Bruce M. Spiegelman

Bio: Bruce M. Spiegelman is an academic researcher from Harvard University. The author has contributed to research in topics: Adipose tissue & Peroxisome proliferator-activated receptor. The author has an hindex of 179, co-authored 434 publications receiving 158009 citations. Previous affiliations of Bruce M. Spiegelman include University of California, San Francisco & Vassar College.

Regulation of hepatic fasting response by PPARγ coactivator-1α (PGC-1): Requirement for hepatocyte nuclear factor 4α in gluconeogenesis

Abstract: The liver plays several critical roles in the metabolic adaptation to fasting. We have shown previously that the transcriptional coactivator peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) is induced in fasted or diabetic liver and activates the entire program of gluconeogenesis. PGC-1α interacts with several nuclear receptors known to bind gluconeogenic promoters including the glucocorticoid receptor, hepatocyte nuclear factor 4α (HNF4α), and the peroxisome proliferator-activated receptors. However, the genetic requirement for any of these interactions has not been determined. Using hepatocytes from mice lacking HNF4α in the liver, we show here that PGC-1α completely loses its ability to activate key genes of gluconeogenesis such as phosphoenolpyruvate carboxykinase and glucose-6-phosphatase when HNF4α is absent. It is also shown that PGC-1α can induce genes of β-oxidation and ketogenesis in hepatocytes, but these effects do not require HNF4α. Analysis of the glucose-6-phosphatase promoter indicates a key role for HNF4α-binding sites that function robustly only when HNF4α is coactivated by PGC-1α. These data illustrate the involvement of PGC-1α in several aspects of the hepatic fasting response and show that HNF4α is a critical component of PGC-1α-mediated gluconeogenesis.

ADD1/SREBP-1c Is Required in the Activation of Hepatic Lipogenic Gene Expression by Glucose

Abstract: The transcription of genes encoding proteins involved in the hepatic synthesis of lipids from glucose is strongly stimulated by carbohydrate feeding. It is now well established that in the liver, glucose is the main activator of the expression of this group of genes, with insulin having only a permissive role. While ADD1/SREBP-1 has been implicated in lipogenic gene expression through temporal association with food intake and ectopic gain-of-function experiments, no genetic evidence for a requirement for this factor in glucose-mediated gene expression has been established. We show here that the transcription of ADD1/SREBP-1c in primary cultures of hepatocytes is controlled positively by insulin and negatively by glucagon and cyclic AMP, establishing a link between this transcription factor and carbohydrate availability. Using adenovirus-mediated transfection of a powerful dominant negative form of ADD1/SREBP-1c in rat hepatocytes, we demonstrate that this factor is absolutely necessary for the stimulation by glucose of l-pyruvate kinase, fatty acid synthase, S14, and acetyl coenzyme A carboxylase gene expression. These results demonstrate that ADD1/SREBP-1c plays a crucial role in mediating the expression of lipogenic genes induced by glucose and insulin.

p38 Mitogen-Activated Protein Kinase Is the Central Regulator of Cyclic AMP-Dependent Transcription of the Brown Fat Uncoupling Protein 1 Gene

Abstract: It is well established that catecholamine-stimulated thermogenesis in brown fat requires β-adrenergic elevations in cyclic AMP (cAMP) to increase expression of the uncoupling protein 1 (UCP1) gene. However, little is known about the downstream components of the signaling cascade or the relevant transcription factor targets thereof. Here we demonstrate that cAMP- and protein kinase A-dependent activation of p38 mitogen-activated protein kinase (MAPK) in brown adipocytes is an indispensable step in the transcription of the UCP1 gene in mice. By phosphorylating activating transcription factor 2 (ATF-2) and peroxisome proliferator-activated receptor gamma (PPARγ) coativator 1α (PGC-1α), members of two distinct nuclear factor families, p38 MAPK controls the expression of the UCP1 gene through their respective interactions with a cAMP response element and a PPAR response element that both reside within a critical enhancer motif of the UCP1 gene. Activation of ATF-2 by p38 MAPK additionally serves as the cAMP sensor that increases expression of the PGC-1α gene itself in brown adipose tissue. In conclusion, our findings illustrate that by orchestrating the activity of multiple transcription factors, p38 MAPK is a central mediator of the cAMP signaling mechanism of brown fat that promotes thermogenesis.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

Obesity is associated with macrophage accumulation in adipose tissue

Abstract: Obesity alters adipose tissue metabolic and endocrine function and leads to an increased release of fatty acids, hormones, and proinflammatory molecules that contribute to obesity associated complications. To further characterize the changes that occur in adipose tissue with increasing adiposity, we profiled transcript expression in perigonadal adipose tissue from groups of mice in which adiposity varied due to sex, diet, and the obesity-related mutations agouti (Ay) and obese (Lepob). We found that the expression of 1,304 transcripts correlated significantly with body mass. Of the 100 most significantly correlated genes, 30% encoded proteins that are characteristic of macrophages and are positively correlated with body mass. Immunohistochemical analysis of perigonadal, perirenal, mesenteric, and subcutaneous adipose tissue revealed that the percentage of cells expressing the macrophage marker F4/80 (F4/80+) was significantly and positively correlated with both adipocyte size and body mass. Similar relationships were found in human subcutaneous adipose tissue stained for the macrophage antigen CD68. Bone marrow transplant studies and quantitation of macrophage number in adipose tissue from macrophage-deficient (Csf1op/op) mice suggest that these F4/80+ cells are CSF-1 dependent, bone marrow-derived adipose tissue macrophages. Expression analysis of macrophage and nonmacrophage cell populations isolated from adipose tissue demonstrates that adipose tissue macrophages are responsible for almost all adipose tissue TNF-alpha expression and significant amounts of iNOS and IL-6 expression. Adipose tissue macrophage numbers increase in obesity and participate in inflammatory pathways that are activated in adipose tissues of obese individuals.