ISB Q&A: Martin Shelton, Post-Doctoral Fellow
Dr. Martin Shelton is a post-doctoral fellow in the Hood Lab.
Q: What are you currently working on?
Our project, which I work on jointly with Rhishikesh Bargaje and Kalliopi Trachana, along with many other great collaborators both within and outside of the ISB, involves measuring the changes that occur within individual cells as populations of those cells transition from one state to another. We use, as a model system, human induced pluripotent stem cells (iPSCs) that have been directed, through a process called cellular differentiation, to become either brain cells (neurons and astrocytes), heart cells (cardiomyocytes), liver cells (hepatocytes), or a handful of other types of specialized cells. This system is especially useful because in the process of going from a stem cell to one of these differentiated cell types, the population of cells transitions through a series of temporary population states. By measuring differences in the levels of the genes, proteins and other components of the cell’s gene regulatory system as the population migrates through these states, we hope to identify the key factors involved in both maintaining and disrupting biological states. That’s big picture. Little picture, I’m currently working on learning enough of the programming language R to be able to analyze the enormous datasets we’ve generated for these transitioning cell populations.
Q: What’s the biggest challenge in doing this work?
A: Big picture: To identify key factors involved at the very earliest stages of the transitions (i.e. the true drivers) required a level of resolution not provided by the typical omics-level techniques applied to bulk samples—samples composed of hundreds, thousands, or even millions of cells. Instead, what was necessary was to take the breadth of the omics-level techniques and apply them to samples composed of only one cell each—a new area of methodology called single-cell analysis. Single-cell analysis is a powerful tool, with enormous potential, but applying it to our project brought with it the challenges typical of utilizing any new technology. Lack of consensus regarding the best approach meant having to test multiple approaches before proceeding to actual data generation and analysis. Similarly, near constant innovation in the field meant that almost as quickly as an approach was selected, it became obsolete, requiring the newly established protocols to be adapted, or at times entirely scrapped. Taking advantage of these technological advances to generate richer and more global datasets, while maintaining both the quality of the data, and its compatibility with data generated from earlier versions of the techniques, was an enormous challenge. At a personal level, the challenge has been developing a new skill set in computational biology. One that includes coding in a couple of programming languages, applying advanced statistical analyses, and communicating effectively with my more computer literate colleagues.
Q: What’s the potential impact of this work?
A: While this project raises many interesting questions, I’m currently most intrigued by two. First, are there fundamental processes that underlie all biological transitions, be they from stem cells to brain cells in embryonic human development, or from healthy tissue to cancerous tumor, or from stable ecosystems to collapse? If so, then identifying the drivers of biological transitions, and the rules that govern them, could one day allow us to better control them. We already have some promising data generated by our team and others at ISB suggesting that by measuring key transcription factors (proteins that bind DNA and regulate the expression of other genes), we can predict the onset of these transitions – their tipping points – and increase the efficiency of the processes that drive populations towards those transitions. An adjacent question we have not asked, but one I think we are well-positioned to address, is what happens to biological populations that approach, but never reach their tipping point? Do they eventually relax back into their initial state? Can they be rescued?
Secondly, with the advent of systems approaches to human biology and medicine, has the concept of the cell type as an organizing principle for studying and understanding human organ systems outlived its usefulness? A fundamental tenet of cell type classification holds that terminally differentiated cells, like neurons and cardiomyocytes, can only beget cells of the same type. Yet as we learn more about our ability to differentiate (go from less to more specialized cell types following along the normal course of development), de-differentiate (go backwards, e.g. from the more specialized brain cell to the least specialized stem cell), and trans-differentiate (go sideways, from specialized to specialized, changing a brain cell directly into a heart cell) cells, it is becoming apparent that, given the right conditions, every cell has the potential to become other types of cells. Work in the Huang Lab here at ISB shows that, to an extent, cancer represents a pathological de-differentiation of previously more specialized cells to a more primitive state. One question I am eager to learn the answer to is: are there examples of non-pathological, regulated de-differentiations and trans-differentiations in human biology that we’ve missed, simply because we never thought to look for them given our understanding at the time of cell types and their limited potential?
Q: What drives you to push forward?
A: Day-to-day, it’s probably a combination of curiosity, ambition, and a slight case of undiagnosed OCD. I’m genuinely interested in the questions we’re asking, and anxious to find out the answers. In so many ways, the world around us is fascinating and full of amazing things waiting to be discovered; and there’s no field in which that is more true than in biology. Like many scientists, I’m both ambitious enough to set “change the world” as a career goal, and naïve or delusional enough to think I actually can. I’m very competitive, and for all the talk of collaboration and collegiality, biology is still mostly a contact sport. If I’m going to participate, I’d rather win than lose. And I’ve got just enough of an obsessive personality to be really bothered by leaving things unfinished.
Big picture: There are people in the world for whom the word “scientist” does not conjure up a picture of someone who looks like me. There are some who will wonder if I am where I am based on something other than my own merit. Some who think that I don’t belong. I’d like to prove them wrong. More importantly, there are some people who have always believed I’d be right where I am. Who called me doctor or professor long before I made it out of middle school. Some for whom their only reference for “scientist” is me. Some who expect great things from me. I’d like to prove them right.