The Evolutionarily-conserved Polyadenosine RNA Binding Protein, Nab2, Cooperates with Splicing Machinery to Regulate the Fate of pre-mRNA

Numerous RNA binding proteins are deposited onto an mRNA transcript to modulate post-transcriptional processing events ensuring proper mRNA maturation. Defining the interplay between RNA binding proteins that couple mRNA biogenesis events is crucial for understanding how gene expression is regulated. To explore how RNA binding proteins control mRNA processing, we investigated a role for the evolutionarily conserved polyadenosine RNA binding protein, Nab2, in mRNA maturation within the nucleus. This work reveals that nab2 mutant cells accumulate intron-containing pre-mRNA in vivo. We extend this analysis to identify genetic interactions between mutant alleles of nab2 and genes encoding the splicing factor, MUD2, and the RNA exosome, RRP6, with in vivo consequences of altered pre-mRNA splicing and poly(A) tail length control. As further evidence linking Nab2 proteins to splicing, an unbiased proteomic analysis of vertebrate Nab2, ZC3H14, identifies physical interactions with numerous components of the spliceosome. We validated the interaction between ZC3H14 and U2AF2/U2AF^(65). Taking all the findings into consideration, we present a model where Nab2/ZC3H14 interacts with spliceosome components to allow proper coupling of splicing with subsequent mRNA processing steps contributing to a kinetic proofreading step that allows properly processed mRNA to exit the nucleus and escape Rrp6-dependent degradation

Evolutionarily conserved polyadenosine RNA binding protein Nab2 cooperates with splicing machinery to regulate the fate of pre-mRNA

Numerous RNA binding proteins are deposited onto an mRNA transcript to modulate posttranscriptional processing events ensuring proper mRNA maturation. Defining the interplay between RNA binding proteins that couple mRNA biogenesis events is crucial for understanding how gene expression is regulated. To explore how RNA binding proteins control mRNA processing, we investigated a role for the evolutionarily conserved polyadenosine RNA binding protein, Nab2, in mRNA maturation within the nucleus. This study reveals that nab2 mutant cells accumulate intron-containing pre-mRNA in vivo. We extend this analysis to identify genetic interactions between mutant alleles of nab2 and genes encoding a splicing factor, MUD2, and RNA exosome, RRP6, with in vivo consequences of altered pre-mRNA splicing and poly(A) tail length control. As further evidence linking Nab2 proteins to splicing, an unbiased proteomic analysis of vertebrate Nab2, ZC3H14, identifies physical interactions with numerous components of the spliceosome. We validated the interaction between ZC3H14 and U2AF2/U2AF(65). Taking all the findings into consideration, we present a model where Nab2/ZC3H14 interacts with spliceosome components to allow proper coupling of splicing with subsequent mRNA processing steps contributing to a kinetic proofreading step that allows properly processed mRNA to exit the nucleus and escape Rrp6-dependent degradation

A systems pharmacology-based approach to identify novel Kv1.3 channel-dependent mechanisms in microglial activation

Abstract Background Kv1.3 potassium channels regulate microglial functions and are overexpressed in neuroinflammatory diseases. Kv1.3 blockade may selectively inhibit pro-inflammatory microglia in neurological diseases but the molecular and cellular mechanisms regulated by Kv1.3 channels are poorly defined. Methods We performed immunoblotting and flow cytometry to confirm Kv1.3 channel upregulation in lipopolysaccharide (LPS)-activated BV2 microglia and in brain mononuclear phagocytes freshly isolated from LPS-treated mice. Quantitative proteomics was performed on BV2 microglia treated with control, LPS, ShK-223 (highly selective Kv1.3 blocker), and LPS+ShK-223. Gene ontology (GO) analyses of Kv1.3-dependent LPS-regulated proteins were performed, and the most representative proteins and GO terms were validated. Effects of Kv1.3-blockade on LPS-activated BV2 microglia were studied in migration, focal adhesion formation, reactive oxygen species production, and phagocytosis assays. In vivo validation of protein changes and predicted molecular pathways were performed in a model of systemic LPS-induced neuroinflammation, employing antigen presentation and T cell proliferation assays. Informed by pathway analyses of proteomic data, additional mechanistic experiments were performed to identify early Kv1.3-dependent signaling and transcriptional events. Results LPS-upregulated cell surface Kv1.3 channels in BV2 microglia and in microglia and CNS-infiltrating macrophages isolated from LPS-treated mice. Of 144 proteins differentially regulated by LPS (of 3141 proteins), 21 proteins showed rectification by ShK-223. Enriched cellular processes included MHCI-mediated antigen presentation (TAP1, EHD1), cell motility, and focal adhesion formation. In vitro, ShK-223 decreased LPS-induced focal adhesion formation, reversed LPS-induced inhibition of migration, and inhibited LPS-induced upregulation of EHD1, a protein involved in MHCI trafficking. In vivo, intra-peritoneal ShK-223 inhibited LPS-induced MHCI expression by CD11b+CD45low microglia without affecting MHCI expression or trafficking of CD11b+CD45high macrophages. ShK-223 inhibited LPS-induced MHCI-restricted antigen presentation to ovalbumin-specific CD8+ T cells both in vitro and in vivo. Kv1.3 co-localized with the LPS receptor complex and regulated LPS-induced early serine (S727) STAT1 phosphorylation. Conclusions We have unraveled novel molecular and functional roles for Kv1.3 channels in pro-inflammatory microglial activation, including a Kv1.3 channel-regulated pathway that facilitates MHCI expression and MHCI-dependent antigen presentation by microglia to CD8+ T cells. We also provide evidence for neuro-immunomodulation by systemically administered ShK peptides. Our results further strengthen the therapeutic candidacy of microglial Kv1.3 channels in neurologic diseases

Progranulin does not bind tumor necrosis factor (TNF) receptors and is not a direct regulator of TNF-dependent signaling or bioactivity in immune or neuronal cells

Progranulin (PGRN) is a secreted glycoprotein expressed in neurons and glia that is implicated in neuronal survival on the basis that mutations in the GRN gene causing haploinsufficiency result in a familial form of frontotemporal dementia (FTD). Recently, a direct interaction between PGRN and tumor necrosis factor receptors (TNFR I/II) was reported and proposed to be a mechanism by which PGRN exerts anti-inflammatory activity, raising the possibility that aberrant PGRN-TNFR interactions underlie the molecular basis for neuroinflammation in frontotemporal lobar degeneration pathogenesis. Here, we report that we find no evidence for a direct physical or functional interaction between PGRN and TNFRs. Using coimmunoprecipitation and surface plasmon resonance (SPR) we replicated the interaction between PGRN and sortilin and that between TNF and TNFRI/II, but not the interaction between PGRN and TNFRs. Recombinant PGRN or transfection of a cDNA encoding PGRN did not antagonize TNF-dependent NFκB, Akt, and Erk1/2 pathway activation; inflammatory gene expression; or secretion of inflammatory factors in BV2 microglia and bone marrow-derived macrophages (BMDMs). Moreover, PGRN did not antagonize TNF-induced cytotoxicity on dopaminergic neuroblastoma cells. Last, co-addition or pre-incubation with various N- or C-terminal-tagged recombinant PGRNs did not alter lipopolysaccharide-induced inflammatory gene expression or cytokine secretion in any cell type examined, including BMDMs from Grn+/- or Grn-/- mice. Therefore, the neuroinflammatory phenotype associated with PGRN deficiency in the CNS is not a direct consequence of the loss of TNF antagonism by PGRN, but may be a secondary response by glia to disrupted interactions between PGRN and Sortilin and/or other binding partners yet to be identified

Additional file 1: Figures S1–S6. of A systems pharmacology-based approach to identify novel Kv1.3 channel-dependent mechanisms in microglial activation

Flow cytometric confirmation of Kv1.3-channel specificity of the ShK-F6CA binding assay is shown in Figure S1. Comparison of ShK-F6CA labeling of Kv1.3 channels in splenic and brain-infiltrating macrophages is shown in Figure S2. Morphological changes induced by LPS, ShK-223, and LPS+ShK-223 treatment conditions are shown in Figure S3. Distribution of missing data in the proteomic data set is shown in Figure S4. Quantitative RT-PCR data showing validation of pro-inflammatory activation of BV2 microglia by LPS are shown in Figure S5. EHD1 upregulation by LPS and inhibition of EHD1 upregulation by ShK-223 is shown in Figure S6. (DOCX 1262 kb

Additional file 1: Table S1. of Trehalose upregulates progranulin expression in human and mouse models of GRN haploinsufficiency: a novel therapeutic lead to treat frontotemporal dementia

List of top compounds identified from the autophagy-lysosome library that increase GRN reporter activity. *, S.D. = standard deviation; **, Z-score = (compound normalized activity – average normalized activity)/population S.D. Figure S1. Validation of mTOR inhibitors on PGRN expression in cultured cells. a Dose–response of mTOR inhibitors in H4 neuroglioma cells. Cells were treated for 24 h and whole cell lysates were analyzed for PGRN expression as well as autophagy induction (p62 and LC3-II). P-S6 and P-4EBP1 were used to monitor mTOR inhibition. Results are representative of two independent experiments. Figure S2. Trehalose treatment increases autophagic flux without affecting lysosomal acidification or cell viability. a Immunoblot of cell lysates from H4 cells showing increased autophagic flux with trehalose treatment. b Quantification of autophagic flux data in a, (n = 3 independent experiments). **P < 0.01, ***P < 0.001, **** P < 0.0001 using one-way ANOVA followed by Tukey’s comparison post-hoc test. c LysoTracker red staining of live H4 cells after 24-h treatment with vehicle (DMSO), bafilomycin A1 (50 nM), or trehalose (50 mM and 100 mM). Scale bar, 100 μM. Images are representative of two independent experiments. d Dose- and time-dependent cell viability after trehalose treatment in H4 cells using trypan-blue exclusion assay, (n = 3 independent experiments measured in duplicate). Statistical differences were calculated by one-way ANOVA followed by Dunnet’s comparison post-hoc test. No significant differences were found for individual treatment groups compared to untreated control. In all graphs, the bars represent the mean ± SEM. Figure S3. Trehalose treatment increases PGRN expression in neuroblastoma cell lines in a dose- and time-dependent manner. a Immunoblot of cell lysates from human SH-SY5Y neuroblastoma cells treated with increasing concentrations of trehalose for 24 h. b Immunoblot of cell lysates from human SH-SY5Y cells treated with 100 mM trehalose for increasing times. c Imunoblot of cell lysates from murine N2a neuroblastoma cells treated with increasing concentrations of trehalose for 24 h. d GRN mRNA levels in SH-SY5Y cells after treatment with 100 mM trehalose for 18 h. **P < 0.01 using unpaired two-tailed Student’s t-test. Results are representative of two independent experiments. In all graphs, the bars represent the mean ± SEM. Figure S4. Characterization of iPSC-derived neurons from primary human fibroblast cultures. a iPSC-derived neurons from a GRN patient express PGRN (green) in cell bodies (arrow) and processes (arrowheads) and neuronal specific marker TUJ1 (magenta). Nuclei (blue) are stained with DAPI. Scale bar, 10 μm. b iPSC-derived neurons from a GRN patient treated with trehalose (100 mM) for 24 h show intense LC3-labeled puncta (arrows), indicating autophagosome formation, compared to vehicle treated GRN neurons. MAP2 (magenta) was used as a neuronal marker. Nuclei (blue) were labeled with DAPI. Scale bar, 10 μm. Figure S5. Oral trehalose treatment does not affect total water consumption, weight change, or plasma PGRN levels in Grn+/− mice. a Average daily water consumption in milliliters (ml) for mice in each treatment group. ****P < 0.0001. b Body weight in grams (g) over time for each treatment group. c Quantification of change in body weight (g) for each treatment group over the duration of the study. d Plasma PGRN levels as determined by Adipogen ELISA. In all graphs, the bars represent the mean ± SEM. Statistical differences of trehalose or sucrose groups relative to vehicle group were calculated by one-way ANOVA followed by Tukey’s comparison post-hoc test. (DOCX 571 kb

A Multi-network Approach Identifies Protein-Specific Co-expression in Asymptomatic and Symptomatic Alzheimer's Disease.

Here, we report proteomic analyses of 129 human cortical tissues to define changes associated with the asymptomatic and symptomatic stages of Alzheimer's disease (AD). Network analysis revealed 16 modules of co-expressed proteins, 10 of which correlated with AD phenotypes. A subset of modules&nbsp;overlapped with RNA co-expression networks, including those associated with neurons and astroglial cell types, showing altered expression in AD, even in the asymptomatic stages. Overlap of RNA and protein networks was otherwise modest, with many modules specific to the proteome, including those linked to microtubule function and inflammation. Proteomic modules were validated in an independent cohort, demonstrating some module expression changes unique to AD and several observed in other neurodegenerative diseases. AD genetic risk loci were concentrated in glial-related modules in the proteome and transcriptome, consistent with their causal role in AD. This multi-network analysis reveals protein- and disease-specific pathways involved in the etiology, initiation, and progression of AD