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The effect of substratum type, orientation and depthon the development of bacterial deep-sea biofilmcommunities grown on artificial substrata deployed inthe Eastern MediterraneanNikoleta Bellou a b , Evangelos Papathanassiou a , Sergey Dobretsov c , Vassilis Lykousis a &Franciscus Colijn ba Hellenic Centre for Marine Research, Institute of Oceanography , Athens , Greeceb Christian-Albrechts-Universität zu Kiel, Forschungs-und Technologiezentrum , Westküste ,Büsum , Germanyc Department of Marine Science and Fisheries , Sultan Qaboos University , Muscat , OmanPublished online: 21 Feb 2012.

To cite this article: Nikoleta Bellou , Evangelos Papathanassiou , Sergey Dobretsov , Vassilis Lykousis & Franciscus Colijn(2012) The effect of substratum type, orientation and depth on the development of bacterial deep-sea biofilm communitiesgrown on artificial substrata deployed in the Eastern Mediterranean, Biofouling: The Journal of Bioadhesion and BiofilmResearch, 28:2, 199-213, DOI: 10.1080/08927014.2012.662675

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The effect of substratum type, orientation and depth on the development of bacterial deep-sea

biofilm communities grown on artificial substrata deployed in the Eastern Mediterranean

Nikoleta Belloua,b*, Evangelos Papathanassioua, Sergey Dobretsovc, Vassilis Lykousisa and Franciscus Colijnb

aHellenic Centre for Marine Research, Institute of Oceanography, Athens, Greece; bChristian-Albrechts-Universitat zu Kiel,Forschungs-und Technologiezentrum, Westkuste, Busum, Germany; cDepartment of Marine Science and Fisheries, Sultan QaboosUniversity, Muscat, Oman

(Received 11 August 2011; final version received 27 January 2012)

An increasing number of deep-sea studies have highlighted the importance of deep-sea biofouling, especially inrelation to the protection of deep-sea instruments. In this study, the microbial communities developed on differentsubstrata (titanium, aluminum, limestone, shale and neutrino telescope glass) exposed for 155 days at differentdepths (1500 m, 2500 m, 3500 m and 4500 m) and positions (vertical and horizontal) in the Eastern MediterraneanDeep Sea were compared. Replicated biofilm samples were analyzed using a Terminal Restriction Fragment LengthPolymorphisms (T-RFLP) method. The restriction enzymes CfoI and RsaI produced similar total numbers (94, 93)of different T-RFLP peaks (T-RFs) along the vertical transect. In contrast, the mean total T-RF number betweeneach sample according to substratum type and depth was higher in more samples when CfoI was used. The totalspecies richness (S) of the bacterial communities differed significantly between the substrata, and depended on theorientation of each substratum within one depth and throughout the water column (ANOVA). T-RFLP analysesusing the Jaccard similarity index showed that within one depth layer, the composition of microbial communities ondifferent substrata was different and highly altered among communities developed on the same substratum butexposed to fouling at different depths. Based on Multidimensional Scaling Analyses (MDS), the study suggests thatdepth plays an important role in the composition of deep-sea biofouling communities, while substratum type andorientation of substrata throughout the water column are less important. To the authors’ knowledge, this is the firststudy of biofilm development in deep waters, in relation to the effects of substratum type, orientation and depth.

Keywords: biofilm; bacteria; deep-sea; fouling; Mediterranean Sea; artificial substratum

Introduction

The number of prokaryotes in the open ocean has beenestimated to be 1.26 1029 and the largest pool ofmicrobes in aquatic systems can be found below 200 mdepth (Whitman et al. 1998). As in situ samplingimproves knowledge of the dark oceans’ microbialecosystem (Arıstegui et al. 2009), several descriptivestudies have been performed on free-living microbialdeep-sea communities. These studies demonstratedthat distinct prokaryotic communities are present atdifferent depth layers (Moeseneder et al. 2001a; DeCorte et al. 2009) and that the deep water free-livingbacterial communities appear to be as compositionallycomplex as those present in surface water (Moesenederet al. 2001a).

Besides their free-living life form, microbes canattach to any surfaces or particles and form biofilms, ieattached microbial cells that are incorporated into aslimy film of extracellular polysaccharides (EPS)(Allison and Sutherland 1987; Costerton et al. 1987).Biofilm formation is an important step in biofouling, a

process described as the undesirable accumulation oforganisms on submerged surfaces (Wahl 1997; Railkin2004). Bathypelagic microbial communities, usuallyconsist of surface-attached bacteria (DeLong et al.2006). In deep-sea environments, surface-attachedbacteria have been studied using a variety of molecularmethods to describe the communities present insediments (Polymenakou et al. 2005b; Fry et al.2008), in the water column (Moeseneder et al. 2001a;Ghiglione et al. 2008; Winter et al. 2009), attached toparticles (Moeseneder et al. 2001a; Vanucci et al. 2001)and on marine snow (Suzuki and Kato 1953; Wiebeand Pomeroy 1972; Kiorboe et al. 2003).

Due to technical difficulties, most studies that havebeen performed in deep-sea environments are descrip-tive and are based on exploration and sampling(Young 2009) and there is a need for experimentationon deep-sea communities (Etter and Mullineaux 2001).Compared to the vast variety of experimental settle-ment studies in coastal areas (Dang and Lovell 2000;Canning-Clode et al. 2008; Wesley and Satheesh 2009),

*Corresponding author. Email: bellou@hcmr.gr

Biofouling

Vol. 28, No. 2, February 2012, 199–213

ISSN 0892-7014 print/ISSN 1029-2454 online

� 2012 Taylor & Francis

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the number of deep-sea field studies that have beenperformed is limited. A few deep-sea pioneer studiesperformed in the 1960s investigated biofouling ofartificial materials deployed in the Pacific Ocean withthe aim of defining the effects of the deep oceanenvironment on the macrofouling communities ofvarious materials (Staley and Konopka 1985; Muraoka1965, 1996a, 1996b, 1996c). More recent studies arelimited to extreme environments, such as seamounts(Mullineaux and Butman 1990), hydrothermal vents(Mullineaux et al. 2003) and the Arctic Ocean (Gallucciet al. 2008; Kanzog et al. 2009). These studies focused onthe identification of fouling species rather than on testingwhich parameters influenced their settlement and com-munity composition. Previous studies conducted onshallow water biofilms indicated that biofouling com-munities are influenced by surface physico-chemicalproperties (Zobell 1943; Dexter et al. 1975; Costerton1995; Dang and Lovell 2000), substratum orientation(ANTARES Collaboration et al. 2003), exposure depth(Head et al. 2004), temperature, salinity (Chiu et al.2005) and nutrient availability (Kjelleberg et al. 1985). Itwas hypothesized that similar factors would affect theformation of deep-sea bacterial biofilms.

Recent investigations into the biofouling of ocea-nographic instruments deployed for a long time in thedeep-sea (Kerr et al. 2003; Head et al. 2004) havehighlighted the need for further investigations to betterunderstand biofilm formation in such environments.Moreover, little progress has been made in defining theparameters that influence biofilm initiation, growthand community composition in deep-sea environments(Fletcher 1996). A few in situ studies on deep-seabiofilms developed on different substrata have focusedon data loss (ANTARES Collaboration et al. 2003),detection of microbial induced corrosion (Venkatesanet al. 2002) or biofilm formation on structuralmaterials (Venkatesan et al. 2003). In all these studies,culture-dependent methods that underestimate bacter-ial diversity and allow detection of only cultivablemicrobes (Staley and Konopka 1985) have been used.Culture-independent methods, such as Terminal Re-striction Fragment Length Polymorphism (T-RFLP)provide a rapid and reproducible way of comparingmicrobial communities (Kitts 2001). In deep-seaenvironments, T-RFLP has only been used to char-acterise particle-associated, free-living bacterial com-munities and bacteria within deep-sea sediments(Moeseneder et al. 2001a, 2001b; Luna et al. 2004;Polymenakou et al. 2005b).

Based on T-RFLP profiles, distinct vertical differ-ences in the community composition of attached andfree-living bacteria were found in mesopelagic waters.Furthermore,*50% of the attached and free-livingbacteria were present throughout the water column in

the Aegean Sea (Moeseneder et al. 2001a). In theNorth Western Mediterranean Sea, the vertical dis-tribution of free-living bacterial communities has beenshown to be driven by biochemical changes from thesurface to deeper waters (Ghiglione et al. 2008). Theregional variability of bacterial communities in sedi-ments was analyzed with T-RFLP, which showed a clearseparation between the deep sediment communities andthe shallow ones (Polymenakou et al. 2005b).

In this study, a DNA-based fingerprinting method(T-RFLP) was used to compare deep-sea bacterialcommunities formed on different substrata exposedvertically or horizontally at different depths. Artificialsubstrata were deployed in the Nestor area of theIonian Sea. This area is characterised by almosthomogeneous depth profiles in terms of temperatureand salinity. The following questions were investi-gated: whether substratum type, orientation andexposure depth influence the composition of thedeep-sea bacterial community. Prior to addressingthese questions, the effectiveness of the two restrictionenzymes CfoI and RsaI on analysis of the PCR productof deep-sea biofilm samples was evaluated.

Materials and methods

Study site description

The Eastern Mediterranean Sea is one of the mostwidely known oligotrophic marine environments(Psarra et al. 2005). It is a phosphorous-limited systemwith corresponding low phytoplankton biomass andproduction (Krom et al. 1991; Robarts et al. 1996). Ithas a high nitrate to phosphate (N:P) ratio (28:1) in thedeep water (Krom et al. 2004) and is characterised byan overall nutrient deficit (Tselepides et al. 2000). Thestudy site lies in the Ionian Sea (Figure 1) close to thedeepest part of the Mediterranean Sea, at a depth of5121 m (Vanney and Gennessaux 1985) and far frommajor river discharges, which results in extremely clearwaters (the NESTOR Collaboration et al. 2006). Thisarea was proposed for the deployment of a neutrinotelescope (which has a volume of at least one km3),which is used to observe high energy neutrinos fromastrophysical sources (Hernandez-Rey 2009). The areais characterised by small fluctuations of temperature(mean* 13.468C) and salinity (mean* 38.76 ppt)between the deep water layers, while homogenousdepth profiles in temperature and salinity were presentduring the course of this study from 1500 m down-wards (Kontoyiannis and Lykoysis 2011) (Figure 2).

Experimental setup

An experimental platform (7006 627 6 226 cm) wasconstructed at the GKSS (Geesthacht, Germany/First-

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identity number 2006-9876-a) and is described in detailin Bellou et al. (2011). Briefly, each platform hosted upto five different materials/substrata (each surface:56 5 6 0.5 cm, see below), each in two orientations,viz. horizontal and vertical (Figure 3). To achieve

replication in the experiment, each material/substra-tum had seven replicates for each orientation. Threereplicates for each substratum/orientation/depth com-bination were sampled and analysed for this study.One experimental platform was deployed at each depth(1500 m, 2500 m, 3500 m and 4500 m) with the aid ofmooring line technology (Figure 3). The deploymentduration was 155 days, from May 2007 to October2007, during research cruises with the research vesselAegaeo.

Artificial substrata

The materials used in this study were chosen based ontheir use in oceanographic instruments or long-termobservatories and their presence in natural marineenvironments, viz. the metals titanium (titanium grade

Figure 2. Temperature and salinity profiles at study siteNestor 4.5.

Figure 1. Study site Nestor 4.5 in the Ionian Sea; EasternMediterranean Sea (Hellenic Centre for Marine Research).

Figure 3. Experimental setup: deployment and retrievalwere performed using mooring line technology.

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2; Bibus Metals A.G., Switzerland) and aluminum(50 mm hard eloxadize; Bibus Metals A.G., Switzer-land), the two typical natural hard substrata in theMediterranean viz. limestone and shale, as well as aspecific pressure resistant glass that is used for thespheres that contain the photo multiplier of theneutrino telescopes.

Collection of samples

Immediately after the mooring line was retrieved, thesubstrata were washed with sterile water and sampleswere obtained by swabbing the entire surface (area¼25 cm2) of each material separately with a sterilecotton swab (Schwartz et al. 1998; Park et al. 2001).Later, the swab sample was placed into a sterileEppendorf tube and immediately stored in the freezerat7208C until processed in the laboratory. Thephysical extent of fouling on the artificial substrataanalyzed in this study has been described by Bellouet al. (2011). Briefly, biofilm adhered loosely onto allsubstrata and Scanning Electron Microscopy (SEM)images showed evidence of attached bacteria on thedeployed artificial substrata.

Molecular biological analyses

Nucleic acid extraction

DNA was extracted from each sample with UltraCleanSoil DNAIsolation Kit (MoBio Laboratories, Inc.)following the manufacturer’s recommendations formaximum yields (alternative protocol with finalvolume 50 ml) (Singer et al. 2006; Deines et al. 2010).The integrity of DNA was checked with the use of 1%(wt/v) agarose gels. DNA concentrations were deter-mined fluorometrically with a ND-1000 spectrophot-ometer (NanoDrop Technologies, Inc.). DNAconcentrations ranged between 3 and 16 ng ml71.

PCR

Extracted DNA was used for PCR amplification. Thebacterial specific primers used for PCR were 6-carboxyfluorescein (6-FAM)-labelled primer 27F (59-AGA GTT TGA TCC TGG CTC AG-39) and 1492R(59-GGT TAC CTT GTT ACG ACT T-39) (Lane1991), which give a 1503-bp product of the 16S rDNAgene. 27F-FAM was 5 end-labelled with phosphor-amidite fluorochrome 5-carboxyfluorescein (5 6-FAM)that was synthesized by Biomers (Germany). Each 90-ml of PCR mixture contained both primers at 0.2 mM,25 mM MgCl2, 106 S buffer, dNTPs (100 mM), Taqpolymerase (5 U/ml) (GenAxon) and Milli-Q water(Merck). Samples were amplified using the followingprotocol: an initial denaturation step of 948C for

3 min, followed by 35 cycles of denaturation at 948Cfor 1 min, annealing at 558C for 1 min and extensionat 728C for 1 min. Cycling was completed by a finalextension at 728C for 7 min. PCR products werepurified with the Qiaquick PCR Purification Kit(Qiagen; final volume 50 ml). DNA integrity waschecked after the PCR and purification on 1% (wt/vol) agarose gels. Purified DNA concentrations weredetermined fluorometrically with a ND-1000 spectro-photometer (NanoDrop Technologies, Inc.) and ran-ged between 6 and 40 ng ml71.

Restriction digests

The choice of restriction enzymes is very crucial as itmay affect the ability of T-RFLP to distinguish species(Dickie and FitzJohn 2007). In this study, the tworestrictions enzymes CfoI and RsaI were tested, todetermine which one enables more OTUs to bedetected in deep-sea biofilm samples.

Prior to digestion, the concentration of digestedPCR productswas standardised. Each digest contained70 ng of a purified PCR product, 10 U of a tetramericrestriction enzyme (4-bp cutter, CfoI and RsaIseparately used; Roche Diagnostics, Germany), andthe respective restriction buffer (106 ShuRE/CUTbuffer L; Roche Diagnostics, Germany) and it wasfilled to a final volume of 50 ml with autoclaved Milli-Qwater (Merck, Germany). Incubation was at 378C for6 h and digestion was stopped by incubation at 648Cfor 20 min. Restriction digests were desalted with theQiaquick Nucleotide Removal Kit (Qiagen, USA).

T-RFLP analysis

Fluorescently labelled fragments were separated anddetected with an ABI PRISM 3700 capillary electro-phoresis apparatus (Applied Biosystems, USA), rununder the default GeneScan mode. The GeneScanTM –1200 LIZ size standard (Applied Biosystems, USA),which contains 73 single-stranded labelled fragments inthe range of 20 to 1200 bp, was added to each sampleand served as internal size standard. Samples weredenaturized for 3 min at 958C, cooled on ice for atleast 1 min and the microtiter plate was centrifugedbriefly at 500 rpm, in a 5810R centrifuge (Eppendorf,Germany). Furthermore, to detect as many real T-RFsas possible in each sample, three aliquots of eachsample were digested (Dunbar et al. 2001) and hence atotal of nine runs, three digests and three replicates persample were performed.

Negative controls (no genomic DNA, only Merckwater) were conducted with every PCR and ABI run.No contamination in PCRs was detected. Occasion-ally, small peaks appeared in negative control lanes,

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but the cumulative peak height was always below 1.000fluorescence units. Two separate restriction digestswere used for the complex bacterial communities, inorder to obtain the fingerprinting information fromdifferent enzymes per sample. The sizes of 5’6-FAM-labelled fragments were determined by comparisonwith the internal size standard, using a Local Southernsize calling method. To analyse the T-RFLP profiles,the GelQuest trial version (Sequentix) was used and allruns were aligned, which is essential for a comparativeanalysis of T-RFLP profiles (Marsh 2005). Fragmentsizing, set with+1 bp as POP6 (Applied Biosystems)was used in the automated high-throughput multi-capillary electrophoresis device (ABI 3700) (Trothaet al. 2002). All T-RFLP electropherograms werevisually inspected to ensure quality runs. T-RFLPpeaks (T-RFs)520 base pairs (bp) and �1200 bp wereeliminated from all datasets and the minimum peakheight threshold was defined at 50 fluorescence units.Wherever the ABI runs failed, data are marked as‘missing values’. Additionally, analysis of 1500 mvertical samples was not performed because therewere no samples taken due to technical issues. The T-RFs observed in all three digests were merged (Dunbaret al. 2001) and these data were used for the dataprocessing of T-RFLP profiles. For matters ofsimplicity, these merged T-RFLP profiles for eachsample are referred as ‘replicates’ from now on.

T-RFLP data processing

A binary matrix, according to the presence andabsence (1 for presence, 0 for absence) and area perheight of aligned fragments, was used for furtheranalyses (Liu et al. 1997; Moeseneder et al. 1999;Dunbar et al. 2000; Kerkhof et al. 2000; Trotha et al.2002). It was assumed that the number of T-RFs in asample represents the number of unique bacterialribotypes. The cumulative peak height of each T-RFLP-profile was calculated, to ensure that it waslarger than 10.000 fluorescence units (Blackwood et al.2003).

Efficiency description of CfoI or RsaI for detectingOTUs in deep-sea biofilms

To test which of the restriction enzymes CfoI or RsaIcan detect more OTUs in deep-sea biofilm samples, T-RFLP results of both datasets were compared (412T-RFLP profiles in total). Therefore, the mean total T-RF number for each sample was calculated based onthe three replicates. The detection ranges in T-RFnumbers as well as the total number of T-RFsobserved within all analysed samples was taken intoaccount when comparing the efficiency of each

restriction enzyme to detect OTUs in deep-sea biofilmsamples. Consequently, the quantitative and qualita-tive analyses as well as the description of bacterialcommunities were based on the T-RFLP profiles thatwere produced from the ‘more efficient enzyme’ (206T-RFLP profiles in total).

Quantitative analyses

The total species richness (S) (total number of T-RFs)was calculated in order to describe the quantitativediversity differences among samples (Liu et al. 1997;Moeseneder et al. 2001b; Luna et al. 2004; Dobretsovet al. 2005, 2010). To test for significant differencesbetween samples according to the parameter (substra-tum types, orientations and depths) a nonparametricmultivariate ANOVA, followed by an HSD post hoctest (Zar 1999) was performed. Prior to ANOVA, thedata were tested for normality and homogeneity. In allcases, the threshold for significance was 5%. Addi-tionally, mean values and standard deviations (SDs) ofthe total number of T-RFs observed for each testedparameter (substratum, orientation) along the verticaldepth gradient were calculated. All calculations andtests were performed with the software STATISTICAVersion 6 (StatSoft, USA).

Qualitative analyses

The similarities of the T-RFLP patterns between thetested parameters (substratum type, depth, orienta-tion) were assessed with the Jaccard coefficient, whichdescribes the similarity of each sample pair based onthe T-RFs that are present in both samples (Kaufmannand Rousseeuw 1990). This distance matrix wasassessed by nonparametric multidimensional scaling(MDS) that is a powerful tool for comparing commu-nity profiles obtained by molecular fingerprint meth-ods (Schafer et al. 2001) and plots the similarity matrixtwo-dimensionally. The goal of the MDS analysis wasto detect whether either the substratum type or thedepth had an influence on the bacterial communitycomposition in deep-sea biofilms. Several MDS plotswere constructed, first, as a function of substratum,second, as a function of depth for each orientationseparately, and, finally, for both orientations com-bined. All calculations and plots were performed withthe software PRIMER Version 6 (Plymouth, UK).

Description of bacterial communities present in deep-seabiofilms

To further describe the bacterial communities ofsampled deep-sea biofilms, the T-RFs detected wereassigned to the same terminal restrictions fragments

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given in the TAP-TRFLP Java Applet program,located on the RDP website [http://rdp8.cme.msu.edu/html/TAP-trflp.html#program] (Marsh et al.2000). The TAP-TRFLP program performed a simu-lated in silico digestion of the submitted 16S sequencesaccording to the primer-enzyme combination used inthe present study (Marsh et al. 2000) and has been usedby several authors for microbial community descrip-tion (Mills et al. 2003; Dobretsov et al. 2005). Theassignment was accomplished with the restrictionenzyme data that had the highest number of T-RFs.To describe microbial community composition withinone depth, and to compare composition of thecommunities at different depths, the individual T-RFs were then compiled according to the TAP-TFLPassigned group and presented as a percentage of theirabundance at each depth.

Results

Efficiency description of CfoI or RsaI for detectingOTUs in deep-sea biofilms

The two restriction enzymes CfoI and RsaI produced asimilar total number of T-RFs, 94 and 93, respectively,when compiling all samples (Table 1). At the sametime, the restriction enzyme CfoI had the highernumber of samples with higher T-RF detection (Table1). Hence, all statistical analyses were performed basedon the T-RFLP data retrieved using the restrictionenzyme CfoI.

Quantitative analyses

An overview of the T-RFPL profiles and distributionpattern of detected T-RFs according to depth is givenin Table 2. Short sized TRFs occurred in almost allsamples, whereas the longer fragments were present atspecific depths (Table 2). The number of T-RFs withlength longer than 200 bp was higher at 3500 m and4500 m depth, in comparison to those at 1500 m and2500 m (Table 2).

The calculated mean total T-RF numbers ofbiofilm developed on each substratum type andorientation separately along the depth gradient arepresented in Figure 4a and b. The number of T-RFs inbiofilms grown on the horizontally deployed substratatitanium, shale, limestone and glass increased withincreasing depth from 1500 to 2500 m, and decreasedwith increasing depth from 3500 m and 4500 m(Figure 4a). In comparison, the number of T-RFs inbiofilms developed on aluminum increased continu-ously with depth (Figure 4a). Biofilms grown onvertically deployed substrata showed different trendsin T-RF number compared to those that werehorizontally deployed (Figure 4b). The number of T-RFs present increased with increasing depth in biofilmsgrown on aluminum and glass; while it decreased withincreasing depth in biofilm grown on shale. Incomparison, the number of T-RFs in biofilms devel-oped on titanium was low at 2500 m and 4500 m, whilethe highest T-RF number was observed at 3500 m. Thedeployment orientation significantly influenced(p5 0.05) the biofilm communities grown on glass,limestone and titanium at 1500 m, 2500 m and 3500 mdepths. On the other hand, at 4500 m the communitiesat the two orientations were not significantly different(p4 0.05).

Overall, within the same depth, the biofilm com-munity composition was significantly (p5 0.001)influenced by the substratum type; on the samesubstratum types, different communities were presentat different depths on almost all tested substrata. Theorientation seemed to play a less important role onbacterial community composition at the highest depth4500 m (Figure 4a, b).

Qualitative analyses

In order to simplify the presentation of results, onlyMultidimensional Scaling (MDS) plots are shown.Briefly, the Jaccard similarity coefficients indicatedthrough cluster analyses that within one depth, themicrobial community composition differed accordingto the substratum type on which the biofilms grew,while large differences were detected between commu-nities grown on the same substratum type but exposedto fouling at different depths.

MDS plots show that bacterial community compo-sition of biofilms developed at 2500 m and 3500 mwere very different from those present at 1500 m and4500 m (Figure 5a1, a3). Although on the verticaldeployed substrata there was no such separation, it canbe seen that the samples from bacterial communitiesdeveloped at 2500 m group closer compared to thoseat 3500 m and 4500 m (Figure 5a2). On the otherhand, the results show that the substratum type did not

Table 1. Number of T-RFs in biofilm samples obtained bythe restriction enzymes CfoI and RsaI.

Range of totalT-RF numbers

TotalT-RF

numbers

Number ofsamples withhigher T-RF

numberdetection

Min. Max.

CfoI 4.33 + 0.58 23.67 + 4.16 94 17RsaI 4.33 + 0.58 20.33 + 1.53 93 10

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affect the composition of the bacterial communitythroughout the water column (Figure 5b1–b3).

Microbial community description

The most common bacterial ribotypes (T-RFs) de-tected with CfoI digestion and assigned using TAP-TRFLP program were possibly the Cytophaga group I(T-RF of 33 bp length; in total 100 T-RFs),Leptospirillum-Nitrospira/NSP Marina subgroup (T-RF of 37 bp length; in total 76 T-RFs), Gram-positive

bacteria (T-RF of 38 bp, 50 bp, 218 bp and 230 bplengths; in total 28, 76, 18 and 36 T-RFs correspond-ingly), Gamma-Proteobacteria (T-RF of 41 bp length;in total 42 T-RFs), Alpha-Proteobacteria (T-RF of336bp length; in total 13 T-RFs: 13) and 13 unknownribotypes.

The composition of microbial biofilm communitiesdeveloped on all deployed substrata at differentdeployment depths is presented in Figure 6. Thecomposition of bacterial communities did not differalong the depth gradient based on the percentage

Table 2. Presence of T-RFs marked by . detected in biofilms that developed on different substrata (aluminum, glass, shale,limestone, titanium) and at different orientations.

1500 m 2500 m 3500 m 4500 m 1500 m 2500 m 3500 m 4500 m

22 . . 206 . . . .24 . . . . 209 . .27 . . . 221 .28 . . . 218 .29 . . . . 257 .31 . . . . 287 .33 . . . . 33635 . . . . 337 . .37 . . . . 339 .38 . . . . 343 .41 . . . . 349 .44 . . . . 352 .47 . . . 35449 . . 361 . . .51 . . . 364 .52 . . . 367 . . .54 . . . . 369 . . . .55 . . 443 .57 . . 495 .60 . . 497 .62 . 515 . .64 . . . . 517 .69 . 553 . .71 . 555 . .74 . . 557 .76 . . . . 559 .78 . . 561 . . .80 . 564 . . .84 . 567 . . . .86 . 581 .87 . . 596 .90 . . . 618 .93 . 760 .95 . . 783 .100 860 .107 . . 900 .122 . 906 .123 . . 1039 .127 . . 1041 . .128 1087 . .142 . 1088 . . .151 . 1091 .190 . 1092 .200 . . . 1160 .203 . . . . 1200 .

Note: Presentation of T-RFs is in relation to deployment depth: 1500, 2500, 3500 and 4500 m. T-RFs were obtained using restriction enzymeCfoI. The sizes of fragments are in base pairs.

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abundances (area/height) of the microbial community.This was further demonstrated by the presence ofAlpha-, Beta-, and Gamma-Proteobacteria, Gram-positive bacteria, Flexibacter/Cytophaga/Bacteroides,Leptospirillum/Nitrospira and Cyanobacteria at alldepths, except at 3500 m, where cyanobacterial ribo-types were absent.

At all depths, the highest abundance of extractedribotypes belonged to unidentified bacteria. About halfof the detected T-RFs (84 out of 140), did not haveclose matches with the RDP (Ribosomal Data Project)database (Figure 6). This suggests that ribotypes ofbiofilm bacteria grown on artificial substrata in a deep-sea environment have not been yet identified and mightbe novel.

Discussion

In this study, despite the technical difficulties involvedin performing in situ deep-sea experiments (Young2009), replicated sampling was achieved with the use ofa platform that hosted several replicates for eachsubstratum type tested. Experiments with sufficientreplication are essential when the research goal is to

define which parameters affect the composition of thebiofilm community, while the achieved data requirecareful statistical analyses (Jackson and Underwood2009). However, not only is replicated samplingimportant when it comes to describe complex commu-nities with culture-independent methods such as T-RFLP, but the restriction enzyme choice (Dickie andFitzJohn 2007) and replicated digestions (Dunbar et al.2001) are also crucial for detecting as many realterminal restriction fragments (T-RFs) as possible. Inthe analyses of free-living, surface-attached andparticular-attached bacteria sampled in deep-sea en-vironments, the restriction enzymes CfoI (HhaI),HhaIII, MvnI and RsaI are mostly used as they havebeen tested for their ability to detect a high number ofOTUs within these deep-sea samples (Moesenederet al. 1999, 2001a; Polymenakou et al. 2005b; DeCorte et al. 2009). The results arising from threereplicated digestions for each deep-sea biofilm sampleshowed that with the use of the restriction enzymeCfoI, higher numbers of T-RFs can be achievedcompared to RsaI. Similarly, in other T-RFLP studiesof estuarine biofilm samples, the restriction enzymeCfoI was used for the statistical description ofcommunity patterns (Nocker et al. 2007). Moreover,T-RFLP analyses of deep-sea sediment samples takenfrom the Eastern Mediterranean showed that diges-tions with the restriction enzyme RsaI produced veryfew T-RFs compared to the digestions with therestriction enzyme HhaI (isoschizomer of CfoI) andHaeIII (Polymenakou et al. 2005a).

Overall, a total number of 94 different T-RFs wasdetected with CfoI in all analysed deep-sea biofilmsamples that grew on artificial substrata and wereexposed to fouling at different depths of the IonianSea. In contrast, in deep-sea sediment samples takenclose to Italy, only 61 different T-RFs were observed(Luna et al. 2004) and in deep-sea sediments takenfrom the Ionian Sea, Cretan Sea and Aegean Sea, thenumber of generated T-RFs was overall lower, rangingfrom 15 to 51 (Polymenakou et al. 2005a). With thecombined use of the two restriction enzymes RsaI andHhaI, 57 to 108 different T-RFs were detected inparticle-attached bacterial communities throughoutthe water column (Moeseneder et al. 2001a). Thehigher T-RF numbers observed in this study can beexplained by a high diversity of bacterial communitiesin deep-sea biofilms. Furthermore, it underlines thatcolonisation of substrata takes place not only on thedeep-sea floor (Muraoka 1965, 1966c) but also in theabyssopelagic (Bellou et al. 2011). These results high-light the hypotheses of several authors (Tselepideset al. 2000; Krom et al. 2004) that, especially inoligotrophic environments similar to the one investi-gated here, surfaces are a source of nutrients (Cooksey

Figure 4. Mean numbers of T-RFs in biofilms developed ondifferent substrata in relation to deployment depth and foreach substratum orientation: a¼ horizontal; b¼ vertical.

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and Wigglesworth-Cooksey 1995) and surface attach-ment is extremely important for marine bacteria underthese environmental conditions (DeLong et al. 2006).

In coastal waters, several studies showed thatparameters such as substratum type, depth anddeployment exposition influence the formation ofbacterial biofilms (Head et al. 2004; Jones et al.2007). For example, it has been shown that bacterialattachment is related to the physico-chemical proper-ties of the substratum (Dexter et al. 1975) and that thesubstratum type influences the composition of thebacterial community (Zobell 1943; Costerton 1995;

Dang and Lovell 2000). Biofilm communities devel-oped on stainless steel and polycarbonate substratawere initially the same in their composition, butdiffered after about 1 week of growth (Jones et al.2007). In this study, the differences detected betweendeep-sea biofilm communities grown within one depthand on different substratum types suggested that depthinfluenced the development of bacterial biofilm com-munities. Moreover, the results indicate that substra-tum orientation significantly influences the formationof microbial communities within the same depth.Similar to these results, a study performed in the

Figure 5. Multidimensional Scaling Analysis (MDS) plots of deep-sea biofilm communities that were performed according todepth (a) and substratum type (b). For both parameters, MDS plots are presented for data arising from (1) horizontally deployedsubstrata, (2) vertically deployed substrata and (3) both orientations combined. The similarity of T-RFLP patterns was assessedwith Jaccard similarity coefficients. [Samples at 1500 m and vertically deployed substrata are not included in the analysis due tosampling loss.]

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costal areas of Australia showed that different micro-bial communities are formed on the same substratumtypes with different orientations (Glasby 2000; Glasbyand Connell 2001). Differences between the verticallyand the horizontally orientated substrata could beexplained by a higher accumulation of bacteria on thehorizontal substrata and accumulation of particles ormarine snow (Suzuki and Kato 1953), which containmicroorganisms (Wiebe and Pomeroy 1972) and arethought to be the principal vehicles by which particlessink in the ocean (Lampitt and John 2001). Never-theless, compared to exposure depth, it seems thatsubstratum type and deployment orientation play aless important role in the bacterial communitycomposition of deep-sea biofilms. The effects oforientation and substrata may interact throughoutthe deep-sea water column, as it has been shown incoastal areas (Glasby 2000) and a generalisation on theorientation preferences along a depth gradient wouldbe misleading.

The MDS analyses clearly showed that depthinfluenced the deep-sea biofilm community composi-tion more than the substratum type. The relationshipbetween depth and community composition changeshas been demonstrated up to now only in one studyperformed in the Clyde Sea (Head et al. 2004). Thisstudy showed that biofilm communities developed onglass substrata varied significantly with exposure depth(from 5 m down to 160 m) and with the time ofexposure (Head et al. 2004). Additionally, the deploy-ment duration can decrease the dissimilarities betweencoastal biofilms grown on different substratum types(Jones et al. 2007). Studies on the free-living andparticle-attached bacteria in the Eastern

Mediterranean Deep Sea showed that bacterial com-munities differed considerably throughout the watercolumn (Moeseneder et al. 2001a). Temperature andsalinity normally co-vary with depth and influenceformation of bacterial communities (Chiu et al. 2005).However, variations in temperature and salinity withdepth cannot explain the results reported in this study,because the temperature and salinity profiles wererelatively homogeneous with depth (Staller 2009;Kontoyiannis and Lykoysis 2011). Even though thesetwo parameters did not visibly vary with depth at thestudy site, this does not exclude the presence ofdifferent deep-sea water masses with differences intheir origin and biogeochemical characterisation. Atthe Ionian basin, the vertical distribution of totalinorganic nitrogen and phosphate clearly showeddifferences in concentration along the depth gradient,while their concentrations at 1500 m and 4500 m depthas well as at 2500 m and 3500 m had a similar range(Staller 2009; Pujo-Pay et al. 2011). Below a depth of1000 m in the Eastern Mediterranean Sea, a youngerEastern Mediterranean Deep Water (EMDW) masslies (Meador et al. 2010) that is formed by deep watersof different origin (Theocharis and Lascaratos 2006;Roether et al. 2007). With respect to the Ionian basin,it has been observed that Ionian water of Adriaticorigin is dominated by bottom stratification (Rubinoand Hainbucher 2007). Studies on free-living bacteriashowed that the physico-chemical conditions at differ-ent depth layers influence them and they developdistinct communities in these water layers (Moesenederet al. 2001a). Furthermore, water masses may act asphysical barriers that limit the dispersal and controlthe diversity of microbes in the ocean (Galand et al.

Figure 6. Overall abundance as a percentage of microbial groups at different depths. T-RFs were assigned to simulated digestsby CfoI of 16S RNA sequences of RDPII database using the TAP-TRFLP program.

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2010) and among different water masses variations inrelative abundances of Bacteria and Archaea occur(Varela et al. 2008). In coastal waters, substratum-attached bacteria are a subset of the total diversity ofthe bacteria living free in the surrounding depth layer(Jones et al. 2007). Hence, indications are that therecorded distinct deep-sea biofilm communities arerelated to the origin and the biogeochemical characterof the surrounding deep-sea water masses.

The number of T-RFs in deep-sea biofilms re-mained similar throughout the water column, which isin contrast to the observed decline in T-RF numbers ofparticle-attached and free-living bacteria observed withincreasing depth in the Eastern Mediterranean Sea(Moeseneder et al. 2001a). Although a comparison ofparticle-attached and free-living bacterial communitiesindicated that an exchange between these communitiesseemed to be rather limited (Moeseneder et al. 2001a),one future approach that would shed more light intodeep-sea biofilm communities would be to comparefree-living, particle- and substratum-attached bacterialcommunities. Moreover, as deep-sea instruments aredeployed for a long time in the water, and as thebiofouling in deep cold seawater develops more slowlythan in the warm surface waters (Berger and Berger1986), further studies should include longer exposureand sampling times at different succession stages astime has been shown to influence the composition andaccumulation of the coastal biofilm community (Headet al. 2004; Jones et al. 2007).

As differences in the sizes of T-RFs reflectdifferences in the sequences of 16S rRNA genes (egsequence polymorphism), phylogenetically distinctpopulations of organisms can be determined. There-fore, terminal fragments separated through the T-RFLP method, can be directly referred to known 16Sgene sequences (Liu et al. 1997; Marsh 1999). In thisstudy, the TAP-TRFLP program allowed the identitiesof single TRFs present in deep-sea biofilm samples tobe obtained. At all depths (except for 3500 m, whereCyanobacteria were not detected) Alpha-, Beta-, andGamma-Proteobacteria, Gram-positive bacteria, Flex-ibacter/Cytophaga/Bacteroides, Leptospirillum/Nitros-pira and Cyanobacteria were present. As most of theextracted TRFs did not match up with the results inthe database, the authors propose that these ribotypesof deep-sea bacteria have not yet been identified ormight be novel. The vast majority of biofilm studieshave investigated bacterial communities in coastalareas, but to the authors’ knowledge, in the deep-sea,only bacteria in sediments (Polymenakou et al. 2005b;Fry et al. 2008), as well as free living and marine snow-associated bacteria (Moeseneder et al. 2001a; Ghi-glione et al. 2008; Winter et al. 2009) have beendescribed. An exception is the pioneer studies

performed at the deep-sea bottom of the Pacific Ocean,where biofilms were visually observed (Muraoka 1965).All other deep-sea settlement studies that haveinvestigated microbial colonisation have been per-formed only in extreme environments such as hydro-thermal events (Guezennec et al. 1998; Alain et al.2004).

It has been hypothesised that the deep-sea environ-ment is populated by a low abundance of highlydiversified microbial organisms (Sogin et al. 2006;Lauro and Bartlett 2008). The deep-sea biofilmsstudied in the Ionian Sea showed a compositionalchange between depths, but no decrease in the overalldiversity was observed. Certainly, the T-RFLP methodcannot provide the exact identity of bacterial groupspresent in deep-sea biofilms, but it still offers anexcellent opportunity to compare bacterial commu-nities and to get an idea about the diversity of thesecommunities and identify of some microbial groups.Nevertheless, in this study, the presence of unidentifiedbacteria and their high abundances could explainsignificant differences between communities developedon different substrata at tested depths. Studies dealingwith free-living bacteria of various origins demon-strated that many free-living bacteria cannot beassigned to known species (Schut et al. 1997). WhileTAP-TRFLP is a good method to get a first descrip-tion of microbial communities (Braker et al. 2001),further investigations using cloning or 16S rRNAHigh-Throughput Methods (Fabrice and Didier 2009)should be carried out. This will significantly contributeto understanding of biofilm ecology in the deep-sea.

In conclusion, this study demonstrates that thecomposition of deep-sea biofilm communities is largelyinfluenced by depth rather than by substratum type.The composition of bacteria present in deep-seabiofilms appears to be as complex as the coastalbacterial biofilm community and very diverse even atgreat depth.

Acknowledgements

This work was supported by the EU FP6 KM3NeT Project,contract no. 011937. The authors want to thank WolfgangVoigt (FTZ, Germany) and Rudiger Kiehn (GKSS, Ger-many) for their the tremendous work and thinking to set theauthors’ ‘surreal’ deep-sea experimental idea and setup intocontext, as well as for their support before, during and afterthe cruises. Torsten Staller (FTZ, Germany) is thanked forhis support throughout the experiment. Tom Mueller andGerd Niehus (IfM-Geomar, Germany) are thanked for theirhelp on the mooring line design. The officers and allcrewmembers of the R/V AEGAEO, as well as the head ofthe cruises Spyros Stavrakakis are acknowledged for theirwork and assistance during the mooring deployments andrecoveries. The cruises were co-financed by the EU FP6SESAME Project, contract no. 036946 and by the EU FP6HERMES Project, contract no. 511234. Many thanks also to

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the Antonis Magoulas laboratory, represented by ElenaSarropoulou (HCMR, Greece), especially for the pleasanthospitality throughout the duration of the analyses, as well asKaterina Skaraki (HCMR, Greece) for her help during theanalyses. Special thanks to Peter Koske (CAU, Germany) forsupporting and believing in this project.

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