Modulation of Nitrous Oxide (N2O) Accumulation by Primary

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Modulation of nitrous oxide (NO) accumulation by primary metabolites in denitrifying cultures adapting to changes in environmental C and N Octavio Perez-Garcia, Cody Mankelow, Kartik Chandran, Silas G. Villas-Boas, and Naresh Singhal Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.7b03345 • Publication Date (Web): 30 Oct 2017 Downloaded from http://pubs.acs.org on October 31, 2017

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Environmental Science & Technology

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Submitted to: Environmental Science and Technology

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Modulation of nitrous oxide (N2O) accumulation by primary metabolites in denitrifying

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cultures adapting to changes in environmental C and N

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Octavio Perez-Garciaa*, Cody Mankelowa, Kartik Chandranb,

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Silas G. Villas-Boasc, Naresh Singhala*

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a

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b

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c

Department of Civil and Environmental Engineering, University of Auckland, New Zealand Department of Earth and Environmental Engineering, Columbia University, USA

School of Biological Sciences, University of Auckland, New Zealand

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*Corresponding authors: Octavio Perez-Garcia and Naresh Singhal. Department of Civil and

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Environmental Engineering, University of Auckland. 2-6 Park Avenue, Grafton, Auckland.

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New Zealand, 1023. Phone: +64 9 923 4512; Fax: +64 9 373 7462; Emails:

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[email protected] and [email protected] and

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Running title: Metabolomics and metabolic modeling of denitrifying cultures producing N2O

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Word count Body Tables Figures TOTAL

Small (x300 words) 1 1

Big (x600 words) 0 3

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ACS Paragon Plus Environment

Total 5509 300 2100 7909


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Abstract (241 words)

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Metabolomics provides insights

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into the actual physiology of cells

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rather than their mere ‘potential’,

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as provided by genomic and

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transcriptomic analysis. We

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investigate the modulation of

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nitrous oxide (N2O) accumulation

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by intracellular metabolites in

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denitrifying bacteria using

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metabolomics and genome based metabolic network modeling. Profiles of metabolites and

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their rates of production/consumption were obtained for denitrifying batch cultures under

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four conditions: initial COD:N ratios of 11:1 and 4:1, with and without nitrite spiking (28

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mg-N L-1). Only the nitrite-spiked cultures accumulated N2O. The NO2- spiked cultures with

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an initial COD:N = 11:1 accumulated 3.3±0.57 % of the total nitrogen added as N2O and

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large pools of tricarboxylic acid cycle intermediates and amino acids. In comparison, the

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NO2- spiked cultures with COD:N =4:1 showed significantly higher (p=0.028) N2O

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accumulation (8.5.3±0.9 % of the total nitrogen added), which was linked to the depletion of

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C11-C20 fatty acids. Metabolic modelling analysis shows that at COD:N of 4:1 the

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denitrifying cells slowly generate electron equivalents as FADH2 through β-oxidation of

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saturated fatty acids while COD:N of 11:1 do it through the TCA cycle. When combined with

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NO2- shock, this prolonged the duration over which insufficient electron equivalents were

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available to completely reduce NOx to N2, resulting in increased N2O accumulation. Results

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extend the understanding of how organic carbon and nitrite loads modulate N2O

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accumulation in denitrification, which may contribute to further design strategies to control

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greenhouse gas emissions from agricultural soils or wastewater treatment systems.

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Key words: denitrification, nitrous oxide, metabolomics, metabolic network, electron

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equivalent distribution, carbon oxidation


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Introduction

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Microbial denitrification in natural and engineered ecosystems accounts for 40% to

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85% of global nitrous oxide (N2O) emissions.1-3 This is of significant concern as N2O

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participates in atmospheric ozone-layer depletion and has a global warming potential 300 fold

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greater than carbon dioxide.4-6 Denitrification involves enzymatic reduction of nitrate (NO3-)

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or nitrite (NO2-) to di-nitrogen gas (N2) through sequential production of the intermediary

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compounds nitric oxide (NO) and nitrous oxide (N2O).7-9 N2O accumulation and emission

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occurs under specific environmental conditions that lead to incomplete denitrification by

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microrganisms.3,10

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Among several biotic and abiotic factors influencing N2O production by biological

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systems, NO2- accumulation and carbon substrate limitation are conditions commonly

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associated with N2O emissions during denitrification. Such conditions can be created by

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seasonal variations in C and N loading in agricultural soils or created in specific process

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configurations such as shortcut nitrification or biological phosphorus removal in wastewater

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treatment systems.10,11 Nitrite, as free nitrous acid (HNO2 or FNA), can result in cell death,

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retarding growth, reducing cellular respiration, and inhibiting NO3- and N2O reduction

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enzymes.12 Carbon substrate limitation results in lowering the production of electron

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equivalents required for the complete reduction of nitrogen oxides (NOx).13 N2O

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accumulation has however also been observed when the carbon substrate is available in

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abundance14,15 and when nitrite accumulation does not occur.11,14 The concentrations of

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carbon and nitrogen substrates in the extracellular environment may not necessarily reflect

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the internal C:N balance in the cell. In this study we investigate the hypothesis that

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intracellular C:N ratio governs N2O accumulation by affecting carbon oxidation and nitrogen

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reduction pathways.

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N2O accumulation during denitrification is intrinsically linked to intracellular carbon

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and nitrogen balance as the carbon oxidation pathways (glycolysis, tricarboxylic acid (TCA)

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cycle and lipid metabolism) provide the electrons equivalents required by denitrifying

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enzymes to reduce N oxides.7,16,17 Independently to denitrification enzymes co-occurrence

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and kinetics, accumulation of N2O occurs when the generated electron equivalents are

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insufficient to completely reduce intracellular NO3- or NO2- to N2. This balance can be

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disturbed via either a decrease in the production rate of electron equivalents or an increase in

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reducible N oxides. The amount and degradability of intracellular carbon affects the rate of

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production of electron equivalents.14,18,19 For example, oxidation of intracellular carbon



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storage compounds (i.e. poly-β-hydroxybutyrate (PHB)) have been shown to influence the

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rate of electron equivalent generation and N2O accumulation.20-23 The consumption of

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electron equivalents is governed by the type and amount of nitrogen oxide. For example,

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NO3- concentration governs the overall denitrification rate, but NO2- and FNA can lower

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NO3- metabolism and increase N2O accumulation by inhibiting N2O reductase (Nos) in a dose

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dependent manner.12,24 An investigation into the interactions between multiple carbon

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oxidation pathways and nitrite reduction has not been previously reported.

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The carbon oxidation and nitrogen reduction pathways are linked via numerous

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metabolites.25 In this study we examine how N2O accumulation during denitrification is

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regulated by these metabolites as well as the reactions that produce or consume them.

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Specifically, we investigate the effect of NO2- addition and organic carbon limitation on N2O

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accumulation by monitoring changes in ~60 intermediate metabolites of the microbial central

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carbon metabolism. Previous studies have investigated the influence of genetic diversity26,27

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and regulation13,15,16 of Nos on N2O accumulation. We focus on the actual metabolic

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phenotype of denitrifying cultures during N2O accumulation, instead of their genomic

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potential. We quantify metabolites using GC-MS metabolomics and model the rates of their

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oxidation and the transfer of electron-equivalents in the respiratory chains (e.g., via NADH,

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lactate, succinate, FADH2, glycerol-P and glycolate) using a genome-informed stoichiometric

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metabolic network (SMN) model. We influence the production and consumption of electron

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equivalents in denitrifying cultures by altering the COD:N ratio in growth medium and

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spiking with nitrite (NO2-) to create conditions that have been reported to yield significant

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N2O accumulation.15,28,29

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Materials and Methods

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Denitrification batch experiments Experiments with batch cultures of denitrifying sludge were conducted in bioreactors

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of 3 L of working volume to test four experimental conditions: two growth mediums with

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different ratios of carbon-to-nitrogen sources, with and without nitrite spiking of 28 mg of

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nitrogen (2 mmol-N) per liter of culture. The two initial COD:N ratios tested were 11:1 and

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4:1 (where the carbon source is referenced as COD (chemical oxygen demand)). These ratios

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were selected to mimic abundant and limited availability of carbon respectively, as described

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in the Supporting Information (SI) document. Nitrite spiking was performed by adding 5 mL

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of a 1.2 M NaNO2 solution when NO3- reduction reached a steady state; this occurred after ~1


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and ~30 hours of cultivation respectively in experiments with COD:N 11:1 or 4:1 mediums.

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NO2- spike concentration was selected, as described in the SI, to partially inhibit N2O

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reduction. The non-spiked cultures were considered as controls. Each condition was tested in

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triplicate by independently running three batch reactors. The reactors were inoculated with

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returning activated sludge (RAS) from a 30 million liter activated sludge reactor. As

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described in the SI, this parental reactor had an SRT of 17 days and treated municipal

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wastewater with average ammonium and COD concentrations of ~60 and ~400 mg-N L-1

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respectively. To obtain the inoculant, 300 mL of sludge was twice washed with autoclaved

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tap water and then diluted to achieve a volatile suspended solids (VSS) content of 1.3±0.2 g

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L-1. Sludge was acclimatized to experimental conditions to avoid N2O production upon

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reactor start-up and to preconditions the internal state of cells to the tested COD:N ratios.

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Acclimation was conducted in the 3 L reactors over four batch cultivation cycles as described

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in the SI. The batch experiments were initiated in the fifth cultivation cycle by adding 0.3 L

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of concentrated phosphate buffer to 2.7 L of the acclimatized sludge. The concentrated

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phosphate buffer consisted of NaNO3 (3 g L-1), NaOH (40 g L-1), KH2PO4 (13.7 g L-1),

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FeSO4-7H2O (0.02 g L-1) and commercial milk powder (0.1 g L-1) to provide micronutrients.

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Sodium acetate served as a carbon source, and was added at concentrations of 0.7 g L-1 or

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0.25 g L-1 of culture to obtain soluble COD (sCOD) of 541 or 196 mg-O2 L-1 depending on

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the tested COD:N ratio. The resulting initial conditions in the growth medium were a nitrate

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(NO3--N) concentration of 49±3 mg-N L-1 (3.5±0.2 mmol-N L-1), VSS of 1±0.13 g L-1, pH of

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7.5±0.1 and COD:N ratios of 11:1 or 4:1. Cultures were mixed with magnetic stirrers at room

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temperature (22 to 25ºC) until NO3- depletion stopped.

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Chemical analyses Denitrifying cultures were monitored using a combination of online and offline

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methods. Dissolved N2O and NO2- concentrations were respectively measured in real time

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using Clark-type N2O-R and NOx--bio microsensors connected to a v2.01microsensor

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multimeter (Unisense, Aarhus, Denmark). Prior to all measurements, the N2O Clark type

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sensors were pre-activated, pre-polarized and calibrated according to manufacturer

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specifications as described in the SI. Obtained N2O data was further corrected due to

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temperature fluctuations30 (SI). NO3-concentration was measured offline in 10 mL culture

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samples using an ion selective electrode (IntelliCAL ISENO318101, Hach Company, USA).

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The 10 mL samples were also analyzed for TSS, VSS (total and volatile suspended solids)

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and sCOD in accordance with the Standard Methods for the Examination of Water and



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Wastewater.31 Microbial biomass concentration was estimated as soluble protein using the

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Bradford colorimetric assay32 in microplate format. All offline measurements were performed

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in triplicate by analyzing three independent samples.

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Metabolite profiling The relative abundance of intracellular metabolites in the bacterial cells of the mixed

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culture was measured following our in house protocol.33 After NO3- depletion with time

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became linear, a 30 mL sample was taken from each bioreactor and immediately vacuum

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filtered using a 0.45 µm pore-size cellulose acetate filter. The biomass retained on the filter

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paper was quenched by rapidly washing it with 10 mL of cold saline solution (0.9 % (wt/vol)

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NaCl at 4 ºC). 110 milligrams of the washed biomass (equivalent to 30±1.6 mg dry weight in

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20 samples previously weighted, dried and re-weighted) were placed in a 15 mL pre-weighed

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centrifuge tube containing 2.5 mL of cold methanol-water solution (1:1 (vol/vol)) at -20 ºC.

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An internal standard 2,3,3,3-d4-alanine at a concentration of 0.5 µmol/mL was added and the

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samples were stored at -80 ºC until further processing. After 4 weeks the intracellular

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metabolites were extracted by subjecting the stored biomass to freeze-thaw cycles as we

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previously described.33 The cell debris collected after metabolite extraction was dried using a

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domestic microwave (250 W for 20 min) and weighed to measure the total biomass content

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(dry weight) of each sample. The extracts were concentrated by adding 10 mL of cold (4 ºC)

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bi-distilled water, freezing the diluted extracts to -80 ºC and then freeze-drying them. The

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freeze-dried samples were re-suspended in 200 µL NaOH (1 N) and then derivatized using

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methyl chloroformate (MCF).33 The MCF derivatives were analyzed using a GC-MS system

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(Agilent GC7890 coupled to a MSD597 unit) equipped with a ZB-1701 GC-capillary column

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(30 m × 250 µm (id) × 0.15 µm film thickness) with a 5 m guard column (Phenomenex,

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Torrance, USA) and operated as we previously described.33 To provide statistical robustness

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to data, six biomass samples were analyzed for each of the four experimental conditions (i.e.

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each condition was tested in three separate cultures, each culture sampled in duplicate).

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Metabolite data mining, normalization and analysis The metabolites were identified by deconvoluting GC-MS chromatograms with

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AMDIS software (NIST, Boulder, CO, USA) and comparing the obtained mass spectrums to

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the in-house MCF MS library as detailed previously.33 Metabolite identification was based on

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the MS spectrum of the derivatized metabolites as well as their chromatographic retention

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times. The relative abundance of identified metabolites was determined with the ChemStation


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software (Agilent Technologies, Santa Clara, USA), using the GC base-peak value of the

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selected reference ion for each metabolite.33 Metabolites detected in only one sample were

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excluded from the analysis. The relative abundance values were normalized (divided) by the

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biomass content of the sample and then by the abundance of the internal standard 2,3,3,3-d4-

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alanine. Finally the normalized values were auto-scaled using the formula S1 of the SI to

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obtain relative abundances of all metabolites on the same scale (from -1 to 1).34 The auto-

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scaled values are denoted as where is the relative abundance of metabolite in sample .

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The statistical differences between metabolite profiles of samples were assessed using Partial

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Least Squares-Discriminant Analysis (PLS-DA). Analysis of variance (ANOVA) was

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performed to determine if relative abundances of the identified metabolites were significantly

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different among samples. Both PLS-DA and ANOVA were performed using the R software35

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as described in the SI. The Pathway Activity Profiling (PAPi) algorithm36 was used to predict and compare

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the relative activity of metabolic pathways given the observed profile of metabolites in

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biomass samples. The PAPi program connects to the KEGG online database

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(http://www.kegg.com) and predicts the metabolic pathway that is likely to be active by

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developing a pathway Activity Score (SA) using the number of identified metabolites and

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their relative abundances in each sample.36 The PAPi analysis was performed for each of the

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24 generated profiles of metabolites and the resulting SA scores for each pathway in each

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experimental condition were averaged (n = 6). The entire data mining, data normalization and

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pathway activity predictions were automated in R software as described previously.33,36

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Graphical representations of the results were generated using gplots and ggplot2 packages in

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R.37

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Genome based metabolic model A genome-informed stoichiometric metabolic network (SMN) model of denitrifiers

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metabolism was developed to estimate the flux of metabolites through the multiple carbon

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oxidation and nitrogen respiration reactions in the biomass. To capture the diversity of

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electron carrier metabolites in denitrification respiratory pathways, the model lumped

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metabolic reactions occurring in the bacterial species Acidovorax ebreus, Azoarcus sp.

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KH32C, Paracoccus denitrificans and Pseudomonas aeruginosa. These are all well-studied

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model denitrifying microbes38 commonly detected in full-scale and laboratory denitrifying

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activated sludge systems.39,40 However, the microbial population in the bioreactors’ biomass



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was not directly characterized in this study. The model was developed using the procedure

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developed by Thiele and Palsson.41 Briefly, literature and the online genomic-biochemical

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databases KEGG (http://www.genome.jp/kegg/), NCBI (http://www.ncbi.nlm.nih.gov/) and

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MetaCyc (http://metacyc.org/) were used to obtain stoichiometric equations of biochemical

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reactions reported to occur in the modeled microbial species and participating in the

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following pathways: (i) assimilation (oxidation) of carbon sources (i.e. acetate, ethanol,

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glucose, C2 to C4 organic acids and common amino acids); (ii) nitrogen respiration and

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oxidative phosphorylation; (iii) synthesis of the 20 common amino acids; and (iv) the

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reduction/oxidation of saturated fatty acids, unsaturated fatty acids, glycerolipids and

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phosphoglycerolipids. Reaction equations of the four microbial species were compiled into a

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single list of equations to assemble a lumped-network as previously described.42 The

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complete model contained 480 metabolic reactions involving 351 metabolites (listed in Table

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S-2 of SI). Assimilation pathways of single carbon compounds (e.g. methanol, methane) were

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not included as acetate was the model carbon source used in the experiments.

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Metabolic flux estimation Intracellular metabolic fluxes (or reaction rates) were estimated by running flux

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balance analyses (FBA43,44 – algorithm description provided in the SI) in the SMN model as

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follows. All model analyses were done using the COBRA toolbox v245 and the GLPK solver

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(GNU project, Moscow, Russia) in Matlab® 7 R2010b (The Mathworks Inc, Massachusetts,

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USA). FBA simulations were performed using biomass production maximization as objective

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function and the substrate consumption rates measured in experimental cultures together with

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the SA scores obtained from the PAPi analysis as model input data (constraints). This was

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done following 3 steps: (i) The fold change of SA scores between control and NO2- spiked

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conditions at the same COD:N ratio was calculated for each metabolic pathway using the

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formula

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calculated for the control condition via FBA. FBA was performed suing the control cultures’

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nitrate and acetate consumption rates (expressed as mmol gVSS-1 h-1) as model input values

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(constraints). Uptake rates of carbon substrates apart from acetate were set to zero while the

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rates of intracellular metabolic reactions were set as unconstrained ( = ∞); (iii) new

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constraints were calculated for the NO2- spiked condition ( ) using the formula

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= ∗

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condition ( ) were obtained via FBA by setting the constraints

= ; (ii) a set of metabolic fluxes ( ) was

; and (iv) finally, the metabolic fluxes of the NO2- spiked


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calculated in the previous step together with the nitrate and acetate consumption rates

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measured in the NO2- spiked cultures. Model accuracy was measured using absolute percent

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errors between model-predicted and experimental rates of N2O, NO3-, NO2-, and acetate

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consumption/production.46

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Results

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Effect of COD:N ratio and NO2- spikes on N2O accumulation Carbon limitation and nitrite exposure influenced the rate and magnitude of N2O

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accumulation of denitrifying batch cultures (Figure 1). The controls (not spiked with NO2-)

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for COD:N 11:1 and COD:N 4:1 showed no N2O accumulation. The consumption rates of

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NO3- and sCOD were much higher for COD:N 11:1 in comparison to COD:N 4:1. The

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COD:N = 11:1 cultures consumed the initial NO3- concentration of 50 mg-N L-1 (3.5 mmol-N

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L-1) within 2.5 hours at a rate of 1.73±0.08 mmol-N gVSS-1 h-1 (Figure 1A), while the 4:1

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cultures only consumed half the available NO3- (~1.9 mmol-N L-1) over a prolonged duration

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of 96 hours at a rate of 0.11±0.022 mmol-N gVSS-1 h-1 (Figure 1B). Similarly, the sCOD

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consumption rate was much higher for COD:N 11:1 (37.9±5.1 mmol-O2 gVSS-1 h-1) than

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for COD:N 4:1 (2.7±0.23 mmol-O2 gVSS-1 h-1). Nitrite spikes generated a slight increase of

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sCOD in initial COD:N 4:1 cultures, possibly due to lysis of carbon starved cells. The

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biomass concentration in all tested conditions (measured as VSS and soluble protein) did not

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vary significantly (according to ANOVA test at α=0.05) over the duration of the experiments,

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indicating that differences in denitrification activity are only from differences in available

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carbon.

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Exposure to NO2- resulted in significant changes in denitrification performance and

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N2O accumulation (Figure 1 and Table 1). While N2O accumulation commenced immediately

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upon the addition of 28 mg-N L-1 NO2- (which yielded ~2.15-2.3 µg L-1 of HNO2-N at pH 7.5

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and 22 to 25°C), the magnitude and duration of accumulation was substantially influenced by

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the COD:N ratio. Nitrite-spiked cultures with COD:N 11:1 produced only 0.54±0.11 mmol

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N2O-N (representing 3.3±0.5 % of the total nitrogen added to the culture or 5.9±0.88 % of the

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denitrified NO3--N) at a rate of 0.14±0.002 mmol-N gVSS-1 h-1 (Figure 1C), while cultures

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with COD:N 4:1 produced a large amount of N2O (1.41±0.27 mmol of N2O-N representing

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8.5±0.9 % of the total nitrogen added or 20.4±2.6 % of denitrified NO3--N) although at a low

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formation rate (0.023±0.007mmol-N gVSS-1 h-1) (Figure 1C). N2O consumption started only



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after NO2- exhaustion. NO2- spiking caused a drop in the acetate and NO3- removal rates,

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indicating a preferential reduction of NO2- over NO3-.

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COD:N ratio and NO2- addition redistribute pools of C & N storage metabolites

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A total of 53 intracellular metabolites were identified in 24 biomass samples (4

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experimental conditions each analyzed using 6 replicate samples), of which: five are

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tricarboxylic acid cycle (TCA) intermediates, fourteen are common amino acids, twenty are

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fatty acids (thirteen saturated and seven unsaturated), four are di-carboxylic organic acids,

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and ten are intermediates of amino acid metabolism. The complete list of identified

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metabolites is presented in Table S-1 of SI. The majority of the identified compounds are

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primary metabolites. Hydroxybutyric acid, the building block of PHB, was detected in only

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one sample, and therefore disregarded from the analysis. Of the 53 metabolites identified, 14

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had relative abundances without significant statistical difference among the four experimental

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conditions (α > 0.05, Table S-1 of SI), indicating activation of metabolic pathways common

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to all experimental conditions as explained in the discussion section.

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The relative abundances of intracellular metabolites were affected by the COD:N ratio

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and NO2- spikes having significant differences among the four tested conditions (Figure 2A).

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In general the relative abundances of metabolites in biomass samples from COD:N 4:1

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cultures were significantly lower than those from COD:N 11:1 cultures (Figure 2B), even

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though all biomass samples had the same dry weight (30 ± 1.6 mg).

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The initial COD:N ratios significantly changed the abundance of 39 metabolites

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(according to ANOVA tests at α = 0.05). Primary metabolites, i.e. TCA cycle intermediates,

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common amino acids and saturated and unsaturated fatty acids were abundant in COD:N11:1

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cultures (Figure 2B), indicating the soluble acetate was used to build up amino and lipids ,

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and to generate electron equivalents through TCA activation. Conversely, the cultures on

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COD:N 4:1 medium were acetate starved and did not accumulate large pools of amino and

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fatty acids (negative ). This famine condition generated low NO3- and acetate consumption

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rates which is consistent with the scarcity of TCA intermediates generating electron-

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equivalents.

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Nitrite spikes influenced the abundance of specific groups of metabolites depending

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on the metabolic state of cells determined by the initial COD:N ratio. COD:N 11:1 NO2-

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spiked cultures had higher relative abundance of TCA cycle intermediates and all amino

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acids (except serine, aspartic acid and glutamic acid) compared with the non-spike COD:N 11

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control (Figure 2C). At COD:N 4:1 the relative abundance of TCA intermediate and amino


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acids of control and NO2- spiked cultures were similar. However, long chain-saturated fatty

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acids (i.e. C8 to C20 fatty acids), were significantly lower in cultures spiked with NO2-

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(Figure 2C), indicating depletion of inner carbon and energy storage compounds in response

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to NO2- addition.

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NO2- addition affects different metabolic pathways depending on initial COD:N ratio The activity of 36 metabolic pathways was estimated on basis of the observed profiles

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of metabolites using the PAPi analysis. Results indicate higher Activity Score (SA) per unit

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biomass in metabolic pathways of cells in COD:N 11:1 cultures in comparison to those in

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COD:N 4:1 (Figure S-2). As with the observed metabolite profiles the predicted SA scores

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indicate that biosynthetic pathways were down-regulated in COD:N 4:1 cultures, which is not

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surprising given the lack of environmental carbon source. Nevertheless the addition of NO2-

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generated specific responses in pathways activities depending on the COD:N ratio. For

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instance, Figure 3 shows the change of pathway activity of cells in NO2- spiked cultures in

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comparison to that of control cultures with the same initial COD:N ratio. In COD:N 11:1

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cultures, NO2- addition increased the metabolic activity of “pyruvate metabolism”,

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“glycolysis/gluconeogenesis” and “TCA cycle” pathways, while in the COD:N 4:1 cultures

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the metabolic activity of “fatty acids biosynthesis” decreased but “fatty acids degradation”

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increased (Figure 3).

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Metabolic response to NO2- addition modulates N2O accumulation

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FBA simulations of the SMN model lumping biochemical reactions from four

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denitrifying species provided estimates of metabolic fluxes in the many reactions occurring in

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external and internal carbon oxidation and nitrogen reduction in the cultures. The

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denitrification pathway is captured as four sequential reactions which are independent of the

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quantity and co-occurrence of genes encoding for Nap, Nir, Nor and Nor enzymes present in

326

the microbial population. The fluxes are a snapshot quantification of the metabolic rates

327

occurring in cultures’ biomass at the moment of maximum N2O productivity (after NO2-

328

addition). Figure 4 presents a comparison of the metabolic fluxes estimated for the biomass in

329

the two tested COD:N ratios after NO2- spikes. The estimation of fluxes through the

330

denitrification reactions showed that NO2- addition both increased the flux of nitrogenous

331

compounds through Nir, Nor and Nos (by 30-50 %), and also inhibited the activity of Nos

332

reaction. Accordingly, the Nos flux was 93 % and 85 % respectively of the value of the Nor

333

flux for experiments in the initial COD:N ratios of 11:1 and 4:1. The model was not



Page 12 of 29

12

334

intentionally constrained to directly capture inhibition of Nos activity by NO2-/FNA spike.

335

However the difference between Nor and Nos rates found by fitting model to observed data

336

(rates of N2O, NO3-, NO2-, and acetate consumption/production) strongly suggest FNA

337

inhibition of Nos. Further, estimated rates show equal flux among Nir and Nor reactions in

338

both scenarios (COD:N of 11:1 and 4:1) and therefore no nitric oxide accumulation, which is

339

consistent with similar denitrification experiments.47,13

340

As shown in Figure 4, cells of cultures on COD:N = 11:1 rapidly assimilated acetate

341

and nitrate (at rates of 0.59±0.08 mmol-acetate gVSS-1 h-1 and 1.73±0.08 mmol-N gVSS-1 h-

342

1

343

serine and threonine) and C11 to C21 saturated fatty acid synthesis at rates ranging between

344

0.1 to 1 mmol-N gVSS-1 h-1. The central carbon pathway was active and, by reducing

345

ubiquinone-8 (UQ8) to ubiquinol-8 (UQ8H2), delivered electron equivalents to the

346

denitrifying electron transport chain via succinate, NADH and FADH2, at rates of 1.41, 3.5

347

and 0.06 mmol gVSS-1 h-1, respectively. None of our results supported the utilization of

348

lactate, glycerol-P or glycolate as electron donors for denitrification. In contrast, cells

349

growing in COD:N 4:1 medium responded to NO2-/FNA excess by consuming acetate and

350

nitrate slowly (respectively 0.038±0.004 mmol-acetate gVSS-1 h-1 and 0.11±0.022 mmol-N

351

gVSS-1 h-1) and depleting C17-C21 fatty acid instead of sCOD in growth medium (Figure

352

1B). β-oxidation of these fatty acids generated electron equivalents in the form of NADH and

353

FADH2 which further reduced UQ8 to UQ8H2 at rates of 0.17 and 0.14 mmol gVSS-1 h-1

354

respectively (Figure 4B). On the basis of NO3- and NO2- consumption rates, the contribution

355

of these compounds to N2O formation was estimated to be 77 % and 22 % respectively in

356

cultures for an initial COD:N of 11:1. In cultures with an initial COD:N of 4, the nitrite

357

contribution increased to 35 %, possibly due to partial inhibition of nitrite reductases

358

(Nar/Nap) by FNA.

) and actively synthesized amino acids (valine, leucine, isoleucine, arginine, proline, glycine,

359 360

Discussion

361 362

Synergistic effect between carbon limitation and nitrite accumulation on N2O

363

production

364

The reactor performance shows that carbon limitation and NO2- shock have a

365

synergistic effect on N2O accumulation. Based on our results, we inferred Nos inhibition by

366

NO2- (or FNA) triggered N2O accumulation in both non-limiting and limiting carbon


Page 13 of 29


13

367

conditions. However carbon availability determined the duration and amplitude of N2O

368

accumulation.

369

The additional N from the NO2- spike increased the rates of Nir, Nor and Nos

370

reactions. However, the increase in Nos was less than that for Nir and Nor resulting in the

371

N2O accumulation. While it is not possible to corroborate the cause of these different rates of

372

increase from the model results, nitrite, in the form of FNA has been shown to partially

373

inhibit Nos activity at the applied concentration range (2.15-2.33 µg L-1 at experimental pH

374

and temperature).24 Further, the NO2- shock treatments exhibited traits typical of FNA

375

inhibition48,49 namely reduction in the rate of NO3- and SCOD removal and cell lysis (Figures

376

1A & 1B).

377

Carbon limitation may also have a compounding as well as synergistic role in N2O

378

accumulation. Firstly, Nar and Nir have shown a higher affinity for electron equivalents

379

(produced through methanol oxidation) than Nor or Nos.15 The low rate of electron

380

equivalent production at a high NO2- concentration should then result in the preferential

381

distribution of the limited available electron equivalents away from Nos, thereby

382

compounding the already inhibitory effect resulting from the NO2- concentrations alone.

383

Secondly, when N2O accumulation was observed, the COD:N ratios in the 11:1 and 4:1

384

cultures were ~2.44:1 and ~1.27:1 respectively. Low COD:N ratios between 4:1 to 1:1 have

385

previously been reported to induce N2O accumulation.15,28 However, at the moment of N2O

386

accumulation, the internal carbon (metabolites) of COD:N 11:1 NO2- spiked cultures

387

remained replete. This indicates the cell had sufficient carbon for the reduction of the

388

additional N introduced. This precludes the possibility of carbon limitation as the cause of the

389

N2O accumulation, and further stresses the importance of internal C:N ratio compared to

390

external COD:N ratio. In contrast, the combined effect of carbon limitation and NO2-

391

mediated inhibition of Nos accounted for the protracted N2O accumulation within the COD:N

392

4:1 cultures. Our results, and those from previous studies14,18,19 suggest that reliance on

393

internal carbon stores as a result of carbon limitation results in a lower rate of electron

394

equivalence production. Thus Nos inhibition by NO2- leads to N2O accumulation, while

395

carbon limitation results in a slower metabolic rate to clear the NO2-, leading to an extended

396

period of Nos inhibition and higher N2O accumulation. In principle, the mechanism described

397

above would be the same if different carbon sources such as ethanol, methanol or complex

398

mixtures were used. However different carbon sources provide different yields and rates of

399

electron equivalent generation.13,18 Therefore the proposed mechanism would result in

400

different durations and amplitudes of N2O accumulation curves.



Page 14 of 29

14

401 402 403

Modulation of denitrification activity by primary metabolites Metabolite profile results indicate that NO2- addition systemically affects the routes of

404

electron equivalent generation depending on the metabolic state of denitrifying cells, which

405

in this case was determined by acetate availability. NO2-/FNA toxicity is known to inactivate

406

electron carrier/generation enzymes.50 This phenomenon might have had an influence on the

407

observed profiles of metabolites and N2O accumulation. Indeed, nitrite addition induced N2O

408

accumulation in both conditions – carbon-substrate limited and feasted cultures (i.e., initial

409

COD:N = 4:1 and 11:1). But carbon limited cultures could not overcome NO2- toxicity and

410

the drop on COD:N ratio, therefore establishing a continuous N2O accumulation due to a lack

411

of electron equivalents to completely reduce the N2O to N2. According to our metabolite

412

results, the electron equivalents available for NO3- and NO2- reduction to N2 in COD:N 4:1

413

cultures would, need to be generated through oxidation (endogenous respiration) of C11 to

414

C21 saturated fatty acids. This is consistent with the null decrease of sCOD observed after the

415

NO2- spike in these cultures (Figure 1B). In COD:N 11:1 cultures, electron equivalents were

416

primarily produced through oxidation of extracellular acetate (sCOD curve in Figure 1A) and

417

subsequently TCA intermediates, and then dissipated via denitrification as well amino and

418

fatty acid synthesis. Metabolite profiles also show the constant presence of metabolites in all

419

tested conditions. These ubiquitous metabolites mediate cellular functions such as: redox

420

signaling (benzoic and pyroglutamic acid),51,52 nitrogen storage (putrescine, histidine),53

421

homolactic fermentation (lactic acid),54 and ω-oxidation of fatty acids (levulinic, pimelic,

422

suberic and azelaic di-carboxylic acids).55,56 Given the function of these compounds on

423

microbial metabolism, they potentially supported intracellular redox adjustments in cultures

424

biomass.

425

Pathway activity results of carbon abundant conditions indicates high activity in the

426

central carbon pathways and delivery of electrons for nitrogen reduction via succinate,

427

NADH and lactate oxidation. Also in this condition, “phenylalanine, valine and leucine

428

metabolism” was up-regulated. Dehydrogenase enzymes specific to such amino acids

429

incorporate inorganic nitrogen into organic compounds, which suggests an active NO3-

430

assimilation into biomass when carbon is abundant. This involves a depletion of storage

431

intracellular fatty acids through endogenous carbon respiration for ATP generation.

432

Additionally, the pathways “arginine and proline metabolism” and “glutathione metabolism”

433

obtained significantly high SA scores on COD:N 11 cultures (Figure S-2). Arginine and

434

glutathione are known to play a key role in the metabolic adaptation of bacteria cells to


Page 15 of 29


15

435

oxidative stress induced by NO2- and reactive oxygen species,52,57 which would explain why

436

cultures on COD:N 11 medium were less perturbed after NO2- spikes.

437

The fluxes are a snapshot quantification of the metabolic rates occurring in cultures’

438

biomass at the moment of maximum N2O productivity (after NO2- addition). Fluxes presented

439

in Figure 4 illustrate that cells in COD:N 11:1 cultures responded to NO2-/FNA excess by

440

increasing the delivery of electrons to nitrogen reduction reactions NADH and succinate

441

generated via the TCA cycle, and increasing the synthesis of amino acids; while cells in

442

COD:N 4:1 responded by generating electron-equivalents through endogenous respiration of

443

small (C6-C10) and long (C11 to C21) chain saturated fatty acids via β-oxidation. Because

444

oxidation of intracellular fatty acid is slower than that for soluble acetate,58 electron

445

equivalents were continuously delivered to nitrogen reduction reactions at a low rate for a

446

prolonged period of time (~48 h). This state of ‘chronic’ electron equivalent scarcity, together

447

with inhibition of Nos by NO2-/FNA, propitiated a slow but steady incomplete reduction of

448

NOx to N2, resulting in N2O to be formed at a low rate (0.023±0.006 mmol-N gVSS-1 h-1),

449

which eventually accumulated to concentration as high as 0.45±0.045 mmol-N L-1. In

450

comparison ‘chronic’ electron scarcity did not occur in cells in cultures with abundant acetate

451

(COD:N ratio 11:1). N2O production in these cultures was quick (at a rate of 0.14±0.002

452

mmol-N gVSS-1 h-1) but transient (active production spammed a window of 1 hour), yielding

453

a maximum accumulation of 0.13±0.02 mmol-N L-1. Denitrification gene diversity was not

454

studied herein. However genomes of several denitrifying microbes commonly found in

455

wastewater, including those species used as reference to develop our lumped SMN model,

456

encode the Nos gene (nosZ) clade I, which is associated to a high N2O emission potential.27

457

Metabolome and physiological data revealed that denitrifying bacteria respond to

458

nitrite additions by decreasing C and N uptakes and increasing/decreasing pools and fluxes of

459

metabolites in specific metabolic pathways in order to maintaining the intracellular C:N

460

balance. Identity of readjusted pathways depends on the metabolic state of cells determined

461

by environment’s carbon availability. While the abundance of metabolites involved in

462

nitrogen storage (putrescine, histidine) and oxidative stress regulation (benzoic and

463

pyroglutamic acid) and ω-oxidation of fatty acids (levulinic, pimelic, suberic and azelaic di-

464

carboxylic acids) remained constant in all tested conditions, fluctuations in COD:N ratio and

465

NO2- significantly affect N2O accumulation and the abundance of metabolites involved in the

466

TCA cycle, biomass synthesis (amino acids) and carbon & energy storage (C11-C21

467

saturated fatty acids). This reveals two properties of the metabolic response of cells in

468

denitrifying cultures: the presence of peripheral functions (not associated to central



Page 16 of 29

16

469

catabolism) which are independent to environmental fluctuations; and the presence of flexible

470

functions (i.e. electron equivalent generation, carbon storage) that adapt in response to

471

changing conditions.

472 473 474

Practical implications of findings While previous studies have reported an influence of environmental carbon and nitrite

475

fluctuations in N2O production by denitrifying cultures,13,28,29 here we show that changes in

476

pools of primary metabolites influence the amount and rate of N2O accumulation under such

477

conditions. The metabolic state determined by carbon source availability and type predispose

478

the response of denitrifying cultures to NO2- fluctuations. When exposed to NO2- addition,

479

denitrifying cultures operating at low COD:N ratios (< 4:1) produce more N2O, and for

480

longer periods of time, than cultures operating at high COD:N ratios (> 4:1). These findings

481

indicate that conditions such as low COD:N ratios, long periods of carbon starvation (famine)

482

or utilization of hard to degrade organics (e.g. fats, proteins, complex carbohydrates, oil

483

derivatives and ligno-cellulosic material) as carbon sources increase the susceptibility of

484

denitrifying systems to accumulating and emitting nitrous oxide. In wastewater treatment

485

plants, these conditions can be avoided by supplying influent at various points in large

486

bioreactors to ensure a constant and homogenous delivery of carbon or by coordinating

487

carbon supplementation schedules with diurnal and weekly peaks of nitrogen in influent. In

488

agricultural soils, compost supply can provide carbon while cattle rotation in paddocks can be

489

used to avoid focal urine deposition, which decreases soil C:N ratios.

490 491

Acknowledgements

492 493

Dr. Ting-Li Han assisted with sample preparation and metabolic data analysis. Dr

494

Diana Spratt Casas assisted with editing of initial draft of the manuscript. OP-G was

495

supported by scholarships from The University of Auckland (No. 1523727) and The Mexican

496

National Council for Science and Technology (No. 214239) during his doctoral studies.

1

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(52) Masip, L.; Veeravalli, K.; Georgiou, G. The many faces of glutathione in bacteria. Antioxid. Redox Signal. 2006, 8 (5-6), 753-762; DOI 10.1089/ars.2006.8.753.


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(53) Schneider, B.L.; Hernandez, V.J.; Reitzer, L. Putrescine catabolism is a metabolic response to several stresses in Escherichia coli. Mol. Microbiol. 2013, 88 (3), 537-550; DOI 10.1111/mmi.12207.

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(54) Romero-Garcia, S.; Hernández-Bustos, C.; Merino, E.; Gosset, G.; Martinez, A. Homolactic fermentation from glucose and cellobiose using Bacillus subtilis. Microb. Cell Fact. 2009, 8, 23. DOI 10.1186/1475-2859-8-23.

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174

Tables

175 176

Table 1. Summary of main results from denitrifying cultures producing N2O.

177

Initial COD:N = 11:1 with NO2spike

Variable

Significant Initial COD:N difference = 4:1 among with NO2treatments*(p spike values)

Total N2O-N produced (mmol-N)

0.54±0.11

1.47±0.29

0.019

Maximum N2O concentration (mmol-N L-1)

0.13±0.03

0.45±0.04

0.013

Fraction of total nitrogen accumulated as N2O-N (%)

3.3±0.57

8.5±0.9

0.028

Fraction of denitrified NO3--N accumulated as N2O-N (%)

5.9±0.92

20.4±2.6

0.01

∆sCOD/∆N before NO2- spike (mmol-O2/ mmol-N)

4.14±0.31

1.12±0.10

0.006

Approximate COD:N ratio after NO2- spike

2.44±0.13

1.27±0.38

0.04

N2O production rate (mmol-N gVSS-1 h-1)

0.14±0.002

0.023±0.006

0.005

NO3-consumption rate (mmol-N gVSS-1 h-1)

1.73±0.08

0.11±0.022

0.015

sCOD consumption rate (mmol-O2 gVSS-1 h-1) or (mmol-Acetate gVSS-1 h-1)*

37.9±5.1 0.69±0.08

2.7±0.23 0.038±0.004

0.015 0.017

5

96

Batch culture duration (h) 178

*according to t-test at α = 0.05

179 180


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181

Figures Captions

182 183

Figure 1. Concentration curves for NO3-, NO2-, N2O and sCOD in denitrifying batch cultures.

184

A) Cultures with initial COD:N ratio of 11:1. B) Cultures with initial COD:N ratio of 4:1. C)

185

Comparison of N2O accumulation curves. Arrows indicates the addition (spike) of 5 mL of a

186

1.2 M NaNO2 solution that added 2 mmol-N of NO2- per liter of culture. Grey background

187

bars indicate periods when cultures were sampled from metabolome analysis. Graphs below

188

the main concentration curves present the average±st.dev. N2O liquid phase concentration.

189 190

Figure 2. Profile of metabolites obtained from biomass samples of denitrifying cultures. A)

191

scatter plot of PLS-DA scores obtained for the analyzed 24 samples (2 technical replicates *

192

3 biological replicates * 4 tested conditions). B) Heatmap of average relative abundances of

193

intracellular metabolites in samples (n = 6). Relative abundance values below -1 or above 1

194

(bright red) indicate that the metabolite abundance in that specific condition (column) is

195

below or above the mean of that of all the samples by more than one standard deviation.

196

Values near zero (black) indicate an average relative abundance. C) Difference between the

197

relative abundance of metabolites observed in NO2- spiked and control cultures with the same

198

COD:N ratio; ∆ = − .

199 200

Figure 3. Change of activity in metabolic pathways of cells in denitrifying cultures provoked

201

by NO2- spikes. The pathway activities scores (SA) were predicted using the intracellular

202

metabolite profile data obtained using the Pathway Activity Profiling (PAPi) algorithm.

203

Predicted activities of control cultures were set to zero (solid black line). Red triangles

204

(COD:N = 11) and green circles (COD:N = 4) indicate the change of predicted SA scores for

205

NO2- spiked cultures relative to SA scores predicted for control cultures at the same COD:N

206

ratio. SA scores relative to control cultures have been plotted using a log2 scale. Positive

207

values indicate the pathways had their activity up-regulated in response to NO2-addition. Data

208

points and whiskers respectively represent average scores ± standard deviation.

209 210

Figure 4. Simplified metabolic network and predicted fluxes in biomass of NO2- spiked

211

denitrifying cultures. All the calculated intracellular rates (fluxes) are represented as arrows

212

an have mmol gVSS-1 h-1 units. Abbreviations meaning as follows: Sdh = succinate

213

dehydrogenase; Nar/Nap = nitrate reductase, Nir = nitrite reductase, Nor = nitric oxide



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214

reductase, Nos = nitrous oxide reductase, Ldh = lactate dehydrogenase; NADHdh = NADH

215

dehydrogenase; FADH2dh = FADH2 dehydrogenase G3Pdh = glycerol-3-P dehydrogenase;

216

Gox = glycolate dehydrogenase; UQ8 = ubiquinone-8 (oxidized); UQ8H2 = ubiquinol-8

217

(reduced); Cyt550 = oxidized cytochrome c550; Cyt550e = reduced cytochrome c550.


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Figure 1. Concentration curves for NO3-, NO2-, N2O and sCOD in denitrifying batch cultures. A) Cultures with initial COD:N ratio of 11:1. B) Cultures with initial COD:N ratio of 4:1. C) Comparison of N2O accumulation curves. Arrows indicates the addition (spike) of 5 mL of a 1.2 M NaNO2 solution that added 2 mmol-N of NO2- per liter of culture. Grey background bars indicate periods when cultures were sampled from metabolome analysis. Graphs below the main concentration curves present the average±st.dev. N2O liquid phase concentration. 327x470mm (96 x 96 DPI)



Figure 2. Profile of metabolites obtained from biomass samples of denitrifying cultures. A) scatter plot of PLS-DA scores obtained for the analyzed 24 samples (2 technical replicates * 3 biological replicates * 4 tested conditions). B) Heatmap of average relative abundances of intracellular metabolites in samples (n = 6). Relative abundance values below -1 or above 1 (bright red) indicate that the metabolite abundance in that specific condition (column) is below or above the mean of that of all the samples by more than one standard deviation. Values near zero (black) indicate an average relative abundance. C) Difference between the relative abundance of metabolites observed in NO2- spiked and control cultures with the same COD:N ratio; ∆x ̃=x ̃_NO2spiked-x ̃_control. 1067x586mm (96 x 96 DPI)


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Figure 3. Change of activity in metabolic pathways of cells in denitrifying cultures provoked by NO2- spikes. The pathway activities scores (SA) were predicted using the intracellular metabolite profile data obtained using the Pathway Activity Profiling (PAPi) algorithm. Predicted activities of control cultures were set to zero (solid black line). Red triangles (COD:N = 11) and green circles (COD:N = 4) indicate the change of predicted SA scores for NO2- spiked cultures relative to SA scores predicted for control cultures at the same COD:N ratio. SA scores relative to control cultures have been plotted using a log2 scale. Positive values indicate the pathways had their activity up-regulated in response to NO2-addition. Data points and whiskers respectively represent average scores ± standard deviation. 287x286mm (96 x 96 DPI)



Figure 4. Simplified metabolic network and predicted fluxes in biomass of NO2- spiked denitrifying cultures. All the calculated intracellular rates (fluxes) are represented as arrows an have mmol gVSS-1 h-1 units. Abbreviations meaning as follows: Sdh = succinate dehydrogenase; Nar/Nap = nitrate reductase, Nir = nitrite reductase, Nor = nitric oxide reductase, Nos = nitrous oxide reductase, Ldh = lactate dehydrogenase; NADHdh = NADH dehydrogenase; FADH2dh = FADH2 dehydrogenase G3Pdh = glycerol-3-P dehydrogenase; Gox = glycolate dehydrogenase; UQ8 = ubiquinone-8 (oxidized); UQ8H2 = ubiquinol-8 (reduced); Cyt550 = oxidized cytochrome c550; Cyt550e = reduced cytochrome c550. 640x356mm (96 x 96 DPI)


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TOC art 313x202mm (96 x 96 DPI)


Modulation of Nitrous Oxide (N2O) Accumulation by Primary

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