Effect of High Expression of IRF5 on B Cell Activation After Antigen Stimulation
Faculty Mentor: Brian Poole, Microbiology and Molecular Biology
While autoimmune diseases are very prevalent in the United States, little is understood
about the cause of autoimmunity, making it difficult to take preventative measures and
develop treatments. Previous studies have determined that a common genetic risk
factor across many autoimmune diseases leads to B cell overexpression of the
transcription factor IRF5 (1,2,4). Researchers have also discovered that high IRF5
levels are strongly associated with autoantibody production, suggesting that IRF5 may
play a role in actually causing autoimmunity. At this point, however, it is unclear how
IRF5 promotes the production of autoantibodies.
Normally during development, a B cell is killed if it binds to self-antigen, but a less
sensitive B cell receptor (BCR) may allow potentially self-binding B cells to escape this
selection process. This would result in autoantibody production and thus autoimmunity.
Previous work in Dr. Poole’s lab has shown that cells that overexpress IRF5 also under
express many genes associated with the BCR signaling pathway, making it very
probable that IRF5 overexpression results in decreased BCR sensitivity (3). The
purpose of this project was to investigate a possible pathway for autoimmune disease
pathogenesis by examining how overexpression of the transcription factor IRF5 affects
B cell receptor sensitivity. I hypothesized that IRF5 overexpression causes B cells to
have a decreased response to signaling through the BCR.
Primary naïve B cells were transduced with the IRF5 gene using the lentiviral
expression vector pULTRA. Magnetic cell sorting was used to isolate cells with sufficient
expression of the transduced IRF5 gene. IRF5-overexpressing, vector transduced
control, and non-transduced control naive B cells were placed into chamber slides and
loaded with Fura-2 dye. The cells were then stimulated with 15 μg/ml anti-IgM, which
stimulates naïve B cells through the BCR and leads to calcium flux. Calcium response
was measured using ratio-imaging microscopy.
Although we have made several attempts to sort IRF5 transduced cells and to measure
BCR sensitivity through calcium microscopy, we do not have any conclusive data as of
yet. While half of our cell sorts yielded 90 percent efficiency, the other half yielded only
70 percent efficiency (meaning that we couldn’t even use 30 percent of those cells).
These yields were too low to correctly measure calcium flux in stimulated B cells.
The first problem we ran into is that the cell sorter is a new machine and wasn’t running
at optimal efficiency, resulting in very low cell counts. The second problem is that
calcium microscopy is not effective with low cell counts. This is because at the required
20x magnification, at least 10 cells need to be in frame. This is difficult to achieve when
there aren’t many cells to begin with. In addition, even when we managed to find 10
cells in a frame, they kept moving out of frame, which meant we couldn’t include them
as data points.
In order to finish this experiment we need a way to either achieve a higher cell count
during cell sorting or keep enough cells in frame to effectively measure calcium flux. We
discovered that coating our chamber slides with D-lysine before loading them with B
cells actually helps the B cells stick in place (5), giving us plenty of cells that stay in
frame rather than moving around everywhere.
The D-lysine coated plate method will be used in our next attempt at calcium
microscopy in January and should allow us to gather significant data whether or not we
continue to get low cell counts during cell sorting. We foresee no further complications
that would prevent us from completing this experiment. The results from this study will
lead to a better understanding of the immune system and a better understanding of how
autoimmune diseases work. They will also have the potential to help us learn how some
autoimmune diseases may be treated or even prevented.
1. Clark, D.N., et al., Four Promoters of IRF5 Respond Distinctly to Stimuli and are Affected by
Autoimmune-Risk Polymorphisms. Front Immunol, 2013. 4: p. 360.
2. Clark, D.N., et al., Molecular Effects of Autoimmune-Risk Promoter Polymorphisms on
Expression, Exon Choice, and Translational Efficiency of Interferon Regulatory Factor 5. J
Interferon Cytokine Res, 2013.
3. Guthridge J, et al. Effects of IRF5 lupus risk haplotype on pathways predicted to influence B cell
functions. Journal of Biomedicine and Biotechnology. 2012 Feb;2012(594056):12.
4. Hayley L. Eames, Alastair L. Corbin, and Irina A. Udalova. Interferon Regulatory Factor 5 (IRF5)
in human autoimmunity and murine models of autoimmune disease. Translational Research,
2015; DOI: 10.1016/j.trsl.2015.06.01
5. Peñaherrera, A, et al., Evaluation of cell culture in microfluidic chips for application in monoclonal
antibody production. Micro and Nano Technologies for Biology and Life Sciences, 2016. 158: p.