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Inhibition of autotrophic nitrifiers in a nitrogen-rich paddy soil by elevated CO2

Nature Geoscience volume 17, pages 1254–1260 (2024)Cite this article

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Abstract

Autotrophic nitrifiers, by catalysing the oxidation of ammonia to nitrate, play a vital role in the global nitrogen cycle. They convert carbon dioxide (CO2) into biomass and, therefore, are expected to respond positively to increasing atmospheric CO2 concentrations. However, in a long-term free-air CO2 enrichment experiment, we demonstrated that elevated atmospheric CO2 inhibited the growth of autotrophic nitrifiers, resulting in a reduction in nitrification in a rice ecosystem. By coupling stable-isotope probing with metagenomics, we found that the CO2 inhibition of nitrifiers was mainly a consequence of CO2-induced functional loss (genomes not recovered from metagenomes) of dominant but previously uncharacterized autotrophic nitrifying species. These species belonged mainly to ammonia-oxidizing archaea and nitrite-oxidizing bacteria and comprised 63% of total dominant members identified from the active nitrifying communities. We further showed that the functional loss of these novel nitrifying species under elevated CO2 was due largely to the CO2-induced aggravation of anoxic stress in the paddy soil. Our results provide insight into the fate of inorganic nitrogen pools in global lowland soil and water systems under climate change.

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Fig. 1: Schematic diagram of study.
Fig. 2: eCO2 suppressed soil autotrophic nitrifiers.
Fig. 3: CO2 inhibition of nitrifiers and nitrification was independent of ammonia substrate.
Fig. 4: eCO2 reduced the abundance of novel and dominant members of active nitrifying communities.
Fig. 5: Inhibition of soil nitrifiers by eCO2-induced anoxic stress.
Fig. 6: A conceptual framework of the eCO2 effect on autotrophic nitrifiers in lowland soil systems.

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Data availability

The data supporting the findings of this study are available from the figshare data repository (https://doi.org/10.6084/m9.figshare.27193713) (ref. 77). Raw DNA reads from 16S rRNA gene and metagenomic sequencing were deposited in the National Center for Biotechnology Information (NCBI) under BioProject ID PRJNA1002562 and PRJNA1004433. The generated MAGs are also available in BioProject ID PRJNA1004433 with the accession numbers from SRR27251721 to SRR27251969.

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Acknowledgements

We thank Y. Han, G. Liu, C. Zhu and G. Zhu for maintaining FACE facilities. This work was supported by grants from the National Natural Science Foundation of China (NSFC nos. 32025024, 92251305 and 32430070 to L.C.; 32101246 to C.X.; 32301286 to S.L.), the Zhejiang Provincial NSFC (LZ24C030001 to L.C., LQ22C030006 to C.X., LQ24C030001 to J.X.) and the Academy of Ecological Civilization of Zhejiang University.

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Authors and Affiliations

  1. MOE Key Laboratory of Biosystems Homeostasis and Protection, College of Life Sciences, Zhejiang University, Hangzhou, China

    Kaihang Zhang, Weilei Lei, Huixin Zhang, Chenchao Xu, Jing Xiao, Maojun Liang, Junpan He, Yancen Lai, Ruiyang Li, Mingkai Jiang & Lei Cheng

  2. School of Life Sciences, Zhengzhou University, Zhengzhou, China

    Shuyao Li

  3. College of Computer Science and Technology, Zhejiang University, Hangzhou, China

    Jiahua Dong

  4. State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China

    Jianguo Zhu

  5. Department of Entomology and Plant Pathology, North Carolina State University, Raleigh, NC, USA

    Shuijin Hu

  6. Department of Biology, Brigham Young University, Provo, UT, USA

    Roger T. Koide

  7. Department of Environmental Science, Policy and Management, University of California, Berkeley, Berkeley, CA, USA

    Mary K. Firestone

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Contributions

K.Z., J.Z. and L.C. conceived and designed the study. K.Z., C.X. and S.L. performed the research. K.Z., W.L., H.Z., C.X., J.X., M.L., J.H., Y.L., R.L., J.D. and L.C. analysed the data. K.Z. and L.C. wrote the first draft with contributions from C.X., J.X., M.J., S.H., R.T.K. and M.K.F.

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Correspondence to Chenchao Xu, Jing Xiao or Lei Cheng.

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Nature Geoscience thanks Romain Barnard, Audrey Niboyet, Lisa Stein and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary Handling Editor: Xujia Jiang, in collaboration with the Nature Geoscience team.

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Extended data

Extended Data Fig. 1 Schematic description of the effect of elevated atmospheric CO2 (eCO2) on nitrifiers in upland soil systems.

CO2-enhancement of plant and microbial activities stimulates the growth of autotrophic nitrifiers by increasing soil CO2 (1) or inhibits their growth by reducing the supply of NH4+ when the system is N limited (2). Also, eCO2 often increases soil moisture through decreasing plant evapotranspiration, leading to either a stimulation effect on nitrifiers by alleviating water stress (3) or a suppression effect by reducing the diffusion of O2 into the soil (4). As such, the apparent eCO2 effect on nitrifiers likely depends on the overall response of nitrifiers to eCO2-induced changes of limiting factors or which of limiting factors will have an overarching effect on nitrifiers under eCO2. Arrows with ‘+’ and ‘-’ represent positive and negative effect, respectively.

Extended Data Fig. 2 Taxonomic structure of soil microbial communities in response to eCO2.

PCoA analysis of 16S rRNA sequencing data was performed using field samples from 2014 and 2018. a, Sep. 2014, surface soil. b, Sep. 2014, subsurface soil. c, Nov. 2014, surface soil. d, Nov. 2014, subsurface soil. e, 2018, surface soil from low-N subplots. f, 2018, subsurface soil from low-N subplots. g, 2018, surface soil from normal-N subplots. h, 2018, subsurface soil from normal-N subplots. PCoA analysis of soil microbiota for samples from the years 2015–2017 also revealed that mirobial communites at eCO2 were separated well from those at aCO2. Dots in blue: aCO2; squares in red: eCO2. Detailed sampling information is presented in Supplementary Table 1.

Extended Data Fig. 3 Effect of eCO2 on soil autotrophs.

a, Heatmap of the net effect of eCO2 on the relative abundance of soil autotrophs identified by 16S rRNA sequencing of field soil samples of 2014–2018. The abundance of each clade (phylum to family level) was calculated as the sum of relative abundance of all known autotrophic lineages (see Supplementary Dataset 2 for the full list) belonging to this clade. b, Net effect of eCO2 on functional genes (see Supplementary Dataset 6 for the list of gene names) belonging to five carbon fixation pathways. Genes were selected according to the KEGG database (map 00720). The net CO2 effect was calculated as Cohen’s d: (mean of eCO2-mean of aCO2)/pooled standard deviations. Green colors: values > 0; purple colors: values < 0. Error bars denote 95% confidence intervals (CI) of the mean net CO2 effect across treatment replicates (n = 3).

Extended Data Fig. 4 Effect of eCO2 on the growth of soil nitrifiers.

a, Net effect of eCO2 on the relative abundance of AOA, AOB and NOB identified by 16S rRNA sequencing. The NOB may include both canonical NOB clades and comammox clades, as comammox was not able to separate from NOB Nitrospira by 16S amplicon sequencing. The average relative abundance of each clade was calculated across 2014–2018. The net CO2 effect was calculated as Cohen’s d: (mean of eCO2-mean of aCO2)/pooled standard deviations. Data are presented with means ± standard error across 5 years (n = 5). b, Effect of eCO2 on the absolute abundance of soil nitrifiers from field soil samples of 2018. The absolute abundance of each clade was expressed as amoA gene copies targeting AOA, AOB or comammox, or nxrB gene copies targeting NOB Nitrospira (see specific primer sets for each nitrifying clade in Supplementary Dataset 3). Blue bars, aCO2. Red bars, eCO2. Data are presented with means ± standard error across treatment replicates (n = 3).

Extended Data Fig. 5 Effect of eCO2 on the absolute abundance of comammox.

The absolute abundance of comammox clade A (a) and clade B (b) in response to eCO2 and N addition was determined using samples from experiment 1. a, Abundance of comammox clade A, expressed as amoA gene copies. Mixed model, main CO2 effect: P = 0.124; N effect: P < 0.01; CO2 × N: P = 0.50. b, Abundance of comammox clade B, expressed as amoA gene copies. Mixed model, main CO2 effect: P = 0.479; N effect: P < 0.01; CO2 × N: P = 0.73. Data are presented with means ± standard error across treatment replicates (n = 3). Specific primer sets for each nitrifying clade are presented in Supplementary Dataset 3. Blue bars, aCO2 soils. Red bars, eCO2 soils.

Extended Data Fig. 6 Effect of eCO2 on the relative abundance of active nitrifiers.

a, b, c and d, Distribution of the relative abundance of AOB (a), AOA (b), NOB Nitrospira (c) and comammox (d) across the CsCl buoyant density gradients of genomic DNA from soil samples taken from experiment 2. The data are the ratios of the amoA or nxrB gene copies (Supplementary Dataset 3) in each gradient fraction to the total gene copies across all gradients. Colored lines, 13CO2-treated groups. Grey lines, 12CO2-treated groups. The shaded rectangles represent the ‘heavy DNA’ of CsCl fractions, enriching with 13C-labelled DNA from each of corresponding nitrifiers. Autotrophic growth of active nitrifiers was expressed using the heavy fraction of 13C-labelled DNA, with a buoyant density of 1.715–1.750 g ml−1, separated from 12C-labelled DNA with a buoyant density of 1.660–1.710 g ml−1. The percentage within each shaded region indicates the relative abundance of 13C-labelled functional genes. No N, Low N and High N denote the three N treatments amended with 0 mM, 0.5 mM and 1.5 Mm NH4+-N, respectively. Data are presented with means ± standard error across treatment replicates (n = 3).

Extended Data Fig. 7 Maximum-likelihood phylogenetic tree of recovered MAGs and reference genomes.

MAGs identified from this study (experiment 2) are indicated using stars at the tip of the node, with those in blue or red stars constructed from aCO2 or eCO2 samples, respectively (see the full taxonomic assignments in Supplementary Dataset 4). The tree does not include MAGs that are marked with an asterisk (*) in Supplementary Dataset 4 as they contain too few single copy genes for alignment. The shaded regions with different colors represent different phylum-level lineages.

Extended Data Fig. 8 Genome-wide, pairwise comparisons of ANI and AAI values between nitrifying MAGs identified from the current study (experiment 2, highlighted in bold) and known genomes of nitrifiers.

a, Symmetrical matrix of pairwise average nucleotide identity (ANI) and average amino acid identity (AAI) values between three AOB MAGs and known genomes of AOBs. b, Symmetrical matrix of pairwise ANI and AAI between three AOA MAGs and known genomes of AOAs. c, Symmetrical matrix of pairwise ANI and AAI between 13 NOB Nitrospira MAGs and known genomes of Nitrospira. ANI, the lower left triangle. AAI, the upper right triangle.

Extended Data Fig. 9 Diversity and function of dominant members of active nitrifying communities under eCO2.

a, b and c, Phylogenetic analyses and metabolic potential of active AOB (a), AOA (b) and NOB (c) MAGs identified in the present study (experiment 2) and known closely-related genomes. MAGs labelled in blue, assembled in aCO2. MAGs labelled in red, assembled in eCO2. Filled or non-filled squares within the heatmaps denote the presence or absence of the specific functional gene in each genome, respectively. The six functional gene groups are differentiated with squares filled with distinct colors.

Extended Data Fig. 10 Effect of eCO2 on the size of soil inorganic N pool in paddy rice and wetland ecosystems.

a and b, Soil extractable NH4+ (a) and NO3− (b) over the 2014–2018 rice growing seasons. Blue bars, aCO2. Red bars, eCO2. Data are presented with means ± standard error across treatment replicates (n = 3). c, Global distribution of the field experimental sites included in the second meta-analysis study. d, Meta-analysis of the eCO2 effect on soil nitrifiers and inorganic nitrogen pools across paddy rice and wetland ecosystems. The number of observations for each variable is shown next to the point. Error bars indicate 95% confidence interval (CI) of the mean net CO2 effect, which was calculated as the natural log of the response ratio (R), and was considered significant if 95% CI did not overlap with 0. Two-tailed Wilcoxon signed-rank test: AOB, P < 0.001; AOA, P = 0.35; NH4+, P < 0.001; NO3−, P < 0.001.

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Supplementary Fig. 1, Tables 1 and 2, Notes I and II and Methods.

Supplementary Data 1–7

Supplementary Datasets 1–7.

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Zhang, K., Lei, W., Zhang, H. et al. Inhibition of autotrophic nitrifiers in a nitrogen-rich paddy soil by elevated CO2. Nat. Geosci. 17, 1254–1260 (2024). https://doi.org/10.1038/s41561-024-01583-2

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