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Bioengineers at the University of California, San Diego have developed a
method of modeling, simultaneously, an organism’s metabolism and its underlying
gene expression. In the emerging field of systems biology, scientists model
cellular behavior in order to understand how processes such as metabolism and
gene expression relate to one another and bring about certain characteristics
in the larger organism.
In addition to serving as a platform for investigating fundamental
biological questions, this technology enables far more detailed calculations of
the total cost of synthesizing many different chemicals, including biofuels. Their
method accounts, in molecular detail, for the material and energy required to
keep a cell growing, the research team reported in Nature Communications.
“This is a major advance in genome-scale analysis that accounts for the
fundamental biological process of gene expression and notably expands the number
of cellular phenotypes that we can compute,” said Bernhard Palsson, Galetti
Professor of Bioengineering, at the UC San Diego Jacobs School of Engineering.
“With this new method, it is now possible to perform computer simulations of
systems-level molecular biology to formulate questions about fundamental life
processes, the cellular impacts of genetic manipulation, or to quantitatively
analyze gene expression data,” said Joshua Lerman, a PhD candidate in Palsson’s
Systems Biology Research Group.
The team’s method can be compared to understanding both the chemical
reactions and the machinery that are required to refine crude oil into petrol in
a large, industrial factory. Modeling metabolism tells you what biochemical
reactions need to take place. Modeling the organism’s gene expression tells you
what kind of machinery you need. The team’s method specifically accounts for
the expression of enzymes, which are the molecular machines responsible for the
biochemical processes of life. With this knowledge, it is possible to explore
how an organism distributes its resources to promote growth and how genetic
manipulation of these organisms alters this distribution.
“What you could hypothetically do with our model is simulate the total cost of
producing a value-added product, such as a biofuel. That includes all the
operating and maintenance costs,” said Daniel Hyduke, a project scientist in
Palsson’s laboratory. Hyduke said the method has the potential to help
streamline industrial metabolic engineering efforts by providing a near
complete accounting of the minimal material and energy costs associated with
novel strain designs for biofuel, commodity chemicals, and recombinant protein
production.
Hyduke and Lerman prototyped the method on the minimal, yet metabolically
versatile, hyperthermophile Thermotoga maritima. Because T.
maritima is not currently ready for use in industrial applications, Hyduke
and Lerman are working as part of a larger team to produce similar models for
industrially relevant microorganisms, such as E. coli.
“We’ve built a virtual reality simulator of metabolism and gene expression
for Thermotoga maritima, and shown that it much better approximates
phenotypes of cells than modeling metabolism in isolation,” said Lerman.
