Once hailed as medical miracles, antibiotics are losing their effectiveness due to the rapid increase of bacterial immunity.
Researchers are scrambling to keep up with evolution, and they are currently exploring how machine learning can be applied to microbiology to develop more effective treatments.
In the past, researchers have studied bacteria behavior and used their findings to work against the natural patterns of bacterial life. In the 1980s, computer-assisted screening methods helped researchers in their efforts but few developments surfaced from their work. It seemed that there were no new antibiotics to be found using traditional methods, and pharmaceutical companies stepped away from funding antibiotic development in favor of more profitable drugs used to treat chronic conditions. But a new field of research shows a way forward, thanks to the massive advances in computing that have occurred over the intervening decades.
Among the pioneering researchers in this field is César de La Fuente, Presidential Assistant Professor in Psychiatry, Microbiology and Bioengineering. De La Fuente is accelerating the discovery of new antibiotics with his Drug Repurposing Hub, a library of more than 6,000 compounds that is using machine learning algorithms to seek out possible solutions for human disease. With his compound library, de La Fuente is able to examine drugs already approved by the FDA and hunt for new, more effective applications.
In addition to this work, de La Fuente and his colleagues are interested in using machine learning to innovate drug design itself. His lab uses a machine learning platform to generate new molecules in silico and perform experiments on them. Once the results of the experiments come in, they are fed back into the computer so the machine learning platform can continuously learn and improve its findings from the data.
In a recent interview with Katherine Harmon Courage in Quanta Magazine, de La Fuente said:
“The hypothesis is that nature has run out of inspiration in terms of providing us with new antibiotics. That’s why we think that machines … could diversify natural molecules to convert them to synthetic versions that would be much more effective.”
Originally posted on the Penn Engineering blog. Read more about de La Fuente’s work and other researchers exploring the computational design of new antibiotics in Quanta Magazine or The Atlantic.
Though the coronavirus situation is changing daily, even hourly, by now the need for physical separation from those not in your household is clear. That doesn’t mean it’s easy, says Penn psychologist Melissa Hunt.
“We’re social animals,” says Hunt, associate director of clinical training in Penn’s Psychology Department. “We have an entire neuroendocrine system that responds to touch and social proximity with people we care about, that contributes to our sense of well-being and connection in the world. Losing out on that is really hard.”
It’s also not something we’ve really been asked to do before, says Lyle Ungar, a Penn computer scientist who is part of the World Well-Being Project, an initiative that uses social media language to measure psychological well-being and physical health. “This is an experiment on a scale that we’ve never seen in the United States,” he says.
Ungar and Hunt offer some suggestions to stay positive and healthy in the face of this new social isolation.
1. Maintain a connection with the people you love, even if it can’t be a physical one.
“Social distance does not mean no social contact,” Ungar says. Psychologically, face-to-face conversations are best, but right now they’re not likely possible. Instead, Ungar suggests video calls. “They’re second best in terms of emotional bonding,” he says. “Phone calls aren’t as good as video chats, and texting is even worse. But of course, being totally isolated is the worst.”
A microscopic view of pancreatic adenocarcinoma. (Image: Emma Furth)
Swept up in a pancreatic cancer diagnosis is inevitably a sense of fear and sadness.
But at Penn, researchers are bringing new hope to this disease. And with patients like Nick Pifani, it’s clear that they’re moving in the right direction.
Pifani, from Delran, New Jersey, first noticed some lingering stomach upset in February 2017. He called his family doctor, concerned—especially given that he was an otherwise healthy marathon runner who was only 42. He was sent to a gastrointestinal specialist. A few weeks later, some crippling stomach pain sent him back to the emergency room and he received an MRI that showed a mass on his pancreas—Stage Three, inoperable, he was told.
He was treated with chemotherapy, along with radiation and, eventually, and after receiving advice from doctors at Penn, his tumor was removed. Thereafter, he realized he had a PALB2 mutation—a cousin of the BRCA gene mutation. At that moment, his long-term needs changed and he found himself seeking specialized care at Penn, where he met Kim Reiss Binder, assistant professor of medicine at the Hospital of the University of Pennsylvania (HUP).
“I’m a planner; I want to understand what [my] potential options are,” Pifani says. “[Reiss Binder] asked why I was there to see her and I explained and quickly I could tell she was—outside of her being remarkably intelligent—a great listener and a compassionate doctor.”
“I have a feeling she worries about me more than I do,” he laughs.
Pifani has now been in remission for two years and four months; he sees Reiss-Binder every three months for checkups. His survival story is inspiring and a sign of momentum, even if a world without pancreatic cancer is still frustratingly out of reach.
Pancreatic cancer at Penn
Pancreatic cancer is the third-leading cause of cancer-related death in the United States, outmatched only by lung cancer (No. 1) and colorectal cancer (No. 2). A person diagnosed with pancreatic cancer is still unlikely to survive past five years—only 9% of survivors do, giving it the highest mortality rate among every major cancer.
In short, pancreatic cancer seldom paves the way for optimistic narratives. Some of the hope that has surfaced, though, is thanks to some talent, dedication to the cause, and hard work at Penn.
A key point of progress in the battle against the disease was made in 2002, when former Assistant Professor of Medicine David Tuveson established a standard model for examining human development of this disease in mice. This model has allowed for a reliable way to study the disease and has influenced progress made here at Penn and elsewhere since.
“There’s been a burst of activity in translational research, from bench to bedside,” explains Ben Stanger, the Hanna Wise Professor in cancer research and director of the Penn Pancreatic Cancer Research Center (PCRC) at the Abramson Cancer Center.
“And there’s a lot of momentum with community building, a dramatic increase in patient volumes, and a dramatic increase in what we know about the cancer,” he says of the status of pancreatic cancer today.
Reiss Binder, meanwhile, explains that one mark of progress at Penn and beyond has been learning about people like Pifani, who have the PALB2 gene, and why they respond differently to treatments than those without it. Platinum-based chemotherapies, for example, are especially effective for people with the PALB2 gene who are battling pancreatic cancer. An ongoing trial at Penn has tested and found some success with using PARP inhibitors—taken orally as an enzyme that fixes single-stranded breaks of DNA—as a maintenance therapy in that same PALB2 demographic after they’ve had chemotherapy. These are less toxic than chemotherapy for patients with the same mutations.
It’s all been slow progress toward better treatments, but there has been progress.
“This is the tip of the iceberg for a disease that we historically have treated with perpetual chemotherapy,” Reiss Binder says. “We owe it to patients to find better options to suppress the cancer but not ruin their quality of life.”
Catching cancer earlier
The consensus on why pancreatic cancer is so deadly? It just can’t be spotted fast enough.
Pancreatic cancer often presents well after it has developed and metastasized, and does so in a way that is not easy to recognize as cancer. Common symptoms include, for example, stomach upset and back pain. And by the time a harder-to-ignore symptom of the cancer surfaces, a sort of yellowing of the skin (a result of a bile duct blockage), it’s likely too late to stop the cancer in its tracks.
One approach to improved detection being tested at Penn, by Research Assistant Professor of Medicine Erica Carpenter, is a liquid biopsy—drawn from a standard blood test. Current means to test for pancreatic cancer—imaging through an endoscopic tube—are invasive and expensive, meaning a common liquid test could transform how many cases are detected early.
Carpenter explains that circulating tumor cells (CTCs) can shed from a tumor that’s adjacent to the wall of a blood vessel; what’s shed then shows up in a blood test. The cells, if detected, can explain more about the nature of the tumor, giving doctors an opportunity to examine characteristics of cancerous cells and decide how to effectively treat a tumor if it can’t be surgically removed. It also allows interpretations of disease burden and the effectiveness of medications—through genome sequencing—that imaging does not.
Ultimately, this gives doctors the potential to track the growth of a tumor before it’s fully developed, all through one tube of blood—detected through an innovative use of technology.
David Issadore, Ph.D.
David Issadore, associate professor of bioengineering and electrical and systems engineering in the School of Engineering and Applied Science, has worked since 2017 to develop a chip that detects cancer in the blood, using machine learning to sort through literally hundreds of billions of vesicles and cells, looking for these CTCs. The chip retrieves data and the machine learning developed interprets that data, attempting to make a diagnosis that not only finds pancreatic cancer but also provides information about its progression—and, importantly, whether a patient might benefit from surgery.
Engheta, who also has appointments in the departments of Bioengineering and Materials Science and Engineering, is honored for pioneering contributions to optical metamaterials and nanoscale optics.
“The Born Award recognizes Nader Engheta’s exceptional contributions to the fields of metamaterials, transformation optics and nanophotonics,” said 2020 OSA President Stephen D. Fantone, founder and president of Optikos Corporation. “This honor is emblematic of the pioneering work he has done in near-zero index metamaterials.”
Danielle Bassett, J. Peter Skirkanich Professor of Bioengineering and Electrical and Systems Engineering, is a curious scientist.
Featured on a recent episode of “Choosing to be Curious” on WERA 96.7 Radio Arlington, Bassett discussed her work in studying curiosity and the potential neural mechanisms behind it. In her work, Bassett strives to re-conceptualize curiosity itself, defining it as not just seeking new bits information, but striving to understand the path through which those bits are connected.
Bassett is a pioneering researcher in the field of network science and how its tools can be applied to understand the brain. Now, Bassett and her research team are using the tools of network science and complex systems theory to uncover what common styles of curiosity people share and how individual styles differ. In addition, the team is exploring if there are canonical types of curiosity among humans or if each person’s curiosity architecture is unique.
This isn’t the first time Bassett has combined the tools of disparate fields to pursue her research. For as long as she can remember, Bassett has been insatiably curious and, while she was homeschooled as a child, she often wandered from one subject to the next and let her own interest guide her path. For Bassett, studying curiosity with the tools of physical, biology, and engineering is a natural step in her research journey.
In her interview with host Lynn Borton, Bassett says:
“What took me to curiosity is the observation that there’s a problem in defining the ways in which we search for knowledge. And that perhaps the understanding of curiosity could be benefitted by a scientific and mathematical approach. And that maybe the tools and conceptions that we have in mathematics and physics and other areas of science are useful for understanding curiosity. Which most people would consider to be more in the world of the humanities than the sciences….“Part of what I’m hoping to do is to illustrate that there are connections between disciplines that seem completely separate. Sometimes some of the best ideas in science are inspired not by a scientific result but by something else.”
To hear more about Bassett’s research on curiosity, listen to the full episode of Choosing to Be Curious.
While genetics and biochemistry research has dominated the conversation about how human bodies are formed, new research — with an old twist — is proposing that there is another star in the show of human development: mechanical forces.
At the turn of the twentieth century, medical research relied on simple mechanics to explain scientific phenomena, including how human cells morph into shape from embryo to newborn and beyond. As better chemistry techniques and DNA research burst onto the scene, however, the idea that cells could be affected by physical forces took a back seat. Now researchers are referring back to this vintage idea and bringing it into the 21st century.
Dennis Discher, Robert D. Bent Professor in the Departments of Chemical and Biomolecular Engineering, Bioengineering and Mechanical Engineering and Applied Mechanics, was featured in a recent article in Knowable Magazine for his research on the human heart and how mechanical forces exerted on heart cells give the vital organ its necessary stiffness during development.
One way to measure the success or influence of a researcher is to consider how many times they’re cited by other researchers. Every published paper requires a reference section listing relevant earlier papers, and the Web of Science Group keeps track of how many times different authors are cited over the course of a year.
Danielle Bassett, Ph.D.
In 2019, two members of the Penn Bioengineering department, Jason Burdick, Ph.D., and Danielle Bassett, Ph.D., were named Highly Cited Researchers, indicating that each of them placed within the top 1% of citations in their field based on the Web of Science’s index. For the past year, only 6,300 researchers were recognized with this honor, a number that makes up a mere 0.1% of researchers worldwide. Bassett’s lab looks at the use of knowledge, brain, and dynamic networks to understand bioengineering problems at a systems-level analysis, while Burdick’s lab focuses on advancements in tissue engineering through polymer design and development.
Jason Burdick, PhD
Burdick’s and Bassett’s naming to the list of Highly Cited Researchers demonstrates that their research had an outsized influence over current work in the field of bioengineering in the last year, and that new innovations continue to be developed from foundations these two Penn researchers created. To be included among such a small percentage of researchers worldwide indicates that Bassett and Burdick are sources of great impact and influence in bioengineering advancements today.
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.
An artist’s illustration of nanoparticles transporting mRNA into a T cell (blue), allowing the latter to express surface receptors that recognize cancer cells (red). (Credit: Ryan Allen, Second Bay Studios)
New cancer immunotherapies involve extracting a patient’s T cells and genetically engineering them so they will recognize and attack tumors. This type of therapy is not without challenges, however. Engineering a patient’s T cells is laborious and expensive. And when successful, the alterations to the immune system immediately make patients very sick for a short period of time, with symptoms including fever, nausea and neurological effects.
Now, Penn researchers have demonstrated a new engineering technique that, because it is less toxic to the T cells, could enable a different mechanism for altering the way they recognize cancer, and could have fewer side effects for patients.
The technique involves ferrying messenger RNA (mRNA) across the T cell’s membrane via a lipid-based nanoparticle, rather than using a modified HIV virus to rewrite the cell’s DNA. Using the former approach would be preferable, as it only confers a temporary change to the patient’s immune system, but the current standard method for getting mRNA past the cell membrane can be too toxic to use on the limited number of T cells that can be extracted from a patient.
Michael Mitchell, Margaret Billingsley, and Carl June
The researchers demonstrated their technique in a study published in the journal Nano Letters. It was led by Michael Mitchell, Skirkanich Assistant Professor of Innovation of bioengineering in the School of Engineering and Applied Science, and Margaret Billingsley, a graduate student in his lab.
They collaborated with one of the pioneers of CAR T therapy: Carl June, the Richard W. Vague Professor in Immunotherapy and director of the Center for Cellular Immunotherapies in the Abramson Cancer Center and the director of the Parker Institute for Cancer Immunotherapy at the Perelman School of Medicine.
We would like to congratulate Assistant Professor in Bioengineering Alex Hughes, Ph.D., on receiving the Maximizing Investigators’ Research Award (MIRA) from the National Institutes of Health (NIH), which funds investigators to create flexible and forward-thinking research programs. Hughes is the first recipient of this award in Penn’s School of Engineering and Applied Science, marking a major accomplishment for him and his lab.
The award recognizes Hughes’ efforts to create new tools used for tissue engineering, in particular by fusing concepts from developmental biology into tissue construction efforts. Hughes believes this approach will have impacts on fundamental understanding human disease, leading to new strategies to combat them. Hughes and his lab specifically focus on kidney disease. As Hughes says, “defects in the kidney and urinary tract account for up to a third of all birth defects.” Furthermore, because kidney development involves many different kinds of cell interactions, there’s a gap in understanding exactly how these defects occur.
Unlike other grants that focus on funding projects, the MIRA prioritizes the people behind the research, giving them funding as a sign of faith in the future work they’ll choose to do. “The MIRA has allowed us significant leeway to integrate several complementary approaches here,” Hughes says. Because of this flexibility, Hughes and his lab thinks it will allow them to reach for more innovative and risky approaches in their research, in the hopes that this will lead to a better understanding of kidney defects and modes of treatment for them.
