Transient Accumulation of NO2- and N2O during Denitrification Explained by Assuming Cell Diversification by Stochastic Transcription of Denitrification Genes

Junaid Hassan, Zhi Qu, Linda L Bergaust and Lars R Bakken

PLOS Computational Biology, 2016, vol. 12, issue 1, 1-24

Abstract: Denitrifying bacteria accumulate NO2−, NO, and N2O, the amounts depending on transcriptional regulation of core denitrification genes in response to O2-limiting conditions. The genes include nar, nir, nor and nosZ, encoding NO3−-, NO2−-, NO- and N2O reductase, respectively. We previously constructed a dynamic model to simulate growth and respiration in batch cultures of Paracoccus denitrificans. The observed denitrification kinetics were adequately simulated by assuming a stochastic initiation of nir-transcription in each cell with an extremely low probability (0.5% h-1), leading to product- and substrate-induced transcription of nir and nor, respectively, via NO. Thus, the model predicted cell diversification: after O2 depletion, only a small fraction was able to grow by reducing NO2−. Here we have extended the model to simulate batch cultivation with NO3−, i.e., NO2−, NO, N2O, and N2 kinetics, measured in a novel experiment including frequent measurements of NO2−. Pa. denitrificans reduced practically all NO3− to NO2− before initiating gas production. The NO2− production is adequately simulated by assuming stochastic nar-transcription, as that for nirS, but with a higher probability (0.035 h-1) and initiating at a higher O2 concentration. Our model assumes that all cells express nosZ, thus predicting that a majority of cells have only N2O-reductase (A), while a minority (B) has NO2−-, NO- and N2O-reductase. Population B has a higher cell-specific respiration rate than A because the latter can only use N2O produced by B. Thus, the ratio BA is low immediately after O2 depletion, but increases throughout the anoxic phase because B grows faster than A. As a result, the model predicts initially low but gradually increasing N2O concentration throughout the anoxic phase, as observed. The modelled cell diversification neatly explains the observed denitrification kinetics and transient intermediate accumulations. The result has major implications for understanding the relationship between genotype and phenotype in denitrification research.Author Summary: Denitrifiers generally respire O2, but if O2 becomes limiting, they may switch to anaerobic respiration (denitrification) by producing NO3−-, NO2−-, NO- and/or N2O reductase, encoded by nar, nir, nor, and nosZ genes, respectively. Denitrification causes transient accumulation of NO2− and NO/N2O emissions, depending on the activity of the four reductases. Denitrifiers lacking nosZ produce ~100% N2O, whereas organisms with only nosZ are net consumers of N2O. Full-fledged denitrifiers are equipped with all four reductases, genetic regulation of which determines NO2− accumulation and NO/N2O emissions. Paracoccus denitrificans is a full-fledged denitrifying bacterium, and here we present a modelling approach to understand its gene regulation. We found that the observed transient accumulation of NO2− and N2O can be neatly explained by assuming cell diversification: all cells expressing nosZ, while a minority expressing nar and nir+nor. Thus, the model predicts that in a batch culture of this organism, only a minor sub-population is full-fledged denitrifier. The cell diversification is a plausible outcome of stochastic initiation of nar- and nir transcription, which then becomes autocatalytic by NO2−and NO, respectively. The findings are important for understanding the regulation of denitrification in bacteria: product-induced transcription of denitrification genes is common, and we surmise that diversification in response to anoxia is widespread.

Date: 2016
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004621 (text/html)
https://journals.plos.org/ploscompbiol/article/fil ... 04621&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pcbi00:1004621

DOI: 10.1371/journal.pcbi.1004621

Access Statistics for this article

More articles in PLOS Computational Biology from Public Library of Science
Bibliographic data for series maintained by ploscompbiol ().