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. 2025 Dec 19;13(5):nwaf581. doi: 10.1093/nsr/nwaf581

Nanomineral-fueled chemolithoautotrophy leads to substantial mercury emission

Zeyou Chen 1,b, Chenyang Zhang 2,b, Zhanhua Zhang 3,b, Qing Chang 4, Cheng Gao 5, Xiao Liang 6, Xin Nie 7, Long Chen 8, Zhi Cao 9, Yan Lin 10, Pedro J J Alvarez 11, Wei Chen 12, Tong Zhang 13,✉, Cong-Qiang Liu 14
PMCID: PMC12949521  PMID: 41768548

ABSTRACT

Elemental mercury (Hg0) is a pervasive pollutant of global concern. Recent research shows that global Hg0 emissions are significantly underestimated, but the additional sources contributing to this gap are unclear. Here, we demonstrate that chemolithoautotrophic microorganisms, such as sulfur-oxidizing and iron-oxidizing bacteria that are ubiquitous in diverse environments, utilize mercury sulfide (HgS) nanoparticles to support growth while releasing substantial amounts of Hg0. Unlike dissolved Hg(II) species, HgS nanoparticles (HgSNP) are internalized into bacterial cells through an adenosine triphosphate (ATP)-independent, highly energy-efficient process. This enhanced internalization leads to rapid metabolism of HgSNP via sulfur-oxidation, as well as the subsequent reduction of the released Hg(II) to Hg0 mediated by the mer operon, superoxide or cytochrome c. Our modeling results show that the annual emission flux of Hg0 from this previously unrecognized source can reach 272.44 ± 134.99 tonnes, equivalent to that of geogenic Hg0 emissions and matching that of the fourth largest anthropogenic source, cement production.

Keywords: HgS nanoparticles, mercury emission, microbial transformation, chemolithoautotrophic bacteria

Chemolithoautotrophic bacteria tap into nanomineral stores of mercury sulfide, converting these particles into gaseous mercury. This study reveals a previously overlooked natural pathway that releases mercury to the atmosphere and quantifies its global significance for the first time.

INTRODUCTION

Elemental mercury (Hg0) is a pervasive pollutant of global concern, due to its ability to vaporize at ambient temperatures and to undergo long-distance atmospheric transport [1–4]. Hg0 is released through both natural processes (e.g. volcanic eruptions, geothermal activities and rock weathering) and anthropogenic activities (e.g. gold mining, coal combustion and industrial operations) [5–11]. Since the Minamata Convention came into effect in 2017, global initiatives have been taken to identify and control the anthropogenic sources of mercury, which account for approximately 30% of the total global mercury emissions [5,12–14]. In contrast, the processes driving natural emission of deposited Hg from the earth’s crust, which contribute to over 60% of Hg0 release [3,10,15], remain understudied. For instance, a recently developed atmospheric–terrestrial–oceanic coupled model reveals that global Hg0 emissions may be underestimated by as much as 40% [16]. Predictions based on global mercury isotope box models also indicate that the standard rate constants used in global mercury cycling models significantly underestimate Hg0 emissions [17]. Thus, identifying additional sources of natural Hg0 release and understanding mechanisms controlling these processes are of critical importance for improving the accuracy of global Hg emission inventories, and for advancing mercury pollution control measures.

Both abiotic and biotic processes contribute to Hg0 formation in natural environments [18–22]. Photochemical reduction of dissolved Hg(II) species by UV light has been recognized as the key abiotic process producing Hg0 in surface waters, surface soils and atmospheric aerosols [18–20]. For biotic sources of Hg0, microbial mercury reduction driven primarily by the mer operon is the most widely recognized pathway [22–24]. It is necessary to note that the majority of the earth’s habitats exist in dark conditions [25], and Hg levels in natural environments are often too low to activate the mer operon, which functions as a defense mechanism against high mercury exposure [26,27]. Nonetheless, mounting evidence indicates the existence of exceptionally high levels of Hg0 in the world’s deepest marine environments such as trench areas and deep-sea cold seeps, wherein dissolved Hg(II) levels are low and light is absent [28–31]. This points to the undiscovered additional mechanisms driving Hg0 production in natural environments.

Previous studies show that autotrophic bacteria may use HgS minerals as natural habitats [32–34]. For example, incubating HgS minerals near a diffuse-flow hydrothermal vent on the East Pacific Rise resulted in colonization of sulfur-oxidizing bacteria at relatively high abundance [34]. Similarly, sulfur-oxidizing bacteria of the genus Thiobacillus were enriched on metacinnabar chips incubated in creek sediments, and laboratory incubation of these mineral samples led to release of Hg(II) and Hg0, though at particularly slow rates [33]. Note that these mercury transformation processes may become dominant when the microbe–mineral interactions occur at nanoscale, since mineral nanoparticles are a major mercury species at microbial habitats [35–37] and nanoparticles often exhibit unique environmental behaviors differing from their dissolved and bulk-scale counterparts [33,38–42]. However, the fundamental processes governing Hg0 formation from HgS nanoparticles (HgSNP) by autotrophic bacteria remain poorly understood and unquantified. Indeed, our research reports direct evidence that chemolithoautotrophy on HgSNP is a previously unrecognized and yet essential source of Hg0. Chemolithoautotrophic bacteria internalize HgSNP through an adenosine triphosphate (ATP)-independent process, and metabolize reduced sulfur while releasing Hg(II). In response, a diverse variety of reduction pathways are triggered to generate substantial amount of Hg0.

RESULTS AND DISCUSSION

HgSNP support chemolithoautotrophy while producing Hg0

Chemolithoautotrophic bacteria, including the archetypes for sulfur-oxidizing bacteria Thiobacillus thioparus (ATCC 8158) and Paracoccus pantotrophus (ATCC 35512), and iron-oxidizing bacteria Acidithiobacillus ferrooxidans (ATCC 23270), were able to use HgSNP as growth substances and consequently, produced substantial quantities of Hg0 during chemolithoautotrophy, with transformation efficiencies of 9.7% ± 1.1%, 7.4% ± 0.8% and 7.9% ± 0.4% of total mercury for T. thioparus, P. pantotrophus and A. ferrooxidans, respectively. When HgSNP were incubated in the culture media as the sole electron donors, cell density of T. thioparus increased rapidly for approximately 160 h, and the growth rate markedly surpassed that of the treatment with bulk-sized HgS (Fig. 1a). Less significant growth was observed for P. pantotrophus (Fig. 1b) and A. ferrooxidans (Fig. 1c), but the overall trend was consistent, i.e. HgSNP sustained cell growth to a higher extent than its bulk-sized counterpart (Fig. 1a–c). More interestingly, production of Hg0 from HgSNP increased appreciably with time, whereas Hg0 production from bulk-sized HgS by all bacterial strains was minimal and increased little with time (Fig. 1d–f). In T. thioparus, microbe–nanoparticle interactions led to the rapid reduction of up to 9.7% ± 1.1% of total mercury to elemental Hg0 during the early exponential growth phase (0–18 h, Fig. 1a and d). Clearly, different mechanisms were in play in the microbial transformation of HgSNP, as compared to bulk minerals.

Figure 1.

Figure 1.

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Substantial Hg0 production during growth of chemolithoautotrophic bacteria upon exposure to HgSNP. (a–c) Growth curves of T. thioparus (a), P. pantotrophus (b) and A. ferrooxidans (c) cells upon exposure to 50 μM HgSNP or bulk HgS. Control group represents culture media without mercury addition. (d–f) Hg0 production by T. thioparus (d), P. pantotrophus (e) and A. ferrooxidans (f) cells upon exposure to 50 μM HgSNP or bulk HgS. Control represents cultures without mercury addition. Abiotic control represents the uninoculated media with HgSNP. Error bars represent ±1 SD of triplicates. Statistically different values (P < 0.01) are indicated by asterisks (**) according to an independent two-sample t-test.

To understand the mechanisms facilitating the transformation of HgSNP into Hg0, we conducted mercury fractionation analysis, including intracellular nanoparticulate mercury, intracellular dissolved mercury and evaporable mercury, during the microbe–nanoparticle interactions (Fig. 2 and Fig. S8). Interestingly, the fraction of intracellular nanoparticles appeared immediately, and at 0.3 h the content of HgSNP in T. thioparus accounted for 16.8% ± 1.2% of the total mercury mass initially added (Fig. 2a). Substantial occurrence of nanoparticulate mercury was also observed for P. pantotrophus and A. ferrooxidans (Fig. 2b and c). Transmission electron microscopy (TEM) coupled with energy-dispersive X-ray spectroscopy (EDX) analysis showed that these nanoparticles were mainly comprised of Hg and S elements and located in the cell cytoplasm (Fig. 2d–i), indicating the direct uptake of HgSNP by the bacteria. Moreover, the time-dependent increase in the concentrations of intracellular dissolved mercury (Fig. 2a–c) suggests that the internalized HgSNP were readily dissolved. In contrast, when bulk-sized HgS was incubated with the bacteria, the intracellular mercury fraction was primarily dissolved species and the abundance was extremely low (Figs S4 and S7), demonstrating that the microbial uptake and dissolution of bulk-sized HgS were minimal. While internalization of nanoparticles into bacterial cells has been reported, this process is typically associated with cell membrane damage [43–45], yet the integrity of cell membranes of all chemolithoautotrophic bacteria in our experiments did not appear to be compromised by interactions with HgSNP (Fig. S5), which infers the existence of a highly efficient pathway for microbial uptake of nanoparticulate mercury.

Figure 2.

Figure 2.

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Hg0 release is accompanied by intracellular uptake and dissolution of HgSNP. (a–c) Comparison of mass fractions of Hg0, intracellular dissolved Hg(II), and intracellular HgSNP in T. thioparus (a), P. pantotrophus (b) and A. ferrooxidans (c) cells upon exposure to 50 μM HgSNP. (d–i) TEM images of thin section of T. thioparus (d and g), P. pantotrophus (e and h) and A. ferrooxidans (f and i) cells before (d–f) and after 6-h exposure (g–i) to 50 μM HgSNP, and EDX spectra of intracellular HgSNP. Error bars represent ±1 SD of triplicates.

ATP-independent transmembrane transport of HgSNP

HgSNP were internalized into the cells through an ATP-independent, passive diffusion fashion (Figs 3 and 4). When exposed to HgSNP, the ATP content of the bacteria remained relatively stable with increasing incubation time (Fig. 3a–c), whereas a continuous decrease in ATP levels was observed when the bacteria were exposed to dissolved Hg(II) (Fig. 3g–i). Apparently, cellular uptake of HgSNP did not require ATP as the key energy carrier, as in the case of dissolved Hg(II). To test this hypothesis, we inhibited ATP production by the bacteria using a proton uncoupler carbonyl cyanide m-chlorophenyl hydrazine (CCCP) and two ATP synthase inhibitors N, N′-dicyclohexylcarbodiimide (DCCD) and oligomycin [46,47]. Consistent with our hypothesis, the decreased intracellular ATP levels in the bacteria resulted in significantly inhibited cellular uptake of dissolved Hg(II) (Fig. 3g–l), in line with the well-acknowledged mechanism of active transport of Hg(II) that consumes ATP [48,49]. Conversely, the decreased ATP levels had no effects on the uptake of HgSNP (Fig. 3a–f). Additionally, no significant membrane damage or acute cytotoxicity was observed under the tested conditions (Figs S9 and S10), indicating that HgSNP uptake was not due to compromised membrane integrity. These results indicate that cross-membrane transport of HgSNP likely occurred through passive diffusion.

Figure 3.

Figure 3.

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ATP-independent cellular uptake of HgSNP. (a–f) Significant decrease in ATP contents (a–c) in T. thioparus (a and d), P. pantotrophus (b and e) and A. ferrooxidans (c and f) cells upon exposure to 50 μM HgSNP in the presence of 5 μM proton uncoupler CCCP, 10 μM ATP synthase inhibitors DCCD and oligomycin did not affect intracellular Hg(II) in bacteria (d–f), showing the uptake of HgSNP is an ATP-independent passive transport process. In contrast (g–l), significant decrease in ATP contents (g–i) in T. thioparus (g and j), P. pantotrophus (h and k) and A. ferrooxidans (i and l) cells upon exposure to 50 μM dissolved Hg(II) in the presence of 5 μM CCCP, 10 μM DCCD and 10 μM oligomycin substantially decreased intracellular Hg(II) in bacteria (j–l), showing the uptake of dissolved Hg(II) by bacteria is an ATP-dependent transport process. Error bars represent ±1 SD of triplicates.

Figure 4.

Figure 4.

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Molecular dynamic simulations showing HgSNP more easily penetrates cell membranes than dissolved Hg(II) due to its lower free energy barrier for transmembrane processes. (a and c) Snapshots of HgSNP (a) and dissolved Hg(II) (c) penetrating the phospholipid bilayer of cell membranes during the simulations. (b and d) Gibbs free energy changes (ΔG) along the penetration processes of HgSNP (b) and dissolved Hg(II) (d). Region I is the lipid alkyl chain (z = 0–1 nm). Region II is the phospholipid headgroup, which is the hydrophobic–hydrophilic interface (z = 1–2 nm). Region III is the phospholipid headgroup–water interface (z = 2–2.5 nm). Region IV is the aqueous phase (z > 2.5 nm). Shaded areas represent ±1 SD of triplicates.

Previous studies showed that nanoparticle internalization is strongly size-dependent [50,51]. Accordingly, we used 4–5 nm HgSNP (Fig. S1) to match the sizes of primary particles identified in laboratory studies [36,40–42,52–54]. To evaluate the thermodynamic feasibility of transmembrane transport and to identify the rate-limiting step, we performed molecular dynamic simulations to quantify the energy landscape associated with membrane crossing by HgSNP within this relevant size range, and compared it with that of dissolved Hg(II) species (natural organic matter was included to better approximate environmentally realistic conditions [55]) (Fig. 4). The energy barriers were calculated across four regions (Fig. 4a and c): (i) the transition from the bulk aqueous phase to the outer membrane (region VI); (ii) passage through the water–phospholipid headgroup interface (region III), (iii) movement from the phospholipid headgroups to the hydrophobic–hydrophilic interface (region II); and (iv) entry from the phospholipid headgroups into the lipid alkyl chains (region I). For the HgSNP, the energy barrier is highest in region I, near the interface with region II, with a Gibbs free energy change (ΔG) value of 105 kJ/mol (Fig. 4b). Notably, this energy barrier is substantially lower than that of dissolved Hg(II), with a ΔG value reaching 212 kJ/mol in region I (Fig. 4d). This significantly lower energy barrier indicates that passive transmembrane transport is thermodynamically far more feasible for the nanoparticle than for the dissolved species. Based on these ΔG values, the estimated cross-membrane rate of HgSNP is 5.6 × 1018 times higher than that of dissolved species (for which passive diffusion is essentially not viable). These theoretical calculations demonstrate that the key limiting factor for HgSNP transport is the energy barrier for membrane translocation, which is surmountable via passive diffusion of the nanoparticles. This theoretical result corroborates the experimentally observed rapid internalization of HgSNP, which enabled ready transformation to release dissolved Hg(II) (Fig. 2).

Intracellular transformation of HgSNP

Upon uptake of HgSNP, oxidative metabolism of sulfide was quickly initiated by the cells, resulting in continuous production of higher-valence sulfur species, which coincided with the release of dissolved Hg(II) (Fig. 5). Significant upregulations of sulfur oxidation-related genes were observed in all chemolithoautotrophic bacteria exposed to HgSNP, although different metabolic genes were involved for each strain (Fig. 5a–c). The gene with the highest upregulated expression was sat in T. thioparus, soxC in P. pantotrophus and aprA in A. ferrooxidans (Fig. 5a–c). The differential expression patterns of the metabolic genes across different bacteria were consistent with previous observations [56–58], and suggests that the ability of internalizing and metabolizing HgSNP may distribute across microbial strains inhabiting distinct ecological niches and harbor different sulfur metabolism pathways.

Figure 5.

Figure 5.

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Chemolithoautotrophic bacteria utilize reduced sulfur from HgSNP for growth, which induces intracellular dissolution of HgSNP. (a–c) Expression of genes related to sulfide oxidation in T. thioparus (a), P. pantotrophus (b) and A. ferrooxidans (c) cells upon exposure to 50 μM HgSNP. (d–f) Concentrations of SO42–, SO32– and S0 produced by T. thioparus (d), P. pantotrophus (e) and A. ferrooxidans (f) cells upon exposure to 50 μM HgSNP. (g–i) Dissolution of HgSNP in the absence and presence of T. thioparus (g), P. pantotrophus (h) and A. ferrooxidans (i) cells upon exposure to 50 μM HgSNP. Error bars represent ±1 SD of triplicates. Statistically different values (P < 0.01) are indicated by asterisks (**) according to an independent two-sample t-test.

Three oxidation products of sulfide were observed during microbe–nanoparticle interactions: SO42−, S2O32− and S0, with SO42− being the most dominant product. The accumulation of SO42− occurred over the entire duration of bacterial growth (Fig. 5d–f), indicating that reduced sulfur from HgSNP was used as the electron donors by the chemolithoautotrophic bacteria. Moreover, the fast SO42− formation in the initial stage of HgSNP transformation (i.e. the insets of Fig. 5d–f) appeared simultaneously with the dissolution of HgSNP (Fig. 5g–i). These consistent trends further demonstrate that the sulfide being metabolized and the Hg(II) being reduced inside bacterial cells likely originated from the same precursor compounds. Overall, it can be concluded that the rapid intracellular oxidation of sulfide provided an energy source to sustain chemolithoautotrophy, and this process resulted in the concurrent intracellular accumulation of dissolved Hg(II).

Mercury detoxification by chemolithoautotrophic bacteria

The Hg(II) released due to intracellular dissolution of HgSNP was reduced to Hg0 by the bacteria via different detoxification mechanisms that likely facilitated sustained bacterial uptake and transformation of HgSNP. Polymerase chain reaction (PCR) amplification data showed that a 285 bp PCR product was amplified in the genomes of T. thioparus and A. ferrooxidans, but not in P. pantotrophus, and sequencing confirmed this product as the merA gene (Fig. 6a). Furthermore, real-time quantitative PCR (RT-qPCR) results showed that the expression of the merA genes increased over time in response to HgSNP exposure (Fig. 6b), indicating that merA-mediated intracellular mercury reduction played an essential role in the conversion of HgSNP to Hg0 by T. thioparus and A. ferrooxidans. These were in line with the widely accepted knowledge that the mer operon system existing in a diverse variety of microbial strains functions as a major defense mechanism to mitigate the damage of dissolved mercury [26,59,60].

Figure 6.

Figure 6.

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Elemental mercury is released as the result of microbial detoxification through multiple intracellular reduction processes. (a) Agarose gel electrophoresis showing merA gene is present in T. thioparus and A. ferrooxidans genomes, but absent in the P. pantotrophus genome. (b) Expression of merA gene in T. thioparus and A. ferrooxidans cells upon exposure to 50 μM HgSNP, showing the presence of an intracellular mercury reduction pathway mediated by the merA gene in T. thioparus and A. ferrooxidans. (c) O2•– produced by T. thioparus, P. pantotrophus and A. ferrooxidans cells upon exposure to 50 μM HgSNP. (d) Hg0 production by P. pantotrophus cells upon exposure to 50 μM HgSNP in the absence and presence of SOD, showing O2•– plays an important role in the reduction of mercury in P. pantotrophus. (e and f) Hg0 production by A. ferrooxidans (e) and the expressions of genes (f) encoding iron oxidase, ceruloplasmin and cytochrome c oxidase in A. ferrooxidans cells upon exposure to dissolved Hg(II) in the absence of KN3 and Fe(II), presence of Fe(II), and presence of KN3, showing the presence of a membrane mercury reduction pathway mediated by cytochrome c oxidase in A. ferrooxidans. Abiotic control represents the uninoculated media. Error bars represent ±1 SD of triplicates. Statistically different values (P < 0.05) are indicated by lowercase letters according to the one-way analysis of variance (ANOVA). Statistically different values (P < 0.01) are indicated by asterisks (**) according to an independent two-sample t-test.

In addition to the mer operon system, two other mechanisms were also responsible for Hg(II) reduction. First, P. pantotrophus, which does not carry merA genes (Fig. 6a), produced a significantly greater amount of O2•– than the other two strains (Fig. 6c), likely due to the oxidative stress induced by mercury exposure [61,62]. This elevated level of O2•– may lead to intracellular substantial mercury reduction in P. pantotrophus. Indeed, the addition of superoxide dismutase (SOD), an O2•– scavenger, to the experimental matrices decreased Hg0 production by over 90% after a 9-h incubation (Fig. 6d), confirming the role of O2•– in Hg0 formation. Second, Hg(II) reduction mediated by cytochrome c, a heme-containing protein, also contributed to the production of Hg0 by A. ferrooxidans. Production of Hg0 was significantly inhibited when KN3, a cytochrome c oxidase inhibitor, was added (Fig. 6e). PCR amplification further confirmed the presence of genes related to this pathway (i.e. iro, coxB, coxC, coxA and rus) in A. ferrooxidans (Fig. S6), and RT-qPCR revealed that the expression of these genes was apparently downregulated in the presence of KN3 (Fig. 6f). Since Fe(II) serves as a key electron donor for cytochrome c-mediated Hg(II) reduction [63], we conducted additional experiments with exogenous Fe(II) supplementation. The results showed that Fe(II) addition enhanced Hg0 production, and RT-qPCR analysis indicated upregulation of the corresponding cytochrome c-related genes, supporting the critical role of Fe(II) in facilitating Hg(II) reduction in this iron-oxidizing bacterium (Fig. 6e and f). Cytochrome c is an important electron transfer mediator [63], and it appears that for iron-oxidizing bacteria, cytochrome c-mediated mercury reduction may be an important mechanism complementing the mer operon-mediated reduction to mitigate mercury toxicity, particularly under iron-rich conditions. Regardless of the specific intracellular location where reduction occurs, the resultant elemental mercury is volatile and readily diffuses across the cellular membrane, ultimately escaping from the aqueous culture medium. However, we cannot rule out the possibility that reduction may also occur directly on the surface of intracellular nanoparticles. Further studies will be required to fully resolve the sequence of the dissolution and reduction events.

Implications for metal biogeochemistry

The observation that chemolithoautotrophic bacteria effectively convert Hg-bearing nanoparticles to form Hg0 unveils a previously unidentified, yet important source of Hg0 in natural microbial habitats. Chemolithoautotrophic microorganisms are prevalent in Hg-impacted regions such as terrestrial soils, marine sediments, deep-sea hydrothermal vents and acid mine drainage areas [64–67]. The three chemolithoautotrophic bacterial taxa (i.e. Thiobacillus, Paracoccus and Acidithiobacillus), to which the bacterial strains tested in this study belong, are widely distributed in terrestrial soils globally (Fig. S12). Moreover, nanoparticulate mercury represents an important fraction of the inorganic mercury pool in terrestrial soils (Table S2) [49,68–70]. Our modeling results show that the Hg0 emission due to the reduction of HgSNP by these chemolithoautotrophic populations can reach 272.44 ± 134.99 tonnes per year (Fig. 7 and Fig. S20), with 50% and 90% confidence intervals of 179.38–362.75 and 40.58–536.87 tonnes per year, respectively. The uncertainty arises from two sources: uncertainty in the key parameters that control Hg0 production at each location, and the spatial heterogeneity across locations. Because the global estimate aggregates all locations, both sources are reflected in the final uncertainty range. (Figs S11–S19). This estimate integrates the reduction mechanism demonstrated in the laboratory with spatially resolved field data on the co-occurrence of HgSNP and relevant chemolithoautotrophic bacteria across major terrestrial biomes. The flux from this newly discovered process is equivalent to that of geogenic Hg0 emissions (∼250 tonnes per year) [16,71], and similar to the emissions from cement production (∼236 tonnes per year), the fourth largest anthropogenic Hg0 emission source [72,73]. The significant role of chemolithoautotrophic metabolism in Hg0 production calls for targeted monitoring of chemolithoautotrophic bacterial activities in mercury-laden environments when evaluating the Hg emission potentials and warrants its inclusion in global mercury budget assessments. The release of volatile Hg0 from this newly identified process represents a missing component in the global atmospheric Hg0 budget. Our model provides a first-order approximation of the Hg0 emission flux potentially generated by this newly identified pathway. By synthesizing data from a range of experimental and observational studies, we derive a globally consistent estimate of this flux. While the modeling framework incorporates the key processes confirmed by laboratory evidence, certain environmental dynamics—such as mercury speciation changes, microbial community interactions and geochemical variability—are represented in a simplified manner due to limited empirical information at the global scale. These factors may affect net Hg0 release in natural settings. Continued empirical and modeling efforts will further refine these estimates and more precisely delineate the role of nanomineral-fueled chemolithoautotrophy in global mercury cycling.

Figure 7.

Figure 7.

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Global spatial distribution of the estimated annual Hg0 emission flux from soils driven by the reduction of HgSNP in chemolithoautotrophic bacteria. The estimation is based on the following key constraints and assumptions: (i) the modeled spatial domain encompasses major terrestrial biomes (agricultural, desert, forest, grassland, wetland, tundra); and (ii) the flux is constrained by field-measured concentrations of HgSNP and the relative abundance of chemolithoautotrophic bacteria capable of HgS reduction.

The conventional wisdom on the origin of life dictates that minerals bearing crust-abundant and non-toxic elements, such as pyrite, serve as the primary energy sources to support life [74–76]. One important observation of this study is that not only are chemolithoautotrophic microorganisms capable of harnessing energy from HgS, a mineral containing toxic metals, but also that this process becomes sustainable and thus the dominant pathway of energy production when the minerals are bioavailable at the nanoscale. This highlights the importance of particle size, in addition to elemental composition, in re-defining the mineral–metal–microbe interactions that are critical to the field of metal biogeochemistry. Our discovery also remarkably expands the spectrum of mineral-supported chemolithoautotrophy and the understanding on how microbial life may evolve to cater for the diversity of energy production.

MATERIALS AND METHODS

Detailed descriptions of materials and methods are presented in the Supplementary data.

Supplementary Material

nwaf581_Supplemental_Files
nwaf581_supplemental_files.zip (33.1MB, zip)

Contributor Information

Zeyou Chen, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Chenyang Zhang, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Zhanhua Zhang, Agro-Environmental Protection Institute, Ministry of Agriculture and Rural Affairs, Tianjin 300191, China.

Qing Chang, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Cheng Gao, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Xiao Liang, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Xin Nie, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Long Chen, School of Geographic Sciences, East China Normal University, Shanghai 200241, China.

Zhi Cao, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Yan Lin, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Pedro J J Alvarez, Department of Civil and Environmental Engineering, Rice University, Houston, TX 77005, USA.

Wei Chen, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Tong Zhang, College of Environmental Science and Engineering, Ministry of Education Key Laboratory of Pollution Processes and Environmental Criteria, Tianjin Key Laboratory of Environmental Remediation and Pollution Control, Nankai University, Tianjin 300350, China.

Cong-Qiang Liu, School of Earth System Science, Tianjin University, Tianjin 300072, China.

DATA AVAILABILITY

The input data, codes and modeling outputs used in this study are available on Zenodo: https://zenodo.org/records/17679469.

FUNDING

This work was supported by the National Natural Science Foundation of China (22125603 and 22536002), the Tianjin Municipal Science and Technology Bureau (21JCJQJC00060) and China–US Center for Environmental Remediation and Sustainable Development. P.J.J.A. was supported by the Rice Water Institute.

AUTHOR CONTRIBUTIONS

Z.C., C.Z., Z.Z., Q.C., C.G., X.L. and X.N. carried out the experiments and data analysis. T.Z. conceived the study and supervised the research. L.C., Z.C., Y.L., P.J.J.A., W.C. and C.Q.L. contributed intellectual input to the experimental design and data analysis. Z.C., C.Z., Z.Z., W.C. and T.Z. drafted the manuscript with input from all authors.

Conflict of interest statement . The authors declare that they have no conflict of interest.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

nwaf581_Supplemental_Files
nwaf581_supplemental_files.zip (33.1MB, zip)

Data Availability Statement

The input data, codes and modeling outputs used in this study are available on Zenodo: https://zenodo.org/records/17679469.

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