Microbiome(2024) 12:95
Masuda et al. Microbiome
https://doi.org/10.1186/s40168-024-01812-1

Open Access

RESEARCH

Global soil metagenomics reveals
distribution and predominanceof Deltaproteobacteria in nitrogen‑fixing
microbiome
Yoko Masuda1,2*†, Kazumori Mise3*†, Zhenxing Xu1, Zhengcheng Zhang1, Yutaka Shiratori4, Keishi Senoo1,2 andHideomi Itoh3*

Abstract
Background Biological nitrogen fixation is a fundamental process sustaining all life on earth. While distribution
and diversity of ­N2-fixing soil microbes have been investigated by numerous PCR amplicon sequencing of nitrogenase genes, their comprehensive understanding has been hindered by lack of de facto standard protocols for amplicon surveys and possible PCR biases. Here, by fully leveraging the planetary collections of soil shotgun metagenomes
along with recently expanded culture collections, we evaluated the global distribution and diversity of terrestrial
diazotrophic microbiome.
Results After the extensive analysis of 1,451 soil metagenomic samples, we revealed that the Anaeromyxobacteraceae and Geobacteraceae within Deltaproteobacteria are ubiquitous groups of diazotrophic microbiome in the soils
with different geographic origins and land usage types, with particular predominance in anaerobic soils (paddy soils
and sediments).
Conclusion Our results indicate that Deltaproteobacteria is a core bacterial taxon in the potential soil nitrogen fixation population, especially in anaerobic environments, which encourages a careful consideration on deltaproteobacterial diazotrophs in understanding terrestrial nitrogen cycling.
Keywords microbial community, soil microbiome, metagenomics, nitrogen fixation†

Yoko Masuda and Kazumori Mise contributed equally to this work.

*Correspondence:
Yoko Masuda
yokomasuda@g.ecc.u-tokyo.ac.jp; ygigico@gmail.com
Kazumori Mise
mise-33@aist.go.jp
Hideomi Itoh
hideomi-itou@aist.go.jp
1
Department of Applied Biological Chemistry, Graduate Schoolof Agricultural and Life Sciences, The University of Tokyo, 1‑1‑1 Yayoi,
Bunkyo‑ku, Tokyo 113‑8657, Japan
2
Collaborative Research Institute for Innovative Microbiology, The
University of Tokyo, 1‑1‑1 Yayoi, Bunkyo‑ku, Tokyo 113‑8657, Japan
3
National Institute of Advanced Industrial Science and Technology (AIST)
Hokkaido, 2‑17‑2‑1 Tsukisamu‑higashi, Toyohira, Sapporo, Hokkaido
062‑8517, Japan

4
Niigata Agricultural Research Institute, 857 Nagakura‑machi, Nagaoka,
Niigata 940‑0826, Japan© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which
permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to theoriginal author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line
to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory
regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of thislicence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Masuda et al. Microbiome(2024) 12:95

Introduction
Biological nitrogen fixation driven by diverse soil microorganisms is a distinct process providing the pedospherewith nitrogen, the major limiting factor for primary
production [1]. Microbial players for nitrogen fixation(diazotrophs) in the soil have drawn significant attention since their discovery in the late nineteenth century[2]. In particular, the distribution and diversity of the
diazotrophs in the soil have been one of the most active
research topics and is constantly updated along with theaccumulation of knowledge and technological innovations [3–5].
Although nitrogenase genes (nif) are conserved ina broad taxonomic range of prokaryotes [6], nif genes
derived from Alphaproteobacteria, Betaproteobacteria,
and Cyanobacteria have been frequently detected invarious soil environments such as farmland, grassland,
forests, rice paddy fields, riparian zones, and tundra by
PCR amplicon surveys targeting nif genes [7–11]. Consequently, these bacteria are considered the primary nitrogen fixers in soil [12, 13]. In our previous work, however,shotgun metagenomic and metatranscriptomic analysesof paddy soil at one site in Japan have detected highly
abundant nif genes and transcripts from the families
Anaeromyxobacteraceae and Geobacteraceae within Deltaproteobacteria (also classified as the phyla Myxococcota
and Desulfobacterota, respectively) compared with theconventional diazotrophic groups [14]. Several amplicon-based studies have also reported the occurrenceof Geobacteraceae nitrogenase genes in soils [15–18].
Considering their prevalence across many soil types asrevealed by 16S rRNA gene-based surveys [19–21], members of the families Anaeromyxobacteraceae and Geobacteraceae may thus represent universal and/or major
components of diazotrophic microbiome in various terrestrial environments. However, these clades, which are
well-known iron-reducing bacterial groups [22], havereceived considerably less attention as diazotrophs in soil
than the conventional groups.
One potential problem is that genomic information of
Anaeromyxobacteraceae and Geobacteraceae has beenpoorly represented in reference databases because pureisolates of these bacteria have been difficult to obtain.
Fortunately, recent studies significantly enriched the reference sequence databases by isolating dozens of novel
members within these families using our previously
developed slurry incubation method; preincubated soil
slurry and Reasoner’s 2A (R2A) agar supplemented with
fumarate were used as isolation source and medium,
respectively, as described in details in Materials andmethods section [23–31]. All of the novel isolates harbor nitrogenase genes, whereas some of them have beenshown to present diazotrophic activities [25, 26, 29, 30].

Page 2 of 16

Another problem is that amplicon sequencing tend
to incur major biases in microbiome studies. Universal
primers often fail to detect (even dominant) genes due tomismatches or abnormal GC contents of template DNA,
whereas they may amplify homologous but unrelated
genes [32–37]. Moreover, the primer sets (and accordingly PCR conditions) used for nitrogenase gene (typically nifH) amplification are not standardized among aplethora of amplicon sequencing studies [38]. This suggests that different studies bear different types anddegrees of PCR biases. These call for extensive analyses of
shotgun metagenomic data, rather than amplicon-based
data, to establish minimally biased knowledge on diazotrophic communities in terrestrial microbiomes.
In this study, we aimed to re-evaluate the global distribution and diversity of the terrestrial diazotrophic
microbiome considering the presence of Anaeromyxobacteraceae and Geobacteraceae bacteria. We scrutinizeda global trend of the terrestrial diazotrophic microbiome using 1,451 shotgun metagenomic datasets, making full use of recently published genomic information
on Anaeromyxobacteraceae and Geobacteraceae isolates.
Our analyses revealed that Anaeromyxobacteraceae andGeobacteraceae are ubiquitous constituents of the diazotrophic microbiome in terrestrial ecosystems, particularly with high dominance in anaerobic environments.

Results and discussion
Diversity of nif‑harboring genomes in public databases

We first reviewed the currently known diversity ofnitrogen-fixing prokaryotes in public databases. KEGG
included 7,152 bacterial genomes (KEGG ftp as of August
31, 2022), and 697 of them encoded all three structuralgenes of nitrogenase, namely nifH, nifD, and nifK. Amongthese genomes, those of Alphaproteobacteria, Firmicutes,
and Gammaproteobacteria, as well as Deltaproteobacteria, were abundant (Fig. 1a).
The representations of Geobacteraceae and Anaeromyxobacteraceae sequences in public databases wererecently improved. At the end of 2018, RefSeq contained
23 genomes from Geobacteraceae and 5 from Anaeromyxobacteraceae, whereas these numbers tripled by September 28, 2022. Approximately 50% of these increases
could be attributed to isolates obtained by the slurry
incubation method since 2019 (Table 1) [23–31], andall of these isolates bear the core nif genes (nifHDK) in
their genomes. Apart from these isolates, we obtained
two other distinct strains belonging to the genus Geomonas, namely Red32 (isolated from paddy soil in Joetsu,
Niigata, Japan) and Red276 (pond sediment in Myoko,
Niigata, Japan; Table 1). These strains displayed 96.3%–
97.4% similarity (based on 16S rRNA gene sequences) toall Geomonas type strains, which was below the standard

Masuda et al. Microbiome(2024) 12:95

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Fig. 1 Currently known diversity of diazotrophs. a A genome-based phylogenetic tree consisting of potential diazotrophic bacteria[i.e., the genomes of which harbor all three core genes of nitrogenase (nifH, nifD, and nifK)], including the genomes of new isolatesof Anaeromyxobacteraceae and Geobacteraceae (Table 1). The colors of branches and the band surrounding the tree denote the phyla
and proteobacterial classes. Genomes of families Anaeromyxobacteraceae and Geobacteraceae, the foci of the present study, are highlighted
with circled letters (A and G) and colored backgrounds (blue and pink, respectively). b Growth curves of the type strains of two type species
within the family Geobacteraceae, namely Geomonas oryzae ­S43T and Oryzomonas japonica ­Red96T. The two isolates were grown on MFM
medium with ­N2 as the sole nitrogen source. Average and standard deviation of each time point (n = 3) are indicated. Some error bars are shorter
than the symbol size

threshold (98.65%) for species delineation [39]. The
genomes of these strains also encoded nifHDK.
In addition to the presence of nif genes on the
genomes, we confirmed the nitrogen-fixing activities
of bacterial strains from these clades. In this study, wedemonstrated that two type species within Geobacteraceae, namely Geomonas oryzae ­S43T and Oryzomonas
japonica ­Red96T (Table 1) [27, 28], were able to grow on­N2 as the sole nitrogen source (Fig. 1b). While the acetylene reduction activity of some strains within Geobacter
and Geomonas has been previously tested [25, 29, 40],
the ammonium-independent steady growth of Geomonas
and Oryzomonas suggests that nitrogen fixation is energetically available. The present result, combined with thepreviously reported N­ 2-dependent growth and acetylene
reduction activity of Anaeromyxobacter and Geobacterstrains [26, 40], indicate that Anaeromyxobacteraceae
and Geobacteraceae are likely to be physiologically relevant to nitrogen fixation. We suspected that the use of
their genomes as references would yield a better sensitivity in shotgun metagenomic analyses of deltaproteobacterial diazotrophs.
Global distribution of diazotrophs in terrestrial
environments

To assess the global distribution of nitrogen-fixing
populations, we collected 1,433 shotgun metagenomic
datasets from public databases, namely NCBI SRA and
MG-RAST [41, 42], coming from various environments
including cropland soils, forest soils, grassland soils,
paddy soils, sediments (including wetlands), and tundra

soils (Fig. 2a and Table S1). Since metagenomes of Japanese soils (including volcanic soils) were poorly represented in public databases, we also collected 18 soil
samples in Japan (Table S2) and sequenced their metagenomes. It should be noted that we only used metagenomic data in the present study, which indicate thequantity and diversity of potential diazotrophic microbes
but do not serve as direct evidence of their diazotrophic
activities.
Following preprocessing and curation of these datasets (i.e., merging of paired-end reads, quality filtering),
we identified reads bearing nitrogenase genes (nifDK formolybdenum nitrogenase, vnfDK for vanadium nitrogenase, anfDK for iron-only nitrogenase [43]), 16S rRNA
genes, or single-copy ribosomal protein genes conservedin most bacterial genomes [44] (Table S3). The phylogenetic compositions of 16S rRNA gene sequences indicated that 100 of these datasets could be contaminatedby members of order Lactobacillales or plants’ plastids (amounting up to 80.5% of Lactobacillales or 71.6%
of Chloroplast 16S rRNA gene reads: Fig. S1), and theremaining 1,351 were used for further analyses (Fig. 2b).
Some of the 1,351 metagenomes were redundant (e.g.,technical replicates), so we clustered metagenomes takenfrom environmental samples within 1 km of each other.
This ended up in 321 samples (Fig. 2b), each considered
to bear independent information. The 321 samples wereoverall dominated by well-known soil-dwelling bacterial
clades such as phyla Proteobacteria, Acidobacteria, Actinobacteria, etc. (Fig. 2c) and showed no obvious hallmarksof abnormality or technical contamination.

Masuda et al. Microbiome(2024) 12:95

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Table 1 Novel bacterial members within the families Anaeromyxobacteraceae and Geobacteraceae that have been recently isolatedusing a slurry incubation method and published to date, including ones isolated in this study. Relevant publications, as well as
genomic information, are also indicated
StrainAccession No. of genomic data

Note

Reference

Anaeromyxobacteraceae
Anaeromyxobacter diazotrophicus ­Red267T

GCF_013340205.1[24, 26]

Anaeromyxobacter oryzae ­Red232T

GCF_023169945.1[24]

Anaeromyxobacter paludicola ­Red630T

GCF_023169965.1[24]

GCF_018919395.1[29]

Geobacteraceae
Geomonas azotofigens ­Red51T
Geomonas diazotrophica ­Red69

aT

GCF_018919385.1[29]

Geomesophilobacter sediminis ­Red875T a

GCF_016458275.1[31]

Geomonas propionica ­Red259T

GCF_016458235.1[31]

Geomonas anaerohicana ­Red421T

GCF_016458305.1[31]

Geomonas silvestris ­Red330T

GCF_014193515.1

Geomonas paludis ­Red736T

GCF_014193585.1[23]
GCF_023221575.1 is includedin KEGG[23]

Geomonas paludis RG22

GCF_023221575.1

Geomonas limicola ­Red745T

GCF_014193675.1

[30]
[23]

Oryzomonas japonica ­Red96T a

GCF_008802365.1[27]

Oryzomonas sagensis ­Red100T

GCF_008802355.1[27]

Oryzomonas rubra ­Red88T

GCF_008369015.1[27]

Geomonas oryzae ­S43T a

GCF_004117875.1[28]

Geomonas edaphica ­Red53T

GCF_004917075.1[28]

Geomonas ferrireducens ­S62T

GCF_004917065.1[28]

Geomonas terrae ­Red111T

GCF_004791675.1[28]

Geomonas fuzhouensis ­RG17T

GCF_020179575.1[30]

Geomonas agri ­RG53T

GCF_020179605.1[30]

Geomonas sp. Red32

JAKLOY010000000

This study

Geomonas sp. Red276

BLXW01000000

Geomonas oryzisoli ­RG10T

GCF_018986915.1

Included in KEGG

This study[25]

Geomonas subterranea ­RG2T

GCF_019063845.1

Included in KEGG

[25]

Geomonas nitrogeniifigens ­RF4T

GCF_019063885.1

Included in KEGG

[25]

Type species of each genus; ICNP: International Code of Nomenclature of Prokaryotes

From each of the 321 samples, we detected 110–
5,714,345 reads (median: 8,050 reads) of ribosomal protein genes listed in Table S3. The number of nitrogenase
gene reads were normalized by the number of ribosomal
protein gene reads, taking into account the differencesin gene lengths between orthologs (corrected by RPKM:
see Materials and Methods). The relative abundances ofnitrogenase gene reads were higher in paddy soils, sediments, and tundra soils (i.e., anaerobic environments)
than those in aerobic environments, namely cropland,
forest, and grassland soils (P < 0.05 in post-hoc pairwise Brunner–Munzel test with Bonferroni correction,
Fig. 2d; Please note that only four data belonged to tundra). On average, nitrogenase genes were detected 17.6
times more frequently in the anaerobic samples than
aerobic samples. This is consistent with both the wellestablished notion that biological nitrogen fixation isan anaerobic process and the oxygen-sensitive nature ofnitrogenase [45].
Relative abundances of nitrogenase gene reads exhibited major variations among samples from aerobic environments (i.e., cropland, forest, and grassland), withsome harboring low numbers, and others dominated bydiazotrophs. Although the reason for such variation is
not clear and require further experimental validation,
here we list several hypotheses. First, several soil physicochemical properties, including total carbon, nitrogen,and available phosphorus contents, have been shown toaffect the abundance of species which encode nitrogenase gene [16, 46]. It is also possible that cropland andgrassland samples are affected by the roots of leguminous
plants and nodule symbionts therein; alphaproteobacterial ­N2-fixing rhizobia such as Bradyrhizobium, Azospirillum, and Mesorhizobium were detected more frequently

Masuda et al. Microbiome(2024) 12:95

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Fig. 2 Overview of metagenomic datasets used in this study and distribution of diazotrophs therein. a The sampling locations for eachmetagenomic datasets used in this study. Six types of environments are differentiated by the shapes and colors of symbols. b Filtering procedureof metagenomic datasets. The filtering criteria, as well as the aggregation of geographically similar samples, are explained in the panel. c
Phylum-level prokaryotic community structure of the 321 metagenomic datasets estimated by 16S rRNA gene sequences. d The dominanceof nitrogen-fixing population in each environment. For each of the 321 metagenomic datasets, the ratio of reads per kilobase of reference sequence
per million sample reads (RPKM) of nitrogenase genes to the RPKM of ribosomal protein genes is displayed. The letters on the right side of the box
indicates the statistical significance in RPKM ratio between different environmental categories (P < 0.05, Brunner–Munzel test with Bonferroni’s
correction). First, second, and third quantiles are indicated by solid lines. The whiskers, if any, denote 1.5*[interquartile range] from first or third
quartilein legume crop soils than in non-legume crop soils [46,47]. Some samples from aerobic environments may belocally anaerobic, and this might explain the variance inthe relative abundance of diazotrophs. We also acknowledge the ambiguity in distinguishing forest or grassland
soils from wetland sediments. For example, samples from
Disney Wilderness Preserve (DWP), which are labeled
as “area of pastureland or hayfields” in MG-RAST andpresented the highest relative abundances of nitrogenase
genes among “grassland” samples, may have originatedfrom wetland-like environments, as the landscape of
DWP bears patches of wetlands [48].
Global diversity of diazotrophs in terrestrial environments

The taxonomic compositions of diazotrophic communities were further investigated for a more limited dataset of 88 samples, each of which comprised at least 50
sequences of nifD/K (Fig. 2b and Fig. S2). Please note that
nifD/K serve as more accurate markers of diazotrophs
compared with nifH (i.e., the conventional marker ofdiazotrophs [36]: see Materials and Methods for detail).

Reads encoding nifD/K from class Deltaproteobacteria,
especially Geobacteraceae and Anaeromyxobacteraceae,
were consistently dominant in anaerobic environments
such as paddy soils and sediments, as well as in some of
the aerobic samples (Fig. 3ab). While nitrogenase genes
have a complicated history of horizontal gene transfer (HGT) that may hinder accurate taxonomic annotation [49, 50], Deltaproteobacterial NifD/K within GroupI nitrogenase [49] are monophyletic (bootstrap value =1.00, Fig. S3) and no clear hallmark of recent HGT [51].
Fortunately, a major part of deltaproteobacterial NifD/K
within metagenomes belonged to this group (Fig. S4), andtherefore it is unlikely that the dominance of Deltaproteobacteria nifD/K in this metagenomics is a byproductof HGT. In addition, the proportion of deltaproteobacterial 16S rRNA genes (i.e., genes less prone to HGT) andfrequency of deltaproteobacterial nitrogenase genes weresignificantly correlated (Fig. S5: Spearman’s ρ = 0.859
and P < 2.2×10–16 when tested using all samples; ρ =0.738 and P < 2.2×10–16 when tested using only anaerobic samples). These results suggest that members ofMasuda et al. Microbiome(2024) 12:95

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Fig. 3 Phylogenetic compositions of nitrogenase genes in the metagenomic datasets with at least 50 reads of nifD and nifK (n = 88 in total). a
Upper panel: phylum- and proteobacterial class-level composition. Lower panel: breakdown of deltaproteobacterial composition at the family level.
The category “Possibly Geobacteraceae or Anaeromyxobacteraceae” comprises deltaproteobacterial reads that were unannotated at the family levelbut received higher-level annotations consistent with family Geobacteraceae or family Anaeromyxobacteraceae. b Family-level distribution of nifDand nifK reads. The correspondence with the phylum- and proteobacterial class-level taxonomy is noted in parentheses: Delta, Deltaproteobacteria;
Alpha, Alphaproteobacteria; Gamma, Gammaproteobacteria; Beta, Betaproteobacteria; Firm, Firmicutes; Actino, Actinobacteria; Cyano, Cyanobacteria.
The area size (not the radius) of each plot is proportional to the relative abundance of each family within each dataset

Geobacteraceae and Anaeromyxobacteraceae are one ofthe prominent drivers of nitrogen fixation in terrestrial
ecosystems. While previous studies in wheat-soybean
rotation croplands [16] and paddy soils [14, 52] are in linewith our results, the metagenomic datasets analyzed here
covering a wide range of environments provide a generalizable insight into the potential contributions of theseclades to nitrogen fixation processes in the pedosphere.
Other major clades within nitrogen-fixing populations included Alphaproteobacteria, such as Nitrobacteraceae and Rhizobiaceae (Fig. 3ab), although some (e.g.,
Bradyrhizobium and Rhizobium) in these families are
symbiotic diazotrophs and thus possibly incapable ofindependent nitrogen fixation outside their host plants.

The community compositions were significantly different between the aerobic and anaerobic samples (permutational analysis of variance (PERMANOVA) of UniFrac
distances, ­R2 = 0.114, P = 0.001), as further evidenced
by a distinct grouping of the two types of samples innonmetric multidimensional scaling (NMDS) analysis(Fig. S6).
Another characteristic of the diazotrophic communities of anaerobic environments (with the exception oftundra) is the high similarity between samples (Fig. 3).
While all the paddy soil and sediment samples are dominated by Deltaproteobacteria and present overall low
beta-diversity levels, environments such as cropland, forest, and grassland are dominated by more diverse cladesMasuda et al. Microbiome(2024) 12:95

of diazotrophs showing high beta-diversity levels. One
possible explanation is the heterogeneity among aerobic
samples: some of the cropland, forest, and grassland samples may be associated with leguminous vegetations (i.e.,
affected by nodule-associated bacteria) [18, 46] or originated from soil physicochemical properties/conditions[16], but they are not explicitly considered in this study.
Another explanation for this divergence in community
structures is ecological drift [53, 54]. Diazotrophs havesmaller population sizes in aerobic samples (Fig. 2d);thus, their communities are expected to be more sensitive to ecological drift, resulting in increased beta-diversities between communities as previously shown [55].
Although we used a limited dataset of 88 samples bearing at least 50 nifDK sequences for the taxonomic composition analysis, the bias introduced by this manipulationis unlikely to be critical. First, the selected samples do notnecessarily present high relative abundances of diazotrophs, since the number of total reads greatly varies
between samples (Fig. S2ab). Second, the abundance ratioof nitrogenase genes to ribosomal protein genes explain
only 5.0% the phylogenetic diversity of nifDK ­(R2 = 0.050,
P = 0.036) within aerobic samples (Fig. S2c).
As a side note, we also analyzed the abundance andphylogeny of nifH, a conventional marker for nitrogenfixing populations. Because the lengths of nifH, nifD, andnifK genes are approximately 3:5:5 (Table S3), the number of these genes should also be around 3:5:5 in eachmetagenome. However, some samples harbored disproportionally higher number of nifH compared with nifD/K:
nine of the metagenomic samples included 1.5 times orhigher number of nifH reads than can be expected fromthe number of nifD/K reads (blue points in Fig. S7a). Thisimplies that some soil samples bear significant amount ofpseudo-nifH genes [36], which are encoded on prokaryotic genomes lacking other essential components ofnitrogenase genes (e.g., nifD and nifK). We suspect that
nifD/K, rather than nifH, serve as a reliable marker genefor nitrogen-fixing populations (especially in shotgun
metagenomic studies). Regarding 79 samples with lower
amounts of pseudo-nifH, deltaproteobacterial nifH were
dominant (Fig. S7b) in congruence with the results of
nifDK analyses (Fig. 3a).
An approximate estimation of the global dominanceof deltaproteobacterial diazotrophs

Analyses of the global metagenomic dataset indicatedthat anaerobic environments harbor high abundancesof diazotrophic prokaryotes and that Anaeromyxobacteraceae and Geobacteraceae are the dominant diazotrophsin these environments. Wetlands (possibly including
waterlogged paddy soils) represent between 5.2% [56]and 8% [57] of all lands, with microbial biomass carbon

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therein amounting to 10.3% of the microbial biomassin all lands [calculated from the data presented in [56]].
Thus, although wetland is a limited area of land, giventhat the relative abundance of nitrogen fixers was 17.6
times higher in anaerobic microbial communities than in
aerobic ones (Fig. 2d), wetland could be a large reservoirof nitrogen fixers on terrestrial environments.
Biases behind amplicon sequencing of nitrogenase genes

The prevalence of diazotrophic Geobacteraceae has actually been reported in some of PCR amplicon sequencing
analyses of nif genes [15, 16, 58], but the dominance ofAnaeromyxobacteraceae has been overlooked in such
PCR-based analyses. We suspected that this discrepancy
is due to PCR biases behind amplicon sequencing. It is
commonly accepted that results of amplicon sequencing are dependent on a series of PCR conditions such as
primer sets and DNA polymerases [37, 59]. The GC contents of templates, as well as primer mismatches, can also
affect the amplification efficiency and therefore cause
biases [34, 35, 37]. Notably, nif genes of Anaeromyxobacteraceae have higher GC contents (65.6–69.7%) thanthose of the other bacteria (Fig. S8).
To elucidate the PCR biases of nif genes, we performed
amplicon sequencing of nitrogenase genes in six soil
DNA samples and compared the results directly withshotgun sequencing of the same samples. We preparedamplicon libraries under ten PCR conditions with different primer sets and DNA polymerases (Tables S4 and S5).
Please note that we here targeted nifH, rather than nifDK,
for the sake of consistency with conventional ampliconsequencing methods. Primer mismatches will not be
extensively discussed here, because nifH of Anaeromyxobacteraceae and other clades present similar identities tothe primers (Fig. S9).
As expected, we found that the phylogenetic compositions of nifH amplicons were dependent on type of DNApolymerases and primer sets (Fig. S10a–f ), and the discrepancy was particularly remarkable in the proportionof Anaeromyxobacteraceae nifH. Anaeromyxobacteraceae
nifH were consistently more highly represented in KOD
One libraries than in DreamTaq libraries (Fig. S10g).
In addition, their proportion in shotgun metagenomic
sequences were comparable to those in KOD One libraries, although dependent on sample identities and primer
sets (Fig. S10h). These suggest that DreamTaq failed toamplify Anaeromyxobacteraceae nifH. What we focus
on here is the high GC contents of nif genes in Anaeromyxobacteraceae (Fig. S8). According to the manufacturers’ reports (https://​lifes​cience.​toyobo.​co.​jp/​user_​data/​pdf/​produ​cts/​manual/​KMM-​101_​201.​pdf[inJapanese; accessed Jan 5, 2024]), KOD One is robust to
amplify GC-rich templates, while DreamTaq shows a low

Masuda et al. Microbiome(2024) 12:95

performance (https://​www.​therm​ofish​er.​com/​order/​catal​
og/​produ​ct/​EP1701?​SID=​srch-​srp-​EP1701[accessed
Jan 5, 2024]), which aligns with the present results. We
speculate that GC richness of Anaeromyxobacteraceae
nifH may be one reason why they have been poorly represented in amplicon surveys.
We also argue that these results represent the major
biases behind amplicon sequencing. Provided that nifH
gene compositions were largely dependent on the typeof DNA polymerases and primer sets, comparing theresults obtained from multiple studies might be difficult.
In this respect, meta-analysis of shotgun metagenomic
data should be a straightforward, solid, and less biased
approach (as has been discussed in Kim et al. [60]).
Even in shotgun metagenomic sequencing, it should
be noted that the abundance of diazotrophic Anaeromyxobacteraceae may be underestimated. First, library
preparation for shotgun sequencing often involves PCR(typically 8–12 cycles), which may fail to amplify GC-richnucleotide fragments [61, 62]. Second, Illumina sequencing technology is known to be biased against sequencing
GC-rich nucleotide fragments even in shotgun sequencing [63]. Considering these biases, the proportion of
Anaeromyxobacteraceae in the soil, the nitrogenase
genes of which are GC-rich (66.9%–69.0%, 65.6%–67.0%,
and 66.9%–69.7% for nifH, nifD, and nifK, respectively,
Fig. S8), might be even higher than estimated in thisstudy. The former issue may be addressed using PCR-freelibrary preparation protocols [62]. Long-read sequencers (i.e., PacBio and Nanopore) are less prone to GC
bias [63] and potentially rectify the latter issue, although
their current yield is orders of magnitude smaller thanthose of short-read sequencers such as Illumina HiSeq
and NovaSeq, and thus currently not a good fit for thecharacterization of samples as heterogenous and rich indiversity as soil metagenomes.
Benefits of expanding culture collection

Previous and current efforts to enrich culture collections[23, 24, 26–29, 31] have substantially expanded the available repertoire of Anaeromyxobacteraceae and Geobacteraceae strains. In fact, an average of 56.9% and 23.9%
of NifD/K sequences derived from Anaeromyxobacteraceae and Geobacteraceae members, respectively, displayed higher similarity to our novel strains than to any
other nitrogenase sequence in KEGG from these families(Fig. 4).
Interestingly, this trend was consistent among a wide
variety of environments including aerobic and anaerobic
environments, although the majority of the novel strains
were isolated from paddy soils or sediments under anaerobic conditions. Based on the present and previous findings, paddy soils and sediments appear to be promising

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Fig. 4 Contribution of nitrogenase gene sequences from newly
isolated strains in the bioinformatic analyses of metagenomes.
a A schematic of the analysis. NifD/K sequences annotatedas Anaeromyxobacteraceae or Geobacteraceae in metagenomes were
mapped onto already known sequences of NifD/K (right-upper)
and those in our new isolates (right-bottom). Only the top hit for eachquery sequence (i.e., one from metagenomes) was considered. b
Relative abundance of metagenome-derived NifD/K sequencesthat were most similar to already known sequences (yellow)
and those from our new isolates (green), as well as those equallysimilar to the nitrogenase genes of already known genomes and our
new isolates (dim green), are summarized. Only datasets with 10
or more sequences of NifD/K for each family are displayed

environments for isolating free-living diazotrophs, representing diverse terrestrial environments including aerobic environments such as cropland, forests and grassland.

Conclusions and outlook
Contrary to the conventional view, our large-scale comparative metagenomics analyses revealed the global
distribution and substantial abundance of Anaeromyxobacteraceae and Geobacteraceae in terrestrial
diazotrophic microbiome, highlighting the potentialMasuda et al. Microbiome(2024) 12:95

importance of Deltaproteobacteria members (phyla
Myxococcota and Desulfobacterota) in terrestrial, especially anaerobic, ecosystems. Although Anaeromyxobacteraceae and Geobacteraceae have been well known asiron- and other metals- reducing bacteria in soil environments, this study is the first to report that they are themost dominant group of terrestrial diazotrophic microbiome on a global scale.
Moreover, nitrogen-fixing bacteria have long been
considered useful microorganisms for improving soil
nitrogen fertility, and methods to promote their activity have been developed for sustainable agriculture [64].
For example, in paddy soils, recent studies showed thatapplication of iron-bearing materials could enhance thenitrogen-fixing activities of indigenous iron-reducing
bacteria within the families Anaeromyxobacteraceae andGeobacteraceae and maintain rice yields under reduced
nitrogen-fertilizer application [65, 66]. Given the ubiquityof iron-reducing diazotrophs (Fig. 3), this strategy may
be effective in a variety of other crop fields. More generally, careful and precise updates of our understanding offunctional microorganisms in soil environments should
advance such attempts towards sustainable agriculture.
It should be noted that the pivotal thing for microbiome discovery is to improve the accuracy of metagenomics, i.e., to expand the available genomic informationof microorganisms. In this study, thousands of obtained
nitrogenase sequences exhibited high proximity to
our newly isolated strains. Our results warrant further
efforts to improve culture collections, which would fill
the knowledge gaps in the diversity and ecology of diazotrophs. Especially in soil environments, the enormity ofuncultured but predominant clades of prokaryotes, as
represented by members of Acidobacteria and Verrucomicrobia [67–69], is widely recognized. To advance ourknowledge of the terrestrial diazotrophic microbiome,
strategies for their cultivation and isolation should bealso updated, for example, by using single-cell sorting.
There is no doubt that Anaeromyxobacteraceae andGeobacteraceae are important diazotrophic members insoils that should not be underestimated or undervalued
as they have been. However, unfortunately, it is impossible to estimate how much Anaeromyxobacteraceae andGeobacteraceae actually contribute to nitrogen fixation insoil environments based on the results of this study alone,since the contribution cannot be directly inferred fromthe detected amount of genes. The insights into the contribution of each diazotrophic taxon to terrestrial nitrogen fixation will be foreseeable, for instance, throughstable isotope probing (SIP) with 15N2 under more natural conditions, using various soil samples. Although preliminary, a recent study based on 15N-DNA-SIP analysis
revealed a high contribution of Anaeromyxobacteraceae

Page 9 of 16

and Geobacteraceae for nitrogen fixation in a paddy soil[70], supporting our conclusion.

Materials and methods
Isolation and genomic sequencing of new soil strains

The Geomonas strains Red32 and Red276 were isolated from paddy soil (Joetsu, Niigata, Japan) and pond
sediment (Myoko, Niigata, Japan) following the slurry
incubation method used to isolate new members of Geobacteraceae [27, 28]. The soils collected from the paddy
field in Nagaoka, Niigata, Japan were air-dried, placed ina 15-mL serum bottle and suspended in distilled water(soil:water, 2:3, w/v). After autoclaving at 120°C for 20
min, 0.1 g of undried soil was added to the bottle as a
microbial inoculum with and without vitamin solution
for strains Red276 and Red32, respectively [26]. Then,
we sealed the bottles with butyl rubber stoppers andaluminum caps, replaced headspace gas with with N­ 2/
CO2 (80:20, v/v), and incubated them at 30°C for 2 weeks
without shaking. Afterward, 200 μL of incubated soil
slurry was transferred to a new bottle of autoclaved soil
slurry and incubated at 30 °C for 2 weeks. After repeating this step once (for strain Red276) or twice (for strain
Red32), the incubated soil slurry was streaked on 1.5%
agar plates of the R2A broth “DAIGO” (Nihon Pharmaceutical, Tokyo, Japan) supplemented with 5 mM disodium fumarate. The plates were incubated at 30°C for 10
days under anaerobic conditions using the AnaeroPack
system (Mitsubishi Gas Chemical, Tokyo, Japan). Redcolored colonies, a typical hallmark of Geobacteraceae
strains [23, 27, 28, 71, 72], were purified by a single-colony isolation using the same medium plates. Genomic
DNA was extracted from the two isolated strains using a
DNeasy Blood and Tissue Kit (Qiagen, Hilden, Germany)and sequenced using an Illumina HiSeq sequencer (Illumina, CA, USA) for 2×150 paired-end configuration. The
resulting sequences were assembled using Velvet v1.2.10[73] as previously described [27, 28].
Diazotrophic activity assay

Following a 5-day culture in nitrogen-free modified
freshwater medium (MFM) as previously described [27,28], the cells of Geomonas oryzae ­S43T and Oryzomonas
japonica ­Red96T were transferred to serum bottles containing 20 mL of nitrogen-free MFM [28] and headspace gas was replaced with ­N2 gas. No contamination ofammonia in used ­N2 gas was confirmed by no growth ofnon-diazotrophic Anaeromyxobacter strain, A. dehalogenans 2CP-1T [26]. Bacterial growth was monitored bymeasuring the suspension absorbance using a spectrophotometer (UV-1900 UV-visible spectrophotometer,
Shimadzu, Kyoto, Japan) at a wavelength of 600 nm. The
experiments were performed in triplicate.

Masuda et al. Microbiome(2024) 12:95

Preparation of custom database

We used KEGG database (as of August 31, 2022) for
functional gene annotations [74]. To increase the sensitivity for genes from Anaeromyxobacteraceae and Geobacteraceae, we customized KEGG database by adding
genomes belonging to these families obtained using
slurry incubation methods (Table 1). Genomes alreadyincluded in KEGG were not added. We predicted theircoding sequences (CDS) using Prodigal [75] with default
parameters, annotated them using KofamScan version 1.3.0 and KOfam version 2022-08-01 with default
parameters [76], and concatenated the CDS with KEGG
database (including those received no K number). The
phylogenies of NifD and NifK within Group I [49] were
determined using MAFFT v7.505 (with “--auto” option)
and FastTree 2.1.11 [77, 78] with a bootstrap test of 100
iterations (otherwise default parameter settings). For thebootstrapping tests, we also used “CompareToBootstrap.
pl” script (http://​www.​micro​beson​line.​org/​fastt​ree/​treec​
mp.​html, accessed April 18, 2023) to merge the resampled trees.
Phylogenetic analysis of bacterial genomes harboring nif
genes

From the aforementioned custom database, we screened
genomes harboring a set of nif core genes, namely nifH
(K02588 in KEGG), nifD (K02586), and nifK (K02591).
Archaeal genomes were excluded from the analysis. The
universal single-copy gene sequences were identified
from each genome, translated amino acid sequences,and mapped onto multiple sequence alignment (MSA) of
GTDB R207 using GTDB-Tk v2.1.0 [44, 75, 79, 80]. Here“identify” and “align” commands were used with default
parameter settings. The MSA was fed into FastTree(default parameters) and a phylogenetic tree was constructed. The tree was manually rerooted using Cyanobacteria as the outgroup [81] and visualized on the iTOL
server [82].
GC content of 16S rRNA genes and nitrogenase genes
among bacterial genomes

Ribosomal RNA genes were identified from each of thebacterial genomes in the custom database explained
above using barrnap version 0.9 (https://​github.​com/​tseem​ann/​barrn​ap; accessed April 18, 2023). Only 16S
rRNA sequences with 1000 bases or longer were picked.
For each genome with at least one valid 16S rRNA genesequence and all of the identified nifH, nifD and nifK
(identified as previously described), the GC contents of
16S rRNA genes, nifH, nifD, and nifK were calculated.
When a genome had multiple copies of each gene, GC

Page 10 of 16

content was calculated for the concatenated sequence of
these copies. Any ambiguous base was excluded from thecalculation of GC content.
Soil collection and shotgun metagenomic sequencing

We collected 18 surface soil samples from various agricultural fields in Japan at an approximate depth of 0–5
or 0–10 cm (Table S1). Following the removal of plant
residues and additional water from the surface, the soil
samples were stored at −80 °C or −30 °C until further
use for DNA extraction. Soil DNA was extracted from
0.5 g (wet weight) of each soil sample using the ISOIL for
Beads Beating Kit (Nippon Gene, Tokyo, Japan) according to the manufacturer’s instruction with the following modifications: prior to the beads beating step, 0.02
g skim milk was added to the lysis buffer to improve theextraction efficiency [83] and post-elution purification
using RNase A (Takara, Shiga, Japan) and DNA Clean &Concentrator (Zymo Research) according to the manufacturer’s introduction. Purified DNA was quantified
using Qubit 2.0 Fluorometer (Invitrogen, Carlsbad, CA,
USA) with Qubit dsDNA HS Assay Kits (Invitrogen). The
construction of DNA libraries, shotgun sequencing onan Illumina MiSeq sequencer, and merging of paired-end
sequences were performed as described previously [14].
Regarding the other 6 soil samples, DNA was extracted
from 0.25 g of each soil using DNesay PowerSoil Pro
Kits (QIAGEN, Hulsterweg, Netherland) following the
manufacturer’s instruction. Shotgun sequencing library
was prepared using MGIEasy FS DNA Library Prep
(MGI Tech, Guangdong, China), where the duration offragmentation reaction was customized to four minutes
and library amplification was performed for eight cycles.
MGIEasy Circularization Kit and DNBSEQ-G400RS
High-throughput Sequencing Kit Set were used to construct DNBs, which were sequenced on DNBSEQ-G400(MGI Tech) under 2x200 bp paired-end mode. Soil
pH(H2O) and electrical conductivity were measured ina suspension sample with soil-water ratio of 1:5 (w/w).
Soil total carbon and nitrogen contents were determinedusing dry combustion method. Crop types and chemical
properties of Japanese soils used in this study were summarized in Table S2.
Collection of publicly available metagenomic data
and their quality assessment

We further collected reusable datasets of bulk soil
metagenomes on INSDC [84] and MG-RAST [85] that
met the following criteria: (i) derived from outdoor samples exempted from post-sampling treatments that canaffect the microbial community structure; (ii) sequenced
on Illumina MiSeq, HiSeq, MiniSeq, NextSeq or NovaSeq(i.e., state-of-the-art, highly accurate sequencers); andMasuda et al. Microbiome(2024) 12:95(iii) reported in the peer-reviewed literature (with the
exception of data obtained by the National Ecological Observatory Network). Moreover, the datasets fromrhizosphere soils were not used in this study because
they are extensively and dynamically affected by theplant roots [86] and not representative of the soil microbial communities. In total, we collected 1451 datasets
as listed in Table S1 [47, 87–121]. The latitude and longitude of each sampling site were obtained from public
databases [INSDC BioSamples database [122] and MGRAST] and verified with the descriptions in each publication. The INSDC data were directly obtained from DDBJ
server, whereas those on MG-RAST were fetched using
MG-RAST API (with the option “file=050.1”).
The collected metagenomic data underwent extensive
curations, followed by homology searches to detect nitrogenase genes, ribosomal protein genes, and 16S rRNA
genes. Detailed procedures are provided in the supplementary information. After a series of data curation, we
decided to use 1,333 metagenomes from public databases
and newly sequenced 18 metagenomes for downstream
analyses. Some of the metagenomes were geographicallyredundant, so we merged metagenomes from samples
taken within < 1 km and treated them as one sample.
The distances between sampling locations were calculated based on the latitude and longitude of each sample
using the geodesic module in GeoPy (https://​geopy.​readt​
hedocs.​io/​en/​stable/#; accessed Jan 5, 2024).
Gene annotations of metagenomic reads

To determine the nitrogen-fixing populations within eachmetagenomic dataset, the filtered sequences were subjected to homology search against the custom databaseexplained above (i.e., KEGG database supplemented withAnaeromyxobacteraceae and Geobacteraceae genomes),
followed by the taxonomic annotation of nitrogenase
gene reads. In short, we determined the relative abundance of nitrogenase-harboring prokaryotes and theirtaxonomic composition for each sample.
Although the details are explained in the supplemental
text, here we note three key strategies. First, we used nifD,
nifK, vnfD, vnfK, anfD, and anfK as the marker genes.
nifH was not used for this purpose because the partial
primary structure of NifH can be confused with those ofother proteins irrelevant to nitrogen fixation [36]. Second, we normalized the number of reads by those of single-copy prokaryotic ribosomal protein genes [81], rather
than by the total number of metagenomic reads that
may be affected by plant- and animal-derived sequences.
Third, we used phylogenetic placement, rather than asimple homology search, for taxonomic annotation of nif
gene reads. The reliability of each taxonomic annotation
was calculated based on the likelihood of phylogenetic

Page 11 of 16

relationships between metagenomic reads and reference
sequences, and therefore we were able to abandon uncertain annotations. For example, short fragmented reads
may bear little phylogenetic signals, and annotations ofsuch reads were to be unreliable and discarded.
Beta‑diversity analyses

Beta-diversity between any pair of diazotrophic communities was calculated using the average of UniFrac
distances for NifD and NifK, which were determinedbased on the results of phylogenetic placement. We used
NMDS with two dimensions to summarize overall betadiversity between communities. We also performed PERMANOVA with 999 times permutation to test the null
hypothesis that community structures of diazotrophs are
similar between aerobic and anaerobic environments.
Homology analyses between NifD/K of metagenomes
and isolate genomes

We further mapped the NifD/K sequences annotatedas family Anaeromyxobacteraceae or Geobacteraceae inmetagenomic reads to NifD/K sequences from that family in our custom database using the Needleman–Wunschalgorithm implemented in USEARCH v11.0.667 [123].
We obtained the sequence similarity between each readand its nearest sequence in the database. We counted thenumber of reads for which the nearest sequence is fromthe genomes of bacterial isolates obtained via the slurry
incubation method (Table 1).
Amplicon sequencing of nitrogenase genes using popular
primer sets

We compared the results of shotgun metagenomic
sequencing and amplicon sequencing of nitrogenase
genes using six of the Japanese soil samples. Using thefour pairs of universal primers (Table S4) and three DNApolymerases that differ in performance (DreamTaq DNA
Polymerase [ThermoFisher Scientific], Ex Taq Hot Start
Version [Takara], and KOD One [TOYOBO]), and we
amplified nifH genes contained in each soil metagenome.
Here we performed two-step tailed PCR to construct
Illumina library, consisting of the first PCR to amplify
nifH genes and the second PCR to attach index sequences
to the amplicons. The amplicon of first PCR were cleaned
up using AMPure XP (Beckman Coulter, Brea, CA, USA)
before subjected to the second round of PCR. Detailed
PCR conditions are summarized in Tables S4 and S5. The
final PCR products were electrophoresed on agarose gels,purified using Wizard® SV Gel and PCR Clean-Up System (Promega, Madison, WI, USA), and sequenced on
Illumina iSeq in a paired-end mode (151 bp × 2). For eachcombination of soil samples, primer pairs, and DNA polymerases, we amplified nifH genes and sequenced them

Masuda et al. Microbiome(2024) 12:95

in triplicates. The obtained reads underwent error correction using DADA2 [124], and the amplicon sequencevariants (ASVs) were further filtered to eliminate chimeras and non-specific amplicons. The filtered ASVs were
taxonomically annotated using phylogenetic placement.
Details are explained in supplemental method.
Estimation of mismatches between nif‑harboring genomes
and nifH universal primers

To determine the mismatches between prokaroytic nitrogenase genes and their universal primers, we mapped
sequences of seven primers (PolF, PolR, nifH-F, nifHR, Ueda19F, Ueda407R, and univ463r: Table S4) onto
12 prokaryotic nifH sequences (Anaeromyxobacter sp.
Fw109-5, Anaeromyxobacter sp. K, A. diazotrophicus­Red267T, A. oryzae ­Red232T, A. paludicola ­Red630T,
Azospirillum brasilense ­Sp7T, Azotobacter vinelandii DJ,
Bradyrhizobium diazoefficiens ­USDA110T, Clostridium
acetobutylicum ­ATCC824T, Frankia casuarinae ­CcI3T,
Geomonas oryzae ­S43T, and Oryzomonas japonica­Red96T). We referred to annotations on KEGG or NCBI
RefSeq to collect nifH sequences. In cases where one
genome owned multiple copies of nifH, we selected one
copy that was accompanied by nifDK in their neighborhood [36]. The collected nifH genes were aligned using
MAFFT v7.505 (with “--auto” option), and then theprimer sequences were manually aligned onto the MSA.
Throughout the study, we used SeqKit v0.16.1/v2.2.0[125] and R 4.0.5/4.1.1 [126], including the package“vegan” [127], to handle fastq and fasta files and to perform statistical tests, respectively.

Supplementary Information
The online version contains supplementary material available at https://​doi.​
org/​10.​1186/​s40168-​024-​01812-1.
Supplementary Material 1.
Supplementary Material 2.
Supplementary Material 3.
Supplementary Material 4.
Acknowledgements
Part of the metagenomic data used in this study was provided by the National
Ecological Observatory Network (NEON) via MG-RAST. We thank Haruka
Ooi and Emiko Kobayashi (National Institute of Advanced Industrial Scienceand Technology) for literature survey, Yumi Sugisawa (National Instituteof Advanced Industrial Science and Technology) and Kawata Laboratory(Tsukuba, Ibaraki, Japan) for performing experiments, and anonymous farmers
for providing soil samples. Computations were partially performed on the NIG
supercomputer at ROIS National Institute of Genetics and the SHIROKANE
supercomputer at Human Genome Center, The Institute of Medical Science,
The University of Tokyo.
Authors’ contributions
Y.M., K.M., K.S., and H.I. designed the study and supervised the project. Y.M.,
Z.X., and Z.Z. performed genomic sequencing and diazotrophy assays ofbacterial strains. K.M., Y.S., and H.I. collected Japanese soil samples, and Y.M.

Page 12 of 16

and K.M. performed metagenomic sequencing of these samples. Y.M. and H.I.
performed the primary bioinformatic analysis of the metagenomic dataset.
K.M. curated and analyzed genomic and metagenomic datasets, and performed amplicon sequencing analysis. Y.M., K.M., and H.I. wrote the paper with
substantial input from all authors.
Funding
This work was financially supported by the CANON Foundation, JSPS KAKENHI
Grant Numbers JP20H00409, JP20H05679, JP20K15423, and JP22K18029,
MEXT KAKENHI Grant Number JP22H04894, JST-Mirai Program grant JPMJMI20E5, and JPNP18016 commissioned by the New Energy and Industrial
Technology Development Organization (NEDO).
Availability of data and materials
Genomic sequences obtained in this study have been deposited in GenBank.
Shotgun metagenomic and amplicon sequences have been deposited in
DDBJ DRA. See Tables 1, S1, and S6 for accession numbers.

Declarations
Ethics approval and consent to participate
Not applicable.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Received: 28 April 2023 Accepted: 9 April 2024

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