While biologists and chemists race to develop new antibiotics to combat constantly mutating bacteria, predicted to lead to 10 million deaths by 2050, engineers are approaching the problem through a different lens: finding naturally occurring antibiotics in the human genome.
The billions of base pairs in the genome are essentially one long string of code that contains the instructions for making all of the molecules the body needs. The most basic of these molecules are amino acids, the building blocks for peptides, which in turn combine to form proteins. However, there is still much to learn about how — and where — a particular set of instructions are encoded.
Now, bringing a computer science approach to a life science problem, an interdisciplinary team of Penn researchers have used a carefully designed algorithm to discover a new suite of antimicrobial peptides, hiding deep within this code.
The study, published in Nature Biomedical Engineering, was led by César de la Fuente, Presidential Assistant Professor in Bioengineering, Microbiology, Psychiatry, and Chemical and Biomolecular Engineering, spanning both Penn Engineering and Penn Medicine, and his postdocs Marcelo Torres and Marcelo Melo. Collaborators Orlando Crescenzi and Eugenio Notomista of the University of Naples Federico II also contributed to this work.
“The human body is a treasure trove of information, a biological dataset. By using the right tools, we can mine for answers to some of the most challenging questions,” says de la Fuente. “We use the word ‘encrypted’ to describe the antimicrobial peptides we found because they are hidden within larger proteins that seem to have no connection to the immune system, the area where we expect to find this function.”
In this guest post, recent Penn Bioengineering graduate and master’s student Casey Colleran writes about her experience in virtual internship at Janssen Pharmaceuticals.
Casey Colleran
During the summer of 2020, I was privileged enough to join the Global Regulatory Affairs team at Janssen Pharmaceutical Companies of Johnson & Johnson. Despite the uncertainties brought on by COVID-19, Janssen was able to bring together a group of five interns to participate in this virtual internship. This remote opportunity provided me with a valuable understanding of Regulatory Affairs, and the pharmaceutical industry. Throughout the 11 weeks, I was able to work alongside Regulatory Scientists in several functional areas of the organization. I learned about the regulations that govern the pharmaceutical industry, and the strategy that goes into communicating with the FDA and other health authorities.
As we rotated through each of these functional areas, myself and the other interns were also able to observe how the pandemic impacted the organization. We were asked to develop our own solutions on how to address these new challenges. Through this task, I learned how to present information in a meaningful way, analyze anecdotal data, improve processes, and communicate across different networks. As a team, myself and four other interns developed probing questions to help us understand how the COVID-19 pandemic has impacted the regulatory landscape, and the different strengths and opportunities employees observed in Janssen’s response to the pandemic. As we rotated through the different functional areas of Janssen’s Global Regulatory Affairs group, we used that time to ask our questions, and make note of anecdotal data that would provide us more insight as to how to address the new challenges brought on by the pandemic, and the virtual work environment. We then created a “COVID-19 Playbook” which broke down the main themes we had heard in our responses, such as the need for a more flexible organization, more efficient and effective communication, improved connectivity in the virtual workplace, and more. We developed suggestions on programming and guidelines that would help strengthen each of these areas, and presented these suggestions to the Senior Leadership Team.
Summer 2020 Janssen interns
Leadership development opportunities were also focal to the internship. I was paired with several amazing mentors who provided me with personalized feedback on how to become a more effective leader. The culture of the organization was extremely welcoming, and I cherish the relationships that I was able to build with my colleagues, so much so that I joined Janssen as a part time contractor this past year. Through this role as a contractor, I have been able to learn more about the day-to-day activities of a Regulatory Scientist through hands-on activities. As a contractor, I have been an integral part of a new “FLEx” Program. As a part of this program, I offer support to Regulatory Scientists by taking on their more routine submissions, giving them the opportunity to work on more strategic based activities, and focus on their personal growth and learning. It has been such a wonderful experience to work closely with these Regulatory Scientists who are still early in their career, as we have been able to learn from each other as well. It has also given me a greater understanding of the regulatory landscape, and by taking part in this new program I again get to see much of my feedback be considered and implemented.
I am so grateful that I had the opportunity to work in such an amazing environment, developed so many skills, and built a network that led me to additional opportunities in Regulatory Affairs at Janssen.
Electromagnetic fields are everywhere, and especially so in recent years. To most of us, those fields are undetectable. But a small number of people believe they have an actual allergy to electromagnetic fields. Ken Foster, a Professor Emeritus of Bioengineering, has heard these arguments before. “Activists would point to all these biological effects studies and say, ‘There must be some hazard’; health agencies would have meticulous reviews of literature and not see much of a problem.”
The Chan Zuckerberg Initiative’s Collaborative Pairs Pilot Project Award is part of its Neurodegeneration Challenge Network
Jennifer Phillips-Cremins, Ph.D.
More than 30 inherited disorders are caused by the unstable expansion of repetitive DNA sequences, including Huntington’s disease, ALS, Fragile X syndrome, and Friedreich’s ataxia. Jennifer E. Phillips-Cremins, associate professor in Penn Engineering’s Department of Bioengineering and in the Perelman School of Medicine’s Department of Genetics, has shown another link between these disorders: the location of these expanding genes relative to the complicated folding patterns the genome exhibits to fit inside the nucleus of a cell.
Now, Phillips-Cremins is among 60 researchers taking part in a $4.5 Million Chan Zuckerberg Initiative project that aims to apply novel, interdisciplinary approaches toward investigating neurodegenerative disorders. The CZI Collaborative Pairs Pilot Project will fund 30 teams that combine clinical and basic science expertise and have at least one early- or mid-career researcher.
Imagine if a computer could learn from molecules found in nature and use an algorithm to generate new ones. Then imagine those molecules could get printed and tested in a lab against some of the nastiest, most dangerous bacteria out there — bacteria quickly becoming resistant to our current antibiotic options.
Or consider a bandage that can sense an infection with fewer than 100 bacterial cells present in an open wound. What if that bandage could then send a signal to your phone letting you know an infection had started and asking you to press a button to trigger the release of the treatment therapy it contained?
These ideas aren’t science fiction. They’re projects happening right now, in various stages, in the lab of Penn synthetic biologist César de la Fuente, who joined the University as a Presidential Professor in May 2019. His ultimate goal is to develop the first computer-made antibiotics. But beyond that, his lab — which includes three postdoctoral fellows, a visiting professor, and a handful of graduate students and undergrads — has many other endeavors that sit squarely at the intersection of computer science and microbiology.
Computer-generated antibiotics
Antibiotic resistance is becoming a dangerous problem, both in the United States and worldwide. According to the Centers for Disease Control and Prevention, each year in the U.S., at least 2.8 million people get infections that antibiotics can’t help, and more than 35,000 die from those infections. Around the world, common ailments like pneumonia and food-borne illness are getting harder to treat.
De la Fuente earned his bachelor’s degree in biotechnology, then a doctorate in microbiology and immunology and a postdoc in synthetic biology and computational biology. Combining these fields led him to the innovative work his lab does today.
New antibiotics are needed, and according to de la Fuente, it’s time to look beyond the traditional approach.
“We’ve relied on nature as a source of antibiotics for many, many years. My whole hypothesis is that nature has perhaps run out of inspiration,” says de la Fuente, who has appointments in the Perelman School of Medicine and the School of Engineering and Applied Science. “We haven’t been able to discover any new scaffolds for many years. Can we digitize that information, nature’s chemistry, to be able to create and discover new molecules?”
To do that, his team turned to amino acids, the building blocks of protein molecules. The 20 that occur naturally bond in countless sequences and lengths, then fold to form different proteins. The sequencing possibilities are expansive, more than the number of stars in the universe. “We could never synthesize all of them and just see what happens,” says postdoc Marcelo Melo. “We have to combine the chemical knowledge — decades of chemistry on these tell us how they behave — with the computational side, because a computer can find patterns unlike any human could.”
Using machine learning, the researchers provide the computer with natural molecules that successfully work against bacteria. The computer learns from those examples, then generates new, artificial molecules. “We try this back and forth and hopefully we find patterns, new patterns that we can explore, instead of blindly searching,” Melo says.
The computer can then test each artificial sequence virtually, setting aside the most successful components and tossing the rest, in a form of computational natural selection. Those pieces with the highest potential get used to create new sequences, theoretically producing better and better ones each time.
De la Fuente’s team has seen some promising results already: “A lot of the molecules we’ve synthesized have worked,” he says. “The best ones worked in animal models. They were able to reduce infections in mice — which was pretty cool, given that the computer generated the whole thing.” Still, de la Fuente says the work is years away from producing anything close to a shelf-ready antibiotic.
When the immune system detects a foreign pathogen, a cascade of chemical signals call white blood cells to the scene. Neutrophils are the most common and abundant type of these cells and while they start accumulating at the site of an infection within minutes, they are essentially at the mercy of the circulatory system’s one-way flow of traffic to get them where they need to go.
Now, research from the University of Pennsylvania’s School of Engineering and Applied Science shows how these cells can be coaxed to fight the direction of blood flow, crawling upstream along the walls of veins and arteries.
The in vitro study suggested that this technique could get neutrophils to the sites of infections faster when they are restricted to the direction of blood flow.
Alexander Buffone and Daniel Hammer
Daniel A. Hammer, Alfred G. and Meta A. Ennis Professor in the Department of Bioengineering, and Alexander Buffone, Jr., a research associate in his lab, led the research. Nicholas R. Anderson, a graduate student in the Hammer lab, also contributed to the study.
The researchers’ experiments involved making synthetic tissues with artificial “cells.” The fibrin network that surrounds these beads pull on them when compressed; by changing the number of beads in their experimental tissues, the researchers could suss out how cell-fiber interplay contributes to the tissue’s overall properties.
Tissue gets stiffer when it’s compressed. That property can become even more pronounced with injury or disease, which is why doctors palpate tissue as part of a diagnosis, such as when they check for lumps in a cancer screening. That stiffening response is a long-standing biomedical paradox, however: tissue consists of cells within a complex network of fibers, and common sense dictates that when you push the ends of a string together, it loosens tension, rather than increasing it.
Now, in a study published in Nature, University of Pennsylvania’s School of Engineering and Applied Science researchers have solved this mystery by better understanding the mechanical interplay between that fiber network and the cells it contains.
The researchers found that when tissue is compressed, the cells inside expand laterally, pulling on attached fibers and putting more overall tension on the network. Targeting the proteins that connect cells to the surrounding fiber network might therefore be the optimal way of reducing overall tissue stiffness, a goal in medical treatments for everything from cancer to obesity.
Paul Janmey and Vivek Shenoy
The study was led by Paul Janmey, Professor in the Perelman School of Medicine’s Department of Physiology and in Penn Engineering’s Department of Bioengineering, and Vivek Shenoy, Eduardo D. Glandt President’s Distinguished Professor in Penn Engineering’s Department of Materials Science and Engineering, Mechanical Engineering and Applied Mechanics, and Bioengineering, along with Anne van Oosten and Xingyu Chen, graduate students in Janmey’s and Shenoy’s labs. Van Oosten is now a postdoctoral fellow at Leiden University in The Netherlands.
Shenoy is Director of Penn’s Center for Engineering Mechanobiology, which studies how physical forces influence the behavior of biological systems; Janmey is the co-director of one of the Center’s working groups, organized around the question, “How do cells adapt to and change their mechanical environment?”
Together, they have been interested in solving the paradox surrounding tissue stiffness.
