Interview
Maximilian Sprang, bioinformatician at the Medical Center of the University of Mainz and Laureate of the Einstein Foundation Early Career Award, answers questions from Prof. Ulrich Dirnagl, Founding Director of the QUEST Center at BIH and Award Secretary.
Ulrich Dirnagl: This year's 100,000 Euro Einstein Foundation Early Career Award goes to Maximilian Sprang, bioinformatician and junior group leader at the University Medical Center Mainz. With his project erring rigorously to make genomic research more reliable and reproducible, he tackles a key challenge in modern bioscience, revealing how errors in high-throughput sequencing affect results. Congratulations on receiving the award and on standing out among more than 70 global applicants. Dr. Sprang, what are the main goals you hope to achieve with your project?
Maximilian Sprang: The main goal is, revealing how errors in high-throughput sequencing affect results. We really want to learn more about the sources that bring these biases into bioscience or to be more precise: into functional genomics. When we learn more about how these biases are actually introduced, we hope to be able to correct them better and then also reveal new biological signal in data that has been already used and where the signal was potentially hidden behind a bias.
Dirnagl: So why do you think your project matters and specifically to whom does it matter?
Sprang: Well, actually switch that order around. It matters to all people that use RNA-Seq. And this brings it to why does the project matter? Because RNA-Seq is used all over the life sciences. It's used from plants, over animals to humans. And nowadays, functional genomics, especially RNA sequencing is also pushed more and more into the clinical setting, into translation. And here it's even more important to know if there is a bias in the data, in the signal and to potentially correct it.
Dirnagl: That sounds challenging. So what do you anticipate with respect to hurdles in the project and how do you plan to tackle them?
Sprang: From my point of view, there are two really big potential hurdles or challenges. The first is that the errors that we introduce are not strong enough or their impact is not strong enough to significantly change the biological signal. The second one is: We plan to use our proven quality control software SecuScorer, but this software might not detect some of the signals or effects that these errors cause. We have already tackled the first challenge with the experimental design. We plan to aim for errors and changes that we expect to have a strong signal, like cell culture density, for example, or directly interfering with the integrity of the RNA. And the other challenge can be tackled by improving the software. If we know that these effects or changes will have significant consequences, and we find that the software does not pick up on this, we need to improve it.
Dirnagl: Now, looking ahead, what impact or changes do you hope your project could bring about?
Sprang: The most immediate impact would be on the dataset itself, as it could actually be a potential standard dataset for all software programs dealing with this problem. And there are already a lot and there will be more in the future. Therefore this would already be very valuable for the community. And in the long run: In the future, we could use our knowledge of where these distortions originate to correct them more effectively and thus learn more about biology from the existing data.
Dirnagl: If a fairy came to you and granted you one wish on how to improve the academic world, what would you wish for?
Sprang: There are many problems in academia, especially for early career researchers. For example, the “publish or perish” paradigm. You need to be very mobile if you want to be a professor, especially in early stages. And this can be a problem if you started a family early like we did. However, my biggest wish, and I think this would also impact these other things, is that instead of only looking for excellence, we should also look for kindness. We should look for respect, especially for the students, especially for the people that work with them. And I say this because I was very fortunate. I was always treated with a lot of respect. I was treated as an equal from day one in my PhD studies, even as a master student. And I wish that for others, too. And sadly, I see a lot of people that really suffer through their PhD, which should have been a scientific journey. In the future, if I make it into scientific leadership myself, I hope to be part of that change.
Dirnagl: I couldn't agree more, and I'm quite sure if there would be such a fairy, she would grant you this wish. Thank you very much for talking to us, and congratulations again on winning the award.
Sprang: Thank you.
