Search

Supplementary Data from Adhesive Interactions Regulate Transcriptional Diversity in Malignant B Cells

Despite numerous studies of immune sexual dimorphism, sexual differences are not rigorously mapped and dimorphic mechanisms are incompletely understood. Current immune research typically studies sex differences in specific cells, tissues, or diseases but without providing an integrated picture. To connect the dots, we suggest comprehensive research approaches to better our understanding of immune sexual dimorphism and its mechanisms.

Alternative splicing results in multiple transcripts of the same gene, possibly encoding for different protein isoforms with different domains. Whereas it is possible to manually determine the effect of alternative splicing on the domain composition for a single event, the process requires the tedious integration of several data sources; it is error prone and not feasible for genome-wide characterization of domains affected by differential splicing. To fulfill the need for an automated solution, we developed the Domain Change Presenter (DoChaP, https://dochap.bgu.ac.il/), a web server for the visualization of exon–domain associations. DoChaP visualizes all transcripts of a given gene, the encoded proteins and their domains, and enables a comparison between the transcripts and between their protein products. The colors and organization make the structural effect of alternative splicing events on protein structures easily identified. To enable the study of the conservation of exons structure, alternative splicing, and the effect of alternative splicing on protein domains, DoChaP also provides a two-species comparison of exon–domain associations. DoChaP thus provides a unique and easy-to-use visualization of the exon–domain association and conservation, and will facilitate the study of the structural effects of alternative splicing in health and disease., Graphical Abstract Graphical AbstractOverview. (A) The DoChaP-database (DoChaP-db) integrates information on transcripts and protein domains from several sources into a single SQLite database. (B) Genes, transcripts, exons, proteins and domain events data was taken from NCBI and Ensembl. Orthology information was taken from Ensembl Compara. Domain types and the mapping of the domain accessions from different sources (Pfam, SMART, CDD and TIGRFAMs) was inferred from InterPro. (C) A simple visualization of the information collected into the DoChaP-db is presented in the DoChaP webserver for a user selected gene. The visualization presents the genomic context of the transcripts (Gene) and the exon structure of the coding region of the mature mRNA of all the transcripts (T1, T2) and their encoded protein domain composition (P1, P2). Exons are represented in different colors, and their encoded protein domains are represented by the corresponding colors. (D) The 'species comparison' feature allows the user to select a gene and a species and visualize the orthologous genes so as to enable a comparison of transcripts and their protein domain organization.

As treatment of the early, inflammatory phase of sepsis improves, post-sepsis immunosuppression and secondary infection have increased in importance. How early inflammation drives immunosuppression remains unclear. Although IFN-γ typically helps microbial clearance, we found that increased plasma IFN-γ in early clinical sepsis was associated with the later development of secondary Candida infection. Consistent with this observation, we found that exogenous IFN-γ suppressed macrophage phagocytosis of zymosan in vivo, and antibody blockade of IFN-γ after endotoxemia improved survival of secondary candidemia. Transcriptomic analysis of innate lymphocytes during endotoxemia suggested that NKT cells drove IFN-γ production by NK cells via mTORC1. Activation of invariant NKT (iNKT) cells with glycolipid antigen drove immunosuppression. Deletion of iNKT cells in Cd1d(–/–) mice or inhibition of mTOR by rapamycin reduced immunosuppression and susceptibility to secondary Candida infection. Thus, although rapamycin is typically an immunosuppressive medication, in the context of sepsis, rapamycin has the opposite effect. These results implicated an NKT cell/mTOR/IFN-γ axis in immunosuppression following endotoxemia or sepsis. In summary, in vivo iNKT cells activated mTORC1 in NK cells to produce IFN-γ, which worsened macrophage phagocytosis, clearance of secondary Candida infection, and mortality.

γδ T cells are situated at barrier sites and guard the body from infection and damage. However, little is known about their roles outside of host defense in nonbarrier tissues. Here, we characterize a highly enriched tissue-resident population of γδ T cells in adipose tissue that regulate age-dependent regulatory T cell (T(reg)) expansion and control core body temperature in response to environmental fluctuations. Mechanistically, innate PLZF(+) γδ T cells produced tumor necrosis factor and interleukin (IL) 17 A and determined PDGFRα(+) and Pdpn(+) stromal-cell production of IL-33 in adipose tissue. Mice lacking γδ T cells or IL-17A exhibited decreases in both ST2(+) T(reg) cells and IL-33 abundance in visceral adipose tissue. Remarkably, these mice also lacked the ability to regulate core body temperature at thermoneutrality and after cold challenge. Together, these findings uncover important physiological roles for resident γδ T cells in adipose tissue immune homeostasis and body-temperature control.

Recent advances in single-cell RNA–sequencing (scRNA-seq) technology increase the understanding of immune differentiation and activation processes, as well as the heterogeneity of immune cell types. Although the number of available immune-related scRNA-seq datasets increases rapidly, their large size and various formats render them hard for the wider immunology community to use, and read-level data are practically inaccessible to the non-computational immunologist. To facilitate datasets reuse, we created the JingleBells repository for immune-related scRNA-seq datasets ready for analysis and visualization of reads at the single-cell level (http://jinglebells.bgu.ac.il/). To this end, we collected the raw data of publicly available immune-related scRNA-seq datasets, aligned the reads to the relevant genome, and saved aligned reads in a uniform format, annotated for cell of origin. We also added scripts and a step-by-step tutorial for visualizing each dataset at the single-cell level, through the commonly used Integrated Genome Viewer (www.broadinstitute.org/igv/). The uniform scRNA-seq format used in JingleBells can facilitate reuse of scRNA-seq data by computational biologists. It also enables immunologists who are interested in a specific gene to visualize the reads aligned to this gene to estimate cell-specific preferences for splicing, mutation load, or alleles. Thus JingleBells is a resource that will extend the usefulness of scRNA-seq datasets outside the programming aficionado realm.

Summary Hematopoietic stem cells (HSCs) are rare cells that generate all the various types of blood and immune cells. High-quality transcriptome data have enabled the identification of significant genes for HSCs. However, most genes are expressed in various forms by alternative splicing (AS), extending transcriptome complexity. Here, we delineate AS to determine which isoforms are expressed in mouse HSCs. Our analysis of microarray and RNA-sequencing data includes differential expression of splicing factors that may regulate AS, and a complete map of splicing isoforms. Multiple types of isoforms for known HSC genes and unannotated splicing that may alter gene function are presented. Transcriptome-wide identification of genes and their respective isoforms in mouse HSCs will open another dimension for adult stem cells., Graphical Abstract, Highlights • This study presents the splicing landscape in mouse hematopoietic stem cells • Many HSC genes express multiple isoforms, some with alternative isoforms • High-resolution analysis allows the discovery of unannotated splicing • HSC-expressed isoforms can have similar or divergent functions, Gazit and colleagues mapped all splicing within mouse hematopoietic stem cells by analysis of microarrays and meta-analysis of RNA-sequencing datasets. They validated co-expression of minor isoforms, variant isoform predominance, multiple isoforms from one gene, and discovery of unannotated splicing. Functionally, variant isoforms may alter the activity of HSC genes, or not. Whole-transcriptome splicing data at nucleotide resolution is providing a useful tool for the community.

Sexual dimorphism in the mammalian immune system is manifested as more frequent and severe infectious diseases in males and, on the other hand, higher rates of autoimmune disease in females, yet insights underlying those differences are still lacking. Here we characterize sex differences in the immune system by RNA and ATAC sequence profiling of untreated and interferon-induced immune cell types in male and female mice. We detect very few differentially expressed genes between male and female immune cells except in macrophages from three different tissues. Accordingly, very few genomic regions display differences in accessibility between sexes. Transcriptional sexual dimorphism in macrophages is mediated by genes of innate immune pathways, and increases after interferon stimulation. Thus, the stronger immune response of females may be due to more activated innate immune pathways prior to pathogen invasion., Sexual dimorphism is observed frequently in immune disorders, but the underlying insights are still unclear. Here the authors analyze transcriptome and epigenome changes induced by interferon in various mouse immune cell types, and find only a restricted set of sexual dimorphism genes in innate immunity and macrophages.

Following the sequencing of the human genome, the next step is to understand the function of all genes in health and disease. However, experimental study of the functions of all genes in all diseases is impossible and unnecessary, as not all genes are functional in all conditions. However, understanding which genes are functional in each condition and how they are regulated requires a laborious and expensive experimental effort. In this paper we suggest a heuristic framework, CSGI (cluster switching genes identification) for identifying promising genes for thorough analysis. In CSGI we project a cluster defined in one context to its projection in another context, identifying genes that behave differently in different contexts.We provide a case study of immune system clusters showing that our approach identifies clusters representing core conserved biological processes, as well as important genes that switch of clusters.

SummaryInducible transcription is essential for consolidation of salient experiences into long-term memory. However, the question of whether inducible transcription relays information representing the identity of the experience being encoded, has not been explored. To this end, we have analyzed transcription across multiple brain regions, induced by a variety of rewarding and aversive experiences. Our results define robust transcriptional signatures uniquely characterizing individual salient experiences. A subset of these induced transcriptional markers suffice for near-perfect decoding of the identity of recent experiences at the level of individual mice. Furthermore, experiences with shared attributes display commonalities in their transcriptional representation, exemplified in the representation of valence, habituation and reinforcement. Taken together, our results demonstrate the existence of a neural transcriptional code that represents the encoding of experiences in the mouse brain. This code is comprised of distinct transcriptional signatures that correlate to the affective attributes of the experiences that are being encoded.

Can we tell what important event a mouse – or even a person – has recently experienced? The current experience of an individual can be inferred from brain imaging experiments. However, along with changing brain activity, such an experience also switches on gene activity throughout the brain. This enables neurons to produce the proteins required to form a long-term memory of the experience. Do distinct, memorable experiences trigger unique signatures of gene activity? To answer this question, Mukherjee, Ignatowska-Jankowska, Itskovits et al. exposed mice to a variety of experiences. Some were unpleasant and induced aversion; for example, the mouse may have felt nauseous or experienced brief pain and fear. Other experiences, such as when the mouse drank sugary water, received food or was injected with cocaine, were rewarding. Each of the experiences led to the activation of unique combinations of genes in different regions of the brain. Analysing a subset of the activated genes in various brain regions led to the identification of unique and reliable gene expression signatures of experience. These signatures allowed the recent experience of mice to be decoded with nearly 100% accuracy. While these unique signatures can distinguish between recent experiences, experiences that share common features do trigger overlapping patterns of gene activation. For example, negative experiences – but not positive or neutral ones – activated similar patterns of genes in a brain region called the amygdala. In contrast, repeated rewarding experiences induced a distinct gene activity pattern that was most pronounced as increased activity in part of the brain called the frontal cortex. These findings increase our understanding of how the brain represents information. The approach described in the paper provides a strategy to measure the changes in the brain that occur when information is encoded for long-term storage. This measure could also be useful during drug development, revealing how new drug compounds affect the brain, as well as providing an objective measure of the subjective experience of an individual. For example, substances that trigger similar patterns of gene activation to addictive drugs may themselves be addictive. On the other hand, substances that induce similar activity patterns to known medications could also have similar therapeutic properties.

In the version of this article initially published, three authors (Hui-Fern Kuoy, Adam P. Uldrich and Dale. I. Godfrey) and their affiliations, acknowledgments and contributions were not included. The correct information is as follows:Ayano C. Kohlgruber1,2, Shani T. Gal-Oz3, Nelson M. LaMarche1,2, Moto Shimazaki1, Danielle Duquette4, Hui-Fern Koay5,6, Hung N. Nguyen1, Amir I. Mina4, Tyler Paras1, Ali Tavakkoli7, Ulrich von Andrian2,8, Adam P. Uldrich5,6, Dale I. Godfrey5,6, Alexander S. Banks4, Tal Shay3, Michael B. Brenner1,10* and Lydia Lynch1,4,9,10*1Division of Rheumatology, Immunology and Allergy, Brigham and Women's Hospital, Boston, MA, USA. 2Division of Medical Sciences, Harvard Medical School, Boston, MA, USA. 3Department of Life Sciences, Ben-Gurion University of the Negev, Beersheba, Israel. 4Division of Endocrinology, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA. 5Department of Microbiology and Immunology, Peter Doherty Institute for Infection and Immunity, University of Melbourne, Parkville, Australia. 6ARC Centre of Excellence in Advanced Molecular Imaging, University of Melbourne, Parkville, Australia. 7Department of General and Gastrointestinal Surgery, Brigham and Women's Hospital, Boston, MA, USA. 8Department of Microbiology and Immunology, Harvard Medical School, Boston, MA, USA. 9School of Biochemistry and Immunology, Trinity College, Dublin, Ireland. 10These authors jointly supervised this work: Michael B. Brenner, Lydia Lynch. *e-mail: mbrenner@research.bwh.harvard.edu; llynch@bwh.harvard.eduAcknowledgementsWe thank A.T. Chicoine, flow cytometry core manager at the Human Immunology Center at BWH, for flow cytometry sorting. We thank D. Sant'Angelo (Rutgers Cancer Institute) for providing Zbtb16-/- mice and R. O'Brien (National Jewish Health) for providing Vg4/6-/- mice. Supported by NIH grant R01 AI11304603 (to M.B.B.), ERC Starting Grant 679173 (to L.L.), the National Health and Medical Research Council of Australia (1013667), an Australian Research Council Future Fellowship (FT140100278 for A.P.U.) and a National Health and Medical Research Council of Australia Senior Principal Research Fellowship (1117766 for D.I.G.).Author contributionsA.C.K., L.L., and M.B.B. conceived and designed the experiments, and wrote the manuscript. A.C.K., N.M.L., L.L., H.N.N., M.S., T.P., and D.D. performed the experiments. S.T.G.-O. and T.S. performed the RNA-seq analysis. A.S.B. and A.I.M. provided advice and performed the CLAMS experiments. A.T. provided human bariatric patient samples. Parabiosis experiments were performed in the laboratory of U.v.A. H.-F.K., A.P.U. and D.I.G provided critical insight into the TCR chain usage of PLZF+ γδ T cells. M.B.B., N.M.L., and L.L. critically reviewed the manuscript.The errors have been corrected in the HTML and PDF version of the article.Correction to: Nature Immunology doi:10.1038/s41590-018-0094-2 (2018), published online 18 April 2018.

Summary Hematopoietic stem cells (HSCs) maintain blood homeostasis and are the functional units of bone marrow transplantation. To improve the molecular understanding of HSCs and their proximal progenitors, we performed transcriptome analysis within the context of the ImmGen Consortium data set. Gene sets that define steady-state and mobilized HSCs, as well as hematopoietic stem and progenitor cells (HSPCs), were determined. Genes involved in transcriptional regulation, including a group of putative transcriptional repressors, were identified in multipotent progenitors and HSCs. Proximal promoter analyses combined with ImmGen module analysis identified candidate regulators of HSCs. Enforced expression of one predicted regulator, Hlf, in diverse HSPC subsets led to extensive self-renewal activity ex vivo. These analyses reveal unique insights into the mechanisms that control the core properties of HSPCs., Highlights • HSCs are transcriptionally primed for rapid activation • A total of 322 HSC-enriched genes, including 51 transcription factors, were identified • Ectopic Hlf expression increased ex vivo self-renewal in stem and progenitor cells • Analysis revealed a transcription factor family hypothesized to regulate multipotency

Although much progress has been made in the understanding of the ontogeny and function of dendritic cells (DCs), the transcriptional regulation of the lineage commitment and functional specialization of DCs in vivo remains poorly understood. We made a comprehensive comparative analysis of CD8 + , CD103 + , CD11b + and plasmacytoid DC subsets, as well as macrophage DC precursors and common DC precursors, across the entire immune system. Here we characterized candidate transcriptional activators involved in the commitment of myeloid progenitor cells to the DC lineage and predicted regulators of DC functional diversity in tissues. We identified a molecular signature that distinguished tissue DCs from macrophages. We also identified a transcriptional program expressed specifically during the steady-state migration of tissue DCs to the draining lymph nodes that may control tolerance to self tissue antigens.

Aberrant activation of kinases has emerged to be a key event along with tumor progression, maintenance of tumor phenotype and response to anticancer treatments. This study documents the existence of an oncogenic auto-regulatory feedback loop that includes the Polo-like kinase-2 (Snk/Plk2) and mutant p53 proteins. Plk2 protein binds to and phosphorylates mutant p53, thereby potentiating its oncogenic activities. Phosphorylated mutant p53 binds more efficiently to p300 consequently strengthening its own transcriptional activity. Plk2 gene is regulated at a transcriptional level by both wt- and mutant p53 proteins. This leads to growth suppression or enhanced cell proliferation and chemo-resistance, respectively. In turn, the siRNA-mediated knock down of either mutant p53 or Plk2 proteins significantly curtails the growth properties of tumor cells and their chemo-resistance to anticancer treatments. Therefore, this paper identifies a novel tumor network including Plk2 and mutant p53 proteins whose triggering in response to DNA damage might disclose important implications for the treatment of human cancers.

Gene expression-based prediction of genomic copy number aberrations in the chromosomal region 12q13 to 12q15 that is flanked by MDM2 and CDK4 identified Wnt inhibitory factor 1 (WIF1) as a candidate tumor suppressor gene in glioblastoma. WIF1 encodes a secreted Wnt antagonist and was strongly downregulated in most glioblastomas as compared with normal brain, implying deregulation of Wnt signaling, which is associated with cancer. WIF1 silencing was mediated by deletion (7/69, 10%) or epigenetic silencing by promoter hypermethylation (29/110, 26%). Co-amplification of MDM2 and CDK4 that is present in 10% of glioblastomas was associated in most cases with deletion of the whole genomic region enclosed, including the WIF1 locus. This interesting pathogenetic constellation targets the RB and p53 tumor suppressor pathways in tandem, while simultaneously activating oncogenic Wnt signaling. Ectopic expression of WIF1 in glioblastoma cell lines revealed a dose-dependent decrease of Wnt pathway activity. Furthermore, WIF1 expression inhibited cell proliferation in vitro, reduced anchorage-independent growth in soft agar, and completely abolished tumorigenicity in vivo. Interestingly, WIF1 overexpression in glioblastoma cells induced a senescence-like phenotype that was dose dependent. These results provide evidence that WIF1 has tumor suppressing properties. Downregulation of WIF1 in 75% of glioblastomas indicates frequent involvement of aberrant Wnt signaling and, hence, may render glioblastomas sensitive to inhibitors of Wnt signaling, potentially by diverting the tumor cells into a senescence-like state.

Normal cells require continuous exposure to growth factors, in order to cross a restriction point and commit to cell cycle progression. This can be replaced by two short, appropriately spaced pulses of growth factors, where the first pulse primes a process, which is completed by the second pulse, and enables restriction point crossing. Through integration of comprehensive proteomic and transcriptomic analyses of each pulse, we identified three processes that regulate restriction point crossing: (i) The first pulse induces essential metabolic enzymes and activates p53-dependent restraining processes. (ii) The second pulse eliminates, via the PI3K/AKT pathway, the suppressive action of p53, as well as (iii) sets an ERK-EGR1 threshold mechanism, which digitizes graded external signals into an all-or-none decision obligatory for S-phase entry. Together, our findings uncover two gating mechanisms, which ensure that cells ignore fortuitous growth factors, and undergo proliferation only in response to consistent mitogenic signals.

The genetic profiling of B-cell malignancies is rapidly expanding, providing important information on the tumorigenic potential, response to treatment, and clinical outcome of these diseases. However, the relative contributions of inherent gene expression versus microenvironmental effects are poorly understood. The regulation of gene expression programs by means of adhesive interactions was studied here in ARH-77 human malignant B-cell variants, derived from the same cell line by selective adhesion to a fibronectin matrix. The populations included cells that adhere to fibronectin and are highly tumorigenic (designated “type A” cells) and cells that fail to adhere to fibronectin and fail to develop tumors in vivo (“type F” cells). To identify genes directly affected by cell adhesion to fibronectin, type A cells deprived of an adhesive substrate (designated “AF cells”) were also examined. Bioinformatic analyses revealed a remarkable correlation between cell adhesion and both B-cell differentiation state and the expression of multiple myeloma (MM)–associated genes. The highly adherent type A cells expressed higher levels of NFκB-regulated genes, many of them associated with MM. Moreover, we found that the transcription of several MM-related proto-oncogenes is stimulated by adhesion to fibronectin. In contrast, type F cells, which display poor adhesive and tumorigenic properties, expressed genes associated with higher levels of B-cell differentiation. Our findings indicate that B-cell differentiation, as manifested by gene expression profiles, is attenuated by cell adhesion to fibronectin, leading to upregulation of specific genes known to be associated with the pathogenesis of MM. Mol Cancer Res; 8(4); 482–93. ©2010 AACR.

Purpose Glioblastomas are notorious for resistance to therapy, which has been attributed to DNA-repair proficiency, a multitude of deregulated molecular pathways, and, more recently, to the particular biologic behavior of tumor stem-like cells. Here, we aimed to identify molecular profiles specific for treatment resistance to the current standard of care of concomitant chemoradiotherapy with the alkylating agent temozolomide. Patients and Methods Gene expression profiles of 80 glioblastomas were interrogated for associations with resistance to therapy. Patients were treated within clinical trials testing the addition of concomitant and adjuvant temozolomide to radiotherapy. Results An expression signature dominated by HOX genes, which comprises Prominin-1 (CD133), emerged as a predictor for poor survival in patients treated with concomitant chemoradiotherapy (n = 42; hazard ratio = 2.69; 95% CI, 1.38 to 5.26; P = .004). This association could be validated in an independent data set. Provocatively, the HOX cluster was reminiscent of a “self-renewal” signature (P = .008; Gene Set Enrichment Analysis) recently characterized in a mouse leukemia model. The HOX signature and EGFR expression were independent prognostic factors in multivariate analysis, adjusted for the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, a known predictive factor for benefit from temozolomide, and age. Better outcome was associated with gene clusters characterizing features of tumor-host interaction including tumor vascularization and cell adhesion, and innate immune response. Conclusion This study provides first clinical evidence for the implication of a “glioma stem cell” or “self-renewal” phenotype in treatment resistance of glioblastoma. Biologic mechanisms identified here to be relevant for resistance will guide future targeted therapies and respective marker development for individualized treatment and patient selection.

Background HOX genes are a family of developmental genes that are expressed neither in the developing forebrain nor in the normal brain. Aberrant expression of a HOX-gene dominated stem-cell signature in glioblastoma has been linked with increased resistance to chemo-radiotherapy and sustained proliferation of glioma initiating cells. Here we describe the epigenetic and genetic alterations and their interactions associated with the expression of this signature in glioblastoma. Results We observe prominent hypermethylation of the HOXA locus 7p15.2 in glioblastoma in contrast to non-tumoral brain. Hypermethylation is associated with a gain of chromosome 7, a hallmark of glioblastoma, and may compensate for tumor-driven enhanced gene dosage as a rescue mechanism by preventing undue gene expression. We identify the CpG island of the HOXA10 alternative promoter that appears to escape hypermethylation in the HOX-high glioblastoma. An additive effect of gene copy gain at 7p15.2 and DNA methylation at key regulatory CpGs in HOXA10 is significantly associated with HOX-signature expression. Additionally, we show concordance between methylation status and presence of active or inactive chromatin marks in glioblastoma-derived spheres that are HOX-high or HOX-low, respectively. Conclusions Based on these findings, we propose co-evolution and interaction between gene copy gain, associated with a gain of chromosome 7, and additional epigenetic alterations as key mechanisms triggering a coordinated, but inappropriate, HOX transcriptional program in glioblastoma. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0583-7) contains supplementary material, which is available to authorized users.

We read with interest the report of Takao and Miyakawa (1), who compare genomic responses to inflammatory challenges in humans and mice, reanalyzing the datasets originally reported by Seok et al. (2), but reaching a diametrically opposite conclusion. In line with its goal to establish the landscape of gene expression and regulation in the immune system, the ImmGen consortium has run focused human/mouse comparisons (3), and we also reanalyzed the datasets of Seok et al. We largely concur with the conclusions reached by Takao and Miyakawa, but wish to make a few additional points.

We previously reported a stem cell related HOX gene signature associated with resistance to chemo-radiotherapy (TMZ/RT- > TMZ) in glioblastoma. However, underlying mechanisms triggering overexpression remain mostly elusive. Interestingly, HOX genes are neither involved in the developing brain, nor expressed in normal brain, suggestive of an acquired gene expression signature during gliomagenesis. HOXA genes are located on CHR 7 that displays trisomy in most glioblastoma which strongly impacts gene expression on this chromosome, modulated by local regulatory elements. Furthermore we observed more pronounced DNA methylation across the HOXA locus as compared to non-tumoral brain (Human methylation 450K BeadChip Illumina; 59 glioblastoma, 5 non-tumoral brain sampes). CpG probes annotated for HOX-signature genes, contributing most to the variability, served as input into the analysis of DNA methylation and expression to identify key regulatory regions. The structural similarity of the observed correlation matrices between DNA methylation and gene expression in our cohort and an independent data-set from TCGA (106 glioblastoma) was remarkable (RV-coefficient, 0.84; p-value < 0.0001). We identified a CpG located in the promoter region of the HOXA10 locus exerting the strongest mean negative correlation between methylation and expression of the whole HOX-signature. Applying this analysis the same CpG emerged in the external set. We then determined the contribution of both, gene copy aberration (CNA) and methylation at the selected probe to explain expression of the HOX-signature using a linear model. Statistically significant results suggested an additive effect between gene dosage and methylation at the key CpG identified. Similarly, such an additive effect was also observed in the external data-set. Taken together, we hypothesize that overexpression of the stem-cell related HOX signature is triggered by gain of trisomy 7 and escape from compensatory DNA methylation at positions controlling the effect of enhanced gene dose on expression.

Much of the knowledge about cell differentiation and function in the immune system has come from studies in mice, but the relevance to human immunology, diseases, and therapy has been challenged, perhaps more from anecdotal than comprehensive evidence. To this end, we compare two large compendia of transcriptional profiles of human and mouse immune cell types. Global transcription profiles are conserved between corresponding cell lineages. The expression patterns of most orthologous genes are conserved, particularly for lineage-specific genes. However, several hundred genes show clearly divergent expression across the examined cell lineages, and among them, 169 genes did so even with highly stringent criteria. Finally, regulatory mechanisms—reflected by regulators’ differential expression or enriched cis -elements—are conserved between the species but to a lower degree, suggesting that distinct regulation may underlie some of the conserved transcriptional responses.

Immunological studies of single proteins in a single cell type have been complemented in recent years by larger studies, enabled by emerging high-throughput technologies. This trend has recently been exemplified by the discovery of gene networks controlling regulatory and effector αβ T cell subset development and human hematopoiesis. The Immunological Genome Project (ImmGen) aims to decipher the gene networks underpinning mouse hematopoiesis. The first phase, completed in 2012, profiled the transcriptome of 249 immune cell types. We discuss the utilities of the datasets in high-resolution mapping of the hematopoietic system. The immune transcriptome compendium has revealed unsuspected cell lineage relations and the network reconstruction has identified novel regulatory factors of hematopoiesis.

The differentiation of αβT cells from thymic precursors is a complex process essential for adaptive immunity. Here we exploited the breadth of expression data sets from the Immunological Genome Project to analyze how the differentiation of thymic precursors gives rise to mature T cell transcriptomes. We found that early T cell commitment was driven by unexpectedly gradual changes. In contrast, transit through the CD4[superscript +]CD8[superscript +] stage involved a global shutdown of housekeeping genes that is rare among cells of the immune system and correlated tightly with expression of the transcription factor c-Myc. Selection driven by major histocompatibility complex (MHC) molecules promoted a large-scale transcriptional reactivation. We identified distinct signatures that marked cells destined for positive selection versus apoptotic deletion. Differences in the expression of unexpectedly few genes accompanied commitment to the CD4[superscript +] or CD8[superscript +] lineage, a similarity that carried through to peripheral T cells and their activation, demonstrated by mass cytometry phosphoproteomics. The transcripts newly identified as encoding candidate mediators of key transitions help define the 'known unknowns' of thymocyte differentiation., National Institutes of Health (U.S.) (AI072073)

We assessed gene expression in tissue macrophages from various mouse organs. The diversity in gene expression among different populations of macrophages was considerable. Only a few hundred mRNA transcripts were selectively expressed by macrophages rather than dendritic cells, and many of these were not present in all macrophages. Nonetheless, well-characterized surface markers, including MerTK and FcγR1 (CD64), along with a cluster of previously unidentified transcripts, were distinctly and universally associated with mature tissue macrophages. TCEF3, C/EBP-α, Bach1 and CREG-1 were among the transcriptional regulators predicted to regulate these core macrophage-associated genes. The mRNA encoding other transcription factors, such as Gata6, was associated with single macrophage populations. We further identified how these transcripts and the proteins they encode facilitated distinguishing macrophages from dendritic cells.

Invariant natural killer T cells (iNKT cells) are innate-like T lymphocytes that act as critical regulators of the immune response. To better characterize this population, we profiled gene expression in iNKT cells during ontogeny and in peripheral subsets as part of the Immunological Genome Project. High-resolution comparative transcriptional analyses defined developmental and subset-specific programs of gene expression by iNKT cells. In addition, we found that iNKT cells shared an extensive transcriptional program with NK cells, similar in magnitude to that shared with major histocompatibility complex (MHC)-restricted T cells. Notably, the program shared by NK cells and iNKT cells also operated constitutively in γδ T cells and in adaptive T cells after activation. Together our findings highlight a core effector program regulated distinctly in innate and adaptive lymphocytes.

The signaling pathways that commit cells to migration are incompletely understood. We employed human mammary cells and two stimuli: epidermal growth factor (EGF), which induced cellular migration, and serum factors, which stimulated cell growth. In addition to strong activation of ERK by EGF, and AKT by serum, early transcription remarkably differed: while EGF induced early growth response-1 (EGR1), and this was required for migration, serum induced c-Fos and FosB to enhance proliferation. We demonstrate that induction of EGR1 involves ERK-mediated down-regulation of microRNA-191 and phosphorylation of the ETS2 repressor factor (ERF) repressor, which subsequently leaves the nucleus. Unexpectedly, knockdown of ERF inhibited migration, which implies migratory roles for exported ERF molecules. On the other hand, chromatin immunoprecipitation identified a subset of direct EGR1 targets, including EGR1 autostimulation and SERPINB2, whose transcription is essential for EGF-induced cell migration. In summary, EGR1 and the EGF-ERK-ERF axis emerge from our study as major drivers of growth factor-induced mammary cell migration.—Tarcic, G., Avraham, R., Pines, G., Amit, I., Shay, T., Lu, Y., Zwang, Y., Katz, M., Ben-Chetrit, N., Jacob-Hirsch, J., Virgilio, L., Rechavi, G., Mavrothalassitis, G., Mills, G. B., Domany, E., Yarden, Y. EGR1 and the ERK-ERF axis drive mammary cell migration in response to EGF.

Cell surface transmembrane signaling receptors EGFR, HER3, and HER4 are activated by ligand-binding-mediated dimerization and phosphorylation. In contrast, HER2 amplification promotes signaling by increasing homo/heterodimerization and ligand binding. Trastuzumab or lapatinib therapy of HER2 amplicon-positive breast cancer cells induces growth inhibition and intracellular growth pathway signaling modulation. The mechanism(s) by which trastuzumab, an IgG1 humanized antibody, induces modification of cell signaling upon binding to an extracellular determinant on a ligand-less “receptor” membrane protein remains unexplained. Using immune detection methodology comprised of antibodies detecting three distinct domains of HER and five tyrosine/threonine phosphorylation sites, the effects of trastuzumab and lapatinib were defined during steady state growth inhibition. Here, we show that lapatinib markedly reduces HER2 tyrosine phosphorylation, while in contrast, no change in tyrosine phosphate levels is detected during trastuzumab-mediated cell growth inhibition. As trastuzumab treatment does not change either the steady state HER2 protein levels or HER2 mRNA, these findings argue against an antibody-dependent alteration in internalization kinetics. We further show a sequenced relationship between lapatinib-induced blockage of phosphorylation (6–8 h) and induction of delayed cell death (5–6 days), while trastuzumab-treated cells showed no evidence of cell death up to 9 days. Taken together, these results demonstrate that inhibition of HER2 phosphorylation by lapatinib is sufficient to induce apoptosis while trastuzumab binding to the extracellular HER2 domain may function by sterically modulating the detection of phosphate moieties by cytoplasmic signal transducers. This investigation also detected a 20 kD protein, which is down-regulated by lapatinib, further demonstrating the complexity of this signal transduction system.

Models of mammalian regulatory networks controlling gene expression have been inferred from genomic data but have largely not been validated. We present an unbiased strategy to systematically perturb candidate regulators and monitor cellular transcriptional responses. We applied this approach to derive regulatory networks that control the transcriptional response of mouse primary dendritic cells to pathogens. Our approach revealed the regulatory functions of 125 transcription factors, chromatin modifiers, and RNA binding proteins, which enabled the construction of a network model consisting of 24 core regulators and 76 fine-tuners that help to explain how pathogen-sensing pathways achieve specificity. This study establishes a broadly applicable, comprehensive, and unbiased approach to reveal the wiring and functions of a regulatory network controlling a major transcriptional response in primary mammalian cells., Burroughs Wellcome Fund (Career Award at the Scientific Interface), National Institutes of Health (U.S.) (Pioneer Award), Alfred P. Sloan Foundation

Transcriptional regulatory circuits govern how cis and trans factors transform signals into messenger RNA (mRNA) expression levels. With advances in quantitative and high-throughput technologies that allow measurement of gene expression state in different conditions, data that can be used to build and test models of transcriptional regulation is being generated at a rapid pace. Here, we review experimental and computational methods used to derive detailed quantitative circuit models on a small scale and cruder, genome-wide models on a large scale. We discuss the potential of combining small- and large-scale approaches to understand the working and wiring of transcriptional regulatory circuits.