Dataset Information

Adaptive laboratory evolution of microbial co-cultures for improved metabolite secretion

ABSTRACT:

Adaptive laboratory evolution has proven highly effective for obtaining microorganisms with enhanced capabilities. Yet, this method is inherently restricted to the traits that are positively linked to cell fitness, such as nutrient utilization. Here, we introduce coevolution of obligatory mutualistic communities for improving secretion of fitness-costly metabolites through natural selection. In this strategy, metabolic cross-feeding connects secretion of the target metabolite, despite its cost to the secretor, to the survival and proliferation of the entire community. We thus co-evolved wild-type lactic acid bacteria and engineered auxotrophic Saccharomyces cerevisiae in a synthetic growth medium leading to bacterial isolates with enhanced secretion of two B-group vitamins, viz., riboflavin and folate. The increased production was specific to the targeted vitamin, and evident also in milk, a more complex nutrient environment that naturally contains vitamins. Genomic, proteomic and metabolomic analyses of the evolved lactic acid bacteria, in combination with flux balance analysis, showed altered metabolic regulation towards increased supply of the vitamin precursors. Together, our findings demonstrate how microbial metabolism adapts to mutualistic lifestyle through enhanced metabolite exchange.

INSTRUMENT(S): Liquid Chromatography MS -, Gas Chromatography MS - positive

SUBMITTER: Dimitrios Konstantinidis

PROVIDER: MTBLS2217 | MetaboLights | 2021-07-02

REPOSITORIES: MetaboLights

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Dataset's files

Source:

			Action	DRS
	MTBLS2217	Other
	FILES	Other
	a_MTBLS2217_GC-MS_positive__metabolite_profiling.txt	Txt
	a_MTBLS2217_Riboflavin_LC-MS___metabolite_profiling-1.txt	Txt
	a_MTBLS2217_Riboflavin_LC-MS___metabolite_profiling-2.txt	Txt

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Publications

Adaptive laboratory evolution of microbial co-cultures for improved metabolite secretion.

Konstantinidis Dimitrios D Pereira Filipa F Geissen Eva-Maria EM Grkovska Kristina K Kafkia Eleni E Jouhten Paula P Kim Yongkyu Y Devendran Saravanan S Zimmermann Michael M Patil Kiran Raosaheb KR

Molecular systems biology 20210801 8

PMID: 34370382

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