Handbook of Systems Biology Concepts and Insights
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Chapter 3 Interactome Networks Anne-Ruxandra Carvunis1,2, Frederick P. Roth1,3, Michael A. Calderwood1,2, Michael E. Cusick1,2, Giulio Superti-Furga4 and Marc Vidal1,2 1Center for Cancer Systems Biology (CCSB) and Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA 02215, USA, 2Department of Genetics, Harvard Medical School, Boston, MA 02115, USA, 3Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Toronto, Ontario M5S-3E1, Canada, & Samuel Lunenfeld Research Institute, Mt. Sinai Hospital, Toronto, Ontario M5G-1X5, Canada, 4Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria Chapter Outline Introduction 45 Predicting Gene Functions, Phenotypes and Disease Life Requires Systems 45 Associations 53 Cells as Interactome Networks 46 Assigning Functions to Individual Interactions, Protein Interactome Networks and GenotypeePhenotype Complexes and Network Motifs 54 Relationships 47 Towards Dynamic Interactomes 55 Mapping and Modeling Interactome Networks 47 Towards Cell-Type and Condition-Specific Towards a Reference ProteineProtein Interactome Map 48 Interactomes 55 Strategies for Large-Scale ProteineProtein Interactome Evolutionary Dynamics of ProteineProtein Interactome Mapping 48 Networks 56 Large-Scale Binary Interactome Mapping 49 Concluding Remarks 57 Large-Scale Co-Complex Interactome Mapping 50 Acknowledgements 58 Drawing Inferences from Interactome Networks 51 References 58 Refining and Extending Interactome Network Models 51 INTRODUCTION generations of scientists and attempt to design new thera- Life Requires Systems peutic strategies. The next question then should be: even if we fully What is Life? The answer to the question posed by understood each of these four basic requirements of Schro¨dinger in a short but incisive book published in 1944 biology, would we be anywhere near a complete under- remains elusive more than seven decades later. Perhaps standing of how Life works? Would we be able to fully a less ambitious, but more pragmatic question could be: explain genotypeephenotype relationships? Would we be what does Life require? Biologists agree on at least four able to fully predict biological behaviors? How close would fundamental requirements, among which three are palpable we be to curing or alleviating suffering from human and easily demonstrable, and a fourth is more intangible diseases? It is becoming clear that even if we knew (Figure 3.1). First, Life requires chemistry. Biomolecules, everything there is to know about the four currently including metabolites, proteins and nucleic acids, mediate accepted requirements of biology, the answer to ‘What Life the most elementary functions of biology. Life also requires is’ would remain elusive. genes to encode and ‘reproduce’ biomolecules. For most The main reason is that biomolecules do not function in organisms, cells provide the fundamental medium in which isolation, nor do cells, organs or organisms, or even biological processes take place. The fourth requirement is ecosystems and sociological groups. Rather, biological evolution by natural selection. Classically, these ‘four great entities are involved in intricate and dynamic interactions, ideas of biology’ [1] have constituted the main intellectual thereby forming ‘complex systems’. In the last decade, framework around which biologists formulate biological novel biological questions and answers have surfaced, or questions, design experiments, interpret data, train younger resurfaced, pointing to systems as a fifth fundamental Handbook of Systems Biology Concepts and Insights. http://dx.doi.org/10.1016/B978-0-12-385944-0.00003-4 45 Copyright Ó 2013 Elsevier Inc. All rights reserved. 46 SECTION | II Network Properties of Biological Systems Equally enlightening theoretical systems properties were imagined beyond small-scale regulatory mechanisms composed of just a few molecules. Waddington introduced the metaphor of ‘epigenetic landscape’, whereby cells respond to genetic, developmental and environmental cues by following paths across a landscape containing peaks and valleys dictated by interacting genes and gene products [9]. This powerful idea, together with theoretical models of ‘randomly constructed genetic nets’ by Kauffman [10], suggested that a cellular system could be described in terms of ‘states’ resulting from particular combinations of genes, gene products, or metabolites, all considered either active or inactive at any given time. Complex wiring diagrams of functional and logical interconnectivity between biomole- cules and genes acting upon each other could be imagined to depict how systems ‘travel’ from state to state over time throughout a ‘state space’ determined by intricate, sophis- ticated combinations of genotype, systems properties and environmental conditions. These concepts, elaborated at a time when the molecular components of biology were FIGURE 3.1 Systems as a fifth requirement for Life. poorly described, remained largely ignored by molecular biologists until recently (see Chapter 15). Over the past two decades, scientific knowledge of the biomolecular components of biology has dramatically requirement for Life [2]. Although conceptual, systems increased. In particular, sequencing and bioinformatics may turn out to be as crucial to biology as chemistry, genes, have allowed prediction of coding and non-coding gene cells or evolution (Figure 3.1). products at genome scale. Transcriptome sequencing approaches have revealed the existence of transcripts that Cells as Interactome Networks had escaped prediction and which often remain of unknown function (see Chapter 2). Additionally, the list of known The study of biological systems, or ‘systems biology’, molecular components of cellular systems, including originated more than half a century ago, when a few nucleic acids, gene products and metabolites, is length- pioneers initially formulated a theoretical framework ening and becoming increasingly detailed. With these according to which multiscale dynamic complex systems advances came a humbling realization, best summed up as formed by interacting biomolecules could underlie cellular ‘too much data, too few drugs’ (see Chapter 8). It has behavior. To explain cellular differentiation, Delbru¨ck become clearer than ever that knowing everything there is hypothesized the existence of positive feedback circuits to know about each biomolecule in the cell is not sufficient required for ‘bistability’, a model in which systems would to predict how the cell will react as a whole to particular remain stably activated after having been turned on, and external or internal perturbations. conversely, remain steadily inactive once turned off [3]. Functional interactions, perhaps more so than indi- Empirical evidence for feedback regulation in biology first vidual components, mediate the fundamental requirements emerged in the 1950s. The Umbarger and Pardee groups of the cell. Consequently, one needs to consider biological uncovered enzymatic feedback inhibition [4,5], and Nov- phenomena as the product of ensembles of interacting ick and Weiner described the positive feedback circuit components with emergent properties that go beyond those regulating the lac operon [6]. Monod and Jacob subse- of their individual components considered in isolation. One quently proposed how negative feedback circuits could needs to step back and measure, model, and eventually account for homeostasis and other oscillatory phenomena perturb nearly all functional interactions between cellular observed in many biological processes [7]. These teleo- components to fully understand how cellular systems work. nomic arguments were later formalized by Rene´ Thomas In analogy to the word genome, the union of all interactions and others in terms of requirements for cellular and whole between all cellular components is termed the ‘inter- organism differentiation based on positive and negative actome’. Our working hypothesis is that interactomes feedback circuits of regulation, using Boolean modeling as exhibit local and global properties that relate to biology in powerful simplifications of cellular systems [8] (see general, and to genotypeephenotype relationships in Chapter 10). particular. Chapter | 3 Interactome Networks 47 Interactome Networks and GenotypeePhenotype Relationships Since drafts of a composite reference human genome sequence were released 10 years ago, powerful techno- logical developments, such as next-generation sequencing, have started a true revolution in genomics [11e14]. With time, most human genotypic variations will be described, together with large numbers of phenotypic associations. Unfortunately, such knowledge cannot trans- late directly into new mechanistic understanding or thera- FIGURE 3.2 Interactome networks and genotypeephenotype peutic strategies, in part because the ‘one-gene/one- relationships. enzyme/one-function’ concept developed by Beadle and Tatum oversimplifies genotypeephenotype relationships the complexity of genotypeephenotype relationships, [15]. In fact, Beadle and Tatum themselves state so in the including susceptibility to human disease (Figure 3.2). introduction of their groundbreaking paper that initiated reductionism in molecular biology: ‘An organism consists essentially of an integrated system of chemical reactions Mapping and Modeling Interactome controlled in some manner by genes. Since the components Networks of such systems are likely to be interrelated in complex ways, it would appear that