Dataset Information

Habitat diversity and type govern potential nitrogen loss by denitrification in coastal sediments and differences in ecosystem-level diversities of disparate N2O reducing communities.

ABSTRACT: In coastal sediments, excess nitrogen is removed primarily by denitrification. However, losses in habitat diversity may reduce the functional diversity of microbial communities that drive this important filter function. We examined how habitat type and habitat diversity affects denitrification and the abundance and diversity of denitrifying and N2O reducing communities in illuminated shallow-water sediments. In a mesocosm experiment, cores from four habitats were incubated in different combinations, representing ecosystems with different habitat diversities. We hypothesized that habitat diversity promotes the diversity of N2O reducing communities and genetic potential for denitrification, thereby influencing denitrification rates. We also hypothesized that this will depend on the identity of the habitats. Habitat diversity positively affected ecosystem-level diversity of clade II N2O reducing communities, however neither clade I nosZ communities nor denitrification activity were affected. The composition of N2O reducing communities was determined by habitat type, and functional gene abundances indicated that silty mud and sandy sediments had higher genetic potentials for denitrification and N2O reduction than cyanobacterial mat and Ruppia maritima meadow sediments. These results indicate that loss of habitat diversity and specific habitats could have negative impacts on denitrification and N2O reduction, which underpin the capacity for nitrogen removal in coastal ecosystems.

SUBMITTER: Wittorf L

PROVIDER: S-EPMC7428367 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Habitat diversity and type govern potential nitrogen loss by denitrification in coastal sediments and differences in ecosystem-level diversities of disparate N2O reducing communities.

Wittorf Lea L Roger Fabian F Alsterberg Christian C Gamfeldt Lars L Hulth Stefan S Sundbäck Kristina K Jones Christopher M CM Hallin Sara S

FEMS microbiology ecology 20200901 9

In coastal sediments, excess nitrogen is removed primarily by denitrification. However, losses in habitat diversity may reduce the functional diversity of microbial communities that drive this important filter function. We examined how habitat type and habitat diversity affects denitrification and the abundance and diversity of denitrifying and N2O reducing communities in illuminated shallow-water sediments. In a mesocosm experiment, cores from four habitats were incubated in different combinati ...[more]

PMID: 32662514

Similar Datasets

Project description:Global atmospheric loading of the climate-active gas nitrous oxide (N2O) continues to increase. A significant proportion of anthropogenic N2O emissions arises from microbial transformation of nitrogen-based fertilizers during denitrification, making microbial N2O emissions a key target for greenhouse gas reduction strategies. The genetic, physiological, and environmental regulation of microbially mediated N2O flux is poorly understood and therefore represents a critical knowledge gap in the development of successful mitigation approaches. We have previously mapped the transcriptional landscape of the model soil-denitrifying bacterium Paracoccus denitrificans Here, we show that a single bacterial small RNA (sRNA) can control the denitrification rate of P. denitrificans by stalling denitrification at nitrite reduction to limit production of downstream pathway intermediates and N2O emissions. Overexpression of sRNA-29 downregulates nitrite reductase and limits NO and N2O production by cells. RNA sequencing (RNA-seq) analysis revealed 53 genes that are controlled by sRNA-29, one of which is a previously uncharacterized GntR-type transcriptional regulator. Overexpression of this regulator phenocopies sRNA-29 overexpression and allows us to propose a model whereby sRNA-29 enhances levels of the regulator to repress denitrification under appropriate conditions. Our identification of a new regulatory pathway controlling the core denitrification pathway in bacteria highlights the current chasm in knowledge regarding genetic regulation of this pivotal biogeochemical process, which needs to be closed to support future biological and chemical N2O mitigation strategies.IMPORTANCE N2O is an important greenhouse gas and a major cause of ozone depletion. Denitrifying bacteria play vital roles in the production and consumption of N2O in many environments. Complete denitrification consists of the conversion of a soluble N-oxyanion, nitrate (NO3 -), to an inert gaseous N-oxide, dinitrogen (N2). Incomplete denitrification can occur if conditions are prohibitive, for example, under conditions of low soil copper concentrations, leading to emission of N2O rather than N2 Although enzymatically well characterized, the genetic drivers that regulate denitrification in response to environmental and physiological cues are not fully understood. This study identified a new regulatory sRNA-based control mechanism for denitrification in the model denitrifying bacterium P. denitrificans Overexpression of this sRNA slows the rate of denitrification. This report highlights that there are gaps in understanding the regulation of this important pathway which need to be filled if strategies for N2O mitigation can be rationally and carefully developed.

Project description:Denitrifying bacteria accumulate [Formula: see text], 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 [Formula: see text]-, [Formula: see text]-, 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 [Formula: see text]. Here we have extended the model to simulate batch cultivation with [Formula: see text], i.e., [Formula: see text], NO, N2O, and N2 kinetics, measured in a novel experiment including frequent measurements of [Formula: see text]. Pa. denitrificans reduced practically all [Formula: see text] to [Formula: see text] before initiating gas production. The [Formula: see text] 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 [Formula: see text]-, 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 [Formula: see text] 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.

Dataset Information

Habitat diversity and type govern potential nitrogen loss by denitrification in coastal sediments and differences in ecosystem-level diversities of disparate N2O reducing communities.

Publications

Habitat diversity and type govern potential nitrogen loss by denitrification in coastal sediments and differences in ecosystem-level diversities of disparate N2O reducing communities.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets