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Title: Partner-assisted artificial selection of a secondary function for efficient bioremediation
Microbial enzymes can address diverse challenges such as degradation of toxins. However, if the function of interest does not confer a sufficient fitness effect on the producer, the enzymatic function cannot be improved in the host cells by a conventional selection scheme. To overcome this limitation, we propose an alternative scheme, termed ‘partner-assisted artificial selection’ (PAAS), wherein the population of enzyme producers is assisted by function-dependent feedback from an accessory population. Simulations investigating the efficiency of toxin degradation reveal that this strategy supports selection of improved degradation performance, which is robust to stochasticity in the model parameters. We observe that conventional considerations still apply in PAAS: more restrictive bottlenecks lead to stronger selection but add uncertainty. Overall, we offer a guideline for successful implementation of PAAS and highlight its potentials and limitations.  more » « less
Award ID(s):
2103545
PAR ID:
10434949
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
iScience
ISSN:
2589-0042
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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