Largest-Ever Antibiotic Discovery Effort Uses AI to Uncover Potential Cures in Microbial Dark Matter

by Eric Horvath

Credit: Georgina Joyce

Almost a century ago, the discovery of antibiotics like penicillin revolutionized medicine by harnessing the natural bacteria-killing abilities of microbes. Today, a new study co-led by researchers at the Perelman School of Medicine at the University of Pennsylvania suggests that natural-product antibiotic discovery is about to accelerate into a new era, powered by artificial intelligence (AI).

The study, published in Cell, the researchers used a form of AI called machine learning to search for antibiotics in a vast dataset containing the recorded genomes of tens of thousands of bacteria and other primitive organisms. This unprecedented effort yielded nearly one million potential antibiotic compounds, with dozens showing promising activity in initial tests against disease-causing bacteria.

“AI in antibiotic discovery is now a reality and has significantly accelerated our ability to discover new candidate drugs. What once took years can now be achieved in hours using computers” said study co-senior author César de la Fuente, PhD, a Presidential Assistant Professor in Psychiatry, Microbiology, Chemistry, Chemical and Biomolecular Engineering, and Bioengineering.

Nature has always been a good place to look for new medicines, especially antibiotics. Bacteria, ubiquitous on our planet, have evolved numerous antibacterial defenses, often in the form of short proteins (“peptides”) that can disrupt bacterial cell membranes and other critical structures. While the discovery of penicillin and other natural-product-derived antibiotics revolutionized medicine, the growing threat of antibiotic resistance has underscored the urgent need for new antimicrobial compounds.

In recent years, de la Fuente and colleagues have pioneered AI-powered searches for antimicrobials. They have identified preclinical candidates in the genomes of contemporary humans, extinct Neanderthals and Denisovans, woolly mammoths, and hundreds of other organisms. One of the lab’s primary goals is to mine the world’s biological information for useful molecules, including antibiotics.

Read the full story in Penn Medicine News.

How “Invitations” from Penn Medicine Restored Mammogram Completion Rates

by Frank Otto

The first few waves of COVID-19 slowed life across the United States, affecting everything from attending school to eating out for dinner and going on vacation. Segments of health care were also affected: Services that were not considered immediately crucial to fighting the virus were slowed or stopped during the pandemic’s first wave.  

But once Penn Medicine invited patients back to resume normal health care—including preventive care, like screenings for disease—there was some lag in numbers. 

“As we opened up to routine outpatient care, screening rates for situations when patients didn’t have symptoms were not returning back to normal,” said Mitchell Schnall, MD, PhD, FACR, a professor of Radiology, now the senior vice president for Data and Technology Solutions at Penn Medicine, and then the head of a team focused on the “resurgence” efforts to ease patients back into outpatient care. “Although a short delay in health screening is likely not going to cause long-term health problems, we were concerned whether screening rates would stay lower and lead to a long-term impact.”  

Read the full story in Penn Medicine News.

Mitchell Schnall is a member of the Penn Bioengineering Graduate Group.

Different Brain Structures in Females Lead to More Severe Cognitive Deficits After Concussion Than Males

by Kelsey Geesler

Top: Axons in female and male subject brains Bottom: damaged axons in male and female brains after injury (Credit: Penn Medicine)

Important brain structures that are key for signaling in the brain are narrower and less dense in females, and more likely to be damaged by brain injuries, such as concussion. Long-term cognitive deficits occur when the signals between brain structures weaken due to the injury. The structural differences in male and female brains might explain why females are more prone to concussions and experience longer recovery from the injury than their male counterparts, according to a preclinical study led by the Perelman School of Medicine at the University of Pennsylvania, published this week in Acta Neuropathologica.

Each year, approximately 50 million individuals worldwide suffer a concussion, also referred to as mild traumatic brain injury (TBI). However, there is nothing “mild” about this condition for the more than 15 percent of individuals who suffer persisting cognitive dysfunction, which includes difficulty concentrating, learning and remembering new information, and making decisions.

Although males make up the majority of emergency department visits for concussion, this has been primarily attributed to their greater exposure to activities with a risk of head impacts compared to females. In contrast, it has recently been observed that female athletes have a higher rate of concussion and appear to have worse outcomes than their male counterparts participating in the same sport.

“Clinicians have observed for a long time that females suffer from concussion at higher rates than males in the same sports, and that they take longer to recover cognitive function, but couldn’t explain the underlying mechanisms of this phenomenon,” said senior author Douglas Smith, MD, a professor of Neurosurgery and director of Penn’s Center for Brain Injury and Repair. “The variances in brain structures of females and males not only illuminate why this disparity exists, but also exposes biomarkers, such as axon protein fragments, that can be measured in the blood to determine injury severity, monitor recovery, and eventually help identify and develop treatments that help patients repair these damaged structures and restore cognitive function.”

Read the full story in Penn Medicine News.

Douglas H. Smith is a member of the Penn Bioengineering Graduate Group.

The CiPD Partners with the Mack Institute for Innovation and Management to Develop Tooth-Brushing Robots

by Melissa Pappas

Left to right: Hong-Huy Tran, Chrissie Jaruchotiratanasakul, Manali Mahajan (Photo Courtesy of CiPD)

The Center for Innovation and Precision Dentistry (CiPD), a collaboration between Penn Engineering and Penn Dental Medicine, has partnered with Wharton’s Mack Institute for Innovation Management on a research project which brings robotics to healthcare. More specifically, this project will explore potential uses of nanorobot technology for oral health care. The interdisciplinary partnership brings together three students from different Penn programs to study the commercialization of a new technology that detects and removes harmful dental plaque.

“Our main goal is to bring together dental medicine and engineering for out-of-the-box solutions to address unresolved problems we face in oral health care,” says Hyun (Michel) Koo, Co-Founding Director of CiPD and Professor of Orthodontics. “We are focused on affordable solutions and truly disruptive technologies, which at the same time are feasible and translatable.”

Read the full story in Penn Engineering Today.

Michel Koo is a member of the Penn Bioengineering Graduate Group. Read more stories featuring Koo in the BE Blog.

To learn more about this interdisciplinary research, please visit CiPD.

This press release has been adapted from the original published by the Mack Institute for Innovation Management.

Sonura Named Among 2023 PHL Inno Under 25 Honorees

Gabriella Daltoso, Sophie Ishiwari, Gabriela Cano, Caroline Amanda Magro, and Tifara Eliana Boyce

A team of recent Penn Bioengineering graduates have been included in list of prominent young Philadelphia innovators as chosen by The Philadelphia Business Journal and PHL Inno.

Gabriella Daltoso, Sophie Ishiwari, Gabriela Cano, Caroline Amanda Magro, and Tifara Eliana Boyce founded Sonura as their Senior Design Project in Bioengineering. The team, who all graduated in 2023, picked up a competitive President’s Innovation Prize for their beanie that promotes the cognitive and socioemotional development of newborns in the NICU by protecting them from the auditory hazards of their environments while fostering parental connection. Now, they have been included in the list of fourteen Inno Under 25 honorees for 2023.

“To determine this year’s list, the Philadelphia Business Journal and PHL Inno sought nominations from the public and considered candidates put forth by our editorial team. To be considered, nominees must be 25 years of age or younger and work for a company based in Greater Philadelphia and/or reside in the region.

Honorees span a wide range of industries, including consumer goods, biotechnology and environmental solutions. Many are products of the region’s colleges and universities, though some studied farther afield before setting up shop locally.”

Read “Announcing the 2023 PHL Inno Under 25 honorees” and “Inno Under 25” in PHL Inno. Penn affiliates can subscribe through Penn’s library services.

Penn Bioengineers Recommend Improvements to Science Communication

Three graduate students in Bioengineering have collaborated to craft a list of recommendations to improve science communication during national health emergencies.

Doctoral students Miles J. Arnett, Dimitris Boufidis, and Melanie Hilman are part of the Penn Science Policy and Diplomacy Group (PSPDG), student organization which creates opportunities for students to get hands-on experience in Science Policy, Diplomacy, and Communication.

Their brief reviews the public health response to the COVID-19 pandemic and recommends specific improvements to science policy and communication by national scientific institutions:

The public health response to the pandemic was dramatically weakened by an uncoordinated communication strategy, inconsistent messaging, and fractured media environments. These shortcomings had a real human cost, with an estimated hundreds of thousands of Americans dying as a consequence of high rates of vaccine hesitancy. Now, in the aftermath of the pandemic, we have a chance to learn from this crisis and develop a more robust science communication infrastructure for future health emergencies.

Read “From Chaos to Clarity: Reinventing Science Communication After COVID-19” at Medium.

Student Spotlight: Cosette Tomita

Cosette TomitaCosette Tomita, a master’s student in Bioengineering, spoke with Penn Engineering Graduate Admissions about her research in cellular therapy and her path to Penn Engineering.

“What were you doing before you came to Penn Engineering? 

After college I wanted to get some industry experience before going to graduate school, so I spent a year working for a pharmaceutical company in New Jersey. I learned a lot—but mostly I learned that I wanted to go back into academia. So I was looking for a more research-oriented position to boost my graduate school applications, and I found a position at Penn’s cyclotron facility. Shortly after that, I applied to the master’s program. I’m still working at the cyclotron, so I’m doing the program part time. 

How has your experience in the program been so far? 

I love the research I’m doing here. I love the collaboration we have and the fact that I’m able to work with whoever I want to. And I can only say good things about my PI, Robert Mach. He’s a very busy man, but he makes time for his people. And he recognizes when somebody has a lot on their plate and he will go to bat for that person.

What’s your research all about? 

The focus of my PI’s lab is on neurodegenerative diseases and opiate use, so we’re looking to make imaging agents and antagonists that can help with the opioid crisis. 

For my project, I wanted to look at treating neurodegenerative disease from the perspective of cellular therapy. My PI doesn’t have that expertise, so when I came to him with this idea, he said I should talk to Mark Sellmyer in the bioengineering department. He does a lot of cellular therapies, cell engineering, protein engineering and things of that nature. So his lab is more biological. 

I don’t have a grant for my research, so my advisors are supporting it out of their own pockets. They could have said, no, you need to work on this project that’s already going on in the lab. But they gave me the intellectual freedom to do what I wanted to do.”

Read the full Q&A at the Penn Engineering Graduate Admissions website.

Mark Sellmeyer is Assistant Professor of Radiology in the Perelman School of Medicine and member of the Penn Bioengineering Graduate Group.

Cesar de la Fuente On the “Next Frontier” of Antibiotics

César de la Fuente
César de la Fuente

In a recent CNN feature, César de la Fuente, Presidential Assistant Professor in Bioengineering, Psychiatry, Microbiology, and in Chemical and Biomolecular Engineering commented on a study about a new type of antibiotic that was discovered with artificial intelligence:

“I think AI, as we’ve seen, can be applied successfully in many domains, and I think drug discovery is sort of the next frontier.”

The de la Fuente lab uses machine learning and biology to help prevent, detect, and treat infectious diseases, and is pioneering the research and discovery of new antibiotics.

Read “A new antibiotic, discovered with artificial intelligence, may defeat a dangerous superbug” in CNN Health.

Penn Bioengineering Graduate Student on T Cell Therapy Improvements

Image: Courtesy of Penn Medicine News

 Neil Sheppard,  Adjunct Associate Professor of Pathology and Laboratory Medicine in the Perelman School of Medicine, and David Mai, a Bioengineering graduate student in the School of Engineering and Applied Science, explained the findings of their recent study, which offered a potential strategy to improve T cell therapy in solid tumors, to the European biotech news website Labiotech.

Mai is a graduate student in the lab of Carl H. June, the Richard W. Vague Professor in Immunotherapy in Penn Medicine, Director of the Center for Cellular Immunotherapies (CCI) at the Abramson Cancer Center, and member of the Penn Bioengineering Graduate Group.

Read “Immunotherapy in the fight against solid tumors” in Labiotech.

Read more about this collaborative study here.

Folding@Home: How You, and Your Computer, Can Play Scientist

by

Greg Bowman kneels, working on a server.
Folding@home is led by Gregory Bowman, a Penn Integrates Knowledge Professor who has appointments in the Departments of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science. (Image: Courtesy of Penn Medicine News)

Two heads are better than one. The ethos behind the scientific research project Folding@home is that same idea, multiplied: 50,000 computers are better than one.

Folding@home is a distributed computing project which is used to simulate protein folding, or how protein molecules assemble themselves into 3-D shapes. Research into protein folding allows scientists to better understand how these molecules function or malfunction inside the human body. Often, mutations in proteins influence the progression of many diseases like Alzheimer’s disease, cancer, and even COVID-19.

Penn is home to both the computer brains and human minds behind the Folding@home project which, with its network, forms the largest supercomputer in the world. All of that computing power continually works together to answer scientific questions such as what areas of specific protein implicated in Parkinson’s disease may be susceptible to medication or other treatment.

Led by Gregory Bowman, a Penn Integrates Knowledge professor of Biochemistry and Biophysics in the Perelman School of Medicine who has joint appointments in the Department of Biochemistry and Biophysics in the Perelman School of Medicine and the Department of Bioengineering in the School of Engineering and Applied Science, Folding@home is open for any individual around the world to participate in and essentially volunteer their computer to join a huge network of computers and do research.

Using the network hub at Penn, Bowman and his team assign experiments to each individual computer which communicates with other computers and feeds info back to Philly. To date, the network is comprised of more than 50,000 computers spread across the world.

“What we do is like drawing a map,” said Bowman, explaining how the networked computers work together in a type of system that experts call Markov state models. “Each computer is like a driver visiting different places and reporting back info on those locations so we can get a sense of the landscape.”

Individuals can participate by signing up and then installing software to their standard personal desktop or laptop. Participants can direct the software to run in the background and limit it to a certain percentage of processing power or have the software run only when the computer is idle.

When the software is at work, it’s conducting unique experiments designed and assigned by Bowman and his team back at Penn. Users can play scientist and watch the results of simulations and monitor the data in real time, or they can simply let their computer do the work while they go about their lives.

Read the full story at Penn Medicine News.