Plunkett MH, Knutson CM, Barney BM. Key factors affecting ammonium production by an Azotobacter vinelandii strain deregulated for biological nitrogen fixation.
Microb Cell Fact 2020;
19:107. [PMID:
32429912 PMCID:
PMC7238568 DOI:
10.1186/s12934-020-01362-9]
[Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 05/04/2020] [Indexed: 11/10/2022] Open
Abstract
Background
The obligate aerobe Azotobacter vinelandii is a model organism for the study of biological nitrogen fixation (BNF). This bacterium regulates the process of BNF through the two component NifL and NifA system, where NifA acts as an activator, while NifL acts as an anti-activator based on various metabolic signals within the cell. Disruption of the nifL component in the nifLA operon in a precise manner results in a deregulated phenotype that produces levels of ammonium that far surpass the requirements within the cell, and results in the release of up to 30 mM of ammonium into the growth medium. While many studies have probed the factors affecting growth of A. vinelandii, the features important to maximizing this high-ammonium-releasing phenotype have not been fully investigated.
Results
In this work, we report the effect of temperature, medium composition, and oxygen requirements on sustaining and maximizing elevated levels of ammonium production from a nitrogenase deregulated strain. We further investigated several pathways, including ammonium uptake through the transporter AmtB, which could limit yields through energy loss or futile recycling steps. Following optimization, we compared sugar consumption and ammonium production, to attain correlations and energy requirements to drive this process in vivo. Ammonium yields indicate that between 5 and 8% of cellular protein is fully active nitrogenase MoFe protein (NifDK) under these conditions.
Conclusions
These findings provide important process optimization parameters, and illustrate that further improvements to this phenotype can be accomplished by eliminating futile cycles.
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