One of my volunteer jobs in HUPO is to interview scholars and broadcast their thinkings to the community. This is a recorded 1v1 interview with Dr Brian Searle. The content was originically released by HUPO official Wechat account: HUPO-Wechat. Permission to reproduce the article was granted.
Original Title: HUPO ReCONNECT 2021 interview: Brian Searle – Xiao Liang
To offer ECRs a better opportunity to have deep communications with established experts in the field of proteomics, HUPO WeChat Official Account has launched a series of interviews conducted by motivated ECRs from China under relevant educational backgrounds. In each interview, HUPO ReCONNECT 2021 speakers will discuss issues of concern with ECRs, ranging from academic challenges, career planning to industry prospects.
Interviewer & Interviewee
For the fifth-round interview, Xiao Liang, a PhD student from Westlake University, interviewed Brian Searle, an Assistant Professor (AP) at the Ohio State University Medical Center in the Department of Biomedical Informatics and a member of the Pelotonia Institute for Immuno-Oncology. Brian’s lab spans the intersection of proteomics, mass spectrometry, bioinformatics, and technology development to study human genetic variation in the backdrop of cancer. He shared with Xiao and ECRs about his current research interests, the popularization of EncyclopeDIA, and advice on collaborations and multi-tasking.
Q1 Brief introduction of your recent research interest.
We just started a new lab in Ohio. And we’re doing a sort of technology development for bioinformatics and mass spectrometry with the goal of doing cancer-oriented research, specifically in Immuno-Oncology, I’m in the department for Biomedical Informatics here but my lab home is in a new immune oncology Institute called the Pelotonia Institute for Immuno-Oncology. And this is an exciting new area of research for me.
The immune Oncology Group has both MDs and PhDs with similar sorts of interests. So, there is a kind of a translational focus to the department. But we also do some basic research as well into understanding what’s going on with T cells and B cells.
In addition, The encyclopedia project is one that we are very excited about and continuing to make improvements. so we’re looking at some new and exciting things on the horizon in the short future to see what will encyclopedia become.
Q2 What’s your topic in the HUPO ReConnect 2021 meeting?
From an informatics perspective, the topic should be “how to analyze and interpret data, how to think about different ways of the data collection, how that affects and how you interpret it”. But mostly, we’re on about the Informatica interpretation and how to get good answers with it. It’s not hard to adapt methods like DDA style methods to make a DIA data acquisition. The difficult steppingstones that people need to make in that transition are figuring out how to interpret the data they collect. That’s one of the bigger hurdles. From an informatics perspective, the topic should be how to analyze and interpret data, how to think about different ways of the data collection, how that affects and how you interpret it. But mostly, we’re on about the Informatica interpretation and how to get good answers with it. It’s not hard to adapt methods like DDA style methods to make a DIA data acquisition. The difficult steppingstones that people need to make in that transition are figuring out how to interpret the data they collect. That’s one of the bigger hurdles.
Q3 How much of your research do you do with DDA versus DIA?
I think that there’s an important place for DDA in the current and the future. For certain types of experiments, I think they’re still good to use DDA methods, if you’ve got sort of one-off samples, or if you’re just interested in cataloging a sample and you’re not interested in detection, or alternatively if your sample is sparse. If there’s not a lot of proteins in the sample, the DDA works great. It’s only in questions of like quantitation, particularly large-scale quantitation. If you have over 20 or 30 samples, I think DIA starts to become much more useful as a method.
But for just sort of general characterization, it’s probably a kind of 50 to 50. We try to apply the right tool to the problem.
Q4 The most valuable experiences when you were an ECR.
In my early career, I was strongly benefited by meetings and conferences. A variety of different people who had major influences over my career trajectory. It is important to meet people at conferences and get to know people at meetings. They’re definitely very specific people I want to introduce who helped me a lot: Sue Weintraub, David Tab, Allie Yagi,[WJ1] Mike McCarthy, David Fangio, etc., they are very important connections for me. Those have shaped my career and changed it to what it is now. Take Ashley McCormick for example, she was one of my earliest mentors. She taught me everything I know about mass spectrometry; I think that those kinds of personal connections with those people are really important.
Q5 The popularization of EncyclopeDIA.
It was a good tool at the right time, and it was reasonably easy to use. We built encyclopedia by accident. Originally, we were interested in trying to build a version of pecan, which was a database search engine, a peptide-centric search engine, developed by Sonia Ting, we were trying to develop a version of that which would be more efficient and easier to run on smaller computers. Because pecan at the time, required a cluster and took a lot of effort computationally so we tried to write something like that, and then we thought about how we could adapt it for library searching. Specifically, we use it a lot for library generation and normal searching for DIA. The workflow is reasonably easy to use. And that’s one of the most important things in trying to popularize a technique is that the tool must be easy to use.
One of the things that made EncyclopeDIA popular was the way of generating libraries was a little bit easier than generating libraries for traditional methods.
There’s an advantage to team up with a team, that is really excited about this type of work. Doing such collaboration, essentially demonstrating Pecan with EncyclopeDIA as being kind of as good as trying to collect large-scale DDA libraries without even having to do any DDA or making those types of measurements ever.
Q6 Advice on collaborations and multi-tasking.
Our field is a collaborative field, it’s impossible to know everything or have sufficient breadth in sort of the scope of what is proteomics. So, from the standpoint of bioinformatics to the analytical chemistry and data acquisition to the biology and biochemistry that’s necessary for generating samples and generating interesting types of questions. I think on one can be an expert in all fields. As science becomes more collaborative, it maintains that type of level of collaboration, finding out where you’re weak and where other people are strong. Take deep learning for example, we know a lot about deep learning through collaboration. And it becomes a powerful tool for us. I’m in an Immuno-Oncology department, but I’m not an expert in cancer nor an expert in immunology, the teamwork is involved and needed, I think is the key to a department’s success.
Time management is important. And make sure that you have time for the things you’re excited about as well as the other people’s things. As soon as you become the PI, you stop being the expert, and your students and your trainees are the experts at that point, those experts are the stronger and more knowledgeable of many types of things. I think it’s important for PI to have intuition about what are the right things to think about.
Q7 Does the COVID-19 pandemic influence your decisions on science? For example, cooperation approaches, research interests, etc.
It makes sense in some ways more challenging. For example, you are not being able to attend a conference. I think that would be a major factor going forward. Right now, the conferences could only be held online only for a significant part. Otherwise, most people wouldn’t be able to attend those meetings. The presence of online availability for conferences will potentially become dangerous because I benefited strongly from having high level important people attend conferences and be present at those meetings and getting a chance to meet them in social settings. That would be a sad loss for junior faculty or junior students, trainees losing connecting with people outside of talks and lecture hall. The most important interactions happened on the poster floors, talking with people in front of their posters and interacting with students in front of their posters talking about science has been one of the greatest losses we’ve had so far. I hope that we find a way to make sure that it is hard to attend long term sort of remote conferences, because it will be a big loss in their ability to learn and progress. I think in front of a whiteboard or a chalkboard, that’s been probably the most challenging to recreate in a zoom environment, a 30-minute discussion over zoom in a camera versus a 3-hour discussion over a beer with a chalkboard, in my opinion, the latter really drives science.
The road of science is never lonely. Senior researchers play significant roles in fostering the development of ECRs especially in the early times. Circumstances like academic meetings, poster presentations, etc., provide great opportunities to get connected to the researchers’ community and be attached by the prospering environment.