A software program created by an engineer at the University of Wisconsin–Milwaukee (UWM) can not only predict the types of specialized cells a stem cell will produce, but also foresee the outcome before the stem cell even divides.
The software, developed by Andrew Cohen, an assistant professor of electrical engineering, analyzes time-lapse images capturing live stem cell behaviors. It will allow scientists to search for mechanisms that control stem cell specialization, the main obstacle in advancing the use of stem cell therapy for treatment of disease. It could also lead to new research into causes of cancer, which involves cells that continuously self-renew.
Stem cells play a key role in human development, and also offer the potential to repair tissues or organs damaged by disease or injury. But, in order to use stem cell-based therapies, biologists need to better understand the mechanisms that control stem cell differentiation.
"This is a brand-new set of tools for developmental biologists," says Cohen, "and it supports an area where no other predictive solutions exist."
The research is published Feb. 7 in the journal Nature Methods. Co-authors are Michel Cayouette and Francisco Gomez neurobiologists at the Institut de recherches cliniques de Montreal, and Badri Roysam, a computer engineering professor at Rensselaer Polytechnic Institute.
The software is 87 percent accurate in determining the specific "offspring" a stem cell will ultimately produce, and 99 percent accurate in predicting when self-renewal of these stem cells will end in specialization.
A hunt for markers
As an example of the software's utility, Cohen cites using stem cells to treat the eye disease macular degeneration. The stem cells would need to produce more photoreceptor neurons for treatment to succeed. "But if you simply implant the stem cells into the retina, there are other types of cells that could develop," he says, "and that could potentially make the patient's vision worse."
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.
"The method isn't perfect," says Link. "It doesn't tell us about the influence of the behaviors. It tells us that a particular behavior is important, but it doesn't tell us how."
Still, the tool has already proven itself, he says. In a study of stem cells from the retinas of rats, Cohen's software independently confirmed the significance of at least one of the cell behaviors that Link's lab had previously identified using a gene manipulation technique
Andrew Cohen | EurekAlert!
Cnidarians remotely control bacteria
21.09.2017 | Christian-Albrechts-Universität zu Kiel
Immune cells may heal bleeding brain after strokes
21.09.2017 | NIH/National Institute of Neurological Disorders and Stroke
Our brains house extremely complex neuronal circuits, whose detailed structures are still largely unknown. This is especially true for the so-called cerebral cortex of mammals, where among other things vision, thoughts or spatial orientation are being computed. Here the rules by which nerve cells are connected to each other are only partly understood. A team of scientists around Moritz Helmstaedter at the Frankfiurt Max Planck Institute for Brain Research and Helene Schmidt (Humboldt University in Berlin) have now discovered a surprisingly precise nerve cell connectivity pattern in the part of the cerebral cortex that is responsible for orienting the individual animal or human in space.
The researchers report online in Nature (Schmidt et al., 2017. Axonal synapse sorting in medial entorhinal cortex, DOI: 10.1038/nature24005) that synapses in...
Whispering gallery mode (WGM) resonators are used to make tiny micro-lasers, sensors, switches, routers and other devices. These tiny structures rely on a...
Using ultrafast flashes of laser and x-ray radiation, scientists at the Max Planck Institute of Quantum Optics (Garching, Germany) took snapshots of the briefest electron motion inside a solid material to date. The electron motion lasted only 750 billionths of the billionth of a second before it fainted, setting a new record of human capability to capture ultrafast processes inside solids!
When x-rays shine onto solid materials or large molecules, an electron is pushed away from its original place near the nucleus of the atom, leaving a hole...
For the first time, physicists have successfully imaged spiral magnetic ordering in a multiferroic material. These materials are considered highly promising candidates for future data storage media. The researchers were able to prove their findings using unique quantum sensors that were developed at Basel University and that can analyze electromagnetic fields on the nanometer scale. The results – obtained by scientists from the University of Basel’s Department of Physics, the Swiss Nanoscience Institute, the University of Montpellier and several laboratories from University Paris-Saclay – were recently published in the journal Nature.
Multiferroics are materials that simultaneously react to electric and magnetic fields. These two properties are rarely found together, and their combined...
MBM ScienceBridge GmbH successfully negotiated a license agreement between University Medical Center Göttingen (UMG) and the biotech company Tissue Systems Holding GmbH about commercial use of a multi-well tissue plate for automated and reliable tissue engineering & drug testing.
MBM ScienceBridge GmbH successfully negotiated a license agreement between University Medical Center Göttingen (UMG) and the biotech company Tissue Systems...
19.09.2017 | Event News
12.09.2017 | Event News
06.09.2017 | Event News
21.09.2017 | Physics and Astronomy
21.09.2017 | Life Sciences
21.09.2017 | Health and Medicine