Cornell University researchers have developed a bioelectric device that can detect and classify new variants of coronavirus to identify those that are most harmful. It has the potential to do the same with other viruses, as well.
The sensing tool uses a cell membrane, aka biomembrane, on a microchip that recreates the cellular environment for — and the biological steps of — infection. This enables researchers to quickly characterize variants of concern and parse the mechanics that drive the disease’s spread, without getting bogged down by the complexity of living systems.
“In the news, we see these variants of concern emerge periodically, like delta, omicron and so on, and it kind of freaks everyone out. The first thoughts are, ‘Does my vaccine cover this new variant? How concerned should I be?'” said Susan Daniel, professor of chemical engineering, and senior author of the paper published in Nature Communications. “It takes a little while to determine if a variant is a true cause for concern or if it will just it fizzle out.”
While plenty of biological elements have been put on microchips, from cells to organelles and organ-like structures, the new platform differs from those devices because it actually recapitulates the biological cues and processes that lead to the initiation of an infection at the cellular membrane of a single cell. In effect, it fools a variant into behaving as if it is in an actual cellular system of its potential host.
“There could potentially be a correlation between how well a variant can deliver its genome across the biomembrane layer and how concerning that variant can be in terms of its ability to infect humans,” Daniel said. “If it’s able to release its genome very effectively, perhaps that’s an indicator that a variant of concern should be something we should monitor closely or formulate a new vaccine that includes it. If it doesn’t release it very well, then maybe that variant of concern is something less worrisome. The key point is we need to classify these variants quickly so we can make informed decisions, and we can do this really fast with our devices. These assays take minutes to run, and it’s ‘label-free,’ meaning you don’t actually have to tag the virus to monitor its progress.”
Because the researchers are able to faithfully recreate the biological conditions and cues that activate a virus, they can also change those cues and see how the virus responds.
“In terms of understanding the basic science of how infection occurs and what cues can assist or hinder it, this is a unique tool,” Daniel said. “Because you can decouple many aspects of the reaction sequence, and identify what factors promote or impede infection.”
The platform can be tailored for other viruses, such as influenza and measles, so long as the researchers know what cell type has the propensity to be infected, as well as what biological idiosyncrasies allow a specific infection to flourish. For example, influenza requires a pH drop to trigger its hemagglutinin, and coronavirus has an enzyme that activates its spike protein.
“Every virus has its own way of doing things. And you need to know what they are to replicate that infection process on chip,” Daniel said. “But once you know them, you can build the platform out to accommodate any of those specific conditions.”
Co-authors include doctoral student Ambika Pachaury; and Konstantinos Kallitsis and Zixuan Lu of University of Cambridge.
The research was supported by the Defense Advanced Research Projects Agency (DARPA), the Army Research Office, Cornell’s Smith Fellowship for Postdoctoral Innovation, the Schmidt Futures program and the National Science Foundation.
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