bacterial community structure of sediments of the bizerte lagoon (tunisia), a southern mediterranean...
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ENVIRONMENTAL MICROBIOLOGY
Bacterial Community Structure of Sediments of the BizerteLagoon (Tunisia), a Southern Mediterranean CoastalAnthropized Lagoon
Olfa Ben Said & Marisol Goñi-Urriza & Monia El Bour &
Patricia Aissa & Robert Duran
Received: 11 April 2009 /Accepted: 27 August 2009 /Published online: 30 September 2009# Springer Science + Business Media, LLC 2009
Abstract In order to estimate how pollution affects thebacterial community structure and composition of sedi-ments, chemical and molecular approaches were combinedto investigate eight stations around the Bizerte lagoon.Terminal restriction fragment length polymorphism(T-RFLP) analysis of PCR-amplified 16S rRNA genesrevealed that each station was characterized by a specificbacterial community structure. The combination of this datawith those of chemical analysis showed a correlationbetween the bacterial fingerprint and the pollutant content,principally with hydrocarbon pollution. The composition ofthe bacterial community of two contrasted stations relatedto the pollution revealed sequences affiliated to α, β, γ, δ,ε subclass of the Proteobacteria, Actinobacteria, andAcidobacteria in both stations although in different extent.Gamma and delta subclass of the Proteobacteria were
dominant and represent 70% of clones in the heavy-metal-contaminated station and 47% in the polyaromatic hydro-carbon (PAH)-contaminated. Nevertheless, most of thesequences found were unaffiliated to cultured bacteria.The adaptation of the bacterial community mainly to PAHcompounds demonstrated here and the fact that thesebacterial communities are mainly unknown suggest thatthe Bizerte lagoon is an interesting environment tounderstand the capacity of bacteria to cope with somepollutants.
Introduction
Organic and inorganic pollution of coastal zones is a majorubiquitous environmental problem since they can accumu-late in sediments [13]. Nevertheless, the contaminant can betransformed in this environment, principally by bacteria,since they are the most abundant organisms in the sediment[13]. On the opposite, the structure and composition ofmicrobial communities are affected by many differentabiotic and biotic parameters including pollutants compo-nents [35, 44]. Recent studies have demonstrated thatnatural attenuation and bioremediation of organic contam-inants and heavy metals cannot be effectively applied atmany sites until we have a better understanding of thephysiology, ecology, and phylogeny of microbial commu-nities at contaminated sites [42]. In light of these data, weneed to increase our understanding of how microbialcommunities are affected by and interact with thesecompounds in contaminated sites. Recently, fundamentalviews of the capacities of the bacterial communitiesinhabiting marine sediments to cope with pollutants havebeen given [6, 7, 21, 22, 29, 38], but relatively little is
Electronic supplementary material The online version of this article(doi:10.1007/s00248-009-9585-x) contains supplementary material,which is available to authorized users.
O. Ben Said :M. Goñi-Urriza : R. Duran (*)Equipe Environnement et Microbiologie-IPREM UMR5254-IBEAS, Université de Pau et des Pays de l’Adour,Avenue de l’Université, BP 1155, 64013 Pau cedex, Francee-mail: [email protected]
O. Ben Said :M. El BourLaboratoire de Bactériologie–Pathologie, Institut Nationaldes Sciences et Technologies de la Mer INSTM,Salammbô, Tunisia
O. Ben Said : P. AissaFaculté des Sciences de Bizerte, Laboratoire de Biosurveillancede l’Environnement,Zarzouna, Tunisia
Microb Ecol (2010) 59:445–456DOI 10.1007/s00248-009-9585-x
known about bacterial communities in contaminated sedi-ments [1, 11, 12, 18]. Moreover, the combined effect ofdifferent pollutants as polyaromatic hydrocarbons (PAH)and heavy metals on microbial activities and communitycomposition is still unclear since few studies haveaddressed this point [10].
Costal urbanized and industrialized zones have oftenbeen shown to be characterized by the concomitantpresence of organic and inorganic pollutants [11]. Thesecoastal zones provide a good study site for the investigationof microbial communities inhabiting mixed contaminatedsediments. The Bizerte lagoon (Tunisia) is an example ofsuch ecosystem; it is located in an urbanized andindustrialized area subjected to the input of variouspollutants. The discharges of untreated domestic effluentsand wastewater from industries generate heavily pollutedsediments characterized by the concomitant presence ofPAHs, heavy metals, and drugs such as antibiotics [27]. Wepreviously characterized the aerobic PAH-degrading bacte-ria isolated from sediments of different stations locatedwithin the Bizerte lagoon [4]. The present work combineschemical and microbial molecular approaches in order toinvestigate the influence of PAHs and heavy metals
concentrations on microbial community structure andcomposition. First, bacterial T-RFLP fingerprints werecorrelated with pollutant concentrations, and second, thebacterial composition of both the most PAH-polluted andthe most heavy metal-polluted stations were determined by16S rRNA gene libraries analyses.
Materials and Methods
Site Description
Bizerte lagoon (Southern Mediterranean), a canalizedlagoon system located in the Northern of Tunisia (Fig. 1),has been exploited for fishing activities since severalcenturies and for mussel farming since 1964. This areaextends over 150 km2 and constitutes a receptor of severalindustrial sewages, aquaculture wastes, fertilizers, andpesticides through runoff and soil erosion, wastewatersfrom towns implanted around. At least, five differentcontamination sources can be identified in the Bizertelagoon: Menzel Bourguiba-Tinja and Menzel Bourguibalandfill; Bizerte, Menzel Abderahmen, and Menzel Jmil
Mediterranean Sea
Jarzouna
Urban zone
37°16’NUrban zone
Bizerte
Industrial zone
1
2
0
Menzel AbderahmenUrban zone Menzel Jmil
Urban zone
6 Industrialzone
8Bizerte Lagoon
Agricultural zone
9
37°08’N
09°56’E5 Km
10Industrial
zone
09°47’E
Tinja12
Industrial zone
Landfill
Menzel BourguibaUrban zone
TU
NISIA
Figure 1 Map of the Bizerte lagoon indicating the location of the sampling stations (dots). Urban zones (dashed circles), industrial zones (solidcircles), and agricultural zones (little dashed circles) are indicated. The arrows indicate streams
446 O. B. Said et al.
industrial zones; and Southeastern agricultural zone [45].Furthermore, this lagoon is connected to Mediterranean Seathrough of a narrow channel that is exposed to intensivemaritime traffic and indirectly to several pollutants comingfrom oil and steel factories.
Sediment Collection and Field Measurements
Undisturbed surface sediments (0–5 cm depth) werecollected in May 2004 with a Van Veen Grab at eightstations (station nos. 0, 1, 2, 6, 8, 9, 10, and 12) locatedaround the Bizerte lagoon and the bay (Fig. 1). Samplingsites were selected because of the extent of anthropogeniccontamination is different [45]. Water column temperature,pH, and salinity were determined in the field with ahandheld multi-parameter system WTW Multi-197i. Thewater temperature and level of dissolved oxygen weredetermined with a multiparameter probe (YSI GRANT3800). Sediments were sampled, quickly homogenized, andfrozen in liquid nitrogen for both chemical and molecularanalyses. Samples were stored at −80°C until analysis.
Chemical Analysis
Chemical analyses, namely, ammonium (NH4), nitrates(NO3), nitrites (NO2), orthophosphate (PO4), and totalphosphorus (Pt), were performed using standard methods[32]. Chlorophyll a concentrations were obtained byspectrophotometry described in [37].
Heavy metal composition analysis (cadmium, cobalt,copper, lead, manganese, nickel, zinc, chromium) wereperformed according to the NF EN ISO 11885 standardsissued in March 1998 [34]. Sediment samples wereacidified using nitric acid (pH<2), then assays were carriedout with an inductively coupled plasma atomic emissionspectrometer. Heterogeneity of samples was determinedduring the calibration checks of the technique. Thedetection limit was estimated lower than 0.005 mg kg−1
for Cd lower than 0.0002 mg kg−1 for Hg and lower than0.050 mg kg−1 for the rest of heave metals analyzed. Thereliability of the quantitative measurements was checked byanalyzing the Standard Reference sediment Sed.IAEA, 405.The deviation of the measure was below to 10%.
Polycyclic aromatic hydrocarbon analyses in the sedi-ments were conducted by an automated extraction withASE 200 (Accelerated Solvent Extractor-Dionex), extractpurification, and gas chromatography-mass spectrometry.Approximately 30 mg of the samples were purified throughlow-pressure liquid chromatography on an open silica-alumina column. The GC was an HP 6890 N (Hewlett-Packard, Palo Alto, CA, USA) equipped with a split/splitless injector (pulsed splitless time: 1 min, flow50 mL min−1). The injector temperature was maintained at
270°C. The interface temperature was 290°C and the GCtemperature programmed from 50°C (1 min) to 300°C(20 min) at 5°C/min. The carrier gas was Helium at aconstant flow of 1 mL min−1. The capillary column usedwas an HP 5 MS (Hewlett-Packard, Palo Alto, CA, USA)=60 m×0.25 mm ID×0.25 μm film thickness. The GC wascoupled to an HP 5973 mass selective detector (ElectronicImpact: 70 eV, voltage: 1,200 V). Quantification wasperformed using Single Ion Monitoring mode with themolecular ion of each compound at 1.4 cycles s−1.
The reliability of the quantitative measurements waschecked by analyzing the Standard Reference Material1941b “Organics in Marine Sediment” (NIST, Gaithers-burg, Maryland, USA). Perdeuterated PAHs were obtainedfrom LGC Standards (Molsheim, France). Calibration curveswere established from n-alkane and PAH mixtures obtainedfrom LGC Standards (Molsheim, France). These mixturescontain n-alkanes from nC8 to nC32, and with regard toPAHs, all the parent PAHs mentioned in result table.
T-RFLP Analysis
Mixed community DNAwas extracted directly from sedimentsamples using an UltraClean soil DNA isolation Kit (MoBioLaboratories, CA) by following the manufacturer’s protocolwith minor modifications as previously described [36]. Genesencoding 16S rRNA were PCR amplified from extractedsamples using fluorescent-labeled bacterial primers 8F HEX(5-Hexa-chloro-fluorescein; 5′-AGAGTTTGATCCTGGCTCAG-3′, [26]) and 1489R TET (5-Tetrachloro-fluorescein;5′-TACCTTGTTACGACTTCA-3′, [43]). The PCR amplifi-cation mixture contained 12.5 µL Hot Start Taq polymerasemaster mix (Qiagen), 0.5 µL of each primer (20 µM), and10 ng of DNA template. A final volume of 50 µL wasadjusted with distilled water. 16S rRNA gene amplificationreactions were cycled in a PTC200 thermocycler (MJResearch) with a hot start step at 94°C for 15 min, followedby 35 cycles of 94°C for 1 min, 52°C for 1.5 min, and 72°Cfor 1 min, with a final extension step at 72°C for 10 min.
PCR products were purified with the GFX PCR DNApurification kit (Amersham-Pharmacia). Purified PCRproducts (600 to 700 ng) were digested with three units ofenzyme HaeIII (New England Biolabs). The length ofterminal fluorescent-labeled fragments from the digestedPCR products was determined by capillary electrophoresison ABI prism 310, (Applied Biosystems) as previouslydescribed [14]. Briefly, about 50 ng of the digested DNAfrom each sample was mixed with 18.5 µL of deionizedformamide and 0.5 µL of TAMRA size standard (AppliedBiosystems) and then denatured at 94°C for 2 min andimmediately chilled on ice prior to electrophoresis. After aninjection step of 10 s, electrophoresis was carried out for upto 30 min applying a voltage of 15 KV.
Bacterial Communities in Bizerte Lagoon-Polluted Sediments 447
The T-RFLP profiles (T-RFs) were analyzed usingGene Scan Software version 3.1 (Applied Biosystem).Dominant T-RFs were selected by comparison of nu-merical values and electropherograms. Only the T-RFsrepresenting more than 1% of the total fluorescence wereconsidered [19].
T-RFLP profiles were compared by canonical correspon-dence analysis (CCA) using MVSP software (multivariatestatistical package 3.12d, Kovach Computing Services,1985–2001, UK). This test is based on the linear correlationbetween community data (abundance of each T-RF) andenvironmental parameters in the sediments. Linear regres-sion analysis between some T-RFs, and chemical data wasperformed in order to avoid overinterpretation of thecorrelation.
16S rRNA Gene Libraries Analyses and 16S rRNA GeneSequencing and Sequences Analysis
Bacterial composition of the stations 1 and 2 was furtheranalyzed by cloning PCR amplified 16S rRNA genes inEscherichia coli. PCR amplifications from these sampleswere carried out with unlabeled 8F and 1489R primers asdescribed previously [7]. PCR products were purified withthe GFX PCR DNA purification kit (Amersham-Pharma-cia) then cloned in E. coli TOP10 using the Topo-TAcloning kit (Invitrogen). Seventy-three clones from eachlibrary were selected randomly, and inserts were amplifiedusing the primers M13F (5′-CTGGCCGTCGTTTTAC-3′)and M13R (5′-GGTCATAAGCTGTTTCCTG-3′).
Partial sequences of the 16S rRNA gene weredetermined by the dideoxy nucleotide chain-terminationmethod using the BigDye cycle sequencing kit (AppliedBiosystems) on an ABI PRISM 310 205 Geneticanalyzer (Applied Biosystems) at the Génotypage-Séquençage de Bordeaux (France) using the primersM13F and M13R.
DNA sequences were compared to those present in thedatabank via the NCBI server (http://www.ncbi.nlm.nih.gov) using the basic local alignment search tool (BLAST)[2]. Sequence data were checked using the CHECKCHIMERA program (http://rdp8.cme.msu.edu/html/) todetermine the presence of hybrid sequences [30]. Nucleo-tide sequences were initially aligned with the ribosomaldatabase project (RDP) database [30] by means of theautomatic alignment function of the RDP phylogenyinference package interface, after sequences were manuallyaligned using ClustalW [41]. The phylogenetic tree wasconstructed with the MEGA software version 3.0 [25] usingNeighbor-Joining method [39]; the distance was calculatedon the basis of Kimura’s two-parameter algorithm [24]; 100bootstrap resamplings were performed to estimate thereproducibility of the tree.
Paleontological Statistics v1.60 software from http://folk.uio.no/ohammer/past/ website was used to perform rarefac-tion analysis and calculate diversity indices for each clonelibrary with clone phenotype identity defined at 97%. Inorder to determine the significance of differences betweenthe clone libraries, LIBSHUFF method was applied [40].
Nucleotide Sequence Accession Numbers
The sequences determined in this study have beensubmitted to the GenBank database and assigned AccessionNos. AM889144 to AM889146, AM889150, AM889157 toAM889198, AM889201 to AM889204, FM211753 toFM211808, and FM211815 to FM211816.
Results
Physicochemical Parameters and Metals and PAHConcentrations in Bizerte Lagoon’s Sediments
The physical and chemical parameters observed in thesampling stations are summarized in Table 1. The channelstations 0, 1, 2 and, in less extent, 6, are submitted to themarine influence with lower temperature and highersalinities. Channel station showed lower O2 concentrations.
Total heavy metal contents varied from 222 (station 9) to1,709 mg kg−1 of dry weight sediment (station 10; Table 1).Whatever the station investigated, magnesium and zincwere dominant (data not shown). Station 2, located in thechannel, showed the second high score for metals contents,mainly contaminated with magnesium, zinc, and chrome(respectively, 397, 322, and 163 mg kg−1 of dry weightsediment).
Total PAH concentrations in the coastal sedimentsranged from 24 (station 8, Southeast zone) to 877 (station1, channel) µg kg−1 dry weight sediment (Fig. 2a andTable 1). Two different PAH concentration profiles weredistinguished: stations 1, 2, and 6 were more contaminatedby high molecular weight PAHs (H PAH, mainly fluoran-thene, pyrene, and benzo(a)pyrene for stations 1 and 2 andfive aromatic rings PAHs for station 6) whereas station 12,10, 8, 9, and 0 where mainly contaminated by lowmolecular weight PAHs (L PAH) such as naphthalene (datanot shown). The unexpected high L PAH/H PAH ratiofound in station 8 is due to a hardly absence of PAHs ofhigh molecular weight.
Bacterial Community Structures
The T-RFLP profiles contained 25±7.5 T-RFs defined asribotypes. The lowest ribotype number (14) was observedin station 0 which is located at the channel entrance with
448 O. B. Said et al.
the Mediterranean Sea subjected to both marine and lagooninfluences. In contrast, the highest ribotype number (37)was recorded in station 12. No clear relationship could beestablished between the number of ribotypes and thepollution level, even if the higher number of ribotypeswere found in the stations showing low level of contam-ination (stations 12 and 8, Table 1, Fig. 2a).
The T-RFs of 73, 192, 204, and 206 bp were detected in allthe stations (Fig. 2b). Whereas most of them showed a lowrelative abundance, the T-RF 204 bp is the more abundant inall the stations except for station 1. It represents up to 60% oftotal fluorescence in station 9. In contrast, some T-RFs werestation-specific such as T-RFs of 36 to 37 bp (station 1),49 bp (station 2), 56 bp (station 0), 114, 120, 127, 186,209 bp (station 8), 110, 111, 215, 259, 388, 399 bp (station12), 227, 290, 291 bp (station 10). Except for T-RF 36 bp instation 1 which is dominant, all of them were low abundant.Some T-RFs (such as 204, 256 bp, and others) have alsobeen detected (after in silico digestion of their 16S rRNAgenes) in strains isolated from the stations. These strains,belonging to the Pseudomonas or Acinetobacter genera,have been described as hydrocarbonoclastics [4].
CCA of the T-RFLP fingerprints correlated with somephysical and chemical parameters (Fig. 3) showing that thebacterial community in station 1 was highly influenced byPAHs contents. Stations 9 and 6 were influenced by NO3
concentrations while station 12 was the least impacted bythis pollutant. Station 2 was mainly influenced by NO3,PO4, and heavy metals. Distribution of T-RFs according tothese parameters is shown in Supplementary Data (Fig. S1).
The T-RFLP fingerprints correlated by CCA with thedifferent PAH molecules (Fig. 4) showed that the sedimentbacterial community of station 1 was influenced by all thePAHs analyzed (Fig. 4, insert). To observe the influence ofthe PAH content on the bacterial community structure ofthe other stations, data concerning the station 1 wasexcluded. In this condition, the first two axes of the CCAdescribed 48.2% of the variation (Fig. 4; axis 1, 25.5% andaxis 2, 22.7%). The bacterial community structures ofstations 6 and 9 were mostly influenced by fluorine,dibenzanthracene, and benzoperylene while those of sta-tions 0, 2, and 10 by fluoranthene and pyrene (Fig. 4). Incontrast, bacterial community structures of stations 8 and12 were not influenced by PAH contents (Fig. 4). Ribotypes73 and 74 bp were positively correlated with the totalcontents of PAH (respectively, R2 of 0.72 and 0.93),whereas ribotype 204 bp was negatively correlated. Also,the ribotype 256 bp, detected in stations 6 and 9, wasmostly influenced by fluorine, dibenzanthracene, andbenzoperylene (see Supplementary Data, Fig. S2).
The impact of heavy metals in the bacterial communitystructure could be observed in stations 8 and 10, whichwere mainly influenced by Mn and Co, and stations 1 andT
able
1Phy
sicochem
ical
parametersof
thestations
locatedarou
ndtheBizerte
lago
on
Statio
nLocation
Depth
(m)
T(°C)
S(psu)
SM
(gm
−3)
O2(gm
−3)
NO2(m
gm−3)
NO3(m
gm−3)
NH4(m
gm−3)
Nt(m
gm−3)
PO4(m
gm−3)
Pt(m
gm−3)
Chla(m
gm−3)
PAHt(µgg
−1)
Metalst(m
gkg−
1)
037°15.452′
N11
21.6
3620
5.5
11.69
308
180
235
4.4
30554
9°51.821
′E
137°14.600′
N11
21.8
36.3
185.5
13.13
26.96
11.94
208.36
11.19
47.21
4.12
877
425
9°50.420
′E
237°14.000′N
1121.9
3611.89
5.5
3.43
45.34
14.01
219.73
18.84
41.57
5.00
340
1065
9°49.400
′E
637°12.460′
N7.5
22.3
35.7
208.3
5.81
37.33
6.77
178.01
1.05
35.83
4.56
91453
9°55.790
′E
837°11.040′
N1.5
23,3
34.2
809.1
7,35
13.67
9.42
227.31
1241,85
4.95
24649
9°55.790
′E
937°09.770′
N3.9
2334.5
807
13.5
359
135
1230
5.1
38222
9°54.893
′E
1037°08.480′
N3
23.1
34.6
656.5
1040
18135
1237
5.4
110
1709
9°49.400
′E
1237°11.042′
N3
22.2
33.7
187.1
6.21
4.49
8.31
200.77
12.4
41.57
5.23
54395
9°47.313
′E
T,S,SM,O2,NO2,NO3,NH4,Nt,PO4,Pt,Chla,
PAHt,andMetalstweredeterm
ined
ineigh
tsitesof
Bizerte
lago
on(M
ay20
04)
Ttemperature,Ssalin
ity,SM
suspendedmatter,O2dissolvedox
ygen,NO2nitrites,NO3nitrates,NH4am
mon
ium,Nttotalnitrog
en,PO4orthop
hosphate,Pttotalph
osph
orus,Chlachloroph
yll,
PAHttotalPA
H,Metalsttotalheavymetals
Bacterial Communities in Bizerte Lagoon-Polluted Sediments 449
0, influenced, respectively, by Cd and Pb (data not shown).Despite the high concentrations of heavy metals in station2, no clear influence of a specific metal in the communitystructure of this station could be characterized. Further-more; no OTU could be associated by the regressionanalysis with a particular heavy metal, neither with thetotal heavy metal content (data not shown).
Bacterial Community Composition of Sedimentsfrom Stations 1 and 2
The bacterial community composition of the channelstations 1 and 2 were determined in order to evaluate theimpact of pollutants on the bacterial diversity. Thesestations were chosen because (1) they are both channel
0
0,5
1
1,5
2
2,5
3
3,5
4
9
0
100
200
300
400
500
600
700
800
900
1000
10 9 12 8 6 2 1 00
10
20
30
40
50
Total PAHs
0
500
1000
1500
2000
0
0,5
1
1,5
2
2,5
3
3,5
4
9
Tot
al P
AH
s (µ
g. k
g-1 dr
y w
eigh
t)0
100
200
300
400
500
600
700
800
900
1000
10 9 12 8 6 2 1 00
10
20
30
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50
0
10
20
30
40
50
L.PAHs/H.PAHs Ribotype number Total HM
0
500
1000
1500
2000
0
500
1000
1500
2000T
otal Heavy M
etals (mg. kg
-1 dry weight)
Ribotype num
ber
Low
PA
Hs
/Hig
h PA
Hs
Outdistance Mediterranean Sea
ChannelLagoon
A
B
Figure 2 Bacterial communitystructure analysis of Bizerte la-goon sediments. A Number ofribotypes in each station, totalPAH contents (µg kg−1 dw),total heavy metal contents(mg kg−1 dw), and low molecu-lar weight PAHs/high molecularweight PAHs ratio (LPAHs/HPAHs) are also indicated. BRelative abundance of T-RFs foreach station from T-RFLP pat-terns obtained by HaeIII diges-tion of 16S rRNA-amplifiedfragment
31 % 0
1
2
6
8
9
10
12
-0.6
-1.3
-1.9
-2.5
0.6
1.3
1.9
2.5
3.2
-0.6-1.3 -1.9 -2.5 0.6 1.3 1.9 2.5 3.2
Total Heavy Metals
Total PAHs
SalinitySM O 2
PO4
NO 3
21 %
31 % 0
1
2
6
8
9
10
12
-0.6
-1.3
-1.9
-2.5
0.6
1.3
1.9
2.5
3.2
-0.6-1.3 -1.9 -2.5 0.6 1.3 1.9 2.5 3.2
Total Heavy Metals
Total PAHs
SalinitySM O 2
PO4
NO 3
21 %
Figure 3 CCA betweensediment bacterial communitiescharacterized by T-RFLP fin-gerprints and some physical–chemical parameters: suspendedmatter (SM), dissolved oxygen(O2), nitrates (NO3), phosphates(PO4), Salinity, Total PAHs, andTotal Heavy Metals
450 O. B. Said et al.
stations and their sediments have relatively similar physi-cochemical parameters (Table 1); (2) they are under theinfluence of PAH at different levels, station 1 being muchmore contaminated (Fig. 2a); and (3) the station 2 is thechannel station that is more contaminated with metals(Table 1). 16S rRNA gene library analysis of the stations 1and 2 was performed in order to determine the compositionof the bacterial communities. From the 73 clone sequencesanalyzed by library, 63 (47 singletons) and 69 (55 single-tons) phylotypes were found in library of stations 1 and 2,respectively. Shannon index was quite similar for bothlibraries (4.22 and 4.28 for library 1 and 2, respectively) andequitability was identical (0.97) indicating a high bacterialdiversity in both stations. No species (cutoff level of <97%identity) were found to be dominant as indicated by lowDominance indexes (1.73% for library 1 and 1.68% for library2). Although the libraries share some common sequences(28% and 41% for libraries 1 and 2, respectively, according tothe 97% identity cutoff), a comparison of the libraries with theLIBSHUFF method revealed that they were composed of
significantly different phylotypes (XY p=0.001; YX p=0.004, with a confidence of 99% (p=0.01)).
The phylogenetic analysis of the clone sequencesrevealed their distribution within six major taxonomicgroups of prokaryotic organisms (Fig. 5). Sequencesaffiliated to α, β, γ, δ, ε subclass of the Proteobacteria,to the phyla of Actinobacteria and Acidobacteria weredetected in both libraries, though in different extent.Sequences affiliated to the phyla of Nitrospirae andVerrucomicrobia were detected only in library 2. Neverthe-less, about 80% (library 1) and 90% (library 2) of the totalsequences could not be closely related to cultured organ-isms or already known sequences suggesting that they mayconstitute new taxa (Fig. 6). About 15% of the totalsequences in library 1 and 6% of the total sequences inlibrary 2 were closely related to 16S rRNA sequences ofunknown bacteria. The library 1 was dominated bysequences related to γ-Proteobacteria (31% of the sequen-ces), and 3% of these sequences were related to 16S rRNAsequences of identified species such as Pseudomonas sp.,
2
12
81
6
10
9 -1.06
5.31
-1.06 5.31
N
ANYF
PAFLPYC
BABBF+BkFBAP
INDBABPE
34.7 %
17.7 %
ANA
2
12
8
6
10
9
0
-1.06
5.31
-1.06 5.31ANYF
PAFLPYC
BABBF+BkFBAP
INDBABPE
34.7 %
17.7 %
ANA
2
12
81
6
10
9 -1.06
5.31
-1.06 5.31
N
ANYF
PAFLPYC
BABBF+BkFBAP
INDBABPE
34.7 %
17.7 %
ANA
2
12
8
6
10
9
0
-1.06
5.31
-1.06 5.31ANYF
PAFLPYC
BABBF+BkFBAP
INDBABPE
34.7 %
17.7 %
ANA
2
12 8
6
10
9
0
-0.4
-0.8
-1.1
0.4
0.8
1.1
1.5
1.9
-0.4-0.8-1.1 0.4 1.1 1.5 1.9
N
ANY
ANA
F
P
A
FL
PY
CBA
BBF+
BkFBAP
IN
DBA
BPE
22.7%
25.5 %
2
12 8
6
10
9
0
-0.4
-0.8
-1.1
0.4
0.8
1.1
1.5
1.9
-0.4-0.8-1.1 0.4 1.1 1.5 1.9
N
ANY
ANA
F
P
A
FL
PY
CBA
BBF+
BkFBAP
IN
DBA
BPE
22.7%
25.5 %
Figure 4 CCA between sedi-ment bacterial communitiescharacterized by T-RFLP fin-gerprints and individual PAHconcentrations. All stations arerepresented in the insert figure.The main figure represents allthe station, except station 1. NNaphthalene; ANY Acenaphty-lene; ANA Acenaphtene; FFluorine; P Phenanthrene; AAnthracene; FL Fluoranthene;PY Pyrene; C Chrysene; BABenzo(a)anthracene; BBF+BkFBenzo[b+k]fluoranthene;BAP Benzo(a)pyrene; IN Indeno(1,2,3-)pyrene; DBA Dibenzo(a,h)anthracène; BPE Benzo(g,h,i)perylene
Bacterial Communities in Bizerte Lagoon-Polluted Sediments 451
Pseudomonas lanceolata, Legionella pneumophila, Acine-tobacter sp. (Fig. 6). Library 2 was characterized by the co-dominance of δ- and γ-Proteobacteria (38% and 37%,respectively; Fig. 5). Numerous sequences in the librarieswere related to sequences previously found in organic andinorganic contaminated sediment. Indeed, the main phylo-type, representing 6.1% and 12.4% of libraries 1 and 2,respectively, is affiliated within the γ-Proteobacteria andrelated to uncultured clones obtained from polluted envi-ronments, heavy metal-rich and/or organic-rich, originatedfrom harbor sediments, marine sediments, or fish farmsediments [5, 15, 46].
Several 16S rRNA gene sequences could be relatedto T-RFLP’s ribotypes by predictive digestions (data notshown). Both molecular methods revealed the samedominant populations, i.e., clones sequences with an insilico digestion size of 204 bp, which is the dominantT-RF in T-RFLP analysis. BLAST analysis of thesequence of these clones having an in silico T-RF of204 affiliated them to γ-Proteobacteria, most of themuncultured strains.
Discussion
The impact of environmental and pollutant variables onsediment microbial communities was studied at eightdifferent stations located in a Southern Mediterraneanlagoon. Considering hydrological and trophic conditions,this ecosystem was divided into two zones: (1) the channel(stations 0, 1, and 2) and (2) the lagoon itself (stations 6, 8,9, 10, and 12). Such a division is attributed to the presenceof inflow streams among which, the Tinja wadi is the mostimportant [20]. The same division could also be observedconsidering the PAH contents in sediments (from 24 to877 ng/g dw), the channel stations being the most
contaminated. T-RFLP analysis revealed differences be-tween the microbial community structures. The lowestbacterial diversity was observed in the station closer to theMediterranean Sea (14 ribotypes, station 0) subjected toboth marine and lagoon influences and showing highestsalinity. In contrast, the highest bacterial diversity wasrecorded in station 12 (37 ribotypes) that shows lowestsalinity, low PAH-levels and that receives Tinja wadieffluent in wet season, when the samples were taken.Microbial diversity was shown to vary along gradients suchas salinity [16], pollution [20], and other parameters [11,14]. The bacterial community structure was correlated withthe PAH content allowing the identification of specificribotype. For example, ribotype of 256 bp wasfound specifically in fluorine-, dibenzanthracene-, andbenzoperylene-contaminated station. Interestingly, this ribo-type could correspond to Acinetobacter sp. and strainsbelonging to this genus (and having a predictive restrictionsize of 256 bp) have been previously isolated from Bizertelagoon sediment for their capacity to degrade PAHs [4].
The stations 1 and 2 showed similar physicochemicalparameters and different PAH and metal contaminationlevels. The comparison of their composition would revealthe effect of contaminants on the bacterial communitystructure. Comparison of 16S rRNA gene library analysisof these stations revealed clear differences between thebacterial community compositions with high diversity inbacterial community inhabiting superficial sediment ofstation 2. A considerable number of singletons in thecomposition of the two rRNA gene libraries were observed,and the majority of phylotypes detected were not closelyrelated to any cultivated representatives. These results are inaccordance with previous observations reported in marineenvironmental sequence analysis [20]. We observed mainlyphylotypes affiliated with α-, β-, γ-, δ-, ε-Proteobacteria.In addition, phylotypes related to the phyla of Actino-
24.6%
21.92%
13.7%
5.48%
12.33%
10.96%
2.74%
34.25%
34.25%
6.85%
1.37%
5.48%
4.11%
1.37% 1.37%
γ –Proteobacteria δ–Proteobacteria β-Proteobacteria ε– Proteobacteria
Acidobacteria Actinobacteria
α-Proteobacteria
Library 1 Library 2
Planctomycetacia Verrucomicribia
4.11%
6.85%
Unknown bacteria
8.22%
Figure 5 Repartition of clonesequences in representativephylogenetic groups detected on16S rRNA gene libraries ofstations 2 and 1 of Bizertelagoon sediment
452 O. B. Said et al.
bacteria and Acidobacteria were also detected. Members ofthese phyla are commonly found in less permeable sedi-ments of Seas and estuaries [28]. Numerous sequences inthe libraries are related to sequences of bacteria that werepreviously found in heavy metal and hydrocarbon-contaminated sediments [5, 8, 17, 20]. The libraries weredominated by sequences related to γ- and δ-Proteobacteria;however, α-Proteobacteria-related sequences are less abun-dant. This is typically observed in marine microbialcommunities [9]. Previous research showed that themicrobial community structure in a long-term mixedwaste-contaminated site might reflect both metal andaromatic hydrocarbon concentrations [33]. The dominanceof γ-Proteobacteria-related bacteria in PAH-contaminated
sediments is not unexpected since rapid and strongselection for γ-Proteobacteria have been reported in oil-treated microcosms [7], in oil-contaminated marine sedi-ments [18, 35], and after oil-spill accident [23]. Moreover,75% of PAHs degrading strains isolated from the Bizertelagoon in a previous study were γ-Proteobacteria [4]. Bycloning and sequencing, we detected clones affiliated toAcinetobacter sp. Interestingly, we have isolated strainsaffiliated to the same genus capable of fluoranthene andpyrene mineralization [4]. They were also resistant to heavymetals (Zn, Pb, Co, Cr, and Ni) and to antibiotics (variousaminosides and β-lactam molecules) [4]. Their relativeabundance associated with their metabolic capacitiesindicates the possible role of strains of this genus in in situ
Sulfurimonas denitrificans (L40808)100
100
100
87
100
100
100
92
100
51
100
61
90
99
100
100
67
89
83
99
58
76
89
53
77
77
66
100
100
96
70
98
100
52
53
58
57
99
89
82
100
99
85
9073
86
83
53
50
59
51
0.02
1 (1.37%); 2 (1.37%)*Comamonas testosteroni (M11224)
Iodobacter fluviatilis (M22511)Achromobacter group
1 (1.37%)Burkholderia group
Nitrosomonas oligotropha (AF272422)Gallionella ferruginea (L07897)
Stenotrophomonas acidaminiphila (AF273080)1 (4.11%); 2 (2.74%)*
2 (1.37%)Beggiatoa alba (AF110274)
1 (8.22%); 2 (16.44%)* 1 (1.37%)
Pseudomonas groupEnterobacter group
Alteromonadales groupsMarinobacter group
Marinomonas mediterranea (AF063027)1 (1.37%)
Acinetobacter group2 (2.74%)
Oceanospirillum beijerinckii (AB006760)1 (1.37%); 2 (1.37%)
Halomonas nitritophilus (AJ309564)Alcanivorax borkumensis (Y12579)
1 (1.37%); 2 (5.48%)*Methylomicrobium pelagicum (X72775)
1 (1.37%); 2 (1.37%)*
Thiothrix nivea (L40993)1 (2.74%)
1 (1.37%)Legionella pneumophila (M59157)
1 (1.37%); 2 (2.74%)Rhodospirillum rubrum (D30778)
Magnetite containing magnetic vibrio (L06455)Rickettsia prowazekii (M21789)
Sphingomonas group1 (2.74%)
Bradyrhizobium elkanii (U35000)1 (1.37%); 2 (2.74%)*
1 (1.37%); 2 (1.37%)Agrobacterium tumefaciens (DQ468100)
1 (2.74%)2 (1.37%)Rhizobiales groups
1 (2.74%); 2 (1.37%)
1 (2.74%); 2 (4.11%)Desulfonatronum lacustre (AF418171)
Desulfovibrio halophilus (U48243)1 (1.37%); 2 (2.74%)
Geobacter metallireducens (L07834)2 (1.37%)Pelobacter carbinolicus (X79413)
1 (4.11%); 2 (1.37%)*Desulfosarcina variabilis (M26632)
1 (2.74%)2 (1.37%)
Desulfococcus multivorans (AF418173)2 (1.37%)
Desulfobacterium anilini (AJ237601)2 (2.74%)
Desulfonema ishimotoei (U45992)Desulfobacca acetoxidans (AF002671)
1 (6.85%); 2 (5.48%)*Syntrophobacter sp. (X94911)
2 (2.74%)Desulfobulbus elongatus (X95180)
Desulfotalea arctica (AF099061)Desulfocapsa thiozymogenes (X95181)
Desulforhopalus vacuolatus (L42613)1 (4.11%); 2 (10.96%)*
1 (5.48%); 2 (2.74%)*Helicobacter baculiformis (EF070342)
Helicobacter nemestrinae (AF348617)1 (2.74%)
Campylobacter fetus subsp. fetus (DQ174128)2 (1.37%)
Candidatus Arcobacter sulfidicus (AY035822)Arcobacter cryaerophilus (L14624)
1 (1.37%)
Psychrobacter marincola (AY292940)
-Proteobacteria
-Proteobacteria
-Proteobacteria
-Proteobacteria
-Proteobacteria
Desulfobacter group
1 (1.37%)
Sulfurimonas denitrificans (L40808)100
100
100
87
100
100
100
92
100
51
100
61
90
99
100
100
67
89
83
99
58
76
89
53
77
77
66
100
100
96
70
98
100
52
53
58
57
99
89
82
100
99
85
9073
86
83
53
50
59
51
0.02
1 (1.37%); 2 (1.37%)*Comamonas testosteroni (M11224)
Iodobacter fluviatilis (M22511)Achromobacter group
1 (1.37%)Burkholderia group
Nitrosomonas oligotropha (AF272422)Gallionella ferruginea (L07897)
Stenotrophomonas acidaminiphila (AF273080)1 (4.11%); 2 (2.74%)*
2 (1.37%)Beggiatoa alba (AF110274)
1 (8.22%); 2 (16.44%)* 1 (1.37%)
Pseudomonas groupEnterobacter group
Alteromonadales groupsMarinobacter group
Marinomonas mediterranea (AF063027)1 (1.37%)
Acinetobacter group2 (2.74%)
Oceanospirillum beijerinckii (AB006760)1 (1.37%); 2 (1.37%)
Halomonas nitritophilus (AJ309564)Alcanivorax borkumensis (Y12579)
1 (1.37%); 2 (5.48%)*Methylomicrobium pelagicum (X72775)
1 (1.37%); 2 (1.37%)*
Thiothrix nivea (L40993)1 (2.74%)
1 (1.37%)Legionella pneumophila (M59157)
1 (1.37%); 2 (2.74%)Rhodospirillum rubrum (D30778)
Magnetite containing magnetic vibrio (L06455)Rickettsia prowazekii (M21789)
Sphingomonas group1 (2.74%)
Bradyrhizobium elkanii (U35000)1 (1.37%); 2 (2.74%)*
1 (1.37%); 2 (1.37%)Agrobacterium tumefaciens (DQ468100)
1 (2.74%)2 (1.37%)Rhizobiales groups
1 (2.74%); 2 (1.37%)
1 (2.74%); 2 (4.11%)Desulfonatronum lacustre (AF418171)
Desulfovibrio halophilus (U48243)1 (1.37%); 2 (2.74%)
Geobacter metallireducens (L07834)2 (1.37%)Pelobacter carbinolicus (X79413)
1 (4.11%); 2 (1.37%)*Desulfosarcina variabilis (M26632)
1 (2.74%)2 (1.37%)
Desulfococcus multivorans (AF418173)2 (1.37%)
Desulfobacterium anilini (AJ237601)2 (2.74%)
Desulfonema ishimotoei (U45992)Desulfobacca acetoxidans (AF002671)
1 (6.85%); 2 (5.48%)*Syntrophobacter sp. (X94911)
2 (2.74%)Desulfobulbus elongatus (X95180)
Desulfotalea arctica (AF099061)Desulfocapsa thiozymogenes (X95181)
Desulforhopalus vacuolatus (L42613)1 (4.11%); 2 (10.96%)*
1 (5.48%); 2 (2.74%)*Helicobacter baculiformis (EF070342)
Helicobacter nemestrinae (AF348617)1 (2.74%)
Campylobacter fetus subsp. fetus (DQ174128)2 (1.37%)
Candidatus Arcobacter sulfidicus (AY035822)Arcobacter cryaerophilus (L14624)
1 (1.37%)
Psychrobacter marincola (AY292940)
δ -Proteobacteria
ε -Proteobacteria
α -Proteobacteria
γ -Proteobacteria
β -Proteobacteria
Desulfobacter group
1 (1.37%)
aFigure 6 16S rRNA-basedphylogenetic reconstructionshowing the affiliation of Aproteobacteria clone sequencesand B nonproteobacteria clonesequences obtained from thesediments of stations 1 and 2 ofBizerte lagoon (in bold) withselected reference sequences.Percentages of 1,000 bootstrapresampling that supported thebranching orders in each analy-sis are shown above or near therelevant nodes (only values upto 50% are shown). The scalebar represents 2% estimatedsequence divergence. In brack-ets: percentage represented byeach sequence related to thetotal analyzed clones for eachlibrary. Asterisk phylotypes(sequences with similaritieshigher than 97%) presents inboth libraries. Accession numb-ers are A library 1:AM889157to AM889198; toAM889159; AM889201to AM889204; AM889144to AM889146; AM889150;FM211816 and FM211788.Library 2: FM211753 to FM211777; FM211779 toFM211808; FN424387FN424390; FN424394;AM889192. b Library 1:AM889146; AM889148;AM889149; AM889151to AM889156; AM889200;FN428746; FN424396. Library2: FN424385; FN424386;FN424388; FN424389;FN424391; FN424392;FN424395; FN424397;FN424398
Bacterial Communities in Bizerte Lagoon-Polluted Sediments 453
biodegradation of these pollutants. In the previous study,we also isolated other hydrocarbonoclastic strains, mainlyaffiliated to the Pseudomonas genus [4] that we could notdetect in this study by library analysis but that we detect byT-RFLP analysis. These strains presented different capaci-ties of hydrocarbon degradation, most of them degradepreferentially the low molecular weight PAH, but somewere able to degrade pyrene more efficiently than phenan-threne, suggesting different ways of degradation. Some ofthem were resistant to the seven heavy metal tested andwere resistant to antibiotics [4].
Sediments of the most heavy-metal contaminated station(station 2) were dominated by δ-Proteobacteria-affiliatedsequences followed by γ-Proteobacteria. Numerous δ-Proteobacteria phylotypes were related to both sulfuroxidizers and sulfate reducers suggesting an active sulfurcycle in the sediments as usually found in sea sediments[20, 35]. Interestingly, δ-Proteobacteria-related sequenceshave been observed as predominant in sediments contam-inated with multiple pollutants (Hg, PAHs, and PCBs [12]).Nevertheless, Cordova-Kreylos and coworkers [11] foundthat metals had a greater effect on microbial communitycomposition than organic pollutants.
Sequences affiliated to β-Proteobacteria were detectedin both stations in low abundance (4% and 1%) as
reported in other studies of marine sediments [3, 8, 31].Since β-Proteobacteria-related phylotypes are knownto play a critical role in ecosystem function, Hunterand coworkers [20] hypothesized that the lack of β-Proteobacteria-related phylotypes is believed to be theresult of the lowest detection limits of these taxa ratherthan their absences.
In conclusion, our results revealed bacterial communitystructure differences along Bizerte lagoon sediments. Weshowed the influence of pollutants on bacterial communitystructure, which is clearly observed by the quantity and thetype of PAHs and to a lesser extent by some heavy metals.Strong relationships were observed between individual-PAH concentrations and some ribotypes. Clone librariesanalysis for two most contaminated PAHs and metalsediment stations have demonstrated significant differencesin bacterial community compositions, gamma proteobacte-rial phylotypes dominated the most PAH-polluted stationand delta and gamma proteobacterial phylotypes the mostmetal-polluted station. However, both libraries were dom-inated by sequences affiliated with uncultured bacteria.Future research might focus on in situ activity level of theγ-Proteobacteria, δ-Proteobacteria in order to determine ifthese groups play a role in the biotransformation of thepollutants.
Verrucomicrobia
Actinobacteria
Acidobacteria
Planctomycetacia
AB015546 Unidentified bacterium
100
60
61
41
95
79
73
91
56
90
74
43
39
97
100
95
52
94
29
31
97
87
82
51
55
38
59
26
33
33
24
43
6
11
39
0.02
X89560 Candidatus Microthrix
Z95733 Uncultured Acidobacteria bacterium X77215 Holophaga foetida DSM 6591T
AF050560 Uncultured eubacterium WCHB1-41
X94145 Nocardioides sp.M37200 Aeromicrobium erythreum
X77439 Rathayibacter rathayi
AF382139 Uncultured bacterium
AF424323 Uncultured bacterium MERTZ_21CM_220
Z95718 Holophaga/Acidobacterium phylum
X62910 Planctomyces marisL10942 Unidentified marine eubacterium
AJ241004 Uncultured Holophaga/Acidobacterium Sva0515
AF507898 Uncultured Verrucomicrobia bacterium clone ML623J-15
AY114335 Uncultured Verrucomicrobia bacterium clone LD1-PB3
AJ231183 Pirellula staleyi (strain DSM 6068T)X62912 Blastopirellula marina DSM 364
X54522 Gemmata obscuriglobus
1 (1.37%); 2 (1.37%)
1 (2.74%)1 (1.37%)
2 (1.37%)
2 (1.37%)1 (1.37%)
1 (1.37%); 2 (1.37%)1 (2.74%)
2 (1.37%)
2 (1.37%)
1 (1.37%)1 (2.74%); 2 (2.74%)
2 (1.37%)
1 (1.37%)
b
Fig. 6 continued.
454 O. B. Said et al.
Acknowledgments This research was supported by the Tunisian“Ministère de la Recherche Scientifique, de la Technologie et duDeveloppement des Competences” (MRSTDC). We acknowledge thefinancial support of the Conseil Régional d’Aquitaine and the ConseilGénéral des Pyrénées Atlantiques. Sequencing experiments presentedin the present publication were performed at the Genotyping andSequencing facility of Bordeaux (grants from the Aquitaine RegionalGovernment Council no. 20030304002FA and 20040305003FA andfrom the European Union, FEDER no. 2003227).
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