Systems Biology and Livestock Science E-Book

• Herausgeber: John Wiley & Sons
• Kategorie: Wissenschaft und neue Technologien
• Sprache: Englisch

Seitenzahl: 697

Veröffentlichungsjahr: 2011

Beschreibung

Systems Biology is an interdisciplinary approach to the study of life made possible through the explosion of molecular data made available through the genome revolution and the simultaneous development of computational technologies that allow us to interpret these large data sets. Systems Biology has changed the way biological science views and studies life and has been implemented in research efforts across the biological sciences. Systems Biology and Livestock Science will be the first book to review the latest advances using this research methodology in efforts to improve the efficiency, health, and quality of livestock production. Systems Biology and Livestock Science opens with useful introductory chapters explaining key systems biology principles. The chapters then progress to look at specific advances in fields across livestock science. Coverage includes, but is not limited to, chapters on systems biology approaches to animal nutrition, reproduction, health and disease, and animal physiology. Written by leading researchers in the field, Systems Biology and Livestock Science, will be an invaluable resource to researchers, professionals, and advance students working in this rapidly developing discipline.

Leseprobe

Contents

Cover

Title Page

Copyright

List of Contributors

Preface

From livestock production to biological science: from systems biology to livestock production

Chapter 1: Introduction to Systems Biology for Animal Scientists

Why Should Animal Scientists Be Interested in Learning About Systems Biology?

What Is Systems Biology?

A Systems Biology Paradigm: The Progress in Analysis of the Mammalian Immune Response Network

What Parts of Systems Biology Are in Use in Animal Science Today?

Further Reading

Partial Listing of Online Resources for Systems Biology

Web sites

Acknowledgments

Chapter 2: Modeling Approaches in Systems Biology, Including Silicon Cell Models

What Is Systems Biology

Various Systems Biological Models

Three Strategies to Build a Model: Top-Down, Middle-Out, and Bottom-Up

Perspectives of Silicon Cell Models: Advantages and Concerns

Use of Systems Biological Models, Including Silicon Cell Models

Acknowledgments

Chapter 3: The IUPS Physiome Project: A Worldwide Systems Biology Initiative

Introduction

Fundamental Principles of the Physiome Project

The Framework and Strategies of the Physiome Project

The Current Status of Physiome Modeling

Conclusions and Future Directions

Acknowledgments

Chapter 4: Systems Biology in Livestock Health and Disease

Introduction

Defining Systems Biology in the Medical Context

Establishing the Need for Systems Biology Approaches in Human and Veterinary Medicine

Systems Biology and Personalized Healthcare in Human Medicine

Areas of Application of Systems Biology to Human Medicine

Barriers to Implementing Personalized Medicine in Human Medical Practice

Systems Biology Techniques

Novel Technologies

Personalized Medicine Versus Livestock Population Health

Molecular Diagnostics

Using Systems Biology to Understand Host–Pathogen Interactions

Molecular Epidemiology

Example of Systems Biology Applications in Livestock Health: Mastitis in Dairy Cattle

Conclusion: Challenges of Applying Systems Biology Concepts and Techniques to Livestock Health Management

Chapter 5: Systems Biology of Host–Food–Microbe Interactions in the Mammalian Gut

The Gastrointestinal Tract and Body Homeostasis

The Need for Systems Approaches to Study Diet–Host–Microbiota Interactions

The Gastrointestinal (GI) Tract

Energy Homeostasis

Signaling and Hormone Homeostasis

Homeostasis of Tolerance and Immunity

Nutritional Challenges

The Intestinal Microbiota

Integrated Modeling Approaches

Challenges Ahead

Conclusions

Chapter 6: From Visual Biological Models Toward Mathematical Models of the Biology of Complex Traits

Introduction

Generation of a Biological Model

Association Studies Relating the Expression Levels of Genes or Proteins to Quantitative Traits

Bioinformatics Toward Systems Biology: Biological Models Toward Mathematical Models

Future Expectations

Acknowledgments

Chapter 7: Molecular Networks as Sensors and Drivers of Uterine Receptivity in Livestock

Introduction

Transcriptome Analysis as a Holistic Approach for the Study of Cellular Changes at the Molecular Level

Resources for Functional Gene Annotation and Gene/Protein Interactions and Corresponding Analysis Tools

Identification of Biological Themes Related to Endometrial Remodeling and Receptivity in a Microarray Study of Bovine Endometrium During the Estrous Cycle

Correlation of Gene Expression Data and Data from Genome-Wide Association Studies (GWAS) Links Differential Gene Expression with Phenotypes Related to Fertility

Identification of Genes Involved in Preparation of the Bovine Endometrium for Embryo Implantation

Analysis of Gene Expression in Endometrium During the Preimplantation Phase in Porcine Endometrium

Analysis of Gene Expression in Endometrium During the Preimplantation Phase in Equine Endometrium

Comparison of Gene Expression Datasets from Different Mammalian Species

Identification of Fertility-Related Genes by the Analysis of Pathological Conditions

Strategies and Approaches to Obtain Deeper Insights into and Better Understanding of the Processes Related to Establishment and Maintenance of Pregnancy

Chapter 8: Modeling Approaches to Link Various Levels of Organization in Animal Physiology

Introduction

Levels of Organization

Modeling Approaches

Some Examples of Physiological Aspects

Implications and Perspectives

Acknowledgments

Chapter 9: Systems Biology and Animal Nutrition: Insights from the Dairy Cow During Growth and the Lactation Cycle

Introduction

The Peripartal Dairy Cow as a Model for Whole-Animal Systems Biology

The Mammary Gland as a Unique System

Intertissue Cross Talk During Prepubertal Bovine Mammary Development

Effect of Prepartal Nutrient and Energy Intake on Dairy Cow Adipose Tissue

Effect of Prepartal Nutrient and Energy Intake on Dairy Cow Liver

Dietary Lipid Supplementation, Ruminal Metabolism, and the Mammary Gland Transcriptome

Perspectives

Acknowledgments

Chapter 10: Host–Pathogen Interactions

Introduction

Data Explosion and the Rationale for Systems Biology Approaches

Infection Biology

Complexity and Scales

Mathematical Models

Interaction Models

Conclusions

Chapter 11: Systems Biology in Livestock Science and Commercial Livestock Business

Introduction

Expectations from Systems Biology for Livestock Science and Industrial Innovations

Conclusions

Color plates

Index

All chapter abstracts are available on Wiley Online Library. Please visit Wiley Online Library at http://onlinelibrary.wiley.com/.

This edition first published 2011 © 2011 by John Wiley & Sons, Ltd.

Wiley-Blackwell is an imprint of John Wiley & Sons, formed by the merger of Wiley's global Scientific, Technical and Medical business with Blackwell Publishing.

Registered office: John Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK

Editorial offices: 2121 State Avenue, Ames, Iowa 50014-8300, USA The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, UK 9600 Garsington Road, Oxford, OX4 2DQ, UK

For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com/wiley-blackwell.

Authorization to photocopy items for internal or personal use, or the internal or personal use of specific clients, is granted by Blackwell Publishing, provided that the base fee is paid directly to the Copyright Clearance Center, 222 Rosewood Drive, Danvers, MA 01923. For those organizations that have been granted a photocopy license by CCC, a separate system of payments has been arranged. The fee codes for users of the Transactional Reporting Service are ISBN-13: 978-0-8138-1174-1/2011.

Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and product names used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners. The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provide accurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that the publisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, the services of a competent professional should be sought.

Library of Congress Cataloging-in-Publication Data

Systems biology and livestock science / edited by Marinus F.W. te Pas, André Bannink, Henri Woelders. p. cm. Includes bibliographical references and index. ISBN-13: 978-0-8138-1174-1 (hardcover : alk. paper) ISBN-10: 0-8138-1174-0 1. Veterinary physiology–Computer simulation. 2. Livestock. 3. Livestock–Genetics–Computer simulation. I. Pas, M. F. W. te. II. Bannink, André. III. Woelders, Henri. SF768.S97 2011 636.089′2–dc23 2011020692

A catalogue record for this book is available from the British Library.

This book is published in the following electronic formats: ePDF [9780470962930]; Wiley Online Library [9780470963012]; ePub [9780470962961]; Mobi [9780470962992]

Disclaimer

The publisher and the author make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation warranties of fitness for a particular purpose. No warranty may be created or extended by sales or promotional materials. The advice and strategies contained herein may not be suitable for every situation. This work is sold with the understanding that the publisher is not engaged in rendering legal, accounting, or other professional services. If professional assistance is required, the services of a competent professional person should be sought. Neither the publisher nor the author shall be liable for damages arising herefrom. The fact that an organization or Website is referred to in this work as a citation and/or a potential source of further information does not mean that the author or the publisher endorses the information the organization or Website may provide or recommendations it may make. Further, readers should be aware that Internet Websites listed in this work may have changed or disappeared between when this work was written and when it is read.

List of Contributors

André Bannink Centre of Animal Nutrition Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Stefan Bauersachs Laboratory for Functional Genome Analysis (LAFUGA) and Chair for Molecular Animal Breeding and Biotechnology Gene Center of the Ludwig-Maximilians Universität München Feodor Lynen Street 25 81377 Munich, Germany

Massimo Bionaz Mammalian NutriPhysioGenomics Department of Animal Sciences and Division of Nutritional Sciences University of Illinois Urbana, IL 61801, USA

Fred C. Boogerd Molecular Cell Physiology VU University Amsterdam de Boelelaan 1085 1081 HV, Amsterdam, The Netherlands

Frank J. Bruggeman Regulatory Networks Group Netherlands Institute of Systems Biology Amsterdam, The Netherlands Life Sciences Centre for Mathematics and Computer Science (CWI) Science Park 123 1098 XG, Amsterdam, The Netherlands

Leo K. Cheng Auckland Bioengineering Institute The University of Auckland Private Bag 92019 Auckland 1142 New Zealand

Willem M. de Vos Laboratory of Microbiology Human and Animal Physiology Wageningen University Dreijenplein 10 6710 HB Wageningen, The Netherlands Department of Veterinary Biosciences University of Helsinki PO Box 66 00014 University of Helsinki, Finland

Jan Dijkstra Animal Nutrition Group Wageningen University PO Box 338 6700 AH Wageningen, The Netherlands

Peng Du Auckland Bioengineering Institute The University of Auckland Private Bag 92019 Auckland 1142 New Zealand

James France Centre for Nutrition Modelling Department of Animal and Poultry Science University of Guelph Guelph, ON, N1G 2W1, Canada

Arend J.W. Hoekman Animal Breeding and Genomics Centre Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Vasant G. Honavar Center for Integrated Animal Genomics Iowa State University Ames, IA 50011, USA Bioinformatics and Computational Biology Program Iowa State University Ames, IA 50011, USA Department of Computer Science Iowa State University Ames, IA 50011, USA Artificial Intelligence Research Laboratory Iowa State University Ames, IA 50011, USA Center for Computational Intelligence, Learning, and Discovery Iowa State University Ames, IA 50011, USA

Guido Hooiveld Nutrition Metabolism and Genomics Group University of Wageningen Wageningen, The Netherlands

Ina Hulsegge Animal Breeding and Genomics Centre Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Guido Invernizzi Mammalian NutriPhysioGenomics Department of Animal Sciences and Division of Nutritional Sciences University of Illinois Urbana, IL 61801, USA

Jaap Keijer Department of Human and Animal Physiology Wageningen University Wageningen, The Netherlands RIKILT-Institute of Food Safety Wageningen, The Netherlands

Gordon M. Kirby Department of Biomedical Sciences Ontario Veterinary College Guelph, Ontario, N1G 2W1, Canada

Alexey N. Kolodkin Molecular Cell Physiology VU University Amsterdam de Boelelaan 1085 1081 HV, Amsterdam, The Netherlands

Juan J. Loor Mammalian NutriPhysioGenomics Department of Animal Sciences and Division of Nutritional Sciences University of Illinois Urbana, IL 61801, USA

Vitor A.P. Martins dos Santos Laboratory of Systems and Synthetic Biology University of Wageningen Wageningen, The Netherlands

Michael Müller Nutrition Metabolism and Genomics Group University of Wageningen Wageningen, The Netherlands

Gregory O’Grady Department of Surgery and Auckland Bioengineering Institute The University of Auckland Private Bag 92019 Auckland 1142 New Zealand

Dirkjan Schokker Wageningen UR Livestock Research Animal Breeding and Genomics Centre PO Box 65 8200 AB Lelystad, The Netherlands

Mari A. Smits Animal Breeding and Genomics Centre Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Marinus F.W. te Pas Animal Breeding and Genomics Centre Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Fadi Towfic Bioinformatics and Computational Biology Program Iowa State University Ames, IA 50011, USA Department of Computer Science Iowa State University Ames, IA 50011, USA Artificial Intelligence Research Laboratory Iowa State University Ames, IA 50011, USA Center for Computational Intelligence, Learning, and Discovery Iowa State University Ames, IA 50011, USA

Christopher K. Tuggle Center for Integrated Animal Genomics Iowa State University Ames, IA 50011, USA Department of Animal Science Iowa State University Ames, IA 50011, USA Bioinformatics and Computational Biology Program Iowa State University Ames, IA 50011, USA Center for Computational Intelligence, Learning, and Discovery Iowa State University Ames, IA 50011, USA

Peter van Baarlen Department of Host-Microbe Interactomics University of Wageningen 6700 AH, Wageningen, The Netherlands

Jerry Wells Department of Host-Microbe Interactomics University of Wageningen 6700 AH, Wageningen, The Netherlands

Hans V. Westerhoff Molecular Cell Physiology VU University Amsterdam de Boelelaan 1085 1081 HV, Amsterdam, The Netherlands Manchester Centre for Integrative Systems Biology Manchester Interdisciplinary Biocentre University of Manchester 131 Princess Street Manchester, M1 7DN, UK

Henri Woelders Animal Breeding and Genomics Centre Wageningen UR Livestock Research PO Box 65 8200 AB Lelystad, The Netherlands

Eckhard Wolf Laboratory for Functional Genome Analysis (LAFUGA) and Chair for Molecular Animal Breeding and Biotechnology Gene Center of the Ludwig-Maximilians Universität München Feodor Lynen Street 25 81377 Munich, Germany

Preface

From livestock production to biological science: from systems biology to livestock production

Biological processes underlie livestock production, many of them only broadly investigated or even unknown. Understanding regulation of livestock production capacity and related traits requires an understanding of life itself. It has been a long waited goal of the biological science to understand life in all its complexity. However, it is also recognized for long that life is too complex for the research with the aim to get an understanding of life to be performed in situ. For this reason, biology has broken up research into increasingly smaller parts and specializations. Each organ, tissue, and cell-type was investigated separately, from the morphology of the entire organ down to the molecular level in specific cell types. Simply, the summing up of all these scientific efforts still does not explain life in all its facets and organizational complexity. In fact, the complete system is more than the sum of its parts. Insight into the numerous interactions between molecules, within and between cells, within and between tissues, within and between organs, within and between organisms, and perhaps also levels of interactions not yet discovered, has to merge with research on the smaller parts to approximate life. It should be taken into account that the isolated study of the different parts may even have resulted in erroneous conclusions due to omission of signals related to these interactions.

The genomics revolution provided the sequence of whole genomes. The analyses of the sequence led to the discovery of (almost) all genes, although the function of most genes is still not understood, or partly understood at best. Fortunately, the genomics revolution supplied biology with amazing new tools enabling the investigation of the expression levels of all genes, proteins, and metabolites in a cell, tissue, or organ at the same time. Thus, interactions between genes and their environment were taken into account for the expression levels. These techniques allowed defining and describing the cellular components in large detail and completeness, but again life was more complex than the summing up of all “omics” data.

Parallel to the genomics revolution, a computer technology revolution enabled the analysis of increasingly large datasets. This enables integration of the datasets resulting from all different levels of research. Such an analysis can produce a more complete description of life that includes the knowledge obtained at separate levels of biological organization and the interactions within and between these diverse levels. This picture is still far too complex to understand at this moment. Therefore, to help understand life and to make testable predictions of complex parts of life, quantitative modeling approaches are necessary. While mathematical equations are based upon the results of investigations, their combination in more complex models can predict new complex patterns of life, and interactions between various elements of life, that were outside the scope of previous research. By doing so, they make these areas accessible to research thereby verifying and extending the possibilities for a mathematical representation of life.

These developments together initiated this whole new phase in biology together called “systems biology.” Systems biology provides the opportunity to obtain a wider and deeper understanding of life because of the incorporation of the knowledge at all separate levels of investigation, including the mathematical representation of the complex interactions between these levels. In this way, the accuracy and completeness of that understanding may be advanced further in an iterative process, as the modeling produces testable predictions, which can be tested empirically, followed by refinement of the modeling, leading to closer understanding of the organization of life.

As said, biological processes underlie livestock production, most of them only broadly investigated and mostly from a practical viewpoint. Research has already shown that most quantitative (production) traits depend on both the genotype and on interactions of the genotype with the environment. The genetic background for a number of traits has been partly uncovered. There are interactions between the genetic background and food (components), animal handling (stress), or temperature and housing that (partly) have been quantified. Also, complex interactions between traits have been shown and a main goal in livestock production science is to improve wanted traits without compromising the basic animal needs and requirements, without deterioration of essential physiological traits negatively affecting other important traits (e.g., fertility), and without inducing problems such as leg weakness, stress, and other (acute as well as long-term) health and welfare problems. Such an aim requires full understanding of the essence of life, including the physiological processes of traits and the interactions at various levels of organization of this physiology. Mathematical modeling of the known processes and of the known interactions between them will increase our understanding of the regulation and mutual dependence of both production (efficiency, product quality) and other traits (robustness, fertility, health well-being) of livestock animals. The testable predictions of the mathematical models enable real progress toward better foods for healthier consumers in a healthy animal with a high well-being, and with less impact on the environment. Systems biology has the potential to make a large contribution to the long-range goals of livestock production science.

At the moment, systems biology is still in its infancy in livestock science research in particular. However, it has high potential in stimulating new directions of research and development of new concepts and new ways of thinking about familiar problems. This book describes several aspects of system biology and gives research examples from other biological disciplines, including simple model organisms and human medicine. The authors draw lines from their own research toward livestock science. We, the editors, hope and expect that this book will introduce systems biology to a wide audience involved with livestock science. We thank especially the publisher, Wiley-Blackwell, and the Executive Editor Mr. Justin Jeffryes, who initiated and stimulated the work on this book. We also thank all contributors to this book. The editors acknowledge the financial contribution of the Ministry of Agriculture and Nature Management through the IP/OP grant KB-04-004-049. We also thank the head of our department Dr. Ir. Roel F. Veerkamp for enabling and stimulating the work on this book.

The EditorsDr. Marinus F.W. te PasDr. Henri WoeldersDr. André Bannink

Chapter 1

Introduction to Systems Biology for Animal Scientists

Christopher K. Tuggle, Fadi Towfic, and Vasant G. Honavar

Why Should Animal Scientists Be Interested in Learning About Systems Biology?

This section describes three arguments to justify why animal scientists should explore the field of Systems Biology.

The Goals of Systems Biology Are Directly Aligned with Those of Animal Science

Systems Biology aims to produce information to make biology predictive, and (at least as a final outcome) to do so at the organism level. Such prediction at the animal level would be very useful for practical goals in animal agriculture such as improving phenotypic traits, especially those with low heritability, that are otherwise recalcitrant to such improvement and for which genomic approaches have been highlighted (Green et al., 2007; Sellner et al., 2007). These include traits that are difficult or expensive to measure such as female reproduction, efficiency of feed utilization, and resistance to disease. However, such predictive power would be extremely useful in studies in animal nutrition, physiology, immunology, and reproductive biology, where the goal is to understand the effect of altered feeds and feeding regimens, feed additives, hormones or other drugs, as well as effects of changes in management, on the whole animal. Of course, more intermediate goals of Systems Biology, such as a deeper understanding of specific important pathways and pathway interactions in relevant cells, tissues and organ systems, will more immediately show the value of the Systems Biology approach in the livestock field as well as in biomedicine.

Translation of Systems Biology Understanding of Human and Model Vertebrates to livestock Species Will Be Highly Instructive

Significant funding is being devoted toward developing the required substantial data and analytical resources for Systems Biology studies of several species, including humans, mice, zebrafish, and a number of invertebrates and microorganisms. Much of these data, and the models and hypotheses generated, will be applicable to modeling the biology of livestock species of interest to animal scientists, especially for data collected on the vertebrate species where the majority of this effort is focused. While the methods necessary to globally compare biological networks need to be developed and refined continually in order to best perform such comparisons, animal scientists have used comparative biology for many years to take advantage of biological data and insights from the biomedical and fundamental biology fields. As discussed in the next section, comparative efforts and value can also work in the reverse, improving the modeling of human and model species biology as well.

Systems Biology Will Best Utilize New Genome Information for All Species

The first two points taken together point to the promise of Systems Biology for making optimal use of the new genomic information from species of interest to address specific questions in animal science. According to some authors, biology has seen a paradigm shift in the past 10–15 years, since the initial fruits of the Human Genome Project (HGP) began to be harvested (Schena et al., 1995; Lander et al., 2001; IHGSC, 2004). The age in which biological molecules are studied using a reductionist approach—in isolation—is fast drawing to a close. This is especially true in very well-funded areas of biology such as human medicine. Funding agencies, journals, and public stakeholders are increasingly interested in how molecular studies and their conclusions are integrated within larger systems, e.g., organs, organisms, species, and ecosystems. This shift is partly due to the expectation that research, even research whose goal is to describe fundamental biological processes, must have a realizable and practical benefit. A “selling point” in the 1980s put forth to encourage funding of the HGP was that a global understanding of the human and model organism genomes would result in practical benefits as yet unknown. However, the shift was greatly accelerated by the very success of the HGP in creating methods for global measurements of the “parts list” of the genome, the variation of parts structure (the genes), and the interactions between these parts. Happily, the animal science community has always had an integrative and practical view of research, developing new knowledge with a focus on applying such information as quickly as possible. Now that most species of interest to animal scientists have substantial genome tools, the concurrent and future development of bioinformatics tools to explore, interpret and integrate molecular-level data across interaction networks, tissues, and organs to predict biological states (read: phenotypes) will be highly beneficial to livestock interests. Conversely, the development of a predictive biology across multiple vertebrate species, including the livestock species, will deepen the understanding of the human species as well. The value of comparative models for human biology will be greatly increased if multilevel, detailed modeling of the same processes can be manipulated, and if perturbation effects can be iteratively predicted, tested, and new predictions be made and retested. Many such perturbations cannot be ethically performed in humans, but may be justified in animals. Thus, improvement in the systems-level modeling of several livestock species, already validated as excellent models for human physiology such as the pig (Dehoux and Gianello, 2007; Lunney, 2007) and sheep (Scheerlinck et al., 2008), will improve biomedical understanding as well.