The work was tiring. The hours were long. However, Ph.D. candidate Li Su wasn’t affected by any of it. She was in her element
During her undergraduate degree in China, Su studied turfgrass science.
“There was a chance for undergraduates to do some research project, so I tried it and, although it was exhausting, I stayed in the lab and time just passed,” Su said. “I felt quiet and at peace. I kind of enjoyed it.”
As part of the Dong Xu lab at Bond Life Sciences Center, Su works on statistics and data analysis for many research studies throughout Bond LSC.
Originally from China, Su moved to Springfield, Missouri in 2016 to earn her master’s in plant science at Missouri State University. Once she graduated in 2018, she moved to Houston, Texas to work at a biomedical research institution. After a while, she applied for graduate school but wanted to go in a new direction.
“While I was in Houston, at that job, I was confused,” Su said. “I was just thinking about my skills, what I liked to do in the lab and what will make me survive … I realized even a lot of postdocs or senior graduate students were kind of limited in the statistics and data analysis, so I tried to figure out how to do those things.”
Su switched her focus, was accepted by Mizzou in 2020 and soon found her place in the Dong Xu lab.
“As we are trying to handle this big data, the main weapon for us is coding,” said Juexin Wang, Dong Xu’s lab manager. “So, when we are trying to deal with that big amount of data, we have to highly rely on the coding skills and [Su] does that very, very well. She is learning fast and uses all her resources to learn that.”
Su joined the lab while it was strictly Zoom lab meetings and everything was remote. Despite the digital barriers, Su stood out to Wang.
He had found a paper where he believed the lab could replace its methodology with theirs and make the study stronger. Wang mentioned this to Su over Zoom, not thinking much of it.
“Probably weeks later, she came to me and she tells me many things about the other methodology,” Wang said. “So, I was really impressed.”
Su understands what it means to do good science in the lab and what that could mean for others.
“I think a lot of people I work with tell me to be honest with yourself about your science, about your work,” Su said. “I want some work to be like this, so you have a novel idea, you scientifically prove it and make the conclusion helpful to a group of people. I feel like if I have such work, I can be part of the [scientific] community.”
Even though Su isn’t working on any of her own projects right now, her main goal is to publish new and better papers during her Ph.D.
“Smarts, diligence, persistence — I think those are very, very key characteristics,” Wang said. “[Su] is making her weapons much more powerful and much sharper. I think she will get some very good achievements.”
It’s all about the journey and Karl Kerns has been places.
Originally from a small town in southwestern Iowa, Kerns did his undergrad years at Iowa State University (ISU), taking internships in Maryland, Texas, southeast Asia, and southern Australia, among other places that focused on animal physiology and fertilization.
“I do like traveling just in the sense of vacation. I like having a purpose while traveling. It’s hard for me to sit back and relax and be in vacation mode,” Kerns said.
This focus and determination eventually brought him to Mizzou where he completed his postdoctoral fellowship in the Dong Xu lab at Bond Life Sciences Center this past spring, co-advised with Peter Sutovsky and Susanta Behura in the Division of Animal Sciences. Kerns was initially attracted to MU for his doctoral training because of the reputation of the animal sciences’ reproductive physiology program, but he then joined Bond LSC to continue his research during his USDA NIFA Postdoctoral Fellowship.
“MU is a world class institution. There are not many places that offer the resources we are fortunate to have here with the combination of animal science, veterinary medicine, and the resources of a research hospital system,” Kerns said. “And it’s not just equipment resources, but also intellect and the people that we [Bond LSC] have, it really provides an atmosphere that lets you dig into science a little bit deeper than you can anywhere else.”
This atmosphere at Bond LSC has aided Kerns in his current position as a newly-minted faculty member at ISU.
“It set me up for success. Especially in the middle of COVID right now, there’s not a lot of faculty positions available, so to get a faculty position when all those other positions were being halted, it speaks volumes to the training I received here,” Kerns said.
Kerns began teaching this fall semester, teaching Anatomy and Physiology labs twice a week.
Going back to his alma mater as a professor was not exactly the homecoming Kerns expected.
“It’s a very odd timeframe coming back during COVID when the buildings are not bustling with students and faculty.”
In the Xu lab, Kerns worked on bioinformatics and artificial intelligence with graduate students. They were able to incorporate machine and deep learning analysis with high throughput, single cell phenotyping, looking at multi-million cell data sets for bioimage analysis.
“There are multiple times that you step back from the microscope or from the computer after doing data analysis and you have so much awe and admiration for how all these intricate biological functions have to come together to support life,” Kerns said. “That is what fuels me.”
Kerns’ first publication at Mizzou was about how zinc, a vital micronutrient, helps regulate fertility in pigs, cattle, and humans.
“Research in the life sciences is extraordinarily rewarding because there is a time between initial discovery and publication that just you and your co-authors know this little piece of how life as we know it functions, previously unknown from the start of time,” Kerns said.
While he enjoys special moments like these in the lab, Kerns has been enjoying his time in the classroom with students during this isolating time of the pandemic as well.
“It’s my duty, being taxpayer funded in the training that I got, to make sure I teach the next generation,” Kerns said, “Let them have a taste of the cutting-edge technologies I learned at Mizzou and cutting-edge research findings that we found. The academia system is all about having people that are experts in a set area and passing it down to the next generation to expand on.”
Along with teaching, Kerns is also doing research at ISU. He is currently working on analyzing the fertility of boars and bulls to see what helps predict their fertility. Significant amounts of research and improvements focus on the female side of reproduction but not male, so by improving male fertility, Kerns will be able to help livestock producers and stakeholders improve their efficiency.
Kerns has big plans for his research in the future.
“Once we optimize male fertility, we can start taking superior genetics to third world countries that need a good protein source that can grow in their particular climate — we know protein is a source of complete amino acids that provides better cognitive function for people — and also provide a source of financial security for their families as well. It’s a win-win,” Kerns said.
Until then, Kerns plans to continue teaching and doing research. His science journey has taken him many places so far, and his is not stopping there.
“Science is always changing,” Kerns said. “When we say, ‘what does the science say?’ The science only says our current interpretation of it. In the grand scheme, we have so much more to learn. Every day we’re learning more about our world and not uncommonly disproving what we used to hold to as true because of new techniques now available to us.”
With two laptops in front of him and a supercomputer on the edge of campus, graduate student Skyler Kramer runs through code daily in the Dong Xu lab with a purpose far beyond deciphering lines of data. He helps his colleagues defeat cancer.
Working in Bond LSC with senior post doctorate David Porciani from the Donald Burke lab, Kramer and the Dong Xu lab are part of an effort to target cancer tissue and develop more precise delivery of treatment.
In addition, they’re trying to learn more about the biology that drives cancer growth and what makes cancer tissue resistant to treatment after a certain point in time.
“[Kramer] has been a tremendous asset for the project,” Porciani said. “His contribution is so critical at many levels.”
Porciani set out four years ago to find a way to easily differentiate between cancer and healthy tissue. By developing small pieces of RNA and DNA called aptamers that can bind to receptors on cancer cells, he slowly tried to determine the pieces that would only interact with cancer — not bothering the healthy cells — that could deliver a cancer-killing drug. But the process meant Porciani would amass mounds of data.
“There is a lot of statistics in there, which is very important,” Porciani said. “So, that brings in the collaboration with Skyler.”
About a year ago, Porciani was presenting his work on aptamers at a talk in Bond LSC. Xu later inquired if Porciani was open to any collaboration, which led to discussion on what the two labs could do together.
“It was just really really fascinating,” Kramer said. “So, I was really interested in it.”
Now, the two are working together to turn microscopy images into something more meaningful.
Through super resolution microscopy images of the receptors on the cancer cells, Porciani took a short video showing the thousands of receptors shaking.
“Most of the receptors like to shake hands with each other, and when that happens it is critical for the growth of the cells,” Porciani said. “So, the handshakes are sort of a signal that says, ‘Okay, let’s move this house to the next stage. Yes, let’s make the cell grow even more.’”
Porciani could analyze only a small part of these shakes with his naked eye but using a bioinformatics approach —using software and statistics to understand biological data — Kramer can take that data from the thousands of receptors and turn it into digestible and meaningful information.
“[I’m] trying to take the massive amounts of data that we’re able to generate and get some sort of useful information out of it,” Kramer said. “So, a lot of times it’s useful not only to get some sort of numeric output but some sort of visualization also.”
This means turning an image of a cancer cell into a receptor density map or a receptor count map. By doing so, researchers can investigate why receptors clump into one area, what that means and why cancer cells become resistant to treatment over time.
“It’s our job to understand why there is this difference,” Porciani said. “This type of information can generate new hypotheses that we need to test.”
With the help of bioinformatics, Porciani and other researchers can find the answers to their questions.
“I think [bioinformatics] is hugely impactful,” Kramer said. “A lot of times, the life sciences will give you the actual experiments and a rough idea of what happened in the experiment, but I think that when you apply the bioinformatics you get more to why specific things are happening.”
The collaboration brings more than just new results, but also can help expand science.
“I think I’m learning a lot from him,” Porciani said. “I think, hopefully, he is learning a lot from me as well.”
To learn more about Porciani and Burke lab’s findings regarding aptamers, the research article can be found here.
Artificial intelligence (AI) can do more than just write a book given a few words. It can help make cancer treatments more effective and predict the presence of disease in cells, which doctoral student Clement Essien did through his recent project.
“It’s exciting because for several years, I was a software engineer, and then I felt like I wanted to do something more with that,” Essien said. “I want to make some contribution to understanding disease and also in the diagnosis and treatment of diseases. So, I had to look for ways that I could apply computing to understand and possibly solve many biological problems.”
Essien — who works with Bond LSC principal investigator Dong Xu — is trying to predict the binding sites of metal-binding proteins called metalloproteins using AI technology, specifically deep learning.
“Metal binding can play a very functional role,” said Dong Xu, Shumaker Endowed Professor in Bioinformatics, Director of Information Technology Program. “That is why it’s important to know whether a protein binds to a particular metal, and also if you really could, you’d want more details on where it binds.”
Even though Essien’s work is still underway, it has big implications.
“[My work] helps to advance the research geared towards improving the prediction capability of machine learning modules that work on this problem and also provide an important step towards understanding protein functions, and their implications for gene product characterization, drug design for certain diseases and enzyme engineering.
Not only could predicting the binding sites of metal proteins help create drug targets and advance other research, but it could also possibly help identify the presence of disease.
By predicting the binding site, researchers can figure out the protein’s structure and therefore infer the function.
“[The function is] what tells you what role the protein plays in the body,” Essien said. “Also, the presence or absence or mutation of a particular protein sequence can cause diseases.”
Essien’s previous project had the same goal of predicting zinc binding sites, but now he is expanding his research to the study of many other metals found in the human body. Essien is also using an AI technique called Natural Language Processing (NLP).
One use for NLP would be to give an AI all the words in the dictionary and then ask it to write a book. In Essien’s work, he is trying to model the protein sequences as a text because they consist of a sequence of letters, and then get the AI to learn representations from it.
“So, we are trying to model the problem as a natural language problem in the sense that those series of letters you see in the protein sequences, they may be represented as words,” Essien said. “So, if you’re able to break that code you might be able to learn some important things.”
Essien published one paper in a conference and expects to have another one out in a few months. Although, he has much more to discover until then.
“It’s one thing to see I’m able to predict these to a certain accuracy, but it’s also important to learn what is going on inside,” Essien said. “Is there any new significance to learn?”
A Bond Life Sciences Center researcher has been inducted into an elite organization comprised of two percent of all medical and biological engineers.
The American Institution for Medical and Biological Engineering (AIMBE) this week announced the induction of Dong Xu, a Bond LSC principal investigator and Shumaker Endowed Professor in the University of Missouri’s College of Engineering.
“Election to the AIMBE College of Fellows is among the highest professional distinctions accorded to a medical and biological engineer,” said Kamrul Islam, chair of the college’s Electrical Engineering and Computer Science department.
Xu was selected for his “distinguished contributions to bioinformatics and computational biology, and extensive services to University of Missouri and his research community.”
In addition to his endowed faculty position, Xu serves as director of the Information Technology program, whose core facility is housed in Bond LSC.
Membership to AIMBE’s College of Fellows recognizes those who have made outstanding contributions to engineering and medicine research, practice or education, and to those pioneering new and developing fields.
Because of health concerns, AIMBE’s annual meeting and induction ceremony scheduled for this spring was canceled. Under special procedures, the induction was held remotely.
Boring may not be the first word that comes to mind when you think of someone’s research story.
But for Juexin Wang, it was a dull job that steered him toward research.
“My undergrad was in Beijing, I was studying computer science,” Wang said. “After I finished my undergrad I went to work in the industry for two years as a software engineer, and I realized that work was so boring to me and I wanted to discover something new.”
Wang went back to school for his masters and Ph.D. in Northeast China. During his Ph.D., Wang had an opportunity to collaborate with Dong Xu in Bond LSC, and he took the chance to come to the states.
“The most advanced technologies were here,” Wang said. “I felt really comfortable when I came here, we could adjust the focus on the research and the platform Mizzou provided was powerful. We have great collaborators, and I think if you have questions people are happy to help you.”
Eight years later you can find Wang going back and forth between the School of Medicine and Bond LSC. His research works with both Dong Xu and Trupti Joshi to combine biology and data sets, a field known as bioinformatics.
“I found possible connections between computer science and biology,” Wang said. “Data that comes from biology reflects biological mechanism on different levels. With computers, software, the algorithms, we can find something new no one has ever seen in wet lab, which may help people understand diseases in human beings and complex traits in other organisms such as plants.”
Wang’s research involves creating new tools and algorithms for the data sets.
“My work has many tasks,” Wang said. “I do algorithms development, and if we have too much data — you can call it ‘big data’ — this causes us to develop new tools that can help understand and tie into the data. My work is trying to develop different tools to help people deal with this same problem in data on their own.”
Too much data, too little time, is why people like Wang are advancing in this science.
“For me, I never found anything really new in my software engineering work, but in research I always touch something new,” Wang said. “New mechanism, new data, new tools. I think that it is fascinating, you always put your passion over yourself. You’re always pushed and this isn’t like anything else.”
“#IAmScience because I want to explore the beauty of biological sequences through computational methods.”
Bioinformatics is a melting pot in the world of science. As a study of analyzing complex data, it’s not a field for everyone, but its applications are vast.
Duolin Wang, a researcher in the Dong Xu Lab at Bond LSC, isn’t intimidated by the complexities her field presents. She came to America from China to conduct research for Xu’s lab while she simultaneously works on her thesis to earn her Ph.D. from Jilin University in China.
“The reason I came to American is because the education is great,” Wang said. “It provides me a very good opportunity to study and do research.”
Wang and her lab practice deep learning, which is a state-of-the-art approach to machine learning.
“There has been a growing interest in applying deep learning methods to understanding the function of biological sequences directly from sequence,” Wang said. “It allows computational models composed of multiple processing layers to learn representations of data with multiple levels of abstraction.”
Essentially, deep learning is a way to better understand the complex data that the bioinformatics field covers. For instance, it turns terabytes of information on a sequence to help researchers predict how best to improve its effectiveness.
She didn’t just stumble into her research position, though. Her supervisor at her university in China had collaborated with Xu in the past. When Xu traveled overseas, Wang was able to meet him in person.
“I showed my interest in his research, and I asked him if I could come to the United States to continue my research,” Wang said.
The rest is history. In the three years she’s been at Mizzou, Wang has been able to work on a number of projects in her field. That’s largely thanks to Xu’s flexibility with the topics she focuses on.
“I have freedom to choose what I want to study,” Wang said. “As a scientist, I can explore what I’m really interested in. Professor Xu didn’t make any barriers to my research field; I can show him my interests and he can see whether it’s a good topic and if I can explore it.”
Wang has even written a few papers, including one for Monsanto thanks to the help of Juexin Wang who also works in the Xu lab. That experience has helped her to prepare for a future in research writing proposals.
It’s not all about the work, though.
“The most valuable thing I got from this lab is the people,” Wang said. “They’re excellent scientists, and I’ve learned a lot from them.”
Wang is on track to finish her Ph.D. this summer, but she’d like to continue what she’s been doing at Bond LSC.
“I might do a postdoc here after I earn my degree,” Wang said. “I want to continue my research here.”
What happens when a chemical engineer, a computer scientist, and an immunologist walk into a lab?
Vaccines are created faster and cheaper.
At least this trio hopes that’s the answer.
Bond Life Sciences Center computer scientist Dong Xu joined forces with immunologist Jeffery Adamovicz and chemical engineer Bret Ulery for the first time in February 2016. After 18 months and a $100,000 Bond Life Sciences startup grant, the team is closing in on a novel approach to vaccinations. They hope to start collecting initial data in the near future.
“Without this grant, it would be hard to work together,” Xu said. “Bond Life Sciences Center really played an important role for the collaboration research on campus and also for providing this seed money. They really foster these types of collaboration.”
Efficiency has plagued the vaccination field for decades.
Traditionally, scientists create new vaccines by continuously guessing which components of the virus or bacteria to test.
“It was a plug-and-play type test system,” explained Adamovicz, who has researched vaccines for years. “We said, ‘well we could try this antigen or that antigen or that antigen and you would mix them together in different combinations and try them and then you would end up selecting one that would work.”
The process is similar to finding a needle in a haystack. It’s like scientists sort through and test every strand of hay until they discovered the needle.
As you can imagine, this method takes a long time to find something usable.
This process becomes a larger issue when viruses emerge that call for immediate measures, such as Zika or Ebola.
Creating vaccines can take a long time because sometimes a variety of different related bacteria cause illnesses. This makes that already inefficient guessing game more complicated by adding, even more, components to test.
Adamovicz explained scientists make a new vaccine each year by predicting which strain of the disease will infect the most people. This is why many people who get a flu vaccination can still get the flu — the strain they caught was not included in the vaccine.
Xu, Ulery and Adamovicz decided to combine their strengths from their different fields to approach creating a vaccine in a new way to solve these two problems.
Adamovicz explained this type of collaboration is not routinely attempted when developing new vaccines.
Computer science and engineering enabled the team to more easily sort through thousands of potential options. Xu’s lab and his students created an algorithm to select candidates to test. Without Xu, the team would have to test tens of thousands of different antigen and peptide combinations. But with the algorithm, the team narrowed the combinations to about 10 to test.
Adamovicz said this method has the potential to create vaccines in half the normal time.
“I feel that it is a very meaningful work; that’s why I am interested in doing it because I do see the potential impact,” Xu said.
Putting a theory to work
Burkholderia is the first Guinea pig for their new approach.
The potentially deadly bacterial infection occurs in places like Thailand and northern Australia and is caused by a family of related bacteria called Burkholderia pseudomallei. But other strains of Burkholderia also cause disease in patients with Cystic Fibrosis across the globe.
“That was part of the challenge,” Adamovicz said. “It wasn’t that we could take a single bacterium and that’s all we had to worry about. We were worrying about a family of bacteria that had this variation in their genomic sequence and the proteins they produce.”
To eventually create a vaccine that could cure all strains of the bacteria, the team aimed to find a small piece of protein all Burkholderia had within their flagella, the whip-like structure of the bacteria that allows them to propel themselves.
To limit the number of segments within the protein, Adamovicz’s lab, on the biology side, determined some requirements for Xu to write an algorithm.
“It’s not to say this is like Star Trek where you just tell the computer and it does it on its own, it requires a lot of knowledgeable human input to spit out the answers,” said Adamovicz.
Adamovicz explained they wanted a vaccine that would trigger two immune responses. When harmful substances enter the body, like viruses or bacteria, the body responds in two ways. One way is through cellular immunity that responds by activating cells that already exist. The other way the body responds is by other cells making proteins called antibodies, which is called the humoral response.
The segment also had to be conservative, meaning it is less likely to mutate so there is a higher chance a vaccine would continue to be effective against the bacteria and would be effective against more members in the bacterial family. The last criteria Xu’s lab coded for ensured the protein is not similar to others found in humans.
All these limitations lowered more than three thousand possible candidates down to a testable amount and a final list of 10 candidates.
Then the research moves on to Ulery’s Lab. Here a team of chemical engineers take the identified candidates from Xu’s work and engineer targeted vaccine antigen nanoparticles termed micelles. These micelles are comprised of fat-based cores that display vaccine antigens on their surface and have been shown to induce strong immune responses.
“Most of them [subunit vaccines] are somewhat hydrophilic — water-liking peptides, portions of a protein — and we tether a fat to them and what happens is now you have something that likes water and something that doesn’t like water, and you throw it in water and they self-assemble into these small micelles,” Ulery said. “That clustering of all those peptide molecules together actually enhances the immune response to them.”
Then, the work goes back to Adamovicz to evaluate what the portions of proteins are going to make the best vaccine.
This cycle continues as all labs work to enhance and develop the design further.
“It’s a process that takes a village. It doesn’t necessarily take the whole village but you need the right people in the village to work together and that’s kind of what we’re doing,” Adamovicz explained. “We’re recognizing that there are areas in previous work that could have been better optimized.”
After months of back and forth, the team is preparing to feed infected cells some of the selected peptides, the small portions of protein. Those candidates that do well in the cell culture will be tested in mice exposed to the Burkholderia bacteria.
The team hopes this round of data collection will serve as a baseboard for future experiments. If this principle is proven in one antigen, a larger grant may enable the theory to be tested in hundreds of other antigens and applied to other diseases. Over the next four to six months, the team hopes to have a clearer vision for the future of this research.
The team credits the Bond LSC grant for bringing them together and for helping establish initial research to prove an approach like this could be impactful.
But, these types of collaborations don’t stop here.
“Previously, it was small stakeholders working on one protein their entire life, but that’s more basic research. To solve real-world problems requires many, many aspects, so the way that we are working in terms of interdisciplinary collaboration, I think that presents the future and this is already on-going in terms of an overall biology trend,” Xu explained.
Dr. Dong Xu is a professor in the University of Missouri’s Electrical Engineering and Computer Science Department and the Bond Life Sciences Center. His Digital Biology Lab develops and uses computers and software programs to help biological and medical researchers analyze large amounts of data.
Dr. Jeffrey Adamovicz is an associate professor in Veterinary Pathobiology and the director of the Laboratory of Infectious Disease Research. He works on developing vaccines and on animal models for zoonotic diseases.
Dr. Bret Ulery is an assistant professor in MU’s Chemical Engineering Department. He directs the Biomodulatory Materials Engineering Lab that creates new biomaterials for applications in immunology and regenerative medicine. He earned his doctorate degree from Iowa State University.