Christoph D. Schmid

CNS immune privilege: hiding in plain sight.

Summary:  Central nervous system (CNS) immune privilege is an experimentally defined phenomenon. Tissues that are rapidly rejected by the immune system when grafted in sites, such as the skin, show prolonged survival when grafted into the CNS. Initially, CNS immune privilege was construed as CNS isolation from the immune system by the blood–brain barrier (BBB), the lack of draining lymphatics, and the apparent immunoincompetence of microglia, the resident CNS macrophage. CNS autoimmunity and neurodegeneration were presumed automatic consequences of immune cell encounter with CNS antigens. Recent data have dramatically altered this viewpoint by revealing that the CNS is neither isolated nor passive in its interactions with the immune system. Peripheral immune cells can cross the intact BBB, CNS neurons and glia actively regulate macrophage and lymphocyte responses, and microglia are immunocompetent but differ from other macrophage/dendritic cells in their ability to direct neuroprotective lymphocyte responses. This newer view of CNS immune privilege is opening the door for therapies designed to harness autoreactive lymphocyte responses and also implies (i) that CNS autoimmune diseases (i.e. multiple sclerosis) may result as much from neuronal and/or glial dysfunction as from immune system dysfunctions and (ii) that the severe neuronal and glial dysfunction associated with neurodegenerative disorders (i.e. Alzheimer’s disease) likely alters CNS‐specific regulation of lymphocyte responses affecting the utility of immune‐based therapies (i.e. vaccines).

Evaluation of methods for modeling transcription factor sequence specificity

Genomic analyses often involve scanning for potential transcription factor (TF) binding sites using models of the sequence specificity of DNA binding proteins. Many approaches have been developed to model and learn a proteins DNA-binding specificity, but these methods have not been systematically compared. Here we applied 26 such approaches to in vitro protein binding microarray data for 66 mouse TFs belonging to various families. For nine TFs, we also scored the resulting motif models on in vivo data, and found that the best in vitro–derived motifs performed similarly to motifs derived from the in vivo data. Our results indicate that simple models based on mononucleotide position weight matrices trained by the best methods perform similarly to more complex models for most TFs examined, but fall short in specific cases (<10% of the TFs examined here). In addition, the best-performing motifs typically have relatively low information content, consistent with widespread degeneracy in eukaryotic TF sequence preferences.

EPD in its twentieth year: towards complete promoter coverage of selected model organisms

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters, experimentally defined by a transcription start site (TSS). Access to promoter sequences is provided by pointers to positions in the corresponding genomes. Promoter evidence comes from conventional TSS mapping experiments for individual genes, or, starting from release 73, from mass genome annotation projects. Subsets of promoter sequences with customized 5′ and 3′ extensions can be downloaded from the EPD website. The focus of current development efforts is to reach complete promoter coverage for important model organisms as soon as possible. To speed up this process, a new class of preliminary promoter entries has been introduced as of release 83, which requires less stringent admission criteria. As part of a continuous integration process, new web-based interfaces have been developed, which allow joint analysis of promoter sequences with other bioinformatics resources developed by our group, in particular programs offered by the Signal Search Analysis Server, and gene expression data stored in the CleanEx database. EPD can be accessed at .

Differential gene expression in LPS/IFNγ activated microglia and macrophages: in vitro versus in vivo

Two different macrophage populations contribute to CNS neuroinflammation: CNS‐resident microglia and CNS‐infiltrating peripheral macrophages. Markers distinguishing these two populations in tissue sections have not been identified. Therefore, we compared gene expression between LPS (lipopolysaccharide)/interferon (IFN)γ‐treated microglia from neonatal mixed glial cultures and similarly treated peritoneal macrophages. Fifteen molecules were identified by quantative PCR (qPCR) as being enriched from 2‐fold to 250‐fold in cultured neonatal microglia when compared with peritoneal macrophages. Only three of these molecules (C1qA, Trem2, and CXCL14) were found by qPCR to be also enriched in adult microglia isolated from LPS/IFNγ‐injected CNS when compared with infiltrating peripheral macrophages from the same CNS. The discrepancy between the in vitro and in vivo qPCR data sets was primarily because of induced expression of the ‘microglial’ molecules (such as the tolerance associated transcript, Tmem176b) in CNS‐infiltrating macrophages. Bioinformatic analysis of the ∼19000 mRNAs detected by TOGA gene profiling confirmed that LPS/IFNγ‐activated microglia isolated from adult CNS displayed greater similarity in total gene expression to CNS‐infiltrating macrophages than to microglia isolated from unmanipulated healthy adult CNS. In situ hybridization analysis revealed that nearly all microglia expressed high levels of C1qA, while subsets of microglia expressed Trem2 and CXCL14. Expression of C1qA and Trem2 was limited to microglia, while large numbers of GABA+ neurons expressed CXCL14. These data suggest that (i) CNS‐resident microglia are heterogeneous and thus a universal microglia‐specific marker may not exist; (ii) the CNS micro‐environment plays significant roles in determining the phenotypes of both CNS‐resident microglia and CNS‐infiltrating macrophages; (iii) the CNS microenvironment may contribute to immune privilege by inducing macrophage expression of anti‐inflammatory molecules.

The genome of the heartworm, Dirofilaria immitis, reveals drug and vaccine targets

The heartworm Dirofilaria immitis is an important parasite of dogs. Transmitted by mosquitoes in warmer climatic zones, it is spreading across southern Europe and the Americas at an alarming pace. There is no vaccine, and chemotherapy is prone to complications. To learn more about this parasite, we have sequenced the genomes of D. immitis and its endosymbiont Wolbachia. We predict 10,179 protein coding genes in the 84.2 Mb of the nuclear genome, and 823 genes in the 0.9‐Mb Wolbachia genome. The D. immitis genome harbors neither DNA transposons nor active retrotransposons, and there is very little genetic variation between two sequenced isolates from Europe and the United States. The differential presence of anabolic pathways such as heme and nucleotide biosynthesis hints at the intricate metabolic interrelationship between the heartworm and Wolbachia. Comparing the proteome of D. immitis with other nematodes and with mammalian hosts, we identify families of potential drug targets, immune modulators, and vaccine candidates. This genome sequence will support the development of new tools against dirofilariasis and aid efforts to combat related human pathogens, the causative agents of lymphatic filariasis and river blindness.—Godel, C., Kumar, S., Koutsovoulos, G., Ludin, P., Nilsson, D., Comandatore, F., Wrobel, N., Thompson, M., Schmid, C. D., Goto, S., Bringaud, F., Wolstenholme, A., Bandi, C., Epe, C., Kaminsky, R., Blaxter, M., Mäser, P. The genome of the heartworm, Dirofilaria immitis, reveals drug and vaccine targets. FASEB J. 26, 4650–4661 (2012). www.fasebj.org

ChIP-Seq Data Reveal Nucleosome Architecture of Human Promoters

Keywords: Promoter Regions, Genetic Note: Comment on: Cell. 2007; 129(4):823-37 Reference EPFL-ARTICLE-154699doi:10.1016/j.cell.2007.11.017View record in Web of Science Record created on 2010-11-09, modified on 2017-05-12

Identification of CIITA Regulated Genetic Module Dedicated for Antigen Presentation

The class II trans-activator CIITA is a transcriptional co-activator required for the expression of Major Histocompatibility Complex (MHC) genes. Although the latter function is well established, the global target-gene specificity of CIITA had not been defined. We therefore generated a comprehensive list of its target genes by performing genome-wide scans employing four different approaches designed to identify promoters that are occupied by CIITA in two key antigen presenting cells, B cells and dendritic cells. Surprisingly, in addition to MHC genes, only nine new targets were identified and validated by extensive functional and expression analysis. Seven of these genes are known or likely to function in processes contributing to MHC-mediated antigen presentation. The remaining two are of unknown function. CIITA is thus uniquely dedicated for genes implicated in antigen presentation. The finding that CIITA regulates such a highly focused gene expression module sets it apart from all other transcription factors, for which large-scale binding-site mapping has indicated that they exert pleiotropic functions and regulate large numbers of genes.

Nuclear factor I revealed as family of promoter binding transcription activators

BackgroundMultiplex experimental assays coupled to computational predictions are being increasingly employed for the simultaneous analysis of many specimens at the genome scale, which quickly generates very large amounts of data. However, inferring valuable biological information from the comparisons of very large genomic datasets still represents an enormous challenge.ResultsAs a study model, we chose the NFI/CTF family of mammalian transcription factors and we compared the results obtained from a genome-wide study of its binding sites with chromatin structure assays, gene expression microarray data, and in silico binding site predictions. We found that NFI/CTF family members preferentially bind their DNA target sites when they are located around transcription start sites when compared to control datasets generated from the random subsampling of the complete set of NFI binding sites. NFI proteins preferably associate with the upstream regions of genes that are highly expressed and that are enriched in active chromatin modifications such as H3K4me3 and H3K36me3. We postulate that this is a causal association and that NFI proteins mainly act as activators of transcription. This was documented for one member of the family (NFI-C), which revealed as a more potent gene activator than repressor in global gene expression analysis. Interestingly, we also discovered the association of NFI with the tri-methylation of lysine 9 of histone H3, a chromatin marker previously associated with the protection against silencing of telomeric genes by NFI.ConclusionTaken together, we illustrate approaches that can be taken to analyze large genomic data, and provide evidence that NFI family members may act in conjunction with specific chromatin modifications to activate gene expression.

MER41 Repeat Sequences Contain Inducible STAT1 Binding Sites

Chromatin immunoprecipitation combined with massively parallel sequencing methods (ChIP-seq) is becoming the standard approach to study interactions of transcription factors (TF) with genomic sequences. At the example of public STAT1 ChIP-seq data sets, we present novel approaches for the interpretation of ChIP-seq data. We compare recently developed approaches to determine STAT1 binding sites from ChIP-seq data. Assessing the content of the established consensus sequence for STAT1 binding sites, we find that the usage of “negative control” ChIP-seq data fails to provide substantial advantages. We derive a single refined probabilistic model of STAT1 binding sequences from these ChIP-seq data. Contrary to previous claims, we find no evidence that STAT1 binds to multiple distinct motifs upon interferon-gamma stimulation in vivo. While a large majority of genomic sites with high ChIP-seq signal is associated with a nucleotide sequence ressembling a STAT1 binding site, only a very small subset of the over 5 million potential STAT1 binding sites in the human genome is covered by ChIP-seq data. Furthermore a surprisingly large fraction of the ChIP-seq signal (5%) is absorbed by a small family of repetitive sequences (MER41). The observation of the binding of activated STAT1 protein to a specific repetitive element bolsters similar reports concerning p53 and other TFs, and strengthens the notion of an involvement of repeats in gene regulation. Incidentally MER41 are specific to primates, consequently, regulatory mechanisms in the IFN-STAT pathway might fundamentally differ between primates and rodents. On a methodological aspect, the presence of large numbers of nearly identical binding sites in repetitive sequences may lead to wrong conclusions about intrinsic binding preferences of TF as illustrated by the spacing analysis STAT1 tandem motifs. Therefore, ChIP-seq data should be analyzed independently within repetitive and non-repetitive sequences.

The Transcription Factor Rfx3 Regulates β-Cell Differentiation, Function, and Glucokinase Expression

OBJECTIVE Pancreatic islets of perinatal mice lacking the transcription factor Rfx3 exhibit a marked reduction in insulin-producing β-cells. The objective of this work was to unravel the cellular and molecular mechanisms underlying this deficiency. RESEARCH DESIGN AND METHODS Immunofluorescence studies and quantitative RT-PCR experiments were used to study the emergence of insulin-positive cells, the expression of transcription factors implicated in the differentiation of β-cells from endocrine progenitors, and the expression of mature β-cell markers during development in Rfx3−/− and pancreas-specific Rfx3-knockout mice. RNA interference experiments were performed to document the consequences of downregulating Rfx3 expression in Min6 β-cells. Quantitative chromatin immunoprecipitation (ChIP), ChIP sequencing, and bandshift experiments were used to identify Rfx3 target genes. RESULTS Reduced development of insulin-positive cells in Rfx3−/− mice was not due to deficiencies in endocrine progenitors or β-lineage specification, but reflected the accumulation of insulin-positive β-cell precursors and defective β-cells exhibiting reduced insulin, Glut-2, and Gck expression. Similar incompletely differentiated β-cells developed in pancreas-specific Rfx3-deficient embryos. Defective β-cells lacking Glut-2 and Gck expression dominate in Rfx3-deficent adults, leading to glucose intolerance. Attenuated Glut-2 and glucokinase expression, and impaired glucose-stimulated insulin secretion, were also induced by RNA interference–mediated inhibition of Rfx3 expression in Min6 cells. Finally, Rfx3 was found to bind in Min6 cells and human islets to two well-known regulatory sequences, Pal-1 and Pal-2, in the neuroendocrine promoter of the glucokinase gene. CONCLUSIONS Our results show that Rfx3 is required for the differentiation and function of mature β-cells and regulates the β-cell promoter of the glucokinase gene.