Synthetic Biology as a Proof of Systems Biology

Synthetic Biology as a Proof of Systems Biology

Andrew Kuznetsov (Freiburg University, Germany)
Copyright: © 2009 |Pages: 19
DOI: 10.4018/978-1-60566-076-9.ch005
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Biologists have used a reductionist approach to investigate the essence of life. In the last years, scientific disciplines have merged with the aim of studying life on a global scale in terms of molecules and their interactions. Based on high-throughput measurements, Systems Biology adopts mathematical modeling and computational simulation to reconstruct natural biological systems. Synthetic Biology seeks to engineer artificial biological systems starting from standard molecular compounds coding in DNA. Can Systems and Synthetic Biology be combined with the idea of creating a new science—‘SYS Biology’ that will not demarcate natural and artificial realities? What will this approach bring to medicine?
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“We live in a society exquisitely dependent on science and technology, in which hardly anyone knows anything about science and technology.”

- Carl Sagan



Sometimes, we are like the three blind Indian philosophers who tried to guess what kind of animal the elephant was by touching various parts of it. One blind man while touching the side of elephant announced the animal was like a wall. The second philosopher hugged its leg and declared that the animal was like a tree and the third blind man, while holding on to its tail said the animal was a snake. All three were correct, but all three had a distorted perspective of an elephant. This allegory captures a weakness of the analytical reductionist approach to biological science and illustrates a paradigm that the whole is greater than the sum of its parts. A system, holistic approach to Biology means the synthesis of knowledge from various sources and by different methods of data extraction. This approach starts with data collection and modeling to understand how components of the system interact, continues with experimentation and then returns to modeling to refine our understanding of interactions and to identify new questions to be addressed. This system of thinking emphasizes relationships rather than isolated entities.

The idea of a system-level understanding of Biology is not new. In 1943, Erwin Schrödinger published the book ‘What is Life’, a seminal work on scientific thought that examined the relationship between the laws of Physics and the mechanisms of life. In particular, it provoked the development of Molecular Biology and led to the research we know as Systems Biology. Norbert Wiener (1948) and Ludwig von Bertalanffy (1969) described a systems approach to living organisms i.e. the holistic view that ‘mysterious’ properties of life arise at the system level from dynamical interactions and diversity of system components. Breakthroughs in Molecular Biology during the last decades have enabled an analysis of dynamical interactions inside living cells and between them. Systems Biology appeared as a result of the Human Genome Project as well as from a growing understanding of how genes and their proteins give rise to biological forms and functions. Recent studies have involved high-throughput experiments in Genomics, Transcriptomics, Proteomics and Metabolomics. These ‘-omics’ should be fused together to reach an understanding of Biology at a top system-level (Kitano, 2002a). The new field has attracted biologists, engineers, mathematicians, physicists and chemists who are tackling complex biological problems. The Internet allows researchers to distribute massive amounts of data. In particular, the theory of dynamical systems, agent-based approach and systems engineering methods provide the opportunity to study the collective behavior of biological entities. The challenge is to connect genetic circuits with physiological behavior.

Following Systems Biology, the goal of Synthetic Biology is both to improve our quantitative understanding of natural phenomenon and to establish an engineering discipline to design artificial biological systems. It will strongly depend on what possibilities there will be in the multi-scale modeling of whole organisms. Biological models often have numerous unknown parameters such as kinetic constants, decay rates and drift terms. A big problem for Systems/Synthetic Biology (‘SYS Biology’ for short) is that these parameters are often very difficult to measure. However, Systems Biology researchers believe that methods of dynamic analysis, modeling and simulation can provide a deeper understanding of life (Kitano, 2002b). Synthetic Biology, with the goal of synthesizing life from scratch, gives us other modern hype-and-hope, namely the ‘understanding by building’. Regarding complex dynamical systems, Richard Feynman wrote: “What I cannot create I do not understand.” By creating artificial life, we are beginning to answer Schrödinger’s question: “What is Life?” This will give us new opportunities to distinguish the health and pathology for treating for example, schizophrenia, cancer and diabetes.

Key Terms in this Chapter

Systems Biology: The study of an organism, viewed as an interacting network of genes, proteins, and biochemical reactions which give rise to life. Instead of analyzing individual aspects of the organism, systems biologists focus on all the components and the interactions among them. Systems Biology is the discipline that specifically addresses the fundamental properties of biological complexity.

Orthogonal Life: A term stressing the complete isolation of artificial life-like creatures from natural processes by using the alternative genetic code and the reliable interface. Chen’s rules should be taken in an account: 1) nanomachines should only be specialized, not general purpose, 2) nanomachines should not be self-replicating, 3) nanomachines should not be made to use an abundant natural compound as fuel, 4) nanomachines should be tagged so they can be tracked.

Competent Cell: A cell that can accept foreign DNA.

Refactoring: Any modification of a computer program which improves its readability or simplifies its structure without changing its results.

Nanorobot (or nanobot): Can be defined as the artificially fabricated object able to freely move in a human body and interact with specific cells at the molecular level itself e.g. seeking out cancer cells and destroying them.

Synthetic Biology: An engineering discipline concerning synthesis of novel biological systems that are not found in nature. It has involved a paradigm enabling scientists to create ‘life from scratch’ that will help to understand principles of Biology. Synthetic Biology holds promise for programming bacteria to seek and destroy tumors. However, the complexity of Biology and emergent effects have provoked many technical and ethical challenges.

Agent: A computing system with a well defined interface capable of adaptive problem-solving actions without user intervention.

Emergence: Refers to new unexpected behaviors and patterns that arise out of a multiplicity of relatively simple interactions. An emergent behavior can appear when a number of simple entities (agents) operate in an environment while forming more complex behaviors as a community.

Amorphous Computing: The action of generating a coherent behavior from a group of unreliable agents such as living cells.

SYS Biology: A speculative merge of Systems Biology and Synthetic Biology that can be defined as an approach to the biological reality, where natural and artificial processes should be described in terms of their components and their interactions in a framework of mathematical models towards a reconstruction of biological systems.

Minimal (or core) Genome: The minimum set of genes necessary for a cell to propagate under specific environmental conditions.

Transgenensis: The introduction of foreign genes into a living organism that confers upon the organism a new property that will be transmitted to a progeny.

Complete Chapter List

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Editorial Advisory Board
Table of Contents
Ralf Herwig
Andriani Daskalaki
Andriani Daskalaki
Chapter 1
Peter Ghazal
An increasing number of biological experiments and more recently clinical based studies are being conducted using large-scale genomic, proteomic and... Sample PDF
Pathway Biology Approach to Medicine
Chapter 2
Peter Wellstead, Sree Sreenath, Kwang-Hyun Cho
In this chapter the authors describe systems and control theory concepts for systems biology and the corresponding implications for medicine. The... Sample PDF
Systems and Control Theory for Medical Systems Biology
Chapter 3
S. Nikolov
In this chapter we investigate how the inclusion of time delay alters the dynamic properties of (a) delayed protein cross talk model, (b) time delay... Sample PDF
Mathematical Description of Time Delays in Pathways Cross Talk
Chapter 4
Elisabeth Maschke-Dutz
In this chapter basic mathematical methods for the deterministic kinetic modeling of biochemical systems are described. Mathematical analysis... Sample PDF
Deterministic Modeling in Medicine
Chapter 5
Andrew Kuznetsov
Biologists have used a reductionist approach to investigate the essence of life. In the last years, scientific disciplines have merged with the aim... Sample PDF
Synthetic Biology as a Proof of Systems Biology
Chapter 6
Tuan D. Pham
Computational models have been playing a significant role for the computer-based analysis of biological and biomedical data. Given the recent... Sample PDF
Computational Models for the Analysis of Modern Biological Data
Chapter 7
Vanathi Gopalakrishnan
This chapter provides a perspective on 3 important collaborative areas in systems biology research. These areas represent biological problems of... Sample PDF
Computer Aided Knowledge Discovery in Biomedicine
Chapter 8
Thomas Meinel
The function of proteins is a main subject of research in systems biology. Inference of function is now, more than ever, required by the upcoming of... Sample PDF
Function and Homology of Proteins Similar in Sequence: Phylogenetic Profiling
Chapter 9
Nikolaos G. Sgourakis, Pantelis G. Bagos, Stavros J. Hamodrakas
GPCRs comprise a wide and diverse class of eukaryotic transmembrane proteins with well-established pharmacological significance. As a consequence of... Sample PDF
Computational Methods for the Prediction of GPCRs Coupling Selectivity
Chapter 10
Pantelis G. Bagos, Stavros J. Hamodrakas
ß-barrel outer membrane proteins constitute the second and less well-studied class of transmembrane proteins. They are present exclusively in the... Sample PDF
Bacterial ß-Barrel Outer Membrane Proteins: A Common Structural Theme Implicated in a Wide Variety of Functional Roles
Chapter 11
L.K. Flack
Clustering methods are used to place items in natural patterns or convenient groups. They can be used to place genes into clusters to have similar... Sample PDF
Clustering Methods for Gene-Expression Data
Chapter 12
George Sakellaropoulos, Antonis Daskalakis, George Nikiforidis, Christos Argyropoulos
The presentation and interpretation of microarray-based genome-wide gene expression profiles as complex biological entities are considered to be... Sample PDF
Uncovering Fine Structure in Gene Expression Profile by Maximum Entropy Modeling of cDNA Microarray Images and Kernel Density Methods
Chapter 13
Wasco Wruck
This chapter describes the application of the BeadArrayTM technology for gene expression profiling. It introduces the BeadArrayTM technology, shows... Sample PDF
Gene Expression Profiling with the BeadArrayTM Platform
Chapter 14
Djork-Arné Clevert, Axel Rasche
Readers shall find a quick introduction with recommendations into the preprocessing of Affymetrix GeneChip® microarrays. In the rapidly growing... Sample PDF
The Affymetrix GeneChip® Microarray Platform
Chapter 15
Jacek Majewski
Eukaryotic genes have the ability to produce several distinct products from a single genomic locus. Recent developments in microarray technology... Sample PDF
Alternative Isoform Detection Using Exon Arrays
Chapter 16
Prerak Desai
The use of systems biology to study complex biological questions is gaining ground due to the ever-increasing amount of genetic tools and genome... Sample PDF
Gene Expression in Microbial Systems for Growth and Metabolism
Chapter 17
Heike Stier
Alternative splicing is an important part of the regular process of gene expression. It controls time and tissue dependent expression of specific... Sample PDF
Alternative Splicing and Disease
Chapter 18
Axel Kowald
Aging is a complex biological phenomenon that practically affects all multicellular eukaryotes. It is manifested by an ever increasing mortality... Sample PDF
Mathematical Modeling of the Aging Process
Chapter 19
Evgenia Makrantonaki
This chapter introduces an in vitro model as a means of studying human hormonal aging. For this purpose, human sebaceous gland cells were maintained... Sample PDF
The Sebaceous Gland: A Model of Hormonal Aging
Chapter 20
R. Seigneuric, N.A.W. van Riel, M.H.W. Starmans, A. van Erk
Complex diseases such as cancer have multiple origins and are therefore difficult to understand and cure. Highly parallel technologies such as DNA... Sample PDF
Systems Biology Applied to Cancer Research
Chapter 21
Matej Orešic, Antonio Vidal-Puig
In this chapter the authors report on their experience with the analysis and modeling of data obtained from studies of animal models related to... Sample PDF
Systems Biology Strategies in Studies of Energy Homeostasis In Vivo
Chapter 22
Axel Rasche
We acquired new computational and experimental prospects to seek insight and cure for millions of afflicted persons with an ancient malady. Type 2... Sample PDF
Approaching Type 2 Diabetes Mellitus by Systems Biology
Chapter 23
Alia Benkahla, Lamia Guizani-Tabbane, Ines Abdeljaoued-Tej, Slimane Ben Miled, Koussay Dellagi
This chapter reports a variety of molecular biology informatics and mathematical methods that model the cell response to pathogens. The authors... Sample PDF
Systems Biology and Infectious Diseases
Chapter 24
Daniela Albrecht, Reinhard Guthke
This chapter describes a holistic approach to understand the molecular biology and infection process of human-pathogenic fungi. It comprises the... Sample PDF
Systems Biology of Human-Pathogenic Fungi
Chapter 25
Jessica Ahmed
Secretases are aspartic proteases, which specifically trim important, medically relevant targets such as the amyloid-precursor protein (APP) or the... Sample PDF
Development of Specific Gamma Secretase Inhibitors
Chapter 26
Paul Wrede
Peptides fulfill many tasks in controlling and regulating cellular functions and are key molecules in systems biology. There is a great demand in... Sample PDF
In Machina Systems for the Rational De Novo Peptide Design
Chapter 27
Ferda Mavituna, Raul Munoz-Hernandez, Ana Katerine de Carvalho Lima Lobato
This chapter summarizes the fundamentals of metabolic flux balancing as a computational tool of metabolic engineering and systems biology. It also... Sample PDF
Applications of Metabolic Flux Balancing in Medicine
Chapter 28
Roberta Alfieri, Luciano Milanesi
This chapter aims to describe data integration and data mining techniques in the context of systems biology studies. It argues that the different... Sample PDF
Multi-Level Data Integration and Data Mining in Systems Biology
Chapter 29
Hendrik Hache
In this chapter, different methods and applications for reverse engineering of gene regulatory networks that have been developed in recent years are... Sample PDF
Methods for Reverse Engineering of Gene Regulatory Networks
Chapter 30
Alok Mishra
This chapter introduces the techniques that have been used to identify the genetic regulatory modules by integrating data from various sources. Data... Sample PDF
Data Integration for Regulatory Gene Module Discovery
Chapter 31
Elizabeth Santiago-Cortés
Biological systems are composed of multiple interacting elements; in particular, genetic regulatory networks are formed by genes and their... Sample PDF
Discrete Networks as a Suitable Approach for the Analysis of Genetic Regulation
Chapter 32
A. Maffezzoli
In this chapter, authors review main methods, approaches, and models for the analysis of neuronal network data. In particular, the analysis concerns... Sample PDF
Investigating the Collective Behavior of Neural Networks: A Review of Signal Processing Approaches
Chapter 33
Paolo Vicini
This chapter describes the System for Population Kinetics (SPK), a novel Web service for performing population kinetic analysis. Population kinetic... Sample PDF
The System for Population Kinetics: Open Source Software for Population Analysis
Chapter 34
Julia Adolphs
This chapter introduces the theory of optical spectra and excitation energy transfer of light harvesting complexes in photosynthesis. The light... Sample PDF
Photosynthesis: How Proteins Control Excitation Energy Transfer
Chapter 35
Michael R. Hamblin
Photodynamic therapy (PDT) is a rapidly advancing treatment for multiple diseases. PDT involves the administration of a nontoxic drug or dye known... Sample PDF
Photodynamic Therapy: A Systems Biology Approach
Chapter 36
Andriani Daskalaki
Photodynamic Therapy (PDT) involves administration of a photosensitizer (PS) either systemically or locally, followed by illumination of the lesion... Sample PDF
Modeling of Porphyrin Metabolism with PyBioS
Chapter 37
Alexey R. Brazhe, Nadezda A. Brazhe, Alexey N. Pavlov, Georgy V. Maksimov
This chapter describes the application of interference microscopy and double-wavelet analysis to noninvasive study of cell structure and function.... Sample PDF
Interference Microscopy for Cellular Studies
Chapter 38
Cathrin Dressler, Olaf Minet, Urszula Zabarylo, Jürgen Beuthan
This chapter deals with the mitochondrias’ stress response to heat, which is the central agent of thermotherapy. Thermotherapies function by... Sample PDF
Fluorescence Imaging of Mitochondrial Long-Term Depolarization in Cancer Cells Exposed to Heat-Stress
Chapter 39
Athina Theodosiou, Charalampos Moschopoulos, Marc Baumann, Sophia Kossida
In previous years, scientists have begun understanding the significance of proteins and protein interactions. The direct connection of those with... Sample PDF
Protein Interactions and Diseases
Chapter 40
Bernard de Bono
From a genetic perspective, disease can be interpreted in terms of a variation in molecular sequence or expression (dose) that impairs normal... Sample PDF
The Breadth and Depth of BioMedical Molecular Networks: The Reactome Perspective
Chapter 41
Jorge Numata
Thermodynamics is one of the best established notions in science. Some recent work in biomolecular modeling has sacrificed its rigor in favor of... Sample PDF
Entropy and Thermodynamics in Biomolecular Simulation
Chapter 42
Isabel Reinecke, Peter Deuflhard
In this chapter some model development concepts can be used for the mathematical modeling in physiology as well as a graph theoretical approach for... Sample PDF
Model Development and Decomposition in Physiology
Chapter 43
Mohamed Derouich
Throughout the world, seasonal outbreaks of influenza affect millions of people, killing about 500,000 individuals every year. Human influenza... Sample PDF
A Pandemic Avian Influenza Mathematical Model
Chapter 44
Mohamed Derouich
Dengue fever is a re-emergent disease affecting more than 100 countries. Its incidence rate has increased fourfold since 1970 with nearly half the... Sample PDF
Dengue Fever: A Mathematical Model with Immunization Program
Chapter 45
Ross Foley
The field of histopathology has encountered a key transition point with the progressive move towards use of digital slides and automated image... Sample PDF
Automated Image Analysis Approaches in Histopathology
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