Jan. 9, 2017
- ISB researchers developed a new theory that uses state-of-the-art single-cell technology to make predictions about how cells will behave in the future.
- The method can predict when a cell will experience a so-called tipping point before it happens.
- Being able to predict these critical transitions in cells may have life-saving ramifications in the ability to detect early warning signals for disease.
By Dr. Sui Huang
Stem cells hold enormous potential for cell-based therapy in regenerative medicine, if we can use drugs in the lab to push the patient’s own stem cells to become desired cell types, such as blood, liver, or heart cells. So far, our successes in controlling the generation of specific cell types have been empirical. Researchers have painstakingly mapped out many of the genes involved in the cell-fate-decision processes. But we still have little clue about the fundamental principles that govern how a multipotent stem cell, which has the potential to become more than one type of cell, makes a decision to become a specific cell type. We have not had a formal theory for such cell-fate decisions – until now.
In a study published in PLOS BIOLOGY, researchers at Institute for Systems Biology (ISB) explain how they developed a new theory for predicting cell-fate decisions and demonstrate, for the first time, that cells indeed undergo a critical transition – or tipping point – when they commit to a particular lineage. The team designed a new computational approach that utilizes single-cell resolution gene-expression profiling data to compute an index that indicates an imminent tipping point in cells before it happens.
Imagine having a list describing what each of the myriad buttons in the cockpit of a plane does, but not knowing the physics of flight or the mechanics of the jet engine. According to Darwin, if biology is not guided by a theory, “one may as well go into a gravel pit and count the pebbles and describe their colors.” In fact, Francois Jacob and Jacques Monod (who shared the 1965 Nobel Prize in Medicine with Andre Lwoff for their discovery of gene regulation) had proposed an elementary mathematical model derived from the theory of nonlinear dynamics. But, the advancement of gene sequencing technology tempted molecular biologists to count the pebbles, so to speak, and focus on mapping individual genes. While the insights have been valuable, the lack of a unifying theory meant there was no understanding of the dynamics of how those cells became those cells.
The research team, led by ISB Professor Dr. Sui Huang (and including then graduate student Mitra Mojtahedi, physicist Alex Skupin, and computational biologist Joseph Zhou), used state-of-the-art single-cell technology to monitor how a blood progenitor cell commits to becoming either a red blood cell or a white blood cell, which resulted in the observation that a stem cell’s decision to become a particular cell type represents a so called critical-state transition or a “tipping point.” We may recognize this concept of tipping points as sudden qualitative changes in societies (revolutions), economies (recessions), ecosystems (collapse), and even mental states (depression). Going through a tipping point is a process that allows a complex system of zillions of interconnected parts, including the previous examples as well as the cell populations in human tissue, to switch its global state quite abruptly, yet in orderly fashion. Until the arrival of new technologies for single-cell resolution molecular profiling of thousands of individual cells, we lacked the capability to understand how individual multipotent cells make decisions during a cell fate transition, thus blurring our grasp of the underlying mechanisms.
Intriguingly, the team also observed that using drugs to steer a cell population left or right toward becoming red or white blood cells is not like turning the steering wheel of a car. The reason, according to the team’s theory, is that, before the tipping point, the cells first destabilize their current internal state. They begin to vacillate like an indecisive person choosing between two options. This cell destabilization opens the path for some cells to switch to the exact opposite direction as intended by the drug treatment: Trying to produce red blood cells inevitably produced some white blood cells as a by-product and vice versa. Thus, steering undecided stem cells to a particular type may be more like herding cats, not sheep. This would explain the notorious inefficiency of cell-type reprogramming. Huang’s theory predicts precisely such “rebellious behaviors” in cells, which may play a role in how some cancer cells are able to resist anti-cancer drugs and, instead, become rejuvenated and more aggressive – a possible reason for cancer recurrence.
The broader significance of the new results is the ability to use single-cell analysis along with an algorithm to predict imminent tipping points in a cell population by detecting “early warning signals,” such as vacillation, before the major state change occurs. The team is now exploring new applications of tipping points in biology and medicine. This could change the way we predict health-to-disease transitions from the current probabilistic approach of finding a statistical correlation between a biomarker and the disease outcome (like predicting election results by polling) to a new theory-based approach that predicts transitions based on the trajectory of molecular profiles approaching a tipping point (like predicting a solar eclipse based on planetary motion). It is clear which one is more accurate.
Title: “Cell Fate Decision as High-Dimensional Critical State Transition”
Journal: PLOS BIOLOGY
Authors: Mitra Mojtahedi, Alexander Skupin, Joseph Zhou, Ivan G. Castano, Rebecca Y. Y. Leong-Quong, Hannah Chang, Kalliopi Trachana, Alessandro Giuliani, Sui Huang