Finding a solution has been hampered by the fact that there are very few markers that can predict cell division outcomes.
Subtle behaviors that characterize populations of stem cells with different fates are difficult or impossible for human observers to recognize. Cohen's tool, which runs on a standard PC, is able to track and generate predictions for up to 40 cells in real time. It outperforms the human eye in detecting differences in how the cells change over time.
Current methods of observing live cells produce terabytes of data, a volume that requires massive amounts of computation to find the most relevant information. A new computer cluster in CEAS was acquired for just this kind of research. To manage the predictive aspects of the program, Cohen used a uniquely sensitive mathematical approach based on algorithmic information theory.
Answers in DNA
Scientists know little about programming of stem cell outcomes except that it is a multifaceted process.
"In many cases, stem cells take their developmental cues from their environment," says Cohen. "Part of the programming mechanism is determined by surrounding cells. But once these cells begin to develop in a particular way, their offspring continue down that path even if the environment changes. So at some point they have been programmed to their fate."
The researchers designed the software to be used for isolating the genes and proteins that control the specialization process, which could allow researchers to identify and ultimately manipulate these programmed mechanisms.
Brian Link is a developmental biologist at the Medical College of Wisconsin who works with Cohen but is not an author on the Nature Methods paper. The two will be putting the software to the test to study behaviors of organelles within the cell as indicators of stem cell fate.
|Contact: Andrew Cohen|
University of Wisconsin - Milwaukee