Summary: A new research suggests that individual cells may reflect learning-like activities, formerly thought unique to animals with nervous techniques. Researchers mimicked habituation, a straightforward method of learning, by using mathematical modelling to demonstrate how metabolic circuits in cells adjust to repeated stimuli. Two chemical circuits, negative comments loops and incomprehensible feedforward loops, were identified as important mechanisms.
This finding ties together the topics of cognition in biology and cognitive science while providing insight into issues like tumor cell resistance to chemotherapy. The findings emphasize the utility of solitary cells as basic learning and memory models. The research serves as the foundation for potential theoretical validation experiments.
Important Information:
- Cells exhibit “learning” behaviors through chemical wires mimicking desensitization.
- Timescale separating in chemical reactions allows cells to adjust and “remember” stimulation.
- These results might help to explain how cells adapt to circumstances like antimicrobial or chemoresistance.
Origin: Center for Genomic Regulation
According to the findings of a new study led by researchers at the Center for Genomic Regulation ( CRG ) in Barcelona and Harvard Medical School in Boston, individual cells now appear to be capable of learning, a trait that was once thought to be exclusive to animals with brains and complex nervous systems.  ,  ,  ,
The findings, published today in the journal , Present Biology, may represent an important change in how we view the essential modules of living.  ,  ,
” More than following pre-programmed biological guidelines, cells are raised to companies equipped with a very simple type of decision making based on learning from their surroundings”, says Jeremy Gunawardena, Associate Professor of Systems Biology at Harvard Medical School, and co-author of the study.  ,
The study focused on habituation, a process that occurs when an organism stops responding to repeated stimuli over time. Why do people stop noticing a clock’s ticking or become less distracted by flashing lights? Animals with complex nervous systems have been subjected to extensive research on this lowest form of learning.  ,
Whether learning-like behaviours like habituation exist at cellular scale is a question that’s remained fraught with controversy.
Early 20th-century studies of the single-celled ciliate Stentor roeselii first revealed behavior that resembled learning, but the studies were later dismissed and forgotten. Other ciliates showed signs of habituation in the 1970s and 1980s, and contemporary experiments have continued to give the theory more weight.  ,
” These things are so different from brain-having people. They would use internal molecular networks, which carry out tasks similar to those of brain neuronal networks, to learn. Nobody knows how they are able to do this, so we thought it is a question that needed to be explored”, says Rosa Martinez, co-author of the study and researcher at the Centre for Genomic Regulation ( CRG ) in Barcelona.  ,
Biochemical reactions are used to process information in cells. For instance, a protein can turn on or off when a phosphate tag is added or removed from its surface.
Instead of working with cells in lab dishes, the researchers used computer simulations based on mathematical equations to track these reactions and decode the cell’s “language” to understand how information is processed.
When exposed to the same stimulus over and over again, this enabled them to observe how the molecular interactions inside cells changed.  ,
Negative feedback loops and incoherent feedforward loops are two common molecular circuits, specifically. In negative feedback, the output of a process inhibits its own production, like a thermostat shutting off a heater when a room reaches a certain temperature.
In incoherent feedforward loops, a signal simultaneously activates both a process and its inhibitor, like a motion-activated light with a timer. After detecting movement, the light automatically shuts off after a set period of time.  ,
The simulations suggest that cells can reproduce all the hallmark characteristics of habituation found in more complex forms of life by combining at least two of these molecular circuits to fine tune their response to a stimulus.
One of the most important discoveries is that some reactions take place much more quickly than others in terms of “timescale separation” in the molecular circuits ‘ behavior.  ,  ,
” We think this could be a type of’ memory’ at the cellular level, enabling cells to both react immediately and influence a future response” explains Dr. Martinez.  ,  ,
The finding may also help to reshape a tense discussion between cognitive and neuroscientific researchers. These two groups have had different opinions for years about how frequency or intensity of stimulation affect habituation strength. Organisms exhibit stronger habituation when they are exposed to more or less intense stimuli, according to neuroscientists, who emphasize observable behavior.  ,  ,
However, cognitive scientists insist on establishing internal variations and memory formation following habituation. When following their methodology, habituation seems stronger for less frequent or more intense stimuli.  ,
The models ‘ behavior corresponds to both viewpoints, according to the study. During habituation, the response decreases more with more frequent or less intense stimuli, but after habituation, the response to a common stimulus is also stronger in these cases.  ,  ,
” Neuroscientists and cognitive scientists have been studying processes that are essentially two sides of the same coin,” says Gunawardena. We think that single cells could become a useful resource for learning the fundamentals.
The study expands our understanding of how memory and learning function at the most fundamental level of existence. If individual cells can “remember,” it might also aid in understanding how cancer cells become resistant to antibiotics or how bacteria become resistant to chemotherapy, both of which are examples of situations where cells appear to “learn” from their surroundings.  ,
However, the predictions need to be confirmed with real-world biological data. Because it was possible to quickly test a number of different scenarios to determine which ones were worthwhile looking into further in real experiments, the study used mathematical modeling to explore the idea of learning in cells.  ,  ,
The research could provide the foundation for future lab experiments and prediction testing by experimental scientists.  ,
The Barcelona Collaboratorium, a joint initiative between the CRG and EMBL Barcelona designed to advance research based on mathematical modeling to address important questions in biology, is the “moonshot in computational biology” to make life as programmable as a computer. However, lab experiments can be expensive and time-consuming, according to Dr. Martinez, who is based there.
Our method can help us identify the experiments that are most likely to save time and resources, leading to new discoveries, and prioritizing. ” We think it can be useful to address many other fundamental questions” . ,
About this news about neuroscience and genetics
Author: Omar Jamshed
Source: Center for Genomic Regulation
Contact: Omar Jamshed – Center for Genomic Regulation
Image: The image is credited to Neuroscience News
Original Research: Open access.
” Biochemically plausible models of habituation for single-cell learning” by Jeremy Gunawardena et al. Current Biology
Abstract
Biochemically plausible models of habituation for single-cell learning
Animals with brains are typically credited with learning. However, the apparently simplest form of learning, habituation, in which a steadily decreasing response is exhibited to a repeated stimulus, is found not only in animals but also in single-cell organisms and individual mammalian cells.
Ten distinctive hallmarks, seven of which involve a single stimulus, have been identified in studies of habitat in both vertebrate and invertebrate animals.
Here, we show by mathematical modeling that simple molecular networks, based on plausible biochemistry with common motifs of negative feedback and incoherent feedforward, can robustly exhibit all single-stimulus hallmarks.
The models refute the assumptions made about frequency and intensity sensitivity in the neuroscience and cognitive science traditions by revealing how the hallmarks of the timescale separation and reversal behavior of memory variables are derived.
Our findings point to the possibility that individual cells may exhibit habituation behaviors that are similar to those found in central nervous system-based multicellular animals, and that their relative simplicity may advance our understanding of learning mechanisms.
