With the ever-increasing potential of new technology and the exponential growth of the life sciences field, researchers are always running into new problems to solve. In this interview series, we get scientists’ opinions on the ‘Big Challenge’ in their field and the steps being taken to address it. From new and unique hurdles to fresh takes on common problems, we dive into the complexities of the research landscape.
In this interview, we chat to Linda Orzolek, Core Director at Johns Hopkins University, who gives her take on the ‘Big Challenge’ in transcriptomics.
FLG: What is your background and current role, and how would you define your general scientific field?
Linda: I completed my undergraduate studies at LaSalle University where I received my Bachelor of Arts in Biology. Then I earned my master’s degree in biotechnology from Johns Hopkins University. I have now been a member of the single-cell and transcriptomics core at Johns Hopkins since 2004. In 2004, it wasn’t single-cell transcriptomics, of course; it was microarrays, and then it progressed to next generation sequencing, and now, single-cell and spatial. I started as a research technician, became lab manager, and a few years ago had the honour of becoming the Director for the Core.
Prior to that, I had an internship for the US Army Medical Research Institute of Chemical Defense, where I started my Affymetrix training and studying transcriptional analysis of various chemical weapon exposures for treatment of soldiers in the line of duty. But the vast majority of my career has been serving as a resource for others, as opposed to having my own research.
I’d define my general field as molecular biology and genetics, with a focus on transcriptomics.
FLG: What is the big challenge in your field?
Linda: I look at this a little bit differently, as I don’t have my own research, but the big challenge that I see is education. There are multiple answers that I could give to this, but, to me, it all stems back to education. How we make people aware of not just the technologies, but the capabilities and limitations of those technologies. This becomes especially critical in the realm of transcriptomics and single-cell with how fast all of this is changing. When you compare where we started in 2015-2016 to where we are now, the progress is astounding, but it is impossible for the average researcher to keep up on everything.
Also, there are assumptions that are made about these technologies because they have become so popular. It means that people sometimes expect more from it or are scared of it. We find that education is the best way to alleviate all of those concerns, and it starts at the beginning of the project all the way through to the end.
FLG: Why should people care about this challenge?
Linda: Well, the other answer to the previous question is data analysis, and that is where so much of this work gets hung up. Particularly with the consistency of analysis. We see what one lab does, while the lab next door will analyse with a completely different approach. That’s why I think education is paramount, understanding not just the molecular biology side, but the bioinformatics as well.
There are so many different categories within this field that, without complete education, people struggle to see the whole picture. Without that whole picture, the answers that you get in the end can be completely varied. You start with sample collection and preparation. Researchers have to understand that anything outside of the normal biological processes can induce stress in a cell, which changes that natural transcriptomic profile. Are you inadvertently activating a T-cell population? Are your neutrophils dying off during isolation because they are too delicate? All of this impacts the downstream picture, but most researchers don’t think about it.
Analysis requires a collaboration between the researcher and the bioinformatician. A bioinformatician may eliminate all cells that have mitochondrial reads over 5%, because that is the default threshold to indicate a dying cell, but the researcher may say ‘no, you have to weigh the meaning behind that,’ and you get completely different answers. We had a client filtering out 80% of their data because of high mitochondrial reads, but the sample was muscle, so those reads are an accurate representation of the biology of the sample. If you don’t understand the limitations and what the data are saying, then you can’t come to a proper conclusion. You see that in all of the downstream translational applications of what you have learned. Analysis of single-cell data is far from black and white.
Without proper education to ensure that researchers understand the methods, the approach and the analysis, we won’t see the full potential of single-cell analysis.
FLG: What is being done to tackle this issue, or what should be done?
Linda: You’ve got to start somewhere. In our core specifically, this year in the Hopkins Graduate Programme, we’re offering a class called ‘Practical applications of single-cell sequencing’ where we introduce graduate students to the different technologies that are available. We explain to them why we’re using each technology and make them think critically about why you choose method A over method B. This really gets them to start realizing the implications of this. And then we take it through to some raw analysis because we address the simple questions like ‘what does this file type mean, what is it used for?’, because some people don’t even understand that.
We are also working with groups on our campus that are developing a training centre, so they can bring people in and have one-on-one, or group, conversations about analysis, so that people can bounce ideas off of one another. We try to do a symposium every year to bring together not just the speakers but also companies who are offering these different technologies. That includes bioinformatics, AI, single-cell, next generation sequencing, all of the different aspects of it. I might be the core director, but I am certainly not an expert in everything. So, if I can bring in the experts and have them all in one place, it gives people an opportunity to learn a lot, very, very quickly.
On top of that, I think some of these social media platforms have been a really great advancement for people to connect all across the world. As these new technologies are released, and become available to select groups, a lot more people get access to your experience and the pitfalls of the technology, and they get to make educated decisions before having to invest significant amounts of money into capital equipment or project design. Relying on the community will make the biggest difference, and I think the biggest necessity in getting people communicating with one another is to share everybody’s little niche of information.
What would be your advice to people breaking into the field?
Linda: Don’t be scared! That’s number one. We have people come in all the time to us and say ‘I’ve heard about this, I want to do this’, and then they hear the cost, and they get scared. I’ve heard people say, ‘I don’t want to be the first one to test it.’ But that’s how we make advances! You have to be the first one. You have to really look at what’s gained from the project, don’t look at it as a final dollar amount. Think of it as a cost per data point and understand the big picture of what you’re really getting.
I had a client years ago in the very early days of next generation sequencing receive a data set from a microarray project and get mad at me that there was too much data. That was a drop in the bucket compared to what we are producing with single-cell. No one should ever say they generated too much information or be intimidated by what we are doing. Be willing to take a chance. Yes, there are a lot of different technologies and versions of these applications available, and they’re coming out very quickly. You have to take that first step – a leap of faith if you will – but it’s the only way that we really advance research properly and effectively.
Want to hear more? Linda Orzolek will be joining us at the Festival of Genomics and Biodata in Boston this October! You don’t want to miss out – tickets are free for 90% of attendees, so grab yours now.