Jessica C. Mar

Arteriolar niches maintain haematopoietic stem cell quiescence

Cell cycle quiescence is a critical feature contributing to haematopoietic stem cell (HSC) maintenance. Although various candidate stromal cells have been identified as potential HSC niches, the spatial localization of quiescent HSCs in the bone marrow remains unclear. Here, using a novel approach that combines whole-mount confocal immunofluorescence imaging techniques and computational modelling to analyse significant three-dimensional associations in the mouse bone marrow among vascular structures, stromal cells and HSCs, we show that quiescent HSCs associate specifically with small arterioles that are preferentially found in endosteal bone marrow. These arterioles are ensheathed exclusively by rare NG2 (also known as CSPG4)+ pericytes, distinct from sinusoid-associated leptin receptor (LEPR)+ cells. Pharmacological or genetic activation of the HSC cell cycle alters the distribution of HSCs from NG2+ periarteriolar niches to LEPR+ perisinusoidal niches. Conditional depletion of NG2+ cells induces HSC cycling and reduces functional long-term repopulating HSCs in the bone marrow. These results thus indicate that arteriolar niches are indispensable for maintaining HSC quiescence.

Interpreting cancer genomes using systematic host network perturbations by tumour virus proteins

Genotypic differences greatly influence susceptibility and resistance to disease. Understanding genotype–phenotype relationships requires that phenotypes be viewed as manifestations of network properties, rather than simply as the result of individual genomic variations. Genome sequencing efforts have identified numerous germline mutations, and large numbers of somatic genomic alterations, associated with a predisposition to cancer. However, it remains difficult to distinguish background, or ‘passenger’, cancer mutations from causal, or ‘driver’, mutations in these data sets. Human viruses intrinsically depend on their host cell during the course of infection and can elicit pathological phenotypes similar to those arising from mutations. Here we test the hypothesis that genomic variations and tumour viruses may cause cancer through related mechanisms, by systematically examining host interactome and transcriptome network perturbations caused by DNA tumour virus proteins. The resulting integrated viral perturbation data reflects rewiring of the host cell networks, and highlights pathways, such as Notch signalling and apoptosis, that go awry in cancer. We show that systematic analyses of host targets of viral proteins can identify cancer genes with a success rate on a par with their identification through functional genomics and large-scale cataloguing of tumour mutations. Together, these complementary approaches increase the specificity of cancer gene identification. Combining systems-level studies of pathogen-encoded gene products with genomic approaches will facilitate the prioritization of cancer-causing driver genes to advance the understanding of the genetic basis of human cancer.

Epstein-Barr virus exploits intrinsic B-lymphocyte transcription programs to achieve immortal cell growth

Epstein-Barr virus nuclear antigen 2 (EBNA2) regulation of transcription through the cell transcription factor RBPJ is essential for resting B-lymphocyte (RBL) conversion to immortal lymphoblast cell lines (LCLs). ChIP-seq of EBNA2 and RBPJ sites in LCL DNA found EBNA2 at 5,151 and RBPJ at 10,529 sites. EBNA2 sites were enriched for RBPJ (78%), early B-cell factor (EBF, 39%), RUNX (43%), ETS (39%), NFκB (22%), and PU.1 (22%) motifs. These motif associations were confirmed by LCL RBPJ ChIP-seq finding 72% RBPJ occupancy and Encyclopedia Of DNA Elements LCL ChIP-seq finding EBF, NFκB RELA, and PU.1 at 54%, 31%, and 17% of EBNA2 sites. EBNA2 and RBPJ were predominantly at intergene and intron sites and only 14% at promoter sites. K-means clustering of EBNA2 site transcription factors identified RELA-ETS, EBF-RUNX, EBF, ETS, RBPJ, and repressive RUNX clusters, which ranked from highest to lowest in H3K4me1 signals and nucleosome depletion, indicative of active chromatin. Surprisingly, although quantitatively less, the same genome sites in RBLs exhibited similar high-level H3K4me1 signals and nucleosome depletion. The EBV genome also had an LMP1 promoter EBF site, which proved critical for EBNA2 activation. LCL HiC data mapped intergenic EBNA2 sites to EBNA2 up-regulated genes. FISH and chromatin conformation capture linked EBNA2/RBPJ enhancers 428 kb 5′ of MYC to MYC. These data indicate that EBNA2 evolved to target RBL H3K4me1 modified, nucleosome-depleted, nonpromoter sites to drive B-lymphocyte proliferation in primary human infection. The primed RBL program likely supports antigen-induced proliferation.

Variance of gene expression identifies altered network constraints in neurological disease

Gene expression analysis has become a ubiquitous tool for studying a wide range of human diseases. In a typical analysis we compare distinct phenotypic groups and attempt to identify genes that are, on average, significantly different between them. Here we describe an innovative approach to the analysis of gene expression data, one that identifies differences in expression variance between groups as an informative metric of the group phenotype. We find that genes with different expression variance profiles are not randomly distributed across cell signaling networks. Genes with low-expression variance, or higher constraint, are significantly more connected to other network members and tend to function as core members of signal transduction pathways. Genes with higher expression variance have fewer network connections and also tend to sit on the periphery of the cell. Using neural stem cells derived from patients suffering from Schizophrenia (SZ), Parkinsons disease (PD), and a healthy control group, we find marked differences in expression variance in cell signaling pathways that shed new light on potential mechanisms associated with these diverse neurological disorders. In particular, we find that expression variance of core networks in the SZ patient group was considerably constrained, while in contrast the PD patient group demonstrated much greater variance than expected. One hypothesis is that diminished variance in SZ patients corresponds to an increased degree of constraint in these pathways and a corresponding reduction in robustness of the stem cell networks. These results underscore the role that variation plays in biological systems and suggest that analysis of expression variance is far more important in disease than previously recognized. Furthermore, modeling patterns of variability in gene expression could fundamentally alter the way in which we think about how cellular networks are affected by disease processes.

Divergent reprogramming routes lead to alternative stem-cell states

Pluripotency is defined by the ability of a cell to differentiate to the derivatives of all the three embryonic germ layers: ectoderm, mesoderm and endoderm. Pluripotent cells can be captured via the archetypal derivation of embryonic stem cells or via somatic cell reprogramming. Somatic cells are induced to acquire a pluripotent stem cell (iPSC) state through the forced expression of key transcription factors, and in the mouse these cells can fulfil the strictest of all developmental assays for pluripotent cells by generating completely iPSC-derived embryos and mice. However, it is not known whether there are additional classes of pluripotent cells, or what the spectrum of reprogrammed phenotypes encompasses. Here we explore alternative outcomes of somatic reprogramming by fully characterizing reprogrammed cells independent of preconceived definitions of iPSC states. We demonstrate that by maintaining elevated reprogramming factor expression levels, mouse embryonic fibroblasts go through unique epigenetic modifications to arrive at a stable, Nanog-positive, alternative pluripotent state. In doing so, we prove that the pluripotent spectrum can encompass multiple, unique cell states.

Data-driven normalization strategies for high-throughput quantitative RT-PCR

BackgroundHigh-throughput real-time quantitative reverse transcriptase polymerase chain reaction (qPCR) is a widely used technique in experiments where expression patterns of genes are to be profiled. Current stage technology allows the acquisition of profiles for a moderate number of genes (50 to a few thousand), and this number continues to grow. The use of appropriate normalization algorithms for qPCR-based data is therefore a highly important aspect of the data preprocessing pipeline.ResultsWe present and evaluate two data-driven normalization methods that directly correct for technical variation and represent robust alternatives to standard housekeeping gene-based approaches. We evaluated the performance of these methods against a single gene housekeeping gene method and our results suggest that quantile normalization performs best. These methods are implemented in freely-available software as an R package qpcrNorm distributed through the Bioconductor project.ConclusionThe utility of the approaches that we describe can be demonstrated most clearly in situations where standard housekeeping genes are regulated by some experimental condition. For large qPCR-based data sets, our approaches represent robust, data-driven strategies for normalization.

Viral perturbations of host networks reflect disease etiology.

Many human diseases, arising from mutations of disease susceptibility genes (genetic diseases), are also associated with viral infections (virally implicated diseases), either in a directly causal manner or by indirect associations. Here we examine whether viral perturbations of host interactome may underlie such virally implicated disease relationships. Using as models two different human viruses, Epstein-Barr virus (EBV) and human papillomavirus (HPV), we find that host targets of viral proteins reside in network proximity to products of disease susceptibility genes. Expression changes in virally implicated disease tissues and comorbidity patterns cluster significantly in the network vicinity of viral targets. The topological proximity found between cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway linking HPV to Fanconi anemia.

Further Evidence for BRCA1 Communication with the Inactive X Chromosome

BRCA1, a breast and ovarian cancer-suppressor gene, exerts tumor-suppressing functions that appear to be associated, at least in part, with its DNA repair, checkpoint, and mitotic regulatory activities. Earlier work from our laboratory also suggested an ability of BRCA1 to communicate with the inactive X chromosome (Xi) in female somatic cells (Ganesan et al., 2002). Xiao et al. (2007) (this issue of Cell) have challenged this conclusion. Here we discuss recently published data from our laboratory and others and present new results that, together, provide further support for a role of BRCA1 in the regulation of XIST concentration on Xi in somatic cells.

Self-renewal of a purified Tie2+ hematopoietic stem cell population relies on mitochondrial clearance

Purified hematopoietic stem cells reveal that mitophagy plays a key role in their expansion. How to maintain hematopoietic stem cells Hematopoiesis provides the body with a continuous supply of blood cells (see the Perspective by Sommerkamp and Trumpp). Taya et al. report that amino acid content is important for hematopoietic stem cell (HSC) maintenance in vitro and in vivo. Dietary valine restriction seems to “empty” the mouse bone marrow niche. Ito et al. used single-cell approaches and cell transplantation to identify a subset of HSCs at the top of the HSC hierarchy. Self-renewal relied on the induction of mitophagy, a quality-control process linked to a cells metabolic state. Both studies may be helpful in improving clinical bone marrow transplantation. Science, this issue p. 1103, p. 1152; see also p. 1156 A single hematopoietic stem cell (HSC) is capable of reconstituting hematopoiesis and maintaining homeostasis by balancing self-renewal and cell differentiation. The mechanisms of HSC division balance, however, are not yet defined. Here we demonstrate, by characterizing at the single-cell level a purified and minimally heterogeneous murine Tie2+ HSC population, that these top hierarchical HSCs preferentially undergo symmetric divisions. The induction of mitophagy, a quality control process in mitochondria, plays an essential role in self-renewing expansion of Tie2+ HSCs. Activation of the PPAR (peroxisome proliferator–activated receptor)–fatty acid oxidation pathway promotes expansion of Tie2+ HSCs through enhanced Parkin recruitment in mitochondria. These metabolic pathways are conserved in human TIE2+ HSCs. Our data thus identify mitophagy as a key mechanism of HSC expansion and suggest potential methods of cell-fate manipulation through metabolic pathways.

Immunogenetics of CD4 Lymphocyte Count Recovery during Antiretroviral Therapy: An AIDS Clinical Trials Group Study

During antiretroviral therapy, CD4 lymphocyte count increases are modest in some patients despite virologic control. We explored whether polymorphisms in genes important for T cell expansion, survival, and apoptosis are associated with the magnitude of CD4 lymphocyte count recovery during antiretroviral therapy. We studied treatment-naive individuals who achieved sustained control of plasma viremia (<400 HIV-1 RNA copies/mL) for at least 48 weeks after initiation of antiretroviral therapy and compared genotypes among individuals who had an increase of either <200 or > or =200 CD4 cells/mm3 from baseline. A total of 137 single-nucleotide polymorphisms across 17 genes were characterized in 873 study participants. In multivariate analyses that controlled for clinical variables, polymorphisms in genes encoding tumor necrosis factor (TNF)-related apoptosis-inducing ligand (TRAIL), TNF- alpha , Bcl-2-interacting molecule (Bim), interleukin (IL)-15, and IL-15 receptor alpha chain (IL-15R alpha ) were associated with the magnitude of the increase in CD4 lymphocyte count, as were haplotypes in genes encoding interferon- alpha , IL-2, and IL-15R alpha (P < .05, for each). Multifactor dimensionality reduction identified a gene-gene interaction between IL-2/IL-15 receptor common beta chain and IL-2/IL-7/IL-15 receptor common gamma chain. Immune recovery during antiretroviral therapy is a complex phenotype that is influenced by multiple genetic variants. Future studies should validate these tentative associations and define underlying mechanisms.