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High‐throughput dilution‐based growth method enables time‐resolved exo‐metabolomics of Pseudomonas putida and Pseudomonas aeruginosa
Author(s) -
Pedersen Bjarke H.,
Gurdo Nicolás,
Johansen Helle Krogh,
Molin Søren,
Nikel Pablo I.,
La Rosa Ruggero
Publication year - 2021
Publication title -
microbial biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.287
H-Index - 74
ISSN - 1751-7915
DOI - 10.1111/1751-7915.13905
Subject(s) - pseudomonas putida , metabolomics , biology , throughput , bacteria , computational biology , metabolic pathway , biochemical engineering , biological system , metabolism , biochemistry , computer science , bioinformatics , genetics , telecommunications , engineering , wireless
Summary Understanding metabolism is fundamental to access and harness bacterial physiology. In most bacteria, nutrient utilization is hierarchically optimized according to their energetic potential and their availability in the environment to maximise growth rates. Low‐throughput methods have been largely used to characterize bacterial metabolic profiles. However, in‐depth analysis of large collections of strains across several conditions is challenging since high‐throughput approaches are still limited – especially for non‐traditional hosts. Here, we developed a high‐throughput dilution‐resolved cultivation method for metabolic footprinting of Pseudomonas putida and Pseudomonas aeruginosa . This method was benchmarked against a conventional low‐throughput time‐resolved cultivation approach using either a synthetic culture medium (where a single carbon source is present) for P. putida or a complex nutrient mixture for P. aeruginosa . Dynamic metabolic footprinting, either by sugar quantification or by targeted exo‐metabolomic analyses, revealed overlaps between the bacterial metabolic profiles irrespective of the cultivation strategy, suggesting a certain level of robustness and flexibility of the high‐throughput dilution‐resolved method. Cultivation of P. putida in microtiter plates imposed a metabolic constraint, dependent on oxygen availability, which altered the pattern of secreted metabolites at the level of sugar oxidation. Deep‐well plates, however, constituted an optimal cultivation set‐up yielding consistent and comparable metabolic profiles across conditions and strains. Altogether, the results illustrate the usefulness of this technological advance for high‐throughput analyses of bacterial metabolism for both biotechnological applications and automation purposes.

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