KAIST researchers develop NUDGE technology to steer cell fate

Which genes need to be controlled to guide a stem cell toward a desired cell type, or to modulate an immune cell's inflammatory response? A Korean research team has developed a general-purpose computational framework that identifies the key targets needed to steer a cell toward a desired state with a single temporary intervention, without permanently altering its genes.

KAIST (President Choongsik Bae) announced on September 23 that a research team led by Professor Kwang-Hyun Cho from the Department of Bio and Brain Engineering has developed NUDGE, a foundational technology that redirects cell fate in a desired direction through a minimal, temporary intervention by harnessing the gene regulatory dynamics already present within cells.

Technologies that redirect cell fate have drawn attention as key tools for treating intractable diseases and advancing regenerative medicine, since they can be used to differentiate stem cells into cells with specific functions or to return diseased or aged cells to a near-normal state. Differentiation, for example, refers to the process by which a stem cell becomes a specific cell type with a distinct function, such as a cardiomyocyte or a neuron.

However, existing methods for controlling cell fate have relied mainly on permanent intervention like keeping specific genes locked in an "on" or "off" state. While this approach can produce the desired cell state, it has a limitation. It can reduce plasticity, the flexibility that allows cells to adapt to future changes in their environment, and it can also give rise to abnormal cell states that do not exist in nature.

Rather than forcing a cell into a fixed state, the research team devised a new strategy that lets the cell reach the desired state on its own through a single temporary stimulus. The approach nudges the gene regulatory dynamics already present inside the cell toward the target direction, much like briefly clearing a blocked channel and letting the water find its own course.

NUDGE (natural dynamics control of gene regulatory networks), the technology the team developed, uses a computational logic model to examine how key genes inside a cell influence one another and to determine which state the cell ultimately reaches as a result. It then mathematically decomposes the logical functions that describe these gene interactions to identify the minimal combination of control factors needed to convert a cell from its current state to the desired one.

For example, if the goal is to differentiate a stem cell into a cardiomyocyte, NUDGE functions as a "blueprint for minimal intervention" that identifies which molecular targets need to be temporarily activated or inhibited.

A key strength of the framework is that its exact method is mathematically guaranteed to identify all minimal control combinations that lead to the desired phenotype within the model. The team also presented an efficient approximation method that extends the framework to large-scale molecular networks.

NUDGE does more than identify which factors to stimulate. It can also analyze which pathways a stimulated cell follows to reach the target state and how stably that state is maintained once reached, making it possible to anticipate whether unexpected states might emerge during the transition.

The researchers assessed permanent control in 63 published biological network models where fixing a single node was sufficient to achieve the target phenotype; 55 showed reduced plasticity or attractors absent from the uncontrolled network. Separately, NUDGE's approximation achieved an average intervention error below 0.01 in more than 90 percent of 552 control problems across 69 large biological networks. Error measured the fraction of simulated converged states with the undesired phenotype. Of the minimum-sized, error-free interventions pooled from the three methods for each problem, NUDGE found an average of 83 percent, compared with 59 percent for IBMFA and 53 percent for LDOI.

To assess how well NUDGE explains real biological phenomena, the researchers applied it to three distinct processes: cardiomyocyte differentiation, fate determination in mast cells involved in allergic responses, and the conversion of macrophages, a type of immune cell, into an anti-inflammatory state.

In cardiomyocyte differentiation, the framework reproduced the known pattern in which MESP1, a gene important for heart development and regeneration, is briefly active early in differentiation but inactive in mature cardiomyocytes. The model shows how a single temporary intervention involving MESP1 and another regulatory target can guide differentiation without keeping MESP1 continuously active.

The team also identified GATA2 and GATA1 as key regulators of cell fate during mast cell formation. In the macrophage model, the team derived optimal strategies for a single temporary intervention, including one using IL-4, to induce anti-inflammatory M2 states while preserving the capacity to transition between inflammatory and anti-inflammatory phenotypes and among M2 subtypes.

The significance of this technology lies in providing a general-purpose framework that identifies where a single temporary intervention can guide a cell to a desired state, provided that a stable state with the desired phenotype exists in the network's uncontrolled dynamics. It is expected to find broad application, from guiding normal stem cells to differentiate into specific cell types such as cardiomyocytes, to normalizing diseased or aged cells, regenerating damaged tissue, modulating immune responses, and designing cancer reversion therapies that return cancer cells to a near-normal state.

NUDGE is not a technology limited to returning a specific cell to a healthy state, but a general-purpose cell-control technology that guides a cell from its current state to a desired state through a single minimal stimulus."

Professor Kwang-Hyun Cho, Department of Bio and Brain Engineering, KAIST

He added that the technology is expected to serve as a foundational tool for designing new control strategies across stem cell differentiation, aging, autoimmune disease, regenerative medicine, and cancer reversion therapy.

The study was conducted by Ferio Brahmana, who holds a master's degree, and Corbin Hopper, a PhD student, both in KAIST's Department of Bio and Brain Engineering, who contributed equally as co-first authors, with PhD student Woojeong Lee as a co-author. The findings were published online on September 14 in the Proceedings of the National Academy of Sciences of the United States of America (PNAS).