Eukaryotic community composition in the sea surface microlayer across an east-west transect in the Mediterranean Sea

. The sea surface microlayer (SML) represents the boundary layer at the air-sea interface. Microbial eukaryotes in the SML potentially influence air-sea gas exchange directly by taking up and producing gases, and indirectly by excreting and degrading organic matter, which may modify the viscoelastic properties of the SML. However, little is known about the 10 controlling factors that influence microbial eukaryote community composition in the SML. We studied the composition of the microbial community, transparent exopolymer particles and polysaccharides in the SML during the PEACETIME cruise along a west-east transect in the Mediterranean Sea, covering the western basin, Tyrrhenian Sea and Ionian Sea. At the stations located in the Ionian Sea, fungi were found in high relative abundances determined by 18S sequencing efforts, making up a significant proportion of the sequences recovered. At the same time, bacterial and phytoplankton counts were decreasing from 15 west to east, while transparent exopolymer particle (TEP) abundance and total carbohydrate (TCHO) concentrations remained the same between Mediterranean basins. Thus, the presence of substrates for fungi, such as Cladosporium known to take up phytoplankton-derived polysaccharides, in combination with decreased substrate competition by bacteria suggests that fungi could be thriving in the neuston of the Ionian Sea and other low nutrient low chlorophyll (LNLC) regions.


Introduction 20
The sea surface microlayer (SML) constitutes the boundary layer between the ocean and the atmosphere (Liss and Duce, 2005;Zhang et al., 2003), and is around 1 to 1000 µm thick (Cunliffe and Murrell, 2009;Liss and Duce, 2005) with distinct physical and chemical properties compared to the underlying water (Cunliffe et al., 2013;Zhang et al., 2003). Due to the prominent position, the SML potentially has a substantial influence on air-sea exchange processes, such as gas transfer and sea spray aerosol formation (Cunliffe et al., 2013;Engel et al., 2017). 25 The microbial food web plays a crucial role in ocean biogeochemistry and has been vastly studied. Despite the fact that microbes in the SML can directly and indirectly influence air-sea gas exchange, few studies have looked at the microbial community composition in the SML, particularly in terms of microbial eukaryotes. While phytoplankton throughout the water column play an important role in the ocean as primary producers, phytoneuston in the SML (Apts, 1989;Hardy and Apts, et al., 2003). Early microscopic observations of the SML reported mostly diatoms, dinoflagellates and cyanobacteria (Hardy et al., 1988). More recent studies using 18S rRNA gene sequencing found a decreased protist diversity in the SML compared to underlying water with chrysophytes and diatoms enriched in the SML (Cunliffe and Murrell, 2010;Taylor and Cunliffe, 2014).
Not only phytoneuston, but also zooneuston, bacterioneuston and myconeuston might influence air-sea gas exchange processes 35 by either parasitizing phytoneuston and thus impacting the primary productivity, or by degrading organic matter available in the SML and producing CO2. While some studies have explored bacterioneuston diversity in the Mediterranean Sea (Agogué et al., 2005;Joux et al., 2006), fungi have not yet been characterized in the SML in this region. Fungi are however abundant in marine environments (Gladfelter et al., 2019;Grossart et al., 2019;Hassett et al., 2019), living a saprotrophic or parasitic lifestyle and have been found in the Mediterranean Sea before (Garzoli et al., 2015;Gnavi et al., 2017), with the myconueston 40 studied in other locations (Taylor and Cunliffe, 2014).
Phytoplankton and phytoneuston can release precursors such as carbohydrates which can aggregate and form gelatinous particles such as transparent exopolymer particles (TEP) (Chin et al., 1998;Engel et al., 2004;Verdugo et al., 2004). TEP contain mainly polysaccharides (Mopper et al., 1995;Passow, 2002) and occur ubiquitously in the ocean (Alldredge et al., 1993;Passow, 2002). Due to their stickiness TEP can aggregate with other particles (Azetsu-Scott and Engel, 45 2000;Passow and Alldredge, 1995). When the aggregate becomes heavier due to the aggregation with additional particles, it eventually sinks out of the euphotic layer into the deep ocean and may thus play an important role in carbon export (Engel et al., 2004). However, the rate of TEP-related carbon export does not only depend on its production by phytoplankton, but also on microbial degradation.
Few studies have looked at spatial distribution of the microbial eukaryote communities in the SML and possible environmental 50 drivers of community composition, especially in the open Mediterranean Sea, a characteristic low nutrient low chlorophyll (LNLC) region (Durrieu de Madron et al., 2011). The present study focuses on the organic matter (OM) and microbial eukaryotes distribution in relation to possible atmospheric inputs, focusing on the myconeuston community composition in the SML of the Mediterranean Sea using samples collected during the PEACETIME cruise in May and June 2017.

Sampling
Samples were collected during the PEACETIME cruise to the Mediterranean Sea onboard the RV Pourquoi pas? from the 10 th May to the 11 th June 2017. A total of 12 stations were sampled from 2.9°E to 19.8°E and 35.5°N to 42.0°N (Fig. 1) collecting water from the SML and the underlying water (ULW) at 20 cm below the SML. SML samples were collected from a zodiac using a glass plate sampler (Cunliffe and Wurl, 2014;Harvey, 1966). The dimensions of the silicate glass plate (50 x 26 cm) 60 resulted in an effective sampling surface area of 2,600 cm 2 considering both sides. To avoid contamination during sampling, the zodiac was located in front of the research vessel into the direction of the wind. The glass plate was immersed and https://doi.org/10.5194/bg-2020-249 Preprint. Discussion started: 21 July 2020 c Author(s) 2020. CC BY 4.0 License. withdrawn perpendicular to the sea surface at a controlled rate of ~17 cm s -1 . With a Teflon wiper, SML samples were collected in acid cleaned and rinsed bottles (Cunliffe and Wurl, 2014). All sampling equipment was acid-cleaned (10 % HCl), rinsed with Milli-Q and copiously rinsed with seawater from the respective depth once the sampling site was reached. The ULW 65 samples were collected concurrently with two acid-cleaned and MilliQ rinsed glass bottles.

Gel particle determination
The abundance and area of TEP and was measured microscopically (Engel, 2009). The sample volume (10-30 ml) was determined onboard the ship according to the prevailing concentration of TEP. Samples were filtered onto 0.4 µm Nucleopore membranes (Whatman) and stained with 1 ml Alcian Blue solution (0.2 g l -1 w/v) for 3 s. Filters were mounted on Cytoclear ® 70 slides and stored at -20°C until analysis. Two filters per sample with 30 images each were analyzed using a Zeiss Axio Scope.A1 (Zeiss) and the AxioCam MRc (Zeiss). The pictures with a resolution of 1388 x 1040 pixels were saved using AxioVision LE64 Rel. 4.8 (Zeiss). All particles larger than 0.2 µm 2 were analyzed. ImageJ was subsequently used for image analysis (Schneider et al., 2012). 10 ml MilliQ water served as a blank.

Bacterioplankton and bacterioneuston abundance 75
Bacterial cell numbers were determined from a 2 ml sample fixed with 100 µl glutaraldehyde (GDA, 1 % final concentration).
Samples were stored at -20°C and stained with SYBR Green I (Molecular Probes) to determine abundance using a flow cytometer (Becton & Dickinson FACScalibur) with a 488 nm laser. A unique signature in a plot of side scatter (SSC) vs. green fluorescence (FL1) was used to detect bacterial cells. Yellow-green latex beads (Polysciences, 0.5 µm) were used as an internal standard. 80

Phytoplankton and phytoneuston abundance
Phytoplankton and phytoneuston cell numbers were determined from a 2 ml sample fixed with 100 µl GDA (1 % final concentration) and stored at -20°C. Samples were filtered through a 50 µm filter and analyzed with a flow cytometer (Becton & Dickinson FACScalibur) using a 488 nm laser and a standard filter set-up. Enumeration of cells was conducted using a high flow rate (app. 39-41 µl min -1 ). The forward or right-angle light scatter (FALS, RALS) as well as the phycoerythrin and chl a 85 related fluorescent signal was used to distinguish the cells. Cell counts were analyzed using the CellQuest Pro-Software (BD Biosciences).
Two replicates per TCHO sample were analyzed.
2.6 DNA extraction and eukaryote 18S rRNA gene sequencing 95 400 ml of sample was pre-filtered through a mesh with 100 µm pore size and subsequently filtered onto a Durapore membrane (Millipore, 47 mm, 0.2 µm) and immediately stored at -80°C. In order to improve cell accessibility for the DNA extraction, filters in cryogenic tubes were immersed in liquid nitrogen and the filter was crushed with a pestle. DNA was extracted according to a modified protocol from Zhou et al. (1996) by Wietz and colleagues (2015). The protocol included bead-beating, phenol-chloroform-isoamyl alcohol purification, isopropanol precipitation and ethanol washing. An additional protein-100 removal step by salting was used to avoid protein contamination.
Library preparation and sequencing was conducted at the Integrated Microbiome Resource at Dalhousie University, Halifax, Canada and is described in detail elsewhere (Comeau et al., 2017). Samples were PCR-amplified in two dilutions (1:1 and 1:10) using the 18S rRNA gene primers E572F and E1009R (Comeau et al., 2011). Prior to pooling, samples were cleaned up and normalized using the Invitrogen SequalPrep 96-well Plate kit (Thermo Fisher Scientific). Sequencing was conducted 105 according to Comeau et al. (2017) on an Illumina MiSeq using 300+300 bp paired-end V3 chemistry.
Sequences were processed using the DADA2 pipeline (Callahan et al., 2016) and sequences shorter than 400 bp, longer than 444 bp, with more than 8 homopolymers or any ambiguous bases were discarded. Sequences were aligned with the 18S rRNA gene sequences of the SILVA 132 alignment (Quast et al., 2013). Subsequently, sequences that aligned outside of most of the dataset and chimeras were removed. Sequences were classified using the SILVA 132 database (Quast et al., 2013) and 110 deposited at the European Nucleotide Archive (ENA accession number PRJEB23731). Sequences were not subsampled and sequence numbers per sample ranged from 1063 sequences (S8 SML) to 43,027 sequences (S5 SML), except for PCA, where all samples were subsampled to 1063 sequences.

Statistical analyses
Statistical analyses and maps were produced using R (R Core Team, 2014) and bathymetry information from NOAA (National 115 Oceanic and Atmospheric Administration). The enrichment factor (EF) was used to compare the concentration of substance A in the SML to the concentration in the ULW and was calculated using the following Eq. (1): Where [A] is the concentration of a parameter in the SML or ULW (World Health Organization, 1995). An EF > 1 indicates enrichment, an EF < 1 indicates depletion and an EF = 1 indicates no change of a phytoplankton genus in the SML compared 120 to the ULW. The significance of difference between the SML and ULW and between the basins of 18S eukaryote sequences and biogeochemical parameters were tested using the Kruskal-Wallis test and PERMANOVA. Correlations were calculated using Spearman's rank correlation.

Data obtained from the ship
Wind speed, salinity and seawater temperature at 5 m were obtained from the RV Pourquoi pas? software. Radiation 125 measurements were obtained with the pyranometer Li-Cor Radiation Sensor (Li-200SZ) measuring wavelengths of 400 to 1100 nm. All parameters were measured every 5 min during the sampling on the zodiac outlined above and the average during the sampling period was taken for statistical analyses (Table 1).

Microbial eukaryote community composition in the SML and ULW 130
The eukaryotic communities in the SML and the ULW were similar (ANOSIM, p=0.039, R=0.1002). The cruise track allowed for sampling in three basins of the Mediterranean Sea: the western basin (Provencal + Algerian basin), the Tyrrhenian Sea and the Ionian Sea. Looking at the three different basins sampled (Fig. 1), differences were detected in their eukaryotic community composition (Fig. 2). ANOSIM showed that the differences in the eukaryotic community composition were slightly larger across basins than between SML and ULW (p=0.0025, R=0.2263). However, the overall diversity and evenness (based on 135 shannon and pielou indices) were not significantly different between basins (Fig. S1). 16 orders were found in relative abundances over 5 % of the total eukaryotic community in one or more of all 12 stations ( fungal ASVs that were recovered throughout the cruise and their relative abundance. It becomes apparent that while fungal ASVs make up a significant amount of sequences in the Ionian Sea (stations to the right of fig. 4), they were barely detectable at the other stations (p=0.014 for differences on fungal ASV level between basins tested with PERMANOVA).

Concentrations and SML enrichments of microorganisms and organic matter
Bacterial numbers did not show any significant differences between depths. In the SML, bacterial abundances ranged from 2.0 150 x 10 5 to 1.0 x 10 6 cells ml -1 with an average of 5.2 x 10 5 ± 2.3 x 10 5 cells ml -1 . In the ULW, bacterial numbers were on average 4.6 x 10 5 ± 1.5 x 10 5 cells ml -1 (range of 2.2 x 10 5 -6.9 x 10 5 cells ml -1 ).

Eukaryotic diversity in the surface of the Mediterranean Sea
The eukaryotic community composition between the SML and the ULW only differed slightly, with larger spatial heterogeneity and significant differences between the communities of the Western, Tyrrhenian and Ionian basins. The shannon diversity did not differ significantly between depths or basins, however there was a slight decrease of species richness from west to east (Fig. S1), possibly due to the transition to more oligotrophic conditions from west to east, as water exchange with 170 the Atlantic is most pronounced in the western basin (Reddaway and Bigg, 1996) and organisms have to adapt to a more oligotrophic environment the further east they come.
Looking at the phytoplankton community (Fig. 3), it becomes apparent that no diatoms were present at high concentrations.
In seasonal studies, diatoms have been important during blooms in March and April in the Mediterranean Sea, but later in the year when a stratified water column was established, their importance decreased (Marty et al., 2002). Even though diatoms 175 most likely were not dominant in the samples, finding no diatom orders over 1 % in at least one of the samples might also indicate a bias of the primers used. Another point that becomes apparent from Figure 3 is the dominance of dinoflagellate genera. Several studies have shown that dinoflagellates have a large number of 18S rRNA gene copies in comparison to other phytoplankton groups, and therefore the abundance of dinoflagellates in 18S rRNA gene sequencing is often overestimated (Godhe et al., 2008;Guo et al., 2016). 180 Previous studies suggested various factors that potentially drive the phytoplankton community composition. Radiation, especially in the SML, where often high levels of UV-radiation occur, could potentially cause damage by photoinhibition.
MAAs, they can still be inhibited by high UV radiation (Ekelund, 1991). However, looking at the current study, no inhibition 185 by UV radiation can be inferred from the data because phytoplankton were enriched despite high radiation values (e.g. stations S4 and 7) ( Table 1). terrestrial influence on the Ionian Sea, either deposited by dust or by rain previous to this research campaign in the Ionian Sea or in other areas closeby. Station FAST_2 in the western basin was highly influenced by dust input in the area (Guieu et al., 2020;Tovar-Sánchez et al., 2020). This resulted not only in a high increase in TEP abundance in the SML, but also in a distinct increase in the abundance of unidentified dinoflagellates in the SML (Fig. 3). The details of the dust input on the organic matter and microbial community composition in the SML and the ULW are discussed elsewhere (Engel et al., in prep). However, 200 figure 4 shows that no fungi were found at station FAST_2 neither in the SML nor in the ULW, showing that dust input does not necessarily deposit fungi to the surface ocean, which potentially also holds true for the Ionian Sea. In addition, the highest amount of fungi was found in the ULW and not the SML, making a direct atmospheric influence unlikely. In addition to atmospheric inputs, riverine inputs can also influence the Mediterranean Sea (Martin et al., 1989). However, the Ionian Sea itself does not experience vast riverine input and riverine influence is even less pronounced in the open sea, making riverine 205 sources of mycophyta unlikely. Ascomycota and Mucoromycota have been recovered from a variety of marine environments (Bovio, 2019;Grossart et al., 2019;Hassett et al., 2019), thus implying that they also might be thriving in the SML of the Mediterranean Sea instead of being the result of terrestrial input.

Fungi in the Ionian Sea
Overall, the most abundant fungal ASV in the Ionian Sea, ASV 8, was identified as belonging to genus Cladosporium which has been found in marine environments before . Another explanation for the high abundance of fungi in 210 the Ionian Sea might be that they are more adapted to dealing with the low nutrient conditions found in the more eastern basin of the Mediterranean Sea.
Bacterial and microalgal numbers determined by flow cytometry decreased significantly from west to east, with bacteria showing the greatest decline. At the same time, TCHO and TEP were still abundant in the Ionian Sea. TEP are often enriched in the SML of various oceans (Engel and Galgani, 2016;Jennings et al., 2017;Wurl et al., 2009;Wurl and Holmes, 2008). In 215 previous studies, TEP enrichment was highest over oligotrophic regions (Jennings et al., 2017;Zäncker et al., 2017). This is in good accordance with the present study in the veryoligotrophic eastern Mediterranean Sea (Durrieu de Madron et al., 2011;https://doi.org/10.5194/bg-2020-249 Preprint. Discussion started: 21 July 2020 c Author(s) 2020. CC BY 4.0 License. Fogg, 1995;Wikner and Hagstrom, 1988) where low phytoplankton abundances, but high TEP enrichments of 1.1-17.3 were found. Wind speed correlated negatively with TEP abundance and area in the SML, showing that wind can negatively affect TEP concentrations at the air-sea interface as has been previously suggested (Sun et al., 2018). 220 Since exchange of water with the Atlantic is mostly pronounced in the western basin, nutrient limitation increases going eastwards in the Mediterranean Sea. TEP production has been shown to be independent of stoichiometric ratios in the surrounding water before (Corzo et al., 2000). Since especially in the SML, light limitation rarely occurs and TEP might serve as light protection (Elasri and Miller, 1999;Ortega-Retuerta et al., 2009), phytoplankton might still photosynthesize and excrete carbohydrates that assemble to TEP. This would not only explain the lack of difference of TEP abundance between 225 basins, but also TCHO concentrations. However, TCHO could also be produced by cell lysis (due to nutrient depletion) and subsequent release of intracellular compounds into the surrounding water.
TCHO and TEP could therefore provide available substrate and microhabitats for marine fungi with reduced competition by bacteria in the Ionian Sea. Malassezia and Cladosporium have been shown to assimilate carbon derived from TEP-associated algal polysaccharides in the English Channel , which highlights that Cladosporium and other fungi might 230 be able to make use of the substrate under decreased bacterial competition in the Ionian Sea.

Conclusions
The present study shows that even though flow cytometry counts suggest that bacteria and phytoplankton numbers are reducing from west to east of the Mediterranean Sea, organic matter such as microgels and TCHO are still prevalent in surface waters.
Our findings from the Ionian Sea suggest that accumulation of organic substrates in the surface under oligotrophic conditions 235 may favour certain taxa such as fungi which can benefit from decreased competition by bacteria. In LNLC regions, where phytoplankton and bacterial counts are typically low, but TEP enrichment is high in the SML might be a specific ecosystem where fungi are able to thrive and to control organic matter degradation.

Acknowledgements
We would like to thank the chief scientist, Cécile Guieu and Karine Desboeufs, of the PEACETIME cruise on the RV Pourquoi 240 pas?. We would also like to thank the captain and crew of the Pourquoi pas? for technical assistance in the field. This work is a contribution of the PEACETIME project (http://peacetime-project.org), a joint initiative of the MERMEX and ChArMEx We thank Jon Roa for his help in analyzing the total combined carbohydrates and Tania Klüver for analyzing the flow 245 cytometry cell counts. We would also like to thank ISOS (Kiel, Germany), for funding part of this work with a PhD-Miniproposal Grant.

Data availability
All biogeochemical data will be made available at the French INSU/CNRS LEFE CYBER database (data manager, webmaster: Catherine Schmechtig). All sequence data is available at the European Nucleotide Archive (ENA accession number 250 PRJEB23731).

Author contributions
BZ, MC and AE wrote the paper and contributed to the data analysis. BZ participated in the sample treatment.