Current Genomics - Volume 5, Issue 7, 2004

Whole genome sequencing has provided us with genetic “parts lists” of a growing number of model organisms and spawned the development of a remarkable array of new technologies to enable the global and quantitative molecular interrogation of biological systems. These global approaches have also catalyzed the development of computational tools for capturing, quantifying, storing, analyzing, displaying and modeling biological information. While these analyses in isolation provide valuable information about various cellular properties, the integration and collective analysis of different data types can provide important new insights at a systems level. Ultimately, a major challenge for systems biologists is to explain biological information, at any of its hierarchical levels (DNA, mRNA, proteins and metabolites; to hierarchical levels of dynamic interacting networks comprised of these elements; to extended networks of cells, organs, organisms and ecologies), in terms of digital genomic information and its interplay with external forces that act upon it. Currently the most accessible system to begin a comprehensive understanding of the relationship between the genome and external cues is that of transcriptional regulation. At this level of hierarchy, we can realistically expect to enumerate a core of relevant players and, using global experimental approaches combined with computational tools, build a comprehensive and predictive network of dynamic molecular interactions. These philosophies and goals lie at the heart of Systems Biology and are presented in two reviews in this issue of Current Genomics. Both reviews highlight the unique challenges and successes of studying cellular regulation from a systems biology perspective and enumerate methods that promise to lead to an understanding of how extrinsic and intrinsic contextual information controls the digital genome. The first article by Facciotti et al. reviews systems biology approaches with a focus on relatively simple prokaryotic systems. This review highlights many aspects of the integrative approach towards fully describing and predicting a simple model organism. The second article by Smith and Thorsson takes these approaches to human innate immunity. While considerably more complex and hindered by the fact that many of the players in the game still need to be identified, this review highlights the advances systems biology enables despite these current limitations. While these reviews represent the state-of-the art for systems biology, they tend to neglect the impact that the spatial organization of the cell has on regulation. Thus, the third review in the series, by Dundr and Misteli, represents some of the most significant challenges systems biologists must ultimately face to fully appreciate and predict biological behavior at the level of gene regulatory networks. In essence, the challenge presented is to understand the regulation of the genome in the context of a living cell, incorporating ideas such as single cell responses (as apposed to that of the population), the dynamic and temporal binding of regulatory proteins, chromatin organization, and gene positioning within the three-dimensional context of the nucleus. Biologists now have the ability to know the identity of the elements in a system and have many of the tools to measure the concentrations or relationships of these elements. These comprehensive measurements, when coupled with emerging methods to fuse divergent large-scale data sets and computer modeling, can yield a global perspective that will enable the functional characterization of biological systems as a whole. The three reviews emphasize the need to generate different types of dynamic molecular data on defined systems and the tight integration of biological inquiry with technological and computational advances that go hand in hand with iterative model refinement. These principles are the essence of systems biology and promise to ultimately lead to the accurate prediction of cellular behavior.

The goal of systems biology is to describe and quantitatively model complete biological systems. It is a reasonable goal to begin by developing quantitative models that accurately recapitulate many aspects of gene regulatory networks for some simple organisms. We consider here the advantages of using prokaryotic organisms as model systems in the initial development of such quantitative models. In addition, we discuss some of the benefits of studying stress responses in these organisms and illustrate some of the biological and theoretical complexities facing the analyses of dynamic biological systems.

Systems biology strives to derive comprehensive and accurate descriptions of complex systems such as the innate immune system. The innate immune system is essential for host defense and is responsible for early detection and containment of pathogens, yet the resulting inflammatory response is a double-edged sword that must be tightly regulated. Our current understanding indicates that the innate immune system is controlled by complex regulatory networks, which contain cross-talk, insulation, feedback loops, signal amplification, integration and dampening. Such dynamic behavior and complexity are essential to innate immunity, and critical for maintaining homoeostasis and accurately distinguishing pathogenic microbial infections from harmless threats. We focus this review on Toll-like receptor regulation of innate immune response to microbial pathogens, and emphasize recent studies using high throughput technologies and computational approaches in this field. The eventual integration of global molecular and interaction data into predictive models will provide the necessary foundation to cultivate a systems level understanding of innate immunity.

The last decades have lead to the identification and characterization of most key steps in gene expression including chromatin remodeling, transcription, RNA processing, export and translation. Extensive biochemical, genetic and molecular approaches have not only revealed the key players involved in these processes, but have yielded detailed insights into the molecular behavior of many. Despite the wealth of molecular and structural information of distinct processes of gene expression and of single molecular components, fundamental aspects of the system behavior of the gene expression machinery have remained elusive. It is just now becoming clear that the single steps in the gene expression process are tightly interlinked and virtually nothing is known about how the various components of genome regulation and expression machineries are integrated into presumably complex networks of interactions and pathways. Even more elusive has been the elucidation of how gene expression processes occur in their natural setting of the cell nucleus in intact living cells. Recent advances in qualitative and quantitative imaging methods are beginning to provide tools to study the complexity of the gene expression process in living cells. We briefly review here some emerging in vivo imaging technologies and summarize the recent results and the conceptual impact these methods are making on understanding transcriptional complexity in vivo.

The completion of the human genome project and the increasing availability of cDNAs to most genes made accessible the possibility of identifying the function of every gene. In contrast to most previous studies which typically examined one or a few human genes at a time for their biological effects, activity, or expression levels, new reagent sets and technological advances now allow large subsets or potentially even all human genes to be studied in a single experiment. Such high throughput approaches not only evaluate expression patterns of known genes, they may also be useful for assigning new activities to genes, placing them in signaling networks not previously known. Functional genomic studies that systematically manipulate either gene overexpression or gene knockdown via RNA interference are particularly useful for gaining global insights into gene function. Expansion of current genomic approaches to phenotypic and functional assays will likely provide new insights into the normal and pathological activities of many genes, undoubtedly accelerating the development of new therapeutic approaches for diagnosing, treating, and preventing disease.

Factors involved in mitochondrial biogenesis and function have been studied classically via mutagenesis screens and subsequent genetic and biochemical analyses. The recent advent of high-throughput technologies has provided a wealth of information regarding mitochondrial function, morphology, gene regulation, protein complexes, and disease in a fraction of the time. This review will describe past and present genomic and proteomic methods used to study mitochondria both in yeast and mammalian cells, their advantages and limitations, and the current knowledge of the number of genes and proteins that are required for proper functioning of the organelle.

The availability of complete genome sequences of more than 160 pathogenic and non-pathogenic bacteria is facilitating the understanding of evolution of bacterial virulence. Comparative genomics revealed that most pathogens have a relative by stable core genome, encoding factors essential for growth in a specific environment and a flexible gene pool, encoding virulence traits, resistance determinants and genes that confer gene-mobility such as transposons, integrases and insertion sequences. The flexible part of the genome often determines the virulence of a particular organism. This concept originally developed for Enterobacteriaceae is now being proven also for gram-positive pathogens such as staphylococci, streptococci and enterococci. For example, pathogenic staphylococci are now the most common cause of nosocomial infections. It is assumed that the enormous genome plasticity of staphylococci is the basis for the rapid adaptation of staphylococci in the highly selective environment of hospitals. The genome of pathogenic staphylococci consists of a complex mosaic of larger regions which have been acquired by horizontal gene transfer. Remarkably, mobile genetic elements such as resistance and pathogenicity islands, bacteriophages, IS-elements, plasmids, and transposons are widespread among clinical isolates. In this review, we summarise the recent results from comparative genomics studies of selected gram-positive bacterial pathogens and discuss the implications of these studies for the evolution of bacterial pathogenicity.

In the last two decades, a number of attempts have been made to unravel the complex genetic background of alcohol dependence. There is evidence from family, twin and adoption studies that the contribution of genetic factors accounts for 40-60% of alcohol dependence. In humans, the main approaches for investigating the complex genetics of alcoholism are linkage and association studies. Linkage studies reported alcoholism to be linked to only 5 chromosomal regions (on chromosomes 1, 7, and possibly 2, 4 and 5) and none of those loci reached a high statistical significance. Association studies are conducted by numerous research groups. They test a potential relationship between a certain genetic variant and alcoholism in a design similar to the classical case-control studies. Polymorphisms in the GABAergic, serotonergic, dopaminergic, and glutamatergic system have been related to alcohol- or alcoholism-associated phenotypes. Many studies failed to confirm initial positive results, raising doubts on the validity and replicability of this study approach. Recently more research has been conducted using genetic microarrays to investigate expression patterns of genes under the influence of chronic alcohol consumption. However, these approaches have several shortcomings, in particular their applicability in humans. In short, approaches in use for years by many research groups such as linkage and association studies showed either controversial or disappointing results. New approaches using endophenotypes and genetic microarrays may be helpful to shed light more light on the complex genetic background of alcoholism.