Biology Reference
In-Depth Information
These strategies illustrate the possible approaches to optimizing production of a
non-growth-associated compound, and highlight the need for further experimental
work to assess the performance of this approach.
DISCUSSION
A primary value of genome-scale metabolic models is their ability to provide a ho-
listic view of metabolism allowing, for instance, for quantitative investigation of de-
pendencies between species existing far apart in the metabolic network [20]. Once
experimentally validated, these models can be used to characterize metabolic resource
allocation, to generate experimentally testable predictions of cell phenotype, to elu-
cidate metabolic network evolution scenarios, and to design experiments that most
effectively reveal genotype-phenotype relationships. Furthermore, owing to their ge-
nome-wide scale, these models enable systematic assessment of how perturbations in
the metabolic network affect the organism as a whole, such as in determining lethality
of mutations or predicting the effects of nutrient limitations. Since these multiple and
intertwined relationships are not immediately obvious without genome-scale analysis,
they would not be found during investigation of small, isolated circuits or genes as is
typical in a traditional reductionist approach [65, 66].
We present here a genome-scale reconstruction and CB model of the
P. putida
strain KT2440, accounting for 815 genes whose products correspond to 877 reactions
and connect 886 metabolites. The manually curated reconstruction was based on the
most up-to-date annotation of the bacterium, the content of various biological data-
bases, primary research publications and specifi cally designed functional genomics
experiments. New or refi ned annotations for many genes were suggested during the
reconstruction process. The model was validated with a series of experimental sets,
including continuous culture data, BIOLOG substrate utilization assays,
13
C fl ux mea-
surements and a set of specifi cally-generated mutant strains. The FBA and FVA were
used to ascertain the distribution of resources in KT2440, to systematically assess gene
and reaction essentiality and to gauge the robustness of the metabolic network. Hence,
this work represents one of the most thorough sets of analyses thus far performed
for an organism by means of CB modeling, providing thereby a solid genome-scale
framework for the exploration of the metabolism of this fascinating and versatile bac-
terium. However, since this modeling endeavor relies upon a number of approxima-
tions, the limits, potential and applicability of the analysis must be clearly identifi ed
and defi ned. We address these points below.
Altogether, our results and analyses show that the model accurately captures a sub-
stantial fraction of the metabolic functions of
P. putida
KT2440. Therefore, the model
was used to generate hypotheses on constraining and redirecting fl uxes towards the
improvement of production of PHAs, which are precursors for industrially and medi-
cally important bioplastics. This is, to our knowledge, the fi rst reported application of
CB modeling to direct and improve the yield of a compound of which the production
is not directly coupled to the growth of the organism. This opens up novel areas of
application for the CB approach. Our approach, based on the OptKnock algorithm,
