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Artificial Intelligence Accurately Predicts Protein Folding

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Caption: Researchers used artificial intelligence to map hundreds of new protein structures, including this 3D view of human interleukin-12 (blue) bound to its receptor (purple). Credit: Ian Haydon, University of Washington Institute for Protein Design, Seattle

Proteins are the workhorses of the cell. Mapping the precise shapes of the most important of these workhorses helps to unlock their life-supporting functions or, in the case of disease, potential for dysfunction. While the amino acid sequence of a protein provides the basis for its 3D structure, deducing the atom-by-atom map from principles of quantum mechanics has been beyond the ability of computer programs—until now. 

In a recent study in the journal Science, researchers reported they have developed artificial intelligence approaches for predicting the three-dimensional structure of proteins in record time, based solely on their one-dimensional amino acid sequences [1]. This groundbreaking approach will not only aid researchers in the lab, but guide drug developers in coming up with safer and more effective ways to treat and prevent disease.

This new NIH-supported advance is now freely available to scientists around the world. In fact, it has already helped to solve especially challenging protein structures in cases where experimental data were lacking and other modeling methods hadn’t been enough to get a final answer. It also can now provide key structural information about proteins for which more time-consuming and costly imaging data are not yet available.

The new work comes from a group led by David Baker and Minkyung Baek, University of Washington, Seattle, Institute for Protein Design. Over the course of the pandemic, Baker’s team has been working hard to design promising COVID-19 therapeutics. They’ve also been working to design proteins that might offer promising new ways to treat cancer and other conditions. As part of this effort, they’ve developed new computational approaches for determining precisely how a chain of amino acids, which are the building blocks of proteins, will fold up in space to form a finished protein.

But the ability to predict a protein’s precise structure or shape from its sequence alone had proven to be a difficult problem to solve despite decades of effort. In search of a solution, research teams from around the world have come together every two years since 1994 at the Critical Assessment of Structure Prediction (CASP) meetings. At these gatherings, teams compete against each other with the goal of developing computational methods and software capable of predicting any of nature’s 200 million or more protein structures from sequences alone with the greatest accuracy.

Last year, a London-based company called DeepMind shook up the structural biology world with their entry into CASP called AlphaFold. (AlphaFold was one of Science’s 2020 Breakthroughs of the Year.) They showed that their artificial intelligence approach—which took advantage of the 170,000 proteins with known structures in a reiterative process called deep learning—could predict protein structure with amazing accuracy. In fact, it could predict most protein structures almost as accurately as other high-resolution protein mapping techniques, including today’s go-to strategies of X-ray crystallography and cryo-EM.

The DeepMind performance showed what was possible, but because the advances were made by a world-leading deep learning company, the details on how it worked weren’t made publicly available at the time. The findings left Baker, Baek, and others eager to learn more and to see if they could replicate the impressive predictive ability of AlphaFold outside of such a well-resourced company.

In the new work, Baker and Baek’s team has made stunning progress—using only a fraction of the computational processing power and time required by AlphaFold. The new software, called RoseTTAFold, also relies on a deep learning approach. In deep learning, computers look for patterns in large collections of data. As they begin to recognize complex relationships, some connections in the network are strengthened while others are weakened. The finished network is typically composed of multiple information-processing layers, which operate on the data to return a result—in this case, a protein structure.

Given the complexity of the problem, instead of using a single neural network, RoseTTAFold relies on three. The three-track neural network integrates and simultaneously processes one-dimensional protein sequence information, two-dimensional information about the distance between amino acids, and three-dimensional atomic structure all at once. Information from these separate tracks flows back and forth to generate accurate models of proteins rapidly from sequence information alone, including structures in complex with other proteins.

As soon as the researchers had what they thought was a reasonable working approach to solve protein structures, they began sharing it with their structural biologist colleagues. In many cases, it became immediately clear that RoseTTAFold worked remarkably well. What’s more, it has been put to work to solve challenging structural biology problems that had vexed scientists for many years with earlier methods.

RoseTTAFold already has solved hundreds of new protein structures, many of which represent poorly understood human proteins. The 3D rendering of a complex showing a human protein called interleukin-12 in complex with its receptor (above image) is just one example. The researchers have generated other structures directly relevant to human health, including some that are related to lipid metabolism, inflammatory conditions, and cancer. The program is now available on the web and has been downloaded by dozens of research teams around the world.

Cryo-EM and other experimental mapping methods will remain essential to solve protein structures in the lab. But with the artificial intelligence advances demonstrated by RoseTTAFold and AlphaFold, which has now also been released in an open-source version and reported in the journal Nature [2], researchers now can make the critical protein structure predictions at their desktops. This newfound ability will be a boon to basic science studies and has great potential to speed life-saving therapeutic advances.

References:

[1] Accurate prediction of protein structures and interactions using a three-track neural network. Baek M, DiMaio F, Anishchenko I, Dauparas J, Grishin NV, Adams PD, Read RJ, Baker D., et al. Science. 2021 Jul 15:eabj8754.

[2] Highly accurate protein structure prediction with AlphaFold. Jumper J, Evans R, Pritzel A, Green T, Senior AW, Kavukcuoglu K, Kohli P, Hassabis D. et al. Nature. 2021 Jul 15.

Links:

Structural Biology (National Institute of General Medical Sciences/NIH)

The Structures of Life (NIGMS)

Baker Lab (University of Washington, Seattle)

CASP 14 (University of California, Davis)

NIH Support: National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences


Celebrating the Fourth with Neuroscience Fireworks

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There’s so much to celebrate about our country this Fourth of July. That includes giving thanks to all those healthcare providers who have put themselves in harm’s way to staff the ERs, hospital wards, and ICUs to care for those afflicted with COVID-19, and also for everyone who worked so diligently to develop, test, and distribute COVID-19 vaccines.

These “shots of hope,” created with rigorous science and in record time, are making it possible for a great many Americans to gather safely once again with family and friends. So, if you’re vaccinated (and I really hope you are—because these vaccines have been proven safe and highly effective), fire up the grill, crank up the music, and get ready to show your true red, white, and blue colors. My wife and I—both fully vaccinated—intend to do just that!

To help get the celebration rolling, I’d like to share a couple minutes of some pretty amazing biological fireworks. While the track of a John Philip Sousa march is added just for fun, what you see in the video above is the result of some very serious neuroscience research that is scientifically, as well as visually, breath taking. Credit for this work goes to an NIH-supported team that includes Ricardo Azevedo and Sunil Gandhi, at the Center for the Neurobiology of Learning and Memory, University of California, Irvine, and their collaborator Damian Wheeler, Translucence Biosystems, Irvine, CA. Azevedo is also an NIH National Research Service Award fellow and a Medical Scientist Training Program trainee with Gandhi.

The team’s video starts off with 3D, colorized renderings of a mouse brain at cellular resolution. About 25 seconds in, the video flashes to a bundle of nerve fibers called the fornix. Thanks to the wonders of fluorescent labeling combined with “tissue-clearing” and other innovative technologies, you can clearly see the round cell bodies of individual neurons, along with the long, arm-like axons that they use to send out signals and connect with other neurons to form signaling circuits. The human brain has nearly 100 trillion of these circuits and, when activated, they process incoming sensory information and provide outputs that lead to our thoughts, words, feelings, and actions.

As shown in the video, the nerve fibers of the fornix provide a major output pathway from the hippocampus, a region of the brain involved in memory. Next, we travel to the brain’s neocortex, the outermost part of the brain that’s responsible for complex behaviors, and then move on to explore an intricate structure called the corticospinal tract, which carries motor commands to the spinal cord. The final stop is the olfactory tubercle —towards the base of the frontal lobe—a key player in odor processing and motivated behaviors.

Azevedo and his colleagues imaged the brain in this video in about 40 minutes using their imaging platform called the Translucence Biosystems’ Mesoscale Imaging System™. This process starts with a tissue-clearing method that eliminates light-scattering lipids, leaving the mouse brain transparent. From there, advanced light-sheet microscopy makes thin optical sections of the tissue, and 3D data processing algorithms reconstruct the image to high resolution.

Using this platform, researchers can take brain-wide snapshots of neuronal activity linked to a specific behavior. They can also use it to trace neural circuits that span various regions of the brain, allowing them to form new hypotheses about the brain’s connectivity and how such connectivity contributes to memory and behavior.

The video that you see here is a special, extended version of the team’s first-place video from the NIH-supported BRAIN Initiative’s 2020 “Show Us Your BRAINS!” imaging contest. Because of the great potential of this next-generation technology, Translucence Biosystems has received Small Business Innovation Research grants from NIH’s National Institute of Mental Health to disseminate its “brain-clearing” imaging technology to the neuroscience community.

As more researchers try out this innovative approach, one can only imagine how much more data will be generated to enhance our understanding of how the brain functions in health and disease. That is what will be truly spectacular for everyone working on new and better ways to help people suffering from Alzheimer’s disease, Parkinson’s disease, schizophrenia, autism, epilepsy, traumatic brain injury, depression, and so many other neurological and psychiatric disorders.

Wishing all of you a happy and healthy July Fourth!

Links:

Brain Research Through Advancing Innovative Neurotechnologies® (BRAIN) Initiative (NIH)

NIH National Research Service Award

Medical Scientist Training Program (National Institute of General Medical Sciences/NIH)

Small Business Innovation Research and Small Business Technology Transfer (NIH)

Translucence Biosystems (Irvine, CA)

Sunil Gandhi (University of California, Irvine)

Ricardo Azevedo (University of California, Irvine)

Video: iDISCO-cleared whole brain from a Thy1-GFP mouse (Translucence Biosystems)

Show Us Your BRAINs! Photo & Video Contest (Brain Initiative/NIH)

NIH Support: National Institute of Mental Health; National Eye Institute


Protein Mapping Study Reveals Valuable Clues for COVID-19 Drug Development

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One way to fight COVID-19 is with drugs that directly target SARS-CoV-2, the novel coronavirus that causes the disease. That’s the strategy employed by remdesivir, the only antiviral drug currently authorized by the U.S. Food and Drug Administration to treat COVID-19. Another promising strategy is drugs that target the proteins within human cells that the virus needs to infect, multiply, and spread.

With the aim of developing such protein-targeted antiviral drugs, a large, international team of researchers, funded in part by the NIH, has precisely and exhaustively mapped all of the interactions that take place between SARS-CoV-2 proteins and the human proteins found within infected host cells. They did the same for the related coronaviruses: SARS-CoV-1, the virus responsible for outbreaks of Severe Acute Respiratory Syndrome (SARS), which ended in 2004; and MERS-CoV, the virus that causes the now-rare Middle East Respiratory Syndrome (MERS).

The goal, as reported in the journal Science, was to use these protein “interactomes” to uncover vulnerabilities shared by all three coronaviruses. The hope is that the newfound knowledge about these shared proteins—and the pathways to which they belong—will inform efforts to develop new kinds of broad-spectrum antiviral therapeutics for use in the current and future coronavirus outbreaks.

Facilitated by the Quantitative Biosciences Institute Research Group, the team, which included David E. Gordon and Nevan Krogan, University of California, San Francisco, and hundreds of other scientists from around the world, successfully mapped nearly 400 protein-protein interactions between SARS-CoV-2 and human proteins.

You can see one of these interactions in the video above. The video starts out with an image of the Orf9b protein of SARS-CoV-2, which normally consists of two linked molecules (blue and orange). But researchers discovered that Orf9b dissociates into a single molecule (orange) when it interacts with the human protein TOM70 (teal). Through detailed structural analysis using cryo-electron microscopy (cryo-EM), the team went on to predict that this interaction may disrupt a key interaction between TOM70 and another human protein called HSP90.

While further study is needed to understand all the details and their implications, it suggests that this interaction may alter important aspects of the human immune response, including blocking interferon signals that are crucial for sounding the alarm to prevent serious illness. While there is no drug immediately available to target Orf9b or TOM70, the findings point to this interaction as a potentially valuable target for treating COVID-19 and other diseases caused by coronaviruses.

This is just one intriguing example out of 389 interactions between SARS-CoV-2 and human proteins uncovered in the new study. The researchers also identified 366 interactions between human and SARS-CoV-1 proteins and 296 for MERS-CoV. They were especially interested in shared interactions that take place between certain human proteins and the corresponding proteins in all three coronaviruses.

To learn more about the significance of these protein-protein interactions, the researchers conducted a series of studies to find out how disrupting each of the human proteins influences SARS-CoV-2’s ability to infect human cells. These studies narrowed the list to 73 human proteins that the virus depends on to replicate.

Among them were the receptor for an inflammatory signaling molecule called IL-17, which has been suggested as an indicator of COVID-19 severity. Two other human proteins—PGES-2 and SIGMAR1—were of particular interest because they are targets of existing drugs, including the anti-inflammatory indomethacin for PGES-2 and antipsychotics like haloperidol for SIGMAR1.

To connect the molecular-level data to existing clinical information for people with COVID-19, the researchers looked to medical billing data for nearly 740,000 Americans treated for COVID-19. They then zeroed in on those individuals who also happened to have been treated with drugs targeting PGES-2 or SIGMAR1. And the results were quite striking.

They found that COVID-19 patients taking indomethacin were less likely than those taking an anti-inflammatory that doesn’t target PGES-2 to require treatment at a hospital. Similarly, COVID-19 patients taking antipsychotic drugs like haloperidol that target SIGMAR1 were half as likely as those taking other types of antipsychotic drugs to require mechanical ventilation.

More research is needed before we can think of testing these or similar drugs against COVID-19 in human clinical trials. Yet these findings provide a remarkable demonstration of how basic molecular and structural biological findings can be combined with clinical data to yield valuable new clues for treating COVID-19 and other viral illnesses, perhaps by repurposing existing drugs. Not only is NIH-supported basic science essential for addressing the challenges of the current pandemic, it is building a strong foundation of fundamental knowledge that will make us better prepared to deal with infectious disease threats in the future.

Reference:

[1] Comparative host-coronavirus protein interaction networks reveal pan-viral disease mechanisms. Gordon DE et al. Science. 2020 Oct 15:eabe9403.

Links:

Coronavirus (COVID-19) (NIH)

Krogan Lab (University of California, San Francisco)

NIH Support: National Institute of Allergy and Infectious Diseases; National Institute of Neurological Disorders and Stroke; National Institute of General Medical Sciences


Discussing the Long Arc of Discovery with NIH’s Newest Nobelist

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Discussion with Dr. Harvey Alter

It’s been a tough year for our whole world because of everything that’s happening as a result of the coronavirus disease 2019 (COVID-19) pandemic. Yet there are bright spots that still shine through, and this week brought some fantastic news about NIH-supported researchers being named 2020 Nobel Prize Laureates for their pioneering work in two important fields: Chemistry and Physiology or Medicine.

In the wee hours of Wednesday morning, NIH grantee Jennifer A. Doudna, a biochemist at the University of California, Berkeley, got word that she and Emmanuelle Charpentier, a microbiologist at the Max Planck Institute for Infection Biology, Berlin, Germany, had won the 2020 Nobel Prize in Chemistry for developing the CRISPR/cas approach to genome editing. Doudna has received continuous NIH funding since 1997, mainly from the National Institute of General Medical Sciences and National Human Genome Research Institute.

The CRISPR/cas system, which consists of a short segment of RNA attached to the cas enzyme, provides the ability to make very precise changes in the sequence, or spelling, of the genetic instruction books of humans and other species. If used to make non-heritable edits in relevant tissues, such technology holds enormous potential to treat or even cure a wide range of devastating diseases, including thousands of genetic disorders where the DNA misspelling is precisely known.

Just two days before Doudna learned of her big award, a scientist who’s spent almost his entire career at the NIH campus in Bethesda, MD, received news that he too was getting a Nobel—the 2020 Nobel Prize in Physiology or Medicine. Harvey Alter, a senior scholar in the NIH Clinical Center’s Transfusion Medicine Department, was recognized for his contributions in identifying the potentially deadly hepatitis C virus. He shares this year’s prize with Michael Houghton, now with University of Alberta, Edmonton, and Charles M. Rice, The Rockefeller University, New York, who’s received continuous NIH funding since 1987, mainly from the National Institute of Allergy and Infectious Diseases.

In a long arc of discovery rooted in basic, translational, and clinical research that spanned several decades, Alter and his colleagues doggedly pursued biological clues that at first led to tests, then life-saving treatments, and, today, the very real hope of eradicating the global health threat posed by hepatitis C infections.

We at NIH are particularly proud of the fact that Alter is the sixth Nobel Prize winner—and the first in 26 years—to have done the entirety of his award-winning research in our Intramural Research Program. So, I jumped at the opportunity to talk with Harvey on NIH’s Facebook Live and Twitter chats just hours after he got the good news on Monday. Here’s a condensed version of our conversation, which took place on the NIH campus, but at a safe physical distance to minimize the risk of COVID-19 spread.

Collins: Harvey, let me start off by asking, how did you find out you’d won the Nobel Prize?

Alter: At 4:15 this morning. I was asleep and heard the telephone ringing. I ignored it. Five minutes later, I got another call. Now, I’m getting kind of perturbed. But I ignored it, thinking the call must be some kind of solicitation. Then, the phone rang a third time. I answered it, prepared to tell the person on the other end not to call me anymore. I heard a man’s voice say, “I’m the Secretary General of the Nobel Prize, calling you from Stockholm.” At that point, I just froze.

Collins: Did you think it might be a hoax?

Alter: No, I didn’t think it was a hoax. But I wasn’t expecting to win the prize. I knew about three years ago that I’d been on a Nobel list. But it didn’t happen, and I just forgot about it. Truthfully, I didn’t know that today was the day that the announcement was being made. The news came as a complete shock.

Collins: Please say a few words about viral hepatitis. What is it?

Alter: Sure. Viral hepatitis is an infection of the liver that causes inflammation and can lead to scarring, or cirrhosis. Early in my career, two viruses were known to cause the disease. One was the hepatitis A virus. You got it from consuming contaminated water or food. The second was the hepatitis B virus, which has a blood-borne transmission, typically from blood transfusions. In the 1970s, we realized that some other agent was causing most of the hepatitis from blood transfusions. Since it wasn’t A and it wasn’t B, we cleverly decided to call it: non-A, non-B. We did that because we hadn’t yet proven that the causative agent was a virus.

Collins: So, even though you screened donor units for the hepatitis B virus to eliminate tainted blood, people were still getting hepatitis from blood transfusions. How did you go about trying to solve this mystery?

Alter: The main thing was to follow patients prospectively, meaning forward in time. We drew a blood sample before they were transfused, and then serially afterwards. We saved those samples and also the donor samples to compare them. Using a liver function test, we found that 30 percent of patients who had open heart surgery at NIH prior to 1970 developed liver abnormalities indicative of hepatitis. That’s 1 in 3 people.

We then looked for the reasons. We found the main one was our source of blood. We were buying blood, which was then in short supply, from commercial laboratories. It turned out that their paid donors were engaging in high-risk behaviors [Note: like IV drug users sharing hypodermic needles]. We immediately stopped using these laboratories, and, through various other measures, we got the rate down to around 4 percent in 1987.

That’s when Michael Houghton, then at Chiron Corp. and a co-recipient of this year’s prize, cloned the virus. Think about it, he and his colleagues looked at 6 million clones and found just one that reacted with the convalescent serum of a patient with non-A, non-B. In other words, having contracted the virus, the patient already made antibodies against it that were present in the serum. If that one clone came from the virus, the antibodies in the serum would recognize it. They did, and Chiron then developed an assay to detect antibodies to the virus.

Collins: And that’s when they contacted you.

Alter: Yes, they wanted to use our panel of patient blood samples that had fooled a lot of people who claimed to have developed a non-A, non-B assay. Nobody else had “broken” this panel, but the Chiron Corp. did. We found that every case of non-A, non-B was really hepatitis C, the agent that they had cloned. Hepatitis C was the missing piece. As far as we could tell, there were no other agents beside hepatitis B and C that would result in transfusion transmission of the disease.

Collins: This story is clearly one of persistence. So, say something about persistence as an important characteristic of a scientist. You’re a great example of someone who was always looking out for opportunities that might not have seemed so promising at first.

Alter: I first learned persistence from Dr. Baruch Blumberg, my first NIH mentor who discovered the hepatitis B virus in 1967. [Note: Other NIH researchers identified the hepatitis A virus in 1977] The discovery started when we found this “Australian antigen,” a molecular structure that the immune system recognizes as foreign and attacks. It was a serendipitous finding that could have been easily just dropped. But he just kept at it, kept at it, kept at it. He had this famous wall where he diagrammed his hypotheses with all the contingencies if one worked or failed. Then, all of a sudden, the antigen was associated with hepatitis B. It became the basis of the hepatitis B vaccine, which is highly effective and used throughout the world. Dr. Blumberg won the Nobel Prize for his work on the hepatitis B virus in 1976.

Collins: Sometimes people look at NIH and ask why we don’t focus all of our efforts on curing a particular disease. I keep answering, ‘Wait a moment, we don’t know enough to know how to do that.’ What’s the balance that we ought to be seeking between basic research and clinical applications?

Alter: There is this tendency now to pursue highly directed research to solve a problem. That’s certainly how biopharma works. They want a payoff. The NIH is different. It’s a place where you can pursue your scientific interests, wherever they lead. The NIH leadership understands that the details of a problem often aren’t obvious at first. Researchers need to be allowed to observe things and then to pursue their leads as far as possible, with the understanding that not everything will work out. I think it’s very important to keep this basic research component in parallel with the more clinical applications. In the case of hepatitis C, it started as a clinical problem that led to a basic research investigation, which led back to a clinical problem. It was bedside-to-bench-to-bedside.

Collins: Are people still getting infected with hepatitis C?

Alter: Yes, hepatitis C remains a global problem. Seventy million people have contracted the virus, though the majority are generally asymptomatic, meaning they don’t get sick from it. Instead, they carry around the virus for decades without knowing it. That’s because the hepatitis C virus likes to persist, and our immune system doesn’t seem to be able to get rid of it easily.

However, some of those infected will have bad outcomes, such as cirrhosis or cancer of the liver. But there’s no way of knowing who will and who won’t get sick over time. The trick now is to identify people when they’re asymptomatic and without obvious disease.

That involves testing. We’re in a unique position with hepatitis C, where we have great tests that are highly sensitive and very specific to the virus. We also have great treatments. We can cure everybody who is tested and found to be positive.

Collins: People may be surprised to hear that. Here is a chronic viral illness, for which we actually have a cure. That’s come along fairly recently. Say a bit more about that—it’s such a great story of success.

Alter: For many years, the only treatment for hepatitis C was interferon, a very difficult treatment that initially had only about a 6 percent cure rate. With further progress, it got up to around 50 percent. But the big breakthrough came in the late 1990s when Gilead Corp., having the sequenced genome of the hepatitis C virus, deduced what it needs to replicate. If we know what it needs and we interfere with that, we can stop the replication. Gilead came out with a blockbuster drug that, now in combination with another drug, aims at two different sites on the virus and cures at least 98 percent of people. It’s an oral therapy taken for only 12 weeks, sometimes as little as 8 weeks, and with virtually no side-effects. It’s like a miracle drug.

Collins: What would you say to somebody who is thinking about becoming a scientist? How do you pick an area of research that will be right for you?

Alter: It’s a tough question. Medical research is very difficult, but there’s nothing more rewarding than doing something for patients and to see a good outcome like we had with hepatitis C.

The best path forward is to work for somebody who’s already an established investigator and a good teacher. Work in his or her lab for a few years and get involved in a project. I’ve learned not get into a lot of projects. Get into something where you can become the expert and pursue it.
The other thing is to collaborate. There’s no way that one person can do everything these days. You need too much technology and lots of different areas of expertise.

Collins: You took on a high-risk project in which you didn’t know that you’d find the answer. What’s the right balance between a project that you know will be productive, and something that might be risky, but, boy, if it works, could be transformative? How did you decide which of those paths to go?

Alter: I don’t think I decided. I just went! But there were interim rewards. Finding that the paid donors were bad was a reward and it had a big impact. And the different donor testing, decreasing the amount of blood [transfused], there were all kinds of steps along the way that gave you a reward. Now, did I think that there would be a treatment, an eradication of post-transfusion hepatitis at the end of my line? No, I didn’t.

And it wouldn’t have happened if it was only me. I just got the ball rolling. But it needed Houghton’s group. It needed the technology of Charlie Rice, a co-recipient of this year’s Nobel Prize. It needed joint company involvement. So, it required massive cooperation, and I have to say that here at NIH, Bob Purcell did most of the really basic work in his lab. Patrizia Farci, my closest collaborator, does things that I can’t do. You just need people who have a different expertise.

Collins: Harvey, it’s been maybe six hours since you found out that you won the Nobel Prize. How are you going to spend the rest of your day?

Alter: Well, I have to tell you a story that just happened. We had a press conference earlier today at NIH. Afterwards, I wanted to return to my NIH office and the easiest route was through the parking garage across the street from where we held the press conference. When I entered the garage, a security guard said, “You can’t come in, you haven’t been screened for COVID.” I assured him that I had been screened when I drove onto the NIH campus. He repeated that I had to go around to the front of the building to get screened.

Finally, I said to him, “Would it make any difference if I told you that I won the Nobel Prize today?” He replied, ‘That’s nice, but you must go around to the front of the building.’” So, winning the Nobel doesn’t give you immediate rewards!

Collins: Let me find that security guard and give him a bonus for doing a good job. Well, Harvey, will there be that trip to Stockholm coming up in December?

Alter: Not this year. I’ve heard that they will invite us to Stockholm next year to receive the award. But there’s going to be something in the US. I don’t know what it will be. I’ll invite you.

Collins: I will be glad to take part in the celebration. Well, Harvey, I really want to thank you for taking some time on this special day to reflect on your career and how the Nobel Committee came calling at 4:30 this morning. We’re really proud of you!

Alter: Thank you.

Links:

Hepatitis C (National Institute of Diabetes and Digestive and Kidney Diseases/NIH)

The Nobel Assembly at Karolinska Institutet has today decided to award the 2020 Nobel Prize in Physiology or Medicine jointly to Harvey J. Alter, Michael Houghton and Charles M. Rice for the discovery of Hepatitis C virus,” Nobel Prize announcement, October 5,2020.

Harvey Alter (Clinical Center/NIH)

The Road Not Taken, or How I Learned to Love the Liver: A Personal Perspective on Hepatitis History” Alter HJ, Hepatology. 2014 Jan;59(1):4-12.

Reflections on the History of HCV: A Posthumous Examination.” Alter HJ, Farci P, Bukh J, Purcell RH. Clinical Liver Disease, 15:1, Feb 2020.

Is Elimination of Hepatitis B and C a Pipe Dream or Reality?” Alter HJ, Chisari FV. Gastroenterology. 2019 Jan;156(2):294-296.

Michael Houghton (University of Alberta, Edmonton)

Charles Rice (The Rockefeller University, New York)

What is genome editing? (National Human Genome Research Institute/NIH)

Jennifer Doudna (University of California, Berkeley)

Emmanuelle Charpentier (Max Planck Institute for Infection Biology, Berlin, Germany)


Electricity-Conducting Bacteria May Inspire Next-Gen Medical Devices

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Nanowires
Credit: Edward H. Egelman

Technological advances with potential for improving human health sometimes come from the most unexpected places. An intriguing example is an electricity-conducting biological nanowire that holds promise for powering miniaturized pacemakers and other implantable electronic devices.

The nanowires come from a bacterium called Geobacter sulfurreducens, shown in the electron micrograph above. This rod-shaped microbe (white) was discovered two decades ago in soil collected from an unlikely place: a ditch outside of Norman, Oklahoma. The bug can conduct electricity along its arm-like appendages, and, in the hydrocarbon-contaminated, oxygen-depleted soil in which it lives, such electrical inputs and outputs are essentially the equivalent of breathing.

Scientists fascinated with G. sulfurreducens thought that its electricity had to be flowing through well-studied microbial appendages called pili. But, as the atomic structure of these nanowires (multi-colors, foreground) now reveals, these nanowires aren’t pili at all! Instead, the bacteria have manufactured unique submicroscopic arm-like structures. These arms consist of long, repetitive chains of a unique protein, each surrounding a core of iron-containing molecules.

The surprising discovery, published in the journal Cell, was made by an NIH-funded team involving Edward Egelman, University of Virginia Health System, Charlottesville. Egelman’s lab has had a long interest in what’s called a type 4 pili. These strong, adhering appendages help certain infectious bacteria enter tissues and make people sick. In fact, they enable bugs like Neisseria meningitidis to cross the blood-brain barrier and cause potentially deadly bacterial meningitis. While other researchers had proposed that those same type 4 pili allowed G. sulfurreducens to conduct electricity, Egelman wasn’t so sure.

So, he took advantage of recent advances in cryo-electron microscopy, which involves flash-freezing molecules at extremely low temperatures before bombarding them with electrons to capture their images with a special camera. The cryo-EM images allowed his team to nail down the atomic structure of the nanowires, now called OmcS filaments.

Using those images and sophisticated bioinformatics, Egelman and team determined that OmcS proteins uniquely fit into the nanowires’ long repetitive chains, spacing their iron-bearing cores at regular intervals to transfer electrons and convey electricity. In fact, bacteria unable to produce OmcS proteins make filaments that conduct electricity 100 times less efficiently.

With these cryo-EM structures in hand, Egelman says his team will continue to explore their conductive properties. Such knowledge might someday be used to build biologically-inspired nanowires, measuring 1/100,000th the width of a human hair, to connect miniature electronic devices directly to living tissues. This is one more example of how nature’s ability to invent is pretty breathtaking—surely one wouldn’t have predicted the discovery of nanowires in a bacterium that lives in contaminated ditches.

Reference:

[1] Structure of Microbial Nanowires Reveals Stacked Hemes that Transport Electrons over Micrometers. Wang F, Gu Y, O’Brien JP, Yi SM, Yalcin SE, Srikanth V, Shen C, Vu D, Ing NL, Hochbaum AI, Egelman EH, Malvankar NS. Cell. 2019 Apr 4;177(2):361-369.

Links:

Electroactive microorganisms in bioelectrochemical systems. Logan BE, Rossi R, Ragab A, Saikaly PE. Nat Rev Microbiol. 2019 May;17(5):307-319.

High Resolution Electron Microscopy (National Cancer Institute/NIH)

Egelman Lab (University of Virginia, Charlottesville)

NIH Support: National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases; Common Fund


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