(466f) EuGeneCD: A Computational Tool for Qualitative Genetic Circuit Design for Eukaryotic Organisms | AIChE

(466f) EuGeneCD: A Computational Tool for Qualitative Genetic Circuit Design for Eukaryotic Organisms


Schroeder, W. - Presenter, The Pennsylvania State University
Saha, R., University of Nebraska-Lincoln

Wheaton Schroeder Wheaton Schroeder 4 8 2019-04-13T01:08:00Z 2019-04-13T01:09:00Z 1 510 2911 24 6 3415 16.00 http://www.zotero.org/styles/american-political-science-association American Political Science Association http://www.zotero.org/styles/american-sociological-association American Sociological Association http://www.zotero.org/styles/chicago-author-date Chicago Manual of Style 16th edition (author-date) http://www.zotero.org/styles/ieee IEEE https://csl.mendeley.com/styles/446088811/ieee IEEE - Wheaton Schroeder, PhD Student http://csl.mendeley.com/styles/446088811/ieee IEEE - Wheaton Schroeder, PhD Student http://www.zotero.org/styles/modern-humanities-research-association Modern Humanities Research Association 3rd edition (note with bibliography) http://www.zotero.org/styles/modern-language-association Modern Language Association 7th edition http://csl.mendeley.com/styles/446088811/PNAS PNAS Citation Style http://www.zotero.org/styles/pnas Proceedings of the National Academy of Sciences of the United States of America True

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text-align:center;line-height:normal"> normal">EuGeneCD " times new roman>: A computational tool for qualitative genetic circuit
design for eukaryotic organisms

text-align:center;line-height:normal"> " times new roman>Wheaton Schroeder and Rajib Saha

text-align:center;line-height:normal"> " times new roman>The University of Nebraska – Lincoln, Lincoln, NE


genetic circuits, first created about two decades ago, are tools which allow
biological systems to perform dynamic or binary computations often with respect
to some external signal allowing for more precise control of redesigned
biological systems. These tools are proving increasingly useful in the rational
redesigning of biological processes directed to the overproduction of a
specific bioproduct, the engineering of a desired behavior, or improvement of a
biological systems performance. However, implementing genetic circuits has been
proven to be challenging, and therefore expensive, to rationally or intuitively
create, screen cultures, and measure behavior normal">in vivo. Therefore, in silico
computational modeling of biological processes, generally metabolism, is often being  used to drive
the understanding and designing of genetic circuits. While some recent
computational tools and models have been created to aid in this process, many
are in silico aids to the design of
specific bioparts, such as ribosome binding sites or
transcription terminators, and as such cannot be used for holistic in silico circuit design, although some
tools for in silico holistic design
do exist. Furthermore, the majority (if not all) of these tools are for
prokaryotic systems, which have significant and important differences in both
transcription and translation compared to eukaryotic systems. Here, we
introduce a mixed integer linear programming (MILP) tool normal"> EuGeneCD ( normal">Eukaryotic Genetic Circuit normal">Design tool), a computational tool which uses inputs of potential
circuit bioparts, qualitative part information, and
desired binary computation behavior to design a genetic circuit with
course-grained information on circuit behavior in response to an input set of
ligands through an optimization-based approach.


justify;line-height:normal"> font-family:" times new roman>Zea normal">

(maize), as an important agricultural species which may benefit from genetic
circuits, was chosen to verify the utility of EuGeneCD
through two in silico case studies.
The first case study involved the use of fluorescent proteins (blue, red,
green, and yellow) as reporters in response to the available carbon source(s) (combinations
of glucose and L-arabinose) in the maize root environment. Several possible
genetic circuit designs were proposed by EuGeneCD which
utilize different combinations of bioparts and
different binary logical structures to perform the desired binary computation,
dominated by internal and, nor, and not logical gates. The resulting circuit
design differs in important ways from equivalent circuit designs for E. coli, highlighting the need for a
eukaryotic tool. The second in silico
case study involves the designing of a genetic circuit for controlling how rhizobiome interacts with maize root through the regulation
of classes of signaling molecule, which has been shown to be responsible for
regulating plant-rhizobiome interactions. In this
case, by controlling strigolactone and flavonoids exudates
through the use of a genetic circuit, the
environmental conditions in and around the maize root may be tuned to favor mycelium
or bacterium which meet current plant needs. Several possible circuit designs
for effecting the desired environmental changes are proposed by EuGeneCD.