Designing minimal microbial strains of desired functionality using a genetic algorithm

Table 3 Features of models used

Model	M1	M2	M3
Model source	[15]	[15]	[15]
Growth conditions	Anaerobic, glucose + minimal media	Aerobic, glucose + minimal media	Aerobic, xylose, arabinose, glucose, galactose and mannose + minimal media
No: reactions	59	60	71
No: metabolites	47	49	68
Total no: EFMs	5010	38001	429275
F ₁	1.6170	1.6103	2.2770
\(\max Y_{Etoh}\)	0.6667	0.6667	0.6667
MCS cardinality	3	4	4
Number of MCSs	22	82	76
Number of EFMs	14	28	62
F ₂	7.7860	8.5283	2.3169
\(\max \eta _{Etoh}\)	0.1390	0.1542	0.1542
MCS cardinality	10	13	16
Number of MCSs	240	240	2880
Number of EFMs	4	2	6

Features of the networks on which the GA was tested. The maximum possible values for ethanol yield, \(Y_{Etoh}\) and efficiency, \(\eta _{Etoh}\) are presented. The minimal cardinality of MCSs which will force the network into these optimal values are also shown along with the total number of such MCSs and the number of EFMs which will survive after application of these MCSs. The corresponding fitness values, \(F_i\) have been obtained using the fitness functions presented in Table 4

ISSN: 1748-7188