Supplementary Information Appendix · 3 27 Materials and Methods 28 Study sites and sampling 29 A...
Transcript of Supplementary Information Appendix · 3 27 Materials and Methods 28 Study sites and sampling 29 A...
1
Supplementary Information Appendix 1
Nitrifier adaptation to low energy flux controls inventory of reduced 2
nitrogen in the dark ocean 3
4
Yao Zhanga,b,1
, Wei Qinc, Lei Hou
a,b, Emily J. Zakem
d, Xianhui Wan
a, Zihao Zhao
e, Li 5
Liua,b
, Kristopher A. Huntf, Nianzhi Jiao
a,b, Shuh-Ji Kao
a,b, Kai Tang
a,b, Xiabing Xie
a, 6
Jiaming Shena,b
, Yufang Lia,b
, Mingming Chena,b
, Xiaofeng Daia,b
, Chang Liua,b
, 7
Wenchao Denga,b
, Minhan Daia,b
, Anitra E. Ingallsc, David A. Stahl
f, and Gerhard J. 8
Herndle,g
9
aState Key Laboratory of Marine Environmental Sciences, Xiamen University, 10
Xiamen 361101, China; bCollege of Ocean and Earth Sciences, Xiamen University, 11
Xiamen 361101, China; cSchool of Oceanography, University of Washington, Seattle, 12
WA 98195, USA; dDepartment of Biological Sciences, University of Southern 13
California, Los Angeles, CA 90089, USA; eDepartment of Limnology and Bio-14
Oceanography, Center of Functional Ecology, University of Vienna, Althanstrasse 14, 15
A-1090 Vienna, Austria; fDepartment of Civil and Environmental Engineering, 16
University of Washington, Seattle, WA 98195, USA; gNIOZ, Department of Marine 17
Microbiology and Biogeochemistry, Royal Netherlands Institute for Sea Research, 18
Utrecht University, 1790 AB Den Burg, The Netherlands. 19
1To whom correspondence should be addressed. Email: [email protected] 20
www.pnas.org/cgi/doi/10.1073/pnas.1912367117
2
This PDF file includes: 21
Materials and Methods 22
Supplementary Text 23
Figs. S1 to S10 24
Tables S1 to S5 25
References for SI Appendix citations 26
3
Materials and Methods 27
Study sites and sampling 28
A 492 km oceanographic transect with six sites (S1–S6) across the continental shelf 29
and slope and the central basin of the South China Sea (SCS) was sampled for 30
molecular analysis of the prokaryotic community during a research cruise on board of 31
RV Shi Yan 1 in September 2014. Three basin sites (S6, S7, and S8) were sampled for 32
nitrification rate measurements in May 2016 on board of RV Dong Fang Hong 2. Site 33
S6 was sampled again in June 2017 for nitrification kinetics on board of RV Tan Kah 34
Kee. In addition, two sites (W1 and W2) were sampled in the Western Pacific Ocean 35
(WP) during a spring and summer research cruise on board of RV Dong Fang Hong 2 36
and Ke Xue in April and August 2015, respectively. Water from ten sites (Fig. S1) was 37
collected along a vertical profile with two to 16 depth layers (see Fig. S2 for depth 38
layers of each site) using a conductivity-temperature-depth (CTD)-rosette sampling 39
system with Go-Flo bottles mounted in the rosette (SBE 9/17 plus; SeaBird Inc, 40
USA). 41
A total of 54 samples was collected for gene analyses while, 34 samples were 42
collected for transcript analyses at sites S6, W1, and W2. Three samples from 5, 200, 43
and 3000 m depth from site S6 were subjected to metatranscriptomics analyses. In 44
addition, 33 samples from sites S6, S7, S8, and W2 were amended with 15
N-labeled 45
ammonium and 15
N-labeled nitrite to measure the corresponding oxidation rates. One 46
sample from 150 m of site W2 and five samples collected between 75 and 200 m at 47
site S6 were used for ammonia (hereafter defined as combined ammonia and 48
4
ammonium) oxidation and nitrite oxidation kinetic experiments, respectively. 49
50
DNA and RNA extraction 51
Two to 4 L water samples were filtered through 0.22 m pore-size polycarbonate 52
membranes (47 mm diameter; Millipore) for DNA and RNA extraction. Samples for 53
RNA analyses were filtered within 30 min and stored instantly in 2 mL RNase-free 54
tubes containing 1 mL RNAlater RNA stabilizer (Ambion). All membranes were 55
flash-frozen in liquid nitrogen and then transferred to −80°C until further analysis. 56
DNA samples from the SCS were extracted using the UltraClean Soil DNA kit 57
(MoBio, San Diego, CA, USA) following the manufacturer’s protocols. DNA samples 58
from the WP were extracted using the phenol-chloroform-isoamyl alcohol method as 59
described by Massana et al. (1). Concentrations and purity of the genomic DNA were 60
determined using a NanoDrop spectrophotometer (Thermo Scientific 2000/2000c). 61
RNA was extracted with TRIzol reagent (Invitrogen, Carlsbad, CA) according to 62
Simms et al. (2) with minor modifications. DNA was digested with Turbo DNase 63
(Life Technologies). DNA contamination was checked by amplifying the bacterial 64
16S rRNA genes with the universal primers 27F and 1492R. Total RNA without DNA 65
contamination was reverse transcribed to synthesize single-strand complementary 66
DNA (cDNA) using the SuperScript RT-PCR system with random primers 67
(Invitrogen, Carlsbad, CA, USA). 68
69
Quantitative PCR amplification 70
5
Abundances of the archaeal and β-proteobacterial amoA genes, thaumarchaeal (MGI) 71
16S rRNA genes, Nitrospira and Nitrospina 16S rRNA genes, and archaeal accA 72
genes were quantified using the qPCR method and a CFX 96™ real-time system 73
(BIO-RAD, Singapore). Standard curves were constructed for archaeal and β-74
proteobacterial amoA genes and the archaeal accA gene using plasmid DNA from 75
clone libraries. For Thaumarchaeota, Nitrospira, and Nitrospina 16S rRNA genes, the 76
target DNA fragments of the pure-culture strains were used. qPCR reactions were 77
performed in triplicate and analyzed against a range of standards (100 to 10
7 copies 78
per l). Primer pair sequences, qPCR mixtures and conditions for each gene are listed 79
in Table S3. The efficiencies of qPCR amplification ranged from 90% to 104% with 80
R2 >0.99. The specificity of the qPCR reactions was checked by melting curve 81
analysis and agarose gel electrophoresis analysis. Ambiguous products were 82
sequenced to confirm their veracity. Inhibition tests were performed by 2-fold and 5-83
fold dilutions of all samples. Based on these tests, we concluded that our samples 84
were not inhibited. 85
86
Metatranscriptomics analysis 87
About 100 L samples were collected from the surface layer (5 m), the bottom of the 88
euphotic zone (200 m), and the bathypelagic zone (3000 m) of site S6 using in situ 89
pump filtration (McLane Large Volume Water Transfer System Sampler, USA) 90
through a 100 m Nitex screen, and 20 m and 0.22 m pore-size polycarbonate 91
filters (142 mm diameter; Millipore) within 30 min. The 0.22 m pore-size filters 92
6
were preserved in RNAlater (Ambion), flash-frozen in liquid nitrogen and transferred 93
to −80°C until further analysis. Total RNA was extracted with TRIzol reagent 94
(Invitrogen) (2). The residual DNA was removed using a Turbo DNA-free kit 95
(Ambion) and the RNA was purified using a RNeasy MinElute Cleanup kit (Qiagen). 96
mRNA was enriched by removing the bacterial and archaeal 16S and 23S ribosomal 97
RNA (rRNA) transcripts in the total RNA with both MICROB Express™ (Ambion) 98
and Ribozero (Epicentre) kits and by removing small RNA and tRNA using the 99
MEGAclearTM
kit (Ambion). Subsequently, mRNA was converted into cDNA using 100
the SuperScript III First Strand Synthesis System (Invitrogen) with random hexamer 101
primers. The cDNA was treated with RiboShredderTM
RNase Blend (Epicentre) to 102
remove trace RNA contaminants. To improve the yield of cDNA, the single-stranded 103
cDNA was amplified once using the GenomiPHITM
V2 method (GE Healthcare) (3) 104
and the amplified samples were then treated with S1 nuclease (4). Three ‒ 11 g 105
cDNA was purified using the QIAquick PCR purification kit (Qiagen) and sequenced 106
(one sequencing library per sample) on an Illumina HiSeq 2000 at the Beijing 107
Genomic Institute, Shenzhen, China following the manufacturer’s instructions. 108
From the raw sequences, the reads with >10% ambiguous bases or 20% low 109
quality bases (<Q20) were removed or those contaminated by the adapter. rRNA 110
transcripts were identified (>90% identity) using the SOAP software by blasting 111
against the Silva database and then removed. Subsequently, de novo assembly of the 112
clean reads was performed using Trinity with default settings (--jaccard_clip; --113
SS_lib_type RF; --min_kmer_cov 1; --min_glue 2; --group_pairs_distance 500; --114
7
path_reinforcement_distance 75) and only transcripts of 200 bp or longer were 115
reported (5). The produced unigenes were taken for further processing, such as 116
sequence splicing and redundancy removal, with sequence clustering software 117
(Illumina) to acquire non-redundant unigenes as long as possible. Subsequently, the 118
unigenes were blasted against public databases including NCBI non-redundant protein 119
(NR), Swiss-Prot, KEGG, COG, and GO (blastx, E-value <10−5
). Summary statistics 120
are given in Table S4. The protein with the highest sequence similarity was retrieved 121
and annotated to each unigene. For annotated unigenes, protein coding sequence 122
(CDS) information was retrieved from the blast results. For unannotated unigenes, 123
ESTscan (6) was used to perform CDS prediction. The predicted CDSs were then 124
blasted (blastp, E-value <10−5
) against databases, including KEGG, eggNOG, CAZy, 125
and ARDB, to obtain further functional information. To assess the quality of 126
assembly, reads of each sample were mapped back to the merged unigenes using 127
Bowtie2 version 2.2.5 with the setting of one mismatch in the seed alignment (7). 128
129
Ammonia and nitrite oxidation rate measurements 130
Incubations to determine ammonia and nitrite oxidation rates with water collected at 131
the S6‒8 and W2 stations were conducted on deck using the 15
N-labelling technique. 132
Briefly, for determining ammonia oxidation rates, 1 mL of 15
N-NH4+ tracer (98% of 133
15N atom, Sigma-Aldrich) was injected into 250 mL samples in Nalgene HDPE 134
bottles to obtain a final tracer concentration of 20 nmol L−1
at W2 and 30 nmol L−1
at 135
S6‒8, and 1 mL of 14
N-NO2− was added as carrier with a final concentration of 1 136
8
mol L−1
to avoid underestimating ammonia oxidation rates due to the oxidation of 137
15N-NO2
− to
15N-NO3
− (8). Immediately after tracer and NO2
− injection, 40 mL of 138
sample was filtered through a 0.2 m syringe filter for determining 15
N-labeling 139
percentages of initial substrate pools. The residual water was kept in the dark at near 140
in-situ (±1°C) temperature for 12 h and terminated by filtering through a 0.2 m 141
syringe filter. Samples were stored at −20°C immediately after collection. Similarly, 142
nitrite oxidation rates were obtained by using 15
N-NO2− tracer (98% of
15N atom, 143
Sigma-Aldrich) with a final tracer concentration of 20 nmol L−1
at W2 and 30 nmol 144
L−1
at S6‒8. All incubations were carried out in the dark and at in-situ (±1°C) 145
temperature. Each of the incubations was performed in triplicate. 146
δ15
N of NO2− was determined using the azide reduction method (9). In brief, a 147
fresh 1:1 (v:v) mixture of 2 mol L−1
sodium azide and 20% acetic acid was prepared 148
and purged with helium gas for 30 min to remove any pre-existing N2O, and then 0.8 149
mL of the mixture was added to each sample. NO2− was quantitatively converted into 150
N2O. Five NO2− stable isotope standards were made by combining different quantities 151
of 98% Na15
NO2 (Sigma-Aldrich) and 99% Na14
NO2 (Merck). The δ15
N of NaNO2 152
standards was calibrated against NO3− isotope standards USGS 34, IAEA N3, and 153
USGS 32 using the bacterial method. δ15
N of NO3− was determined using the 154
bacterial method (10). Briefly, samples were first treated with sulfamic acid for 12 h 155
at room temperature (22‒26°C) in the dark to remove NO2−
(11), and then neutralized 156
with NaOH and stored at −20°C before isotope analysis. NO3− was quantitatively 157
converted to N2O using the bacterial strain Pseudomonas aureofaciens (ATTC no. 158
9
13985). Three NO3− international reference materials (USGS 34, IAEA N3, and 159
USGS 32) were used to calibrate the δ15
N of NO3−. The N2O was then introduced to a 160
gas chromatography isotope ratio mass spectrometry (GC-IRMS, Thermo Delta V 161
Advantage) coupled with an on-line N2O cryogenic extraction and purification 162
system. Accuracy (pooled standard deviation) was better than ±0.2‰ for bacterial 163
method and ±0.4‰ for azide reduction method according to the analyses of these 164
standards at an injection concentration of 20 nmol N. 165
Ammonia oxidation and nitrite oxidation rates were primarily determined by the 166
accumulation of 15
N in the product pool relative to the initial. We used Equation (1) to 167
quantify the transformation rate of bulk substrate (8). 168
𝑅 =𝐶×(𝑛𝑡−𝑛0)
𝑡×𝑓15 (1) 169
where R represents the bulk reaction rates for all substrates after tracer enrichment 170
(nmol N L−1
h−1
), C denotes the product concentrations (nmol N L−1
), f15
is the 171
fraction of 15
N of the substrate pool at the beginning of incubation, nt and n0 are at% 172
15N of the product pool at the end and beginning of the incubation (%), respectively, t 173
is the incubation time (h). The detection limits for ammonia oxidation rates and nitrite 174
oxidation rates were 0.001–0.08 nmol N L−1
d−1
and 0.0003–0.085 N L−1
d−1
, 175
respectively, which were estimated by taking three times the pooled standard 176
deviation as a reliable enrichment of 15
N in the product pool. 177
178
Kinetics experiments 179
Ammonia oxidation kinetics experiments were performed with water collected at 150 180
10
m depth at site W2. The dependence of NH4+ oxidation rate on substrate concentration 181
was investigated using five different concentrations (0.03, 0.048, 0.096, 0.4, and 2 182
M) of 15
N-NH4+ (98% of
15N atom, Sigma-Aldrich).
14NO2
− at a final concentration 183
of 0.5 M was added as a carrier. For each set, the tracer was added separately into 184
duplicate 250 mL Nalgene HDPE bottles. Immediately after tracer injection, around 185
40 mL of sample was filtered through a 0.2 m syringe filter to represent the initial 186
condition. The remaining samples were incubated in a thermostat incubator at in-situ 187
(±1°C) temperature in the dark for 12 h and terminated by filtration. δ15
N of NO2− was 188
measured as described above. 189
Nitrite oxidation kinetics experiments were performed with water collected at 75, 190
95, 110, 150, and 200 m depths at site S6. 15
N-NO2− tracer (98% of
15N atom, Sigma-191
Aldrich) was injected into five Nalgene HDPE bottles with 250 mL samples to reach a 192
final tracer concentration of 0.03, 0.1, 0.2, 0.5, and 2 M. For samples from 75 m, 0.5 193
mL of 14
N-NO3− was additionally added as carrier to obtain a final concentration of 1 194
M. Each of the incubations was performed in duplicate. After tracer addition, 40 mL 195
sample was immediately filtered through a 0.2 m syringe filter to represent initial 196
condition (t0). The remaining samples were kept in a thermostat incubator at in-situ 197
(±1°C) temperature in the dark for time-series incubations (26 (t1) and 52 (t2) hours), 198
and at each time interval, incubation was terminated by filtration. δ15
N of NO3− was 199
measured as described above. Ammonia and nitrite oxidation rates were calculated 200
from the slopes of linear regression with 15
N-production as a function of time. 201
The kinetics constants (Vmax and Ks) were estimated using Equation (2): 202
11
𝑉 =𝑉max×[𝑆]
𝐾s+[𝑆] (2) 203
Where Vmax is the potential maximum rate of ammonia or nitrite oxidation and Ks 204
denotes the half-saturation constant. S represents the substrate concentration. 205
206
Laboratory experiments with specific bacterial strains 207
Nitrosopumilus maritimus SCM1 (at 24°C) Nitrospira moscoviensis NSP M-1 (at 208
26°C), and Nitrospina gracilis 3/211 (at 26°C) were cultured according to previous 209
reports (12−14) with minor modifications. Additionally, we also performed 210
incubation experiments with Nitrococcus mobilis Nb-231 (at 26°C) inhabiting mainly 211
oxygen-deficient zones, with initial cell abundances of ~4.0 × 105 cell mL
−1. 212
213
Estimating global oceanic dark DIC fixation 214
The depth profiles of ammonia and nitrite oxidization are consistent with a rapid 215
decrease in sinking organic matter because ammonia is only supplied by 216
mineralization in the meso- and bathypelagic zones of the ocean (15). Thus, we fitted 217
the depth profiles below the euphotic zone (100 m in the SCS and 200 m in the WP) 218
of ammonia and nitrite oxidation rates into the Martin curve using a Power Law 219
Equation (3) (16). 220
𝐹 = 𝐹100 (𝑍
100)𝑏
(3) 221
Integrated ammonia and nitrite oxidation rates were calculated and then integrated 222
DIC fixation rates were calculated according to the stoichiometric relations (Type I 223
regression) between inorganic nitrogen oxidization and DIC fixation rates obtained in 224
12
the laboratory experiments (see above). Extrapolating this integrated value to the 225
entire volume of the ocean below the euphotic zone based on a mean ocean depth of 226
3700 m and area of 3.6 × 1014
m2 (17) gives an estimate of global oceanic dark DIC 227
fixation. 228
229
Statistical analysis 230
Since normality in the distribution of the individual data sets was not always met, we 231
used the non-parametric Wilcoxon tests for comparing two related variables. 232
Polynomial and logarithm models (Sigmaplot) were used to determine the 233
relationships between variables. 234
235
Supplementary Text 236
Text S1. Abundance patterns of marine AOA and NOB 237
Archaeal and β-proteobacterial genes encoding the subunit A of the key enzyme for 238
ammonia oxidation, ammonia monooxygenase (amoA), as well as the 16S rRNA 239
genes of Thaumarchaeota, Nitrospira and Nitrospina (two major NOB groups in the 240
marine environment) were quantified via qPCR. As observed in many other studies, 241
the archaeal amoA was orders of magnitude more abundant than the β-proteobacterial 242
amoA gene (Table S5) with the highest abundance near the bottom of the euphotic 243
zone (Fig. S2 A‒C). Depth profiles of thaumarchaeotal 16S rRNA gene abundance 244
were generally similar to that of archaeal amoA genes and the two gene abundances 245
were positively correlated (R = 0.85‒0.91, P <0.01) with an average amoA : 16S 246
13
rRNA gene ratio of 1.6±0.4 (n = 48), suggesting all Thaumarchaeota are capable of 247
ammonia oxidation, with limited exceptions (18, 19). 248
Higher gene abundances of Thaumarchaeota 16S rRNA than archaeal amoA 249
mainly occurred in the WP, suggesting that some Thaumarchaeota may not be 250
capable of ammonia oxidation (19). Higher gene abundances of archaeal amoA than 251
Thaumarchaeota 16S rRNA occurred in the shelf waters and above 200 m of the slope 252
of the SCS. Possibly, there were other AOA groups (e.g. pSL12, also coined Marine 253
Benthic Group A) in the area close to the estuary. Hu et al. (20) have detected pSL12 254
16S rRNA genes in the SCS by qPCR. Similar discrepancies between 255
Thaumarchaeota 16S and archaeal amoA gene abundances were also observed in the 256
Pacific such as at Monterey Bay and the North Pacific Subtropical Gyre and the 257
pSL12 gene copy numbers agreed well with the difference between archaeal amoA 258
and thaumarchaeotal 16S rRNA gene abundance (21). 259
We also determined the abundance of the acetyl-coenzyme A carboxylase gene 260
(accA), involved in thaumarchaeotal carbon fixation. The ratio of archaeal accA : 261
amoA gene abundance increased along the SCS transect from the shelf to the basin, as 262
well as with depth (Fig. S2 D). A positive correlation was observed between archaeal 263
accA and amoA gene abundances in mesopelagic waters below 100 m with a slope of 264
1.03 (Fig. S2 E), suggesting that AOA biomass production is primarily 265
chemoautotrophic (22). 266
Nitrospina and Nitrospira 16S rRNA gene abundances varied from 2.71 × 102 to 267
4.93 × 106 copies L
−1 and 22 to 7.60 × 10
4 copies L
−1 in the SCS water column, 268
14
respectively, as well as from 62 to 3.77 × 105 copies L
−1 and below detection limit to 269
5.25 × 104 copies L
−1 in the WP, respectively (Fig. S8). Thus, AOA was one to two 270
orders of magnitude more abundant than NOB (Wilcoxon, P <0.01) (Fig. S2 A‒C). 271
Nevertheless, AOA and NOB abundances were correlated, as indicated by the 272
distribution pattern of archaeal amoA and NOB 16S rRNA gene abundances (R = 273
0.83‒0.89, P <0.01). 274
275
Text S2. Gene copy number per genome 276
All genes targeted in the present study are typically present as single copy per genome 277
(21, 23‒25). Only the β-proteobacterial amo operon was found in multiple (2‒3) 278
nearly identical copies in the representative strains (26). We downloaded a total of 23 279
Thaumarchaeota and five NOB (four Nitrospira and one Nitrospina) publically 280
available complete genome sequences from the NCBI database. Alignment results 281
also indicated that the Thaumarchaeota amoA, accA, and 16S rRNA genes and the 282
Nitrospina and Nitrospira 16S rRNA genes are present as a single copy in the 283
respective genome. We also noted that, different from our alignment results, Mincer et 284
al. (21) suggested two copies of the rRNA operon per genome in Nitrospina. Further 285
studies on Nitrospina, which has rarely been investigated, are required to resolve this. 286
Nevertheless, two copies per genome would not affect our conclusion that there is a 287
major difference in abundance between the low abundance of NOB and the one to two 288
orders of magnitude more abundant AOA. 289
290
15
Text S3. Coverage of the qPCR primers targeting NOB 291
The primers Nspra675f and Nspra746r were used in our qPCR approach for targeting 292
NOB Nitrospira 16S rRNA genes. Alignments of the primer sequences within the 293
SILVA rRNA database using TestPrime indicated a coverage of 92.6%. The primers 294
NitSSU_130F and NitSSU_282R were used for detecting the NOB Nitrospina 16S 295
rRNA gene. Among 29 OTU sequences of Nitrospina 16S rRNA genes available in 296
the databases listed by Levipan et al. (27), only one sequence could not be targeted by 297
the primers NitSSU_130F and NitSSU_282R due to >3 mismatching bases for either 298
primer, indicating a ~97% coverage of the primers. Alignments of the sequences of 299
the primer NitSSU_130F and NitSSU_282R within the SILVA rRNA database using 300
TestPrime indicated a 91.4% coverage. 301
302
Text S4. Activities measured on representative AOA and NOB strains 303
Physiological investigations were performed on Nitrosopumilus maritimus SCM1, 304
Nitrospira moscoviensis NSP M-1, Nitrospina gracilis 3/211, and Nitrococcus mobilis 305
Nb-231. SCM1 is the first isolated marine AOA strain (12) and has been widely used 306
as a model organism for developing an understanding of marine AOA physiology and 307
biochemistry (28). NSP M-1 is widespread in a diverse range of habitats. Strain 3/211 308
is the only isolated NOB Nitrospina strain from the oxygenated ocean (29). Nb-231 is 309
the only isolated NOB Nitrococcus strain, which originates from the surface waters of 310
Pacific Ocean collected from a foamy surface slick (29). The strains were cultivated 311
in batch cultures with a similar initial cell abundance. The abundance of SCM1 (107 312
16
cells mL−1
) was two times higher than that of NSP M-1 and one order of magnitude 313
higher than those of strains 3/211 and Nb-231 (106 cells mL
−1) in the stationary phase 314
(Fig. S3 A, E, I, and M). In contrast, ammonia oxidation rates of SCM1 were one to 315
two orders of magnitude lower than nitrite oxidation rates of NSP M-1, 3/211, and 316
Nb-231 in the exponential phase. The concomitantly measured DIC fixation rates of 317
SCM1 on a volume base were similar to strains NSP M-1 and 3/211 and 318
approximately three times lower than that of Nb-231 (Fig. S3 B, F, J, and N). Thus, 319
the cell-specific nitrite oxidation rates of NSP M-1, 3/211, and Nb-231 were 2-fold, 320
one and two orders of magnitude higher, respectively, than cell-specific ammonia 321
oxidation rates of SCM1. Cell-specific DIC fixation rates of SCM1 were similar to 322
those of NSP M-1 and 3/211, and one order of magnitude lower than those of Nb-231 323
(Fig. S3 C, G, K, and O). Taken together, the measured activities confirmed the 324
expected higher DIC fixation efficiency (per-N oxidized) of SCM1 than all NOB 325
strains (Fig. S3 D, H, L, and P). Nitrococcus mobilis Nb-231 had an extremely low 326
efficiency, which was not included in Fig. 1 since it abundantly occurs in the oxygen-327
deficient zones. In addition, we also performed physiological investigations on 328
Nitrosopumilus maritimus SCM1 at 30°C and Nitrospira moscoviensis NSP M-1 at 329
35°C. The results (Fig. S9) were generally consistent with the findings shown in Fig. 330
S3 while the time reaching the stationary phase was reduced greatly. 331
332
Text S5. Thermodynamic analysis 333
Ammonia and nitrite oxidizers have different carbon fixation yields and therefore 334
17
different biomass production rates, which is hypothesized to be due to the available 335
free energy of their redox reactions. Convoluting matters further, the production and 336
consumption of the shared metabolite nitrite creates an interdependence of relative 337
free energy on the relative activity of the two metabolisms. Two scenarios were 338
modeled to constrain this interdependence that represent 1) surface water, where the 339
ammonia concentration is high and nitrate concentration low, and 2) deep water where 340
the ammonia concentration is low and nitrate concentration high. Using the 341
commonly accepted overall metabolism for ammonia and nitrate oxidizers, nitrite 342
concentration was varied to quantify the response of relative free energy availability 343
between the two metabolisms on the basis of relative joule per mol of nitrogen reacted 344
(Fig. S4). As nitrite concentration increased, the energy available from ammonia 345
oxidation per energy available from nitrite oxidation decreased, shifting from 3.7 to 346
3.5 J/J for high ammonia and 4.5 to 4.2 J/J for high nitrate at the minimum and 347
maximum observed nitrite concentrations, respectively (Fig. S4). These relative free 348
energies provide an estimate for the relative carbon fixation efficiencies of the two 349
chemolithoautotrophs since they assume the machinery needed for energy 350
conservation has been tuned to the relevant concentrations. 351
352
Text S6. Relationship of transcriptional levels to measured activities 353
Since NOB are one to two orders of magnitude lower in abundance than AOA, they 354
exhibit one to two orders of magnitude higher cell-specific oxidation rates than AOA 355
throughout the water column except for the surface waters (Wilcoxon, P <0.05) (Table 356
18
1). This is consistent with activity differences between NOB and AOA inferred from 357
the 16S rRNA:gene ratio as an activity proxy (30, 31). The ratio of 16S rRNA to 16S 358
rRNA gene abundance was significantly higher (Wilcoxon, P <0.05) for the low 359
abundance NOB than for the more abundant ammonia-oxidizing Thaumarchaeota, but 360
their 16S rRNA:gene ratios were positively related (R = 0.90, P <0.01) (Fig. S10) 361
supporting a coupling of relative activities of the two dominant oceanic nitrifying 362
groups. Higher relative activity of the NOB was also supported by metatranscriptomic 363
analysis of samples from S6, showing high representation of transcripts of genes 364
encoding the key enzyme for nitrite oxidation, nitrite oxidoreductase (comprising 365
nxrA and nxrB subunits) at 200 m and 3000 m depths. Notably, nxrAB transcript 366
abundance was higher than that for archaeal amo genes (comprising amoA, amoB, and 367
amoC subunits) at 200 m depth (Fig. 2). Transcripts for genes associated with carbon 368
fixation by the two groups were also compared. Transcripts encoding enzymes 369
involved in the rTCA cycle of NOB (Nitrospina and Nitrospira) were more abundant 370
than transcripts for the thaumarchaeotal HP/HB cycle at 200 m depth, and expressed 371
at comparable levels at 3000 m depth (Fig. 2 and Table S2). Therefore, although NOB 372
are present at lower abundance than AOA, they are highly active throughout the 373
mesopelagic and bathypelagic zones and even exhibit higher relative transcript 374
abundances than AOA in the upper mesopelagic ocean. 375
19
376
377
Fig. S1. Site locations and bathymetry. Gene analysis was performed on samples 378
from all sites except for sites S7 and S8. The purple asterisks indicate the location 379
where samples were collected for metatranscriptomes/transcript analyses. The yellow 380
solid squares indicate locations where ammonia and nitrite oxidation rates were 381
measured, and underlines indicate stations where ammonia and nitrite oxidation 382
kinetics were determined. This figure was produced using Ocean Data View (32). 383
CHINA
Pearl R.
Lu
zo
n
JAPANL
ati
tud
e
Longitude
20
384
385
Fig. S2. Distribution of ammonia-oxidizing archaea (AOA) and nitrite-oxidizing 386
bacteria (NOB) based on gene abundance. (A) Depth profiles of the archaeal amoA 387
gene and Thaumarchaeota (error bars representing standard deviations of three 388
technical replicates are not visible because they are smaller than the symbols) and 389
NOB (sum of Nitrospira and Nitrospina, no error bars) 16S rRNA gene abundances in 390
the South China Sea (SCS) shelf (sites S1‒3), (B) slope and basin (sites S4‒6), and 391
(C) the western Pacific Ocean (WP) (sites W1 and 2). The black lines indicate the 392
depths of the sea bottom. The dashed lines indicate the depth of the euphotic zone 393
Ocean
Data
Vie
w /
D
Ratio of archaeal accA:amoA genes
114°E 114.5°E
Longitude
115°E 116°E115.5°E
0
1000
2000
3000
4000
Depth
(m
)
S1 S2 S3 S4 S5 S6
6
5
4
3
2
1
0
DIV
A
Genes (copies L 1
)
101102103104105 106 107 108
Genes (copies L 1
)
101102103 104 105 106 107 108
3000
2000
1000
800
500
200
100
75
5
101
Genes (copies L 1
)
101 103 104 105 106 107 108
De
pth
(m
)
90
75
50
25
5
3000
2000
1000
800
750
650
500
450
400
350
300
250
200
150
SCS Shelf
SCSSlope & Basin WP
A B C
100
101 10
3
AOA amoA
S1 S2 S3 S4 S5 S6
NOB 16S rRNA
Thaumarchaeota 16S rRNA
W1 W2
5
100
103
S1
S2
S3
_ _ _
Genes (copies L 1
)
101102103104105 106 107 108
Genes (copies L 1
)
101102103 104 105 106 107 108
3000
2000
1000
800
500
200
100
75
5
101
Genes (copies L 1
)
101 103 104 105 106 107 108
De
pth
(m
)
90
75
50
25
5
3000
2000
1000
800
750
650
500
450
400
350
300
250
200
150
SCS Shelf
SCSSlope & Basin WP
A B C
100
101 10
3
AOA amoA
S1 S2 S3 S4 S5 S6
NOB 16S rRNA
Thaumarchaeota 16S rRNA
W1 W2
5
100
103
S1
S2
S3
_ _ _
AOA amoA genes
(107 copies L 1)
0.0 0.6 1.2 1.8 3.04.0
Arc
haeal accA
genes (
10
7 c
opie
s L
1)
0.0
0.4
0.8
1.2E
Slope = 1.03R = 0.66P < 0.05
<100 m≥100 m
_
_
21
(0.1% of PAR). (D) Ratio of archaeal accA : amoA gene abundance along the transect 394
with six sites across the SCS continental shelf (S1–S3), slope (S4–S5), and the central 395
basin (S6). The filled grey area is bathymetry. There is a statistically significant 396
correlation between (E) archaeal amoA and accA gene abundance in the water column 397
below 100 m depth. The error bars for gene abundance represent standard deviations 398
of three technical replicates. 399
22
400
0 3 6 9 12 15 18 21 24 27 30 33N-n
utr
ient concentr
ation
(m
M)
0.0
0.4
0.8
1.2
Abundance (
10
7 c
ells
mL
1)
0
1
2
3
4
5
6
7
0 3 6 9 12 15 18 21 24 27 30 33
DIC
fix
ation r
ate
(μM
C d
1)
0
3
6
9
12
15
18
Am
moniu
m o
xid
ation
rate
(10
2 μ
M N
d 1
)
0.0
0.2
0.4
0.6
0.8
1.0
1.2
0 3 6 9 12 15 18 21 24 27 30 33
DIC
fix
ation r
ate
per
cell
(fm
ol C
cell
1 d
1)
0
1
2
3
Am
moniu
m o
xid
ation
rate
per
cell
(10
2 fm
ol N
cell
1 d
1)
0.0
0.1
0.2
0.3
0 3 6 9 12 15 18 21 24 27 30 33
Carb
on y
ield
(10
-2 m
ol C
fix
ed p
er
mol N
oxid
ized)
0
5
10
15
20
Ratio o
f 16S
rR
NA
:rD
NA
0
10
20
30
40
50
NH
4+
NO
2N
H4+
+ N
O2-
0 2 4 6 8 10 12 14 16 18
N-n
utr
ient concentr
ation
(m
M)
0.0
1.1
2.2
3.3
Abundance (
10
7 c
ells
mL
1)
0
1
2
3
A B C D
E
Time (days)
0 1 2 3 4 5 6 7 8 9 10N-n
utr
ient concentr
ation
(m
M)
0
5
10
15
20
25
Abundance (
10
6 c
ells
mL
1)
0
1
2
3
4
NO
2
NO
3
NO
2 +
NO
3
M
Time (days)
0 1 2 3 4 5 6 7 8 9 10
DIC
fix
ation r
ate
(μM
C d
1)
0
10
20
30
40
50
Nitrite
oxid
ation r
ate
(10
2 μ
M N
d 1
)
0
10
20
30
40
50N
Time (days)
0 1 2 3 4 5 6 7 8 9 10
Ratio o
f 16S
rR
NA
:rD
NA
0
100
200
300
400
Carb
on y
ield
(10
-2 m
ol C
fix
ed p
er
mol N
oxid
ized)
0
1
2
3
4P
Time (days)
0 1 2 3 4 5 6 7 8 9 10
DIC
fix
ation r
ate
per
cell
(fm
ol C
cell
1 d
1)
0
10
20
30
40
50 N
itrite
oxid
ation r
ate
per
cell
(10
2 fm
ol N
cell
1 d
1)
0
10
20
30
40
50O
NOB Nitrococcus mobilis Nb-231 (26 C)
NOB Nitrospira moscoviensis NSP M-1 (26 C)
NOB Nitrospina gracilis 3/211 (26 C)
AOA Nitrosopumilus maritimus SCM1 (24 C)
NO
2
NO
3
NO
2 +
NO
3
0 2 4 6 8 10 12 14 16 18
DIC
fix
ation r
ate
(μM
C d
1)
0
3
6
9
12
15
18
Nitrite
oxid
ation r
ate
(10
2μM
N d
1)
0
1
2
3
4
5
6
7
0 2 4 6 8 10 12 14 16 18
DIC
fix
ation r
ate
per
cell
(fm
ol C
cell
1 d
1)
0
1
2
3
Nitrite
oxid
ation r
ate
per
cell
(10
2 fm
ol N
cell
1 d
1)
0.0
0.2
0.4
0.6
0 2 4 6 8 10 12 14 16 18
Carb
on y
ield
(10
-2 m
ol C
fix
ed p
er
mol N
oxid
ized)
0
1
2
3
4
Ratio o
f 16S
rR
NA
:rD
NA
0
100
200
300
400F G H
0 1 2 3 4 5 6 7 8 9 101112
N-n
utr
ient concentr
ation
(m
M)
0
1
2
3
4
Abundance (
10
6 c
ells
mL
1)
0
3
6
9I
NO
2
NO
3
NO
2 +
NO
3
0 1 2 3 4 5 6 7 8 9 101112
DIC
fix
ation r
ate
(μM
C d
1)
0
3
6
9
12
15
18
Nitrite
oxid
ation r
ate
(10
2μM
N d
1)
0
1
2
3
4
5
6
7
0 1 2 3 4 5 6 7 8 9 101112
Nitrite
oxid
ation r
ate
per
cell
(10
2 fm
ol N
cell
1 d
1)
0
1
2
3
DIC
fix
ation r
ate
per
cell
(fm
ol C
cell
1 d
1)
0
1
2
3
0 1 2 3 4 5 6 7 8 9 101112
Carb
on y
ield
(10
-2 m
ol C
fix
ed p
er
mol N
oxid
ized)
0
1
2
3
4J K L
°
°
°
°
_
_
__
_ _
_
_
_
_
_
__
__
__
__
__
_ _
_
__
_
_ _
__
__
__
__
__
__
23
Fig. S3. Physiological characteristics of the ammonia-oxidizing archaeal and 401
nitrite-oxidizing bacterial strains. Physiological experiments of Nitrosopumilus 402
maritimus SCM1 (A–D), Nitrospira moscoviensis NSP M-1 (E–H), Nitrospina 403
gracilis 3/211 (I–L), and Nitrococcus mobilis Nb-231 (M–P) from batch cultures 404
show variations in (A, E, I, M) cell abundance and N-nutrient concentration, (B, F, J, 405
N) total and (C, G, K, O) cell-specific ammonium/nitrite oxidation and dissolved 406
inorganic carbon (DIC) fixation rates, (D, H, L, P) the ratios of DIC fixation rate to 407
ammonium/nitrite oxidation rate and 16S rRNA:rDNA during batch growth. The error 408
bars for SCM1 and NSP M-1 represent standard deviations of biological replicates (n 409
= 3) except for gene (three technical replicates); some are not visible because they are 410
smaller than the symbols. Twice experiments were performed for strain 3/211. For the 411
first experiment (solid lines), biological replicates for strain 3/211 were not taken 412
because of the very small culture volumes; only two nitrite oxidation and one DIC 413
fixation rates were measured. Grey symbols in J and K panels represent the estimate 414
values of nitrite oxidation rate based on nitrate concentration changes over time. The 415
error bars for cell abundance of 3/211 represent standard deviations of technical 416
replicates (n = 3). For the second experiment (dashed lines), biological replicates were 417
performed and the error bars represent standard deviations of triplicate biological 418
replicates except for gene (three technical replicates); DIC fixation rates were 419
measured only at two time-points. For strain Nb-231, the error bars for cell abundance 420
and nutrient concentration represent standard deviations of biological replicates (n = 421
3) and for gene abundance standard deviations are from technical replicates (n = 3); 422
24
the rate values are means from two biological replicates. 423
25
424
425
Fig. S4. The favorability of ammonia oxidation over nitrite oxidation decreases 426
with increasing nitrite concentration. 427
26
428
429
Fig. S5. Fitting the depth profiles below the euphotic zone of ammonia and nitrite 430
oxidation rates into the Martin curve using a power law equation. (A) Ammonia 431
oxidation (black symbols are from a previous study at the same stations (33)) and (B) 432
nitrite oxidation rates at sites S6 (circles), S7 (triangles), and S8 (squares) in the South 433
China Sea (SCS). (C) Ammonia oxidation and (D) nitrite oxidation rates at site W2 434
(diamonds) in the Western Pacific Ocean (WP). Euphotic zone depth is 100 m in the 435
Ammonia oxidation rate (nM N d-1
)
0 5 10 15 20
De
pth
(m
)
0
500
1000
1500
2000
2500
3000
Ammonia oxidation rate (nM N d-1
)
0 10 20 30 40 50D
epth
(m
)
0
500
1000
1500
2000
2500
3000
Nitrite oxidation rate (nM N d-1
)
0 5 10 15 20 250
500
1000
1500
2000
2500
3000
Nitrite oxidation rate (nM N d-1
)
0 5 10 15 20 250
500
1000
1500
2000
2500
3000
WP
Rate = 17.44 × (
)-3.84
R2 = 0.99 P < 0.01
WP
Rate = 21.7 × (
)-3.5
R2 = 0.95 P < 0.01
SCS
Rate = 21.03 × (
)-3.13
R2 = 0.9 P < 0.01
SCS
Rate = 21.83 × (
)-3.1
R2 = 0.88 P < 0.01
A B
C D
27
SCS and 200 m in the WP. Error bars represent standard deviations of biological 436
replicates (n = 3). Some are not visible because they are smaller than the symbols. 437
28
438
439
Fig. S6. Michaelis-Menten kinetics of ammonia oxidation. Ammonia oxidation 440
rates were measured at different substrate concentrations in the South China Sea 441
(colored lines and dots; data are from a previous study (34)) and the Western Pacific 442
Ocean (black lines and diamonds; data are from 150 m of site W2 in this study). 443
Measured rates were obtained from the slope of the linear regression of four 444
independent time course bottles (see Materials and Methods). Error bars represent the 445
standard error of the regression coefficient. The solid lines were fitted using the 446
Michaelis-Menten equation. R2, coefficients (Vmax and Ks) of the best fit and their 447
standard errors are shown in the figure. 448
29
449
Fig. S7. Simple estimate of the steady state concentration of nitrite incorporating 450
observed uptake kinetic parameters and an exponential fit of these constants that 451
extend the measurements to depth. (A) Maximum uptake rate Vmax as measured 452
(dots) and with a simple extension of the values to depth (line). (B) Half-saturation 453
constant Ks as measured (dots) and with a simple extension to depth (line). (C) Two 454
estimates of population level specific loss rates, assuming constant (blue line) and 455
exponentially decreasing (red line) rates with depth. (D) Observed and calculated 456
nitrite concentrations (calculated using Equation (1) for subsistence concentration 457
R*). The calculation uses the yield of nitrite oxidation of y = 1/334 mol biomass N 458
synthesized per mol NO2− (35) and two estimates of loss rate L: a constant loss rate 459
(0.005 d−1
) and an exponentially decreasing loss rate with depth (𝐿 = 𝐿0𝑒−(𝑧−𝑧0)
𝑧∗⁄ 460
with L0 = 0.01 d−1
, z0 = 75 m, and z* = 50 m), and converts the bulk uptake rate to a 461
specific uptake rate using a cell abundance of 2.4×105 cells mL
−1 as estimated from 462
the observations and a cell quota of 6 fmol N per cell. With the exception of the most 463
shallow data point, the calculations illustrate how the decrease in both Vmax and Ks 464
with depth compensates for one another to give relatively similar steady state 465
concentrations of nitrite. 466
30
467
468
Fig. S8. Abundance of subgroups of 16S rRNA genes of nitrite-oxidizing bacteria 469
along the water column obtained by quantitative PCR. The error bars represent 470
standard deviations of technical replicates (n = 3). Some are not visible because they 471
are smaller than the symbols. 472
Genes (copies L 1
)
101 102 103 104 105 106 107D
ep
th (
m)
5
25
50
75
90
100
Genes (copies L 1
)
101 102 103 104 105 106 107
5
75
100
200
500
800
1000
2000
3000
Genes (copies L 1
)
101 102 103 104 105 106 107
150
200
250
300
350
400
450
500
650
750
800
1000
2000
3000
5
100
Nitrospira 16S rRNA
Nitrospina 16S rRNA
S1 S2 S3 S4 S5 S6 W1 W2
SCS Shelf
SCSSlope & Basin WP
A B C
_ _ _
31
473
474
Fig. S9. Physiological characteristics of the ammonia-oxidizing archaeal and nitrite-oxidizing bacterial strains. Physiological 475
experiments of Nitrosopumilus maritimus SCM1 (A–D) and Nitrospira moscoviensis NSP M-1 (E–H) from batch cultures show variations in 476
(A, E) cell abundance and N-nutrient concentration, (B, F) total and (C, G) cell-specific ammonium/nitrite oxidation and477
0 2 4 6 8 10 12 14
N-n
utr
ien
t co
nce
ntr
atio
n (
mM
)
0.0
0.4
0.8
1.2
Ab
un
da
nce
(1
07 c
ells
mL
1)
0
2
4
6
8
10
NO
2
NH
4+
NH
4+
+ N
O2
0 2 4 6 8 10 12 14
Ra
tio
of 1
6S
rR
NA
:rD
NA
0
20
40
60
80
100
Ca
rbo
n y
ield
(10
-2 m
ol C
fix
ed
pe
r m
ol N
oxid
ize
d)
0
5
10
15
20
0 2 4 6 8 10 12 14
Am
mo
niu
m o
xid
atio
n r
ate
pe
r ce
ll (1
02 fm
ol N
ce
ll 1 d
1)
0.0
0.1
0.2
0.3
DIC
fix
atio
n r
ate
pe
r ce
ll (f
mo
l C
ce
ll 1 d
1)
0
1
2
3A C D
0 2 4 6 8 10 12 14
DIC
fix
atio
n r
ate
(μM
C d
1)
0
5
10
15
20
Am
mo
niu
m o
xid
atio
n r
ate
(10
2 μ
M N
d 1
)
0
1
2
3B
Time (days)
0 1 2 3 4 5 6 7 8 9 101112N-n
utr
ien
t co
nce
ntr
atio
n (
mM
)
0.0
0.5
1.0
1.5
2.0
2.5A
bu
nd
an
ce
(1
07 c
ells
mL
1)
0.0
0.5
1.0
1.5
2.0
Time (days)
0 1 2 3 4 5 6 7 8 9 101112
Nitrite
oxid
atio
n r
ate
pe
r ce
ll (1
02 fm
ol N
ce
ll 1 d
1)
0.0
0.4
0.8
1.2
DIC
fix
atio
n r
ate
pe
r ce
ll (f
mo
l C
ce
ll 1 d
1)
0
2
4
6
NO
2
NO
3N
O2 +
NO
3
Time (days)
0 1 2 3 4 5 6 7 8 9 101112
Ca
rbo
n y
ield
(10
-2 m
ol C
fix
ed
pe
r m
ol N
oxid
ize
d)
0
2
4
6
8
Time (days)
0 1 2 3 4 5 6 7 8 9 101112
Nitrite
oxid
atio
n r
ate
(10
2 μ
M N
d 1
)
0
2
4
6
8
DIC
fix
atio
n r
ate
(μM
C d
1)
0
5
10
15
20
E
F G H
AOA Nitrosopumilus maritimus SCM1 (30 C)
NOB Nitrospira moscoviensis NSP M-1 (35 C)°
°
__
_
__
_ _
_
_
__
_
__
__
__
__
32
dissolved inorganic carbon (DIC) fixation rates, (D, H) the ratios of DIC fixation rate 478
to ammonium/nitrite oxidation rate and 16S rRNA : rDNA during growth in batch 479
cultures. The error bars for cell abundance and nutrient concentration represent 480
standard deviations of biological replicates (n = 3) and for gene abundance standard 481
deviations are from technical replicates (n = 3). All rate values are means from two 482
biological replicates.483
33
484
485
Fig. S10. The ratio of Thaumarchaeota 16S rRNA to rRNA gene abundance 486
versus the ratio of nitrite-oxidizing bacteria (NOB) 16S rRNA to rRNA gene 487
abundance. The dashed line is the 1:1 line. Linear regression is on the log-log scale. 488
Ratio of Thaumarchaeota 16S rRNA:rDNA
10-5 10-4 10-3 10-2 10-1 100 101 102
Ra
tio
of
NO
B 1
6S
rR
NA
:rD
NA
10-5
10-4
10-3
10-2
10-1
100
101
102
R = 0.90P < 0.01
1:1S6 W1 W2
34
Table S1. Taxonomic breakdown for target groups in metatranscriptomes (Please refer 489
to the excel file). 490
491
Table S2. Detected sequences for nitrogen, carbon, and sulfur metabolism related 492
genes in metatranscriptomes (Please refer to the excel file). 493
35
Table S3. Primer pair sequences, qPCR mixtures and conditions for each gene. 494
Target gene Primer Sequence (5'-3') PCR mixture PCR conditions Efficiency Detection
limita
References
β-proteobacterial
amoA
amoA-1F GGGGHTTYTACTGGTGGT 25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa, Dalian, China) 12.5
l, BSA 5 g, primers 0.4
M, DNA template 1 l
94 °C for 30 s;
45 × (94 °C for
15 s, 60 °C for
60 s, and 72 °C
for 90 s).
96-104 % 2
Hu et al. (20);
Mincer et al.
(21)
amoA-2R CCCCTCKGSAAAGCCTTCTTC
Archaeal amoA Arch-amoAF STAATGGTCTGGCTTAGACG
25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 12.5 l, BSA 5 g,
primers 0.4 M, DNA
template 1 l
95 °C for 30 s;
40 × (95 °C for
30 s, 53 °C for
60 s, and 72 °C
for 45 s).
91-98% 3
Hu et al. (20);
Francis et al.
(36)
Arch-amoAR GCGGCCATCCATCTGTATGT
Archaeal amoAb
Arch-
amoAFB CATCCRATGTGGATTCCATCDTG
25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 12.5 l, BSA 5 g,
primers 0.4 M, DNA
template 1 l
95 °C for 240 s;
40 × (95 °C for
30 s, 55 °C for
45 s, and 72 °C
for 60 s).
91-100% 2 Beman et al.
(37)
Arch-amoAR GCGGCCATCCATCTGTATGT
Thaumarchaeota
16S rRNA
GI_751F GTCTACCAGAACAYGTTC
20 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 10 l, BSA 4 g,
primers 0.4 M, DNA
template 1 l
95 °C for 30 s;
40 × (95 °C for
15 s, 58 °C for
30 s, and 72 °C
for 30 s).
92-98 % 1
Hu et al. (20);
Mincer et al.
(21)
GI_956R HGGCGTTGACTCCAATTG
Nitrospira
16S rRNA
Nspra-675f GCGGTGAAATGCGTAGAKATCG
25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 12.5l, BSA 15 g,
primers 0.2 M, DNA
template 1 l
95 °C for 10 min;
45 × (94 °C for
30 s, 64 °C for
30 s, 72 °C for
60 s).
92-98 % 2 Attard et al.
(38)
Nspra-746r TCAGCGTCAGRWAYGTTCCAGAG
36
Nitrospina
16S rRNA
NitSSU_130F GGGTGAGTAACACGTGAATAA
25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 12.5l, BSA 1 g,
primers 0.4 M, DNA
template 1 l
94 °C for 15 min;
45 × (94 °C for
15 s, 57.5 °C for
15 s, 72 °C for
30 s, 77 °C for 1
s).
90-100 % 3 Mincer et al.
(21)
NitSSU_282R TCAGGCCGGCTAAMCA
Archaeal accA Crena_529F GCWATGACWGAYTTTGTYRTAATG
25 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 12.5 l, BSA 30 g,
primers 1.6 M, MgCl2 2mM,
DNA template 1 l
40 × (95 °C for
30 s, 53 °C for
45 s, and 72 °C
for 45 s).
91-97 % 1
Yakimov et al.
(39); Hu et al.
(20)
Crena_981R TGGWTKRYTTGCAAYTATWCC
Bacterial 16S
rRNAc
EUB338 ACTCCTACGGGAGGCAGCAG 30 l reaction mixture:
SYBR® Premix Ex Taq™
(TakaRa) 15 l, BSA 0.38 g,
primers 0.2 M, DNA
template 1 l
95 °C for 3.25
min; 40 × (95 °C
for 15 s, 55 °C
for 30 s, 72 °C
for 30 s).
98-100 % 4 Castro et al.
(40) EUB518 ATTACCGCGGCTGCTGG
aThe unit of detection limit of the qPCR reaction: gene copies per PCR reaction. 495
bThe primer set was used in the samples from waters column below 450 m at the sites in the West Pacific. 496
cThe primer set was used in the samples from the culture of Nitrococcus mobilis Nb-231. 497
37
Table S4. Summary statistics for metatranscriptome sequencing, assembly, 498
annotation, and read mapping. 499
5m 200m 3000m
Sequences quality control
Raw data (Mbp) 6,844.90 6865.70 5,314.06
Clean data (Mbp) 6,193.43 6,090.97 5,000
Clean data rate (%) 90.48 88.72 94.09
High quality data (Mb) 6,186.30 6,090.04 4,990.64
High quality data rate (%) 90.38 88.70 93.91
Assembly Resultsa
Number of Contig 3,079,143
Mean Length (nt) of Contig 203
Number of Unigene 419,084
Mean Length (nt) of Unigene 649
Assessment of assembly
Number of Total Reads Pairs 30,931,478 30,450,216 27,725,767
Alignment rate (%) 72.71 49.36 65.70
Number of annotated Unigene
NR 321,088
KEGG 240,237
GO 205,814
ALL 322,138
Number of mapped readsb 9,784,207 10,597,309 11,149,154
aThe clean data from the three samples were pooled for assembly. 500
bAlignment of the clean data to the merge-Unigene was carried out using Bowtie. 501
38
Table S5. Archaeal and β-proteobacterial amoA gene abundances in the South China 502
Sea and Western Pacific Ocean. 503
Station Depth
(m)
β-proteobacterial amoA Archaeal amoA
Gene abundance
(copies L−1
) SD
Gene abundance
(copies L−1
) SD
S1 5 0
2.23 × 10
3 452
25 3.15 × 103 32 1.10 × 10
6 1.68 × 10
4
S2
5 0
1.92 × 103 89
25 0
6.34 × 104 2.47 × 10
3
50 613
1.81 × 107 4.97 × 10
5
S3
5 44 15 3.23 × 103 130
25 0
1.51 × 106 4.82 × 10
4
50 76 18 5.92 × 106 3.47 × 10
5
75 0
9.02 × 106 4.04 × 10
5
90 1.09 × 103 259 3.40 × 10
7 1.08 × 10
6
S4
5
Not detected (ND)
6.05 × 103 171
75 1.51 × 107 8.11 × 10
5
200 5.53 × 106 2.16 × 10
5
500 4.22 × 106 3.23 × 10
5
S5
5
ND
2.07 × 103 3
75 4.17 × 106 3.65 × 10
5
200 4.74 × 106 9.40 × 10
4
500 3.35 × 106 1.86 × 10
5
800 1.46 × 106 1.27 × 10
5
1000 9.83 × 105 9.11 × 10
4
2000 2.39 × 105 3.77 × 10
3
S6
5
ND
70 8
75 4.15 × 105 3.22 × 10
4
100 1.30 × 106 1.22 × 10
5
200 3.57 × 106 6.34 × 10
5
500 1.87 × 106 8.43 × 10
4
800 8.24 × 105 1.03 × 10
5
3000 1.29 × 105 2.06 × 10
4
W1
5 0
0
25 0
0
50 384 38 0
75 57 10 0
100 29 5 3.62 × 103 143
200 92 27 1.33 × 106 7.48 × 10
4
500 402 50 1.34 × 106 1.66 × 10
5
800 42
4.67 × 105 1.56 × 10
4
2000 141 63 5.43 × 104 4.62 × 10
3
3000 26
1.89 × 104 243
39
W2
25 110 5 2.09 × 103 87
50 0
6.05 × 105 4.19 × 10
4
55 106 92 3.06 × 105 2.68 × 10
4
75 260 30 3.51 × 106 8.82 × 10
4
150 79 21 3.42 × 106 3.03 × 10
5
200 66 20 1.84 × 106 4.68 × 10
4
250 53 6 2.61 × 106 1.29 × 10
5
300 217 101 2.68 × 106 8.17 × 10
4
350 563
3.29 × 106 2.33 × 10
5
400 167 22 1.24 × 106 1.52 × 10
4
450 279 144 2.53 × 105 1.60 × 10
4
500 314 102 6.23 × 105 1.15 × 10
4
650 122 18 1.62 × 106 8.38 × 10
4
750 391 78 1.46 × 106 1.39 × 10
4
800 266 176 1.36 × 106 1.19 × 10
5
1000 97 41 4.67 × 105 1.48 × 10
4
504
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