Epigenomics and transcriptomics of inflammation

Leveraging microfluidics to facilitate immune research

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My first exposure to immune research was during a post-baccalaureate research fellowship at the National Institute on Aging. During my time there, I learned traditional immunological research methods such as flow cytometry, western blot, and immunoprecipitation. I also became familiar with handling mice and dissected out almost every organ in their body at one time or another, as well as lymph nodes and bones. Some of the cells we were looking at were very limited and I recall my coworkers having to pool many mice together to have enough cells to perform their study or to send elsewhere for analysis. It was always a balancing act - using more mice cost more resources, but if they used too few then the resulting data might be unusable. 

It was not the most straightforward path, but I eventually was lucky enough to join Dr. Chang Lu's group at Virginia Tech as a PhD candidate. There, I became familiar with their novel microfluidic technologies - devices  developed that leverage the micro-scale in order to map the epigenome with only a fraction of the cells normally required.  Although I started utilizing bioinformatics while at the NIA, I cemented my focus in bioinformatics by expanding my skills to include analysis of the epigenome, our lab's specialty, and the methylome. I would work with an experimentalist from our group while our samples would come from our collaborators. Due to the wide applicability of our biotechnologies, we've had the pleasure of developing several effective collaborations with other researchers that span a variety of fields. One collaborator that we worked with on multiple occasions is Dr. Liwu Li, a professor of inflammation biology and immunology at Virginia Tech. 

In this study, we utilized our MOWChIP technology to profile the epigenome of bone marrow-derived monocytes that were chronically stimulated with lipopolysaccharide (LPS) at a low- or high-dose, or to a PBS control. This allowed us to see the differences between low-grade inflammation and severe monocyte exhaustion. To supplement this, we also used low-input transcriptomic methods to correlate these enhancer changes to those in gene expression.  However, signaling cascades are intricate and simply studying WT C57BL/6 mice would have limited our conclusions. In particular, the primary signaling pathway in monocytes exposed to bacterial endotoxins is the Toll-like Receptor 4 (TLR4) pathway, which has two main sub-pathways. Thus, we chose to also include epigenomic and transcriptomic analysis of TRAM-deficient and IRAK-M-deficient monocytes to target each of these two sub-pathways. Broadly, we were able to determine that low-dose LPS preferentially utilizes the TRAM-dependent pathway of TLR4 signaling while high-dose LPS uniquely upregulates exhaustion signatures with metabolic and proliferative pathways, and our data suggest the importance of epigenetic regulations in driving differential responses. 

As time goes on, there seem to be two interdependent and necessary prongs of immunology research. Traditional immunology research methods are powerful techniques that can provide significant insight into the structure, function, and activity of a few select targets at a given time. In contrast, genome-wide technologies have become more widespread and they provide a strong picture of the whole while revealing patterns that might otherwise be missed. Furthermore, low-input technologies that profile the epigenome or transcriptome are a significant boon to any community, but particularly the immunology field with their many rare or limited cell types. Yet, such technologies often have steep learning curves for labs unfamiliar with them, and I wholly believe it was the interdisciplinary aspect of our project that provided us with a large measure of success. It took the work of all of us to bring this research to fruition, and I hope it spurs more collaborative work in the future.

Lynette Naler

PhD Graduate, Virginia Tech