Systems engineering to systems biology.
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Affiliation: Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
A converse system biology approach is to infer properties of biological systems in a ‘top-down' fashion, using a variety of network reverse engineering methods, data-driven modeling and data integration strategies... Application of a top-down approach to the quantitative biology of a small size system is however less common... In a recent publication, have insightfully applied such a strategy to successfully decode critical properties of osmo-adaptation in the yeast Saccharomyces cerevisiae... Input–output relationships can be defined and experimentally measured for a variety of biological systems and may thus be used to uncover hidden biological properties... Quantitative modeling of the osmo-adaptation pathway would require a huge amount of experimental data as well as intense computer simulations; yet measurement of many of the experimental parameters is problematic, making reliable predictions uncertain... Measuring input–output characteristics and applying LTI-based analysis reduces the underlying complex map to its simplest form, identifying key chemical reactions that dominate the response of the yeast cell to osmotic shock... The resulting reduced set of reactions permits accurate and experimentally verifiable predictions... The HOG pathway is favorable for input–output analysis, as both input and output are easily manipulated and measured, most molecular components are known and the system relies on multiple negative feedback circuits with unclear properties. measured input–output signals with square-wave stimuli with frequencies ranging from 2 to 128 min, transformed the data into frequency domain and calculated the response function to osmolar shocks... However, as yeast cells can adapt to osmotic shock within 15 min, much shorter than the time required for induction of gene expression, the authors hypothesize that changes in gene expression provide a longer timescale feedback response to osmolar shock... They confirm this hypothesis by inhibiting new protein production. successfully apply engineering principles that have seldom been used to understand biological systems... First, the linearity property has to be checked, as most biological systems would violate it... However, many systems have a linear regime and many experiments could be performed within this regime to avoid nonlinear effects; nonlinear correction factors could be added as was done for osmo-regulation... Second, the time-invariance property should be established before using LTI system analysis... Moreover, for all this to succeed, one needs to be able to translate the characteristics of LTI system into biology using knowledge about underlying components and pathways. Related in: MedlinePlus |
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Mentions: Mettetal et al followed a different systems reverse-engineering approach by which they considered the system first as a ‘black box' and assumed it to be equivalent to a linear time-invariant (LTI) system (Oppenheim et al, 1997) (Figure 1A and B). An LTI system has two defining properties: first, the output from a set of inputs represents the linear sum of the outputs from each individual input (Figure 1C). Second, the generated output is independent of the time point at which the causal input was applied (Figure 1D). An LTI system is characterized by a single ‘response function.' Once the response function is known, the output for any arbitrary input can be deterministically calculated. If the response function is unknown, which is generally the case, then one can methodically apply different inputs and observe changes in output to attempt to decode the response function (Figure 1E). For example, when a sinusoidal periodic input with a certain frequency is applied to an LTI system, the output will have the same frequency. Jean Baptiste Joseph Fourier (1768–1830) was the first to suggest that almost any physical input function can be uniquely written as a linear combination of sinusoidal functions, the famous ‘Fourier transform'. A Fourier transform describes the original function in the frequency domain instead of time domain, where the frequencies come from the sinusoids (Figure 1F). As an input to an LTI system can be expressed as a linear combination of sinusoids, the output can also be expressed with the same sinusoidal functions (with a possible time shift), whose coefficients are related in a precisely computable manner to the coefficients of input signal. In the frequency domain, the input–output relation becomes a straightforward multiplication rule, which makes it easier to determine the response function (Figure 1G). If a series of input signals each having a different frequency is applied, then in theory the response function can be fully described. |
View Article: PubMed Central - PubMed
Affiliation: Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, USA.
A converse system biology approach is to infer properties of biological systems in a ‘top-down' fashion, using a variety of network reverse engineering methods, data-driven modeling and data integration strategies... Application of a top-down approach to the quantitative biology of a small size system is however less common... In a recent publication, have insightfully applied such a strategy to successfully decode critical properties of osmo-adaptation in the yeast Saccharomyces cerevisiae... Input–output relationships can be defined and experimentally measured for a variety of biological systems and may thus be used to uncover hidden biological properties... Quantitative modeling of the osmo-adaptation pathway would require a huge amount of experimental data as well as intense computer simulations; yet measurement of many of the experimental parameters is problematic, making reliable predictions uncertain... Measuring input–output characteristics and applying LTI-based analysis reduces the underlying complex map to its simplest form, identifying key chemical reactions that dominate the response of the yeast cell to osmotic shock... The resulting reduced set of reactions permits accurate and experimentally verifiable predictions... The HOG pathway is favorable for input–output analysis, as both input and output are easily manipulated and measured, most molecular components are known and the system relies on multiple negative feedback circuits with unclear properties. measured input–output signals with square-wave stimuli with frequencies ranging from 2 to 128 min, transformed the data into frequency domain and calculated the response function to osmolar shocks... However, as yeast cells can adapt to osmotic shock within 15 min, much shorter than the time required for induction of gene expression, the authors hypothesize that changes in gene expression provide a longer timescale feedback response to osmolar shock... They confirm this hypothesis by inhibiting new protein production. successfully apply engineering principles that have seldom been used to understand biological systems... First, the linearity property has to be checked, as most biological systems would violate it... However, many systems have a linear regime and many experiments could be performed within this regime to avoid nonlinear effects; nonlinear correction factors could be added as was done for osmo-regulation... Second, the time-invariance property should be established before using LTI system analysis... Moreover, for all this to succeed, one needs to be able to translate the characteristics of LTI system into biology using knowledge about underlying components and pathways.