Abstract：
:Microbial communities are under constant influence of physical and chemical components in ecosystems. Shifts in conditions such as pH, temperature or carbon source concentration can translate into shifts in overall ecosystem functioning. These conditions can be manipulated in a laboratory setup using evolutionary computation methods such as genetic algorithms (GAs). In work described here, a GA methodology was successfully applied to define sets of environmental conditions for microbial enrichments and pure cultures to achieve maximum rates of perchlorate degradation. Over the course of 11 generations of optimization using a GA, we saw a statistically significant 16.45 and 16.76-fold increases in average perchlorate degradation rates by Dechlorosoma sp. strain KJ and Dechloromonas sp. strain Miss R, respectively. For two bacterial consortia, Pl6 and Cw3, 5.79 and 5.75-fold increases in average perchlorate degradation were noted. Comparison of zero-order kinetic rate constants for environmental conditions in GA-determined first and last generations of all bacterial cultures additionally showed marked increases.
journal_name
J Biotechnoljournal_title
Journal of biotechnologyauthors
Kucharzyk KH,Crawford RL,Paszczynski AJ,Soule T,Hess TFdoi
10.1016/j.jbiotec.2011.10.011subject
Has Abstractpub_date
2012-01-01 00:00:00pages
189-97issue
1eissn
0168-1656issn
1873-4863pii
S0168-1656(11)00616-Xjournal_volume
157pub_type
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