Certainly one of the 12 labors of Hercules, based on ancient lore, was to destroy a nine-headed monster called the Hydra. The challenge was that when Hercules used his sword to cut off considered one of the monster’s heads, two would grow back instead. He due to this fact needed a further weapon, a torch, to conquer his foe.
There are parallels between this legend and our three-years-and-counting battle with SARS-Cov-2, the virus that causes Covid-19. Each time scientists have thought they’d subdued one strain of the virus — be it alpha, beta, delta, or omicron — one other variant or subvariant emerged a short time later.
For that reason, researchers at MIT and other institutions are preparing a recent strategy against the virus — a novel vaccine that, unlike those in use today, could potentially counteract all variants of the disease, having a property called “pan-variance” that would circumvent the necessity for a unique booster shot each time a recent strain comes into circulation. In a paper published today within the journal , the teamreports on experiments with mice that display the vaccine’s effectiveness in stopping death from Covid-19 infection.
Viral vaccines typically work by exposing the immune system to a small piece of the virus. That may create learned responses that protect people later after they’re exposed to the actual virus. The premise of ordinary Covid-19 vaccines, similar to those produced by Moderna and Pfizer, is to activate the a part of the immune system that releases neutralizing antibodies. They do that by providing cells with instructions (in the shape of mRNA molecules) for making the spike protein — a protein found on the surface of the Covid-19 virus whose presence can trigger an immune response. “The issue with that approach is that the goal keeps changing” — the spike protein itself can vary amongst different viral strains — “and that could make the vaccine ineffective,” says David Gifford, an MIT professor in electrical engineering and computer science and biological engineering, in addition to a coauthor of the paper.
He and his colleagues, accordingly, have taken a unique approach, choosing a unique goal for his or her vaccine: activating the a part of the immune system that unleashes “killer” T cells, which attack cells infected with the virus. A vaccine of this kind is not going to keep people from getting Covid-19, nevertheless it could keep them from getting very sick or dying.
A key innovation made by this group — which included researchers from MIT, the University of Texas, Boston University, Tufts University, Massachusetts General Hospital, and Acuitas Therapeutics — was to bring machine learning techniques into the vaccine design process. A critical aspect of that process involves determining which parts of SARS-Cov-2, which peptides (chains of amino acids which are the constructing blocks of proteins), should go into the vaccine. That entails sifting through 1000’s of peptides within the virus and picking out just 30 or in order that must be incorporated.
But that call has to have in mind so-called HLA molecules — protein fragments on the surface of cells that function “billboards,” telling immune cells (which lack X-ray vision) what is occurring inside other cells. The display of specific protein fragments can indicate, as an illustration, that a certain cell is infected by SARS-Cov-2 and must be gotten rid of.
Machine learning algorithms were used to resolve an advanced set of “optimization problems,” notes Brandon Carter, a PhD student in MIT’s Department of Electrical Engineering and Computer Science, an affiliate of the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL), and a lead creator of the brand new paper. The overriding goal is to pick out peptides which are present, or “conserved,” in all variants of the virus. But those peptides also should be related to HLA molecules which have a high likelihood of being displayed in order that they can alert the immune system. “You would like this to occur in as many individuals as possible to get maximum population coverage out of your vaccine,” Carter says. Moreover, you would like each individual to be covered multiple times by the vaccine, he adds. “Because of this a couple of peptide within the vaccine is predicted to be displayed by some HLA in everyone.” Achieving these various objectives is a task that could be significantly expedited by machine learning tools.
While that touches on the theoretical end of this project, the most recent results got here from experiments carried out by collaborators on the University of Texas Medical Branch in Galveston, which showed a robust immune response in mice given the vaccine. The mice on this experiment didn’t die but were were “humanized,” meaning that they’d an HLA molecule present in human cells. “This study,” Carter says, “offers proof in a living system, an actual mouse, that the vaccines we devised using machine learning can afford protection from the Covid virus.” Gifford characterizes their work as “the primary experimental evidence that a vaccine formulated on this fashion could be effective.”
Paul Offit, a professor of pediatrics within the Division of Infectious Diseases at Children’s Hospital of Philadelphia, finds the outcomes encouraging. “Loads of people wonder about what approaches can be used to make Covid-19 vaccines in the long run,” Offit says. “On condition that T cells are critical in protection against severe Covid-19, future vaccines that deal with inducing the broadest T cell responses can be a very important step forward in the subsequent generation of vaccines.”
More animal studies — and eventual human studies — would must be done before this work can usher within the “next generation of vaccines.” The undeniable fact that 24 percent of the lung cells in vaccinated mice were T cells, Gifford says, “showed that their immune systems were poised to fight viral infection.” But one needs to be careful to avoid too strong of an immune response, he cautions, in order to not cause lung damage.
Other questions abound. Should T-cell vaccines be used as a substitute of, or together with, standard spike protein vaccines? While it is likely to be possible to boost existing vaccines by including a T-cell component, Gifford says, “putting two things together might not be strictly additive, as one a part of the vaccine could mask the opposite.”
Nevertheless, he and his colleagues consider their T-cell vaccine has the potential to assist immunocompromised individuals who cannot produce neutralizing antibodies and thus may not profit from traditional Covid vaccines. Their vaccine may additionally alleviate affected by “long Covid” in individuals who proceed to harbor reservoirs of the virus well after their initial infection.
The mechanism behind current flu vaccines, like current Covid-19 vaccines, is to induce neutralizing antibodies, but those vaccines don’t all the time work for various influenza strains. Carter sees potential for flu vaccines based on a T-cell response, “which can prove to be more practical, providing broader coverage, due to their pan-variance.”
Nor are the methods they’re developing limited to Covid-19 or the flu, he maintains, as they could someday be applied to cancer. Gifford agrees, saying that a T-cell vaccine — designed to maximise immune protection each inside a person and among the many biggest number of people — could turn out to be a key asset within the fight against cancer. “That’s not inside the scope of our present study,” he says, “nevertheless it might be the topic of future work.”
Other MIT contributors to the work were Ge Liu and Alexander Dimitrakakis. The work was supported, partially, by Schmidt Futures and a C3.ai grant to David Gifford.