New research by scientists at North Carolina State University (NC State) has demonstrated that genes are capable of identifying and responding to coded information in light signals, as well as filtering out some signals entirely. Their study findings showed how a single mechanism can trigger different behaviors from the same gene. “The fundamental idea here is that you can encode information in the dynamics of a signal that a gene is receiving,” said Albert Keung, PhD, an assistant professor of chemical and biomolecular engineering at NC State. “So, rather than a signal simply being present or absent, the way in which the signal is being presented matters.”
The researchers say there are practical applications for their work in the pharmaceutical and biotech sectors. “In biomanufacturing, you often want to manage both the growth of cells and the rate at which those cells are producing specific proteins,” said Jessica Lee, PhD, research assistant at NC State. “Our work here can help manufacturers fine-tune and control both of those variables.” Lee is first author, and Keung is corresponding author of the team’s published paper in Cell Systems, which is titled, “Mapping the dynamic transfer functions of eukaryotic gene regulation,” and in which they concluded, “This work directly demonstrates the signal processing potential of a single individual gene and develops molecular and computational tools that can be used to harness it.”
There is plenty of evidence that biological information can be encoded in the dynamics of signaling components, and not just in their biochemical identities, the authors noted. This has been implicated in a range of physiological processes, such as the stress response, stem cell differentiation, and oncogenesis. “Cells, with a limited number of components, utilize dynamic signal processing to perform sophisticated functions in response to complex environments,” the researchers stated. “Transcription factors (TFs) may be a particularly important archetype for this type of information transmission, as they are relatively low in diversity but must command many distinct and complex gene expression programs.”
For their reported study, the researchers developed a platform that combined optogenetics and flow cytometry to map the protein expression response to different dynamic inputs. They modified a yeast cell to express a gene that produces fluorescent proteins when the cell is exposed to blue light. The promoter region of the gene is responsible for controlling the gene’s activity, and in the modified yeast cells, a specific protein binds to the promoter region of the gene. When blue light is shone on that protein, it becomes receptive to a second protein. When the second protein binds to the first protein, the gene becomes active. And that’s easy to detect, because the activated gene produces proteins that glow in the dark.
The researchers exposed these yeast cells to 119 different light patterns. Each light pattern differed in terms of the intensity of the light, how long each pulse of light was, and how frequently the pulses occurred. The researchers then mapped out the amount of fluorescent protein that the cells produced in response to each light pattern.
We may tend to think of genes being turned either on or off, but—less like a light switch and more like a dimmer switch—a gene can be activated a little bit, a lot, or anywhere in between. So, if a given light pattern led to the production of a lot of fluorescent protein, that meant the light pattern made the gene very active. If the light pattern led to the production of just a little fluorescent protein, that meant the pattern only triggered mild activity of the gene.
“We found that different light patterns can produce very different outcomes in terms of gene activity,” said Lee. “The big surprise, to us, was that the output was not directly correlated to the input. Our expectation was that the stronger the signal, the more active the gene would be. But that wasn’t necessarily the case. One light pattern might make the gene significantly more active than another light pattern, even if both patterns were exposing the gene to the same amount of light.”
The researchers found that all three light pattern variables—intensity of the light, frequency of the light pulses, and how long each pulse lasted—could influence gene activity, but they also found that controlling the frequency of light pulses gave them the most precise control over gene activity.
“We also used the experimental data here to develop a computational model that helped us better understand why different patterns produce different levels of gene activity,” said Leandra Caywood, co-author of the paper and a PhD student at NC State. “For example, we found that when you bunch rapid pulses of light very closely together, you get more gene activity than you would expect from the amount of light being applied. Using the model, we were able to determine that this is happening because the proteins can’t separate and come back together quickly enough to respond to every pulse. Basically, the proteins don’t have time to fully separate from each other between pulses, so are spending more time connected —meaning that the gene is spending more time activated. Understanding these sorts of dynamics is very useful for helping us figure out how to better control gene activity using these signals.”
“Our finding is relevant for cells that respond to light, such as those found in leaves,” Keung added. “But it also tells us that genes are responsive to signal patterns, which could be delivered by mechanisms other than light.”
So how might this work in cells? A cell may receive a chemical signal. The presence of the chemical can’t be patterned—it’s either present or it is not. However, the cell can respond to the presence of the chemical by creating a patterned signal for the target gene. The cell does this by controlling the rate at which the protein that binds to the promoter region enters and exits the nucleus of the cell. We could think of controlling the presence and absence of this protein as sending a Morse code message from the cell to the gene. Depending on a suite of other variables—such as the presence of other chemicals—the cell can fine-tune the message it sends to the gene in order to modulate its activity.
“This tells us that you can use the same protein to give different messages to the same gene,” Keung said. “So the cell can use one protein to have a gene respond differently to different chemicals.”
In a separate set of experiments, the researchers found that genes were also able to filter out some signals. The mechanics of this are both straightforward and mysterious. The researchers could tell that when a second protein attached to the promoter region of the gene, some frequencies of light pulses did not trigger the production of fluorescent proteins. In short, the researchers know the second protein ensured that a gene responds only to a specific suite of signals—but they don’t know exactly how the second protein accomplishes that.
The researchers also found that they could control the number of distinct signals a gene could respond to by manipulating the number and type of proteins attached to the promoter region of the gene.
For example, you could attach proteins to the promoter region that serve as filters to limit the number of signals that activate the gene. Or you could attach proteins to the promoter region that trigger different degrees of activation of the gene.
“One additional contribution of this work is that we’ve determined we can communicate about 1.71 bits worth of information through the promoter region of a gene with just one protein attachment,” Lee said. As the authors explained, “This system revealed tunable gene expression and filtering behaviors and provided a quantification of the limit to the amount of information that can be reliably transferred across a single promoter as ~ 1.7 bits.” Lee continued, “In practical terms that means that the gene, without a complex network of protein attachments, is able to distinguish between more than three signals without error. Previous work had set that baseline at 1.55 bits, so this study advances our understanding of what’s possible here. It’s a foundation we can build on.”
The researchers say their work will enable future studies that help scientists to understand the dynamics of cell behavior and gene expression. “This work directly demonstrates the signal processing potential of a single individual gene and develops molecular and computational tools that can be used to harness it,” they wrote. “There are many avenues to expand into and explore. In our work, we relied on endpoint measurements that could be rapidly measured by flow cytometry. However, information can also be stored in the dynamics of the output signal, e.g., the production rate, time delay of repression/activation, or oscillatory behavior. High throughput approaches that can track the output dynamics of thousands of cultures would unlock this potential space for investigation.”
And while the reported study focused on a single promoter, different promoter structures would likely confer distinct transfer functions, the investigators further noted. “Continued advances in experimental and computational systems that can handle the large parameter space of dynamic signals will unlock our ability to measure, quantify, and understand information transmission in biological systems and reveal the underpinnings of how limited numbers of components can give rise to the rich complexity of biological functions.”