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Updated: Sep 10, 2025

Measuring Nitrite and Nitrate, Metabolites in the Nitric Oxide Pathway, in Biological Materials using the Chemiluminescence Method
Published on: December 25, 2016
Nitrate reduction for survival in a nanomolar world, not the millimolar world of a laboratory
1School of Biosciences and Institute of Microbiology and Infection, University of Birmingham, Birmingham UK.
Abstract:
This review focuses on some of the persisting misconceptions and even errors in the literature of bacterial denitrification and the respiratory reduction of nitrate to ammonia. Both processes were traditionally investigated using pure culture laboratory techniques and substrate concentrations in the high micromolar or millimolar range. These concentrations are 1000-fold higher than those found in the nanomolar natural environments in which bacterial metabolism continues to evolve. Many of the enzymes involved in anaerobic nitrate reduction are metalloproteins that are easily inactivated by exposure to reactive oxygen and reactive nitrogen species. However, the metal centers of some of these proteins retain the ability to catalyze chemical reactions irrelevant to their physiological function. The review highlights some of the errors and misconceptions persisting in the literature, especially in the context of sensing, production and reduction of nitric oxide. It challenges many statements about physiological relevance. It demonstrates how knowledge of mechanisms that regulate gene transcription and mRNA translation provide clues to enzyme function. Four criteria are proposed to judge whether a protein-dependent reaction is physiologically relevant. They include whether (i) the protein is present in the correct cellular location; (ii) its synthesis is regulated in response to, or in preparation for, its proposed role; (iii) the catalytic efficiency is adequate to fulfil the need; and (iv) alternative enzymes are available that better meet the first three criteria. How errors become embedded in the literature, perpetuated and reinforced by annotation errors in genome databases are highlighted.
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