Marine Biology

, Volume 146, Issue 1, pp 133–142 | Cite as

Phylogenetic diversity of Archaea in prawn farm sediment

  • Peng Shao
  • Yueqin Chen
  • Hui Zhou
  • Lianghu Qu
  • Ying Ma
  • Heyang Li
  • Nianzhi Jiao
Research Article


The structure and diversity of the Archaea collected from prawn farm sediment were investigated for the first time. A partial 16S ribosomal DNA library was constructed with Archaea-specific primers. Subsequently, 80 randomly selected archaeal clones from the library were analyzed by restriction fragment length polymorphism (RFLP), and resulted in 50 different RFLP patterns. Sequence analysis of representatives from each unique RFLP type revealed high diversity in the archaeal populations, and the majority of archaeal clones were either members of novel lineages or most closely related to uncultured clones. In the phylogenetic analysis, the archaeal clones could be grouped into discrete phylogenetic lineages within the two kingdoms Crenarchaeota and Euryarchaeota. Euryarchaeota dominated in our archaeal library, with up to 72.2% of the total clones, and Crenarchaeota represented 27.8%. Of all the Euryarchaeota clones, three clones (5.6%) were affiliated with Methanosarcinales, four clones (7.4%) were related to Methanomicrobiales, three clones (5.6%) were related to Halobacterium (with 93% similarity), and the remaining clones (81.5%) were related to those uncultured Euryarchaeota in the aquatic sediment ecosystem. None of the crenarchaeal clones were associated with any known cultured lineages. The selective dispersal of the archaeal population indicates that their ecological niches are associated with environmental characteristics. Novel phylotypes of Archaea would expand our understanding of the genetic diversity of Archaea in aquatic sediment systems and would be significant in the phylogenetic study of Archaea.


Due to the favorable climate and availability of space, shrimp aquaculture has quickly developed, mainly in tropical and subtropical coastal lowlands (Paez-Osuna 2001). Large amounts of compounds are used in aquaculture operations, including additives in artificial feed, such as immunostimulants, disinfectants, antibiotics, algaecides, and herbicides, which are introduced to increase the resistance to infectious disease (Chou et al. 2002) and, thus, the output of prawns (Boyd and Massaut 1999). Studies have also shown that the pond sediment of prawn aquacultural areas is enriched in organic matter (Maguire and Allen 1986; Boyd 1990, 1992; Pillay 1992; Smith 1993; Hopkins et al. 1994), due mainly to the overuse of nutrients. Therefore, prawn farms (pond sediment) are usually considered eutrophic ecosystems. The black sediment, which accumulates on the bottom of ponds, is a major concern for both the industry and the environment (Boyd 1992; Pillay 1992; Smith 1993; Hopkins et al. 1994). The anthropogenic inputs may affect the natural microbial composition and activity, and thereby change the ecological structure of the microbial communities. The accumulation of toxic components (DDT and heavy metal) in pond sediment can lead to a decrease in microbial biodiversity or inhibit microbial activity in the sediment (Han et al. 1999; Gräslund and Bengtsson 2001).

As expected, microorganisms play an important role in the dynamics of sediment environments, particularly in biogeochemical cycles, biodegradation, and food webs (Nedwell 1984; Leahy and Colwell 1990). Investigations on the composition of microbial communities are an important step in understanding the role of bacterial and archaeal populations in biogeochemical processes. Therefore, the biodiversity of sediment microbial communities draws great interest in microbiological and ecological studies. Of the three major evolutionary domains of life on earth, Archaea are the least well understood in terms of diversity (Vetriani et al. 1998), especially the archaeal diversity in sediment communities. This lack of knowledge is, for the most part, due to the limitations of standard cultivation procedures. Ward et al. (1992) reported that >90% of the microorganisms in nature are thought to have escaped traditional cultivation techniques. Recently, use of the 16S rDNA approach to assess prokaryotic biodiversity in different ecosystems has, in part, alleviated the limitations of traditional cultivation and has facilitated microbiological studies. The application of molecular techniques, which allows identification of microorganisms without prior use of standard cultivation and isolation techniques has revealed much of the microbial diversity that previously escaped identification (Delong 1992; Massana et al. 1997; Dojka et al. 1998; Hugenholtz et al. 1998a) and has indicated that the actual number of bacterial species exceeds the number of cultivated ones by at least two orders of magnitude (Amann et al. 1995). The 16S rDNA approach has now been applied to a wide variety of ecosystems and has resulted in the description of as yet uncultivated groups of Archaea. In most cases, a high degree of archaeal diversity was found, even in extreme environments, including those with high temperatures (Barns et al. 1994; Sako et al. 1996; Huber et al. 2002), high salinity (Arahal et al. 1996; Cytryn et al. 2000), and pH extremes (Grant et al. 1999). On the other hand, some studies have revealed a much lower level of diversity, with one or two predominant species; this is the case for some marine environments and in hypersaline lakes and sediments. On the whole, the idea that Archaea seem to be ubiquitous has been widely accepted, and they appear to thrive especially well in aquatic ecosystems.

Presently, the Archaea are subdivided into three kingdoms: Crenarchaeota, Euryarchaeota, and the recently proposed Korarchaeota, a group of 16S rDNA sequences retrieved from a hot spring in Yellowstone National Park, USA (Barns et al. 1996).

Although many investigations have been carried out to study archaeal diversity and many new lineages have been found in sediment environments, such as in salt marsh sediments, continental shelf anoxic sediments, freshwater sediments, and deep subsurface sediments, the phylogenetic diversity of Archaea in prawn farm sediments has not yet been surveyed. Here, we report on a high diversity of novel Crenarchaeota and Euryarchaeota associated with the pond sediments of a prawn farm, and we compare archaeal populations with those in other sediment ecosystems. These results may improve our knowledge of archaeal phylogenetic diversity in the pond sediments of prawn farms.

Materials and methods

Sample collection

Sediment cores of 25 cm (length) by 7.5 cm (diameter), covered with seawater, were collected at a depth of 50 m near the center of prawn pond no. 1 of the Kehua Company in Bachimen (23°33′N; 117°30′E), Dongshan County, Fujian province, on 22 May 2000. The top 0–12 cm of the sediment cores showed a clearly visible thin black layer of compact sediment with a sickly smell, whereas below 12 cm the sediment layer appeared to be thicker and gray. The samples were taken from the surface (0–2 cm), middle layer (6–8 cm), and the substratum (14–16 cm) of the above-mentioned cylindrical subcores, and were wrapped in sterile tinfoil. Then, the samples were kept in the dark at −20°C until they were processed in the laboratory.

DNA extraction, amplification, library construction, and screening

Genomic DNA was extracted from 0.2 g of the sediment subcore. The sample was thawed on ice, and resuspended in 250 μl extraction buffer (0.15 M NaCl; 0.1 M EDTA, pH 8.0). Then, 10 μl lysozyme (22 mg ml−1) was added to the sample, which was incubated at 37°C for 1 h with gentle shaking. Next, 30 μl 10% (w/v) SDS and 5 μl proteinase K (6 mg ml−1) were added to the mixture, followed by incubation at 55°C for 3 h with slow rotation. The treated sample was centrifuged at 10,000 g for 10 min, and the supernatant fluids were extracted twice with an equal volume of phenol/chloroform/isoamyl alcohol (25:24:1). To each part of the aqueous phase, 0.1 parts of 3 M sodium acetate (pH 5.2) and 2 parts of 100% ethanol were added to precipitate DNA, and the mixture was kept at −20°C. The DNA was collected by centrifugation at 14,000 g for 10 min, washed in 70% ethanol, dried, and resuspended in sterile (121°C/15 min) distilled water. The partial 16S rRNA gene sequences were selectively amplified from the genomic DNA by polymerase chain reactions (PCR) using two Archaea-specific primers, w017 (5′-ATTCYGGTTGATCCYGSCRG-3′, Escherichia coli F6) (Godon et al. 1997) and S-D-Arch-0915-a-A-20 (5′-GTGCTCCCCCGCCAATTCCT-3′) (Amann et al. 1990). Serial dilutions of template DNA were incubated in a thermal cycler in the presence of ExTaq DNA polymerase (TaKaRa) under the following conditions: 94°C for 4 min, followed by 30 cycles of denaturation at 94°C for 1 min, annealing at 50°C for 1 min, and extension at 72°C for 2 min. Reactions were run at 72°C for 10 min to elongate any uncompleted product. PCR products of ca. 900 bp were gel purified by using QIAquick spin columns (Qiagen) and resuspended in sterile distilled water. Amplified 16S rRNA gene fragments were cloned in pMD-18 T-vector (TaKaRa), and the resulting ligation products were transformed into E. coli TG1 (kept in our laboratory) competent cells with ampicillin selection and blue/white screening. The M13/pUC sequencing primers P47 (5′-CGCCAGGGTTTTCCCAGTCACGAC-3′) and P48 (5′-AGCGGATAACAATTTCACACAGGA-3′) were used for clone screening. A total of 80 recombinant clones showing positive signals was used in the following analyses.

RFLP, sequence, and phylogenetic analyses

PCR-RFLP was performed using the tandem tetrameric restriction endonuclease pairs, MspI and HaeIII (TaKaRa). The reaction products were visualized by electrophoresis on a 2.0% agarose gel containing ethidium bromide. Representative clones for the library showing unique RFLP patterns were selected, and the plasmid DNA was extracted and purified using the QIAprep Spin Miniprep Kit (Qiagen) for sequencing. The sequencing was performed for both strands with the ABI PRISM BigDye Terminator Cycle Sequencing Ready Reaction Kit (PE Applied Biosystems, Foster City, Calif.) using protocols supplied by the manufacturer. Sequencing reaction products were resolved using ureapolyacrylamide electrophoresis on an ABI PRISM 377 DNA sequencer (PE Applied Biosystems) in our laboratory according to the manufacturer’s recommended protocols. Finally, partial sequences of 500–600 bp, suitable for phylogenetic analysis, were determined. Clones were designated BCMS (for Bachimen’s sediment). Partial 16S rDNA sequences were first analyzed with the program CHIMERA_CHECK, ver. 2.7 (, and ambiguous sequences were excluded from the subsequent analysis. Then, the partial rDNA sequences were analyzed using ALIGN_SEQUENCE from the gapped-BLAST search algorithm (Benson et al. 1998) to estimate the degree of similarity to other rDNA sequences. In this study, we tentatively defined that >98% similarity represented the same rDNA clone type among rDNA sequences obtained from the pond sediment of the prawn farm. To increase the speed of analyses, taxa with identical sequences were removed from the data set and only a single representative sequence was retained for the analysis. Representatives of the archaeal sequences available through GenBank for most environments were included in our analysis, in order to obtain an accurate description of the phylogenetic relationships of Archaea from pond sediments. A total of 61 sequences of Crenarchaeota and 63 of Euryarchaeota were involved and aligned for phylogenetic analysis using the CLUSTAL X computer program (Thompson et al. 1997). Pre-aligned sequences were checked manually for correct alignment and edited using the BioEdit program. Sequence regions containing gaps and primer sequences and ambiguous nucleotides were removed from the multiple alignments before phylogenetic analysis. After the alignments, 655 and 517 aligned nucleotide positions for Crenarchaeota and Euryarchaeota data sets, respectively, were used to infer the phylogenetic position. The MODELTEST program (ver. 3.06) was run to determine the best-fit model of DNA evolution (Posada and Crandall 1998). Maximum-likelihood (ML) scores were calculated for 56 nested ML models. Phylogenetic analyses were done using ML analyses and Bayesian inference (BI). The beta version of PAUP*4.0 (Swofford 2000) was used for ML analysis. Gaps were treated as missing data. The ML tree was constructed by using the tree-bisection-reconnection (TBR) branch-swapping algorithm, with randomized stepwise addition of taxa under the heuristic search method (ten random taxon additions). The TBR branch-swapping algorithm was conducted to assess the confidence values of branches in the ML tree. BI was done using MrBayes, ver. 2.01 (Rannala and Yang 1996; Mau and Newton 1997; Mau et al. 1999). The number of states (nst) was set to 6, the rates parameter was set to an invgamma distribution, and the shape parameter was set as measured by MODELTEST for Bayesian inference. The Bayesian Markov chains reached a stationary position at ca. 30,000 generations; the program was run for 1,000,000 generations. Trees were sampled after every 100 generations, for a total of 10,001 trees. The output file created by MrBayes was executed in PAUP*4.0 to derive the consensus tree with the probabilities of each clade indicated.

Nucleotide sequence accession numbers

The sequences from this study are available through GenBank under accession numbers AJ579722–AJ579761.


Characterization of archaeal rDNA recovered from the pond sediment environment

Total DNA from three samples at different depths was extracted; only the 16S rDNA from the surface section could be amplified with Archaea-specific primers. The archaeal populations of the microbial communities in the surface sediments, which were exposed to anthropogenic influences, were examined based on partial nucleotide sequences through the analysis of a number of insert-containing plasmids. To estimate the diversity of Archaea in the pond sediment of the prawn farm, a total of 80 recombinant clones showing positive signals were selected and subjected to RFLP analysis. All archaeal rDNA fragments in the positive clones were digested with the endonucleases MspI and HaeIII, resulting in 50 different RFLP patterns. Each distinct RFLP pattern obtained usually represented a different phylotype. Phylotypes were then defined and were equivalent to operational taxonomic units (OTU), with each unit containing clones with >0.98 similarity. This cut-off value accounts for sequence microheterogeneity, which usually exists between closely related taxa (McCaig et al. 1999). Details on the frequency of RFLP patterns for different clones are shown in Table 1. Of the 50 unique RFLP patterns detected in these clones, most of the RFLP types were represented by a single clone. BLAST results showed that 54 clones were found to be archaeal small subunit (SSU) rDNA sequences and 3 clones to be proteobacterial SSU rDNA sequences (5%, data not shown). In the RFLP analysis, we found that different RFLP patterns may belong to only one phylotype. For instance, results based on gapped-BLAST analysis showed that five clones in our archaeal library were all related to the sample Arc.No.5, with 91–96% similarity (Table 1), but their RFLP patterns were found to be representative of five different types rather than one type. In addition, we tentatively defined that >98% similarity in archaeal sequences represented an identical rDNA clone type, as described in “Materials and methods”. However, none of these sequences were found to be identical with >98% similarity to any known archaeal sequences.
Table 1

Similarity values of archaeal 16S rDNA sequences retrieved from the pond sediment of a prawn farm. In parentheses, the number of rDNA clones having >98% identity to each representative clone. The sequence identity was based on gapped-BLAST analysis

Clone (no. >98%)

Accession number

Results of BLAST analysis

Sequence length (bp)


Closest relative and its accession number


  BCMS-11 (1)




Uncultured archaeon (AB094524)

  BCMS-15 (1)




Uncultured archaeon clone MA-B1-3 (AY093447)

  BCMS-11B (1)




Uncultured archaeon clone MA-B1-5 (AY093449)

  BCMS-3 (1)




Uncultured archaeon clone MA-B1-5 (AY093449)

  BCMS-18 (1)




Uncultured archaeon clone MA-C1-3 (AY093450)

  BCMS-26 (1)




Uncultured archaeon clone MA-C1-3 (AY093450)

  BCMS-27B (1)




Uncultured archaeon arc. 171 (AF005765)

  BCMS-32 (1)




Unidentified crenarchaeote (AF004345)

  BCMS-1 (2)




Uncultured archaeon OHKA2.33 (AB094532)

  BCMS-19B (1)




Uncultured archaeon OHKA2.33 (AB094532)

  BCMS-13B (1)




Uncultured archaeon OHKA1.43 (AB094528)

  BCMS-17B (1)




Uncultured archaeon OHKA1.16 (AB094522)

  BCMS-29B (1)




Uncultured archaeon clone: OHKA1.27 (AB094524)

  BCMS-16 (1)




Uncultured archaeon gene OHKA2.14 (AB094531)


  BCMS-21 (2)




Uncultured archaeon (AF395423)

  BCMS-28 (3)




Uncultured archaeon (AF395423)

  BCMS-37 (2)




Uncultured archaeon (AF395423)

  BCMS-8B (3)




Uncultured archaeon (AF395423)

  BCMS-12B (1)




Uncultured archaeon (AF395423)

  BCMS-24 (1)




Uncultured archaeon 2MT16 (AF015984)

  BCMS-25 (1)




Uncultured archaeon 33-P74A98 (AF355811)

  BCMS-23B (1)




Uncultured archaeon CS_R002 (AF419645)

  BCMS-31 (1)




Uncultured archaeon CS_R002 (AF419645)

  BCMS-46 (2)




Uncultured archaeon 63-A3 (AJ305064)

  BCMS-44 (1)




Uncultured euryarchaeote EHB158 (AF374277)

  BCMS-7B (2)




Uncultured euryarchaeote EHB154 (AF374278)

  BCMS-16B (1)




Uncultured euryarchaeote EHB154 (AF374278)

  BCMS-9B (1)




Uncultured archaeon 20c-47 (AJ299200)

  BCMS-28B (1)




Uncultured archaeon 2C25 (AF015971)

  BCMS-5 (1)




Uncultured archaeon TA1f2 (AF134390)

  BCMS-7 (2)




Uncultured archaeon 33-P74A98 (AF355811)

  BCMS-8 (1)




Uncultured archaeon 19b-2 (AJ294853)

  BCMS-10 (1)




Uncultured archaeon LKS8 (AJ310857)

  BCMS-6 (2)




Methanosarcina semesiae (AJ012742)

  BCMS-19 (1)




Methnosarcina siciliae (U89773)

  BCMS-54 (1)




Methanogenium organophilum (M59131)

  BCMS-20 (2)




Uncultured Methanogenium sp. clone LH23 (AY177807)

  BCMS-55 (1)




Methanosaeta sp. (AJ133791)

  BCMS-36 (3)




Halobacterium cutirubrum NCIMB 763 (AB073365)

  BCMS-52 (1)




Uncultured archaeon BURTON2_A (AF142981)

Phylogenetic diversity of archaeal 16S rDNA sequences

The BLAST results showed that the newly obtained sequences were most similar to those of Crenarchaeota and Euryarchaeota, and 16S rDNA data sets of the two taxa were consequently constructed. The 54 clones of representatives for the archaeal library were partially sequenced. No chimeric molecules were detected. MODELTEST analysis determined the GTR+I+G (GTR, general time reversible) model (Rodríguez et al. 1990) as being the best-fit model of DNA evolution for the two 16S rDNA sets (the Crenarchaeota set: G=0.7936, I=0.0565, −lnL=9,750.1377; the Euryarchaeata set: G=0.8813, I=0.1641, −lnL=10,378.6729). In the Bayesian analyses, the three independent MCMC runs resulted in concordant joint posterior probability distributions for the topology and the estimated parameters of the model of sequence evolution. This result suggests that the chains were run for a sufficient number of generations and sampled the same posterior probability landscape.

Largely congruent topological trees were generated using the ML method and Bayesian inference (Figs. 1, 2). Phylogenetic analyses revealed that the vast majority of the archaeal domain clones were most closely related to uncultured archaeal clones. In an overview of the trees, the archaeal rDNA sequences obtained, not only from the marine group, but also from other aquatic sediment environments were found to form two large phylogenetic assemblages: one consisting of BCMSC-groups I–V within the crenarchaeal lineage (Fig. 1) and the other one with BCMS-groups I–VI placed in deep lineages within the Euryarchaeota (Fig. 2).
Fig. 1

Phylogenetic relationship of crenarchaeotic 16S rDNA sequences as determined by the maximum-likelihood analysis. The values at the nodes represent the posterior probability of each clade calculated by Bayesian analysis. Only values >50% are shown. Scale bar: 0.1 nucleotide substitution per site. The sequences from the pond sediment of the prawn farm in BaChiMen are indicated by boldface type. The remaining sequences were obtained from GenBank. Thermotoga matitima (M21774) was used as outgroup. Abbreviations for as-yet-uncultivated phylotypes from various environments: pSL78 (U63344), a Yellowstone National Park hot spring; pGrfC26 (U59986) and pGrfA4 (U59968), freshwater sediments; MA-B1-5 (AY093449), MA-B1-3 (AY093447), MA-C1-3 (AY093450), deep-marine sediments in forearc basin; CRA8-27cm (AF119128), APA4-0cm (AF119138), APA2-17cm (AF119135), APA3-11cm (AF119137), LMA226 (U87520), LMA238 (U87517) deep-sea sediment; OHAK1.27 (AB094524), OHAK2.14 (AB094531), OHAK1.43 (AB094528), OHAK2.33 (AB094532), OHAK1.16 (AB094522), sub-seafloor sediments from the Sea of Okhotsk; FFSB10 (X96695), SCA1173 (U62818), soil environments; SAGMA-A (AB050205), SAGMA-W (AB050228), SAGMA-X (AB050229), South African gold mine environments; Arc.3 (AF005754), deep-subsurface paleosol

Fig. 2

Phylogenetic relationship of euryarchaeotic 16S rDNA sequences as determined by the maximum-likelihood analysis. The values at the nodes represent the posterior probability of each clade calculated by Bayesian analysis. Only values >50% are shown. Scale bar: 0.1 nucleotide substitution per site. The sequences from the pond sediment of the prawn farm in BaChiMen are indicated by boldface type. The remaining sequences were obtained from GenBank. Desulfurococcus mobilis (M36474) was used as outgroup. Abbreviations for as-yet-uncultivated phylotypes from various environments: APA6-17cm (AF119139), CRA13-11cm (AF119124), deep-sea sediments; 33-P47A98 (AF355811), 33-P120A98 (AF355810), mid-ocean ridge sub–sea floor habitat; ARR19 (AJ227932), rice roots; KTK.9A (AJ133622), KTK18A (AJ133623), deep-sea brine sediments; 19b-2 (AJ294853), 20c-47 (AJ299200), BURTON2_A (AF142981), CS_R002 (AF419645), marine sediment; TA1b12 (AF134385), TA1f2 (AF134390), anaerobic methane rich marine sediments; Archaeon 2C25 (AF015971), Archaeon 2C129 (AF015967), 2MT16 (AF015984), salt marsh sediment; EHB154 (AF374278), EHB158 (AF374277), East Hill Bridge sediments; (AF395423), acetate-enriched culture

In our archaeal library, 15 clones (27.8%) were related to Crenarchaeota, and none of them were associated with any known cultured lineages (Fig. 1). In BCMSC-group I, BCMS-1 and BCMS-16 were allied to OHKA clones obtained from sub-seafloor sediments from the Sea of Okhotsk, with moderate probability values supported. BCMS-19B and BCMS-13B stably formed an independent clade and then were grouped within the clade including BCMS-1 and BCMS-16. Although no phylogenetic analysis was carried out for the OHKA clones, they were allied to the deep-sea group, including the clones of CRA8–27 cm and APA3–11 cm, with a strong probability value (100%). It was indicated that BCMSC-group I and OHKA clones belonged to deep-sea group. In BCMSC-group II, four clones were also allied to other OHKA clones, but with probability values supported by 100%. BCMS-15 was grouped with pGrfC26, obtained from freshwater sediments. BCMS-11B and BCMS-26 formed a monophyletic clade, with strong probability values (100%) in BCMSC-group V, which was allied to the NT-A3 group from deep marine sediments in a forearc basin. In BCMSC-group IV, BCMS-3 and BCMS-18 also formed a monophyletic lineage, clustered with NT-A3 and BCMSC-group V, but the probability support was moderate (74%).

Of all the euryarchaeal clones that dominated our archaeal library (72.2%), ten (18.5%) were related to known lineages, and the remaining clones (81.5%) were related to uncultured or novel lineages of Euryarchaeota from aquatic sediment. In the ML tree (Fig. 2), six new euryarchaeal groups were found. In BCMS-group II, four clones (BCMS-8, BCMS-52, BCMS-46, BCMS-28B) clustered and were involved in the marine group, with strong probability values (99%). Another four clones (BCMS-5, BCMS-7, BCMS-25, BCMS-9B) formed a monophyletic clade in BCMS-group I, which was allied to the marine group and BCMS-group II with moderate probability values. BCMS-group III, including two clones (BCMS-24, BCMS-36), was grouped with the salt marsh clade, with 100% probability support, indicating that BCMS-group III was related to the salt marsh group. Besides, four clones (7.4%) of methane-metabolizing families were allied to the mesophilic or moderately thermophilic family Methanomicrobiales. The four clones, represented by BCMS-44, BCMS-54, BCMS-7B, BCMS-16B, also formed the independent BCMS-group IV and were related to the H2-/CO2- and formate-utilizing genera Methanogenium. BCMS-group V, including the representative clones BCMS-6 and BCMS-19 (5.6%), was grouped with the Methanosarcianles clade, with 100% probability support, showing that BCMS-group V may be a new Methanosarcianles lineage. BCMS-19 and BCMS-6 were similar to cultured Methnosarcina siciliae and Methnosarcina semesiae, with 91% and 94% similarity, respectively. M. siciliae, which was transferred from the genus Methanolobus, uses only methyl compounds (Ni and Boone 1991; Nei et al. 1994) and is similar in this trait to M. semesiae (Lyimo et al. 2000). Another five clones (BCMS-37, BCMS-55, BCMS-8B, BCMS-12B, BCMS-28) are closely related to each other, appearing to represent a novel phylogenetic group (BCMS-group VI), and were only distantly related to clones of isolated from acetate-enriched culture. These six clones together were allied to the Methanosarcianles clade, with strong probability support.

On the whole, the marine group and the sediment group included most of the archaeal assemblage, and groups related to methanogens were also important populations in the sediment environment. None of the archaeal groups were found to be associated with the other environments studied.


Archaeal diversity in the pond sediment of the prawn farm

Although studies on phylogenetic diversity have been carried out in other sediment environments, such as anoxic marine sediment, deep-sea sediment, continental shelf sediment, coastal salt marsh sediment and freshwater sediment, this work represents the first study dealing with prawn farm sediment. The results showed a high level of archaeal diversity in the eutrophic ecosystem.

Molecular methods described here allow the study of archaeal diversity without prior cultivation and description of specific organisms. Our results suggest that the microorganisms concerned probably represent many novel groups of Archaea within the two kingdoms Euryarchaeaota and Crenarchaeaota. Except for three groups related to known Methanomicrobiales and Methanosarcianles, other representatives of archaeal groups are associated with environmental clones that have not yet been isolated in culture, and the basic features of their physiology are unknown. Although quantitative estimates of relative numbers were not carried out in this study, our results indicate that these marine sediment groups and methanogenic lineages must be major contributors to the archaeal population in prawn pond sediment. Furthermore, little similarity existed between the phylotypes detected in this study of prawn farm sediment, suggesting that enormous archaeal diversity occurs within marine sediments. However, it is unlikely that the 54 clones inspected exhaust the diversity of this archaeal community, since many of the sequence types were recovered only once (Table 1). The facts that clones belonging to the same OTU were seldom identical and that the sampling for the clone library from the sediment had not reached saturation (Fig. 3) indicate that we may have underestimated the true diversity. In addition, it is important to recognize that these data are not necessarily representative of the in situ archaeal community. The biases inherent in DNA extraction, PCR, cloning, library screening, and RFLP methods prevent a full accounting of sequences in the environment and limit our ability to characterize total archaeal diversity (von Wintzingerode et al. 1997; Hugenholtz et al. 1998b). Moreover, the heterogeneity of natural environments precludes complete representative sampling (Reed et al. 2002). Nonetheless, the very specialized archaeal community present at this site suggests that at least some of the archaeal sequences identified here are unique to pond sediment. This remarkable diversity includes a number of previously uncharacterized archaeal lineages that are likely to be discovered in anoxic and eutrophic ecosystem. Future research considering even deeper sediment areas and involving more sampling may help to further explain the biodiversity of these communities and characterize community structure.
Fig. 3

Estimation of the diversity in the archaeal community from the pond sediment of the prawn farm. The sequential detection of cumulative RFLP patterns following RFLP analysis of 61 archaeal 16S rDNA clones is presented. The 16S rDNA clone numbers reflect the order of initial detection, which was assumed to be stochastic relative to the distribution of clones generated in the library

Comparison with other 16S rDNA clone library studies of marine sediments

Most studies of marine ecosystems have concentrated on the water column and on communities of aggregated plankton. Generally, the same groups of Eubacteria and Archaeabacteria are dominant in oceanic regions with similar climatic conditions (Mullins et al. 1995; Fuhrman and Davis 1997). Similar comparisons could reveal which archaeal groups prosper particularly well in sediments with certain characteristic environmental parameters (Bowman et al. 2000). Unfortunately, comparisons are not yet possible between clone library data, because of the general lack of data on sediment samples from aquacultural facilities. The only clone library studies based on aquatic sediments that are available for comparison included a fairly limited analysis of sediment samples from a coastal salt marsh (Munson et al. 1997), of marine benthic Archaea from deep-sea sediment (Vetriani et al. 1999), and of a sample from freshwater sediment (Schleper et al. 1997).

A higher level of archaeal diversity was found in prawn farm sediments compared to that in other marine sediments. The 16S rDNA clones recovered were limited to two distinct lineages, the Euryarchaeota and Crenarchaeota, which was consistent with studies of the deep marine sediment along the continental shelf (Vetriani et al. 1998) and in a forearc basin (Reed et al. 2002), of Lake Michigan sediment (Macgregor et al. 1997) and of deep-sea sediments (Vetriani et al. 1999). Of the new groups in this study, eight were related to archaeal sequences obtained from either the marine or deep-sea sediment environment. The salt marsh and marine benthic Euryarchaeota were both detected in our sample and in that from the continental shelf. Although three novel groups (BCMS-group IV, BCMS-group V, and BCMS-group VI) related to methanogens were found in our study, no methanogen-like sequences were detected in the coastal salt marsh or the continental shelf sediment. Meanwhile, five novel groups within the Crenarchaeaota were also detected. The BCMS-15 clone in BCMSC-group III clustered with the freshwater crenarchaeal sequence pGrfC26 (Hershberger et al. 1996). According to the report by Vetriani et al. (1998), three clones (BBA2, BBA4, and BBA6) from coastal anoxic, sulfide-rich marine sediments also have close affinity with the clones of pGrfC26. This indicated that the close affinities among BCMSC-group III, marine sediment groups, and pGrfC26 are consistent with their distribution in similar environments. In addition, a unique phylogenetic group closely related to the NT group was recovered; it was found in the deep marine sediment of a forearc basin (Reed et al. 2002). Phylogenetic analyses showed that the six clone sequences and the NT-A3 group were all assigned to the deep Crenarchaeota branch, and were distant from any cultured archaeal sequences. This result was consistent with the results of Reed et al. (2002). In fact, the presence of Crenarchaeota-related sequences in marine sediments has been described previously (Macgregor et al. 1997; Cifuentes et al. 2000). To further examine the relationships among these sequences, more sediment samples from different locations with similar and different environmental characteristics are required.

Selective dispersal of the Archaea population: ecological implications

Environmental characteristics have impacts on the microbial communities in a given environment and might be important in determining the magnitude, content, and diversity of microbial communities (Takai and Horikoshi 1999). The diversity of archaeal populations may reflect differences in environmental conditions, such as geological location, chemical composition, or temperature, among different sediment systems. Comparing our sequences with others obtained from geologically different aquatic sediment ecosystems, certain archaeal rDNA sequences were only associated with marine and sediment-like ecosystems, and most of them shared several similar phylogenetic affiliations. On the other hand, these sequences showed no significant similarity to any rDNA sequences from other environments, such as the soil group, gold mine group, UEII group, rice root group or marine hydrothermal vent group. This indicates that in aquatic and sediment ecosystems only a certain kind of population thrives; the other archaeal groups that cannot adapt to the ecosystem are in an inactive state or even perish.

It was shown that the feces, unconsummated feed pellets, fertilizer, and toxic pesticide left in the sediment need to be decomposed. Archaea play an important role in this decomposition process. Studies have previously indicated that Archaea are involved in the anaerobic oxidation of methane in sediments (Hinrichs et al. 1999), and methanogens are known to inhabit marine sediments (Cifuentes et al. 2000). Some authors have also retrieved methanogen-related 16S rDNA sequences from sediment environments, and active methanogenesis has been found in the salt marsh sediment samples (Munson et al. 1997) and in sulfate-rich marine sediments (Oremland et al. 1982). As methanogens are involved in the complete remineralization of sedimentary organic matter to methane, they are usually associated with low-temperature anoxic marine sediments. Therefore, it was not surprising to find sequences related to the methanogens in our sample, such as BCMS-group IV (Methanobacteriales-like group) and BCMS-group V (Methanosarcinales-like group). Thus, the occurrence of methanogens indicated the presence of biogenic methane and active catabolism, as well as methanogenesis within the sediment to some extant. The presence of archaeal gene sequences further demonstrates that the aquaculture sediment is a suitable archaeal habitat. On the whole, our sequences and related sequences obtained from other sediment ecosystems demonstrate that the dispersal of Archaea, at least in prawn farm sediment, is selective.

Although many 16S rDNA sequences were determined in this study, it is not possible, from these limited data, to fully describe the ecological role of Archaea in the sediment. As the most important components in the prokaryotic community, their selective dispersal is consistent with certain environmental factors, such as anoxic and eutrophic conditions in the aquaculture sediments.

In conclusion, our study demonstrates the presence of many novel groups of Archaea in the pond sediment of a prawn farm, and suggests their association with a well-established sediment layer below the oxic zone. To date the physiological properties of the sedimentary Archaea have been assessed. Studies on archaeal diversity and their vertical distribution in coastal and aquaculture sediments collected at different sites and depths are in progress. Biogeochemical measurements will be the next critical step in correlating the distribution of these novel Archeae with potential activity and ecological roles in pond sediments.



This study was supported by NSFC projects (no. 40176037, 40232021) and the Red Tide Key Project of the National Natural Science Foundation of Guangdong province, China (no. 011208). The experiments comply with current laws of the country in which the experiments were performed.


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Copyright information

© Springer-Verlag 2004

Authors and Affiliations

  • Peng Shao
    • 1
  • Yueqin Chen
    • 1
  • Hui Zhou
    • 1
  • Lianghu Qu
    • 1
  • Ying Ma
    • 2
  • Heyang Li
    • 2
  • Nianzhi Jiao
    • 2
  1. 1.Key Laboratory of Gene Engineering of the Ministry of Education, Biotechnology Research CenterZhongshan UniversityGuangzhouP.R. China
  2. 2.Key Laboratory for Marine Environmental Science of the Ministry Education, Environmental Science Research CenterXiamen UniversityXiamenP.R. China

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