Microbial potential to mitigate neurotoxic methylmercury accumulation in farmlands and rice

Domain: earth_science
Published: 2025-06-02
Editorial outcome: minor_revision

Abstract
Toxic methylmercury (CH3Hg+) is produced by microbial conversion of inorganic mercury in hypoxic environments such as rice paddy soils, and can accumulate in rice grains. Although microbial demethylation has been recognized as a crucial pathway for CH3Hg+ degradation, the identities of microbes and pathways accountable for CH3Hg+ degradation in soil remain elusive. Here, we combine 13CH3Hg+-DNA stable-isotope probing experiments with shotgun metagenomics to explore microbial taxa and associated biochemical processes involved in CH3Hg+ degradation in paddy and upland soils. We identify Pseudarthrobacter, Methylophilaceae (MM2), and Dechloromonas as the most significant taxa potentially engaged in the degradation of 13CH3Hg+ in paddy soil with high mercury contamination. We confirm that strains affiliated with two of those taxa (species Dechloromonas denitrificans and Methylovorus mentalis) can degrade CH3Hg+ in pure culture assays. Metagenomic analysis further reveals that most of these candidate 13CH3Hg+ degraders carry genes associated with the Wood-Ljungdahl pathway, dicarboxylate-hydroxybutyrate cycle, methanogenesis, and denitrification, but apparently lack the merB and merA genes involved in CH3Hg+ reductive demethylation. Finally, we estimate that microbial degradation of soil CH3Hg+ contributes to 0.08–0.64 fold decreases in CH3Hg+ accumulation in rice grains across China (hazard quotient (HQ) decrements of 0.62–13.75%). Thus, our results provide insights into microorganisms and pathways responsible for CH3Hg+ degradation in soil, with potential implications for development of bioremediation strategies.

Introduction
Methylmercury (CH3Hg+) poses significant environmental concerns due to its ability to biomagnify in food chains and its profound toxicity to both humans and wildlife1,2. Even low-level dietary exposure to CH3Hg+ can cause irreversible neurological damage to humans3, reducing the intelligence quotient (IQ) of newborns4. Paddy fields are particularly concerning as they serve as hotspots for CH3Hg+ production due to their hypoxic condition favoring Hg-methylating microorganisms5. CH3Hg+ produced in the soil has a high propensity to accumulate in rice grains, and is also a crucial source of CH3Hg+ in adjacent aquatic environments5,6. In many regions, paddy and upland rotations are commonly practiced as cropping systems7, making it critical to assess the dynamics of CH3Hg+ in both soil types. Recent discoveries of CH3Hg+ production even in oxic habitats indicated that CH3Hg+ accumulation and associated environmental processes are more complex than previously understood8. Prior research disclosed that specific microorganisms have the capacity to degrade CH3Hg+ in pure culture. It was reported in the 1960s that Staph. aureus, originally isolated from medical waste, had the ability to demethylate CH3Hg+ to Hg0 9. Subsequently, Desulfovibrio desulfuricans LS, a sulfur-reducing bacteria, and Methanococcus maripaludis, a methanogen, were identified as potential CH3Hg+ degraders10. Recent studies have further confirmed the ability of iron-reducing bacterium Geobacter bemidjiensis Bem and methanotrophic bacterium Methylosinus trichosporium OB3b to degrade CH3Hg+ in pure culture settings11,12. Nevertheless, a significant challenge lies in the quest to identify active CH3Hg+ degraders within natural environments. This arises from the considerable variability of the merB gene, which encodes the organomercury lyase responsible for CH3Hg+ degradation among various microorganisms13,14. As a result, the development of dependable biomarkers specifically targeting CH3Hg+ degradation by microorganisms remains a largely uncharted territory14. In the context of complex soil conditions, a recent work has proposed potential microbial taxa associated with CH3Hg+ degradation in soils through ecological statistical analyses15. While these findings have offered valuable insights into microbial degradation of CH3Hg+ in soils, there is still a lack of experimental evidence pinpointing the specific microbial taxa responsible for this process.

Two predominant pathways have been identified in the microbial degradation of CH3Hg+: reductive degradation mediated by the mer operon and oxidative degradation linked to one-carbon (C1) metabolism16,17. The mer operon has garnered attention, particularly the merB gene, which encodes the alkaline mercury lyase responsible for demethylating CH3Hg+ into Hg(II), and the subsequent merA gene, which catalyzes the transformation of reducing Hg(II) into Hg(0). Oxidative degradation is believed to involve a co-metabolism of CH3Hg+ resembling the metabolism of other small organic substrates (e.g., C1 compounds) by heterotrophic bacteria, including sulfate-reducing bacteria, methanogens, and certain aerobic bacteria. Studies have demonstrated that a significant portion of putative microbial taxa associated with CH3Hg+ degradation exhibits metabolic potentials related to sulfur metabolism and nitrate reduction18,19. For instance, known microbial taxa associated with CH3Hg+ degradation through non-merB-mediated pathways often exhibit sulfate reduction abilities20,21. While previous research has emphasized the significance of microbial taxa in CH3Hg+ degradation in sediments and paddy soils20,22, there has been limited exploration of the metabolic pathways associated with CH3Hg+ degradation by soil microorganisms.

Here, we aimed to explore specific microbial taxa and metabolic pathways involved in CH3Hg+ degradation and to estimate the microbial contribution to CH3Hg+ mitigation in rice. We employed 13CH3Hg+-DNA stable-isotope probing (SIP) combined with 16S rRNA long-read sequencing to identify microbial taxa responsible for 13CH3Hg+ degradation, and subsequently validated the degradation ability of candidate taxa through pure culture assays. We further reconstructed metagenome-assembled genomes (MAGs) to explore potential metabolic pathways associated with CH3Hg+ degradation. Finally, we estimated potential changes in rice CH3Hg+ accumulation and associated health risks resulting from microbial degradation of soil CH3Hg+ in the typical paddy soils from main rice-producing areas in China.

Results
13CH3Hg+ degradation in soils
Using 13C-labeled CH3Hg+ as a metabolic tracer, we investigated microbial taxa involved in CH3Hg+ demethylation in two contrasting soils (i.e., paddy and upland soils) with historically low or high Hg contamination levels (Supplementary Table S1). Twelve microcosm experiments were conducted by incubating each soil with CH3Hg+ at a spiked concentration of 50 μg kg−1 in the dark. The CH3Hg+ concentration in sterilized soils had no discernible changes during the incubation (Fig. 1A, B). We observed consistent microbial degradation of CH3Hg+ in the eight unsterilized treatments, but the extent of degradation depended on the soil types and the initial background Hg levels (Fig. 1 and Supplementary Table S1). For the soil from high Hg-contaminated site, the mean concentrations of CH3Hg+ after 28 days of incubation were 5.16 μg kg−1 and 23.16 μg kg−1 in the paddy soil (High-P) and upland soil (High-U), respectively, and the degradation efficiencies reached 86 and 37% (Fig. 1C). Differently, the mean concentrations of CH3Hg+ were 28.05 μg kg−1 and 14.10 μg kg−1 in the paddy soil (Low-P) and upland soil (Low-U) that were from the low Hg-contaminated region, respectively, and the degradation efficiencies of CH3Hg+ were 40 and 64% (Fig. 1D). Among these treatments, CH3Hg+ concentration in the High-P and Low-U soils showed a clear decline with the spiked 13CH3Hg+, similar to the trends observed with the addition of 12CH3Hg+ in the soils (Supplementary Fig. 1). Additionally, the degradation rates of CH3Hg+ were generally positive over the entire incubation period in the 13CH3Hg+ treatments (Supplementary Fig. 2). The highest degradation rates were observed on day 14 in the High-P soil (2.95 μg kg−1 d−1) and Low-U soil (1.43 μg kg−1 d−1), whereas peak rates occurred on day 3 in the High-U soil (1.57 μg kg−1 d−1) and Low-P soil (5.30 μg kg−1 d−1). These results suggest that soil microorganisms had a strong ability to degrade the spiked CH3Hg+, with higher CH3Hg+ degradation potential in the High-P and Low-U soils compared with the High-U and Low-P soils.

Identification of microorganisms degrading 13CH3Hg+
To identify candidate microbial taxa involved in CH3Hg+ degradation, DNA-SIP experiments were performed using 13C-labeled or unlabeled 12CH3Hg+ as substrates on the High-P and Low-U soils. Genomic DNAs from the microcosm soil with 12CH3Hg+ and 13CH3Hg+ were separated into heavy (i.e., 13C-DNA) fractions and light (i.e., 12C-DNA) fractions by CsCl gradient ultracentrifugation. The abundances of 16S rRNA genes in these fractions were then quantified using real-time quantitative PCR to assess the distribution of bacterial communities across buoyant density (BD) gradients. Results showed that 16S rRNA genes were detected at the maximum abundance in the light DNA fractions (at day 7) from both the 12CH3Hg+ and 13CH3Hg+ treatments in the examined soils, while a gradual shifting of 16S rRNA gene abundance to the heavier fractions occurred at day 14 and 28 and only in the 13CH3Hg+ treatment (Fig. 2A–F). Therefore, the fractionation of DNA subsamples reveals a promising approach to trace and identify the microorganisms degrading 13CH3Hg+.

Given that the obvious shift of the 16S rRNA gene abundance in light fractions was detected at day 28, the fractions (from nine to 14 fractions) with higher 16S rRNA gene abundance from the 12CH3Hg+ and 13CH3Hg+ treatments were selected for long-read sequencing of 16S rRNA genes on the PacBio RSII platform. Microorganisms showing 13C enrichment in the DNA fractions of the 13CH3Hg+ treatment are assumed to have the ability to assimilate CH3Hg+ and thus incorporate 13C into their DNA. By examining the abundance of 16S rRNA genes across CsCl gradient fractions in the microcosm incubation over time, the risk of potential cross-feeding of assimilated 13C within microbial communities was minimized (Fig. 2A–F). We showed significant 13C enrichments in the fraction of the highest 16S rRNA gene copies from the 13CH3Hg+ treatment of both soils, comparing with the corresponding fraction in the 12CH3Hg+ treatment (Fig. 2G–J). In brief, there were 509 OTUs and 54 OTUs significantly enriched in 13CH3Hg+-spiked soils in High-P (Fig. 2G) and Low-U (Fig. 2H), respectively. Most of the OTUs were close to Planctomycetota, Proteobacteria and Acidobacteria in the 13C-DNA from spiked-13CH3Hg+ soils (Fig. 2I, J; Supplementary Fig. 3).

Moreover, dominant families, such as Xanthomonadaceae, Xanthobacteraceae and Comamonadaceae were significantly enriched in the 13CH3Hg+ treatment in both the High-P and Low-U soils (Fig. 3A, B). We further identified 34 genera with significantly different abundances between the 13CH3Hg+ and 12CH3Hg+ treatments in the High-P soil (p < 0.05), and Pseudarthrobacter, Dechloromonas and MM2 were significantly enriched in the 13CH3Hg+ treatment (Fig. 3C, D). Furthermore, Dechloromonas and MM2 exhibited significant enrichment in both light and heavy fractions (from nine to 14 fractions) from the 13CH3Hg+ treatment compared with the 12CH3Hg+ treatment (Fig. 3D; Supplementary Fig. 4). This broad distribution prompted us to further investigate their potential roles in CH3Hg+ degradation. Pure culture assays with Dechloromonas denitrificans and Methylovorus mentalis, belonging to the candidate taxa, confirmed their ability to degrade CH3Hg+ (Supplementary Fig. 5). For the Low-U soil, the relative abundance of VadinHA49 exhibited a significant increase in the 13CH3Hg+ treatment compared to the 12CH3Hg+ treatment (Fig. 3E, F).

Putative metabolic pathways of CH3Hg+ degradation by metagenomic analyses
Combined analyses of metagenome sequencing and reconstruction of MAGs were performed to retrieve the draft genomes involved in 13C-labeled metabolic processes, and then putative metabolic pathways of CH3Hg+ degradation were proposed. Due to insufficient 13C-labeled DNA from a single extraction for shotgun metagenomic sequencing, DNA was extracted three times from the same soil sample for each replicate. The DNA from each extraction was subjected to DNA-SIP gradient fractionation. After DNA-SIP fractionation, composite samples were formed by combining the fractions with the highest 16S rRNA gene copies from the 13CH3Hg+ treatment of the High-P soil on day 28 for sequencing. At the community level in the paddy soil, the relative abundances of genes involved in Hg reduction (e.g., merA and merB) were comparable between the 13CH3Hg+ and 12CH3Hg+ treatments (Fig. 4A; Supplementary Fig. 6).

To further explore the multifunctional metabolic characteristics related to the 13CH3Hg+ degradation, genes involved in sulfate reduction, carbon metabolism (e.g., methane metabolism) and nitrogen metabolism (e.g., nitrate reduction and denitrification) were searched within the metagenomic contigs11,19,23 (Fig. 4A; Supplementary Fig. 6). Specifically, genes associated with sulfate reduction including those encoding sulfate adenylyl transferase (sat), dissimilatory sulfite reductase (dsrAB), and adenylylsulfate reductase (aprAB) were detected, showing comparable relative abundances between the 13CH3Hg+ and 12CH3Hg+ treatments (Fig. 4A). Furthermore, several key biochemical pathways related to carbon metabolism were annotated by the presence of genes involved in tetrahydrofolate (H4F) pathway, TCA cycle, pyruvate metabolism, methane metabolism and purine metabolism. For instance, genes encoding isocitrate dehydrogenase (IDH3), 2-oxoglutarate ferredoxin oxidoreductase (korAB), tetrahydromethanopterin S-methyltransferase subunit B (mtrB), phosphoribosylaminoimidazole-succinocarboxamide synthase (purC), dimethylglycine dehydrogenase, 5-methyltetrahydrofolate-homocysteine methyltransferase (metH), aconitate hydratase (acnA) and succinate dehydrogenase (sdhA) exhibited significant enrichment in the 13CH3Hg+ treatment compared with the 12CH3Hg+ treatment (Fig. 4A; Supplementary Fig. 6). Among them, the metH gene was the most abundant, accounting for 0.16% of the annotated genes. In addition, genes related to nitrogen metabolism and membrane transport, such as nitrate reduction, denitrification and ABC transporter, were also significantly enriched in the 13CH3Hg+ treatment (Fig. 4A; Supplementary Fig. 6). For instance, genes encoding glutamine synthetase (glnA), glutamate synthase (gltB), periplasmic nitrate reductase (napA and napB), nitrite reductase (nirS) and D-methionine transport system ATP-binding protein (metN) exhibited higher relative abundance in the 13CH3Hg+ treatment compared with the 12CH3Hg+ treatment.

Read assembly and binning from 13C-SIP metagenomics recovered a total of 5 fairly-complete MAGs associated with candidate CH3Hg+ degraders (completeness > 70% and contamination < 10%) (Fig. 4B; Supplementary Table S2), and the metabolic reconstruction of these MAGs revealed the potential functions of the genomes20. Among the five MAGs, 3 were identified as novel species associated with the genus Pseudarthrobacter (Supplementary Fig. 7). These Pseudarthrobacter-associated MAGs generally harbored mer operons, such as merP (encoding a periplasmic protein) and merR (encoding a regulatory protein), but none carried the merA and merB genes. Meanwhile, additional MAGs (MAG3 and MAG4) did not carry any genes associated with mer operons. Moreover, all the MAGs contained genes encoding carbon metabolism pathways, such as the Wood-Ljungdahl pathway (folD, fhs, fdhA, and metF) and dicarboxylate-hydroxybutyrate cycle (sucC, sucD, and mdh) (Fig. 4B). Furthermore, genes related to methanogenesis, denitrification and nitrate reduction were detected in all MAGs, and abundant genes involved in pyruvate metabolisms, purine metabolism, and ABC transporter were found in all MAGs consuming the spiked 13CH3Hg+, but genes involved in sulfate reduction were absent in all MAGs (Supplementary Fig. 8).

Estimation of rice CH3Hg+ and health risks through microbial degradation of soil CH3Hg+
To evaluate the mitigation of CH3Hg+ in rice through microbial degradation of CH3Hg+ in soils across the main rice-producing areas of China, we used the bioaccumulation factor (BAF) to link CH3Hg+ concentrations in grains to soils (Supplementary Table 3). Results indicated that the microbial degradation efficiencies of soil CH3Hg+ ranged from 8.16 to 64.26% in these typical soils across China, leading to decreases of 0.10–2.25 μg kg⁻¹ in rice CH3Hg+ (Supplementary Table 4). Health risks associated with dietary exposure to rice CH3Hg+ were further estimated by calculating HQ and IQ decrements (ΔIQ). According to the health risk model, the potential decreases in rice CH3Hg+ concentration equate to HQ reduction of 0.62–13.75%, corresponding to ΔIQ decreases of 0.13 to 2.84%, in response to microbial degradation of CH3Hg+ in the soils (Supplementary Table 4). These results highlight the crucial role of microbial degradation in mitigating rice CH3Hg+ and associated health risks.

Methods
Soil sampling and characterization
Both paddy and upland soils (0~15 cm depth) were collected from the two typical agricultural regions in Wanshan, Southwest China (27.52°N, 109.21°E), and Xianning, Center China (29.90°N, 114.23°E), in 2018 (from September to November). The mean annual precipitation and temperature in these areas ranged from 1378.7–1577.4 mm and 13.7–16.8 °C, respectively. Wanshan is known as the Hg hotspot of China, with more than 600 years of Hg mining and smelting activities, leading to elevated Hg concentrations in these soils (referred to here as high Hg-contaminated). While there are no documented Hg pollution sources in Xianning, Hg in the soil is most likely derived from parent materials and atmospheric deposition (referred to here as low Hg-contaminated). Paddy and upland rotations are used as common cropping systems in both regions7, so the presence of CH3Hg+ in the soil in both areas should not be disregarded. The collected soils were kept in an ice box during shipping and stored at 4 °C prior to incubation experiments. Details of soil geochemical properties are shown in Table S1 in the Supplementary Information.

Microcosm incubation
The 13CH3Hg+ used in this study was synthesized from 13CH3I and HgO in our laboratory37, and then dissolved in methanol. The purity of the synthesized 13CH3Hg+ compounds was evaluated by comparing the measured 13CH3Hg+ concentration with the theoretical value based on the synthesis procedure. The close match between the measured and theoretical concentrations suggests a high level of purity. In addition, we performed liquid chromatography to check for organic impurities. The conversion efficiency of 13CH3Hg+ ranged from 50.23 to 61.45%, and it could reach up to 99% after extraction and back-extraction using methylene chloride and water to remove inorganic components. The CH3Hg+ contaminated soils were prepared as follows: 10 g soil (dry weight) was spiked with CH3Hg+ solutions (both 12CH3Hg+ and 13CH3Hg+ were used in parallel for microbial comparison) to give a fixed concentration of 50 μg kg–1. As a result, the actual CH3Hg+ concentrations in the microcosms reflected the sum of the background CH3Hg+ (ranging from 0.45 to 3.48 μg kg–1; Supplementary Table 1) and the spiked CH3Hg+ (50 μg kg–1). The background CH3Hg+ concentrations may be substantial in general CH3Hg+ transformation studies; however, soil microorganisms assimilated only small amounts of 13C from 13CH3Hg+. Considering the relatively high cost of DNA-SIP, we increased the spiked CH3Hg+ concentration (50 μg kg–1) to ensure sufficient 13C enrichment for effectively tracing 13C-consuming microorganisms and identifying those involved in 13CH3Hg+ degradation. This concentration is comparable to CH3Hg+ concentrations observed in polluted farmland soils from Hg mining areas (ranging from 0.14 to 67 μg kg–1)38. A higher concentration of 13CH3Hg+ was used to obtain sufficient 13C-labeled target DNA for microbial analysis. The experiments were conducted in 50 mL serum bottles, and the microcosm experiment included the following treatments: (1) High-P, which used paddy soil from Wanshan (high Hg contaminated areas); (2) High-U, which used upland soil from Wanshan; (3) Low-P, which used paddy soil from Xianning (low Hg contaminated areas); (4) Low-U, which used upland soil from Xianning. These four treatments were all prepared using both ambient CH3Hg+ and 13C-labeled CH3Hg+. Controls were set up as follows: (5) High-SP, and (6) High-SU, representing sterilized paddy and upland soil by gamma rays from areas with high Hg-contamination, respectively; (7) Low-SP, and (8) Low-SU, representing sterilized paddy and upland soil by gamma rays from areas with low Hg-contamination, respectively. This resulted in a total of twelve treatments. During the incubation, water content was kept constant by checking the weight of the bottles regularly and adding ddH2O39. All treatments in this study were conducted in triplicate and incubated for 28 days at 25 °C in the dark. The experiment duration of 28 days was carefully selected based on literature and our pre-experiments40,41. This duration can balance both the degradation of 13CH3Hg+ and the sufficient 13C enrichment in 13CH3Hg+-degrading microorganisms.

CH3Hg+ analysis and chemical analyses
For soil CH3Hg+ analysis, ∼0.50 g dry soil of each sample was accurately weighed and then digested with 1.5 mL CuSO4 (2 mol L−1) and 7.5 mL HNO3 (25%, v/v) in an individual PE centrifuge tube. Subsequently, 10 mL dichloromethane (CH2Cl2) was added to the centrifuge tubes and closed with clean lids. These centrifuge tubes were tightly attached to an orbital shaker and shaken for 30 min at a rotational speed of 240 rpm. Then, the substrate digestion solution was transferred to a new centrifuge tube and allowed to settle in a water bath (50 °C) until all visible CH2Cl2 had completely volatilized. Finally, the extracting solution was obtained by removing any residual CH2Cl2 with high purity N2 in a water bath at 75 °C for 10 min. The concentration of CH3Hg+ in the extracting solution was measured by an automated Methyl Mercury Analytical System (Brooks Rand Labs, Seattle, WA, USA), which provides precise determination at picogram levels. CH3Hg+ concentration was measured at days 0, 3, 7, 14, and 28 in both the 13CH3Hg+ and 12CH3Hg+ treatments. However, the measured soil CH3Hg+ concentrations at day 0 (around 45 μg kg−1) did not always match the theoretical values, likely due to inevitable experimental errors, including variations in extraction efficiency and analytical recovery. According to previous studies, acceptable recoveries of CH3Hg+ from reference materials typically range from 75 to 115%, depending on soil properties15,22,42. The degradation efficiencies of CH3Hg+ were calculated based on the averaging differences of total CH3Hg+ concentrations for 28 days, using the measured CH3Hg+ concentrations at day 0 (including the background CH3Hg+) as the baseline. While we did not analytically distinguish the two isotopologues (13CH3Hg+ and 12CH3Hg+), and the individual degradation efficiencies of 13CH3Hg+ and 12CH3Hg+ were not directly quantified, the observed decline in total CH3Hg+ concentration, along with the significant 13C enrichment of microbial taxa in the heavy DNA fractions from 13CH3Hg+-DNA-SIP analyses, provide strong evidence for microbial demethylation of 13CH3Hg+ during the incubation. Moreover, soil pH was measured by a Delta pH-meter (Mettler-Toledo Instruments Co., Columbus, OH, USA) in a soil slurry with a water-to-soil ratio of 2.5:1. Dissolved C in soils was extracted with 0.5 M K2SO4 43. The extracted solution was used for analyses of DOC by a total organic C (TOC) analyzer (vario TOC; Elementar).

DNA extraction and SIP gradient fractionation
On the basis of the CH3Hg+ concentration changes, three typical time points (at days 7, 14, and 28) of the incubation experiment were selected for DNA extraction. Total genomic DNA was extracted using a MoBio powersoil DNA isolation kit (MOBIO Laboratories, Inc., Carlsbad, CA) according to the manufacturer’s instruction. DNA concentrations were determined using an ND-2000 UV-vis spectrophotometer (NanoDrop Technologies, Wilmington, DE). To separate 12C- and 13C-DNA, nucleic acid ultracentrifugation was conducted. Briefly, ∼2500 ng of genomic DNA was mixed with CsCl gradient in 5.1 mL Quick-Seal polyallomer tubes (Beckman Colter, Pasadena, USA) to achieve an initial BD of 1.7152 g mL−1. After balancing and sealing, density gradient centrifugation was performed at 176,770 × g for 45 h at 20 °C in an Optima XPN-100 ultracentrifuge (Beckman Colter) equipped with a VTi65.2 vertical rotor (Beckman Colter, USA). After ultracentrifugation, DNAs were immediately fractionated into 18 gradient fractions (∼280 μL per fraction) following the published protocol44,45. Briefly, the tube was fixed in a clamp, and the bottom was carefully pierced with a needle in a smooth and controlled manner, after which the needle was discarded. A syringe pump was used to inject sterile deionized water into the top of the tube through the needle, and drops were collected from the bottom into sterile 1.5 mL tubes. The pump rate was set to yield ∼18 × 280 µL fractions within 12 minutes (425 µL min−1, ~40 s per fraction). To ensure the gradients formed correctly, the BD value of each fraction was measured using a digital refractometer (Reichert AR2000), and then CsCl was removed by glycogen-assisted ethanol precipitation46,47. Additionally, fractions were collected in a consistent manner to avoid mixing between them, and the process was performed rapidly to prevent gradient mixing.

Quantitative PCR and PacBio sequencing of the 16S rRNA genes
To quantify the 16S rRNA genes in each fraction, qPCR was performed using a CFX Connect real-time system (BioRad, CA, USA) with the 341F (5′-CCTACGGGNGGCWGCAG-3′) and 805R (5′-GACTACHVGGGTATCTAATCC-3′) paired primers48, which match ∼90% of all bacterial sequences and cover all phyla in the Ribosomal Database Project release 10.25. The qPCR protocol proceeded as follows: an initial step at 95 °C for 5 min, followed by 40 cycles of 94 °C for 60 s, 58 °C for 30 s, and 72 °C for 30 s, with a final extension at 72 °C for 5 min. The standards with known copy numbers of the target sequence were diluted in a ten-fold serial dilution to achieve a concentration range spanning from 10 to 107 copies μL−1. All qPCR reactions were run in triplicate, including the blank that ran with water as a template instead of DNA.

Amplification of full-length (V1–V9) 16S rRNA gene sequences was performed on a PacBio RSII platform (Majorbio Bio-Pharm Technology, Co., Ltd., Shanghai, China). Briefly, the full-length 16S rRNA genes were amplified by PCR using the universal bacterial primer set 27F (5′-AGAGTTTGATCCTGGCTCAG-3′) and 1492R (5′-GGTTACCTTGTTACGACTT-3′)49. The two primers contained a set of 16-nucleotide barcodes. PCR was prepared with the following reaction components: 4 μL of 5× FastPfu Buffer, 2 μL of 2.5 mM dNTPs, 0.8 μL of Forward Primer (5 μM), 0.8 μL of Reverse Primer (5 μM), 0.4 μL of FastPfu Polymerase, 0.2 μL of BSA, 10 ng of Template DNA, and ddH2O adjusted for the sample to a 20 μL of reaction total volume. The PCR program was as follows: 95 °C for 3 min, 25 cycles of 98 °C for 20 s, 57 °C for 30 s and 72 °C for 90 s, with a final extension of 72 °C for 2 min.

The fractions (from nine to 14 fractions) with higher 16S rRNA gene abundance from the 12CH3Hg+ and 13CH3Hg+ treatments were selected for long-read sequencing of 16S rRNA genes. Moreover, we focused on analyzing the 16S rRNA gene amplicon sequences from the fraction with the highest abundance of 16S rRNA gene copies in the 13CH3Hg+ treatment and the corresponding fraction in the 12CH3Hg+ treatment50. This targeted analysis better represents the active microbial taxa directly involved in 13CH3Hg+ degradation. Sequencing of the amplicons was performed on a PacBio Sequel instrument (Pacific Biosciences, Menlo Park, CA, USA) at Shanghai Majorbio Bio-pharm Technology Co., Ltd., Shanghai, China (https://www.majorbio.com/). Raw data were retrieved and filtered with the circular consensus sequencing (CCS) software of the SMRT Link (min full pass = 3, polish min Predicted Accuracy = 0.8, minLength = 500) to obtain the Raw CCS Reads. The barcode reads of every sample were recognized with Lima (https://github.com/PacificBiosciences/barcoding) to acquire Raw CCS, whereafter the CCS (accuracy above 99%) of each sample was tested and chimeric reads were removed with UCHIME (http://drive5.com/uchime, v8.1) to acquire quality controlled sequences. Subsequently, the representative sequences were compared using the Mothur (https://mothur.org/wiki/Classify.seqs, v1.40.0) software with Silva 132 database (classified at a bootstrap threshold of 0.9) to gain classified information.

Shotgun metagenomic sequencing
The metagenomic shotgun sequencing (2×150 bp) was conducted exclusively on the High-Hg contaminated paddy soil (High-P), which was selected due to its highest potential of microbial 13CH3Hg+ degradation. The sequencing was carried out on an Illumina NovaSeq 6000 platform (Shanghai Majorbio Bio-pharm Technology), which generally requires 1–5 μg of DNA for sequencing51,52. Since the DNA quantity did not meet these requirements, composite DNA samples were obtained by pooling the DNA from heavy fractions with the highest 16S rRNA gene copies from each of the triplicates of the 13CH3Hg+. The corresponding fractions from the 12CH3Hg+ treatment underwent the same procedure. A total of 10.7–18.6 Gb clean reads were obtained for each sample after quality control following the KneadData pipeline (v0.6.1), accounting for 94.3–97.9% of raw bases. De novo assembly of clean reads into contigs was performed using megahit (https://github.com/voutcn/megahit, -k-min 47 -k-max 97 -k-step 10, v1.2.9), CD-HIT (http://www.bioinformatics.org/cd-hit/, v4.6.1) and Salmon (https://github.com/COMBINE-lab/salmon, v1.10.0) were employed for subsequent open reading frames prediction53–55, non-redundant gene catalog clustering, and non-redundant gene quantification. Biological function annotation of the non-redundant genes was conducted on GhostKOALA annotation servers (Automatic KO assignment by GHOSTX sequence similarity search56. Binning of the assembled metagenome was computed and refined using MaxBin2 (http://sourceforge.net/projects/maxbin/, v2.2.7)57 and metaBAT2 (https://bitbucket.org/berkeleylab/metabat, v2.12.1)58 in MetaWRAP59,60. Completion and contamination estimation of all the bins were computed by CheckM (https://github.com/Ecogenomics/CheckM/wiki, v1.1.6)61. Taxonomic classification of MAGs was performed using GTDB-Tk v0.3.3 classify_wf command against the GTDB (http://gtdb.ecogenomic.org/, v2.3.2)62,63. Among all reconstructed MAGs, 13 were classified as medium-quality according to the Minimum Information about a Single Amplified Genome (MIMAG; >50% completeness, <10% contamination)64. Only 5 fairly complete MAGs with more than 70% completeness and less than 10% contamination were selected for further analysis65. An overview of the assembly statistics for MAGs in the selected soils was provided in Supplementary Table 2. The predicted genes of MAGs were annotated using the HMM profile database for KEGG orthology with predefined score thresholds through KofamScan (v1.3.0)66.

Validation of CH3Hg+ degradation by candidate bacterial taxa
To validate the ability of candidate microbial taxa to degrade CH3Hg+, we conducted a series of bioassays using Dechloromonas denitrificans (DSM 15892) and Methylovorus mentalis (DSM 24715), which belong to the proposed genera associated with CH3Hg+ degradation. Dechloromonas denitrificans (DSM 15892) and Methylovorus mentalis (DSM 24715) were purchased from the Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures (Braunschweig, Germany). Both cultures were grown in the recommended media at 30 °C. Cells were harvested at the exponential growth phase and subsequently washed twice by repeated centrifugation (10 min at 1610 × g) and resuspension in phosphate buffer saline (PBS) at pH 7.2. The PBS consisted of 0.14 mol·L−1 NaCl, 3 mmol·L−1 KCl, 10 mmol·L−1 Na2HPO4, and 2 mmol·L−1 KH2PO4. The cell density was obtained by measuring optical density at 600 nm.

The CH3Hg+ degradation bioassays were conducted in sealed amber glass vials (4 mL). Each vial contained washed cells (5 × 108 cells·mL−1), supplemented once (at time zero) with 5 mmol·L−1 metal salt solution (MgCl2). The CH3Hg+ was added to the cell suspension to obtain a final concentration of 1 ng·mL−1 CH3Hg+. Experiments were performed in triplicate and included heated-killed culture controls (80 °C for 1 h) and PBS blanks. The final reaction volume was 1 mL in each vial. All vials were sealed immediately and placed on an orbital shaker and kept in the dark. At selected time points, replicate sample vials were taken out and analyzed for CH3Hg+ concentration.

Changes in rice CH3Hg+ and health risks resulting from microbial degradation of soil CH3Hg+
Exposure to CH3Hg+ through rice consumption has a prolonged effect on human health, as rice is a major source of dietary CH3Hg+ exposure in China, accounting for up to 96% of total CH3Hg+ exposure67. In our study, microorganisms may reduce the accumulation of CH3Hg+ in rice through the degradation of soil CH3Hg+. To predict the changes of CH3Hg+ accumulation in rice grains, we use the BAF to link CH3Hg+ in grains and in soils. The decreases in rice CH3Hg+ concentrations due to microbial degradation of soil CH3Hg+ are calculated using the BAFs, measured soils CH3Hg+ and microbial degradation efficiencies34:

ΔRiceCH3Hg+ = BAF × SoilCH3Hg+ × Microbial degradation efficiency (1)

Where soil CH3Hg+ values and microbial degradation efficiencies of CH3Hg+ were obtained from our unpublished study, in which we collected ten typical paddy soils, quantified CH3Hg+ concentrations in sterilization and unsterilization treatments, and calculated the microbial degradation efficiencies of CH3Hg+ (Supplementary Table 3). Microbial degradation efficiency (the percent of CH3Hg+ degraded over 28 days by the microbial community) was incorporated into the model to calculate changes in rice CH3Hg+ concentrations. It is important to note that the observed degradation efficiencies during the 28-day period represent net changes, accounting for both production and degradation processes. We chose microbial degradation efficiency over degradation rate as it provides a standardized index. While degradation rates vary over time, microbial degradation efficiency offers a relatively stable estimate of microbial CH3Hg+ degradation potential in environments.

Estimated daily intake (EDI) would be determined by calculations as described below34:

EDI = Ii × Ci / BW (2)

Where Ii represents the per-capita intake rate (g d−1 capita−1) in province i, Ci represents the rice CH3Hg+ (μg kg−1) while BW represents the average body weights of females (57.3 kg).

Health risks associated with dietary exposure to rice CH3Hg+ are estimated by calculating the HQ and ΔIQ in per-fetus across China. The equations for the calculation of HQ and ΔIQ are provided blow34,68:

HQ = EDI / RfD (3)

ΔIQ = λ × γ × β × (ΔEDI × BW) (4)

In the formulas, HQ is used to evaluate the non-cancer health hazard, ΔEDI is the changes in daily intake, and RfD represents the reference dose for CH3Hg+, i.e., 0.1 μg kg−1·d−1 according to the USEPA (1997). Meanwhile, ΔIQ represent the change in IQ points for per-fetus due to intake of CH3Hg+. BW represent the average body weights of females, and coefficients including λ (μg Hg g-1 hair per μg Hg L−1 blood), γ (IQ points change per μg Hg g-1 hair), and β (μg Hg L−1 blood per μg Hg d−1) show the conversion from rice CH3Hg+ intake to per-fetus IQ change4,69. The values of λ, γ, and β are 0.20, 0.30, and 0.60, respectively.

We further conducted the one-at-a-time sensitivity analysis and uncertainty analysis based on interval methods to assess uncertainties in health risk estimates70,71. We identified the most important parameters for HQ and IQ decrements (ΔIQ) from microbial degradation efficiency, soil CH3Hg+ concentration, BAF, and rice ingestion rate. The results showed that microbial degradation efficiency and soil CH3Hg+ concentration were the most important, with microbial degradation efficiency having the highest sensitivity coefficients for HQ and ΔIQ (Supplementary Tables 5, 6). For instance, when microbial degradation efficiency increased from 8.16 to 64.26% under identical conditions, the reduction in HQ increased from 0.0095 to 0.0749, representing an eight-fold increase. We further conducted an uncertainty analysis based on interval methods by varying key parameters within their observed ranges (Supplementary Table 7). We quantified potential variability in HQ and ΔIQ, which ranged from 0.0027 to 0.3301 and 0.0006 to 0.0681, respectively. The results consistently demonstrated that microbial degradation efficiency is the key factor in reducing health risks.

Statistical analysis
A minimum of three independent microcosms were considered for each analysis. One-way analysis of variance followed by a two-sided Tukey post hoc test was performed by SPSS Statistics 21.0 (IBM, Chicago, IL) to detect the significant differences between treatments in the pure culture assays. LEfSe analysis (p < 0.05, LDA score > 2) was used to identify bacterial biomarkers for the 13CH3Hg+ and 12CH3Hg+ treatments on the open website (http://huttenhower.sph.harvard.edu/galaxy). A two-sided Student’s t test was conducted to identify genes or microbial species that exhibited significant enrichment in the heavy fraction of the 13C-labeled treatment compared to the corresponding fraction in the 12C control (* representing p < 0.05), and to assess differences in CH3Hg+ degradation efficiency between paddy and upland soils from both high and low Hg-contaminated sites. The phylogenetic trees were generated and visualized using a CVTree4 algorithm (https://cvtree.online/v4/prok/)72 and the Evolview v3 web application (https://www.evolgenius.info/evolview/#/treeview)73, respectively.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Authors are presenting findings about methylmercury degradation by rice paddy microorganisms based on incubation with labeled methylmercury coupled to DNA-SIP, metagenomic and tests on living bacterial strains.\nThe topic is relevant from different perspectives, including food safety and environmental microbiology, adding important information on the identity of methylmercury degraders and their potential impact on food safety. Referenced literature is adequate and conclusions fit with the aims and the results of the experiments.\nThe manuscript is generally well written, with minor revisions needed in the English and some typos (i.e., Line 49: Change “Hg methylating” with “Hg-methylating”; Lines 56-58: Revise English of the sentence “Subsequently … degraders.”; Line 152: Add final s to “Arenimona” and “Dechloromona”).\nIn the results section, since \"Materials and methods\" are at the end, authors should provide a few details for clarity (i.e., the platform used to perform long-read sequencing; the fact that 16S genes were quantified with qPCR).\nThere is one experimental point that is absolutely not clear for me in Lines 162-166: how was DNA pooling managed? According to what is written, heavy DNA was pooled with 16S rRNA copies, but I think this does not make sense. Authors should clarify well this point.", "reviewer_2": "The manuscript by Zhou et al provide interesting new data and findings about microbial mercury detoxification in farmland soil and also present some back of the envelope estimates of how ambient microbial mercury demethylation processes can lower the health burden related to human mercury exposure. The methods used to estimate rates and identify active microbial populations are state of the art and the data appear very convincing to this reviewer and my main critique relates to the uncertain modeling of the health hazards from MeHg exposure (where some modifications and further discussion are warranted).\n(1) Line 104: Does these concentrations account for in situ MeHg concentration? Background concentrations may be substantial.\n(2) Line 109-117: The degradation efficiency is arbitrarily defined as % degraded over a 28 day period. It would be much more useful to provide degradation rates.\n(3) Line 199-211, 454-485: The estimates of health risks are critically depending on a number of rather uncertain assumptions and the estimates should be presented as such (acknowledging uncertainties). I also wonder how the “degradation efficiency” (fraction degraded MeHg in 28 days) come into play here. Why limit the assessment to this period? Do you assume that degradation halts after 28 days? The data does not support that. All in all I feel that a proper sensitivity analysis of this modeling effort is warranted to illustrate/assess the uncertainties in the numbers presented.\n(4) General and line 270-272: Carrying a gene does not necessarily mean it is being used or expressed un der the given environmental conditions. I don’t thin k you can make the claim that the TCA cycle or assimilatory sulfate reduction is linked to MHg demethylation here. For that you need transcriptomic or proteomic data (or activity measuements). Uisng this indirect data to claim that SRB and methanogens play an important role in oxic MeHg demethylation is speculative.\n(5) Line 317-319: How did you assess the purity of the synthesized compounds?\n(6) Please provide a motivation for duration of the experiment (28 days). Would a shorter or longer incubation time change the major results?\n(7) Line 369: How was the fractionation done? Is there a risk of cross-contamination between fractions?\n(8) Line 376-378: The indicated reference is not the original one for the indicated primers. Please use the original reference and mention something about the taxonomic coverage since this is an important parameter.\n(9) Line 387-388: These are very old primers known to miss several groups (even entire phyla). A cautionary discussion about the potential to overlook some active MeHg demethylators is warranted.\n(10) Line 499-501: There are plenty of easy access and persistent data archives available for depositing sequence data. This contribute to reproducible science and I would rplease ask the authors to deposit their data in such repositories before publication can ber considered. There is really now excuse for not doing so.\n(11) Ther reference list is very long and for sure it can be trimmed to remove redundancies without compromising the rigor of the article.\n(12) Figure 5 is hard to interpret and can be removed while the numbers can be presented in running text.\nMinor:\nTitle (line 1): “unraveling” is a vague term and is not really needed in the title.\nLine 32-33: Strange sentence. I would write “are known to degrade CH3Hg+ in pure culture”.\nLine 34: The metagenome assembled genomes are fictional population genomes and as such they are not involved in any biological process (the organisms they were assembled from are on the other hand).\nLine 36+89: This is not an assessment, but an estimate or prediction (depending on how you see it).\nLine 136: “enrichment” should be “13C enrichment”\nLine 146: “dominated both in the” is redundant and can be deleted.\nLine 156: “putative microbial taxa” is awkward and pointless. Do you mean Candidate taxa?\nLine 160: Clarify that you mean “metagenome sequencing and reconstruction of metagenome assembled genomes”.\nLine 163: What are these requirements? Is it a fixed limit or depending on service provider?\nLine 225-226: This is an incorrect statement. Please specify that this relates to degradation of organic substrates for energy acquisition.\nLine 233: Remove “the”, since many more taxa may be shared beyond the most abundant.\nLine 239: “especially” rather than “specifically”.\nLine 283: “to decreases of” does not fit here. Revise.\nLine 287: Reading the sentence one can interpret this as if you actually were able to enhance the in situ activities of these putative demethylators, but I think this is only a suggestion, right?\nLine 341: “accurate” is not the right word.\nLine 403: What is “optimized” sequence? You mean “trimmed or quality controlled?\nLine 415: Remove “proceeded”", "reviewer_3": "The authors attempted to elucidate the microbial communities and their functions involved in degrading highly toxic methylmercury (CH3Hg) through SIP and metagenomic analyses, using DNA extracted from soils treated with CH3Hg.\nAdditionally, they calculated the potential for CH3Hg degradation in various soils across China.\nThe key flow of this manuscript is summarized as follows:\n(1) CH3Hg was added to High-Hg contaminated paddy soil, High-Hg contaminated upland soil, Low-Hg contaminated paddy soil, and Low-Hg contaminated upland soil. The CH3Hg degradation rates were determined (Fig. 1, Supplementary Fig. 1).\n(2) A SIP analysis was conducted using DNA extracted from soils treated with CH3Hg, focusing on High-Hg contaminated paddy soil and Low-Hg contaminated upland soil. Quantitative PCR targeting 16S rRNA was performed, and the community structures of the peak fractions were analyzed via amplicon sequencing. Arenimonas, Dechloromonas, and MM2 predominantly assimilated 13C in High-Hg contaminated paddy soil, while Ramlibacter and Sumerlaea were identified in Low-Hg contaminated soil, suggesting their involvement in CH3Hg degradation (Fig. 2, 3, Supplementary Fig. 2, 3).\n(3) Among these, isolates of Dechloromonas (the second most abundant) and Methylovorus (possibly related to the fifth most abundant Methylotenera) were obtained from DSMZ or another source, and their ability to degrade CH3Hg was experimentally demonstrated (Supplementary Fig. 4).\n(4) Shotgun metagenomics was performed on DNA extracted from soils (13CH3Hg-treated?), and MAGs were constructed. More than half of the constructed MAGs were derived from Actinobacteria, while bacteria identified as dominant in (2) were absent. The authors examined the CH3Hg degradation pathways and other metabolic pathways encoded in the genomes of these MAGs (Fig. 4, Supplementary Fig. 5).\n(5) Using metagenomic analysis, the relative abundance of various metabolic pathways was compared between soils treated with 12CH3Hg and 13CH3Hg (Supplementary Fig. 6-9).\nMajor Comments:\n(2) Analysis of High-Hg contaminated upland soil and Low-Hg contaminated paddy soil\n・There is no mention about High-Hg contaminated upland soil and Low-Hg contaminated paddy soil in this manuscript. Why were these soil types not selected for subsequent analysis? This information is missing throughout the manuscript.\n・The Discussion states that similar bacteria contributed to CH3Hg degradation in soils located 500 km apart. Does this mean that upland and paddy soils were being compared? Given that the potential for CH3Hg degradation across different Hg contamination levels within China was calculated, wouldn’t it be more appropriate to compare to each other among paddy soils? If upland soils were analyzed, the Introduction should provide a clear rationale, and the comparisons should extend to upland soils as well.\n(3) Selection of Dechloromonas and Methylovorus\n・Why were Dechloromonas and Methylovorus selected? Dechloromonas is the second most abundant, and Methylovorus, possibly related to Methylotenera, ranks fifth. Is it unnecessary to examine other bacteria?\n(4) Issues with the constructed MAGs\nThis is considered the most critical issue.\n・More than half of the constructed MAGs were derived from Actinobacteria, and none of the bacteria identified in the SIP analysis as contributors to CH3Hg degradation were present.\n・Actinobacteria are known to have high GC content, as does the second most abundant Gemmatimonas. Since the MAGs were constructed from metagenomic data of the heavy fractions, it is possible that the bacteria identified are not contributors to 13CH3Hg degradation but were enriched due to their high GC content. The authors should evaluate whether genes from Actinobacteria or Gemmatimonas are significantly more abundant in soils treated with 13CH3Hg than in soils treated with 12CH3Hg. If discrepancies arise between the metagenomic and SIP analyses, the reasons for these differences should be addressed.\n・If the study aims to discuss the microbial communities and their functions involved in CH3Hg degradation, greater emphasis should be placed on bacteria identified through SIP analysis as 13CH3Hg degraders. The metabolic pathways associated with functional genes from these bacteria should be evaluated via metagenomics.\nSpecifically, the microbial origins of functional genes obtained through metagenomics should first be identified. Functional genes derived from microbes identified as 13CH3Hg degraders in the SIP analysis should be prioritized for discussion.\nMaterials and Methods of Shotgun Metagenomic Sequencing\nWas shotgun metagenomics conducted only for High-Hg contaminated paddy soil?\nThe authors should specify which fraction from which day was used.\n(5) Discussion of metabolic pathways from metagenomic analysis\nThe abundance of various pathways obtained from metagenomic analysis of soils treated with 12CH3Hg and 13CH3Hg is discussed, but no significant differences were observed between 12C and 13C.\nBased on these results, it is difficult to discuss microbial functions associated with 13CH3Hg degradation.\nGeneral Impression\nOverall, the analysis and discussion of the samples possibly with high degradation potential (as demonstrated in (1)) seems to be insufficient."}, "author_response": "Responses to reviewer’s comments:\nReviewer #1 (Remarks to the Author):\nAuthors are presenting findings about methylmercury degradation by rice paddy\nmicroorganisms based on incubation with labeled methylmercury coupled to DNA-SIP,\nmetagenomic and tests on living bacterial strains.\nThe topic is relevant from different perspectives, including food safety and\nenvironmental microbiology, adding important information on the identity of\nmethylmercury degraders and their potential impact on food safety. Referenced\nliterature is adequate and conclusions fit with the aims and the results of the\nexperiments.\nThe manuscript is generally well written, with minor revisions needed in the English\nand some typos (i.e., Line 49: Change “Hg methylating” with “Hg-methylating”; Lines\n56-58: Revise English of the sentence “Subsequently … degraders.”; Line\n152: Add final s to “Arenimona” and “Dechloromona”).\n1. Thank you very much for the positive and constructive comments on our manuscript.\nWe have carefully checked the manuscript and corrected English typos. Please see\nour revisions in lines 52, 62-64 and 165.\nIn the results section, since \"Materials and methods\" are at the end, authors should\nprovide a few details for clarity (i.e., the platform used to perform long-read sequencing;\nthe fact that 16S genes were quantified with qPCR).\n2. We have supplemented the necessary details of methods in the result section. For\ninstance, we have now provided information on the long-read sequencing of 16S\nrRNA genes using the PacBio R RS II platform and the quantification of 16S rRNA\ngene abundances by real-time quantitative PCR. Please see our revisions in lines\n136-138, 145-148 and 176-184.\nThere is one experimental point that is absolutely not clear for me in Lines 162-166:\nhow was DNA pooling managed? According to what is written, heavy DNA was pooled\nwith 16S rRNA copies, but I think this does not make sense. Authors should clarify\nwell this point.\n3. Thanks for your valuable comment. We conducted the DNA-SIP experiments with\nthree replicates for both the 13CH Hg+ and 12CH Hg+ treatments. Due to insufficient\n3 3\n13C-labeled DNA from a single extraction for shotgun metagenomic sequencing,\nDNA was extracted three times from the same soil for each replicate. The DNA\nfrom each extraction was subjected to DNA-SIP gradient fractionation. After DNA-\nSIP fractionation, composite samples were formed by combining the fractions with\nthe highest abundance of 16S rRNA gene from the 13CH Hg+ treatment for\n3\nsequencing. We have clarified these important points in the revised manuscript\n(lines 179-184 and 476-480).\nReviewer #2 (Remarks to the Author):\nThe manuscript by Zhou et al provide interesting new data and findings about microbial\nmercury detoxification in farmland soil and also present some back of the envelope\nestimates of how ambient microbial mercury demethylation processes can lower the\nhealth burden related to human mercury exposure. The methods used to estimate rates\nand identify active microbial populations are state of the art and the data appear very\nconvincing to this reviewer and my main critique relates to the uncertain modeling of\nthe health hazards from MeHg exposure (where some modifications and further\ndiscussion are warranted).\n4. Thank you very much for your positive comments and valuable feedback on our\nwork. We also greatly appreciate your insightful critique regarding the uncertainties\nin the modeling of health hazards from CH Hg+ exposure, which substantially\n3\nimproves our manuscript. In response, we have now expanded the discussion on the\nassumptions and uncertainties in the health risk estimates, providing a clearer\nexplanation of the key parameters (e.g., microbial degradation efficiency and soil\nCH Hg+ concentration) and their contributions to variability in the results (lines\n3\n324-328 and 529-540). Additionally, we conducted uncertainty and sensitivity\nanalyses to assess the robustness of our conclusions and identified the parameters\nwith the most significant influence on health risk estimates (lines 560-574). The\nresults underscore the critical role of microbial degradation efficiency and soil\nCH Hg+ concentration in mitigating health risks. We have also clarified the\n3\nrationale for our modeling framework while discussing potential avenues for future\nimprovements, including the integration of larger datasets and more comprehensive\nuncertainty analysis methods (lines 328-334). Please find our point-by-point\nresponses to your concerns below.\n(1) Line 104: Does these concentrations account for in situ MeHg concentration?\nBackground concentrations may be substantial.\n5. We appreciate your concern. The background CH Hg+ concentrations may be\n3\nsubstantial in general CH Hg+ transformation studies; however, soil\n3\nmicroorganisms assimilated only small amounts of 13C from 13CH Hg+.\n3\nconcentration (~45 μg kg-1) to ensure sufficient 13C enrichment with 13CH Hg+ for\n3\neffectively tracing 13C-consuming microorganisms and identifying those involved\nin 13CH Hg+ degradation. Meanwhile, this spiked concentration is comparable to\n3\n(ranging from 0.14 to 67 μg kg-1)1. We have clarified this important point in lines\n361-368 of the revised manuscript.\n(2) Line 109-117: The degradation efficiency is arbitrarily defined as % degraded over\na 28 day period. It would be much more useful to provide degradation rates.\n6. Thanks for this valuable suggestion. We have now calculated the degradation rates\nof 13CH Hg+ over the incubation period (Supplementary Fig. 2). The rates were\n3\ngenerally greater than 0, indicating continuous degradation of 13CH Hg+.\nThe\n3\ndegradation rates showed an initial increase followed by a decline in later stages,\nlikely due to the depletion of the substrate 13CH Hg+. Moreover, the highest\n3\ndegradation rates were observed on day 14 in the High_P soil (2.95 μg kg-1 d-1) and\nLow_U soil (1.43 μg kg-1 d-1), whereas peak rates occurred on day 3 in the High_U\nsoil (1.57 μg kg-1 d-1) and Low_P soil (5.30 μg kg-1 d-1). To better evaluate the\nCH Hg+ degradation potential across different soils, we combined the analysis of\n3\ndegradation rates with degradation efficiency2, 3. This integrated approach provides\na more comprehensive assessment, as relying solely on degradation rates makes it\nchallenging to identify the soil with the highest CH Hg+ degradation potential.\nanalysis revealed both high CH Hg+ degradation efficiency and rate in the High_P\n3\nand Low_U soils, providing valuable insights into the microbial processes involved.\nPlease see our revisions in lines 124-130 and Supplementary Fig. 2.\n(3) Line 199-211, 454-485: The estimates of health risks are critically depending on a\nnumber of rather uncertain assumptions and the estimates should be presented as such\n(acknowledging uncertainties). I also wonder how the “degradation efficiency”\n(fraction degraded MeHg in 28 days) come into play here. Why limit the assessment to\nthis period? Do you assume that degradation halts after 28 days? The data does not\nsupport that. All in all I feel that a proper sensitivity analysis of this modeling effort is\nwarranted to illustrate/assess the uncertainties in the numbers presented.\n7. We appreciate the reviewer’s insightful comments. Below, we provide detailed\nresponses to these concerns.\n(1). Role of microbial degradation efficiency and rationale for the incubation period\nMicrobial degradation efficiency (the percent of CH Hg+ degraded over 28\n3\ndays by the microbial community) was incorporated into the model to calculate\nchanges in rice CH Hg+ concentrations, which subsequently affected the estimated\n3\ndaily intake (EDI) and health risk (HQ and ΔIQ). This efficiency was quantified by\ncomparing the difference in CH Hg+ concentration between sterilized and non-\n3\nsterilized soil samples over the incubation period. It is important to note that the\nobserved degradation efficiencies during the 28-day period represent net changes,\naccounting for both production and degradation processes. We chose microbial\ndegradation efficiency over degradation rate as it provides a standardized index.\nWhile degradation rates vary over time, microbial degradation efficiency offers a\nrelatively stable estimate of microbial CH Hg⁺ degradation potential in\n3\nenvironments.\nThe 28-day incubation period was chosen based on the balance between\nobserved CH Hg+ degradation and microbial activity. During this period, 41%-88%\n3\nof CH Hg+ degradation occurred, with degradation rates slowing significantly\n3\ntowards the end. Shorter incubation periods, such as 14 days, were insufficient to\nachieve measurable 13C enrichment in CH Hg+ degraders in DNA-SIP experiments.\nmicrobial groups, potentially confounding the identification of key CH Hg+\n3\ndegraders. Moreover, extended incubation time may lead to re-methylation of\ninorganic Hg, obscuring our focus on CH Hg+ degradation. Importantly, our model\n3\ndoes not assume degradation halts after 28 days. We recognize that both\nmethylation and demethylation processes occur simultaneously in soils, making it\ndifficult to determine the exact time when CH Hg+ degradation halts. Previous\n3\nstudies have shown that CH Hg+ production stabilizes at day 28 of incubation4.\n3\ndecomposed during a 28-day incubation period but that the total amount of Hg did\nnot change5, indicating an equilibrium between methylation and demethylation\nprocesses. This suggests that CH Hg+ degradation likely reaches a stable state by\n3\n28 days. Therefore, we selected the 28-day period as it provides a balance, ensuring\nsufficient 13C enrichment for downstream sequencing analysis while minimizing\nthe risk of confounding factors. We have clarified these points in lines 381-384 and\n529-540.\n(2). Uncertainties and sensitivities in health risk estimates\nThe health risk estimates inherently depend on multiple assumptions, which\nmay introduce uncertainties into the model. To address this, we conducted\nadditional one-at-a-time sensitivity analysis and uncertainty analysis based on\ninterval methods6, 7 (Supplementary Tables 5-7). We identified the most important\nparameters for hazard quotient (HQ) and IQ decrements (ΔIQ) from microbial\ndegradation efficiency, soil CH Hg+ concentration, bioaccumulation factor (BAF),\n3\nand rice ingestion rate. The results showed that microbial degradation efficiency\nand soil CH Hg+ concentration were the most important, with microbial degradation\n3\nefficiency having the highest sensitivity coefficients for HQ and ΔIQ\n(Supplementary Tables 5-6). For instance, when microbial degradation efficiency\nincreased from 8.16% to 64.26% under identical conditions, the reduction in HQ\nincreased from 0.0095 to 0.0749, representing an 8-fold increase. In contrast,\nvarying other parameters (e.g., soil CH Hg+ concentration or BAF) resulted in much\n3\nsmaller changes in HQ and ΔIQ. These results highlight that microbial degradation\nefficiency is the most critical factor in mitigating the health risks.\nWe further conducted an uncertainty analysis based on interval methods by\nvarying key parameters within their observed ranges (Supplementary Table 7),\nfollowing the previous study7. We quantified potential variability in HQ and ΔIQ,\nwhich ranged from 0.0027-0.3301 and 0.0006-0.0681, respectively. The results\nconsistently demonstrated that microbial degradation efficiency is the key factor in\nreducing health risks, with its influence far surpassing other parameters like soil\nCH Hg+ concentration or BAF. These analyses revealed the critical role of\n3\nmicrobial degradation efficiency in mitigating the health risks, while also\nemphasizing the importance of considering other factors contributing to overall\nuncertainty. We acknowledge the limitations of these analyses, which assume\nparameter independence and do not account for joint variability or probabilistic\ndistributions. These methods were chosen due to the limited size of our dataset,\nwhich precluded the use of more advanced probabilistic approaches like Monte\nCarlo simulations. Therefore, further studies expanding the dataset are warranted to\nreinforce and consolidate the findings presented in this study, though the field\nsampling and experimental analyses are enormously challenging. We have now\ndiscussed these important points in the revised manuscript (Supplementary Tables\n5-7, lines 324-334 and 560-574).\nIn summary, we demonstrate that microbial degradation of CH Hg+ plays a\n3\nsignificant role in mitigating the health risks by assessing uncertainties in key\nparameters, providing a clear rationale for the 28-day incubation period, and\nperforming a detailed sensitivity analysis. These clarifications and additional\nanalyses have been incorporated into the revised manuscript (Supplementary Tables\n5-7, lines 324-334, 381-384, 529-540 and 560-574).\n(4) General and line 270-272: Carrying a gene does not necessarily mean it is being\nused or expressed under the given environmental conditions. I don’t think you can make\nthe claim that the TCA cycle or assimilatory sulfate reduction is linked to MeHg\ndemethylation here. For that you need transcriptomic or proteomic data (or activity\nmeasurements). Using this indirect data to claim that SRB and methanogens play an\nimportant role in oxic MeHg demethylation is speculative.\n8. We agree that the presence of genes does not necessarily imply it is actively\nexpressed or functional under specific environmental conditions. As such, we have\nnow removed the previously speculative statements regarding the linkages between\nthe TCA cycle, assimilatory sulfate reduction, and CH Hg+ degradation, as well as\n3\nthe assumption of the important role of SRB and methanogens in oxic CH Hg+\n3\ndemethylation. Instead, we now emphasize the potential multifunctional roles of\nmicrobial taxa involved in 13CH Hg+ degradation, including their potential in\n3\ncarbon, sulfur, and nitrogen cycling. Using 13CH Hg+-DNA-SIP combined with\n3\nmetagenomics, we identified the microbial taxa and metabolic pathways involved\nin CH Hg+ degradation. Our analysis recovered five fairly complete MAGs linked\n3\nto 13CH Hg+ degradation. Importantly, these MAGs lacked the merA and merB\n3\ngenes (Fig. 4B), which are crucial for the demethylation of CH Hg+.\nthat mer-mediated reductive demethylation is unlikely to be the dominant 13CH Hg+\n3\ndegradation pathway in these taxa, and this is further supported by the absence of\nsignificant differences in the relative abundance of mer gene abundance between\nthe 13CH Hg+ and 12CH Hg+ treatments at the community level (Fig. 4A;\n3 3\nSupplementary Fig 6). In contrast, we observed significant enrichments of genes\nassociated with carbon and nitrogen metabolism in both MAGs and metagenomic\nanalyses, particularly those involved in the H F pathway, which plays a critical role\n4\nin one-carbon metabolism8. This result indicated that oxidative degradation via one-\ncarbon metabolism could be the primary pathway for CH Hg+ degradation in the\n3\npaddy soil. Please see our revisions in lines 271-288.\n(5) Line 317-319: How did you assess the purity of the synthesized compounds?\n9. We assessed the purity of the synthesized 13CH Hg+ compounds using the MERX\n3\nautomated methylmercury analysis system, which provides precise determination\nat picogram (pg) levels. This system integrates distillation, ethylation, gas\nchromatography, and atomic fluorescence detection, offering high sensitivity and\nspecificity for methylmercury detection. The purity was evaluated by comparing\nthe measured 13CH Hg+ concentration with the theoretical value based on the\n3\nsynthesis procedure. The close match between the measured and theoretical\nconcentrations suggests a high level of purity. In addition, we performed liquid\nchromatography to check for organic impurities. The initial purity of the\nsynthesized compound was about 70%, but further purification through extraction\nand back-extraction to remove inorganic components. The purity of the synthesized\ncompound then increased over 90%. Finally, we measured the actual concentration\nof spiked CH Hg+ in soils for subsequent analysis of CH Hg+ degradation efficiency,\n3 3\nthereby minimizing potential impacts from purity. We have supplemented these\ndetails in lines 350-358 and 394-397.\n(6) Please provide a motivation for duration of the experiment (28 days). Would a\nshorter or longer incubation time change the major results?\n10. That is an important point. As responded in #7, the experiment duration of 28 days\nwas carefully selected based on literature and our pre-experiments4, 5. This duration\ncan balance both the degradation of 13CH Hg+ and the sufficient 13C enrichment in\n3\nsoil microorganisms. The mean concentrations of 13CH Hg+ in the soils ranged from\n3\n5.16 μg kg-1 to 28.05 μg kg-1 after 28 days of incubation, with biotic degradation\nefficiencies reaching 41%-88%. This result demonstrates active microbial 13CH Hg\n3\ndegradation occurred during this period. Moreover, previous studies have suggested\nthat CH Hg+ degradation likely reaches a stable state by 28 days4, 5. For the\n3\n13CH Hg+-DNA-SIP experiments, a shorter incubation period would not allow\n3\nsufficient 13C incorporation into the 13CH Hg+ degraders. Conversely, a longer\n3\nincubation time could result in cross-feeding between microbial groups. Moreover,\nextended incubation time may lead to re-methylation of inorganic Hg, obscuring\nour focus on CH Hg+ degradation. Previous studies suggest that CH Hg+\n3 3\ndegradation likely reaches a stable state by 28 days4, 5. Therefore, the 28-day\nduration was chosen as an optimal balance, ensuring sufficient 13C enrichment for\ndownstream sequencing analysis while minimizing the risk of confounding factors.\nWe have clarified these points in lines 381-384.\n(7) Line 369: How was the fractionation done? Is there a risk of cross-contamination\nbetween fractions?\n11. The stratified DNA-CsCl solution was fractionated into 18 aliquots following the\npublished protocol9, 10. Briefly, the tube was fixed in a clamp, and the bottom was\ncarefully pierced with a needle in a smooth and controlled manner, after which the\nneedle was discarded. A syringe pump was used to inject sterile deionized water\ninto the top of the tube through the needle, and drops were collected from the bottom\ninto sterile 1.5 mL tubes. The pump rate was set to yield approximately 18 × 280\nµL fractions within 12 minutes (425 µL min-1, ~ 40s per fraction). The density of\nall fractions was checked using a refractometer to confirm that the gradients were\nconsistent across all tubes. Importantly, the tubes were carefully and immediately\nretrieved after centrifugation to avoid disturbing the gradients. To minimize\ndiffusion and cross-contamination between fractions, the gradients were processed\nas quickly as possible. New sterile equipment (e.g., syringe, needle, and 1.5-mL\ntubes) was used for each fraction to further reduce the risk of contamination.\nAdditionally, fractions were collected in a consistent manner to avoid mixing\nbetween them, and the process was performed rapidly to prevent gradient mixing.\nWe have supplemented these details in lines 416-428.\n(8) Line 376-378: The indicated reference is not the original one for the indicated\nprimers. Please use the original reference and mention something about the taxonomic\ncoverage since this is an important parameter.\n12. We have provided the original reference and supplemented the taxonomic coverage\nabout the primers in lines 430-434 “qPCR was performed using a CFX Connect\nreal-time system (BioRad, CA, USA) with the 341F (5′-\nCCTACGGGNGGCWGCAG-3′) and 805R (5′-\nGACTACHVGGGTATCTAATCC-3′) paired primers (Herlemann et al., 2011,\nISME J)11, which match approximately 90% of all bacterial sequences and cover all\nphyla in the Ribosomal Database Project release 10.25.”\n(9) Line 387-388: These are very old primers known to miss several groups (even entire\nphyla). A cautionary discussion about the potential to overlook some active MeHg\ndemethylators is warranted.\n13. We appreciate the constructive comments. We acknowledge that the primers 27F\nand 1492R may miss some active CH Hg+ demethylators, though they are widely\n3\nused for full-length 16S rRNA gene amplification due to their broad coverage\nacross a wide range of bacterial phyla. We have included a cautionary discussion of\nthis potential limitation in the revised manuscript (lines 261-264). Moreover, we\nperformed shotgun metagenomic sequencing, which provides additional species-\nlevel annotations and enables the identification of microbes involved in CH Hg+\n3\ndegradation. Results showed that the dominant and differential microbial taxa\nidentified through metagenomics were generally consistent with those detected by\n16S rRNA gene amplicon sequencing (Fig. 2; Supplementary Figs. 3 and 9). This\ncomplementary approach allows for a more comprehensive identification of\nmicrobial groups involved in CH Hg+ degradation (lines 261-270).\n3\n(10) Line 499-501: There are plenty of easy access and persistent data archives\navailable for depositing sequence data. This contribute to reproducible science and I\nwould rplease ask the authors to deposit their data in such repositories before\npublication can ber considered. There is really now excuse for not doing so.\n14. We have now deposited the full-length 16S rRNA gene amplicon sequences and\nmetagenomic sequences generated in this study to the NCBI SRA database under\nthe BioProject IDs of PRJNA1183541 and PRJNA1183649 (lines 586-589).\n(11) The reference list is very long and for sure it can be trimmed to remove\nredundancies without compromising the rigor of the article.\n15. We have checked the reference list and removed redundant references without\ncompromising the rigor of the article.\n(12) Figure 5 is hard to interpret and can be removed while the numbers can be\npresented in running text.\n16. Thank you for your suggestion. We have removed the figure and presented the data\nas a new table (Supplementary Table 3).\nMinor comments:\nTitle (line 1): “unraveling” is a vague term and is not really needed in the title.\n17. Revised to “Microbial potential to mitigate neurotoxic methylmercury\naccumulation in farmlands and rice”.\nLine 32-33: Strange sentence. I would write “are known to degrade CH Hg+ in pure\n3\nculture”.\n18. Sorry for the strange sentence. The ability of these candidate taxa (i.e.,\nDechloromonas denitrificans and Methylovorus menthalis) to degrade CH Hg+ was\n3\nconfirmed by this study. Therefore, we have revised the sentence to “Some of which\n(i.e., Dechloromonas denitrificans and Methylovorus menthalis) are subsequently\nconfirmed to degrade CH Hg+ through pure culture assays” (lines 34-36).\nsuch they are not involved in any biological process (the organisms they were\nassembled from are on the other hand).\n19. We have made the necessary revisions to clarify this point in lines 36-37\n“Metagenomic analysis further reveals that most of these candidate 13CH Hg+\n3\ndegraders…….”\nLine 36+89: This is not an assessment, but an estimate or prediction (depending on how\nyou see it).\n20. We have changed “assess” to “estimate” in lines 39 and 95.\nLine 136: “enrichment” should be “13C enrichment”\n21. Revised as suggested (line 149).\nLine 146: “dominated both in the” is redundant and can be deleted.\n22. Deleted.\nLine 156: “putative microbial taxa” is awkward and pointless. Do you mean Candidate\ntaxa?\n23. Yes, we have changed “putative microbial taxa” to “candidate taxa”.\nLine 160: Clarify that you mean “metagenome sequencing and reconstruction of\nmetagenome assembled genomes”.\n24. Clarification as suggested (lines 176-177).\nLine 163: What are these requirements? Is it a fixed limit or depending on service\nprovider?\n25. The requirements here refer to the typical DNA quantity needed for shotgun\nmetagenomic sequencing. These are not fixed limits but depend on the sequencing\nplatform required. For example, using the Illumina NovaSeq 6000 platform (2 ×\n150 bp), 1-5 μg of DNA is generally needed for sequencing12, 13. Due to the low\nrecovery of 13C-labeled DNA in DNA-SIP, we pooled DNA from multiple\nreplicates to meet these requirements. We have clarified this point in lines 472-480.\nLine 225-226: This is an incorrect statement. Please specify that this relates to\ndegradation of organic substrates for energy acquisition.\n26. Sorry for this incorrect statement. The primary biodegradation pathway for\ncompounds by Methylophilaceae is related to energy acquisition. We have now\nremoved this sentence to refocus the discussion on the microbial taxa identified\nfrom both 16S rRNA gene amplification and metagenomic sequencing analyses\naccording to Reviewer 3’s comments.\nLine 233: Remove “the”, since many more taxa may be shared beyond the most\nabundant.\n27. Done.\nLine 239: “especially” rather than “specifically”.\n28. Revised as suggested (line 248).\nLine 283: “to decreases of” does not fit here.\n29. Revised as “to decrease CH Hg+ accumulation” (lines 306-307)\nenhance the in situ activities of these putative demethylators, but I think this is only a\nsuggestion, right?\n30. Yes, this section is an extended discussion on how to enhance the activity of\ncandidate CH Hg+ degraders in situ to mitigate health risks. We suggest promoting\n3\nthe in situ microbial activity for degrading CH Hg+, thereby reducing health risks.\nLine 341: “accurate” is not the right word.\n31. We have removed this word.\nLine 403: What is “optimized” sequence? You mean “trimmed or quality controlled?\n32. We are referring to “the process of obtaining clean reads by removing chimeric\nsequences with UCHIME” in this context. We have revised this in lines 465-467\n“chimeric reads were removed with UCHIME to acquire quality controlled\nsequence.”\nLine 415: Remove “proceeded”.\n33. Done.\nReviewer #3 (Remarks to the Author):\nThe authors attempted to elucidate the microbial communities and their functions\ninvolved in degrading highly toxic methylmercury (CH Hg+) through SIP and\n3\nmetagenomic analyses, using DNA extracted from soils treated with CH Hg+.\n3\nacross China.\nThe key flow of this manuscript is summarized as follows:\n(1) CH Hg+ was added to High-Hg contaminated paddy soil, High-Hg contaminated\n3\nupland soil, Low-Hg contaminated paddy soil, and Low-Hg contaminated upland soil.\nThe CH Hg+ degradation rates were determined (Fig. 1, Supplementary Fig. 1).\n3\n(2) A SIP analysis was conducted using DNA extracted from soils treated with CH Hg+,\n3\nfocusing on High-Hg contaminated paddy soil and Low-Hg contaminated upland soil.\nQuantitative PCR targeting 16S rRNA was performed, and the community structures\nof the peak fractions were analyzed via amplicon sequencing. Arenimonas,\nDechloromonas, and MM2 predominantly assimilated 13C in High-Hg contaminated\npaddy soil, while Ramlibacter and Sumerlaea were identified in Low-Hg contaminated\nsoil, suggesting their involvement in CH Hg+ degradation (Fig. 2, 3, Supplementary\n(3) Among these, isolates of Dechloromonas (the second most abundant) and\nMethylovorus (possibly related to the fifth most abundant Methylotenera) were\nobtained from DSMZ or another source, and their ability to degrade CH Hg+ was\n3\nexperimentally demonstrated (Supplementary Fig. 4).\n(4) Shotgun metagenomics was performed on DNA extracted from soils (13CH Hg+-\n3\ntreated?), and MAGs were constructed. More than half of the constructed MAGs were\nderived from Actinobacteria, while bacteria identified as dominant in (2) were absent.\nThe authors examined the CH Hg+ degradation pathways and other metabolic pathways\n3\nencoded in the genomes of these MAGs (Fig. 4, Supplementary Fig. 5).\n(5) Using metagenomic analysis, the relative abundance of various metabolic pathways\nwas compared between soils treated with 12CH Hg+ and 13CH Hg+ (Supplementary Fig.\n3 3\n6-9).\n34. We appreciate that the reviewer highlighted the key flow of our work. Shotgun\nmetagenomics was performed on the fraction with the highest 16S rRNA gene\ncopies from the 13CH Hg+ treatment, as well as the corresponding fraction from the\n3\n12CH Hg+ treatment (lines 472-480). We now provide detailed responses to all your\n3\nconcerns below.\nMajor Comments:\n(2) Analysis of High-Hg contaminated upland soil and Low-Hg contaminated paddy\nsoil\nThere is no mention about High-Hg contaminated upland soil and Low-Hg\ncontaminated paddy soil in this manuscript. Why were these soil types not selected for\nsubsequent analysis? This information is missing throughout the manuscript.\n35. We appreciate your concerns. In this study, degradation efficiencies of 13CH Hg⁺\n3\nvaried among soil types. The paddy soil from the high Hg-contaminated site\n(High_P) and upland soil from the low Hg-contaminated site (Low_U) exhibited\nhigher microbial degradation potential, with degradation efficiencies of 88% and\n65%, respectively. Considering the relatively high cost of DNA-SIP experiments\nand the need for sufficient 13C incorporation to ensure accurate identification of key\nmicrobial taxa, we selected the High_P and Low_U soils for subsequent analyses.\nWe have now clarified these important points in lines 124-130 and 132-134 of the\nrevised manuscript.\nThe Discussion states that similar bacteria contributed to CH Hg+ degradation in soils\n3\nlocated 500 km apart. Does this mean that upland and paddy soils were being compared?\nGiven that the potential for CH Hg+ degradation across different Hg contamination\n3\nlevels within China was calculated, wouldn’t it be more appropriate to compare to each\nother among paddy soils? If upland soils were analyzed, the Introduction should provide\na clear rationale, and the comparisons should extend to upland soils as well.\n36. Yes, we initially compared the microbial taxa from upland and paddy soils to\nhighlight their shared role in the 13CH Hg+ degradation process, demonstrating their\n3\npotential ubiquity across different environments. We acknowledge that comparing\npaddy soils with varying Hg contamination levels would indeed be more\nappropriate for the specific focus of this study. However, to ensure sufficient 13C\nenrichment and accurate identification of key microbial taxa and metabolic\npathways, we selected High_P and Low_U soils for the 13CH Hg+-DNA-SIP\n3\nexperiments, which exhibited higher microbial 13CH Hg+ degradation potentials.\nChina, where uplands are often converted to paddy fields seasonally, and this\ncontributes to our initial inclusion of both soil types. We have supplemented the\nrationale in the Introduction section and comparisons between the paddy and upland\nsoils in the result section (lines 54-57 and 153-174).\n(3) Selection of Dechloromonas and Methylovorus\nWhy were Dechloromonas and Methylovorus selected? Dechloromonas is the second\nmost abundant, and Methylovorus, possibly related to Methylotenera, ranks fifth. Is it\nunnecessary to examine other bacteria?\n37. We selected Dechloromonas denitrificans and Methylovorus menthalis for further\npure culture assays based on their broad distribution patterns observed in both light\nand heavy fractions of the 13CH Hg+ and 12CH Hg+ treatment. While most\n3 3\nbiomarkers were only enriched in the 13C-DNA heavy fraction (the fraction 11),\nsuggesting their potential as CH Hg⁺ degraders, the two genera exhibited significant\n3\nenrichment in both light and heavy fractions (the fractions 9-14) from the 13CH Hg+\n3\ntreatment (Fig. 3; Supplementary Fig. 4). This broad distribution prompted us to\nvalidate whether they are involved in CH Hg+ degradation. Pure culture assays with\nto degrade CH Hg+, thus supporting their potential role in CH Hg⁺ degradation.\n3 3\nWhile other biomarkers were also enriched in the 13CH Hg+ treatment, the two\n3\ngenera were prioritized for further investigation due to their distinct distribution\npatterns. Future studies, such as isolating these specific taxa in pure culture, are\nwarranted to reinforce and consolidate the results of this study. The rationale for\nselecting these two genera for pure culture assays has now been provided in the\nmanuscript (lines 166-172).\n(4) Issues with the constructed MAGs.\nThis is considered the most critical issue.\nMore than half of the constructed MAGs were derived from Actinobacteria, and none\nof the bacteria identified in the SIP analysis as contributors to CH Hg+ degradation\n3\nwere present.\n38. We appreciate the reviewer’s concerns. In the previous manuscript, we compared\nmicrobiota in the fractions of 9-14 in the 12CH Hg+ and 13CH Hg+ treatments,\n3 3\nincluding both heavy and light fractions, which may have masked differences\nbetween the active microbial taxa in treatments. To address this, we have now\nfocused on analyzing the 16S rRNA gene amplicon sequences from the fraction\nwith the highest abundance of 16S rRNA gene copies in the 13CH Hg+ treatment\n3\nand the corresponding fraction in the 12CH Hg+ treatment14. This targeted analysis\n3\nbetter represents the active microbial taxa directly involved in 13CH Hg+\n3\ndegradation. The results revealed that genera such as Pseudarthrobacter,\nDechloromonas and MM2 were significantly enriched in the 13CH Hg+ treatment\n3\n(Fig. 3C), suggesting that these taxa are key microorganisms involved in CH Hg+\n3\ndegradation (see lines 161-172).\nWe further re-analyzed the 13CH Hg+-SIP-metagenomics in the fraction with\n3\nthe highest abundance of 16S rRNA gene copies in the 13CH Hg+ treatment and its\n3\ncorresponding fraction in the 13CH Hg+ treatment to investigate the role of these\n3\ntaxa in CH Hg+ degradation. Among the five MAGs identified, three were\n3\nannotated as g_Arthrobacter_I in the GTDB database (Supplementary Table 2),\nwhere the “I” typically indicates an inadequately classified genus. Phylogenetic\nanalysis revealed that MAG1, MAG2, and MAG5 clustered with\nPseudarthrobacter, indicating a strong phylogenetic relationship (Supplementary\nFig. 7). Metabolic potential and pathway analyses of these MAGs further support\ntheir potential role in CH Hg+ degradation, providing functional evidence to link\n3\nthese MAGs to the key taxa identified in the 13C-DNA fraction (lines 205-220).\nMoreover, the dominance of Actinobacteria in the reconstructed MAGs is not\nsurprising, as these taxa are abundant in many soil environments, particularly in\npolluted soils, due to their metabolic versatility and stress adaptation. Their high\nGC content likely led to overrepresentation in metagenomic assembly. To assess\nwhether the enrichment of Actinobacteria in the 13C-DNA heavy fraction was solely\ndue to GC content, we compared their relative abundance in the fraction with the\nhighest abundance of 16S rRNA gene copies from the 13CH Hg+ treatment and its\n3\ncorresponding fraction in the 12CH Hg+ treatment. Interestingly, Actinobacteria-\n3\nassociated taxa showed higher relative abundances in the 13CH Hg+ treatment\n3\ncompared to the 12CH Hg+ treatment (Supplementary Fig. 9), supporting their\n3\nfunctional role in CH Hg+ degradation rather than simply reflecting a GC content\n3\nbias (lines 289-304).\nIn summary, we re-analyzed both the 16S rRNA gene amplicon and shotgun\nmetagenomic sequences in the fraction with the highest abundance of 16S rRNA\ngene copies in the 13CH Hg+ treatment and its corresponding fraction in the\n3\n12CH Hg+ treatment. The results highlighted Actinobacteria-associated genera (i.e.\n3\nfurther improving the alignment between SIP-derived taxa and MAG annotations.\nWe have updated these analyses in the revised manuscript (lines 161-172, 205-220\nand 289-304).\nActinobacteria are known to have high GC content, as does the second most abundant\nGemmatimonas. Since the MAGs were constructed from metagenomic data of the\nheavy fractions, it is possible that the bacteria identified are not contributors to\n13CH Hg+ degradation but were enriched due to their high GC content. The authors\n3\nshould evaluate whether genes from Actinobacteria or Gemmatimonas are significantly\nmore abundant in soils treated with 13CH Hg+ than in soils treated with 12CH Hg+.\n3 3\nIf discrepancies arise between the metagenomic and SIP analyses, the reasons for these\ndifferences should be addressed.\n39. We sincerely thank the reviewer for the thoughtful comments and for highlighting\nthe potential role of Actinobacteria and Gemmatimonas (i.e., Gemmatimonadota)\nin CH Hg+ degradation, as well as the possible influence of high GC content on\n3\ntheir enrichment in the 13C-DNA heavy fractions. To assess whether the enrichment\nof Actinobacteria and Gemmatimonadota in the 13C-DNA heavy fractions was\ndriven solely by GC content, we compared their relative abundance in the 13CH Hg+\n3\nand 12CH Hg+ treatments. If GC content were the primary factor, similar relative\n3\nabundances would be expected in both 13CH Hg+ and 12CH Hg+ treatments.\n3 3\nOur\nresults revealed consistently higher relative abundances of both Actinobacteria and\nGemmatimonadota in the fraction with the highest abundance of 16S rRNA gene\ncopies from the 13CH Hg+ treatment compared with the corresponding fraction in\n3\nthe 12CH Hg+ treatment (Supplementary Fig. 9), suggesting their functional role in\n3\n293).\nAdditionally, we analyzed the functional genes involved in key biochemistry\npathways (e.g., mercury reduction, H F pathway and carbon metabolism) within\nin the relative abundance of mer operon genes (e.g., merA and merB) between the\n13CH Hg+ and 12CH Hg+ treatments (Supplementary Fig. 10). In contrast, genes\n3 3\nassociated with one-carbon (C1) compound metabolisms, such as fdoG (formate\ndehydrogenase) and gcv (glycine cleavage system protein), were significantly more\nabundant in the 13CH Hg+ treatment compared with the 12CH Hg+ treatment.\n3 3\nThese\nC1 metabolism-related genes, enriched in both Actinobacteria and Gemmatimonas,\nsuggest that other pathways, rather than mer-mediated reductive demethylation,\nmay be the predominant CH Hg+ degradation mechanism in the paddy soil. This\n3\nwas further supported by the lack of significant enrichment of mer genes and the\nnotable enrichment of genes associated with carbon and nitrogen metabolism at the\ncommunity level (lines 293-304).\nAs detailed in our response to #38, we re-analyzed the 16S rRNA gene\namplification and shotgun metagenomics in the fraction with the highest abundance\nof 16S rRNA gene copies in the 13CH Hg+ treatment and its corresponding fraction\n3\nin the 12CH Hg+ treatment. The results improve the alignment between SIP-derived\n3\ntaxa and MAG annotations, further emphasizing the functional role of\nActinobacteria-associated genera (i.e. Pseudarthrobacter), particularly in\nmetabolism pathways. These clarifications have been incorporated into the revised\nmanuscript (lines 161-172, 205-220 and 271-304).\nIf the study aims to discuss the microbial communities and their functions involved in\nCH Hg+ degradation, greater emphasis should be placed on bacteria identified through\n3\nfunctional genes from these bacteria should be evaluated via metagenomics.\nSpecifically, the microbial origins of functional genes obtained through metagenomics\nshould first be identified. Functional genes derived from microbes identified as\n13CH Hg+ degraders in the SIP analysis should be prioritized for discussion.\n3\n40. We appreciate the constructive suggestions on the improvement of our manuscript.\nWe have now re-analyzed the 16S rRNA gene amplification and metagenomic data\nfrom the fraction with the highest abundance of 16S rRNA gene copies in the\n13CH Hg+ treatment. This fraction more accurately represents the active microbial\n3\ntaxa contributing to CH Hg+ degradation. As shown in Fig. 3C, genera such as\n13CH Hg+ treatment, suggesting that these taxa may be key microorganisms\n3\ninvolved in 13CH Hg+ degradation. Furthermore, we reconstructed a total of 5\nSupplementary Fig. 7). In particular, these Pseudarthrobacter-associated MAGs\nwere subsequently analyzed to investigate the metabolic pathways related to CH Hg\n3\ndegradation. In the revised manuscript, we identified functional genes associated\nwith pathways such as reductive degradation mediated by the mer operon, oxidative\ndegradation related to one-carbon (C1) metabolism, as well as sulfur metabolism\nand nitrate reduction from these MAGs related to the identified candidate CH Hg+\n3\ndegraders through long-read sequencing analysis and metagenomics. These\nfunctional genes from microbes identified as 13CH Hg+ degraders in the SIP\n3\nanalysis have now been prioritized for discussion (lines 161-220 and 252-288).\nMaterials and Methods of Shotgun Metagenomic Sequencing\nWas shotgun metagenomics conducted only for High-Hg contaminated paddy soil?\n41. Yes, shotgun metagenomics was conducted exclusively on the High-Hg\ncontaminated paddy soil (High_P), which was selected due to its highest potential\nof microbial 13CH Hg+ degradation. The health risks associated with CH Hg+ are\n3 3\nmost prominent in paddy fields, where the flooded conditions create an anoxic\nenvironment favorable for CH Hg+ production. Exploring the key taxa and\n3\nmetabolic potential of CH Hg+ degraders in paddy soils is essential for\n3\nunderstanding and mitigating CH Hg+ risks in agroecosystems. Moreover, given\n3\nthat soil microorganisms assimilated only small amounts of 13C from 13CH Hg+,\n3\nwe\nmonitored 13C assimilation at multiple time points to ensure sufficient 13C\nenrichment for accurate DNA-SIP analysis. For the paddy soil from the high Hg-\ncontaminated region, we performed three rounds of ultracentrifugation and 48\nDNA-SIP fractionations, followed by quantitative analysis of about 800 DNA\nsamples from the fractions. The choice to conduct shotgun metagenomics on the\nHigh_P soil was made after considering the relatively high cost and time consuming\nof both DNA-SIP experiments and metagenomic sequencing, as well as the need\nfor sufficient 13C markers with 13CH Hg+ for accurate analysis. Based on the\n3\n13CH Hg+-DNA-SIP methodology we developed, future studies on additional soil\n3\nsamples will deepen our understanding of CH Hg+-degrading microorganisms and\n3\ntheir metabolic pathways. We have added this detail to the revised manuscript (lines\n181-184 and 472-474).\nThe authors should specify which fraction from which day was used.\n42. The fraction with the highest 16S rRNA gene copies from the 13CH Hg+ treatment\n3\nof the High_P soil on day 28, was selected for shotgun metagenomic sequencing.\nWe have added this detail to the revised manuscript (lines 182-184).\n(5) Discussion of metabolic pathways from metagenomic analysis\nThe abundance of various pathways obtained from metagenomic analysis of soils\ntreated with 12CH Hg+ and 13CH Hg+ is discussed, but no significant differences were\n3 3\nobserved between 12C and 13C.\n43. We acknowledge this point. As addressed in response to comment #38, we initially\ncompared the differential microbiota in the 9-14 fractions of the 12CH Hg+ and\n3\n13CH Hg+ treatments in the previous manuscript. However, since these fractions\n3\nincluded both heavy and light fractions, this approach may have masked the\ndifferences between the active microbial populations associated with CH Hg+\n3\ndegradation. In the revised manuscript, we have now focused on comparing the\nfraction with the highest 16S rRNA gene copies from the 13CH Hg+ treatment and\n3\nthe corresponding fraction from the 12CH Hg+ treatment. The results showed that\n3\nthe relative abundances of genes related to sulfate metabolism (e.g., cysH, cysD and\ncysN), the H F pathway (e.g., metH and mtgA), the TCA cycle (e.g., acnA and sdhA),\n4\nnitrate reduction, and denitrification (e.g., glnA, nirB and napAB) were significantly\nhigher in the 13CH Hg+ treatment compared with the 12CH Hg+ treatment (Fig. 4;\n3 3\nSupplementary Fig. 6). Please see the revisions highlighted in lines 184-204.\nBased on these results, it is difficult to discuss microbial functions associated with\n13CH Hg+ degradation.\n3\n44. We appreciate the reviewer’s comment. In earlier version of the manuscript, the\ncomparison of the 12CH Hg+ and 13CH Hg+ treatments did not show significant\n3 3\ndifferences, which may have made it difficult to link microbial functions with\nCH Hg+ degradation. However, as detailed in the revised manuscript, we have\n3\nrefined our analysis by focusing on the fraction with the highest abundance of 16S\nrRNA gene copies in the 13CH Hg+ treatment and the corresponding fraction in the\n3\n12CH Hg+ treatment. This refined approach revealed significant differences\n3\nbetween the two treatments. Specifically, genes related to sulfate metabolism (e.g.,\ncysH, cysD and cysN), the H F pathway (e.g., metH and mtgA), the TCA cycle (e.g.,\n4\nacnA and sdhA), nitrate reduction, and denitrification (e.g., glnA, nirB and napAB)\nwere significantly more abundant in the 13CH Hg+ treatment compared with the\n3\n12CH Hg+ treatment, while no significant differences were observed for mer genes\n3\nbetween the 12CH Hg+ and 13CH Hg+ treatments (Fig. 4; Supplementary Fig. 6).\n3 3\nThese findings combined with the analyses of 16S rRNA gene amplification and\nMAGs suggest that these microbial functions could be associated with CH Hg+\n3\ndegradation, while mer-mediated reductive demethylation is unlikely to be the\ndominant CH Hg+ degradation pathway in the paddy soil. We have discussed these\n3\nresults in the revised manuscript (lines 271-288) to better link microbial functions\nwith 13CH Hg+ degradation.\nOverall, the analysis and discussion of the samples possibly with high degradation\npotential (as demonstrated in (1)) seems to be insufficient.\n45. We appreciate the reviewer’s comments. In the revised manuscript, we have\nexpanded the analyses based on both 16S rRNA gene amplification and shotgun\nmetagenomic sequencing. Specifically, we compared the relative abundance of\nmicroorganisms in the fraction with the highest abundance of 16S rRNA gene\ncopies from the 13CH Hg+ treatment with the corresponding fraction from the\n3\n12CH Hg+ treatment. Linear discriminant analysis effect size (LEfSe) analysis\n3\nidentified genera such as Pseudarthrobacter and Dechloromonas as biomarkers in\nthe 13CH Hg+ treatment (Fig. 3C), suggesting that these taxa may be key taxa\n3\ninvolved in 13CH Hg+ degradation.\npathways are involved in 13CH Hg+ degradation (Fig. 4). We reconstructed a total\n3\nof five fairly complete MAGs linked to 13CH Hg+ degradation, predominantly\n3\naffiliated with Actinobacteria and Gemmatimonadota. Among these MAGs, 3 were\nidentified as novel species associated with the genus Pseudarthrobacter\n(Supplementary Fig. 7). Notably, these MAGs did not contain the merA and merB\ngenes, which are pivotal for reductive demethylation via the mer operon, suggesting\nthat mer-mediated reductive demethylation is unlikely to be the dominant CH Hg+\n3\ndegradation pathway in these taxa. This was further supported by the no significant\ndifference in the relative abundances of mer genes between the 12CH Hg+ and\n3\n13CH Hg+ treatments at the community level (Supplementary Fig. 6). In contrast,\n3\nsignificant enrichments of genes associated with carbon and sulfur metabolism were\nobserved in both MAGs and metagenomic analyses, particularly those involved in\nthe H F pathway, which plays a critical role in one-carbon metabolism. This finding\n4\nindicated that oxidative degradation involved the co-metabolism of CH Hg+\n3\nresembling the metabolism of other small organic substrates (e.g., C1 compounds)\nby heterotrophic bacteria, including sulfate-reducing bacteria and methanogens,\ncould be the primary pathway for CH Hg+ degradation in the paddy soil.\nof the microbial functions and pathways potentially involved in CH Hg+\n3\ndegradation, shedding light on the underlying mechanisms in paddy soil. Please see\nour revision in Figs. 3-4 and lines 161-174, 205-220 and 271-304.\nWe sincerely thank all the comments/suggestions of reviewers, which\nsubstantially improve our manuscript."}, {"round": 2, "reviewer_comments": {"reviewer_2": "The authors have dealt diligently and effectively with my previous comments (and those from the other reviewers). The manuscript is now much more clear and less speculative. I have only a few remaining questions and suggested edits as outlined below.\n(1) The way the manuscript is written it's still hard to decipher the actual methyl mercury concentrations in the microcosms.\nIt is stated that the systems were spiked with ca 45 microgram/kg (line 364) but it's also stated that the final concentration was 50 microgram/kg (line 360), and looking at the original features of the soils, the in situ methylmercury concentration seems to vary quite a bit from less than one to a few micrograms per kg (Supplementary table 1). I also don't see how this agrees with results presented in figure 1 and supplementary figure 1 where the measured concentration of methylmercury varies quite a lot and typically is way below 50 microgram/kg. How was in situ methyl mercury was handled in estimating the degradation efficiency? Please clarify this. How did you analytically distinguish between 13C-methylmercury and 12C-methylmercury? (fig 1A,B)? Many questions left unanswered here.\nLine 185-187, 300-304: The absence of merAB genes in the \"heavy\" fraction is interpreted as if another methylmercury pathway is in operation. But can't it just be that the methyl group that is produced in the demethylation is not assimilated into DNA to any major extent? In such a case the demethylating microbes would still be in the isotopically \"light\" fractional. Assimilation into biomass is a critical assumption in this work and it is not a law of nature, so alternative explanations should at least be mentioned.\nLine 155/156: should read \"the 12CH3Hg+ treatment\"\nLine 176: What is \"combination analyses\"? Should this read \"Combined analyses\"?\nLine 279: \"The no significant difference\" is awkward and should be revised. \"similar\"?\nLine 334: \"enormously\" should be deleted. Unclear what it means.\nLine 467: \"sequence\" should read \"sequences\" and \"sequences were\"", "reviewer_3": "While the authors have made meaningful progress in refining their analysis and the overall quality of the paper, several issues still need to be addressed, as outlined below.\nL184–204:\nMost of the genes discussed in the main text are either absent from Supplementary Fig. 6 or not indicated as significantly enriched. This discrepancy suggests that either the figure needs to be replaced with a more representative version, or the corresponding descriptions in the main text should be substantially revised to align with the data shown.\nL187–189:\nReferences should be added here.\nL297–304:\nWhy were fdoG (Gemmatimonadota) and gcvP (Actinobacteria) highlighted as significantly enriched among the numerous genes related to carbon metabolism? While the shift in focus toward carbon metabolism is understandable due to the absence of significant differences in merA and merB, the rationale behind this focus should be more explicitly justified (as described above: L187-189's reference). Additionally, the biological or ecological significance of these specific genes must be elaborated upon in greater detail.\nCurrently, the discussion risks appearing selective or post hoc—as if only the genes that support a convenient narrative were chosen from Supplementary Fig. 6.\nTo strengthen the discussion, it is essential to clarify the reasoning behind the observed enrichment of bacteria lacking merA and merB under the 13C-Hg treatment and to ensure that all descriptions accurately reflect the underlying data."}, "author_response": "Responses to reviewer’s comments:\nReviewer #2 (Remarks to the Author):\nThe authors have dealt diligently and effectively with my previous comments (and\nthose from the other reviewers). The manuscript is now much more clear and less\nspeculative. I have only a few remaining questions and suggested edits as outlined\nbelow.\n1. We appreciate the positive comments on our responses and modifications to the\nprevious concerns. We now address your remaining concerns as follows.\n(1) The way the manuscript is written it’s still hard to decipher the actual methyl\nmercury concentrations in the microcosms.\nIt is stated that the systems were spiked with ca 45 microgram/kg (line 364) but it’s also\nstated that the final concentration was 50 microgram/kg (line 360), and looking at the\noriginal features of the soils, the in situ methylmercury concentration seems to vary\nquite a bit from less than one to a few micrograms per kg (Supplementary table 1). I\nalso don’t see how this agrees with results presented in figure 1 and supplementary\nfigure 1 where the measured concentration of methylmercury varies quite a lot and\ntypically is way below 50 microgram/kg. How was in situ methyl mercury was handled\nin estimating the degradation efficiency? Please clarify this. How did you analytically\ndistinguish between 13C-methylmercury and 12C-methylmercury? (fig 1A,B)? Many\nquestions left unanswered here.\n2. We are sorry for the unclear statements. We now explain the concentration of\nmethylmercury (CH Hg+) used in the microcosms. All soils were spiked with\n3 3\nconcentrations in the microcosms reflected the sum of the background CH Hg+\n3\n(ranging from 0.45 to 3.48 μg kg-1; Supplementary Table 1) and the spiked CH Hg+\n3\n(50 μg kg-1). We acknowledge that the CH Hg+ concentrations measured at day 0\n3\n(around 45 μg kg-1) did not always match the theoretical values (Fig. 1A-B;\nSupplementary Fig. 1), likely due to inevitable experimental errors, including\nvariations in extraction efficiency and analytical recovery. According to previous\nstudies, acceptable recoveries of CH Hg+ from reference materials typically range\n3\nfrom 75% to 115%, depending on soil properties1-3. To ensure the accuracy of\ndegradation efficiency calculations, we used the measured CH Hg+ concentrations\n3\nat day 0 (including the background CH Hg+) as the baseline, rather than relying on\n3\nthe theoretical concentration. These clarifications have been provided in lines 368-\n378 and lines 410-419.\nAdditionally, CH Hg+ concentration was measured at multiple time points in\n3\nboth the 13CH Hg+ and 12CH Hg+ treatments during the incubation (Fig. 1A-B;\n3 3\nSupplementary Fig. 1); however, we did not analytically distinguish the two\nisotopologues. We have clarified this point in lines 419-425, and revised Fig. 1 and\nSupplementary Fig. 1, accordingly. While the individual degradation efficiencies of\n13CH Hg+ and 12CH Hg+ were not directly quantified, the observed decline in total\n3 3\nCH Hg+ concentration, along with the significant 13C enrichment of microbial taxa\n3\nin the heavy DNA fractions from 13CH Hg+-DNA-SIP analyses, provide strong\n3\nevidence for microbial demethylation of 13CH Hg+ during the incubation. This\n3\napproach effectively supports our goal of identifying the active microbial taxa and\nassociated metabolic pathways involved in CH Hg+ degradation.\ninterpreted as if another methylmercury pathway is in operation. But can’t it just be that\nthe methyl group that is produced in the demethylation is not assimilated into DNA to\nany major extent? In such a case the demethylating microbes would still be in the\nisotopically “light” fractional. Assimilation into biomass is a critical assumption in this\nwork and it is not a law of nature, so alternative explanations should at least be\nmentioned.\n3. We appreciate the reviewer’s insightful comments. We agree that not all microbial\ntaxa incorporate methyl-derived carbon into DNA, and some demethylating\nmicrobes may remain in the light fraction due to the limited amount of 13C-methyl\nassimilation. We have now discussed this possibility in the revised manuscript\n(lines 308-310) as “We acknowledge that some merAB-mediated demethylators\nmay have remained in the light fraction and were not detected due to the limited\namount of 13C-methyl assimilation.”.\nHowever, our 13CH Hg+-DNA-SIP analyses provide direct evidence that at\n3\nleast a subset of the microbial community actively assimilated 13C from 13CH Hg+.\n3\nthe DNA fractionation patterns between the 12CH Hg+ and 13CH Hg+ treatments\n3 3\nwould be similar. Instead, we observed a gradual shift of the highest 16S rRNA\ngene abundance from the light DNA fractions (at day 7) to heavier fractions (at days\n14 and 28) in the 13CH Hg+ treatment (Fig. 2A-F), indicating that certain soil\n3\nmicroorganisms had incorporated 13C from 13CH Hg+. Moreover, 16S rRNA gene\n3\nand metagenomic analyses revealed significant 13C enrichments of microbial taxa\n(e.g., Pseudarthrobacter, MM2 and Dechloromonas), along with the absence of\nmerA and merB genes in the reconstruction MAGs from the 13CH Hg+ treatment\n3\n(Figs. 3-4). Consistently, merA and merB genes did not exhibit significant\nenrichment in the 13CH Hg+ treatment at the community level compared with the\n3\n12CH Hg+ treatment (Fig. 4A).\ndominate CH Hg+ degradation in the actively 13C-labeled taxa. Nonetheless, we\n3\nacknowledge that some merAB-mediated demethylators could have not been\ndetected due to the limited amount of 13C assimilation, and emphasize the need for\ncomplementary methods to further elucidate the underlying metabolic mechanisms\ninvolved in CH Hg+ degradation (lines 308-314).\n3\n4. Revised as suggested (lines 155-156).\nLine 176: What is “combination analyses”? Should this read “Combined analyses”?\n5. Revised as “Combined analyses of metagenome sequencing and……” (line 177).\nLine 279: “The no significant difference” is awkward and should be revised. “similar”?\n6. Revised as suggested (line 289).\nLine 334: “enormously” should be deleted. Unclear what it means.\n7. Deleted.\nLine 467: “sequence” should read “sequences” and “sequences were”\n8. Done.\nReviewer #3 (Remarks to the Author):\nWhile the authors have made meaningful progress in refining their analysis and the\noverall quality of the paper, several issues still need to be addressed, as outlined below.\n9. Thank you for your comprehensive review and the positive comments on our efforts\nto refine the analyses and improve the manuscript. We have carefully considered\nyour comments and made substantial revisions to address your concerns. Please see\nour point-by-point responses below.\nL184–204: Most of the genes discussed in the main text are either absent from\nSupplementary Fig. 6 or not indicated as significantly enriched. This discrepancy\nsuggests that either the figure needs to be replaced with a more representative version,\nor the corresponding descriptions in the main text should be substantially revised to\nalign with the data shown.\n10. We appreciate the reviewer’s concerns. We would like to clarify that the genes\ndiscussed in the results section are primarily represented in Fig. 4A, which\nhighlights key genes involved in Hg reduction and some biochemical pathways (e.g.,\nsulfate, carbon and nitrogen metabolism)4-6. The data presented in Fig. 4A and\nSupplementary Fig. 6 were integrated to provide a comprehensive overview of the\nmultifunctional metabolic characteristics related to the 13CH Hg+ degradation at the\n3\ncommunity level. To improve consistency between the main text and the figures,\nwe have provided detailed statements of Supplementary Fig. 6 in lines 197-214. For\nexample, “genes encoding isocitrate dehydrogenase (IDH3), 2-oxoglutarate\nferredoxin oxidoreductase (korAB), tetrahydromethanopterin S-methyltransferase\nsubunit B (mtrB), phosphoribosylaminoimidazole-succinocarboxamide synthase\n(purC)… exhibited significant enrichment in the 13CH Hg+ treatment compared\n3\nwith the 12CH Hg+ treatment (lines 200-206).”\n11. We have provided references in lines 190-192 as “genes involved in sulfate\nreduction, carbon metabolism (e.g., methane metabolism) and nitrogen metabolism\n(e.g., nitrate reduction and denitrification) were searched within the metagenomic\ncontigs4-6”.\nL297–304: Why were fdoG (Gemmatimonadota) and gcvP (Actinobacteria)\nhighlighted as significantly enriched among the numerous genes related to carbon\nmetabolism? While the shift in focus toward carbon metabolism is understandable due\nto the absence of significant differences in merA and merB, the rationale behind this\nfocus should be more explicitly justified (as described above: L187-189’s reference).\nAdditionally, the biological or ecological significance of these specific genes must be\nelaborated upon in greater detail.\nCurrently, the discussion risks appearing selective or post hoc—as if only the genes that\nsupport a convenient narrative were chosen from Supplementary Fig. 6.\n12. We thank the reviewer for the thoughtful comments regarding our discussion of\nfdoG (encoding formate dehydrogenase) and gcvP (encoding glycine\ndehydrogenase). As explained, both genes are involved in carbon metabolism,\nparticularly one-carbon (C ) transformations. fdoG is involved in the oxidation of\n1\nformate, a key step in C metabolism that contributes to the generation of C units\n1 1\nused in various biosynthetic pathways7, while gcvP is a critical component of the\nglycine cleavage system, contributing to the production of methylene-\ntetrahydrofolate in the C metabolic network8. Given that oxidative demethylation\n1\nof CH Hg+ has been hypothesized to mediate via co-metabolic pathways involving\n1 3\ntreatment suggests their potential role in mer-independent CH Hg+ degradation.\nhighlighted these genes as representative examples enriched in Actinobacteria and\nGemmatimonadota in the previous manuscript, in support of the hypothesis that\nmer-independent oxidative demethylation may be the predominant degradation\npathway in the paddy soil.\nTo address the concern regarding potential selectivity or post hoc bias, we have\nnow removed the gene-specific discussion to avoid overinterpretation. Instead, we\nemphasize broader functional trends across multiple analytical levels. At the MAG\nlevel, all reconstructed 13C-labeled MAGs lacked both merA and merB, but\ncontained genes involved in carbon and nitrogen metabolism (Fig. 4B). At the\nphylum (i.e., Actinobacteria and Gemmatimonadota) and community levels, the\ncomparable relative abundances of mer operon genes were observed between the\n13CH Hg+ and 12CH Hg+ treatments, while genes associated with carbon and\n3 3\nnitrogen metabolism were significantly enriched in the 13CH Hg+ treatment\n3\ncompared with the 12CH Hg+ treatment (Fig. 4A; Supplementary Fig. 6;\ncommunity levels strongly support that alternative pathways, such as oxidative\ndemethylation, rather than mer-mediated reductive demethylation, may dominate\nCH Hg+ degradation in the actively 13C-labeled microbial communities. We also\n3\nhighlight the need for complementary methods to further elucidate the underlying\nmetabolic mechanisms involved in CH Hg+ degradation. Overall, we now modify\n3\nthe discussion to provide a more balanced and integrative interpretation of the\nmetagenomic data (see revised lines 286-296 and 301-314).\nTo strengthen the discussion, it is essential to clarify the reasoning behind the observed\nenrichment of bacteria lacking merA and merB under the 13C-Hg treatment and to\nensure that all descriptions accurately reflect the underlying data.\n13. We appreciate the reviewer’s insightful comment. In response, we have\nsubstantially revised the discussion to clarify the potential reasoning behind the\nobserved enrichment of bacteria lacking merA and merB in the 13CH Hg+ treatment,\n3\nand to ensure that all descriptions are precisely aligned with the underlying data. At\nthe MAG level, all reconstructed MAGs in the 13CH Hg+ treatment lacked both\n3\nmerA and merB genes (Fig. 4B), suggesting that mer-mediated reductive\ndemethylation was not accountable for the dominant 13CH Hg+ degradation\n3\npathway in these taxa. This was further supported by community- and phylum-level\n(i.e., Actinobacteria and Gemmatimonadota) metagenomic analyses, which showed\ncomparable relative abundances of mer operon genes between the 12CH Hg+ and\n3\n13CH Hg+ treatments (Fig. 4A; Supplementary Fig. 6; Supplementary Fig. 10).\nmetabolism were present in the reconstructed genomes, while both community- and\nphylum-level analyses showed significant enrichment of these genes in the\n13CH Hg+ treatment. These findings suggest the involvement of mer-independent\n3\nprocesses involving simple carbon sources (i.e., C compounds)9. While our results\n1\nprovide functional and genomic evidence supporting the existence of mer-\nindependent degradation pathways, the underlying biochemical mechanisms remain\nto be experimentally validated. To avoid overinterpretation, we have now modified\nthe discussion to present a more cautious and integrative narrative that highlights\nthe potential role of alternative pathways (e.g., oxidative demethylation), while also\nacknowledging the need for complementary methods to further elucidate the\nunderlying metabolic mechanisms involved in CH Hg+ degradation. All relevant\n3\nstatements and discussions have been carefully updated to ensure they are supported\nby the data from this study (lines 286-296 and 301-314)."}]

Decision letter