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    Microbial niche differentiation explains nitrite oxidation in marine oxygen minimum zones

    Experimental site
    Seawater samples were collected from two stations (Fig. S1a, offshore OMZ station PS2 and coastal OMZ station PS3) in the ETNP in March and April 2018 on board R/V Sally Ride (Cruise ID: SR 1805). NO2− kinetics and O2 effects experiments (≤1 day incubation) were performed at the oxycline, the oxic/anoxic interface (top) of the ODZ and the core of the ODZ at each station (Fig. S1b and Table S1). Long incubations (6–7 days) were performed at the core of the ODZ at both stations to investigate nitrogen reaction rates at very low O2 concentrations.
    Sampling and incubation experiments for NO2− kinetics and O2 effects
    Twelve 30-L Niskin bottles on a rosette with a conductivity–temperature–depth (CTD) profiler were used to collect seawater while recording in situ O2 concentration, temperature, pressure, salinity, and chlorophyll fluorescence. O2 concentration at selected ODZ depths was measured by STOX sensor (on the CTD profiler) with detection limit of 10 nM [42]. NO2− concentrations were measured by standard spectrophotometric methods onboard. O2 and NO2− concentrations were used to select sampling depths. NO3− and NO2− concentrations in incubation samples were measured on a chemiluminescence NO/NOx Analyzer (Teledyne API, San Diego, CA, USA) in the lab.
    Seawater was collected from Niskin bottles into 60 mL air-tight serum bottles after overflowing three times in order to minimize O2 contamination. Serum bottles were sealed with rubber septa and aluminum seals ensuring the absence of bubbles inside bottles. Septa were deoxygenated in anaerobic chambers with three cycles of vacuum/helium flushing over a period of 1 month prior to the cruise. A helium headspace was created for each sample collected from anoxic depths (the top and the core of the ODZ), and then samples were flushed with helium for at least 15 min to remove O2 that might have been introduced during sampling.
    To determine a single NO2− oxidation rate, a set of five serum bottles amended with 15NO2− tracer was incubated on board at 12 °C in the dark. Incubations were terminated in time series (one bottle at day zero (T0), two at 0.5 day and two at 1 day) by adding 0.2 mL of saturated ZnCl2. The T0 bottles served as killed controls for both tracer contamination and abiotic reactions. The observed temporal changes in isotopic signals that occurred in the live samples over a few days in the time courses would not be detected if abiotic reactions were taking place during the >3 months that elapsed before all samples were measured on the mass spec.
    In the lab, NO2− was removed from samples using sulfamic acid, and NO3− in serum bottles was converted into N2O using the denitrifier method [43, 44]. Both concentration and isotopic composition of N2O were measured on a mass spectrometer (Delta Vplus, Thermo Fisher Scientific, Waltham, MA, USA) for calculating nitrite oxidation rate from the linear regression of the five nitrate concentrations at the three time points as previously described [3]. NO2− kinetics of NO2− oxidation were determined by measuring NO2− oxidation rates under different 15NO2− tracer concentrations (0.5–13.8 μM). For responses of NO2− oxidation to O2, different amounts (0, 0.2, 0.5, 1, 2, and 5 mL) of O2 saturated seawater collected from the same Niskin bottle were added into serum bottles to achieve different O2 concentrations. O2 concentrations in serum bottles were monitored by optical oxygen sensors with a detection limit of 62.5 nM (PyroScience GmbH, Aachen, Germany).
    Half-saturation constant
    Half-saturation constant (Km) is the nitrite concentration at which nitrite oxidation rate (V) equals half of the potential maximum rate (Vm). The curve fitting tool in MATLAB_R2015a was used to fit the Michaelis–Menten model (Eq. (2)) to determine Km.

    $${{V}} ,=, {{V}}_{mathrm{m}} ,times,left[ {{mathrm{NO}}_2^-} right]{mathrm{/}}left( {left[ {{mathrm{NO}}_2^-} right] ,+, {{K}}_{mathrm{m}}} right).$$
    ( 2)

    Long incubation experiments
    Longer (≥6 days) incubations were performed in 12-mL exetainers. Seawater from the core of the ODZ (250 m at station PS2, 160 m at station PS3) was sampled into 320 mL ground glass-stoppered bottles, which were immediately transferred into a N2 flushed glove bag. 15NO2− was added into these bottles to reach final concentrations of 7.24 and 8.01 µM at stations PS2 and PS3, respectively. 15NO2− labeled seawater was aliquoted into exetainers and capped within the glove bag. The septa had been stored under helium for at least 1 month. Exetainers were purged with helium for 5 min. Every 12 h, microbial activity in triplicate exetainers was terminated by adding 0.05 mL of 50% w/v ZnCl2. In the lab, N2 produced in exetainers was measured on a mass spectrometer (Europa Scientific 20–20, Crewe, UK) [45]. Denitrification and anammox rates were computed from linear regression of N2 produced at three time points. 15NO3− was measured (as described above) in the same exetainers, and NO2– oxidation rates were computed from linear regression of NO3− produced at three time points. O2 was monitored throughout the incubations in parallel exetainer vials using LUMOS sensors [12, 13]. Each O2 production or consumption rate was determined by linear regression of O2 concentrations at 32 time points. One sensing spot, glued inside an exetainer vial, allowed the optode to measure O2 concentrations every 5 min from the outside. Detection limit and resolution of LUMOS sensors was ≈1 nM.
    DNA sampling, extraction, sequencing, metagenomics, and metatranscriptomics analysis
    Particulate DNA samples were collected by filtration onto 0.22 µm Sterivex filters from the ODZ core samples (250 m at station PS2, 160 m at station PS3). DNA was extracted using the modified plant tissue protocol (All Prep DNA/RNA Mini Kit, Qiagen, Valencia, CA, USA), and subjected to paired-end sequencing on an Illumina MiSeq to generate over 10 million read pairs for each sample by the Genomics Core Facility of Lewis-Sigler Institute for Integrative Genomics at Princeton University. Quality control of raw reads was performed by BBDuk (DOE Joint Genome Institute, Walnut Creek, CA, USA), and assembled into contigs using metaSPAdes v3.12.0 [46] with specified options (-k 21, 33, 55, 77, 99, 127 -m 500). Metagenome-assembled genomes (MAGs) were constructed using MetaBAT v2.12.1 [47] with default (sensitive) mode and contigs longer than 1500 bp. The quality of MAGs was determined by checkM [48]. Taxonomy of MAGs was predicted by GTDB-tk [49]. ETNP PS2 MAG-11 from the ODZ core at station PS2 and ETNP PS3 MAG-54 from the ODZ core at station PS3 were identified as Nitrospina-like NOB. The taxonomy of these two NOB MAGs (ETNP PS2 MAG-11 and ETNP PS3 MAG-54) was further confirmed by comparing them with known OMZ NOB MAGs (MAG-1 and MAG-2) [8] using ANI. ANI between MAGs was assessed using enveomics [50]. MAG-2 [8], ETNP PS2 MAG-11 and ETNP PS3 MAG-54 belong to the same species (threshold for species: ANI ≥95%) based on their ANI values (Table S3). Considering the low completeness of MAG-11 and the high contamination of MAG-54 constructed from the two new metagenomes here (Table S4), we decided to use MAG-2 as the representative for this NOB species.
    We estimated the relative abundance and the transcriptional activity of the two known OMZ NOB species in different oceanic regions (including the two ETNP stations in this study) by mapping metagenomes and metatranscriptomes from this and other studies to MAG-1 and MAG-2. The relative abundance of MAG-1 or MAG-2 at stations PS2 and PS3 in the ETNP was calculated as RPKG (the number of metagenomic reads obtained in this study mapped to a MAG per MAG length (kb) per genome equivalents) [15]. Genome equivalents were estimated using MicrobeCensus v1.1.1 [15]. The transcriptional activity of MAG-1 or MAG-2 in ETNP and ETSP OMZs was assessed by mapping published metatranscriptomic reads from the ETNP (PRJNA263621) [51] and the ETSP (SRA023632.1) [52] to MAG-1 and MAG-2. The relative abundance of RNA in Fig. S4 was calculated as the number of metatranscriptomic reads mapped to a MAG divided by the number of total reads. Mapping was performed by Bowtie2 [53] using “very-sensitive” mode, and only reads with a mapping quality above 20 were included as mapped reads.
    In order to explore the possibility of the presence of other NOB in the ODZ core at stations PS2 and PS3, we also estimated the relative abundance of other (putative) NOB using their marker gene, nxrB (nitrite oxidoreductase). First, we downloaded previously identified (putative) nxrB sequences from the ETSP OMZ [8]. Then, we color coded the genes in Fig. 4 based on previously defined clusters in a phylogenetic tree (see Fig. 3 in [8]): the Nitrospina cluster (blue) contains nxrB grouped with cultured marine NOB, Nitrospina gracilis. Based on BLASTp search results, amino acid sequence identities between all the OMZ nxrB in this cluster and that of Nitrospina gracilis were 96.71%, 96.71%, and 96.87% for NODE_69234, NODE_114897, and NODE_102582, respectively. Only this cluster is associated with known NOB, and the nitrite oxidation capacity of all the other genes associated with nxrB needs to be confirmed. The anammox cluster (red) contains anammox nxrB sequences. The putative cluster (black) contains nxrB grouped with microbes in which nitrite oxidation capacity has not been proven. This putative cluster fell between known NOB and anammox, and was implied to represent unidentified NOB [54]. The last cluster is called unknown nxrB (gray) because neither their phylogeny nor function can be determined based on their distant relationship with known NOB or anammox nxrB. Finally, we mapped the ETNP metagenomic reads obtained in this study to each nxrB gene. Relative abundance of nxrB genes was also expressed as RPKG: relative abundance of nxrB gene = (number of mapped reads to a certain nxrB gene)/(length of this nxrB in kb)/(genome equivalents).
    To explore the potential metabolisms of NOB in anoxic ODZ cores, we searched for chlorite dismutase and NO dismutase (nod) genes in the NOB MAGs. First, protein-coding sequences in the two new NOB MAGs obtained here (ETNP PS2 MAG-11 and ETNP PS3 MAG-54) were predicted by Prodigal v2.6.3 [55]. The protein-coding sequences were annotated by the best BLASTp hits against the nr protein database. DNA sequences encoding Cld were identified in both ETNP NOB MAGs. Predicted Cld amino acid sequences encoded by ETNP MAGs were too short (120 aa) to be compared to Cld of Candidatus Nitrospira defluvii, but they only had one mismatch with Cld amino acid sequences of MAG-2 from the ETSP OMZ based on MUSCLE alignment using MEGA 7 software (Fig. S5b). Thus, we looked for the arginine173, the Cld activity marker, in longer Cld sequences of MAG-1 and MAG-2 by aligning their Cld with the Cld of Candidatus Nitrospira defluvii using MUSCLE in MEGA 7 software. Since nod was not found in the ETNP MAGs via annotation and was not reported in MAG-1 and MAG-2 in the previous study [8], gene search (i.e., searching nod against NOB MAGs) was performed using Hidden Markov Models by HMMER3 [56]. Reference sequences of the search included a nod sequence retrieved from Candidatus Methylomirabilis oxyfera [32] genome (accession numbers FP565575.1), and three environmental nod sequences (accession numbers: KX364450.1, KX364454.1, and KU933965.1). Search queries were the two ETNP MAGs and two ETSP MAGs in Table S3.
    Estimation of NO2− oxidation through disproportionation using an inverse isotope model
    We simulated the distribution of NO2− oxidation rates via disproportionation using a 1-D inverse isotope model [37] in the anoxic ODZ core from two stations in the ETSP OMZ (Fig. S6), where the complete suite of isotope and rate data have been previously published (Table S7). Briefly, the net biochemical production or consumption rate of each nitrogen compound (R14Ammonium, R14Nitrite, R14Nitrate, R15Nitrite, and R15Nitrate) was balanced by vertical diffusion and advection at steady state, and then five equations were used to balance measured 14NH4+, 14NO2−, 15NO2−, 14NO3−, and 15NO3− concentrations (Eqs. (3–7)). The exclusion of horizontal processes was justified [37] since the model was not run all the way to the surface, and using a constant vertical advection term does not violate continuity of the model. F is the rate of each nitrogen cycle process represented in this model (Fig. 5a, b). We modified the previous model by replacing canonical NO2− oxidation with NO2− disproportionation and using the recently determined stoichiometry of nitrate production by anammox from 0.3 to 0.16 [24]. Since OMZ NOB genomes encode nitrite oxidoreductase (catalyzes NO2−→NO3−) and nitrite reductase (catalyzes NO2−→NO), we assumed that the fractionation factor of nitrate production from nitrite by disproportionation is the same as by canonical nitrite oxidation (αDis = αNxr) based on the close clustering between OMZ NOB nxr and aerobic NOB (Nitrospina gracilis) nxr [8], and the fractionation factor of N2 produced by disproportionation is the same as by denitrification (αDisN2 = αNir). Rates of NO2− disproportionation (FDis), NO3− reduction (FNar), denitrification (FNir), and anammox (FAmx) were solved from the equations by the nonnegative least squares optimization routine (lsqnonneg) in MATLAB_R2015a as described previously [37].

    $$R_{14Ammonium} ,=, 0.11,times {,}^{14}F_{Nir} ,+, 0.07,times {,}^{14}F_{Nar} ,- {,}^{14}F_{Amx},$$
    ( 3)

    $$R_{14Nitrite} = – ,^{14}F_{Nir} ,+, {,}^{14}F_{Nar} ,-, (1 ,+, c) ,times,{,}^{14}F_{Amx} \ -, left( {5/3} right) ,times,{,}^{14}F_{Dis},$$
    ( 4)

    $$R_{14Nitrate} ,=, – ^{14}F_{Nar} ,+, c ,times {,}^{14}F_{Amx} ,+, {,}^{14}F_{Dis},$$
    ( 5)

    $$R_{15Nitrite} = -!! {,}^{14}F_{Nir}/alpha_{Nir} ,times,left( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right) \ +, {,}^{14}F_{Nar}/alpha_{Nar},times,left( {left[ {{,}^{15}{rm{NO}}_{3}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{3}^{-}} right]} right)\ -, {,}^{14}F_{Amx}/alpha_{Amx},times,left( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right) \ -, c times !{,}^{14}F_{Amx}/alpha_{NxrAmx},times,left( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right)\ -, {,}^{14}F_{Dis}/alpha_{Dis}timesleft( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right) \ -, left( {2/3} right) !times ! {,}^{14}F_{Dis}/alpha_{DisN2} !times left(! {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ !{{,}^{14}{rm{NO}}_{2}^{-}} right]} !right),$$
    (6)

    $$R_{15Nitrate} = -!! {,}^{14}F_{Nar}/alpha_{Nar} ,times,left( {left[ {{,}^{15}{rm{NO}}_{3}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{3}^{-}} right]} right) \ +, c times !{,}^{14}F_{Amx}/alpha_{NxrAmx},times,left( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right)\ +, ^{14}F_{Dis}/alpha_{Dis},times,left( {left[ {{,}^{15}{rm{NO}}_{2}^{-}} right]/left[ {{,}^{14}{rm{NO}}_{2}^{-}} right]} right).$$
    (7) More

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