Moving Away From ‘Average,’ Toward the Individual

by Michele W. Berger

In a course from Annenberg’s David Lydon-Staley, seven graduate students conducted single-participant experiments. This approach, what’s known as an “n of 1,” may better capture the nuances of a diverse population than randomized control trials can.

David Lydon-Staley is an assistant professor of communication and principal investigator of the Addiction, Health, & Adolescence Lab in the Annenberg School for Communication.

To prep for an upcoming course he was teaching, Penn researcher David Lydon-Staley decided to conduct an experiment: Might melatonin gummies—supplements touted to improve sleep—help him, as an individual, fall asleep faster?

For two weeks, he took two gummies on intervention nights and none on control nights. The point, however, wasn’t really to find out whether the gummies worked for him (which they didn’t), but rather to see how an experiment with a single participant played out, what’s known as an “n of 1.”

Randomized control experiments typically include hundreds or thousands of participants. Their aim is to show, on average, how the intervention being studied affects people in the treatment group. But often “there’s a failure to include women and members of minoritized racial and ethnic groups in those clinical trials,” says Lydon-Staley, an assistant professor in the Annenberg School for Communication. “The single-case approach says, instead of randomizing a lot of people, we’re going to take one person at a time and measure them intensively.”

In Lydon-Staley’s spring semester class, Diversity and the End of Average, seven graduate students conducted their own n-of-1 experiments—on themselves—testing whether dynamic stretching might improve basketball performance or whether yoga might decrease stress. One wanted to understand the effect of journaling on emotional clarity. They also learned about representation in science, plus which analytical approaches might best capture the nuance of a diverse population and individuals with many intersecting identities.

“It’s not just an ‘n of 1’ trying to do what the big studies are doing. It’s a different perspective,” says Lydon-Staley. “Though it’s just one person, you’re getting a much more thorough characterization of how they’re changing from moment to moment.”

Read the full story in Penn Today.

David Lydon-Staley is an Assistant Professor of communication and principal investigator of the Addiction, Health, & Adolescence Lab in the Annenberg School for Communication at the University of Pennsylvania. Lydon-Staley is a former postdoctoral research in the Complex Systems Lab of Dani S. Bassett, J. Peter Skirkanich Professor in Bioengineering and in Electrical and Systems Engineering.

Penn Engineers Secure Wellcome Leap Contract for Lipid Nanoparticle Research Essential in Delivery of RNA Therapies

by Melissa Pappas

The Very Large Scale Microfluidic Integration (VLSMI) platform, a technology developed by the Penn researchers, contains hundreds of mixing channels for mass-producing mRNA-carrying lipid nanoparticles.

Penn Engineering secured a multi-million-dollar contract with Wellcome Leap under the organization’s $60 million RNA Readiness + Response (R3) program, which is jointly funded with the Coalition for Epidemic Preparedness Innovations (CEPI). Penn Engineers aim to create “on-demand” manufacturing technology that can produce a range of RNA-based vaccines.

The Penn Engineering team features Daeyeon Lee, Evan C Thompson Term Chair for Excellence in Teaching and Professor in Chemical and Biomolecular Engineering, Michael Mitchell, Skirkanich Assistant Professor of Innovation in Bioengineering, David Issadore, Associate Professor in Bioengineering and Electrical and Systems Engineering, and Sagar Yadavali, a former postdoctoral researcher in the Issadore and Lee labs and now the CEO of InfiniFluidics, a spinoff company based on their research. Drew Weissman of the Perelman School of Medicine, whose foundational research directly continued to the development of mRNA-based COVID-19 vaccines, is also a part of this interdisciplinary team.

The success of these COVID-19 vaccines has inspired a fresh perspective and wave of research funding for RNA therapeutics across a wide range of difficult diseases and health issues. These therapeutics now need to be equitably and efficiently distributed, something currently limited by the inefficient mRNA vaccine manufacturing processes which would rapidly translate technologies from the lab to the clinic.

Read more in Penn Engineering Today.

Newly Discovered ‘Encrypted Peptides’ Found in Human Plasma Exhibit Antibiotic Properties

by Melissa Pappas

The antimicrobial peptides the researchers studied are “encrypted” in that they are contained within Apolipoprotein B, a blood plasma protein that is not directly involved in the immune response, but are not normally expressed on their own.

The rise of drug-resistant bacteria infections is one of the world’s most severe global health issues, estimated to cause 10 million deaths annually by the year 2050. Some of the most virulent and antibiotic-resistant bacterial pathogens are the leading cause of life-threatening, hospital-acquired infections, particularly dangerous for immunocompromised and critically ill patients. Traditional and continual synthesis of antibiotics will simply not be able to keep up with bacteria evolution.

To avoid the continual process of synthesizing new antibiotics to target bacteria as they evolve, Penn Engineers have looked at a new, natural resource for antibiotic molecules.

César de la Fuente, Ph.D.

A recent study on the search for encrypted peptides with antimicrobial properties in the human proteome has located naturally occurring antibiotics within our own bodies. By using an algorithm to pinpoint specific sequences in our protein code, a team of Penn researchers along with collaborators, led by César de la Fuente, Presidential Assistant Professor in Psychiatry, Bioengineering, Microbiology, and Chemical and Biomolecular Engineering, and Marcelo Torres, a post doc in de la Fuente’s lab, were able to locate novel peptides, or amino acid chains, that when cleaved, indicated their potential to fend off harmful bacteria.

Now, in a new study published in ACS Nano, the team along with Angela Cesaro, the lead author and post doc in de la Fuente’s lab, have identified three distinct antimicrobial peptides derived from a protein in human plasma and demonstrate their abilities in mouse models. Angela Cesaro performed a great part of the activities during her PhD under the supervision of corresponding author, Professor Angela Arciello, from the University of Naples Federico II. The collaborative study also includes Utrecht University in the Netherlands.

“We identified the cardiovascular system as a hot spot for potential antimicrobials using an algorithmic approach,” says de la Fuente. “Then we looked closer at a specific protein in the plasma.”

Read the full story in Penn Engineering Today.

A New Way to Profile T Cells Can Aid in Personalized Immunotherapy

by Melissa Pappas

A scanning electron micrograph of a healthy human T cell. A better understanding the wide variety of antigen receptors that appear on the surfaces of these critical components of the immune system is necessary for improving a new class of therapies. (Credit: NIAID)

Our bodies are equipped with specialized white blood cells that protect us from foreign invaders, such as viruses and bacteria. These T cells identify threats using antigen receptors, proteins expressed on the surface of individual T cells that recognize specific amino acid sequences found in or on those invaders. Once a T cell’s antigen receptors bind to the corresponding antigen, it can directly kill infected cells or call for backup from the rest of the immune system.

We have hundreds of billions of T cells, each with unique receptors that recognize unique antigens, so profiling this T cell antigen specificity is essential in our understanding of the immune response. It is especially critical in developing targeted immunotherapies, which equip T cells with custom antigen receptors that recognize threats they would otherwise miss, such as the body’s own mutated cancer cells.

Jenny Jiang, Ph.D.

Jenny Jiang, Peter and Geri Skirkanich Associate Professor of Innovation in Bioengineering, along with lab members and colleagues at the University of Texas, Austin, recently published a study in Nature Immunology that describes their technology, which simultaneously provides information in four dimensions of T cell profiling. Ke-Yue Ma and Yu-Wan Guo, a former post doc and current graduate student in Jiang’s Penn Engineering lab, respectively, also contributed to this study.

This technology, called TetTCR-SeqHD, is the first to provide such detailed information about single T cells in a high-throughput manner, opening doors for personalized immune diagnostics and immunotherapy development.

There are many pieces of information needed to comprehensively understand the immune response of T cells, and gathering all of these measurements simultaneously has been a challenge in the field. Comprehensive profiling of T cells includes sequencing the antigen receptors, understanding how specific those receptors are in their recognition of invading antigens, and understanding T cell gene and protein expression. Current technologies only screen for one or two of these dimensions due to various constraints.

“Current technologies that measure T cell immune response all have limitations,” says Jiang. “Those that use cultured or engineered T cells cannot tell us about their original phenotype, because once you take a cell out of the body to culture, its gene and protein expression will change. The technologies that address T cell and antigen sequencing with mass spectrometry damage genetic information of the sample. And current technologies that do provide information on antigen specificity use a very expensive binding ligand that can cost more than a thousand dollars per antigen, so it is not feasible if we want to look at hundreds of antigens. There is clearly room for advancement here.”

The TetTCR-SeqHD technology combines Jiang’s previously developed T cell receptor sequencing tool, TetTCR-Seq, described in a Nature Biotechnology paper published in 2018, with the new ability of characterizing both gene and protein expression.

Read the full story in Penn Engineering Today.

César de La Fuente Uses AI to Discover Germ-fighting Peptides

César de la Fuente, PhD

The impending danger of bacterial resistance to antibiotics is well-documented within the scientific community. Bacteria are the most efficient evolvers, and their ability to develop tolerance to drugs, in addition to antibiotic overuse and misuse, means that researchers have had to get particularly resourceful to ensure the future of modern medicine.  

Presidential Assistant Professor in Bioengineering, Microbiology, Psychiatry, and Chemical and Biomolecular Engineering César de la Fuente and his team are using an algorithm to search the human genome for microbe-fighting peptides. So far, the team has synthesized roughly 55 peptides that, when tested against popular drug-resistant microbes such as the germ responsible for staph infections, have proven to prevent bacteria from replicating.  

WIRED’s Max G. Levy recently spoke with de la Fuente and postdoctoral researcher and study collaborator Marcelo Torres about the urgency of the team’s work, and why developing these solutions is critical to the survival of civilization as we know it. The team’s algorithm, based on pattern recognition software used to analyze images, makes an otherwise insurmountable feat tangible.  

De la Fuente’s lab specializes in using AI to discover and design new drugs. Rather than making some all-new peptide molecules that fit the bill, they hypothesized that an algorithm could use machine learning to winnow down the huge repository of natural peptide sequences in the human proteome into a select few candidates.

“We know those patterns—the multiple patterns—that we’re looking for,” says de la Fuente. “So that allows us to use the algorithm as a search function.”

Read Max G. Levy’s An AI Finds Superbug-Killing Potential in Human Proteins” at WIRED. 

This story previously appeared in Penn Engineering Today.

Yogesh Goyal Selected as 2021 STAT Wunderkind

Yogesh Goyal, Ph.D.

Yogesh Goyal, Ph.D.,  a postdoctoral researcher in Genetics and Bioengineering, has been selected as a 2021 STAT Wunderkind, which honors the “next generation of scientific superstars.” Goyal’s research is centered around developing novel mathematical and experimental frameworks to study how a rare subpopulation of cancer cells are able to survive drug therapy and develop resistance, resulting in relapse in patients. In particular, his work provides a view of different paths that single cancer cells take when becoming resistant, at unprecedented resolution and scale. This research aims to help devise novel therapeutic strategies to combat the challenge of drug resistance in cancer.

Goyal is a Jane Coffin Childs Postdoctoral Fellow in the systems biology lab of Arjun Raj, Professor in Bioengineering and Genetics at Penn. He will begin an appointment as Assistant Professor in the Department of Cell and Developmental Biology (CDB) in the Feinberg School of Medicine at Northwestern University in spring 2022.

Read the announcement in Penn Medicine News.

Penn Researchers Show ‘Encrypted’ Peptides Could be Wellspring of Natural Antibiotics

by Melissa Pappas

César de la Fuente, Ph.D.

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.”

Read the full story in Penn Engineering Today.

BE Seminar: “Phage and Robotics-Assisted Biomolecular Evolution” (Emma Chory)

Emma Chory, Ph.D.

Speaker: Emma Chory, Ph.D.
Postdoctoral Fellow
Sculpting Evolution Laboratory
Massachusetts Institute of Technology

Date: Thursday, October 21, 2021
Time: 3:30-4:30 PM EDT
Zoom – check email for link or contact
Room: Moore 216

Abstract: Evolution occurs when selective pressures from the environment shape inherited variation over time. Within the laboratory, evolution is commonly used to engineer proteins and RNA, but experimental constraints have limited our ability to reproducibly and reliably explore key factors such as population diversity, the timing of environmental changes, and chance. We developed a high-throughput system for the analytical exploration of molecular evolution using phage-based mutagenesis to evolve many distinct classes of biomolecules simultaneously. In this talk, I will describe the development of our open-source python:robot integration platform which enables us to adjust the stringency of selection in response to real-time evolving activity measurements and to dissect the historical, environmental, and random factors governing biomolecular evolution. Finally, I will talk about our many on-going projects which utilize this system to evolve previously intractable biomolecules using novel small-molecule substrates to target the undruggable proteome.

Emma Chory Bio: Emma Chory is a postdoctoral fellow in the Sculpting Evolution Group at MIT, advised by Kevin Esvelt and Jim Collins. Emma’s research utilizes directed evolution, robotics, and chemical biology to evolve biosynthetic pathways for the synthesis of novel peptide-based therapeutics. Emma obtained her PhD in Chemical Engineering in the laboratory of Gerald Crabtree at Stanford University. She is the recipient of the NSF Graduate Research Fellowship and a pre- and postdoctoral NIH NRSA Fellowship.

Atomically-thin, Twisted Graphene Has Unique Properties

by Erica K. Brockmeier

New collaborative research describes how electrons move through two different configurations of bilayer graphene, the atomically-thin form of carbon. These results provide insights that researchers could use to design more powerful and secure quantum computing platforms in the future.

New research published in Physical Review Letters describes how electrons move through two different configurations of bilayer graphene, the atomically-thin form of carbon. This study, the result of a collaboration between Brookhaven National Laboratory, the University of Pennsylvania, the University of New Hampshire, Stony Brook University, and Columbia University, provides insights that researchers could use to design more powerful and secure quantum computing platforms in the future.

“Today’s computer chips are based on our knowledge of how electrons move in semiconductors, specifically silicon,” says first and co-corresponding author Zhongwei Dai, a postdoc at Brookhaven. “But the physical properties of silicon are reaching a physical limit in terms of how small transistors can be made and how many can fit on a chip. If we can understand how electrons move at the small scale of a few nanometers in the reduced dimensions of 2-D materials, we may be able to unlock another way to utilize electrons for quantum information science.”

When a material is designed at these small scales, to the size of a few nanometers, it confines the electrons to a space with dimensions that are the same as its own wavelength, causing the material’s overall electronic and optical properties to change in a process called quantum confinement. In this study, the researchers used graphene to study these confinement effects in both electrons and photons, or particles of light.

The work relied upon two advances developed independently at Penn and Brookhaven. Researchers at Penn, including Zhaoli Gao, a former postdoc in the lab of Charlie Johnson who is now at The Chinese University of Hong Kong, used a unique gradient-alloy growth substrate to grow graphene with three different domain structures: single layer, Bernal stacked bilayer, and twisted bilayer. The graphene material was then transferred onto a special substrate developed at Brookhaven that allowed the researchers to probe both electronic and optical resonances of the system.

“This is a very nice piece of collaborative work,” says Johnson. “It brings together exceptional capabilities from Brookhaven and Penn that allow us to make important measurements and discoveries that none of us could do on our own.”

Read the full story in Penn Today.

Charlie Johnson is the Rebecca W. Bushnell Professor of Physics and Astronomy in the Department of Physics and Astronomy in the School of Arts & Sciences at the University of Pennsylvania and a member of the Penn Bioengineering Graduate Group.

Reimagining Scientific Discovery Through the Lens of an Artist

by Erica K. Brockmeier

Rebecca Kamen, Penn artist-in-residence and visiting scholar, has a new exhibition titled “Reveal: The Art of Reimagining Scientific Discovery” at American University Museum at the Katzen Arts Center that explores curiosity and the creative process across art and science. (Image: Greg Staley)

Rebecca Kamen, Penn artist-in-residence and visiting scholar, has long been interested in science and the natural world. As a Philadelphia native and an artist with a 40-plus-year career, her intersectional work sheds light on the process of scientific discovery and its connections to art, with previous exhibitions that celebrate Apollo 11’s “spirit of exploration and discovery” to new representations of the periodic table of elements.

Now, in her latest exhibition, Kamen has created a series of pieces that highlight how the creative processes in art and science are interconnected. In “Reveal: The Art of Reimagining Scientific Discovery,” Kamen chronicles her own artistic process while providing a space for self-reflection that enables viewers to see the relationship between science, art, and their own creativity.

The exhibit, on display at the Katzen Art Center at American University, was inspired by the work of Penn professor Dani Bassett and American University professor Perry Zurn, the exhibit’s faculty sponsor. The culmination of three years of work, “Reveal” features collaborations with a wide range of scientists, including philosophers at American University, microscopists at the National Institutes of Health studying SARS-CoV-2 , and researchers in Penn’s Complex Systems Lab and the Addiction, Health, and Adolescence (AHA!) Lab.

Continue reading at Penn Today.

Dani S. Bassett is the J. Peter Skirkanich Professor in the departments of Bioengineering and Electrical and Systems Engineering in the School of Engineering and Applied Science at the University of Pennsylvania. She also has appointments in the Department of Physics and Astronomy in Penn’s School of Arts & Sciences and the departments of Neurology and Psychiatry in the Perelman School of Medicine at Penn.

Rebecca Kamen is a visiting scholar and artist-in-residence in the Department of Physics & Astronomy in Penn’s School of Arts & Sciences.

David Lydon-Staley is an assistant professor in the Annenberg School for Communication at Penn and was formerly a postdoc in the Bassett lab.

Dale Zhou is a Ph.D. candidate in Penn’s Neuroscience Graduate Group.

“Reveal: The Art of Reimagining Scientific Discovery,” presented by the Alper Initiative for Washington Art and curated by Sarah Tanguy, is on display at the American University Museum in Washington, D.C., until Dec. 12.

The exhbition catalog, which includes an essay on “Radicle Curiosity” by Perry Zurn and Dani S. Bassett, can be viewed online.