Science of the Total Environment 497–498 (2014) 50–59

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Science of the Total Environment

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Bacterial diversity in a contaminated Alpine glacier as determined byculture-based and molecular approaches

Fabrizio Cappa a, Nicoleta Suciu b, Marco Trevisan b, Susanna Ferrari c,Edoardo Puglisi a,⁎, Pier Sandro Cocconcelli a

a Istituto di Microbiologia, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italyb Istituto di Chimica Agraria ed Ambientale, Università Cattolica del Sacro Cuore, Via Emilia Parmense 84, 29122 Piacenza, Italyc Centro Ricerche Biotecnologiche, Università Cattolica del Sacro Cuore, Via Milano 24, 26100 Cremona, Italy

H I G H L I G H T S

• We analyzed bacterial diversity and pollutants in a ski resort close to a glacier.• The ski resort is a source of PCB and PAH contaminants.• Bacterial species phylogenetically close to xenobiotic degraders were found.• Organic contamination in glaciers can select xenobiotic degraders adapted to cold.

⁎ Corresponding author. Tel.: +39 0523599249; fax: +E-mail address: edoardo.puglisi@unicatt.it (E. Puglisi).

http://dx.doi.org/10.1016/j.scitotenv.2014.07.0940048-9697/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 12 May 2014Received in revised form 24 July 2014Accepted 24 July 2014Available online 10 August 2014

Editor: D. Barcelo

Keywords:GlaciersBiodiversityPAHsPCBsXenobiotic degradersPCR-DGGE

Glaciers are important ecosystems, hosting bacterial communities that are adapted to cold conditions and scar-city of available nutrients. Several works focused on the composition of bacterial communities in glaciers andon the long-range atmospheric deposition of pollutants in glaciers, but it is not clear yet if ski resorts can repre-sent a source of point pollution in near-by glaciers, and if these pollutants can influence the residing bacterialcommunities.To test these hypotheses, 12 samples were analyzed in Madaccio Glacier, in a 3200 m a.s.l. from two areas, oneundisturbed and one close to a summer ski resort that is active since the 1930s. Chemical analyses found concen-trations up to 43 ng L−1 for PCBs and up to 168 μg L−1 for PAHs in the contaminated area: these values aresignificantly higher than the ones found in undisturbed glaciers because of long-range atmospheric depositionevents, and can be explained as being related to the near-by ski resort activities. Isolation of strains on rich me-dium plates and PCR-DGGE analyses followed by sequencing of bands allowed the identification of a bacterialcommunity with phylogenetic patterns close to other glacier environments, with Proteobacteria andActinobacteria the mostly abundant phyla, with Acidobacteria, Firmicutes and Cyanobacteria also represented inthe culture-independent analyses. A number of isolates were identified by molecular and biochemical methodsas phylogenetic related to known xenobiotic-degrading strains: glaciers subjected to chemical contaminationcan be important reservoirs of bacterial strains with potential applications in bioremediation.

© 2014 Elsevier B.V. All rights reserved.

1. Introduction

Glaciers are unique ecosystems covering a surface of about15 million km2, approximately 10% of the total land surface area of theEarth (Anesio and Laybourn-Parry, 2012). These ecosystems are domi-nated by psychrotolerant and psychrophilic microorganisms that canthrive under cold conditions, thanks to a range of adaptations of cellmetabolism that include the production of cold-active enzymes, anti-freezing proteins and exopolymeric substances, as well as an increase

39 0523599246.

in the proportion of unsaturated fatty acids aimed at ensuring fluidityof the membranes at low temperatures (Margesin and Miteva, 2011;Nichols et al., 1993; Sakamoto and Murata, 2002). Bacteria are knownto constitute up to the 90% of the glacier microbiota, followed by micro-bial eukaryotes (mainly fungi and yeasts), while archaea and viruseswere recently found to be present in relative proportions lower than1% (Margesin and Miteva, 2011). A recent pyrosequencing assessmentof 336 16S rRNA sequences retrieved from the Northern SchneefernerGlacier in Germany indicated that Proteobacteriawas the dominant phy-lum (up to 65% of all analyzed sequences, with Betaproteobacteria themost represented class), followed by Bacteroidetes and Actinobacteria.Other phyla such as Gemmatimonadates, Chloroflexi, Acidobacteria and

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Firmicuteswere also represented, but in a total amount of less than 4% ofanalyzed sequences (Simon et al., 2009). These outcomes are generally inaccordance with other studies carried out in glaciers from Alaska(Segawa et al., 2010), Tibet (Zhang et al., 2010b), China (Xiang et al.,2009), Canada (Cheng and Foght, 2007) and New Zealand (Foght et al.,2004), and are also reflected in the composition of approximately 1500phylogenetically identified isolates maintained in the Korean Polar andAlpine Microbial Collection (PAMC) (Lee et al., 2012).

Glacier ecosystems are also exposed to the fall-out and accumulationof chemical pollutants, and they are thus important proxies of pollutionevents. The presence of pollutants such as polycyclic aromatic hydrocar-bons (PAHs), polychlorobiphenyls (PCBs) and chlorinated pesticides isoften linked to atmospheric deposition and transport path of airmasses:an assessment of organic pollutants deposited from the mid-1960s in a20.8 m ice core sampled at 6518 m a.s.l. of the East Rongbuck Glacier,Mt. Everest revealed a concentration of total PAHs up to 100 ng L−1 inthe mid-1990s and peaks for lindane and DDT of respectively 6 and1.8 ng L−1 in the 1970s, in accordance with the historical economicaldevelopment trends in India (Wang et al., 2008a). Li et al. (2011)assessed the presence of the sixteen U.S. EPA priority PAHs along fourdifferent glaciers of the Tibetan Plateau, and found concentrations oftotal PAHs ranging between 20.45 and 60.57 ng L−1, with a predomi-nance (i.e., between 88 and 98% of the PAH sum) represented by 2 or3 ring PAHs (naphthalene, anthracene, acenaphthene, acenaphthylene,fluorene). According to a modeling of backward air trajectories, theauthors of the study indicate westerly wind circulation from CentralAsia and arid areas of Northwest China as the most probable sourcesof the contamination. The contamination of ice glaciers is indeed atopic of high interest, since their partial melting due to climate changecan be a significant source of persistent contaminants reaching watercatchments at lower altitudes (Bettinetti et al., 2011; Elliott et al.,2012). Skiing activities can also represent a source of local contamina-tion in glaciers, but the issue has been just marginally considered inthe scientific literature. It was recently demonstrated that ski waxescontain and can release fluorinated pollutants such as perfluoroalkylcarboxylic acids (PFCAs), resulting in snow contaminations up to hun-dreds of μg per m2 (Plassmann and Berger, 2013). Ski resort areashave been proposed as possible sources of pollution butwith no insightsabout the chemical quantification of pollutants and their possible influ-ence on the structure of ice microbial communities (Kopp et al., 2012;Rodriguez, 1987; Tsuyuzaki, 1994).

From an ecological point of view, glaciers are carbon-poor ecosys-tems,wheremost of the available organic carbon is derived from alloch-thonous inputs (Stibal et al., 2008): accumulation of organic pollutantscan thus represent a relevant source of nutrients, and drive for the selec-tion of xenobiotic-degrading microorganisms more efficiently than incarbon-rich polluted environments such as soils and sediments. Accord-ingly, a number of strainswith potential xenobiotic-degrading activitieshave been isolated from ice environments and characterized: examplesinclude a strain of Bacillus sphaericus isolated from theGangotri glacier inWestern Himalayas and producing a stable cold-active lipase (Josephand Ramteke, 2013), the identification of a bacterial community able todegrade the herbicide 2,4-D (2,4-dichlorophenoxyacetic acid) in theGreenland ice sheet (Stibal et al., 2012), the isolation of hydrocarbon-degrading Pseudomonas, Acinetobacter, Rhodococcus, andMycobacteriumstrains from sites in the Alpine area (Margesin et al., 2003; Shin et al.,2012). Glaciers subjected to contamination events can thus host bacterialspecies with potential biotechnological applications related to theiradaptation to cold environments characterized by carbon scarcity andxenobiotic-presence.

The presentworkwas carried outwith the aim to assess the bacterialdiversity and isolate cultivable strains in an ItalianAlps glacier subjectedto possible contamination by a nearby ski-resort. Microbiological inves-tigations were carried out by a combination of culture-dependent andculture-independent methods, while chemical analyses were carriedout to quantify the presence of organic contaminants.

2. Materials and methods

2.1. Sample collections

Ice cores samplingwas carried out in October 2010 in the northwestarea of Madaccio Glacier (Bolzano, Italy, 46°30′29.63″N, 10°28′9.27″E)at 3200 m a.s.l. Six samples (M1–M6) were collected downstream of asummer ski area served by a platter lift, while other five (M7–M11)were collected in a control area at the same altitude (46°29′56.50″N,10°29′00.27″E) but far from the ski-resort (Fig. 1). The ice core sampleshad a diameter of 8 cmandwere drilled to a depth between 10 and 50 cmafter removing snowand thefirst 10 cmof glacier surface. The ice sampleswere sealed in sterile plastic bags and immediately recovered in boxcontaining dry ice to avoid ice melting. The ice cores were preservedat−20 °C prior to analyses. Since point accumulation of solid materials(debris and organic black materials) was found in sample M4, two sub-samples were derived and analyzed from it: M4a andM4b, where M4bcontained the solid materials.

2.2. Sample treatment and cell recovery

The ice core sampleswere handled in a UV-treated, positive-pressurelaminar-flowhood under aseptic conditions; the outer 1.5 cmof ice layerwas removedby sterile knife scraping; all procedures of ice core handlingwere carried out at temperature below 15 °C. A control sample was alsoprepared using ultrapure sterile water and treated following the sameprotocol applied for ice core samples. The ice samples were melted at4 °C in sterile glass vessels, obtaining 350 mL of water per sample thatwas filtered through 0.22 μm pore size sterile cellulose acetate mem-branes (Whatman) by vacuum pump. The filter membrane was trans-ferred in appropriate sterile bag with 5 mL of sterile physiological saltsolution (0.9%w/vNaCl) and shacked in a homogenizer for 5min: the so-lution obtainedwas then used for all concomitantmicrobiological analy-ses, while the eluted water was collected and subjected to chemicalanalyses.

2.3. Chemical analyses of PAHs and PCBs

Analytical standards for mixtures of PCBs (IUPAC congener numbers28, 52, 101, 118, 138, 153, 180) and PAHs (acenaphtylene, fluorene,phenanthrene, fluoranthene, benzo(jkb)fluoranthene, benzo(a)pyrene,indeno(1,2,3-cd)pyrene, benzo(ghi)perylene) and the internalstandards (anthracene-d10, perylene-d12) were purchased fromDr. Ehrenstorfer GmbH, Augsburg, Germany.

Filtered water deriving from the melted ice samples (350 mL) wasextracted in a separating funnel by soaking in 50 mL of n-hexane and20 mL sulfuric acid 1 N at 200 rpm for 10 min, repeating the operationthree times. The organic phase was passed over anhydrous sodiumsulfate to remove water. The volumes of the extraction solutions werereduced to dryness using vacuum rotary evaporation. The sampleswere dissolved again with approximately 5 mL of n-hexane andunderwent clean-up using a Florisil column that was previously condi-tioned using 6 mL of n-hexane. The residues were eluted twice with2mL of n-hexane and further driedwith a gentle flow of nitrogen. Final-ly, the samples were recovered in 0.5 mL of n-hexane containing theinternal standards anthracene-d10 (1.14 mg L−1) and perylene-d12(1.05 mg L−1).

Analyses of PAHs and PCBs were performed with a gas chromato-graph coupled to a mass spectrometer (GC–MS). The chromatographicconditions together with the identification of ions used for PAHs werepreviously described (Zaccone et al., 2009). The mass to charge ratios(m/z) used for PCBs were: m/z 256 for congener 28, m/z 292 for 52,m/z 326 for 101 and 118, m/z 360 for 138 and 153 and m/z 394 fornr. 180. The quantification of PCBs wasmade using the Single IonMon-itoring (SIM) mode whereas the PAHs were quantified using the TotalIon Monitoring (TIM) mode. The limit of detection (LOD) for PCBs was

Fig. 1. Outline map of two sampling locations in the Madaccio Glacier, Province of Bozen, Northern Italian Alps. Ice core replicates M1–M6were retrieved close to the summer ski resort;replicates M7–M11 from a nearby area at the same altitude but separated from the ski resort by a mountain peak. Ski lifts are indicated in red.

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0.9 ng L−1 whereas for PAHs it was 0.01 μg L−1. Recoveries werebetween 54% and 106% for PCBs and between 55% and 104% for PAHs.

2.4. Isolation and characterization of cultivable strains

Analyses of the cultivable fraction of bacteria were carried out byplate counting techniques. Onemilliliter aliquot ofmicrobial cells recov-ered from the filters in physiological solution for each of the 12 sampleswas used for serial dilutions plating on R2A agar (Oxoid Ltd.,Basingstoke, England) in single replicates. Plates were incubatedunder aerobic conditions at 4 °C for three days to adapt bacteria, follow-ed by incubation at 20 °C up tofiveweeks. Representative colonieswereselected on the basis of shape and color, sub-cultured, and stored in theUCSC Institute of Microbiology collection.

DNAwas extracted from each colony grown on R2A agarmedium at20 °C after striking a R2A broth culture of the isolated strain. DNA wasextracted using microLYSIS® method (Labogen, UK) following theinstruction of the manufacturer, and used for Random Amplified Poly-morphic DNA (RAPD) and 16S rDNA analyses. RAPD analysis wasperformed using RAPD2 primer 5′ AGC AGC GTG G 3′ (Cocconcelliet al., 1995) and assembled with goTaq polymerase (Promega, Italy)and Master Mix 5× (Promega, Italy). Amplifications were carried outin a Gene Amp PCR System 9700 thermocycler (Applied Biosystems)following the conditions described earlier (Fontana et al., 2010). RAPDproducts were separated by electrophoresis at 100 V on 2.5% agarosegel stained with SYBR safe (Invitrogen, Italy).

Taxonomic identification of isolateswas carried out by sequencing of16S amplicons after PCR reaction. PCR was assembled with goTaq

polymerase (Promega, Italy) and Master Mix 5× (Promega, Italy) andthe amplification of a region of 16S rRNA gene was performed byusing the primers P0 (5′-GAGAGTTTGATCCTGGCTCAG-3′) and P6 (5′-CTACGGCTACCTTGTTACGA-3′). PCR amplification was carried out in50 μL reaction mixtures using 5 μL of 10× buffer, 5 μL of MgCl2(25 mM final concentration), 5 μL of dNTPs (2mM final concentration),1 μL of each primer (10 μM final concentration), 0.5 μL of TaqDNA poly-merase at 5 U/μL, 20 μL of DNA extract by microLYSIS® method anddH2O to the final volume of 50 μL. The thermal cycling conditionswere 94 °C for 30 s, 30 cycles of 94 °C for 30 s denaturation, 58 °C for30 s annealing, 72 °C for 2 min extension, and a final extension step of72 °C for 2 min. Capillary Sanger sequencing of 16S rRNA geneamplicons was carried out at BMR Genomics facilities (Padua, Italy).Phylogenetic analyses on the sequences were carried out as describedbelow in the PCR-DGGE section. 16S rRNA sequences were depositedin GenBank under the accession numbers KJ728984–KJ729009.

API ZYM (Humble et al., 1977) and API 20E (Amy et al., 1985) diag-nostic strips (API-bioMerieux, Marcy l'Etoile, France) were applied inorder to obtain a biochemical characterization of the substrate utiliza-tion and enzymatic patterns of the isolates. Both tests were carried outat 20 °C after confirming the ability of all isolates to grow at thistemperature.

2.5. Direct microscopic cell counts

Direct microbial counts were carried out on an aliquot of microbialcells recovered in physiological solution by filter shacking. Staining ofsamples with propidium iodide and SYTO9 was carried out following

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the instructions of the LIVE/DEAD® BacLight™ Bacterial Viability Kit(Invitrogen, Eugene, Oregon, US), and samples were examined underan Olympus BXE1 in order to count the number of living cells (Mesaet al., 2003).

Table 1Concentrations (ng L−1) of PCB congeners in melted ice samples from Madaccio Glacier.

Sample/PCBcongener

28–3Cl 52–4Cl 101–5Cl 118–5Cl 138–5Cl 153–6Cl 180–6Cl

Ski-resort areaM1 n.d 3 8 9 11 10 n.dM2 n.d n.d bLOQ 4 4 6 bLOQM3 n.d bLOQ bLOQ 5 6 9 bLOQM4a bLOQ 7 7 5 4 4 n.dM4b n.d 3 29 28 4 39 bLOQM5 n.d n.d 45 n.d n.d n.d n.dM6 n.d n.d 1.6 n.d n.d n.d n.d

Control areaM7 n.d n.d n.d n.d n.d n.d n.dM8 n.d n.d 1 3 n.d 6 n.dM9 n.d n.d 8 n.d n.d n.d n.dM10 n.d n.d n.d n.d n.d n.d n.dM11 n.d n.d n.d n.d n.d n.d n.d

n.d = not detected, i.e., below the limit of detection of 0.9 ng L−1; LOQ— limit of quanti-fication, considered to be three times the limit of detection.

2.6. PCR-DGGE analyses of uncultivated bacteria

DNA for PCR-DGGE analyses was extracted from 0.5 mL samples offiltered pellet diluted in physiological solution. The FastDNA® SPIN kitfor soil (MoBio Laboratories, Carlsbad, CA, USA) with a FastPrep® 24 in-strument (MP Biomedicals, LLC, Solon, OH, USA) was applied accordingto themanufacturer's instructions. DNAwas checked spectrophotomet-rically for purity (260/280 and 260/230 nm ratios) and for possibleshearing and degradation by electrophoresis on 0.8 and 1% agarosegels, respectively. Nucleic acid concentrations were assessed with theQuant-iT™HS dsDNA Assay kit (Invitrogen, Paisley, UK) in combinationwith the Qubit™ fluorometer (Invitrogen).

DNA samples were analyzed bymeans of a nested Polymerase ChainReaction — Denaturing Gradient Gel Electrophoresis (PCR-DGGE) ap-proach targeting the 16S rRNA V3 region of the bacteria. The first ampli-fication stepwas carried out using the primers 338F/805R, followed by asecond amplification with the same primer set but adding a 40 bp GCclamp to the reverse primers (Sousa et al., 2007). PCR amplificationwas carried out in 50 μL reaction mixtures using the PromegaMasterMix (Promega Corporation, Madison, WI, USA) containing50 units/mL of Taq DNA polymerase in pH 8.5 reaction buffer, with400 μM dNTPs. 2.5 μL of DNA template was added in each mixture con-taining 12.5 μL of Promega MasterMix, 2.5 μL of each primer set (1 μMfinal concentration), 2.5 μL of MgCl2 (25 mM final concentration) anddH2O to the final volume of 50 μL. The thermal cycling conditionswere 94 °C for 2 min, 30 cycles of 94 °C for 30 s denaturation, 55 °Cfor 30 s annealing, 72 °C for 30 s extension, and a final extension stepof 72 °C for 10 min. Conditions of the second amplification step werethe same, except for the annealing temperature that was raised to56 °C, and the extension step time, raised to 60 s.

DGGE was carried out using the INGENY phorU electrophoresisapparatus (Ingeny International BV, Goes, The Netherlands). Polyacryl-amide gels (6%) in 1× TAE buffer (40 mM Tris base, 20 mM aceticacid, and 1mMdisodiumEDTA, pH 8.2)were preparedwith denaturinggradient ranging from 45 to 65%. The electrophoresis was run for 18 h at60 °C and 90 V. Gels were SYBR Green-stained and visualized by UVradiation. Banding patterns of DGGE profiles were analyzed with Fin-gerprinting II software (Bio-Rad Laboratories, Richmond, CA, USA)using the Dice correlation coefficient and the unweighted-pair groupmethod with averages (UPGMA) for the generation of dendrograms.

Individual bands were excised from the gels, placed in 50 μL steriledH2O and incubated overnight at 4 °C. Two microliters of the eluatewas re-amplified with the original primer pairs and amplification prod-ucts were checked by agarose gel electrophoresis. PCR products werepurified using the Wizard SV Gel and PCR Clean-Up System (Promega)and subjected to sequencing at the BMR Genomics facilities (Padova,Italy). The resulting sequenceswere aligned against the ribosomal data-base project (RDP) database (http://rdp.cme.msu.edu) using the NaïveBayesian classifier (Wang et al., 2007). All 16S rRNA sequences werealso screened for possible presence of chimera with the DECIPHERsoftware (Wright et al., 2011). Multiple alignments of the identifiedsequences and closer hits on RDP database were carried out with theMUSCLE algorithm (Edgar, 2004), while phylogenetic trees wereconstructed on the aligned sequenceswith the PhyML (PhylogenyMax-imum Likelihood) approach (Guindon et al., 2003) by applying theShimodaira–Hasegawa [SH]-aLRT test. Alignments and tree generationwere carried out with the SeaView software (Gouy et al., 2010) aftertrimming the reference sequences to the region aligned with the shortsequences. The same approach was applied also for the analyses of the16S rRNA sequences obtained from the cultivated isolates.

3. Results

3.1. Persistent organic pollutants in glacier ice samples

Chemical analyses were carried out in order to identify and quantifychemical pollutants in the ice samples from Madaccio Glacier, andfocused on 7 PCB congeners and 9 PAHs. All samples were analyzedfor the presence of 7 PCB congeners: 8 out of 12 samples had concentra-tions of at least one PCB above the detection limit (Table 1), with amin-imum of 3 ng L−1 of melted ice (PCB52 in sample M8 from the controlarea) and a maximum of 43 ng L−1 (PCB101 in sample M4b from thearea close to the ski resort). The PCB congener 101 was the most repre-sented, while the two samples M4a and M4b showed the higher con-centrations in terms of sum of PCB congeners. All analyzed PCBs wereidentified in at least one sample, even if PCB28 and PCB180were alwaysunder the limit of quantification (LOQ).

Concentrations of PAHswere three orders of magnitude higher thanPCBs, with a minimum of 0.03 μg L−1 (benzo(ghi)perylene in sampleM5) and a maximum of 168 μg L−1 (benzo(ghi)perylene in sampleM4b) (Table 2). Ten out of twelve analyzed samples contained detect-able amounts of PAHs from 3 (phenanthrene) to 6 rings (benzo(ghi)perylene), with higher concentrations found in the area close to the skiresort. The sample M4b in particular had high concentrations (up to0.1 parts per million) of the most recalcitrant and toxic high-molecularweight PAHs benzo(a)pyrene, and benzo(ghi)perylene. Furthermore, inthe same sample values of 16.9 μg L−1 and 31.4 μg L−1 were also ob-served respectively for benzo(jkb)pyrene and indeno(1,2,3-cd)pyrene.

3.2. Microbial enumerations of cultivable and live bacteria

Inoculations on R2A agar medium were carried out in order to iso-late strains of interest and count total heterotrophic bacteria fromMadaccio Glacier melted ice samples. Inoculated plates were incubatedaerobically, firstly for 3 days at 4 °C to adapt the bacteria, then at 20 °C,and the first colonies were observed after 10 days of incubation. Totalcounts of colonies are reported in Table 3, and show that the totalheterotrophic bacteria cultivable in R2A medium were in the1 log CFUsmL−1 range, with aminimumof 1.1 (sampleM8) and amax-imum of 71 CFUsmL−1 (sample M4a). Total numbers of live bacteria asdetermined by microscopic cell counts in propidium iodide stainedsamples were between three and four orders of magnitude higherthan counts on R2A, and ranged from 2.2 ∗ 103 to a maximum of 3.7∗ 104 live cells per mL of melted ice. The twomethods did not show sig-nificant correlations of results (Table 3) and showed no differences be-tween cores of the contaminated and the control area.

Table 2Concentrations (μg L−1) of PAHs in melted ice samples fromMadaccio Glacier.

Ace Flu Phe Flh Pyr B(jbk)flu B(a)pyr Ind(1,2,3-cd)pyr B(ghi) per

Ski-resort areaM1 n.d n.d n.d n.d n.d n.d n.d n.d n.dM2 n.d n.d n.d n.d n.d n.d n.d n.d n.dM3 n.d n.d n.d n.d n.d n.d n.d 1.1 0.23M4a n.d n.d n.d n.d n.d 17.9 n.d 14.1 8M4b n.d n.d n.d n.d n.d 16.9 10.5 31.4 168M5 n.d n.d n.d n.d n.d n.d n.d n.d 0.03M6 n.d n.d bLOQ n.d bLOQ n.d n.d n.d n.d

Control areaM7 n.d n.d n.d n.d bLOQ n.d n.d n.d n.dM8 n.d n.d bLOQ bLOQ bLOQ bLOQ 0.03 n.d n.dM9 n.d n.d 0.04 bLOQ n.d n.d n.d n.d n.dM10 n.d n.d 0.04 bLOQ bLOQ n.d 0.04 n.d n.dM11 n.d n.d 0.05 bLOQ bLOQ 0.05 n.d n.d n.d

n.d = not detected, i.e., below the limit of detection of 0.01 μg L−1; LOQ — limit of quantification, considered to be three times the limit of detection.

54 F. Cappa et al. / Science of the Total Environment 497–498 (2014) 50–59

3.3. Isolation, identification and characterization of bacterial strains

A total of 40 isolates from different R2A agar plates with differentshapes and colors were sub-cultured in liquid R2A medium, and finallystored and classified in the UCSC collection of theMicrobiology Instituteof Piacenza. After RAPD screening of the isolates (data not shown), 25were identified as unique and further characterized. Taxonomic identi-fication of the isolates was carried out by sequencing of the 16S rRNAsmall subunit and by concomitant analyses of the obtained sequencesagainst the ribosomal database project (RDP). All isolates were identi-fied at least at the genus level, while 14 of them were also classified atspecies level, with identities to the reference database always higherthan 0.86 (S_ab score values, where 1 is the complete identity to a ref-erence sequence). Sphingomonas was the most represented genus (4isolates), followed by Pseudomonas, Arthrobacter and Afipia (3 isolatedstrains each), Polaromonas, Cryobacterium and Janthinobacterium (2 iso-lates each). Dyella and Frigoribacteriumwere finally represented by oneisolated strain each. The strains were isolated from different samples,with M6, M4a, M4b and M3 the most represented ones (Table 4).

A biochemical characterization of the isolate enzymatic activities andsubstrate utilization patterns was obtained by the application of APIZYM and API 20E tests (Supplementary Tables S1 and S2). The threePseudomonas (UC7206, UC7246 and UC7153), the four Sphingomonas(UC7208, UC7211, UC7232 and UC7247), the two Polaromonas(UC7248 and UC7250) and the two Afipia massiliensis (UC7236 andUC7240) isolates generally showed a higher metabolic versatility, withesterases, aminopeptidases, and enzymes for theutilization ofmonosac-charides usually represented. Intra-genus variability in the enzymatic

Table 3R2A plate counts of total aerobic heterotrophs and direct microscopic cell counts of totallive bacteria in samples from Madaccio Glacier.

Sample Aerobic heterotrophs(CFUs mL−1 ice)

Total live bacteria(cells mL−1 ice)

Ski-resort areaM1 6.0 ± 0.2 1.5 ∗ 104

M2 11 ± 0.3 6.8 ∗ 103

M3 32 ± 0.2 3.7 ∗ 104

M4a 71 ± 0.5 7.9 ∗ 103

M4b 9.8 ± 0.3 2.0 ∗ 104

M5 1.9 ± 0.1 2.2 ∗ 104

M6 4.7 ± 0.2 1.4 ∗ 104

Control areaM7 1.5 ± 0.1 3.1 ∗ 104

M8 1.1 ± 0.2 7.6 ∗ 103

M9 7.6 ± 0.5 2.2 ∗ 103

M10 2.6 ± 0.1 6.8 ∗ 103

M11 1.4 ± 0.1 7.4 ∗ 103

patterns of isolates was also found, as exemplified in the API ZYM pat-terns for Sphingomonas, Cryobacterium and Janthinobacterium isolatedstrains (Table S1). The utilization of different substrates also indicatedseveral differences among strains, with Pseudomonas sp. UC7246 andPseudomonas grimontii UC7153 displaying the widest substrate utiliza-tion patterns, followed by Rhodanobacter terrae UC7239, Cryobacteriumsp. UC7234 and Cryobacterium mespohilum UC7241. None of the 25isolate strains showed the ability to utilize urea or tometabolize organicsulfur, while only Arthrobacter sp. UC7207, Arthrobacter sp. UC7210 andMethylobacterium adhaesivum UC7212 had nitrate reduction activities.Several isolates were finally found to be able to utilize only one or twoof the tested substrates (Table S2).

3.4. Culture-independent assessment of bacterial diversity inMadaccio glacier

All samples from the two areas in Madaccio Glacier were analyzedby means of PCR-DGGE followed by excision and sequencing of a num-ber of bands. UPGMA clustering of DGGE patterns showed that samplesof the two areas were partly overlapping, pointing to a similar bacterialcommunity (Fig. 2).

A total number of 26 bands of interest were excised, purified and an-alyzed with Sanger sequencing. Out of the sequences obtained, 3 wereidentified as chimeras and discarded. The alignment of the remaining23 sequences against the ribosomal database project allowed a taxonom-ical identification up to the species level for 6 sequences, up to the genuslevel for 10, up to the family level for 1, while for 6 sequences it was notpossible to obtain a taxonomical identification (S_ab score b 0.5).Actinobacteria was the most represented phylum with 6 sequences,followed by Proteobacteria (5 sequences), and Bacteroidetes (2 se-quences) (Fig. 3). Firmicutes, Acidobacteria and Cyanobacteriawere pres-ent in one sequence each, corresponding respectively to a Clostridium, aGranulicella and a GpVIII strain (Table 5).

4. Discussion

In the present study we have collected and analyzed twelve ice coresamples in two 50 m2 areas in the Madaccio Glacier, located at 3200 ma.s.l. in the North-East Italian Alps. One area is located downstream of asummer ski resort area that dates back to 1930s, while the second areais at the same altitude, but it is more than 1 km far from the ski resort,and separated by a mountain peak (Fig. 1). Our first hypothesis wasthat the contaminated area would present higher concentration of or-ganic xenobiotics as a consequence of decades of possible contamina-tion events related with lift engines, snowmobiles and with the skiersactivities. In order to test this hypothesis, chemical analyses were per-formed, and showed significant concentrations up to 40 ng L−1forPCBs (Table 1) and up to 168 μg L−1 for PAHs, with the ice cores from

Table 4List of bacterial isolates retrieved from Madaccio Glacier sampling campaign. Identification was carried out by means of amplification and sequencing of 16S rRNA small subunit.

Strain Family Genus Species/closest hit S_ab score Sample name

UC7206 Psedomonadaceae Pseudomonas Antarctic bacterium N25 1.000 M4a, M4bUC7246 Psedomonadaceae Pseudomonas sp. 150 0.863 M11UC7153 Psedomonadaceae Pseudomonas grimontii (T) 1.000 M1UC7207 Micrococcaceae Arthrobacter sp. Asd M2L1 1.000 M4a, M4bUC7210 Micrococcaceae Arthrobacter sp. R-36550 1.000 M3UC7231 Micrococcaceae Arthrobacter cryoconiti 1.000 M6UC7208 Sphingomonadaceae Sphingomonas glacialis 0.906 M4a, M4bUC7211 Sphingomonadaceae Sphingomonas Antarctic bacterium GA036 0.938 M1UC7232 Sphingomonadaceae Sphingomonas glacialis (T) 1.000 M6UC7247 Sphingomonadaceae Sphingomonas sp. PMXh3 1.000 M6UC7243 Comamonadaceae Variovorax paradoxus 0.989 M7UC7248 Comamonadaceae Polaromonas naphtalenivorans 0.986 M3UC7250 Comamonadaceae Polaromonas sp. TP-snow-C81 0.955 M3UC7239 Xanthomonadaceae Rhodanobacter terrae 0.977 M6UC7242 Xanthomonadaceae Dyella japonica 0.949 M6UC7236 Bradyrhizobiaceae Afipia massiliensis (T) 0.913 M6UC7237 Bradyrhizobiaceae Rhodopseudomonas sp. ORS 1416ri 0.961 M6UC7238 Bradyrhizobiaceae Afipia glacier bacterium FXI3 0.946 M6UC7240 Bradyrhizobiaceae Afipia massiliensis (T) 0.953 M6UC7234 Microbacteriaceae Cryobacterium sp. MBD1-18-2 1.000 M5UC7241 Microbacteriaceae Cryobacterium mesophilum (T) 0.975 M5UC7249 Microbacteriaceae Frigoribacterium cryocola sp. KAR3 1.000 M3UC7209 Oxalobacteraceae Janthinobacterium sp. RHLS18 0.989 M4a, M4bUC7214 Oxalobacteraceae Janthinobacterium lividum 1.000 M4a, M4bUC7212 Methylobacteriaceae Methylobacterium adhaesivum 1.000 M2

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the contaminated area generally showing higher concentrations(Table 2). The literature on the accumulation of these pollutants inremote glacier areas because of long-range atmospheric transport anddeposition events is quite vast, and thus allows the definition of bench-mark levels for comparison. Wang et al. (2008b) assessed the levels ofpollutants in a location at 6720 m a.s.l. in the Dasuopo Glacier (Mt.Xixiabangma, central Himalayas), and found concentrations of PCBsranging between 0.09 and 0.34 ng L−1, while PAHs were quantified inthe 8.9–97 ng L−1 range; another study conduced in the Himalayanarea (East Rongbuck Glacier, 6572 m a.s.l., Mt. Everest) indicated PCBconcentrations in the surface ice between 3 and 48 pg L−1 (Kanget al., 2009); an assessment of PAHs in 4 different glaciers from theTibetan Plateau revealed a maximum peak of 60.57 ng L−1 (Li et al.,2011); finally, a study from different mountain areas around Europeshowed that the highest concentrations found were respectively2.2 ng L−1 for PCBS and 81 ng L−1 for PAHs (Carrera et al., 2001). Theconcentrations we found in Madaccio Glacier are higher in the ski-resort areas for both PCBs and PAHs. In particular, concentrations ofhigh-molecular weight PAHs are up to 4 orders of magnitude higherthan the one reported in the literature. Long-range atmospheric

Fig. 2. PCR-DGGE profiles with UPGMA clustering of the V3

transport is thus unlikely to be the source of these high concentrations.As far as we know, the only other report on organic xenobiotics close toski resort was provided by Finizio et al. (2006), who identified concen-trations up to 0.8 ng L−1 for PCBs close to the Punta Indren ski locationin the Monte Rosa area of the Italian Alps. This value is slightly lowerthan the one we found in the Madaccio ski area but significantly higherthan the values reported in the literature for uncontaminated glaciers.The hypothesis that engines used in the adjacent ski resort areas arethe source of these higher concentrations is also confirmed by evidencefrom Rice et al. (2008), who found that high peaks of PAHs in Alaskanlakes are related to the traffic of jet skis and power boats.

Data presented in Tables 1 and 2 also show a high variability of pol-lutant concentrations between samples: this finding is consistentwith apoint source of pollutions, aswell as to seasonal freeze–thaw cycles thatare typical of such altitude in the Italian Alps and that can increase theheterogeneity of concentrations. As also shown by the comparison ofsamples M4a andM4b, ice samples containing debris accumulated ma-terials were also found to have higher PCB and PAH concentrations, inaccordance with a short-range transport of pollutants from the nearbyski area. If we consider possible future scenarios of glacier melting

hypervariable region of bacterial 16S rRNA amplicons.

Fig. 3. Bacterial 16S rRNA gene-based dendrogram showing the phylogenetic relationship between the excised band sequences and closely related sequences in RDP. The tree was routedusing Enterococcus faecalis as outgroup. The scale bar represents a 0.05 change per nucleotide position. Type strains are highlighted with “T”.

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related to global warming (Bettinetti et al., 2011), the high pointconcentrations found for some of the contaminants can also poseconcerns. This is the case of sample M4b, where a concentration ofbenzo(ghi)perylene of 168 μg L−1 was found, which is more than10,000 times higher than the maximum concentration of 10 ng L−1

allowed in drinking water by the European Union for this compound(Council Directive 98/83/CE, 3 November 1998). This is, as far as weknow, the highest reported concentration of a high-molecular weightPAH in a glacier environments: it is important to notice anyway thatthe concentrations we found in the ski-resort area are much lowerthat the ones found in contaminated soils, and even high point concen-trations are supposed to be largely diluted in case of melting events.

The bacterial populations residing in the glacier area contaminatedby PCBs and PAHs were investigated by means of culture dependentand culture independent methods. The total number of cultivableaerobic heterotrophs, as estimated by aerobic plating on R2A agar at20 °C, varied between 1.1 and 71 CFUs mL−1, while the total viablemicrobial cells microscopically counted varied between 2.2 ∗ 103 and3.7 ∗ 104 cells mL−1, showing no significant differences between thecontrol and the ski-resort area: these results are exactly in the sameorders of magnitude and thus in agreement with evidence from theanalyses of samples from the South Pole (Carpenter et al., 2000), fromthe Kongsgeven Glacier (Svalbard) (Amato et al., 2007), from the EastRongbuk Glacier of Mt. Everest (Zhang et al., 2010a) and from the

Table 5Identification of excised bands from PCR-DGGE profiles of Madaccio Glacier bacterial communities. Most closely species and class from ribosomal database project are reported, togetherwith the samples covered and the Sab value provided by RDP, ameasure of the similarity to known sequence. Bands giving a Sab lower than 0.5 were classified as nd, not determinable. SeeFig. 1 for band position in the DGGE picture.

Band Phylum Family Genus Species S_ab value Samples

bac2 nd nd nd nd b0.5 M1bac3 nd nd nd nd b0.5 M1, M2, M3bac4 nd nd nd nd b0.5 M1bac5 Actinobacteria Microbacteriaceae Frigoribacterium Antarctic bacterium 3C3 0.838 M1, M2, M3, M4a, M4b, M5bac6 Proteobacteria Xanthomonadaceae Dyella nd 0.532 M1, M2, M3, M4a, M4bbac7 Proteobacteria Sphingomonadaceae Sphingomonas nd 0.593 M2, M3, M4a, M4b, M5, M6bac9 Actinobacteria Microbacteriaceae Cryobacterium mesophilum (T) 1 M1, M2, M3, M4a, M4b, M6, M7, M8bac10 Proteobacteria Oxalobacteraceae nd nd 0.611 M1, M2, M3, M4a, M4bbac11 Actinobacteria Micromonosporaceae Actinoplanes ianthinogenes 0.594 M1, M2, M4a, M4b, M5, M6, M7, M8, M9,

M10, M11bac12 Actinobacteria Segniliparaceae Segniliparus rugosus (T) 0.750 M1, M2, M3, M4a, M4b, M5, M6, M7, M8bac13 Actinobacteria Sporichthyaceae Sporichtya nd 0.897 M1, M2, M3, M4a, M4b, M5, M6, M7, M8,

M9, M10, M11bac14 Actinobacteria Nocardiaceae Rhodococcus equi (T) 1 M1, M2, M3, M4a, M4b, M5, M6, M7, M8bac15 nd nd nd nd b0.5 M2, M3, M4a, M4bbac16 Proteobacteria Bradyrhizobiaceae Afipia glacier bacterium FX13 0.942 M2, M4a, M4bbac17 Firmicutes Clostridiaceae Clostridium nd 0.634 M1, M3bac18 Bacteroidetes Chtinophagaceae Ferruginibacter Uncultured TP-snow-17 0.647 M3bac19 Bacteroidetes Cytophagaceae Hymenobacter nd 0.777 M1, M2, M3, M4a, M4bbac20 nd nd nd nd b0.5 M1, M2, M3, M4a, M4bbac21 Proteobacteria Sphingomonadaceae Sphingomonas azotifigens (T) 1.000 M1, M2, M3, M4a, M4b, M5, M6, M7, M8bac22 Proteobacteria Sphingomonadaceae Sphingomonas rhizovicinum (T) 0.911 M2, M4a, M4b, M6, M7, M8, M9, M10bac23 Acidobacteria Gp1 Granulicella nd 0.894 M1, M2, M3, M4a, M4bbac24 Proteobacteria Comamonadaceae Polaromonas Uncultured TP-snow-55 0.507 M1, M2, M3, M4a, M4bbac25 Cyanobacteria VIII GpVIII nd 0.752 M1, M2, M3, M4a, M4b

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Franz Josef and Fox Glaciers in NewZealand (Foght et al., 2004). The dif-ferences between total live bacteria and aerobic heterotrophs cultivatedon R2A are explained by the fact that only a fraction of living bacteriacan be cultivated under aerobic conditions. This evidence is in accor-dance with previous evidence indicating that less than 1% of bacteriafrom glacier environments are cultivable (Brinkmeyer et al., 2003;Zhang et al., 2008, 2010a) and in line with microbiological conceptknown as “the great plate count anomaly” (Stanley and Konopka,1985). In the present study we also carried out isolations on R2A agarplates under anaerobic conditions, but no colonies could be obtained(data not shown). Sequencing of PCR-DGGE bands revealed howeverthe presence of Clostridia (bac17, Table 5), thus confirming the issues re-lated with the cultivation of a vast majority of bacterial species from iceglacier samples, at least on a rich medium such as R2A.

The taxonomical identification of isolates (Table 4) and DGGE bandsequences (Table 5) showed however a good accordance betweenculture-dependent analyses of the bacterial microbiota in MadaccioGlacier samples. At phylum level, all isolates belonged to Proteobacteriaor Actinobacteria, which were the mostly represented phyla also in theDGGE analyses. The latter approach identified however a wider diversi-ty, that included sequences also belonging to Acidobacteria, Firmicutesand Cyanobacteria, in a relative proportion of phyla similar to the onesreported for glaciers from Germany (Simon et al., 2009), Alaska(Segawa et al., 2010), Tibet (Zhang et al., 2010b), China (Xiang et al.,2009), Canada (Cheng and Foght, 2007) and New Zealand (Foghtet al., 2004). Our data show correspondences between isolates andDGGE bands also at the genus level, namely in the case of Sphingomonas,Polaromonas, Dyella and Cryobacterium. In the latter case the same spe-cies, Cryobacterium cryocola, was isolated and identified as well amongthe DGGE bands.

Twenty-five different strains were isolated from the ski-resortarea of Madaccio Glacier, and afterwards characterized by API tests.Pseudomonas, Polaromonas and Sphingomonas were represented byat least two strains each, and their relative abundance is in accor-dance with evidence from Polar environments (Michaud et al.,2012). Coherently with the high level of organic pollutants quanti-fied in some samples from this area (Tables 1 and 2), some of thespecies isolated from these samples are closely related to known

xenobiotic-degrading strains. The strain UC7248 had a 16S rRNAidentity N98% with Polaromonas naphtalenivorans, a strain isolatedfor the first time in 2004 from a coal tar contaminated sediment(Jeon et al., 2004), whose genes for naphthalene degradationwere afterwards identified and characterized (Jeon et al., 2006).The Pseudomonas genus is also known to comprise a high numberof degrading strains: in this study the isolate UC7153 had a high ho-mology with Pseudomonas spp. PAMC 25886, a strain with pollutantsdegradation abilities isolated from a glacier cryoconite in theAustrian Alps (Shin et al., 2012), while the other two Pseudomonasisolates from Madaccio also proved a wide metabolic versatility asdetermined by API tests (Supplementary Tables S1 and S2). AnotherMadaccio Glacier isolate (UC7243) was identified as Variovoraxparadoxus, an aerobic β-proteobacterium which has degradationabilities towards several organic xenobiotics such as PAHS, PCBs, ar-omatic sulfonates, trichloroethylene and 2,4-dichlorophenoxyaceticacid (Satola et al., 2013). Other genera represented among the iso-lates are Cryobacterium (UC7234 and UC7241), Janthinobacterium(UC7209 and UC7214), Sphingomonas (UC7208, UC7211, UC7232and UC7247), Arthrobacter (UC7207, UC7210, UC7231) andFrigoribacterium (UC7249), which have all been previously reportedas constituents of bacterial communities from glacier environments(Garcia-Echauri et al., 2011; Miteva et al., 2004; Xiang et al., 2005;Zhang et al., 2007).

5. Conclusions

The present work was conducted with the aim of assessing the bac-terial diversity in two glacier areas at 3200 m a.s.l., one close to a sum-mer ski resort, and the other in a neighboring control area. Samplesclose to the ski-resort had concentrations of PAHs and PCBs, ordersof magnitude higher than the ones usually found in uncontaminatedglaciers because of long-range atmospheric transports, and are thus tobe related with decades of emissions from the nearby ski area. Thelevel of pollutants retrieved in the ice core samples was reflected bythe composition of bacterial community, as determined by culture-dependent and culture-independent approaches. Among 26 isolates,at least 5 of them were identified by phylogenetic analyses as close

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relatives with known xenobiotic-degraders, while other ones alsodisplayed a range of metabolic activities that possibly suggest catabolicactivities towards organic pollutants. Isolation was carried out with arich medium, without relying on organic xenobiotics as sole carbon re-sources: the relatively high proportion of potential xenobiotic degradersretrieved indicates that in these carbon-poor environments the pres-ence of pollutants can strongly drive for the ecological selection ofstrains able to metabolize them. Our results indeed indicate that con-taminated areas in glaciers can be very important reservoirs of bacterialstrainswith potential applications in bioremediation. Further investiga-tions will be important in order to test at different temperatures thedegradation abilities of the isolates towards several organic pollutants,and to confirm at genetic and genomic level the presence of catabolicand cold-adaptation genes.

6. Acknowledgments

We thank the Konsortium National Park Stilfser Joch-ConsorzioParco Nazionale Stelvio for the permission to perform the study in theMadaccio Glacier, and the Director of the SIFAS-Società ImpiantiFuniviari Stelvio, Umberto Capitani, for offering us the support in thetransportation of ice samples and technical equipment.

Appendix A. Supplementary data

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.scitotenv.2014.07.094.

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