CORDIS - Forschungsergebnisse der EU

The molecular regulation of T helper cell subtype plasticity.

Final Report Summary - THPLAST (The molecular regulation of T helper cell subtype plasticity.)

Differences in gene expression patterns determine development, differentiation and the physiology of an organism. Naïve CD4+ T cells differentiate into distinct lineages to achieve successful adaptive immune responses to diverse categories of pathogens. The molecular regulation of this development to the distinct subsets of cells is still incompletely resolved. Methods to explore gene expression in T helper (Th) cells include conventional transcriptomics either by microarrays or mRNA-sequencing, which are based on populations of cells. Expression profiles from these types of experiment are averages over large numbers of cells. Averaging across a cell population hides whether there are one or more distinct cell types within the population. This is crucial, as in most experimental samples it is unclear to what extent a cell population is truly homogeneous.
In this research, my goal is to study the dynamics of the immune system in the N. brasiliensis mouse model, a worm that is known to induce a type 2 immune response in rodents. I determined the molecular changes during Th cell differentiation upon the worm immune response by monitoring gene expression at the single cell level using the BioMark microfluidics robot to perform qPCR for 96 genes in parallel in 96 cells. Single CD4+ T helper cells were monitored from different mouse tissues: mediastinal lymph nodes, mesenteric lymph nodes, lungs, and gut, from infected and uninfected mice, and at different times points: 0, 3, 5, and 7 days.
My specific objectives included first, a technical assessment of the qPCR protocol on the platform, including checking whether mRNAs level correlate with the corresponding protein levels in single cells. Secondly, to quantify changes in gene expression during T helper cell differentiation, to reveal the heterogeneity in this compartment of the immune system, and thirdly, to detect changes in cell populations in different tissues and time points during the infection.
For my first objective, I found that the BioMark technical error between sample replicates in the same dynamic array is 0.127±0.502 Ct, while in different dynamic arrays the error is 0.167±0.766 Ct. The technical error of the protocol was found to be less than 0.707±0.327 Ct. This corresponds to less than a 2-fold change in gene expression, which is an acceptable error. In addition, I found that 90% of the cells (n=105) that were sorted to contain high protein levels, also expressed the corresponding mRNA. 38% of cells (n=232) sorted for low protein levels, also expressed the transcript, and finally, 10% of cells (n=468) that did not contain the protein, did express the mRNA. This is an acceptable level of concordance between protein and mRNA levels in single cells, so the gene expression level can indeed be used to reflect protein levels.
Toward my second objective, I examined expression for a penal of 96 genes in both naïve and activated single T helper cells across 618 cells in total. I identified genes up- and downregulated between naïve and activated cells. The genes that were highly expressed in naïve included genes that are known to be highly expressed in those cells, genes that are known to be expressed in activated th1 subtypes, and genes that are not known to have a role in T helper cells.
Genes that are found to be high in the activated cells, include known th2 regulators gene, and T regulatory cells (Treg) regulator genes. Those two subtypes are known to be involved in Type 2 immunity. However, in addition to those genes, I could also find other genes that are know to be regulators in other subtypes or genes that are not known to be expressed in T helper cells.
Next, I checked which sub populations are found among activated cell, and found 3 major groups. The first group express FOXP3 and GATA3, which probably correspond to Tregs. The second express GATA3 and CXCR5, which might correspond to Follicular Th cells (Tfh). And finally, I discovered a previously unknown population of cells that express GATA3 and RORA. This is of interest, as the nuclear hormone receptor transcription factor plays an important role in other cell types, such as ILC2 cells, but has not yet been characterized in the T helper cell compartment. RORA (RAR-Related Orphan Receptor A) is a nuclear hormone receptor. It can bind DNA as a monomer or homodimer, and recognizes hormone response elements. RORA has been shown to bind different ligands. This might suggest that this population is involved in cytokine secretion in the peripheral tissues, first to enhance activation, and then to reduce it, depending on the signal and RORA ligand.
Toward my third aim, I analyzed when and where these subpopulations of cells were present. I found that Tregs and potentially Tfh cells are mostly located in lymph nodes, while RORA-expressing cells are mostly located in the peripheral tissues (lung and gut). I also find that RORA-expressing cells are present at days 5-7, and 67% of the cytokine-expressing cells express RORA as well.
In summary, the results of this study shed light on different areas of biology, including basic molecular biology, immunology, and regulation of transcription. First, we showed that mRNA levels correlate well with protein levels in single cells, which was known in terms of bulk populations of cells but not individual cells.. Second, we find new genes that are differentially expressed between naive and activated cells, which implicate them in this differentiation process. Identification of such genes can help to gain a more complete understanding of the regulatory network involved in T helper cell development, and the changes in gene expression in response to extrinsic signals. We also find that some cells express several key regulators together, which imply that they might be plastic in terms of their cellular identity.
Th2 cells are associated with exacerbation of disease, such as autoimmune diseases, allergies and asthma. Therefore, reprogramming of this cell lineage is a potential target of autoimmune- and allergen-specifictherapy. In this study, we also find a new subset of cells that express the transcription factor RORA. RORA is a nuclear hormone receptor, which can bind different ligands and thus control expression of a set of genes. We show that these RORA-expressing cells are involved in cytokine secretion at peripheral sites (lungs, gut). This finding may yield new avenues for research with implications for drug design, such as identifying the specific ligand of RORA, its target genes and its specific role in the immune response in the peripheral tissues.