and hydrometallurgical recycling processes are the safety conditions for operators, operations at atmospheric pressure and room temperature, lower chemical and energy consumption, lower CO₂ emissions, and low initial investments (Baniasadi et al., 2019). Over the last decade, bioleaching of PCBs has been investigated at the research level in shake flasks (Adhapure et al., 2013; Arshadi and Mousavi, 2015; Bryan et al., 2015; Guezennec et al., 2015) and stirred tank reactors (STR) with capacities above 1 L (Ilyas and Lee, 2014; Guezennec et al., 2015; Mäkinen et al., 2015; Xia et al., 2017; Hubau et al., 2020).

Microorganisms employed in the bioleaching of PCBs are diverse, with both autotrophs (Xiang et al., 2010) and heterotrophs (Chi et al., 2011) and mesophilic and thermophilic (Ilyas et al., 2007) species. Chemolithotrophs acidophilic iron-oxidizing bacteria (FeOB) stand out among the group of microorganisms most frequently studied for dissolving metals (Xiang et al., 2010; Işıldar et al., 2019; Hubau et al., 2020). Ferric iron and sulfuric acid act as oxidizing agents to mobilize the metals from the solid matrix (Eqs 1, 2). FeOB uses the resulting Fe(II) as a source of energy to regenerate the ferric iron in the presence of dissolved oxygen (Eq. 3), which accelerates the bioleaching process.

$$nFe^{3+} + Me \rightarrow n Fe^{2+}Me^{n+} \quad (1)$$

$$nMe + 2nH^{+} + 0.5n O_{2} \rightarrow nMe^{n+} + nH_{2}O \quad (2)$$

$$2Fe^{2+} + 0.5O_{2} + 2H^{+} \xrightarrow{\text{Bacteria}} 2Fe^{3+} + H_{2}O \quad (3)$$

*Leptospirillum* can potentially thrive in bioleaching environments as they have a greater capacity for iron oxidation activity than other FeOBs (Rawlings et al., 1999; Kinnunen and Puhakka, 2004; Rawlings, 2005; Bryan et al., 2011; Guezennec et al., 2015). These acidophilic and moderately thermophilic species are highly resistant to environments containing high concentrations of Fe(III) and can survive high concentrations of other metals (Dopson and Holmes, 2014). Dopson and Holmes (2014) describe possible passive and active mechanisms these microorganisms might use to grow in the presence of a high metal content. *Leptospirillum ferriphilum* is a dominant FeOB in industrial continuous-flow biooxidation tanks for mineral extraction (Rawlings et al., 1999; Coram and Rawlings, 2002). These Gram-negative bacteria have a large number of genes related to heavy metal detoxification, oxidative stress defense, DNA repair, pH tolerance to acidic environments, and signal transduction to adapt to the external environment (Mi et al., 2011). However, one of the major challenges in PCB bioleaching remains the inhibiting effects of the waste material on the metabolism of these microorganisms (Guezennec et al., 2015; Wu et al., 2018; Arya and Kumar, 2020). PCBs can slow down/delay microbial growth and reduce microbial capacity to oxidize iron (Edward et al., 2018). Consequently, the regeneration of Fe(III) decreases along with leaching rates. It is not clear whether the toxic effect results from the metal content, the organic content of PCBs, or both (Bryan et al., 2015; Baniasadi et al., 2019). Yang et al. (2014) suggest that Pb, Ni, and plastics have

inhibiting effects on bacterial growth, but it is not evident whether there is a main limiting factor. Besides, a synergy between different metal ions can increase the level of toxicity compared to the individual effect of each metal, as described by Nurmi et al. (2009). Finally, damage to bacterial cells can also result from attrition of the bacterial membrane by solid particles (Haghshenas et al., 2009).

Different strategies have been proposed to tackle the toxicity effect of PCB bioleaching processes. The first strategy consists of separating biogenic Fe(III) production from the PCB leaching (Brandl et al., 2001; Zhu et al., 2011; Guezennec et al., 2015; Wang et al., 2018; Hubau et al., 2020), which alloys microorganisms to thrive in a system without the toxic effect of PCBs. This strategy can be employed in continuous flow bioreactors to achieve high bioleaching efficiencies over short periods. Hubau et al. (2020) showed high PCB bioleaching efficiency in steady-state conditions within 48 h and 1% (w/v) PCBs. However, a long transitional regime of several months was required to achieve high and stable microbial activity.

The second strategy seeks to adapt microorganisms to the toxic waste material to improve the iron-oxidizing activity and trigger leaching efficiency (Rawlings, 2005; Haghshenas et al., 2009; Yang et al., 2009, 2014; Hubau et al., 2020). A typical method involves subculturing in a specific environment. Serial subculturing can, for instance, enhance tolerance to a high metal content and improve microbial iron oxidation activity (Bryan et al., 2011; Liu et al., 2019). The period before the microbial oxidation of iron, referred here as the pre-oxidation phase, can be used as an indicator of microbial iron oxidation activity (Das et al., 1998; Haghshenas et al., 2009). This pre-oxidation phase reflects the time required for bacteria to start actively catalyzing iron oxidation. In this sense, it is possible to estimate the evolution of bacterial tolerance to PCBs by means of serial subcultures following the pre-oxidation phase.

The main objective of this study was to investigate the capacity of FeOB cultures dominated by *L. ferriphilum* to grow and improve the iron oxidation kinetics in PCB-enriched environments. The inhibiting effects of PCBs on microorganisms were covered (i) by studying the inhibiting effect of chemically dissolved PCB metals on the microbial growth and activity of a FeOB culture in shake flasks and (ii) by investigating the microbial growth and oxidizing activity of two cultures referred to as “adapted” and “non-adapted” in a batch STR at different PCB solid loads. Strategies to tackle this inhibition were then investigated. They rely on (i) successive subcultures in batch mode and (ii) different operational modes to reach the steady state in continuous mode, as fast as possible and with high microbial activity.

# MATERIALS AND METHODS

## Bacterial Culture

This study used two FeOB cultures, referred to here as “adapted” and “non-adapted” cultures. Both come from a two-step bioprocess for PCB bioleaching, which is fully described
in previous studies (Hubau et al., 2018, 2020). The non-adapted culture, which came from a 150-mL bio-oxidation aerated column, run in continuous mode and inoculated with an acidophilic FeOB culture, showed highly efficient oxidation of Fe(II) at 1 g L⁻¹ h⁻¹, but was never in contact with PCBs. This culture was mainly made up of *L. ferriphilum* and *Sulfobacillus benefaciens*, with *L. ferriphilum* being the predominant species (Hubau et al., 2018). This ferric iron-rich lixiviant was used to feed a PCB-bioleaching STR, operated in continuous mode with 1% (w/v) PCBs for over 4 months at a hydraulic retention time (HRT) of 48 h. The adapted culture came from a leachate of the bioleaching reactor. High metal dissolution yields and rates were obtained under these conditions (Hubau et al., 2020). *L. ferriphilum* was the predominant bacterium in both cultures (Hubau et al., 2018, 2020).

The 0Cm medium used in this study is derived from 0Km with a reduced (NH₄)₂SO₄ concentration (Hubau et al., 2018) and has previously enabled a robust performance of Fe(II) bio-oxidation in the aerated column and a high bioleaching yield in the STR (Hubau et al., 2020). This medium is composed of 0.4 g L⁻¹ (NH₄)₂SO₄ (extra pure, Merck, Darmstadt, Germany), 0.81 g L⁻¹ H₃PO₄ (analytical grade, Merck), 0.48 g L⁻¹ KOH (pure pellets, Merck), and 0.52 g L⁻¹ MgSO₄·7H₂O (analytical grade, Merck). The medium was supplemented with 3 g L⁻¹ of Fe(II) as FeSO₄·7H₂O (99+%, Acros Organics, Fair Lawn, NJ, United States) and was thus denoted 3Cm. The pH was adjusted to 1.2 with H₂SO₄ (>95%, analytical grade, Fisher Chemical, Waltham, MA, United States).

## PCB Composition and Preparation

Samples of low-grade PCBs were collected from small appliances at the Envie 2E Midi-Pyrenees WEEE sorting center (France). Preparation of the PCBs and determination of the metal composition are fully described in Hubau et al. (2019). Briefly, the PCBs were shredded to reduce the particle size below 750 µm (750 µm corresponding to the mesh size of the shear shredder Bohmier Maschinen GmbH) and a laboratory knife mill (Retsch, 2000). Table 1 shows the metal composition of the samples (Hubau et al., 2019).

<table><caption>TABLE 1 | Element composition in % weight of low-grade PCB samples.</caption><thead><tr><th>Element</th><th>Concentration (% weight)</th><th>Element</th><th>Concentration (% weight x 10<sup>-5</sup>)</th></tr></thead><tbody><tr><td>Cu</td><td>14.58</td><td>Cr</td><td>842</td></tr><tr><td>Fe</td><td>12.23</td><td>Co</td><td>358</td></tr><tr><td>Al</td><td>6.04</td><td>Ag</td><td>209</td></tr><tr><td>Zn</td><td>1.67</td><td>Mo</td><td>152</td></tr><tr><td>Sn</td><td>1.67</td><td>In</td><td>100</td></tr><tr><td>Pb</td><td>1.17</td><td>Au</td><td>44</td></tr><tr><td>Mn</td><td>0.61</td><td>Pd</td><td>25</td></tr><tr><td>Ni</td><td>0.34</td><td>V</td><td>22</td></tr><tr><td>Sb</td><td>0.20</td><td>W</td><td>15</td></tr><tr><td>Mg</td><td>0.14</td><td>Ga</td><td>12</td></tr><tr><td></td><td></td><td>Ta</td><td>7.5</td></tr><tr><td></td><td></td><td>Ge</td><td>0.75</td></tr><tr><td></td><td></td><td>Pt</td><td>0.59</td></tr></tbody></table>

A solution of dissolved PCB metal ions was prepared by abiotic chemical leaching of 10% (w/v) PCBs in a stirred tank bioreactor with a working volume of 2.2 l. The setup of the STR was previously presented by Hubau et al. (2020). The chemical leaching was performed in the 0Cm culture medium with 10 g L⁻¹ of Fe(III) added as Fe₂(SO₄)₃·xH₂O as a leaching agent in sulfuric acid media and adjusted to pH 1.2 with H₂SO₄ (>95%, analytical grade, Fisher Chemical). An airflow rate of 90 L h⁻¹ injected beneath the turbine at the bottom of the reactor via a stainless-steel pipe provided with surplus oxygen to facilitate the leaching of metals. A dual (axial/radial) impeller system in stainless steel ensured the mixing of gas, liquid, and solids with a stirring speed of 650 rpm. The temperature of the reactor was maintained at 35°C with a thermostatic bath (Lauda), and the pH was daily adjusted to 1.2 with H₂SO₄ until the end of the experiment. Once the metal concentrations were stable (see section “Analytical Techniques”), the solution was filtered.

## Microbial Performance at Different Concentrations of PCB Leachate

The microbial growth and activity of the adapted culture were evaluated in 100-mL (working volume) shake flasks. The experiments contained 20% (v/v), 40% (v/v), 60% (v/v), or 80% (v/v) of the chemical PCB leachate (Table 2), which represented the equivalent of 2, 4, 6, and 8% of PCBs, respectively. Each flask had 10% (v/v) inoculum, the 0Cm culture medium (supplemented with a 10-fold solution of concentrated nutrients), and 8 g L⁻¹ Fe(II) (adjusted with a 10-g L⁻¹ Fe(II) solution). All solutions were adjusted to pH 1.2 at the beginning of the experiments. The experiments were run in triplicate, with two control duplicates: 10% (v/v) inoculum without PCB leachate, and uninoculated 80% (v/v) PCB leachate. The cultures were incubated in a rotary shaker at 107 rpm and 35°C. The initial microbial concentration was 10⁷ cells mL⁻¹. Experiments were run for 25 days, with pH, redox potential, and bacterial concentration monitored daily (See section “Analytical Techniques”). Water losses by evaporation were compensated with sterile distilled water.

## Microbial Performance During Bioleaching at Different Concentrations of Solid PCBs

The microbial growth and iron oxidation activity of the adapted and non-adapted cultures were evaluated in a 2.2-L STR with shredded solid PCBs at 1% (w/v) or 2% (w/v) in batch mode. First, bacteria were inoculated at 10% (v/v) in 3Cm medium (containing 3 g L⁻¹ Fe(II) and acidified to pH 1.2) without PCBs. This step ended when the redox potential reached values above 800 mV [adjusted to be relative to a standard hydrogen electrode (SHE)], i.e., when Fe(II) was oxidized (See section “Analytical Techniques”). PCBs were subsequently added at either 1% (w/v) PCBs or 2% (w/v) PCBs. pH was daily adjusted to 1.2 ± 0.1 with concentrated H₂SO₄. pH, redox potential, planktonic cell concentration, and metal concentration were monitored over time.
<table><caption>TABLE 2 | Metal concentration of the chemical PCB leachate used to test the microbial performance in shake flasks.</caption><thead><tr><th>Element</th><th>Concentration (g L<sup>-1</sup>)</th><th>Element</th><th>Concentration (g L<sup>-1</sup>)</th><th>Element</th><th>Concentration (g L<sup>-1</sup>)</th></tr></thead><tbody><tr><td>Cu</td><td>15.2</td><td>Mg</td><td>0.069</td><td>Pb</td><td>0.006</td></tr><tr><td>Fe</td><td>12.8</td><td>Mn</td><td>0.046</td><td>Co</td><td>0.006</td></tr><tr><td>Al</td><td>3.89</td><td>Sn</td><td>0.022</td><td>V</td><td>0.001</td></tr><tr><td>Zn</td><td>2.21</td><td>Cr</td><td>0.008</td><td>Sb</td><td>0.001</td></tr><tr><td>Ni</td><td>0.22</td><td></td><td></td><td></td><td></td></tr></tbody></table>

Leaching conditions: 10% (w/v) PCBs, 10 g L⁻¹ Fe, Ag, Au, Mo, In, Pd, W, Ga, Ta, Ge, and Pt were below the detection limit (1 µg L⁻¹).

The same reactor used for the chemical leaching of PCBs was employed for these experiments. An air flow of 60 L h⁻¹ enriched with 1% CO₂ was maintained, to ensure the carbon supply for microbial growth and iron oxidation activity (Guezennec et al., 2018). STR stirring speed was set at 650 rpm, and the reactor was maintained at 35°C.

## Subculturing Protocol in STR

The subcultures were studied in a two-step process, similar to the one described in the previous section, in the 2.2-L STR configuration in batch mode.

In the first experiment (S0), the batch reactor was inoculated with 10% (v/v) of the adapted culture in a 3Cm medium as first step. This step ended when the redox reached values above 800 mV vs. SHE. In the second step, 2% (w/v) PCBs were added to the reactor and the pH was daily adjusted to 1.2 with concentrated H₂SO₄. The test was ended when the redox again reached values above 800 mV vs. SHE. The subculture batch reactors were inoculated with 10% (v/v) from the previous test into a 3Cm medium, and the protocol as in S0 was repeated. A diagram of the subculture procedure is presented in Figure 1. Subcultures named S1 and S2 were successively inoculated with an interval of 1–2 days between subcultures to assure that stable conditions were reached. After the second subculture (S2), the culture was stored at room temperature in a hermetic and sterile plastic vessel for 10 days in a basement without light. Subsequently, subcultures S3, S4, and S5 were carried out as in S0. Bacterial cells at the beginning and at the end of each experiment were counted in an optimal microscope as detailed in the section “Analytical Techniques.” This quantitative method was as indicator of microbial growth. No changes were observed in the bacterial concentration after the storage period.

## Start-Up Scenarios in Continuous Mode

For these experiments, we employed a two-stage bioleaching process in continuous flow. The first stage is the aerated column with non-adapted bacteria feeding the 2.2-L STR containing the PCBs as the second stage. The aerated column contained a solid support on polypropylene for bacterial growth, while no support was included in the second stage (PCB bioleaching STR). The setup is described in detail in a previous study (Hubau et al., 2020). Three scenarios were proposed to evaluate the microbial iron oxidation activity during the start-up of the continuous process and to determine a strategy to reach the steady state as fast as possible.

In the first scenario (I), the 2.2-L STR reactor was progressively filled with the ferric iron lixiviant (generated in the aerated column), containing non-adapted bacteria and 3 g L⁻¹ of Fe(III) at redox potential above 800 mV vs. SHE. The output flow from the aerated column continuously fed the STR at 47 mL h⁻¹ with a pump to maintain an HRT of 48 h. PCBs were added once per hour at 0.45 g h⁻¹ to maintain a PCB load of 1% (w/v). Agitation started after 24 h. After 48 h, when the working volume reached 2.2 L, pumping of the effluent began.

In the second scenario (II), a test in batch mode was performed with adapted bacteria as described in the subculturing protocol. The batch had 10% (v/v) inoculum in a 3Cm medium, and the equivalent of 1% (w/v) PCBs was loaded once the redox reached over 800 mV vs. SHE. The continuous-flow bioleaching mode started at the end of this batch with the total pulp in the reactor. The aerated column effluent and PCBs fed the reactor continuously at 48 h of HRT and 1% (w/v) PCBs as in the first scenario.

In the third scenario (III), an initial bioleaching batch process was performed with 10% (v/v) of the adapted bacteria and 2% (w/v) PCBs, followed by two successive batch subcultures. Each subculture was inoculated with 50% (v/v) from the previous batch. The other 50% volume contained 3Cm. One percent (w/v) of PCBs was added after the redox rose above 800 mV vs. SHE in each subculture. After the second subculture, the continuous-flow mode started. As in scenarios I and II, the reactor worked with an HRT of 48 h and 1% (w/v) PCBs and was fed with non-adapted bacteria from the aerated column.

All the bioleaching reactors in batch and continuous-flow modes operated at 35°C, with an airflow enriched with 1% CO₂ of 60 L h⁻¹, and agitation at 650 rpm. The pH was maintained lower than 1.6 to avoid Fe(III) precipitation. The start-up phase was considered finished when the redox potential maintained values above 800 mV vs. SHE in continuous mode for at least two HRT.

## Analytical Techniques

The pH values and redox potentials were monitored daily for all experiments with pH (IDS SenTix® 940) and redox (BlueLine 32-3 RX IDS) electrodes, respectively, both connected to a multiparameter portable meter (Multi 3630 IDS, WTW). Metals were analyzed with a Varian SpectrAA 300 flame atomic absorption spectroscope (FAAS). The oxidation of iron was deduced from the correlation of Yue et al. (2016) expressed in Eq. 4. This involves the redox potential (Eh in mV vs. SHE), the temperature (T in K), the number of electrons exchanged (n), the gas constant (R = 8.3 J K⁻¹ mol⁻¹) and the Faraday
<figure><img src="image_108.png" /><figcaption>**FIGURE 1** | Scheme of the successive subculturing procedure applied on 2.2 L-STR in batch conditions. Each culture contained 3Cm medium and 2% (w/v) PCBs.</figcaption></figure>

constant (F = 96485 C mol⁻¹), and the concentration of Fe ([Fe] in mg L⁻¹).

$$Eh \ 10^{-3}x[T]^2 + 0,91T + 2,303 \times 10^3 \frac{RT}{nF} \log \frac{[Fe(III)]}{[Fe(II)]} + 492 \quad (4)$$

To estimate the microbial growth, 20-µL samples of the leachate were placed in a Thoma cell counting chamber and observed through an optical microscope at ×400 magnification. This technique shows the growth tendency of planktonic bacteria. The diversity of the bacterial (or prokaryotic) consortium was characterized using the capillary electrophoresis single-strand conformational polymorphism (CE-SSCP) molecular fingerprinting technique on the 16S rRNA gene encoding, using the protocol described by Hubau et al. (2018).

# RESULTS

## Microbial Performance at Different Leachate Concentrations

These experiments performed in shake flasks aimed to characterize the bacterial performance of the adapted FeOB culture in PCB environments. The PCB environment was reproduced from a concentrated PCB leachate, whose metal concentration is detailed in Table 2. The data show that the PCB leachate contained mainly Cu, Fe, Al, Zn, and Ni. A wide range of other metals was present in concentrations below 100 mg L⁻¹.

The effect of increased concentrations of metal-rich PCB leachates on bacterial growth and Fe(II)-oxidizing activity is presented in Figure 2. Figure 2A shows that the lag phase lasted longer at increased concentrations of PCBs, with 1 day at 20% (v/v) of PCB leachate, 2 days at 40% (v/v) of PCB leachate, and 7 days at 60% (v/v) of PCB leachate. Starting from 10⁷ cells mL⁻¹, the bacterial concentration increased exponentially and reached a stationary phase at 10⁸ cells mL⁻¹ in conditions containing up to 60% (v/v) of PCB leachate. A similar behavior was observed in the biotic control without dissolved PCBs, which had a lag phase of 1 day. The control assay with 80% (v/v) of leachate (corresponding to 8% of PCBs) did not present a microbial growth over the 25 days of experiments, as verified through bacterial counting.

Figure 2B shows that the redox potential increased simultaneously with the exponential microbial growth when the solutions contained 20% (v/v) to 60% (v/v) of PCB leachate. The duration of the lag phase and the pre-oxidation phase were equal under these conditions, indicating that substrate oxidation and microbial growth were correlated. At the end of the pre-oxidation phase, the redox increased exponentially

from less than 650 mV vs. SHE to more than 900 mV vs. SHE in at most 2 days. This redox behavior can be attributed to the iron oxidation catalyzed by microorganisms and continued to a plateau, which corresponds to a complete oxidation of iron according to Eq. 4. In the biotic control without leachate, the microbial iron oxidation and the stationary microbial growth phase took 1 day longer than in the assay with 20% (v/v) of PCB. At 80% (v/v) of PCB leachate, the redox gradually increased over time, representing 37% of iron oxidized in 25 days regardless of the presence of bacteria. Therefore, no bacterial growth or iron oxidation related to the microbial iron oxidation activity were found during this period at 80% (v/v) of PCB leachate.

Despite the delay of 7 days in microbial growth and iron oxidation activity, the culture thrived in a medium with a concentration of metals six times higher than in the medium to which they were initially adapted. Based on the initial leachate concentration (Table 2), the solution at 60% (v/v) of PCB leachate contained 9 g L⁻¹ Cu, 2 g L⁻¹ Al, 1 g L⁻¹ Zn, 0.1 g L⁻¹ Ni, 10 mg L⁻¹ Pb, and 4 mg L⁻¹ Co, among other elements. According to the molecular fingerprinting test, *L. ferriphilum* is the predominant species whatever the leachate concentration, as in the test with no leachate (Supplementary Figure 1). This confirms the capacity of *L. ferriphilum* to grow and oxidize iron at high concentrations of mixed metals and other elements.

## Effects of Solid PCBs on Microbial Performance During Bioleaching

The purpose of these experiments was to investigate the inhibiting effect of solid PCBs on the microbial growth and pre-oxidation phase. In the experiments, metal leaching (Eqs 1, 2) and the microbial oxidation of Fe(II) to regenerate Fe(III) as a leaching agent (Eq. 3) occurred in the same reactor.

Table 3 presents the final planktonic cell concentration and the duration of the pre-oxidation phase of cultures in the presence of 1% (w/v) PCBs and 2% (w/v) PCBs. The tendency of planktonic bacteria to grow in bioreactors with 2% (w/v) PCBs seems higher compared to reactors with 1% (w/v) PCBs. There could be an increased supply of iron for microbial growth thanks to the iron dissolution from 2% (w/v) PCBs. However, this result must be considered carefully since the addition of PCBs may interfere with the counting of bacterial cells. Besides, a considerable proportion of biomass can attach to the solids. The effects of PCB load on microbial growth were therefore difficult to measure in these conditions.

On the other hand, the increase in the PCB load prolonged the pre-oxidation phase, as in the previous experiments with the PCB leachates (Figure 2). The onset of microbial iron oxidation
<figure><img src="image_109.png" /></figure>

<figure><img src="image_110.png" /><figcaption>**FIGURE 2** | Microbial activity at various concentrations of the chemical leachate produced with 10% (w/v) PCBs: (A) Bacterial concentration and (B) redox potential. The experiments were performed in shake flasks and started with 8 g L⁻¹ Fe(II) and 10⁷ cells mL⁻¹. The error bars represent the range of all values obtained under fixed operating conditions. Additional information on experiments with 80% (v/v) leachate the abiotic control is available up to day 25, although no significant changes in either redox behavior or bacterial concentration were observed.</figcaption></figure>

<table><caption>**TABLE 3** | Final planktonic cell concentration and duration of the pre-oxidation phase in 2.2-L STR PCB bioleaching reactors in batch mode.</caption><thead><tr><th rowspan="2"></th><th colspan="2">Non-adapted culture</th><th colspan="2">Adapted culture</th></tr><tr><th>1% (w/v) PCB</th><th>2% (w/v) PCB</th><th>1% (w/v) PCB</th><th>2% (w/v) PCB</th></tr></thead><tbody><tr><td>Final planktonic cell concentration (cells mL<sup>-1</sup>)</td><td>10<sup>7</sup></td><td>6 × 10<sup>7</sup></td><td>3 × 10<sup>7</sup></td><td>10<sup>8</sup></td></tr><tr><td>Pre-oxidation phase during PCB bioleaching (days)</td><td>>16<sup>a</sup></td><td>29</td><td>11</td><td>18</td></tr></tbody></table>

took 11 days at 1% (w/v) PCBs and 18 days at 2% (w/v) PCBs with the adapted culture (Supplementary Figure 2). This pre-oxidation phase took consistently longer compared to the shake flask tests containing PCB leachates (Figure 2). Despite the different configuration, the presence of solids in the bioleaching experiments may have affected the microbial iron oxidation due to the presence of toxic solid elements such as plastics, resins, and heavy metals.

The evolution of metal concentration and dissolution yield over time is presented in Supplementary Figure 3. The bioleaching system took 7 days to reach a maximum dissolution

yield of 100% Cu, 70% Ni, and 100% Zn, regardless of the solid load and the microbial culture. Leachates of 1% (w/v) PCBs reached a maximum of 2.6 g L⁻¹ Cu, 30 mg L⁻¹ Ni, and 303 mg L⁻¹ Zn, whereas leachates of 2% (w/v) PCBs contained up to 4.2 g L⁻¹ Cu, 52 mg L⁻¹ Ni, and 543 mg L⁻¹ Zn. The leachates started with 3 g L⁻¹ Fe coming from the 3Cm medium and reached up to 3.3 g L⁻¹ Fe at 1% (w/v) PCBs and 3.6 g L⁻¹ Fe at 2% (w/v) PCBs. The dissolution yield of Fe appears low (below 20%), but it did not consider Fe precipitation (Chen et al., 2015; Hubau et al., 2020).

<footnote>ªNo exponential rise of the redox observed in 16 days.</footnote>

<footnote>The planktonic cell concentration before the addition of PCBs was 10⁷ cells mL⁻¹.</footnote>
## Subculturing of Bacteria From PCBs Bioleaching in Batch Conditions

The subculturing experiments in the 2.2-L STR were carried out with the adapted culture to improve the microbial capacity to oxidize iron in PCB environments by shortening the pre-oxidation phase. Each subculture initially contained $10^7$ cells mL$^{-1}$ and led to a final concentration of $10^8$ cells mL$^{-1}$ (for S0, S1, S2) and $2 \times 10^8$ cells mL$^{-1}$ (S3, S4, and S5). The bacterial concentration in the liquid phase increased exponentially in the first step (absence of PCBs) and continued to grow slowly afterward with no well-defined lag or exponential phases (Supplementary Figure 4).

Figure 3 shows the redox behavior of each subculture during the first stage with 3Cm medium and the second stage with the PCBs. The reference point or day 0 is considered to be the moment when 2% (w/v) PCBs were added to the system. Before that reference point, the redox increased from 600 mV vs. SHE to over 900 mV vs. SHE within 3–7 days depending on the subculture. At this point, 3 g L$^{-1}$ of Fe were in ferric form. Drops in redox potential of around 400 mV were observed in every batch within the first hour after adding PCBs, indicating that Fe(III) was being reduced. Subsequently, a gradual increase in redox was followed by an exponential rise and a plateau phase as in the presence of PCB leachates without solids (Figure 2). All the subcultures showed an exponential rise of 250–300 mV in approximately 2 days, reaching values close to 900 mV vs. SHE. At the plateau phase, iron was considered to be completely oxidized.

After the addition of PCBs, the subcultures improved the bio-oxidation of Fe(II) by shortening the pre-oxidation phase over time. This decreased from 18 days for the first batch (S0), to 13 for the first subculture (S1), then 7 days for the second subculture (S2), as shown in Figure 3A. The pre-oxidation phase for S2 was therefore 2.6 times faster than for S0. Subsequently, the effect of storing the culture between two subcultures was tested with a 10-day pause between S2 and S3 (Figure 1). The pre-oxidation phase of S3 lasted longer (11 days), but further subcultures S4 and S5 were able to reduce this pre-oxidation phase to 10 and 7 days, respectively (Figure 3B). A similar pattern was observed in the first stage, but no pre-oxidation phase values are given since the redox was not monitored every day.

The evolution of the metal content in the leachate (Supplementary Figure 5) showed a maximum dissolution yield after 7 days as in the previous experiments, regardless of the subculture. At the end of the experiments, the leachate contained, on average, 4.5 g L$^{-1}$ Cu, 50 mg L$^{-1}$ Ni, and 550 mg L$^{-1}$ Zn, among other elements.

## Start-Up Scenarios in Continuous Mode

Continuous mode enables complete dissolution of PCB metals in a short time (less than 48 h) once the bacteria adapted to the bioleaching environment (Hubau et al., 2020). However, microbial adaptation to PCBs is obtained after a long transitional regime of several months. In these experiments, the capacity of the culture to shorten the nonsteady period of a PCB bioleaching reactor in continuous mode was investigated. Three start-up

scenarios were explored to accelerate the transitional regime before the culture achieved high iron oxidation activity.

Figure 4 shows the evolution of the redox potential and bacterial concentration in the liquid phase during the start-up of the three scenarios. The first scenario (I) starts with non-adapted bacteria from the aerated column output as the only source of inoculum. In scenario II and scenario III, the adapted bacteria were first cultivated in batch mode before being used in PCBs bioleaching CSTR, without and with subcultures, respectively. These batch steps with PCBs lasted 18 days for scenario II and 14 days for scenario III (Supplementary Figure 6). Scenario I maintained a low redox and a constant planktonic bacterial concentration throughout the experiment. Besides, no growth was observed in the liquid phase. In scenario II, the redox was initially high from the previous batch and dropped during the first day as the Fe(III) was rapidly reduced. From the third day, the redox increased simultaneously with microbial growth. After 6 days, the redox reached 830 mV vs. SHE, implying complete Fe(II) oxidation, and the bacterial concentration gradually increased to reach $2 \times 10^8$ cells mL$^{-1}$. Scenario III did not show any significant drop in redox over 4 days, equivalent of two HRTs. Iron was therefore maintained as Fe(III) despite the continuous addition of PCBs. At the same time, minor microbial growth was observed (the planktonic bacterial counts increased from $4 \times 10^7$ to $8 \times 10^7$ cells mL$^{-1}$), but no clear exponential growth was detected.

## DISCUSSION

This study characterized the inhibition of microbial growth in metal-rich leachates and the iron oxidation activity of an adapted FeOB culture dominated by the iron-oxidizing species *L. ferriphilum*. The remarkable ability of *L. ferriphilum* to thrive at very low pH values and high redox potentials is well known (Rawlings et al., 1999; Hedrich et al., 2016). However, its capacity to catalyze iron oxidation can be limited by the inhibiting effect of high PCB concentrations (Arshadi and Mousavi, 2014; Wu et al., 2018). This inhibition can be due to the elevated dissolved metal concentrations, to other nonmetallic elements that may be present in PCBs, and to the solid PCB particles themselves. The FeOB culture adapted to 1% (w/v) PCBs grew and oxidized iron 1 day faster in the presence of 20% (v/v) PCB leachate (equivalent to 2% of PCBs) compared to the biotic control without PCBs. It is difficult to say whether the culture was more efficient when adapted to the leachate in this case or if the values enter in the measurement uncertainty. For media containing up to 60% (v/v) of PCB leachate, the study demonstrates a link between the concentration of the PCB leachate and the delay in bio-oxidation of Fe(II). This study also demonstrated that the addition of leachates [up to 60% (v/v)] had no impact on the final planktonic cell concentration and Fe(II) oxidation yield. In a previous study (Hubau et al., 2020), similar results were obtained with the non-adapted culture, but the bio-oxidation delay was observed at a lower metal content. An improved metal tolerance capacity of the culture adapted to elevated PCB concentrations was likely to be achieved in this study. This is consistent with the study by
<figure><img src="image_111.png" /><figcaption>**FIGURE 3** | Follow up of redox potential in bioleaching batch subcultures in 2.2 L-STRs: (A) subcultures SO, S1, and S2, (B) subcultures S3, S4, and S5. The first stage involves the microbial oxidation of the 3 Cm medium while the second stage starts with the addition of 2% (w/v) PCBs.</figcaption></figure>

Edward et al. (2018) who reported uninhibited iron oxidation by a *L. ferriphilum*-dominated culture adapted to 1 g L⁻¹ of Cu, achieving full oxidation of 3 g L⁻¹ iron in 4 days in the presence of 10 g L⁻¹ Cu. The combined inhibitory effects of different metals contained in PCB leachates might explain the impact on microbial activity kinetics in our FeOB culture, as has been observed by Nurmi et al. (2009). Achieving high PCB

loads is favorable for the economics of the bioleaching process. However, inhibitions of the microbial cultures have to be taken into account and only non-inhibitory pulp densities can be used.

The batch STR bioleaching experiments confirmed that elevated PCB loads extended the pre-oxidation phase. This delay was noted with both the adapted and non-adapted cultures. There was a pre-oxidation phase of 11 days at 1% (w/v) PCBs, even
<figure><img src="image_112.png" /></figure>

<figure><img src="image_113.png" /></figure>

**FIGURE 4** | Follow-up of (A) redox potential and (B) bacterial concentration overtime during the startup of continuous flow PCB bioleaching experiments in 2.2 L-STRs. Three scenarios of the startup were tested: I was only inoculated with the non-adapted culture; II performed a batch test on the adapted culture before starting the continuous flow process; III performed two successive batch subcultures on the adapted culture prior to the continuous flow process. Conditions of continuous flow bioleaching were set at 48 h of HRT and 1% (w/v) PCBs.

though the culture was adapted to that environment. The delays observed in the STRs were longer than those in shake flasks. The difference in operating conditions certainly affected the microbial activity, but the prolonged inhibiting effect in the STRs might also be related to (i) the shear stress caused by the solids and (ii) the presence of toxic elements in the solid phase.

A subculturing strategy reduced the inhibiting effect of PCBs in batch STRs. This improvement may be related to the

development of microbial resistance mechanisms allowing faster adaptation to the toxic effect of PCBs. It is also consistent with the work of Hedrich et al. (2016), in which successive subcultures improved the bioleaching rate of metals in batch bioleaching reactors. The subculturing strategy in this report achieved a maximum metal dissolution yield in 7 days despite the enhanced iron oxidation activity within subcultures. In all subcultures, the leaching agent was rapidly consumed during
the first hour. Therefore, leaching mostly occurred through
the rapid reduction of Fe(III) and the slow acidic dissolution,
regardless of the pre-oxidation phase (Mäkinen et al., 2015;
Hubau et al., 2020). The improvement of the pre-oxidation phase
was not sufficient to accelerate the dissolution of metals since,
as demonstrated by Hubau et al. (2020), the regeneration of
Fe(III) by bio-oxidation of Fe(II) in batch mode is longer than
the time required for the chemical dissolution of metals (acidic
hydrolysis). By reducing the pre-oxidation phase to less than
these 7 days, dissolution of metals could be accelerated. In our
study, this was not reached, and the shortest duration of the pre-
oxidation phase was not determined due to the difficulty of the
operational mode: the study demonstrated that the time between
the end of a batch and the next subculture should be reduced
to a minimum to maintain short pre-oxidation phases. The
10-day pause between subcultures adversely affected microbial
iron oxidation by extending the duration of the pre-oxidation
phase. At the end of one subculture, iron is completely oxidized,
resulting in a lack of electron supply for bacterial metabolism.
It is therefore preferable to keep the periods of time between
batch subcultures short, to maintain a better supply of electrons.
Long periods before subculturing have a negative effect on
the attempts to shorten the pre-oxidation phase. Nevertheless,
this negative effect proved to be transient, as the cultures in
this study eventually regained high oxidation performance after
several subcultures.

A continuous-flow bioreactor offers an interesting alternative to avoid the pauses between batch subcultures by ensuring a constant supply of iron to be oxidized, from both the medium and the PCBs themselves. It also enables the cultures to be adapted to PCBs, as well as Fe(III) to be regenerated in parallel with its consumption, thus favoring the metal dissolution by Fe(III) over the acidic hydrolysis (Hubau et al., 2020). The challenge is to reach and maintain steady-state conditions since the start-up can be a limiting issue. Thanks to the successive batch subcultures before the start-up in continuous mode, Scenario III was the most suitable strategy. It maintained high and constant microbial oxidation of iron, indicating that Fe was maintained as Fe(III) despite the continuous addition of PCBs. It was also considerably faster than in a previous study where 67 days were required to reach high redox potentials in a steady state (Hubau et al., 2020). The start-up of the process until high microbial iron oxidation activity was now almost immediate. This is a great advantage for further development of the process and its scale-up.

CONCLUSION

This study investigated the capacity of an FeOB culture to
oxidize iron in PCB environments by means of indicators such as
the redox potential and microbial growth. Exponential bacterial

growth was observed and the bacteria oxidized 8 g L⁻¹ of iron
in the presence of a PCB leachate equivalent to 6% PCBs, which
represented six times the metal content they were adapted to.
However, the inhibiting effect of PCBs on microbial activity
was evidenced by the delay in the bio-oxidation of Fe(II), i.e.,
a pre-oxidation phase. Successive subculturing shortened this
delay by up to 2.5 times, reducing the inhibiting effect of PCBs
in the bioleaching tests operated in batch mode. This strategy
also enhanced the start-up of the continuous flow bioleaching
reactor at 1% (w/v) PCBs. High microbial oxidation of iron was
maintained by running several subcultures before switching to
the continuous mode.

DATA AVAILABILITY STATEMENT

The raw data supporting the conclusions of this article will be
made available by the authors, without undue reservation.

AUTHOR CONTRIBUTIONS

JA-G: conceptualization, methodology, investigation, writing—original draft, writing—review and editing, and visualization.
AH: conceptualization, methodology, writing—review and editing, supervision, and project administration.
CJ: conceptualization, methodology, writing—review and editing, and supervision.
A-GG: conceptualization, resources, writing—review and editing, supervision, and funding acquisition.
All authors contributed to the article and approved the submitted version.

FUNDING

The *Mines Urbaines* Chair from the ParisTech foundation and the French Geological Survey (BRGM) funded this study with the support of Ecosystem.

ACKNOWLEDGMENTS

The authors acknowledge the technical support of H. Tris in the
characterization of the bacterial consortium. Funding provided
by BRGM and the *Mines Urbaines* Chair are acknowledged.

SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found
online at: https://www.frontiersin.org/articles/10.3389/fmicb.
2021.669738/full#supplementary-material

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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<figure><img src="image_114.png" /></figure>

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# Bioaugmentation With a Consortium of Bacterial Sodium Lauryl Ether Sulfate-Degraders for Remediation of Contaminated Soils

Ludovica Rolando¹, Anna Barra Caracciolo¹*, Paola Grenni¹, Livia Mariani¹, Jasmin Rauseo², Francesca Spataro², Gian Luigi Garbini¹,³, Andrea Visca¹ and Luisa Patrolecco²

¹ Water Research Institute, National Research Council, Monterotondo, Italy, ² Institute of Polar Sciences, National Research Council, Monterotondo, Italy, ³ Department of Ecological and Biological Sciences, Tuscia University, Viterbo, Italy

The anionic surfactant sodium lauryl ether sulfate (SLES) is the main component of most commercial foaming agents (FAs) used in the excavation of highway and railway tunnels with Earth pressure balance-tunnel boring machines (EPB-TBMs). Several hundreds of millions of tons of spoil material, consisting of soil mixed with FAs, are produced worldwide, raising the issue of their handling and safe disposal. Reducing waste production and reusing by-products are the primary objectives of the “circular economy,” and in this context, the biodegradation of SLES becomes a key question in reclaiming excavated soils, especially at construction sites where SLES degradation on the spot is not possible because of lack of space for temporary spoil material storage. The aim of the present work was to apply a bacterial consortium (BC) of SLES degraders to spoil material excavated with an EPB-TBM and coming from a real construction site. For this purpose, the BC capability to accelerate SLES degradation was tested. Preliminary BC growth, degradation tests, and ecotoxicological evaluations were performed on a selected FA. Subsequently, a bioaugmentation experiment was conducted; and the microbial abundance, viability, and SLES concentrations in spoil material were evaluated over the experimental time (0.5, 3, 6, 24, 48, and 144 h). Moreover, the corresponding aqueous elutriates were extracted from all the soil samples and analyzed for SLES concentration and ecotoxicological evaluations with the bacterium *Allivibrio fischeri*. The preliminary experiments showed the BC capability to grow under 14 different concentrations of the FA. The maximum BC growth rates and degradation efficiency (100%) were achieved with initial SLES concentrations of 125, 250, and 500 mg/L. The subsequent bioaugmentation of the spoil material with BC significantly (sixfold) improved the degradation time of SLES (DT₅₀ 1 day) compared with natural attenuation (DT₅₀ 6 days). In line with this result, neither SLES residues nor toxicity was recorded in the soil extracts showing the spoil material as a by-product promptly usable. The bioaugmentation with BC can be a very useful for cleaning spoil material produced in underground construction where its temporary storage (for SLES natural biodegradation) is not possible.

**Keywords:** anionic surfactant, foaming agents, spoil material, bioremediation, underground construction, bacterial consortium

## OPEN ACCESS

**Edited by:**
Muhammad Bilal,
Huaiyin Institute of Technology, China

**Reviewed by:**
Pankaj Bhatt,
South China Agricultural University,
China
Sikandar I. Mulla,
REVA University, India

*Correspondence:
Anna Barra Caracciolo
anna.barracaracciolo@irsa.cnr.it

**Specialty section:**
This article was submitted to
Microbiotechnology,
a section of the journal
Frontiers in Microbiology

Received: 12 July 2021
Accepted: 12 August 2021
Published: 22 September 2021

**Citation:**
Rolando L, Barra Caracciolo A, Grenni P, Mariani L, Rauseo J, Spataro F, Garbini GL, Visca A and Patrolecco L (2021) Bioaugmentation With a Consortium of Bacterial Sodium Lauryl Ether Sulfate-Degraders for Remediation of Contaminated Soils. *Front. Microbiol.* 12:740118. doi: 10.3389/fmicb.2021.740118
# INTRODUCTION

The anionic surfactant sodium lauryl ether sulfate (SLES) is the main component in most foaming agents (FAs) used in the excavation of highway and railway tunnels with Earth pressure balance-tunnel boring machines (EPB-TBMs) (Barra Caracciolo et al., 2017). FAs are used to change the mechanical properties and hydraulic behavior of soil, ensuring a malleable material that can be manageably excavated and transported to temporary areas (Peila, 2014; Peila et al., 2016). Due to the numerous tunneling projects currently in progress, several hundreds of millions of tons of soil debris (spoil material) are produced worldwide annually, raising the question of how to handle and dispose of them (Rahimzadeh et al., 2018; Rolando et al., 2020). Surfactants, including SLES, can be toxic for aquatic ecosystems if present at concentrations higher than the critical micellar one (Barra Caracciolo et al., 2017; Mariani et al., 2020; Rolando et al., 2020). The presence of SLES in spoil material can influence its recycling as a by-product; in fact, if the residual concentration of SLES is high, there can be toxic effects.

Previous experiments conducted on spoil material from tunnel excavation sites demonstrated that SLES was not toxic for terrestrial organisms (e.g., *Lepidium sativum* and *Eisenia fetida*) (Galli et al., 2019). However, in some cases, it showed detrimental effects on two aquatic species (*Pseudokirchneriella subcapitata* and *Aliivibrio fischeri*) (Grenni et al., 2018; Finizio et al., 2020; Patrolecco et al., 2020; Barra Caracciolo et al., 2021). Interestingly, the bacterium *A. fischeri* was shown to be very sensitive to SLES residues. In fact, a positive correlation between SLES concentrations and a toxic effect (inhibition of bioluminescence) on the bacterium was found in a 2-year monitoring of the spoil material from a highway construction site, making it possible to establish 2 mg/L as a “threshold value” of the toxic effect in the elutriates produced from spoil material (Mariani et al., 2020).

Reducing waste production and reusing by-products are the primary objectives of the “circular economy,” and in this context, the biodegradation of SLES becomes a key question in the safe reclaiming of excavated soils. Currently, tunnel debris can be used for refilling old quarries, road constructions, and green areas and as a raw material for industrial production (Bellopede and Marini, 2011).

Sodium lauryl ether sulfate has been shown to be a biodegradable compound in soils from tunnel excavation sites, but with highly variable degradation rates (Barra Caracciolo et al., 2019, 2021). In fact, concentrations of SLES in the range of 27–350 mg/kg showed variable half-lives (DT₅₀) from 8 to 46 days (Finizio et al., 2020). These results were ascribable not only to the initial SLES concentrations but also to site-specific characteristics such as soil texture, depth, structure, mineralogy, microbial abundance, water content, and temperature, which influenced its biodegradation differently.

Although a natural attenuation (with no human intervention) of SLES is expected due to the environmental microorganisms

present in the excavated soil, degradation times cannot always meet construction site requirements. In some cases, the spoil material can be temporarily stored at the construction site for the time needed for SLES biodegradation (Barra Caracciolo et al., 2019). This practice was successfully used in a recent tunnel construction site in Italy (Mariani et al., 2020). Unfortunately, in other cases, such as tunneling for a metro inside a city, an area for spoil material temporary storage is not available. In this case, the excavated materials have to be considered waste, requiring transportation, treatment, and disposal, with a significant increase in project costs and unnecessary landfill use (Barra Caracciolo et al., 2017; Rahimzadeh et al., 2018; Patrolecco et al., 2020).

In Italy, spoil material can be classified as a by-product if the chemical thresholds for some organic and inorganic contaminants (e.g., heavy metals, hydrocarbons C > 12) are not exceeded (Italian Decree, 2017). However, there are no SLES soil concentration limits (Annex 4 of the Italian Decree 120/2017) in EU and national legislation (Italian Decree, 2017). Consequently, the possibility that soil debris can be really considered a safe by-product is strongly related to SLES persistence and their residual concentrations, which in turn depend on abiotic and biotic site-specific conditions.

Sodium lauryl ether sulfate degradation is common in environmental bacteria able to resist the toxic effects of SLES and to degrade it (Barra Caracciolo et al., 2019). Several Gamma-Proteobacteria possess esterase enzymes that are able to break the SLES ester bond (Bornscheuer, 2002; Panda and Gowrishankar, 2005). In a recent previous work, a bacterial consortium (BC) capable of degrading completely pure SLES within 24 h was selected using enrichment cultures. The BC consisted of Gamma-Proteobacteria (99%), and the predominant (ca. 90%) genus was Pseudomonas (Rolando et al., 2020).

The aim of the present work was to test if adding the SLES pre-grown microbial culture (BC) to spoil material from a tunnel construction site enhanced the removal of the anionic surfactant residues, with potentially significant economic and environmental benefits.

# MATERIALS AND METHODS

## Chemicals

Methanol and chloroform of high-performance liquid chromatography (HPLC) grade, hydrochloric acid (37%), sulfuric acid (98%), and methylene blue were purchased from VWR (Radnor, PA, United States). Sodium hydrogen carbonate and anhydrous sodium carbonate were obtained from CARLO ERBA Reagents (Milan, Italy). SLES of technical grade purity was from BOC Sciences (Shirley, NY, United States). The stock solution of SLES (1,000 mg/L) was prepared in methanol and stored at -20°C. The dilution of this stock solution was performed using ultrapure water. Ultrapure water (18 MΩ·cm quality) was obtained using a Milli-Q system Millipore (Bedford, MA, United States). Diatomaceous earth was purchased from Thermo Fisher Scientific Inc. (Waltham, MA, United States).
# Analytical Determination of Sodium Lauryl Ether Sulfate in the Foaming Agent

The SLES concentration in FA solutions, used for the preliminary BC growth and degradation test described in the *Chemicals* section, was determined by applying the methylene blue active substances (MBAS) method<fnref n="1" />. This method includes three consecutive chloroform extractions of the ionic-pair reaction between SLES and methylene blue. Subsequently, the absorbance of the SLES-MBAS complex was measured with spectrophotometry at a wavelength of 650 nm (Lambda 25UV-VIS spectrophotometer, PerkinElmer, Waltham, MA, United States). Finally, the SLES concentration was calculated using the equations obtained with the standard calibration curve (in the range from 0.05 to 4 mg/L of SLES), as previously described (Barra Caracciolo et al., 2019; Patrolecco et al., 2020). The limit of detection (LOD), calculated following the IUPAC method (IUPAC, 1999), was 0.013 mg/L.

## Preparation of Elutriates From Soil Samples

The elutriates (soil water extracts) were produced from soil samples in a 1:10 (solid/liquid) ratio, as reported in Grenni et al. (2018), following the procedure described in UNI EN 12457-4:2004 (UNI EN, 2004). This standard procedure was used to simulate possible leaching of SLES from soil to water. Briefly, an aliquot (10 g) of fresh soil sample was put into a 250-ml bottle, and the calculated amount of distilled water (taking into account the moisture of the soil sample) was added. The suspension was shaken for 24 h at 20°C in the dark and settled, and the supernatant was then centrifuged for 15 min at 9,000 rpm.

# Analytical Determination of Sodium Lauryl Ether Sulfate in Soil and Elutriates

Sodium lauryl ether sulfate was extracted from soil samples with the pressurized liquid extraction (PLE) technique (Buchi mod. E-916; Cornaredo, Milan, Italy), using methanol as the extraction solvent and following the operative conditions reported in Pescatore et al. (2020). The PLE extracts and aqueous elutriates were analyzed for SLES content using the spectrophotometric MBAS method (see section “Analytical Determination of Sodium Lauryl Ether Sulfate in the Foaming Agent”). The PLE recovery was 96.5 ± 1.6%.

## Preliminary Bacterial Consortium Growth and Degradation Test on the Foaming Agent Selected

The previously isolated BC, capable of degrading pure SLES in 24 h and using it as the only carbon source (Rolando et al., 2020), was initially tested on a commercial FA consisting of a water solution of SLES (16%). FA was selected because it is one of the most common commercial products used in Italy and Europe for tunnel excavation with EPB-TBMs.

The capability of the BC to grow on different FA amounts was tested. For this purpose, various FA water solutions were prepared to obtain 14 SLES concentrations (0.5 mg/L, 1 mg/L, 2 mg/L, 4 mg/L, 8 mg/L, 16 mg/L, 31 mg/L, 62.5 mg/L, 125 mg/L, 250 mg/L, 500 mg/L, 1 g/L, 2 g/L, and 4 g/L). For each concentration, three replicates were considered. A control with only a mineral medium and a control with a mineral medium (MB1) and the BC were also set up. The bacterial growth was measured (every 15 min for 24 h) in terms of optical density (OD, 600nm), using a Multiskan Sky Microplate Spectrophotometer (Thermo Fisher Scientific). A 96-well plate was used to incubate the cultures at 37°C with a background shaking (180 rpm) and then read with the spectrophotometer for BC growth.

The capability of the BC to degrade the FA was then verified with the five concentrations that showed the highest growth rates (125 mg/L, 250 mg/L, 500 mg/L, 1 g/L, 2 g/L, and 4 g/L). Culture flasks (100 ml, three replicates for each condition) containing MB1 and FA solutions were incubated at 28°C in the dark and maintained on a rotary shaker at 130 rpm. A control with only MB1 and a control with MB1 and the BC were also set up. Cell growth (OD) and SLES concentration (% residual SLES concentration) were measured at 0, 6, 24, and 48 h.

# Ecotoxicological Evaluation (EC₂₀ and EC₅₀) of the Foaming Agent

The intrinsic toxicity of the FA was evaluated using the bioluminescent bacterium *A. fischeri*, following the UNI EN ISO 11348-3:2019 protocol, reported in detail in section “Aliivibrio fischeri Acute Toxicity Test.” The test with *A. fischeri* was used because previous studies have demonstrated it to be very sensitive to SLES residues in spoil material (Grenni et al., 2018; Mariani et al., 2020; Patrolecco et al., 2020).

The FA toxicity was expressed as the effective concentration (EC), i.e., the concentration that causes an effect (bioluminescence inhibition in percentage) on 20% (EC₂₀) or 50% (EC₅₀) of the organisms tested.

A higher EC value corresponds to a lower ecotoxicological effect. The EC₂₀ and EC₅₀ were determined using the Basic Test (81.9%) performed three times. The bacterium *A. fischeri* was exposed to various FA concentrations prepared with subsequent dilutions (using distilled water) from an FA stock solution (105 mg/L). Seven diluted solutions (in the range 1.34–86.00 mg/L) of the FA were used. The EC₂₀ and EC₅₀ were statistically estimated (Microtox Omni® software V 4.2, Milan, Italy). Based on the results obtained (see sections “Preliminary Bacterial Consortium Growth and Degradation Test on the Foaming Agent Selected” and “Ecotoxicological Evaluation (EC₂₀ and EC₅₀) of the Foaming Agent”), the commercial product FA was used for the subsequent bioaugmentation and ecotoxicological experiments, as described in the following paragraphs.

## Bioaugmentation Experiment With Spoil Material From the Construction Site

The soil samples consisted of spoil material directly obtained from the EPB-TBM operating in a railway tunnel construction

<footnote n="1">¹https://www.nemi.gov/methods/method_summary/7612/</footnote>
in Southern Italy. The experimental set consisted of glass beakers (2,000-ml capacity) filled with about 800 g of the excavated soil. The spoil material consisted of a silty clay soil conditioned with the commercial FA containing SLES (16%). The FA treatment ratio was 1.017 L/m³, which corresponded to an expected SLES concentration of 130 mg/kg. The soil water content was 60%, corresponding to 70% of the maximum soil water-holding capacity.

The BC was seeded on the spoil material to test its capability to accelerate the FA degradation.

The overall experimental conditions were as follows (three replicates for each condition):

- Soil batches with the FA and the BC: FA + BC soil.

- Soil batches with only the FA: FA soil.

- Soil batches with only the BC: BC soil.

- Untreated soil batches: Control.

The overall experimental set was maintained at room temperature 20 ± 2°C and kept open in order to simulate the temporary storage of the spoil material at the construction site. At selected times (0.5, 3, 6, 24, 48, and 144 h), three subsamples of soil from each batch were collected to analyze the microbial community [4,6-diamidino-2-phenylindole (DAPI) counts and Live/Dead] and the concentration of SLES over time. Moreover, from each soil sample, the corresponding aqueous elutriate was produced (see section "Preparation of Elutriates From Soil Samples") and analyzed for SLES concentration and ecotoxicological evaluations with the bacterium *A. fischeri*. All results refer to dry weight.

## Preparation of the Bacterial Inoculum

The BC was cultured in a mineral medium [MB1: 0.8 g/L of K₂HPO₄, 0.2 g/L of KH₂PO₄, 0.05 g/L of CaSO₄·2H₂O, 0.5 g/L of MgSO₄·7H₂O, 0.01 g/L of FeSO₄, and 1 g/L of (NH₄)₂SO₄] with 250 mg/L of SLES and maintained at 28°C overnight. From the overnight static culture, the bacterial cells were centrifuged (9,000 rpm for 2 min) and re-suspended in distilled water and the latter plus the FA. Before the spoil material was seeded, the bacterial abundance and viability of the BC were also measured using the DAPI count and Live/Dead methods, respectively. The bacterial abundance was 2.19 × 10⁷ ± 1.22 × 10⁶ cell/ml with a 90.7 ± 0.2% of live cells.

## Total Bacterial Abundance and Cell Viability by Epifluorescence Direct Methods

A fluorescence microscope (Leica DM 4000B, Leica Microsystems GmbH, Wetzlar, Germany) was used to observe and count the total bacterial abundance and cell viability. Briefly, total bacterial abundance (No. cells/g soil) was obtained (three subsample replicates) using aliquots of samples (ranging from 0.25 to 1 ml), fixed with formaldehyde (2% final concentration), and filtered through a 25-mm black polycarbonate membrane with a porosity of 0.2 µm (Whatman) using a gentle vacuum (<0.2 bar). The filters were treated with DAPI as described in detail elsewhere (Barra Caracciolo et al., 2005a,b). The total number of bacterial cells using DAPI can detect all microbial cells in a sample regardless of their physiological status and metabolic activity.

Cell viability (% live cells/live + dead) was assessed (three subsample replicates) using aliquots of fresh samples (the same volumes used for total bacterial abundance), which were filtered through the same filters as for the DAPI counts. The filters were treated with two fluorescent dyes, SYBR Green II and propidium iodide, as described in detail elsewhere (Grenni et al., 2009). This method can detect the viability of microorganisms, because

<figure><img src="image_115.png" /><figcaption>**FIGURE 1** | Bacterial consortium growth measured as optical density (OD) at 600nm, under 14 concentrations (from 0.5 mg/L to 4 g/L) of SLES. The vertical bars represent the standard errors. SLES, sodium lauryl ether sulfate.</figcaption></figure>
propidium iodide dye can only enter dead or damaged cells, and they appear red under a fluorescence microscope. Finally, the abundance of viable cells (No. viable cells/g soil) was calculated by multiplying the total bacterial abundance (obtained by DAPI counting) by cell viability.

## Aliivibrio fischeri Acute Toxicity Test

The acute toxicity test with A. fischeri was performed using a Microtox® analyzer (Model 500; Ecotox LDS, Milan, Italy) in accordance with the UNI EN ISO 11348-3: 2019 standard protocol (UNI EN, 2019). This test is based on the inhibition of the luminescence naturally emitted by the marine bacterium A. fischeri after its exposure to a toxic substance. Light output of the test organism, compared with a blank (toxic-free solution: distilled water containing 22% NaCl), was measured at least three times after each exposure period (5, 15, and 30 min). The difference in light output (between the sample and the blank) was ascribed to the matrix (elutriate) effect on the bacterium. The effect was calculated as a percentage of inhibition, using specific software (Microtox Omni® software V 4.2, Milan, Italy). Before the tests were carried out, the pH value of each elutriate was recorded and eventually corrected (range 6.0–8.0) using an HCl 0.1 M solution (Scheerer et al., 2006), as required by the standard procedures. The coefficient of variation (CV%: standard deviation/mean × 100) as a validity criterion (has to be <20%) was also calculated. The bacterial response (% bioluminescent inhibition) was considered toxic if it was more than 20% (Persoone et al., 2003), in accordance with the UNI EN ISO 11348-3:2019 protocol (UNI EN, 2019).

## Statistical Analysis

Any differences among data were evaluated using the Kruskal–Wallis test. The relationship between variables was calculated using a linear regression model. All statistical analyses were performed using R software version 4.1.0. Average and standard errors were estimated from three technical replicates of three biological replicates using MS Excel version 16.16.27. All figures were made using MS Excel version 16.16.27.

# RESULTS

## Preliminary Bacterial Consortium Growth and Degradation Test on the Foaming Agent Selected

A significant growth in the BC was observed with all 14 concentrations tested (Figure 1), confirming that the anionic surfactant SLES contained in the FA was a suitable carbon source.

The maximum BC growth rates are reported in Table 1. The growth rates were calculated with the following formula (Monod, 1949):

$$ \mu = \frac{\log_{10}OD_x - \log_{10}OD_0}{t_x - t_0} \quad (1) $$

where ODₓ, optical density measured at sampling time; OD₀, optical density measured at time 0; tₓ, sampling time; and t₀, time 0.

The five SLES concentrations (125 mg/L, 250 mg/L, 500 mg/L, 1 g/L, and 2 g/L), which showed significantly (*p* < 0.01, Kruskal–Wallis test) higher BC growth rates, were used for the subsequent degradation experiment.

The BC was capable of growing with all five SLES concentrations tested (Figure 2A). However, a complete degradation of the anionic surfactant was observed at 48 h only with the 125, 250, and 500 mg/L concentrations (Figure 2B).

## Ecotoxicological Evaluation (EC₂₀ and EC₅₀) of the Foaming Agent

The dose-response relationship between the FA concentration and the bioluminescence inhibition (%) after 30 min of exposure of the bacterium A. fischeri was determined. The EC₂₀ and EC₅₀ average values for the FA were 3.66 ± 0.72 (corresponding to 0.59 mg/L of SLES) and 10.34 ± 1.20 (corresponding to 1.66 mg/L of SLES) mg/L, respectively. In both cases, the CV% was less than 20%.

## Bioaugmentation Experiment

### Total Microbial Abundance and Cell Viability in Soil

The initial microbial abundance (expressed as No. of live cells/g soil) in the spoil material used for the bioaugmentation experiment was similar in all conditions (1.65 × 10⁶ ± 1.24 × 10⁵). FA treatment did not have any initial detrimental effect on this microbiological parameter. An increasing trend in microbial numbers was observed between 0.5 and 48 h. A significantly (*p* < 0.01, Kruskal–Wallis test) higher abundance was observed in the bioaugmented soil (FA + BC soil), with a peak at 48 h (Figure 3).

### Sodium Lauryl Ether Sulfate Concentration in Soil and Elutriates

The residual concentrations of SLES measured over the experimental time (0.5, 3, 6, 24, 48, and 144 h) in the spoil material and in the corresponding elutriates produced are shown in Figure 4 and Table 2, respectively. The initial SLES amounts in the spoil material (FA soil) and in the

<table><caption>TABLE 1 | Maximum growth rates of the bacterial consortium grown under 14 different SLES concentrations.</caption><thead><tr><th>SLES concentration (mg/L)</th><th>4,000</th><th>2,000</th><th>1,000</th><th>500</th><th>250</th><th>125</th><th>62.5</th><th>31</th><th>16</th><th>8</th><th>4</th><th>2</th><th>1</th><th>0.5</th></tr></thead><tbody><tr><td>μ<sub>max</sub> (h<sup>-1</sup>)</td><td>0.037</td><td>0.047</td><td>0.043</td><td>0.044</td><td>0.043</td><td>0.043</td><td>0.037</td><td>0.035</td><td>0.037</td><td>0.023</td><td>0.018</td><td>0.014</td><td>0.013</td><td>0.010</td></tr></tbody></table>

SLES, sodium lauryl ether sulfate.

μ<sub>max</sub> = maximum growth rate during the exponential phase.
<figure><img src="image_116.png" /><figcaption>**FIGURE 2** | (A) Growth of the BC (OD at 600nm) on the foaming agent containing SLES. (B) Biodegradation of SLES (residual concentration) at five concentrations (125 mg/L, 250 mg/L, 500 mg/L, 1 g/L, and 2 g/L). The vertical bars represent the standard errors. BC, bacterial consortium; SLES, sodium lauryl ether sulfate.</figcaption></figure>

bioaugmented soil (FA + BC soil) were 136 ± 3.6 and 132.3 ± 2.8 mg/kg, respectively.

In the bioaugmented soil (FA + BC soil), 91% of SLES was degraded at 144 h. At the same sampling time, in the absence of the BC, only 54% of SLES was degraded (FA soil; **Figure 4A**).

The degradation pathways followed first-order kinetics, and the theoretical values of the disappearance time of 50% of the initial SLES concentrations (DT₅₀) were calculated from correlations (r² = 0.93 for FA + BC soil and 0.95 for FA soil; *p*-value < 0.01) between concentrations [expressed as ln(Ct/C₀), where Ct, SLES concentration at the sampling time and C₀, SLES concentration at day 0] versus time (**Figure 4B**).

The SLES concentration in the elutriates reflected that of the soil samples (Table 2). To the SLES initial concentrations in the spoil material of 136 and 132.3 mg/kg corresponded 6.0 and 5.2 mg/L of SLES in the elutriates produced from FA soil and FA + BC soil conditions, respectively.

<figure><img src="image_117.png" /><figcaption>**FIGURE 3** | Number of live cells (No. live cells/g soil) evaluated using direct fluorescence methods at different experimental times (0.5–144 h) in the various conditions. Control: untreated soil batches; BC soil: soil batches with only the bacterial consortium; FA soil: soil batches with only the foaming agent; FA + BC soil: soil batches with the foaming agent and the bacterial consortium. The vertical bars represent the standard errors.</figcaption></figure>

In line with the SLES degradation observed in soil, the anionic surfactant also decreased over time in the corresponding water extract. In the bioaugmented soil, significantly lower SLES residues were detected; for example, at 24 h, a SLES concentration of 1 mg/L was found in FA + BC soil and at the same time of 5.4 mg/L in FA soil. At the end of the bioaugmentation experiment, no SLES residues were found in the FA + BC soil condition.

## Alivibrio fischeri Acute Toxicity Test

The *A. fischeri* test (Figure 5) was performed on water extracts (elutriates) of unconditioned (Control) and conditioned (FA soil and FA + BC soil) soils from the bioaugmentation experiment. The test was executed on samples collected at selected times (0.5, 24, 48, and 144 h).

In the Control condition (as expected), the bacterial bioluminescence was not inhibited. At the start (0.5 h) of the experiment, a toxic effect (bioluminescence inhibition >20%) was observed in elutriates of both FA and FA + BC soil; at the subsequent sampling, FA + BC soil elutriates did not show any toxicity for the *A. fischeri* bacterium. On the other hand, a toxic effect (bioluminescence inhibition >20%) was observed in FA soil until 48 h.

All validity criteria for the test were met, and all the data reported can therefore be considered valid.

## DISCUSSION

The aim of the present work was to test the capability of a previously isolated BC to enhance SLES degradation, in FA-conditioned soil collected from a tunnel construction site, in order to verify its possible use for routine bioaugmentation purposes. Bioaugmentation is a green technology used successfully for bioremediation of soil and water from several contaminants (e.g., petroleum hydrocarbons and pesticides) (Gentry et al., 2004; Abatenh et al., 2017; Arora, 2018). It consists in adding exogenous microbial populations or autochthonous ones (as in this work) with the catabolic potential to remove specific pollutants, such as pesticides
<figure><img src="image_118.png" /><figcaption>**FIGURE 4** | SLES degradation in soil batches with only the foaming agent (FA soil) and soil batches with the foaming agent and the bacterial consortium (FA + BC soil). (A) Residual concentrations of SLES expressed in percentage (%) over the experimental time (144 h). (B) Plot of ln(Ct/C₀) versus time for calculating the theoretical SLES DT₅₀ (days) by the linear regression equations. The vertical bars represent the standard errors. SLES, sodium lauryl ether sulfate.</figcaption></figure>

(Plangklang and Reungsang, 2011; Sun et al., 2020). One advantage of bioaugmentation is that the degradation process starts as soon as specific microbial degraders are introduced (Wu et al., 2019). The success of bioaugmentation depends on the ability of the inoculated microorganisms to continue their activity in the environment as long as necessary for contaminant removal. However, if the degradation times are relatively long (such as in the case of pesticides), competitive interactions with non-degrading microbial populations can occur, and specific environmental conditions can limit bioaugmentation efficiency during *in situ* remediation (Hibbing et al., 2010; Asok and Jisha, 2012; Stelting et al., 2014; Cavinato et al., 2017).

The fact that in our work the bacterial populations were isolated from the same soil and that SLES removal times were very low made this bioremediation strategy an example of a real nature-based solution.

Although there are several works (Cycoń et al., 2017; Nur Zaida and Piakong, 2018; Tondera et al., 2021) dealing with contaminant removal by bioaugmentation, most of them have been performed using culture media and/or in liquid media and at concentrations which do not reflect those found in real contamination scenarios (Silva et al., 2004). There are few works in which adding microbial strains to soil improved degradation of organic contaminants in field studies or directly in environmental

soil samples. Bioaugmentation can be applied using single microbial populations or a microbial consortium. For example, microbial consortia have been reported to degrade oils in polluted soil (Silva-Castro et al., 2012), in waste lubricating oil (Bhattacharya et al., 2015), in seawater (Dellagnezze et al., 2016), and in petroleum hydrocarbon in contaminated groundwater (Poi et al., 2018) and triazines in water and soil (Nasseri et al., 2014; Sagarkar et al., 2014). Triazine degradation has been performed in several bioaugmentation experiments with concentrations of these herbicides much higher than those commonly found in soil, such as in the study by Silva et al. (2004). However, in a recent work, Chen et al. (2021) showed the capability of a single bacterial population to degrade atrazine in a real contaminated soil (Chen et al., 2021).

<table><caption>**TABLE 2** | SLES concentrations (mg/L) in elutriates obtained from the soil samples of the conditioned batches (FA soil and FA + BC soil) over the experimental time; SE = standard error.</caption><thead><tr><th rowspan="2"></th><th colspan="4">SLES (mg/L) in elutriates</th></tr><tr><th>0.5 h</th><th>24 h</th><th>48 h</th><th>144 h</th></tr></thead><tbody><tr><td>FA soil</td><td>6.0 ± 0.01</td><td>5.4 ± 0.01</td><td>2.2 ± 0.00</td><td>1.2 ± 0.00</td></tr><tr><td>FA + BC soil</td><td>5.2 ± 0.00</td><td>1.0 ± 0.01</td><td>0.2 ± 0.00</td><td>&lt;LOD<sup>a</sup></td></tr></tbody></table>

SLES, sodium lauryl ether sulfate;

FA, foaming agent;

BC, bacterial consortium.

a LOD, limit of detection.

<figure><img src="image_119.png" /><figcaption>**FIGURE 5** | Bioluminescence inhibition (%) of *Aliivibrio fischeri* bacterium exposed for 30 min to elutriates from FA, FA + BC soil, and Control at selected experimental times (0.5, 24, 48, and 144 h) of the bioaugmentation experiment. Control: untreated soil batches; FA soil: soil batches with only the foaming agent; FA + BC soil: soil batches with the foaming agent and the bacterial consortium. The bars represent the standard errors. The black line represents the threshold of toxicity (20%).</figcaption></figure>
Most works on anionic surfactants are aimed at evaluating biodegradation of sodium dodecyl sulfate, linear alkylbenzene sulfonate, and SLES in activated sludge (Hosseini et al., 2007), industrial wastewater (Karray et al., 2016; Fedeila et al., 2018), municipal wastewater (de Faria et al., 2019), and wastewater treatment plants (Paulo et al., 2017), because they are contaminants widely used in cosmetics, cleaning products, and personal care products (Barra Caracciolo et al., 2017; Hashim et al., 2018).

On the other hand, there have been no bioaugmentation experiments for remediating SLES, except for the work by Dhouib et al. (2003). These authors found a bacterial population of Gamma-Proteobacteria (Citrobacter braakii) that was able to degrade high concentrations of SLES in an enrichment culture using wastewater samples from a cosmetic plant as the inoculum. This work supports our results and the role of Gamma-Proteobacteria class in removing this anionic surfactant. Interestingly, in our study, where the soil came from a real construction site and the surfactant concentrations (130 mg/kg) were those used for the excavation, the bioaugmentation of the spoil material with the BC significantly (sixfold) improved the natural degradation time of SLES. Moreover, from an applied perspective, using a microbial consortium rather than a pure culture is more advantageous because it provides the metabolic diversity and robustness needed for field applications (Tyagi et al., 2011).

Finally, the ecotoxicological results confirmed the depollution of the soil (SLES in elutriates did not exert any toxicological effect) and the high sensitivity of A. fischeri to SLES residues higher than 2 mg/L (before SLES degradation), in line with the findings of previous works (Mariani et al., 2020; Patrolecco et al., 2020). The use of this ecotoxicological test in supporting chemical analysis is very powerful because it is an effective tool that can evaluate an overall matrix toxicity including chemicals (e.g., possible metabolites and/or unknown elements present in soil) non-directly analyzed. Other studies used A. fischeri as an effective screening test for soil samples (Parvez et al., 2006; Abbas et al., 2018).

## CONCLUSION

Bioaugmentation with the BC identified at a construction site makes it possible to remove anionic surfactant residues

and clean up spoil material in a few hours, ensuring a safe by-product and saving execution time and overall costs for the tunneling industry. To our knowledge, this study is the first using a SLES-degrading BC for bioaugmentation purposes in a contaminated soil from a real environmental scenario. This remediation strategy is a promising low-cost and nature-based solution, for a prompt and safe reuse of the spoil material, avoiding its temporary storage and unnecessary waste production and transfer to landfills. This technique could be used, e.g., in the case of metro tunneling inside a city or through mountains along a sea coast, where the lack of space prevents temporary storage of the spoil material for its natural attenuation. The overall results show how a diversified approach involving chemical, microbiological, and ecotoxicological assessments of polluted soil can improve our understanding of the biodegradability of pollutants in bioremediation strategies. Further studies are in progress for finding the best practice (e.g., alginate microspheres) for seeding the BC on a large scale in construction sites.

## DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author/s.

## AUTHOR CONTRIBUTIONS

LR, AB, PG, LM, JR, FS, GG, AV, and LP: methodology, formal analysis, and validation. LR and AB: writing, original draft preparation, and editing. AB, PG, and LP: supervision. AB: funding acquisition. All authors have read and agreed to the published version of the manuscript.

## FUNDING

This work was partially funded by Italferr Spa— Project N. 100032057.

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Copyright © 2021 Rolando, Barra Caracciolo, Grenni, Mariani, Rauseo, Spataro, Garbini, Visca and Patrolecco. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
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# The Response of Extracellular Polymeric Substances Production by Phototrophic Biofilms to a Sequential Disturbance Strongly Depends on Environmental Conditions

Emilie Loustau¹,²†, Joséphine Leflaive¹*†, Claire Boscus¹, Quentin Amalric¹, Jessica Ferriol¹, Olga Oleinikova³, Oleg S. Pokrovsky³,⁴, Elisabeth Girbal-Neuhauser² and Jean-Luc Rols¹

¹ Laboratoire Ecologie Fonctionnelle et Environnement, Université de Toulouse, CNRS, Toulouse INP, Université Toulouse 3 – Paul Sabatier (UPS), Toulouse, France, ² LBAE, Université de Toulouse, Université Toulouse 3 – Paul Sabatier (UPS), Auch, France, ³ GET, Université de Toulouse, CNRS, IRD, Université Toulouse 3 – Paul Sabatier (UPS), Toulouse, France, ⁴ BIO-GEO-CLIM Laboratory, Tomsk State University, Tomsk, Russia

**OPEN ACCESS**

**Edited by:**
Carmen Palacios,
Université de Perpignan Via Domitia,
France

**Reviewed by:**
Giulia Gionchetta,
Swiss Federal Institute of Aquatic
Science and Technology, Switzerland
Ian Hawes,
University of Waikato, New Zealand

*Correspondence:
Joséphine Leflaive
josephine.leflaive@univ-tlse3.fr

† These authors share first authorship

**Specialty section:**
This article was submitted to
Microbiotechnology,
a section of the journal
Frontiers in Microbiology

**Received:** 15 July 2021
**Accepted:** 20 September 2021
**Published:** 11 October 2021

**Citation:**
Loustau E, Leflaive J, Boscus C, Amalric Q, Ferriol J, Oleinikova O, Pokrovsky OS, Girbal-Neuhauser E and Rols J-L (2021) The Response of Extracellular Polymeric Substances Production by Phototrophic Biofilms to a Sequential Disturbance Strongly Depends on Environmental Conditions. *Front. Microbiol.* 12:742027.
doi: 10.3389/fmicb.2021.742027

Phototrophic biofilms are exposed to multiple stressors that can affect them both directly and indirectly. By modifying either the composition of the community or the physiology of the microorganisms, press stressors may indirectly impact the ability of the biofilms to cope with disturbances. Extracellular polymeric substances (EPS) produced by the biofilm are known to play an important role in its resilience to various stresses. The aim of this study was to decipher to what extent slight modifications of environmental conditions could alter the resilience of phototrophic biofilm EPS to a realistic sequential disturbance (4-day copper exposure followed by a 14-day dry period). By using very simplified biofilms with a single algal strain, we focused solely on physiological effects. The biofilms, composed by the non-axenic strains of a green alga ( *Uronema confervicolum* ) or a diatom ( *Nitzschia palea* ) were grown in artificial channels in six different conditions of light intensity, temperature and phosphorous concentration. EPS quantity (total organic carbon) and quality (ratio protein/polysaccharide, PN/PS) were measured before and at the end of the disturbance, and after a 14-day rewetting period. The diatom biofilm accumulated more biomass at the highest temperature, with lower EPS content and lower PN/PS ratio while green alga biofilm accumulated more biomass at the highest light condition with lower EPS content and lower PN/PS ratio. Temperature, light intensity, and P concentration significantly modified the resistance and/or recovery of EPS quality and quantity, differently for the two biofilms. An increase in light intensity, which had effect neither on the diatom biofilm growth nor on EPS production before disturbance, increased the resistance of EPS quantity and the resilience of EPS quality. These results emphasize the importance of considering the modulation of community resilience ability by environmental conditions, which remains scarce in the literature.

**Keywords:** EPS production, phototrophic biofilm, resistance, recovery, photosynthetic efficiency
# INTRODUCTION

Understanding and predicting how communities respond and resist to disturbances in terms of composition or function are current concerns for microbial ecologists (Gonzalez et al., 2012). Ecological disturbance is defined as a causal event inducing a perturbation in a community (Rykiel, 1985). Many definitions have been proffered for the resilience of communities exposed to a disturbance. We consider here, following the recommendation by Hodgson et al. (2015), the resilience as the ability of a system to persist or maintain a function in the face of disturbance. The two measurable components of resilience are the resistance, that is the degree to which a community remains unchanged when it is subjected to a disturbance, and the recovery, that is the ability of a system to return to pre-disturbance levels (Hodgson et al., 2015; Oliver et al., 2015). Consequently, a resilient system is able to minimize the impact of the disturbance and has the ability to resume functioning under changing conditions. The resilience of microbial communities is crucial to preserve the ecological services they provide. With global change, the intensity and frequency of disturbances are likely to increase (IPCC, 2013), threatening the upholding of ecological services. By impacting the ability of microbial communities to resist to and recover after disturbances, small modifications of the environmental conditions may also represent an underestimated threat. The aim of this study was to assess in what extent the environmental conditions could influence the response of a microbial community to a complex disturbance.

Very simplified phototrophic biofilms were chosen as model of microbial community. In natural environment, biofilms are complex microbial communities composed of heterotrophic and phototrophic, eukaryotic and prokaryotic microorganisms embedded in a protective matrix of extracellular polymeric substances (EPS) (Lock, 1993). The functions fulfilled by phototrophic biofilms, such as photosynthesis, primary production, oxygen production, nutrients uptake, and contaminants removal are at the base of key ecological functions of fluvial ecosystems (Lawrence et al., 2001; Battin et al., 2003, 2016; Corcoll et al., 2012). Phototrophic biofilms are often exposed to chemical disturbances when freshwater ecosystems receive organic or inorganic pollutants (pesticides, organic solvents, heavy metals) through agriculture, domestic, and industrial uses (Segner et al., 2014). In addition to these multiple chemical stresses, the biofilms are also exposed to desiccation when the flow decreases. This stress is particularly severe in intermittent rivers which completely dry out part of the year (Datry et al., 2017). It is generally agreed that climate change will lead to more intense summer drought, higher temperatures, and more frequent episodes of intense rainfall (Acuna, 2010; Sabater et al., 2016). Hydrological and chemical stresses may affect aquatic systems either simultaneously or successively. For example, a decrease of flow before full desiccation can induce an increase in the concentration of riverine solutes (Gomez et al., 2017).

Light intensity, temperature, and nutrients are among the main environmental factors that affect the growth of phototrophic microbial communities (Lear et al., 2008;

Sabater et al., 2016; Bengtsson et al., 2018). Light is the principal energy source fueling biofilm primary production: a modification of light intensity affects biofilm growth, its physiology and the community composition (Sabater et al., 2002). Temperature increase can change algal diversity (Stevenson et al., 1996). Furthermore, temperature has a marked influence on chemical toxicity (Holmstrup et al., 2010). Lambert et al. (2016) and Pesce et al. (2018) showed that temperature can modulate phototrophic biofilm response to chronic Cu exposure: an increase in temperature reduced Cu effects on algal biomass, photosynthetic efficiency, and diatom composition. The availability and the concentration of nutrients also play an important role on changes in the structure of phototrophic biofilm communities with consequences on the sensitivity of biofilms to disturbances. For instance, as inorganic nutrient concentrations increase, the proportion of species tolerant to organic pollution increases whereas the abundance of sensitive species declines (Delgado et al., 2012). This is particularly true for phosphorus (P) which is a limiting nutrient in many aquatic ecosystems (Schindler, 1977; Schindler et al., 2008). Increasing P concentration led to a significant shift in the biofilm community composition; these changes being more pronounced in diatom- than in cyanobacteria-dominated biofilm (Leflaive et al., 2015).

One essential component of biofilms is the EPS matrix which provides a cohesion to the assemblage of organisms. EPS are produced by bacteria and microalgae through excretion, sorption, or cell lysis, and are mainly composed by polysaccharides and proteins with a certain amount of lipids, DNA and humic substances (Loustau et al., 2018). EPS create strong gradients within the biofilm by limiting access to nutrients, oxygen and light for the cells located far from the biofilm surface (Hill, 1996). Besides other functions (adhesion of microorganisms on immersed substratum, resource for the growth of heterotrophic microorganisms), the EPS matrix protects the cells from desiccation and other environmental stresses (pollutants, UV radiation, etc.), and adsorbs and accumulates organic pollutants or metal cations present in the water column (Flemming et al., 2016). EPS are certainly involved in the ability of phototrophic microorganisms to cope with disturbance and tolerate stresses, as it has been suggested for heavy metals, nanoparticles (Kroll et al., 2014), salinity (Shetty et al., 2019), or drought (Sasaki et al., 2020). Since EPS production is quantitatively and qualitatively affected by environmental conditions such as temperature and light intensity (Wolfstein and Stal, 2002; Di Pippo et al., 2012) or the presence of nanoparticles (Verneuil et al., 2015), our main hypothesis is that slight variations in environmental conditions in terms of light, temperature or nutrient concentration may impact the resilience of EPS quality and quantity to a disturbance. To test this hypothesis, we monitored the production and composition of EPS in response to a complex disturbance, in different environmental conditions of light, temperature, and nutrients. Biofilms composed by one phototrophic microorganism and the associated bacterial communities were produced in artificial streams. Such simplified biofilms were chosen in order to mainly focus on direct effects on algal physiology rather than on indirect effects through modifications of algal composition. The sequence
of disturbance was chosen to be representative of flow decrease and cessation in a river: an increase in pollutant concentration followed by desiccation. Copper, commonly found is small intermittent rivers in vineyard areas (Montuelle et al., 2010), was chosen here as a model of pollutant. Our hypotheses are that (i) the environmental conditions influence the resilience of the quality and quantity of EPS when the biofilms are exposed to a disturbance and (ii) the more an environmental parameter affects the biofilm growth, the more it affects the resilience of EPS.

# MATERIALS AND METHODS

## Pre-culture of Microorganisms

The diatom *Nitzschia palea* (Kützing) W. Smith and the green alga *Uronema confervicolum* Lagerheim, isolated from phototrophic biofilms in the rivers Tarn and Garonne (Southwestern France), were used as the main phototrophic organisms for the two different biofilms. They were maintained in non-axenic conditions in the algae collection of the laboratory "Ecologie Fonctionnelle et Environnement" at 18°C under white light (30 ± 5 µmol photons s⁻¹ m⁻²) with light/dark periods of 16/8 h in Combo medium (Kilham et al., 1998). Individual pre-cultures were prepared for 21 days in 500-mL Erlenmeyer flasks and the biomass was homogenized using an Ultra-Turrax disperser (T25, Janke-Kunkel, 13,500 rpm, 1 min) before inoculation in the hydraulic mini-channels.

## Experimental Setup

Very simplified biofilms (one algal strain and the associated bacteria) were grown in several hydraulic mini-channels described in Loustau et al. (2019). Three modules were used, each one composed of two blocks corresponding to two separated closed circulating loops of Combo medium for the supply of four mini-channels in each block (Figure 1A). Only three mini-channels in each block were sampled for this study. Two successive experiments were performed, one for each type of biofilm cultivated on eighty supports (polyoxymethylene coupons, size 29 mm × 10 mm × 5 mm) transversally placed along each mini-channel. A flow velocity of 0.4 m s⁻¹ allowing to create a homogeneous turbulent flow regime on the surface of coupons, and a circadian cycle of light/dark periods of 16/8 h were applied. A pH of 8 ± 0.1 (pH meter Multi 3430 SET C) was observed during the light period. Biofilms were cultivated with a combination (Figure 1B) of two light intensities (70 µmol photons s⁻¹ m⁻², *L* - high light intensity or 30 µmol photons s⁻¹ m⁻², *l* - low light intensity) measured with a flat quantum sensor (model LI-189, LI-COR, Inc., Lincoln, Nebraska) and two temperatures of the circulating water (22°C, *T* - high temperature or 19°C, *t* - low temperature). Two additional conditions at high temperature and high light intensity were obtained by modifying initial P concentration compared to the initial P concentration of the culture medium (5.23 mg L⁻¹, P100 - 100%): a higher concentration of 8.71 mg L⁻¹ (P165 - increase of 165%) and a lower concentration of 2.61 mg L⁻¹ (P50 - decrease of 50%). For each condition, a block was inoculated

(Figure 1C). The six culture conditions were then: LTP100, LtP100, ITP100, ltP100, LTP50, and LTP165.

After 14 days of biofilm growth, the physiological state of biofilm was assessed with maximum quantum yield measurements directly inside the mini-channels, and some coupons were randomly sampled for the determination of biomass and EPS (amount and composition).

After the sampling at day 14, copper (CuSO₄) was added in the circulating nutrient medium to reach an increase of the initial Cu concentration by 50 µg L⁻¹. Due to Cu presence in Combo culture medium (0.3 µg L⁻¹), the initial Cu concentration corresponded to 50.3 µg L⁻¹. Dissolved Cu²⁺(aq) speciation in the presence of cell exometabolites and organic ligands of the nutrient medium was assessed by using the Visual MINTEQ computer code (Gustafsson, 2011, version 3.1 for Windows, October 2014) in conjunction with a database and the NICA-Donnan humic ion binding model. Thermodynamic calculation demonstrated that Cu²⁺(aq) speciation was dominated by EDTA complexes in the form of Cu-anions, with negligible role of other organic complexes from nutrient media constituents.

At day 18, the mini-channels were quickly dried-out by removing the water in each block. The biofilms were then kept at room temperature (17°C). After 14 days of dry period (day 32), the mini-channels were re-filled with fresh culture medium with corresponding initial P concentration (P50, P100, or P165) for another 14-day rewetting period (until day 46).

Before the disturbance event (day 14), ten coupons were randomly selected and collected per mini-channel for the biomass characterization and fifteen for the EPS extraction, to obtain three replicates from three mini-channels per block. Biofilms were scraped from these coupons with a sterile toothbrush and suspended in 15 mL (biomass) or in 100 mL (EPS) of culture medium before analysis. At the end of the disturbance sequence (day 32), and after the rewetting period (day 46), fifteen coupons were sampled in each of the three mini-channel and biofilm was suspended in 100 mL of culture medium for EPS extraction, to obtain three replicates per block.

## Biofilm Biomass

A subsample of the biofilm suspension obtained as described above was used to assess biofilm biomass by measuring the dry weight (DW) after 72 h of drying at 70°C in a pre-weighted aluminum dish.

## Maximum Quantum Yield

The physiological state of phototrophic microorganisms was estimated by the maximal quantum yield of the photosystem II (PSII) (yield, Φ PSII), corresponding to the number of open reaction centers (Rohacek and Bartak, 1999). In stressed organisms, the yield strongly decreases (Rohacek and Bartak, 1999). Though it is primarily linked to the PSII, the yield may reflect the physiological state of the organism (Parkhill et al., 2001; Laviale, 2008). The photosynthetic efficiency is specific to each algal group, precluding the comparison between the values of the different species used here. Non-invasive PhytoPAM measurements (Phytoplankton Analyzer, Heinz Walz GMBH, Effeltrich, Germany) were performed on the surface of the
<figure><img src="image_121.png" /><figcaption>FIGURE 1 | (A) Photographs of one module with a detail view of the mini-channels. (B) Experimental design applied for the two biofilms. The experimental conditions were the same in the four mini-channels of one block. Six different conditions were tested with two levels of temperature (T = 22°C or t = 19°C), light intensity (I = 70 µmol s⁻¹ m⁻² or I = 30 µmol s⁻¹ m⁻²) and P concentration (P100 corresponds to the initial P concentration of 5.23 mg L⁻¹ in the culture medium, P50 with a decrease of 50% and P165 with an increase of 165%). (C) Experimental setup with the step of inoculation of the mini-channels at day 0, the addition in the culture medium of Cu for a final concentration of 50.3 µg L⁻¹ at day 14, followed by a 14-day dry period, and finally a 14-day rewetting.</figcaption></figure>

biofilm by measuring fluorescence response to a saturating light flash after 20 min of dark adaptation [dark-adapted state (DAS) conditions] (Baker, 2008):

$$ \Phi_{\text{PSII}}(\text{DAS conditions}) = 1 - (F_0/F_M); 0 < \Phi_{\text{PSII}} < 1 \quad (1) $$

$F_M$ represents the maximal fluorescence and $F_0$ corresponds to the minimal fluorescence of the photosystem II. For each condition (in one block), thirty-two measurements were performed at day 14 (eight for each mini-channel).

## Extracellular Polymeric Substances
### Extracellular Polymeric Substances Extraction

The biofilm suspension was homogenized with an Ultra-Turrax disperser at 13,500 rpm for 1 min at room temperature. Then, a volume of the homogenized suspension corresponding to 10 mg DW was centrifuged at 4,000 g for 15 min. The pellet was washed with Phosphate Buffer Saline (PBS) solution and centrifuged again. Finally, two EPS extraction steps, following the sequential method previously developed by Loustau et al. (2018), were applied in sequence with intermediate centrifugations

(4,000 g for 15 min) to collect the supernatants containing the solubilized EPS. The first extraction step was performed with 0.22% formamide in PBS solution (stirring at 150 rpm and 4°C for 60 min) and the second one with cation exchange resin (CER, Dowex Marathon) at 50 g g⁻¹ DW of biomass in PBS solution (stirring at 150 rpm and 4°C for 90 min).

The cellular integrity during the extraction steps was controlled by the measurement of chlorophyll a released in the supernatants, giving a cell lysis level less than 3.5% for all samples.

The total amount of EPS extracted was the sum of the EPS amounts contained in both supernatants (formamide + CER). After acidification of EPS extract with hydrochloric acid and volatilization of inorganic carbon by catalytic oxidation at 720°C, the Total Organic Carbon (TOC) was analyzed (Shimatzu TOC-L analyzer).

## Proteins and Polysaccharides Quantification

For each EPS extract, the amounts of proteins and polysaccharides were measured in analytical triplicates. Protein (PN) concentration was measured by the bicinchoninic acid (BCA) method (Smith et al., 1985). Twenty-five µL of EPS extract
<table><caption>**TABLE 1** | *P*-values for two-way and one-way ANOVAS to test the effect of environmental conditions on the biomass (DW), maximum quantum yield (ΦPSII), EPS quantity (TOC), and EPS quality (PN/PS) of the biofilms before the disturbance.</caption><thead><tr><th></th><th></th><th>Temperature</th><th>Light intensity</th><th>Temp * Light</th><th>P concentration</th></tr></thead><tbody><tr><td rowspan="4">N. palea biofilm</td><td>Biomass</td><td><strong>0.0256</strong></td><td>0.5431</td><td>0.6095</td><td>0.0854</td></tr><tr><td>ΦPSII</td><td><strong>0.000001</strong></td><td><strong>0.0008</strong></td><td><strong>0.0461</strong></td><td><strong>0.0042</strong></td></tr><tr><td>TOC</td><td><strong>0.0006</strong></td><td>0.8876</td><td>0.5189</td><td><strong>0.0004</strong></td></tr><tr><td>PN/PS</td><td>0.0569</td><td>0.0777</td><td>0.0564</td><td><strong>0.0481</strong></td></tr><tr><td rowspan="4">U. confervicolum biofilm</td><td>Biomass</td><td><strong>0.0011</strong></td><td><strong>0.000002</strong></td><td>0.4683</td><td><strong>0.0010</strong></td></tr><tr><td>ΦPSII</td><td>0.0549</td><td>0.1909</td><td>0.1909</td><td><strong>0.0496</strong></td></tr><tr><td>TOC</td><td>0.1989</td><td><strong>0.0062</strong></td><td>0.0991</td><td>0.0509</td></tr><tr><td>PN/PS</td><td><strong>0.0011</strong></td><td><strong>0.000002</strong></td><td>0.4683</td><td><strong>0.0047</strong></td></tr></tbody></table>

Significant *p*-values are in bold, *n* = 3.

and 200 µL of BCA reagent (Sigma-Aldrich) were incubated in a 96-well microplate (15 min at 60°C) before measuring the optical density at 540 nm (microplate reader, Synergy Mx Biotek). Bovine serum albumin (BSA) with concentrations ranging from 0 to 800 mg L⁻¹ was used as a standard. Polysaccharide (PS) concentration was measured by the anthrone method (Dreywood, 1946). One hundred µL of EPS extract and 200 µL of anthrone reagent (2% anthrone in 96% sulfuric acid) were incubated in a 96-well microplate (30 min at 60°C), cooled at room temperature for 10 min before measuring the optical density at 620 nm. Glucose with concentrations ranging from 0 to 100 mg L⁻¹ was used as a standard.

## Statistical Analyses

The pre-disturbance state was used as a reference to assess the impact of the disturbance sequence and the recovery after rewetting on EPS production (quantity and quality). The measurements realized at day 32 (D32, end of disturbance) and day 46 (D46, end of re-wetting period) were normalized by the measures realized at day 14 (D14, before disturbance), by the following expressions:

$$ \text{Impact}(\%) = 100 - (100 \times V_{\text{D32}}/V_{\text{D14}}) \quad (2) $$

$$ \text{Recovery}(\%) = 100 \times V_{\text{D46}}/V_{\text{D14}} \quad (3) $$

where $V_{\text{D14}}$ represents the mean value of the parameter for the measurements performed from one block (including three mini-channels sampled) at day 14, and $V_{\text{D32}}$ and $V_{\text{D46}}$ represent the mean value of the same parameter for the measures performed from one mini-channel of the same block at day 32 and day 46, respectively.

Statistical analyses were performed using Statistica software (version 8). For all analyses, the normality and homoscedasticity were checked on each dataset (biofilm biomass, photosynthetic efficiency, EPS amount) with the Shapiro-Wilk test and data were transformed if needed. Two-way ANOVAs and one-way ANOVAs were used to test the effects of environmental factors (temperature and light intensity or P concentration) (i) on biofilm biomass, photosynthetic efficiency and EPS amount and composition before the disturbance or (ii) on the impact and recovery of EPS amount and composition after the disturbance

and the rewetting periods, respectively, followed by a Tukey post hoc test. The magnitude of the difference between pre- and post-disturbance (end of disturbance or end of rewetting period) was assessed using Hedges'g (Hedges, 1981) effect size calculated from *t*-statistics derived from student tests (Berben et al., 2012) using the R package {esc}. The magnitude of the effects of temperature, light and phosphorous concentration was measured using the partial eta-squared effect size calculated from 2-way and one-way ANOVAs with the R package {effectsize}. Data given in the text are means ± standard error (SE). For all statistical analyses, significance was inferred at *p* < 0.05.

## RESULTS

### Combined Effects of Light Intensity, Temperature, and Phosphorus on Biofilm Physiology and Extracellular Polymeric Substances Production Before the Sequential Disturbance

The effects of light intensity, temperature, and P concentration were considered during the first 14-day period on biofilm (growth and maximum quantum yield) and EPS production (quantity as extracted TOC and quality as PN/PS ratio) (Table 1). The two biofilms showed very contrasted responses to the environmental conditions, with a higher influence of temperature on the diatom biofilm and a higher influence of light intensity and phosphorus concentration on the green alga biofilm.

The biomass production varied from 0.21 ± 0.03 to 0.51 ± 0.06 mg DW cm⁻² for *N. palea* biofilm, with a 2.4 ratio between the lowest and the highest mean values (Figure 2). The diatom growth and Φ PSII were positively affected by the temperature. Those parameters were less impacted by the light intensity. The modification of phosphorus concentration tented to decrease both growth and Φ PSII (Figure 2). The response of EPS production (TOC) to the environmental conditions was opposite to that of the biomass. The range of variation was narrower than for the biomass, with a 1.4 ratio between the lowest and the highest mean values. The ratio PN/PS was only significantly affected by P concentration, with the lowest value obtained at the lowest P concentration.
<figure><img src="image_122.png" /><figcaption>**FIGURE 2** | Scatter plot of the biomass (DW = dry weight) (A), maximum quantum yield (B), total organic carbon (quantity of EPS) (C), and ratio protein/polysaccharide in the EPS (D) in *N. palea* biofilm before the disturbance. The letters indicate statistically homogeneous groups (Tukey *post hoc* test after ANOVA). No letters for non-significant ANOVA (the bars represent the means, *n* = 3). L/t: high/low light intensity (P100), T/t: high/low temperature (P100), P50, P100, P165: 50, 100, and 165% of the standard initial phosphorous concentration, respectively, associated with *L* and *T* conditions.</figcaption></figure>
The biomass production was more variable for the *U. confervicolum* biofilm, with mean values from 0.50 ± 0.06 to 2.29 ± 0.17 mg DW cm⁻² (4.6 highest/lowest ratio) (Figure 3). It was positively influenced by light intensity and negatively affected by the temperature (Table 1). The biofilm growth was also negatively impacted by P concentration. The Φ PSII was only slightly modified by the environmental conditions. The same tendency was observed for the EPS production, with an additional negative effect of high light intensity. The PN/PS ratio in the green alga biofilm was very variable, with a 4.1 ratio between the highest and the lowest mean values. It was increased with a decrease of light intensity and temperature, and by a modification in P concentration compared to the reference condition.

To summarize these results, the increase in temperature yielded higher accumulation of diatom biofilm biomass and decreased EPS content and PN/PS ratio, while green alga biofilm accumulated more biomass at the highest light condition and exhibited lower EPS content and PN/PS ratio.

For the two biofilms, there was a significant negative correlation between biomass and EPS production (r = -0.49, p = 0.025 and r = -0.73, p < 0.001 for the diatom and green alga biofilms, respectively) (Supplementary Figure 1). For the diatom biofilm, EPS production was also negatively correlated with the maximum quantum yield (r = -0.70, p < 0.001). For the green alga biofilms, a positive correlation was observed (r = 0.63, p = 0.002), but it was driven by one treatment only. Without these points the correlation was similar to the one of the diatom biofilms (r = -0.47, p = 0.05).

## Impact of the Disturbance and Recovery of Extracellular Polymeric Substances Quantity and Quality

The response of the biofilms to the disturbance, in terms of EPS quantity and quality, was analyzed in two steps. First, we compared pre- and post-disturbance values to show potential resistance and recovery for each environmental condition (Figures 4, 5). The post-disturbance values were either measured at the end of the disturbance (indication of resistance) or at the end of the rewetting period (indication of recovery). Second, we assessed the effects of light, temperature and P concentration on the resistance and resilience with ANOVA and derived effect size (Figure 6 and Table 2).

The sequential disturbance had a strong impact on EPS quantity (Figure 4 and Supplementary Figures 1, 2). For the *N. palea* biofilm, it induced a decrease in EPS quantity, with the exception of the LtP100 condition (increase) and LtP100 and LTP50 conditions (no effect). For the *U. confervicolum* biofilm, the decrease in EPS quantity was observed in all conditions except the LTP50. For both biofilms, the increase in temperature increased the negative impact of the disturbance. For the *N. palea* biofilm, at the end of the rewetting period, the EPS quantity values were either identical or higher than the pre-disturbance values, while in the *U. confervicolum* biofilm they remained lower in all but one condition. For both algae, EPS quantity was less

affected by the disturbance at low phosphorus concentration than at medium and high concentrations.

The quality of EPS was very sensitive to the combined disturbance in *N. palea* biofilm but only marginally affected in *U. confervicolum* biofilm (Figure 5 and Supplementary Figures 2, 3). The disturbance induced a decrease in the PN/PS ratio in the diatom biofilm in all conditions except the LTP100 one, where no effect was observed. Contrary to the EPS quantity, no recovery was observed at the end of the rewetting period for the EPS quality.

Combined effects of temperature, light, and phosphorous concentration on the resistance and recovery were assessed with ANOVAs (Table 2) and eta-squared effect sizes (Figure 6). For the impact of disturbance on EPS quantity (Figure 6A), all the environmental factors had a significant effect for the *N. palea* biofilm. When temperature, light intensity, and P concentration increased, the impact of the disturbance increased as well. In contrast, the environmental factors had no effect on the impact of disturbance on EPS quality (Figure 6B). For *U. confervicolum* biofilm, only the phosphorus concentration modified the impact of the disturbance on both EPS quantity and quality, with opposite directions: for the quantity the impact was lower at the lowest concentration, while for EPS quantity, the impact was lower at the highest concentration.

The recovery of EPS after the rewetting period was not influenced by the same factors than the resistance to the disturbance. For the *N. palea* biofilm, P concentration modified the recovery of both EPS quantity and quality, with the lowest resilience observed for the highest concentration. The recovery of EPS quality also increased with an increase in temperature and light intensity.

## DISCUSSION

EPS are critical for the resilience of biofilms exposed to various stresses (Kroll et al., 2014; Flemming et al., 2016; Shetty et al., 2019). It is thus important that their production remains stable despite the disturbance biofilms may be exposed to. EPS production by biofilms is known to be influenced by environmental conditions (Wolfstein and Stal, 2002; Di Pippo et al., 2012). The question tackled here is in what extent variations in the environmental conditions could affect the resilience properties of EPS when biofilms are disturbed. A follow-up study would be to assess if modifications in biofilm EPS resilience can impact the functional resilience of biofilms. Our first hypothesis was confirmed, the results showing a strong influence of light, temperature, or phosphorous on the resilience of EPS quantity and quality. Contrary to our second hypothesis, the factors that influenced the most biofilm growth were not necessarily the factors influencing the EPS resilience. Moreover, factors that had no effects on biofilm growth or EPS production strongly influenced EPS resistance and recovery (e.g., light intensity for the *N. palea* biofilm).

Given that diatoms and green algae are well-known to produce high amount of EPS (de Brouwer et al., 2002; Xiao and Zheng, 2016; Bohorquez et al., 2017) and that the
<figure><img src="image_123.png" /><figcaption>**FIGURE 3** | Scatter plot of the biomass (DW = dry weight) (A), maximum quantum yield (B), total organic carbon (quantity of EPS) (C), and ratio protein/polysaccharide in the EPS (D) in *U. confervicolum* biofilm before the disturbance. The letters indicate statistically homogeneous groups (Tukey *post hoc* test after ANOVA). No letters for non-significant ANOVA (the bars represent the means, *n* = 3). *L/l*: high/low light intensity (P100), *T/t*: high/low temperature (P100), P50, P100, P165: 50, 100, and 165% of the standard initial phosphorous concentration, respectively, associated with *L* and *T* conditions.</figcaption></figure>
<figure><img src="image_124.png" /><figcaption>**FIGURE 4** | Effect size (Hedges's ± 95% confidence interval) on the total organic carbon (EPS quantity) measured before the disturbance and at the end of the disturbance (gray circles) or before the disturbance and at the end of the rewetting period (black circles), for the *N. palea* biofilm and *U. confervicolum* biofilm. The effect size was measured for each growth condition. Full circles: significant effects, open circles: non-significant effects. L/I: high/low light intensity (P100), T/t: high/low temperature (P100), P50, P100, P165: 50, 100, and 165% of the standard initial phosphorous concentration, respectively, associated with L and T conditions.</figcaption></figure>

biomass of the algal cells accounted for the majority of biofilm biomass (microscopic observations), we assumed that the EPS found in the biofilms were mainly produced by algal cells. However, the analyses that were performed did not allow the distinction between algal and bacterial EPS.

## The Effects of Light Intensity, Temperature, and P Concentration on Biofilm Physiology and Extracellular Polymeric Substances Production

Despite the moderate amplitudes in the variations of the environmental conditions, strong impacts on biofilm and physiology have been observed. Although the study considered only two different simplified biofilms, it demonstrated very different patterns in the response to environmental conditions: the diatoms were more sensitive to the temperature, and the green algae were more sensitive to the light intensity. Such contrasting patterns are consistent with the conclusion of Falk et al. (1996) who stated that it is not possible to describe a general mechanism for photosynthetic adjustment to temperature that encompasses all phototrophic species because of genetic diversity and differential strategies in growth and development.

Unlike Di Pippo et al. (2012) conclusion, 30 µmol photons s⁻¹ m⁻² in the present study provided sufficient light intensity for the development of the phototrophic biofilms. Light intensity, from 30 to 70 µmol photons s⁻¹ m⁻², induced no significant effect for *N. palea* biofilm growth. For the green alga biofilm, and in agreement with Ylla et al. (2009), light intensity was the limiting parameter which control the growth. *U. confervicolum* is a filamentous species and forms a thick biofilm with streamers in the water at the biofilm surface that can create a self-shading effect and the light intensity can therefore quickly become a limiting factor during biofilm development (Rao, 2010; Villanueva et al., 2011). On the contrary, the pennate diatom forms a thin biofilm and the light can be accessed by most cells. These differences in algal morphology, associated with the higher biomass reached in *U. confervicolum* biofilms, may explain the differential response to light intensity increase.

Phosphorus which is often directly involved in eutrophication processes (Smith et al., 1999), had an effect on the two phototrophic biofilms with an increase in P concentration inducing a decrease of the green alga biofilm growth and an increase in the diatom biofilm growth. These results suggest that the composition of natural phototrophic biofilms should strongly depend on the P concentration in the surface water. The
<figure><img src="image_125.png" /></figure>

**FIGURE 5** | Effect size (Hedges's ± 95% confidence interval) on the protein/polysaccharide ratio (EPS quality) measured before the disturbance and at the end of the disturbance (gray circles) or before the disturbance and at the end of the rewetting period (black circles), for the *N. palea* biofilm and *U. confervicolum* biofilm. The effect size was measured for each growth condition. Full circles: significant effects, open circles: non-significant effects. *L/t*: high/low light intensity (P100), *T/t*: high/low temperature (P100), P50, P100, P165: 50, 100, and 165% of the standard initial phosphorous concentration, respectively, associated with *L* and *T* conditions.

<figure><img src="image_126.png" /></figure>

**FIGURE 6** | Effect size (partial eta-squared ± 95% confidence interval) on the impact (gray circles) or recovery (black circles) of the total organic carbon (A) and the protein/polysaccharide ratio (B) for the *N. palea* biofilm and *U. confervicolum* biofilm for the environmental factors tested: temperature (Temp), light intensity (Light), phosphorous concentration (P). The temperature * light intensity interaction is also given. Closed circles: significant effects, open circles: non-significant effects.
<table><caption>**TABLE 2** | *P*-values for two-way and one-way ANOVAS to test the effect of environmental conditions on the resistance and recovery of biofilm EPS quantity and quality.</caption><thead><tr><th></th><th></th><th></th><th>Temperature</th><th>Light intensity</th><th>Light * Temp</th><th>P concentration</th></tr></thead><tbody><tr><td rowspan="4">Resistance</td><td rowspan="2">N. palea biofilm</td><td>TOC</td><td><strong>0.000001</strong></td><td><strong>0.00004</strong></td><td><strong>0.00005</strong></td><td><strong>0.0002</strong></td></tr><tr><td>PN/PS</td><td>0.1018</td><td>0.6656</td><td>0.2587</td><td>0.15000</td></tr><tr><td rowspan="2">U. confervicolum biofilm</td><td>TOC</td><td>0.0950</td><td>0.7290</td><td>0.2400</td><td><strong>0.00004</strong></td></tr><tr><td>PN/PS</td><td>0.0525</td><td>0.7690</td><td>0.3680</td><td><strong>0.0004</strong></td></tr><tr><td rowspan="4">Recovery</td><td rowspan="2">N. palea biofilm</td><td>TOC</td><td>0.0624</td><td>0.7152</td><td>0.9074</td><td><strong>0.0004</strong></td></tr><tr><td>PN/PS</td><td><strong>0.0308</strong></td><td><strong>0.0033</strong></td><td>0.2344</td><td><strong>0.002</strong></td></tr><tr><td rowspan="2">U. confervicolum biofilm</td><td>TOC</td><td>0.1114</td><td><strong>0.0043</strong></td><td>0.0637</td><td><strong>0.00001</strong></td></tr><tr><td>PN/PS</td><td>0.7769</td><td>0.1984</td><td>0.2503</td><td>0.67</td></tr></tbody></table>

Significant *p*-values are in bold, *n* = 3.

maximum quantum yield of the green alga biofilm was promoted by increasing *P* concentration in the culture medium, until it reached a plateau. In contrast, for the diatom biofilm, a decrease of the yield was observed for the highest *P* concentration, suggesting that a threshold was exceeded. The yield is known to be influenced by nutrient stress in algae (Parkhill et al., 2001). The *P* concentration used in the experiment was very high, but it was chosen according to the concentration in combo medium to keep similar growth conditions than the stock cultures. Note that the nutrient level was not adjusted during the experiments.

Concerning EPS production, weak negative correlations were observed between the maximum quantum yield and the quantity of TOC extracted. This result is rather unexpected, given that many authors have shown that EPS are released by cells concomitantly to oxygenic photosynthesis (Staats et al., 2000a) and primary production (Underwood and Paterson, 2003), assimilated to a metabolic response to stresses (Perkins et al., 2001; Orvain et al., 2003). However, there is no direct and clear link between the maximum quantum and the photosynthetic activity. The negative relationship between biofilm growth and EPS production suggests that when algal growth is limited and the photosynthesis is not, organic carbon produced through photosynthesis may be accumulated under the form of EPS, similarly to the Growth-Differentiation Balance Hypothesis for the synthesis of defense metabolites (Herms and Mattson, 1992). However, other regulation mechanisms are likely to be involved since EPS production was increased under low light intensity conditions for the green alga biofilm. Note that an increased EPS production in nutrient-limited cells has also been observed in marine diatoms (Staats et al., 2000b; Khandeparker and Bhosle, 2001).

In addition to EPS quantity, their nature was directly influenced by the environmental factors. In the two biofilms, the EPS were dominated by proteins (PN/PS ratio above 1) in all the growth conditions. EPS are often considered as essentially composed of polysaccharides, but a similar high content in proteins has been reported elsewhere, for instance for biofilms at the sediment surface, in freshwater (Gerbersdorf et al., 2009) and marine (Agogue et al., 2014) environments. The PN/PS ratio was highly variable in *U. confervicolum* biofilms. The PN/PS ratio significantly decreased (resulting from an increase of the quantity of polysaccharides) with an increase in temperature.

## The Effects of Light Intensity, Temperature, and *P* Concentration on Extracellular Polymeric Substances Response to the Disturbance

Although several studies considered the effects of environmental conditions on biofilm EPS quantity and quality, to our knowledge none assessed how these conditions could modulate the resistance and recovery of EPS after a disturbance. Here we showed, in agreement with our first hypothesis, that the resilience of EPS production after a complex disturbance, i.e., metal exposure followed by dry and rewetting periods, strongly depended on the environmental conditions. This dependency to the environmental conditions varied between the two simplified biofilms that were tested. Moreover, the environmental conditions impacted differently the quantitative and qualitative response of EPS to the disturbance. This opposition of the response pattern of EPS quantity and quality in the two biofilms indicates a decoupling of the regulation of those two parameters. Contrary to our second hypothesis, the environmental factors that affected the resilience of EPS production were not completely the same that affected biofilm growth, as assessed with our factorial design. Indeed, in diatom biofilms, light intensity had no effect on growth while it significantly modified the resistance of EPS quantity and the recovery of EPS quality (see **Table 2**). Algal species have developed various metabolic adaptations and defense systems to survive under variety of environmental stresses. A four-day metal exposure at non-toxic concentration followed a 2-week dry period was enough to cause changes in the EPS production by the two phototrophic biofilms. At the end of the disturbance, the quantity of EPS was either higher or lower than that before the disturbance, depending on growth conditions and on algal species.

The underlying idea of this experiment is that EPS resilience should contribute to biofilm functional resilience. Unfortunately, this could not directly be assessed because such experiments require the measurement of gross or net primary production. Concerning the protective role of EPS, contrasting results can be found in the literature, notably for the heavy metals. The latter can have either increasing (e.g., Miao et al., 2009) or nil effect (Mota et al., 2015) on EPS production while EPS supposedly contribute to the defense of the cells against metals. EPS are
supposed to contribute to the protection of microorganisms against disturbance through different mechanisms. For instance, drying disturbance encompasses multiple stresses such as limitation of substrate and nutrient diffusion, which can be limited by the use of extracellular polymers as a C source by the cells. Inversely, EPS produced by filamentous cells form the viscous mucilage that surrounds cells (Underwood and Paterson, 2003) and probably play an important direct role in cell protection under unfavorable conditions. Microorganisms tolerate desiccation through a set of molecular mechanisms including the production of polysaccharides that form a reservoir for water and proteins thus capable to stabilize macromolecules and membranes. Extracellular polysaccharides, probably very hydrophilic, could be very efficient to retain interstitial pore water and protect phototrophic cells against desiccation. Only for the diatom biofilm, we observed modifications of EPS composition with an increase in polysaccharides at the end of the disturbance period. However, to verify the stability of this new status, it would have been necessary to follow rewetted biofilms during a longer period. This is in agreement with Orvain et al. (2003) who suggested that polysaccharides are involved in the formation of a protective wall, supplying hydrophilic and stabilizing properties that could convey important functions to the biofilm matrix in terms of resistance to environmental stresses.

The results of this study showed a divergence in the resilience ability of two very simplified phototrophic biofilms regarding to their EPS production. It appeared that in several cases small variations in the environmental conditions had no direct effect on EPS production, while exhibited a significant effect on the resistance and recovery of EPS production after a realistic disturbance. Though the experiment was performed with very simplified biofilms, under artificial conditions, it calls a need for further investigations which are necessary to anticipate the effect of a disturbance on microbial physiology in natural biofilms. The fact that the 3-degrees temperature increase amplified the impact of the disturbance on EPS quantity suggests the existence of non-additive effects between the contamination-dry period disturbance and warming. In a context of global change, this is a preoccupying observation, which highlights the importance of considering not only the direct effects of warming and climate change on the microbial communities, but also on their indirect effects on the ability of communities to cope with additional disturbances. During the last decade, the number

of studies considering the resilience of biofilms increased, as well as the number of studies considering the responses of ecosystem components to combined stresses. However, the studies focusing on the modulation of ecosystem resilience ability by environmental conditions remain very scarce. In a context of global change, with an increasing frequency of disturbances, a considerable effort should be made in this direction.

## DATA AVAILABILITY STATEMENT

The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.

## AUTHOR CONTRIBUTIONS

EG-N, EL, JL, and J-LR designed the experiments. CB, EL, JF, J-LR, and QA contributed to the laboratory work and analyses. OO and OP realized Cu speciation calculation. EL and JL wrote the first manuscript, and then improved by the other authors.

## FUNDING

EL was supported by a Ph.D. fellowship from the French "Ministère de l'Enseignement Supérieur, de la Recherche et de l'Innovation." This work was funded by the Idex UNITI grant of the University of Toulouse, France (No. 2016-46-CIF-D-DRDV).

## ACKNOWLEDGMENTS

We thank Didier Lambrigot for TOC measurements.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2021.742027/full#supplementary-material

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**Conflict of Interest:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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# Diversity, Functions and Antibiotic Resistance of Sediment Microbial Communities From Lake Geneva Are Driven by the Spatial Distribution of Anthropogenic Contamination

Emilie Lyautey¹,², Chloé Bonnineau¹, Patrick Billard³, Jean-Luc Loizeau⁴, Emmanuel Naffrechoux⁵, Ahmed Tlili⁶, Edward Topp⁷,⁸, Benoît J.D. Ferrari⁹ and Stéphane Pesce¹*

**OPEN ACCESS**

**Edited by:**
Carmen Palacios,
Université de Perpignan Via Domitia,
France

**Reviewed by:**
Kevin Thomas Finneran,
Clemson University, United States
Naresh Singhal,
The University of Auckland,
New Zealand

*Correspondence:
Stéphane Pesce
stephane.pesce@inrae.fr

**Specialty section:**
This article was submitted to
Microbiotechnology,
a section of the journal
Frontiers in Microbiology

**Received:** 09 July 2021
**Accepted:** 28 September 2021
**Published:** 18 October 2021

**Citation:**
Lyautey E, Bonnineau C, Billard P, Loizeau J-L, Naffrechoux E, Tlili A, Topp E, Ferrari BJD and Pesce S (2021) Diversity, Functions and Antibiotic Resistance of Sediment Microbial Communities From Lake Geneva Are Driven by the Spatial Distribution of Anthropogenic Contamination. *Front. Microbiol.* 12:738629.
doi: 10.3389/fmicb.2021.738629

¹ INRAE UR RiverLy, Villeurbanne, France, ² INRAE, Université Savoie Mont Blanc, CARRTEL, Thonon-les-Bains, France, ³ Université de Lorraine, CNRS, LIEC, Nancy, France, ⁴ Department F.A. Forel for Environmental and Aquatic Sciences, University of Geneva, Geneva, Switzerland, ⁵ EDYTEM, CNRS, Université Savoie Mont Blanc, Chambéry, France, ⁶ Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland, ⁷ Agriculture and Agri-Food Canada, London, ON, Canada, ⁸ Department of Biology, University of Western Ontario, London, ON, Canada, ⁹ Swiss Centre for Applied Ecotoxicology (Ecotox Centre), Lausanne, Switzerland

Lake sediments are natural receptors for a wide range of anthropogenic contaminants including organic matter and toxicants such as trace metals, polycyclic aromatic hydrocarbons, polychlorinated biphenyls that accumulate over time. This contamination can impact benthic communities, including microorganisms which play a crucial role in biogeochemical cycling and food-webs. The present survey aimed at exploring whether anthropogenic contamination, at a large lake scale, can influence the diversity, structure and functions of microbial communities associated to surface sediment, as well as their genetic potential for resistance to metals and antibiotics. Changes in the characteristics of these communities were assessed in surface sediments collected in Lake Geneva from eight sampling sites in October 2017 and May 2018. These sampling sites were characterized by a large concentration range of metal and organic compound contamination. Variation between the two sampling periods were very limited for all sampling sites and measured microbial parameters. In contrast, spatial variations were observed, with two sites being distinct from each other, and from the other six sites. Benthic communities from the most contaminated sampling site (Vidy Bay, near the city of Lausanne) were characterized by the lowest bacterial and archaeal diversity, a distinct community composition, the highest abundance of antibiotic resistance genes and functional (respiration, denitrification, methanogenesis, phosphatase, and beta-glucosidase) activity levels. The second sampling site which is highly influenced by inputs from the Rhône River, exhibited low levels of diversity, a distinct community composition, high abundance of antibiotic resistance genes and the highest bacterial abundance. Overall, our results suggest that local anthropogenic contamination, including organic
matter and toxicants, is a major driver of the diversity and functioning of sediment-
microbial communities in Lake Geneva. This highlights the need to consider benthic
microbial communities and a suite of complementary ecotoxicological endpoints for
more effective environmental risk assessments of contaminants in lake sediments.

Keywords: benthic communities, microbial ecotoxicology, metals, organic matter, PCB, PAH, resistance genes, urban contamination

INTRODUCTION

The sediment compartment in lakes can act as a sink for contaminants, including not only nutrients and organic matter but also metals, persistent organic pollutants [e.g., polycyclic aromatic hydrocarbons, polycyclic aromatic hydrocarbons (PAHs); polychlorinated biphenyls, polychlorinated biphenyls (PCBs)] and other substances such as pesticides or pollutants of emerging concerns (e.g., pharmaceuticals including antibiotics) (Xu et al., 2017; Codling et al., 2018; Golovko et al., 2020). Due to their hydrophobic nature, once deposited most of these contaminants associate strongly to the sediment (Sedláček et al., 2020). Therefore, the vertical depth profiles of contaminants in sediment cores generally reflect the temporal history of contamination, with increasing depth being associated with older contamination events (Lécrivain et al., 2018). On the other hand, horizontal gradients of contamination depend mainly on the distance from the contamination sources. The contamination of surface sediments (0–5 cm layer) in the littoral and pelagic zones of lakes can thus exhibit substantial spatial heterogeneity according to the distribution of point- and diffuse sources of pollution in the surrounding watershed, and contaminant fluxes carried into the lake by tributaries (Marvin et al., 2004; Lécrivain et al., 2019). Therefore, benthic communities in lake sediments can experience different exposures to contaminants including nutrients and organic matter according to their location. However, the resulting effects on these communities still under-investigated (Pesce et al., 2018) and little is known about the potential relationships between the spatial contamination heterogeneity in lake surface sediment, and the consequent spatial alterations of benthic community diversity, structure and functions (Haller et al., 2011; Sauvain et al., 2014; Jin et al., 2019).

In lake surface sediments, microorganisms are highly
abundant and characterized by a large taxonomic and functional
diversity, making them key players in a multitude of ecosystem
processes (Schallenberg and Kalff, 1993; Pearman et al., 2020).
These processes include biogeochemical cycling of nitrogen, the
recycling of autochthonous and allochthonous organic matter,
and the dissipation of organic contaminants (Vadeboncoeur
et al., 2002; Haglund et al., 2003; Bedard, 2008; Schultz and
Urban, 2008). Several laboratory studies have shown that
environmental concentrations of metals (Mahamoud Ahmed
et al., 2018, 2020) and organic contaminants such as pesticides
(Widenfalk et al., 2004, 2008), PCBs (Diepens et al., 2015)
and PAHs (Zhang et al., 2014) can affect the diversity,
structure and functional potential of exposed sediment microbial
communities. The structural and functional properties of
microbial communities in lake sediments can vary horizontally at

a relatively limited geographical scale, according to several local
environmental factors (Krzmarzick et al., 2013; Pearman et al.,
2020). However, the role of anthropogenic contamination in
the spatial structuration of those microbial assemblages and the
resulting effects on the functional properties of lake benthic
ecosystems remain largely unknown.

The contamination of Lake Geneva has been monitored with a focus on various groups of contaminants such as PAHs, PCBs, metals, pharmaceuticals, and pesticides in surface water and sediments (e.g., Poté et al., 2008; Perazzolo et al., 2010; Hoerger et al., 2014; Larras et al., 2016). For example, a large sampling survey undertaken in 2015 mapped the contamination of the surface sediments at the whole lake scale (Loizeau et al., 2017). Sediments in the Vidy Bay near the city of Lausanne were the most contaminated by metals, organic pollutants and organic matter (Loizeau et al., 2017). The high contamination of sediments in this area has been documented for decades (Grandjean et al., 1990; Poté et al., 2008; Loizeau et al., 2013; Gascon Diez et al., 2014; Masson and Tercier-Waeber, 2014). This is mainly due to historic inputs from urban sewage effluents (Gascón Díez et al., 2017), which is also reflected by the prevalence of fecal-indicator bacteria (Poté et al., 2008) and antibiotic-resistance genes (Czekalski et al., 2014). The contamination has been suggested as an important driver of microbial community structure (Haller et al., 2011). Besides this hotspot of contamination, there is relative spatial heterogeneity in the contamination at the whole Lake scale with a strong influence of the Rhone River, which is the main Lake tributary, and of the lakeshore (Loizeau et al., 2017).

In this context, we performed two sampling campaigns to
investigate the spatio-temporal variations in benthic microbial
communities collected in surface sediments from eight sampling
sites in Lake Geneva. These sites, which are widely geographically
distributed at the lake scale, cover a large range of contamination
levels by metals and organic toxicants (Loizeau et al., 2017).
We included one site located in the Vidy Bay and one site
located near the Rhone River mouth into the lake. The objective
was to assess whether spatial and/or temporal changes in
the structural and functional characteristics of the studied
community are driven by anthropogenic contamination. For
this purpose, microbial communities in sediment samples
were characterized for bacterial and archaeal population
diversity, composition and structure, bacterial abundance,
functional (respiration, denitrification, methanogenesis, leucine
aminopeptidase, phosphatase, and beta-glucosidase) potential
activities and the abundance of gene targets associated with
resistance to selected metals and antibiotics. We expected
the microbial community structure from these eight sites
to exhibit spatial and temporal dynamics, with functional properties linked both to community composition and to the environmental conditions prevailing in the sediment compartment on the sampling dates. Contamination levels by metals and organic toxicants were expected to select for more tolerant populations at the sampling site scale, leading to change in community structure and to increasing genetic potential of resistance, with possible impacts on ecosystem functions.

# MATERIALS AND METHODS

## Sampling Sites and Sample Collection

Lake Geneva is the largest natural lake in western Europe (580 km², 72 km long and 14 km wide), with a maximum depth of 309 m, and a watershed surface area of 7,999 km². The lake is located between France and Switzerland, and its major tributary and outflow is the Rhône River. The water residence time is 11.3 years (CIPEL, 2018). Lake Geneva is a deep monomictic lake with irregular complete winter overturns occurring on average every 5 years (Schwefel et al., 2016).

Sample collection was carried out on October 2017 (26th) and May 2018 (23rd, 24th, and 25th) at eight sampling sites. Sampling sites were referred as sites number 5, 6, 21, 29, 32, 36, 53, and 78 (Figure 1), according to the map of sampling sites of Loizeau et al. (2017). The sites were chosen to cover a large range of contamination levels by metals and organic toxicants, as reported by Loizeau et al. (2017). Sites 29, 32, 53, and 78 were sampled both years whereas sites 5, 6, 21, and 36 were only sampled in 2018 due to weather conditions in 2017. Sampling site descriptions, sampling date, geographical coordinates, and depth are provided in Table 1.

Surface sediment sampling was carried out using an Eckman grab sampler, and the top 15–25 cm of sediment were grabbed. Samples for subsequent analyses were collected in the Eckman grab, from the first 2-cm of sediment directly in the field, and stored for further analyses. For each site, three independent samples were collected. Each sample was sub-sampled directly on the boat, and samples were stored at 4°C during transport to the laboratory with arrival within 6 h.

## Sediment Chemical Characterization

The analyses of the physico-chemical properties of sediment from sites 29, 32, 53, and 78 were carried out on samples collected on October 2017, and from sites 5, 6, 21, and 36 on samples collected on May 2018. These analyses included concentrations of trace metals (Ti, Cr, Co, Ni, Cu, Zn, As, Mo, Ag, Cd, Sn, Pb, and Hg), 12 PCBs, 16 PAHs, and ancillary parameters [grain size distribution, organic matter (OM), carbonate and total organic carbon content (TOC), total phosphorus content (Ptot)]. Ti was used as a proxy of the Rhône River influence on Lake Geneva, as suspended particle load from this river mainly originate from the erosion of Alpine rocks richer in Ti-bearing minerals than rocks from the calcareous Jura mountains drained by the others tributaries, or calcite particles directly precipitated from the water column.

Sediment grain-size distribution was determined on wet sediments using a laser diffraction analyzer (Coulter LS-100, Beckman-Coulter, United States), following the procedure described by Loizeau et al. (1994).

Samples were freeze-dried in a CHRIST BETA 1-8 K freeze drying unit (−54°C, 6 Pa) for a minimum of 48 h. Organic matter and calcium carbonate (CaCO₃) contents in sediments were estimated by Loss on Ignition. Samples were heated to 550°C for 30 min to estimate the OM mass loss and then heated to 1000°C for another 30 min to estimate the CaCO₃ content (Dean, 1974). The CaCO₃ content was calculated by multiplying the mass loss at 1000°C by 2.2742, the molar mass ratio of calcite to carbon dioxide.

Total phosphorus (TP) was measured with a spectrophotometer (Helios Gamma UV-Vis Thermo Electroporation, Thermo scientific, United States) at 850 nm. The sediment sample preparation for TP analysis was performed as follow; 50 mg of ignited sediment (after heating at 550°C for 1 h) were diluted in 5 mL HCl 1 N and introduced in centrifuge tubes. The mixture was ultrasonicated (at ambient temperature) during 16 h and centrifuged (4000 × rpm) during 20 min. The TP concentration was determined by measuring the absorbance of the blue complex obtained after reduction of molybdophosphoric acid according to previously described method (Murphy and Riley, 1962; Harwood et al., 1969; Burrus et al., 1990).

Quadrupole based inductively coupled plasma mass spectrometry (ICPMS, model 7700 series, Agilent) was performed following sediment digestion in Teflon bombs heated to 150°C in analytical grade 2 M HNO₃ according to the Swiss Soil Protection Ordinance (OSol, Office Fédéral de l'environnement [OFEV], 1998). Multi-element standard solutions of different concentrations (0, 0.02, 1, 5, 20, 100, and 200 mg L⁻¹) were used for calibration. The total variation coefficients for triplicate sample measurements were less than 10%.

Total Hg was analyzed by Cold Vapor Atomic Absorption 187 Spectrophotometry (CV-AAS) using an Advance Mercury Analyzer (Model AMA 254, Altec, Czech Republic) through dry mineralization and pre-concentration of Hg and amalgamation on a gold trap (Szakova et al., 2004). The detection limit and working range were 0.01 ng and 0.05–600 ng, respectively. The relative error was usually ±5% and always less than 10% (Roos-Barraclough et al., 2002).

Polychlorinated biphenyls and PAHs were quantified on freeze-dried sediments. PCBs and PAHs were characterized according to the method described in Mwanamoki et al. (2014). Briefly, 5 g of dry sediment were extracted with a mixture of acetone (20% of the volume) and hexane (80% of the volume) for 4 h with a Soxhlet apparatus. At this point, interfering sulfur compounds were removed by adding activated copper to the extract. The organic extract was then concentrated to 1 mL in a vacuum rotary evaporator. The extract was further subject to fractionation and clean-up over a chromatographic column containing 3 g of Silica gel. Three separated fractions were collected: first with 16 mL of hexane, then 35 mL of hexane, and finally 50 mL of hexane:dichloromethane (v/v, 1:1). The
<figure><img src="image_128.png" /><figcaption>**FIGURE 1** | Map showing the location of Lake Geneva and of the sampling sites. ○ Sites sampled in May 2018 only; ● Sites sampled in both October 2017 and May 2018.</figcaption></figure>

first fraction should contain PCBs while PAHs are distributed in the three fractions. Following reduction of the volume, chemicals were measured by gas chromatography with triple mass spectrometry detection (GC-MS/MS, Thermo Scientific, TSQ Quantum XLS Ultra, Waltham, MA, United States).

## Bacterial Abundance and Functional Potential of the Microbial Community

Bacterial abundance was estimated by flow cytometry as described in Frossard et al. (2012). Briefly, 3 g of wet sediment were suspended in 10 mL of 2% formalin containing 0.1% pyrophosphate. After an ultrasonic treatment for 1 min (Branson Digital Sonifier 250, Germany) and homogenization, 1 mL subsample of each suspension was placed on top of 0.5 mL Histodenz solution (Sigma-Aldrich, Buchs, Switzerland) and centrifuged at 17,135 × g at 4°C for 90 min. The upper layer, containing bacterial cells, was recovered and stained with 0.1 mL mL⁻¹ of SYBER® Green I (Promega, Switzerland) in anhydrous dimethylsulfoxide and incubated during 15 min in the dark. A known concentration of fluorescent beads (Beckman Coulter, Switzerland) was added to the samples as a standard to determine the cell concentration. Samples were analysed with a Gallios flow cytometer (Beckman Coulter, Switzerland).

The functional potential of the microbial community was assessed through the measurement of three enzymatic activities: β-glucosidase, β-glu, EC 3.2.1.21; leucine aminopeptidase, LAP, EC 3.4.11.1; and phosphatase, Pase, EC 3.1.3.1; and three metabolic activities: aerobic respiration, denitrification and methanogenesis.

Briefly, to measure enzymatic activities, 1.2 g of wet sediment were incubated for 30 min with pre-determined optimal concentrations of the fluorogenic substrates 4-methylumbelliferyl-β-D-glucopyranoside (MUF-Glu, CAS No. 18997-57-4) for β-glu, L-leucine-7-amido-4-methylcoumarin

hydrochloride (Leu-AMC, CAS No. 62480-44-8) for LAP, and 4-methylumbelliferyl phosphatase (MUF-P, CAS No. 3368-04-5) for Pase (Mahamoud Ahmed et al., 2018). After the activities were stopped with glycine buffer (0.05 M glycine, 0.2 M NH₄OH, pH 10.4), the samples were centrifuged and the fluorescence in the supernatant was measured using a microplate reader (Exc: 360 nm/Em: 460 nm, Synergy HT BioTek Instruments). Results are expressed as nmol of fluorochrome (MUF or MCA) per g of sediment dw⁻¹ h⁻¹.

Potential rates of aerobic respiration, denitrification and methanogenesis were measured with 10 g of wet sediment according to the protocols described by Foulquier et al. (2013) and slightly adapted by Mahamoud Ahmed et al. (2018). Sediment was mixed with 10 mL of distilled water under aerobic conditions (aerobic respiration), or 10 mL of a KNO₃ (2.16 g L⁻¹) solution under anaerobic conditions (denitrification), or 10 mL of distilled water under anaerobic conditions (methanogenesis) in 150-mL glass flasks with rubber stoppers. Incubation flasks assigned to denitrification and methanogenesis measurements were purged three times with He to achieve anaerobiosis, and the internal pressure was then adjusted to atmospheric. For denitrification measurements, 15 mL of acetylene (C₂H₂, 10% v/v final volume) was added to inhibit N₂O reductase. All samples were incubated at 20°C in the dark with gentle shaking. After 2 h and 5 h, headspace gasses were sampled and analyzed by gas chromatography (Agilent 490 MICRO GC). Aerobic respiration, denitrification and methanogenesis activities are expressed as ng of gaseous product (CO₂ or N₂O or CH₄, respectively) per g of sediment dw⁻¹ h⁻¹.

## Microbial Community Structure
### DNA Extraction

Microbial sediment DNA was extracted from 0.5 g of wet sediment using a NucleoSpin Soil Kit (Macherey-Nagel EURL)
<table><caption>**TABLE 1** | Presentations of the sampling site characteristics: sampling date (in bold, those when the presented physico-chemical parameters were measured), geographical coordinates, depth, and physico-chemical sediment characteristics: organic matter (OM) content (± SD), total organic carbon (TOC) content, total phosphorus (Ptot), and Ti concentrations, median grain size (± SD), and the sums of sediment concentrations of the following trace metals (Cr, Co, Ni, Cu, Zn, As, Mo, Ag, Cd, Sn, Pb, and Hg) of the seven indicator PCBs, and of PAHs.</caption><thead><tr><th>Site</th><th>Date</th><th>Coordinates</th><th>Depth</th><th>Organic matter</th><th>Carbonate</th><th>TOC</th><th>Ptot</th><th>Median grain size</th><th>Ti</th><th>Σ other metals</th><th>Σ7PCBi</th><th>ΣPAH</th></tr><tr><th></th><th></th><th>Longitude</th><th>(m)</th><th>± SD (%)</th><th>± SD (%)</th><th>(%)</th><th>(mg kg<sup>-1</sup> dw)</th><th>± SD (µm)</th><th>(mg kg<sup>-1</sup> dw)</th><th>(mg kg<sup>-1</sup> dw)</th><th>(µg kg<sup>-1</sup> dw)</th><th>(µg kg<sup>-1</sup> dw)</th></tr></thead><tbody><tr><td>5</td><td>May 18</td><td>E6.18008</td><td>N46.26927</td><td>47</td><td>8.64 ± 0.35</td><td>48.14 ± 0.83</td><td>4.35</td><td>848.6</td><td>14.77 ± 3.26</td><td>37.3 ± 1.0</td><td>206.6</td><td>1120.8</td></tr><tr><td>6</td><td>May 18</td><td>E6.19270</td><td>N46.29642</td><td>55</td><td>8.95 ± 0.10</td><td>44.33 ± 0.26</td><td>4.59</td><td>834.8</td><td>7.73 ± 2.73</td><td>37.6 ± 1.5</td><td>294.5</td><td>1372.4</td></tr><tr><td>21</td><td>May 18</td><td>E6.33359</td><td>N46.37907</td><td>50</td><td>7.18 ± 0.33</td><td>42.09 ± 0.76</td><td>2.93</td><td>750.4</td><td>7.98 ± 2.79</td><td>75 ± 1.6</td><td>267.1</td><td>9.81</td><td>1139.4</td></tr><tr><td>29</td><td>May 18, Oct 17</td><td>E6.38462</td><td>N46.45147</td><td>95</td><td>6.38 ± 0.13</td><td>31.21 ± 0.22</td><td>2.76</td><td>872.0</td><td>10.57 ± 3.01</td><td>405.5 ± 1.8</td><td>321.8</td><td>7.40</td><td>1922.2</td></tr><tr><td>32</td><td>May 18, Oct 17</td><td>E6.42316</td><td>N46.46618</td><td>22</td><td>5.27 ± 0.21</td><td>36.61 ± 0.36</td><td>2.08</td><td>670.1</td><td>14.95 ± 3.90</td><td>177.7 ± 4.5</td><td>212.1</td><td>7.69</td><td>2262.5</td></tr><tr><td>36</td><td>May 18</td><td>E6.45097</td><td>N. 46.37102</td><td>32</td><td>4.79 ± 0.04</td><td>48.87 ± 0.35</td><td>2.67</td><td>549.3</td><td>19.07 ± 5.31</td><td>42.5 ± 2.4</td><td>169.8</td><td>5.20</td><td>13581.1</td></tr><tr><td>53</td><td>May 18, Oct 17</td><td>E6.58810</td><td>N46.51014</td><td>44</td><td>13.65 ± 0.09</td><td>19.70 ± 0.23</td><td>6.96</td><td>3900.0</td><td>34.82 ± 5.00</td><td>170.7 ± 6.2</td><td>1193.4</td><td>386.55</td><td>25261.9</td></tr><tr><td>78</td><td>May 18, Oct 17</td><td>E6.89261</td><td>N46.40998</td><td>60</td><td>2.73 ± 0.30</td><td>14.40 ± 0.32</td><td>0.68</td><td>659.4</td><td>11.12 ± 2.52</td><td>1735.6 ± 30.2</td><td>293.0</td><td>0.89</td><td>774.3</td></tr></tbody></table>

Detailed metals, PCB and HAP concentrations are presented in Supplementary Tables 1-3.

following the manufacturer's instructions with SL1 lysis buffer and additive Enhancer SX buffer. The extracted DNA was quantified fluorometrically after staining with QuantiFluor dsDNA Dye (QuantiFluor dsDNA System, Promega) using a Plate Chameleon™ fluorometer (Hidex; excitation 485 nm, emission 590 nm).

## High-Throughput 16S rRNA Gene Sequencing and Bioinformatic Analysis

PCR amplification for high-throughput 16S rRNA gene amplicon sequencing was carried out with the universal primer pair 515F and 909R targeting the V4–V5 hypervariable region of the 16S rRNA gene (Wang and Qian, 2009). Indexes were integrated to both primers following the dual-indexing procedure described by Kozich et al. (2013). Triplicate PCR amplification for each sample was carried out with a total amount of ~5 ng of DNA per reaction. Amplicon products were quantified using the Picogreen assay (Life Technologies, Carlsbad, United States) and pooled equimolarly. The final pool was purified with CleanPCR beads (CleanNA). Sequencing was done by Fasteris (Geneva, Switzerland) on an Illumina HiSeq system with 2 × 300 bp. The analysis yielded 3.7 Gb of sequences with an average error rate of 1.480%, and average Q30 of 85.0%. Adapters were removed using Trimmomatic (Bolger et al., 2014) and barcodes sorted using a Fasteris internal script. Sequences were then processed using the FROGS (Find Rapidly OTUs with Galaxy Solution) Galaxy-supported pipeline (Escudié et al., 2018). Paired-end reads were joined using FLASH (Magoè and Salzberg, 2011) and a quality check was performed using FastQC. Sequences with primers having no mismatch were kept. They were then filtered by size (350–500 bp) and those containing N bases were discarded. The 16S rRNA gene sequences were then denoised and clustered using the Swarm method (Mahé et al., 2015) with a three-base maximum difference, deletion of clusters with less than 0.005% abundance and cluster occurrence in a minimum of two samples of the total library. Chimeras were removed using vchime of vsearch package (Rognes et al., 2016). Affiliation was done using the Silva SSU database 123 (Quast et al., 2013) through BLAST (Altschul et al., 1990) with allowed multiple affiliation and manual curation. All analyses were done on the Galaxy instance of the INRA MIGALE bioinformatics platform<fnref n="1" />. Sequences are available at GenBank under accession number PRJNA742879.

## Microbial Community Genetic Resistance Potential

Real-time PCR quantification of bacterial 16S rRNA gene abundance was carried out using the primers 968F and 1401R according to Cébron et al. (2008). For the quantification of *cusA* (encoding a copper efflux system inner membrane protein), the primer pair *cusF1* and *cusR2* (Mahamoud Ahmed et al., 2020) was used, and for the quantification of *czcA* (inner membrane protein contributing to cobalt, zinc, and cadmium efflux) the primer pair *czcF3* (5'-CCCTGGACTTCGGCATCATYGTBGAYGG-3') and *czcR1* (5'-GGGCCATGGGGTGAACATYTTNCC-3') was used. The previously described reactions and cycling conditions

<footnote n="1">¹http://migale.jouy.inra.fr</footnote>