Table Of Content

Gene Regulation and Metabolism Computational Molecular Biology Sorin Istrail, Pavel Pevzner, and Michael Waterman, editors Computational Methods for Modeling Biochemical Networks James M. Bower and Hamid Bolouri, editors, 2000 Computational Molecular Biology: An Algorithmic Approach Pavel A. Pevzner, 2000 Current Topics in Computational Molecular Biology Tao Jiang, Ying Xu, and Michael Q. Zhang, editors, 2002 Gene Regulation and Metabolism: Postgenomic Computational Approaches Julio Collado-Vides and Ralf Hofesta¨dt, editors, 2002 Microarrays for an Integrative Genomics Isaac S. Kohane, Alvin Kho, and Atul J. Butte, 2002 Gene Regulation and Metabolism Postgenomic Computational Approaches edited by Julio Collado-Vides and Ralf Hofesta¨dt A Bradford Book The MIT Press Cambridge, Massachusetts London, England (2002MassachusettsInstituteofTechnology Allrightsreserved.Nopartofthisbookmaybereproducedinanyformbyanyelectronic ormechanicalmeans(includingphotocopying,recording,orinformationstorageandre- trieval)withoutpermissioninwritingfromthepublisher. ThisbookwassetinPalatinoon3B2byAscoTypesetters,HongKongandwasprinted andboundintheUnitedStatesofAmerica. LibraryofCongressCataloging-in-PublicationData Generegulationandmetabolism:postgenomiccomputationalapproaches/editedby JulioCollado-Vides&RalfHofesta¨dt. p. cm.— (Computationalmolecularbiology) Includesbibliographicalreferencesandindex. ISBN0-262-03297-X(hc.:alk.paper) 1.Genetics—Mathematicalmodels. 2.Molecularbiology—Mathematicalmodels. I.Collado-Vides,Julio. II.Hofesta¨dt,Ralf. III.Series. QH438.4.M3G462002 572.800105118—dc21 2001056247 Contents Preface vii 1 Are the Eyes Homologous? 1 Jeremy C. Ahouse I Information and Knowledge Representation 17 2 Automation of Protein Sequence Characterization and Its Application in Whole Proteome Analysis 19 Rolf Apweiler, Margaret Biswas, Wolfgang Fleischmann, Evgenia V. Kriventseva, and Nicola Mulder 3 Information Fusion and Metabolic Network Control 49 Andreas Freier, Ralf Hofesta¨dt, Matthias Lange, and Uwe Scholz II Gene Regulation: From Sequence to Networks 85 4 Specificity of Protein-DNA Interactions 87 Gary D. Stormo 5 Genomics of Gene Regulation: The View from Escherichia coli 103 Julio Collado-Vides, Gabriel Moreno-Hagelsieb, Ernesto Pe´rez-Rueda, Heladia Salgado, Araceli M. Huerta, Rosa Mar´ıa Gutie´rrez, David A. Rosenblueth, Andre´s Christen, Esperanza Ben´ıtez-Belloń, Arturo Medrano-Soto, Socorro Gama-Castro, Alberto Santos-Zavaleta, Ce´sar Bonavides-Mart´ınez, Edgar D´ıaz-Peredo, Fabiola Sańchez-Solano, and Dulce Mar´ıa Millań 6 Discovery of DNA Regulatory Motifs 129 Abigail Manson McGuire and George M. Church 7 Gene Networks Description and Modeling in the GeneNet System 149 Nikolay A. Kolchanov, Elena A. Ananko, Vitali A. Likhoshvai, Olga A. Podkolodnaya, Elena V. Ignatieva, Alexander V. Ratushny, and Yuri G. Matushkin 8 Regulation of Cellular States in Mammalian Cells from a Genomewide View 181 Sui Huang III Postgenomic Approaches 221 9 Predicting Protein Function and Networks on a Genomewide Scale 223 Edward M. Marcotte 10 Metabolic Pathways 251 Steffen Schmidt and Thomas Dandekar 11 Toward Computer Simulation of the Whole Cell 273 Masaru Tomita Glossary 289 Corresponding Authors 297 Index 299 vi Contents Preface Weareinthemiddleofagenomeperiodmarkedbythefullsequencing of complete genomes. Last year (2001) will be identified in the history of biology by the publication of the first draft of the complete sequence ofthehumangenome.Muchworkstillliesaheadtoachievethegoalof fully finishing many of these eukaryotic and prokaryotic genomes that, as published, still contain gaps. At a first glance, genomics has not produced a strong conceptual change in biology. The fundamental problems remain: understanding the origin of life, the complex organization of a cell, the pathways of differentiation, aging, and the molecular and cellular bases for the capabilities of the brain. What has happened is an explosion of molec- ularinformation;genomicsequenceswillbefollowedinthenearfuture by exhaustive catalogs of protein interactions and protein function (as proteomicstakesthelead). Thiswealth ofinformation can be analyzed, visualized, and manipulated only with the help of computers. This basic contribution of computers was initially not recognized by biologists. Certainly, by the time of the beginning of GenBank, in the 1980s, the experimentalist could imagine an institute where computational biology was merely technical support for databases and access to Gen- Bank, and maybe a classic Bohering metabolic chart hung on the wall (initiated in the 1960s by G. Michal). The influence of genomes is such that today what FrançoisJacob conceived as theMouseInstitutewould do much better having on staff experimentalists, computer scientists, statisticians, mathematicians, and computational biologists. We have reachedapointwherebiologyarticlesarepublishedwithcontributions from researchers who recently were, for instance, computer scientists working in logic programming. This is no small change if we remember the place of theoretical and mathematical biology as an activity that could be fascinating, but to a large extent was done in isolation, having little influence on main- stream experimental molecular biology. Today, the student, post- doctoralfellow,orevenyoungprofessorwhoisknowledgeableboth in biology and in computer science has much broader opportunities. Gen- omics may really be opening the door to a more profound conceptual change in the way we study living systems in the laboratory. With a foot in sequence analysis, this book is centered on current computational approaches to metabolism and gene regulation. This is an area of computational biology that welcomes new methods, ideas, and approaches with the goal of generating a better understanding of the complex networks of metabolic and regulatory capabilities of the cell. Classical concepts have to be redefined or clarified to address the study ofthegeneticsof populationsand ofthebiochemicalinteractions and regulatory networks organizing a living system. Given the con- stant and pervading importance of comparative genomics, these concepts must be precise when comparing genes, proteins, and systems across different species. The first chapter, by Jeremy Ahouse, is an exercise in thinking about the concept of homology (the common origin of similarities) in order to use it adequately when considering homologous networks of gene regulation between species. Currently, DNA sequence data is the most abundant material with whichtobeginaprojectincomputationalbiology.Rawsequencesfrom genomes have to be analyzed and annotated, in ways that improve continuously as the databases expand and sharper methods are used. The second chapter, by Rolf Apweiler and colleagues, describes an integrated system for this task. Databases centering on specific signals, motifs, or structures have exploded in number in the last years. The databases describe those pieces of macromolecules whose function we know, and therefore are essential for algorithmic analyses. The third chapter, by the team of Ralf Hofesta¨dt, shows a system capable of in- tegrating data from different databases, and its subsequent use in the integration and modeling of metabolic pathways using a rule-based system. Once the computational and basic annotations are in place, we can move from sequences to networks of gene regulation and cell differen- viii Preface tiation. The second part of the book begins with chapter 4, by Gary Stormo, who describes the foundations of weight matrices and their biophysical interpretation in protein-DNA interactions. In a way, this method and its variants are for regulatory motifs what the Smith- Waterman algorithm was for coding sequence comparisons. Defining the best matrix is based on the problem of defining the best multiple alignment,giventheconstraints ofno gaps, symmetry,andotherprop- erties describing most protein-DNA binding sites in upstream regions. Abigail McGuire and George Church, in chapter 6, show how the integration of gene regulation has to be supported by experimental studies oftranscriptomeanalysescombinedwithcomputationalmotifsearches. Chapter 5, by Julio Collado-Vides and colleagues, is devoted to computational studies of gene regulation in E. coli in which different pieces are put together, making it feasible to think of a global computational study of a complete network of transcription initiation in a cell. A pair of chapters illustrate the complexity of these issues when studying eukaryotes, as seen in the signal transduction modeling by Nikolay Kolchanov and colleagues (chapter 7), and by the Boolean network methodology and its plausible application to modeling the network of factors involved in the biology of asthma by Sui Huang (chapter 8). In chapter 9 Edward Marcotte presents a relatively novel approach using phylogenetic profiles to define a quantitative definition of function in genomics. This is a powerful method that does not require homology among genes to identify groups of genes involved in the same function. Metabolic flux analysis as well as the comparison of pathways in different genomes is illustrated in chapter 11, by Steffen Schmidt and Thomas Dandekar. The book ends with a chapter by Masaru Tomita that describes a more ambitious modeling that inte- grates metabolism, regulation, translation, and membrane transport. A comprehensive in silico complete cell model is still in its infancy, but Tomitapointstowhatliesahead.Stillmoreimportantisevaluatingthe predictive capability of all these computational modeling and simulation projects. This book does not attempt to provide a complete account of this expanding and exciting area of research. Many other databases, algorithms, and mathematical approaches are enriching postgenomic computational research. In 1995 and 1998 we participated in the organization of two Dagstuhl seminars centered on modeling and ix Preface