Deconvolving the contributions of cell-type heterogeneity on cortical gene expression.

Complexity of cell-type composition has created much skepticism surrounding the interpretation of bulk tissue transcriptomic studies. Recent studies have shown that deconvolution algorithms can be applied to computationally estimate cell-type proportions from gene expression data of bulk blood samples, but their performance when applied to brain tissue is unclear. Here, we have generated an immunohistochemistry (IHC) dataset for five major cell-types from brain tissue of 70 individuals, who also have bulk cortical gene expression data. With the IHC data as the benchmark, this resource enables quantitative assessment of deconvolution algorithms for brain tissue. We apply existing deconvolution algorithms to brain tissue by using marker sets derived from human brain single cell and cell-sorted RNA-seq data. We show that these algorithms can indeed produce informative estimates of constituent cell-type proportions. In fact, neuronal subpopulations can also be estimated from bulk brain tissue samples. Further, we show that including the cell-type proportion estimates as confounding factors is important for reducing false associations between Alzheimer's disease phenotypes and gene expression. Lastly, we demonstrate that using more accurate marker sets can substantially improve statistical power in detecting cell-type specific expression quantitative trait loci (eQTLs).

Meta-Analysis of the Alzheimer's Disease Human Brain Transcriptome and Functional Dissection in Mouse Models.

We present a consensus atlas of the human brain transcriptome in Alzheimer's disease (AD), based on meta-analysis of differential gene expression in 2,114 postmortem samples. We discover 30 brain coexpression modules from seven regions as the major source of AD transcriptional perturbations. We next examine overlap with 251 brain differentially expressed gene sets from mouse models of AD and other neurodegenerative disorders. Human-mouse overlaps highlight responses to amyloid versus tau pathology and reveal age- and sex-dependent expression signatures for disease progression. Human coexpression modules enriched for neuronal and/or microglial genes broadly overlap with mouse models of AD, Huntington's disease, amyotrophic lateral sclerosis, and aging. Other human coexpression modules, including those implicated in proteostasis, are not activated in AD models but rather following other, unexpected genetic manipulations. Our results comprise a cross-species resource, highlighting transcriptional networks altered by human brain pathophysiology and identifying correspondences with mouse models for AD preclinical studies.

BIN1 favors the spreading of Tau via extracellular vesicles.

Despite Bridging INtegrator 1 (BIN1) being the second most statistically-significant locus associated to Late Onset Alzheimer's Disease, its role in disease pathogenesis remains to be clarified. As reports suggest a link between BIN1, Tau and extracellular vesicles, we investigated whether BIN1 could affect Tau spreading via exosomes secretion. We observed that BIN1-associated Tau-containing extracellular vesicles purified from cerebrospinal fluid of AD-affected individuals are seeding-competent. We showed that BIN1 over-expression promotes the release of Tau via extracellular vesicles in vitro as well as exacerbation of Tau pathology in vivo in PS19 mice. Genetic deletion of Bin1 from microglia resulted in reduction of Tau secretion via extracellular vesicles in vitro, and in decrease of Tau spreading in vivo in male, but not female, mice, in the context of PS19 background. Interestingly, ablation of Bin1 in microglia of male mice resulted in significant reduction in the expression of heat-shock proteins, previously implicated in Tau proteostasis. These observations suggest that BIN1 could contribute to the progression of AD-related Tau pathology by altering Tau clearance and promoting release of Tau-enriched extracellular vesicles by microglia.

Identification and validation of a tumor-infiltrating Treg transcriptional signature conserved across species and tumor types.

FoxP3+ T regulatory (Treg) cells are central elements of immunologic tolerance. They are abundant in many tumors, where they restrict potentially favorable antitumor responses. We used a three-pronged strategy to identify genes related to the presence and function of Tregs in the tumor microenvironment. Gene expression profiles were generated from tumor-infiltrating Tregs (TITRs) of both human and mouse tumors and were compared with those of Tregs of lymphoid organs or normal tissues from the same individuals. A computational deconvolution of whole-tumor datasets from the Cancer Genome Atlas (TCGA) was performed to identify transcripts specifically associated with Tregs across thousands of tumors from different stages and locations. We identified a set of TITR-differential transcripts with striking reproducibility between tumor types in mice, between mice and humans, and between different human patients spanning tumor stages. Many of the TITR-preferential transcripts were shared with "tissue Tregs" residing in nonlymphoid tissues, but a tumor-preferential segment could be identified. Many of these TITR signature transcripts were confirmed by mining of TCGA datasets, which also brought forth transcript modules likely representing the parenchymal attraction of, or response to, tumor Tregs. Importantly, the TITR signature included several genes encoding effective targets of tumor immunotherapy. A number of other targets were validated by CRISPR-based gene inactivation in mouse Tregs. These results confirm the validity of the signature, generating a wealth of leads for understanding the role of Tregs in tumor progression and identifying potential targets for cancer immunotherapy.

Connective Tissue Growth Factor Domain 4 Amplifies Fibrotic Kidney Disease through Activation of LDL Receptor-Related Protein 6.

Connective tissue growth factor (CTGF), a matrix-associated protein with four distinct cytokine binding domains, has roles in vasculogenesis, wound healing responses, and fibrogenesis and is upregulated in fibroblasts and myofibroblasts in disease. Here, we investigated the role of CTGF in fibrogenic cells. In mice, tissue-specific inducible overexpression of CTGF by kidney pericytes and fibroblasts had no bearing on nephrogenesis or kidney homeostasis but exacerbated inflammation and fibrosis after ureteral obstruction. These effects required the WNT receptor LDL receptor-related protein 6 (LRP6). Additionally, pericytes isolated from these mice became hypermigratory and hyperproliferative on overexpression of CTGF. CTGF is cleaved in vivo into distinct domains. Treatment with recombinant domain 1, 1+2 (N terminus), or 4 (C terminus) independently activated myofibroblast differentiation and wound healing responses in cultured pericytes, but domain 4 showed the broadest profibrotic activity. Domain 4 exhibited low-affinity binding to LRP6 in in vitro binding assays, and inhibition of LRP6 or critical signaling cascades downstream of LRP6, including JNK and WNT/ß-catenin, inhibited the biologic activity of domain 4. Administration of blocking antibodies specifically against CTGF domain 4 or recombinant Dickkopf-related protein-1, an endogenous inhibitor of LRP6, effectively inhibited inflammation and fibrosis associated with ureteral obstruction in vivo Therefore, domain 4 of CTGF and the WNT signaling pathway are important new targets in fibrosis.

CAT7 and cat7l Long Non-coding RNAs Tune Polycomb Repressive Complex 1 Function during Human and Zebrafish Development.

The essential functions of polycomb repressive complex 1 (PRC1) in development and gene silencing are thought to involve long non-coding RNAs (lncRNAs), but few specific lncRNAs that guide PRC1 activity are known. We screened for lncRNAs, which co-precipitate with PRC1 from chromatin and found candidates that impact polycomb group protein (PcG)-regulated gene expression in vivo A novel lncRNA from this screen, CAT7, regulates expression and polycomb group binding at the MNX1 locus during early neuronal differentiation. CAT7 contains a unique tandem repeat domain that shares high sequence similarity to a non-syntenic zebrafish analog, cat7l Defects caused by interference of cat7l RNA during zebrafish embryogenesis were rescued by human CAT7 RNA, enhanced by interference of a PRC1 component, and suppressed by interference of a known PRC1 target gene, demonstrating cat7l genetically interacts with a PRC1. We propose a model whereby PRC1 acts in concert with specific lncRNAs and that CAT7/cat7l represents convergent lncRNAs that independently evolved to tune PRC1 repression at individual loci.

Cytometry by time-of-flight immunophenotyping identifies a blood Sjögren's signature correlating with disease activity and glandular inflammation.

BACKGROUND: Mass cytometry has recently emerged as a promising tool for clinical research. However, few studies have demonstrated its benefit for patient stratification and biomarker identification. Primary Sjögren's syndrome (pSS) is a prototype of chronic autoimmune disease, the pathogenesis of which remains unclear and for which treatment does not exist. OBJECTIVE: This observational case-control study was designed to discover new cellular biomarkers and therapeutic targets in patients with pSS. METHODS: Forty-nine patients with pSS and 45 control subjects were enrolled for clinical evaluation and mass cytometry quantification of 34 protein markers in blood. For a third of these subjects, matched labial salivary gland biopsy specimens were also analyzed by mass cytometry and immunohistochemistry. RESULTS: In salivary gland biopsy specimens from patients with pSS, we identified a high number of activated CD8(+) T cells, terminally differentiated plasma cells, and activated epithelial cells, pointing to new pathogenic mechanisms for future clinical intervention. In blood, we identified a 6-cell disease signature defined by decreased numbers of CD4 and memory B lymphocytes, decreased plasmacytoid dendritic cell numbers, and increased representation of activated CD4 and CD8 T cells and plasmablasts. These blood cellular components correlated with clinical parameters and, when taken together, clustered patients into subsets with distinct disease activity and glandular inflammation. CONCLUSION: This first application of mass cytometry to a well-stratified clinical cohort and small biopsy tissues establishes the benefits of such an approach for the discovery of new biomarkers and therapeutic targets. Similar high-dimensional immunophenotyping strategies could be implemented in longitudinal and interventional clinical settings in this and other disease areas.

Chromatin topology is coupled to Polycomb group protein subnuclear organization.

The genomes of metazoa are organized at multiple scales. Many proteins that regulate genome architecture, including Polycomb group (PcG) proteins, form subnuclear structures. Deciphering mechanistic links between protein organization and chromatin architecture requires precise description and mechanistic perturbations of both. Using super-resolution microscopy, here we show that PcG proteins are organized into hundreds of nanoscale protein clusters. We manipulated PcG clusters by disrupting the polymerization activity of the sterile alpha motif (SAM) of the PcG protein Polyhomeotic (Ph) or by increasing Ph levels. Ph with mutant SAM disrupts clustering of endogenous PcG complexes and chromatin interactions while elevating Ph level increases cluster number and chromatin interactions. These effects can be captured by molecular simulations based on a previously described chromatin polymer model. Both perturbations also alter gene expression. Organization of PcG proteins into small, abundant clusters on chromatin through Ph SAM polymerization activity may shape genome architecture through chromatin interactions.

Small molecule mediated inhibition of RORγ-dependent gene expression and autoimmune disease pathology in vivo.

Retinoic acid receptor-related orphan nuclear receptor γ (RORγ) orchestrates a pro-inflammatory gene expression programme in multiple lymphocyte lineages including T helper type 17 (Th17) cells, γδ T cells, innate lymphoid cells and lymphoid tissue inducer cells. There is compelling evidence that RORγ-expressing cells are relevant targets for therapeutic intervention in the treatment of autoimmune and inflammatory diseases. Unlike Th17 cells, where RORγ expression is induced under specific pro-inflammatory conditions, γδ T cells and other innate-like immune cells express RORγ in the steady state. Small molecule mediated disruption of RORγ function in cells with pre-existing RORγ transcriptional complexes represents a significant and challenging pharmacological hurdle. We present data demonstrating that a novel, selective and potent small molecule RORγ inhibitor can block the RORγ-dependent gene expression programme in both Th17 cells and RORγ-expressing γδ T cells as well as a disease-relevant subset of human RORγ-expressing memory T cells. Importantly, systemic administration of this inhibitor in vivo limits pathology in an innate lymphocyte-driven mouse model of psoriasis.

Secreted Metabolites of Bifidobacterium infantis and Lactobacillus acidophilus Protect Immature Human Enterocytes from IL-1ß-Induced Inflammation: A Transcription Profiling Analysis.

Combination regimens of Bifidobacterium infantis and Lactobacillus acidophilus have been demonstrated to prevent necrotizing enterocolitis (NEC) in clinical trials. However, the molecular mechanisms responsible for this protective effect are not well understood. Additionally, conditioned media from individual cultures of these two probiotics show strain specific modulation of inflammation using in vitro human intestinal NEC models. Here we report a transcription profiling analysis of gene expression in immature human fetal intestinal epithelial cells (H4 cells) pretreated with conditioned media from B. infantis (BCM) or L. acidophilus (LCM) prior to IL-1ß stimulation. Compared with control media, the two probiotic-conditioned media (PCM) treatments altered the expression of hundreds of genes involved in the immune response, apoptosis and cell survival, cell adhesion, the cell cycle, development and angiogenesis. In IL-1ß-stimulated cells, PCM treatment decreased the upregulation of genes in the NF-κB activation pathway and downregulated genes associated with extracellular matrix (ECM) remodeling. Compared with LCM, BCM showed more significant modulatory effects on ECM remodeling, reflected by a lower p value. IL-6 and IL-8 production was significantly reduced in IL-1ß-stimulated cells pretreated with PCM (p<0.05), which was consistent with their altered gene expression. Western blot analysis showed that compared with IL-1ß stimulation alone, PCM treatment attenuated the decrease of cytoplasmic IκBα and NF-κB p65 levels as well as the increase of nuclear NF-κB p65 levels in the stimulated cells (p<0.05). In conclusion, PCM treatment exerted anti-inflammatory effects in immature human fetal enterocytes primarily by modulating genes in the NF-κB signaling and ECM remodeling pathways. Additionally, some components of these signaling pathways, particularly the ECM remodeling pathway, were more profoundly affected by BCM than LCM.

ATRX directs binding of PRC2 to Xist RNA and Polycomb targets.

X chromosome inactivation (XCI) depends on the long noncoding RNA Xist and its recruitment of Polycomb Repressive Complex 2 (PRC2). PRC2 is also targeted to other sites throughout the genome to effect transcriptional repression. Using XCI as a model, we apply an unbiased proteomics approach to isolate Xist and PRC2 regulators and identified ATRX. ATRX unexpectedly functions as a high-affinity RNA-binding protein that directly interacts with RepA/Xist RNA to promote loading of PRC2 in vivo. Without ATRX, PRC2 cannot load onto Xist RNA nor spread in cis along the X chromosome. Moreover, epigenomic profiling reveals that genome-wide targeting of PRC2 depends on ATRX, as loss of ATRX leads to spatial redistribution of PRC2 and derepression of Polycomb responsive genes. Thus, ATRX is a required specificity determinant for PRC2 targeting and function.

Interindividual variation in human T regulatory cells.

FOXP3(+) regulatory T (Treg) cells enforce immune self-tolerance and homeostasis, and variation in some aspects of Treg function may contribute to human autoimmune diseases. Here, we analyzed population-level Treg variability by performing genome-wide expression profiling of CD4(+) Treg and conventional CD4(+) T (Tconv) cells from 168 donors, healthy or with established type-1 diabetes (T1D) or type-2 diabetes (T2D), in relation to genetic and immunologic screening. There was a range of variability in Treg signature transcripts, some almost invariant, others more variable, with more extensive variability for genes that control effector function (ENTPD1, FCRL1) than for lineage-specification factors like FOXP3 or IKZF2. Network analysis of Treg signature genes identified coregulated clusters that respond similarly to genetic and environmental variation in Treg and Tconv cells, denoting qualitative differences in otherwise shared regulatory circuits whereas other clusters are coregulated in Treg, but not Tconv, cells, suggesting Treg-specific regulation of genes like CTLA4 or DUSP4. Dense genotyping identified 110 local genetic variants (cis-expression quantitative trait loci), some of which are specifically active in Treg, but not Tconv, cells. The Treg signature became sharper with age and with increasing body-mass index, suggesting a tuning of Treg function with repertoire selection and/or chronic inflammation. Some Treg signature transcripts correlated with FOXP3 mRNA and/or protein, suggesting transcriptional or posttranslational regulatory relationships. Although no single transcript showed significant association to diabetes, overall expression of the Treg signature was subtly perturbed in T1D, but not T2D, patients.

Combined administration of testosterone plus an ornithine decarboxylase inhibitor as a selective prostate-sparing anabolic therapy.

Because of its anabolic effects on muscle, testosterone is being explored as a function-promoting anabolic therapy for functional limitations associated with aging; however, concerns about testosterone's adverse effects on prostate have inspired efforts to develop strategies that selectively increase muscle mass while sparing the prostate. Testosterone's promyogenic effects are mediated through upregulation of follistatin. We show here that the administration of recombinant follistatin (rFst) increased muscle mass in mice, but had no effect on prostate mass. Consistent with the results of rFst administration, follistatin transgenic mice with constitutively elevated follistatin levels displayed greater muscle mass than controls, but had similar prostate weights. To elucidate signaling pathways regulated differentially by testosterone and rFst in prostate and muscle, we performed microarray analysis of mRNAs from prostate and levator ani of castrated male mice treated with vehicle, testosterone, or rFst. Testosterone and rFst shared the regulation of many transcripts in levator ani; however, in prostate, 593 transcripts in several growth-promoting pathways were differentially expressed after testosterone treatment, while rFst showed a negligible effect with only 9 transcripts differentially expressed. Among pathways that were differentially responsive to testosterone in prostate, we identified ornithine decarboxylase (Odc1), an enzyme in polyamine biosynthesis, as a testosterone-responsive gene that is unresponsive to rFst. Accordingly, we administered testosterone with and without α-difluoromethylornithine (DFMO), an Odc1 inhibitor, to castrated mice. DFMO selectively blocked testosterone's effects on prostate, but did not affect testosterone's anabolic effects on muscle. Co-administration of testosterone and Odc1 inhibitor presents a novel therapeutic strategy for prostate-sparing anabolic therapy.

Differential splicing across immune system lineages.

Alternative splicing (AS) allows increased diversity and orthogonal regulation of the transcriptional products of mammalian genomes. To assess the distribution and variation of alternative splicing across cell lineages of the immune system, we comprehensively analyzed RNA sequencing and microarray data generated by the Immunological Genome Project Consortium. AS is pervasive: 60% of genes showed frequent AS isoforms in T or B lymphocytes, with 7,599 previously unreported isoforms. Distinct cell specificity was observed, with differential exon skipping in 5% of genes otherwise coexpressed in both B and T cells. The distribution of isoforms was mostly all or none, suggesting on/off switching as a frequent mode of AS regulation in lymphocytes. From the identification of differential exon use in the microarray data, clustering of exon inclusion/exclusion patterns across all Immunological Genome Project cell types showed that ∼70% of AS exons are distributed along a common pattern linked to lineage differentiation and cell cycling. Other AS events distinguished myeloid from lymphoid cells or affected only a small set of exons without clear lineage specificity (e.g., Ptprc). Computational analysis predicted specific associations between AS exons and splicing regulators, which were verified by detection of the hnRPLL/Ptprc connection.

A multiply redundant genetic switch 'locks in' the transcriptional signature of regulatory T cells.

The transcription factor Foxp3 participates dominantly in the specification and function of Foxp3(+)CD4(+) regulatory T cells (T(reg) cells) but is neither strictly necessary nor sufficient to determine the characteristic T(reg) cell signature. Here we used computational network inference and experimental testing to assess the contribution of other transcription factors to this. Enforced expression of Helios or Xbp1 elicited distinct signatures, but Eos, IRF4, Satb1, Lef1 and GATA-1 elicited exactly the same outcome, acting in synergy with Foxp3 to activate expression of most of the T(reg) cell signature, including key transcription factors, and enhancing occupancy by Foxp3 at its genomic targets. Conversely, the T(reg) cell signature was robust after inactivation of any single cofactor. A redundant genetic switch thus 'locked in' the T(reg) cell phenotype, a model that would account for several aspects of T(reg) cell physiology, differentiation and stability.

microRNA regulatory network inference identifies miR-34a as a novel regulator of TGF-ß signaling in glioblastoma.

UNLABELLED: Leveraging The Cancer Genome Atlas (TCGA) multidimensional data in glioblastoma, we inferred the putative regulatory network between microRNA and mRNA using the Context Likelihood of Relatedness modeling algorithm. Interrogation of the network in context of defined molecular subtypes identified 8 microRNAs with a strong discriminatory potential between proneural and mesenchymal subtypes. Integrative in silico analyses, a functional genetic screen, and experimental validation identified miR-34a as a tumor suppressor in proneural subtype glioblastoma. Mechanistically, in addition to its direct regulation of platelet-derived growth factor receptor-alpha (PDGFRA), promoter enrichment analysis of context likelihood of relatedness-inferred mRNA nodes established miR-34a as a novel regulator of a SMAD4 transcriptional network. Clinically, miR-34a expression level is shown to be prognostic, where miR-34a low-expressing glioblastomas exhibited better overall survival. This work illustrates the potential of comprehensive multidimensional cancer genomic data combined with computational and experimental models in enabling mechanistic exploration of relationships among different genetic elements across the genome space in cancer. SIGNIFICANCE: We illustrate here that network modeling of complex multidimensional cancer genomic data can generate a framework in which to explore the biology of cancers, leading to discovery of new pathogenetic insights as well as potential prognostic biomarkers. Specifically in glioblastoma, within the context of the global network, promoter enrichment analysis of network edges uncovered a novel regulation of TGF-ß signaling via a Smad4 transcriptomic network by miR-34a.

A cluster of coregulated genes determines TGF-beta-induced regulatory T-cell (Treg) dysfunction in NOD mice.

Foxp3(+) regulatory T cells (Tregs) originate in the thymus, but the Treg phenotype can also be induced in peripheral lymphoid organs or in vitro by stimulation of conventional CD4(+) T cells with IL-2 and TGF-ß. There have been divergent reports on the suppressive capacity of these TGF-Treg cells. We find that TGF-Tregs derived from diabetes-prone NOD mice, although expressing normal Foxp3 levels, are uniquely defective in suppressive activity, whereas TGF-Tregs from control strains (B6g7) or ex vivo Tregs from NOD mice all function normally. Most Treg-typical transcripts were shared by NOD or B6g7 TGF-Tregs, except for a small group of differentially expressed genes, including genes relevant for suppressive activity (Lrrc32, Ctla4, and Cd73). Many of these transcripts form a coregulated cluster in a broader analysis of T-cell differentiation. The defect does not map to idd3 or idd5 regions. Whereas Treg cells from NOD mice are normal in spleen and lymph nodes, the NOD defect is observed in locations that have been tied to pathogenesis of diabetes (small intestine lamina propria and pancreatic lymph node). Thus, a genetic defect uniquely affects a specific Treg subpopulation in NOD mice, in a manner consistent with a role in determining diabetes susceptibility.

MicroRNAs as modulators of smoking-induced gene expression changes in human airway epithelium.

We have shown that smoking impacts bronchial airway gene expression and that heterogeneity in this response associates with smoking-related disease risk. In this study, we sought to determine whether microRNAs (miRNAs) play a role in regulating the airway gene expression response to smoking. We examined whole-genome miRNA and mRNA expression in bronchial airway epithelium from current and never smokers (n = 20) and found 28 miRNAs to be differentially expressed (P < 0.05) with the majority being down-regulated in smokers. We further identified a number of mRNAs whose expression level is highly inversely correlated with miRNA expression in vivo. Many of these mRNAs contain potential binding sites for the differentially expressed miRNAs in their 3'-untranslated region (UTR) and are themselves affected by smoking. We found that either increasing or decreasing the levels of mir-218 (a miRNA that is strongly affected by smoking) in both primary bronchial epithelial cells and H1299 cells was sufficient to cause a corresponding decrease or increase in the expression of predicted mir-218 mRNA targets, respectively. Further, mir-218 expression is reduced in primary bronchial epithelium exposed to cigarette smoke condensate (CSC), and alteration of mir-218 levels in these cells diminishes the induction of the predicted mir-218 target MAFG in response to CSC. These data indicate that mir-218 levels modulate the airway epithelial gene expression response to cigarette smoke and support a role for miRNAs in regulating host response to environmental toxins.

Construction of point process adaptive filter algorithms for neural systems using sequential Monte Carlo methods.

The stochastic state point process filter (SSPPF) and steepest descent point process filter (SDPPF) are adaptive filter algorithms for state estimation from point process observations that have been used to track neural receptive field plasticity and to decode the representations of biological signals in ensemble neural spiking activity. The SSPPF and SDPPF are constructed using, respectively, Gaussian and steepest descent approximations to the standard Bayes and Chapman-Kolmogorov (BCK) system of filter equations. To extend these approaches for constructing point process adaptive filters, we develop sequential Monte Carlo (SMC) approximations to the BCK equations in which the SSPPF and SDPPF serve as the proposal densities. We term the two new SMC point process filters SMC-PPFs and SMC-PPFD, respectively. We illustrate the new filter algorithms by decoding the wind stimulus magnitude from simulated neural spiking activity in the cricket cercal system. The SMC-PPFs and SMC-PPFD provide more accurate state estimates at low number of particles than a conventional bootstrap SMC filter algorithm in which the state transition probability density is the proposal density. We also use the SMC-PPFs algorithm to track the temporal evolution of a spatial receptive field of a rat hippocampal neuron recorded while the animal foraged in an open environment. Our results suggest an approach for constructing point process adaptive filters using SMC methods.