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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 Hellal, Saaidi, Bristeau, Crampon, Muselet, Della-Negra, Mauffret, Mouvet and Joulian. 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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# Bacterial Abundance, Diversity and Activity During Long-Term Colonization of Non-biodegradable and Biodegradable Plastics in Seawater

Charlene Odobel<fnref n="1" />†, Claire Dussud<fnref n="1" />†, Lena Philip<fnref n="1" />,², Gabrielle Derippe³, Marion Lauters<fnref n="1" />, Boris Eyheraguibel<fnref n="4" />, Gaëtan Burgaud⁵, Alexandra Ter Halle⁶, Anne-Leila Meistertzheim², Stephane Bruzaud³, Valerie Barbe⁷ and Jean-François Ghiglione<fnref n="1" />*

**OPEN ACCESS**

**Edited by:**
Fabrice Martin-Laurent,
Institut National de la Recherche
Agronomique (INRA), France

**Reviewed by:**
Vineet Kumar,
Guru Ghasidas Vishwavidyalaya, India
Prosun Tribedi,
The Neotia University, India

*Correspondence:
Jean-François Ghiglione
ghiglione@obs-banyuls.fr

† These authors share first authorship

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

**Received:** 01 July 2021
**Accepted:** 17 September 2021
**Published:** 18 November 2021

**Citation:**
Odobel C, Dussud C, Philip L, Derippe G, Lauters M, Eyheraguibel B, Burgaud G, Ter Halle A, Meistertzheim A-L, Bruzaud S, Barbe V and Ghiglione J-F (2021) Bacterial Abundance, Diversity and Activity During Long-Term Colonization of Non-biodegradable and Biodegradable Plastics in Seawater. *Front. Microbiol.* 12:734782.
doi: 10.3389/fmicb.2021.734782

The microorganisms living on plastics called “plastisphere” have been classically described as very abundant, highly diverse, and very specific when compared to the surrounding environments, but their potential ability to biodegrade various plastic types in natural conditions have been poorly investigated. Here, we follow the successive phases of biofilm development and maturation after long-term immersion in seawater (7 months) on conventional [fossil-based polyethylene (PE) and polystyrene (PS)] and biodegradable plastics [biobased polylactic acid (PLA) and polyhydroxybutyrate-co-hydroxyvalerate (PHBV), or fossil-based polycaprolactone (PCL)], as well as on artificially aged or non-aged PE without or with prooxidant additives [oxobiodegradable (OXO)]. First, we confirmed that the classical primo-colonization and growth phases of the biofilms that occurred during the first 10 days of immersion in seawater were more or less independent of the plastic type. After only 1 month, we found congruent signs of biodegradation for some bio-based and also fossil-based materials. A continuous growth of the biofilm during the 7 months of observation (measured by epifluorescence microscopy and flow cytometry) was found on PHBV, PCL, and artificially aged OXO, together with a continuous increase in intracellular (³H-leucine incorporation) and extracellular activities (lipase, aminopeptidase, and β-glucosidase) as well as subsequent changes in biofilm diversity that became specific to each polymer type (16S rRNA metabarcoding). No sign of biodegradation was visible for PE, PS, and PLA under our experimental conditions. We also provide a list of operational taxonomic units (OTUs) potentially involved in the biodegradation of these polymers under natural seawater conditions, such as *Pseudohongiella* sp. and *Marinobacter* sp. on PCL,

<footnote n="1">¹ CNRS, UMR 7621, Laboratoire d'Océanographie Microbienne (LOMIC), Sorbonne Université, Observatoire Océanologique de Banyuls, Banyuls-sur-Mer, France,
² SAS Plastic@Sea, Observatoire Océanologique de Banyuls, Banyuls-sur-Mer, France,
³ CNRS, UMR 6027, Institut de Recherche Dupuy de Lôme (IRDL), Université de Bretagne-Sud, Lorient, France,</footnote>

<footnote n="4">⁴ CNRS, UMR 6296, Institut de Chimie de Clermont-Ferrand (ICCF), Université Clermont Auvergne, Clermont-Ferrand, France,
⁵ CNRS, EA 3882, Université de Brest, Laboratoire Universitaire de Biodiversité et d'Ecologie Microbionte (LUBEM), Plouzané, France,
⁶ CNRS, UMR 5623, Laboratoire des Interactions Moléculaires et Réactivité Chimique et Photochimique (IMRCP), Université de Toulouse, Toulouse, France,
⁷ CEA, CNRS, Génomique Métabolique, Genoscope, Institut François Jacob, Univ Evry, Université Paris-Saclay, Evry, France</footnote>
*Marinicella litoralis* and *Celeribacter* sp. on PHBV, or Myxococcales on artificially aged OXO. This study opens new routes for a deeper understanding of the polymers' biodegradability in seawaters, especially when considering an alternative to conventional fossil-based plastics.

**Keywords: microbial ecotoxicology, plastisphere, biofouling, biofilm, plastic pollution**

## INTRODUCTION

The marine environment has become sinks for vast quantities of anthropogenic debris, including mismanaged plastic waste, estimated to 4.8–12.7 million metric tons entering the oceans every year (Jambeck et al., 2015). Microplastics (< 5 mm) represent more than 90% of the total counts of marine plastic debris, mostly originated from larger debris fragmentation by a combination of physical, chemical, and biological processes (Eriksen et al., 2014). Microplastics are generally composed of polyethylene (PE), polypropylene (PP), and polystyrene (PS), three conventional polyolefins highly refractory to biodegradation because of their intrinsic features (Poulain et al., 2019). Issues related to marine plastic pollution are multifaceted and cross-sectoral, leading to numerous environmental, economic, and social impacts and thus calling for non-trivial legislative and non-legislative strategies, with some that have already been reported worldwide (Schnurr et al., 2018). Within the frame of transition to blue economy, a wide range of biodegradable plastics were developed as potential substitutes to conventional plastics (Science Advice for Policy by European Academies, 2020). Some are still petroleum-based, such as polycaprolactone (PCL) or oxobiodegradable plastics (OXO) made of PE with prooxidant additives stimulating abiotic oxidation processes needed for its biodegradation (Yashchuk et al., 2012; Eyheraguibel et al., 2017). Others are made from renewable resources including biological materials or agricultural resources (so called “bio-based”), such as polylactic acid (PLA) and polyhydroxybutyrate-co-hydroxyvalerate [PHBV, a commercially available polyhydroxyalkanoate (PHA)] (RameshKumar et al., 2020).

In the marine environment, the very diverse microbial communities living on any kind of plastic debris has been called “plastisphere” (Zettler et al., 2013). Microplastics offer a new habitat characterized by higher abundance and distinct communities as compared to the surrounding free-living or organic particle-attached bacteria (Dussud et al., 2018a). The colonization of new plastics released at sea until the formation of a mature biofilm has been described as a succession of several phases (Wright et al., 2020). During the first hours in marine waters, a “conditioning film” made of inorganic and organic matter supports the initial colonization phase generally initiated by Gammaproteobacteria and Alphaproteobacteria regardless of the polymer type and representing microorganisms with efficient surface adhesion (Oberbeckmann et al., 2015; Dussud et al., 2018b). A second phase consists of the biofilm growth involving a succession of rapidly growing bacteria such as Acidobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Firmicutes, and Planctomycetes (Salta et al., 2013). The last phase that generally

appears after 15 to 30 days in seawater relates to a mature biofilm and remains stable for several months (Kirstein et al., 2018). The description of these colonization phases has been done on several conventional plastic types, including on PE-based plastic bags (Lobelle and Cunliffe, 2011; Harrison et al., 2014), polyethylene terephthalate (PET)-based plastic bottles (Oberbeckmann et al., 2014), polyvinyl chloride (PVC) (Dang et al., 2008), PS coupons (Briand et al., 2012), and in comparisons between PE, PP, PET, and polycarbonate (PC) materials (Webb et al., 2009; De Tender et al., 2017). Fewer studies have compared conventional to biodegradable plastics (including PLA, PHBV, and OXO) in terms of community composition and dynamics (Eich et al., 2015; Dussud et al., 2018a; Cheng et al., 2021), with different experimental conditions and microbial parameters that made more challenging comparison between these studies.

In this study, we describe the colonization dynamics of microplastics made of conventional (PE and PS) and biodegradable polymers (PCL, PLA, and PHBV) in seawater. We also tested the initial formulation of OXO that is recalcitrant to biodegradation and different artificially aged OXO (AA-OXO) that can be further biodegraded by oxidative mechanisms in the environment. We hypothesized that mature biofilms from biodegradable plastics differed from conventional materials, both in terms of abundance, diversity, and activities. Such differences should permit the description of potentially biodegrading plastisphere members, which may differ according to the plastic type. We present here an original and comprehensive comparison of the bacterial colonization potential on six plastic formulations incubated in seawater by coupling heterotrophic production and ectoenzyme measurements, in parallel to bacterial abundance (epifluorescence microscopy and flow cytometry) and bacterial diversity (16S rRNA metabarcoding) during a long-term colonization in seawater (7 months).

## MATERIALS AND METHODS

### Plastic Manufacturing Process

The first four polymer films were commercially available, made of low-density PE (Borealis, ref. FA6224, Austria), PS (Goodfellow, ref. 065-289-66, United States), PCL (CAPA 6800, Perstorp Company, Sweden), and PLA (Goodfellow, ref. 247-628-87, United States). The fifth film was formed from dried PHBV pellets (supplied by Tianan Biological Materials Co. Ltd., under the trade name ENMAT Y1000P, China) by using compression molded in a CarverR hydraulic press at 180°C under a pressure of 10 metric tons for 3 min. The sixth film was made of OXO with the same low-density PE as described above, but additivated with
D₂W formulation based on manganese and iron and extruded at 180°C using a laboratory scale Rondol linear 18 mm blown film (provided by Symphony Environmental Ltd., United Kingdom).

We also used two artificially aged OXO (AA-OXO) made of the same OXO as described above but differing by the exposure time to UV (according to ASTM D5208: UVA 340, 0.78 W m⁻³ nm⁻¹) during 48 h for AA₄₈OXO and during 144 h for AA₁₄₄OXO. In both cases, UV aging was followed by a thermal aging during 96 h at 70°C (ASTM D5510) to increase the oxidation level. The same protocol was used for artificially aging of PE film by UV exposure for 144 h followed by a thermal aging during 96 h at 70°C, called AA₁₄₄PE film hereafter. Artificial aging was stopped when reaching carbonyl index of 1x/100 for AA₄₈OXO and 3x/100 for AA₁₄₄OXO, where x was the film thickness. Carbonyl index values were determined as the ratio of the peak intensity at 1,715 cm⁻¹ to the peak intensity at 1,460 cm⁻¹ (Selke et al., 2015) by Fourier transform infrared spectroscopy (FTIR) analysis (Spectrum 100 equipped with an ATR attenuated total reflectance, Perkin-Elmer). The level of 1x/100 was previously demonstrated as a prerequisite for biodegradability of OXO, according to the French agreement Association Française de NORmalization (AFNOR AC t51-808, 2012). No sign of oxidation was observed for the AA₁₄₄PE film by FTIR, which served as a control in our experiment.

The film's thicknesses were 200 µm for PS, PHBV, PCL, and PLA and 100 µm for PE, AA₁₄₄PE, OXO, AA₄₈OXO, and AA₁₄₄OXO. Each of the nine films was cut into 100 circular pieces of 9 mm diameter with a puncher machine. Polymer pieces were sterilized with 70% ethanol and rinsed three times with sterile seawater (SSW) before incubation in natural seawater.

## Incubation Under Natural Seawater Conditions During 7 Months

Each material type was incubated in aquariums with direct circulation to the sea, as previously described (Dussud et al., 2018a). Briefly, we used 10 identical aquariums consisting of trays of 1.8 L capacity (Sodispan, Spain) continually renewed with 20 µm pre-filtered seawater (Leroy Merlin, France) by individual water delivery valves and overflow ports setting a flow rate of 0.1 L min⁻¹. Seawater was pumped at 30 m from the coast and 4 m depth in the Banyuls bay, close to the SOLA observatory station (NW Mediterranean Sea, France). During the experiment, seawater temperature in the aquariums and in the Banyuls bay was between 12.5 and 19.5°C and salinity remained stable at 38.5. Incubations in aquariums were processed in the dark to avoid UV-related degradation of the polymers and algal development. One aquarium was used as control and contained only circulating seawater. The nine other aquariums contained the pieces of each film (PE, AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, and PLA). Plastic pieces of each material type were sampled after 3, 10, 31, 74, 116, and 206 days, together with seawater from the control aquarium.

## Epifluorescence Microscopy

One piece of each polymer was rinsed at each sampling time with sterilized seawater and fixed for 1 h at 4°C with

1% (v/v) glutaraldehyde (final concentration) before freezing. Epifluorescence microscopy observations were done using an Olympus AX70 PROVIS after 4',6-diamidino-2-phenylindole (DAPI) staining according to Porter and Feig (1980). Pictures were taken on 10 fields of each polymer type and cell counting was done with the software Microbe Counter.

## Flow Cytometry

Three pieces of each polymer were rinsed at each sampling time with sterile seawater before cell detachment, as previously described (Dussud et al., 2018b). Briefly, cell detachment pretreatment was performed using 1 mM pyrophosphate (30 min at room temperature in the dark) followed by a sonication step (3 × 5 s, 40 kHz, 30% amplitude, sterilized probe Branson SLPe). Cells were fixed for 1 h at 4°C with 1% (v/v) glutaraldehyde (final concentration) before freezing. In parallel, 3 × 1 ml of seawater from the control aquarium were also fixed using the same procedure. A 500 µl subsample was mixed with the nucleic acid dye SYBR Green I (final concentration 0.05% v/v, Sigma Aldrich) at room temperature for 15 min in the dark. Cell counts were performed with a FACSCanto II flow cytometer (BD Bioscience, San Jose, CA) equipped with a blue laser (488 nm, air-cooled, 20 mW solid state), as previously described (Mével et al., 2008). Cell counts were expressed as number of cells mm⁻² for polymers and as number of cells ml⁻¹ for seawater.

## Heterotrophic Bacterial Production

Bacterial production (BP) was measured for each polymer type and at each sampling time by ³H-leucine incorporation into proteins, as previously described (Dussud et al., 2018b). Briefly, ³H-leucine (specific activity 112 Ci mmol⁻¹, Perkin Elmer) was added at 1 nM final concentration (completed with cold leucine to 150 nM) for polymer samples and 4.3 nM (completed with cold leucine to 42.8 nM) for 3 µm filtered seawater from the control aquarium. Triplicate samples were incubated in the dark at *in situ* temperature for 3 h. The polymers were rinsed with 5% TCA and 70% ethanol and then resuspended in 1.0 ml of a liquid scintillation cocktail (Ultima Gold). Radioactivity was determined in a Beckman Scintillation Counter (LS 5000CE) and data analyzed with the Microwin 2000 software. We used the empirical conversion factor of 1.55 ng C pmol⁻¹ of incorporated leucine to calculate BP (Simon and Azam, 1989). Values were given in ng C mm⁻² h⁻¹ for plastics and in ng C ml⁻¹ h⁻¹ for seawater.

## Extracellular Enzymatic Activities

Three extracellular enzymatic activities were analyzed for amino peptidase, β-glucosidase, and lipase. Triplicates of 1/4 of plastic piece of each material type were placed in a 96-well plate with fluorogenic model substrates that were L-leucine-7amido-4-methyl coumarin (Leu-MCA, 10 mM final, Sigma Aldrich) for amino peptidase, 4-methylumbelliferyl-β-D-glucoside at 20 mM for β-glucosidase (MUF-β-Glc, 20 mM final, Sigma Aldrich), and 4-methylumbelliferyl-oleate for lipase (MUF-Oleate, 20 mM final, Sigma Aldrich). These saturated concentrations for amino peptidase, β-glucosidase and lipase and optimized time incubations were determined prior to the extracellular enzymatic
activity measurement (data not shown). After 4 h (for seawater) or 8 h (for plastics) of incubation, 50 µl of a stop solution (SDS 10%) was added in all wells. Fluorescence was quantified using VICTOR3 spectrofluorometer (PerkinElmer) at a 380 nm wavelength for MCA and 364 nm for MUF substrates. A control was done in triplicate for each activity and each plastic type by adding the stop solution at the beginning of incubation. The spectrofluorometer was calibrated with MCA and MUF standard solutions diluted in sterile seawater. Values were given in nmol mm⁻² h⁻¹ for polymers and in nmol ml⁻¹ h⁻¹ for seawater.

## DNA Extraction, PCR Amplification, and Sequencing

Plastic pieces were sampled for all plastic types and at each sampling time with sterilized forceps and stored at -80°C until analysis. In parallel, 1 L seawater was sampled on the same day in the control aquarium, successively filtered onto 3-µm and 0.2-µm pore size polycarbonate filters (47 mm diameter, Nucleopore), and filters were stored at -80°C until analysis. DNA extraction was performed on polymers or seawater at all sampling time, using a classical phenol-chloroform method for seawater samples, modified for the plastic samples as previously described (Dussud et al., 2018b). Briefly, the modification consisted in a sonication pretreatment (3 × 5 s with 30% amplitude, sterilized probe Branson SLPe) in order to increase the detachment of biofilm forming bacteria. The molecular size and purity of the DNA extracts were analyzed by agarose gel electrophoresis (1%) and the DNA was quantified by spectrophotometry (GeneQuant II, Pharmacia Biotech). Primers for Polymerase Chain Reaction (PCR) amplification of the 16S V3-V5 region were 515F-Y and 926R, well-suited for marine samples according to Parada et al. (2016) with Illumina-specific primers and barcodes. Sequencing was performed on Illumina MiSeq by Genoscope (Evry, France). Raw FASTA files were deposited at EBI under the accession number PRJEB37662. Sequence analysis was conducted using the FROGS pipeline (Escudié et al., 2017) supported on the Galaxy instance of Toulouse Midi-Pyrenees bioinformatics platform. The pre-process tool was used to merge the paired-ends raw reads using Flash (Magoè and Salzberg, 2011) and quality filtering and primers trimming with cutadapt (Martin, 2011). Sequence clustering was performed with the Swarm algorithm (Mahé et al., 2014). Chimeras were detected with the VSEARCH algorithm, by de novo UCHIME method (Edgar et al., 2011; Rognes et al., 2016) and were removed. Clusters were assigned with the Silva 128 16S rRNA database (Quast et al., 2012) and clusters that did not belong to Bacteria kingdom were removed as well as chloroplast and mitochondrial sequences. The clusters that had a reads number abundance lower than 0.005% of all reads were removed, according to Bokulich et al. (2013). The number of sequences per sample was normalized by rarefaction (n = 17,865). Finally, a table with 66 samples and 1,517 clusters was obtained.

## Statistical Analysis

For each sample, we calculated Chao1 species richness estimator, Simpson and Shannon diversity indexes, and Pielou's evenness

<table><caption>**TABLE 1** | OTUs richness (Observed) and diversity indexes (Chao1, Pielou, Shannon and Simpson) of free-living (F), organic particle-attached bacteria (A) and biofilms of different plastic types (PE, AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, PLA) according to immersion time in seawater (3, 10, 31, 74, 116 and 206 days).</caption><thead><tr><th>Sample type</th><th>Day</th><th>Observed</th><th>Chao1 ± se</th><th>Pielou</th><th>Shannon</th><th>Simpson</th></tr></thead><tbody><tr><td rowspan="5">F</td><td>3</td><td>445</td><td>568 ± 27</td><td>0.67</td><td>4.11</td><td>0.95</td></tr><tr><td>10</td><td>535</td><td>742 ± 40</td><td>0.66</td><td>4.16</td><td>0.94</td></tr><tr><td>31</td><td>696</td><td>913 ± 40</td><td>0.67</td><td>4.40</td><td>0.95</td></tr><tr><td>74</td><td>505</td><td>693 ± 38</td><td>0.65</td><td>4.07</td><td>0.94</td></tr><tr><td>116</td><td>376</td><td>545 ± 40</td><td>0.62</td><td>3.69</td><td>0.91</td></tr><tr><td rowspan="5">A</td><td>3</td><td>810</td><td>946 ± 28</td><td>0.74</td><td>4.95</td><td>0.98</td></tr><tr><td>10</td><td>905</td><td>1001 ± 21</td><td>0.80</td><td>5.47</td><td>0.98</td></tr><tr><td>31</td><td>901</td><td>982 ± 19</td><td>0.86</td><td>5.86</td><td>0.99</td></tr><tr><td>74</td><td>897</td><td>979 ± 19</td><td>0.80</td><td>5.46</td><td>0.99</td></tr><tr><td>116</td><td>793</td><td>872 ± 19</td><td>0.81</td><td>5.40</td><td>0.99</td></tr><tr><td rowspan="5">PE</td><td>3</td><td>226</td><td>336 ± 31</td><td>0.51</td><td>2.78</td><td>0.90</td></tr><tr><td>10</td><td>404</td><td>532 ± 31</td><td>0.58</td><td>3.48</td><td>0.90</td></tr><tr><td>31</td><td>938</td><td>1041 ± 23</td><td>0.82</td><td>5.63</td><td>0.99</td></tr><tr><td>74</td><td>738</td><td>879 ± 27</td><td>0.63</td><td>4.18</td><td>0.93</td></tr><tr><td>116</td><td>412</td><td>486 ± 20</td><td>0.54</td><td>3.23</td><td>0.88</td></tr><tr><td rowspan="5">AA₁₄₄PE</td><td>3</td><td>286</td><td>375 ± 25</td><td>0.56</td><td>3.16</td><td>0.91</td></tr><tr><td>10</td><td>433</td><td>561 ± 32</td><td>0.66</td><td>4.01</td><td>0.95</td></tr><tr><td>31</td><td>882</td><td>1000 ± 24</td><td>0.80</td><td>5.44</td><td>0.99</td></tr><tr><td>74</td><td>592</td><td>681 ± 22</td><td>0.72</td><td>4.57</td><td>0.96</td></tr><tr><td>116</td><td>599</td><td>654 ± 15</td><td>0.75</td><td>4.83</td><td>0.98</td></tr><tr><td rowspan="5">OXO</td><td>3</td><td>240</td><td>344 ± 30</td><td>0.54</td><td>2.96</td><td>0.89</td></tr><tr><td>10</td><td>479</td><td>607 ± 28</td><td>0.71</td><td>4.40</td><td>0.98</td></tr><tr><td>31</td><td>702</td><td>909 ± 37</td><td>0.64</td><td>4.22</td><td>0.96</td></tr><tr><td>74</td><td>611</td><td>691 ± 21</td><td>0.72</td><td>4.64</td><td>0.97</td></tr><tr><td>116</td><td>559</td><td>599 ± 12</td><td>0.77</td><td>4.88</td><td>0.98</td></tr><tr><td rowspan="5">AA₄₈OXO</td><td>3</td><td>182</td><td>225 ± 16</td><td>0.51</td><td>2.66</td><td>0.91</td></tr><tr><td>10</td><td>375</td><td>485 ± 26</td><td>0.62</td><td>3.70</td><td>0.94</td></tr><tr><td>31</td><td>420</td><td>530 ± 26</td><td>0.52</td><td>3.12</td><td>0.85</td></tr><tr><td>74</td><td>501</td><td>601 ± 25</td><td>0.70</td><td>4.36</td><td>0.96</td></tr><tr><td>116</td><td>528</td><td>609 ± 21</td><td>0.72</td><td>4.50</td><td>0.97</td></tr><tr><td rowspan="5">AA₁₄₄OXO</td><td>3</td><td>639</td><td>777 ± 29</td><td>0.72</td><td>4.65</td><td>0.97</td></tr><tr><td>10</td><td>183</td><td>254 ± 26</td><td>0.50</td><td>2.61</td><td>0.82</td></tr><tr><td>31</td><td>519</td><td>665 ± 30</td><td>0.59</td><td>3.70</td><td>0.94</td></tr><tr><td>74</td><td>519</td><td>654 ± 31</td><td>0.71</td><td>4.42</td><td>0.96</td></tr><tr><td>116</td><td>486</td><td>573 ± 22</td><td>0.68</td><td>4.23</td><td>0.95</td></tr><tr><td rowspan="5">PS</td><td>3</td><td>503</td><td>682 ± 35</td><td>0.53</td><td>3.33</td><td>0.90</td></tr><tr><td>10</td><td>488</td><td>647 ± 32</td><td>0.57</td><td>3.55</td><td>0.93</td></tr><tr><td>31</td><td>666</td><td>791 ± 26</td><td>0.61</td><td>3.95</td><td>0.92</td></tr><tr><td>74</td><td>674</td><td>868 ± 35</td><td>0.56</td><td>3.62</td><td>0.88</td></tr><tr><td>116</td><td>825</td><td>902 ± 18</td><td>0.80</td><td>5.38</td><td>0.99</td></tr><tr><td rowspan="5">PHBV</td><td>3</td><td>260</td><td>332 ± 20</td><td>0.43</td><td>2.39</td><td>0.79</td></tr><tr><td>10</td><td>388</td><td>541 ± 37</td><td>0.67</td><td>3.98</td><td>0.96</td></tr></tbody></table>

(Continued)
<table><caption>**TABLE 1** (Continued)</caption><thead><tr><th>Sample type</th><th>Day</th><th>Observed</th><th>Chao1 ± se</th><th>Pielou</th><th>Shannon</th><th>Simpson</th></tr></thead><tbody><tr><td rowspan="10">PCL</td><td>31</td><td>317</td><td>471 ± 38</td><td>0.55</td><td>3.19</td><td>0.92</td></tr><tr><td>74</td><td>609</td><td>835 ± 46</td><td>0.70</td><td>4.51</td><td>0.97</td></tr><tr><td>116</td><td>535</td><td>667 ± 29</td><td>0.68</td><td>4.30</td><td>0.97</td></tr><tr><td>206</td><td>343</td><td>430 ± 25</td><td>0.69</td><td>4.00</td><td>0.96</td></tr><tr><td>3</td><td>478</td><td>631 ± 31</td><td>0.51</td><td>3.12</td><td>0.89</td></tr><tr><td>10</td><td>271</td><td>452 ± 47</td><td>0.54</td><td>3.04</td><td>0.91</td></tr><tr><td>31</td><td>738</td><td>853 ± 23</td><td>0.64</td><td>4.24</td><td>0.94</td></tr><tr><td>74</td><td>357</td><td>495 ± 32</td><td>0.58</td><td>3.44</td><td>0.92</td></tr><tr><td>116</td><td>370</td><td>511 ± 34</td><td>0.53</td><td>3.12</td><td>0.87</td></tr><tr><td>206</td><td>158</td><td>248 ± 29</td><td>0.33</td><td>1.67</td><td>0.67</td></tr><tr><td rowspan="10">PLA</td><td>3</td><td>223</td><td>327 ± 29</td><td>0.47</td><td>2.53</td><td>0.88</td></tr><tr><td>10</td><td>665</td><td>815 ± 29</td><td>0.70</td><td>4.52</td><td>0.97</td></tr><tr><td>31</td><td>739</td><td>884 ± 28</td><td>0.65</td><td>4.31</td><td>0.94</td></tr><tr><td>74</td><td>793</td><td>887 ± 21</td><td>0.76</td><td>5.11</td><td>0.98</td></tr><tr><td>116</td><td>840</td><td>944 ± 24</td><td>0.84</td><td>5.62</td><td>0.99</td></tr><tr><td>206</td><td>785</td><td>908 ± 26</td><td>0.75</td><td>5.02</td><td>0.98</td></tr></tbody></table>

using the Phyloseq package (McMurdie and Holmes, 2013) of R software suite (Table 1). The non-parametric estimator of Chao1 was calculated as follows: $S = S_{obs} + a^2/2b^* (N - 1)/N$, where $S_{obs}$ is the number of OTUs observed in the sample, $N$ is the number of sequences per sample, $a$ is the number of OTUs detected only once, and $b$ is the number of OTUs detected only twice (Chiu et al., 2014). Simpson diversity index was computed as $D = 1 - \sum [N_i^*(N_i - 1)/N^*(N - 1)]$, where $N_i$ is the abundance of the $i^{th}$ OTU in the sample (Simpson, 1949). Shannon index was calculated as $H = -\sum [p_i^* \log(p_i)]$, where $p_i$ is the proportion of the $i^{th}$ OTU (Shannon and Weaver, 1949) and Pielou's evenness index was $R = H/\log_2 S_{obs}$ (Pielou, 1966). Differences with incubation time and between biodegradable and non-biodegradable plastics in richness and diversity indexes were tested using an ANOVA test (for normally distributed data, determined by a Shapiro test) or a Kruskal-Wallis test with R software.

Unweighted-pair group method with arithmetic mean (UPGMA) dendrogram based on Bray-Curtis dissimilarities was used for visualization of beta-diversity. A series of dissimilarity profile permutation tests (SIMPROF, PRIMER 6) was performed under a simple null hypothesis of no meaningful structure within a sub-cluster. Significant branches (SIMPROF, $p < 0.05$, in black in Figure 4) were used to define sample clusters. One-way analysis of similarity was performed on the same distance matrix (ANOSIM, PRIMER 6) to test the significant difference and to partition the variance of the beta-diversity matrix between days of incubation and between polymer types and seawater. Similarity Percentage analysis (SIMPER) was performed to identify the contribution of each operational taxonomic unit (OTU), using PRIMER 6. A first comparison between PE and AA₁₄₄PE revealed no specific species contribution of the plastisphere of one polymer to the other. The analyses then focused on the contributions of PE compared to other polymers (PHBV, PCL, OXO, AA₄₈OXO, AA₁₄₄OXO, AA₁₄₄PE, PS, and PLA) at final time (D206). A threshold at 50% was applied to

identify the most relevant species. For each OTU identified, in order to improve the affiliation attributed by Silva 128 16S rRNA database, the sequence was blasted to the NCBI databases "16S ribosomal RNA from bacteria and archaea" and "nt." In some cases and depending on the identity percentage of the matches, a new affiliation has been proposed (Table 2). The data and graphical representations were performed using R statistical software version 3.5.0 (R Core Team, 2018).

## RESULTS

### Visual Changes of the Materials

After 3 days of immersion in seawater, we observed that the translucent PHBV fragment whitened and that AA₁₄₄OXO was very breakable, whereas the other plastic pieces showed no visual changes (Figure 1). The only change after 206 days in seawater was observed for PCL pieces, which showed a fivefold reduction in size compared to day 3.

### Epifluorescence Microscopy and Flow Cytometry

Epifluorescence microscopy showed the successive steps of colonization and maturation of the biofilm during 206 days in seawater (Figure 2). No or very few cells were detected on plastics after their sterilization and before their immersion in seawater. The presence of a mature biofilm together with extracellular polymeric substances was visible in all plastic types at the end of the experiment, but biofilms presented higher thickness for PCL and AA₁₄₄OXO compared to the other plastics. Counting was not possible for PHBV because of autofluorescence background signal of the polymer.

It is noteworthy that no or very few cells were counted by flow cytometry after the sterilization of the plastic films and before their immersion in seawater, as found by epifluorescence microscopy. Flow cytometry confirmed the succession of phases during the colonization of the plastics (Figure 3A). The primocolonization was characterized by a relatively high number of cell counts at day 3 (mean = $1.6 \times 10^4$, SD = $1.1 \times 10^4$ cells mm⁻², $n = 9$) that decreased at day 10 (mean = $4.6 \times 10^3$, SD = $1.1 \times 10^3$ cells mm⁻², $n = 9$), whatever the polymer type. Interestingly, a clear difference was found between PE and OXO (mean = $4.7 \times 10^3$, SD = $5.6 \times 10^2$ cells mm⁻², $n = 9$) and the same polymer but artificially aged (one order of magnitude higher for AA₁₄₄PE, AA₄₈OXO, and AA₁₄₄OXO).

A growing phase was found from day 10 to day 31 in all plastic films, followed by a stabilization phase of the biofilm that became mature and remains unchanged from day 31 to day 206 for PE, AA₁₄₄PE, OXO, AA₄₈OXO, PS, and PLA. Exceptions were found for PCL, PHBV, and AA₁₄₄OXO that showed a continuous growth of biofilm until the end of the experiment (up to $2.0 \times 10^4$ cells mm⁻² after 116 days for PHBV, PCL, and AA₁₄₄OXO). From 116 days in seawater, significant differences were found between cell counts on PHBV, PCL, and AA₁₄₄OXO compared to other plastics (t-test, $p$-value < 0.05). The cell detachment treatment was less efficient after 116 days for PHBV, PCL, and AA₁₄₄OXO, since we observed much lower
<table><caption>**TABLE 2** | Taxonomy, relative abundance (r.a.) and contribution (cb) details (in %) of the 41 OTUs identified by SIMPER analysis, up to 30% of cumulative dissimilarity between PE and the other 8 plastics materials (AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, PLA) after 206 days of immersion in seawater.</caption><thead><tr><th rowspan="2">OTU taxonomy</th><th colspan="2">AA<sub>144</sub>PE</th><th colspan="2">OXO</th><th colspan="2">AA<sub>48</sub>OXO</th><th colspan="2">AA<sub>144</sub>OXO</th><th colspan="2">PS</th><th colspan="2">PHBV</th><th colspan="2">PCL</th><th colspan="2">PLA</th></tr><tr><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th><th>r.a.</th><th>cb</th></tr></thead><tbody><tr><td>Marinicella litoralis</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.017</td><td>0</td><td>5.9</td><td>3.2</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Oceanospirillales</td><td>3.0</td><td>1.6</td><td>0.17</td><td>0</td><td>0.10</td><td>0</td><td>0.034</td><td>0</td><td>0.18</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.37</td><td>0</td></tr><tr><td>Oceanospirillales</td><td>4.5</td><td>3.5</td><td>0.20</td><td>0</td><td>0.067</td><td>0</td><td>0.017</td><td>0</td><td>0.19</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.25</td><td>0</td></tr><tr><td>Pseudohongiella sp.</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>52</td><td>26</td><td>0.011</td><td>0</td></tr><tr><td>Polycyclovorans sp.</td><td>7.9</td><td>3.4</td><td>4.7</td><td>0</td><td>7.6</td><td>0</td><td>0.022</td><td>0</td><td>0.43</td><td>0</td><td>0</td><td>0</td><td>0.062</td><td>0</td><td>5.7</td><td>0</td></tr><tr><td>Thiopfundaceae</td><td>0.44</td><td>0</td><td>0.12</td><td>0</td><td>0.067</td><td>0</td><td>0.43</td><td>0</td><td>2.5</td><td>1.8</td><td>0.12</td><td>0</td><td>0</td><td>0</td><td>0.68</td><td>0</td></tr><tr><td>Chromatiaceae</td><td>0.011</td><td>0</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.034</td><td>0</td><td>0</td><td>0</td><td>0.056</td><td>0</td><td>3.7</td><td>2.8</td></tr><tr><td>Chromatiales</td><td>1.3</td><td>0</td><td>0.13</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Spongiibacter sp.</td><td>0.23</td><td>0</td><td>0.22</td><td>0</td><td>0.52</td><td>0</td><td>0.011</td><td>0</td><td>0.062</td><td>0</td><td>0</td><td>0</td><td>0.073</td><td>0</td><td>4.5</td><td>0</td></tr><tr><td>Cellvibrionaceae</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.090</td><td>0</td><td>12</td><td>6.8</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>1.2</td><td>0</td><td>0.15</td><td>0</td></tr><tr><td>Arenicellaceae</td><td>0.011</td><td>0</td><td>0</td><td>0</td><td>0.056</td><td>0</td><td>0.63</td><td>0</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.017</td><td>0</td></tr><tr><td>Arenicellaceae</td><td>3.9</td><td>2.6</td><td>0.85</td><td>0</td><td>1.3</td><td>0</td><td>1.3</td><td>0</td><td>1.5</td><td>0</td><td>0.045</td><td>0</td><td>0</td><td>0</td><td>0.20</td><td>0</td></tr><tr><td>Pseudoalteromonas sp.</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>2.5</td><td>2.2</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Marinobacter sp.</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>19</td><td>9.4</td><td>0.44</td><td>0</td></tr><tr><td>Gammaproteobacteria</td><td>1.8</td><td>1.3</td><td>14</td><td>9.9</td><td>5.0</td><td>2.8</td><td>0.017</td><td>0</td><td>0.15</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.76</td><td>0</td></tr><tr><td>Gammaproteobacteria</td><td>0.13</td><td>0</td><td>0.050</td><td>0</td><td>0.028</td><td>0</td><td>8.0</td><td>4.5</td><td>0.77</td><td>0</td><td>2.8</td><td>0</td><td>0</td><td>0</td><td>0.34</td><td>0</td></tr><tr><td>Gammaproteobacteria</td><td>3.0</td><td>3.4</td><td>1.9</td><td>0</td><td>0.062</td><td>0</td><td>0.12</td><td>0</td><td>0.42</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.017</td><td>0</td></tr><tr><td>Gammaproteobacteria</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>9.7</td><td>5.2</td><td>0.0056</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Gammaproteobacteria</td><td>0.36</td><td>0</td><td>0.084</td><td>0</td><td>0.10</td><td>0</td><td>0.0056</td><td>0</td><td>2.3</td><td>1.8</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.24</td><td>0</td></tr><tr><td>Myxococcales</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.16</td><td>0</td><td>10</td><td>5.7</td><td>0.011</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Desulfovibrio sp.</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3.1</td><td>2.5</td></tr><tr><td>Nitrospira sp.</td><td>0.57</td><td>0</td><td>0.17</td><td>0</td><td>0.022</td><td>0</td><td>0.028</td><td>0</td><td>1.9</td><td>1.4</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.63</td><td>0</td></tr><tr><td>Celeribacter sp.</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>3.4</td><td>1.8</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>Marivita sp.</td><td>0</td><td>0</td><td>15</td><td>11</td><td>3.4</td><td>2.6</td><td>0.017</td><td>0</td><td>0.039</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.011</td><td>0</td></tr><tr><td>Rhodobacteraceae</td><td>0.31</td><td>0</td><td>0.050</td><td>0</td><td>0.88</td><td>0</td><td>0.0056</td><td>0</td><td>0.073</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.16</td><td>0</td></tr><tr><td>Rhodobacteraceae</td><td>0.050</td><td>0</td><td>0.045</td><td>0</td><td>0.27</td><td>0</td><td>0.039</td><td>0</td><td>0.10</td><td>0</td><td>8.9</td><td>4.8</td><td>0.38</td><td>0</td><td>1.4</td><td>0</td></tr><tr><td>Rhodobacteraceae</td><td>0.034</td><td>0</td><td>0.011</td><td>0</td><td>0.0056</td><td>0</td><td>0.028</td><td>0</td><td>0.11</td><td>0</td><td>4.4</td><td>2.3</td><td>0</td><td>0</td><td>0.13</td><td>0</td></tr><tr><td>Hyphomonadaceae</td><td>1.1</td><td>0</td><td>0.11</td><td>0</td><td>0.16</td><td>0</td><td>0</td><td>0</td><td>0.078</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4.8</td><td>3.3</td></tr><tr><td>Hyphomonadaceae</td><td>0</td><td>0</td><td>0.011</td><td>0</td><td>3.2</td><td>2.4</td><td>0.0056</td><td>0</td><td>0.011</td><td>0</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>0.0056</td><td>0</td></tr><tr><td>Rhodobacterales</td><td>0.017</td><td>0</td><td>20</td><td>15</td><td>6.3</td><td>4.7</td><td>0.0056</td><td>0</td><td>0.034</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.022</td><td>0</td></tr><tr><td>Rhizobiales</td><td>0</td><td>0</td><td>0</td><td>0</td><td>7.5</td><td>5.7</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.039</td><td>0</td></tr><tr><td>Selenomonadales</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4.7</td><td>3.8</td></tr><tr><td>Clostridiales</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4.8</td><td>3.9</td></tr><tr><td>Saprospirales</td><td>5.1</td><td>3.0</td><td>1.8</td><td>0</td><td>0.39</td><td>0</td><td>0.0056</td><td>0</td><td>1.1</td><td>0</td><td>0.022</td><td>0</td><td>0</td><td>0</td><td>0.20</td><td>0</td></tr><tr><td>Saprospirales</td><td>2.7</td><td>0</td><td>0.20</td><td>0</td><td>0.078</td><td>0</td><td>0</td><td>0</td><td>0.57</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0.050</td><td>0</td></tr><tr><td>Saprospirales</td><td>1.2</td><td>0</td><td>0.49</td><td>0</td><td>0.034</td><td>0</td><td>0</td><td>0</td><td>0.16</td><td>0</td><td>0.0056</td><td>0</td><td>0</td><td>0</td><td>0.0056</td><td>0</td></tr><tr><td>Flavobacteriaceae</td><td>0.15</td><td>0</td><td>0.13</td><td>0</td><td>1.7</td><td>0</td><td>17</td><td>9.8</td><td>0.067</td><td>0</td><td>1.7</td><td>0</td><td>0</td><td>0</td><td>0.028</td><td>0</td></tr><tr><td>Flavobacteriaceae</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>8.2</td><td>4.4</td><td>0.0056</td><td>0</td><td>0.0056</td><td>0</td></tr><tr><td>Cryomorphaceae</td><td>0.19</td><td>0</td><td>0.073</td><td>0</td><td>0.050</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>4.8</td><td>3.7</td></tr><tr><td>Acidobacteria</td><td>3.2</td><td>0</td><td>0.82</td><td>0</td><td>0.45</td><td>0</td><td>0.045</td><td>0</td><td>0.70</td><td>0</td><td>0.11</td><td>0</td><td>0</td><td>0</td><td>0.034</td><td>0</td></tr><tr><td>Flavobacteriaceae</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td><td>16</td><td>8.0</td><td>0.0056</td><td>0</td></tr></tbody></table>

cell counts by flow cytometry while epifluorescence microscopy confirmed the presence of abundant biofilms after 206 days. Control seawater cell counts remained stable during the entire experiment (mean = 2.3 ± 1.4 × 10⁵ cells ml⁻¹).

## Bacterial Activities

### Bacterial Heterotrophic Production

A clear distinction between biodegradable and non-biodegradable plastics was observed by cell incorporation

of radiolabeled ³H-leucine (Figure 3B). The primo-colonizers on PE, AA₁₄₄PE, OXO, PS, and PLA showed high heterotrophic activities during the first 3 days of immersion (between 3.94 × 10⁻² ng C mm⁻² h⁻¹ and 1.01 × 10⁻¹ ng C mm⁻² h⁻¹) followed by a dramatic and continuous decrease until the end of the experiment (between 3.87 × 10⁻³ and 1.77 × 10⁻² ng C mm⁻² h⁻¹ at day 206). AA₄₈OXO exhibited the same dynamics with a slight delay in time, with high activities until day 10, followed by a sharp decrease. The three other
<figure><img src="image_148.png" /><figcaption>**FIGURE 1** | Plastic pieces of different composition (PE, OXO, PS, PHBV, PCL, and PLA) at the beginning (3 days) and at the end (206 days) of the experimental immersion in seawater. A pretreatment by artificial aging was applied for PE and OXO films by UV-A exposure during 48 h (AA₄₈) or 144 h (AA₁₄₄) followed by a thermal aging during 96 h at 70°C.</figcaption></figure>

<figure><img src="image_149.png" /><figcaption>**FIGURE 2** | Epifluorescence micrographs of a selection of DAPI-stained plastics (PE, AA₁₄₄OXO, and PCL) showing the formation and evolution of the biofilms of after 3, 10, 74, and 206 days of immersion in seawater. Artificial aging (AA) pretreatment applied for OXO polymers consisted in UV-A exposure during 144 h (AA₁₄₄) followed by a thermal aging during 96 h at 70°C.</figcaption></figure>

materials (PCL, PHBV, and AA₁₄₄OXO) also presented high heterotrophic activities at the primo-colonization phase (day 3), but differed from the other plastics since their activities remained high and relatively stable until the end of the 206 days of seawater immersion. Maximum activities were found for PCL (2.45 × 10⁻¹ ng C mm⁻² h⁻¹), followed by PHBV (1.34 × 10⁻¹ ng C mm⁻² h⁻¹) and AA₁₄₄OXO (8.69 × 10⁻² ng C mm⁻² h⁻¹). Bacterial heterotrophic production remained stable during the entire experiment in control seawater (mean = 67.6 ± 42.2 ng C L⁻¹ h⁻¹).

## Extracellular Enzymatic Activities

Similar trends were found when observing the extracellular aminopeptidase, β-glucosidase, and lipase activities (Figures 3C-E, respectively). The general trend found for bacterial heterotrophic production (see Section 3.3.1) of a high activity of the primo-colonizers (day 3;

mean = 9.5 × 10⁻⁵ ± 3.3 × 10⁻⁵ µmol mm⁻² h⁻¹,
mean = 7.1 × 10⁻⁷ ± 8.8 × 10⁻⁷ µmol mm⁻² h⁻¹, and
mean = 3.8 × 10⁻⁵ ± 1.8 × 10⁻⁵ µmol mm⁻² h⁻¹ for aminopeptidase, β-glucosidase, and lipase, respectively) followed by a drastic decrease and further stabilization until the end of the experiment (206 days) was also found for extracellular activities. It was particularly true for lipase activities on PE, AA₁₄₄PE, OXO, AA₄₈OXO, PS, and PLA biofilms. Aminopeptidase activities (mean = 3.75 × 10⁻⁴ ± 8.95 × 10⁻⁵ µmol mm⁻² h⁻¹ with *n* = 30 for all plastics) and β-glucosidase (mean = 1.49 × 10⁻⁵ ± 4.49 × 10⁻⁶ µmol mm⁻² h⁻¹ with *n* = 30 for all plastics) remained low for these plastics during the entire experiment. Again, PCL, PHBV, and AA₁₄₄OXO showed different trends when compared to other plastics. The highest extracellular activities were found when the biofilms became mature (after 31 days), with higher activities always found on PCL (3.0 × 10⁻³ ± 1.2 × 10⁻³ µmol
<figure><img src="image_150.png" /><figcaption>**FIGURE 3** | Bacterial cell counts (A), bacterial heterotrophic production (B), and bacterial extracellular aminopeptidase (C), β-glucosidase (D), and lipase activities (E) on the different plastic types (PE, AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, and PLA) immersed in seawater for 3, 10, 31, 74, 116, and 206 days. No data available on day 10 for extracellular activities. Error bars indicate standard deviation.</figcaption></figure>

$mm^{-2} h^{-1}$, 3.9 × 10⁻⁴ ± 2.1 × 10⁻⁵ μmol mm⁻² h⁻¹, and 1.4 × 10⁻⁴ ± 2.3 × 10⁻⁵ μmol mm⁻² h⁻¹ for aminopeptidase, β-glucosidase, and lipase, respectively) and PHBV (3.0 × 10⁻³ ± 2.5 × 10⁻⁴ μmol mm⁻² h⁻¹, 1.1 × 10⁻⁴ ± 3.6 × 10⁻⁵ μmol mm⁻² h⁻¹, and

1.8 × 10⁻⁵ ± 2.6 × 10⁻⁵ μmol mm⁻² h⁻¹ for aminopeptidase, β-glucosidase, and lipase, respectively), followed by AA₁₄₄OXO (9.8 × 10⁻⁴ ± 1.0 × 10⁻⁴ μmol mm⁻² h⁻¹, 8.5 × 10⁻⁵ ± 9.5 × 10⁻⁵ μmol mm⁻² h⁻¹, and 6.2 × 10⁻⁵ ± 1.1 × 10⁻⁵ μmol mm⁻² h⁻¹ for
aminopeptidase, β-glucosidase, and lipase, respectively). On the other hand, extracellular enzymatic activities remained stable during the entire experiment in control seawater (1.1 × 10⁻² ± 8.6 × 10⁻³ µmol L⁻¹ h⁻¹, 5.3 × 10⁻⁵ ± 1.2 × 10⁻⁴ µmol L⁻¹ h⁻¹, and 1.9 × 10⁻³ ± 3.5 × 10⁻³ µmol L⁻¹ h⁻¹ for aminopeptidase, β-glucosidase, and lipase, respectively).

# Dynamics of Bacterial Diversity

## Alpha- and Beta-Diversity

Illumina Miseq DNA sequencing generated 9,054,841 paired sequences for the 66 samples, failing into 1517 OTUs after randomly resampling to 17,865 sequences per sample to provide statistical robustness when comparing diversity among samples.

The evolution of the Alpha-diversity was assessed with Chao1, Pielou, Shannon, and Simpson indexes (**Table 1**). Whatever plastic types, all indexes increased significantly between the primo-colonization (day 3) and the maturation phase of the biofilm (day 31) (pairwise *t*-test, *p* < 0.05). Chao1 species richness estimator almost doubled for all plastics between the primo-colonization and the maturation phase of the biofilm (mean = 390, SD = 135, *n* = 9 at day 3 and mean = 846, SD = 184, *n* = 9 at day 31) (**Table 1**). This index remained relatively stable until the end of the experiment for PE, AA₁₄₄PE, OXO, AA₄₈OXO, PS, and PLA biofilms, while after day 74 and up to day 206, a decrease was observed on PCL, PHBV, and AA₁₄₄PE biodegradable polymers (mean = 753, SD = 147, *n* = 3 at day 31 and mean = 411, SD = 155, *n* = 3 at day 206). Shannon diversity index showed similar trends, with the exception of the decrease observed on the biodegradable polymers after day 74 and up to day 206, which was less on AA₁₄₄PE and PHBV compared to PCL (**Table 1**). Bacterial diversity found in seawater on both free-living and organic particle-attached fractions was much less influenced by the temporal dynamics, where all Alpha-diversity indexes remained relatively stable during the entire course of the experiment (Shannon mean = 3.9, SD = 0.5, *n* = 6 on free-living and mean = 5.2, SD = 0.6, *n* = 6 on organic particle-attached fractions).

Beta-diversity analysis showed strong dissimilarity (> 90%) between the free-living bacterial communities in seawater compared to plastic samples (**Figure 4**). Organic particle-attached bacterial communities in seawater also formed a separated cluster, with closer similarity with plastic samples, and especially with the non-biodegradable polymers (see below). Both free-living and organic particle-attached bacterial communities remained stable during the course of the experiment, which contrasted with the succession of distinct communities found on plastics. First, bacterial communities of all plastic materials clustered together during the primo-colonization phase (day 3), with little but significant changes observed on the biofilm growing phase (ANOSIM *R* = 0.622, *p* = 0.001 between day 3 and day 10). Second, we found a clear distinction between the mature biofilms (after 31 days) found on non-biodegradable (PE, AA₁₄₄PE, OXO, AA₄₈OXO, PS, and PLA) compared to biodegradable polymers (PHBV, PCL, and AA₁₄₄OXO) (ANOSIM *R* = 0.287, *p* = 0.001). In particular, PCL and PHBV

clusters strongly differed from the mature biofilms on other plastics, and AA₁₄₄OXO formed a distinct cluster together with AA₄₈OXO especially after 116 days of immersion in seawater.

## Taxonomic Composition

Taxonomic analyses confirmed the specificity of the plastisphere compared to seawater free-living bacteria, the latter being dominated by Alphaproteobacteria (40%, mainly SAR11 clade with 24.8%), followed by Flavobacteriia (18.5%) and Gammaproteobacteria (28%, mainly Oceanospirillaceae with 7.9%) (**Figure 4**). Organic particle-attached bacterial communities were also dominated by Gammaproteobacteria (34.9%, mainly *Spongiibacter* sp. 4.3%), followed by Alphaproteobacteria (16%), Flavobacteriia (15%, mainly *Luteibaculum* sp. 5.3%), and Planctomycetacia (5.6%).

Whatever the plastic type, primo-colonizers (day 3) together with bacteria of the biofilm growing phases (day 10) belonged to Alteromonadales (mean = 21% SD = 11, *n* = 18), Oceanospirillales (mean = 17% SD = 14, *n* = 18, mainly represented by *Oleibacter* sp. and *Alcanivorax* sp.), and Cellvibrionales (mean = 10.1% SD = 9.4, *n* = 18, mainly represented by *Aestuariicella* sp.). Some exceptions were found for PCL (exhibiting higher proportions of *Oleiphilus* sp.), PLA (higher proportion of *Neptuniibacter* sp.), PS, and AA₁₄₄OXO (dominated by *Spongiibacter* sp.) (**Figure 4**).

The mature biofilms (after 31 days) differed between material types. The non-biodegradable materials (PE, AA₁₄₄PE, OXO, AA₄₈OXO, and PS) together with PLA shared high proportions of Gammaproteobacteria (mean = 34 ± 11%), Alphaproteobacteria (mean = 24 ± 16%), Sphingobacteriia (mean = 8.8 ± 6.2%), and Flavobacteriia (mean = 5.0 ± 5.6%). Gammaproteobacteria class is composed of Cellvibrionales (mean = 13 ± 9%), with *Spongiibacter* sp. and *Zhongshania* sp. as main representatives as well as Xanthomonadales (mean = 5.6 ± 5.4%) with *Polycyclovorans* sp. PE and AA₁₄₄PE showed increasing proportions of Saprospiraceae (up to 23%), Planctomycetes (up to 14%, mainly OM190 clade and *Planctomyces* sp.), and Arenicellaceae (up to 7%, mainly *Arenicella* sp.) over time. The same tendency was observed for OXO and AA₄₈OXO with Rhodobacteraceae (up to 16%) and Flavobacteriaceae (up to 5%, mainly *Gilvibacter* sp.). Interestingly, AA₄₈OXO was distinguished by large proportions of Rhizobiales (OCS116 clade, up to 9.3%) and Hyphomonadaceae (mainly *Hirshia* sp., up to 36%). PS diversity profiles displayed higher proportions of Saprospiraceae (up to 19%, mainly *Lewinella* sp.) and Planctomycetaceae (up to 6.3%) at the end of the experiment. Likewise, PLA mature biofilm was composed of Planctomycetaceae (up to 12%, mainly *Planctomyces* sp. and *Rhodopirellula* sp.) and Flavobacteriales (up to 7%, mainly *Luteibaculum* sp.) with increasing proportions over the course of the experiment.

The diversity of mature biofilms was clearly distinct among PHBV, PCL, and AA₁₄₄OXO, with higher proportions of Alphaproteobacteria (mean = 36 ± 24%) compared to the non-biodegradable ones, followed by Gammaproteobacteria (mean = 29 ± 18%) and Flavobacteriia (mean = 11 ± 8.1%). PHBV is composed of Flavobacteriaceae (up to 26%, mainly
<figure><img src="image_151.png" /><figcaption>**FIGURE 4** | Temporal variation of taxonomic abundances and community structure of free-living (F), organic particle-attached bacteria (A) and biofilms of different materials (PE, AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, and PLA) immersed in seawater for 3, 10, 31, 74, 116, and 206 days (D), by cumulative bar charts comparing taxonomic relative abundances (left) and by UPGMA dendrogram based on Bray-Curtis dissimilarities between 16S rRNA-based sequencing profiles (right).</figcaption></figure>

*Maritimonas* sp.), Cellvibrionaceae (up to 15%, mainly *Marinicella* sp.) and Rhizobiales (up to 12%, OCS116 clade), especially at the end of the incubation. PCL and AA₁₄₄OXO shared high proportions of Cellvibrionaceae (up to 23%) and Oceanospirillaceae (up to 52%, mainly *Pseudohongiella* sp.), but also specificities among Flavobacteriaceae, mainly *Aquibacter* sp. for PCL and *Gilvibacter* sp. for AA₁₄₄OXO. PCL also comprised Hyphomonadaceae (up to 40%, mainly *Hirshia* sp. and *Hyphomonas* sp.), whereas AA₁₄₄OXO showed noticeable proportions of Myxococcales (up to 23%, mainly Sandaracinacea family).

SIMPER analysis highlighted 40 dominant OTUs contributing to a cumulative 30% of the dissimilarity between PE, used as control, and the other polymers after 206 days in seawater (Figure 5). Among non-biodegradable polymers, comparison between PE and AA₁₄₄PE biofilms included six specific OTUs (Oceanospirillales, *Polycyclovorans* sp., Arenicallaceae, and Saprospirales). These OTUs shared low relative abundance and contribution, indicating a rather limited effect of artificial aging on PE. Limited specificities were also found on the

other non-biodegradable materials when compared to PE control. AA₄₈OXO biofilm exhibited five contributive OTUs, including two exclusive (affiliated to Rhizobiales and Hyphomonadaceae) and three shared with OXO (affiliated to Rhodobacterales, *Marivita* sp., and Gammaproteobacteria). PLA exhibited six specific OTUs contributing between 3.6 and 3.9% (Clostridiales, Selenomonadales, Cryomorphaceae, Hyphomodadaceae, Chromatiaceae, and *Desulfuvibrio* sp.). Note that the most abundant taxon found on PLA (*Polycyclovorans* sp., 5.7% in relative abundance) was not found as PLA-specific taxa by SIMPER analysis. PS hosted four specific OTUs (Pseudoalteromonas, Thioprofundaceae, Gammaproteobacteria, and *Nitrospira* sp.) but with low relative abundance (1.9 to 2.5%) and low contribution to dissimilarity with the PE control (1.4 to 2.2%).

Interestingly, the most distinct taxa were found among the biodegradable polymers (PCL, PHBV, and AA₁₄₄OXO). PCL biofilm presented two highly abundant and contributive OTUs affiliated with *Pseudohongiella* sp. and *Marinobacter* sp. (52% and 19% in relative abundance, 26% and 9%
<figure><img src="image_152.png" /><figcaption>**FIGURE 5** | Bubble plot showing the relative abundance and the taxonomy of the OTUs contributing to a cumulated 30% of the dissimilarity between PE and the eight other plastic materials (AA₁₄₄PE, OXO, AA₄₈OXO, AA₁₄₄OXO, PS, PHBV, PCL, and PLA) after 206 days of immersion in seawater (SIMPER analysis). Points are sized according to the relative abundance and colored by their contribution to dissimilarity.</figcaption></figure>

contribution, respectively). A third PCL-specific OTU affiliated with Flavobacteriaceae was identified (8% contribution and 16% relative abundance). PHBV biofilm highlighted six specific OTUs with 1.8% to 5.2% of contribution, affiliated with Cellvibrionaceae, Bacteroidetes, Rhodobacteraceae, and Flavobacteraceae as well as *Marinicella litoralis* and *Celeribacter* sp. AA₁₄₄OXO biofilm exhibited four very abundant (from 8 to 17%) and contributive (from 4.5 to 9.8%) OTUs, affiliated with Flavobacteriaceae (also present on PHBV and AA₄₈OXO), Gammaproteobacteria, Cellvibrionaceae, and Myxococcales.

# DISCUSSION

## Successive Phases of Biofilm Formation on Plastics

Both epifluorescence microscopy and flow cytometry confirmed the succession of primo-colonization, growth, and maturation phases of the plastics biofilm, as it has been described earlier (see review by Jacquin et al., 2019). Most of the previous studies were based on experiments conducted over a several-week period, mainly on conventional polymer types generally found in the ocean (mostly PE, PET, PVC, and PS) and our study brings new data on microbial colonization of biodegradable plastics in seawater.

Our results showed a rapid bacterial colonization of more than 5 × 10³ cells mm⁻² on all material types, which is consistent with values found in studies focusing on

the primo-colonization of plastic biofilms (Lee et al., 2008; Oberbeckmann et al., 2015). Interestingly, we found a significant difference in cell counts on PE or OXO after only 3 days of immersion in seawater as compared to same but artificially aged polymer(one order of magnitude higher for AA₁₄₄PE, AA₄₈OXO, and AA₁₄₄OXO). Such differences may be explained by the change in surface properties accompanying the artificial aging by UV and temperature (Attwood et al., 2006). Material properties (crystallinity and crystal structure, hydrophobicity, roughness, glass transition temperature, melting temperature, and modulus of elasticity) indeed play a crucial role in the selection of bacterial community in the early stage of colonization (Pompilio et al., 2008). We also observed significantly higher cell counts on PS, PHBV, and PCL as compared to PLA or PE during the primo-colonization phase, but complete characterization of surface properties was not done in this study.

The growth phase of the biofilms was characterized by cell count increase (visible by flow cytometry) together with the production of extracellular matrix (visible by epifluorescence microscopy) after 10 days of immersion in seawater. The final expansion of the biofilm to maturity was visible from day 31 to day 206 on the non-biodegradable polymers (PE, AA₁₄₄PE, OXO, AA₄₈OXO, and PS), as well as for PLA. Interestingly, the biofilm maturity was not reached for the biodegradable polymers (PCL, PHBV) and for the AA₁₄₄OXO that continue to increase even after 206 days of incubation in seawater. Few other long-term studies (> 6 months) have also shown limited differences in biofilm maturation on
non-biodegradable polymers, i.e., PE, PP, PET, or polycarbonate (PC) (Webb et al., 2009; De Tender et al., 2017). Our results are consistent with another study underlining the continuous growth of PHBV biofilms in seawater (Dussud et al., 2018b), albeit limited to 45 days of immersion. Our results thus confirm this trend on PHBV but for much longer period (206 days) and extend this observation to PCL and AA₁₄₄OXO. These results open new questions on the final expansion of the biofilms growing on biodegradable polymers in seawater and call for long-term incubation period in controlled conditions.

## Dynamics of Extra- and Intracellular Bacterial Activities on Plastics

This study presents pioneer results of intra- and extracellular activities of biofilms growing on various plastics. Extracellular enzymes are necessary to hydrolyze polymers and organic particles into small molecules (< 600 Da) that can cross the bacterial cell membranes *via* permeases for further intracellular degradation (Azam and Malfatti, 2007). Activities of hydrolytic enzymes such as protease, lipase, and glucosidase have already been examined for various marine particles including suspended particulate matter, marine snow, and sinking particles collected by sediment traps (Severin et al., 2016 and references cited there in), but not on plastic particles. So far, only one study evaluated the intracellular bacterial heterotrophic production on plastics (Dussud et al., 2018b). To the best of our knowledge, this is the first study to merge extra- and intracellular activities. Overall, we found that the measured extra- and intracellular activities gave the same trends, with higher activities found on biodegradable compared to non-biodegradable materials. This result underlines the complementary role of extra- and intracellular enzyme activities to decompose and transform polymers and organic molecules for further metabolization.

The primo-colonizers (day 3) were particularly active whatever the plastic types, as depicted by intracellular heterotrophic activity and also by extracellular aminopeptidase and lipase (not for b-glucosidase). Such activity peak may certainly be due to the utilization of organic matter present in the “conditioning film” that forms rapidly on hard surfaces placed in seawater (Loeb and Neihof, 1975; Dobretsov, 2010).

Thereafter, clear distinction could be made for non-biodegradable vs. biodegradable materials. Both inter- and extracellular activities decreased to remained low values from day 3 and until the end of the experiment on all the conventional materials (PE, AA₁₄₄PE, OXO, and PS). Interestingly, a significant and consistent decrease was also observed on PLA, a polymer known as biodegradable under industrial composting conditions or degradable in human body (Pillai and Sharma, 2010), but not biodegradable under marine conditions (Karamanlioglu et al., 2017).

Intra- and extracellular activities (including b-glucosidase) remained stable or even increase until 206 days of immersion in seawater for the biodegradable polymers, with higher activities found for PCL and PHBV compared to AA₁₄₄OXO. This appears consistent based on the intrinsic features of PCL and PHBV whose ester linkages will be degraded by hydrolytic enzymes

such as lipases. The potential activity of plastic biodegradation in seawater is determined by several standard tests based on biomass and respirometric activity measurements (mainly CO₂ production) under laboratory conditions during 3 months (ASTM D6691-09), 6 months (ASTM D7473-12), or 24 months (ISO 18830, ISO 19679, ASTM D7991-15). Other activity tests can be considered as alternative methods, such as tests based on ATP measurements (Fontanella et al., 2013) or bacterial heterotrophic production (Jacquin et al., 2021). We are aware that intra- and extracellular bacterial activities under natural conditions may be related to processes other than plastic biodegradation (biodegradation of organic matter and cross-feeding in the biofilm) (Pande et al., 2014), but this study provides a set of congruent results that, although not definitely compelling, gives concrete hints for effective biodegradability in seawater (Jacquin et al., 2021).

## Microbial Community Dynamics in Seawater and for Biodegradable and Non-biodegradable Plastics

Illumina MiSeq sequencing provided a set of complementary information to better understand the dynamics of bacterial abundance and activities on plastic described above, including (i) a clear distinction between communities living on plastics and the surrounding seawater, (ii) contrasted communities on biodegradable and non-biodegradable materials after 7 months of immersion in seawater, which allowed to (iii) describe new potential candidates for the biodegradation of PCL, PHBV, and artificially aged OXO in natural seawater.

First, cluster analysis showed significant distinction between bacterial communities living on plastics when compared to the free-living and organic particle-attached fractions. Such observation is now a common feature observed in the oceans worldwide (Wright et al., 2021) that reinforce the originality of the “plastisphere” compared to other microorganisms living in the surrounding seawater. In our study, we noticed that organic particle-attached communities formed a separate group that was more similar to the plastisphere compared to the free-living fraction, as already mentioned on PET drinking bottles and glass substrates in seawaters (Oberbeckmann et al., 2016). These authors suggested that the similarity between organic particle-associated and plastic biofilms may be explained by the presence of non-specific surface-colonizing microbes that represent another part of the diversity around the core plastisphere microbiome. Indeed, surface attachment capabilities of microorganisms can be triggered by organelles (e.g., flagella, pili) (Rogers et al., 2020), hydrophobicity of the outer membrane (e.g., modifications of the lipopolysaccharidic composition of some bacteria allowing better interactions with hydrophobic substances) (Krasowska and Sigler, 2014), or synthesis of surfactants (e.g., higher ability of *Lysinibacillus fusiformis* to degrade polyethylene in the presence of biosurfactants) (Mukherjee et al., 2016). We also found clear dissimilarities between the bacterial communities in the free-living fraction (dominated by Alphaproteobacteria, mainly SAR11) and the organic particle-attached fraction (dominated
by Gammaproteobacteria), which is also a common pattern in seawaters (Li et al., 2021). Both free-living and organic particle- attached communities remained relatively stable during the entire course of the experiment, with classical values found in the Mediterranean seawaters in terms of abundance, heterotrophic bacterial production, and extracellular activities (Severin et al., 2016). These results validated our capability to maintain realistic conditions for up to 206 days in an experimental setup renewed with natural seawater every 30 min.

Second, we observed a succession of communities with clear dissimilarities between biodegradable and non-biodegradable materials after 7 months of immersion in seawater. Such dissimilarities were not found during the primo-colonization (day 3) and the growth of the biofilm (day 10) that showed distinct but close communities whatever the plastic type. Primo- colonizers (day 3) together with bacteria on the growth phase of the biofilm (day 10) belonged to Gammaproteobacteria (mainly *Alteromonadaceae*, *Oceanospirillaceae*, and *Alcanivoraceae*), which is in accordance with previous studies (Dussud et al., 2018a; Cheng et al., 2021). Under our conditions, significant dissimilarities were observed after 31 days, which corresponds to the maturity of biofilms for non-biodegradable materials on the one hand, and to the continuous growth with high extra- and intracellular activities for biodegradable materials on the other hand. After 31 to 74 days of immersion in seawater, biofilms on PCL and PHBV strongly differed from the mature biofilms of other plastics. AA<sub>144</sub>OXO also formed a distinct cluster after 116 days. This is the first time such comparison has been reported for long-term studies, as the only one study comparing bacterial abundance, activity, and diversity on biodegradable materials ended their experiment at the beginning of the biofilm maturity, i.e., after 45 days of immersion in seawater (Dussud et al., 2018a). Most of the other long-term studies over a period of more than 6 months restricted their analysis on bacterial diversity colonizing non-biodegradable polymers, such as PE, PP, PET, and PC (Webb et al., 2009; De Tender et al., 2017). We emphasized here that further studies may take into account not only the bacterial diversity living on plastics, but also the extra- and intracellular activities of the biofilm that will provide new insights into the functional role played by the plastisphere in seawaters.

Third, we describe new potential candidates for the biodegradation of PCL, PHBV, and artificially aged OXO in natural seawater, based on the congruent results of biomass increase together with high extra- and intracellular activities. We used similarity percentage analysis (SIMPER, Ghiglione et al., 2012) to identify OTUs primarily responsible for dissimilarities between pairs of PE versus PCL, PHBV, and AA-OXO after 206 days of incubation in seawater. A clear trend was observed with biodegradable polymers being dominated by a low number of highly abundant contributive OTUs when compared to non-biodegradable polymers, suggesting a specialization of the bacterial communities, providing more information to the contrasted results obtained so far, not allowing to answer whether plastics really select for specific microbial communities (Wright et al., 2020). The most important OTUs that influenced the dissimilarity between PCL and PE were *Pseudohongiella* sp. and *Marinobacter* sp. These two genera have never been listed as PCL

degraders, but the first was found highly abundant after crude oil pollution (Valencia-Agami et al., 2019; Peng et al., 2020) and the second contains well-known hydrocarbonoclastic species (Grimaud et al., 2012; Cui et al., 2016), which is consistent with the petroleum nature of the polymer. Another contributing OTU was affiliated with Flavobacteriaceae that were already shown as potential PCL degraders (Lopardo and Urakawa, 2019) or capable of using complex carbon sources (Rodriguez-Sanchez et al., 2016). We also identified putative PHBV degraders, some of them being already highlighted in similar studies, such as Bacteroidetes and others presenting the enzymatic machinery for PHA degradation, such as Celeribacteria (Volova et al., 2016). We also found *Marinicella litoralis* that has never been described as a potential PHBV degrader to date (Romanenko et al., 2010; Shoji et al., 2014), as well as Rhodobacteraceae that was abundant in all material types with known ability to form biofilm on plastics and to degrade complex organic matter (Kessler et al., 2011; Flood et al., 2018). Finally, putative degraders of artificially aged OXO (AA<sub>144</sub>OXO) belonged to Gammaproteobacteria, Cellvibrionaceae, Myxococcales, and Flavobacteriaceae, which are classically observed on the plastisphere of various material types found in seawaters including PE (Zettler et al., 2013), PET (Oberbeckmann et al., 2016), and PVC (Pinto et al., 2019). Members of Myxococcales and Flavobacteriaceae presented high hydrolytic enzymes excretion and complex biopolymers degradation capacities (Shimkets et al., 2006; Amaral-Zettler et al., 2020) together with hydrocarbon degradation capabilities (Pollet et al., 2018; Gutierrez, 2019). We are aware that the description of putative OTUs involved in the biodegradation of PCL, PHBV, and AA-OXO are sometimes limited to the poor taxonomic identification based on 16S rRNA metabarcoding; however, it opens new routes for further studies to delve deeper into the understanding of the biodegradability of these materials in seawaters.

## CONCLUDING REMARKS

Through the analysis of a broad set of microbial parameters (abundance, diversity, and activities) to describe the evolution of the marine biofilms growing on six different plastic types during a long-term experiment, we demonstrated clear evidence of biodegradation on PCL, PHBV, and artificially aged OXO in seawater. Signs of biodegradation were visible after 1 month and until the end of the experiment, with significant increases of the biofilm biomass, of the intra- and extracellular activities, together with drastic changes in bacterial diversity. In contrast, we found no sign of biodegradation for PE, PS, and PLA under our experimental conditions, where the biofilms became mature after 1 month and remained relatively stable until the end of the experiment. We encourage the recording of these microbial parameters for a comprehensive connection between biofilm formation and polymer degradation when evaluating the plastic biodegradation in seawater, which is currently not taken into account in the current standards (mainly based on respirometry activities and generally performed under laboratory conditions). Our study opens also new routes for further studies
on biodegradation mechanisms, by providing a list of putative OTUs that may serve as model organisms potentially involved in the biodegradation of PCL, PHBV, and artificially aged OXO under natural seawater conditions.

Finally, it is noteworthy that the bio-based polymer PLA showed no signs of biodegradation under our experimental conditions, whereas the fossil-based polymer PCL showed significant evidence of biodegradation. This reinforced the distinction that has to be made between biobased and biodegradable polymers but also the different certification schemes for biodegradation in contrasted environments (compost, freshwater, and seawater) when considering an alternative to conventional fossil-based plastics.

## DATA AVAILABILITY STATEMENT

The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found below: https://www.ebi.ac.uk/metagenomics/, PRJEB37662.

## AUTHOR CONTRIBUTIONS

CD, A-LM, SB, and J-FG have conceived and designed the study. CD, ML, and CO carried out all the experiments and

acquired the data. SB and BE provided the equipment. CD, CO, LP, GD, A-LM, VB, and J-FG analyzed and interpreted the data. CO, CD, VB, and J-FG drafted the manuscript. LP, GD, ML, BE, GB, AT, A-LM, and SB revised the manuscript and approved the version of the manuscript to be published. All authors contributed to the article and approved the submitted version.

## FUNDING

This work was funded by the French National Research Agency (project ANR-OXOMAR), by the Tara Ocean Foundation (project Microplastic 2019), by the European project JRA-ASSEMBLE+, and by the CNRS (project PEPS'I-PHABIO).

## ACKNOWLEDGMENTS

We are grateful to Philippe Catala for his laboratory support, to Matthieu George and Pascale Fabre for insightful comments on the manuscript, to G Baby for technical support, and Guigui PA, VF, and JPJS for helpful discussion. This work is part of the Ph.D. thesis of CD supported by the French Ministry of Education.

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<figure><img src="image_153.png" /></figure>

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# Dynamics of Soil Microbial Communities During Diazepam and Oxazepam Biodegradation in Soil Flooded by Water From a WWTP

Marc Crampon¹*, Coralie Soulier¹, Pauline Sidoli¹, Jennifer Hellal¹, Catherine Joulian¹, Mickaël Charron¹, Quentin Guillemoto¹,², Géraldine Picot-Colbeaux¹ and Marie Pettenati¹

¹ Bureau de Recherches Géologiques et Minières, Orléans, France, ² UMR 7619 METIS, Sorbonne Université, Paris, France

The demand for energy and chemicals is constantly growing, leading to an increase of the amounts of contaminants discharged to the environment. Among these, pharmaceutical molecules are frequently found in treated wastewater that is discharged into superficial waters. Indeed, wastewater treatment plants (WWTPs) are designed to remove organic pollution from urban effluents but are not specific, especially toward contaminants of emerging concern (CECs), which finally reach the natural environment. In this context, it is important to study the fate of micropollutants, especially in a soil aquifer treatment (SAT) context for water from WWTPs, and for the most persistent molecules such as benzodiazepines. In the present study, soils sampled in a reed bed frequently flooded by water from a WWTP were spiked with diazepam and oxazepam in microcosms, and their concentrations were monitored for 97 days. It appeared that the two molecules were completely degraded after 15 days of incubation. Samples were collected during the experiment in order to follow the dynamics of the microbial communities, based on 16S rRNA gene sequencing for Archaea and Bacteria, and ITS2 gene for Fungi. The evolution of diversity and of specific operating taxonomic units (OTUs) highlighted an impact of the addition of benzodiazepines, a rapid resilience of the fungal community and an evolution of the bacterial community. It appeared that OTUs from the *Brevibacillus* genus were more abundant at the beginning of the biodegradation process, for diazepam and oxazepam conditions. Additionally, Tax4Fun tool was applied to 16S rRNA gene sequencing data to infer on the evolution of specific metabolic functions during biodegradation. It finally appeared that the microbial community in soils frequently exposed to water from WWTP, potentially containing CECs such as diazepam and oxazepam, may be adapted to the degradation of persistent contaminants.

**Keywords:** benzodiazepines, soil, microbial community, biodegradation, WWTP

## INTRODUCTION

Due to the non-specificity of wastewater treatment plants (WWTPs) toward many micropollutants and in particular contaminants of emerging concern (CECs), these are frequently discharged to the environment. Several solutions exist to treat CECs, but significant knowledge gaps remain (Basheer, 2018). Recently, in order to minimize wastewater treatment costs regarding energy and

**OPEN ACCESS**

**Edited by:**
Dimitrios Georgios Karpouzas,
University of Thessaly, Greece

**Reviewed by:**
Panagiotis A. Karas,
University of Thessaly, Greece
Federica Spina,
University of Turin, Italy

*Correspondence:
Marc Crampon
m.crampon@brgm.fr

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

**Received:** 15 July 2021

**Accepted:** 20 October 2021

**Published:** 29 November 2021

**Citation:**
Crampon M, Soulier C, Sidoli P, Hellal J, Joulian C, Charron M, Guillemoto Q, Picot-Colbeaux G and Pettenati M (2021) Dynamics of Soil Microbial Communities During Diazepam and Oxazepam Biodegradation in Soil Flooded by Water From a WWTP. *Front. Microbiol.* 12:742000.
doi: 10.3389/fmicb.2021.742000
chemicals consumption, multi-barrier treatment systems that
can combine engineered systems and nature-based solution
(NBS), such as soil aquifer treatment (SAT) systems, were
described. Hermes et al. (2019) studied the removal processes
involved in a SAT context, by focusing on trace organic
chemicals and their metabolites. They found that the fate of
these compounds was mainly controlled by sorption onto soil
constituents (especially linked to organic matter content and
clays for cationic compounds), dilution, and to the nature
of the compounds themselves (cationic, non-ionic, molecular
weight, etc.). Biodegradation was also described as a removal
process for a variety of organic contaminants, depending
especially on the specificity of microorganisms present in
the system (Rauch-Williams et al., 2010; Falås et al., 2016;
Regnery et al., 2016), as well as the biodegradability of the
considered compounds. Natural attenuation linked to microbial
communities' adaptation represents a NBS for the remediation
of CECs. The identification of biodegradation mechanisms could
help to increase the efficiency of treatments in WWTPs and
consequently limit environmental impacts. In this context, it
is necessary to understand the adaptation capacity of endemic
microbial communities exposed to CECs stress, and their
possible role in CECs remediation in the case of soil and
aquifer treatments.

Benzodiazepines are pharmaceutical CECs that are frequently
found in water from WWTPs. They belong to a class of
psychoactive drugs that contain a benzene and a diazepine
ring in their core chemical structure. They have anticonvulsant,
sedative, muscle relaxant, hypnotic, and anxiolytic properties.
These molecules, especially diazepam (DZ), are described as
poorly biodegradable when introduced into the environment
(Redshaw et al., 2008). Some degradation pathways have been
highlighted, such as demethylation, especially due to fungal
enzymes (Helbling et al., 2010), but an efficient biodegradation
in the environment has not yet been reported. Some researchers
found that DZ was not directly degradable by bacteria, especially
when other carbon sources that are more easily accessible are
available, which is the case in soils (Tappin et al., 2014). They also
showed that DZ degradation products from photodegradation
are much more easily biodegraded by bacteria. The first stages of
biodegradation could be linked to soil fungal activity, the bacteria
then taking over the less complex metabolites. Oxazepam (OXA)
seems to be more easily biodegradable by bacteria derived from
WWTPs (Redshaw et al., 2008), but these benzodiazepines are
generally described as poorly biodegradable (Tappin et al., 2014).
DZ (Valium®) is certainly the best known molecule of this group
and has a long-term impact because of its persistent metabolites.
In humans, it is metabolized to N-desmethyldiazepam (also
called nordazepam) (t₁/₂ ~ 100 h). Nordazepam (ND, Calmday®)
is then 3-hydroxylated to OXA (Serax®). The presence of the
hydroxyl group allows its glucuronation and excretion in urine
and explains its low half-life (~4–15 h) compared to DZ and ND
(Kosjek et al., 2012).

Benzodiazepines are halogenated molecules, which are often
considered as a factor that negatively affects biodegradation.
The dehalogenation of molecules with more than two to three
halogen groups is often considered possible only under anaerobic

conditions. Most of the data on the efficiency of wastewater
treatments concern DZ and show that (i) less than 10% is
removed during conventional biological treatment, (ii) the
efficiency seems to be higher during anaerobic treatment (10-
50%), and (iii) the removal rate is mainly related to sorption
rather than degradation (Ternes et al., 2004; Löffler et al., 2005;
Ghattas et al., 2017). Similarly, OXA is persistent in both aerobic
and anaerobic treatment in the environment (Patterson et al.,
2010). DZ appears to be subject to photodegradation in the
environment, which may be a pathway for the removal of DZ
from surface water (Boreen et al., 2003).

Although the Kow of benzodiazepines [DZ: 2.8, ND: 2.9, OXA: 2.2, Episuite (EPA)] does not appear to indicate that sorption plays a significant role in their removal (or delay), Ternes et al. (2004) classified DZ as readily adsorbable on activated carbon (99% removal on 0.2 mg L⁻¹ activated carbon), and Calisto and Esteves (2009) showed that temazepam and OXA can undergo sorption on humic substances. On the other hand, sorption could limit bioaccessibility and thus decrease potential biodegradation. Löffler et al. (2005) showed that DZ was highly persistent with rapid and extensive sorption on sediments, stable in soils, groundwater, and during wastewater treatment. The same study showed that OXA is moderately persistent in the environment with a lower DT50 and a lower sorption rate on sediments than DZ. In addition, Löffler et al. (2005) did not observe any degradation of DZ to OXA in sediments, suggesting that it is difficult to compare the fate of DZ in the environment and in humans.

Consequently, the use of benzodiazepines to simultaneously
study the processes of sorption and biodegradation—in order
to quantitatively differentiate these two processes in the
dissipation of molecules in soils—is needed to better understand
its behavior in contaminated environments. Considered as
persistent, resistant to biodegradation, and with supposed
limited sorption (Kow < 3), we aimed at studying the fate
of DZ and OXA in soils flooded by water from WWTP with
known benzodiazepine inputs. The present study focuses on
biodegradation. The objectives were to assess the capacity of soil
microbial communities (bacteria, archaea, and fungi), to resist
and potentially degrade benzodiazepine molecules, especially DZ
and OXA. A focus was made on (i) the biodegradation of mother
molecules DZ and OXA in soils, and (ii) the dynamics of bacteria,
archaea, and fungi communities during the degradation kinetics.
The evolution of metabolic pathways was also explored, as well as
links between degradation and biodiversity.

## MATERIALS AND METHODS

### Context and Soil Sampling

Soils were sampled in the reed-bed area of a SAT system
implanted in the city of Agon-Coutainville (France, Normandy),
located along the English Channel Coastline (Figure 1). The
commune, with an estimated population of 2,800 residents
(INSEE, 2015), is one of the oldest seaside resorts of the Manche
department and harbors the largest production of shellfish in
France (production and storage, ~400 ha of shellfish parks).
The conservation of the coastal ecosystem and the associated sanitary stakes are essential for local economy and have to be fully integrated to the ongoing development of residential areas, tourism, and shellfish aquaculture (approximately 7 km of coast). Subject to a large tidal range, groundwater resources are prone to salinization in this coastal area, limiting the fresh water supply. Sustainable water management in this area must consider seasonal variations of the population (during summer vacations) and the irrigation needs of a backshore golf course. In addition, environmental regulations as well as the water framework directive must be followed (DIRECTIVE 2006/7/CE), in spite of financial constraints.

To face this demanding challenge and to preserve the estuary ecosystem from secondary treated wastewater discharged to surface water (river or sea) in Agon-Coutainville, the SAT system has been considered for more than 14 years as locally more efficient and sustainable (Picot-Colbeaux et al., 2020). The SAT consists of a fed reed-bed area of 35,000 m² with secondary treated wastewater provided by a biological WWTP. This area is divided into three parts alternatively flooded by the treated water with an average daily volume of 1,390 m³ (mean 2,005–2,019) which infiltrates into a 7- to 9-m-thick sandy aquifer. Monitoring boreholes intercept sands (fine to coarse) and silty sands, which become rich in fragments of shells with depth, and then reach the altered clay from the bed rock (schist). The first meters of the aquifer always contain organic matter.

The quality of discharged treated wastewater and downstream groundwater is monitored and respects the according French regulations although many questions remain about the fate of CECs in this system. The efficiency of this combined engineered and natural system were addressed in the European AquaNES project<fnref n="1" /> (Pettenati et al., 2019a,b; Picot-Colbeaux et al., 2020). Previous chemical monitoring of the study site and released water have shown non-negligible concentrations of benzodiazepines in the water at the outlet of the WWTP, especially for OXA (approximately 1,678 ng L⁻<fnref n="1" />), which is maybe also present as a DZ degradation by-product.

Five FR4N soil samples were taken from a 25 m² square (four points and one in the middle) from the 0–20 cm layer and were mixed and homogenized on site, representing about 25 kg of soil. Plants residues and roots were discarded. The soil sample was analyzed for main agronomic properties: granulometry, organic matter content, cation exchange capacity (CEC), N (%), C/N ratio, pH, and metal content (Aurea AgroSciences, Ardon, France), and the rest was stored at 4°C for further experiments. Sampled soil consists of a calcareous sandy soil (12.5% CaCO₃ content and 73.1% sand content, including 65.6% coarse sand) with an organic matter content of 4.7% and a pH<sub>KCl</sub> value of 7.5. All results for the studied parameters are listed in **Supplementary Table 3**. Metal and metalloid concentrations in the studied soil were monitored in a previous project (AquaNES H2020 project). They were found to be globally low, and these compounds do not represent a major concern on site. CECs are often detected in water samples from the site. A monitoring of the concentrations of several CECs was performed on a 3-year period on water from

the site (AquaNES project, H2020). DZ was always found below the detection limit (<20 ng L⁻<fnref n="1" />). OXA was detected in nearly each point, at every sampling date. OXA concentrations reached 40 ng L⁻<fnref n="1" /> in a pond upstream of the site filled with water from the golf ponds, and 2,663 ng L⁻<fnref n="1" /> in the WWTP outlet water.

## Experimental Setup

### Chemicals and Reagents

Diazepam and OXA standards of high purity grade (>98%) were purchased from Sigma-Aldrich (Steinheim, Germany). Diazepam D5 and oxazepam D5, used as soil extraction standards, were purchased from CIL Cluzeau (Sainte-Foy-la-Grande, France) and Sigma-Aldrich, respectively. Acetonitrile and water with UPLC/MS quality were purchased from Fisher (Illkirch, France). Methanol, phosphate buffer (KH₂PO₄), and formic acid were purchased from Sigma-Aldrich (Steinheim, Germany). QuEChERS commercial extraction kits (EN method) were obtained from Agilent Technologies (Santa Clara, PA, United States).

### Experimental Conditions and Soil Spiking

After sampling, the water contents and water holding capacity (WHC) were determined. Soils were sieved at 5 mm to discard all gravel or plant debris. Then, four sets of soils used for spiking the experiment (dried and crushed, one for each condition) were prepared with a final concentration of 10 mg kg⁻<fnref n="1" /> of DZ or OXA. These were prepared using stock solutions prepared in HPLC-grade acetone. After adding the DZ or OXA, spiked soils were left for 24 h at room temperature under an extractor hood to allow the acetone to evaporate and were then homogenized by mixing. The concentrations in these spiked soils were checked and were 9.47 mg kg⁻<fnref n="1" /> DW for OXA abiotic condition, 8.98 mg kg⁻<fnref n="1" /> DW for OXA biotic condition, 8.42 mg kg⁻<fnref n="1" /> DW for DZ abiotic condition, and 8.12 mg kg⁻<fnref n="1" /> DW for DZ biotic condition.

The experiment was then set up by adding the same aliquot of these dry spiked soils to fresh soils by distributing the powder as homogeneously as possible to each of the 82 microcosms (41 DZ and 41 OXA). The initial concentration of both DZ and OXA was quantified in microcosms by using QuEChERS extraction, as described below. These concentrations were 1.96 ± 0.10 mg kg⁻<fnref n="1" /> DW for the DZ biotic condition, 2.05 ± 0.04 mg kg⁻<fnref n="1" /> DW for the DZ abiotic condition, 1.71 ± 0.17 mg kg⁻<fnref n="1" /> DW for the OXA biotic condition, and 1.88 ± 0.06 mg kg⁻<fnref n="1" /> DW for the OXA abiotic condition. It must be noted that DZ was not detected (<LQ) in the native soil, and OXA was found at a concentration of 25 µg kg⁻<fnref n="1" /> DW soil. This native concentration was considered as negligible compared to the added OXA. To obtain a water content equal to 70% of the maximum soil WHC, deionized water was added to each microcosm and soils were homogenized again.

The experiment was conducted in triplicate for 97 days. Microcosms were sacrificed at nine sampling dates, after 0, 8, 14, 21, 33, 47, 61, 76, and 97 days of incubation. Sterile controls were performed in duplicate for seven of the sampling dates (controls at 8 and 21 days were not performed) with soils sterilized by gamma ray ionization, in the same conditions as the biotic samples. The experimental setup is presented in **Supplementary Figure 1**. Measurements of water moisture were

<footnote n="1">¹www.aquanes.eu</footnote>
<figure><img src="image_154.png" /><figcaption>**FIGURE 1** | Location of the study area and sampling point FR4N in Manche department (50), Normandy, France (image modified from Google earth).</figcaption></figure>

<figure><img src="image_155.png" /><figcaption>**FIGURE 2** | Diazepam (DZ) (A) and oxazepam (OXA) (B) biodegradation kinetics over a 97-day period. Values for biotic conditions are presented as mean values of triplicates with standard deviations, and points for sterile controls are presented as sole values for both duplicates (see **Figure 3** for details).</figcaption></figure>

also performed during the course of the experiment to ensure its stability at values approximately 70% WHC.

## Chemical Analyses

### QuEChERS Extraction of Benzodiazepines

Five grams of sieved soil was weighed in a 50-ml polypropylene extraction tube and spiked with 80 µl of a solution of isotopically labeled compounds (internal standards) and then vortexed. The

soil was then mixed with 8 ml of phosphate buffer (KH₂PO₄) and 10 ml of acetonitrile containing 5% formic acid. The mixture was agitated with an Agitax shaking device (AgytaxLab, Madrid, Spain) for 30 s, after which QuEChERS salt was added. The tube was again agitated for 60 s and finally centrifuged (5 min, 4,000 rpm). The supernatant was entirely collected (about 10 ml per sample) and weighed. For each experimental replicate, three extractions were performed (three samples per microcosm). The
three supernatants of these three extractions were combined, yielding a total extraction volume of approximately 30 ml. This was then evaporated down to 12 ml and kept at -20°C prior to analysis by UPLC-MS/MS.

Performance characteristics of the QuEChERS method for the selected pharmaceutical compounds were evaluated on the same soil as the one used in the microcosms. The recovery rate was calculated for each compound by spiking the soil at about 30 µg kg⁻¹ of dry soil (in triplicate) and then processing the extraction as described above. Matrix effects were studied by first extracting the sample (in triplicate, and with the procedure described above) and then spiking the total extracted sample at about 30 µg kg⁻¹ of dry soil for each compound (i.e., about 120 µg L⁻¹ in total supernatant).

## Quantification of Benzodiazepines

The analytical method was established to quantify a list of 24 pharmaceutical compounds in soil extracts. Chromatographic separation was performed with a Waters Acquy UPLC using a 150 mm × 2.1 mm UPLC-HSST3 C18 1.8 µm column (Waters, Guyancourt, France). Ten microliters of soil extract was injected. The mobile phase was composed of solvent A (0.007% formic acid in water) and solvent B (0.007% formic acid in acetonitrile) at a constant flow of 0.4 ml/min. The initial amount of B was 0% during 0.75 min and linearly increased to 100% in 15 min, followed by a 1-min isocratic mode and returned quickly to the initial conditions. These conditions were maintained for 2.5 min; the total run time was 19 min. Column and autosampler temperatures were maintained, respectively, at 45°C and 10°C. For more details, see Togola *et al.* (2014).

Mass spectrometry was performed on a triple quadripole (Quattro Premier XE, Waters) in Multiple Reaction Monitoring (MRM) fitted with an electrospray ionisation (ESI) interface and controlled by MassLynx software. Mass spectrometry conditions were previously described (Togola *et al.*, 2014). Briefly, positive and negative polarity modes were used simultaneously during the same analytical run.

The limits of quantification for DZ and OXA were evaluated at 4 µg kg⁻¹ of fresh soil. The half-life dissipation time (DT50) for DZ and OXA was calculated with a first-order kinetic model.

## Microbial Community Analyses

### Extraction and Quantification of Soil DNA

DNA extractions were performed on soils from each condition at all of the sampling times, using the FastPrep DNA Spin Kit for soils (MP Biomedicals) following the manufacturer's instructions, at a speed of 5 m s⁻¹ for 30 s, on 0.7–1 g of humid soil sample and eluted in 100 µl of DES. Total extracted DNA was quantified with a Quantus Fluorometer (Promega) and stored at -20°C prior to further analysis.

### qPCR of 16S rRNA and 18S rRNA Genes

Quantification of the bacterial 16S rRNA and fungal 18S rRNA gene copies was performed on all DNA samples by qPCR using a CFX Connect™ Real-Time PCR Detection System (Bio-Rad, France). The primers used were 341F (3'-CCTACGGGAGGCAGCAG-5') and

515R (3'-ATTACCGCGGCTGCTGGCA-5') (Lopez-Gutierrez *et al.*, 2004) for 16S rRNA genes, and primers FF390 (5'-CGATAACGAACGAGACCT-3') and FR1 (5'-A5CCAT TCAATCGGTAA5T-3') for 18S rRNA genes (Vainio and Hantula, 2000). qPCR reactions were performed in a total volume of 20 µl, with a mix containing 7.6 µl of sterile, nuclease- and nucleic acid-free water (MP Biomedicals, CA, United States), 10 µl of SSO Advanced Universal SYBR Green Supermix (Bio-Rad), 400 nM (16S rRNA genes) or 500 nM (18S rRNA genes) of each primer, 100 ng of T4 GP32 (16S rRNA genes), and 2 µl of template DNA (0.1–5 ng·µl⁻¹). Sterile, nuclease- and nucleic acid-free water was used instead of DNA in negative controls. For 16S rRNA gene, PCR reactions were performed as follows: 3 min at 95°C, followed by 35 cycles: 30 s at 95°C/30 s at 60°C/30 s at 72°C/30 s at 80°C. For 18S rRNA gene, PCR reactions were performed as follows: 30 s at 95°C/30 s, 40 cycles: 15 s at 95°C/30 s at 50°C/30 s at 72°C/30 s at 80°C. At the end of the qPCR, an additional step rising from 60 to 95°C at 0.5°C/s was applied for melt curves generation.

A calibration curve was obtained from serial dilutions of a known quantity of linearized plasmids containing known copy numbers of 16S rRNA or of 18S rRNA gene. All samples, controls, and standards were analyzed in duplicate. Results were reported as number of gene copies per gram of dry soil. Generation of a specific PCR product was confirmed by melting curve analyses and agarose gel electrophoresis.

## Next-Generation Sequencing (16S rRNA Gene and ITS2)

Microbial diversity was evaluated by Illumina MiSeq sequencing of the 16S rRNA gene for bacteria and archaea and ITS2 region for fungi. Sequencing was performed on 19 samples: native soil (FR4N), and three sampling dates, in triplicates, for DZ and OXA microcosms. Chosen dates were T0, T14, and T97 for microcosms corresponding at 0, 14, and 97 days after benzodiazepines spiking, respectively. The native soil corresponded to the fresh soil that was used for microcosms, before spiking.

Amplicon libraries were constructed by INRAE Transfert (Toulouse, France). Briefly, a portion of the 16S rRNA gene (V4–V5 region) was amplified using the barcoded, universal primer set 515WF—GTGYCAGCMGCCGCGGTA/928WR— CCCCGYCAATTCCMTTTTRAGT (Wang and Qian, 2009). Concerning ITS2 gene for fungi, a portion of the ITS2 gene was amplified using the specific primer set w404 CTTTCCCTACACGACGCTCTTCCGATCTTGTGARTCATCG AATCTTTG/w40 GGAGTTCAGACGTGTGCTCTTCCGATCT TCCTCCGCTTATTGATATGC (Hadziavdic *et al.*, 2014). PCR reactions were performed using the AccuStart II PCR ToughMix kit, followed by cleaning (HighPrep PCR beads, Mokascience), and pooled triplicates were submitted for sequencing on Illumina MiSeq instrument at GeT-PlaGe (Auzeville, France). Fastq files were uploaded to the Galaxy web platform (Sygenae), and the public server at usegalaxy.org was used to analyze the data, with the FROGS analysis platform (Escudié *et al.*, 2017). For 16S rRNA gene sequences, affiliations were obtained using the Silva 138_16S database. For ITS2, Unite_Fungi_8.0_18112018 reference database was used for OTUs affiliation. The affiliation
tables and sequence counts can be found in **Supplementary Tables 1, 2**. The sizes of reads for R1 and R2 (forward and reverse) were 250 bp. For trimming, the FROGS Pre-process merging, denoising, and dereplication tool was used (Galaxy Version r3.0-3.0). Mismatch rate was set to 0.1 (maximum rate of mismatch in the overlap region of R1 and R2 in consensus sequences), and merge calculations were performed using Flash software for an expected amplicon size of 413 bp (min 340 bp and max 450 bp) for 16S rRNA genes, and 389 bp (min 267 bp and max 511 bp) for highly variable ITS2 region extracted using the FROGS ITSx tool (Galaxy Version r3.0-1.0). Then, clustering was performed using FROGS Clustering swarm amplicon sequence clustering tool (Galaxy Version r3.0-1.4) with denoising. The aggregation distance clustering was set to a maximum of 3 bp for inclusion into clusters. To remove the PCR chimera in each sample, the FROGS Remove chimera tool was used (Galaxy Version r3.0-7.0). This tool is based on the VSEARCH tool for chimera detection and removal (Rognes et al., 2016). Alpha diversity indices were calculated from the NGS data. The first index corresponds to the observed number of OTUs in data from 16S rRNA gene and ITS2 region sequencing. The Chao1 index estimates the unobserved OTUs by correcting values with OTUs that are observed only one or two times in data (correction for the rarest OTUs). The Shannon and Inverse Simpson indices give an indication of the specific richness in the samples, by linking the number of species with the specific abundance of these species in the different samples. Tax4Fun data were also generated from FROGS platform, and potential metabolic pathways were recovered by comparison of the 16S rRNA gene sequences with the KEGG database (Aßhauer et al., 2015). For the 19 samples, only 1.79-2.91% of OTUs could be mapped to KEGG organisms. All 16S rRNA gene sequences and ITS2 sequences were submitted to European Nucleotide Archive (ENA) and are available under accession numbers ERS7290419 (SAMEA9567684) to ERS7290437 (SAMEA9567702). The whole project is referenced under accession number PRJEB47338.

## Statistical Analyses

Statistical analyses were performed on XLStat software v2013.3.2 (Addinsoft, 2020). Alpha and beta diversity calculations were performed using FROGS platform. Co-occurrence networks were built using Cytoscape software v3.8.0 with CoNet add-on.

## RESULTS

### Evolution of Benzodiazepine Concentrations in Microcosms

Concentrations of DZ and OXA over time, in the different microcosms and their sterile controls, were monitored on nine sampling dates (Figure 2). It firstly appeared that concentrations in the sterile controls treated by gamma-ray remained high over time, especially for DZ, indicating that sterilization was effective. Consequently, the observed results in microcosms were linked to biodegradation of DZ and OXA. In the biotic soil microcosms, biodegradation or biotransformation occurred both for DZ and for OXA very quickly: DT50 for DZ, based

on a first order degradation model, was 3.9 and 3.6 days for OXA. After 20 days, barely all the spiked benzodiazepines were dissipated [95.5% ± 0.5% (n = 3) and 96.9% ± 0.2% (n = 3) for DZ and OXA, respectively] (Figure 2), and only trace concentrations remained, whereas concentrations remained stable in sterile controls at approximately 1.5-2 mg kg⁻¹ DW soil. OXA concentrations tended to decrease slightly over time in sterile controls. It is not impossible that gamma-ray treatment did not destroy all microorganisms, especially sporulating microorganisms. Microorganisms in sporulated form during the sterilization could have grown later, explaining a slight biodegradation in controls especially for OXA conditions. It is also possible that abiotic degradation of OXA occurred during the experiment. Samples were stored in the dark, and benzodiazepines are resistant to photodegradation, but other abiotic reactions could have led to the observed OXA concentrations decrease in sterile controls. Results are, however, globally satisfying in sterile controls, and significantly different compared to biotic conditions. These results highlight a good removal rate of the two studied benzodiazepines in the studied soil, rather by biodegradation or biotransformation of the mother molecules.

### Bacteria and Archaea Dynamics Based on 16S rRNA Gene Abundance and Diversity

#### Initial Bacteria and Archaea Soil Diversity

Prokaryote community diversity was compared to the average diversity observed among 2,173 studied soils in France (Karimi et al., 2018). At the phylum level, differences were observed between the native FR4N soil and the mean diversity described in Karimi et al. (2018) for soils in France (Figure 3A). Among dominant phyla, Acidobacteria and Chloroflexi were approximately two and three times more represented, respectively, in FR4N soil compared to mean values in French soils. Although they are not highly represented, Chlamydiae, Cyanobacteria, Euryarchaeota, Spirochaetes, Nitrospinae, and Nitrospirae are, respectively, 10, 16, 422, 229, 6, and 7 times more represented in the FR4N soil compared to mean values in French soils. On the contrary, among dominant phyla, Actinobacteria, Crenarchaeota, and Firmicutes were approximately two to three times less represented in the FR4N soil compared to the mean values in French soils. Verrucomicrobia were approximately six times less represented. Among the rarest phyla, Chlorobi (0.25% in the soils of France) are absent from the studied soil. On the contrary, Calditrichaeota, Zixibacteria, Rokubacteria, Nanoarchaeaeota, Latescibacteria, and Entotheonellaeota represented 0.25-1% of the global studied soil diversity, whereas they are not described in the main phyla found in French soils (Karimi et al., 2018).

#### Evolution of Bacterial and Archaeal Abundance

Bacterial and archaeal abundances were evaluated by quantification of the number of 16S rRNA gene copies per gram of DW soil (Supplementary Figure 2A for DZ conditions and Supplementary Figure 2B for OXA conditions). In both
<figure><img src="image_156.png" /></figure>

<figure><img src="image_157.png" /></figure>

**FIGURE 3** | Comparison of microbial diversity at the phylum level for (A) bacteria and archaea between FR4N soil and data from Karimi et al. (2018), and (B) fungal diversity between FR4N soil and data from Tedersoo et al. (2014). Data from Karimi et al. (2018) correspond to mean diversity in 2,173 soil samples from France and data from Tedersoo et al. (2014) correspond to mean values in a selection of 127 samples corresponding to representative couples of soil/climate that can be found in France (i.e., temperate coniferous forests, temperate deciduous forests, grassland, and shrubland and Mediterranean soils).

<figure><img src="image_158.png" /></figure>

<figure><img src="image_159.png" /></figure>

**FIGURE 4** | (A) Ward D2 linkage clustering tree of the different samples based on the 16S OTUs repartition and beta diversity values (Bray–Curtis dissimilarities) and (B) principal coordinate analysis (PCoA) based on Bray–Curtis dissimilarity distances between the different samples.
DZ and OXA conditions, the abundance of 16S rRNA gene was significantly lower at T0, maybe due to the toxicity of added contaminants. At T8, values are intermediate, and a plateau is reached after 14 days. It appears that the period between T0 and T14 corresponds to a growth phase and that the bacterial and archaeal communities remain stable after 14 days up to the end of the monitoring at 97 days. However, they remained slightly less abundant compared to the native soil.

## Evolution of Bacterial and Archaeal Diversity

As shown by the total number of OTUs and Chao1 index, biodiversity increased after benzodiazepine addition, compared to the native soil, and did not significantly change after (Supplementary Figures 3A,B; Kruskal-Wallis test with Conover-Iman comparison, *p* < 0.05, Supplementary Figure 3). Results are comparable between DZ and OXA. This increase is overall low (approximately 50-100 OTUs compared to the native soil), but significant, especially looking at the “corrected” Chao1 index (Supplementary Figure 3B). The total number of OTUs is maximum at T14 (Supplementary Figure 3A), when the majority of DZ and OXA were biodegraded, and it tends to decrease at T97.

Shannon and Inverse Simpson indices (Supplementary Figures 3C,D) were lowest at T0 and highest (and significantly different, Kruskal-Wallis test with Conover-Iman comparison, *p* < 0.05) at T14, for both DZ and OXA. They then tended to decrease to recover values comparable to T0 and the native soil at T97. A ward linkage-clustering tree (beta diversity; Figure 4A) highlighted three distinct groups: (i) T0 and native soil, (ii) T14, and (iii) T97. Bacterial and archaeal communities were consequently similar in native soil and at T0 (abundance was lower in T0 samples but the bacterial and archaeal diversity were similar), and they changed at T14 and T97. Biodiversity was more similar at T14 and T97 compared to T0, highlighting a change due to the addition of benzodiazepines. Small differences were observed between DZ and OXA conditions, independently from the sampling date. The PCoA analysis (Figure 4B) also revealed the three-group repartition of OTUs, for T0, T14, and T97 samples, respectively.

Evolution of the relative abundance of the 100 most abundant OTUs (sum for the 19 samples) is shown and agglomerative hierarchical clustering (AHC) of these OTUs was performed and is presented in Figure 5A. The six classes defined by the AHC are also presented in Figure 5C. Six evolution patterns could be highlighted, corresponding to the six classes defined for bacterial and archaeal OTUs. Classes a and b (yellow and brown on Figure 5C) correspond to OTUs that are much more abundant at T0 compared to the other sampling dates, in DZ and OXA conditions. They are also more abundant at T14 and T97 compared to the native soil, but to a lower extent. These classes correspond to Firmicutes, and more precisely to two different OTUs of the *Brevibacillus* genus. Class c corresponds to OTUs that are relatively more abundant at T97. This class corresponds to three archaeal OTU from the Crenarchaeota phylum and one bacterial OTU from the Firmicutes phylum (*Bacillus* genus); two of the archaeal OTUs belong to the Nitrosopumilaceae order,

and were unknown or multi-affiliated at the genus taxonomic level, and the other one belongs to the Nitrososphaeraceae order. Classes d and f correspond to the high majority of OTUs (93 OTUs over the 100 most abundant). The relative abundance of these 93 OTUs remained stable during the whole experiment. Lastly, class e corresponds to an OTU that was significantly more abundant at T14 compared to the native soil and T0, and more abundant at T97 but in a lower extent. This OTU belongs to Gammaproteobacteria, *Hydrogenophaga* genus. It appears that differences concern a low proportion of the detected OTUs and are limited to OTUs belonging to the Crenarchaeota, Firmicutes, and Gammaproteobacteria phyla.

Overall, few differences were found between DZ and OXA conditions, and the structure of the bacterial and archaeal communities was not deeply modified, indicating little effect with the addition of these contaminants.

## Fungal Biodiversity Dynamics Based on 18S rRNA Gene Abundance and ITS2 Region Sequencing

### Initial Fungal Diversity

Contrary to prokaryotes, data for fungal diversity in French soils are not available. However, Tedersoo et al. (2014) published a worldwide repartition of soil fungal diversity. Samples corresponding to the climates/environments that can be found in France (temperate coniferous forests, temperate deciduous forests, grassland, scrubland, and Mediterranean soils, for 127 samples) were selected and compared to the fungal diversity in the FR4N soil (Figure 3B). In comparison with bacterial and archaeal diversity, larger differences were observed. Indeed, if classically Basidiomycetes are dominant in such soils, they were about six times less represented in the FR4N soil. On the contrary, Ascomycota and Mortierellomycota were two to three times more represented in the FR4N soil. Among phyla that are not highly represented, Chytridiomycota and Glomeromycota were 3.5 and 5.3 times more represented, and the Rozellomycota phylum was about 5,000 times more represented in the FR4N soil. Monoblepharomycota, Olpidiomycota, and Aphelidiomycota phyla were detected in the FR4N soil, even if they are not reported in Tedersoo et al. (2014). On the contrary, Rozellida phylum was not detected in the FR4N soil.

### Evolution of Fungal Abundance

Fungal abundance in soils was monitored by quantifying the 18S rRNA gene. The same trend as for bacterial abundance was highlighted. Indeed, a lower fungal abundance was observed at the beginning of the experiment, and this abundance then increased up to a plateau reached after 14 days of incubation (Supplementary Figure 4). The fungal abundance remains, however, lower compared to the native soil, with approximately one log abundance difference. Differences between DZ and OXA conditions are low.

### Evolution of Fungal Diversity

Results for fungi were different compared to bacteria and archaea ones. Indeed, for alpha diversity indices, compared to the native soil, the number of observed fungal OTUs was significantly lower
<figure><img src="image_160.png" /></figure>

**FIGURE 5** | Agglomerative Hierarchical Clustering evaluated from Bray–Curtis distances with proportional link as aggregation method for the 100 most abundant OTUs (sum on the 19 samples), for (A) bacterial and archaeal OTUs and (B) fungal OTUs. Panel (C) corresponds to the histogram presenting the repartition of the six different classes defined by AHC for bacterial and archaeal OTUs and (D) the three classed defined by AHC for fungal OTUs.

at T0 (Supplementary Figures 5A,B). The difference was less marked regarding specific richness of OTUs (Supplementary Figures 5C,D). Concerning the number of observed OTUs and Chao1, values were again comparable to the native soil at T14,

as they were significantly higher compared to T0 (Kruskal–Wallis test with Conover–Iman comparison, *p* < 0.05). The Shannon and InvSimpson indices tended to decrease during the experiment up to T97 but no significant difference could be highlighted here. The ward linkage clustering tree of fungal OTUs
<figure><img src="image_161.png" /></figure>

(beta diversity; **Figure 6A**) highlighted three distinct groups: (i) T0, (ii) T14 and native soil, and (iii) T97. Results thus differed from those for bacteria and archaea. Indeed, whereas T0 was similar with the native soil for bacterial and archaeal OTUs, here the native soil seems to be closer to the T14 samples. This is coherent with results from alpha diversity indices. Indeed, the impact on fungi seems to be higher right after benzodiazepines spiking. Consequently, samples from T0 are more different compared to native soil, T14 and T97. The PCoA analysis (**Figure 6B**) also revealed this “three-group” repartition. Samples from T14 and T97 were closer, and T14 was especially close to the native soil. T0 samples were the more different compared to the others, highlighting a possible higher impact of the addition of benzodiazepines for fungi.

## Identification of Fungi Taxa

Even if biodiversity indices did not show a clear response of the global fungal community to DZ and OXA spiking, some OTUs showed a specific evolution as shown by the AHC on the 100 most abundant fungal OTUs (**Figures 5B,D**). Trends are overall more difficult to observe compared to bacteria and archaea, as in some cases, there is a high variability between triplicates. Three classes could, however, be highlighted regarding their evolution during DZ and OXA biodegradation (**Figure 5D**). Classes 2 and 3 corresponded to the majority of OTUs, 29 and 65 over the 100 most abundant, respectively. These OTUs did not present a high evolution during the degradation kinetics, and values remained overall stable and comparable to the native soil.

Class 1 corresponds to six OTUs, for which the observed evolution during biodegradation was different. These six OTUs belonged to two phyla, Ascomycota (four OTUs) and Mortierellomycota (two OTUs). Among Ascomycota, one OTU had multi-affiliation at a higher taxonomic level, two OTUs belonged to the Hypocreales order (unidentified at a higher taxonomic rank), and one was affiliated to the *Chaetomium* genus. Among Mortierellomycota, one OTU belonged to the *Mortierella* genus, and the other was affiliated to the Mortierellaceae family. Both of these six OTUs presented a slightly higher abundance during the biodegradation kinetics experiments and tended to be more present at T97 compared to the native soil (**Figure 5D**).

## Co-occurrence Between Most Abundant Bacterial, Archaeal, and Fungal Operating Taxonomic Units

To explore potential interactions between bacteria, archaea, and fungi, a co-occurrence network was built with the 23 most abundant bacterial OTUs and fungal OTUs and 9 most abundant OTUs for archaea (**Figure 7**). No significant mutual exclusion could be highlighted between the selected bacterial OTUs. Overall, seven significant mutual exclusions were highlighted, one between bacteria and archaea, three between bacteria and fungi, and three between archaea and fungi. Mutual exclusions were observed (i) between the Sutterellaceae and Nitrosopumilaceae families and (ii) an OTU affiliated
to the Pleosporale order; (iii) between the Chloroplast order and Mortierellaceae family; (iv) between *Mortierella* genus (close from *Mortierella gamsii*) and Thaumarchaeota archaeon MY2; (v) between *Methanosarcina* genus and (vi) one OTU from the Nitrososphaeraceae family; and (vii) between the *Hydrogenophaga* genus and an OTU from the GS11 fungal order (Figure 7). Co-occurrences were more abundant compared to mutual exclusions, but within kingdoms only. Indeed, no significant co-occurrences were highlighted between taxa of bacteria/archaea/fungi. High co-occurrence of the 23 most abundant bacterial OTUs was observed, not for every OTU but for the majority of them. For archaea, co-occurrence was especially observed between Nitrososphaeraceae family and *Methanosarcina* genus, and between one OTU from the Nitrosopumilaceae family and another one close to Thaumarchaeota archaeon MY2. Concerning fungi, no co-occurrence between the 23 selected OTUs could be highlighted.

## Exploration of the Evolution of Metabolic Pathways Using Tax4Fun

Only approximately 2% of bacterial and archaeal OTUs could be mapped to KEGG pathways; fungi were not considered in this approach. Nevertheless, a total of 3,554 metabolic pathways were detected in the data from the OTUs affiliation. These were compared between samples from microcosms during benzodiazepine biodegradation and the native soils. Among the 3,554 pathways, some were enhanced compared to the native soils (the majority), and some declined. Indeed, among the 3,554 characterized pathways, between 44.9 and 49.4% were enhanced by at least 10% compared to the native soil, 9.7-21.1% by 50%, 3.3-8.6% by 100%, 0.1-1.4% by 500%, and 0.06% to 0.6% by 1,000% (20 pathways). The latter were five transferases, five Oxidoreductases, seven hydrolases, one lyase, and three proteins linked to ADP/ATP metabolism (Supplementary Table 1). Most of them were linked to redox reactions and to ADP-ATP cycles, highlighting an increase in microbial global activity. A few more functions were highlighted in DZ conditions compared to OXA, but overall results are close between the two molecules, suggesting that the processes involved in their biodegradation may be similar.

## DISCUSSION

The objectives of this study were to assess the capacity of soil microbial communities (bacteria, archaea, and fungi) from a study site periodically flooded by water from a WWTP, to resist and potentially degrade benzodiazepine molecules, especially DZ and OXA when introduced into the soil. The study was based on a soil sampled in a soil aquifer treatment (SAT) context, where water previously treated in a WWTP are injected in the SAT area. The aim was to focus on two recalcitrant CECs, DZ, and OXA, and simulate an

input in the studied soil to study their behavior, including microbial biodegradation.

## Soil Biodiversity in a Soil Aquifer Treatment Context at Agon-Coutainville

It was previously shown that biodiversity in river could be affected by WWTP effluents (Drury et al., 2013; Blunt et al., 2018). Our study highlights that it may also be the case for soils in a SAT context. At the prokaryotic phylum level, several differences were found between the study soil and the mean diversity of French soils as described by Karimi et al. (2018) (Figure 3A). Among dominant phyla, Acidobacteria and Chloroflexi were approximately two and three times more represented, respectively, in our soil. Acidobacteria and Chloroflexi phyla contain diverse metabolic profiles, including strong links with carbon cycle. Acidobacteria are very commonly found in different environments including soils (de Chaves et al., 2019). Genomic and physiological characteristics of Acidobacteria were recently reviewed (Kielak et al., 2016). They concluded that many gaps still exist to fully understand the functional role of Acidobacteria in the soil C degradation process. However, it was also shown that both microbial C degradation processes and acidobacterial communities can be affected by soil management (de Chaves et al., 2019), suggesting a potential impact of soil use and characteristics on the abundance of Acidobacteria. The phylum Chloroflexi is composed of diverse groups of organisms that include anoxygenic photoautotrophs, aerobic chemoheterotrophs, thermophilic organisms, and anaerobic organisms that obtain energy through reductive dehalogenation of organic chlorinated compounds (Gupta, 2013). Other phyla such as Chlamydiae, Cyanobacteria, Euryarchaeota, Spirochaetes, Nitrospinae, and Nitrospirae were found to be overrepresented compared to mean values in French soils. Actinobacteria, Crenarchaeota, and Firmicutes were approximately two to three times less represented, and Verrucomicrobia were approximately six times less represented. The identity of the rarest phyla (such as Calditrichaeota, Rokubacteria, Nanoarchaeota, Latescibacteria, Chlorobi, and Elusimicrobia) was also found to be different. The repeated inputs of organic substances from WWTP in the studied soil could explain their higher abundance compared to “classical” abundances in soil. Differences could also come from the microbial inputs from the WWTP biological treatment. Indeed, Drury et al. (2013) showed that the input of WWTP effluent modified the nature of bacterial communities in water and sediments (Drury et al., 2013), especially due to the input of contaminants from WWTP.

Concerning fungi in the studied soil (Figure 3B), Basidiomycetes were found to be about six times less represented, whereas Ascomycota and Mortierellomycota were two to three times more represented. Basidiomycetes are generally described as the principal fungal phylum in soils in terms of abundance (Tedersoo et al., 2014). In our case, Ascomycota were the dominant phyla. Fungi are heterotrophic organisms; they need organic carbon from external sources to live. With soil pH and plant cover (Wubet et al., 2012), total organic carbon (TOC)
<figure><img src="image_162.png" /><figcaption>**FIGURE 7** | Co-occurrence network between the 23 most abundant bacterial OTUs, the 9 most abundant archaeal OTUs, and the 23 most abundant fungal OTUs. Network was built using Pearson, Spearman, and Bray-Curtis analyses, both for significance thresholds <0.05. Co-occurrences (co-presence marked in green, mutual exclusion marked in red) are highlighted if significant for at least two of the three previously cited methods. The line width is proportional to the weight of the correlation, ranged from -0.828 to -0.710 for mutual exclusion (red) and from 0.881 to 0.981 for co-presence (green). The number of OTUs represented was chosen arbitrarily after many assays to make the network more readable as possible.</figcaption></figure>

content is generally described as the main parameter controlling the abundance and diversity of soil fungal communities (Tedersoo et al., 2014; Liu et al., 2015, 2018a,b). The specificity of the studied soil, with high organic matter, and contaminants, contains all the ingredients for fungal development. Liu et al. (2015) showed that the relative abundance of Basidiomycota was negatively correlated (r = -0.600) to the soil carbon content in a selection of 25 soil samples (Liu et al., 2015). For Ascomycota, a high carbon content was more positively correlated to Ascomycota abundance. Our soil contains 4.7% of organic matter, corresponding to 47 g kg⁻¹ dw soil, which is a quite high OM content. This is possibly the reason why Basidiomycota were found to be less abundant, and Ascomycota more abundant compared to classical values. Moreover, it was shown that Ascomycota were the main representatives of the fungal community in a soil contaminated by PAHs and trace metals (Bourceret et al., 2016). The input of (organic) contaminants from WWTP effluents could then also explain the dominance of Ascomycota. Among phyla that are not highly represented classically, significant differences could also be highlighted. Rozellomycota were about 5,000 times more represented in our soil compared to mean values from Tedersoo et al. (2014). Rozellomycota constitutes the basal lineage of the kingdom of fungi. They predominantly feed by osmotrophic nutrition (Tedersoo et al., 2018), meaning that they feed on dissolved substances. The high inputs of dissolved substance

from WWTP could explain why Rozellomycota are 5,000 times more represented compared to classical soils. They could also take part in the degradation of organic micropollutants. Presently, little is known about Rozellomycota, but our results suggest that they may be used as a bioindicator to characterize an environment impacted by WWTP effluents or sewage sludges.

## Biodegradation/Biotransformation of Diazepam and Oxazepam

In our study, sorbed DZ and OXA were extracted during the QueChers procedure; biodissipation as well as extraction procedure could be attested thanks to comparison with sterile gamma-ray ionized controls, where concentrations remained stable during the experiment. It is thus possible to affirm that a biological process occurred, explaining the observed dissipation of DZ and OXA in the microcosms. Our dissipation kinetics results are highly more rapid compared to most of the results previously described. Indeed, in the studied soil, DT50 was 3.9 and 3.6 days for DZ and OXA, respectively, and after 97 days (and even almost after 20 days), 95.51% ± 0.49% and 96.87% ± 0.22% of the spiked DZ and OXA, respectively, were dissipated due to biological activity of fungi, bacteria, and/or archaea.

The biodegradability of DZ and OXA is often described as very limited in the environment as well as in lab-scale biological experiments (Ternes et al., 2004; Redshaw et al.,
2008; Suarez et al., 2010; Klaminder et al., 2015; Greskowiak et al., 2017; Min et al., 2018). They were also shown to be resistant to biological treatments in WWTPs (Falàs et al., 2016), explaining their inputs in the studied soil. Indeed, most of the data on the efficiency of WWTP treatments concerns DZ and shows that (i) less than 10% is removed during conventional biological treatment, (ii) the efficiency seems to be higher during anaerobic treatment (10–50%), and (iii) the removal rate is mainly related to sorption rather than degradation (Ghattas et al., 2017). Similarly, OXA is described as persistent in both aerobic and anaerobic treatments (Patterson et al., 2010; Kosjek et al., 2012). Some degradation pathways were, however, highlighted, such as demethylation (Helbling et al., 2010), but an efficient biodegradation in the environment has not yet been reported. Different values available in the literature for DZ and OXA biodegradation are listed in **Table 1**. Some researchers found that DZ was not directly degradable by bacteria, especially when other carbon sources more easily accessible are available, which is the case in soils (Tappin et al., 2014). A mixed microbial culture from activated sludge treatment has also been shown to demethylate DZ to form 7-chloro-5-phenyl-3H-1,4-benzodiazepin-2-one (Helbling et al., 2010). The same culture also formed a mono-hydroxylated DZ derivative, but the exact position of the hydroxyl group was not further specified. Redshaw et al. (2008) investigated the susceptibility to microbial degradation of a selection of CECs, including DZ and OXA, in short-term (60 days) bacterial liquid cultures derived from sewage sludge amended soil. They highlighted that DZ was not degraded or transformed after 60 days, but up to 40% OXA was removed in liquid cultures (**Table 1**). Kosjek et al. (2012) compared the reports of PBT profiler<fnref n="2" /> (21.10.2011) with the results of their WWTP pilot, consisting of a succession of 4-L units in open circuit under oxic and then anoxic conditions. According to pbtprofiler.net, DZ and OXA are not persistent in water (DT50 < 60 days). These molecules are moderately persistent in soils (DT50 = 60–180 days) and very persistent in sediments (DT50 > 180 days). Based on their experience in anoxic bioreactors or oxic–anoxic cascades, the removal of DZ (100 µg L⁻¹ continuous feed) was less than 32%. Similarly, the OXA abatement in oxic conditions was less than 24%. On the other hand, removal in anoxic conditions reached 67% after 1 year of feeding the bioreactor, and the authors suggest an effect of biomass adaptation over time to be confirmed by biomass analyses (quantity and diversity). In our soil, a continuous exposure to CECs, including benzodiazepines, by periodic flooding by WWTP water, could have led to a strong adaptation of the soil microbial community. Löffler et al. (2005) showed that DZ was highly persistent with rapid and extensive sorption on sediments, stable in soils, groundwater, and during wastewater treatment. The same study showed that OXA is moderately persistent in the environment with a DT50 and a lower sorption rate on sediments than DZ. In addition, Löffler et al. (2005) did not observe any degradation of DZ to OXA in sediments. Carballa et al. (2006) showed a removal of 38% ± 21% to 60% ± 18% of DZ (depending on temperature) in anaerobic

bioreactors simulating a WWTP treatment. An adaptation of the bacterial community in sludge was highlighted, and better yields were obtained with water thermal pretreatment. Suarez et al. (2010) investigated the degradation of CECs in lab-scale experiments using activated sludge reactors under aerobic and anoxic conditions (Suarez et al., 2010). They highlighted that DZ and trimethoprim were highly resistant to biological transformation, and that the degradation rate for studied CECs was highly dependent on the specific microbial species.

Other studies showed that fungi, especially *via* laccases enzymes, are able to degrade and or transform benzodiazepines. Ostadhadi-Dehkordi et al. (2012) showed a DZ and OXA removal after 48 h of 18.6 and 18.7%, respectively, in lab-scale experiment using purified fungal laccase from Ascomycete *Paraconiothyrium*. They showed that adding enzyme mediators increased the yields up to 61.4 and 71.2% for DZ and OXA, respectively. However, this study was performed in water samples, in controlled conditions, and with a purified laccase (Ostadhadi-Dehkordi et al., 2012). Ambrus et al. (1975) showed that the fungus *Aspergillus niger* J/8 N was able to demethylate DZ to form 7-chloro-5-phenyl-3H-1,4-benzodiazepin-2-one. This study is the first to describe the ability of fungi to biotransform DZ. Rodarte-Morales et al. (2011) studied the potential ability of three white rot fungi strains to degrade pharmaceutical and personal care products (PPCPs) including DZ: an anamorph species of *Bjerkandera* sp. R1, *Bjerkandera adusta*, and *Phanerochaete chrysosporium*. They showed that most of the studied PPCPs were completely degraded except fluoxetine and DZ. DZ recoveries were between 23 and 57% at the end of the experiment, where, for example, carbamazepine was completely degraded.

Overall, DZ and OXA seem to be highly recalcitrant to microbial degradation, but, even if research in this way is still needed, some bacteria or fungi, *via* several degradation pathways, are able to biotransform and/or biodissipate and/or completely biodegrade these compounds. The monitoring of the biodiversity evolution during the biodegradation can then help to find candidates able to perform DZ and OXA biodegradation.

## Bacterial and Archaeal Candidates for Biodegradation of Diazepam and Oxazepam

As shown in **Figure 8A**, the main bacteria showing a specific behavior during DZ and OXA biodegradation are two OTUs from the *Brevibacillus* genus and one from the *Hydrogenophaga* genus. *Brevibacillus* has been proposed as a biological tool by Panda et al. (2014) especially for biotechnological applications due, for example, to their ability to biodegrade low-density polyethylene, to act as a candidate bio-control agent, and as a tool for structural and functional biology (Panda et al., 2014). *Brevibacillus parabrevis* has been shown to degrade low-density polyethylene (LDPE), a recalcitrant thermoplastic made from petroleum, by forming a biofilm on LDPE surface, or with granular LDPE as sole carbon source and without nitrogen (Pramila et al., 2012). Also, *Brevibacillus brevis* has been described as able to biodegrade triphenyltin (TPT), a highly toxic endocrine disruptor used as ingredient for antifouling products and

<footnote n="2">²pbtprofiler.net</footnote>
<table><caption>TABLE 1 | Generally described DZ and OXA biodegradation in environmental samples, cultures from environmental sample, or experimental biodegradation studies.</caption><thead><tr><th></th><th>DT50 (days)</th><th>Removal (%) (after X days)</th><th>Matrix</th><th>Concentrations</th><th>Comments</th><th>References</th></tr></thead><tbody><tr><td rowspan="12">Diazepam</td><td>311 ± 25 (water: 34 ± 5)</td><td>–</td><td>Sediment/water</td><td>500 ng/g</td><td>Batchs OECD 308 (mineralization: &lt;2%, sorption: 60%)</td><td>Löffler et al., 2005</td></tr><tr><td>38</td><td>–</td><td>Water</td><td></td><td>PBT profiler; &lt;60 days: not persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>75</td><td>–</td><td>Soil</td><td></td><td>PBT profiler: &gt;60 days: moderately persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>340</td><td>–</td><td>Sediment</td><td></td><td>PBT profiler: &gt;180 days: very persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>–</td><td>–</td><td>River sediment</td><td></td><td>Batchs (Kd = 1.9–24.8 L/Kg, log Koc = 2.4–2.8)</td><td>Stein et al., 2008</td></tr><tr><td>280</td><td>–</td><td>Freshwater</td><td></td><td>Drinking water intake (Lake Mead)</td><td>Blunt et al., 2018</td></tr><tr><td>280</td><td>–</td><td>Freshwater</td><td></td><td>Colorado river</td><td>Blunt et al., 2018</td></tr><tr><td>–</td><td>0% (60 days)</td><td>Bacterial liquid culture from sewage sludge amended soil</td><td></td><td>Aerobic bioreactor</td><td>Redshaw et al., 2008</td></tr><tr><td>–</td><td>18.6% (2 days)</td><td>Lab-scale experiment using purified fungal laccase from Ascomycete Paraconiothyrium</td><td></td><td>In water samples, in controlled conditions, and with a purified laccase, Without enzyme mediators</td><td>Ostadhadi-Dehkordi et al., 2012</td></tr><tr><td>–</td><td>61.4% (2 days)</td><td>Lab-scale experiment using purified fungal laccase from Ascomycete Paraconiothyrium</td><td></td><td>In water samples, in controlled conditions, and with a purified laccase, With enzyme mediators</td><td>Ostadhadi-Dehkordi et al., 2012</td></tr><tr><td>–</td><td>38 ± 21%–60 ± 18% (20 days)</td><td>Anaerobic digesters simulating WWTP treatment</td><td></td><td>Mesophilic at 37°C and pre-treatment thermophilic at 55°C, better results with thermal pre-treatment</td><td>Carballa et al., 2006</td></tr><tr><td>–</td><td>17 ± 11% (440 days)</td><td>Aerobic bioreactor fed with WWTP influent</td><td></td><td>Experiments performed under nitrifying and denitrifying conditions</td><td>Suarez et al., 2010</td></tr><tr><td>–</td><td>16 ± 17% (440 days)</td><td>Anoxic bioreactor fed with WWTP influent</td><td></td><td>Experiments performed under nitrifying and denitrifying conditions</td><td>Suarez et al., 2010</td></tr><tr><td>3.9</td><td>95.51 ± 0.49% (97 days)</td><td>Soil</td><td>1 mg/kg</td><td>Soil in a SAT context, infiltration reed bed area, periodically flooded by WWTP effluent</td><td>This study</td></tr><tr><td rowspan="12">Oxazepam</td><td>54 ± 3 (water: 34 ± 5)</td><td>–</td><td>Sediment/water</td><td>100 ng/g</td><td>Batchs OECD 308 (mineralization: nd, sorption: 19–29%)</td><td>Löffler et al., 2005</td></tr><tr><td>38</td><td>–</td><td>Water</td><td></td><td>PBT profiler: &lt;60 days: not persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>75</td><td>–</td><td>Soil</td><td></td><td>PBT profiler: &gt;60 days: moderately persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>340</td><td>–</td><td>Sediment</td><td></td><td>PBT profiler: &gt;180 days: very persistent</td><td>Kosjek et al., 2012</td></tr><tr><td>–</td><td>–</td><td>River sediment</td><td></td><td>Batchs (Kd = 2.0–23.50 L/Kg, log Koc = 2.4–2.7)</td><td>Stein et al., 2008</td></tr><tr><td>–</td><td>40% (60 days)</td><td>Bacterial liquid culture from sewage sludge amended soil</td><td></td><td>Aerobic bioreactor</td><td>Redshaw et al., 2008</td></tr><tr><td>–</td><td>18.7% (2 days)</td><td>Lab-scale experiment using purified fungal laccase from Ascomycete Paraconiothyrium</td><td></td><td>In water samples, in controlled conditions, and with a purified laccase, without enzyme mediators</td><td>Ostadhadi-Dehkordi et al., 2012</td></tr><tr><td>–</td><td>71.2% (2 days)</td><td>Lab-scale experiment using purified fungal laccase from Ascomycete Paraconiothyrium</td><td></td><td>In water samples, in controlled conditions, and with a purified laccase, with enzyme mediators</td><td>Ostadhadi-Dehkordi et al., 2012</td></tr><tr><td>3.6</td><td>96.87 ± 0.22% (97 days)</td><td>Soil</td><td>1 mg/kg</td><td>Soil in a SAT context, infiltration reed bed area, periodically flooded by WWTP effluent</td><td>This study</td></tr></tbody></table>
<table><caption>**TABLE 2** | Percentage of metabolic pathways (KEGG) increased or decreased compared to the native soil, at T0, T14, and T97.</caption><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="6">Percentage among the 3,554 metabolic pathways</th></tr><tr><th>T0D</th><th>T14D</th><th>T97D</th><th>T0O</th><th>T14O</th><th>T97O</th></tr></thead><tbody><tr><td rowspan="5">Metabolic pathways increased compared to the native soil</td><td>&gt;+10%</td><td>44.88</td><td>45.61</td><td>46.65</td><td>47.89</td><td>48.51</td><td>49.41</td></tr><tr><td>&gt;+50%</td><td>17.14</td><td>21.05</td><td>9.74</td><td>20.26</td><td>19.75</td><td>13.28</td></tr><tr><td>&gt;+100%</td><td>6.56</td><td>3.55</td><td>3.29</td><td>8.58</td><td>3.32</td><td>4.00</td></tr><tr><td>&gt;+500%</td><td>1.44</td><td>0.11</td><td>0.11</td><td>1.35</td><td>0.11</td><td>0.11</td></tr><tr><td>&gt;+1,000%</td><td>0.56</td><td>0.11</td><td>0.06</td><td>0.34</td><td>0.06</td><td>0.06</td></tr><tr><td rowspan="3">Metabolic pathways decreased compared to the native soil</td><td>&lt;−10%</td><td>37.14</td><td>36.07</td><td>16.04</td><td>30.78</td><td>30.84</td><td>17.75</td></tr><tr><td>&lt;−50%</td><td>3.15</td><td>2.08</td><td>0.39</td><td>2.59</td><td>2.00</td><td>0.20</td></tr><tr><td>&lt;−100%</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td><td>0.00</td></tr></tbody></table>

For increased functions, results are presented for functions increased by 10, 50, 100, 500, and 1,000%; for decreased functions, results are presented for functions decreased by 10, 50, and 100%.

<figure><img src="image_163.png" /><figcaption>**FIGURE 8** | Principal coordinate analysis built from Bray-Curtis dissimilarity matrix of the 100 most abundant (A) bacterial and archaeal OTUs and (B) fungal OTUs. The OTUs of interest are in bold.</figcaption></figure>

fungicides (Ye et al., 2013). Yang and Lee (2007) highlighted the ability of *Brevibacillus* sp. strain P-6 to degrade phenol. The strain was isolated from an acclimated mixed culture, and cultivated with phenols. They found that *Brevibacillus* sp. strain P-6 was able to completely remove phenol within 93 h of incubation, at concentrations lower than 200 mg L⁻¹ (Yang and Lee, 2007). Overall, *Brevibacillus* genus has often been described as able to biodegrade organic contaminants, including contaminants with an aromatic ring, which could explain why it was highly more abundant in our soil after DZ and OXA introduction. This suggests that *Brevibacillus* strains were involved in the first biodegradation steps. This higher abundance of *Brevibacillus* is connected to the higher abundance of specific metabolic pathways (increased by more than 1,000% compared to native soil, Supplementary Table 4) highlighted with tax4fun tool. Some pathways involving Oxidoreductase, hydrolase, and lyase enzymes are acting on ester bonds, methane metabolism, or biosynthesis of secondary metabolites. These pathways were probably involved in the observed biotransformation of DZ and

OXA, even if the high range of possible reactions involving these enzymes does not help to clearly identify the pathways.

*Hydrogenophaga* genus has often been described as able to biodegrade aromatic compounds such as polycyclic aromatic hydrocarbons (PAHs). A species from *Hydrogenophaga* genus was found to be relatively more abundant especially at T14 when most of DZ and OXA were degraded. Xin et al. (2010) showed that *Hydrogenophaga palleronii* LHJ38 grew on naphthalene as sole carbon and energy source, in minimal medium with 2 g L⁻¹ naphthalene, highlighting its naphthalene biodegradation capacity (Xin et al., 2010). Yan et al. (2017) identified a PAHs-degrading strain, *Hydrogenophaga* sp. PYR1, isolated from PAH-contaminated river sediments. *Hydrogenophaga* sp. PYR1 was able to degrade high-molecular-weight polycyclic aromatic hydrocarbons (pyrene and Benzo[a]pyrene) under both aerobic and anaerobic conditions (Benzo[a]pyrene was degraded only under anaerobic conditions). These PAHs, being recalcitrant to microbial biodegradation, especially Benzo[a]pyrene, suggest that *Hydrogenophaga* may representa
good candidate for bioremediation approaches (Yan et al., 2017). Yang et al. (2016) showed that *Hydrogenophaga atypical* QY7-2 efficiently degraded 3-Methyldiphenylether (MDE), an important alkyl-substituted diphenyl ether compound that is widely used as an intermediate in the synthesis of pyrethroid insecticides. The strain was isolated from activated sludge and was able to grow with MDE as sole carbon source, and to perform MDE complete mineralization, suggesting the ability to degrade aromatic rings (Yang et al., 2016). Gan et al. (2011) studied a co-culture consisting of *Hydrogenophaga* sp. PBC and *Ralstonia* sp. PBA, isolated from textile WWTP. The culture could tolerate and utilize 4-aminobenzenesulfonate (4-ABS) as sole carbon, nitrogen, and sulfur source under aerobic condition (Gan et al., 2011). *Hydrogenophaga* sp. H7 was also shown to simultaneously degrade 3-hydroxybenzoate (3-HBA) or 4-HBA (3-/4-HBA) during culture (Fan et al., 2019). Their results suggest that *Hydrogenophaga* sp. H7 is an ideal candidate for degradation of aromatic compounds. Regarding archaea, mainly Nitrosopumilaceae and Nitrososphaeraceae families presented specific evolutions, but in a lower extent compared to previously described bacteria, with a slightly higher abundance at T97. Both Nitrosopumilaceae and Nitrososphaeraceae belong to the Thaumarchaeota phylum, which is an important ammonia oxidizer group in different environments including soils, in aerobic conditions, and was the first archaeal phylum identified as involved in nitrification (Brochier-Armanet et al., 2012). Thaumarchaeota and especially Nitrosopumilaceae and Nitrososphaeraceae families are consequently chemolithoautotrophic organisms, able to grow *via* aerobic ammonia oxidation and CO₂ fixation, with some organic material needed to support growth. The water from WWTP containing ammonia (approximately 0.2 mg/L), with regular inputs, could explain the presence of these taxa. The higher abundance observed at the end of our experiment could be linked to previous biodegradation of contaminants, leading to CO₂ releases. All conditions could then have been reached during the experiment for the archaeal taxa growth. Thaumarchaeota may not have been specifically involved in DZ and OXA biodegradation, but their abundance could be part of the result of the biodegradation.

Regarding tax4Fun results, the highest impact is observed at T0, partly due to the *Brevibacillus* abundance at T0. These results concern only highly increased functions, but many others could have been necessary for benzodiazepine biodegradation. The tax4fun results may give perspectives for further studies, but it is not possible here to state on the different steps and enzymes involved in benzodiazepines biodegradation, as there are many, and it is not an obligation to observe an increase higher than 1,000% to explain a degradation pathway. For example, all function from group 3.5 (Acting on carbon-nitrogen bonds, other than peptide bonds), detected 131 times, increased between 15.7 and 28.3% compared to the native soil, with maximum at T14 after most of benzodiazepines were degraded. Such enzymes were probably necessary to perform benzodiazepine degradation, but

their relative abundance did not increase significantly compared to the native soil. Functions increased by >1,000% were consequently probably involved in a high range of reactions and are not highly specific to benzodiazepine biodegradation (list of these functions in **Supplementary Table 4**). Most of these functions were detected mainly at T0. At T97, only two functions remain higher than 1,000% compared to the native soil, phenylalanine ammonia-lyase (EC:4.3.1.24) and NAD(P)H-quinone oxidoreductase subunit 6 (EC:1.6.5.3), suggesting that once biodegradation is completed, the soil returns to its original functions. If tax4fun provides a means to further exploit 16S rRNA genes dataset and draw hypotheses on the functional capabilities of microbial communities, results should be taken with caution as they remain only predictive and depend on functional information available from public genome databases.

Other functions decreased compared to the native soil (Table 2), but to a lower extent. Indeed, no function decreased lower than 100% compared to the native soil, and only 0.2–3.2% were decreased up to 50% compared to the native soil. This highlights that soil functions were conserved after benzodiazepines addition.

## Fungal Candidates for Biodegradation of Diazepam and Oxazepam

Fungi are heterotrophic organisms. It is consequently harder to clearly link biodegradation of specific organic compounds to their abundance, especially when other carbon sources are available, which is the case in soils. It is, however, assumed that the abundance and growth of some specific OTUs in both microcosms (n = 3) suggest that these OTUs resisted DZ and OXA presence, and that they could have been involved in their biodegradation as their abundance increased over time. Six OTUs belonging to two phyla presented this evolution. Four OTUs belonged to Ascomycota and two OTUs belonged to Mortierellomycota (Figure 8B). Many *Mortierella* spp. are chitinolytic, and some species were described as able to degrade cellulose from plants to get sugar for their growth, *via* the xylanase enzymatic reaction. Ascomycota, as well as other fungi, require organic compounds as energy sources. This phylum has a wide range of metabolic capabilities and is also able to degrade biopolymers from plants such as lignin and cellulose (Boddy and Hiscox, 2017). It is admitted that fungi able to degrade complex biopolymers such as lignin or cellulose are also able to degrade recalcitrant organic compounds, such as polychlorobiphenyls (PCB), chlordecone, or polycyclic aromatic hydrocarbons (Cvancarova et al., 2012; Mao and Guan, 2016; Kadri et al., 2017). Consequently, the higher abundance of some OTUs belonging to Mortierellomycota and Ascomycota phyla after 97 days in our experiments could be linked to the biodegradation of the studied compounds.

Our results suggest that some specific OTUs evolved differently compared to others and were sometimes highly more abundant compared to the initial native soil. For
bacteria and archaea, the shift in the community seemed to remain even after contaminant degradation, whereas for fungi, the structure of the community recovered values comparable to the native soil. A direct identification of degraders, bacteria, archaea, or fungi, is not possible in this kind of experiment, but it is interesting to observe the evolution and possible implications of specific OTUs, at the community level, as occurring in the environment. The biodegradation of the targeted compounds DZ and OXA when introduced onto soil was highly more rapid compared to the literature. This result suggests that the soil microbial community is well adapted to these CECs, due to regular inputs from WWTP, and that in that case, biodegradation can occur rapidly, with DT50 of less than 4 days in our study. The study site infiltration zone, being close from the sea and with low depth groundwater, is reassuring about the fate of DZ and OXA and the possible contamination of the sea. Moreover, the potential degradation/transformation by-products were not yet studied, and further studies will explore these aspects, to ensure that no more toxic and/or recalcitrant compounds are released by these biological reactions in soil.

## CONCLUSION

Biodegradation or biotransformation of DZ and OXA faster than previously described was observed in a soil receiving water from a WWPT, with a DT50 of less than 4 days. The analysis of the abundance, diversity, identity, and potential metabolisms of the soil bacterial, archaeal, and fungal communities has provided information on the identity of the microorganisms that potentially participated in benzodiazepines dissipation. The *Brevibacillus* and *Hydrogenophaga* bacterial genera especially presented specific evolution, with higher abundances right after DZ and OXA addition for *Brevibacillus*, and right after most DZ and OXA were degraded for *Hydrogenophaga*. These genera are known to degrade persistent organic contaminants, and seem to be good candidates to perform assays on benzodiazepine biodegradation. Future research on the metabolic capacities of *Brevibacillus* and *Hydrogenophaga* genera, as pure cultures or rather in bacterial, archaeal, and fungal communities in soil to promote cometabolism processes, could be explored. Moreover, the implication of the fungal Ascomycota, Mortierellomycota, or Rozellomycota phyla, which were found to be more abundant in the initial soil, on xenobiotics, and especially CEC biodegradation or biotransformation, could be explored. The abundance of Rozellomycota could represent a good bioindicator of a contamination by WWTP effluent rich in dissolved organic contaminants. A screening of this fungal OTU could be interesting in diverse contexts, especially in (ground)water impacted by WWTP effluents or sewage sludge spreading.

Even if disappearance of mother molecules DZ and OXA was clearly highlighted in the biotic soil microcosms in our study, it is so far not possible to clearly affirm if this was due to

biodegradation (up to biodegradation by-products or to complete mineralization) or biotransformation of mother compounds. Performing a complete non-target screening of the different extracted samples, with the aim to identify the degradation compounds produced during the experiment and to confirm biodegradation or biotransformation pathways, is consequently planned.

## DATA AVAILABILITY STATEMENT

All sequences were submitted to European Nucleotide Archive (ENA) database. 16S rRNA gene sequences and ITS2 sequences are available for the 19 samples under accession numbers ERS7290419 (SAMEA9567684) to ERS7290437 (SAMEA9567702). The whole project is referenced under accession number PRJEB47338.

## AUTHOR CONTRIBUTIONS

MaC contributed to the experimental design, carried out experimental work, data analysis, and drafted the manuscript. CS, PS, JH, and CJ contributed to the experimental design, data analysis, and drafting and revising of the manuscript. GP-C, QG, and MP allowed access and provided information on the Agon-Coutainville site, and revised the manuscript. MiC carried out a part of the lab experiments in the study. All authors contributed to the article and approved the submitted version.

## FUNDING

We thank European Commission for financial support through the H2020 AquaNES EU project under agreement number no. 689450. The authors also gratefully acknowledge the financial support provided to the PIVOTS project by the Centre - Val de Loire Region (ARD 2020 program and CPER 2015-2020) and the French Ministry of Higher Education and Research (CPER 2015-2020 and public service subsidy to BRGM). Support from the European Union via the European Regional Development Fund is also acknowledged. Finally, the authors wish to thank BRGM for the financial support on the internal TOFIDEM project and funds received for open access publication.

## ACKNOWLEDGMENTS

We wish to thank SIGENAE Group and UMR-1280 PhAN Inra-Université de Nantes for their work on FROGS platform.

## SUPPLEMENTARY MATERIAL

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fmicb.2021.742000/full#supplementary-material
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