Week in BioE (July 31, 2018)

New Data Analysis Methods

Like many other fields, biomedical research is experiencing a data explosion. Some estimates suggest that the amount of data generated from the health sciences is now doubling every eighteen months, and experts expect it to double every seventy-three days by 2020.  One challenge that researchers face is how to meaningfully analyze this data tsunami.

The challenge of interpreting data occurs at all scales, and a recent collaboration shows how new approaches can allow us to handle the volumes of data emerging at the level of individual cells to infer more about how biology “works” at this level.  Wharton Statistics Department researchers Mo Huang and Jingshu Wang (PhD Student and Postdoctoral Researcher, respectively) collaborated with Arjun Raj’s lab in Bioengineering and published their findings in recent issues of Nature Methods and Proceedings of the National Academy of Sciences.  One study focused on a de-noising technique called SAVER to provide more precise data from single cell experiments and significantly improves the ability to detect trends in a dataset, similar to how increasing sample size helps improve the ability to determine differences between experimental groups.  The second method, termed DESCEND, creates more accurate characterization of gene expression that occur in individual cells. Together these two methods will improve data collection for biologists and medical professionals working  to diagnose, monitor, and treat diseased cells.

Dr. Raj’s team contributed data to the cause and acted as consultants on the biological aspects of this research. Further collaboration involved Mingyao Li, PhD, Professor of Biostatistics at the Perelman School of Medicine, and Nancy Zhang, PD, Professor Statistics at the Wharton School. “We are so happy to have had the chance to work with Nancy and Mingyao on analyzing single cell data,” said Dr. Raj. “The things they were able to do with our data are pretty amazing and important for the field.”

Advancements in Biomaterials

This blog features many new biomaterials techniques and substances, and there are several exciting new developments to report this week. First, the journal of Nature Biomedical Engineering published a study announcing a new therapy to treat or even eliminate lung infections, such as those acquired while in hospital or as the result of cystic fibrosis, which are highly common and dangerous. Researchers identified and designed viruses to target and kill the bacteria which causes these infections, but the difficulty of administering them to patients has proven prohibitive. This new therapy, developed by researchers at the Georgia Institute of Technology, is administered as a dry powder directly to the lungs and bypasses many of the delivery problems appearing in past treatments. Further research on the safety of this method is required before clinical trials can begin.

A team at Harvard University published another recent study in Nature Biomedical Engineering announcing their creation of a tissue-engineered scale model of the left human heart ventricle. This model is made from degradable fibers that simulate the natural fibers of heart tissue. Lead investigator Professor Kevin Kit Parker, PhD, and his team eventually hope to build specific models culled from patient stem cells to replicate the features of that patient’s heart, complete with the patient’s unique DNA and any heart defects or diseases. This replica would allow researchers and clinicians to study and test various treatments before applying them to a specific patient.

Lastly, researchers at the Tufts University School of Engineering published in the Proceedings of the National Academy of Sciences on their creation of flexible magnetic composites that respond to light. This material is capable of macroscale motion and is extremely flexible, allowing its adaptation into a variety of substances such as sponges, film, and hydrogels. Author and graduate student Meg Li explained that this material differs from similar substances in its complexity; for example, in the ability for engineers to dictate specific movements, such as toward or away from the light source. Co-author Fiorenzo Omenetto, PhD, suggests that with further research, these movements could be controlled at even more specific and detailed levels.

CFPS: Getting Closer to “On Demand” Medicine

A recent and growing trend in medicine is the move towards personalized or “on demand” medicine, allowing for treatment customized to specific patients’ needs and situations. One leading method is Cell-Free Protein Synthesis (CFPS), a way of engineering cellular biology without using actual cells. CFPS is used to make substances such as medicine, vaccines, and chemicals in a sustainable and portable way. One instance if the rapid manufacture of insulin to treat diabetic patients. Given that many clinics most in need of such substances are found in remote and under-served locations far away from well-equipped hospitals and urban infrastructure, the ability to safely and quickly create and transport these vital substances to patients is vitally important.

The biggest limiting factor to CFPS is difficulty of replicating Glycosylation, a complex modification that most proteins undergo. Glycosylation is important for proteins to exert their biological function, and is very difficult to synthetically duplicate. Previously, achieving successful Glycosylation was a key barrier in CFPS. Fortunately, Matthew DeLisa, PhD, the Williams L. Lewis Professor of Engineering at Cornell University and Michael Jewett, PD, Associate Professor of Chemical and Biological Engineering at Northwestern University, have created a “single-pot” glycoprotein biosynthesis that allows them to make these critical molecules very quickly. The full study was recently published in Nature Communications. With this new method, medicine is one step closer to being fully “on demand.”

People and Places

The Institute of Electrical and Electronics Engineers (IEEE) interviewed our own Penn faculty member Danielle Bassett, PhD, the Edwardo D. Glandt Faculty Fellow and Associate Professor in Bioengineering, for their website. Dr. Bassett, who shares a joint appointment with Electrical Systems Engineering (ESE) at Penn, has published groundbreaking research in Network Neuroscience, Complex Systems, and more. In the video interview (below), Dr. Bassett discusses current research trends in neuroscience and their applications in medicine.

Finally, a new partnership between Case Western Reserve University and Cleveland Clinic seeks to promote education and research in biomedical engineering in the Cleveland area. Cleveland Clinic Lerner Research Institute‘s Chair of Biomedical Engineering, Geoff Vince, PhD, sees this as an opportunity to capitalize on the renown of both institutions, building on the region’s already stellar reputation in the field of BME. Dozens of researchers from both institutions will have the opportunity to collaborate in a variety of disciplines and projects. In addition to professional academics and medical doctors, the leaders of this new partnership hope to create an atmosphere that can benefit all levels of education, all the way down to high school students.

Researchers Visualize Resistant Cancer Cells

by Meagan Ita, Ph.D. Student in Bioengineering and GABE Co-President

Cancer is a disease that affects millions, and over the last several decades, researchers have delved deeply into the biological underpinnings of the disease in the hopes of finding a cure. One major discovery is that mistakes in your DNA “instructions” can lead to cancer by crossing the wires in your cellular circuitry, and researchers have developed amazing new drugs that can cause tumors to melt away by targeting these broken components. The problem though is that, most of the time, the tumors come back, and this is a huge barrier to cures.

Shaffer ASCO
Picture of patient treated with vemurafenib and then developing resistance. Courtesy of the American Society of Clinical Oncology

For a long time, everyone assumed that the reason the tumors came back was  DNA mistakes on top of the original mistakes, with these new mistakes blocking the activity of the anti-cancer drug. However, new work led by Sydney Shaffer from the Arjun Raj Lab at Penn Bioengineering, published this week in Nature, challenges this view by looking all the way down at individual cancer cells and seeing how they respond to these drugs on a cell-by-cell basis.

Sydney found that in melanoma, contrary to what researchers thought, it need not be a DNA mistake that leads a cell to become resistant to the drug, but rather a change in cellular identity. Just like your body has cells of all different types, like skin cells and brain cells, cancer cells appear to change between different types, but unlike in the body, cancer cells do it in a seemingly random and uncontrolled way, and the cells exploit this variability to allow those rare cells that have changed their type to survive the drug.

Here, we talk with Sydney about the inspiration, triumphs, and challenges she faced in her research.

What was the initial inspiration for looking at drug resistance in melanoma?

For the first two years of working on this project, we actually didn’t have a clear question in mind. I was just trying a bunch of different experiments with melanoma cells, and I noticed something that we found thought-provoking. Whenever we gave the melanoma cells a particular drug, they would become resistant at exactly the same point in time. At first, this may not seem unusual, but for example, if everyone showed up at a restaurant to eat lunch at exactly noon, you would guess this was not happening purely by chance. Maybe classes let out right beforehand? Or a big meeting? For the melanoma cells, we would similarly expect there to be a range of different times for the cells to become resistant, but instead it all happened at once.

This observation helped us figure out that the drug-resistant cells probably already exist before we treat them. It also got us curious about the particular processes that make the cells resistant, and we spent many lab meetings discussing this observation until one postdoc, Gautham Nair, suggested trying some experiments based upon the classical molecular biology experiments of Luria and Delbrück.

Who were Luria and Delbrück, and how did they influence your work?

Max Delbrück and Salvador Luria (below) were scientists who, in the 1940s, performed a clever experiment that demonstrated that bacteria become resistant to viruses through random DNA mutations. According to Wikipedia, Luria actually had the idea for these experiments while watching slot machines!

Shaffer D&L
Delbrück (left) and Luria. Courtesy of the Genetics Society of America.

Their experiment was super simple: it was basically a statistical way to see whether cells “sense and respond” to a challenge, or whether they just passively get a mutation that lets some fraction of them survive the challenge, basically like Darwinian evolution. The idea is that, in the first scenario, there is no history: every cell has an equal chance to respond when challenged.

But in the second scenario, history matters in that if your great-grandparent was a survivor, then all your relatives would be too. If you could redo history over and over, then sometimes maybe your great-great-great-great-grandparent would be a survivor, and so you would get a whole bunch of survivors when the challenge came. Luria and Delbrück’s results showed that this second scenario was what happened with bacteria, providing the first evidence for genetic mutations in bacteria occurring in the absence of selection, and they both went on to win a Nobel prize in 1969.

Arjun actually had just lectured about these experiments in our graduate course on modeling biological systems. We adapted the same strategy and theory as Luria and Delbrück’s experiments for our work but applied it to melanoma and actually found a different result. Our experiments showed that resistance in melanoma does not arise through a heritable DNA mutation.

Shaffer colony
Picture of a resistant colony growing in the Raj lab.

Based upon this work, do you have any ideas for how we might prevent resistance in patients?

Yes. The recommended dosing for many of these drugs is daily. Our work would suggest that something like interval therapy might be more effective, for instance, if you gave the drug for a few days, killed many of the tumor cells, and then stopped the drug. During the time that the drug is stopped, the cells that initially survived the drug (we call these cells pre-resistant) could then transition out of this cell state and back to a sensitive state. Then, when the patient takes the drug again, it would be more effective at killing the remaining tumor cells. Another idea would be to find drugs that are specific to the pre-resistant cells and give these drugs in combination with other targeted therapies.

Were there any “Aha!” moments while working on this project?

One of the most exciting moments of this research was when we first found the pre-resistant cells. Hidden among thousands of pictures of empty cells, we were shocked to actually see the rare cells full of brightly tagged resistance genes (below).

Shaffer cells
Resistant cells growing in the Raj lab.

What were some low points in working on the project? Do you recall any specific moments that you just felt intellectually and/or emotionally stumped? How did you get through them?

Oh yes, there were definitely low points during this project. One that stands out to me specifically was this one Friday afternoon where I presented at lab meeting. At the time, I only had a little bit of preliminary data. One of the members of the lab asked me a series of questions about resistance: How many different drug doses had I tried? Could I just give a lot and kill them all? What dose of drug is relevant for patients? What about drug resistance? Was I really interested in? All reasonable questions to ask. However, this was really overwhelming to a first-year graduate student because it made me realize that I didn’t have a clearly defined project that I was working on yet. There were just so many different questions that I didn’t know where to start.

Ultimately, with Arjun’s guidance, I came to realize that this was part of the process of figuring out what my thesis project would be, and the vagueness of our ideas at this time was a great thing because it left me open to find a problem that I found really interesting.

At another point in working on this: I remember that we were clearly conceptually stuck. We had identified the rare cells, but it wasn’t clear how to find out if these were the same cells that become resistant to drug. I had an entire lab meeting where we discussed this concern and came to the conclusion that, without some connection between the cells in this state and resistance, the work would be very speculative, which felt unsatisfying to me. Unfortunately, there wasn’t a quick fix to this problem. We just ended up trying a whole bunch of different ideas and eventually one of our strategies worked out.

Were there any funny moments that stand out to you?

Yeah! I was 40 weeks pregnant as we were finishing off our first submission of the paper! As my due date passed, I was really feeling the pressure to finish everything. Each day, I was coming into lab and just hoping I wouldn’t go into labor yet! Actually, the members of our lab had placed bets on when the baby would be born. Fortunately, those who bet on a late arrival ended up winning, and we submitted the paper the day before my daughter, Julien, was born. I was actually still at the hospital when I got the e-mail that the paper went to review.

So even though it might seem like this project is checked off the list with a kick-ass publication, there are probably a bunch of unfinished ideas you have. So,what are you working on next? Will this project ever be “done?”

For sure. The list of unfinished ideas is very long, and some of the questions that came from this work are now being pursued by other people in the lab. Right now, I’m working on ways of measuring the length of time that individual cells remain in these different cell states.

Interested in sharing your research in Penn BE? Contact penngabe@gmail.com for an interview by GABE (Graduate Association of Bioengineers) and let us know!