A new way to see activity inside a living cell

Living cells are bombarded with many types of incoming molecular signals that influence their behavior. Being able to measure these signals and how cells respond to them via downstream molecular signaling networks could help scientists learn much more about how cells work, including what happens as they age or fall off. sick.

Currently, this type of in-depth study is not possible because current cell imaging techniques are limited to a handful of different types of molecules within a cell at a time. However, MIT researchers have developed an alternative method that allows them to observe up to seven different molecules at once, and potentially even more.

“There are many examples in biology where one event triggers a long cascade of downstream events, which then causes a specific cellular function,” says Edward Boyden, the Y. Eva Tan Professor of Neurotechnology. “How does this happen? It’s arguably one of the fundamental problems in biology, and so we wondered: Could you just watch this happen?”

The new approach uses green or red fluorescent molecules that flicker at different rates. By imaging a cell for several seconds, minutes, or hours, then extracting each of the fluorescent signals using a computer algorithm, the amount of each target protein can be tracked as it changes over time.

Boyden, who is also a professor of biological engineering and brain and cognitive sciences at MIT, an investigator at the Howard Hughes Medical Institute, and a member of MIT’s McGovern Institute for Brain Research and the Koch Institute for Integrative Cancer Research, as well as co – director of the K. Lisa Yang Center for Bionics, is the lead author of the study, which appears in Cell. Yong Qian, a postdoctoral fellow at MIT, is the lead author of the paper.

Fluorescent signals

Labeling molecules inside cells with fluorescent proteins has allowed researchers to learn a lot about the functions of many cellular molecules. This type of study is often performed with green fluorescent protein (GFP), which was first deployed in imaging in the 1990s. Since then, several fluorescent proteins that glow in other colors have been developed at high experimental purposes.

However, a typical optical microscope can only distinguish two or three of these colors, giving researchers only a small glimpse of the overall activity taking place inside a cell. If they could track a larger number of labeled molecules, researchers could, for example, measure a brain cell’s response to different neurotransmitters during learning, or study the signals that prompt a cancer cell to metastasize.

“Ideally, you would be able to observe the signals in a cell as they fluctuate in real time, and then you could understand how they relate to each other. This would tell you how the cell is calculating,” says Boyden. “The problem is you can’t look at a lot of things at the same time.”

In 2020, Boyden’s lab developed a way to simultaneously image up to five different molecules in a cell, by targeting light reporters to distinct locations inside the cell. This approach, known as “spatial multiplexing,” allows researchers to distinguish signals from different molecules even if they all emit the same fluorescent color.

In the new study, the researchers took a different approach: instead of distinguishing signals based on their physical location, they created fluorescent signals that vary over time. The technique relies on “switchable fluorophores”: fluorescent proteins that turn on and off at a specific rate.

For this study, Boyden and his group members identified four switchable green fluorophores, then designed two more, all of which turn on and off at different rates. They also identified two red fluorescent proteins that switch at different rates and designed an additional red fluorophore.

Each of these switchable fluorophores can be used to mark a different type of molecule in a living cell, such as an enzyme, a signaling protein, or part of the cell cytoskeleton. After photographing the cell for several minutes, hours, or even days, researchers use a computer algorithm to detect the specific signal from each fluorophore, in the same way that the human ear can detect different sound frequencies.

“In a symphony orchestra, you have high instruments, like the flute, and low instruments, like the tuba. And in the middle are instruments like the trumpet. They all have different sounds, and our ear sorts them out,” Boyden said.

The mathematical technique researchers use to analyze signals from fluorophores is known as linear unmixing. This method can extract different fluorophore signals, in the same way that the human ear uses a mathematical model known as the Fourier transform to extract different pitches from a piece of music.

Once this analysis is complete, researchers can see when and where each of the fluorescently labeled molecules was found in the cell during the entire imaging period. The imaging itself can be performed with a simple optical microscope, with no specialized equipment required.

Biological phenomena

In this study, the researchers demonstrated their approach by labeling six different molecules involved in the cell division cycle in mammalian cells. This allowed them to identify patterns in how the levels of enzymes called cyclin-dependent kinases change as a cell progresses through the cell cycle.

The researchers also showed that they could mark other types of kinases, involved in almost all aspects of cell signaling, as well as cellular structures and organelles such as the cytoskeleton and mitochondria. In addition to their experiments using mammalian cells grown in a laboratory dish, the researchers showed that this technique could work in the brains of larval zebrafish.

According to the researchers, this method could be useful for observing how cells respond to any type of input, such as nutrients, immune system factors, hormones or neurotransmitters. It could also be used to study how cells respond to changes in gene expression or genetic mutations. All of these factors play an important role in biological phenomena such as growth, aging, cancer, neurodegeneration and memory formation.

“One might think of all of these phenomena as representing a general class of biological problems, in which a short-term event, such as eating a nutrient, learning something, or contracting an infection, generates a long-term change,” says Boyden.

In addition to pursuing these types of studies, Boyden’s lab is also working to expand the repertoire of switchable fluorophores so they can study even more signals within a cell. They also hope to adapt the system so that it can be used in mouse models.

This story is republished courtesy of MIT News (web.mit.edu/newsoffice/), a popular site that covers news about MIT research, innovation and education.