Fate of Eight Different Polymers under Uncontrolled Composting

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Fate of eight different polymers under uncontrolled composting conditions: relationships between deterioration, biofilm formation and the material surface properties Anne Mercier, Kevin Gravouil, Willy Aucher, Sandra Brosset-Vincent, Linette Kadri, Jenny Colas, Didier Bouchon, and Thierry Ferreira Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.6b03530 • Publication Date (Web): 23 Jan 2017 Downloaded from http://pubs.acs.org on January 28, 2017

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Environmental Science & Technology

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Fate of Eight Different Polymers under Uncontrolled Composting Conditions:

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Relationships Between Deterioration, Biofilm Formation and the Material Surface

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Properties

4 5 6 7 8 9 10 11 12 13 14 15 16

Anne Mercier†, Kevin Gravouil†, Willy Aucher†, Sandra Brosset-Vincent†, Linette Kadri†, Jenny Colas†, Didier Bouchon†,‡, Thierry Ferreira†*

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ABSTRACT

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With the ever-increasing volume of polymer wastes and their associated detrimental impacts

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on the environment, the plastic life-cycle has focused increasing attention. Here, eight

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commercial polymers selected from biodegradable to environmentally-persistent materials, all

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formulated under a credit card format, were incubated in an outdoor compost to evaluate their

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fate over time and to profile the microbial communities colonizing their surfaces. After 450

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days in compost, the samples were all colonized by multispecies biofilms, these latest

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displaying different amounts of adhered microbial biomass and significantly distinct bacterial

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and fungal community compositions depending on the substrate. Interestingly, colonization

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experiments on the eight polymers revealed a large core of shared microbial taxa,

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predominantly composed of microorganisms previously reported from environments

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contaminated with petroleum-hydrocarbons or plastics debris. These observations suggest that

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biofilms may contribute to the alteration process of all the polymers studied. Actually, four

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substrates, independently of their assignment to a polymer group, displayed a significant

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deterioration, which might be attributed to biologically-mediated mechanisms. Relevantly, the

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deterioration appears strongly associated with the formation of a high-cell density biofilm

†

Laboratoire coopératif ThanaplastSP - Carbios Bioplastics - Ecologie et Biologie des Interactions, Centre National de la Recherche Scientifique, UMR 7267, Université de Poitiers, Poitiers, France ‡ Equipe Ecologie Evolution Symbiose, Ecologie et Biologie des Interactions, Centre National de la Recherche Scientifique, UMR 7267, Université de Poitiers, Poitiers, France

1 ACS Paragon Plus Environment


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onto the polymer surfaces. The analysis of various surface properties revealed that roughness

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and hydrophilicity are likely prominent parameters for driving the biological interactions with

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the polymers.

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ABSTRACT ART

38 39 40

Keywords: polymer, biofilm, biodegradable, surface property, plastic, deterioration

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INTRODUCTION

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Due to their unique chemical properties, both natural and synthetic polymers are widely used

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worldwide for a large variety of applications including the formulation of plastics, which offer

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many advantages over other materials, such as high performance and durability, ease of

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processing, high productivity and low production costs.1 Constant innovations in the plastic

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industry have resulted in technical breakthroughs in medicine, agriculture or transportation in

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particular.1 Nevertheless, this widespread and increasing use of plastics is also directly

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responsible for the serious public and environmental issues related to their accumulation as

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wastes, which have emerged within the last 40 years.2-5 Accidental disposal of solid polymers,

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the major components of plastics, are visible as litter in the environment, including open

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landfills, coastal sediments, oceans and rivers and can induce harmful environmental

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damages.4,6 Without preventive actions, such as implementation of remediation or 2 ACS Paragon Plus Environment

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introduction of new environmentally compatible and friendly polymers, this anthropogenic

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contamination and the ensuing long-term threats to living organisms are expected to last for

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decades to centuries.2

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Polymer degradation is achieved mostly through scission of the main or side-chains to

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transform polymers into oligomers, dimers and finally monomers. These initial cleavage steps

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are usually catalysed by abiotic factors such as UV-radiation, thermal activation or/and

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chemical treatments.7-9 Also, polymers may undergo biodegradation through microbial

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hydrolysis and oxidation. This process occurs via several sequential steps, including bio-

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deterioration, bio-fragmentation, bio-assimilation and bio-mineralisation.4,8,10 Due to their

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high molecular weights and their poor solubility in water, long-chain polymers are not easily

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captured and assimilated by surrounding microorganisms.11 To circumvent this limitation,

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secretion of extracellular enzymes and free-radicals occurs first to depolymerise the polymer

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chain(s) outside the cells. Subsequently, when the molecular weight of the polymer is

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sufficiently reduced, intermediate products can be transported into the cytoplasm of the cell

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and introduced into the microorganisms’ metabolic pathways. Biodegradation requires a

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crucial initial step that is the formation and development of a microbial biofilm, either at the

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surface of the polymer or directly into the polymer matrix itself following abiotic alterations,

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in a process which is influenced by the chemical and the physical properties of the polymer,

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as well as by the environmental conditions.11-15 Surprisingly, data presently available on

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polymer-associated microbial communities are scarce compared to the large amount of studies

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on biofilm formation and development on other physical supports.16 To date, the few studies

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on the microbial communities inhabiting the so-called “plastisphere” are mostly related to the

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micro- to macro- plastic debris collected from sea environments, and are mainly focused on

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the potential toxicity of persistent organic pollutants adsorbed to plastic particles and the risk

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of pathogen dispersion with plastic transport.5,16-19 Nevertheless, the bio-mineralization



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(resulting in excretion of completely oxidized metabolites: H2O, CO2, N2, CH4) appears as a

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suitable long-term answer for the management of polymer wastes once they have reached the

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environment, since it can result in the complete elimination of the primary and secondary

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intermediate products and therefore avoid their leaching and/or accumulation in environments

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with unknown and/or ignored effects on biodiversity and health. In this context, more

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investigations are required to profile the microbial communities colonizing each type of

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polymer, and to identify the main parameters driving microbial attachment onto polymer

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surfaces, in relation with the polymer degradation efficiency.

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The present study falls within this context. Here, cards obtained by compression moulding of

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commercial granules from eight polymers of various natures were all incubated under the

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same environmental conditions at a fixed location (an outdoor compost system) for the same

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period of time, in order to investigate the fate of the substrates and to address the relationships

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between the attached bacterial and fungal taxa, and the surface properties of the polymer

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samples.

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MATERIALS AND METHODS

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Polymers, card preparation and surface properties. Eight different polymer types were

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selected from biodegradable (or claimed as such) to environmentally-persistent materials

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(namely polyesters, polyolefins and polyamide) and with the highest purity available from the

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manufacturers (Table 1, see the chemical structures in Fig. S1, Supporting Information SI1).

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The raw polymers were supplied as granules and used to form card (850 x 550 x 20 mm; see

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SI2 for detail on card preparation).

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The degree of crystallinity of each polymer card was determined using a Mettler Toledo

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DSC1 (differential scanning calorimeter) by Technopolym (Toulouse, France). Contact angles

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with three liquid probes were determined at the Alençon Institute of Plastics (ISPA, Alençon,


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France), using a GBX Digidrop goniometer. The values were used to estimate the energy of

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surface to the card surface as well as its dispersive and polar components. Additionally, the

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surface micro-structures of each polymer card were observed using a Scanning Electron

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Microscope JEOL JSM 5600LV (see SI2 for detail on surface property analyses).

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Compost-incubated experiment. Fifteen clean cards of each polymer type were positioned

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vertically in an outdoor compost (see SI2 for detail on compost site preparation). The natural

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microorganisms found in the compost were regarded as the source of colonizers of polymer

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cards and deterioration was based on naturally occurring composting reactions. Hence, no

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microbial bio-augmentation and additional organic amendment were conducted over the

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experiment. The experimental plot was subjected to the oceanic and temperate climate of the

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region characterized by mild temperatures (on average 12.5-13°C), average rainfall of 800–

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900 mm/year (Poitiers), and narrow seasonal ranges (http://www.infoclimat.fr/).

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Compost-incubated experiments were conducted for 450 days. Ten replicate cards of each

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type of polymer were weighed using an OHAUS TS120 Precision Standard analytical balance

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(Bioblock Scientific) after washing, thoroughly scraping off to remove cells and particles,

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rinsing and drying the cards to a constant weight was obtained. The polymer card weight loss

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was calculated using the following formula: Percentage of weight loss = [(initial weight−final

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weight after compost incubation) / initial weight] × 100.

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DNA extraction from polymer card associated- and soil microbial communities. Three

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compost-incubated cards of each polymer type were washed 4-times by complete immersing

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and moderate movements in sterile water to remove non-adherent cells and particles to the

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card surface. Both sides of the card were thoroughly scraped off for 5 min using a sterile cell

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scraper perpendicular to the surface and rinsed with a total of 50 mL of sterile water.

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Extractable fraction of biofilm was centrifuged 12 800 g, 20 min at 4 degrees C. The

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supernatant was discarded and samples were stored at -20°C until DNA extraction.



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Additionally, the soil from 5 cores was taken in compost area surrounding the cards and

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pooled to yield one single composite sample, sieved to 2 mm and portioned into 500 mg (dry

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weight) aliquots used for analysis.

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DNA extraction from the polymer card associated- and soil microbial communities were

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performed using the same procedure based on the ISO 1106321 (see SI2 for detail on DNA

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extraction and purification). Quality and size of the crude and purified extracted DNA were

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checked by electrophoresis. DNA quantifications were estimated with the BIO-1D image

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analysis software (Vilber Lourmat) using a standard curve of HindIII-digested λ DNA

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fragments (Promega). Aliquots of 0.5 ng/µL diluted DNA were stored at -20°C ready for

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molecular applications.

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Pyrosequencing of 16S and 18S rRNA gene sequences. The microbial communities

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inhabiting the surface of each type of polymer card were analysed by pyrosequencing of

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ribosomal genes. Each sample was prepared from the same DNA input quantity in order to

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normalize the libraries and achieve even representation of each library in the pyrosequencing

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results. The V3-V4 region of the bacterial 16S rRNA genes was amplified using the primers

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F479 (5′-CAGCMGCYGCNGTAANAC-3′) and R888 (5′-CCGYCAATTCMTTTRAGT-3′)

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as described.21 Additionally, a fungal 18S rRNA gene fragment was amplified using the

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primers

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CGATAACGAACGAGACCT-3′)22 as described21 (see SI2 for detail on amplicon preparation

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and purification). The two pyrosequencing runs were conducted out in a GS Junior Sequencer

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(Roche Applied Science) following manufacturer's recommendations.

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Bioinformatic analysis of 16S and 18S rRNA gene sequences. Pyrosequencing data were

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analysed using the GnS-PIPE (version 1.1.13) pipeline21 (see SI2 for detail on bioinformatic

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analysis). Normalization by random selection was conducted to obtain the same number of

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reads for each sample and to avoid biased bacterial or fungal community comparisons.

FR1

(5′-ANCCATTCAATCGGTANT-3′)


and

FF390

(5′-

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All the taxonomy-based analyses using similarity approaches against SILVA r114 reference

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database obtained from the GnS-PIPE were then post-processed using R packages and

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BioVenn.23,24 The complexities of the bacterial and fungal communities adhered onto the eight

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polymer surfaces and collected from the surrounding compost were investigated by measuring

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within-sample diversity (α-diversity) including richness (number of genus-level Operational

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taxonomic units (OTUs)), and the Shannon and Evenness indices, using the defined OTU

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composition. Bray-Curtis dissimilarity distances were calculated from the normalized OTU

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tables for each fraction to construct a dissimilarity matrix and Principal Coordinate Analysis

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(PCoA) was carried out with the Vegan package in R.25 Datasets are available on the EBI

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database system in the Sequence-Read Archive (SRA), under study accession numbers

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PRJEB14758.

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Statistical analysis. Comparisons in card weight were performed using Mann-Whitney test

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(significance assessed at the level of p < 0.05). The Spearman’s rank correlation test was used

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to measure the strength of the linear association between values from the microbial biomass

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of the biofilm developed at the card surface and the compost-incubated card weight loss.

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Comparison of multiple groups was performed using the R Vegan software program and the

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analysis of similarity (ANOSIM).25 Data from card properties (Table 1) were fit to the

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distance matrix generated from sequencing using the R Vegan software program and the

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envfit function25, producing coefficient of determination r2 and combined p-values, in order to

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evaluate the direct contributions of variables to the microbial community patterns (i.e.

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bacterial and fungal β-diversity analysis). The significance of the variable fitting was

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determined using 999 permutations.

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RESULTS

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Polymer card properties. In this study, the fate in compost of five polyesters (namely PBAT,



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PBS, PET, PLLA and PHA; Table 1), four of them being considered as biodegradable, at least

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under industrial, controlled composting conditions (PBAT, PBS, PLLA and PHA26), of two

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polyolefins (EVOH and PP) and of one polyamide (PA66) was evaluated. Characteristic

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surface properties of the polymer cards, with potential relations with biomass recruitment

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and/or degradation were determined. A first observation was that the degree of crystallinity

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varied greatly from one polymer to the other, with values ranging from 9.8 to 60.1%. PBS

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cards appeared to be the most crystalline polymer whereas PET was the most amorphous

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material (Table 1). Surface energy determinations revealed that PHA displayed the highest

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surface energy with 60.0 mJ/m2, whereas values ranged from 32.1 to 48.9 mJ/m2 for the other

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polymers. The dispersive component was quite homogenous among the various samples,

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ranging from 31.8 to 44.6 mJ/m2. By contrast, the polar component was significantly higher

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on the surface of PHA, with 22.7 mJ/m2, whereas this parameter ranged from 0.3 to 6.9 mJ/m2

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for the other polymers (Table 1). Finally, the surface of the eight polymer cards displayed

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different micro-structures (SI1 Fig. S2). The cards synthetized from PBS, PHA, PBAT and

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PA66 showed a rough appearance, with micron-sized depressions and protuberances covering

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their surface, while EVOH, PET, PP and PLLA cards appeared rather smoother and more

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homogenous.

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Compost-incubated polymer cards. In a next step, the polymer cards were removed from

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compost after 450 days of incubation and their relative deterioration was assessed by weight

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loss. The initial and final weights of the various samples are displayed in Fig. 1A.

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Interestingly, the results of this study demonstrated that deterioration took place in our

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compost simulation and showed that the weight loss did not occur to a similar extent for the

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eight substrates studied. Two of the five polyesters and the polyamide polymers showed a low

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but significant weight loss (%), with a decrease reaching 7.9 (± 0.7)%, 5.5 (± 0.3)% and 1.1

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(± 0.2)% for PHA, PBS and PA66, respectively. Whereas weight loss was not significant (Fig.


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1A), surface (SI1 Fig. S3) and mechanical alterations (i.e. increased flexibility) were

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noticeable for compost-incubated PBAT cards. Therefore, for this specific polymer, an

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additional Gel Permeation Chromatography (GPC) analysis was conducted to evaluate a

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potential reduction of the average length of the PBAT chains after incubation in compost.

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Relevantly, both Mw and Mn were decreased after compost incubation for this polymer (from

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39 400 Da to 36 000 Da for Mw, and from 35 000 Da to 18 400 Da for Mn, respectively), and

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the polydispersity index was increased (from 1.125 to 1.957 Da), showing a clear-cut

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reduction of the PBAT chain length (SI1 Table S1).

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Microbial biomass colonizing the polymer card surface. Relative DNA amounts were used

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as estimates of the microbial biomass colonizing the surface of the polymer cards27. Results

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revealed that a microbial colonization occurred for all the compost-incubated cards studied,

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however to a variable extent depending on the polymer considered (Fig. 1B). Indeed, the

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relative amounts of DNA recovered ranged from 28.2 (± 2.6) to 238.2 (± 27.0) ng DNA/cm2

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of card. Remarkably, the formation of a high cell-density biofilm was quantified on both PHA

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and PBS polyester cards, which displayed the most important weight loss (see above). By

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contrast, the microbial colonization appeared to be lesser on PET (Mann-Whitney test

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between values from PET and PHA; p < 0.05), which is also assigned to the polyester group,

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but which remained unaltered under compost incubation. In compost, the microbial biomass

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was estimated to 8.7 (±1.6) DNA/g of dry soil, in agreement with literature.27

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Interestingly, a significant Spearman coefficient value of 0.738 (p < 0.05) revealed a positive

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correlation between the microbial biomass adhered at the polymer surface and the card weight

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loss after compost incubation.

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Bacterial and fungal OTUs richness, Shannon and Evenness diversity indices. A high

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throughput sequencing was used to characterize both bacterial and fungal communities

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colonizing each polymer card surface. A total of 5 400 (with a mean length of 371 bases) and



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3 000 reads (with a mean length of 317 bp) for bacteria and fungi respectively, were obtained

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after sequencing quality filtering and homogenization steps, for each type of polymer card and

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for the compost samples.

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The compost-incubated PHA, PBS and PBAT polymer cards displayed a lower bacterial

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richness on their surfaces than the one initially present in the compost, but also than the one

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adhered to the surface of the other polymers studied (Table 2). Between 250 to 290 bacterial

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OTUs were identified at 95% identity in the biofilm communities onto the surface of PHA,

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PBS and PBAT, while more than 550 bacterial OTUs were assigned to the biofilm collected

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from the surface of the PET card, for example. The Shannon index ranged from 3.82 to 5.56,

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indicating a bacterial diversity on the surface of all the polymer cards. Nevertheless, the

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Shannon index was also significantly lower for PBS, PHA and PBAT than for the other

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polymers. The Evenness index of all the polymer samples showed few differences, ranging

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from 0.69 to 0.88, suggesting there was not a discrepancy in the repartition of OTU

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abundance in favor of a few, but highly dominant, bacterial OTUs on the polymer cards.

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Interestingly, regarding fungal diversity metrics, compost-incubated PBS, PHA and PBAT

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polymer cards displayed also a lower fungal richness and Shannon index than for the other

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polymers (SI3 Table S1).

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Bacterial and fungal community structures. A principal coordinate analysis (PCoA) from

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Bray-Curtis distance matrix was performed to examine the overall variations among bacterial

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and fungal communities colonizing the polymer cards after incubation in compost (Fig. 2A).

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PCoA analysis showed that the three replicate cards from each type of polymer clustered

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closely, underscoring the reproducibility of the bacterial and fungal community structures and

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the robustness of the molecular characterization of these microbial communities. Moreover,

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PCoA analysis also revealed that each polymer displayed the ability to support distinct

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microbial communities (Fig. 2A and SI3 Fig. S1; ANOSIM permutation test, R = 0.918 and


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0.728 for bacterial and fungal communities respectively, R significance = 0.001).

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Interestingly, the bacterial communities colonizing the PHA, PBS and PBAT cards were

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clearly distinct from those identified on the five other polymers, but also from the

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autochthonous bacterial community of the surrounding compost: they clustered together,

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along the first principal coordinates (PCoA1), which accounts for 34.18% of the total

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variability (Fig. 2A). Along the PCoA2 axis (16.76% of the variability), the bacterial

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community associated to the PHA card surface appeared clearly separated from those attached

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to PBS and PBAT. Similar results were obtained from PCoA analysis of the fungal

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communities colonizing the polymer cards (see SI3 Fig. S1 for description).

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Thus, according to the two PCoA analyses, the microbial communities on the 8 polymers can

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be clustered into three groups: PHA, [PBS, PBAT] and [PLLA, PA6.6, PP, EVOH, PET].

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Bacterial and fungal community composition associated to polymer cards. Taxonomic

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classification at the phylum level of the OTU representative sequences revealed the

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dominance of Proteobacteria and Bacteroidetes in compost soil and at the surface of all the

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incubated polymer cards, with 71.54 to 93.76% of the total pyrosequencing sequences being

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assigned to these two phyla (SI4 Table S1). Members of the Planctomyces (< 5.26% of the

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total pyrosequencing sequences) and Acidobacteria (< 4.89%) were also found. Notably, the

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Firmicutes phylum reached 11.90% of the total pyrosequencing sequences at the surface of

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the PET cards, a value higher than for the other polymers (0.79 to 8.32% only). The most

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abundant bacterial classes were Alphaproteobacteria (9.81 – 23.60% of the total

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pyrosequencing sequences at the class level), Gammaproteobacteria (8.01 – 16.66%),

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Sphingobacteria (14.88 – 29.05%). Interestingly, the Betaproteobacteria class reached

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15.14%, 23.98% and up to 25.19% of the total pyrosequencing sequences at the surfaces of

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PHA, PBS and PBAT cards respectively, whereas their relative abundance remained in the

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range of 4.06 to 7.18% for the other samples (SI4 Table S2). Differences between the



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bacterial communities colonizing the polymer cards were also obvious at the family level (see

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SI3 Fig. S5 for description and SI4 Table S3).

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A similar fungal community composition was observed at the phylum level at the surface of

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all the polymer cards, with a predominance of Ascomycota, Basidiomycota, Chytridiomycota

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and Glomeromycota, their relative abundance varying with the type of polymer (SI4 table S4).

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For example, the Ascomycota phylum reached 70.96 (± 2.48)% and 52.05 (± 4.57)% of the

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sequences assigned at the surface of the PBAT and PHA cards, respectively, and only 8.64 (±

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1.05)% for PET cards. Nevertheless, unknown fungi represented from 2.25% to 8.75% of the

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total sequences assigned at the phylum level, unclassified fungi, 2.26% and 26.82%, and

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environmental fungi, 8.09% and 44.71%. Differences in the compositions of the polymer-

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associated communities were also highlighted at the fungal class level (SI4 Table S5). For

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example, Dothideomycetes was the most represented fungal class observed at the surface of

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PBAT cards (with 65.26 (± 4.03)% of the sequence assigned at the class level),

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Sordariomycetes for PHA cards (33.48 ± 4.15%) and Agaricomycetes for EVOH cards (35.47

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± 5.38%). Differences between the fungal communities colonizing the polymer cards were

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also obvious at the family level (SI3 Fig. S2 for description and SI4 Table S6).

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Comparison of bacterial and fungal communities colonizing polymers: unique and

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shared OTUs. A three-set Venn diagram analysis was performed to represent the unique and

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shared OTUs and sequences among the three bacterial and fungal community clusters

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identified from the PCoA analyses (see above): this diagram was elaborated using the

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communities colonizing either PHA, PET (as representative of the [PLLA, PA6.6, PP, EVOH,

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PET] cluster) and PBS (as representative of the [PBS, PBAT] cluster). A total of 130 bacterial

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OTUs were shared by the three community clusters and accounted for 87.53%, 78.66% and

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94.47% of total classified sequences for PHA, PET and PBS, respectively (Fig. 2B).


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Regarding the fungal communities (SI3 Fig. S3), a high proportion of the total sequences

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were also common to the three defined polymer clusters. From 1.65% to 13.97% of total

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bacterial and fungal classified sequences were identified in only one cluster and from 1.29%

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to 21.60% in two clusters. This analysis revealed a common core within the bacterial and

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fungal communities colonizing the surface of polymers (core microbiome). Hence, the

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differences in the bacterial and fungal community structures observed as a function of the

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polymer studied (as revealed by the PCoA analyses) resulted mainly from variable

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abundances of dominant microbial OTUs, rather than from the emergence of specific yet rare

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OTUs. Among the sequences of the core microbiome, the most represented OTUs belonged to

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the bacterial phyla Bacteroidetes (with the families: Chitinophagaceae, Bacteroidaceae,

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Cytophagaceae, Flavobacteriaceae) and Proteobacteria (with the families: Pseudomonadaceae,

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Sphingomonadaceae), and to the fungal family Mortierellaceae.

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Drivers of microbial colonization: relationships between material surface properties and

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microbial taxa of biofilms. A combined analysis of the card-surface properties and of the

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microbial community structure was conducted to evaluate the contribution of these physico-

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chemical parameters (Table 1) to the polymer-associated microbial community patterns (Fig.

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3 and SI3 Fig. S4). In the ordination plots, the length of the arrow corresponding to a given

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surface parameter indicates the strength of the relationship between this parameter and the

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community composition. From this analysis, it appeared that the best correlations were

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obtained for the bacterial composition dissimilarity matrices from PHA and the polar

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component (r2 = 0.907) and with the energy of surface (r2 = 0.665). The PBS and PBAT cards

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were associated with the dispersive component (r2 = 0.347). All associated p-values were

325

below 0.01, indicating that these results can be considered as robust (Fig. 3). Interestingly,

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crystallinity did not appear to be an important determinant of microbial community structure

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on polymer surface (r 2 = 0.2657 for bacterial communities) since the correlation did not reach



328

a statistical significance (p > 0.01). Similar results were obtained from the fungal

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communities (see SI3 Fig. S4 for description). Whereas the scanning electron microscopy

330

(SEM) observations were not converted into quantitative data, the biological interactions with

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a given polymer appeared strongly dependent on its surface roughness, as suggested by the

332

presence of micron-sized irregularities covering the surface of the PHA, PBS, PBAT and

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PA66 polymer cards (SI1 Fig. S2), providing favourable microniches for microbial

334

attachment.

335 336

DISCUSSION

337

Most of the current investigations on the biomass and diversity in microbial communities

338

colonizing the surface of plastics focus on marine debris, randomly collected from different

339

locations after variable submersion periods.18,19,28-32 Under these conditions, the samples

340

correspond almost exclusively to polypropylene and polyethylene-based plastic wastes, the

341

most prominent polymers used worldwide, and originate from different and unknown

342

production sites. As a consequence, they display, for a given type of polymer, different

343

molecular weight distributions and oxidation levels, and are likely to contain various levels of

344

adjuvants and prooxidant additives. Moreover, the exposition of the debris to abiotic stresses

345

such as UV-radiations, remain uncontrolled and is likely to vary greatly from one sample to

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the other, making difficult a clear-cut correlation between the intrinsic properties of a given

347

polymer and the recruitment of a selective microbial community.19 Considering these

348

foregoing observations, and to avoid as much as possible some of these bias and allow direct

349

comparisons, eight different commercial raw polymer types, ranging from polyolefin,

350

polyester to polyamide groups, all formulated under the same credit-card format, were

351

incubated in the present study at a fixed outdoor location under uncontrolled conditions that

352

resemble home-composting conditions. This approach allowed us replicating the samples to


Page 14 of 32

Page 15 of 32


353

profile and compare the microbial communities forming a biofilm at the surface of a specific

354

polymer.

355

Whatever the substrate studied (i.e. claimed as biodegradable or environmentally-persistent,

356

chemical structure; Table 1), all compost-incubated cards were colonized by a multispecies

357

biofilm. Interestingly, some supports, independently of their belonging to a specific polymer

358

group, developed biofilms displaying significant variations in both bacterial and fungal

359

community compositions as compared to the surrounding compost soil, indicating that these

360

substrates represent distinct environmental niches. However, microspatial variations of the

361

soil microbial community cannot be completely excluded. Microbial richness and diversity

362

metrics confirmed that each polymer card develops a heterogeneous and complex ecological

363

system.

364

The microorganisms detected at the surface of polymer belonged mostly to the bacterial phyla

365

Proteobacteria and Bacteroidetes. The prevalence of these phyla has already been reported

366

from petroleum-hydrocarbon contaminated environments and some of their members have

367

been directly implicated in hydrocarbon degradation.16,33-35 Dominance of Proteobacteria

368

(mainly Alpha and/or Gammaproteobacteria) and Bacteroidetes has also been reported on

369

plastic debris collected from marine environments.19,31 Their relative abundance was used in

370

several studies as putative signatures of biofilm formation stages, Proteobacteria and

371

Bacteroidetes behaving as primary and secondary biofilm colonizers, respectively.18,36,37

372

Filamentous fungi were also detected at the polymer card surfaces, as from hydrocarbon-

373

contaminated soils.38-40 Some of these organisms have been reported to be potent hydrocarbon

374

bio-degraders, but fungi are also suspected to increase bacterial access to hydrophobic organic

375

substrates.41,42

376

The colonization experiments performed in this study also revealed that the different

377

polymers share a large core of microbial taxa, mainly composed of members of the



378

Bacteroidetes phylum. Members of this phylum, common in ecosystems, have been reported

379

to be fast-acting decomposers of the organic matter and are known to degrade high-molecular-

380

weight organic compounds, including petroleum hydrocarbons.43,44 Altogether, these

381

observations strongly support the presence of a biodiversity displaying potent microbial

382

polymer-degrading capacities on virtually all the card surfaces, most polymers being formed

383

from hydrocarbon molecules. Nevertheless, the direct involvement of all these

384

microorganisms in the alteration process should be now demonstrated. Relevantly, three of

385

the five polyesters (PHA, PBS and PBAT) and the polyamide (PA66) showed a significant

386

weight loss and/or visual surface alterations that might be attributed to biologically-mediated

387

processes based on our experimental conditions, in which abiotic factors such as mechanical

388

constraints and exposition to UV radiations are likely to be moderate (i.e. in a buried static

389

system) in comparison with aquatic systems. However, the weight loss remained low after

390

450 days in the compost, confirming the expected long–term persistence of polymeric

391

material contaminations in the environment. These results sustain that actions such as

392

preventing plastic waste from reaching the environment, optimizing plastic management

393

(reducing, reusing, recycling), or developing new environmentally compatible and friendly

394

polymers (i.e. truly degradable under natural conditions) should be promoted.

395

The most significant weight loss was observed with PHA, which is in good agreement with

396

previously published data on this hydrolysable polyester produced from renewable

397

resources.45 The hydrolysis of PHA can take place in different environments. However, the

398

degradation rate depends on several parameters, including the duration of the experiment, the

399

temperature and the soil pH, but also on the material thickness, experiments being often

400

conducted with thin films of few micrometers.45 Many microorganisms isolated from various

401

environments such as the model bacteria Pseudomonas putida KT 2440, belonging to the

402

family Pseudomonadaceae identified here on the card surfaces, are able to intracellularly


Page 16 of 32

Page 17 of 32


403

hydrolyse PHA in a wide range of hydroxyalkanoic acids and thus may indirectly contribute

404

to the polymer deterioration.45-47

405

Altogether, our results do not suggest that some of the eight polymers studied are non-

406

degradable per se, but rather that they differ for their ability to support a high cell-density

407

biomass from the surrounding environment, with effective deterioration capacities. Indeed, if

408

all the polymers studied in this work recruit potent degraders on their surface, we could notice

409

that the deterioration potential for a given polymer could be related with the amounts of

410

fungal and bacterial biomass. The results suggest a cell-density dependent polymer

411

degradation process. Another important bottleneck in polymer degradation is very likely the

412

environmental conditions, which have to be optimal to initiate the first cleavage steps that are

413

required to generate the pre-substrates compatible with their further assimilation by the

414

recruited microorganisms. Such conditions may be quite difficult to achieve when the samples

415

are buried in the soil. In this context, microorganisms may also preferentially degrade simpler

416

carbon sources that are available from the environment, rather than initiate a switching of

417

their metabolism to access the more complex carbon-sources offered by the polymer cards.

418

In the present study, under uncontrolled composting conditions, the property of

419

biodegradability was not confirmed for PHA, PBAT, PBS and PLLA, suggesting a

420

discrepancy with environmental marketing claims. This is explained by the test methods used

421

to determine the degree and rate of aerobic biodegradation of plastic materials, which are

422

based on exposure to a controlled-composting environment under laboratory conditions, at

423

thermophilic temperatures.48 Clearly, most of the plastic packaging that claims to be

424

“biodegradable” will only weakly or partially deteriorate under conditions typical of most

425

home-compost piles and will probably not be degraded at all in natural soil environments, in

426

which they often end up.

427

An important conclusion of the present study is also that the surface properties of the



428

polymers may strongly influence the formation and the microbial composition of the biofilms.

429

An intriguing observation was that, among the various surface properties tested in this study,

430

crystallinity appeared to be poorly correlated with biofilm formation. Indeed, intuitively, one

431

may suspect that microorganisms may more easily adhere and consume a less organised (i.e.

432

less crystalline or more amorphous) material. Accordingly, previous data showed that

433

enzymes indeed mainly attack the amorphous domains of a polymer.49-52 A clear

434

counterexample here was PBS, which displayed the highest crystallinity index, but recruited

435

biofilms very efficiently and was the second most degraded polymer under our experimental

436

conditions.

437

By contrast to crystallinity, a high surface energy, in conjunction with a high surface

438

roughness, may represent a driving parameter for biofilm formation. Obviously, a hydrophilic

439

surface, as observed for PHA cards, is prone to favour microbial adherence, as previously

440

reported.53-54 However, the present results also showed that relatively hydrophobic polymeric

441

surfaces, as observed with the PBAT and PBS cards, are also efficiently colonized and

442

degraded by surrounding microorganisms. A common parameter to the most degradable

443

polymers of this study (namely, PHA, PBS, PBAT and PA66) clearly appeared to be their

444

surface micro-structures: they all displayed a quite rough surface as compared to the other

445

materials. These micron-sized irregularities provide sites for microbial attachment, due to

446

their dimensions similar to those of bacteria, and thus favour microorganisms-polymer

447

contacts that may accelerate polymer degradation by the microbial community from the

448

compost. Therefore, the present results tend to confirm that the surface wettability (water

449

contact angle) could be a less important parameter for microbial attachment to polymer

450

surface than the surface roughness, as also suggested in the literature.55 However, a set of

451

material properties may act synergistically to sustain optimal biofilm formation and therefore

452

facilitate further degradation, as is the case of PHA. Altogether, our study points at the


Page 18 of 32

Page 19 of 32


453

modulation of surface properties as a crucial determinant to consider in order to enhance the

454

recruitment of potent microbial polymer degraders from the surrounding environment. In this

455

context, surface irregularities and wettability appear as the most promising parameters to

456

target. Future studies, aiming at evaluating the impacts of these properties on polymer

457

degradation in soil (with a main focus on the most persistent polymers) will undoubtfully

458

bring new perspectives for a better control of the fate of plastics in the environment and for a

459

significant reduction of their detrimental impacts on living organisms.

460 461

ASSOCIATED CONTENT

462

Supporting Information

463

Supporting Information1 (SI1, Fig. S1-S3 and Table S1) includes data on surface properties of

464

the polymer cards, SI2 provides a detailed experimental procedure, SI3 (Table S1 and Fig. S1-

465

S5) provides results on fungal (Part1) and bacterial (Part2) communities colonizing the

466

surface of the compost-incubated polymer cards and SI4 (Tables S1-S6) provides the relative

467

abundances of the microbial taxonomic groups colonizing the card surface.

468

This material is available free of charge via the Internet at http://pubs.acs.org.

469 470

AUTHOR INFORMATION

471

Corresponding author

472

*Thierry Ferreira, Laboratoire coopératif ThanaplastSP- Carbios Bioplastics - Ecologie et

473

Biologie des Interactions, Centre National de la Recherche Scientifique, UMR 7267,

474

Université de Poitiers, UFR SFA, Pôle Biologie Santé, 1 rue Georges Bonnet, bât B37, 86073

475

Poitiers, cedex 9, France, E-mail address: [email protected], phone: +33 (5) 49

476

45 40 04; fax:+33(5) 49 45 40 14

477

Notes



478

The authors declare no competing financial interest.

479 480

ACKNOWLEDGMENTS

481

Authors are grateful to the laboratory of Ecology and Biology of Interactions (University of

482

Poitiers) and Carbios (Biopôle Clermont-Limagne) for collaboration and support. We want to

483

acknowledge the staff of Parks Department at the University of Poitiers, E. Leroy (Valagro-

484

Carbone Renouvelable, Poitiers) and E. Beere (ImageUP platform, Poitiers).

485

Authors are sincerely thankful for the scientific support and helpful discussions provided by

486

S. Terrat and the technical recommandations from M. Lelièvre and V. Novak (GenoSol

487

platform, INRA Dijon, France, www2.dijon.inra.fr/plateforme_genosol/) for the development

488

of the pyrosequencing. A. M. dedicates this work to J. Lesobre.

489 490

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491

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642 643

Table legends

644

Table 1: Name, origin of the polymers used in this study and card properties (n = 1).

645

Table 2: Bacterial OTU richness and diversity indices from the compost and the different

646

polymers (mean ± standard error of the mean).

647 648 649

Figure captions

650

Fig. 1: Compost-incubated cards analysis. (A) Polymer card weight before and after

651

incubation in the compost (mean ± standard error of the mean). * indicates significant weight


Page 26 of 32

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652

loss (Mann-Whitney test, p < 0.05). The percentage of weight loss (mean ± standard error of

653

the mean) is given above the bars. (B) Amounts of DNA measured after direct extraction from

654

biofilms colonizing the compost-incubated cards (mean ± standard error of the mean).

655

Fig. 2: (A) Principal coordinate analysis (PCoA) of the bacterial communities associated with

656

the different polymer cards and the compost. Two-dimensional PCoA plot was based on the

657

Bray-Curtis distance matrix. Percentage of the diversity distribution explained by each axis is

658

indicated on the figure. (B) Three-set Venn diagram representing the unique and shared

659

bacterial OTUs at 95% identity (in bold) among polymers. Percentages indicate the

660

corresponding proportions of associated sequences.

661

Fig. 3: Polymer card properties (see Table 1) fitted onto bacterial community PCoA (see Fig.

662

2A) after pyrosequencing and taxonomic assignment by GnS-PIPE. Arrows represent the

663

contribution of each property to the discrimination of the bacterial diversity in contact with

664

polymer card surface. A long arrow shows a strong correlation. 95% confidence ellipses are

665

drawn for each plastic. Explained variations for the first five dimensions are indicated on the

666

figure (labels and bar plot).



Page 28 of 32

Table 1 Surface energy (mJ/m2) Crystallinity Polymer

Abbreviation Manufacturer Reference

dispersive

polar

(%)

total component

Polyolefin Ethylene-vinyl alcohol

EVOH

Kuraway

33.7

33.7

3.2

36.9

Poly(propylene)

PP

LyondellBasell Moplen HP 520H

36.9

31.8

0.3

32.1

Poly(butylene adipate terephthalate) PBAT

BASF

ecoflex® F Blend C1200 †, ‡

18.8

44.6

4.3

48.9

Poly(ethylene terephthalate)

PET

NaturePlast

PTI 001 ‡

9.8

40.2

5.4

45.6

Poly(butylene succinate)

PBS

NaturePlast

PBE 003 †, ‡

60.1

38.1

6.3

44.4

Poly(hydroxy alkanoate)

scl-PHA*

Mirel®

M4100 †, ‡

21.5

37.3

22.7

60.0

Poly(-L-lactide)

PLLA

NaturePlast

PLE 001 †, ‡

19.7

33.4

6.9

40.3

PA 66

DuPont™

Zytel® 101F NC010

29.8

37.8

3.8

41.6

Eval™ E105B

Polyester

Polyamide Poly(amide) 66

* short-chain-length PHA, † claimed as biodegradable polymer, ‡ bio-based ou partially bio-based polymer ACS Paragon Plus Environment

Page 29 of 32


Table 2

Number of OTU

Shannon

Evenness

507 (± 26)

5.27 (± 0.14)

0.85 (± 0.02)

442 (± 2)

4.90 (± 0.01)

0.80 (± 0.00)

511 (± 22)

5.37 (± 0.10)

0.86 (± 0.01)

289 (± 12)

3.96 (± 0.09)

0.70 (± 0.01)

PET

557 (± 7)

5.56 (± 0.02)

0.88 (± 0.00)

PBS

250 (± 6)

3.82 (± 0.10)

0.69 (± 0.02)

PHA

261 (± 13)

4.30 (± 0.05)

0.77 (± 0.00)

PLLA

459 (± 6)

4.99 (± 0.02)

0.81 (± 0.00)

483 (± 18)

5.04 (± 0.07)

0.82 (± 0.00)

Compost Polyolefin EVOH PP Polyester PBAT

Polyamide

PA 66

ACS Paragon Plus Environment


Page 30 of 32

A initial weight

weight after incubation in the compost

card weight (g)

10 9

5.5%

7.9%

(± 0.3%)

(± 0.7%)

*

8

1.1% (± 0.2%)

*

*

7 6 5 EVOH

PP

PBAT

PET

Polyolefin

PBS

PHA

PLLA

Polyester

PA66 Polyamide

B 300

ng DNA /cm2 of card

250 200 150 100 50 0 EVOH Polyolefin

PP

PBAT

PET

PBS Polyester

Fig. 1


PHA

PLLA

PA66 Polyamide

Page 31 of 32


PBS

B

A

214 OTUs 4923 sequences

26 OTUs 1.65%

38 OTUs PBS = 1.34% PET = 3.74%

150 OTUs 13.97%

PET


130 OTUs PHA = 87.53% PBS = 94.47% PET = 78.66%

20 OTUs PHA = 7.05% PBS = 2.54%

35 OTUs PHA = 1.97% PET = 3.63%

41 OTUs 3.45%

Sample Compost EVOH PA66 PET PP PBAT PBS PHA PLLA

PHA


Fig. 2A and 2B ACS Paragon Plus Environment


Fig. 3


Page 32 of 32

Fate of Eight Different Polymers under Uncontrolled Composting

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