Betaproteobacterial clade II nosZ activated under high N2O concentrations in paddy soil microcosms

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Skip to main content Home About Submit ALERTS / RSS Search for this keyword Advanced Search New Results Betaproteobacterial clade II nosZ activated under high N 2 O concentrations in paddy soil microcosms View ORCID Profile Kazumori Mise , View ORCID Profile Yoko Masuda , View ORCID Profile Keishi Senoo , Hideomi Itoh doi: https://doi.org/10.1101/2025.02.17.638610 Kazumori Mise 1 National Institute of Advanced Industrial Science and Technology , Sapporo, Hokkaido 062-8517, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Kazumori Mise For correspondence: mise-33{at}aist.go.jp hideomi-itou{at}aist.go.jp Yoko Masuda 2 Department of Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo , Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan 3 Collaborative Research Institute for Innovative Microbiology, The University of Tokyo , Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Yoko Masuda Keishi Senoo 2 Department of Biological Chemistry, Graduate School of Agricultural and Life Sciences, The University of Tokyo , Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan 3 Collaborative Research Institute for Innovative Microbiology, The University of Tokyo , Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Keishi Senoo Hideomi Itoh 1 National Institute of Advanced Industrial Science and Technology , Sapporo, Hokkaido 062-8517, Japan Find this author on Google Scholar Find this author on PubMed Search for this author on this site For correspondence: mise-33{at}aist.go.jp hideomi-itou{at}aist.go.jp Abstract Full Text Info/History Metrics Supplementary material Preview PDF ABSTRACT Aims Microbial communities in paddy soils act as potential sinks of nitrous oxide (N 2 O), a notorious greenhouse gas, but their potential to reduce external N 2 O is unclear. The direct observation of N 2 O reduction in submerged field soils is technically difficult. Here, we aimed to identify soil microbial clades that underpin the strong N 2 O mitigation capacity. Methods and Results We constructed paddy soil microcosms with external N 2 O amendment that enabled the simultaneous evaluation of N 2 O reductase gene ( nosZ ) transcripts and N 2 O consumption. Although the amount of N 2 O amended was large, it was mostly consumed after 6– 8 days of microcosm incubation. Metatranscriptomic sequencing revealed that betaproteobacterial nosZ , especially those classified as clade II nosZ belonging to the orders Rhodocyclales or Nitrosomonadales , occupied >50% of the nosZ transcripts in three of the five paddy soils used. On the other hand, publicly available shotgun metagenomic sequences of 46 paddy soils were not dominated by betaproteobacterial clade II nosZ sequences, although they were ubiquitous. The same applied to the 16S rRNA sequences of Rhodocyclales or Nitrosomonadales . Conclusions The results indicated that betaproteobacterial N 2 O reducers potentially serve as powerful N 2 O sinks. Betaproteobacteria holding clade II nosZ can be targets of biostimulation, although further studies are required to understand their ecophysiology. Impact Statement Our results indicate that Rhodocyclales or Nitrosomonadales have the potential to serve as powerful N 2 O sinks in soils. INTRODUCTION Nitrous oxide (N 2 O) is a potent greenhouse gas, with a global warming potential approximately 265 times that of carbon dioxide ( Pachauri et al., 2014 ). N 2 O depletes ozone and is expected to become the dominant ozone-depleting compound of this century, surpassing chlorofluorocarbons and hydrochlorofluorocarbons, for which countermeasures have been developed ( Ravishankara et al., 2009 ). Its long atmospheric lifetime, typically spanning over a century, allows it to persist in the atmosphere and exert a lasting impact on both global warming and ozone depletion. Over the past four decades, anthropogenic N 2 O emissions have increased by >40%, primarily driven by agricultural activities, especially the application of nitrogen fertilizers ( Tian et al., 2023 ). Currently, >30% of anthropogenic N 2 O emissions are ascribed to agricultural soils ( Tian et al., 2023 ), a proportion that is expected to increase with continued chemical fertilizer use, which triggers microbial processes, such as nitrification and denitrification that release N 2 O ( Shcherbak et al., 2014 ). Natural soils contribute more than one-half of global N 2 O emission from nature ( Tian et al., 2023 ). In short, soil is a major source of N 2 O emissions. Flooded paddy soils are agricultural soils with relatively low N 2 O emissions ( Bouwman et al., 2002 ; Yan et al., 2003 ; Nishimura et al., 2005 ; Akiyama et al., 2006 ). Under anoxic conditions, which develop in flooded paddy soils, electron acceptors other than oxygen play vital roles, resulting in high denitrification activity, which includes both N 2 O production and consumption (NO 3 ⁻ → NO 2 ⁻ → NO → N 2 O → N 2 ) ( Kuypers et al., 2018 ). Indeed, >97% of the N 2 O produced in paddy soil is consumed without release to the atmosphere ( Wang et al., 2022 ), and this tendency has been observed regardless of the soil type ( Wang et al., 2024a ). These suggest that paddy soils exhibit high N 2 O reduction activity. Thus, paddy soils are not only characterized by low N 2 O emissions but also increasingly recognized for their ecological function as N 2 O sinks ( Zhong et al., 2023 ; Wang et al., 2024b ). However, which microbes underpin this strong N 2 O mitigation capacity in paddy soil is unclear. N 2 O-reducing microbes comprise phylogenetically diverse clades of bacteria, and the kinetics of N 2 O-reducing activity is also diverse ( Hiis et al., 2024 ). Microbial N 2 O reduction is driven by N 2 O-reductase, NosZ, which is encoded by nosZ gene ( Kuypers et al., 2018 ). Currently known nosZ sequences are classified into two distinct groups with different molecular machineries and phylogeny, namely clade I (also known as typical nosZ , nosZI, or TAT-dependent type) and clade II (atypical nosZ , nosZII, or Sec-dependent type). Clade I nosZ is distributed across Alphaproteobacteria , Betaproteobacteria , and Gammaproteobacteria , whereas clade II nosZ is distributed among more diverse lineages of bacteria, including Bacteroidota , Gemmatimonadota , Myxococcota , Verrucomicrobiota , and some clades of Betaproteobacteria ( Jones et al., 2013 ). Metagenomic studies have indicated that soils harbor diverse lineages of nosZ holders, with a dominance of clade II nosZ ( Orellana et al., 2014 ; Nadeau et al., 2019 ). A metatranscriptomic study using field soils reported that Myxococcota nosZ (presumably belonging to clade II) is highly abundant in waterlogged paddy soils ( Masuda et al., 2017 ). In addition to soils, activated sludge and wastewater treatment plants are dominated by clade II nosZ transcripts ( Li et al., 2021 ). Although many studies have reported community structures of N 2 O reducers in paddy soils, their potential to reduce external N 2 O is unclear. Direct observation of N 2 O dynamics in paddy fields is technically challenging under flooded conditions (Masuda et al., 2019). The only feasible method to simultaneously observe N 2 O reduction and N 2 O-reducing community structures would be to use closed systems, such as soil microcosms. Previous studies have utilized microcosm experiments with labile carbon sources and DNA/PCR-based analyses to investigate the microbial communities responsible for N 2 O reduction in paddy soils ( Ishii et al., 2011 ; Qin et al., 2020 ; Xing et al., 2021 ; Maheshwari et al., 2023 ; Shaaban et al., 2023 ; Xiang et al., 2023 ). However, these DNA-based approaches primarily reflect microbial potential rather than actual activity, because they do not capture gene expression or microbial functions in real-time ( Prosser, 2015 ). PCR-based methods are susceptible to biases, including the preferential amplification of certain sequences and variations in primer specificity and amplification efficiency ( Polz and Cavanaugh, 1998 ; Ruijter et al., 2009 ; Jones et al., 2013 ; Masuda et al., 2024 ). The external input of labile carbon sources, such as glucose or succinate, may disturb microbial communities in a way that is unrealistic in field soils. To address these limitations, using carbon sources more representative of the natural environment or RNA-based analyses can offer a more sensitive and accurate method to identify microorganisms that actively respond to N 2 O. RNA-based approaches, such as metatranscriptomics, provide insights into the gene expression of N 2 O reducers, offering a better understanding of their role in N 2 O reduction and improving the overall assessment of microbial activity in paddy soils. Here, we aimed to identify paddy soil microbes that can reduce a substantial amount of external N 2 O. We constructed soil microcosms amended with rice straw and N 2 O and obtained time-series metatranscriptomic profiles while monitoring the amount of N 2 O consumed, to identify active members within N 2 O-reducing communities. To put the results into a more general context, we analyzed the metatranscriptome of N 2 O-reducing communities constructed using paddy soils from four distinct locations. We further investigated the global distributions of these actively expressed nosZ through a meta-analysis of soil metagenomic datasets collected worldwide. EXPERIMENTAL PROCEDURES Soil sampling The soils used in this study, named Soils X or Y1–Y4, were taken from the surfaces of five paddy fields in Japan ( Table 1 ). Soil X was from a long-term fertilization field managed by a public research organization, with its physicochemical and microbiome profiles intensively investigated ( Itoh et al., 2013 ; Masuda et al., 2023 ). Soils Y1–Y4 were provided by private farmers. The sampled soils were stored at 4 °C until use. The physicochemical properties of soil were determined, as described previously ( Masuda et al., 2024 ). In brief, soil pH(H 2 O) and electrical conductivity were determined in the water suspension (soil:water = 1:5 [w/w]), whereas soil total carbon and nitrogen were measured using the dry combustion method. View this table: View inline View popup Download powerpoint Table 1. Descriptions of soil samples used in this study. Soil microcosm incubation We first constructed dozens of microcosms using Soil X ( Table 1 ) and 10-mL glass vials (with approximately 13 mL of inner capacity). We mixed the wet soils and distilled water and preincubated the sieved mixture at 25 °C without light for 7 days. Soils were sieved through a 2-mm mesh to remove large plant residues and gravel. Then, we adjusted the water content so that each microcosm consisted of 2.5 g of wet soil (water content = 40% [w/w]) and 1.0 mL of distilled water. This means that the final water content was (2.5 × 40% + 1.0)/(2.5 + 1.0) = 57.1%. Each microcosm was amended with 25 mg of dried rice straw powder (<0.25 mm in length) as possible electron donors ( Eusufzai et al., 2011 ; Zhang et al., 2023 ). The microcosm vials were tightly sealed with butyl rubber stoppers and aluminum caps, with their headspaces completely replaced with N 2 O and argon (Ar) gas. We applied N 2 O and Ar to some of the microcosms with N 2 O concentrations of 4.46 mM, whereas the others were amended only with Ar. We defined this point as Day 0. Glass vials with 3.5 mL of sterilized distilled water, with N 2 O-Ar gas (N 2 O concentration: 4.46 mM) amended in their headspace gas phases, were prepared as negative controls. After 0–7 days of incubation at 25 °C without light, the microcosm soils were destructively sampled for measuring headspace N 2 O content or for metatranscriptomic sequencing. Four N 2 O-added microcosms were sampled for metatranscriptomics every day, and three microcosms without added N 2 O were sampled on Days 2, 4, and 7. For N 2 O measurement, four microcosms with and without N 2 O addition (eight in total) were destructively sampled and analyzed using a gas chromatograph, as described previously ( Kuroda et al., 2022 ). For comparison, we constructed three microcosms using each of Soils Y1–Y4 ( Table 1 ). The microcosms were prepared in the same manner as those for Soil X, with the final water content adjusted to ∼57.1% (the same as Soil X). In total, 20 mg of straw was applied. All 12 microcosms received N 2 O amendment, and the N 2 O content of each microcosm was monitored using a GC3210 Gas Chromatograph (GL Science, Tokyo, Japan) and a column packed with ShinCarbon-ST 50/80 (Shinwa Chemical Industries, Kyoto, Japan). The temperatures of the TCD and columns were set at 210 and 150 °C, respectively. The flow rate of the carrier gas was 30 mL/min. The microcosms were destructively sampled for metatranscriptomic sequencing when they largely ran out of spiked N 2 O. The microcosms of Soils Y1, Y2, Y3, and Y4 were sampled on Days 8, 7, 6, and 8, respectively. RNA extraction and metatranscriptomic sequencing RNA was extracted from each microcosm immediately after sampling using RNesay PowerSoil Total RNA Kit (Qiagen), according to the manufacturer’s protocol. Concomitant DNA was eliminated using TURBO DNA-free Kit (ThermoFisher). The resulting RNA solutions were purified and concentrated using RNA Clean & Concentrator-5 (ZYMO RESEARCH). Bacterial rRNA was eliminated using riboPool (siTOOLs Biotech), followed by sequencing library construction using MGIEasy RNA Directional Library Prep Set (MGI Tech) with a fragmentation step at 82 °C for 8 minutes. The quantity and quality of the constructed libraries were verified using Synergy H1 (Bio Tek), QuanitFluor dsDNA System (Promega), Fragment Analyzer (Advanced Analytical Technologies), and Bioanalyzer (Agilent Technologies). The libraries were transformed into DNA nanoballs (DNBs) using MGIEasy Circularization Kit (MGI Tech) and DNBSEQ-G400RS High-throughput Sequencing Kit (MGI Tech). DNBs were sequenced using DNBSEQ-G400 in the 200-bp paired-end mode. Bioinformatic analyses of metatranscriptomic reads Metatranscriptomic reads underwent the following analyses. Adaptor sequences were trimmed off each read using Cutadapt v4.8 ( Martin, 2011 ) with default parameter settings. The low-quality region of each read was eliminated using vsearch v2.15.2_linux_x86_64 ( Rognes et al., 2016 ) with the options “--fastq_truncee 1 --fastq_minlen 50”. We eliminated reads bearing rRNA gene sequences using SortMeRNA v4.3.6 ( Kopylova et al., 2012 ) with the default reference database and “--paired_in” option. The filtered reads were finally assembled using SPAdes v3.15.5 (default parameters under “--rna” flag) ( Bushmanova et al., 2019 ; Prjibelski et al., 2020 ). Reads obtained from the same soil (listed in Table 1 ) were assembled together (i.e., coassembled), resulting in five sets of contigs. Regarding Soil X, which yielded 41 samples and >4.7 × 10 11 bases of metatranscriptomic reads, we randomly selected 5,000,000 read pairs per sample (quality-filtered reads only) and used them for assembly to save computational resources. Note that this subsampling applies only to the assembly process; the read depth of each contig or coding sequence (CDS) was calculated using all reads (details explained later in this section). CDS predictions and functional annotations were given to contigs of ≥500 bp, using eggNOG-mapper v2.1.2 ( Cantalapiedra et al., 2021 ) and the default reference database ( Huerta-Cepas et al., 2019 ), with the parameter settings of “--itype proteins --tax_scope_mode inner_narrowest --tax_scope 1 --target_taxa 1”. Contigs of <500 bp were discarded and not used for downstream analyses. For CDSs predicted to encode NosZ (K00376 in KEGG orthology, ( Kanehisa et al., 2024 )), we performed a more stringent phylogenetic and taxonomic annotation using phylogenetic placement implemented in pplacer v1.1.alpha19-0-g807f6f3 ( Matsen et al., 2010 ) and a custom database of NosZ sequences. We also used MAFFT v7.525 ( Katoh et al., 2002 ) for phylogenetic placement. The construction of the custom NosZ database was dependent on Prodigal ( Hyatt et al., 2010 ), FunGene ( Fish et al., 2013 ), KOfam ( Aramaki et al., 2020 ), HMMER ( Eddy and Wheeler, 2007 ), and GTDB ( Parks et al., 2022 ). The full details are explained in Supplementary Text 1. To evaluate the abundance of the transcripts of each gene, we mapped all the preassembled reads back onto the contigs using BWA-MEM2 version 2.2.1 ( Vasimuddin et al., 2019 ). We then calculated transcripts per kilobase million (TPM) of each CDS using “bedcov” command implemented in SAMtools version 1.18 ( Danecek et al., 2021 ). The CDSs annotated as betaproteobacterial nosZ , with a TPM of ≥ 5.0 in at least one sample, were aligned using MAFFT, and their phylogenetic tree was constructed using FastTree version 2.1.11 with “pseudo” option ( Price et al., 2009 ). We also performed canonical bootstrapping test (100 times) using a custom script for randomizing alignments (see Data Availability) and FastTree. DNA extraction and metagenomic analyses We obtained shotgun metagenomic sequences of the soils used in the microcosm experiments. Metagenomic sequencing of Soil X has been reported in a previous study—“SF” samples described in Masuda et al. (2023 )—therefore, we sequenced the metagenomes of Soils Y1–Y4. DNA was extracted from approximately 0.25 g of each soil using DNeasy PowerSoil Pro Kit (Qiagen). The extracted DNA samples were sequenced on DNBSEQ following the protocol established by the manufacturer with slight modifications ( Masuda et al., 2024 ). The metagenomic reads underwent adaptor trimming and quality filtering as described previously ( Masuda et al., 2024 ). Regarding the metagenomic data of Soil X, all reads from the three biological replications were pooled and treated as one sample in this study. Global distribution and diversity of nosZ sequences in metagenomes In addition to the metagenomic sequence data described above, we used intermediate data obtained in a meta-analysis study ( https://plus.figshare.com/articles/dataset/Quality-filtered_soil_shotgun_metagenomes/25332547 from Masuda et al., 2024 ). This dataset includes quality-filtered sequences from 41 shotgun metagenomic datasets from paddy soils collected worldwide, in addition to other metagenomic sequences. We analyzed the metagenomic data to investigate the distribution and ubiquity of betaproteobacterial nosZ sequences, which were abundant in our metatranscriptomic sequences (see Results). To search for nosZ from the metagenomic reads with minimal computational costs, we performed a two-step homology search. First, all reads were subjected to homology search against the NosZ database constructed from the eggNOG database. This database consists of all protein sequences with annotations of K00376 in the eggNOG database and is compatible with a large number of query sequences because of its small size. Here we used the blastx command in DIAMOND v2.1.9.163, with the options “-e 1e-5 -k 1”. Query sequences that had a significant hit were regarded as candidates for nosZ sequences. To select “true” nosZ sequences, they were mapped onto the whole size of the eggNOG database using the blastx command in DIAMOND (options: -e 1e-5 -k 200). Although we used only the top hits to identify nosZ sequences, we obtained the top 200 hits per query to mitigate the inaccuracy resulting from the heuristics of DIAMOND. The determined nosZ reads were further subjected to a more stringent phylogenetic annotation. See Supplementary Text 1 for details. Furthermore, we calculated the proportion of 16S rRNA sequences belonging to order Rhodocyclales or Nitrosomonadales in each metagenome. The 16S rRNA sequences were picked and annotated using SortMeRNA, blastn search, SINTAX ( Edgar, 2016 ), and SILVA v138.1, as described previously ( Masuda et al., 2024 ). Part of this analysis has been reported in a previous work ( Masuda et al., 2024 ). We reused the intermediate results that are available in FigShare ( https://figshare.com/articles/dataset/Microbiome_12_95/25894636 ). Throughout the study, we used SeqKit ( Shen et al., 2016 ), TaxonKit ( Shen and Ren, 2021 ), The Newick Utilities ( Junier and Zdobnov, 2010 ), and R v4.0.5 ( R Core Team https://www.R-project.org/ ) to handle fastq/fasta files, to manage NCBI taxonomy IDs, to edit newick files, and to visualize data, respectively. RESULTS N 2 O consumption in Soil X We first overview the time-series datasets obtained from Soil X microcosms. The temporal changes in N 2 O concentration in the microcosms are shown in Fig. 1a . N 2 O concentration at Day 0 was 3.53 ± 0.15 mM (mean ± SD), which is 21% lower than the due concentrations of amended N 2 O. The amount of lost N 2 O was 9.3 ± 1.5 μmol, which is 8.8 times lower than the solubility of N 2 O in water (1.2 g/L = 82 μmol per 3 mL of water). Despite the high concentration of N 2 O applied, inoculated N 2 O was largely consumed in the fresh-soil microcosms within 7 days of incubation. The rate of N 2 O consumption gradually increased with a peak at Days 2–4, and then decreased until N 2 O ran out ( Fig. 1a ). Although N 2 O is highly soluble in water, such a decline in N 2 O concentration was not observed in microcosms consisting only of water without soil ( Fig. 1a ). Download figure Open in new tab Figure 1. Overview of the results of the microcosm experiments using Soil X. (a) Dynamics of N 2 O concentrations in the microcosm headspaces. Results for samples with and without N 2 O amendment are displayed in closed and open circles, respectively. The average of four biological replications is indicated. Error bars indicate standard deviations. Some of the error bars are shorter than the circles. (b) Dynamics of the overall taxonomic composition of the metatranscriptomic sequences. All bacterial contigs that received valid annotations were considered. The transcripts per kilobase million (TPMs) of bacterial phyla and proteobacterial classes are indicated. Each bar indicates data from one microcosm (i.e., one biological replication). NA denotes not available. (c) Dynamics of the nosZ TPM in the metatranscriptomic sequences. The scales are the same between the two panels, each representing samples without and with N 2 O amendment. NA denotes not available. (d) Dynamics of betaproteobacterial nosZ TPM in the metatranscriptomic sequences. The scales are the same between the two panels, although a magnified plot of the upper panel is presented. NA denotes not available. Time-series transitions of metatranscriptomic profiles A total of 1,181,867,200 read pairs (22,549,292–33,206,316 per sample) were obtained in high-throughput sequencing, and 1,001,865,287 (84.8%) passed quality filtering and rRNA removal. De novo assembly of the filtered sequences yielded 3,699,693 contigs, and 1,002,468 (27.1%) were ≥500 bp (the remainders were discarded in downstream analysis). Functional and phylogenetic annotations using eggNOG-mapper indicated that 854,624 (85.3%) encoded at least one prokaryotic gene, and 483 encoded nosZ (484 nosZ CDSs in total). Phylogenetic analysis indicated that 438 (90.7%) of nosZ belonged to clade II (also known as “atypical” nosZ ) rather than clade I (“typical” nosZ ). Although most of the nosZ -harboring contigs were <2000 bp in length and their operon structures were not observed, longer contigs presented conserved structures of nos operons. In particular, several long contigs bearing Rhodocyclales clade II nosZ were obtained. They presented conserved structures, with cytC1 , nosD , nosH , and nosF encoded immediately downstream (some examples are shown in Fig. S1). They are congruent with the known structures of nos operons in Rhodocyclales genomes ( Sanford et al., 2012 ; Semedo et al., 2020 ; He et al., 2024 ). The same applies to the nosZ of Nitrosomonadales , a group phylogenetically close to Rhodocyclales . For comparison, clade I nosZ was adjacent to nosRDFYL ., which is also consistent to known structures of clade I nosZ ( Sanford et al., 2012 ). We mapped the metatranscriptomic reads onto the contigs, and a large portion of the metatranscriptomic reads (78.4%–94.2%) were successfully mapped. The time-series metatranscriptomic profiles showed that the taxonomic compositions of the transcripts were overall similar during the 7-day incubation ( Fig. 1b ), whereas the expression of nosZ was dynamically promoted in samples with N 2 O amendment ( Fig. 1c ). The TPM of nosZ increased by 3.05 times on Day 2 with N 2 O applied (compared with Day 0), whereas it remained stable in microcosms without N 2 O amendment. This result aligns with the contemporary decrease in N 2 O concentration: the expression of nosZ and the decrease in N 2 O concentration coincided. At this moment, we observed increased expression of accessory genes that are encoded in the neighbors of clade II, such as nosD , nosH , and nosF (Fig. S2). Betaproteobacterial nosZ dominated the metatranscriptome of Soil X The phylogeny of expressed nosZ spanned diverse bacterial clades, with the dominant phyla of Pseudomonadota , Acidobacteriota , and Myxococcota encoding clade II nosZ ( Fig. 1c ). By contrast, the increase in overall nosZ expression was largely attributed to Betaproteobacteria , with dominance of order Rhodocyclales . The TPM of clade II nosZ annotated as Betaproteobacteria increased by 69.8 times between Days 0 and 2, respectively. The same applied to the TPM of Rhodocyclales nosZ ( Fig. 1d ). At the later stages of incubation, particularly after Day 5, the TPM of Nitrosomonadales clade II nosZ increased. Nitrosomonadales (also known as Spirillales in ICNP nomenclature) belongs to Betaproteobacteria and is phylogenetically closer to Rhodocyclales than other subgroups ( Boden et al., 2017 ). Regarding lineages other than Betaproteobacteria , N 2 O amendment did not have a major impact on their expression levels. In addition, those of other nosZ did not present such drastic changes ( Fig. 1c ). Most of the nosZ of Rhodocyclales belonged to clade II nosZ , whereas clade I nosZ of Rhodocyclales was encoded on only two contigs. By contrast, the nosZ sequences of Rhodocyclales or Nitrosomonadales were not phylogenetically uniform and comprised multiple genera or species. Several clades of nosZ presented two distinct temporal patterns: some peaked at Day 2 and gradually decreased by Day 4, whereas others presented a major increase at a later stage ( Fig. 2 ). These two types of nosZ were phylogenetically conserved, although it should be noted that the phylogenetic tree presented low bootstrap values ( Fig. 2 ). Overall, although N 2 O-reducing traits are conserved within Rhodocyclales and Nitrosomonadales , they exhibit some diversity. Download figure Open in new tab Figure 2. Phylogeny and detailed dynamics of betaproteobacterial nosZ expression in Soil X microcosms. The tree dendrogram represents an approximate maximum-likelihood phylogeny of betaproteobacterial NosZ encoded on metatranscriptomic contigs. Circles indicate canonical bootstrap values of 70% or higher. Note that the bootstrap values are different from “local support values” implemented in FastTree. The heatmap indicates the transcripts per kilobase million (TPM) of each CDS. The two rightmost stripes represent the clade and taxonomic classification of each NosZ. Only betaproteobacterial nosZ CDSs with a TPM of ≥ 5.0 in at least one sample are shown. The TPM of all Rhodocyclales transcripts (including but not limited to nosZ ) steadily increased, indicating that the increased transcription of Rhodocyclales nosZ supported their growth and the inoculated N 2 O served as the terminal electron acceptor. By contrast, the overall expression profiles (summarized by KEGG pathways) were not extensively affected by N 2 O inoculation ( Fig. 3 ). They depended more on different incubation periods than whether N 2 O was inoculated. Download figure Open in new tab Figure 3. Comparison of the overall metatranscriptomic profiles among the Soil X microcosms. The heatmap indicates the TPM of each pathway (KEGG pathways). Each column represents one sample, and the sample attributes are indicated above the heatmap. Clustering was performed using Ward’s method with Manhattan distances. Atypical nosZ and Rhodocyclales dominate in microcosms of different paddy soils To investigate if the observations in Soil X are applicable to other paddy soils, we performed similar microcosm experiments using four types of paddy soils (Soils Y1–Y4; Table 1 ). In all soils, N 2 O was rapidly consumed within a week ( Fig. 4a ). At the time when microcosms largely ran out of N 2 O, metatranscriptomic analyses proved the transcription of diverse lineages of nosZ . TPMs of nosZ in the four soils were comparable to those of Soil X (350.0–1260.4, Fig. 4b ). Other statistical summaries of metatranscriptomic sequencing and assemblies can be found in Table S2. Download figure Open in new tab Figure 4. Overview of the results of the microcosm experiments using Soils Y1–Y4. (a) Dynamics of N 2 O concentrations in the microcosm headspaces. Blue arrows indicate the time point for metatranscriptomic sequencing. (b) Abundance and diversity of nosZ reads in the metatranscriptomic sequences. (c) Abundance and diversity of betaproteobacterial nosZ reads in the metatranscriptomic sequences. Most of the nosZ sequences belonged to clade II, particularly those of Betaproteobacteria and Rhodocyclales , with the exception of Soil Y2. This trend was similar to Soil X microcosms. By contrast, the expression of Nitrosomonadales nosZ was relatively minor in all four soils. The other dominant nosZ holders included Alphaproteobacteria , Acidobacteriota , Gemmatimonadota , and Myxococcota . Campylobacterota nosZ were dominant in two of the microcosms with Soil Y3, but were not observed in other soils. nosZ -holding Betaproteobacteria are not dominant in soil microbiomes We asked whether betaproteobacterial nosZ are prevalent and dominant in soils in nature, especially in paddy soils. We performed a semiglobal-scale meta-analysis of 46 paddy soil samples (mostly from Asia), which comprises 41 samples analyzed in Masuda et al. (2024) and the five raw soils used for our microcosm experiments. The geographic origins of the 46 samples are displayed in Fig. 5a . Each sample yielded 72–20,704 reads of nosZ and 1,023–253,450 reads of 16S rRNA genes. Download figure Open in new tab Figure 5. Distribution of betaproteobacterial nosZ in soil metagenomic sequences collected worldwide. (a) Geographic origins of the paddy soil metagenomic data used in this study. (b) Relative abundances of nosZ reads belonging to clade II and/or Betaproteobacteria . Each bar indicates the composition of one sample. Bars are sorted by the proportion of clade II betaproteobacterial nosZ . Arrows indicate the results for the five soils used in our microcosm experiments. (c) Relative abundances of 16S rRNA gene reads annotated as Rhodocyclales or Nitrosomonadales . The bars are sorted in the same order as that in panel (b). Arrows indicate the results for the five soils used in our microcosm experiments. We found that betaproteobacterial nosZ were not dominant in paddy soils ( Fig. 5b ), with some variations between samples ( Fig. 5b ). Clade II nosZ was overall dominant, in congruence with our metatranscriptomic results and previous metagenomic studies ( Orellana et al., 2014 ). In addition, the 16S rRNA gene reads of Rhodocyclales and Nitrosomonadales were distributed ubiquitously, with the relative abundances of 0.45–2.85% and 0.20–2.24%, respectively ( Fig. 5c ). DISCUSSION Our findings revealed that clade II nosZ , especially those harbored by members of Rhodocyclales or Nitrosomonadales within the class Betaproteobacteria , exhibited substantial transcriptional activity in N 2 O-amended soils, suggesting a key role for these taxa in reducing external N 2 O. The phylogeny of NosZ sequences ( Fig. 2 ) and the operon structures of nosZ -bearing contigs (Fig. S1) indicated that the sequences are likely bona fide nosZ . Clade II nosZ was dominant in all five soils, whereas Rhodocyclales nosZ transcripts were dominant in four of the five soils investigated ( Figs. 1d and 4bc ). These trends are likely not specific to the soils used in this study, given that the five or four soils were different in geographic origins and physicochemical properties, such as pH and carbon content ( Table 1 ). In all soils, inoculated N 2 O was consumed by Days 6–8 ( Figs. 1a and 4a ), although their initial concentrations being 10 5 times higher than atmospheric levels. This rapid consumption underscores the pivotal role of clade II nosZ -bearing Betaproteobacteria , particularly Rhodocyclales , in N 2 O mitigation. These results align with the potential of paddy soils as N 2 O sinks, likely driven by the N 2 O-reducing capabilities of Rhodocyclales . Although the prevalence of clade II nosZ is somewhat expected from previous metagenomic studies ( Orellana et al., 2014 ), the dominance of Rhodocyclales nosZ transcripts raises several questions. First, this trend is inconsistent with the metagenomic data. Our metagenomic analysis indicated that clade II nosZ were consistently dominant but betaproteobacterial nosZ , especially those encoded by Rhodocyclales or Nitrosomonadales , were minor ( Fig. 5b ). In a metatranscriptomic study of soils in paddy fields, a marginal amount of betaproteobacterial nosZ was detected ( Masuda et al., 2017 ). These results indicate that a limited number of nosZ -harboring microbes were activated in our microcosm experiments. Second, the extreme dominance of Rhodocyclales clade II nosZ may be counterintuitive in terms of the phylogeny of nosZ -holding bacteria. Both clade I nosZ and clade II nosZ are distributed among Betaproteobacteria (including Rhodocyclales ), and phylogenetically close members of Rhodocyclales can harbor different types of nosZ . As an extreme example, Thauera linaloolentis 47Lol T , a member of Rhodocyclales , harbors both types of nosZ in its genome ( Semedo et al., 2020 ). Despite this, the transcripts of clade I nosZ from Rhodocyclales were not dominant, and clade II nosZ was selectively favored in terms of expression. Moreover, the high concentrations of amended N 2 O are unlikely to favor clade II NosZ over clade I NosZ. Clade II NosZ tends to exhibit lower V max and K m values than clade I NosZ ( Yoon et al., 2016 ; Suenaga et al., 2019 ), suggesting that a high concentration of N 2 O would selectively favor bacteria holding clade I nosZ rather than clade II nosZ . This expectation, however, disagrees with our results. Third, clade II nosZ are prevalent among various lineages of bacteria, including Myxococcota and Acidobacteriota . Although their 16S rRNA genes are ubiquitous and often dominant in paddy soils ( Masuda et al., 2024 ), their expression was not promoted by N 2 O inoculation ( Figs. 1b and 4b ). Why only Rhodocyclales was selectively activated in nosZ holders is unclear. Although there are several factors specific to our experimental setup, they do not explain the increased expression of Rhodocyclales nosZ . First, high concentrations of N 2 O can have toxic effects on microbes, for example by inhibiting cobalamin activities ( Sullivan et al., 2013 ). However, the effect of N 2 O amendment was marginal on expression profiles compared with the timepoint of sampling ( Fig. 3 ). Second, members of Rhodocyclales can catabolize recalcitrant carbon substrates ( Salinero et al., 2009 ; Xu et al., 2021 ); therefore, they are likely to be favored by rice straw amendment. In fact, previous studies have reported the enrichment of Rhodocyclales in soils amended with hydroxyethylcellulose or cellulose-rich materials ( Si et al., 2018 ; Maheshwari et al., 2023 ). Similar results were observed in woodchip bioreactors, which are rich in lignocellulose ( Schiml et al., 2024 ). In this regard, our results contrast with a soil microcosmic study using succinate as the electron donor: members of Burlholderiales rather than Rhodocyclales were presumably activated under N 2 O-reducing conditions ( Ishii et al., 2011 ). Nevertheless, the TPM of Rhodocyclales nosZ did not increase in microcosms without N 2 O amendment ( Figs. 1d and 2 ). Overall, it remains unclear why Rhodocyclales nosZ is special. From the viewpoint of social needs for eliminating N 2 O gas, the present study may suggest that Betaproteobacteria holding clade II nosZ are potential targets of bioaugmentation and biostimulation. In fact, a previous study showed that clade II nosZ of Rhodocyclales might work as N 2 O sinks in wastewater plants ( Kim et al., 2022 ; Maeda et al., 2024 ). Although betaproteobacterial nosZ is not dominant in native soils ( Fig. 5b ), it could reside or be activated in soils because their 16S rRNA gene sequences are prevalent, if not dominant, in soil metagenomes ( Fig. 5c ). In addition, some strains of Rhodocyclales have plant growth-promoting functions ( Sakoda et al., 2019 ; Fernández-Llamosas et al., 2020 ) as well as nitrogen fixation activities ( Reinhold-Hurek et al., 1993 ). A limitation of this study is the major difference between the field environments and microcosms. Although the amount of N 2 O amended is comparable with N 2 O flux from field soils, N 2 O emitted from outfield soils rapidly disperses into the air. An N 2 O concentration of 4.46 mM is unrealistic in field environments and is far higher than the typical K m (the so-called Michaelis constant) of NosZ ( Yoon et al., 2016 ; Suenaga et al., 2019 ; Wang et al., 2023 ). We may consider that the N 2 O consumption observed in this study represents an upper limit of NosZ produced in microcosms. In conclusion, although the presence of clade II nosZ is not unexpected in soils, the exceptional dominance of nosZ transcripts derived from Rhodocyclales in response to N 2 O amendment provides insights into the microbial diversity of N 2 O reduction in paddy soils. Our results suggest that Rhodocyclales plays a pivotal role in mitigating N 2 O emissions, which has important implications for sustainable agricultural practices and greenhouse gas management strategies, such as biostimulation and bioaugmentation. In vitro assessments revealed that Rhodocyclales members tends to exhibit higher N 2 O reduction activity among the cultured strains ( Hiis et al., 2024 ), suggesting that stimulating Rhodocyclales in soils may enhance soil N 2 O uptake. If strains with superior persistence and colonization capabilities in soil environments can be identified, introducing Rhodocyclales to agricultural soils prone to N 2 O emissions could help reduce N 2 O release, as seen in a recent example ( Hiis et al., 2024 ). Future studies should explore the ecological factors driving the selective activation of Rhodocyclales in soils and examine how this activation may contribute to the overall functioning of paddy soil microbiomes. Data Availability The metagenomic and metatranscriptomic data obtained in this study have been deposited in DDBJ DRA under the accession numbers DRA019863, DRA019864, and DRA019865. See Table S1 for details. Source codes for the bioinformatic analyses are available in FigShare ( https://figshare.com/s/5eb9d7d02e35ea07102a ). Conflict of Interest Statement The authors declare no competing financial interests. Ethical Statement This study involves no experiments or analyses requiring ethical approval. Author Contributions KM: methodology, software, validation, data curation, formal analysis, investigation, resources, writing: original draft, writing: review and editing, visualization. YM: conceptualization, methodology, validation, investigation, resources, writing: review and editing, funding acquisition. KS: conceptualization, resources, writing: review and editing, supervision, funding acquisition. HI: conceptualization, methodology, validation, investigation, resources, writing: review and editing, supervision, funding acquisition. Acknowledgements This work was financially supported by JPNP18016 commissioned by the New Energy and Industrial Technology Development Organization (NEDO) and JST-Mirai Program grant JPMJMI20E5. We thank Momoko Hamatani, Emiko Kobayashi, Kyohei Kuroda, and Aika Sawaguchi (National Institute of Advanced Science and Technology [AIST]) for supporting the study and Hirotomo Ohba (Niigata Agricultural Research Institute) and anonymous farmers for providing the soil samples. Computations were partially performed on the Bioresource Analysis Platform supercomputer implemented in the AIST Hokkaido and SHIROKANE supercomputers at the Human Genome Center, The Institute of Medical Science, The University of Tokyo. REFERENCES ↵ Akiyama , H. , Yan , X. , and Yagi , K . 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Share Betaproteobacterial clade II nosZ activated under high N 2 O concentrations in paddy soil microcosms Kazumori Mise , Yoko Masuda , Keishi Senoo , Hideomi Itoh bioRxiv 2025.02.17.638610; doi: https://doi.org/10.1101/2025.02.17.638610 Share This Article: Copy Citation Tools Betaproteobacterial clade II nosZ activated under high N 2 O concentrations in paddy soil microcosms Kazumori Mise , Yoko Masuda , Keishi Senoo , Hideomi Itoh bioRxiv 2025.02.17.638610; doi: https://doi.org/10.1101/2025.02.17.638610 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Area Microbiology Subject Areas All Articles Animal Behavior and Cognition (7637) Biochemistry (17705) Bioengineering (13899) Bioinformatics (41970) Biophysics (21463) Cancer Biology (18605) Cell Biology (25526) Clinical Trials (138) Developmental Biology (13385) Ecology (19911) Epidemiology (2067) Evolutionary Biology (24329) Genetics (15615) Genomics (22514) Immunology (17743) Microbiology (40424) Molecular Biology (17194) Neuroscience (88650) Paleontology (667) Pathology (2835) Pharmacology and Toxicology (4827) Physiology (7648) Plant Biology (15160) Scientific Communication and Education (2046) Synthetic Biology (4302) Systems Biology (9825) Zoology (2271)