# Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis

Cédric Hubas, Julie Gaubert-Boussarie, An-Sofie D'hondt, Bruno Jesus, Dominique Lamy, Vona Meleder, Antoine Prins, Philippe Rosa, Willem Stock, Koen Sabbe

► To cite this version:

Cédric Hubas, Julie Gaubert-Boussarie, An-Sofie D'hondt, Bruno Jesus, Dominique Lamy, et al. Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis. Peer Community Journal, 2023, 3, pp.e104. 10.24072/pcjournal.336. hal-04001920

HAL Id: hal-04001920

https://hal.science/hal-04001920

Submitted on 21 Dec 2023

HAL is a multi-disciplinary open access
archive for the deposit and dissemination of sci-
entific research documents, whether they are pub-
lished or not. The documents may come from
teaching and research institutions in France or
abroad, or from public or private research centers.

L'archive ouverte pluridisciplinaire HAL, est
destinée au dépôt et à la diffusion de documents
scientifiques de niveau recherche, publiés ou non,
émanant des établissements d'enseignement et de
recherche français ou étrangers, des laboratoires
publics ou privés.

<figure><img src="image_1.png" /></figure>

Distributed under a Creative Commons Attribution 4.0 International License
RESEARCH ARTICLE

Published
2023-10-31

**Cite as**
Cédric Hubas, Julie Gaubert-Boussarie, An-Sofie D'Hondt, Bruno Jesus, Dominique Lamy, Vona Meleder, Antoine Prins, Philippe Rosa, Willem Stock and Koen Sabbe (2023) *Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis*, Peer Community Journal, 3: e104.

**Correspondence**
cedric.hubas@mnhn.fr

**Peer-review**
Peer reviewed and
recommended by
PCI Ecology,
https://doi.org/10.24072/pci.ecology.100519

<figure><img src="image_2.png" /></figure>

This article is licensed
under the Creative Commons
Attribution 4.0 License.

# Identification of microbial exopolymer producers in sandy and muddy intertidal sediments by compound-specific isotope analysis

Cédric Hubas<sup>1,1</sup>, Julie Gaubert-Boussarie<sup>1</sup>, An-Sofie D'Hondt<sup>1,2</sup>, Bruno Jesus<sup>1,3</sup>, Dominique Lamy<sup>4,5</sup>, Vona Meleder<sup>1,3</sup>, Antoine Prins<sup>1,3</sup>, Philippe Rosa<sup>1,3</sup>, Willem Stock<sup>1,6</sup>, and Koen Sabbe<sup>1,6</sup>

Volume 3 (2023), article e104

https://doi.org/10.24072/pcjournal.336

## Abstract

Extracellular polymeric substances (EPS) refer to a wide variety of high molecular weight molecules secreted outside the cell membrane by biofilm microorganisms. In the present study, EPS from marine microphytobenthic biofilms were extracted and their isotope ratios were analysed. A comparison of these ratios with the carbon isotope ratios of fatty acid biomarkers allowed the identification of the main EPS producers of two contrasting types of intertidal marine sediments. Our study reveals that EPS sources are more diverse in sandy sediments than in muddy sediments. We also found distinct patterns in the production and breakdown of EPS in sandy and muddy environments. The main difference observed was in how epipelic and epipsammic diatoms affected the chemistry of EPS, which had significant implications for the growth of bacteria specialized in utilizing EPS. These differences were likely linked to variations in the functioning of epipelic and epipsammic communities, specifically in how EPS was used either for motility or for cell attachment.

<footnote n="1"><sup>1</sup>Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques (BOREA) Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, IRD, Université des Antilles, Université de Caen Normandie; Station Marine de Concarneau, Place de la croix,29900, Concarneau, France, <sup>2</sup>Department of Biology, Marine Biology Research Group, Ghent University, Krijgslaan 281/S8, 9000, Belgium, <sup>3</sup>Nantes Université, Institut des Substances et Organismes de la Mer, ISOMer, UR 2160, F-44000 Nantes, France, <sup>4</sup>Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques (BOREA) Muséum National d'Histoire Naturelle, CNRS, Sorbonne Université, IRD, Université des Antilles, Université de Caen Normandie; Jardin des plantes, Bâtiment arthropodes, Paris, France, <sup>5</sup>Institute of Ecology and Environmental Sciences of Paris (iEES-Paris), Sorbonne Université, Univ Paris Est Créteil, IRD, CNRS, INRA, 4 place Jussieu, 75005 Paris, France, <sup>6</sup>Department of Biology, Research Group Protistology and Aquatic Ecology, Ghent University, Krijgslaan 281/S8, 9000, Belgium</footnote>
## Contents

<table><tr><td>Introduction</td><td>2</td></tr><tr><td>Material and methods</td><td>3</td></tr><tr><td>Results and discussion</td><td>6</td></tr><tr><td>Conclusions</td><td>13</td></tr><tr><td>Acknowledgements</td><td>13</td></tr><tr><td>Fundings</td><td>13</td></tr><tr><td>Contributions</td><td>13</td></tr><tr><td>Conflict of interest disclosure</td><td>13</td></tr><tr><td>Data, script, code, and supplementary information availability.</td><td>13</td></tr><tr><td>References</td><td>14</td></tr></table>

## Introduction

The term extracellular polymeric substances (EPS) is generic and refers to a wide variety of macromolecules whose main characteristic is to be of high molecular weight (> 10 kDa) and secreted by microbes outside the cell membrane. In intertidal sediments, these molecules are, for instance, secreted as a protection in response to changing environmental conditions or to allow cell motility (Tolhurst et al., 2003). But these secretions can also indirectly serve a number of ecosystem functions such as increasing the cohesion and adhesion properties of sediments (Lubarsky et al., 2010), or providing a significant source of organic matter at the base of the food web (Bellinger et al., 2009; Middelburg et al., 2000). They also represent a privileged pathway for cooperation between ecosystem engineers, leading to an improvement of the engineering effects on benthic communities (Passarelli et al., 2014).

Although many authors have studied these compounds and reviewed their multiple roles in aquatic ecosystems (Cescutti, 2010; Costerton et al., 1994; Decho, 2000; Underwood and Paterson, 2003; Wotton, 2004), there is currently no clear classification probably because of their high chemical diversity and complexity. Exopolymers are generally classified into three categories which are basically distinguished by the proximity of the polymers to the membrane of the producing cells.

Capsular polymer substances (CPS) are often defined as linked to the cell surface by a covalent bond to phospholipid or lipid A molecules, whereas EPS are released on the cell surface without being chemically attached to it and are often excreted to form a matrix more or less adherent to the surfaces (Cescutti, 2010). EPS are further separated in two distinct fractions: bound-EPS which are tightly-bound long-chain material, and colloidal-EPS which are less refractory, small chain, easily extractable molecules. Colloidal EPS can be extracted by water at room temperature, while bound-EPS extraction requires hot water or bicarbonate (Underwood and Paterson, 2003) or even cationic resins that trap the bivalent cations linking the EPS together, allowing the extraction of bound compounds (Takahashi et al., 2009). Thus, EPS are also sometimes described according to the extraction procedures. For instance, hot-bicarbonate and hot-water EPS (EPS<sub>HB</sub>, EPS<sub>HW</sub>), correspond to insoluble compounds solubilised using hot bicarbonate or water extraction protocols (Bellinger et al., 2005; Hanlon et al., 2006).

These different EPS fractions differ in their biochemical composition (Passarelli et al., 2015) and it has been shown that different types of diatom-derived EPS drive changes in heterotrophic bacterial communities in intertidal sediments (Bohórquez et al., 2017; Haynes et al., 2007).

The most significant progress on the subject concerns bacterial exopolysaccharides from microbial cultures (in particular pathogenic microorganisms), whose EPS metabolism and regulation mechanisms have been very well described. The genomic characterisation of these bacterial models of interest has led to fascinating discoveries. For example, it has been shown that EPS production (which underlies the development of bacterial biofilms) is under close control of a social behaviour called Quorum Sensing that allows interactions between members of microbial
communities (Branda et al., 2005; Solano et al., 2014). Quorum sensing is based on the produc-
tion and release of signalling molecules called autoinducers, which increase in concentration as
a function of cell density (Camilli and Bassler, 2006). It was shown that these compounds were
also present and particularly diverse in microbial mats (Decho, 2010; Decho et al., 2009).

However, in the natural environment, the precise composition of EPS is still largely unknown.
¹³C-labelling experiment have highlighted the role of diatom organic matter as a growth sub-
strate for benthic bacteria (Middelburg et al., 2000; Oakes et al., 2010; Veuger et al., 2012). These
studies traced diatom carbon and found that diatom EPS likely represent a link between benthic
microalgae and higher trophic levels. Furthermore, the precise origin of these compounds in in-
tertidal food webs is still subject to debate. Are diatoms the main, if not the only, producers of
EPS in microphytobenthic assemblages, or do exopolymers present themselves rather as a pool
of extracellular compounds of diverse origin?

In this study, we extracted colloidal and bound EPS from intertidal biofilms and analysed
the natural stable isotope ratios (SIR) of carbon (δ¹³C) and nitrogen (δ¹⁵N). In order to identify
the main contributors of EPS in muddy and sandy sediments, the SIR of EPS were compared to
those of fatty acid biomarkers. These fatty acids are specific indicators of certain microorganisms,
as their relative proportions vary distinctly across different organisms. For example, the major
fatty acid in diatoms is 20:5n-3 (Dijkman et al., 2010; Dunstan et al., 1994; Leu et al., 2007). By
examining the isotope ratios of EPS alongside these fatty acid biomarkers, the study aimed to
determine the primary microorganisms responsible for EPS production.

Fatty acids are well recognised chemotaxonomic markers although they have a very limited
taxonomic resolution and are hardly exclusive of a given organism (De Carvalho and Caramujo,
2014). However, the ratios between the different fatty acids (for instance, the 16:0/16:1n-7
ratio, Kharlamenko et al., 1995) have shown convincing results in the identification and quantifi-
cation of algal and bacterial groups and have already been successfully used to determine the
composition of microbial mat (Dijkman et al., 2010) and sediment microbial communities (Findlay
et al., 1989; Gaubert-Boussarie et al., 2020; Hubas et al., 2017; Passarelli et al., 2015).

The aim of this study was therefore to compare data of the natural stable isotopes of EPS
with those of fatty acid biomarkers in two sediment types representative of intertidal environ-
ments (i.e. a muddy site and a sandy site), in order 1/ to accurately identify the main exopolymer
producers and 2/ determine whether EPS production and dynamics was comparable between
the microbial communities of contrasting sediment types.

**Material and methods**

Sampling site

The sediment sampling took place in June 2017 at 2 tidal flat sites in France near La Coupelasse (Baie of Bourgneuf, France, Fig. 1). Bourgneuf Bay is a macrotidal bay located south of the Loire estuary on the French Atlantic coast, containing large intertidal mudflats (100 km²) colonized by microphytobenthic biofilms. The site is characterised by the extensive aquaculture of the Pacific oyster *Crassostrea gigas*. Oyster farms cover about 10 % of the intertidal area, while most of the rocky areas (about 17 % of the intertidal area) are colonized by wild oysters (Le Bris et al., 2016) or macroalgae (Combe et al., 2005; Kazemipour et al., 2012). Two contrasting sites were selected: a muddy site (47°470′ 53.326″ N, 2°1′ 24.919″ W) characterised by epipelic diatom communities and a high mud content (i.e. 50-90%, Meleder et al., 2005) and a sandy site (47°0′ 57.453″ N, 2° 1′ 33.676″ W) characterised by epipsammic diatom communities and a low mud content (i.e. 40-60%, Meleder et al., 2007). The muddy site was sampled 4 times between 23ᵗʰ and 28ᵗʰ June 2017 (between 5 and 12 replicates depending on the date) while the sandy site was sampled 3 times (between 4 and 10 replicates).

Chlorophyll *a* analysis

Chlorophyll *a* concentration was measured using High Performance Liquid Chromatography (HPLC) following the method described by (Van Heukelem and Thomas, 2001). Briefly, approximately 1 cm³ of freeze-dried sediment (i.e. subsample of 10 cm diameter, 0.5 cm depth sediment
<figure><img src="image_3.png" /><figcaption>**Figure 1** – Studied area. Top panel: Map of Bourgneuf Bay (France) and location of the sampling sites (Pleiades image acquired on the 2017/06/24 at 11:15 - UTC). left = true colors, right = Normalized Difference Vegetation Index (NDVI); Bottom panel: sampling occasions according to the tidal level at the study sites (data provided by the Naval Hydrographic and Oceanographic Service (SHOM) for coordinates: 047°06'00.0"N, 002°07'00.0"W (Pornic). The first capital letter indicates the type of sediment (M=mud, S=sand), the other letters (s1 to s4) indicate the sampling point.</figcaption></figure>

cores) was utilised for the analysis. The sediment was treated with 3 ml of 90% acetone, followed by sonication (1 min) and overnight extraction in darkness at 4°C. The extracts were then filtered through a 0.2 µm PTFE filter prior to HPLC analysis. The concentration of chlorophyll *a* was determined by injecting progressively diluted samples of a standard with a known concentration of chlorophyll *a*. This allowed the establishment of a calibration curve, correlating the peak area on the chromatogram obtained using a diode array detector (DAD) with the final chlorophyll *a* concentration (in µg/g sediment dry weight (SDW)).

## Exopolymeric substances (EPS)

Colloidal EPS were extracted by rotating sediment (for each sampling occasion, a minimum number of 3 replicates of sediment core 10 cm diameter, 0.5 cm depth) in artificial sea water (salinity 30, Sea salts, NutriSelect Basic) 1.5 h at 4°C. Samples were then centrifuged (1500 g,
15 min) and the supernatant retrieved. Bound EPS were thereafter recovered by adding 2 g of a previously PBS (Phosphate Buffered Saline)-activated (4°C) Dowex Marathon C resin (sodium form, Sigma-Aldrich, Inc.) to the remaining pellet (Jahn and Nielsen, 1995; Takahashi et al., 2009). After homogenisation, a second extraction was performed by rotating in artificial sea water 1.5 h at 4°C. Samples were then centrifuged (1500 g) again and the supernatant retrieved. Both supernatants form respectively the colloidal and bound fraction of EPS and were freeze-dried.

Freeze-dried colloidal and bound EPS were weighted (in average 60 ± 11mg) and the whole content was encapsulated in tin (Sn) capsules. They were placed in a 96 wells tray and analysed by an Elementar Vario EL Cube or Micro Cube elemental analyzer (Elementar Analysensysteme GmbH, Hanau, Germany) interfaced to either an Isoprime VisION IRMS (Elementar UK Ltd, Cheddle, UK) or a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Cheshire, UK) by UC Davis Stable Isotope Facility. Samples were combusted at 1080[ per-mode = symbol]°C in a reactor packed with chromium oxide and silvered copper oxide. Following combustion, oxides were removed in a reduction reactor (reduced copper at 650°C). The helium carrier then flows through a water trap (magnesium perchlorate and phosphorous pentoxide). CO₂ is retained on an adsorption trap until the N₂ peak is analyzed; the adsorption trap is then heated releasing the CO₂ to the IRMS.

In parallel, carbohydrate and protein concentrations were measured following the phenol assay protocol (Dubois et al., 1956) and the Lowry procedure (Lowry et al., 1951), respectively. For carbohydrate analyses, 200 µL phenol (5%) and 1 mL sulphuric acid (98%) were added to 200 µL of previously extracted colloidal and bound supernatants. They were then incubated for 35 min at 30°C and the carbohydrate concentration was measured using a spectrophotometer (Milton Roy Spectronic Genesys 2). The optical density of the solution was measured at 488 nm. For protein analyses, 250 µL subsamples were incubated for 15 min at 30°C with 250 µL of 2% sodium dodecyl sulphate salt (SDS) and 700 µL of a chemical reagent prepared as described in Lowry et al., (1951). The subsamples were then incubated for another 45 min at 30°C with 100µL of Folin reagent (diluted with distilled water 5:6 v/v). The protein concentration was measured by spectrophotometry at 750 nm. Calibration curves were prepared using glucose and bovine serum albumin (BSA) as standards for carbohydrates and proteins, respectively.

## Fatty acid extraction

Fatty acid (FA) analysis was performed on triplicates of sediment core (10 cm diameter, 0.5 cm depth) following the method of Bligh and Dyer, (1959) as modified by Meziane and Tsuchiya (2000) and Passarelli et al., (2015). Lipids were extracted with a 20 min ultrasonication (sonication bath, 80kHz, Fisherbrand™) in a mixture of distilled water, chloroform and methanol in ratio 1:1:2 (v:v:v, in mL). Lipids were concentrated under N₂ flux, and saponified, in order to separate FA, with a mixture of NaOH (2 mol/L) and methanol (1:2, v:v, in mL) at 90°C during 90 min. Saponification was stopped with 500 µL hydrochloric acid. Samples were then incubated with BF3-methanol at 90°C during 10 min to transform free fatty acids into fatty acid methyl esters (FAME), which were isolated and kept frozen in chloroform. Just before analysis, samples were dried under N₂ flux and transferred to hexane.

## Fatty acid quantification and identification

Fatty acids were further quantified by flame ionisation detection (FID) and identified by mass spectrometry (GCMS, Varian 450GC with Varian 220MS). Compound annotation was performed by comparing mass spectra with NIST 2017 library. Corresponding fatty acids are designated as X:Yn-Z, where X is the number of carbons, Y the number of double bonds and Z the position of the ultimate double bond from the terminal methyl (see Fahy et al., 2005 for additional information about naming convention).

## Compound specific isotope analysis (CSIA) of FAME

Carbon stable isotope ratios (expressed in ‰) of individual fatty acids were measured by gas-chromatography-isotope ratio mass spectrometry (GC-IRMS). Measurements were performed at the Stable Isotope Platform of the European Institute for Marine Studies (IUEM, Brest, France).
FAMES were injected in splitless mode and separated using a B5HT column 30 m × 0.25 mm ID × 0.2 µL, Phenomenex) with a Thermo Fisher Scientific TRACE GC ULTRA equipped with GC isolink combustion, Conflo IY interace and Delta V plus (Thermo Fisher Scientific) isotope ratio mass spectrometer (IRMS). Fatty acids were converted into CO₂ by combustion in the ISOLINK furnace and transferred to the CONFLO IV interface and then introduced to the IRMS. Fatty acid methyl esters were identified by comparison of their retention time with those of commercial standards and in-house standard mixtures. Both FA 18:1n-9 and 18:3n-3 coeluted and were analysed simultaneously. Fatty acids kept for δ¹³C analyses were selected based on their abundance and detection in CSIA (i.e., with amplitudes > 800mV). Stable carbon isotope ratios for individual FA were calculated from FAME data by correcting for the one carbon atom in the methyl group that was added during the derivatization process. This correction was made according to Gladyshev et al., (2012) by taking into account the isotope ratio of the derivatized methanol (BF3 methanol), and the fractional carbon contribution of the free FA to the ester.

$$ (1) \qquad \delta^{13}C_{FA} = \frac{(\delta^{13}C_{FAME} - (1-f)\delta^{13}C_{CH_3OH})}{f} $$

where δ¹³CFA and δ¹³CFAME (in ‰) are the isotopic composition of the free FA, and the FA methyl ester respectively, f is the fractional carbon contribution of the free FA to the ester and δ¹³CCH₃OH is the isotopic composition of the methanol derivatization reagent (–39.1 ‰).

## Statistical analyses

Univariate statistics were carried out by checking the normality of the data per group (Shapiro test) and the homogeneity of the variances (Bartlett or Levene test). Where the data did not meet these criteria or the sample size were too small, we applied van der Waerden normal scores test followed by Fisher's least significant difference (LSD) post-hoc test. In case the sample size was larger but the conditions were still not met, we used Permutation one-way Welch's Anova followed by Tukey HSD posthoc test.

In case we had to compare two samples, we checked for normality and equality of variance (Fisher-Snedecor test) and used Welch's permutation t-test, student t-test or Wilcoxon rank sum exact test. All analyses were performed using R version 4.0.3 using the "stats" package.

We performed a smoothed density estimation on the fatty acid isotope ratio data using the geom.smooth function of the "ggplot2" package. The function, computed and drawn kernel density estimate based on the observed distribution of the stable isotopes ratio.

## Results and discussion

### Comparison of the study sites

As indicated by the 16:0/16:1n-7 ratio (see suppl. figure SF1, both sites were predominantly composed of diatoms (average ratio > 1, Kharlamenko et al., 1995). However, a slightly higher ratio was observed in the muddy sediment (Wilcoxon rank sum exact test: W = 232, p-value = 0.02), suggesting a higher dominance of diatoms in the microphytobenthic (MPB) assemblages of muddy sediments. The mud site also exhibited a higher total phototrophic biomass, as indicated by the higher chlorophyll a concentration compared to the sandy site (Welch Two Sample t-test: t = 17.291, df = 42.215, p-value < 0.001). Furthermore, the analysis of the proportion of branched fatty acids, which serve as bacterial biomarkers, indicates a higher abundance of bacteria in muddy sediments as well (Wilcoxon rank sum exact test: W = 264, p-value <0.001). No significant differences between the two sites were found in terms of saturated fatty acid (SFA) content (Wilcoxon rank sum exact test: W = 219, p-value = 0.05) but significant differences were found in terms of polyunsaturated (PUFA) and monounsaturated (MUFA) content (PUFA: Two Sample t-test, t = 2.68, df = 34, p-value = 0.01; MUFA: Wilcoxon rank sum exact test, W = 84, p-value = 0.02). Fatty acids, particularly mono- and poly-unsaturated fatty acids, are commonly used as chemotaxonomic markers (De Carvalho and Caramujo, 2014). In diatoms, the proportions of unsaturated fatty acids can be utilised to differentiate morphotypes (such as Pennales
<table><caption>**Table 1** – Comparison of Carbon and Nitrogen contents and isotopic ratios of colloidal and bound EPS at all sampling occasions using the van der Waerden (Normal Scores) non parametric test. df = degree of freedom. Results of the post-hoc test using the criterium Fisher's least significant difference (LSD) are shown in Fig. 2</caption><thead><tr><th>Variable</th><th>χ<sup>2</sup></th><th>df</th><th>p-value</th></tr></thead><tbody><tr><td>Carbon content</td><td>46.83024</td><td>13</td><td>1.03209e-05</td></tr><tr><td>Nitrogen content</td><td>27.364</td><td>14</td><td>6.74533e-06</td></tr><tr><td>δ<sup>13</sup>C</td><td>36.31005</td><td>13</td><td>0.00053</td></tr><tr><td>δ<sup>15</sup>N</td><td>35.02141</td><td>13</td><td>0.00084</td></tr></tbody></table>

<table><caption>**Table 2** – Comparison of Carbon and Nitrogen contents and isotopic ratios of colloidal and bound EPS in mud and sand. The sampling occasions for mud (Ms) and sand (Ms) were grouped together. The van der Waerden (Normal Scores) non-parametric test was used, with consideration of degrees of freedom (df). The post-hoc test results using Fisher's least significant difference (LSD) as the criterion are shown in the table</caption><thead><tr><th></th><th></th><th>Carbon content</th><th>Nitrogen content</th><th>δ<sup>13</sup>C</th><th>δ<sup>15</sup>N</th></tr></thead><tbody><tr><td>Van der Waerden test statistics</td><td>χ<sup>2</sup>, df, p-value</td><td>26.7, 3, &lt;0.001</td><td>31.1, 3, &lt;0.001</td><td>32.1, 3, &lt;0.001</td><td>23.7, 3, &lt;0.001</td></tr><tr><td rowspan="4">Posthoc tests</td><td>Bound EPS - Mud</td><td>a</td><td>a</td><td>a</td><td>a</td></tr><tr><td>Bound EPS - Sand</td><td>ab</td><td>b</td><td>a</td><td>b</td></tr><tr><td>Colloidal EPS - Mud</td><td>b</td><td>b</td><td>b</td><td>bc</td></tr><tr><td>Colloidal EPS - Sand</td><td>c</td><td>c</td><td>c</td><td>c</td></tr></tbody></table>

vs. Centrales) or even specific species (Dunstan et al., 1994). The observed differences could thus be attributed to variation in the composition of the microphytobenthic (MPB) communities between the two sites.

## Elemental EPS compositions

Carbon and nitrogen contents were significantly different between sampling occasions as well as between bound and colloidal EPS (table 1, Fig. 2). Bound EPS were almost always richer in carbon and nitrogen than colloidal EPS (fig. 2a,c). The only noticeable exception was at Ms1. We also noted a very significant decrease in the N and C contents in the colloidal fraction at this site (i.e. muddy site) between Ms1 and Ms2. Both were sampled the same day but respectively at ebbing and rising tide. These findings are partly consistent with those of Hanlon et al., (2006). During periods of diurnal emersion at a muddy site, these authors reported that bacteria converted bound EPS into more labile colloidal EPS. By analogy, we can hypothesise that bacteria at our site were very efficient at converting bound EPS to colloidal EPS (hence the slight decrease in N and C content in bound EPS) but that they probably also consume colloidal EPS at very high rates.

The same patterns were observed for sugar and protein concentrations measured by colorimetry, but with greater variability between measurements (supplementary figure SF2). If we focus on colloidal EPS, we notice that the consumption of these between Ms1 and Ms2 mainly concerned carbohydrates. Exopolymers are mainly composed of carbohydrates and proteins (Wotton, 2004) which therefore represent the main sources of C and N in EPS. Overall, bacterial EPS contain more proteins and higher molecular diversity than diatomaceous EPS (Decho and Moriarty, 1990). The carbohydrates produced by microphytobenthos are mainly heteropolymers, with a large diversity of molecules. They range in molecular weight from few monosaccharides to highly complex molecules whose relative proportion in terms of monomers determines the physicochemical structure and hydrophobic characteristics of the EPS matrix (Passarelli et al., 2015; Underwood and Paterson, 2003). The higher C content of the EPS is therefore probably partly related to a higher proportion of sugars of diatom origin.

We also examined the crossed impact of EPS and sediment type (i.e. BoundMud, BoundSand, ColloidalMud, and ColloidalSand). Our findings revealed significant differences between these levels in terms of C and N content and stable isotope ratios. For detailed information on these differences, please refer to table 2.
<figure><img src="image_4.png" /></figure>

**Figure 2** – Chemical composition of the EPS. **a,c**: Carbon (C) and Nitrogen (N) contents in µg permg of freeze dried EPS. **b,d**: Carbon and Nitrogen stable isotope ratio (δ notation against atmospheric N₂ and Vienna PDB respectively) of the EPS. Colloidal EPS corresponded to loose, water-extractable exopolymers whereas bound EPS correspond to ion exchange resin-extractable exopolymers. Letters within the graph represent results of Fisher's least significant difference (LSD) post-hoc test. For the corresponding van der Waerden test, please see Table 1

## EPS isotopic compositions

At the muddy site, bound EPS were always ¹³C or ¹⁵N depleted in comparison to colloidal EPS at this site (Fig. 2b,d). At the sandy site, the same pattern is observed but both nitrogen and carbon stable isotope ratio showed a higher variability.

All sampling dates together, δ¹³C (Fig. 3a, top panel) and δ¹⁵N values were significantly different between bound and colloidal EPS at the muddy site (Permutation two Sample t-tests, δ¹³C: t = -10.678, p-value = 0.002; δ¹⁵N: t = -4.4325, p-value = 0.002).

At the sandy site, δ¹³C values were also significantly different (Fig. 3a, bottom panel) between bound and colloidal EPS (two Sample Student's t-test, t = -4.9474, df = 22, p-value = 5.984e-05) but δ¹⁵N was not significantly different (two Sample Student's t-test, t = -0.97547, df = 22, p-value = 0.3399).

All sampling dates grouped together δ¹³C between bound and colloidal EPS were thus always significantly different at both sites (Fig. 3a), indicating that these two fractions were from different EPS producers. Comparison with the literature is difficult as it is the first time that C and N natural stable isotopes ratio are reported on intertidal bound and colloidal EPS. The values reported in the literature for the main monosaccharides constituting the extracellular sugars are however in agreement with our results (i.e. a natural δ¹³C of -15 to -18 ‰, Oakes et al., 2010).

## Carbon isotope ratio of fatty acid classes

In sandy sediment δ¹³C were significantly different between fatty acids classes (F=23.128, df1=3, df2=109, p= 1.16 10⁻¹¹) and showed a gradual ¹³C enrichment (Fig. 3b) from branched fatty acids (BFA) to mono- (MUFA) and poly-unsaturated (PUFA) fatty acids. Such differences
<figure><img src="image_5.png" /><figcaption>**Figure 3** – Comparison of δ¹³C (corrected according to equation 1) between fatty acid classes and EPS fractions. a: bound and colloidal EPS were significantly different (t-tests, p < 0.001) at both sites. b: numbers indicate significantly different groups as evidenced by post-hoc tests. BFA=branched, SFA=saturated, MUFA=monounsaturated and PUFA=polyunsaturated fatty acids</figcaption></figure>

were not observed in the muddy site. In the mud, δ¹³C of BFA, saturated (SFA) and MUFA were not significantly different. Only PUFA showed a slightly higher mean δ¹³C (Permutation one-way Welch Anova followed by Tukey HSD posthoc test, F=33.588, p < 2.2 10⁻¹⁶).

In comparison with similar ecosystems (i.e. intertidal muddy sediments), the isotope ratios of the main fatty acids are quite consistent. Previous studies recorded δ¹³C ranging from -16 to -21‰ for branched, -14 to -26‰ for saturated, -13 to -22‰ for monounsaturated and -15 to -22‰ for polyunsaturated fatty acids (Middelburg et al., 2000; Taylor et al., 2013; Veuger et al., 2012). Taylor et al., (2013) also showed that natural carbon isotope ratios were highly variable even over relatively short periods (i.e. 30h). These changes indicate that subtle modifications in the metabolic processes of carbon assimilation as well as interactions between microorganisms can take place over very short periods and could explain the variability of our δ¹³C values.

The tetracosanoic acid (SFA, 24:0) was excluded from the above mentioned analyses as it increased dramatically the variability because of extreme and unusually negative δ¹³C values indicative of a specific metabolism. The mean δ¹³C of 24:0 was -66.89 ± 35.84‰ and -59.24 ± 71.82‰ in the mud and sand respectively. It also sometimes showed a plurimodal distribution (as shown by density plots figure 4b) which indicate that 24:0 had likely varied microbial origins. This particular fatty acid was the only one to show extremely low δ¹³C values in line with the isotopic ratios generally found in methane-rich ecosystems for which direct links could be established between δ¹³C values and the presence of methane-oxidizers in bacterial communities (Paul et al., 2017; Uhlig et al., 2018). It is indeed possible that the 24:0 originated from anaerobic bacteria
related to the oxidation of methane or the sulphur cycle. The most negative δ¹³C values were recorded in highly reduced muddy sediments. Unfortunately, it is not possible to establish a direct link in our study.

## Biomarkers revealed contrasting EPS producers between sites

In the present study, compound-specific isotope analysis (CSIA) of fatty acid biomarkers was used to infer the possible origin of microbial EPS. Our main assumption was that isotopic fractionation between the microorganisms and the product of their metabolism (i.e. EPS, fatty acids) is null or negligible. At present, no study has been able to demonstrate with certainty whether this hypothesis is true or false. There is, however, evidence that fractionation exists between microorganisms and their food sources. In bacteria, substantial isotopic fractionation has been shown between biomarker lipids and their growth substrate (Summons et al., 1994) with bacterial biomarkers being significantly depleted in ¹³C compared to the food source. In *Escherichia coli*, respired CO₂ was 3.4‰ depleted in ¹³C relative to glucose (used as the carbon source) although total cellular carbon was only 0.6‰ depleted in ¹³C, and lipid fractions by 2.7‰ (Blair et al., 1985). But to date however, there is no evidence in the literature that the same phenomenon exists between microorganisms and their metabolites.

Based on this reasoning, we compared the distribution of individual fatty acids (Fig. 4a-d) with the carbon isotope ratio of the EPS (Fig. 4e). This approach allowed us to easily identify the fatty acids that exhibited the closest isotope ratios to those of bound and colloidal EPS. Based on figure 4 and taking into account the quality of the alignment between fatty acids and EPS, a detailed literature review of the potential origins of EPS in the studied sediments was performed. The result is available in the supplementary table ST1. The analysis revealed that EPS producers were very different between the two sites. In the mud, colloidal EPS were potentially mainly produced by bacteria, whereas bound EPS were mainly produced by diatoms with a significant contribution from cyanobacteria and bacteria. In the sand, the origins of EPS were more diversified. Colloidal EPS were mainly produced by diatoms and bacteria with a potential contribution from cyanobacteria. Bound EPS were mainly produced by bacteria. The sediments of the study site are, indeed, known to harbour microphytobenthic assemblages dominated by diatoms (i.e. 97%). Depending on the site, these are accompanied by cyanophyceae, euglenophyceae and chlorophyceae (Méléder et al., 2007).

## Epipelic and epipsammic diatoms contributed differently to the EPS chemistry

Most common fatty acids in diatoms are myristic acid (14:0), palmitic acid (16:0), palmitoleic acid (16:1n-7), docosahexaenoic acid (DHA, 22:6n-3), and eicosapentaenoic acid (EPA, 20:5n-3) (Yi et al., 2017). In terms of relative proportions, however, 16:1n-7 and 20:5n-3 generally dominate the total fatty acids (Dunstan et al., 1994). These two fatty acids had relatively close δ¹³C values that best aligned respectively with bound EPS in muddy sediments (−20.3 ± 1.1‰) and with colloidal EPS (−13.4 ± 4.5‰) in sandy sediments. This indicated a very different functioning between the assemblages at these two sites.

The microphytobenthic (MPB) assemblages at the two sites exhibited notable differences, as evidenced by biomass indicators (chlorophyll *a* and bacterial biomarkers) and chemotaxonomic markers (see Supplementary Figure SF1). This was further confirmed by microscopic observations (unpubl. obs.) which indicated that the muddy site hosted an epipelic MPB community typical of these environments (i.e. presence of characteristic migratory behaviour). In contrast, the sandy site MPB community had all the characteristics of epipsammic communities. These observations were in line with previous observations on nearby sites of the Baie of Bourgneuf (Méléder et al., 2007).

Thus, by analogy, it appears that epipelic diatoms mainly contributed to the bound EPS fraction while epipsammic diatoms mainly contributed to the colloidal EPS pool. This differential contribution according to habitat can be explained by the implementation of different adaptation strategies of diatoms to environmental parameters.

Epipelic diatoms secrete large quantities of extracellular exopolymers that are involved in motility. Mucilage is secreted from the raphe and adheres to the sediment following hydration.
<figure><img src="image_6.png" /><figcaption>**Figure 4** – C and N isotopic ratio of fatty acids and EPS fractions. **a-d**: Kernel density estimates of δ¹³C of fatty acid biomarkers (corrected according to equation 1). **e**: δ¹³C and δ¹⁵N biplots of bound and colloidal EPS. All sampling points were grouped together. In panels **a-d**, fatty acids are grouped by classes they belong to according to fig. 3</figcaption></figure>
Cellular movement is then generated when the EPS associated with the trans-membrane complexes is displaced along the raphe line by actine microfilament bundles (Cartaxana et al., 2008; Underwood and Paterson, 2003). The products necessary for the migration of the diatoms are therefore secreted and used in the immediate vicinity of the cell. This is most probably the reason why we observed a massive contribution of diatoms to bound EPS at the muddy site.

In a previous study, our team measured the monosaccharide compositions of sandy intertidal sediment EPS (Passarelli et al., 2015). As a result of the accumulation of silt in these sediments (caused by the implantation of biogenic structures), and the evolution of the diatom assemblage towards an epipelic community, we observed a modification of the sugars produced, which only occurred in the bound fraction. This further confirms the large contribution of epipelic diatoms to the bound EPS pool of muddy sediments.

In contrast, epipsammic diatoms mainly contributed to colloidal extracellular polymers together with cyanobacteria, green algae and bacteria. Epipsammic diatoms do not migrate because they live in sediments which are very dynamic and which have a low light extinction coefficient over achievable distances of the order of hundreds of micrometers (Cartaxana et al., 2011). As a result, these diatoms do not migrate but instead used adhesion to sand particle to avoid being resuspended. In the absence of photomigratory response, they much more rely on strong photophysiological protection mechanisms than epipelic motile diatoms (Cartaxana et al. 2011). Capsular and bound EPS were thus instead rather produced sparingly and used for attachment and fixation purposes.

In a benthic freshwater diatom, it has been shown that capsular EPS mainly consist of glycoprotein that develop from fibrillar precursors and that bacteria preferentially attach to encapsulated diatom cells (Leinweber and Kroth, 2015). This is probably a strategy of the bacteria to maximise the chances of success in terms of adhesion and also to ensure access to an important food source. This may explain why bound EPS were mainly aligned with bacterial biomarkers at the this site.

## Multiple EPS origins favour the development of EPS-specialised bacteria

Since bound EPS best aligned with branched fatty acids, 18:1n-7 and some SFA at the sandy site (Table ST1), we could conclude that bound EPS were mainly of bacterial origin (Boon et al., 1977; Hubas et al., 2013; Kharlamenko et al., 1995; Middelburg et al., 2000; Perry et al., 1979; Taylor et al., 2013) at this site either as a direct production or as a result of degradation of bound and capsular diatomic EPS. Therefore, diatoms mainly contributed directly to the colloidal fraction which was also degraded by specialised bacteria (as shown by 18:1n-7).

It is very difficult and even impossible to assign a given branched fatty acid to a specific bacterial taxon. Certain fatty acids may represent a significant proportion of total fatty acids in certain bacterial groups or taxa. Vaccenic acid (18:1n-7), for example, can account for more than 30% of the total in purple bacteria (Kharlamenko et al., 1995). Similarly, 15:0iso and 15:0anteiso fatty acids may be dominant in *Desulfovibrio* sp. species (Boon et al., 1977). But only a limited number of bacteria have unusual fatty acids. By contrast, branched-chain fatty acids of the iso and anteiso series occur widely in bacteria, give a complex pattern, and are therefore valuable in bacterial systematics (Kaneda, 1991). In the present study, it is therefore the changes in the relative composition and/or dominance of bacterial fatty acids within the different EPS fractions that indicated changes in microbial assemblages, rather than the presence of any particular fatty acid.

In addition, we also observed that branched fatty acids 15:0anteiso and 15:0iso (Fig. 4a) showed a bimodal distribution of their $\delta^{13}$C value at the sandy site. This can be explained by the fact that these fatty acids originated from different bacterial species with different C sources (i.e. bound vs. colloidal EPS) and further confirm the existence of prokaryotic assemblages dedicated to each EPS fractions.

Earlier $^{13}$C enrichment experiments have already shown EPS consumption by bacteria through 15:0anteiso and 15:0iso enrichment but also provided additional evidence that some taxa (e.g. Acinetobacter) might be considered specialist EPS-degrading bacteria (Taylor et al., 2013).
Similarly, the presence of "EPS degraders" can also be demonstrated at the muddy site. At this site, colloidal EPS aligned well with 17:0iso indicating that specific taxa rich in this branched fatty acid are predominantly involved in the production of colloidal EPS, probably from the degradation of diatom bound EPS.

## Conclusions

By comparing the natural C and N stable isotope ratios of fatty acids and bound and colloidal EPS fractions in intertidal sediments, we identified a very different dynamics of EPS production and degradation between sandy and muddy sites. The most noticeable difference was that epipelic and episammic diatoms contributed differently to the chemistry of the EPS, which had an important implication for the development of EPS specialised bacteria. These differences are thought to be related to differences in the functioning of the epipelic and epipsammic communities and in particular to the use of EPS either for motility or for cell attachment purposes.

## Acknowledgements

Some data were acquired on research platforms, which we would like to thank. CSIA data were acquired at Stable Isotope Platform of the European Institute for Marine Studies (IUEM, Brest, France). EA-IRMS data were acquired at the UC Davis stable isotope facility. The Pleiades image used in this study was ordered as part of the ISIS program of the French National Centre for Space Studies (CNES) and provided by DataTerra via the DINAMIS platform. The image is available on the Airbus Geostore catalogue (https://www.intelligence-airbusds.com/en/4871-geostore-ordering) with the following identifier: DS_PHR1B_201706241115350_FR1_PX_W003N47_1201_01276. Preprint version 2 of this article has been peer-reviewed and recommended by Peer Community In Ecology (https://doi.org/10.24072/pci.ecology.100519, Risse-Buhl and Rädecker, 2023).

## Fundings

This study was supported by the BIO-Tide project (The role of microbial biodiversity in the functioning of marine tidal flat sediments), funded through the 2015-2016 BiodivERsA COFUND call for research proposals, with the national funders BelSPO (BRAIN-be contract BR/175/A1/BIO-Tide-BE), FWO (3G0H6816), ANR (ANR-16-EBI3-0008), and SNSF. We additionally acknowledge funding from FWO project G003820N. The post-doctoral grant of J. G-B was supported by the Regional Council of Brittany, SAD program and META-Tide projects.

## Contributions

Conceptualization: KS, BJ, CH ; Data Curation: CH ; Formal analysis: CH ; Funding acquisition: KS, BJ, CH ; Investigation: all authors ; Methodology: all authors ; Project administration: KS, BJ, CH ; Resources: all authors ; Software: CH ; Supervision: KS ; Validation: all authors ; Visualization: CH ; Writing - original draft: CH ; Writing - review & editing: CH, BJ, VM, KS.

## Conflict of interest disclosure

The authors declare that they have no financial conflicts of interest in relation to the content of the article.

## Data, script, code, and supplementary information availability

Data and supplementary material are available at https://doi.org/10.5281/zenodo.7351530 (Hubas et al., 2023). Statistical scripts and command lines are available on GitHub at the following address : https://github.com/Hubas-prog/EPS_FA_CSIA. At the date of publication, the study relies on GitHub release V2.0. The release is published at the following address https://doi.org/10.5281/zenodo.7387066 (Hubas, 2023).
References

Bellinger B. J. et al. (2005). *Biofilm Polymers: Relationship between Carbohydrate Biopolymers from Estuarine Mudflats and Unialgal Cultures of Benthic Diatoms*. Aquatic Microbial Ecology **38**, 169-180. https://doi.org/10.3354/ame038169.

Bellinger B. J. et al. (2009). *Significance of Diatom-Derived Polymers in Carbon Flow Dynamics within Estuarine Biofilms Determined through Isotopic Enrichment*. Aquatic Microbial Ecology **55**, 169-187. https://doi.org/10.3354/ame01287.

Blair N. et al. (1985). *Carbon Isotopic Fractionation in Heterotrophic Microbial Metabolism*. Applied and Environmental Microbiology **50**, 996-1001. https://doi.org/10.1128/aem.50.4.996-1001.1985.

Bligh E. G. et al. (1959). *A Rapid Method of Total Lipid Extraction and Purification*. Canadian Journal of Biochemistry and Physiology **37**, 911-917. https://doi.org/10.1139/o59-099.

Bohórquez J. et al. (2017). *Different Types of Diatom-Derived Extracellular Polymeric Substances Drive Changes in Heterotrophic Bacterial Communities from Intertidal Sediments*. Frontiers in Microbiology **8**, 245. https://doi.org/10.3389/fmicb.2017.00245.

Boon J. J. et al. (1977). *Significance and Taxonomic Value of Iso and Anteiso Monoenoic Fatty Acids and Branded Beta-Hydroxy Acids in Desulfovibrio Desulfuricans*. Journal of Bacteriology **129**, 1183-1191. https://doi.org/10.1128/jb.129.3.1183-1191.1977.

Branda S. S. et al. (2005). *Biofilms: The Matrix Revisited*. Trends in microbiology **13**, 20-26. https://doi.org/10.1016/j.tim.2004.11.006.

Camilli A. et al. (2006). *Bacterial Small-Molecule Signaling Pathways*. Science (New York, N.Y.) **311**, 1113-1116. https://doi.org/10.1126/science.1121357.

Cartaxana P. et al. (2011). *Physiological versus Behavioral Photoprotection in Intertidal Epipelic and Epipsammic Benthic Diatom Communities*. Journal of Experimental Marine Biology and Ecology **405**, 120-127. https://doi.org/10.1016/j.jembe.2011.05.027.

Cartaxana P. et al. (2008). *Effects of Two Motility Inhibitors on the Photosynthetic Activity of the Diatoms Cylindrotheca Closterium and Pleurosigma Angulatum*. Diatom research **23**, 65-74. https://doi.org/10.1080/0269249X.2008.9705737.

Cescutti P. (2010). *Chapter 6 - Bacterial Capsular Polysaccharides and Exopolysaccharides*. In: Microbial Glycobiology. Ed. by Otto Holst et al. San Diego: Academic Press, pp. 93-108. https://doi.org/10.1016/B978-0-12-374546-0.00006-7. (Visited on 10/18/2023).

Combe J. P. et al. (2005). *Mapping Microphytobenthos Biomass by Non-Linear Inversion of Visible-Infrared Hyperspectral Images*. Remote Sensing of Environment **98**, 371-387. https://doi.org/10.1016/j.RSE.2005.07.010.

Costerton J. W. et al. (1994). *Biofilms, the Customized Microniche*. Journal of Bacteriology **176**, 2137-2142. https://doi.org/10.1128/jb.176.8.2137-2142.1994.

De Carvalho C. C. R. C. R. et al. (2014). *Fatty Acids as a Tool to Understand Microbial Diversity and Their Role in Food Webs of Mediterranean Temporary Ponds*. Molecules (Basel, Switzerland) **19**, 5570-5598. https://doi.org/10.3390/molecules19055570.

Decho A. W. (2000). *Microbial Biofilms in Intertidal Systems: An Overview*. Continental Shelf Research **20**, 1257-1273. https://doi.org/10.1016/S0278-4343(00)00022-4.

Decho A. W. et al. (1990). *Bacterial Exopolymer Utilization by a Harpacticoid Copepod: A Methodology and Results*. Limnology and Oceanography **35**, 1039-1049. https://doi.org/10.4319/lo.1990.35.5.1039.

Decho A. W. (2010). *Overview of Biopolymer-Induced Mineralization: What Goes on in Biofilms? Ecological Engineering **36**, 137-144. https://doi.org/10.1016/j.ecoleng.2009.01.003.

Decho A. W. et al. (2009). *Autoinducers Extracted from Microbial Mats Reveal a Surprising Diversity of N-acylhomoserine Lactones (AHLs) and Abundance Changes That May Relate to Diel pH*. Environmental microbiology **11**, 409-420. https://doi.org/10.1111/j.1462-2920.2008.01780.x.

Dijkman N. et al. (2010). *Composition and Heterogeneity of the Microbial Community in a Coastal Microbial Mat as Revealed by the Analysis of Pigments and Phospholipid-Derived Fatty Acids*. Journal of Sea Research **63**, 62-70. https://doi.org/10.1016/j.seares.2009.10.002.
Dubois M. et al. (1956). *Colorimetric Method for Determination of Sugars and Related Substances*. Analytical Chemistry **28**, 350-356. https://doi.org/10.1021/ac60111a017.

Dunstan G. A. et al. (1994). *Essential Polyunsaturated Fatty Acids from 14 Species of Diatoms (Bacillariophyceae)*. Phytochemistry **35**, 155-161. https://doi.org/10.1016/S0031-9422(00)90525-9.

Fahy E. et al. (2005). *A Comprehensive Classification System for Lipids*. Journal of Lipid Research **46**, 839-861. https://doi.org/10.1194/jlr.E400004-JLR200.

Findlay R. H. et al. (1989). *Efficacy of Phospholipid Analysis in Determining Microbial Biomass in Sediments*. Applied and Environmental Microbiology **55**, 2888-2893. https://doi.org/10.1128/aem.55.11.2888-2893.1989.

Gaubert-Boussarie J. et al. (2020). *An Untargeted Metabolomic Approach for Microphytobenthic Biofilms in Intertidal Mudflats*. Frontiers in Marine Science **7**, 250. https://doi.org/10.3389/FMARS.2020.00250.

Gladyshev M. I. et al. (2012). *Stable Isotope Composition of Fatty Acids in Organisms of Different Trophic Levels in the Yenisei River*. PloS one **7**, e34059. https://doi.org/10.1371/journal.pone.0034059.

Guerrero R. et al. (2002). *Microbial Mats and the Search for Minimal Ecosystems*. International microbiology : the official journal of the Spanish Society for Microbiology **5**, 177-188. https://doi.org/10.1007/s10123-002-0094-8.

Hanlon A. R. M. et al. (2006). *Dynamics of Extracellular Polymeric Substance (EPS) Production and Loss in an Estuarine, Diatom-Dominated, Microalgal Biofilm over a Tidal Emersio-Immersion Period*. Limnology and Oceanography **51**, 79-93. https://doi.org/10.4319/lo.2006.51.1.0079.

Haynes K. et al. (2007). *Diatom-Derived Carbohydrates as Factors Affecting Bacterial Community Composition in Estuarine Sediments*. Applied and Environmental Microbiology **73**, 6112-6124. https://doi.org/10.1128/AEM.00551-07.

Hubas C. et al. (2013). *Proliferation of Purple Sulphur Bacteria at the Sediment Surface Affects Intertidal Mat Diversity and Functionality*. PLoS ONE **8**. https://doi.org/10.1371/journal.pone.0082329.

Hubas C. et al. (2017). *A Nanoscale Study of Carbon and Nitrogen Fluxes in Mats of Purple Sulfur Bacteria: Implications for Carbon Cycling at the Surface of Coastal Sediments*. Frontiers in Microbiology **8**. https://doi.org/10.3389/fmicb.2017.01995.

Hubas C. et al. (2023). *Identification of Microbial Exopolymer Producers in Sandy and Muddy Intertidal Sediments by Compound-Specific Isotope Analysis*. https://doi.org/10.5281/zenodo.8116986. (Visited on 10/18/2023).

Hubas C. (2023). *Hubas-prog/EPS_FA_CSIA: EPS_FA_CSIA GitHub release*. https://doi.org/10.5281/zenodo.7387066.

Jahn A. et al. (1995). *Extraction of Extracellular Polymeric Substances (EPS) from Biofilms Using a Cation Exchange Resin*. Water Science and Technology **32**, 157-164. https://doi.org/10.2166/wst.1995.0287.

Jónasdóttir S. H. (2019). *Fatty Acid Profiles and Production in Marine Phytoplankton*. **17**, 151. https://doi.org/10.3390/md17030151.

Kaneda T. (1991). *Iso- and Anteiso-Fatty Acids in Bacteria: Biosynthesis, Function, and Taxonomic Significance*. Microbiological Reviews **55**, 288-302. https://doi.org/10.1128/mr.55.2.288-302.1991.

Kazemipour F. et al. (2012). *Microphytobenthos Biomass Mapping Using the Optical Model of Diatom Biofilms: Application to Hyperspectral Images of Bourgneuf Bay*. Remote Sensing of Environment **127**, 1-13. https://doi.org/10.1016/J.RSE.2012.08.016.

Kharlamenko V. I. et al. (1995). *Fatty Acids as Markers of Food Sources in a Shallow-Water Hydrothermal Ecosystem (Kraternaya Bight, Yankich Island, Kurile Islands)*. Marine Ecology-Progress Series **120**, 231-241. https://doi.org/10.3354/meps120231.

Le Bris A. et al. (2016). *Hyperspectral Remote Sensing of Wild Oyster Reefs*. Estuarine, Coastal and Shelf Science **172**, 1-12. https://doi.org/10.1016/J.ECSS.2016.01.039.
Leinweber K. et al. (2015). Capsules of the Diatom Achnanthidium Minutissimum Arise from Fibrillar Precursors and Foster Attachment of Bacteria. PeerJ 3, e858. https://doi.org/10.7717/peerj.858.

Leu E. et al. (2007). Ultraviolet Radiation Negatively Affects Growth but Not Food Quality of Arctic Diatoms. Limnology and Oceanography 52, 787-797. https://doi.org/10.4319/lo.2007.52.2.0787.

Lowry O. et al. (1951). Protein Measurement with the Folin Phenol Reagent. Journal of Biological Chemistry 193, 265-275. https://doi.org/10.1016/S0021-9258(19)52451-6.

Lubarsky H. V. et al. (2010). The Stabilisation Potential of Individual and Mixed Assemblages of Natural Bacteria and Microalgae. PLoS ONE 5, e13794. https://doi.org/10.1371/journal.pone.0013794.

Méléder V. et al. (2005). Spatio-Temporal Changes in Microphytobenthos Structure Analysed by Pigment Composition in a Macrotidal Flat (Bourgneuf Bay, France). Marine Ecology Progress Series 297, 83-99. https://doi.org/10.3354/meps297083.

Méléder V. et al. (2007). Spatiotemporal Changes in Microphytobenthos Assemblages in a Macrotidal Flat (Bourgneuf Bay, France). Journal of Phycology 43, 1177-1190. https://doi.org/10.1111/J.1529-8817.2007.00423.X.

Meziane T. et al. (2000). Fatty Acids as Tracers of Organic Matter in the Sediment and Food Web of a Mangrove/Intertidal Flat Ecosystem, Okinawa, Japan. Marine Ecology Progress Series 200, 49-57. https://doi.org/10.3354/meps200049.

Middelburg J. J. et al. (2000). The Fate of Intertidal Microphytobenthos Carbon: An in Situ 13C-labeling Study. Limnology and Oceanography 45, 1224-1234. https://doi.org/10.4319/lo.2000.45.6.1224.

Oakes J. M. et al. (2010). Composition, Production, and Loss of Carbohydrates in Subtropical Shallow Subtidal Sandy Sediments: Rapid Processing and Long-Term Retention Revealed by 13C-labeling. Limnology and Oceanography 55, 2126-2138. https://doi.org/10.4319/lo.2010.55.5.2126.

Passarelli C. et al. (2014). Organisms as Cooperative Ecosystem Engineers in Intertidal Flats. Journal of Sea Research 92. https://doi.org/10.1016/j.seares.2013.07.010.

Passarelli C. et al. (2015). Seasonal Variations of the Composition of Microbial Biofilms in Sandy Tidal Flats: Focus of Fatty Acids, Pigments and Exopolymers. Estuarine, Coastal and Shelf Science 153, 29-37. https://doi.org/10.1016/j.ecss.2014.11.013.

Paul B. G. et al. (2017). Methane-Oxidizing Bacteria Shunt Carbon to Microbial Mats at a Marine Hydrocarbon Seep. Frontiers in Microbiology 8, 186. https://doi.org/10.3389/FMICB.2017.00186.

Pegu B. K. et al. (2020). Isolation and Characterization of A-I-Rhamnosidase Producing Bacterium, Agrococcus Sp. Bkd37, from a Warehouse Soil and Partial Optimization of Its Culture Conditions. Applied Biological Research 22, 203-214. https://doi.org/10.5958/0974-4517.2020.00028.2.

Perry G. J. et al. (1979). Fatty Acids of Bacterial Origin in Contemporary Marine Sediments. Geochimica et Cosmochimica Acta 43, 1715-1725. https://doi.org/10.1016/0016-7037(79)90020-6.

Remize M. et al. (2020). Study of Synthesis Pathways of the Essential Polyunsaturated Fatty Acid 20:5n-3 in the Diatom Chaetoceros Muelleri Using 13 c-Isotope Labeling. Biomolecules 10, 797. https://doi.org/10.3390/biom10050797.

Risse-Buhl U. et al. (2023). Disentangling microbial exopolymer dynamics in intertidal sediments. Peer Comm. Ecol. 100519. https://doi.org/10.24072/pci.ecology.100519.

Sahu A. et al. (2013). Fatty Acids as Biomarkers of Microalgae. Phytochemistry 89, 53-58. https://doi.org/10.1016/j.phytochem.2013.02.001.

Solano C. et al. (2014). Biofilm Dispersion and Quorum Sensing. Current Opinion in Microbiology 18, 96-104. https://doi.org/10.1016/j.mib.2014.02.008.

Summons R. E. et al. (1994). Carbon Isotopic Fractionation in Lipids from Methanotrophic Bacteria: Relevance for Interpretation of the Geochemical Record of Biomarkers. Geochimica et Cosmochimica Acta 58, 2853-2863. https://doi.org/10.1016/0016-7037(94)90119-8.
Takahashi E. et al. (2009). Optimising Extraction of Extracellular Polymeric Substances (EPS) from Benthic Diatoms: Comparison of the Efficiency of Six EPS Extraction Methods. Marine and Freshwater Research **60**, 1\{textbackslash slashtextendash\}10. https://doi.org/10.1071/MF08258.

Taylor J. D. et al. (2013). Microphytobenthic Extracellular Polymeric Substances (EPS) in Intertidal Sediments Fuel Both Generalist and Specialist EPS-degrading Bacteria. Limnology and Oceanography **58**, 1463–1480. https://doi.org/10.4319/lo.2013.58.4.1463.

Tolhurst T. J. et al. (2003). Diatom Migration and Sediment Armouring - An Example from the Tagus Estuary, Portugal. In: Hydrobiologia. Vol. 503. Springer, pp. 183–193. https://doi.org/10.1023/B:HYDR.0000008474.33782.8d.

Uhlig C. et al. (2018). Methane-Oxidizing Seawater Microbial Communities from an Arctic Shelf. Bio-geosciences (Online) **15**, 3311–3329. https://doi.org/10.5194/BG-15-3311-2018.

Underwood G. J. C. et al. (2003). The Importance of Extracellular Carbohydrate Production by Marine Epipelagic Diatoms. Advances in Botanical Research **40**, 183–240. https://doi.org/10.1016/S0065-2296(05)40005-1.

Vallet M. et al. (2018). Chemically-Mediated Interactions Between Macroalgae, Their Fungal Endophytes, and Protistan Pathogens. Frontiers in Microbiology **9**. https://doi.org/10.3389/fmicb.2018.03161.

Vallet M. et al. (2020). Laminariales Host Does Impact Lipid Temperature Trajectories of the Fungal Endophyte Paradendryphiella Salina (Sutherland.) Marine Drugs **18**, 379. https://doi.org/10.3390/MD18080379.

Van Heukelem L. et al. (2001). Computer-Assisted High-Performance Liquid Chromatography Method Development with Applications to the Isolation and Analysis of Phytoplankton Pigments. Journal of Chromatography A **910**, 31–49. https://doi.org/10.1016/S0378-4347(00)00603-4.

Veuger B. et al. (2012). Fate of Microbial Nitrogen, Carbon, Hydrolysable Amino Acids, Monosaccharides, and Fatty Acids in Sediment. Geochimica et Cosmochimica Acta **83**, 217–233. https://doi.org/10.1016/j.gca.2011.12.016.

Vyssotski M. et al. (2015). Chemical Synthesis and Gas Chromatographic Behaviour of γ-Stearidonic (18:4n-6) Acid. JAOCS, Journal of the American Oil Chemists' Society **92**, 383–391. https://doi.org/10.1007/s11746-014-2588-x.

Wotton R. S. (2004). The Essential Role of Exopolymers (EPS) in Aquatic Systems. Oceanography and Marine Biology: an Annual Review **42**, 57–94. https://doi.org/10.1201/9780203507810.

Yi Z. et al. (2017). Exploring Valuable Lipids in Diatoms. **4**. https://doi.org/10.3389/fmars.2017.00017.
<figure><img src="image_7.png" /></figure>

**Figure SF1** – Comparison of biomass indicators and general composition of the micro-phytobenthos between the two study sites. a: Ratio of 16:0/16:1n-7 (dimensionless). b: Chlorophyll *a* concentration (in µg/g sediment dry weight). c: Relative contribution of various fatty acid classes. BRA = branched fatty acids, SFA = saturated fatty acids, MUFA = monounsaturated fatty acids and PUFA = polyunsaturated fatty acids
<figure><img src="image_8.png" /><figcaption>**Figure SF2** – Colorimetric measurements of EPS concentrations in mg equivalent to Glucose or Bovine Serum Albumine (BSA) for carbohydrates and proteins respectively. permL of extracted EPS; colloidal EPS corresponded to loose, water-extractable exopolymers whereas bound EPS correspond to ion exchange resin-extractable exopolymers.</figcaption></figure>
<table><caption>**Table ST1** – Presumed sources of colloidal and bound EPS (carbohydrates, proteins) at muddy and sandy sites. Position refers to the quality of alignment between fatty acids and EPS δ¹³C values: Aligned = the mean δ¹³C value of a given fatty acid was within the standard deviation or confidence interval of the corresponding EPS isotope ratio. Sup. (Superimposed)= δ¹³C values of EPS and fatty acids overlapped by their standard deviations or confidence intervals. **Bold underlined** = major fatty acid (20-40%) in the corresponding sources. **Bold** = important fatty acid (10-20%), **Italic** = present in trace amounts (<10%)</caption><thead><tr><th>Location</th><th>EPS type</th><th>Fatty acids</th><th>Position</th><th>Possible origin of FA</th></tr></thead><tbody><tr><td rowspan="4">Colloidal</td><td rowspan="4">Mud</td><td>22:6n-3</td><td rowspan="4">Aligned</td><td>Dinoflagellates, Haptophyta (Jónasdóttir, 2019), Diatoms, Cyanobacteria (Dijkman et al., 2010; Dunstan et al., 1994; Jónasdóttir, 2019)</td></tr><tr><td>20:0</td><td>Bacteria (Pegu et al., 2020; Perry et al., 1979)</td></tr><tr><td>18:4n-3</td><td>Haptophyta, Pheophyceae (Guerrero et al., 2002), Diatoms (Dunstan et al., 1994)</td></tr><tr><td>17:0iso</td><td>Bacteria (Kaneda, 1991; Perry et al., 1979)</td></tr><tr><td rowspan="5">Bound</td><td rowspan="5">Colloidal</td><td>20:4n-6</td><td rowspan="5">Aligned</td><td>Diatoms (Dijkman et al., 2010; Dunstan et al., 1994; Jónasdóttir, 2019)</td></tr><tr><td>17:1n-5/7</td><td>Bacteria (Pegu et al., 2020)</td></tr><tr><td>16:4n-1</td><td>Diatoms (Leu et al., 2007), Diatoms (Dunstan et al., 1994; Jónasdóttir, 2019)</td></tr><tr><td>22:0</td><td>Diatoms (Leu et al., 2007), Cyanobacteria (Sahu et al., 2013)</td></tr><tr><td>20:5n-3</td><td>Diatoms (Dijkman et al., 2010; Dunstan et al., 1994; Leu et al., 2007), Diatoms (Jónasdóttir, 2019)</td></tr><tr><td rowspan="10">Sand</td><td rowspan="10">Colloidal</td><td>18:4n-6</td><td>Cyanobacteria (Vysotski et al., 2015)</td></tr><tr><td>18:2n-6</td><td>Cyanobacteria, Chlorophyta (Jónasdóttir, 2019; Sahu et al., 2013)</td></tr><tr><td>18:1n-9/18:3n-3</td><td>Cyanobacteria, Chlorophyta (Jónasdóttir, 2019; Sahu et al., 2013) / (Dijkman et al., 2010; Jónasdóttir, 2019) *</td></tr><tr><td>17:0</td><td>Bacteria, Diatoms (Leu et al., 2007; Perry et al., 1979)</td></tr><tr><td>17:iso</td><td>Bacteria (Kaneda, 1991; Perry et al., 1979)</td></tr><tr><td>16:3n-4/16:4n-3</td><td>Diatoms (Jónasdóttir, 2019; Remize et al., 2020)/ Chlorophyta (Jónasdóttir, 2019)</td></tr><tr><td>15:0</td><td>Bacteria (Pegu et al., 2020), Diatoms, Chlorophyta (Dijkman et al., 2010; Dunstan et al., 1994; Sahu et al., 2013)</td></tr><tr><td>22:6n-3</td><td>Dinoflagellates, Haptophyta (Jónasdóttir, 2019), Diatoms, Cyanobacteria (Dijkman et al., 2010; Dunstan et al., 1994; Jónasdóttir, 2019)</td></tr><tr><td>20:5n-3</td><td>Diatoms (Leu et al., 2007)</td></tr><tr><td>20:4n-6</td><td>Diatoms (Dijkman et al., 2010; Dunstan et al., 1994; Jónasdóttir, 2019), Chlorophyta (Jónasdóttir, 2019)</td></tr><tr><td>18:4n-6</td><td>Cyanobacteria (Vysotski et al., 2015)</td></tr><tr><td>18:2n-6</td><td>Cyanobacteria, Chlorophyta (Jónasdóttir, 2019; Sahu et al., 2013)</td></tr><tr><td>18:1n-9/18:3n-3</td><td>Cyanobacteria, Chlorophyta (Jónasdóttir, 2019; Sahu et al., 2013) / (Dijkman et al., 2010; Jónasdóttir, 2019) *</td></tr><tr><td>18:1n-7</td><td>Bacteria (Middelburg et al., 2000)</td></tr><tr><td>17:1n-5/7</td><td>Bacteria (Pegu et al., 2020)</td></tr><tr><td>17:0</td><td>Bacteria, Diatoms (Leu et al., 2007; Perry et al., 1979)</td></tr><tr><td>16:3n-4/16:4n-3</td><td>Diatoms (Jónasdóttir, 2019; Remize et al., 2020)/ Chlorophyta (Jónasdóttir, 2019)</td></tr><tr><td>16:1n-7</td><td>Diatoms (Dunstan et al., 1994; Leu et al., 2007), Cyanobacteria, Bacteria (Dijkman et al., 2010; Jónasdóttir, 2019; Perry et al., 1979; Sahu et al., 2013), Chlorophyta (Sahu et al., 2013)</td></tr><tr><td>16:1n-5</td><td>Diatoms, Bacteria (Dunstan et al., 1994; Leu et al., 2007; Perry et al., 1979)</td></tr><tr><td>16:0</td><td>Major or important fatty acid in various sources (Dijkman et al., 2010; Dunstan et al., 1994; Guerrero et al., 2002; Jónasdóttir, 2019; Leu et al., 2007; Perry et al., 1979; Sahu et al., 2013; Vallet et al., 2018)</td></tr><tr><td>15:0</td><td>Bacteria (Pegu et al., 2020), Diatoms, Chlorophyta</td></tr><tr><td rowspan="2">Bound</td><td>15:0iso, 15:0an-Aligned</td><td>14:0</td><td>Diatoms (Leu et al., 2007)</td></tr><tr><td>teiso</td><td>18:0</td><td>Dinoflagellates (Jónasdóttir, 2019) *</td></tr><tr><td></td><td></td><td></td><td>Bacteria (Boon et al., 1977), Bacteria (Middelburg et al., 2000; Perry et al., 1979; Taylor et al., 2013)</td></tr><tr><td rowspan="4">Colloidal</td><td>18:1n-7</td><td>Sup.</td><td>Bacteria (Hubas et al., 2013; Hcharlamenko et al., 1995; Middelburg et al., 2000; Perry et al., 1979; Taylor et al., 2013), Cyanobacteria, Chlorophyta, Diatoms (Dijkman et al., 2010; Dunstan et al., 1994; Jónasdóttir, 2019) *</td></tr><tr><td>18:0</td><td>Sup.</td><td>Dinoflagellates (Jónasdóttir, 2019) *</td></tr><tr><td>16:0</td><td>Sup.</td><td>Major or important fatty acid in various sources (Dijkman et al., 2010; Dunstan et al., 1994; Guerrero et al., 2002; Jónasdóttir, 2019; Leu et al., 2007; Perry et al., 1979; Sahu et al., 2013; Vallet et al., 2018)</td></tr><tr><td>15:0</td><td>Sup.</td><td>Bacteria (Pegu et al., 2020), Diatoms, Chlorophyta</td></tr><tr><td></td><td></td><td></td><td>Diatoms (Leu et al., 2007)</td></tr></tbody></table>

<footnote>* also detected in all sources in trace amounts (Dijkman et al., 2010; Dunstan et al., 1994; Guerrero et al., 2002; Jónasdóttir, 2019; Leu et al., 2007; Pegu et al., 2020; Perry et al., 1979; Sahu et al., 2013; Vallet et al., 2020).</footnote>