RNA bends, folds, tangles—and those shapes determine everything
At Singapore's A*STAR Genome Institute, scientists have long known that RNA molecules are not passive messengers but dynamic, shape-shifting structures whose folds determine the fate of proteins, the stability of genes, and the course of disease. The challenge has always been that conventional methods dissolve individual behavior into collective averages, obscuring the very variation that matters most. A new technology called sm-PORE-cupine now reads single RNA molecules in full, revealing how different folds from the same gene produce different biological outcomes — a development that may quietly reorder how humanity understands illness and designs its cures.
- For decades, RNA structure research has been blinded by its own methods — averaging millions of molecules together and missing the individual variations that drive disease.
- The stakes are high: RNA shape directly controls how fast proteins are made, how long molecules survive, and how viruses like SARS-CoV-2 exploit infected cells.
- sm-PORE-cupine breaks the impasse by chemically tagging exposed RNA bases and running full-length nanopore sequencing, producing a molecule-by-molecule structural portrait that was previously impossible.
- The team confirmed that RNA molecules from the same gene can fold differently and that those differences measurably alter protein production and RNA degradation rates.
- The technology is now pointing toward concrete applications — new antiviral and antifungal targets, RNA-based drug discovery, and precision therapies tailored to individual patients.
A research team at Singapore's A*STAR Genome Institute has built a tool capable of watching individual RNA molecules fold and shift — and understanding what those shapes mean for how cells actually work.
RNA is far more than a molecular messenger. It bends, folds, and tangles with other molecules, and those shapes carry enormous consequence: they govern how quickly proteins are manufactured, how long an RNA survives before being broken down, and how viruses like SARS-CoV-2 behave inside infected cells. The problem has been that most existing methods produce only a blurred average across millions of molecules, making it impossible to see that two RNA strands from the same gene might fold in entirely different ways.
The new method, sm-PORE-cupine, resolves this. Chemical compounds tag the exposed, unpaired bases of each RNA molecule, acting as structural signposts. Nanopore sequencing then reads the full length of each molecule base by base, while computational analysis assembles a precise picture of how individual RNAs fold and function. What emerged from this view was striking: structural differences between molecules from the same gene directly correlate with differences in protein production efficiency and RNA degradation rates — core mechanisms of gene regulation whose failure underlies disease.
The implications extend well beyond the laboratory bench. Scientists can now probe how RNA structure shapes viral infection, identify new targets for RNA-based drugs, and pursue antivirals, antifungals, and precision therapies with a molecular clarity that was not previously available. Published in Nature Methods, the work represents a foundational step — with the harder task ahead being the translation of this discovery into tools that clinicians and drug developers can put to practical use.
A team at Singapore's A*STAR Genome Institute has built a tool that does something scientists have struggled with for years: watching individual RNA molecules fold and shift in real time, and understanding what those shapes mean for how cells actually work.
RNA has a reputation as a messenger—the molecule that ferries instructions from DNA to the protein-making machinery. But RNA is far more than a delivery service. It bends. It folds. It tangles with other molecules. These shapes matter enormously. They determine how quickly a cell can manufacture a protein from a given instruction. They affect how long an RNA molecule survives before the cell breaks it down. They influence how viruses like SARS-CoV-2 behave inside an infected cell. Yet until now, scientists studying RNA structure have faced a fundamental problem: most methods show only an average picture, a blurred composite of thousands or millions of molecules. They cannot see that two RNA strands from the same gene might fold completely differently, each one behaving in its own way.
The new method, called sm-PORE-cupine, changes that. Researchers use chemical compounds to tag the exposed, unpaired bases of an RNA molecule—the parts that stick out rather than tucking inward. These tags act as signposts. Then nanopore sequencing reads the full length of each RNA molecule, base by base, while the chemical markers reveal structural information along the way. Advanced computational analysis stitches it all together, giving scientists a view of how individual RNA molecules actually fold and function.
What the team discovered matters. They found that RNA molecules from the same gene can adopt different structures, and that these structural differences directly correlate with how efficiently proteins get made and how quickly the RNA degrades. This is not abstract. Protein production and RNA stability are core mechanisms of gene regulation. When they malfunction, disease follows. A clearer picture of how individual RNA molecules behave opens a new window into what goes wrong in illness.
The implications ripple outward. Researchers can now study how RNA structure influences viral infection, including in coronaviruses. They can begin to identify new targets for RNA-based drugs. The technology could accelerate the discovery of antivirals and antifungal treatments, and support the development of therapies that work by targeting RNA directly. In the longer view, this kind of molecular precision could reshape how doctors diagnose disease and how drug developers design treatments tailored to individual patients.
Dr. Niranjan Nagarajan, one of the researchers leading the work, framed it this way: the team now has a unique ability to watch how RNA molecules shape-shift in real time. The research builds on years of work in nanopore sequencing at the institute. The findings were published in Nature Methods, one of the field's most selective journals. What comes next is the harder work—translating this fundamental discovery into tools that clinicians and drug makers can actually use.
Citações Notáveis
By leveraging direct RNA sequencing using nanopores, we now have a unique capability to study the dynamics of how RNAs shape-shift.— Dr. Niranjan Nagarajan, A*STAR GIS
By uncovering how RNA molecules adopt different structures and how these structures influence gene regulation, this work lays the foundation for more precise approaches to diagnosis and treatment.— Dr. Wan Yue, Executive Director, A*STAR GIS
A Conversa do Hearth Outra perspectiva sobre a história
Why does it matter that we can see individual RNA molecules now instead of just averages?
Because RNA from the same gene doesn't always fold the same way. Two cells might read the same instruction differently based on how the RNA happens to be shaped. If you only see the average, you miss those variations—and those variations are where disease often hides.
So the shape of RNA actually changes how much protein gets made?
Exactly. A tightly folded RNA might be harder for the cell's machinery to read, slowing down protein production. A loosely folded one might be more accessible, or it might get destroyed faster. The shape determines the outcome.
How does this help with viruses?
Viruses like SARS-CoV-2 use RNA too. If we understand how their RNA folds and what shapes make them more or less infectious, we can design drugs that target those specific structures. Right now we're mostly guessing.
What's the actual innovation here—the chemical tags or the sequencing?
It's the combination. The chemical tags mark where the RNA is exposed. The nanopore sequencing reads through the whole molecule while those marks are still there. Together, they give you structural information at single-molecule resolution. Neither alone would work.
How far away is this from actual medicine?
The science is solid and published. But there's still translation work ahead. We need to show this can identify real drug targets, that it works in disease models, that it's practical at scale. That's years of work, not months.