The Sum of the Parts: Large-Scale Modeling in Systems Biology

Abstract

Systems biologists often distance themselves from reductionist approaches and formulate their aim as understanding living systems "as a whole." Yet, it is often unclear what kind of reductionism they have in mind, and in what sense their methodologies would offer a superior approach. To address these questions, we distinguish between two types of reductionism which we call "modular reductionism" and "bottom-up reductionism." Much knowledge in molecular biology has been gained by decomposing living systems into functional modules or through detailed studies of molecular processes. We ask whether systems biology provides novel ways to recompose these findings in the context of the system as a whole via computational simulations. As an example of computational integration of modules, we analyze the first whole-cell model of the bacterium M. genitalium. Secondly, we examine the attempt to recompose processes across different spatial scales via multi-scale cardiac models. Although these models rely on a number of idealizations and simplifying assumptions as well, we argue that they provide insight into the limitations of reductionist approaches. Whole-cell models can be used to discover properties arising at the interfaces of dynamically coupled processes within a biological system, thereby making more apparent what is lost through decomposition. Similarly, multi-scale modeling highlights the relevance of macroscale parameters and models and challenges the view that living systems can be understood "bottom-up." Specifically, we point out that system-level properties constrain lower-scale processes. Thus, large-scale modeling reveals how living systems at the same time are more and less than the sum of the parts. Editorial introduction: This contribution from Fridolin Gross and Sara Green focuses on the promises and possible pitfalls of large-scale modelling in systems biology, from both a practical and a theoretical point of view. As readers will be aware, molecular biology has often been accused of being "reductionist." Systems biology has been presented as a potential response to this reductionism. Gross and Green distinguish two types of reductionisms: "modular reductionism" (the claim that living systems consist of individual functional subunits) and "bottom-up reductionism" (the claim that biological phenomena can and should be studied at the molecular level, understood as the "fundamental" biological level). They show how systems biology questions both forms of reductionism. To this end, they use two examples: whole-cell modelling of a very "simple" bacterium (from a piece published in 2012), and multi-scale computer modelling of the human heart. Without masking the limitations of these models, Gross and Green show the insights they can yield for anyone interested in ontologies of the living world. KeywordsAs with some of the other contributions in this special issue (e.g. Fagan's, and Kendig and Eckdahl's), a virtue of this paper is to illustrate how research strategies-particularly modelling strategies-can in...

Can biological complexity be reverse engineered?

“…Robustness of biological functions against perturbations to the system components and underlying connectivity is one of the major research topics in systems biology (Gross, 2013). Contrary to what one would expect from Braun and Marom's (this issue) account, a key insight provided by reverse engineering analyses is that robustness is often not attained through fine-tuning of specific mechanisms but due to features associated with the organization of the system.…”

“…Modeling all measurable details of organisms does not necessarily provide the information needed for understanding how the system is functionally organized. Whereas reverse engineering of network topology risks oversimplifying the system of study, the pre-occupation with details runs the opposite risk of overcomplicating the task by overlooking common dynamic patterns (Gross, 2013). In the words of Marom: 'One good reason to bother with formulation of an abstract model is the hope that it leads up to a mathematical construct that dramatically reduces the dimensionality of the problem at hand.…”

“…While the results of model of M. genitalium may readily be considered a success, the example also offers a lesson in modesty regarding the prospects of applying this strategy to complex systems (Gross, 2013). The example shows that also large-scale models have to rely on decomposition strategies that separate operations of functional modules on short time-scales.…”

“…Contrary to what one would expect from Braun and Marom's (this issue) account, a key insight provided by reverse engineering analyses is that robustness is often not attained through fine-tuning of specific mechanisms but due to features associated with the organization of the system. Architectural features of robust systems have been demonstrated for robustness to gradients in embryonic patterning (Eldar et al, 2002), concentration robustness in biochemical reaction networks (Shinar and Feinberg, 2011), for bacterial chemotaxis (reviewed in Braillard, 2010), and for the spindle assembly checkpoint mechanism in cell division (reviewed in Gross, 2013). Thus, engineering-inspired research in systems biology is directly related to the aim of understanding what robust networks have in common in terms of system-level organizational features, and to identify organizational features that may or may not work for a given property.…”

Introduction to Philosophy of Systems Biology

“…Graph-theoretical analysis spans historically from analysis of random networks and regular lattices, to the recent discovery that many networks share a small-world and scale-free structure with important implications for their functions (see Bechtel, Chapter 2). The importance of global network analysis for biological research is a controversial issue, and an important question is whether systems biology can bridge the gap between the local and global approaches (Gross, 2013; Chapter 10). Bechtel highlights one candidate for a middle-way, namely the search for frequently occurring patterns of connections (see also Peter, Chapter 22).…”