Systems biology uses information about the parts of the system (shown on the left) in order to build working models of biological systems (right). These models are built of mathematical descriptions of the interconnected parts. The models can be changed and rebuilt infinitely, to explore the behaviour of the system and to take account of new experimental information. They can also be used to predict the outcome of changes to the system, which can then be tested experimentally.
Pictures adaped from:
A. vandenBerg, L. Ringrose, First annual meeting of the EpiGeneSys Network of Excellence: moving epigenetics towards systems biology. BioEssays : news and reviews in molecular, cellular and developmental biology34, 620 (Jul, 2012).
Systems Biology approaches are promising to help scientists advance the field of Epigenetics.
Written by: Alysia L. vandenBerg, PhD
Systems biology is the study of systems of biological components. Since living systems are dynamic and complex, their behavior can be hard to predict from the properties of their individual parts. Therefore researchers use methods like making quantitative measurements of the behavior of groups of interacting components using systematic measurement technologies such as genomics, bioinformatics, and proteomics, and implement mathematical and computational models to describe and predict dynamical behavior. [adapted from the Harvard Systems Biology website, for more information see (1)].
“Systems biology focuses on the interaction of myriad components and how these give rise to the dynamic and complex behavior of biological systems” (2). The amount of epigenetic information contained in all of the different cell types of the body, and acquired under different environmental conditions is vast (3) . Dynamic changes in epigenetic marks can occur during cellular processes such as: DNA replication, cell fate decisions, and response to environmental stresses, just to name a few. Considered together, we begin to see there is a large amount of epigenetic information contained within an organism that is accrued throughout its lifetime. How epigenetic marks are copied and propagated under different conditions, at different stages of development, or across generations and how they are sometimes lost, all remain important topics of active research. We need to address these questions and fundamental epigenetic mechanisms in quantitative terms both spatially and temporally in order to understand them on a system-wide level (4).
Systems biology approaches are already being used by researchers, in order to further elucidate epigenetic questions. Researchers like our EpiGeneSys Network Members seek to derive the epigenetic information in different cell types and organisms by using computational methods to look holistically at a genome and its epigenome(s). Epigenetic information can be, stable in order to be transmitted through mitosis and/or meiosis, but also flexible, in order to respond to changing signals from the environment, respond to changes throughout the cell cycle, etc. So for example, mathematical modeling of the changes in dynamic binding of epigenetic regulators to chromatin will hopefully shed light on how the biological system—the cell—enables seemingly contradictory objectives of both stability and flexibility. The interaction between genome and epigenome is also an important consideration – how does genetic variation impact gene expression and genome function, through epigenetic changes? Combining genetic and epigenetic approaches in a quantitative fashion in a systems biology context will be essential for this. Systems Biology approaches are therefore very promising to help us advance the field of Epigenetics via gaining a better understanding of the dynamics of epigenetic regulators, the nature of signaling affecting the epigenome and the link between genotype and epigenotype.
1. F. Marcus, Bioinformatics and Systems Biology: Collaborative Research and Resources. (Springer, New York City, 2008), pp. 288.
2. C. D. Smolke, P. A. Silver, Informing biological design by integration of systems and synthetic biology. Cell144, 855 (Mar 18, 2011).
3. A. vandenBerg, L. Ringrose, First annual meeting of the EpiGeneSys Network of Excellence: moving epigenetics towards systems biology. BioEssays : news and reviews in molecular, cellular and developmental biology34, 620 (Jul, 2012).
4. P. A. Steffen, J. P. Fonseca, L. Ringrose, Epigenetics meets mathematics: towards a quantitative understanding of chromatin biology. BioEssays : news and reviews in molecular, cellular and developmental biology34, 901 (Oct, 2012).