Systems Biology Left and Right

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Systems Biology Left and Right Hans V. Westerhoff Contents 1. A Fundamental Definition of Systems Biology 2. The Importance of the Integration of In Vivo and In Vitro Analyses 3. Alternative Definitions of Systems Biology 4. Different Types of Systems Biology Acknowledgments References

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Abstract Systems biology has come of age. In most scientifically active countries, significant research programs are funded. Various scientific journals, standards, repositories, and Web sites are devoted to the topic. Systems biology has spun off new subdisciplines such as synthetic biology and systems medicine. There are training courses at the M.Sc. and Ph.D. level at various Universities. And various industries are engaging systems biology in their R&D. Systems biology has also developed numerous new methodologies. This chapter attempts to organize these methodologies from the perspectives of the unique aims of systems biology, and by comparing with one of its parents, molecular biology.

1. A Fundamental Definition of Systems Biology Definitions of systems biology abound. This may explain why some see systems biology as vague, others see it as nothing new, while yet others see it as hype. Some vehemently disagree with any definition that has been published, or refuse to take note of the literature that has been explicit on defining it (Alberghina and Westerhoff, 2005; Boogerd et al., 2007; Klipp et al., 2005). The discipline of molecular biology has passed through a similar history, now, many years ago. First, tenets of molecular biology were deemed unimportant, then they were accepted to be potentially Manchester Centre for Integrative Systems Biology, The University of Manchester, Manchester, United Kingdom Netherlands Institute for Systems Biology, VU University Amsterdam, Amsterdam, The Netherlands Methods in Enzymology, Volume 500 ISSN 0076-6879, DOI: 10.1016/B978-0-12-385118-5.00001-3

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2011 Elsevier Inc. All rights reserved.

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important but wrong, and then they were understood to be right but judged to be nothing new. Ultimately, molecular biology changed the way both biology and medicine were practiced. It was a paradigm shift. And it did bring a scientific revolution (Kuhn, 1962), more recently leading to functional genomics. Systems biology is another such new discipline (Westerhoff et al., 2009). It is useful to demarcate what it is, because that will explain why much of what is present in this book on methods in systems biology is similar to what could be done in any of the other sciences and yet is different because of a different perspective. Systems biology is not just an item on the list of biomedical disciplines (Fig. 1.1). It is much more the in-between. Where molecular biology deals with the structure of macromolecules, and biochemistry with the chemical conversions in biology, systems biology attempts to understand how in the interactions between components new properties arise that give the pathways their functional properties (Kolodkin et al., 2010; Westerhoff et al., 1984). While cell biology looks at the compartments in living cells and describes how these function and how molecules are moving within and between them, systems biology attempts to understand how the functions of Object of study

Systems biology type

Science

Ecology

Eco system SB Organism SB T o p

Tissue SB SB Cell SB Compartment SB

d o w n

B o t t o m u p

M i d d l e

Biology Physiology Cell physiology

O u t

Cell biology Biochemistry

Pathway SB Macromolecule

Molecular biology

Figure 1.1 The position of systems biology and its different forms relative to its topics of interest and the underpinning other sciences. Systems biology is the in-between: it examines how nonlinear interactions between components lead to functional properties of a system that are not present in the components themselves. It does this either downward, from system to components, or upward, that is, from components to system.

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compartments come about in the nonlinear interactions between their pathways and their macromolecules (Bakker et al., 2000; Haanstra et al., 2008; Westerhoff et al., 1981). And where biology looks at the functioning of an organism such as a rabbit, systems biology tries to understand how much of that function comes about in the interactions between its organs/tissues. In short, systems biology focuses on the emergence of biological function from interactions. Since systems biology is a science, it aims at understanding, not only in descriptive but also in mechanistic terms (Alberghina and Westerhoff, 2005). For interactions to lead to properties that are not yet present in the components themselves, they need to be nonlinear, in any out of a number of ways. The nonlinearity can reside in nonlinear kinetic equations such as those that give rise to oscillations (Reijenga et al., 2005; Tyson et al., 2001), in vectorial reactions such as the ones that lead to ion pumping (Mitchell, 1961; Westerhoff and Van Dam, 1987), in catalytic hierarchies giving rise to amplification in regulation (Bruggeman et al., 2005; Hellingwerf et al., 1995; Kholodenko, 2006; Koshland et al., 1982; Rhee et al., 1989), in network motifs such as the ones that give rise to robust detection (Alon, 2007), and in differences in concentrations of conserved moieties giving rise to temporal organization (Hardin et al., 2009; Hofmeyr et al., 1986). As a consequence, systems biology depends on the understanding of nonlinear interactions. This has three implications: First, systems biology cannot reduce its objects of study to simplicity: at least part of their complexity is essential. Indeed, systems biology may aim at making its analyses as simple as possible, but not simpler (Einstein, 1934; Westerhoff et al., 2009). Second, systems biology requires mathematics of some sort in order to be able to deal with the necessary complexity. And third, systems biology requires “detail” and hence accurate experimentation in vivo, or under in vivo conditions (ex vivo).

2. The Importance of the Integration of In Vivo and In Vitro Analyses The reason for the requirement of in vivo conditions is the phenomenon that the nonlinearity is diverse. First, if one is interested in how a function f depends on a molecular property x, then that function may be nonlinear in x itself, such as in f ðxÞ ¼ ax þ bx2 This implies that the dependence of the function on the molecular property x (which may be quantified as df/dx) depends on the magnitude of x, that is,

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df ¼ a þ 2bx dx Therefore, one needs to determine the value of the molecular property (x) experimentally before one analyzes the functional role x plays in the system. The function may also depend on other molecules, such as y. And therefore one also has to determine the concentration of y to be able to understand the function of y. The situation is more complex, however, for the function of x is likely to depend on the magnitude of the molecule y, that is, f ðxÞ ¼ ax þ bx2 þ gy þ dy2 þ exy so that df ¼ a þ 2bx þ ey dx Consequently, in any assay that aims to determine the dependence of function on a particular molecule, one needs to have all other molecules that affect this dependence present at their actual concentrations. It may seem that this pleads for doing all further experiments exclusively in vivo. Here, there is an issue with validation, however, of the understanding that would be achieved. Suppose one measures in vivo the parameters a, b, e, the actual magnitudes of x and y, as well as df/dx, and that the above equation is found to hold. This would suggest that the system is understood. Yet, it would be possible (and in view of biological complexity, likely) that there is a hidden dependence on yet another molecule, z, for instance, such that a ¼ aðzÞ ¼ a0 z with z in vivo equalling a/a0. Then we would not have understood that z determines the role of x; hence, we would not have understood the system completely. Moreover, if for some reason z would vary between conditions (e.g., because of a mutation) for which x and y would be the same, then one would find the determination of the function of x (df/dx) to be irreproducible. How reminiscent of biological practice this is! If one were to determine all parameter values in vitro, one would find absence of correspondence between the predictions based on the determination of the parameter values in vitro and the function in vivo. This would then lead to the discovery of the role of z and, ultimately, to complete understanding (Snoep et al., 2006). The issue we raise here is profound and has wide implications. Intracellular networks are strongly connected, to the extent that (almost) any

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molecule is connected with any other molecule ( Jeong et al., 2000). Consequently, in vitro assays would have to consider the roles of all other gene products in determining the function of any single one of them. For an organism of 25,000 genes, this would require more than 625 million accurate studies. Luckily, there are arguments that suggest the scaling is linear (Westerhoff et al., 2010), such that the number may be closer to 50,000. And, more strategic thinking will reduce the amount of work needed (Westerhoff et al., 2010). Recently, a tip of this iceberg was lifted when an “in vivo-like” medium was designed for the in vitro determination of enzyme kinetic parameters: various components of this medium that are usually thought of as “neutral” had significant effects on these parameters (van Eunen et al., 2010).

3. Alternative Definitions of Systems Biology The above may serve to appreciate why there are multiple definitions of systems biology and may provide place for these definitions in perspective. Systems biology is often defined as the application of mathematical modeling to biology. This definition accords with the fact that systems biology requires mathematical modeling because it depends on precision, and it requires biology because it must deal with actual function. This definition has some disadvantages, however. First, it is secondary rather than primary, that is, it can be deduced from the more fundamental definition given above. Second, there are many fields outside systems biology that would fall under this definition, including the extensive field of structural biology. X-ray or NMR data are input to extensive computations that then lead to the understanding of structures of proteins. Also enzyme kinetics combines computation with experimentation and biology. Another definition of systems biology is the utilization of genome-wide datasets in biology. This definition also derives from our more fundamental definition because the role that every type of molecule plays in function may depend on all other molecules in the system. Hence all analyses should be genome-wide or at least be wary of the entire genome. A fourth definition of systems biology is “the interface between biology and medicine on the one hand and physics, chemistry, and mathematics on the other hand.” Although systems biology has to be at this interface due to its fundamental definition, there are many other activities at this interface that do not study emergence of function from interactions. Genome sequencing, for instance, requires analytical chemistry, molecular biology, and computation but is not systems biology.

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4. Different Types of Systems Biology Figure 1.1 shows that there are different types of systems biology. These different types can be distinguished in multiple ways. One distinction is whether they work in an upward or a downward direction. The former is called bottom-up systems biology. It considers components and their interactions and then tries to understand how new properties emerge when the components are allowed to interact (Novak et al., 1998; Teusink et al., 1998). The latter, top-down systems biology looks for patterns of behavior in the whole and tries to find empirical laws for correlations and ultimately cause–effect relations (Lauffenburger, 2000). Top-down and bottom-up systems biology can begin and end at any points in biological organization (see Fig. 1.1): they may try to explain ecological phenomena on the basis of interactions of the organisms within an ecosystem (e.g., Getz et al., 2003; Roling et al., 2007), or the production of ATP or DNA structure at the biochemical level from detailed molecular biology (e.g., Westerhoff et al., 1981, 1988). Top-down systems biology is not the same as genome-wide molecular biology. In Fig. 1.2, we illustrate this further. One may look at biology from different perspectives, such as the molecular perspective, the chemical perspective, or the structure perspective. The molecular perspective tries to understand how interactions of molecules lead to the dynamic behavior of all molecules together. This is only one aspect of function however. A different aspect is that of Physics, where one wonders how the forces that reign between components lead to forces or displacement at high levels of organization. From the chemical perspective, one may see detailed biochemical reactions such as the anabolic chemical pathways that lead to the synthesis of new individuals of the organism. And then there is the genetic perspective, which connects molecular genetics to Mendelian genetics and ultimately to population genetics. There is yet another perspective on systems biology, that is, the historical one. Part of it has emerged from physical chemistry and mathematical biology, and part from molecular biology through genomics (Westerhoff and Palsson, 2004). We have drawn up Fig. 1.2 because we think that at present, these different perspectives operate like silos in which different types of systems biology are being professed. We note, however, that there is much excitement in trying to connect the silos, for instance, when asking how the structure and composition of the membranes of mammalian cells depend on the activity of multiple chemical and physical processes (e.g., Maeder et al., 2007). We call the systems biology that attempts to integrate such different perspectives left–right systems biology. In this sense, there are

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Whole

Genomewide

Biceps force; action potential

Biomass synthesis

Anatomy

Phenotype

Molecular

Physical

Chemical

Structural

Genetic

2 Molecules

ATP Gibbs energy, molecular charge

Enzyme reaction

Macrom olecule structure

Genotype

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Figure 1.2 Left–right consideration of systems biology. The various perspectives of systems biology may all work downward (top-down) from more intact systems to interacting components, or upward (bottom-up). One of the upcoming challenges for systems biology is not only to integrate top-down or bottom-up but also left–right, that is, for example, to integrate the molecular with the physical perspective, or the chemical with the structural perspective.

different types of systems biology, therefore. In another, there may be only one, as all perspectives described in Fig. 1.2 are needed to understand the functioning of living organisms and the role of each perspective therein.

ACKNOWLEDGMENTS This work reflects discussions with many of my colleagues, too many to mention: most of what I wrote here I owe to the insights of others and to funding by various organizations— STW, the NGI-Kluyver Centre, NWO-SysMo, BBSRC-MCISB, SysMO, ERASysBio and BRIC, EPSRC, AstraZeneca—and by the EU grants BioSim, NucSys (and extensions), ECMOAN, and UniCellSys.

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