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    Vegetation and microbes interact to preserve carbon in many wooded peatlands

    Study sites and soil samplingOur major study sites were located in a shrub-dominated bog13 in the Pocosin Lakes National Wildlife Refuge, NC, USA and a Sphagnum-dominated bog47 in the Marcell Experimental Forest, MN, USA (Supplementary Tables 1 and 2). Three sites ( >1 km apart) around Pungo Lake including Pungo West, Pungo Southwest, and Pungo East were selected at the shrub bogs in North Carolina. Ilex glabra and Lyonia lucida cover about 85% and 10%, respectively at Pungo West. Ilex glabra and Lyonia lucida also dominate Pungo Southwest but distribute evenly, also there are many Woodwardia virginica ferns during the growing season. The water level at Pungo Southwest is always higher than at Pungo West. Both Pungo West and Pungo Southwest have prescribed light fire every 4–5 years. There has been no fire disturbance at the Pungo East site over last 30 years, where more dominant plant species exist, including Lyonia lucida, Ilex glabra, Zenobia pulverulenta, Gaylussacia frondosa, Vaccinium formosum.One hollow and one hummock were selected at the Sphagnum-dominated bogs in Minnesota. A lot of mature trees including Picea mariana, Pinus resinosa, Larix laricina with different bryophytes and shrubs grow at both the hollows and the hummocks. S. fallax dominates the bryophyte layer at the hollows, and S. angustifolium and S. magellanicum dominate at the hummocks. The understory has a layer of ericaceous shrubs including Rhododendron groenlandicum, Chamaedaphne calyculata, Vaccinium oxycoccos at the hummocks, however, only scattered shrubs present in the hollows. Other site information is described in Supplementary Tables 1 and 2. We took three soil cores at each sites (with a distance >4 m from each other), and each soil core was sliced to four subsamples (0–5, 5–10, 10–15, and 15–20 cm). Big roots were removed in lab. The hair roots of all plants were included in the soil samples.Additionally, we took three soil cores at depth 0–10 cm in the shrub-dominated area in Dajiuhu peatlands in Shennongjia, China (31°29′N, 109°59′E) in May 2017. The dominant shrub at Dajiuhu is Betula albosinensis and Spiraea salicifolia with a dense Sphagnum layer (detailed plant information is described in Supplementary Tables 1 and 2). The samples were transported to the laboratory in iceboxes. Half of the samples were frozen at −80 °C for DNA isolation; the other half was stored at 4 °C for chemical analysis.Soil chemistry analysisWe used the deionized water extraction of fresh soil for DOC and soluble phenolics measurements. DOC was measured as the difference between total C and inorganic C with a total C analyzer (Shimadzu 5000 A, Kyoto, Japan). Soluble phenolics were measured by following the Folin-Ciocalteu procedure50. Inorganic nitrogen (NH4+–N and NO3−–N + NO2−–N) extract with 2 M KCl was determined colorimetrically on a flow-injection analyzer (Lachat QuikChem 8000, Milwaukee, WI, USA). Total carbon and nitrogen in soil were analyzed with combustion CN soil analyzer equipped with a TCD detector (ThermoQuest Flash EA1112, Milan, Italy). A 1:10 soil/water solution was used to measure soil pH.DNA extraction, PCR, and sequencingGenomic DNA was extracted from 0.25 g (fresh weight) of each homogenized soil sample using the PowerSoil DNA isolation kit (Mo Bio Laboratories, Carlsbad, CA, USA). DNA of each replicate was extracted 3 times and homogenized together as one DNA template. For Pocosin and Minnesota samples, a set of fungus-specific primers, ITS1F (3′-CTTGGTCATTTAGAGGAAGTAA-5′) and ITS4 (3′-TCCTCCGCTTATTGATATGC-5′), were used to amplify the internal transcribed spacer (ITS) region using barcoded ITS1F primers. For Dajiuhu samples, ITS1F and ITS2 (3′-GCTGCGTTCTTCATCGATGC-5′) were used. All PCR reactions were repeated in triplicate, together with the negative controls in which the template DNA was replaced with deionized H2O. The amplicon concentration of each sample was determined after purification using Qubit® 2.0 Fluorometer (Invitrogen, Grand Island, NY, USA), samples pooled at equimolar concentrations, purified using AMPure Bead cleanup. The amplicons from Pocosin, Minnesota and Dajiuhu samples were submitted to the core facility at Duke University (Durham, NC, USA) and Allwegene Tech Beijing (Beijing, China) for sequencing using Illumina MiSeq (Illumina, San Diego, CA, USA), respectively.Bioinformatics processingSequence data of Pocosins and Minnesota samples were obtained from both ITS1 and ITS2 gene regions. ITS sequences were quality filtered and processed using the standard QIIME pipeline, with each fungal taxon represented by an OTU at the 97% sequence similarity level. Singleton OTUs were omitted51, and OTUs classified taxonomically using a QIIME-based wrapper of BLAST against the UNITE database52,53 (see Supplementary Methods for further details). The quality and depth of coverage of both primers’ reads were not significantly different, thus libraries from ITS4 reads were used for further analysis of fungal communities. Taxonomic-based alpha diversity was calculated as the total number of phylotypes (richness) and Shannon’s diversity index (H′). A total of 150,967 ITS sequences from ITS2 region passed quality control criteria in the Pocosin and Minnesota sites. These sorted into 590 OTUs. Following the same procedure, a total of 115,936 ITS1 sequences from Dajiuhu samples were assigned into 307 OTUs. Following the processing procedure described by Wilson et al.47, relative abundance of beta-proteobacteria at the controlled site in the boreal Sphagnum site was recalculated from Wilson and others’ sequence data34 available from the National Center for Biotechnology Information at SRP071256. Relative abundance of fungi from a bog forest at the Calvert Island in Canada was recalculated from the raw amplicon reads in the European Nucleotide Archive, ITS (ERS1798771-ERS1799064).Lab incubationsThe decomposing capability of microbes in the Sphagnum- and shrub-dominated peatlandsWe tested the decomposing capability of microbes in the Sphagnum- and shrub-dominated peatlands by amending peat inocula from both sites in North Carolina and Minnesota to their peats and labile carbon-enriched mineral soil. Fresh Sphagnum- and shrub-formed peat inocula were prepared by mixing 0.5 kg of each type of fresh peat (10–20 cm) with 2 L of deionized water. After 1 h of stirring and 1-day settlement, the suspension liquid inoculum was filtered through a Buchner funnels (without filter, pore size 0.25–0.5 mm). We added 2 g of glucose to 50 g of nutrient-poor mineral soil (initially 0.05% total nitrogen, 0.64% total soil carbon) to produce a mineral soil medium with high labile carbon content. All incubation media (peat and mineral soil) and jars were sterilized by an autoclave before inoculation. About 30-g fresh Sphagnum-formed peat (2.5–2.8 g in dry weight) or shrub-formed peat (9.1–9.3 g in dry weight), or 50-g mineral soil with 2-g glucose was placed in Mason jars (triplicate, 8-cm diameter, 12-cm height, vacuum seal lid with a stainless-steel fitting with sampling septum), then 20 ml of its own or other’s inoculum was added to the peat media, and 5 ml of inoculum from each site was added to the mineral soil. Finally, all samples were aerobically incubated at a constant temperature of 25 °C. We initially used Parafilm M® Laboratory film, which is air permeable but water resistant, to seal the top for 3-day equilibration, afterward we collected gas samples by syringe from the headspace of each jar at the beginning and end of 1-h sealed incubation and used a GC (Varian 450, CA, USA) to analyze CO2 concentration. As microbial biomass itself is a factor regulating soil respiration rates, standardized CO2 emissions at the microbial biomass were calculated based on the elevated CO2 concentration, time, air volume in the jar, and the amount of added MBC from the inoculum. To prevent microbial acclimation to the assay chemistry18,31, we only incubated the soils for a short time. A chloroform fumigation-extraction method (0.5 M K2SO4 to extract biomass C)54 was used to determine soil MBC by the difference in measured carbon contents between fumigated and control replicates of each sample.Temperature sensitivityTo test temperature sensitivity of soil respiration, nine fresh peat samples (30 g) from each site were added to jars and sealed with Parafilm M® Laboratory film. Triplicate samples were incubated at 4, 25, and 44.5 °C. The highest temperature in this incubation does not match the in situ conditions in our sites, but it may happen shortly in tropical wooded peatlands in the future. After 3-day equilibration, we used the same method as above to measure gas emission and calculated soil respiration based on soil dry weight. We conducted regression analyses for soil from each site using R = αeβT, where R is soil respiration, coefficient α is the intercept of soil respiration when temperature is zero, coefficient β represents the temperature sensitivity of soil respiration, and T is soil temperature.The relative contributions of fungi and bacteria to peat decompositionWe subsampled 20 g each of our archived material from the Sphagnum-dominated bog in Minnesota and the shrub-dominated peatland in North Carolina, then subsamples were well mixed to make two composite bulk samples (one for Sphagnum-formed peat, one for shrub-formed peat) for the following incubations.A total of nine broad-spectrum antibiotics were tested either alone or in combination for their inhibition on bacteria or/and fungal respiration using a selective inhibition (SI) technique55 without glucose. The antibiotics include 5 fungicides (cycloheximide, benomyl, nystatin, natamycin, amphotericin B) and 4 bactericides (streptomycin, penicillin, oxytetracycline hydrochloride, neomycin). Both fungicide and bactericide were used alone or combined at concentrations of 0, 10, 20, 100, 500, and 1000 µg g−1 soil for the shrub-formed peat or 0, 35, 71, 357, 1785, and 3571 µg g−1 soil for the Sphagnum-formed peat. Each concentration of antibiotics (triplicate) was added to a 3-g fresh peat placed in a 50-ml tube. Mason jars (8-cm diameter, 12-cm height, vacuum seal lid with a stainless-steel fitting with sampling septum) are used to incubate the treated samples. CO2 accumulation rates over 24 h was measured and calculated as same as testing temperature sensitivity of soil respiration above. We found that all bactericides used in this study increased CO2 emission along with their concentrations. The results suggest that: (1) the contribution of bacteria to peat decomposition in general was simply very little, (2) the bacteria that were inhibited by bactericide contribute negligibly to peat decomposition, (3) the non-targeted bacteria were stimulated after the targeted-bacteria were inhibited, although the bactericides are broad-spectrum antibiotics, they did not inhibit the dominant bacteria at all in our sites, and /or (4) both bacteria and fungi in our sites may utilize these bactericides as a carbon source. As to the fungicide, only cycloheximide at a concentration of 357 µg g−1 soil slightly decrease CO2 emission in the Sphagnum-formed peat, but not the shrub-formed peat. Other fungicides did not suppress the CO2 emission regardless of their concentrations, or increased the CO2 emission along with increase in concentrations of fungicide, which suggest that these fungicides did not inhibit the dominant fungi in our sites. Therefore, we found no evidence that SI technique could detect the relative contribution of bacteria and fungi to peat decomposition in our sites. To further examine our fungal dominance hypothesis, we next used filtration by size to assess dominant decomposers.According to the literature (e.g., refs. 56,57,58), the average size of most bacteria is between 0.2 and 2.0 µm in diameter, with most of them less than 1.5 µm; while most fungi grow as hyphae in soil, which are cylindrical, thread-like structures 1.5–10 µm in diameter and up to several centimeters in length57,59,60. The sizes of most fungal spore are more than 2.0 µm in diameter61,62,63. Theoretically, porous filters could physically separate bacteria from fungi58. Domeignoz-Horta et al.64 used 0.8-μm filter to exclude fungi successfully64. In our test, filters with pore sizes of 0.22, 0.45, 1.2, and 1.5 μm were selected. The filtrates through 1.2- and 1.5-μm filters contain most of the bacteria, in which a small portion of larger bacteria and small fungi may pass through pores due to a lack of rigidity of their cells58.Sphagnum- and shrub-formed peat inocula were made by mixing 50 g of each type of fresh peat with 250 ml of sterilized deionized water. After 1 h of stirring and 1-day settlement, the suspension liquid inoculum was first filtered through a Buchner funnels (without filter, pore size 0.25–0.5 mm). The filtrate, we assumed, contain all bacteria and fungi while removing large decomposers like insects and worms. The 0.25–0.5 mm filtrate was used to make other inocula containing no-bacteria/fungi, nanobacteria and non-fungi, and most bacteria and non-fungi by filtering through 0.22- (nylon), 0.45- (nylon), 1.2- (glass fiber), and 1.5-μm (glass fiber) filters, separately. In total, 6 treatments including 5 inocula (filtrates through 0.22, 0.45, 1.2, 1.5, and 250–500-μm filters) and control (sterilized deionized water) were established. Either inoculum or sterilized deionized water was added to a 3-g sterilized Sphagnum- or shrub-formed peat (triplicate) and incubated at 25 °C. CO2 emission was measured within 24 h.Statistical analysisOne-way ANOVA with Duncan’s multiple-range test was used to compare the means of soil physicochemical parameters. Standard error of the mean was calculated for each mean. The significant level of the test was set at a probability of 0.05. The ANOSIM function in the vegan package in R was used to test statistical significance in fungal composition within and among sites in the shrub- and the Sphagnum-dominated peatlands (999 permutations), which shows that fungal communities were significantly different within sites at the shrub-dominated peatlands (Pungo East, Pungo West, and Pungo Southwest) and at the Sphagnum-dominated peatlands (hollows and hummocks) (Supplementary Fig. 5). Mantel test and redundancy analysis (RDA) were employed to explain the relative roles of soil physicochemical factors in fungal community composition using vegan package in R. The correlation of the redundancy axes with the explanatory matrix was determined with the general permutation test (anova.cca function; 999 permutations). Stepwise regression was further run to test what primarily control the slow-growing versus fast-growing fungi and soil acidity. More

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    Persistent microbiome members in the common bean rhizosphere: an integrated analysis of space, time, and plant genotype

    Sequencing summary and microbial diversity across growing regionsThere were 31,255 to 506,166 and 22,716 to 252,810 reads per sample for 16S rRNA and ITS biogeography datasets, respectively. We rarefied samples to 31,255 reads for 16S rRNA gene amplicons and to 22,716 for ITS. With these thresholds, we achieved richness asymptotes for both datasets, suggesting that sequencing efforts were sufficient to capture comparative dynamics and diversity (Fig. S3). The total richness observed at this rarefaction depth was 1,505 fungal and 23,872 bacterial and archaeal OTUs.As reported in other rhizosphere studies, the total fungal diversity was lower than bacterial/archaeal diversity in the rhizosphere of the common bean [41,42,43]. Richness varied by growing location (ANOVA, F value = 12.4, p-value  2.5), as well as connector (Pi  > 0.62, Zi  More

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    Selective enrichment and metagenomic analysis of three novel comammox Nitrospira in a urine-fed membrane bioreactor

    Bioreactor operation and samplingA continuous-flow MBR made from Plexiglass with a working volume of 12 L was used for enrichment (Supplementary Fig. S1). The reactor was installed with a submerged hollow fiber ultrafiltration membrane module (0.02 μm pore size, Litree, China) with a total membrane surface area of 0.03 m2. A level control system was set up to prevent liquid overflowing. The reactor was fed with diluted real urine with Total Kjeldahl Nitrogen (TKN) concentration of 140–405 mg N L−1 (for detailed influent composition see Supplementary Table S1). Initially, the reactor was inoculated with activated sludge taken from the aeration tank of a municipal wastewater treatment plant (Tsinghua Campus Water Reuse). The pH was maintained at 6.0 ± 0.1 by adding 1 M NaOH to buffer acidification by ammonia oxidation. The airflow was controlled at 2 L min−1, leading to the dissolved oxygen (DO) concentration above 4 mg O2 L−1 as regularly measured by a DO probe (WTW Multi 3420). The airflow also served to wash the membrane and mix the liquid. The temperature was controlled at 22–25 °C. The initial hydraulic retention time (HRT) was 3 days and was decreased to 1.5 days on day 222. The sludge retention time (SRT) was infinite as no biomass was discharged.The MBR was operated for 490 days. During this period, influent and effluent samples (10 mL each) were collected 1–3 times per week and used to determine the concentrations of TKN, total nitrite nitrogen (TNN = NO2−-N + HNO2-N), and nitrate nitrogen, according to standard methods.19 Mixed liquid samples (25 mL) were also taken weekly to measure mixed-liquor suspended solids (MLSS) and mixed-liquor volatile suspended solids (MLVSS).19 Biomass samples (10 mL) were regularly taken for qPCR and microbial community analyses (see below).Batch testsIn order to test urea hydrolysis and subsequent nitrification in the enrichment culture, short-term incubations were performed in a cylindrical batch reactor (8 ×18.5 cm [d × h], made from Plexiglass). 150 mL biomass was sampled from the reactor and washed three times in 1 x PBS buffer to remove any remaining nitrogen source. Subsequently, the biomass was resuspended in a 400 mL growth medium, which contained urea (about 40 mg N L−1), NaHCO3 (120 mg L−1), and 2 mL Hunter’s trace elements stock. Dissolved oxygen was controlled above 4 mg O2 L−1. Biotic and abiotic controls were performed under identical conditions with NH4Cl (~40 mg N L−1) instead of urea. The pH in all batch assays was maintained at 6.0 ± 0.1 by adding 1 M HCl or NaOH. According to the microbial activities during long-term operation, each batch assay lasted 6 to 8 h, and samples (5 mL) were taken every 20 to 60 min. Biomass was removed by sterile syringe filter (0.45 μm pore size, JINTENG, China), and urea, ammonium, nitrite, and nitrate concentrations were determined as described above. All experiments were performed in triplicate.DNA extractionBiomass (2 mL) for DNA extraction was collected on days 0, 53, 98, 131, 161, 189, 210, 238, 266, 301, 321, 358, 378, 449, and 471. DNA was extracted using the FastDNA™ SPIN Kit for Soil (MP Biomedicals, CA, U.S.) according to the manufacturer’s protocols. DNA purity and concentration were examined using agarose gel electrophoresis and spectrophotometrically on a NanoDrop 2000 (ThermoFisher Scientific, Waltham, MA, USA).16S rRNA gene amplicon sequencing and data analysisThe V4-V5 region of the 16 S rRNA gene was amplified using the universal primers 515F (5′-barcode-GTGCCAGCMGCCGCGG-3′) and 907 R (5′-CCGTCAATTCMTTTRAGTTT-3′).20 PCR products were purified using the AxyPrep DNA Gel Extraction Kit (Axygen Biosciences, Union City, CA, USA) according to manufacturer’s instructions and quantified using the QuantiFluor™ -ST (Promega, USA). Amplicons were pooled in equimolar concentrations and sequenced using the Illumina MiSeq PE3000 sequencer as per the manufacturer’s protocol. Amplicon sequences were demultiplexed and quality filtered using QIIME (version 1.9.1).21 Reads 10 bp were assembled. UPARSE (version 7.0.1090 http://drive5.com/uparse/) was used to cluster operational units (OTUs) on a 97% similarity cut-off level, and UCHIME to identify and remove chimeric sequences. The taxonomy of each 16S rRNA gene sequence was assigned by the RDP Classifier algorithm (http://rdp.cme.msu.edu/) according to the SILVA (SSU132) 16S rRNA database using a confidence threshold of 70%.Quantification of various amoA by qPCRTo quantify the abundances of comammox Nitrospira, AOB and AOA in the bioreactor, qPCR targeting the functional marker gene amoA was performed on DNA extracted from the bioreactor at different time points. We used the specific primers Ntsp-amoA 162F/359R amplifying comammox Nitrospira clades A and clade B simultaneously,12 Arch-amoAF/amoAR targeting AOA amoA,22 and amoA-1F/amoA-2R for AOB amoA.23 Reactions were conducted on a Bori 9600plus fluorescence quantitative PCR instrument using previously reported thermal profiles (Supplementary Table S2). Triplicate PCR assays were performed the appropriately diluted samples (10–30 ng μL−1) and 10-fold serially diluted plasmid standards as described by Guo et al.24. Plasmid standards containing the different amoA variants were obtained by TA-cloning with subsequent plasmid DNA extraction using the Easy Pure Plasmid MiniPrep Kit (TransGen Biotech, China). Standard curves covered three to eight orders of magnitude with R2 greater than 0.999. The efficiency of qPCR was about 95%.Library construction and metagenomic sequencingThe extracted DNA was fragmented to an average size of about 400 bp using Covaris M220 (Gene Company Limited, China) for paired-end library construction. A paired-end library was constructed using NEXTFLEX Rapid DNA-Seq (Bioo Scientific, Austin, TX, USA). Adapters containing the full complement of sequencing primer hybridization sites were ligated to the blunt-end of fragments. Paired-end sequencing was performed on Illumina NovaSeq PE150 (Illumina Inc., San Diego, CA, USA) at Majorbio Bio-Pharm Technology Co., Ltd. (Shanghai, China) using NovaSeq Reagent Kits according to the manufacturer’s instructions (www.illumina.com).Metagenomic assembly and genome binningRaw metagenomic sequencing reads (in PE150 mode) were trimmed and quality filtered with in-house Perl scripts as described previously.25 Briefly, duplicated reads caused by the PCR bias during the amplification step were dereplicated. Reads were eliminated if both paired-end reads contained >10% ambiguous bases (that is, “N”). Low-quality bases with phred values 2.5 kbp were retained for later analysis. Genome binning was conducted for each sample using sequencing depth and tetranucleotide frequency. To calculate coverage, high-quality reads from all samples were mapped to the contigs using BBMap v38.85 (http://sourceforge.net/projects/bbmap/) with minimal identity set to 90%. The generated bam files were sorted using samtools v1.3.1.27 Then, sequencing depth was calculated using the script “jgi_summarize_bam_contig_depths” in MetaBAT.28 Metagenome-assembled genomes (MAGs) were obtained in MetaBAT. MAG quality, including completeness, contamination, and heterogeneity, was estimated using CheckM v1.0.12.29 To optimize the MAGs, emergent self-organizing maps30 were used to visualize the bins, and contigs with abnormal coverage or discordant tetranucleotide frequencies were removed manually. Finally, all MAGs were reassembled using SPAdes with the following parameters: –careful –k 21,33,55,77,99,127. The reads used for reassembly were recruited by mapping all high-quality reads to each MAG using BBMap with the same parameter settings as described above.Functional annotation of metagenomic assemblies and metagenome-assembled genomesGene calling was conducted for the complete metagenomic assemblies and all retrieved MAGs using Prodigal v2.6.3.31 For the MAGs, predicted protein-coding sequences (CDSs) were subsequently aligned to a manually curated database containing amoCAB, hao, and nxrAB genes collected from public database using DIAMOND v0.7.9 (E-values < 1e−5 32) MAGs found to contain all these genes were labeled as comammox Nitrospira MAGs and kept for later analysis. Functional annotations were obtained by searching all CDSs in the complete metagenomic assemblies and the retrieved MAGs against the NCBI-nr, eggNOG, and KEGG databases using DIAMOND (E-values < 1e−5).Phylogenetic analysisPhylogenomic treeThe taxonomic assignment of the three identified comammox Nitrospira MAGs was determined using GTDB-tk v0.2.2.33 To reveal the phylogenetic placement of these MAGs within the Nitrospirae, 296 genomes from this phylum were downloaded from the NCBI-RefSeq database. The download genomes were dereplicated using dRep v2.3.234 (-con 10 -comp 80) to reduce the complexity and redundancy of the phylogenetic tree, which resulted in the removal of 166 genomes. In the remaining genomes, the three comammox Nitrospira MAGs and 25 genomes from phylum Thermotogae which were treated as outgroups, a set of 16 ribosomal proteins were identified using AMPHORA2.35 Each gene set was aligned separately using MUSCLE v3.8.31 with default parameters,36 and poorly aligned regions were filtered by TrimAl v1.4.rev22 (-gt 0.95 –cons 5037) The individual alignments of the 16 marker genes were concatenated, resulting in an alignment containing 118 species and 2665 amino acid positions. Subsequently, the best phylogenetic model LG + F + R8 was determined using ModelFinder38 integrated into IQ-tree v1.6.10.39 Finally, a phylogenetic tree was reconstructed using IQ-tree with the following options: -bb 1000 –alrt 1000. The generated tree in newick format was visualized by iTOL v3.40 amoA treeReference amoA sequences of AOB, AOA, and comammox Nitrospira were obtained from NCBI. Together with the amoA genes from the present study, all sequences were aligned and trimmed as described above. IQ-tree was used to generate the phylogenetic tree, with “LG + G4” determined as the best model.ureABC gene treeureABC gene sequences detected in this study were extracted and used to build a database using “hmmbuild” command in HMMER.41 ureABC gene sequences from genomes in NCBI-RefSeq database (downloaded on July 1st, 2019) were identified by searching against the built database using AMPHORA2. The same procedures as above were conducted to construct the phylogenetic tree of concatenated ureABC genes, except for the sequence collection step. To reduce the complexity of the phylogenetic tree, the alignment of concatenated ureABC genes was clustered using CD-HIT42 with the following parameters: -aS 1 -c 0.8 -g 1. Only representative sequences were kept for phylogeny reconstruction, which resulted in an alignment containing 858 sequences and 1263 amino acids positions. “LG + R10” was determined as the best model and used to build the phylogenetic tree. Regarding the Nitrospirae-specific ureABC gene tree, ureABC gene sequences were recruited from the genomes as described above, but without the sequence clustering step. The final Nitrospirae-specific phylogeny of ureABC genes was built on an alignment containing 62 sequences and 1015 amino acid positions with “LG + F + I + G4” as the best model. More