NEW YORK (GenomeWeb) – A team led by researchers at the Massachusetts Institute of Technology has developed carbon nanotube-based sensors capable of detecting proteins secreted from microorganisms and human cells with single-molecule sensitivity.
Detailed in a study published last month in Nature Nanotechnology, the device could prove useful for applications including single-cell analyses, said Michael Strano, professor of chemical engineering at MIT and senior author on the paper.
The sensors consist of arrays of single-walled carbon nanotubes (SWNT) functionalized with aptamers to target proteins and using near-infrared emitters for their readout. When the target proteins bind to the aptamers, they trigger an optical signal from the near-infrared emitter that the researchers detected using a custom near-infrared microscope.
The high sensitivity of the carbon nanotubes allowed Strano and his team to measure proteins at the single-molecule and single-cell level, even as they were secreted from individual cells.
In the Nature Nanotechnology study, the researchers looked at the microorganisms Escherichia coli, Pichia pastoris, and the HEK 293 cell line.
In the case of E. coli, they engineered the organism to express and secrete the RAP1 peptide in response to treatment with anhydrotetracycline. Using this model, they established a titration of RAP1-secreting E. coli populations, which allowed them to test the sensitivity of their system. In this way, they determined that they could detect the secretion of a single RAP1 peptide from a single E. coli cell in a 200 µl chamber, which, they noted, amounted to an 8.3 zeptomolar level of sensitivity.
They followed this work by using the sensor to monitor RAP1 secretions from a collection of 22 E. coli cells over the course of an hour, observing that cells that showed signs of division during the experiment had lower levels of secretion than did those showing no signs of cell division.
Strano and his team then used their device to measure the protein HIV1 integrase in P. pastoris and HEK 293 cells, detecting secretions of the protein both at the bulk cell and single-cell level.
They also used the platform to monitor RAP1 production in a T7 bacteriophage engineered to secrete the peptide, tracking the release of the protein during lysis of an E. coli cell infected with the engineered T7 bacteriophage.
The study authors noted that the findings suggest the sensors could prove useful as a tool for, among other things, monitoring recombinant protein expression systems.
"Although intensive efforts have been devoted to improve protein expression through vector design, host cell engineering, and upstream process development, there is limited knowledge and experience regarding single-cell analysis of protein secretion," they wrote, adding that their device could provide new information on "protein secretion processes in industrial protein expression systems."
Strano noted, as well, that the technique could prove useful for pharmaceutical research, particularly as technologies like gene therapy and cell-based therapies grow more prevalent.
"We're entering an era where living cells are going to be therapeutic," he said. "But one of the things that field has been crying out for is they need tools to better understand what they have done to each and every cell. So they are really asking for single-cell analytics."
Researchers are particularly interested in approaches, like the nanotube platform, that are label-free, Strano added. "We can know a lot about a cell if you're willing to express genetically encoded reporters inside the cell, if you're willing to put fluorescent molecules inside the cell and so forth. But that field is very resistant to do that for cells that are ultimately going to go as therapy in your body."
"So this we think is a very promising area for nanosensors," he said. "Nanosensors have a big advantage. They're much, much smaller than the cell."
He cited another recent paper from his group in Proceedings of the National Academy of Sciences in which he and his colleagues placed more than 20,000 nanosensors underneath a single cell in an effort to detect dopamine.
"So every ten nanometers or so, we could map with some precision where dopamine was coming out of that cell," he said.
One of the main technical hurdles in developing the sensors used in the Nature Nanotechnology work was figuring out how to attache the aptamer to the carbon nanotube in such a way that it was close enough to generate signal upon binding to its target, but far away enough that its binding is not affected by the nanotube.
In work led by the paper's first author Markita Patricia Landry, formerly a post-doc in Strano's lab and now an assistant professor at the University of California, Berkeley, the researchers determined that use of a spacer between the aptamer and the nanotube provided the best performance.
"Basically, if you make the spacer too large the aptamer will bind but it's nowhere near your transducer," Strano said. "If the spacer's too short, the aptamer itself is actually getting affected by the [nanotube] surface, and it won't bind anymore."
He noted, however, that even with the use of the spacer, binding and cross-reactivity still remain challenges.
"If you optimize the spacer you have your best chance of getting it to work, but in our paper we still only really got very, very good specificity with just two examples," he said. "So there's no guarantee you can get all aptamers to work using this format."
Nonetheless, the technique is ready to be deployed as a research method, Strano said. "I would say the technique is something that other researchers can read about and with a little bit of help probably set up in their own lab."
A more scalable model remains several years down the line, he added, noting that he has patented the method and is currently "working with partners to make these tools available to the community."
"I think we are a few years out," Strano said. "It's one thing to measure isolated cells here and there, but we have work out and learn from the rest of the community about how to extract information from ten million cells, right? However, as a viable technique ready to do measurements and basic research, it's ready to go."