Gaining a deeper understanding of the immune system
August 17, 2020
As researchers probe the possibilities of cell-based therapeutics, they are discovering new ways to treat disease that have the potential to significantly improve the lives of patients suffering from chronic illnesses and cancer. T cell receptor sequencing is a powerful tool in the quest to better understand the dynamics of the T cell response.
We spoke with Prof. Dirk Busch and Dr. Kilian Schober of the Technical University of Munich who are using human samples and mouse models to study the T cell response during cytomegalovirus (CMV) infection. Through a collaborative effort between Dr. Kilian Schober and ENPICOM scientists Enzo Nio and Lorenzo Fanchi, they were able to gain a deeper understanding of the effects of chronic CMV infection on the T cell receptor repertoire and publish these findings as part of a larger study in Nature Immunology. The insights from their further investigation of the obtained CDR3 sequences with respect to their public occurrence were recently published in the Pathogens MDPI journal.
TUM immunologists Dr. Kilian Schober (left), Dr. Dirk Busch (center), and Dr. Florian Voit (right).
Why study chronic CMV infection?
Prof. Busch: CMV infects a lot of people, many of them latently. But for the immunocompromized, this can be a fatal disease. So, that’s why it’s interesting from a clinical perspective. From an immunology perspective, it is fascinating that the T cell response against CMV can reach astonishing sizes. Over 50% of all CD8+ cells that we studied in this project can be specific for one particular CMV antigen. To put that into perspective, consider that T cells need to cover millions, perhaps billions of targets. Why devote so much of your resources to one target? So, in this study, we looked into the affinity of these cells and if the binding strength of these inflationary T cells increases over time. This was the basic hypothesis. And it was surprising to observe a reverse repertoire evolution in the chronic phase of the disease: the longer the infection lasts, the lower the average binding strength of the T cells.
What was the most challenging part of the research?
Dr. Schober: Technologically it was very challenging. First, we had to identify the alpha and beta chain of each T cell receptor through a single-cell PCR (polymerized chain reaction). Then, taking a mouse T cell and directly inserting the TCR via genetic engineering in a petri dish didn’t work. We had to use mice bone marrow and do genetic engineering with stem cells to generate so-called retrogenic mice. It was time consuming and a technical challenge because we were interested in 15 T cell receptors and had to wait sometimes for a year of infection in the mice just to see if we had it right.
How did repertoire sequencing help your work?
Dr. Schober: We knew that the answers to our questions must lie in how the TCR repertoire evolves. Modern repertoire sequencing adds value because of its resolution. With this technology, we can much more precisely identify which T cells are expanding or contracting.
What are the implications of your findings?
Prof. Busch: Biologically, high and low affinity of T cell receptors may have distinct and complementary advantages for T cell therapy. Our findings suggest that while in the early stages of the disease we see more enrichment of high-affinity T cells, in cases of chronic immune responses T cells with lower binding strength are particularly well maintained.
From a technology perspective, with the help of ENPICOM, we further developed methods that enabled us to track the T cell receptor repertoire over time, monitor how it evolves, and get insight into the underlying mechanism that drives this evolution.
As substantial contributors to research in infectious diseases, cancer immunotherapy, and T cell biology, what do you see are the biggest challenges of working with immune repertoire data and how do you see the future for repertoire sequencing?
Dr. Schober: Most certainly correlating the sequencing data with functionality is a challenge. Despite the high throughput, there’s no method to know what the affinity is and functionality of the T cell receptor. The future is in predicting antigen specificity from sequence alone, and perhaps even predicting functionality. Whether it is experimentally or computationally done; we must link the functionality of the cells to the TCR sequence.
Combining transcriptomic information with TCR sequencing data leads to a different level of data load, which makes it extremely important to do hypothesis-driven research. We are starting to see that often our technology is better than our hypothesis. Now it is good to be using AI to tackle questions we can’t grasp intellectually, but we can’t expect AI to do the research itself. These technologies might be enormously powerful, and they might hold the information we need, but first we must ask the right questions. If research is a linear process, with the hypothesis in the beginning, Rep-Seq in the middle, and analysis at the end, it’s the beginning and the end that need the most attention. Data alone is not enough. We must use technology to investigate the intellectual question and the hypothesis and then combine human intellect and AI for careful, unbiased, systematic downstream analysis to find the truth.
Looking ahead, what could the next generation of immunotherapies and infectious disease treatment look like?
Prof. Busch: First of all, we need to be able to generate cell products faster. We need to reduce the time needed to identify T cell receptors, transgenically re-express them, and genetically engineer the T cells of interest. Secondly, we need to focus on polyclonality and polyfunctionality of T cell populations, for example by generating T cell products that are polyclonal that target many antigens at the same time. Evolution of our immune system has been taking place for millions of years, and in very rare instances we are able to outsmart it. With genetic engineering tools, we are now able to manufacture specialized cells that are highly similar to physiological immune cells. We have never been able to do this before. With the new technological advancements, we can imitate nature more accurately. Physiological T cells are not monoclonal, they are diverse and target different antigens as well as the same antigens with different affinities. We need to learn from nature and use it as a guideline for many research questions and technological developments.
We would like to thank Prof. Dirk Busch and Dr. Kilian Schober for sharing their insights with us. Visit our knowledge center to see how ENPICOM is contributing to scientific research and learn more about our professional software solution to manage, store, analyze, visualize, and compare immune repertoire sequencing data from T and B cell receptors.