# Microbiome associated to an H2-emitting zone in the São Francisco basin Brazil

Otávio Henrique Bezerra Pinto, Rafael da Silva Oliveira, Brendo Ramos Ferreira, Julianna Peixoto, Maria Regina Silveira Sartori, Betania Ferraz

Quirino, Fabrice Brunet, Ricardo Henrique Kruger

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Otávio Henrique Bezerra Pinto, Rafael da Silva Oliveira, Brendo Ramos Ferreira, Julianna Peixoto, Maria Regina Silveira Sartori, et al. Microbiome associated to an H2-emitting zone in the São Francisco basin Brazil. Environmental Microbiome, 2024, 19 (1), pp.80. 10.1186/s40793-024-00627-9. [https://doi.org/10.1186/s40793-024-00627-9](https://doi.org/10.1186/s40793-024-00627-9). [hal-04778028](https://HAL.inhal-04778028)

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# Microbiome associated to an H₂-emitting zone in the São Francisco basin Brazil

Otávio Henrique Bezerra Pinto¹,<fnref n="2" />,<fnref n="3" />, Rafael da Silva Oliveira¹, Brendo Ramos Ferreira¹, Julianna Peixoto¹, Maria Regina Silveira Sartori<fnref n="4" />, Betania Ferraz Quirino<fnref n="5" />, Fabrice Brunet<fnref n="6" /> and Ricardo Henrique Kruger¹*

**Abstract**

**Background** Dihydrogen (H₂) natural gas is a clean and renewable energy source of significant interest in the transition to sustainable energy. Unlike conventional petroleum-based fuels, H₂ releases only water vapor upon combustion, making it a promising alternative for reducing carbon footprints in the future. However, the microbial impact on H₂ dynamics in H₂-emitting zones remains unclear, as does the origin of H₂ — whether it is produced at greater depths or within shallow soil layers. In the São Francisco Basin, soil hydrogen concentrations of approximately 200 ppm were identified in barren ground depressions. In this study, we investigated the microbiome associated with this area using the 16S rRNA gene sequencing, with a focus on metabolic processes related to H₂ consumption and production. Soil samples were collected from two monitored (< 1 m) depths – 10 cm and 1 m – in the emission zone, which is predominantly covered with pasture vegetation, and from an adjacent area with medium and small trees.

**Results** Our findings suggest that the H₂-emitting zone significantly influences the composition and function of the microbiome, with *Bacillus* emerging as the dominant genus. In contrast to typical Cerrado soil, we observed a higher prevalence of *Actinobacteriota* (~40%) and *Firmicutes* (~20%). Additionally, we identified an abundance of sporulating bacteria and taxonomic groups previously described as H₂-oxidizing bacteria.

**Conclusions** The H₂-emitting zone in the São Francisco Basin presents a unique opportunity to deepen our understanding of the impact of H₂ on microbial communities. This study is the first to characterize a natural H₂-associated bacterial community in Cerrado soil using a culture-independent approach.

**Keywords** Cerrado, Natural hydrogen, H₂-oxidizing bacteria, Microbiome

<footnote>*Correspondence:
Ricardo Henrique Kruger
kruger@unb.br
¹Laboratory of Enzymology, Institute of Biological Sciences, Department of Cell Biology, University of Brasília, Brasília, Brazil</footnote>

<footnote n="2">²Genomics for Climate Change Research Center, Universidade Estadual de Campinas, Campinas, SP 13083-875, Brazil</footnote>

<footnote n="3">³Centro de Biologia Molecular e Engenharia Genética, Universidade Estadual de Campinas, Campinas, SP 13083-875, Brazil</footnote>

<footnote n="4">⁴Ecosystem Ecology, Institute of Biological Sciences, Department of Ecology, University of Brasília, Brasília, Brazil</footnote>

<footnote n="5">⁵Microbiology Graduate Program, Institute of Biological Sciences, University of Brasília, Brasília, Brazil</footnote>

<footnote n="6">⁶University Grenoble Alpes, University Savoie Mont Blanc, CNRS, IRD, IFSTTAR, ISTerre, Grenoble, France</footnote>
## Background

In modern society, energy demands heavily rely on fossil fuels. However, these resources are finite and unsustainable, primarily due to their significant greenhouse gases (GHG) emissions. The combustion of fossil fuels releases significant amounts of carbon dioxide (CO₂), accounting for up to 80% of estimated GHG emissions, which is detrimental to both human and environmental health [1]. Therefore, there is an urgent need to explore and develop alternative energy sources to replace carbon-intensive fuels and reduce the global carbon footprint [2, 3].

Natural dihydrogen (H₂) gas, also called “white hydrogen”, is emerging as a promising clean and, possibly, renewable energy source. One of its most attractive advantages is that H₂ combustion produces only water vapor, providing a sustainable option for reducing the carbon footprint of the energy sector [4]. The potential of hydrogen as a green fuel is related to its clean-burning properties, capacity for domestic production, suitability for fuel cell vehicles, and energy efficiency of 2–3 times greater than gasoline [5, 6]. However, it is important to note that hydrogen has a lower volumetric energy density compared to gasoline, which has implications for H₂ transport and storage. For instance, the energy content of 1 m³ of hydrogen gas at standard conditions is significantly lower than that of 1 m³ of gasoline [7].

Despite its potential benefits, the economic viability of H₂ as an alternative energy source has often been underestimated due to misconceptions about its properties. H₂ is odorless, invisible and the most diffusive gas, leading to the widespread belief that it primarily exists in a dispersed state in the natural environment rather than in underground reserves [8]. However, this perception changed in 1987 when a geological accumulation of natural H₂ was discovered during a water drilling project in Bourakebougou, north of Bamako, Mali [9, 10]. This finding was the first effective documentation of a geological accumulation of natural H₂. Since 2011, a pilot well in the region has been producing a gas composed of 98% H₂, which is subsequently converted into electricity for local use [9]. This successful pilot project has sparked serious consideration of natural H₂ as an abundant, eco-friendly and cost-effective energy source [11]. However, the exact volume of the Bourakebougou accumulation has yet to be estimated and the existence of large gaseous H₂ accumulation of economic potential has yet to be confirmed. Therefore, the notion that “white hydrogen” is a viable alternative to conventional petroleum-based fuels remains unproven.

It is important to recognize that hydrogen exploration is still in its early stages, and reliable exploration tools and workflows are yet to be fully developed [12, 13]. A widely used tool for H₂ exploration in cratonic settings is the identification of geomorphological depressions [14].

These circular depressions, often characterized by gaps in vegetation, can be conveniently detected and visualized using satellite imaging [15–17]. Satellite observations were critical to detect the circular depression that turned out to be an H₂-emitting structure of approximately 500 m in diameter in the São Francisco basin, Brazil [18]. The site has been continuously monitored for soil H₂ concentrations at a depth of ca. 80 cm for over two years. Concentration oscillations with amplitudes of approximately 200 ppm were recorded along with larger pulses reaching a few thousands of ppm [16, 18]. These H₂ concentration spikes coincide with peak daily temperatures [18], and it was proposed that temporal variations of H₂ levels at a depth of 1 m are driven by daily pressure fluctuations [19].

Soil microbiota directly impacts the H₂ dynamics in subsurface environments through biotic H₂-producing and H₂-consuming processes [20]. In vitro microbial studies have demonstrated that soil bacteria can significantly consume H₂ before it reaches the surface, highlighting the importance of investigating the microbiome associated with H₂-emitting zones [21]. Indeed, microbial metabolism can be supported by H₂ in several metabolic processes, including (i) methanogenesis, (ii) acetogenesis, (iii) sulfate/sulfur/iron reduction, (iv) aerobic hydrogen oxidation, (v) dehalorespiration, (vi) fumarate respiration, (vii) denitrification and (viii) anoxygenic photosynthesis. In underground storage sites, the predominant H₂-oxidizing microorganisms are hydrogenotrophic sulfate reducers, hydrogenotrophic methanogens, and homoacetogens. Hydrogenotrophic sulfate reducers oxidize hydrogen (H₂) while reducing sulfate (SO₄²⁻) to hydrogen sulfide (H₂S), hydrogenotrophic methanogens convert carbon dioxide (CO₂) to methane (CH₄) using H₂ as an electron donor and homoacetogens oxidize H₂ and reduce CO₂ to produce acetate [22–30].

Similarly, several microorganisms can produce H₂ through mechanisms typically mediated by hydrogenases and nitrogenases. Microbial metabolic processes that lead to H₂ generation involve (i) fermentation, (ii) nitrogen fixation, and (iii) anaerobic carbon monoxide oxidation [31–34]. However, it remains unclear how H₂-emitting zones may shape the metabolic behavior and the population dynamics of microbial communities, as well as the extent of microbial impact on H₂ dynamics in these environments. In this context, this work aims to investigate the naturally occurring microbes potentially involved in H₂ consumption and production in the São Francisco Basin area, along with the influence of this H₂-emitting zone on the surrounding microbiota.
# Methods

## Study area and soil sampling

The H₂-emitting zone, approximately 500 m in diameter, is located near São Romão in Minas Gerais, Brazil. This area features a ring-shaped pattern with a dense Cerradão edge, deciduous forest [35], encircling a central circular pasture dominated by *Brachiaria brizantha* and scattered shrubs. Outside the H₂-emitting zone, the vegetation consists of Cerrado *sensu stricto*, typical Brazilian savannah vegetation (Fig. 1). Soil samples were collected during the dry season of June 2019 using a Dutch auger. Approximately 2 kg of sandy clay loam soil was collected from a total of eight points across two locations: five samples from the H₂-emitting zone (Spot 1: S16°33.532, W45°20.513; Spot 2: S16°33.559, W45°20.602; Spot 3: S16°33.622, W45°20.724; Spot 4: S16°33.839, W45°20.573; Spot 5: S16°33.274, W45°20.387), and three control samples from the adjacent Cerrado area (Control 1: S16°33.681, W45°20.793; Control 2: S16°33.556,

W45°20.323; Control 3: S16°33.418, W45°20.502) (Fig. 1). Soil sampling at each point was performed at depths of 10 cm and 1 m. The 1-meter depth was selected based on previous studies where sensors were installed to monitor H₂ concentrations at a depth of 80 cm within the circular depression soil [16, 18].

The general distribution pattern of H₂-concentration in barren depressions shows the lowest levels at the center and the highest towards the rim. Consequently, we collected samples from both the rim and the center, near points where H₂-concentrations were monitored by [16] over an 8-month period. Spot 1 and Spot 3 are located inside the depression, close to the rim. As expected, Spot 3 showed relatively high H₂ concentrations, averaging 35–120 ppm over 8 months, whereas Spot 1 had comparatively lower concentrations (10–20 ppm) despite its proximity to the rim [16]. Spot 2 is located in the center of the depression within the flood zone defined by [16], with an average H₂ concentration of 10–20 ppm. Spot 4

<figure><img src="image_3.png" /><figcaption>**Fig. 1** Circular geological structures in the São Francisco basin (State of Minas Gerais, Brazil) and the locations of the collected samples are depicted. The main depression in the center (Spot 1 to 3), referred to as "Campinas", is approximately 500 m in diameter, with an elevation difference of about 8 m between the rim and center. Campinas has been identified as an H₂-emitting structure based on H₂-concentration monitoring at an 80-cm soil depth, which revealed levels significantly higher than the atmospheric background. Samples labeled as "spot" indicate the sampling points within the H₂-emitting zone, characterized by grass vegetation. Samples labeled as "control" correspond to the sampling points in the adjacent region, which features arboreal Cerradão vegetation</figcaption></figure>
and Spot 5 were situated in satellite depressions where H₂ concentrations have not been previously monitored.

Soil samples were sieved through a 2-mm mesh to remove large particles, then stored separately in sealed plastic bags at -80 °C until microbial DNA extraction. A portion of the soil samples was ground for quantitative mineralogical analyses using X-ray powder diffraction. The diffraction patterns were processed to determine mineral composition through Rietveld refinement using BGMN software [36].

## H₂-emitting zone physical and chemical parameters

The soil chemical analyses were conducted at the Federal University of Viçosa (UFV-MG) in the Forest Soils Laboratory. Soil pH was measured after resuspending the sediment, which was extracted using distilled water in a 1:2.5 ratio, with a HI 2221 Calibration Check pH/ORP calibrated potentiometer [37] (HANNA instruments, Rhode Island, USA). For measurement of nitrate (NO₃⁻) and ammonium (NH₄⁺) concentrations, soil samples were extracted with 1 M KCl for 1 h and the inorganic-N concentrations were determined by colorimetry. Ammoniacal nitrogen (NH₄-N) was determined by the Nessler colorimetric method (soil analysis kit), while nitric nitrogen (NO₃-N) was measured by direct spectrophotometric analysis (UV-absorption) (Shimadzu, Japan) [38, 39]. To remove interferences by organic matter, the difference in absorbance between 254 and 280 nm was utilized [40]. Soil gravimetric water content was determined after drying the samples for 72 h at 105 °C [41]. Available phosphorus (P) and potassium (K) were extracted using the Mehlich-1 extractant [42], whereas calcium (Ca), magnesium (Mg) and aluminum (Al) were extracted using a 1 M KCl solution [37]. Organic matter (OM) content was determined according to the Walkley-Black method [43]. Aluminum was quantified by titrimetry [44]. These chemical analyses were conducted according to protocols established by EMBRAPA (Brazilian Agricultural Research Corporation) [45].

## DNA extraction and 16S rRNA gene amplification

Total microbial DNA was extracted from 0.5 g of soil using a Power soil kit (QIAGEN, USA) following the manufacturer's instructions. DNA integrity was verified by electrophoresis on a 1% agarose (Sigma-Aldrich, USA) gel. DNA samples were first prepared by Macrogen Inc. (South Korea), then subjected to a bidirectional sequencing through Illumina MiSeq technology. Dual primers were used to target both 16S rRNA V3-V4 region and ITS2 genes, which resulted in 150 bp paired-end reads. Sequencing data was imported into QIIME 2 v.2023.5 for further processing and analysis [46]. The primer sequences for the bacterial 16S rRNA gene were removed using the 'cutadapt' tool

(Bakt_341F: 5'-CCTACGGGNGGCWGCAG-3' forward and Bakt_805R 5'-CTACHVGGGTATCTAATCC-3' reverse) [47]. Subsequently, the trimmed sequences were processed by several 'vsearch' functions to (i) merge paired-end sequence reads, (ii) filter low quality reads with quality threshold below 20, (iii) remove replicated sequences, and (iv) cluster the sequences based on a 97% identity threshold. Additionally, the remaining clusters were scanned to evaluate the presence of chimeras [48].

## 16S rRNA gene sequencing and analysis

Operational taxonomic units (OTUs) were assigned to the processed data using the QIIME 2 'classifier' plugin [49] with the classify-sklearn method, utilizing the Silva 138 99% OTUs full-length sequences OTUs database [50]. Sequences corresponding to mitochondria, chloroplasts, eukaryotes, and unassigned categories were then removed from the dataset. For comparative analyses, including core microbiome, top coefficients beta diversity, and enzyme prediction analyses using PICRUSt, we combined the 1 cm and 1 m samples for each group (H₂ emitting zone and adjacent soil area). To ensure consistent comparisons among samples, taxonomic sequence data were normalized to a depth of 34,788 sequences and MetaCyc pathway prediction to 5,571,585 per sample using the Phyloseq package, with replacement [51]. Next, the Phyloseq package was also used to transform the data into compositional.

Bray-Curtis dissimilarities were estimated using the 'distance' function method from the Phyloseq package. These dissimilarities were then used to plot the first two Principal Coordinates (PCoA) [51]. To determine statistically significant differences between microbiome groups, a Permutational Multivariate Analysis of Variance (PERMANOVA) was performed using the 'adonis2' function from the Vegan package, with 999 permutations, and an α significance level of 0.05 [52]. The top Bray-Curtis dissimilarities (OTU and MetaCyc pathway) were extracted using the coefficients function from the stats package and visualized in a barplot.

The core microbiome, the essential set of microorganisms consistently present across a given sample, was determined using the core_members function and filtered with the core function from the microbiome package in R [53]. A prevalence of 70% and a detection threshold of 0.01 were established. Picrust2 v.2.5.2 pipeline was used to predict 16S rRNA associated with Metagenome pathway and hydrogen metabolism, executing each of the four key steps: (i) sequence placement, (ii) hidden-state prediction of genomes, (iii) metagenome prediction, and (iv) pathway-level predictions [54]. For hydrogen metabolism prediction, we used the following enzymes: EC.1.12.1.2, Hydrogen dehydrogenase; EC.1.12.1.3, Hydrogen dehydrogenase (NADP(+)); EC.1.12.2.1,
Cytochrome-c3 hydrogenase; EC.1.12.5.1, Hydrogen
oxidoreductase; EC.1.12.7.2, Ferredoxin hydrogenase;
EC.1.12.98.1, Coenzyme F420 hydrogenase; EC.1.12.99.6,
Hydrogenase (acceptor); and EC.1.18.6.1, Nitrogenase.
Pairwise group comparisons were conducted using the
Wilcoxon test [55]. P-values were adjusted using the Ben-
jamini-Hochberg method [56].

Results

Comparative soil physicochemical parameters

Despite the significant differences in vegetation (Fig. 2)
between the two areas (i.e., H₂-emitting zone and adja-
cent control Cerradão vegetation area), the evaluated
physicochemical parameters showed remarkable simi-
larities (Table 1). Differences were observed in specific
soil properties (Table 1). In particular, the soil in the
H₂-emitting zone had higher concentrations of copper
and clay-size fraction, whereas the adjacent control area
had a higher proportion of sand fraction (Wilcoxon test,
p<0.05). Samples collected at 1-m depth from within
the main circular depression (Spot 1 to 3) and at its edge
(Control 1) showed quartz concentration of 80, 11, 68
and 84 wt%, respectively, and kaolinite concentration of
20, 87, 28, 13 wt%, respectively. Smectite traces (<5 wt%)
were detected in Spots 2 and 3, while Control 1 contained
traces of gypsum (approximately 3 wt%). Spot 2, with its
notably high kaolinite content, differs significantly from
the other samples, which are predominantly composed
of quartz. Qualitative diffraction analysis of Spot 4 also
indicates a quartz-dominated composition.

H₂-emitting zone associated bacterial community

Bacterial communities exhibited variations in abundance across different depths, as well as between the H₂-emitting zone and the adjacent area (Fig. 3). Among the major phyla observed, *Actinobacteriota* was the most abundant across all the investigated spots, with a mean abundance of 40.73% (±13.47) in the H₂-emitting zone at a depth of 10 cm, and 48.73% (±4.66) in the adjacent soil. At a depth of 1 m, the proportion of *Actinobacteriota* relative to other phyla decreased to 25.56% (±5.40) in the H₂-emitting zones and 32.85% (±4.43) in the control soil, though it remained the dominant phylum (Wilcoxon test, *p* > 0.05). Within *Actinobacteriota*, several orders presented an average relative abundance greater than 1%, including *Corynebacteriales*, *Frankiales*, *Gaiellales*, IMCC26256, *Micromonosporales*, *Solirubrobacterales*, *Streptomycetales*, and unclassified *Actinobacteriota*.

Firmicutes emerged as the second most abundant phy-
lum in the H₂-emitting zone, with a mean abundance of
19.68% (±19.94) at 1 m and of 16.74% (±13.60) at 10 cm
depth. Conversely, their abundance was lower in the con-
trol area, with mean values of 8.56% (±4.79) at 10 cm
and 2.28% (±1.52) at 1 m depth. These variations were
primarily attributed to the *Bacillales* order, which was
the most dominant at a depth of 10 cm in the H₂-emit-
ting zone with a mean abundance of 14.09% (±13.22),
and increased to 17.56% (±19.51) at a depth of 1 m. In
contrast, *Bacillales* in the control area showed lower
mean abundances, with 6.55% (±4.23) at 10 cm depth,
decreasing to 1.25% (±0.90) at 1 m depth (Wilcoxon test,

<figure><img src="image_4.png" /><figcaption>**Fig. 2** Sampled areas (a) H₂-emitting zone with pasture and adjacent area with surrounding Cerradão vegetation (b) pasture of the H₂-emitting zone with rare, spaced shrubs (c) barren ground depression in Spot 5 also with Cerradão on the edge (d) collection point in the H₂-emitting zone (e) collection point in the adjacent area covered by leaf litter (f) adjacent area</figcaption></figure>
<table><caption>**Table 1** Physicochemical parameters of soil samples from H₂-emitting zones (spots 1–5) and adjacent cerrado areas (controls 1–3) collected at different depths (10 and 1 cm)</caption><thead><tr><th rowspan="2"></th><th colspan="2">Spot 1</th><th colspan="2">Spot 2</th><th colspan="2">Spot 3</th><th colspan="2">Spot 4</th><th colspan="2">Spot 5</th><th colspan="2">Control 1</th><th colspan="2">Control 2</th><th colspan="2">Control 3</th></tr><tr><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th><th>10 cm</th><th>1 m</th></tr></thead><tbody><tr><td>Silt</td><td>300</td><td>50</td><td>325</td><td>100</td><td>50</td><td>25</td><td>300</td><td>75</td><td>25</td><td>75</td><td>25</td><td>75</td><td>50</td><td>50</td><td>50</td><td>50</td></tr><tr><td>Sand</td><td>375</td><td>700</td><td>325</td><td>250</td><td>700</td><td>750</td><td>325</td><td>425</td><td>750</td><td>600</td><td>800</td><td>750</td><td>750</td><td>675</td><td>725</td><td>700</td></tr><tr><td>Clay</td><td>325</td><td>250</td><td>350</td><td>650</td><td>250</td><td>225</td><td>375</td><td>500</td><td>225</td><td>325</td><td>175</td><td>175</td><td>200</td><td>275</td><td>225</td><td>250</td></tr><tr><td>WSC</td><td>18.27</td><td>51.13</td><td>17.91</td><td>23.64</td><td>2.51</td><td>5.87</td><td>6</td><td>12.62</td><td>2.42</td><td>8.5</td><td>7.38</td><td>53.7</td><td>4.45</td><td>5.44</td><td>2.26</td><td>3.9</td></tr><tr><td>pH</td><td>5.32</td><td>5.38</td><td>5.12</td><td>4.28</td><td>4.77</td><td>5.1</td><td>5.64</td><td>5.35</td><td>4.81</td><td>5.48</td><td>5.33</td><td>5.3</td><td>5.1</td><td>5.21</td><td>6.02</td><td>5.07</td></tr><tr><td>P</td><td>2.3</td><td>0.1</td><td>2.6</td><td>0</td><td>0.9</td><td>0</td><td>4.1</td><td>1</td><td>1.6</td><td>0.4</td><td>2.2</td><td>0.8</td><td>1.8</td><td>0</td><td>2</td><td>0.3</td></tr><tr><td>Ca<sup>2+</sup></td><td>0.88</td><td>0.82</td><td>1.63</td><td>3.63</td><td>0.86</td><td>0.4</td><td>1.18</td><td>1.56</td><td>0.62</td><td>1.48</td><td>1.36</td><td>0.12</td><td>0.49</td><td>0.09</td><td>2.9</td><td>0.78</td></tr><tr><td>Mg<sup>2+</sup></td><td>0.1</td><td>0.19</td><td>0.25</td><td>0.51</td><td>0.06</td><td>0.03</td><td>0.33</td><td>0.26</td><td>0.2</td><td>0.05</td><td>0.3</td><td>0.02</td><td>0.12</td><td>0.01</td><td>0.7</td><td>0.15</td></tr><tr><td>K</td><td>31</td><td>0</td><td>47</td><td>1</td><td>7</td><td>0</td><td>163</td><td>19</td><td>5</td><td>0</td><td>7</td><td>0</td><td>15</td><td>0</td><td>29</td><td>1</td></tr><tr><td>Na</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.06</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Al<sup>3+</sup></td><td>0.89</td><td>0.3</td><td>0.69</td><td>1.08</td><td>0.99</td><td>0.59</td><td>0.2</td><td>1.58</td><td>0.69</td><td>0.49</td><td>0.2</td><td>0.79</td><td>0.59</td><td>0.69</td><td>0</td><td>0.39</td></tr><tr><td>H+Al</td><td>6.8</td><td>1</td><td>7.6</td><td>2.9</td><td>4.4</td><td>1</td><td>3.6</td><td>2.9</td><td>3.3</td><td>1.3</td><td>2.6</td><td>1.5</td><td>3.3</td><td>2</td><td>1.8</td><td>1.6</td></tr><tr><td>SB<sub>s</sub></td><td>1.06</td><td>1.01</td><td>2</td><td>4.14</td><td>0.94</td><td>0.43</td><td>1.99</td><td>1.87</td><td>0.83</td><td>1.53</td><td>1.68</td><td>0.14</td><td>0.65</td><td>0.1</td><td>3.67</td><td>0.93</td></tr><tr><td>CEC</td><td>7.86</td><td>2.01</td><td>9.6</td><td>7.04</td><td>5.34</td><td>1.43</td><td>5.59</td><td>4.77</td><td>4.13</td><td>2.83</td><td>4.28</td><td>1.64</td><td>3.95</td><td>2.1</td><td>5.47</td><td>2.53</td></tr><tr><td>V</td><td>13.5</td><td>50.2</td><td>20.8</td><td>58.8</td><td>17.6</td><td>30.1</td><td>35.6</td><td>39.2</td><td>20.1</td><td>54.1</td><td>39.3</td><td>8.5</td><td>16.5</td><td>4.8</td><td>67.1</td><td>36.8</td></tr><tr><td>%</td><td>45.6</td><td>22.9</td><td>25.7</td><td>20.7</td><td>51.3</td><td>57.8</td><td>9.1</td><td>45.8</td><td>45.4</td><td>24.3</td><td>10.6</td><td>84.9</td><td>47.6</td><td>87.3</td><td>0</td><td>29.5</td></tr><tr><td>m</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1.14</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>NaSi</td><td>73.9</td><td>2.7</td><td>110.8</td><td>8.1</td><td>20.2</td><td>0</td><td>50.4</td><td>2.7</td><td>13.4</td><td>1.3</td><td>13.4</td><td>1.3</td><td>13.4</td><td>5.4</td><td>17.5</td><td>1.3</td></tr><tr><td>OM</td><td>0.27</td><td>0.22</td><td>0.31</td><td>0.21</td><td>0.26</td><td>0.2</td><td>0.3</td><td>0.22</td><td>0.23</td><td>0.18</td><td>0.27</td><td>0.22</td><td>0.43</td><td>0.25</td><td>0.35</td><td>0.2</td></tr><tr><td>BS</td><td>0.95</td><td>1</td><td>1.68</td><td>2.44</td><td>2.62</td><td>1.32</td><td>4.19</td><td>1.85</td><td>0.85</td><td>0.83</td><td>0.22</td><td>0.28</td><td>0.16</td><td>0.01</td><td>0.62</td><td>1.34</td></tr><tr><td>Cu</td><td>69</td><td>19.2</td><td>137.3</td><td>28.6</td><td>96.4</td><td>11.8</td><td>57.5</td><td>6.8</td><td>89.2</td><td>5.5</td><td>64.2</td><td>4.8</td><td>54.9</td><td>5.2</td><td>8.5</td><td>7.9</td></tr><tr><td>Fe</td><td>10.3</td><td>6.4</td><td>42.6</td><td>24</td><td>2.6</td><td>1</td><td>16.6</td><td>16.7</td><td>2.2</td><td>0.3</td><td>8.6</td><td>1</td><td>6.2</td><td>0.4</td><td>69</td><td>43.9</td></tr><tr><td>Mn</td><td>2.57</td><td>0.75</td><td>3.25</td><td>0.84</td><td>0.21</td><td>0.29</td><td>0.34</td><td>0.41</td><td>0.1</td><td>0.17</td><td>0.33</td><td>0.11</td><td>0.29</td><td>0.1</td><td>0.45</td><td>0.15</td></tr><tr><td>Zn</td><td>20.1</td><td>6.2</td><td>12.6</td><td>14.8</td><td>12.7</td><td>9</td><td>20.4</td><td>12.9</td><td>12.9</td><td>10.9</td><td>9</td><td>16</td><td>11.1</td><td>15</td><td>5</td><td>9.6</td></tr><tr><td>S</td><td>2.52</td><td>0.51</td><td>3.71</td><td>0.77</td><td>0.98</td><td>0.72</td><td>2</td><td>0.72</td><td>0.7</td><td>0.65</td><td>0.82</td><td>0.63</td><td>0.74</td><td>0.58</td><td>0.76</td><td>0.73</td></tr><tr><td>TN</td><td>27.2</td><td>51.5</td><td>37.1</td><td>39.9</td><td>39.6</td><td>48.4</td><td>32.2</td><td>33</td><td>41.8</td><td>35.1</td><td>42.4</td><td>43.6</td><td>43.8</td><td>30.4</td><td>43.9</td><td>38.5</td></tr><tr><td>P-Rem</td><td>27.2</td><td>51.5</td><td>37.1</td><td>39.9</td><td>39.6</td><td>48.4</td><td>32.2</td><td>33</td><td>41.8</td><td>35.1</td><td>42.4</td><td>43.6</td><td>43.8</td><td>30.4</td><td>43.9</td><td>38.5</td></tr><tr><td>Ni</td><td>0.55</td><td>0</td><td>1.57</td><td>0.77</td><td>0.85</td><td>0</td><td>1.95</td><td>0</td><td>0.61</td><td>0</td><td>0</td><td>0.38</td><td>0</td><td>0</td><td>0.29</td><td>0</td></tr><tr><td>Pb</td><td>0.32</td><td>1.54</td><td>1.33</td><td>2.42</td><td>2</td><td>1.65</td><td>0.68</td><td>3.25</td><td>2.69</td><td>3.14</td><td>1.68</td><td>1.1</td><td>1.36</td><td>0.74</td><td>0</td><td>0</td></tr></tbody></table>

TN: Total Nitrogen; NaSi: Sodium Saturation Index; OM: Organic Matter; BS: Base Saturation; CEC: Cation Exchange Capacity; P-rem: Phosphorus Remaining; WSC: Water Soil Content; DS: Dry Solids; m: Aluminum Saturation; V: Base Saturation; SBS: Sum of Bases in Soil; H+Al: Exchangeable Acidity
<figure><img src="image_5.png" /><figcaption>**Fig. 3** Relative abundance (%) of different phyla based on 16S ribosomal RNA (16S rRNA) gene sequences in the microbiomes of the H₂-emitting structure (S) at five sampling points (S1, S2, S3, S4, and S5) and the adjacent control area (C) at three sampling points (C1, C2, and C3) at depths of 10 cm and 1 m. Phyla are color-coded as detailed in the inset at the right side. “Others” refer to phyla with less than 3% relative abundance in the microbial community</figcaption></figure>

*p>* > 0.05). *Paenibacillus* was detected with a mean abundance of 1% at a depth of 10 cm, but it was below 1% at a depth of 1 m.

*Chloroflexi* was also abundant in the H₂-emitting zone, comprising a relative abundance of 9.77% (±4.91) at 10 cm and 17.18% (±11.16) at 1 m depth. At 1 m, the predominant orders within this phylum were *Ktedonobacterales* (7.70% ±4.87) and *Chloroflexi* AD3 (7.72% ±11.36). While the proportion of *Ktedonobacterales* remained relatively stable at 10 cm (8.35% ±4.96), *Chloroflexi* AD3 showed a substantial decrease at this depth (0.21% ±0.08). In the adjacent area, both groups constituted a smaller fraction of the microbiome: *Ktedonobacterales* accounted for 3.58% (±3.20) and *Chloroflexi* AD3 for 3.73% (±1.64) at 1 m, and 0.95% (±0.64) and 0.12% (±0.05) at 10 cm, respectively (Wilcoxon test, *p* > 0.05).

*Proteobacteria* exhibited a remarkable shift in abundance between the control and H₂-emitting area. In the control soil at a depth of 10 cm, *Proteobacteria* had a mean abundance of 25.86% (±3.97), which slightly decreased to 20.63% (±3.07) at a depth of 1 m. Nevertheless, in the H₂-emitting area, its abundance decreased to 15.66% (±3.87) at 10 cm depth and 14.61% (±3.50) at 1 m depth. Distinct patterns were observed when focusing on two specific orders within *Proteobacteria* that had a mean relative abundance greater than 1%. For the order *Rhizobiales* in the H₂-emitting zone, the mean abundance was 7.79% (±1.68) at a depth of 10 cm, which slightly decreased to 7.02% (±2.23) at 1 m. In the control area,

*Rhizobiales* displayed a higher mean abundance of 16.06% (±1.93) at 10 cm depth, decreasing to 13.04% (±1.95) at 1 m. For the order *Elsterales*, in the H₂-emitting zone, the mean abundance was 1.86% (±0.82) at a depth of 10 cm, slightly decreasing to 1.64% (±0.74) at 1 m. Similarly, in the control area, *Elsterales* had a mean abundance of 2.55% (±1.57) at 10 cm depth, which slightly decreased to 2.87% (±0.64) at 1 m depth (Wilcoxon test, *p* > 0.05). *Burkholderiales* and *Acetobacterales* were also detected with an abundance of 1% in some samples.

Changes were also observed in the 1-meter-deep samples within the *Acidobacteria* community. In the control soil, their abundance was 18.93% (±1.32), compared to 12.03% (±5.74) in the H₂-emitting zone. At a depth of 10 cm, *Acidobacteria* were more abundant in the H₂-emitting zone, with a mean abundance of 9.10% (±5.10), compared to 5.72% (±1.22) in the adjacent soil (Wilcoxon test, *p* > 0.05). *Acidobacterales* was the only order detected with a mean abundance of 3–10% in some sample groups. Other phyla were less abundant across all samples, with their relative abundance varying based on depth and environmental conditions. Additionally, a few OTUs assigned to *Archaea* were detected, but their relative abundance was below 3%. Specifically, *Methanocellales*, an order of methanogenic archaea potentially involved in H₂ production in this region, were detected exclusively in the control samples at a depth of 1 m, with low proportions of 0.00095% (±0.001).
<figure><img src="image_6.png" /><figcaption>**Fig. 4** Core microbiome. (a) H₂ emitting zone, (b) Adjacent Cerrado control area. Microbial genera present with detection threshold 0.01 and a minimum prevalence of 70% are shown. We combined 10 cm and 1 m samples from each group</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Fig. 5** Microbial composition in the H₂-emitting zone (blue) and control area (red). (a) Principal Coordinate Analysis (PCoA) of Bray-Curtis dissimilarity showing differences in microbiome composition between the two areas. (b) The top 20 operational taxonomic units (OTUs) contributing to Bray-Curtis dissimilarities were identified by combining samples collected from depths of 10 cm and 1 m in each group. Circles represent samples from a depth of 10 cm, whereas squares represent samples from a depth of 1 m. Sample collection points are labeled as "s" for spot (H₂-emitting zone) and "c" for control (adjacent area)</figcaption></figure>

## Core microbiome

In the H₂-emitting samples, *Bacillus* was identified as the most dominant and widespread genus. In contrast, the control adjacent area was predominantly occupied by genera of the *Xanthobacteraceae* family. The core microbiome of the control area also included *Bradyrhizobium*, *Acidimicrobii*, and *Streptomyces*, which were absent in the H₂-emitting zone top core microbiome. Both the H₂-emitting samples and the control area shared common bacterial groups such as *Conexibacter*, *Acidothermus*, *Acidobacteriales*, *Xanthobacteraceae*, *Gaiellales*, and *Elsterales* (Fig. 4).

## Diversity responses to H₂ emitting zone

Beta diversity analysis revealed a significant influence of the H₂-emitting zone on microbial community composition (R² = 0.17818, and p=0.013) (Fig. 5). This finding

indicates that this area significantly shapes the microbial communities compared to the control area, accounting for approximately 17.82% of the total variation. Additionally, the PCoA shows that the first two axes (Axis 1 and Axis 2) explain 36.5% and 20% of the total variation, respectively, capturing a combined 56.5% of the variation in the microbial community composition. The 'Spot 5' sample appeared to be an outlier in terms of its microbiome composition, exhibiting characteristics more closely resembling those of the adjacent control region rather than the H₂-emitting zone (Fig. 5). It is important to note that 'Spot 5' was sampled from an area lacking arboreal vegetation (Fig. 2c), located at a considerable distance from the major H₂ emission structure (i.e., 'Spot1, 2, and 3'), where H₂ detector sensors were installed. The beta diversity analysis also revealed a significant impact of depth on the microbial community composition
(R²=0.13744, and p=0.048) (Fig. 5a). This result indicates that different depths harbor distinct microbial communities within the studied ecosystem.

The main factor contributing to dissimilarity between the H₂-emitting zone and the adjacent area is an OTU associated with *Bacillus*, which is more prevalent in the H₂-emitting zone. Additionally, among the top 20 most influential OTUs, two other OTUs affiliated with the *Bacillales* order also demonstrated significant contributions to the observed variations in this zone. Furthermore, within the top 20 OTUs associated with the H₂-emitting zone, OTUs affiliated with the AD3 group from *Chloroflexi*, *Ktedonobacteraceae*, *Thermosporotrichaceae*, and *Ktedonobacter* were particularly prominent, exerting substantial influence on the distinct microbial composition observed in this area. Conversely, in the control area, the most influential OTUs included those affiliated with *Xanthobacteraceae*, *Gaiellales*, *Acidobacteriales*, *Conexibacter*, and *Acidothermus* highlighting their significance in shaping the microbial community in the adjacent region (Fig. 5b).

## Metabolic function predictions in H₂-emitting zone

Metabolic function prediction using 16S rRNA gene association with the PICRUSt2 MetaCyc database identified distinctions between the H₂-emitting zone and the adjacent control area in MetaCyc pathway composition (R² = 0.20234, *p* = 0.03) (Fig. 6a). The predicted metabolic differences between the two areas show a prevalence of pathways involved in fatty acid metabolism in the adjacent control area. In the H₂-emitting zone, the pathway differences are more diverse but are not related to H₂ production or consumption (Fig. 6b).

Functional analysis by microbial association predicted that enzymes related to the metabolism of H₂ production and consumption are present at proportions below

0.04%. No significant differences were found between the samples from the H₂-emitting zone and the adjacent area (Fig. 7).

## Discussion

In H₂-emitting zone of the Cerrado, we identified a distinctive microbiome dominated by *Actinobacteriota* and *Firmicutes*. Significant differences were observed between the central part of the H₂-emitting zone and the adjacent area. The central zone was characterized by a higher abundance of *Bacillus* and *Chloroflexi* 'AD3' (formerly known as *Dormibacteraeota*), whereas the control area was predominantly populated by *Xanthobacteraceae*.

A previous study revealed that *Bacillus* species thrived in the soil from this area when exposed to H₂ at 50 °C, comprising approximately 90% of the microbial community. However, at 25 °C, *Firmicutes* did not show the same enrichment [21], suggesting that temperature might be a more critical parameter than H₂ levels. *Bacillus* species are known for their ability to form spores, allowing them to survive under extreme conditions, such as high temperatures, desiccation, and intense UV radiation [57]. Additionally, other spore-forming microbes, including members of *Chloroflexi* class Ad3, *Ktedonobacteria*, and the family *Thermosporotrichaceae*, were also more prevalent in the H₂-emitting zone [58, 59]. These findings indicate that the H₂-emitting zone favors the presence of spore-forming microorganisms, likely due to constant exposure to solar radiation.

In the same study, the treatment with H₂ at 25 °C significantly increased the abundance of *Acidobacteria* and had a modest positive effect on the members of the *Chloroflexi* group, suggesting their ability to oxidize H₂ [21]. *Chloroflexi* Ad3 was identified as the second major contributor to the differences observed among our study groups. The *Chloroflexi* supergroup includes

<figure><img src="image_8.png" /><figcaption>**Fig. 6** MetaCyc pathway composition of the H₂-emitting zone (blue) and the control area (red) soil microbial communities. (a) Principal Coordinate Analysis (PCoA) of Bray-Curtis dissimilarity comparing the predicted pathways. (b) The top 20 MetaCyc pathways associated with the studied areas, contributing to Bray-Curtis dissimilarities, were combined 10 cm and 1 m samples from each group. Circles represent samples from a depth of 10 cm, whereas squares represent samples from a depth of 1 m. Sample collection points are labeled as "s" for spot (H₂-emitting zone) and "c" for control (adjacent area)</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Fig. 7** H₂-metabolism enzymes predicted in the H₂ emitting zone and adjacent control area soil bacterial communities using 16S rRNA gene. The relative abundance of predicted genes transformed into log scale. The groups are highlighted using blue for H₂-emitting zone predicted enzymes, and red for adjacent soil group. We combined 10 cm and 1 m samples from each group</figcaption></figure>

H₂-dependent haloalkane reducers (*Dehalococcoidia*), spore-forming members (*Ktedonobacteria*), and groups capable of aerobically oxidizing gases such as CO and H₂ [60]. The presence of high-affinity group 1 h [NiFe]-hydrogenase, which are widely distributed within *Chlo-roflexi*, supports bacterial persistence by facilitating H₂ oxidation at atmospheric to sub-atmospheric levels (0.53 ppmv) [61–63]. This H₂-dependency highlights their potential as bioindicators of hydrogen availability.

*Acidobactéries*, which showed an increase in the previously described experiment, emerged as dominant in both areas. Studies have shown that certain *Acidobactéria* strains can consume atmospheric levels of H₂ due to their high-affinity [NiFe] hydrogenases [64]. For example, *Acidobacteriaceae bacterium* KBS 83 can reduce H₂ levels of approximately 20 ppmv down to 0.25±0.03 ppmv, while *E. aggregans* can lower it to 0.36±0.06 ppmv after 172 h [65]. In addition, it is reported that members of *Conexibacter*, *Xanthobacteraceae*, and *Gaiellales*, which were identified as part of the core microbiome, also possess [NiFe] hydrogenases, a characteristic feature of H₂-oxidizing bacteria [66–68].

In addition to the previously described groups, *Brady-rhizobium* and *Streptomyces* are dominant microor-ganisms detected in the adjacent area (Controls 1–3). *Bradyrhizobium* forms nodules on legume roots, where it facilitates nitrogen fixation and releases H₂ as a byprod-uct [69]. These bacteria can also grow lithoautotrophi-cally, utilizing H₂ as both energy and electron source [70, 71]. Conversely, *Streptomyces* species consume atmo-spheric H₂ through their high-affinity group 5 [NiFe]-hydrogenases during sporulation. These hydrogenases are capable of uptaking H₂ at picomolar concentrations (50 to 400 pM) and can oxidize tropospheric H₂ with a

$K_m$ of approximately 50 nM in pure culture. This suggests a potential link between sporulation and H₂ consump-tion in microorganisms beyond *Streptomyces*, given the high abundance of sporulating microorganisms in the H₂-emitting zone and the fact that *Streptomyces* con-sumes H₂ only in its sporulated state [61, 72, 73]. More-over, the high abundance of H₂-oxidizing bacteria at the edges of the H₂-emitting zone (Controls 1–3) suggests that, despite being below the detection threshold of the H₂ measurement device, the concentration of H₂ in these peripheral areas of the circular depression may still exceed atmospheric levels.

In both areas, the microbiome differs from those previ-ously reported for the Cerrado [74], with *Actinobacteria* and *Firmicutes* predominating. This dominance makes it challenging to identify metabolic differences using 16S rRNA gene functional association. The *Bacillus* and *Xanthobacteraceae* detected in our study were unrelated to known species and lacked functional annotations in available databases. The limitations of PICRUSt2 arise from its dependence on known genomes and 16S rRNA gene data, potentially overlooking novel functions or rare genes [54]. Additionally, 16S rRNA gene data may not always accurately reflect functional capabilities due to limitations in taxonomic resolution. The discrepancies between the herein detected *Bacillus* and those in the database further complicate accurate estimation of their involvement in hydrogen metabolism.

In addition to high H₂ concentration, we hypothe-size that other factors may contribute to the differences observed in the microbiomes of the two areas studied. The H₂-emitting zone is characterized by pasture veg-etation, which receives constant solar radiation and is utilized for cattle grazing. Studies suggest that the
conversion of natural grasslands to managed and culti-
vated pastures reduces the abundance of *Acidobacteria*
and *Verrucomicrobia*, while increasing the populations
of α-, γ-, and δ-*Proteobacteria*, *Gemmatimonadetes*, *Bac-
teroidetes*, *Patescibacteria*, and *Latescibacteria* [75]. This
shift notably differentiates the microbial composition
observed in the H₂-enriched pasture in this study.

During the rainy season, a pond forms in the cen-
ter of the H₂-emitting zone as a result of flooding. The
increased water availability likely encourages denser veg-
etation growth along the edges of the zone, while vegeta-
tion in the center becomes submerged and eventually dies
off. This process leads to the deposition of clay minerals,
primarily kaolinite, in the central area. We compared the
microbiome from our study with the one from sediment
of dry Cerrado ponds. Typically, these sediments exhibit
a microbiome composition characteristic of the Cerrado,
with *Proteobacteria* and *Acidobacteria* as the most abun-
dant groups, and *Actinobacteria* constituting less than
4% of the community [76]. One notable observation was
the increase in *Firmicutes* during the rainy-to-dry transi-
tion, reaching up to 40% of the microbiome in one of the
lakes tested [76]. However, the microbiome composition
observed in our study differs significantly from this typi-
cal pattern.

The origin of the elevated H₂ concentrations in the soil of the Campinas depression remains uncertain based on surface observations alone. However, both these observations and modeling efforts [19, 77] suggest that the top layer of the barren zone, primarily composed of clay minerals accumulating in the depression's center, plays a significant role. This impermeable layer may be responsible for the lower H₂ concentrations observed at the center of the emitting structure by limiting gas diffusion. During hot periods, water evaporation could facilitate the transport of H₂ to the surface, while the presence of copper may promote the enrichment of H₂-oxidizing bacteria.

Conclusions

This study characterized the bacterial microbiome asso-
ciated with an H₂-emitting zone, which may originate
from a deep geological source or have a biogenic origin
[78]. We identified several bacterial groups, including
H₂-oxidizing and sporulating bacteria, present in signifi-
cant abundance – even at the periphery of the geologi-
cal formation where no H₂ emissions have been detected.
The findings highlight the critical role of hydrogen in
shaping microbial communities and influencing eco-
system processes. Further research into the interactions
between hydrogen, soil physicochemistry, and microbial
activity is essential to deepen our understanding of these
complex dynamics and their implications for environ-
mental health and sustainability.

Acknowledgements

This study was funded by the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES) and the Federal District Research Support Foundation (FAP-DF). O.H.B.P. received a technical training fellowship from Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP). The authors thank H3 Fazenda Mangueiras for granting access to the sampling areas. FB would like to thank I. Moretti who initiated with him the research on the relationship between H₂ and microbiology in Campinas soil as well as A. Prinzhofer for is guidance on the field and for sharing his vast knowledge of H₂ dynamics in Campinas and other circular depressions.

Author contributions

O.H.B.P, R.S.O, M.R.S.S, and R.H.K designed the study. The biological sampling was performed by O.H.B.P, R.S.O, M.R.S.S, B.R. and R.H.K. Data analysis were carried out by O.H.B.P, R.S.O, M.R.S.S. The manuscript was prepared by O.H.B.P, J.P, R.H.K and B.F.Q revised by all authors. O.H.B.P, J.P, R.H.K and B.F.Q and F.B. critically revised and substantially edited the manuscript. R.H.K secured the funding for the research. All authors read and approved the manuscript.

Funding

This study was funded by the National Council for Scientific and Technological Development (CNPq), the Coordination for the Improvement of Higher Education Personnel (CAPES and CAPES PRINT) and the Federal District Research Support Foundation (FAP-DF). O.H.B.P. received a technical training fellowship from São Paulo Research Foundation (FAPESP), Brasil, Process Number (2022/08797-4), during the manuscript writing period. IRD funded FB's stay at the Dept of Cell Biology of UnB.

Data availability

Sequence data were submitted to NCBI GenBank (https://www.ncbi.nlm.nih.gov/) and can be found under the Project code PRJNA1147869.

Declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

Received: 17 August 2024 / Accepted: 19 October 2024

Published online: 26 October 2024

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