Success of synthetic model

Researchers studying simple, synthetic gene networks created mathematical models that enabled them to predict more complex network behaviors, providing a proof-of-principle of one of the central tenets of synthetic and systems biology, according to a report in this week?s Nature.?This broad kind of approach that we call a bottom-up approach is in fact feasible,? senior author J. J. Collins of Boston University told The Scientist. He added that other studies have shown that mathematical models can describe simple synthetic network behavior, but no one had yet shown that these models could then be used to predict more complex behaviors.Led by Collins and first author Nicholas Guido, the researchers engineered four different types of simple gene networks in Escherichia coli cultures. Due to differences in transcriptional promoters, adding certain chemicals to the cultures activated transcription of the green fluorescent protein (GFP) gene in one system, but repressed transcription of GFP in another system. GFP expression was simultaneously activated and repressed in a third system and was neither activated nor repressed in a control. The researchers measured the amount of GFP fluorescence to determine the amount of gene transcription in each of the four systems. They developed and fit a mathematical model that accounted for the variation in each system, and they then used this model to predict how much fluorescence they would see in a new type of network behavior, positive feedback. They tweaked a component of the simultaneous activation/repression system so that expression of the activator component fed back to induce its own transcription. They found that GFP fluorescence in this new system matched the amount predicted by their model.?The model predictions seem to correspond quite well to the experimental observations of the more complex system,? said Ron Weiss of Princeton University, who was not involved in the study. Many researchers in synthetic biology have been operating on the assumption that this bottom-up approach to studying gene regulation would work, Weiss told The Scientist, but no one had yet proven that.Collins and his co-workers also found that their model predicted an unexpected effect of cell growth and division on variation in GFP expression between bacterial cells. According to the model, this variation should decrease when cells are actively growing and dividing ? a counterintuitive pattern, given that the researchers suspected that variation in gene expression should actually increase during cell division, Collins noted.When they ran the experiment, however, they found that the model?s prediction was indeed correct: Dividing cells show less variation in expression levels than do stationary cells. The authors theorize that cell division may allow continuous balancing of the number of plasmid copies in each cell. In stationary phase, on the other hand, discrepancies in plasmid numbers between cells are permanent and contribute to increased variation. ?We were able to use the model to make testable predictions that turned out to be biologically meaningful,? Collins said.Creating a model that can predict new network behaviors is an ?encouraging result,? said James Liao of the University of California, Los Angeles, who was not involved in the study. The methods that Collins and colleagues used to build the mathematical model are extremely detailed, Liao said, which likely led to their ability to conduct a more complicated study than what?s been done in the past, Liao said. ?This method applies to this particular system very well.?Whether this method is useful for investigating other types of gene networks, however, ?remains to be seen,? Liao told The Scientist. ?We hope it is.??If you can characterize the [network] components relatively well? then I think you could do a reasonable job for even much more complicated networks,? Collins predicted. ?But the models are only going to be as good as the experimental data that go in.?Melissa Lee Phillips mlp@nasw.orgLinks within this articleJ. Lucentini, ?Is this life?? The Scientist, January 1, 2006. http://www.the-scientist.com/article/display/18854/D. Endy, ?Useful construction,? The Scientist, January 1, 2006. http://www.the-scientist.com/2006/1/1/37/1/P. Hunter, ?Putting Humpty Dumpty back together again,? The Scientist, February 24, 2003. http://www.the-scientist.com/article/display/13563/N. J. Guido et al., ?A bottom-up approach to gene regulation,? Nature, February 16, 2006. http://www.nature.com/natureJ. J. Collins http://www.bu.edu/ablT. S. Gardner et al., ?Construction of a genetic toggle switch in Escherichia coli,? Nature, January 20, 2000. PM_ID: 10659857H. M. Sauro, ?The next frontier in cellular networking,? The Scientist, August 1, 2005. http://www.the-scientist.com/article/display/15652/Ron Weiss http://www.ee.princeton.edu/people/Weiss.phpC. A. Hutchison, III, et al., ?The new biological synthesis,? The Scientist, January 1, 2006. http://www.the-scientist.com/2006/1/1/38/1/James Liao http://www.seas.ucla.edu/~liaoj/index.htm

Success of synthetic model

The Scientist ARCHIVES

Become a Member of

Meet the Author

Melissa Lee Phillips

Related Research Resources

Why Do We Feel Butterflies in the Stomach?

Research Resources

Podcasts

Webinars

Videos

Infographics

eBooks

Long-Read RNA Sequencing Reveals a Regulatory Role for Splicing in Immunotherapy Responses

Research Roundtable: The Evolving World of Spatial Biology

Exploring the State of the Art in Gene Editing Techniques

Simplifying Early Alzheimer’s Disease Diagnosis with Blood Testing

Products

Product News

Research on rewiring neural circuit in fruit flies wins 2025 Eppendorf & Science Prize

EVIDENT's New FLUOVIEW FV5000 Redefines the Boundaries of Confocal and Multiphoton Imaging

EVIDENT Launches Sixth Annual Image of the Year Contest

10x Genomics Launches the Next Generation of Chromium Flex to Empower Scientists to Massively Scale Single Cell Research