Nobel Prize goes to technology for mRNA vaccines
When Drew Weissman received a call from Katalin Karikó in the early morning hours this past Monday, he assumed his longtime research partner was calling to share a nascent, nagging idea. Weissman, a professor of medicine at the Perelman School of Medicine at the University of Pennsylvania, and Karikó, a professor at Szeged University and an adjunct professor at UPenn, both struggle with sleep disturbances. Thus, middle-of-the-night discourses between the two, often over email, has been a staple of their friendship. But this time, Karikó had something more pressing and exciting to share: They had won the 2023 Nobel Prize in Physiology or Medicine.
The work for which they garnered the illustrious award and its accompanying $1,000,000 cash windfall was completed about two decades ago, wrought through long hours in the lab over many arduous years. But humanity collectively benefited from its life-saving outcome three years ago, when both Moderna and Pfizer/BioNTech’s mRNA vaccines against COVID were found to be safe and highly effective at preventing severe disease. Billions of doses have since been given out to protect humans from the upstart viral scourge.
“I thought of going somewhere else, or doing something else,” said Katalin Karikó. “I also thought maybe I’m not good enough, not smart enough. I tried to imagine: Everything is here, and I just have to do better experiments.”
Unlocking the power of mRNA
Weissman and Karikó unlocked mRNA vaccines for the world back in the early 2000s when they made a key breakthrough. Messenger RNA molecules are essentially instructions for cells’ ribosomes to make specific proteins, so in the 1980s and 1990s, researchers started wondering if sneaking mRNA into the body could trigger cells to manufacture antibodies, enzymes, or growth agents for protecting against infection, treating disease, or repairing tissues. But there was a big problem: injecting this synthetic mRNA triggered a dangerous, inflammatory immune response resulting in the mRNA’s destruction.
While most other researchers chose not to tackle this perplexing problem to instead pursue more lucrative and publishable exploits, Karikó stuck with it. The choice sent her academic career into depressing doldrums. Nobody would fund her work, publications dried up, and after six years as an assistant professor at the University of Pennsylvania, Karikó got demoted. She was going backward.
“I thought of going somewhere else, or doing something else,” Karikó told Stat in 2020. “I also thought maybe I’m not good enough, not smart enough. I tried to imagine: Everything is here, and I just have to do better experiments.”
A tale of tenacity
Collaborating with Drew Weissman, a new professor at the University of Pennsylvania, in the late 1990s helped provide Karikó with the tenacity to continue. Weissman nurtured a goal of developing a vaccine against HIV-1, and saw mRNA as a potential way to do it.
“For the 20 years that we’ve worked together before anybody knew what RNA is, or cared, it was the two of us literally side by side at a bench working together,” Weissman said in an interview with Adam Smith of the Nobel Foundation.
In 2005, the duo made their 2023 Nobel Prize-winning breakthrough, detailing it in a relatively small journal, Immunity. (Their paper was rejected by larger journals, including Science and Nature.) They figured out that chemically modifying the nucleoside bases that make up mRNA allowed the molecule to slip past the body’s immune defenses. Karikó and Weissman followed up that finding by creating mRNA that’s more efficiently translated within cells, greatly boosting protein production. In 2020, scientists at Moderna and BioNTech (where Karikó worked from 2013 to 2022) rushed to craft vaccines against COVID, putting their methods to life-saving use.
The future of vaccines
Buoyed by the resounding success of mRNA vaccines, scientists are now hurriedly researching ways to use mRNA medicine against other infectious diseases, cancer, and genetic disorders. The now ubiquitous efforts stand in stark contrast to Karikó and Weissman’s previously unheralded struggles years ago as they doggedly worked to realize a shared dream that so many others shied away from. Katalin Karikó and Drew Weissman were brave enough to walk a scientific path that very well could have ended in a dead end, and for that, they absolutely deserve their 2023 Nobel Prize.
This article originally appeared on Big Think, home of the brightest minds and biggest ideas of all time.
As We Wait for a Vaccine, Scientists Work to Scale Up the Best COVID-19 Antibodies to Give New Patients
When we get sick, our immune system sends its soldier cells to the battlefield. Called B-cells, they "examine" the foreign particles that shouldn't be in our bloodstream—and start producing the antibodies, the proteins to neutralize the invaders.
To screen the antibodies, scientists have developed a proprietary way to make the effective ones glow – like a literal "lightbulb" moment.
The better these antibodies are at neutralizing the pathogen, the faster we recover.
The antibodies acquired from COVID-19 survivors already showed promise in treating other patients, but because they must be obtained from people, generating a regular supply is not feasible. To close the gap, researchers are trying to identify the B-cells that make the best antibodies—and then farm them in laboratories at scale.
Scientists at Berkley Lights, a biotechnology company in California, have been screening B-cells from recovered patients and testing the antibodies they release for virus-neutralizing abilities. To screen the antibodies, scientists there have developed a proprietary way to make the effective ones glow – like a literal "lightbulb" moment.
So how does it work? First, the individual B-cells are placed into microscopic chambers called nano-pens, where they secrete the antibodies. Once released, the antibodies are flushed over tiny beads that have bits of the viral particles attached to them, along with special molecules that can emit fluorescent light.
"When an antibody binds to the bead, we see a bright light on the bead," explains John Proctor, the company's senior vice president of antibody therapeutics. "So we can identify which cells are making the antibodies."
Then the antibodies are tested for their ability to counteract the coronavirus's spike proteins, which the virus uses to break into our cells. Not all antibodies are equally good at this crucial defense move—some can block only parts of the virus's machinery, while others can neutralize it completely. Proctor and his colleagues are looking for the latter.
Once scientists identify the best performing B-cells, they crack the cells open—or in scientific terms "lyse" them—and extract the genetic instructions for making the antibodies. As it turns out, B-cells aren't very efficient at pumping out massive amounts of antibodies, so scientists insert these genetic instructions into a different, more prolific type of cell.
Named Chinese Hamster Ovary Cells or CHO, these cells are commonly used in the pharmaceutical industry because they can generate therapeutic proteins en masse. Under the right nutrient conditions, which include a lot of sugar, CHO cells can keep making the antibodies at commercial levels. "They are engineered to operate in very large bioreactors," Proctor explains.
While traditional antibody screening can take three months, the Beacon System can do it in less than 24 hours.
Berkeley Lights' technology has already been used to screen the antibodies of recovered patients from Vanderbilt University Medical Center. In another example, a biotech company GenScript ProBio used the platform to screen mice engineered to have human antibodies for the coronavirus.
In addition to its small, lab-on-a-chip size, Berkeley Lights' system allows scientists to greatly speed up the screening process. While traditional antibody screening can take three months, the Beacon System can do it in less than 24 hours. "We only need one B-cell per pen and a couple of beads to see that fluorescent signal," Proctor says. "It is a more advanced way to process and analyze cells, and that level of sensitivity is unique to our technology."
B-cells secreting antibodies inside the Berkeley Lights Beacon System Nano-Pens.
While vaccines are likely to take months to develop and test, antibodies might arrive to the battleground sooner. With the extremely limited treatment options for COVID-19, antibody-based therapeutics can potentially bridge this gap.
Lina Zeldovich has written about science, medicine and technology for Popular Science, Smithsonian, National Geographic, Scientific American, Reader’s Digest, the New York Times and other major national and international publications. A Columbia J-School alumna, she has won several awards for her stories, including the ASJA Crisis Coverage Award for Covid reporting, and has been a contributing editor at Nautilus Magazine. In 2021, Zeldovich released her first book, The Other Dark Matter, published by the University of Chicago Press, about the science and business of turning waste into wealth and health. You can find her on http://linazeldovich.com/ and @linazeldovich.
Have you felt a bit like an armchair epidemiologist lately? Maybe you've been poring over coronavirus statistics on your county health department's website or on the pages of your local newspaper.
If the percentage of positive tests steadily stays under 8 percent, that's generally a good sign.
You're likely to find numbers and charts but little guidance about how to interpret them, let alone use them to make day-to-day decisions about pandemic safety precautions.
Enter the gurus. We asked several experts to provide guidance for laypeople about how to navigate the numbers. Here's a look at several common COVID-19 statistics along with tips about how to understand them.
Case Counts: Consider the Context
The number of confirmed COVID-19 cases in American counties is widely available. Local and state health departments should provide them online, or you can easily look them up at The New York Times' coronavirus database. However, you need to be cautious about interpreting them.
"Case counts are the obvious numbers to look at. But they're probably the hardest thing to sort out," said Dr. Jeff Martin, an epidemiologist at the University of California at San Francisco.
That's because case counts by themselves aren't a good window into how the coronavirus is affecting your community since they rely on testing. And testing itself varies widely from day to day and community to community.
"The more testing that's done, the more infections you'll pick up," explained Dr. F. Perry Wilson, a physician at Yale University. The numbers can also be thrown off when tests are limited to certain groups of people.
"If the tests are being mostly given to people with a high probability of having been infected -- for example, they have had symptoms or work in a high-risk setting -- then we expect lots of the tests to be positive. But that doesn't tell us what proportion of the general public is likely to have been infected," said Eleanor Murray, an epidemiologist at Boston University.
These Stats Are More Meaningful
According to Dr. Wilson, it's more useful to keep two other statistics in mind: the number of COVID tests that are being performed in your community and the percentage that turn up positive, showing that people have the disease. (These numbers may or may not be available locally. Check the websites of your community's health department and local news media outlets.)
If the number of people being tested is going up, but the percentage of positive tests is going down, Dr. Wilson said, that's a good sign. But if both numbers are going up – the number of people tested and the percentage of positive results – then "that's a sign that there are more infections burning in the community."
It's especially worrisome if the percentage of positive cases is growing compared to previous days or weeks, he said. According to him, that's a warning of a "high-risk situation."
Dr. George Rutherford, an epidemiologist at University of California at San Francisco, offered this tip: If the percentage of positive tests steadily stays under 8 percent, that's generally a good sign.
There's one more caveat about case counts. It takes an average of a week for someone to be infected with COVID-19, develop symptoms, and get tested, Dr. Rutherford said. It can take an additional several days for those test results to be reported to the county health department. This means that case numbers don't represent infections happening right now, but instead are a picture of the state of the pandemic more than a week ago.
Hospitalizations: Focus on Current Statistics
You should be able to find numbers about how many people in your community are currently hospitalized – or have been hospitalized – with diagnoses of COVID-19. But experts say these numbers aren't especially revealing unless you're able to see the number of new hospitalizations over time and track whether they're rising or falling. This number often isn't publicly available, however.
If new hospitalizations are increasing, "you may want to react by being more careful yourself."
And there's an important caveat: "The problem with hospitalizations is that they do lag," UC San Francisco's Dr. Martin said, since it takes time for someone to become ill enough to need to be hospitalized. "They tell you how much virus was being transmitted in your community 2 or 2.5 weeks ago."
Also, he said, people should be cautious about comparing new hospitalization rates between communities unless they're adjusted to account for the number of more-vulnerable older people.
Still, if new hospitalizations are increasing, he said, "you may want to react by being more careful yourself."
Deaths: They're an Even More Delayed Headline
Cable news networks obsessively track the number of coronavirus deaths nationwide, and death counts for every county in the country are available online. Local health departments and media websites may provide charts tracking the growth in deaths over time in your community.
But while death rates offer insight into the disease's horrific toll, they're not useful as an instant snapshot of the pandemic in your community because severely ill patients are typically sick for weeks. Instead, think of them as a delayed headline.
"These numbers don't tell you what's happening today. They tell you how much virus was being transmitted 3-4 weeks ago," Dr. Martin said.
'Reproduction Value': It May Be Revealing
You're not likely to find an available "reproduction value" for your community, but it is available for your state and may be useful.
A reproduction value, also known as R0 or R-naught, "tells us how many people on average we expect will be infected from a single case if we don't take any measures to intervene and if no one has been infected before," said Boston University's Murray.
As The New York Times explained, "R0 is messier than it might look. It is built on hard science, forensic investigation, complex mathematical models — and often a good deal of guesswork. It can vary radically from place to place and day to day, pushed up or down by local conditions and human behavior."
It may be impossible to find the R0 for your community. However, a website created by data specialists is providing updated estimates of a related number -- effective reproduction number, or Rt – for each state. (The R0 refers to how infectious the disease is in general and if precautions aren't taken. The Rt measures its infectiousness at a specific time – the "t" in Rt.) The site is at rt.live.
"The main thing to look at is whether the number is bigger than 1, meaning the outbreak is currently growing in your area, or smaller than 1, meaning the outbreak is currently decreasing in your area," Murray said. "It's also important to remember that this number depends on the prevention measures your community is taking. If the Rt is estimated to be 0.9 in your area and you are currently under lockdown, then to keep it below 1 you may need to remain under lockdown. Relaxing the lockdown could mean that Rt increases above 1 again."
"Whether they're on the upswing or downswing, no state is safe enough to ignore the precautions about mask wearing and social distancing."
Keep in mind that you can still become infected even if an outbreak in your community appears to be slowing. Low risk doesn't mean no risk.
Putting It All Together: Why the Numbers Matter
So you've reviewed COVID-19 statistics in your community. Now what?
Dr. Wilson suggests using the data to remind yourself that the coronavirus pandemic "is still out there. You need to take it seriously and continue precautions," he said. "Whether they're on the upswing or downswing, no state is safe enough to ignore the precautions about mask wearing and social distancing. 'My state is doing well, no one I know is sick, is it time to have a dinner party?' No."
He also recommends that laypeople avoid tracking COVID-19 statistics every day. "Check in once a week or twice a month to see how things are going," he suggested. "Don't stress too much. Just let it remind you to put that mask on before you get out of your car [and are around others]."