How a Nobel-Prize Winner Fought Her Family, Nazis, and Bombs to Change our Understanding of Cells Forever
Rita Levi-Montalcini survived the Nazis and eventually won a Nobel Prize for her work to understand why certain cells grow so quickly.
When Rita Levi-Montalcini decided to become a scientist, she was determined that nothing would stand in her way. And from the beginning, that determination was put to the test. Before Levi-Montalcini became a Nobel Prize-winning neurobiologist, the first to discover and isolate a crucial chemical called Neural Growth Factor (NGF), she would have to battle both the sexism within her own family as well as the racism and fascism that was slowly engulfing her country
Levi-Montalcini was born to two loving parents in Turin, Italy at the turn of the 20th century. She and her twin sister, Paola, were the youngest of the family's four children, and Levi-Montalcini described her childhood as "filled with love and reciprocal devotion." But while her parents were loving, supportive and "highly cultured," her father refused to let his three daughters engage in any schooling beyond the basics. "He loved us and had a great respect for women," she later explained, "but he believed that a professional career would interfere with the duties of a wife and mother."
At age 20, Levi-Montalcini had finally had enough. "I realized that I could not possibly adjust to a feminine role as conceived by my father," she is quoted as saying, and asked his permission to finish high school and pursue a career in medicine. When her father reluctantly agreed, Levi-Montalcini was ecstatic: In just under a year, she managed to catch up on her mathematics, graduate high school, and enroll in medical school in Turin.
By 1936, Levi-Montalcini had graduated medical school at the top of her class and decided to stay on at the University of Turin as a research assistant for histologist and human anatomy professor Guiseppe Levi. Levi-Montalcini started studying nerve cells and nerve fibers – the tiny, slender tendrils that are threaded throughout our nerves and that determine what information each nerve can transmit. But it wasn't long before another enormous obstacle to her scientific career reared its head.
Science Under a Fascist Regime
Two years into her research assistant position, Levi-Montalcini was fired, along with every other "non-Aryan Italian" who held an academic or professional career, thanks to a series of antisemitic laws passed by Italy's then-leader Benito Mussolini. Forced out of her academic position, Levi-Montalcini went to Belgium for a fellowship at a neurological institute in Brussels – but then was forced back to Turin when the German army invaded.
Levi-Montalcini decided to keep researching. She and Guiseppe Levi built a makeshift lab in Levi-Montalcini's apartment, borrowing chicken eggs from local farmers and using sewing needles to dissect them. By dissecting the chicken embryos from her bedroom laboratory, she was able to see how nerve fibers formed and died. The two continued this research until they were interrupted again – this time, by British air raids. Levi-Montalcini fled to a country cottage to continue her research, and then two years later was forced into hiding when the German army invaded Italy. Levi-Montalcini and her family assumed different identities and lived with non-Jewish friends in Florence to survive the Holocaust. Despite all of this, Levi-Montalcini continued her work, dissecting chicken embryos from her hiding place until the end of the war.
"The discovery of NGF really changed the world in which we live, because now we knew that cells talk to other cells, and that they use soluble factors. It was hugely important."
A Post-War Discovery
Several years after the war, when Levi-Montalcini was once again working at the University of Turin, a German embryologist named Viktor Hamburger invited her to Washington University in St. Louis. Hamburger was impressed by Levi-Montalcini's research with her chicken embryos, and secured an opportunity for her to continue her work in America. The invitation would "change the course of my life," Levi-Montalcini would later recall.
During her fellowship, Montalcini grew tumors in mice and then transferred them to chick embryos in order to see how it would affect the chickens. To her surprise, she noticed that introducing the tumor samples would cause nerve fibers to grow rapidly. From this, Levi-Montalcini discovered and was able to isolate a protein that she determined was able to cause this rapid growth. She later named this Nerve Growth Factor, or NGF.
From there, Levi-Montalcini and her team launched new experiments to test NGF, injecting it and repressing it to see the effect it had in a test subject's body. When the team injected NGF into embryonic mice, they observed nerve growth, as well as the mouse pups developing faster – their eyes opening earlier and their teeth coming in sooner – than the untreated group. When the team purified the NGF extract, however, it had no effect, leading the team to believe that something else in the crude extract of NGF was influencing the growth of the newborn mice. Stanley Cohen, Levi-Montalcini's colleague, identified another growth factor called EGF – epidermal growth factor – that caused the mouse pups' eyes and teeth to grow so quickly.
Levi-Montalcini continued to experiment with NGF for the next several decades at Washington University, illuminating how NGF works in our body. When Levi-Montalcini injected newborn mice with an antiserum for NGF, for example, her team found that it "almost completely deprived the animals of a sympathetic nervous system." Other experiments done by Levi-Montalcini and her colleagues helped show the role that NGF plays in other important biological processes, such as the regulation of our immune system and ovulation.
"The discovery of NGF really changed the world in which we live, because now we knew that cells talk to other cells, and that they use soluble factors. It was hugely important," said Bill Mobley, Chair of the Department of Neurosciences at the University of California, San Diego School of Medicine.
Her Lasting Legacy
After years of setbacks, Levi-Montalcini's groundbreaking work was recognized in 1986, when she was awarded the Nobel Prize in Medicine for her discovery of NGF (Cohen, her colleague who discovered EGF, shared the prize). Researchers continue to study NGF even to this day, and the continued research has been able to increase our understanding of diseases like HIV and Alzheimer's.
Levi-Montalcini never stopped researching either: In January 2012, at the age of 102, Levi-Montalcini published her last research paper in the journal PNAS, making her the oldest member of the National Academy of Science to do so. Before she died in December 2012, she encouraged other scientists who would suffer setbacks in their careers to keep pursuing their passions. "Don't fear the difficult moments," Levi-Montalcini is quoted as saying. "The best comes from them."
COVID Variants Are Like “a Thief Changing Clothes” – and Our Camera System Barely Exists
Being able to track variants of concern in real time is crucial to our ability to stay ahead of the virus.
Whether it's "natural selection" as Darwin called it, or it's "mutating" as the X-Men called it, living organisms change over time, developing thumbs or more efficient protein spikes, depending on the organism and the demands of its environment. The coronavirus that causes COVID-19, SARS-CoV-2, is not an exception, and now, after the virus has infected millions of people around the globe for more than a year, scientists are beginning to see those changes.
The notorious variants that have popped up include B.1.1.7, sometimes called the UK variant, as well as P.1 and B.1.351, which seem to have emerged in Brazil and South Africa respectively. As vaccinations are picking up pace, officials are warning that now
is not the time to become complacent or relax restrictions because the variants aren't well understood.
Some appear to be more transmissible, and deadlier, while others can evade the immune system's defenses better than earlier versions of the virus, potentially undermining the effectiveness of vaccines to some degree. Genomic surveillance, the process of sequencing the genetic code of the virus widely to observe changes and patterns, is a critical way that scientists can keep track of its evolution and work to understand how the variants might affect humans.
"It's like a thief changing clothes"
It's important to note that viruses mutate all the time. If there were funding and personnel to sequence the genome of every sample of the virus, scientists would see thousands of mutations. Not every variant deserves our attention. The vast majority of mutations are not important at all, but recognizing those that are is a crucial tool in getting and staying ahead of the virus. The work of sequencing, analyzing, observing patterns, and using public health tools as necessary is complicated and confusing to those without years of specialized training.
Jeremy Kamil, associate professor of microbiology and immunology at LSU Health Shreveport, in Louisiana, says that the variants developing are like a thief changing clothes. The thief goes in your house, steals your stuff, then leaves and puts on a different shirt and a wig, in the hopes you won't recognize them. Genomic surveillance catches the "thief" even in those different clothes.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context.
Understanding variants, both the uninteresting ones and the potentially concerning ones, gives public health officials and researchers at different levels a useful set of tools. Locally, knowing which variants are circulating in the community helps leaders know whether mask mandates and similar measures should be implemented or discontinued, or whether businesses and schools can open relatively safely.
There's more to it than observing new variants
Analysis is complex, particularly when it comes to understanding which variants are of concern. "So the question is always if a mutation becomes common, is that a random occurrence?" says Phoebe Lostroh, associate professor of molecular biology at Colorado College. "Or is the variant the result of some kind of selection because the mutation changes some property about the virus that makes it reproduce more quickly than variants of the virus that don't have that mutation? For a virus, [mutations can affect outcomes like] how much it replicates inside a person's body, how much somebody breathes it out, whether the particles that somebody might breathe in get smaller and can lead to greater transmission."
Along with all of those factors, accurate and useful genomic surveillance requires an understanding of where variants are occurring, how they are related, and an examination of why they might be prevalent.
For example, if a potentially worrisome variant appears in a community and begins to spread very quickly, it's not time to raise a public health alarm until several important questions have been answered, such as whether the variant is spreading due to specific events, or if it's happening because the mutation has allowed the virus to infect people more efficiently. Kamil offered a hypothetical scenario to explain: Imagine that a member of a community became infected and the virus mutated. That person went to church and three more people were infected, but one of them went to a karaoke bar and while singing infected 100 other people. Examining the conditions under which the virus has spread is, therefore, an essential part of untangling whether a mutation itself made the virus more transmissible or if an infected person's behaviors contributed to a local outbreak.
One of the tricky things about variants is recognizing the point at which they move from interesting, to concerning at a local level, to dangerous in a larger context. Genomic sequencing can help with that, but only when it's coordinated. When the same mutation occurs frequently, but is localized to one region, it's a concern, but when the same mutation happens in different places at the same time, it's much more likely that the "virus is learning that's a good mutation," explains Kamil.
The process is called convergent evolution, and it was a fascinating topic long before COVID. Just as your heritage can be traced through DNA, so can that of viruses, and when separate lineages develop similar traits it's almost like scientists can see evolution happening in real time. A mutation to SARS-CoV-2 that happens in more than one place at once is a mutation that makes it easier in some way for the virus to survive and that is when it may become alarming. The widespread, documented variants P.1 and B.1.351 are examples of convergence because they share some of the same virulent mutations despite having developed thousands of miles apart.
However, even variants that are emerging in different places at the same time don't present the kind of threat SARS-CoV-2 did in 2019. "This is nature," says Kamil. "It just means that this virus will not easily be driven to extinction or complete elimination by vaccines." Although a person who has already had COVID-19 can be reinfected with a variant, "it is almost always much milder disease" than the original infection, Kamil adds. Rather than causing full-fledged disease, variants have the potiental to "penetrate herd immunity, spreading relatively quietly among people who have developed natural immunity or been vaccinated, until the virus finds someone who has no immunity yet, and that person would be at risk of hospitalization-grade severe disease or death."
Surveillance and predictions
According to Lostroh, genomic surveillance can help scientists predict what's going to happen. "With the British strain, for instance, that's more transmissible, you can measure how fast it's doubling in the population and you can sort of tell whether we should take more measures against this mutation. Should we shut things down a little longer because that mutation is present in the population? That could be really useful if you did enough sampling in the population that you knew where it was," says Lostroh. If, for example, the more transmissible strain was present in 50 percent of cases, but in another county or state it was barely present, it would allow for rolling lockdowns instead of sweeping measures.
Variants are also extremely important when it comes to the development, manufacture, and distribution of vaccines. "You're also looking at medical countermeasures, such as whether your vaccine is still effective, or if your antiviral needs to be updated," says Lane Warmbrod, a senior analyst and research associate at Johns Hopkins Center for Health Security.
Properly funded and extensive genomic surveillance could eventually help control endemic diseases, too, like the seasonal flu, or other common respiratory infections. Kamil says he envisions a future in which genomic surveillance allows for prediction of sickness just as the weather is predicted today. "It's a 51 for infection today at the San Francisco Airport. There's been detection of some respiratory viruses," he says, offering an example. He says that if you're a vulnerable person, if you're immune-suppressed for some reason, you may want to wear a mask based on the sickness report.
The U.S. has the ability, but lacks standards
The benefits of widespread genomic surveillance are clear, and the United States certainly has the necessary technology, equipment, and personnel to carry it out. But, it's not happening at the speed and extent it needs to for the country to gain the benefits.
"The numbers are improving," said Kamil. "We're probably still at less than half a percent of all the samples that have been taken have been sequenced since the beginning of the pandemic."
Although there's no consensus on how many sequences is ideal for a robust surveillance program, modeling performed by the company Illumina suggests about 5 percent of positive tests should be sequenced. The reasons the U.S. has lagged in implementing a sequencing program are complex and varied, but solvable.
Perhaps the most important element that is currently missing is leadership. In order to conduct an effective genomic surveillance program, there need to be standards. The Johns Hopkins Center for Health Security recently published a paper with recommendations as to what kinds of elements need to be standardized in order to make the best use of sequencing technology and analysis.
"Along with which bioinformatic pipelines you're going to use to do the analyses, which sequencing strategy protocol are you going to use, what's your sampling strategy going to be, how is the data is going to be reported, what data gets reported," says Warmbrod. Currently, there's no guidance from the CDC on any of those things. So, while scientists can collect and report information, they may be collecting and reporting different information that isn't comparable, making it less useful for public health measures and vaccine updates.
Globally, one of the most important tools in making the information from genomic surveillance useful is GISAID, a platform designed for scientists to share -- and, importantly, to be credited for -- their data regarding genetic sequences of influenza. Originally, it was launched as a database of bird flu sequences, but has evolved to become an essential tool used by the WHO to make flu vaccine virus recommendations each year. Scientists who share their credentials have free access to the database, and anyone who uses information from the database must credit the scientist who uploaded that information.
Safety, logistics, and funding matter
Scientists at university labs and other small organizations have been uploading sequences to GISAID almost from the beginning of the pandemic, but their funding is generally limited, and there are no standards regarding information collection or reporting. Private, for-profit labs haven't had motivation to set up sequencing programs, although many of them have the logistical capabilities and funding to do so. Public health departments are understaffed, underfunded, and overwhelmed.
University labs may also be limited by safety concerns. The SARS-CoV-2 virus is dangerous, and there's a question of how samples should be transported to labs for sequencing.
Larger, for-profit organizations often have the tools and distribution capabilities to safely collect and sequence samples, but there hasn't been a profit motive. Genomic sequencing is less expensive now than ever before, but even at $100 per sample, the cost adds up -- not to mention the cost of employing a scientist with the proper credentials to analyze the sequence.
The path forward
The recently passed COVID-19 relief bill does have some funding to address genomic sequencing. Specifically, the American Rescue Plan Act includes $1.75 billion in funding for the Centers for Disease Control and Prevention's Advanced Molecular Detection (AMD) program. In an interview last month, CDC Director Rochelle Walensky said that the additional funding will be "a dial. And we're going to need to dial it up." AMD has already announced a collaboration called the Sequencing for Public Health Emergency Response, Epidemiology, and Surveillance (SPHERES) Initiative that will bring together scientists from public health, academic, clinical, and non-profit laboratories across the country with the goal of accelerating sequencing.
Such a collaboration is a step toward following the recommendations in the paper Warmbrod coauthored. Building capacity now, creating a network of labs, and standardizing procedures will mean improved health in the future. "I want to be optimistic," she says. "The good news is there are a lot of passionate, smart, capable people who are continuing to work with government and work with different stakeholders." She cautions, however, that without a national strategy we won't succeed.
"If we maximize the potential and create that framework now, we can also use it for endemic diseases," she says. "It's a very helpful system for more than COVID if we're smart in how we plan it."
Recent leaps in technology represent an important step forward in unlocking artificial photosynthesis.
Since the beginning of life on Earth, plants have been naturally converting sunlight into energy. This photosynthesis process that's effortless for them has been anything but for scientists who have been trying to achieve artificial photosynthesis for the last half a century with the goal of creating a carbon-neutral fuel. Such a fuel could be a gamechanger — rather than putting CO2 back into the atmosphere like traditional fuels do, it would take CO2 out of the atmosphere and convert it into usable energy.
If given the option between a carbon-neutral fuel at the gas station and a fuel that produces carbon dioxide in spades -- and if costs and effectiveness were equal --who wouldn't choose the one best for the planet? That's the endgame scientists are after. A consumer switch to clean fuel could have a huge impact on our global CO2 emissions.
Up until this point, the methods used to make liquid fuel from atmospheric CO2 have been expensive, not efficient enough to really get off the ground, and often resulted in unwanted byproducts. But now, a new technology may be the key to unlocking the full potential of artificial photosynthesis. At the very least, it's a step forward and could help make a dent in atmospheric CO2 reduction.
"It's an important breakthrough in artificial photosynthesis," says Qian Wang, a researcher in the Department of Chemistry at Cambridge University and lead author on a recent study published in Nature about an innovation she calls "photosheets."
The latest version of the artificial leaf directly produces liquid fuel, which is easier to transport and use commercially.
These photosheets convert CO2, sunlight, and water into a carbon-neutral liquid fuel called formic acid without the aid of electricity. They're made of semiconductor powders that absorb sunlight. When in the presence of water and CO2, the electrons in the powders become excited and join with the CO2 and protons from the water molecules, reducing the CO2 in the process. The chemical reaction results in the production of formic acid, which can be used directly or converted to hydrogen, another clean energy fuel.
In the past, it's been difficult to reduce CO2 without creating a lot of unwanted byproducts. According to Wang, this new conversion process achieves the reduction and fuel creation with almost no byproducts.
The Cambridge team's new technology is a first and certainly momentous, but they're far from the only team to have produced fuel from CO2 using some form of artificial photosynthesis. More and more scientists are aiming to perfect the method in hopes of producing a truly sustainable, photosynthetic fuel capable of lowering carbon emissions.
Thanks to advancements in nanoscience, which has led to better control of materials, more successes are emerging. A team at the University of Illinois at Urbana-Champaign, for example, used gold nanoparticles as the photocatalysts in their process.
"My group demonstrated that you could actually use gold nanoparticles both as a light absorber and a catalyst in the process of converting carbon dioxide to hydrocarbons such as methane, ethane and propane fuels," says professor Prashant Jain, co-author of the study. Not only are gold nanoparticles great at absorbing light, they don't degrade as quickly as other metals, which makes them more sustainable.
That said, Jain's team, like every other research team working on artificial photosynthesis including the Cambridge team, is grappling with efficiency issues. Jain says that all parts of the process need to be optimized so the reaction can happen as quickly as possible.
"You can't just improve one [aspect], because that can lead to a decrease in performance in some other aspects," Jain explains.
The Cambridge team is currently experimenting with a range of catalysts to improve their device's stability and efficiency. Virgil Andrei, who is working on an artificial leaf design that was developed at Cambridge in 2019, was recently able to improve the performance and selectivity of the device. Now the leaf's solar-to-CO2 energy conversion efficiency is 0.2%, twice its previous efficiency.
The latest version also directly produces liquid fuel, which is easier to transport and use commercially.
In determining a method of fuel production's efficiency, one must consider how sustainable it is at every stage. That involves calculating whenever excess energy is needed to complete a step. According to Jain, in order to use CO2 for fuel production, you have to condense the CO2, which takes energy. And on the fuel production side, once the chemical reaction has created your byproducts, they need to be separated, which also takes energy.
To be truly sustainable, each part of the conversion system also needs to be durable. If parts need to be replaced often, or regularly maintained, that counts against it. Then you have to account for the system's reuse cycle. If you extract CO2 from the environment and convert it into fuel that's then put into a fuel cell, it's going to release CO2 at the other end. In order to create a fully green, carbon-neutral fuel source, that same amount of CO2 needs to be trapped and reintroduced back into the fuel conversion system.
"The cycle continues, and at each point, you will see a loss in efficiency, and depending on how much you [may also] see a loss in yield," says Jain. "And depending on what those efficiencies are at each one of those points will determine whether or not this process can be sustainable."
The science is at least a decade away from offering a competitive sustainable fuel option at scale. Streamlining a process to mimic what plants have perfected over billions of years is no small feat, but an ever-growing community of researchers using rapidly advancing technology is driving progress forward.