and fused it to a fragment of a protein that naturally grips messenger RNA by its poly(A) tail, the string of adenosine nucleotides that caps the end of most mammalian transcripts. When the modified Gag assembles at the cell membrane and buds off a vesicle, it drags RNA along for the ride. The resulting particles, around 65 nanometres across and not unlike natural extracellular vesicles in appearance, accumulate in the culture medium above the cells. Researchers collect the supernatant, crack open the vesicles, and sequence what is inside.

The method, which the team calls NTVE (non-destructive transcriptomics via vesicular export), showed high concordance with conventional lysis-based RNA sequencing: a Pearson correlation of 0.95 across roughly 14,500 detected genes. Mitochondrial transcripts, which should not be accessible from inside mitochondria to a budding mechanism at the outer cell membrane, were strongly depleted in the exported fraction. That depletion mattered: it confirmed the cell’s membranes were staying intact, that the RNA was being actively packaged and exported rather than leaking out of damaged cells.

“This method provides biomedical research with a powerful new tool,” Westmeyer said. “We will gain day-by-day insights into the maturation and functionality of stem cells. This could make future cell therapies more precise and effective.”

Watching a Heart Cell Being Born

To demonstrate what that daily access actually looks like, the team differentiated human induced pluripotent stem cells into beating cardiomyocytes over nine days, sampling the transcriptome from the supernatant each morning without touching the cells below. By day six, the cells had started contracting visibly (roughly once per second, at about 1 Hz, the same resting rate as a human heart). The gene expression data told the molecular story leading up to that moment: a cascade of cardiac-specific transcripts rising in sequence, each wave activating the next, in a pattern the researchers could now observe continuously rather than reconstruct from snapshots. Standard markers previously used to identify the three embryonic germ layers, it turned out, were less informative than the time-resolved profiles suggested. NTVE flagged better candidates, genes with expression patterns that more cleanly distinguished ectoderm from mesoderm from endoderm across the full time course.

The system also works in primary neurons, which are notoriously difficult to transfect, so the team delivered the NTVE machinery via adeno-associated virus instead, then treated the neurons with a drug that activates a major signaling pathway. The exported transcriptome correctly captured the expected gene expression changes, including upregulation of Bdnf and several other CREB pathway targets, without any need to harvest the cells.

There are real limitations. NTVE cannot currently reach nuclear-localized transcripts, which include many non-coding RNAs; the RNA stays cytoplasmic before it gets packaged. Single-cell resolution is not yet possible either: the exported transcripts cannot be traced back to individual cells within a mixed population, though affinity tags on the vesicle surface can at least separate transcriptomes from two different co-cultured cell types. And the method requires introducing the Gag-based machinery into cells via lentivirus or transposon, which adds complexity, particularly in primary tissue.

Beyond Simple Monitoring

Armbrust and Truong noted that the approach opens territory beyond simple observation. “Our new method also makes it possible to genetically prepare cells for implantation into tissue,” they said. “In addition, NTVE can potentially be used for long-term analysis of organoids as well as for further research into tumors and their intercellular communication.” That last point hints at something the paper also demonstrates: the vesicle system can be run in reverse, pseudotyped with glycoproteins to fuse with specific target cells and deliver mRNA or even CRISPR editing machinery from sender to receiver cells in co-culture. The same particle that reads gene expression can, with modification, write into the genome of a neighboring cell.

Organoids are perhaps where the stakes are highest. Three-dimensional organ models grown from stem cells are inherently variable; each organoid is its own experiment, and comparing one sacrificed on day three with another sacrificed on day seven introduces noise that is very hard to control for. A method that samples the transcriptome of the same organoid repeatedly, using it as its own longitudinal baseline, could change how drug testing and disease modeling in these systems actually work. Whether NTVE scales into three-dimensional tissue with sufficient efficiency remains to be seen, but the Munich group is already thinking about integrating it with microfluidic systems that could cycle nutrients and collect vesicles continuously, closing the loop on real-time transcriptomic feedback during differentiation.

The cell, it turns out, was always willing to tell us what it was doing. We just needed to stop killing it long enough to listen.

DOI: 10.1038/s41467-026-72072-w

Frequently Asked Questions

Why did scientists have to destroy cells just to read their gene activity?

Measuring which genes a cell is actively using requires accessing its internal messenger RNA, and the standard approach involves breaking the cell open entirely, a process called lysis. Once lysed, the cell is gone, making repeated measurements on the same cell impossible. NTVE sidesteps this by coaxing the cell to export RNA-carrying vesicles into the surrounding fluid, where they can be collected without touching the cell itself.

How does repurposing HIV machinery make this work?

HIV uses a protein called Gag to bud new virus particles out through the host cell’s membrane. The Munich team stripped away the infectious components and fused the budding machinery to a fragment that grabs messenger RNA by its poly(A) tail. The result is a cellular assembly line that packages RNA into tiny membrane bubbles and pinches them off, harmlessly, into the culture medium above.

Could this method be used to track cancer cells without harming them?

That is one of the explicit goals. Because NTVE vesicles carry a snapshot of which genes are active at the moment of export, monitoring the exported transcriptomes of tumor cells over time could reveal how they respond to drugs, acquire resistance, or communicate with surrounding tissue, all without disturbing the tumor model. The researchers also note that the vesicle system can be equipped to study intercellular communication, which is particularly relevant to how cancers recruit neighboring cells to support their growth.

What is stopping NTVE from being used in whole organs or living animals?

Currently, the system requires delivering the Gag-based export machinery into cells, which adds a genetic engineering step that is more manageable in cell culture than in complex tissue. The method also cannot yet reach transcripts that stay inside the nucleus, and it cannot assign exported RNA to individual cells within a mixed population. Extending NTVE into three-dimensional organoids and eventually into ex vivo tissue is the next target, but each step adds engineering challenges around delivery efficiency and vesicle collection.

Is the gene activity data from NTVE as reliable as conventional sequencing?

Across roughly 14,500 detected genes, the exported transcriptomes showed a Pearson correlation of 0.95 with standard lysis-based RNA sequencing, a level of agreement that held across experiments using different cell types and different perturbations. Some transcripts, particularly longer ones, showed slight differences in coverage profiles, and nuclear RNA is not accessible at all. But for cytoplasmic messenger RNA, the method captures the gene expression landscape with fidelity that the researchers describe as competitive with existing approaches and, in some respects, superior to them.