By Adam Bonislawski
Researchers at the University of Bordeaux have developed a fluorescent labeling technique that allows the simultaneous tracking of hundreds of thousands of proteins with nanometer resolution.
The technique, which was described in a paper in the August issue of Biophysical Journal, enables researchers to study localization and movement patterns of specific proteins on living cells, and could potentially have applications for proteomics research, Laurent Cognet, a researcher at the University of Bordeaux and one of the paper's authors, told ProteoMonitor.
Named universal PAINT, or uPAINT, the method builds upon another single-molecule-based superresolution imaging technique, called points accumulation for imaging in nanoscale topography, or PAINT, that was developed several years ago and used to study the topographies of lipid bilayers. PAINT images the surface of target objects through the use of probes that turn fluorescent upon binding to the object.
In uPAINT, Cognet and his colleagues have sought to apply the principle behind PAINT to single proteins while also increasing the amount of dynamic information obtained. The new method uses fluorescent ligands to continuously and randomly label endogenous proteins on the membranes of living cells while imaging them using oblique illumination. With it researchers can track hundreds of thousands of individual proteins, monitoring their movement over periods of time as long as tens of seconds.
“What we obtain is a localization map of the endogenous proteins on a given cell with nanometer resolution,” Cognet said. “[The resolution] is around 50 nanometers — in between what you get with electron microscopy and classical fluorescence microscopy. So you look at a very high number of proteins, which allows you to have a high-density map of these proteins for localization.”
Because the technique tracks proteins on live cells, researchers are able to quantify the proteins' movement across the cell, as well, he added. “On a single cell you can have a very clear picture of the spatial-temporal organization of a given endogenous protein.”
This sort of information could have uses in proteomics work, Cognet said, noting that “in the sense that proteomics aims at screening proteins by different criteria, the method could help in doing that. If you stimulate the cell in some way, for example, you might see what spatial-temporal organization changes in the proteins [that causes]. That could be of interest for people in proteomics.”
In other words, in addition to gathering data on protein expression and activation levels in given samples, researchers might examine proteins' localization and dynamic properties.
Cognet said that currently the University of Bordeaux researchers are looking into using uPAINT to study the localization and movement patterns of receptors for neurotransmitters in the synapses of neurons.
“We are interested in the ultrastructure of synapses during synaptic plasticity” he said. “By understanding the spatio-temporal organization of different types of synaptic receptors, one should learn about the way they work together”
The technique could also be potentially useful for examining localization and dynamic patterns of proteins like epidermal growth factor receptors in cancer cells, Cognet said.
"It could be interesting to look at these kinds of proteins,” he said. “If a cell expresses a type of receptor, how are those receptors localized? Do they cluster? When they're activated do they cluster or not cluster?”
The scientists are also investigating the use of uPAINT to simultaneously track multiple types of proteins, a capacity that Cognet said would allow for the study of things like co-localization patterns. In the Biophysical Journal study, the team successfully tracked several different types of proteins using uPAINT, but not at the same time.
“People are very interested in co-localization of proteins,” he said. “Seeing where they are, how many there are, do they interact? Are they co-localized with this protein or with this protein?”
In principle, looking at multiple kinds of proteins at once should be fairly simple, Cognet said.
“The method relies on classical live immunocytochemistry, so as long as you're able to have different ligands with different colors, it should be straightforward,” he said.
The main difficulty is in building software capable of registering and analyzing the flood of data obtained by following such a large number of proteins.
“You generate a lot of data, and then clearly you have to handle that data,” Cognet said. “It's clear that to use the full capacity of the method there will need to be new strategies to visualize the data because you really have a high density of information. You're dealing with tens of thousands of molecules, so you have to create [a system for data analysis] that's quite automatic and – at the beginning – quite simple so that the analysis doesn't become too complicated.”
Previous work done by single-molecule researchers offers some insights into possible techniques for analysis of protein movement, he said, but “adapting these strategies to such large numbers of [proteins] will require some development.”
Were any commercial opportunities to emerge based on the technique, it would likely be from the software side, Cognet suggested. The uPAINT method itself requires little in the way of specialized equipment and is straightforward enough “that I don't really see how we could commercialize the optical method,” he said.