Patterns in transcription factor binding help predict whether undifferentiated cells (center) become neurons (left) or muscle cells (right). Image credit: Sevi Durdu/FMI
August 8, 2025
Decoding how cells choose to become muscles or neurons
FMI researchers have uncovered new clues about how cells decide what type of cell to become — whether muscle, neurons, or something else entirely. By studying proteins called transcription factors, they identified patterns that predict where these proteins bind on DNA and how they influence a cell’s fate. The findings could help scientists better understand development and disease.
Every cell in the body has the same DNA, but different cell types — such as muscle or brain cells — use different parts of it. Transcription factors help cells activate specific genes by reading certain DNA sequences, but since these sequences are common across the genome, scientists have long wondered how the factors know exactly where to bind.
Researchers in the Schübeler lab set out to address this question by looking at two closely related transcription factors — NGN2 and MyoD1 — that steer cells toward becoming neurons and muscle cells, respectively. Using stem cells, they switched these transcription factors on one at a time and watched where they attached to the DNA and how they influenced gene expression.
They found that the binding of transcription factors to the DNA molecule depends not only on the DNA sequence but also on how open the DNA is and which partner proteins are present. Sometimes, transcription factors act as “pioneer factors” and are able to open tightly packed DNA at specific sites to turn on genes. Small DNA changes — sometimes just one letter — and the proteins these factors partner with can affect whether genes are activated.
Next, the team trained a machine learning model to recognize patterns in transcription factor binding. Using this model, they identified a “DNA language” that predicts where and how these factors bind. The model accurately predicted outcomes across different cell types, helping explain how similar transcription factors can guide distinct developmental trajectories.
The findings not only deepen our understanding of how transcription factors drive cell fates, but they also offer powerful tools to predict and possibly steer these decisions in development and disease, the authors say.
Original publication
Sevi Durdu, Murat Iskar, Luke Isbel, Leslie Hoerner, Christiane Wirbelauer, Lukas Burger, Daniel Hess, Vytautas Iesmantavicius, and Dirk Schübeler Chromatin-dependent motif syntax defines differentiation trajectories Molecular Cell (2025) Advance online publication
Patterns in transcription factor binding help predict whether undifferentiated cells (center) become neurons (left) or muscle cells (right). Image credit: Sevi Durdu/FMI
About the first author:
Sevi Durdu grew up in Izmir, Turkey, and studied Molecular Biology and Genetics at Bilkent University in Ankara. She completed her PhD in biology at EMBL Heidelberg before joining the Schübeler lab in 2020, where she investigates how transcription factors drive cell differentiation. Sevi is passionate about mentoring, science communication, and equity in science — and she can survive solo on a Mediterranean shoreline, fishing, foraging, and chatting with octopuses.
