Biology Reference
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tion of strain-specifi c metabolic pathways. Due to its applicability across the numer-
ous P. putida strains iJP815 provides a sound basis for many future studies towards
the elucidation of habitat-specifi c features, bioremediation applications and metabolic
engineering strategies with members of this ubiquitous, metabolically versatile, and
fascinating genus.
MATERIALS AND METHODS
Constraint-based Models
The P. putida model we present was built using a CB approach. A CB model consists
of a genome-wide stoichiometric reconstruction of metabolism and a set of constraints
on the fluxes of reactions in the system [19, 20, 24]. The reconstruction represents
stoichiometry of the set of all reactions known to act in metabolism of the organism,
which can be determined in large part from genomic data since most cellular reactions
are catalyzed by enzymes. Thus the model does not require any knowledge regarding
the kinetics of the reactions, and the requisite thermodynamic knowledge is limited to
the directionality of reactions.
In addition to the reactions, the model includes a set of genes tied via Boolean logic
to reactions that their protein products catalyze, which allows for accurate discrimina-
tion of the effects of genetic perturbations such as knockouts [33, 72]. These Boolean
rules together form the GPRs relationships of the metabolic reconstruction [33].
The second part of the CB model, namely the constraints, constitutes a set of rules
that narrow down the interval within which the fl ux of particular reaction must lie.
These constraints rest upon physico-biological knowledge. One of them, the informa-
tion regarding reaction directionality, has already been mentioned above. Another con-
straint that is widely applied in biological systems is the PSSA [73], which states that
a concentration of a chemical compound stays constant over the simulated time frame.
The reactants to which this constraint is applied are usually called internal compounds,
and in biological models correspond to the chemical substances located inside the cell
or its compartments. Remaining substances, external compounds, correspond to spe-
cies that can be taken up or secreted and thus exchanged with the environment. Other
types of constraints are top and bottom limits that correspond to catalytic capabilities
of the enzymes. More detailed description of constraint-based modeling approach can
be found in [74].
Analysis Methods
Flux Balance Analysis
The FBA is a primary method for analysis of CB models. Generally, a constraint-based
model of metabolism represents an underdetermined system, that is, one in which a
range of flux distributions are mathematically possible. The FBA narrows the flux pos-
sibilities by determining a point in closed flux space that maximizes a certain linear
combination of fluxes. [75]. The FBA poses a linear programming (LP) problem and
thus a global maximum always exists, provided that the problem is feasible (i.e., there
exists at least one combination of fluxes which fulfills all the constraints). Using the
matrix notation the FBA problem can be stated as following:
 
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