Tom C. Freeman

Transcriptome-Based Network Analysis Reveals a Spectrum Model of Human Macrophage Activation

Summary Macrophage activation is associated with profound transcriptional reprogramming. Although much progress has been made in the understanding of macrophage activation, polarization, and function, the transcriptional programs regulating these processes remain poorly characterized. We stimulated human macrophages with diverse activation signals, acquiring a data set of 299 macrophage transcriptomes. Analysis of this data set revealed a spectrum of macrophage activation states extending the current M1 versus M2-polarization model. Network analyses identified central transcriptional regulators associated with all macrophage activation complemented by regulators related to stimulus-specific programs. Applying these transcriptional programs to human alveolar macrophages from smokers and patients with chronic obstructive pulmonary disease (COPD) revealed an unexpected loss of inflammatory signatures in COPD patients. Finally, by integrating murine data from the ImmGen project we propose a refined, activation-independent core signature for human and murine macrophages. This resource serves as a framework for future research into regulation of macrophage activation in health and disease.

The Systems Biology Graphical Notation

Circuit diagrams and Unified Modeling Language diagrams are just two examples of standard visual languages that help accelerate work by promoting regularity, removing ambiguity and enabling software tool support for communication of complex information. Ironically, despite having one of the highest ratios of graphical to textual information, biology still lacks standard graphical notations. The recent deluge of biological knowledge makes addressing this deficit a pressing concern. Toward this goal, we present the Systems Biology Graphical Notation (SBGN), a visual language developed by a community of biochemists, modelers and computer scientists. SBGN consists of three complementary languages: process diagram, entity relationship diagram and activity flow diagram. Together they enable scientists to represent networks of biochemical interactions in a standard, unambiguous way. We believe that SBGN will foster efficient and accurate representation, visualization, storage, exchange and reuse of information on all kinds of biological knowledge, from gene regulation, to metabolism, to cellular signaling.

Tissue distribution of adenosine receptor mRNAs in the rat

1 A degree of ambiguity and uncertainty exists concerning the distribution of mRNAs encoding the four cloned adenosine receptors. In order to consolidate and extend current understanding in this area, the expression of the adenosine receptors has been examined in the rat by use of in situ hybridisation and the reverse transcription‐polymerase chain reaction (RT‐PCR). 2 In accordance with earlier studies, in situ hybridisation revealed that the adenosine A1 receptor was widely expressed in the brain, whereas A2A receptor mRNA was restricted to the striatum, nucleus accumbens and olfactory tubercle. In addition, A1 receptor mRNA was detected in large striatal cholinergic interneurones, 26% of these neurones were also found to express the A2A receptor gene. Central levels of mRNAs encoding adenosine A2B and A3 receptors were, however, below the detection limits of in situ hybridisation. 3 The more sensitive technique of RT‐PCR was then employed to investigate the distribution of adenosine receptor mRNAs in the central nervous system (CNS) and a wide range of peripheral tissues. As a result, many novel sites of adenosine receptor gene expression were identified. A1 receptor expression has now been found in the heart, aorta, liver, kidney, eye and bladder. These observations are largely consistent with previous functional data. A2A receptor mRNA was detected in all brain regions tested, demonstrating that expression of this receptor is not restricted to the basal ganglia. In the periphery A2A receptor mRNA was also found to be more widely distributed than generally recognised. The ubiquitous distribution of the A2B receptor is shown for the first time, A2B mRNA was detected at various levels in all rat tissues studied. Expression of the gene encoding the adenosine A3 receptor was also found to be widespread in the rat, message detected throughout the CNS and in many peripheral tissues. This pattern of expression is similar to that observed in man and sheep, which had previously been perceived to possess distinct patterns of A3 receptor gene expression in comparison to the rat. 4 In summary, this work has comprehensively studied the expression of all the cloned adenosine receptors in the rat, and in so doing, resolves some of the uncertainty over where these receptors might act to control physiological processes mediated by adenosine.

Somatic retrotransposition alters the genetic landscape of the human brain

Retrotransposons are mobile genetic elements that use a germline ‘copy-and-paste’ mechanism to spread throughout metazoan genomes. At least 50 per cent of the human genome is derived from retrotransposons, with three active families (L1, Alu and SVA) associated with insertional mutagenesis and disease. Epigenetic and post-transcriptional suppression block retrotransposition in somatic cells, excluding early embryo development and some malignancies. Recent reports of L1 expression and copy number variation in the human brain suggest that L1 mobilization may also occur during later development. However, the corresponding integration sites have not been mapped. Here we apply a high-throughput method to identify numerous L1, Alu and SVA germline mutations, as well as 7,743 putative somatic L1 insertions, in the hippocampus and caudate nucleus of three individuals. Surprisingly, we also found 13,692 somatic Alu insertions and 1,350 SVA insertions. Our results demonstrate that retrotransposons mobilize to protein-coding genes differentially expressed and active in the brain. Thus, somatic genome mosaicism driven by retrotransposition may reshape the genetic circuitry that underpins normal and abnormal neurobiological processes.

Network visualization and analysis of gene expression data using BioLayout Express(3D)

Network analysis has an increasing role in our effort to understand the complexity of biological systems. This is because of our ability to generate large data sets, where the interaction or distance between biological components can be either measured experimentally or calculated. Here we describe the use of BioLayout Express3D, an application that has been specifically designed for the integration, visualization and analysis of large network graphs derived from biological data. We describe the basic functionality of the program and its ability to display and cluster large graphs in two- and three-dimensional space, thereby rendering graphs in a highly interactive format. Although the program supports the import and display of various data formats, we provide a detailed protocol for one of its unique capabilities, the network analysis of gene expression data and a more general guide to the manipulation of graphs generated from various other data types.

Microglial brain region−dependent diversity and selective regional sensitivities to aging

Microglia have critical roles in neural development, homeostasis and neuroinflammation and are increasingly implicated in age-related neurological dysfunction. Neurodegeneration often occurs in disease-specific, spatially restricted patterns, the origins of which are unknown. We performed to our knowledge the first genome-wide analysis of microglia from discrete brain regions across the adult lifespan of the mouse, and found that microglia have distinct region-dependent transcriptional identities and age in a regionally variable manner. In the young adult brain, differences in bioenergetic and immunoregulatory pathways were the major sources of heterogeneity and suggested that cerebellar and hippocampal microglia exist in a more immune-vigilant state. Immune function correlated with regional transcriptional patterns. Augmentation of the distinct cerebellar immunophenotype and a contrasting loss in distinction of the hippocampal phenotype among forebrain regions were key features during aging. Microglial diversity may enable regionally localized homeostatic functions but could also underlie region-specific sensitivities to microglial dysregulation and involvement in age-related neurodegeneration.

Construction, Visualisation, and Clustering of Transcription Networks from Microarray Expression Data

Network analysis transcends conventional pairwise approaches to data analysis as the context of components in a network graph can be taken into account. Such approaches are increasingly being applied to genomics data, where functional linkages are used to connect genes or proteins. However, while microarray gene expression datasets are now abundant and of high quality, few approaches have been developed for analysis of such data in a network context. We present a novel approach for 3-D visualisation and analysis of transcriptional networks generated from microarray data. These networks consist of nodes representing transcripts connected by virtue of their expression profile similarity across multiple conditions. Analysing genome-wide gene transcription across 61 mouse tissues, we describe the unusual topography of the large and highly structured networks produced, and demonstrate how they can be used to visualise, cluster, and mine large datasets. This approach is fast, intuitive, and versatile, and allows the identification of biological relationships that may be missed by conventional analysis techniques. This work has been implemented in a freely available open-source application named BioLayout Express 3D.

Gateways to the FANTOM5 promoter level mammalian expression atlas

The FANTOM5 project investigates transcription initiation activities in more than 1,000 human and mouse primary cells, cell lines and tissues using CAGE. Based on manual curation of sample information and development of an ontology for sample classification, we assemble the resulting data into a centralized data resource (http://fantom.gsc.riken.jp/5/). This resource contains web-based tools and data-access points for the research community to search and extract data related to samples, genes, promoter activities, transcription factors and enhancers across the FANTOM5 atlas.

The genome of a pathogenic rhodococcus : cooptive virulence underpinned by key gene acquisitions

We report the genome of the facultative intracellular parasite Rhodococcus equi, the only animal pathogen within the biotechnologically important actinobacterial genus Rhodococcus. The 5.0-Mb R. equi 103S genome is significantly smaller than those of environmental rhodococci. This is due to genome expansion in nonpathogenic species, via a linear gain of paralogous genes and an accelerated genetic flux, rather than reductive evolution in R. equi. The 103S genome lacks the extensive catabolic and secondary metabolic complement of environmental rhodococci, and it displays unique adaptations for host colonization and competition in the short-chain fatty acid–rich intestine and manure of herbivores—two main R. equi reservoirs. Except for a few horizontally acquired (HGT) pathogenicity loci, including a cytoadhesive pilus determinant (rpl) and the virulence plasmid vap pathogenicity island (PAI) required for intramacrophage survival, most of the potential virulence-associated genes identified in R. equi are conserved in environmental rhodococci or have homologs in nonpathogenic Actinobacteria. This suggests a mechanism of virulence evolution based on the cooption of existing core actinobacterial traits, triggered by key host niche–adaptive HGT events. We tested this hypothesis by investigating R. equi virulence plasmid-chromosome crosstalk, by global transcription profiling and expression network analysis. Two chromosomal genes conserved in environmental rhodococci, encoding putative chorismate mutase and anthranilate synthase enzymes involved in aromatic amino acid biosynthesis, were strongly coregulated with vap PAI virulence genes and required for optimal proliferation in macrophages. The regulatory integration of chromosomal metabolic genes under the control of the HGT–acquired plasmid PAI is thus an important element in the cooptive virulence of R. equi.

Structural and functional annotation of the porcine immunome

BackgroundThe domestic pig is known as an excellent model for human immunology and the two species share many pathogens. Susceptibility to infectious disease is one of the major constraints on swine performance, yet the structure and function of genes comprising the pig immunome are not well-characterized. The completion of the pig genome provides the opportunity to annotate the pig immunome, and compare and contrast pig and human immune systems.ResultsThe Immune Response Annotation Group (IRAG) used computational curation and manual annotation of the swine genome assembly 10.2 (Sscrofa10.2) to refine the currently available automated annotation of 1,369 immunity-related genes through sequence-based comparison to genes in other species. Within these genes, we annotated 3,472 transcripts. Annotation provided evidence for gene expansions in several immune response families, and identified artiodactyl-specific expansions in the cathelicidin and type 1 Interferon families. We found gene duplications for 18 genes, including 13 immune response genes and five non-immune response genes discovered in the annotation process. Manual annotation provided evidence for many new alternative splice variants and 8 gene duplications. Over 1,100 transcripts without porcine sequence evidence were detected using cross-species annotation. We used a functional approach to discover and accurately annotate porcine immune response genes. A co-expression clustering analysis of transcriptomic data from selected experimental infections or immune stimulations of blood, macrophages or lymph nodes identified a large cluster of genes that exhibited a correlated positive response upon infection across multiple pathogens or immune stimuli. Interestingly, this gene cluster (cluster 4) is enriched for known general human immune response genes, yet contains many un-annotated porcine genes. A phylogenetic analysis of the encoded proteins of cluster 4 genes showed that 15% exhibited an accelerated evolution as compared to 4.1% across the entire genome.ConclusionsThis extensive annotation dramatically extends the genome-based knowledge of the molecular genetics and structure of a major portion of the porcine immunome. Our complementary functional approach using co-expression during immune response has provided new putative immune response annotation for over 500 porcine genes. Our phylogenetic analysis of this core immunome cluster confirms rapid evolutionary change in this set of genes, and that, as in other species, such genes are important components of the pig’s adaptation to pathogen challenge over evolutionary time. These comprehensive and integrated analyses increase the value of the porcine genome sequence and provide important tools for global analyses and data-mining of the porcine immune response.