Phosphorylation of the smooth muscle master splicing regulator RBPMS regulates its splicing activity.

We previously identified RBPMS as a master regulator of alternative splicing in differentiated smooth muscle cells (SMCs). RBPMS is transcriptionally downregulated during SMC dedifferentiation, but we hypothesized that RBPMS protein activity might be acutely downregulated by post-translational modifications. Publicly available phosphoproteomic datasets reveal that Thr113 and Thr118 immediately adjacent to the RRM domain are commonly both phosphorylated. An RBPMS T113/118 phosphomimetic T/E mutant showed decreased splicing regulatory activity both in transfected cells and in a cell-free in vitro assay, while a non-phosphorylatable T/A mutant retained full activity. Loss of splicing activity was associated with a modest reduction in RNA affinity but significantly reduced RNA binding in nuclear extract. A lower degree of oligomerization of the T/E mutant might cause lower avidity of multivalent RNA binding. However, NMR analysis also revealed that the T113/118E peptide acts as an RNA mimic which can loop back and antagonize RNA-binding by the RRM domain. Finally, we identified ERK2 as the most likely kinase responsible for phosphorylation at Thr113 and Thr118. Collectively, our data identify a potential mechanism for rapid modulation of the SMC splicing program in response to external signals during the vascular injury response and atherogenesis.

Identification of RBPMS as a mammalian smooth muscle master splicing regulator via proximity of its gene with super-enhancers.

Alternative splicing (AS) programs are primarily controlled by regulatory RNA-binding proteins (RBPs). It has been proposed that a small number of master splicing regulators might control cell-specific splicing networks and that these RBPs could be identified by proximity of their genes to transcriptional super-enhancers. Using this approach we identified RBPMS as a critical splicing regulator in differentiated vascular smooth muscle cells (SMCs). RBPMS is highly down-regulated during phenotypic switching of SMCs from a contractile to a motile and proliferative phenotype and is responsible for 20% of the AS changes during this transition. RBPMS directly regulates AS of numerous components of the actin cytoskeleton and focal adhesion machineries whose activity is critical for SMC function in both phenotypes. RBPMS also regulates splicing of other splicing, post-transcriptional and transcription regulators including the key SMC transcription factor Myocardin, thereby matching many of the criteria of a master regulator of AS in SMCs.

All the cells in our body contain the same genetic information, but they only switch on the genes that they need to fulfill their specific role in the organism. Genetic sequences known as enhancers can turn on the genes that are required by a particular cell to perform its tasks. Once a gene is activated, its sequence is faithfully copied into a molecule of RNA which contains segments that code for a protein. A molecular machine then processes the RNA molecule and splices together the coding segments. RNA binding proteins can also regulate this mechanism, and help to splice the coding sections in different ways depending on the type of cell. The process, known as alternative RNA splicing, therefore creates different RNA templates from the same gene. This gives rise to related but different proteins, each suited to the needs of the particular cell in which they are made. However, in some cell types, exactly how this happens has not yet been well documented. For example, in cells that line blood vessels ­ known as vascular smooth muscle cells ­ the RNA binding proteins that drive alternative splicing have not been identified. To find these proteins, Nakagaki-Silva et al. used catalogs of DNA regions called super-enhancers as clues. These sequences strongly activate certain genes in a tissue-specific manner, effectively acting as labels for genes important for a given cell type. In vascular smooth muscle cells, if a super-enhancer switches on a gene that codes for a RNA-binding protein, this protein is probably crucial for the cell to work properly. The approach highlighted a protein called RBPMS, and showed that it controlled alternative RNA splicing of many genes important in smooth muscle cells. This may suggest that when RBPMS regulation is disrupted, certain diseases of the heart and blood vessels could emerge. Finally, the results by Nakagaki-Silva et al. demonstrate that super-enhancers can signpost genes important in regulating splicing or other key processes in particular cell types.

Distinct patterns of cellular immune response elicited by influenza non-adjuvanted and AS03-adjuvanted monovalent H1N1(pdm09) vaccine.

The study aimed at identifying biomarkers of immune response elicited by non-adjuvanted-(NAV) and adjuvanted-(AV) H1N1(pdm09) vaccines. The results showed that despite both vaccines elicited similar levels of anti-H1N1 antibodies at day30 after vaccination, higher reactivity was observed in AV at day180. While AV induced early changes in cell-surface molecules on monocytes, CD4+, CD8+ T-cells and B-cells, NAV triggered minor changes, starting later on at day3. Furthermore, AV induced a late and persistent increase in TLR gene expression after day3, except for tlr4, while NAV displayed earlier but transient tlr3/4/7/9 up-regulation. Contrasting with NAV, prominent chemokine gene expression (cxcl8,cxcl9,ccl5) and a broad spectrum up-regulation of plasmatic biomarkers (CXCL8,IL-6,IL-1ß,IL-12,IL-10) was evident in AV, which showed a major involvement of TNF and IL-10. Similarly, AV induced a robust IL-10-modulated proinflammatory storm, with early and persistent involvement of TNF-α/IL-12/IFN-γ axis derived from NK-cells, CD4+ and CD8+ T-cells along with promiscuous production of IL-4/IL-5/IL-13. Conversely, NAV promotes a concise and restricted intracytoplasmic chemokine/cytokine response, essentially mediated by TNF-α and IL-4, with late IL-10 production by CD8+ T-cells. Systems biology approach underscored that AV guided the formation of an imbricate network characterized by a progressive increase in the number of neighborhood connections amongst innate and adaptive immunity. In AV, the early cross-talk between innate and adaptive immunity, followed by the triad NK/CD4+/CD8+ T-cells at day3, sponsored a later/robust biomarker network. These findings indicate the relevance of adjuvanted vaccination to orchestrate broad, balanced and multifactorial cellular immune events that lead ultimately to a stronger H1N1 humoral immunity.