# Methylmercury degradation by hot spring sulfur-linked microbial communities as a dominant pathway in regulating mercury speciation

Jin-Ping Xue, Rosanna Margalef-Marti, Aubin Thibault de Chanvalon, Emmanuel Tessier, Rémy Guyoneaud, Zoyne Pedrero, Claire Gassie, Mathieu Sebilo, Michael Bank, David Amouroux

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## To cite this version:

Jin-Ping Xue, Rosanna Margalef-Marti, Aubin Thibault de Chanvalon, Emmanuel Tessier, Rémy Guyoneaud, et al.. Methylmercury degradation by hot spring sulfur-linked microbial communities as a dominant pathway in regulating mercury speciation. Water Research, 2025, 268 (part B), pp.122652. 10.1016/j.watres.2024.122652. hal-04776844

HAL Id: hal-04776844

https://univ-pau.hal.science/hal-04776844v1

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Distributed under a Creative Commons Attribution 4.0 International License
Methylmercury degradation by hot spring sulfur-linked microbial
communities as a dominant pathway in regulating mercury speciation

Jin-Ping Xue a,*, Rosanna Margalef-Marti a,b, Aubin Thibault De Chanvalon a, Emmanuel Tessier a,
Rémy Guyoneaud a, Zoyne Pedrero a, Claire Gassie a, Mathieu Sebilo c, Michael S. Bank d,e, David
Amouroux a,\*

ª Université de Pau et des Pays de l'Adour, E2S UPPA, CNRS, Institut des Sciences Analytiques et de Physico-Chimie pour l'Environnement et les Matériaux (IPREM), Pau 64000, France

ᵇ Grup MAiMA, MAGH, Departament de Mineralogia, Petrologia i Geologia Aplicada, Facultat de Ciències de La Terra, Universitat de Barcelona (UB), Barcelona 08028, Spain

ᶜ Sorbonne Université, CNRS, INRAE, IRD, UPD, UPEC, Institute of Ecology and Environmental Sciences – Paris, iEES, Paris 75005, France

d Institute of Marine Research, Bergen 5005, Norway

e University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States

**Jin-Ping Xue, David Amouroux**

Email addresses: jinping.xue@univ-pau.fr, david.amouroux@univ-pau.fr

CRediT author statement:

Jin-Ping Xue: *Conceptualization*, *Methodology*, *Validation*, *Formal analysis*, *Investigation*, *Visualization*, *Writing* – *original draft*, *Writing – review & editing*;

Rosanna Margalef-Marti: *Methodology, Validation, Investigation, Writing – review & editing*;

Aubin Thibault De Chanvalon: Methodology, Investigation, Writing – review & editing;

Emmanuel Tessier: Methodology, Validation, Investigation, Resources; Writing – review & editing;

Rémy Guyoneaud: Methodology, Resources, Writing – review & editing;

Zoyne Pedrero: Validation, Writing – review & editing;

Claire Gassie: Methodology, Resources, Writing – review & editing;

Mathieu Sebilo: Investigation, Writing – review & editing;

Michael S. Bank: Writing – review & editing;

David Amouroux: Conceptualization, Methodology, Validation, Resources, Investigation, Writing – review & editing, Project administration, Funding acquisition.

<footnote>*Corresponding authors:</footnote>
GRAPHICAL ABSTRACT

<figure><img src="image_3.png" /><figcaption>Sulfidic hot spring biofilm/sediment</figcaption></figure>
Sulfidic hot springs harbor unique microbial communities and are important in mercury (Hg) species transformations, although the fine scale drivers of these processes remain poorly understood. Here we studied Hg speciation in water, biofilms, and sediment across three sampling seasons in a French sulfidic hot spring with low Hg concentrations. Microbial Hg species methylation and demethylation potentials were evaluated using incubation experiments with species-specific Hg isotope tracers. Temporal variation in inorganic Hg (iHg) and methylmercury (MeHg) concentrations in water, biofilm, and sediment was observed. The incubation of microbial communities in biofilms and sediment under dark conditions exhibited low iHg methylation potentials, whereas a significant extent of biotic MeHg demethylation to oxidized iHg was found in relation to MeHg concentrations. Results from microbial diversity (16S rDNA) and the metabolic inhibition experiments suggest an important role of sulfur-linked bacterial metabolism dynamics. Specifically, sulfate-reducers and anoxygenic phototrophs were important factors in the regulation of MeHg concentrations in our study site. Overall, the observed dominance of microbial MeHg demethylation demonstrates a strong Hg detoxification capacity in sulfidic aquatic environments.

**Keywords:** Sulfidic hot spring; Microbial communities; Methylmercury demethylation; Mercury speciation; Stable isotope tracers
# 1. INTRODUCTION

Mercury (Hg) is a global contaminant of considerable importance to ecosystem and public health (Driscoll et al., 2013; Peakall and Lovett, 1972). Methylmercury (MeHg) is a highly toxic, organic form of Hg and in natural systems depends on the net MeHg production driven by both biotic (e.g., activity of Hg methylators) (Bouchet et al., 2018; Bravo and Cosio, 2020; Compeau and Bartha, 1985; Ma et al., 2019), and abiotic factors (e.g., sulfide and organic matter) (Benoit et al., 1999a; Jiang et al., 2018). Despite numerous studies, there are still considerable uncertainties regarding the ideal environmental conditions under which microbial-facilitated Hg pathways are enhanced, as well as the identification of the key microbes involved (Capo et al., 2023; Vigneron et al., 2021).

Terrestrial hot springs are unique and extreme ecosystems, and often have high total Hg (THg) concentrations (e.g., up to tens of µg L⁻¹) especially in volcanic areas where water may come into contact with extremely hot rock heated by magma (Gionfriddo et al., 2020; Sherman et al., 2009), representing a potential Hg source in aquatic environments. However, the fate of released Hg, especially microbial transformations (e.g., MeHg production) remains poorly understood (Gionfriddo et al., 2020; King et al., 2006). Early studies in hot springs reported THg concentrations (McCleskey et al., 2004; Nakagawa, 1974), with limited focus on MeHg dynamics (Hirner et al., 1998). More recently research has begun to more fully understand microbial interactions with Hg species, by considering both Hg speciation data and microbial diversity in microbial media (e.g., 16S rDNA in mats) (Boyd et al., 2009; King et al., 2006). These studies, for instance, found generally low %MeHg (e.g., < 0.1%) in water (Boyd et al., 2009; King et al., 2006), but high %MeHg in microbial mats (e.g., 5–10%) (King et al., 2006). The potential methylation in mats, however, has only been reported by indirect observations, such as the detection of potential Hg methylators, including the primary sulfate reducers (SRB; e.g., *Thermodesulfobacterium*) (King et al., 2006). Trial experiments have traced inorganic Hg (iHg) methylation by using a radioactive tracer (i.e., ²⁰³HgCl₂) in hot spring mats, yet failed to identify the mechanistic drivers of such processes including MeHg demethylation (Boyd et al., 2009). More recently, a conceptual Hg transformation model of hot springs has been proposed based on metagenomics data (Gionfriddo et al., 2020), however quantitative assessments of Hg
transformations and their species-specific rates have not yet been undertaken. To summarize, significant knowledge gaps remain in both the quantitative analysis of key Hg species concentrations and transformations in hot spring environments and the understanding of associated microbial drivers that may predominantly influence these transformations.

In sulfidic hot springs, microbial matrices, such as biofilms, are found to be dominated by cyanobacteria and sulfur-oxidizing bacteria as well as sulfate reducers (Elshahed et al., 2003; Gionfriddo et al., 2020; Kubo et al., 2011; Revsbech and Ward, 1984). Sulfur-oxidizing phototrophs may form metabolic linages with sulfate reducers (e.g., cryptic sulfur cycle), thus facilitating rapid growth of the community (e.g., phototrophic bloom) in these highly sulfidic environments (Bhatnagar et al., 2020; Elshahed et al., 2003). Furthermore, oxygenic phototrophs (e.g., cyanobacteria and algae) and sulfate reducers are respectively recognized for their involvement in various Hg transformations, such as iHg reduction, MeHg demethylation, and iHg methylation (Grégoire and Poulain, 2016; Liang et al., 2023; Parks et al., 2013; Vigneron et al., 2021). Thus, sulfidic hot springs may serve as an effective model system for studying microbial control of Hg speciation dynamics and cycling at the community level (King et al., 2006). However, the primary drivers of microbial community dynamics governing Hg transformations are not well understood, which limits our mechanistic understanding of MeHg accumulation and cycling in extreme, sulfidic aquatic ecosystems. Furthermore, due to similarities between sulfidic hot springs and marine hydrothermal vents, including elevated sulfide concentrations, and comparable microbial sulfur cycling dynamics (Brazelton, 2017; Zhou et al., 2023), research in sulfidic hot springs may offer valuable insights into the key Hg biogeochemical processes in hydrothermal vent ecosystems, where such studies are scarce.

Until now, Hg data have primarily been reported for Hg-enriched hot springs (e.g., with volcanic origin) (Gionfriddo et al., 2020; King et al., 2006; Sherman et al., 2009). The distinct nature and importance of non-volcanic hot springs with trace Hg levels in understanding global geothermal systems have been widely recognized (Anuar et al., 2021; Baioumy et al., 2015; Escuder-Rodríguez et al., 2022; Maitra et al., 2020; Yaguchi et al., 2014). In addition, the hot springs (e.g., non-volcanic thermal sources) and under sulfidic conditions are poorly studied, due largely to analytical challenges
to perform accurate Hg speciation measurements (e.g., trace levels and high sulfide interferences)

(Nakagawa, 1974; Olson et al., 1997). This research gap impedes a comprehensive understanding of global Hg concentrations and speciation dynamics in different types of terrestrial hot springs. It also affects proper global assessments of Hg sources, fate, and transport in hydrothermal systems such as marine hydrothermal vents (Torres-Rodriguez et al., 2024). Additionally, low Hg hot springs, which mimic the Hg concentrations found in aquatic ecosystems such as freshwater lakes, feature naturally selected microbial communities due to extreme environmental conditions (Shu and Huang, 2022).

Studying these springs provides unique insights into microbial-driven transformations, including iHg methylation and MeHg demethylation rates. Such investigations are crucial for understanding the functional dynamics of representative microbial communities (e.g., anoxygenic phototrophs and SRB) in Hg cycling, particularly within the context of complex sulfur cycling, as expected in low Hg sulfidic hot springs.

To fill those knowledge gaps, the TdM hot spring in Southwest France was used as a model study system. The TdM hot spring is located in the Pyrenees Mountains area, one of the four major regions where the majority of thermal springs in France are found (Waring et al., 1965). The hot spring is a sulfidic (i.e., sulfide-rich) hydrothermal system in non-volcanic areas, but it is heated geothermally as the water descends deeper into the earth crust and then circulates back to the surface of the ground (i.e., sodium chloride-sulfate water) (Berard et al., 1997). We hypothesized that sulfidic hot spring environments would be important drivers of Hg cycling owing to the presence of representative sulfur-linked microbial communities (e.g., sulfur oxidizers and reducers), which may influence Hg species transformations, particularly potential MeHg production and/or degradation, ultimately regulating MeHg concentrations. Given these hypotheses, the specific objectives of this investigation were to: 1) determine Hg speciation in various ecosystem compartments, including water, biofilm, and sediment; 2) perform incubation experiments to assess Hg species transformation potentials by microbial communities in biofilm and sediment. Furthermore, we also assessed how sulfur metabolism, driven by phototrophic and heterotrophic microbial communities, may control MeHg fate and transport via microbial Hg cycling processes.
## 2. MATERIALS AND METHODS

### 2.1. Site description, field sampling and processing

The TdM hot spring is located in Préchacq-les-Bains, southwest France (Figure S1; 43° 45' 43.2" N, 0° 56' 9.6" W). The hot spring is characterized with concentrations of sulfide and sulfate previously reported, in 1975, as 52 and 415 mg L⁻¹, respectively (Berard et al., 1997). Water temperature was reported as 30.1 °C, with a conductivity of 2.8 mS cm⁻¹, and a pH of 7.2 (Berard et al., 1997). A meandering channel allows spring pool water to flow for tens of meters into an adjacent, freshwater forest river. Additional study site information is provided in Supplementary Text S1.

Water, biofilm, and sediment samples were collected for Hg speciation and incubations during three different sampling seasons: October 15 / November 15, 2021 (wet period), June 21, 2022 (dry period), and April 27, 2023 (wet period). The June 2022 field period in TdM was characterized as a comparatively dry period, attributed to reduced precipitation and elevated temperature ranges (both maximum and minimum temperatures). This was notably distinct from the wet periods experienced in 2021 and 2023, respectively. Precipitation and temperature data before each sampling period and the basis for categorizing wet and dry periods are provided in Figure S2. An initial visual inspection identified obvious spatial trends in microbial communities along the outflow channel of the spring pool (Figure S3a–d). Green and white biofilms were observed attached to rocks (upstream; < 5 m from the pool), and we also detected floating, white biofilms (midstream; 5–15 m from the pool), as well as microbial communities in downstream sediment (> 15 m from the pool).

Unfiltered water samples were collected into 250 / 500 ml acid-cleaned PFA bottles (Nalgene, ThermoFisher Scientific, USA), and were acidified *in-situ* to 1% HCl (v/v) using Optima™ grade HCl (Fisher Chemical™) for subsequent Hg speciation analyses. A separate set of non-acidified bulk water samples were collected and kept for water incubations. Biofilm and sediment samples for Hg speciation and incubations were obtained by using 100 ml wide-mouth polypropylene jars (Greiner Bio-One™). Specifically, a clean sampling brush and a plastic tweezer were used to separate biofilm samples from upstream rock surfaces and to remove rock and gravel particles. For biofilms floating on the water (midstream) and attached to the sediments (downstream), samples were directly placed into
jars using powder free, gloved hands. Biofilm and sediment samples for DNA extractions were simultaneously collected into sterile cryovials, and quickly put into cooler with ice packs in the field, and then stored at -80 °C in the laboratory within a few hours (e.g., < 4 h). Water quality parameters including temperature, pH, Eh, O₂ saturation, and conductivity were determined *in-situ* by using a field multimeter (Aquaread AP-5000). Additional 0.22 µm-filtered water samples were obtained, and *in-situ* conditioned for laboratory determination of sulfur species (e.g., sulfide and sulfate), major ions, and dissolved organic carbon (DOC). Our sampling protocols followed previously reported methods described by Bouchet et al., 2018, Duval et al., 2023, and Margalef-Marti et al., (2023, 2024), and detailed information on all sample collection, processing, and preservation is reported in Supplementary Text S2.

## 2.2. Incubation experiments with stable Hg isotope tracers

Water incubations were carried out without headspace (e.g., to avoid oxygen interference) and in triplicate by using 60 / 125 ml PFA bottles for ~24 hours ($t_f$) under dark conditions (e.g., mimicking the water temperature of 28 °C and flowing water conditions by using a shaking water bath at ~100 rpm). The water incubations were stopped by acidification with 1% HCl v/v. Triplicate controls ($t_0$) were acidified in a similar manner before spiking. In specific, 50 µl of a solution containing isotopically enriched Hg species tracers were added into $t_0$ and $t_f$ incubation vials, preferably within ~5–10 times of ambient concentration ranges (e.g., 1 ng·L⁻¹ Me²⁰¹Hg and 5 ng·L⁻¹ i¹⁹⁹Hg¹¹). The incubated $t_f$ and $t_0$ samples were stored under dark conditions at 4 °C prior to analysis.

Upstream biofilms and downstream sediment slurries were incubated at environmental conditions similar to water incubations for ~24 hours under dark conditions after the spike addition, then stopped by freezing into a dry shipper containing liquid N₂ and preserved at -20 °C prior to analysis.

Experimental controls ($t_0$) were immediately frozen after spike addition by putting them into liquid nitrogen. Approximately 10 g of biofilm / sediment slurries were pooled, homogenized, and distributed within 60 ml polypropylene (i.e., Nov. 2021 and Jun. 2022) / PFA (i.e., Apr. 2023) jars with additions of 1–5 ml MilliQ water (i.e., Nov. 2021) / *in-situ* waters (i.e., Jun. 2022 and Apr. 2023). Appropriate amounts of isotopically enriched tracers were mixed and generally added within 2–5 times of ambient
concentration ranges (e.g., 1 ng·g⁻¹ *dw* for Me²⁰¹Hg and 100 ng·g⁻¹ *dw* for i¹⁹⁹HgII) in the incubation system. The amount of added spike depended on the availability and preparation of corresponding working solutions. We performed biofilm and sediment incubations under dark conditions, and excluded abiotic, light-induced transformation pathways, and thus the microbial-driven processes could be realistically estimated. Detailed information for the experimental incubations is reported in Supplementary Text S3, following protocols in literature (Alanoca et al., 2016; Bouchet et al., 2022, 2018; Duval et al., 2023). Incubation workflow details are briefly summarized in Table 1, and shown as a flowchart in Figure S4.

Three additional control experiments were consistently conducted in upstream biofilms, informed by an enhanced understanding of Hg speciation and dominant transformation processes, to clarify the factors influencing observed Hg transformations (Table 1, Figure S4). The experimental design started with enhancing the understanding of key transformation processes, particularly the reductive MeHg demethylation, which necessitated an additional purging step. The focus then shifted to identifying microorganisms potentially involved in these dominant pathways, such as MeHg demethylation.

Specifically, control experiment I evaluated the production of dissolved gaseous Hg (DGM) forms and estimated the extent of reductive demethylation and iHg reduction in upstream biofilm sampled during June 2022. Monitoring the Hg⁰ produced these processes can help understand if the hot spring acts as a source of Hg to surrounding environments due to the potential evasion of Hg⁰ from the ecosystem.

Control experiment II, conducted in April 2023, assessed the impact of visible light on biofilm incubations, focusing on photobiological effects based upon the initial finding that *Cyanobacteria* consistently dominated the microbial communities (> 50% relative abundance). Control experiment III employed metabolic inhibitors to delineate the roles of phototrophs (e.g., by adding 20 µM Diuron) and SRB (e.g., by adding 20 mM Na-molybdate) in Hg species transformations in this sulfidic hot spring where the cryptic sulfur cycle driven by these sulfur-linked bacteria (e.g., *Cyanobacteria* and *Desulfobacterota*) is expected. Detailed methodologies are documented in Supplementary Text S4.
## 2.3. Mercury speciation analyses

Mercury species concentrations in water, biofilm, and sediment samples were determined using gas chromatography (GC) coupled to ICP-MS with species-specific isotope dilution, as described previously (Feng et al., 2016; Monperrus et al., 2008, 2005). Water samples were purged for detecting Hg signals on GC chromatograph by Hg-free compressed air or argon before analysis by removing excess sulfide. For biofilm and sediment samples, approximately 0.2 g of freeze-dried samples were subjected to microwave-assisted extraction (CEM Corporation) using ~4 ml of ultra-pure 6N HNO₃ at 85 °C for 5 minutes. The resulting digest was analyzed for iHg (i.e., iHgII + Hg⁰) and MeHg (i.e., MMHg + dimethylmercury as DMHg). Briefly, a 100 mL water sample or 200 µL acid digest was spiked with isotopically enriched i¹⁹⁸HgII and MM²⁰²Hg (ISC-Science, Oviedo, Spain) with known isotopic composition and concentrations. The mixture was buffered with 5 mL of 0.1 M sodium acetate buffer (pH 3.9), and the pH was adjusted to 3.9 for optimal derivatization. Proper volumes of isooctane (e.g., 200 µL) and 5% (w/v) sodium tetraethylborate/tetrapropylborate were added, and the flask was immediately capped and shaken on an orbital shaker at 400 rpm for 20 minutes. The organic phase was recovered, transferred to an injection vial, and injected in triplicate into the GC-ICP-MS using an autosampler. Details on GC-ICP-MS operating conditions are available elsewhere (Kleindienst et al., 2024). Detection limits for iHg and MeHg in biofilm / sediment samples were 0.008 ± 0.006 ng g⁻¹ ww and 0.001 ± 0.0006 ng g⁻¹ ww, respectively (n = 5 for each), with similar protocols applied to water samples yielding detection limits of 0.010 ± 0.008 ng L⁻¹ for iHg and 0.002 ± 0.001 ng L⁻¹ for MeHg (n = 3). Verification of THg (i.e., iHg + MeHg) levels measured by ID-GC-ICPMS in biofilms / sediments via cross-checks with an Advanced Mercury Analyzer (AMA 254) had an overall recovery of 89.7–92.0% (n = 3). Analytical reproducibility was maintained with triplicate GC injections, reported as averages and standard deviations (nGC = 3). In addition, certified reference materials including IAEA456 (marine sediment) were periodically checked for analytical accuracy. Overall, for Hg speciation analyses, this study followed previous studies in water (Cavalheiro et al., 2016; Duval et al., 2023), and in sediment and biofilms (Feng et al., 2016; Sánchez-Fortún et al., 2024).
## 2.4. Mercury species transformation rates

The incubation samples were analyzed in a similar way as the speciation analyses, while Hg species concentrations were calculated by employing the isotopic pattern deconvolution (IPD) method (Bouchet et al., 2018; Duval et al., 2023; Rodriguez-Gonzalez et al., 2013). Dissolved gaseous Hg species from incubation samples were trapped in gold-coated sand traps and were analysed by thermal desorption cryogenic trapping (CT)-GC-ICP-MS (Amouroux et al., 1998), followed by IPD, and quantification by external calibration (Calleja, 2022).

Mercury species concentration data were used to calculate various transformation rates (% h⁻¹) including iHg reduction (iHg'' to Hg⁰) and methylation (iHg'' to MeHg), MeHg demethylation (MeHg to iHg''), MeHg loss (MeHg to iHg'' and Hg⁰) as well as reductive demethylation (MeHg to Hg⁰) following methods described by Rodriguez-Gonzalez et al., (2013) and Duval et al., (2023). Both MeHg demethylation rates and MeHg loss can be used to assess MeHg demethylation potentials, and their discrepancies may result from shifts in mass balance during the incubation experiment (e.g., loss of i²⁰¹Hg'' or ²⁰¹DGM) (Duval et al., 2023; Kleindienst et al., 2024). We assumed that trapped DGM from purged biofilm incubations was mainly present as Hg⁰ due to the fact of the extremely low (CH₃Hg)₂S (e.g., < 0.05%) modelled in TdM water (see Table S5). This predicted bis(methylmercury) sulfide intermediate, (CH₃Hg)₂S, has been recently suggested as a good predictor of the observed DMHg formation rate in sulfidic solutions (Kanzler et al., 2018). The calculation formulas for assessing Hg species transformation rates (% h⁻¹) are as follows:

$$ iHg\ reduction = \frac{^{199}\text{DGM}_{t_f} - ^{199}\text{DGM}_{t_0}}{i^{199}\text{Hg}_{t_0}} \times \frac{100\%}{t} \qquad (1) $$

$$ iHg\ methylation = \frac{Me^{199}\text{Hg}_{t_f} - Me^{199}\text{Hg}_{t_0}}{i^{199}\text{Hg}_{t_0}} \times \frac{100\%}{t} \qquad (2) $$

$$ Demethylation = \frac{i^{201}\text{Hg}_{t_f} - i^{201}\text{Hg}_{t_0}}{Me^{201}\text{Hg}_{t_0}} \times \frac{100\%}{t} \qquad (3) $$

$$ MeHg\ loss = \frac{Me^{201}\text{Hg}_{t_0} - Me^{201}\text{Hg}_{t_f}}{Me^{201}\text{Hg}_{t_0}} \times \frac{100\%}{t} \qquad (4) $$
$$ \textit{Reductive demethylation} = \frac{^{201}\text{DGM}_{tf} - ^{201}\text{DGM}_{t0}}{Me^{201}\text{Hg}_{t0}} \times \frac{100\%}{t} \qquad (5) $$

where t is the time of incubation (hour), i^XXXHg_{t0}, Me^XXXHg_{t0} and ^XXXDGM_{t0} are the measured concentrations at the beginning (t0) of the incubation experiment, i^XXXHg_{tf}, Me^XXXHg_{tf} and ^XXXDGM_{tf} are the measured concentrations at the end (tf) of the incubation experiment. Detection limits for water and biofilm / sediment incubations are referred to Supplementary Text S3.

## 2.5. Physicochemical and microbial analyses

Elemental analyses (i.e., major cations and anions) were conducted for spring water samples. Briefly, the SO₄²⁻ content was assessed through nephelometry or ion chromatography (April 2023), while DOC was determined by combustion of organic matter. The concentration of ΣS²⁻ (H₂S, HS⁻ and S²⁻) was measured spectrophotometrically by adding 500 µL of a zinc acetate trapping solution at 20 g L⁻¹ into 1 ml water samples immediately after field sampling collections (Fonselius et al., 1999). Major ion concentrations, including Ca, Mg, K, and Na, were quantified using ICP-OES (iCAP 6000 series, Thermo Scientific) following previous studies (Margalef-Marti et al., 2023). The DNA extractions on collected biofilm and sediment samples were performed on pellets using DNeasy PowerSoil kit (QIAGEN, Germany) following the manufacturer's instructions and stored at -20 °C until further use. The procedures and data treatments associated with the metabarcoding of the V4-V5 region of the 16S rDNA gene are detailed in Supplementary Text S5.

## 2.6. Mercury speciation modelling

Equilibrium speciation modelling was conducted using Visual MINTEQ V. 3.1 to simulate the interactions of iHg species with inorganic ligands and DOC in the spring pool water over three sampling seasons. The spring chemistry data were entered into MINTEQ, and pH was fixed using the measured values (Supplementary Text S6). The MINTEQ software was adapted for MeHg speciation modelling by adding relevant inorganic MeHg-bearing species (e.g., CH₃HgS⁻, CH₃HgSH, and (CH₃Hg)₂S), their corresponding reactions as well as equilibrium constants (log K) (Blanc et al., 2018; Kanzler et al., 2018). Details on MeHg speciation modelling are found in Table S1.
## 2.7. Statistical analyses

Data visualization for Hg speciation and transformation rates were done with Veusz, an open access scientific plotting package (https://veusz.github.io/), as well as OriginPro 2021 (OriginLab Corporation, Northampton, Massachusetts, USA). OriginPro 2021 was also used for statistical purposes. Statistical significance was accepted at *p* ≤ 0.05 and differences among groups were determined by one-way ANOVA and Tukey's multiple comparison test. Linear correlations between MeHg concentrations in biofilm/sediment and water were performed using Excel 2019 with default settings.

# 3. RESULTS

## 3.1. Geochemical and microbiological conditions

### 3.1.1. Geochemical conditions

Spring water temperature (27.6 ± 1.5 °C, *n* = 8), pH (7.4 ± 0.2, *n* = 9), and major ions in spring did not show significant spatiotemporal variation (Table S2). From upstream to downstream, dissolved O₂ saturation slightly increased but stayed below 20%, while the H₂S levels decreased along the channel. In contrast, the SO₄²⁻ levels did not show a significant increase along the channel (Table S2), likely attributed to the combined influence of sulfide oxidation and bacterial sulfate reduction (see Figure S5 for bacterial sulfate reduction in downstream sediment) in water. The conservative behavior of major cations (e.g., Ca²⁺, Mg²⁺ and K⁺) was consistently observed along the outflow channel across all sampling campaigns (Table S2).

### 3.1.2. Biofilm and sediment microbial communities

In upstream biofilm, the five main phyla were *Cyanobacteria* 49.1%–93.3% as *Limnotrichaceae* (i.e., *Limnothrix*), *Chloroflexi* 11.2%, *Bacteroidota* 9.5%, *Desulfobacterota* 5.5%–34.1% as *Desulfocapsaceae* and 20.2% as *Geobacteraceae*, and *Pseudomonadota* 4.4% (Figure 1a–b). The biofilms from upstream and midstream in 2021 showed greater patterns of similarity regarding the overall taxonomic diversity (Figure 1). The microbial distribution in downstream sediment was more
diverse, with the previously mentioned phyla accounting for < 50% of the total. Similar distribution patterns for upstream biofilm phylum were observed in 2022 with a slight increase in the relative proportion of *Cyanobacteria* (i.e., 59.2%) relative to the 2021 (i.e., 49.1%) sampling campaign. Phase contrast microscopic analysis of upstream biofilm samples from 2023 also confirmed the presence of cyanobacteria, purple sulfur bacteria, and likely SRBs. (Figure S3e–f).

Sulfur-related prokaryotes detected in TdM samples was compiled (Table S3), and a theoretical model was proposed for the microbial sulfur cycle mediated by these bacteria (Figure S6). The scheme showed the dominant pathway of H₂S oxidation into SO₄²⁻ and intermediate sulfur compounds (mainly thiosulfate and elemental sulfur) by phototrophs (e.g., *Chromatiaceae* and *Rhodobacteraceae*) and aerobic sulfur oxidizers (e.g., *Halothiobacillaceae*), followed by sulfate reduction by SRBs (i.e., *Desulfocapsaceae*) under highly sulfidic conditions. In this oligotrophic, sulfide-rich hot spring ecosystem (~1 mg L⁻¹ DOC; Table S2), autotrophic taxa such as *Limnotrichaceae* and *Chromatiaceae* near the spring pool likely generated biomass subsequently utilized by downstream heterotrophs (e.g., *Desulfocapsaceae*).

## 3.2. Hg species distribution and transformations in water

### 3.2.1. Hg species distribution in water

Both iHg and MeHg in water were found at trace concentrations (e.g., ng L⁻¹). Inorganic Hg upstream showed relatively low and comparable levels between October 2021 and April 2023 (Figure 2a–b). Slightly higher concentrations of iHg were found in October 2021 compared to April 2023 at both midstream and downstream sites. In comparison, significantly higher concentrations of iHg occurred during June 2022 compared to other seasons. Along the outflow channel, iHg concentrations decreased downward from the pool in 2022. Similarly, higher MeHg concentrations were also observed in June 2022 compared to other seasons. MeHg concentrations also decreased downward during June 2022, and %MeHg was correspondingly higher in June 2022 compared to other seasons (Figure 2c).

Inorganic Hg and MeHg were modelled over three sampling seasons in the hot spring outflow water (Table S5). Our data showed that iHg species were dominated by HgS₂H⁻ (76.3–79.7%), followed by
Hg(HS)₂₀ (aq) (12.4–13.0%), HgS₂²⁻ (4.0–4.2%), as well as aqueous Hg-DOC complexes including FA2-Hg(6) (aq) (3.1–7.1%) and HA2-Hg(7) (aq) (0.1–0.2%). These Hg-DOC complexes are supposed to be mainly iHg species binding with organic thiol functional groups. The MeHg species predominantly comprised CH₃HgSH (> 99.9%) with a minimal presence of (CH₃Hg)₂S (< 0.1%).

### 3.2.2. Hg species transformations in water

Data from the dark incubation experiments showed low MeHg demethylation (< 0.08% h⁻¹) and iHgII methylation (< 0.02% h⁻¹) rates at the spring pool across the different seasons and from the pool to downstream during November 2021 (Table 2). Rates of MeHg loss during incubation are shown in Table 2. Notably, higher demethylation rates were observed under natural sunlight conditions (9.11 ± 1.28% h⁻¹) and rates of MeHg loss during sunlight incubations were comparable to rates of MeHg demethylation. Under sunlight conditions, the iHgII methylation rate in the spring pool was below the detection limit (i.e., 0.001% h⁻¹), similar to the rates observed during dark incubations. Additionally, DGM species were not purged during water incubations, so iHg reduction was not assessed.

## 3.3. Hg species distribution and transformations in biofilm and sediments

### 3.3.1. Biofilm and sediment Hg species distribution

Inorganic Hg concentrations in upstream biofilm increased from 2021 to 2022 (Figure 2d). Midstream biofilm had similarly higher concentrations (57.7 ± 0.4 ng g⁻¹ *dw*, only analyzed in October 2021). For downstream sediment, slightly higher concentrations of iHg were observed from November 2021 to April 2023, with the highest concentrations observed during 2022 (i.e., 91.5 ± 1.4 ng g⁻¹ *dw*).

Comparable levels of iHg were found in midstream sediment during June 2022 and April 2023 and significantly higher MeHg concentrations were detected in both biofilm and sediment in June 2022 compared to the other two seasons (Figure 2e). Overall, %MeHg was low (i.e., < 1.0%), with higher values observed in June 2022 (Figure 2f).

### 3.3.2. Hg species transformations

Minimal methylation potential (≤ 0.002% h⁻¹) was determined in biofilm and sediment incubations under dark conditions (Table 2). In comparison, demethylation rates were higher and appeared to
mirror changes in ambient MeHg concentrations. Specifically, upstream biofilm in June 2022 exhibited significantly lower demethylation rates (0.14 ± 0.08% h⁻¹) with higher MeHg concentrations. Conversely, the highest demethylation rates (3.95 ± 0.59% h⁻¹) were observed during November 2021 when MeHg concentrations were lowest. In downstream sediment, the observed increase in MeHg concentrations from November 2021 to June 2022 was correlated with an estimated 71% decrease in demethylation rates from 1.92 ± 0.53 to 0.55 ± 0.24% h⁻¹ and MeHg loss exhibited values comparable to demethylation rates.

To investigate the exact route of demethylation of Me²⁰¹Hg, the produced ²⁰¹DGM was purged onto gold-coated sand traps and determined from a biofilm control experiment conducted in April 2023. The rate of MeHg demethylation (to iHg²¹; 0.14 ± 0.08% h⁻¹) was greater compared to the reductive MeHg demethylation rate with a value of 0.0009 ± 0.0001% h⁻¹ (*p* < 0.05). Additionally, ¹⁹⁹DGM was simultaneously purged, trapped, and analyzed, and no significant difference between *t*₀ and *t*₁ (data not shown) was detected. Thus, it was inferred that iHg reduction by upstream biofilm was likely negligible (e.g., < 0.02 × 10⁻³ % h⁻¹).

For upstream biofilm, the metabolic inhibition experiment revealed higher methylation rates under visible light conditions (0.008 ± 0.004% h⁻¹) when compared to the dark treatment (0.001 ± 0.002% h⁻¹) (Figure 3a). Similarly, higher demethylation rates were determined under artificial light conditions (Figure 3b). Upon using the metabolic inhibitors, a significant decrease in demethylation rate was observed using Diuron and molybdate simultaneously (*p* < 0.05). Under light conditions, the addition of molybdate appeared to lower demethylation rates, even though this was not statistically different (*p* > 0.05). MeHg loss was consistently and slightly higher compared to demethylation rates yet revealed similar patterns (Figure 3c).
# 4. DISCUSSION

## 4.1. Influence of microbial demethylation on MeHg concentrations

### 4.1.1. Microbial communities as drivers of MeHg demethylation

Sulfidic hot springs have been considered as potential hotspots of MeHg production as a result of the occurrence of sulfur-linked bacteria such as sulfate reducers (Elshahed et al., 2003; King et al., 2006). Our results from the dark treatment incubations on biofilms and sediments led to different conclusions and exhibited overall rate ranges of demethylation to iHg<sup>II</sup> (0.14–3.95% h<sup>-1</sup>) which were constantly higher compared to iHg<sup>II</sup> methylation (< 0.002% h<sup>-1</sup>) in this ecosystem (Table 2).

The dominance of MeHg demethylation under dark conditions was likely due to the abundance and availability of potential microorganisms for MeHg demethylation and the speciation and bioavailability of MeHg. Reported MeHg demethylators such as *Cyanobacteria* and *Desulfobacterota* (Liang et al., 2023; Marvin-DiPasquale and Oremland, 1998; Pak and Bartha, 1998), were also retrieved in TdM biofilms and sediment with relatively high abundance (> 50%) (Figure 1). However, given species variations and differing physiological activities of MeHg methylators across studies, further laboratory and field studies are needed to identify the bacterial species and environmental conditions driving MeHg demethylation (Bridou et al., 2011; Liang et al., 2023). Additionally, our modelled results suggest that MeHg mainly formed the dissolved CH<sub>3</sub>HgSH complex (> 99.96%) in sulfidic waters of TdM (Table S5). This uncharged complex is likely more bioavailable than other MeHg complexes (e.g., CH<sub>3</sub>HgCl) to demethylators at nearly neutral pH conditions with elevated sulfide levels (Jackson, 1998). Lastly, a recent study identified Hg<sup>0</sup> as the main MeHg demethylation product by cyanobacteria *Synechocystis* sp. and *Microcystis* sp., with ~50–75% of MeHg degraded under laboratory conditions (Liang et al., 2023). In contrast, we observed the dominance of iHg<sup>II</sup> as the final demethylation product in TdM hot spring biofilms, with negligible production of DGM species (Hg<sup>0</sup> + DMHg). This distinct pattern may further indicate the complexity of MeHg degradation at the community level in natural aquatic ecosystems.
The low microbial methylation potential could similarly be attributed to the lower bioavailability of iHg as well as to the lower activity of SRB. Specifically, results from our speciation model suggest the dominance of anionic disulfide complex, HgS<sub>2</sub>H<sup>-</sup>, relative to the neutral Hg(HS)<sub>2</sub><sup>0</sup>(aq) in the TdM water (Table S5). As mentioned above, HgS<sub>2</sub>H<sup>-</sup> complex is considered less bioavailable than Hg(HS)<sub>2</sub><sup>0</sup> to Hg methylators (e.g., SRB) due to the preferential uptake of neutral Hg species via passive uptake (Benoit et al., 2001, 1999b, 1999a). Additionally, although we observed a relatively high abundance of potential Hg methylators (e.g., 5.5% *Desulfobacterota*—34.1% as *Desulfocapsaceae* and 20.2% as *Geobacteraceae*), it is possible that the activity of these bacteria remains limited, likely because of the low organic matter content observed in TdM water (e.g., ~1 mg L<sup>-1</sup> DOC), which may result in lower MeHg production. In addition, the higher sulfate content compared to sulfides in TdM water suggests that sulfate reduction does not compensate microbial sulfide oxidation in this hot spring ecosystem.

Inorganic Hg speciation may also be biotically altered within microbial matrices (e.g., biofilm) to become less bioavailable to potential Hg methylators. For instance, previous culture studies have reported the transformation of iHg<sup>II</sup> to β-HgS by *Cyanobacteria*, particularly by *Limnothrix* (i.e., *Limnotrichaceae*), with the involvement of intracellular thiols (Lefebvre et al., 2007). Interestingly, *Limnothrix* represented over 90% of the *Cyanobacteria* detected in the upstream TdM biofilm. This observation may suggest that the production of less-bioavailable β-HgS could also contribute to the low iHg methylation potential in the TdM microbial mats. Collectively, this suggests that the observation of low methylation potential primarily resulted from high sulfide concentrations that may have influenced iHg speciation and bioavailability, as well as potentially limited bacterial sulfate reduction activity.

### 4.1.2. MeHg sources and fate dynamics

Aqueous ratios of MeHg and iHg<sup>II</sup> to Mg<sup>2+</sup> (i.e., a conservative element) were 2.24–8.04% for iHg<sup>II</sup> and 1.73–2.89% for MeHg, in June 2022, and were relatively higher compared to other sampling periods (i.e., 1.25–3.02% for iHg<sup>II</sup> and < 0.53% for MeHg) (Figure S7a–b). Despite June 2022 being a relatively dry period in TdM, with reduced precipitation and elevated temperatures (Figure S2), we assumed that terrestrial surface runoff could still influence the hot spring during this time. This
disturbance affected both iHg and MeHg concentrations, as evidenced by sharp increases in microbial
mats, especially in upstream biofilm, and in water from 2021 to 2022 (Figure 2d–e). Additionally, in-
situ MeHg production in biofilm and/or sediment may also contribute to increased MeHg
concentrations that were observed during June 2022. This is supported by the net methylation rates in
upstream biofilm samples, where methylation exceeded demethylation, (1.2 ± 0.2) × 10⁻³ vs. (0.7 ±
0.1) × 10⁻³ ng g⁻¹ h⁻¹ *dw*, respectively, based on measured rates and ambient Hg species
concentrations. This pattern suggests that MeHg accumulation could be driven by *in-situ* biological
methylation. Using similar calculations, a net demethylation potential (i.e., 1.8 × 10⁻³–3.7 × 10⁻³ ng g⁻¹
h⁻¹ *dw*), was also determined for upstream biofilm during other sampling periods, supporting
significant annual changes in MeHg production and accumulation in hot spring biofilms.

Combining all our experimental results, we attempted to assess the drivers of the observed MeHg
dynamics in the upstream biofilm-water ecosystem (Figure 4). Our data indicated rapid turnover rates
of MeHg (i.e., MeHg degradation), in water exposed to sunlight and within biofilm under dark
conditions, with estimated half-lives ranging from 0.23 to 1.61 days. Moreover, MeHg production
largely relies on biofilm photobiological activity. Consequently, a stable MeHg balance is achievable
if photochemical degradation of MeHg is significantly constrained by a biofilm-mediated supply as a
limiting factor. This also implies that variation in MeHg concentrations can often occur in hot spring
water, underscoring the need for high-resolution temporal investigations to more fully understand Hg
species distribution patterns in this ecosystem.

Strong relationships were also observed between MeHg in biofilms (R² = 0.89) and sediment (R² =
0.88) and in water, although they were not statistically significant (*p* > 0.05) (Figure S9). This suggests
that the microbial communities within biofilm and sediment may regulate ambient MeHg
concentrations in water. In the presence of sunlight, demethylation potentials were significantly
increased in this sulfidic water relative to the dark conditions (Table 2), with a rate of 9.11 ± 1.28% h⁻¹.
This suggests that photochemical degradation likely governs MeHg concentrations in sulfidic hot
spring water when optimal sunlight exposure is achieved, while significant tree cover occurs in the
TdM hot spring. Collectively, our results showed that MeHg demethylation to iHgII was the dominant
Hg species pathway mainly driven by biofilm and sediment microbial communities, even though external environmental influences and inputs generate temporal variability in Hg species distribution.

## 4.2. MeHg demethylation in biofilm by sulfur-linked bacteria

### 4.2.1. Microbial activity and MeHg demethylation under dark conditions

Despite the dominance of the anoxygenic cyanobacteria (i.e., > 95% of *Limnotrichaceae*; see Table S3) in hot spring biofilm, oxygenic photosynthesis of cyanobacteria could occur under sulfidic natural conditions when H₂S becomes limiting (e.g., 0.2–1 mM) (Cohen et al., 1986; Klatt et al., 2015), as that in TdM waters (~0.4–1 mM of H₂S). The addition of Diuron as a PS-II inhibitor thus guaranteed the sole occurrence of the PSI-driven anoxygenic photosynthesis by cyanobacteria. Our data showed that, under dark treatment incubations, only the simultaneous addition of Diuron and molybdate decreased demethylation potentials of biofilm MeHg (Figure 3b). In contrast, the addition of Diuron or molybdate, individually, exhibited only slight decreases (< 5%) relative to control conditions (i.e., without inhibitor), respectively.

Previous studies have confirmed the capacities of SRB for MeHg demethylation by field evidence and laboratory pure cultures (Bridou et al., 2011; Marvin-DiPasquale and Oremland, 1998; Pak and Bartha, 1998), thus demethylation rates are expected to decrease after the addition of molybdate (Figure 3b). The small extent of decrease (~5%) is also probably related to the lower activity and abundance of *Desulfocapsaceae* (e.g., 2% of relative abundance) in biofilm (Gentès et al., 2013). With respect to the addition of Diuron, the low inhibitory effect may be due to the altered metabolism of cyanobacteria under dark conditions from anaerobic respiration for sulfur reduction or fermentation, and depending on sulfur availability (Oren and Shilo, 1979; Stal and Moezelaar, 1997). The large decrease in demethylation rates by simultaneously addition of both inhibitors cannot be fully explained by direct inhibition of the targeted metabolisms (i.e., oxygenic photosynthesis and sulfate reduction) potentially relevant to *Cyanobacteria* and *Desulfobacterota*, respectively. Instead, it was suspected that a synergistic effect of biotic and abiotic factors occurred under these highly sulfidic conditions. For instance, the dual addition of inhibitors can possibly terminate the metabolic association between these sulfur-linked bacteria (i.e., *Cyanobacteria* and SRBs) in biofilm under the sulfidic conditions
found in the hot spring. This effect would hamper microbial-specific physiology in both bacterial
groups (carbon and sulfur availabilities) and also modify Hg speciation and uptake to some extent.

4.2.2. *Photobiological effects on MeHg demethylation dynamics*

The inhibition experiments were also performed under visible light conditions (artificial light conditions; see Supplementary Text S4 and Figure S10b) to disentangle the effects of light on the observed MeHg patterns by biofilm microbial communities (i.e., photobiological influence). The increase in demethylation rates in the control group, relative to the dark treatment, possibly suggests an important contribution of photobiological degradation potentially related to enhanced anoxygenic phototrophic activities (i.e., sulfide oxidation) by *Cyanobacteria* and *Chloroflexi*, the only abundant phototrophs detected in biofilm. Only < 5% oxygenic photosynthesis by PSII system of cyanobacteria is expected to occur given that sulfide concentrations are within 0.35–1 mM (i.e., 11.93–34.08 mg L⁻¹) in the TdM system (Stal, 1995). Co-occurrence of sulfur-oxidizing phototrophs, *Cyanobacteria* and *Chloroflexi*, are well-known in aquatic environments such as in hot springs as well as in sulfide-rich lagoons (Bennett et al., 2020; Bhatnagar et al., 2020; Kanno et al., 2019), and photosynthetic activities by *Cyanobacteria* can provide organic substrates to *Chloroflexi* (Kanno et al., 2019).

By adding Diuron, there was no significant influence on observed rates in comparison to the light
control (p > 0.05) (Figure 3b). This pattern was expected, as *Cyanobacteria* is considered to mainly
conduct sulfide-dependent anoxygenic photosynthesis as demonstrated above (Stal, 1995). The sole
addition of molybdate induced ~50% decrease of demethylation rate but not significant relative to the
control group (p > 0.05). This pattern seemingly indicates an insignificant role of SRBs in MeHg
demethylation under light conditions. This finding is, however, in contrast to a recent study suggesting
that molybdate does not affect MeHg demethylation by the pure culture of a sulfate reducer (i.e.,
BerOc1) regardless of metabolism (Scuvée et al., 2024). Notably, the inhibition of SRBs may cause
adverse effects on photosynthesis of cyanobacteria given the role of SRBs in the cryptic sulfur cycle
involving both cyanobacteria and SRBs under sulfidic conditions. Similar to the dark treatment
incubations, addition of both inhibitors significantly limited MeHg demethylation, suggesting the
potential for strong interactions between microorganisms (i.e., *Cyanobacteria*, *Chloroflexi*, and SRB) under visible (PAR) light conditions where photobiological interactions between bacteria may occur.

### 4.3. Environmental implications

Sulfur-linked bacteria, such as those found in this study, are prevalent in both terrestrial and marine hydrothermal systems (Konrad et al., 2023; Zhang et al., 2012). These bacteria play a crucial role in understanding Hg land-sea exchange dynamics and how Hg is transported within, the ocean, via hydrothermal systems. Currently, direct measurements have provided critical insights into Hg speciation and fluxes from marine hydrothermal vents (Torres-Rodriguez et al., 2024), however knowledge gaps still exist regarding the potential for Hg species release and transformations in shallow systems, including phototrophic sulfur-linked bacteria. Our investigation provides valuable insights on the potential transformations of Hg species by specific microbes likely involved in sulfur metabolism (e.g., *Limnotrichaceae* and *Desulfocapsaceae*), in these environments. Additionally, certain sulfur-linked phototrophic microbes, like cyanobacteria, are found in varied environments such as shallow, nutrient-rich lakes (Gkelis et al., 2005; Mayer et al., 1997). Sulfide accumulation, linked to eutrophication and deoxygenation from excessive nutrients from farming and aquaculture, is common in these environments (Zuo et al., 2024). Overall, our findings on the dominant microbial MeHg degradation pathway significantly advances our understanding of Hg species distributions in these sulfidic environments.

### 4.4. Study Limitations

As initial exploratory research in this area, our study employed incubation experiments that did not account for kinetic temporal changes in Hg species. This approach may overlook intermediate transformation processes, such as the formation and re-oxidation of DGM species (e.g., Hg⁰) during biofilm MeHg degradation, potentially leading to an underestimate of the extent of reductive MeHg demethylation. Therefore, high-resolution kinetic incubation studies on biofilms with timely DGM species isolation are crucial to provide a more mechanistic understanding of these processes.

Moreover, the use of 16S rDNA for assessing microbial diversity does not reflect the entire functional capabilities of microbial communities, and employing metagenomic approaches may provide a more
comprehensive evaluation of microbial function (Capo et al., 2023). Alternatively, it is preferable to
concomitantly measure isotopic composition and concentrations of sulfur species for a thorough
investigation of microbial sulfur cycling, including oxidation and reduction processes (Margalef-Marti
et al., 2023). Integrating these types of data with kinetic Hg transformation rates in incubation
experiments would likely enhance our understanding of the microbial-driven, Hg species dynamics in
sulfidic hot springs.

5. CONCLUSIONS

The formation and degradation of MeHg in aquatic ecosystems is relatively well studied, yet important
questions remain unresolved regarding abiotic, microbial, and other biotic factors governing the
methylation-demethylation processes. Sulfidic hot springs are model systems for studying microbial
transformations of Hg species, including iHg methylation; however, these processes in these systems
remain understudied. Our research highlights the role of sulfur-linked bacteria as a dominant MeHg
demethylation pathway within sulfidic, hot spring ecosystems with non-toxic amounts of Hg species.
The rapid turnover of MeHg, driven by both photochemical and microbial processes across different
ecosystem compartments of the hot spring (e.g., water and biofilm), demonstrates the dynamic cycling
processes of MeHg in these extreme systems. Thus, this study provides a strong foundation for
understanding the fate, transport, and transformations of Hg species in hot, sulfidic, aquatic systems
dominated by phototrophic activities.

ACKNOWLEDGMENTS

This work has been supported by Université de Pau et de Pays de l'Adour (UPPA) in the framework of
the Energy Environment Solutions (E2S-UPPA) initiative of excellence (I-SITES, PIA France) for the
Scientific Hub 'Metals in Environmental Systems Microbiology (MeSMic)' and by the French
National Programme EC2CO (Hybige) in the context of the Fe/N-ICS project. We extend our gratitude
to Céline Lavergne for her valuable suggestions during the preparation of this manuscript. J. X.
acknowledges the doctoral fellowship funded by I-site E2S UPPA. R.M.M. is grateful to the Spanish
Government and University of Barcelona for the awarded Margarita Salas grant (Next Generation EU
funds).

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<figure><img src="image_4.png" /><figcaption>**Figure 1.** Relative microbial abundance at the phylum level in biofilms and the sediment from November 2021 and June 2022 with (a) and without (b) showing cyanobacteria in the TdM hot spring. Potential phyla containing iHg methylators: *Chloroflexi*, *Bacteroidota*, *Desulfobacterota*, *Pseudomonadota*, *Spirochaetota*, *Planctomycetota*, *Actinobacteriota*, *Firmicutes*, and *Verrucomicrobiota* (Capo et al., 2022; Jones et al., 2019; Leclerc et al., 2021; Peterson et al., 2020; Xu et al., 2021). Potential phyla containing MeHg de-methylators: *Cyanobacteria* and *Desulfobacterota* (Bridou et al., 2011; Cossart et al., 2021; Liang et al., 2023).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>**Figure 2.** Concentrations of iHg and MeHg, as well as the MeHg percentage (%MeHg) in waters (represented by backward diagonals) (a–c), and in biofilms (represented by triangles) / sediments (represented by forward diagonals) (d–f). Samples from October 2021, June 2022, and April 2023 are marked in green, tawny, and blue, respectively. *n.a.*: not analyzed. Data are also complied in Table S4.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 3.** Methylation (a) and demethylation (b) rates as well as MeHg loss (c) from the inhibition experiments (n = 3 for all treatments) performed under dark and light conditions by using 20 µM Diuron and 20 mM Na-molybdate for the upstream biofilm collected from April 2023. Transformation rates were calculated from experimental triplicates (n = 3). Uncertainty propagation is applied when calculating the standard deviation. DL: detection limit. Different superscript letters signify statistically significant differences (p < 0.05) in transformation rates determined by one-way ANOVA and Tukey's multiple comparison test. Note that the test is only performed *within* dark or light groups; comparing differences between these groups is not meaningful. Data are also complied in Table S6.</figcaption></figure>
<figure><img src="image_7.png" /></figure>

**Figure 4.** The MeHg balance estimated for the upstream water-biofilm system in 2023 when minimal disturbance was expected. The amount of MeHg (ng d⁻¹) formed (in green) or loss (in red) was calculated by assuming a 1-m³ water mass where biofilm occupies a bottom 1-m² area with a thickness of 0.5 cm, as typically observed in the field (Figure S3). The half-life of MeHg (MeHg<sub>t[1/2]</sub>) is calculated considering the net MeHg degradation rates. *Note that Hg transformation rates were measured in water under sunlight, whereas biofilm rates were assessed under visible light to examine photobiological effects (see Supplementary Text S4). Detailed information on the calculations of MeHg amounts, along with relevant ambient levels and transformation rates, is presented in Figure S8.
<table><caption>**Table 1.** A brief summary of all incubation experiments conducted in this study. <sup>21</sup>November 2021, <sup>22</sup>June 2022, <sup>23</sup>April 2023.</caption><thead><tr><th>Incubation matrix</th><th>Treatments and times</th></tr></thead><tbody><tr><td>Water<sub>spring pool</sub></td><td>Darkness conditions<sup>21,22,23</sup><br>Sunlight conditions<sup>23</sup></td></tr><tr><td>Water<sub>upstream, midstream</sub></td><td>Darkness conditions<sup>21</sup></td></tr><tr><td>Biofilm<sub>upstream</sub></td><td>Darkness conditions<sup>21,22,23</sup><br>Control experiments I<sup>22</sup>, II–III<sup>23</sup></td></tr><tr><td>Sediment<sub>downstream</sub></td><td>Darkness conditions<sup>21,22</sup></td></tr></tbody></table>
**Table 2.** Methylation, demethylation rates (% h⁻¹) of Hg species as well as MeHg loss in water, biofilm, and sediment incubations (darkness conditions) across sampling seasons. Note that transformation rates were calculated from experimental triplicates (n = 3). *light*: spring pool water incubation under sunlight conditions. Uncertainty propagation is applied when calculating the standard deviation (values in brackets if applicable). DL: detection limit. *n/a.*: not applicable.

<table><thead><tr><th rowspan="2">Matrix</th><th rowspan="2">Sampling time</th><th colspan="3">iHg methylation (% h<sup>-1</sup>)</th><th colspan="3">MeHg demethylation (% h<sup>-1</sup>)</th><th colspan="3">MeHg loss (% h<sup>-1</sup>)</th></tr><tr><th>Nov. 2021</th><th>Jun. 2022</th><th>Apr. 2023</th><th>Nov. 2021</th><th>Jun. 2022</th><th>Apr. 2023</th><th>Nov. 2021</th><th>Jun. 2022</th><th>Apr. 2023</th></tr></thead><tbody><tr><td rowspan="4">Water</td><td>Spring pool</td><td>0.02 (0.02)</td><td>&lt; DL</td><td>&lt; DL</td><td>0.08 (0.12)</td><td>0.06 (0.06)</td><td>&lt; DL</td><td>0.90 (0.42)</td><td>0.27 (0.63)</td><td>&lt; DL</td></tr><tr><td>Spring pool <sup>light</sup></td><td>n./a.</td><td>n./a.</td><td>&lt; DL</td><td>n./a.</td><td>n./a.</td><td>9.11 (1.28)</td><td>n./a.</td><td>n./a.</td><td>8.68 (3.30)</td></tr><tr><td>Upstream</td><td>0.002 (0.009)</td><td>n./a.</td><td>n./a.</td><td>0.18 (0.07)</td><td>n./a.</td><td>n./a.</td><td>1.13 (0.19)</td><td>n./a.</td><td>n./a.</td></tr><tr><td>Midstream</td><td>0.01 (0.02)</td><td>n./a.</td><td>n./a.</td><td>0.04 (0.04)</td><td>n./a.</td><td>n./a.</td><td>1.05 (0.11)</td><td>n./a.</td><td>n./a.</td></tr><tr><td>Biofilm</td><td>Upstream</td><td>0.001 (0.001)</td><td>0.002 (0.004)</td><td>0.001 (0.001)</td><td>3.95 (0.59)</td><td>0.14 (0.08)</td><td>1.61 (0.62)</td><td>3.16 (0.67)</td><td>0.33 (0.25)</td><td>2.26 (0.67)</td></tr><tr><td>Sediment</td><td>Downstream</td><td>0.002 (0.002)</td><td>0.002 (0.006)</td><td>n./a.</td><td>1.92 (0.53)</td><td>0.55 (0.24)</td><td>n./a.</td><td>1.09 (0.94)</td><td>0.83 (1.96)</td><td>n./a.</td></tr></tbody></table>

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